bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal Design and Experimental Verification of Wound Rotor Synchronous Machine Using Subharmonic Excitation for Brushless Operation
Authors: Hussain Asif , Atiq Shahid , Kwon Byung-il
Published: March 2018

This paper presents an optimal design of a recently introduced brushless wound-rotor synchronous machine (BL-WRSM). The BL-WRSM, with a special stator winding arrangement, utilizes a single three-phase inverter for generating an additional spatial subharmonic component in the stator magnetomotive force (MMF). This subharmonic component of the stator MMF is used for the brushless excitation of the rotor. The pole span and pole shoe height were the optimized parameters, with the goals of improving the quality of output power and reducing torque ripple. Moreover, the average torque of the machine was improved by optimizing the harmonic winding placed on the rotor. The optimized BL-WRSM was further analyzed for the flux weakening operation. Finite element analysis (FEA) was carried out to analyze the performance of the BL-WRSM. Finally, the performance of the optimal BL-WRSM model was verified through an experimental test, which demonstrated good agreement with the simulation results.
An Optimal Source-Load Coordinated Restoration Method Considering Double Uncertainty
Authors: Jiang Ping , Chen Qiwei
Published: March 2018

The security of power system restoration is severely affected by uncertain factors, especially the start-up time of generating unit and the amount of load pick-up. Solving the optimization restoration problem is challenging since it needs to determine different priorities in which units and loads are restored with the consideration of double uncertainty. Therefore, an optimal source-load coordinated restoration method that is based on information gap decision theory (IGDT) is proposed. Firstly, the time-domain restoration characteristics of black-start unit (BSU), non-black-start unit (NBSU), and load are described with analysis of double uncertainty. On this basis, a coupled multi-objective optimization model is built with double uncertainty, in which source-load coordinated restoration is realized. Then, IGDT is adopted to convert the uncertainty optimization model to a certain one with robustness, which tolerates the most uncertainty and still meets the desired requirement. Finally, the optimization model is solved by non-dominated genetic algorithm II (NSGA-II). The effectiveness and robustness of the proposed method is further illustrated through a case study based on the IEEE 39-bus system.
On the Effectiveness of the Abatement Policy Mix: A Case Study of China’s Energy-Intensive Sectors
Authors: Liu Xin , Li Yuan , Zhang Dayong , Zhu Lei
Published: March 2018

To achieve carbon emissions control targets, policymakers often need a basket of policies to account for the complexity of abatement. The instruments in the policy mix are often interconnected. It is of great importance to study how different abatement policies perform in practice—in other words, to evaluate the effectiveness of the abatement policy mix. This paper builds a multisector partial equilibrium model and then studies the policy effectiveness using data from two energy-intensive sectors in China, namely, the iron and steel sector and the cement sector. The results show clear evidence that these policies interact, and the policy mix is not a simple aggregation but rather differs across sectors, which leads to fundamentally different scenarios in terms of energy savings, emissions reductions and production behaviors. Energy-savings subsidies can increase production and profit with a lower equilibrium level of carbon prices, whereas output-based rebating of allowances reduces production and is associated with higher carbon prices.
A Two-Zone Combustion Model for Knocking Prediction of Marine Natural Gas SI Engines
Authors: Xiang La , Song Enzhe , Ding Yu
Published: March 2018

The further thermal efficiency improvement of marine natural gas engine is constrained by a knocking phenomenon that commonly occurs in gas-fueled spark-ignited engines. It plays an important role to investigate how the knocking occurs and how to predict it based on the engine simulation model. In this paper, a two-zone model is developed to provide the prediction of knocking performance and NO emission, which is verified by engine test bed data from a transformed marine natural gas spark ignition (SI) engine. Cylindrical division theory is used to describe the shape of the two zones to decrease the computational cost, as well as a basic mechanism for NO concentration calculation. In order to solve the volume balance, three boundary parameters are introduced to determine the initial condition and mass flow between the two zones. Furthermore, boundary parameters’ variation and knocking factor (compression ratio and advanced ignition angle) will be discussed under different working conditions. Result shows that the two-zone model has sufficient accuracy in predicting engine performance, NO emission and knocking performance. Both the increasing compression ratio and advanced ignition angle have a promoting effect on knocking probability, knocking timing and knocking intensity. The knocking phenomenon can be avoided in the targeted natural gas SI engine by constraining the compression ratio smaller than 14 and advanced ignition angle later than 30° before top dead center (BTDC).
Catalytic Hydrothermal Liquefaction of Food Waste Using CeZrOx
Authors: Maag Alex , Paulsen Alex , Amundsen Ted , Yelvington Paul , Tompsett Geoffrey , Timko Michael
Published: March 2018

Approximately 15 million dry tons of food waste is produced annually in the United States (USA), and 92% of this waste is disposed of in landfills where it decomposes to produce greenhouse gases and water pollution. Hydrothermal liquefaction (HTL) is an attractive technology capable of converting a broad range of organic compounds, especially those with substantial water content, into energy products. The HTL process produces a bio-oil precursor that can be further upgraded to transportation fuels and an aqueous phase containing water-soluble organic impurities. Converting small oxygenated compounds that partition into the water phase into larger, hydrophobic compounds can reduce aqueous phase remediation costs and improve energy yields. HTL was investigated at 300 °C and a reaction time of 1 h for conversion of an institutional food waste to bio-oil, using either homogeneous Na2CO3 or heterogeneous CeZrOx to promote in situ conversion of water-soluble organic compounds into less oxygenated, oil-soluble products. Results with food waste indicate that CeZrOx improves both bio-oil higher heating value (HHV) and energy recovery when compared both to non-catalytic and Na2CO3-catalyzed HTL. The aqueous phase obtained using CeZrOx as an HTL catalyst contained approximately half the total organic carbon compared to that obtained using Na2CO3—suggesting reduced water treatment costs using the heterogeneous catalyst. Experiments with model compounds indicated that the primary mechanism of action was condensation of aldehydes, a reaction which simultaneously increases molecular weight and oxygen-to-carbon ratio—consistent with the improvements in bio-oil yield and HHV observed with institutional food waste. The catalyst was stable under hydrothermal conditions (≥16 h at 300 °C) and could be reused at least three times for conversion of model aldehydes to water insoluble products. Energy and economic analysis suggested favorable performance for the heterogeneous catalyst compared either to non-catalytic HTL or Na2CO3-catalyzed HTL, especially once catalyst lifetime differences were considered. The results of this study establish the potential of heterogeneous catalysts to improve HTL economics and energetics.
Smart Global Maximum Power Point Tracking Controller of Photovoltaic Module Arrays
Authors: Chang Long-Yi , Chung Yi-Nung , Chao Kuei-Hsiang , Kao Jia-Jing
Published: March 2018

This study first explored the effect of shading on the output characteristics of modules in a photovoltaic module array. Next, a modified particle swarm optimization (PSO) method was employed to track the maximum power point of the multiple-peak characteristic curve of the array. Through the optimization method, the weighting value and cognition learning factor decreased with an increasing number of iterations, whereas the social learning factor increased, thereby enhancing the tracking capability of a maximum power point tracker. In addition, the weighting value was slightly modified on the basis of the changes in the slope and power of the characteristic curve to increase the tracking speed and stability of the tracker. Finally, a PIC18F8720 microcontroller was coordinated with peripheral hardware circuits to realize the proposed PSO method, which was then adopted to track the maximum power point of the power–voltage (P–V) output characteristic curve of the photovoltaic module array under shading. Subsequently, tests were conducted to verify that the modified PSO method exhibited favorable tracking speed and accuracy.
Optimization of Phasor Measurement Unit (PMU) Placement in Supervisory Control and Data Acquisition (SCADA)-Based Power System for Better State-Estimation Performance
Authors: Shahriar Mohammad , Habiballah Ibrahim , Hussein Huthaifa
Published: March 2018

Present-day power systems are mostly equipped with conventional meters and intended for the installation of highly accurate phasor measurement units (PMUs) to ensure better protection, monitoring and control of the network. PMU is a deliberate choice due to its unique capacity in providing accurate phasor readings of bus voltages and currents. However, due to the high expense and a requirement for communication facilities, the installation of a limited number of PMUs in a network is common practice. This paper presents an optimal approach to selecting the locations of PMUs to be installed with the objective of ensuring maximum accuracy of the state estimation (SE). The optimization technique ensures that the critical locations of the system will be covered by PMU meters which lower the negative impact of bad data on state-estimation performance. One of the well-known intelligent optimization techniques, the genetic algorithm (GA), is used to search for the optimal set of PMUs. The proposed technique is compared with a heuristic approach of PMU placement. The weighted least square (WLS), with a modified Jacobian to deal with the phasor quantities, is used to compute the estimation accuracy. IEEE 30-bus and 118-bus systems are used to demonstrate the suggested technique.
An Improved Crow Search Algorithm Applied to Energy Problems
Authors: Díaz Primitivo , Pérez-Cisneros Marco , Cuevas Erik , Avalos Omar , Gálvez Jorge , Hinojosa Salvador , Zaldivar Daniel
Published: March 2018

The efficient use of energy in electrical systems has become a relevant topic due to its environmental impact. Parameter identification in induction motors and capacitor allocation in distribution networks are two representative problems that have strong implications in the massive use of energy. From an optimization perspective, both problems are considered extremely complex due to their non-linearity, discontinuity, and high multi-modality. These characteristics make difficult to solve them by using standard optimization techniques. On the other hand, metaheuristic methods have been widely used as alternative optimization algorithms to solve complex engineering problems. The Crow Search Algorithm (CSA) is a recent metaheuristic method based on the intelligent group behavior of crows. Although CSA presents interesting characteristics, its search strategy presents great difficulties when it faces high multi-modal formulations. In this paper, an improved version of the CSA method is presented to solve complex optimization problems of energy. In the new algorithm, two features of the original CSA are modified: (I) the awareness probability (AP) and (II) the random perturbation. With such adaptations, the new approach preserves solution diversity and improves the convergence to difficult high multi-modal optima. In order to evaluate its performance, the proposed algorithm has been tested in a set of four optimization problems which involve induction motors and distribution networks. The results demonstrate the high performance of the proposed method when it is compared with other popular approaches.
LoRaWAN-Based Energy-Efficient Surveillance by Drones for Intelligent Transportation Systems
Authors: Sharma Vishal , You Ilsun , Pau Giovanni , Collotta Mario , Lim Jae , Kim Jeong
Published: March 2018

Urban networks aim at facilitating users for better experience and services through smart platforms such as the Intelligent Transportation System (ITS). ITS focuses on information acquisition, sensing, contrivance control, data processing and forwarding to ground devices via user-specific application-interfaces. The utility of ITS is further improved via the Internet of Things (IoT), which supports “Connectivity to All”. One of the key applications of IoT-ITS is urban surveillance. Current surveillance in IoT-ITS is performed via fixed infrastructure-based sensing applications which consume an excessive amount of energy leading to several overheads and failures in the network. Such issues can be overcome by the utilization of on-demand nodes, such as drones, etc. However, drones-assisted surveillance requires efficient communication setup as drones are battery operated and any extemporaneous maneuver during monitoring may result in loss of drone or complete failure of the network. The novelty in terms of network layout can be procured by the utilization of drones with LoRaWAN, which is the protocol designated for Low-Power Wide Area Networks (LPWAN). However, even this architectural novelty alone cannot ascertain the formation of fail-safe, highly resilient, low-overhead, and non-redundant network, which is additionally the problem considered in this paper. To resolve such problem, this paper uses drones as LoRaWAN gateway and proposes a communication strategy based on the area stress, resilient factor, and energy consumption that avail in the efficient localization, improved coverage and energy-efficient surveillance with lower overheads, lower redundancy, and almost zero-isolations. The proposed approach is numerically simulated and the results show that the proposed approach can conserve a maximum of 39.2% and a minimum of 12.6% of the total network energy along with an improvement in the area stress between 89.7% and 53.0% for varying number of drones over a fixed area.
Leaf Trait Variation with Environmental Factors at Different Spatial Scales: A Multilevel Analysis Across a Forest-Steppe Transition
Authors: Shi Haijing , Wen Zhongming , Guo Minghang
Published: March 2018

In mountain areas, the distribution of plant communities is affected by both regional and microhabitat conditions. The degree to which these different spatial factors contribute to plant communities is not well understood, because few studies have used a uniform sampling methodology to measure trait variation across the range of ecological scales. In this study, a stratified sampling method was used to study community weighted leaf traits and environment factors at different spatial (transect and plot) scales. We measured 6 leaf traits (specific leaf area, leaf tissue density, leaf thickness, leaf carbon, nitrogen and phosphorus content) in 258 communities from 57 sites in 9 transects nested within 3 vegetation zones. These communities are located in the loess hilly and gully area of the Yanhe river watershed. We coupled climatic factors at the transect scale with topographic and edaphic factors at the plot scale using multilevel regression modeling to analyze the trait variation associated with spatial scales. At the transect scale, the mean annual rainfall showed a highly significant positive effect on the leaf nitrogen concentration (LNC) (p < 0.01), while it had a highly significant negative effect on leaf thickness (LT) and leaf tissue density (LTD) (p < 0.001) and a significant negative effect on leaf carbon concentration (LCC) (p < 0.05), explaining 10.91%, 36.08%, 57.25% and 66.01% of LTD, LT, LCC and LNC variation at transect scale respectively. At a plot scale, the slope aspect showed a highly significant positive effect on specific leaf area (SLA) and LNC but a highly significant negative effect on LT and LTD. The soil water content had a significant negative effect on LT (p < 0.05) and LTD (p < 0.001) while soil organic matter showed a positive effect on SLA (p < 0.001) and LNC (p < 0.01). Totally, plot scale variables explained 7.28%, 43.60%, 46.43%, 75.39% and 81.17% of LCC, LT, LNC, LTD and SLA variation. The elevation showed positive effect only on LCC (p < 0.05). The results confirmed the existence of consistent trait–environment relationships at both transect and plot scales. These trait–environment relationships at different spatial scales will provide mechanistic understanding on the vegetation community assembly in the study area. Practically, ignoring trait variation within transects will underestimate roles of microhabitat filters in community assembly, and leads to the homogenization of restoration species. This will be like the past restoration plans and programs, causing serious environmental problems such as dwarf trees and soil desiccation.
Relationship between Soil Characteristics and Stand Structure of Robinia pseudoacacia L. and Pinus tabulaeformis Carr. Mixed Plantations in the Caijiachuan Watershed: An Application of Structural Equation Modeling
Authors: Wei Xi , Bi Huaxing , Liang Wenjun , Hou Guirong , Kong Lingxiao , Zhou Qiaozhi
Published: March 2018

In order to study the multi-factor coupling relationships between typical Robinia pseudoacacia L. and Pinus tabulaeformis Carr. mixed plantations in the Caijiachuan basin of the Loess Plateau of Shanxi Province, West China, 136 sample plots were selected for building a structural equation model (SEM) of three potential variables: terrain, stand structure, and soil characteristics. Additionally, the indicators (also known as observed variables) were studied in this paper, including slope, altitude, diameter at breast height (DBH), tree height (TH), tree crown area, canopy density, stand density, leaf area index (LAI), soil moisture content, soil maximum water holding capacity (WHC), soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), ammonia-nitrogen (NH3-N), nitrate-nitrogen (NO3-N), and available phosphorus (AP). The results showed that terrain was the most important factor influencing soil moisture and nutrients, with a total impact coefficient of 1.303 and a direct path coefficient of 0.03, which represented mainly positive impacts; while correspondingly stand structure had a smaller negative impact on soil characteristics, with a total impact coefficient of −0.585 and a direct path coefficient of −0.01. The terrain also had a positive impact on the stand structure, with a total impact coefficient of 0.487 and a direct path coefficient of 0.63, indicating that the topography factors were more suitable for site conditions and both the stand structure and the soil moisture and nutrient conditions were relatively superior. By affecting the stand structure, terrain could restrict some soil, water, and nutrient functions of soil and water conservation. The influence coefficients of the four observed variables of DBH, stand density, soil water content, and organic matter, and potential variable topography reached 0.686, −0.119, 1.117, and 0.732, respectively; and the influence coefficients of soil moisture, organic matter and stand structure were −0.502 and −0.329, respectively. Therefore, besides observing the corresponding latent variables, the observed variables had a considerable indirect influence on other related latent variables. These relationships showed that the measures, such as changing micro-topography and adjusting stand density, should effectively maintain or enhance soil moisture and nutrient content so as to achieve improved soil and water conservation benefits in the ecologically important Loess Area.
TwinNet: A Double Sub-Network Framework for Detecting Universal Adversarial Perturbations
Authors: Ruan Yibin , Dai Jiazhu
Published: March 2018

Deep neural network has achieved great progress on tasks involving complex abstract concepts. However, there exist adversarial perturbations, which are imperceptible to humans, which can tremendously undermine the performance of deep neural network classifiers. Moreover, universal adversarial perturbations can even fool classifiers on almost all examples with just a single perturbation vector. In this paper, we propose TwinNet, a framework for neural network classifiers to detect such adversarial perturbations. TwinNet makes no modification of the protected classifier. It detects adversarially perturbated examples by enhancing different types of features in dedicated networks and fusing the output of the networks later. The paper empirically shows that our framework can identify adversarial perturbations effectively with a slight loss in accuracy when predicting normal examples, which outperforms state-of-the-art works.
Synthetic Strategies for the Fabrication of Cationic Surface-Modified Cellulose Nanocrystals
Authors: Sunasee Rajesh , Hemraz Usha
Published: March 2018

Cellulose nanocrystals (CNCs) are renewable nanosized materials with exceptional physicochemical properties that continue to garner a high level of attention in both industry and academia for their potential high-end material applications. These rod-shaped CNCs are appealing due to their non-toxic, carbohydrate-based chemical structure, large surface area, and the presence of ample surface hydroxyl groups for chemical surface modifications. CNCs, generally prepared from sulfuric acid-mediated hydrolysis of native cellulose, display an anionic surface that has been exploited for a number of applications. However, several recent studies showed the importance of CNCs’ surface charge reversal towards the design of functional cationic CNCs. Cationization of CNCs could further open up other innovative applications, in particular, bioapplications such as gene and drug delivery, vaccine adjuvants, and tissue engineering. This mini-review focuses mainly on the recent covalent synthetic methods for the design and fabrication of cationic CNCs as well as their potential bioapplications.
Evaluation of Fresh Azolla pinnata as a Low-Cost Supplemental Feed for Thai Silver Barb Barbonymus gonionotus
Authors: Das Mousumi , Rahim Ferdous , Hossain Md.
Published: March 2018

Aquatic fern Azolla pinnata comprises significant high food value with a good proportion of protein, vitamins, and minerals. This study was carried out to examine the effect of fresh A. pinnata as a substitution of commercial fish feed (CFF) for Thai silver barb Barbonymus gonionotus. Post fingerlings of B. gonionotus were reared in five treatments, labeled T1 to T5, by substituting 0%, 25%, 50%, 75%, and 100% protein of CFF with A. pinnata protein (dry matter basis) respectively for 56 days. The specific growth rate, net production rate, protein efficiency ratio, proximate composition, and overall conditions of fish were not significantly varied between the fish reared completely with CFF and 25% substitution with A. pinnata. However, a significantly higher profit rate (431.49 USD ha−1 56 day−1) was calculated for fish reared in T2 than other treatments. In contrast, there was a significant reduction of growth and other parameters of the fish that were observed in the case where more than 25% CFF was substituted with A. pinnata. The poorest performance was observed in fish fed completely with A. pinnata, at T5. Based on the results, 25% of CFF of Thai silver barb could be substituted with fresh A. pinnata without significantly lowering their growth and product quality and could contribute significant to a higher profit margin.
Increased Effectiveness of Microbiological Verification by Concentration-Dependent Neutralization of Sanitizers Used in Poultry Slaughter and Fabrication Allowing Salmonella enterica Survival
Authors: Mohammad Zahra , Hasan Amer , Kerth Chris , Riley David , Taylor T.
Published: March 2018

Sanitizer neutralizers can assist foodborne pathogen detection during routine testing by counteracting sanitizer residues carried over into fluids collected and tested from food samples. This study tested sanitizer-matched neutralizers applied at increasing concentrations to facilitate Salmonella enterica survival following exposure to cetylpyridinium chloride (CPC) or peracetic acid (PAA), identifying minimum required concentrations of neutralizers to facilitate pathogen survival. Salmonella isolates were individually inoculated into a non-selective medium followed immediately by CPC (0.1 to 0.8% v/v) or PAA (0.0125 to 0.2% v/v) application, followed by neutralizers application. CPC was neutralized by lecithin and polysorbate 80, each supplemented into buffered peptone water (BPW) at 0.125 to 2.0X its respective content in Dey-Engley (D/E) neutralizing buffer. PAA was neutralized in BPW supplemented with disodium phosphate, potassium monophosphate, and sodium thiosulfate, each at 0.25 to 3.0X its respective concentration in BPW (phosphates) or D/E buffer (thiosulfate). Addition of neutralizers at 1X their respective concentrations in D/E buffer was required to allow Salmonella growth at the maximum CPC concentration (0.8%), while 2X neutralizer addition was required for Salmonella growth at the maximum PAA level (0.2%). Sanitizer neutralizers can assist pathogen survival and detection during routine food product testing.
Does Imperfect Data Privacy Stop People from Collecting Personal Data?
Authors: Schudy Simeon , Utikal Verena
Published: March 2018

Many companies try to access personal information to discriminate among consumers. We analyse how privacy regulations affect the acquisition and disclosure of information in a simple game of persuasion. Theory predicts that no data will be acquired with Disclosure Duty of collected data whereas Consent Law with perfect privacy results in complete information acquisition. Imperfect privacy, i.e., an environment in which leaks of collected data are possible, gives rise to multiple equilibria. Results from a laboratory experiment confirm the qualitative differences between Consent Law and Disclosure Duty and show that imperfect privacy does not stop people from collecting personal information.
Relationship between Areas of Cognitive Functioning on the Mini-Mental State Examination and Crash Risk
Authors: Huisingh Carrie , Wadley Virginia , McGwin Jr. Gerald , Owsley Cynthia
Published: March 2018

Previous studies have suggested that the pattern of cognitive impairment in crash-involved older drivers is different from non-crash-involved older drivers. This study assessed the relationship between seven areas of cognitive functioning (orientation to time, orientation to place, registration, attention and calculation, recall, language, and visual construction) on the Mini-Mental State Examination (MMSE) collected at baseline and rates of future crash involvement in a prospective population-based sample of older drivers. Motor vehicle collision (MVC) involvement was obtained from the Alabama Department of Public Safety. Poisson regression was used to calculate crude and adjusted rate ratios (RR). Older drivers having difficulties in place orientation were more than 6 times (95% CI 1.90–19.86) more likely to be involved in a future crash (adjusted RR = 6.14, 95% confidence interval (CI) 1.90–19.86) and at-fault crash (adjusted RR = 6.39, 95% CI 1.51–27.10). Impairment in the other cognitive areas was not associated with higher rates of crash or at-fault crash involvement. The findings were validated in an independent sample of high-risk older drivers and a similar pattern of results was observed. Spatial orientation impairment can help identify older drivers who are more likely to crash in the future.
Harmful Cyanobacterial Material Production in the North Han River (South Korea): Genetic Potential and Temperature-Dependent Properties
Authors: Kim Keonhee , Park Chaehong , Yoon Youngdae , Hwang Soon-Jin
Published: March 2018

Cyanobacteria synthesize various harmful materials, including off-flavor substances and toxins, that are regarded as potential socio-economic and environmental hazards in freshwater systems, however, their production is still not well understood. In this study, we investigated the potential and properties of harmful materials produced by cyanobacteria, depending on temperature, and undertook a phylogenetic analysis of cyanobacteria present in the North Han River (South Korea). Production potentials were evaluated using gene-specific probes, and the harmful material production properties of strains showing positive potentials were further characterized at different temperatures in the range 15 to 30 °C. We identified six cyanobacterial strains based on 16S rDNA analysis: two morphological types (coiled and straight type) of Dolichospermum circinale, Aphanizomenon flos-aquae, Oscillatoria limosa, Planktothricoides raciborskii, Pseudanabaena mucicola, and Microcystis aeruginosa. We confirmed that cyanobacterial strains showing harmful material production potential produced the corresponding harmful material, and their production properties varied with temperature. Total harmful material production was maximal at 20~25 °C, a temperature range optimal for cell growth. However, harmful material productivity was highest at 15 °C. These results indicate that the expression of genes related to synthesis of harmful materials can vary depending on environmental conditions, resulting in variable harmful material production, even within the same cyanobacterial strains.
A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection
Authors: Sun Huifang , Dang Yaoguo , Mao Wenxin
Published: March 2018

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.
Impact of the Social and Natural Environment on Preschool-Age Children Weight
Authors: Petraviciene Inga , Grazuleviciene Regina , Andrusaityte Sandra , Dedele Audrius , Nieuwenhuijsen Mark
Published: March 2018

Background: The complex impact of environmental and social factors on preschool children being overweight/obese is unclear. We examined the associations between the levels of green space exposure and the risk of being overweight/obese for 4–6 year-old children and assessed the impact of maternal education on these associations. Methods: This cross-sectional study included 1489 mother-child pairs living in Kaunas, Lithuania, in 2012–2013. We assessed children overweight/obesity by standardized questionnaires using international body mass index cut-off points, and the level of greenness exposures by satellite-derived normalized difference vegetation index (NDVI) of each child’s home and by the distance to a nearest city park. The maternal education was used as the SES indicator. We used logistic regression models to investigate the strength of the associations. Results: Children from families with poorer maternal education, pathological mother-child relations and smoking mothers, and living in areas with less greenness exposure (NDVI-100 m), had significantly higher odds ratios of being overweight/obese. Lower maternal education and distance to a city park modified the effect of greenness cover level exposure on the risk of children being overweight/obese. Conclusions: Higher greenness exposure in the residential settings has beneficial effects on children’s physical development. The green spaces exposures for psychosocial stress management is recommended as a measure to prevent overweight/obesity among children.
Demonstrating Impact: Lessons Learned from the Queensland Aboriginal and Islander Health Council’s AOD-Our-Way Program
Authors: Cartwright Kimberly , Gray Dennis , Fewings Eddie
Published: March 2018

In this paper, we describe the innovative way in which the Queensland Aboriginal and Islander Health Council uses “clicker technology” to gather data to report on the key performance indicators of its “AOD-our-way” program, and how, with the subsequent combination of those data with other performance measures, it was possible to go beyond the initial evaluation. The paper also illustrates how the application of survey research methods could further enable enhanced reporting of program outcomes and impacts in an Indigenous context where Indigenous community controlled organisations want to build the evidence base for the issues they care about and ultimately drive their own research agendas.
Community Readiness for the Promotion of Physical Activity in Older Adults—A Cross-Sectional Comparison of Rural and Urban Communities
Authors: Gansefort Dirk , Brand Tilman , Princk Christina , Zeeb Hajo
Published: March 2018

Communities can play an important role in delivering public health programs to older adults, but they differ in the provision of local structures and resources. The community readiness (CR) approach applies a stage model of change to the community level and analyzes structures and the degree of willingness to take action on a health issue. This study compared the CR regarding the promotion of physical activity as part of healthy ageing for older adults among urban and rural communities in North-West Germany. A cross-sectional CR assessment with key respondents in 23 municipalities (11 urban and 12 rural communities) was conducted using a semi-structured interview. Interviews were scored across the five CR dimensions and global CR score was calculated (scores between 1 = no awareness and 9 = professionalization). Wilcoxon rank-sum test and hierarchical regression models were used to compare urban and rural communities. In total, 118 interviews were conducted (response rate 69.8%). On average, the communities showed moderate CR scores (4.9 ± 0.3; Range: 4.3–5.4; preplanning or preparation phase). The global CR score was slightly higher in rural than in urban communities (regression coefficient = 0.29, 95% confidence interval (CI): −0.02–0.59). The rural communities showed significantly higher CR scores in the ‘Knowledge of efforts’ dimension (0.70, 95% CI: 0.26–1.14) and in the ‘Knowledge of the issue’ (0.37, 95% CI: 0.04–0.70). Rural communities display a slightly higher CR level than urban communities. In the next step, targeted capacity building activities will be initiated among communities with low CR levels.
Exposure to Suicide in High Schools: Impact on Serious Suicidal Ideation/Behavior, Depression, Maladaptive Coping Strategies, and Attitudes toward Help-Seeking
Authors: Gould Madelyn , Lake Alison , Kleinman Marjorie , Galfalvy Hanga , Chowdhury Saba , Madnick Alison
Published: March 2018

Adolescents’ exposure to a peer’s suicide has been found to be associated with, as well as to predict, suicidal ideation and behavior. Although postvention efforts tend to be school-based, little is known about the impact of a schoolmate’s suicide on the school’s student population overall. The present study seeks to determine whether there is excess psychological morbidity among students in a school where a schoolmate has died by suicide, and whether students’ attitudes about coping and help-seeking strategies are more or less problematic in such schools. Students in twelve high schools in Suffolk and Westchester counties in New York State—2865 students at six schools where a student had died by suicide within the past six months, and 2419 students at six schools where no suicide had occurred within the current students’ tenure—completed an assessment of their suicidal ideation and behavior, depressive symptoms, coping and help-seeking attitudes, stressful life events, and friendship with suicide decedent (if applicable). No excess morbidity (i.e., serious suicidal ideation/behavior and depression) was evident among the general student population after a schoolmate’s death by suicide; however, the risk of serious suicidal ideation/behavior was elevated among students at exposed schools who had concomitant negative life events. There was a significant relationship between friendship with the decedent and morbidity, in that students who were friends, but not close friends, of the decedents had the greatest odds of serious suicidal ideation/behavior. Overall, students in exposed schools had more adaptive attitudes toward help-seeking; but this was not true of the decedents’ friends or students with concomitant negative life events. The implications of the findings for postvention strategies are discussed.
Pathogen-Derived Carbohydrate Recognition in Molluscs Immune Defense
Authors: Wang Weilin , Song Xiaorui , Wang Lingling , Song Linsheng
Published: March 2018

Self-nonself discrimination is a common theme for all of the organisms in different evolutionary branches, which is also the most fundamental step for host immune protection. Plenty of pattern recognition receptors (PRRs) with great diversity have been identified from different organisms to recognize various pathogen-associated molecular patterns (PAMPs) in the last two decades, depicting a complicated scene of host-pathogen interaction. However, the detailed mechanism of the complicate PAMPs–PRRs interactions at the contacting interface between pathogens and hosts is still not well understood. All of the cells are coated by glycosylation complex and thick carbohydrates layer. The different polysaccharides in extracellular matrix of pathogen-host are important for nonself recognition of most organisms. Coincidentally, massive expansion of PRRs, majority of which contain recognition domains of Ig, leucine-rich repeat (LRR), C-type lectin (CTL), C1q and scavenger receptor (SR), have been annotated and identified in invertebrates by screening the available genomic sequence. The phylum Mollusca is one of the largest groups in the animal kingdom with abundant biodiversity providing plenty of solutions about pathogen recognition and immune protection, which might offer a suitable model to figure out the common rules of immune recognition mechanism. The present review summarizes the diverse PRRs and common elements of various PAMPs, especially focusing on the structural and functional characteristics of canonical carbohydrate recognition proteins and some novel proteins functioning in molluscan immune defense system, with the objective to provide new ideas about the immune recognition mechanisms.
The Multiplicity of Infection-Dependent Effects of Recombinant Adenovirus Carrying HGF Gene on the Proliferation and Osteogenic Differentiation of Human Bone Marrow Mesenchymal Stem Cells
Authors: Wen Qian , Zhang Shimeng , Du Xialin , Wang Ruining , Li Yanfen , Liu Honglin , Hu Shengfeng , Zhou Chaoying , Zhou Xinying , Ma Li
Published: March 2018

Absence of effective therapeutic methods for avascular necrosis of femoral head (ANFH) is still perplexing the world’s medical community. Bone marrow mesenchymal stem cells (BMSCs) adoptive cell therapy combined with core decompression is a promising modality, which is highly dependent on the cellular activities of BMSCs. Hepatocyte growth factor (HGF) is a survival factor for BMSCs, yet the underlying mechanism is not fully elucidated. In this study, the effects of multiplicity of infections (MOIs) of recombinant adenovirus carrying HGF gene (rAd-HGF) on human BMSC proliferation and osteogenic differentiation were systemically examined. Infection of rAd-HGF produced secretory HGF and promoted hBMSC proliferation in a MOI-dependent manner, while the osteogenesis was also strengthened as indicated by enhanced calcium nodule formation with the strongest effects achieved at MOI = 250. Blocking the activities of c-MET or its downstream signaling pathways, WNT, ERK1/2, and PI3K/AKT led to differential consequents. Specifically, blockage of the WNT pathway significantly promoted osteogenic differentiation, which also showed additive effects when combined application with rAd-HGF. Our data demonstrated the pro-osteogenic effects of optimized MOIs of rAd-HGF, while inhibition of WNT pathway or activation of PI3K/AKT pathway may act as candidate adjuvant modalities for promoting osteogenic differentiation in rAd-HGF-modified hBMSC treatment on ANFH.
The Role of Oral Cavity Biofilm on Metallic Biomaterial Surface Destruction–Corrosion and Friction Aspects
Authors: Mystkowska Joanna , Niemirowicz-Laskowska Katarzyna , Łysik Dawid , Tokajuk Grażyna , Dąbrowski Jan , Bucki Robert
Published: March 2018

Metallic biomaterials in the oral cavity are exposed to many factors such as saliva, bacterial microflora, food, temperature fluctuations, and mechanical forces. Extreme conditions present in the oral cavity affect biomaterial exploitation and significantly reduce its biofunctionality, limiting the time of exploitation stability. We mainly refer to friction, corrosion, and biocorrosion processes. Saliva plays an important role and is responsible for lubrication and biofilm formation as a transporter of nutrients for microorganisms. The presence of metallic elements in the oral cavity may lead to the formation of electro-galvanic cells and, as a result, may induce corrosion. Transitional microorganisms such as sulfate-reducing bacteria may also be present among the metabolic microflora in the oral cavity, which can induce biological corrosion. Microorganisms that form a biofilm locally change the conditions on the surface of biomaterials and contribute to the intensification of the biocorrosion processes. These processes may enhance allergy to metals, inflammation, or cancer development. On the other hand, the presence of saliva and biofilm may significantly reduce friction and wear on enamel as well as on biomaterials. This work summarizes data on the influence of saliva and oral biofilms on the destruction of metallic biomaterials.
Unix Domain Sockets Applied in Android Malware Should Not Be Ignored
Authors: Jiang Xu , Mu Dejun , Zhang Huixiang
Published: March 2018

Increasingly, malicious Android apps use various methods to steal private user data without their knowledge. Detecting the leakage of private data is the focus of mobile information security. An initial investigation found that none of the existing security analysis systems can track the flow of information through Unix domain sockets to detect the leakage of private data through such sockets, which can result in zero-day exploits in the information security field. In this paper, we conduct the first systematic study on Unix domain sockets as applied in Android apps. Then, we identify scenarios in which such apps can leak private data through Unix domain sockets, which the existing dynamic taint analysis systems do not catch. Based on these insights, we propose and implement JDroid, a taint analysis system that can track information flows through Unix domain sockets effectively to detect such privacy leaks.
Multiple Input Energy Harvesting Systems for Autonomous IoT End-Nodes
Authors: Estrada-López Johan , Abuellil Amr , Zeng Zizhen , Sánchez-Sinencio Edgar
Published: March 2018

The Internet-of-Things (IoT) paradigm is under constant development and is being enabled by the latest research work from both industrial and academic communities. Among the many contributions in such diverse areas as sensor manufacturing, network protocols, and wireless communications, energy harvesting techniques stand out as a key enabling technology for the realization of batteryless IoT end-node systems. In this paper, we give an overview of the recent developments in circuit design for ultra-low power management units (PMUs), focusing mainly in the architectures and techniques required for energy harvesting from multiple heterogeneous sources. The paper starts by discussing a general structure for IoT end-nodes and the main characteristics of PMUs for energy harvesting. Then, an overview is given of different published works for multisource power harvesting, observing their main advantages and disadvantages and comparing their performance. Finally, some open areas of research in multisource harvesting are observed and relevant conclusions are given.
Monitoring Litter Inputs from the Adour River (Southwest France) to the Marine Environment
Authors: Bruge Antoine , Barreau Cristina , Carlot Jérémy , Collin Hélène , Moreno Clément , Maison Philippe
Published: March 2018

Rivers are major pathways for litter to enter the ocean, especially plastic debris. Yet, further research is needed to improve knowledge on rivers contribution, increase data availability, refine litter origins, and develop relevant solutions to limit riverine litter inputs. This study presents the results of three years of aquatic litter monitoring on the Adour river catchment (southwest of France). Litter monitoring consisted of collecting all litter stranded on river banks or stuck in the riparian vegetation in defined areas identified from cartographic and hydromorphological analyses, and with the support of local stakeholders. Litter samples were then sorted and counted according to a list of items containing 130 categories. Since 2014, 278 litter samplings were carried out, and 120,632 litter items were collected, sorted, and counted. 41% of litter could not be identified due to high degradation. Food and beverage packaging, smoking-related items, sewage related debris, fishery and mariculture gear, and common household items represented around 70% of identifiable items. Overall, the present study contributes to our knowledge of litter sources and pathways, with the target of reducing the amounts entering the ocean. The long-term application of this monitoring is a way forward to measure societal changes as well as assess effectiveness of measures.
Adult Word Learning as a Function of Neighborhood Density
Authors: Jones Skott
Published: March 2018

Previous studies exploring the influence of neighborhood density (ND) during adult word learning have largely relied on tasks designed for young, preliterate children. In order to examine effects of ND on adult word learning during an ecologically valid task, eight nonwords varying in neighborhood density (4 dense, 4 sparse) were taught to 50 typical adults in the context of a lecture. Half of the participants (n = 25) were solely exposed to the phonological forms of the nonwords, while the other half of the participants (n = 25) were exposed to both the phonological forms and orthographic representations. Results indicated that participants who only heard the nonwords learned more dense words than sparse words, similar to prior work. However, participants who heard as well as saw the nonwords learned dense words and sparse words to a similar degree, in addition to overall greater learning of sparse words. Thus, learning of sparse words can improve when orthographic information supplements the phonological information. An account of working memory is re-visited to interpret the results related to auditory and visual processing during lexical acquisition.