bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantifying the Spatiotemporal Trends of Canopy Layer Heat Island (CLHI) and Its Driving Factors over Wuhan, China with Satellite Remote Sensing
Authors: Li Long , Huang Xin , Li Jiayi , Wen Dawei
Published: May 2017

Canopy layer heat islands (CLHIs) in urban areas are a growing problem. In recent decades, the key issues have been how to monitor CLHIs at a large scale, and how to optimize the urban landscape to mitigate CLHIs. Taking the city of Wuhan as a case study, we examine the spatiotemporal trends of the CLHI along urban-rural gradients, including the intensity and footprint, based on satellite observations and ground weather station data. The results show that CLHI intensity (CLHII) decays exponentially and significantly along the urban-rural gradients, and the CLHI footprint varies substantially and especially in winter. We then quantify the driving factors of the CLHI by establishing multiple linear regression (MLR) models with the assistance of ZY-3 satellite data (with a spatial resolution of 2.5 m), and obtain five main findings: (1) built-up area had a significant positive effect on daily mean CLHII in summer and a negative effect in winter; (2) vegetation had significant inhibiting effects on daily mean CLHII in both summer and winter; (3) absolute humidity has a significant inhibiting effect on daily mean CLHII in summer and a positive effect in winter; (4) anthropogenic heat emissions exacerbated the daily mean CLHII by about 0.19 °C (90% confidence interval −0.06–0.44 °C) on 17 September 2013 and by about 0.06 °C (−0.06–0.19 °C) on 23 January 2014; and (5) if most of the urban area is transformed into roads (i.e., an extreme case), we estimate that the daily mean CLHII would reach 1.41 °C (0.38–2.44 °C) on 17 September 2013 and 0.14 °C (0.08–0.2 °C) on 23 January 2014 in Wuhan metropolitan area. Overall, the results provide new insights into quantifying the CLHI and its driving factors, to enhance our understanding of urban heat islands.
An Enhanced Satellite-Based Algorithm for Detecting and Tracking Dust Outbreaks by Means of SEVIRI Data
Authors: Marchese Francesco , Sannazzaro Filomena , Falconieri Alfredo , Filizzola Carolina , Pergola Nicola , Tramutoli Valerio
Published: May 2017

Dust outbreaks are meteorological phenomena of great interest for scientists and authorities (because of their impact on the climate, environment, and human activities), which may be detected, monitored, and characterized from space using different methods and procedures. Among the recent dust detection algorithms, the RSTDUST multi-temporal technique has provided good results in different geographic areas (e.g., Mediterranean basin; Arabian Peninsula), exhibiting a better performance than traditional split window methods, in spite of some limitations. In this study, we present an optimized configuration of this technique, which better exploits data provided by Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard Meteosat Second Generation (MSG) satellites to address those issues (e.g., sensitivity reduction over arid and semi-arid regions; dependence on some meteorological clouds). Three massive dust events affecting Europe and the Mediterranean basin in May 2008/2010 are analysed in this work, using information provided by some independent and well-established aerosol products to assess the achieved results. The study shows that the proposed algorithm, christened eRSTDUST (i.e., enhanced RSTDUST), which provides qualitative information about dust outbreaks, is capable of increasing the trade-off between reliability and sensitivity. The results encourage further experimentations of this method in other periods of the year, also exploiting data provided by different satellite sensors, for better evaluating the advantages arising from the use of this dust detection technique in operational scenarios.
Urbanization Effects on Vegetation and Surface Urban Heat Islands in China’s Yangtze River Basin
Authors: Yao Rui , Wang Lunche , Gui Xuan , Zheng Yukun , Zhang Haoming , Huang Xin
Published: May 2017

In the context of rapid urbanization, systematic research about temporal trends of urbanization effects (UEs) on urban environment is needed. In this study, MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature (LST) data and enhanced vegetation index (EVI) data were used to analyze the temporal trends of UEs on vegetation and surface urban heat islands (SUHIs) at 10 big cities in Yangtze River Basin (YRB), China during 2001–2016. The urban and rural areas in each city were derived from MODIS land cover data and nighttime light data. It was found that the UEs on vegetation and SUHIs were increasingly significant in YRB, China. The ∆EVI (the UEs on vegetation, urban EVI minus rural EVI) decreased significantly (p < 0.05) in 9, 7 and 5 out of 10 cities for annual, summer and winter, respectively. The annual daytime and nighttime SUHI intensity (SUHII; urban LST minus rural LST) increased significantly (p < 0.05) in 10 and 4 out of 10 cities, respectively. The increasing rate of daytime SUHII and the decreasing rate of ∆EVI in old urban areas were much less than the whole urban area (0.034 °C/year vs. 0.077 °C/year for annual daytime SUHII; 0.00209/year vs. 0.00329/year for ∆EVI). The correlation analyses indicated that the annual and summer daytime SUHII were significantly negatively correlated with ∆EVI in most cities. The decreasing ∆EVI may also contribute to the increasing nighttime SUHII. In addition, the significant negative correlations (r < −0.5, p < 0.1) between inter-annual linear slope of ∆EVI and SUHII were observed, which suggested that the cities with higher decreasing rates of ∆EVI may show higher increasing rates of SUHII.
A Novel Complex-Coefficient In-Band Interference Suppression Algorithm for Cognitive Ultra-Wide Band Wireless Sensors Networks
Authors: Xiong Hailiang , Zhang Wensheng , Xu Hongji , Du Zhengfeng , Tang Huaibin , Li Jing
Published: May 2017

With the rapid development of wireless communication systems and electronic techniques, the limited frequency spectrum resources are shared with various wireless devices, leading to a crowded and challenging coexistence circumstance. Cognitive radio (CR) and ultra-wide band (UWB), as sophisticated wireless techniques, have been considered as significant solutions to solve the harmonious coexistence issues. UWB wireless sensors can share the spectrum with primary user (PU) systems without harmful interference. The in-band interference of UWB systems should be considered because such interference can severely affect the transmissions of UWB wireless systems. In order to solve the in-band interference issues for UWB wireless sensor networks (WSN), a novel in-band narrow band interferences (NBIs) elimination scheme is proposed in this paper. The proposed narrow band interferences suppression scheme is based on a novel complex-coefficient adaptive notch filter unit with a single constrained zero-pole pair. Moreover, in order to reduce the computation complexity of the proposed scheme, an adaptive complex-coefficient iterative method based on two-order Taylor series is designed. To cope with multiple narrow band interferences, a linear cascaded high order adaptive filter and a cyclic cascaded high order matrix adaptive filter (CCHOMAF) interference suppression algorithm based on the basic adaptive notch filter unit are also presented. The theoretical analysis and numerical simulation results indicate that the proposed CCHOMAF algorithm can achieve better performance in terms of average bit error rate for UWB WSNs. The proposed in-band NBIs elimination scheme can significantly improve the reception performance of low-cost and low-power UWB wireless systems.
Internal Model-Based Robust Tracking Control Design for the MEMS Electromagnetic Micromirror
Authors: Tan Jiazheng , Sun Weijie , Yeow John
Published: May 2017

The micromirror based on micro-electro-mechanical systems (MEMS) technology is widely employed in different areas, such as scanning, imaging and optical switching. This paper studies the MEMS electromagnetic micromirror for scanning or imaging application. In these application scenarios, the micromirror is required to track the command sinusoidal signal, which can be converted to an output regulation problem theoretically. In this paper, based on the internal model principle, the output regulation problem is solved by designing a robust controller that is able to force the micromirror to track the command signal accurately. The proposed controller relies little on the accuracy of the model. Further, the proposed controller is implemented, and its effectiveness is examined by experiments. The experimental results demonstrate that the performance of the proposed controller is satisfying.
Modelling and Optimization of Four-Segment Shielding Coils of Current Transformers
Authors: Gao Yucheng , Zhao Wei , Wang Qing , Qu Kaifeng , Li He , Shao Haiming , Huang Songling
Published: May 2017

Applying shielding coils is a practical way to protect current transformers (CTs) for large-capacity generators from the intensive magnetic interference produced by adjacent bus-bars. The aim of this study is to build a simple analytical model for the shielding coils, from which the optimization of the shielding coils can be calculated effectively. Based on an existing stray flux model, a new analytical model for the leakage flux of partial coils is presented, and finite element method-based simulations are carried out to develop empirical equations for the core-pickup factors of the models. Using the flux models, a model of the common four-segment shielding coils is derived. Furthermore, a theoretical analysis is carried out on the optimal performance of the four-segment shielding coils in a typical six-bus-bars scenario. It turns out that the “all parallel” shielding coils with a 45° starting position have the best shielding performance, whereas the “separated loop” shielding coils with a 0° starting position feature the lowest heating value. Physical experiments were performed, which verified all the models and the conclusions proposed in the paper. In addition, for shielding coils with other than the four-segment configuration, the analysis process will generally be the same.
A Multiple Sensors Platform Method for Power Line Inspection Based on a Large Unmanned Helicopter
Authors: Xie Xiaowei , Liu Zhengjun , Xu Caijun , Zhang Yongzhen
Published: May 2017

Many theoretical and experimental studies have been carried out in order to improve the efficiency and reduce labor for power line inspection, but problems related to stability, efficiency, and comprehensiveness still exist. This paper presents a multiple sensors platform method for overhead power line inspection based on the use of a large unmanned helicopter. Compared with the existing methods, multiple sensors can realize synchronized inspection on all power line components and surrounding objects within one sortie. Flight safety of unmanned helicopter, scheduling of sensors and exact tracking on power line components are very important aspects when using the proposed multiple sensors platform, therefore this paper introduces in detail the planning method for the flight path of the unmanned helicopter and tasks of the sensors before inspecting power lines, and the method used for tracking power lines and insulators automatically during the inspection process. To validate the method, experiments on a transmission line at Qingyuan in Guangdong Province were carried out, the results show that the proposed method is effective for power line inspection.
DOA Finding with Support Vector Regression Based Forward–Backward Linear Prediction
Authors: Pan Jingjing , Wang Yide , Le Bastard Cédric , Wang Tianzhen
Published: May 2017

Direction-of-arrival (DOA) estimation has drawn considerable attention in array signal processing, particularly with coherent signals and a limited number of snapshots. Forward–backward linear prediction (FBLP) is able to directly deal with coherent signals. Support vector regression (SVR) is robust with small samples. This paper proposes the combination of the advantages of FBLP and SVR in the estimation of DOAs of coherent incoming signals with low snapshots. The performance of the proposed method is validated with numerical simulations in coherent scenarios, in terms of different angle separations, numbers of snapshots, and signal-to-noise ratios (SNRs). Simulation results show the effectiveness of the proposed method.
Generalized Chirp Scaling Combined with Baseband Azimuth Scaling Algorithm for Large Bandwidth Sliding Spotlight SAR Imaging
Authors: Yi Tianzhu , He Zhihua , He Feng , Dong Zhen , Wu Manqing
Published: May 2017

This paper presents an efficient and precise imaging algorithm for the large bandwidth sliding spotlight synthetic aperture radar (SAR). The existing sub-aperture processing method based on the baseband azimuth scaling (BAS) algorithm cannot cope with the high order phase coupling along the range and azimuth dimensions. This coupling problem causes defocusing along the range and azimuth dimensions. This paper proposes a generalized chirp scaling (GCS)-BAS processing algorithm, which is based on the GCS algorithm. It successfully mitigates the deep focus along the range dimension of a sub-aperture of the large bandwidth sliding spotlight SAR, as well as high order phase coupling along the range and azimuth dimensions. Additionally, the azimuth focusing can be achieved by this azimuth scaling method. Simulation results demonstrate the ability of the GCS-BAS algorithm to process the large bandwidth sliding spotlight SAR data. It is proven that great improvements of the focus depth and imaging accuracy are obtained via the GCS-BAS algorithm.
Belief Interval of Dempster-Shafer Theory for Line-of-Sight Identification in Indoor Positioning Applications
Authors: Wu Jinwu , Zhao Tingyu , Li Shang , Own Chung-Ming
Published: May 2017

Location data are among the most widely used contextual data in context-aware and ubiquitous computing applications. Numerous systems with distinct deployment costs and levels of positioning accuracy have been developed over the past decade for indoor positioning purposes. The most useful method focuses on the received signal strength (RSS) and provides a set of signal transmission access points. Furthermore, most positioning systems are based on non-line-of-sight (NLOS) rather than line-of-sight (LOS) conditions, and this cause ranging errors for location predictions. Hence, manually compiling a fingerprint database measuring RSS involves high costs and is thus impractical in online prediction environments. In our proposed method, a comparison method is derived on the basis of belief intervals, as proposed in Dempster-Shafer theory, and the signal features are characterized on the LOS and NLOS conditions for different field experiments. The system performance levels were examined with different features and under different environments through robust testing and by using several widely used machine learning methods. The results showed that the proposed method can not only retain positioning accuracy but also save computation time in location predictions.
Decoupling and Decomposition Analysis of Carbon Emissions from Electric Output in the United States
Authors: Jiang Xue-Ting , Li Rongrong
Published: May 2017

The rapid growth of the electricity sector in the United States has been accompanied by a dramatic rise in CO2 emissions. To understand the driving effects that contribute to the increase in CO2 emissions during electricity generation, as well as the relationship between the emissions and electricity output, a novel decoupling index on the basis of the multilevel logarithmic mean divisia index (LMDI) method is presented in this paper. The results of our study indicate that, on the one hand, the electricity output effect played a crucial role in increasing CO2 emissions. On the other hand, the energy mix effect and the conversion efficiency effect made a contribution to curbing the related CO2 emissions in most of the years covered by our study. The power production structure effect and emission factor effect each played a negative role in the decoupling process. No decoupling was the main status during most of the years covered in our study, with a strong decoupling status being the least common state.
An Agent-Based Model to Project China’s Energy Consumption and Carbon Emission Peaks at Multiple Levels
Authors: Wu Jing , Mohamed Rayman , Wang Zheng
Published: May 2017

To assess whether China’s emissions will peak around 2030, we forecast energy consumption and carbon emissions in China. We use an agent-based model driven by enterprises’ innovation. Results show some differences in both energy consumption peaks and carbon emission peaks when we compare trends at different levels. We find that carbon emissions and energy consumption will peak in 2027 and 2028, respectively. However, the primary, secondary, and tertiary industries will reach energy consumption in different years: 2023, 2029, and 2022, respectively, and reach carbon emission peaks in 2022, 2028, and 2022, respectively. At the sectoral level, we find a wider range of energy consumption peaks and carbon emission peaks. Peak energy consumption occurs between 2020 and 2034, and peak carbon emissions between 2020 and 2032. Commercial and catering businesses, utilities and resident services, and finance and insurance achieve peak energy consumption and carbon emissions earliest in 2020, while building materials and other non-metallic mineral products manufacturing and metal products manufacturing are the two latest sectors to reach peak energy consumption and emissions, in 2034 and 2032, respectively.
Deep Learning-Based Corporate Performance Prediction Model Considering Technical Capability
Authors: Lee Joonhyuck , Jang Dongsik , Park Sangsung
Published: May 2017

Many studies have predicted the future performance of companies for the purpose of making investment decisions. Most of these are based on the qualitative judgments of experts in related industries, who consider various financial and firm performance information. With recent developments in data processing technology, studies have started to use machine learning techniques to predict corporate performance. For example, deep neural network-based prediction models are again attracting attention, and are now widely used in constructing prediction and classification models. In this study, we propose a deep neural network-based corporate performance prediction model that uses a company’s financial and patent indicators as predictors. The proposed model includes an unsupervised learning phase and a fine-tuning phase. The learning phase uses a restricted Boltzmann machine. The fine-tuning phase uses a backpropagation algorithm and a relatively up-to-date training data set that reflects the latest trends in the relationship between predictors and corporate performance.
Meteorological Drought Analysis in the Lower Mekong Basin Using Satellite-Based Long-Term CHIRPS Product
Authors: Guo Hao , Bao Anming , Liu Tie , Ndayisaba Felix , He Daming , Kurban Alishir , De Maeyer Philippe
Published: May 2017

Lower Mekong Basin (LMB) experiences a recurrent drought phenomenon. However, few studies have focused on drought monitoring in this region due to lack of ground observations. The newly released Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) with a long-term record and high resolution has a great potential for drought monitoring. Based on the assessment of CHIRPS for capturing precipitation and monitoring drought, this study aims to evaluate the drought condition in LMB by using satellite-based CHIRPS from January 1981 to July 2016. The Standardized Precipitation Index (SPI) at various time scales (1–12-month) is computed to identify and describe drought events. Results suggest that CHIRPS can properly capture the drought characteristics at various time scales with the best performance at three-month time scale. Based on high-resolution long-term CHIRPS, it is found that LMB experienced four severe droughts during the last three decades with the longest one in 1991–1994 for 38 months and the driest one in 2015–2016 with drought affected area up to 75.6%. Droughts tend to occur over the north and south part of LMB with higher frequency, and Mekong Delta seems to experience more long-term and extreme drought events. Severe droughts have significant impacts on vegetation condition.
Two Saporin-Containing Immunotoxins Specific for CD20 and CD22 Show Different Behavior in Killing Lymphoma Cells
Authors: Polito Letizia , Mercatelli Daniele , Bortolotti Massimo , Maiello Stefania , Djemil Alice , Battelli Maria , Bolognesi Andrea
Published: May 2017

Immunotoxins (ITs) are hybrid proteins combining the binding specificity of antibodies with the cytocidal properties of toxins. They represent a promising approach to lymphoma therapy. The cytotoxicity of two immunotoxins obtained by chemical conjugation of the plant toxin saporin-S6 with the anti-CD20 chimeric antibody rituximab and the anti-CD22 murine antibody OM124 were evaluated on the CD20-/CD22-positive cell line Raji. Both ITs showed strong cytotoxicity for Raji cells, but the anti-CD22 IT was two logs more efficient in killing, probably because of its faster internalization. The anti-CD22 IT gave slower but greater caspase activation than the anti-CD20 IT. The cytotoxic effect of both immunotoxins can be partially prevented by either the pan-caspase inhibitor Z-VAD or the necroptosis inhibitor necrostatin-1. Oxidative stress seems to be involved in the cell killing activity of anti-CD20 IT, as demonstrated by the protective role of the H2O2 scavenger catalase, but not in that of anti-CD22 IT. Moreover, the IT toxicity can be augmented by the contemporary administration of other chemotherapeutic drugs, such as PS-341, MG-132, and fludarabine. These results contribute to the understanding of the immunotoxin mechanism of action that is required for their clinical use, either alone or in combination with other drugs.
Observational Consequences of an Interacting Multiverse
Authors: Robles-Pérez Salvador
Published: May 2017

The observability of the multiverse is at the very root of its physical significance as a scientific proposal. In this conference we present, within the third quantization formalism, an interacting scheme between the wave functions of different universes and analyze the effects of some particular values of the coupling function. One of the main consequences of the interaction between universes can be the appearance of a pre-inflationary stage in the evolution of the universes that might leave observable consequences in the properties of the CMB.
The Critical Depth of Freeze-Thaw Soil under Different Types of Snow Cover
Authors: Fu Qiang , Hou Renjie , Li Tianxiao , Yan Peiru , Ma Ziao
Published: May 2017

Snow cover is the most common upper boundary condition influencing the soil freeze-thaw process in the black soil farming area of northern China. Snow is a porous dielectric cover, and its unique physical properties affect the soil moisture diffusion, heat conduction, freezing rate and other variables. To understand the spatial distribution of the soil water-heat and the variable characteristics of the critical depth of the soil water and heat, we used field data to analyze the freezing rate of soil and the extent of variation in soil water-heat in a unit soil layer under bare land (BL), natural snow (NS), compacted snow (CS) and thick snow (TS) treatments. The critical depth of the soil water and heat activity under different snow covers were determined based on the results of the analysis, and the variation fitting curve of the difference sequences on the soil temperature and water content between different soil layers and the surface 5-cm soil layer were used to verify the critical depth. The results were as follows: snow cover slowed the rate of soil freezing, and the soil freezing rate under the NS, CS and TS treatments decreased by 0.099 cm/day, 0.147 cm/day and 0.307 cm/day, respectively, compared with that under BL. In addition, the soil thawing time was delayed, and the effect was more significant with increased snow cover. During freeze-thaw cycles, the extent of variation in the water and heat time series in the shallow soil was relatively large, while there was less variation in the deep layer. There was a critical stratum in the vertical surface during hydrothermal migration, wherein the critical depth of soil water and heat change gradually increased with increasing snow cover. The variance in differences between the surface layer and both the soil water and heat in the different layers exhibited “steady-rising-steady” behavior, and the inflection point of the curve is the critical depth of soil freezing and thawing. This critical layer is a demarcation point between frozen soil and non-frozen soil, delineating the boundary between soil water and heat migration and non-migration. Furthermore, with increasing snow cover thickness and increasing density, the critical depth gradually increased.
The Performance and Potentials of the CryoSat-2 SAR and SARIn Modes for Lake Level Estimation
Authors: Nielsen Karina , Stenseng Lars , Andersen Ole , Knudsen Per
Published: May 2017

Over the last few decades, satellite altimetry has proven to be valuable for monitoring lake levels. With the new generation of altimetry missions, CryoSat-2 and Sentinel-3, which operate in Synthetic Aperture Radar (SAR) and SAR Interferometric (SARIn) modes, the footprint size is reduced to approximately 300 m in the along-track direction. Here, the performance of these new modes is investigated in terms of uncertainty of the estimated water level from CryoSat-2 data and the agreement with in situ data. The data quality is compared to conventional low resolution mode (LRM) altimetry products from Envisat, and the performance as a function of the lake area is tested. Based on a sample of 145 lakes with areas ranging from a few to several thousand km 2 , the CryoSat-2 results show an overall superior performance. For lakes with an area below 100 km 2 , the uncertainty of the lake levels is only half of that of the Envisat results. Generally, the CryoSat-2 lake levels also show a better agreement with the in situ data. The lower uncertainty of the CryoSat-2 results entails a more detailed description of water level variations.
Evaluation of the SMOS-Derived Soil Water Deficit Index as Agricultural Drought Index in Northeast of Brazil
Authors: Paredes-Trejo Franklin , Barbosa Humberto
Published: May 2017

Northeast Brazil (NEB) has recently experienced one of its worst droughts in the last decades, with large losses on rainfed agriculture. Soil moisture is the main variable to monitor agricultural drought. The remote sensing approach for drought monitoring has been enriched with the launch of the Soil Moisture and Ocean Salinity (SMOS) in November 2009 by European Space Agency (ESA). In this work, the Soil Water Deficit Index (SWDI) was calculated using the SMOS L2 soil moisture in the NEB. The SMOS-derived SWDI data (SWDIS) were evaluated against the atmospheric water deficit (AWD) calculated from in situ observations. Comparisons were made at seven-day and 0.25° scales, over the time-span of June 2010 to December 2013. It was found that the SWDIS has a reasonably good overall performance in terms of the drought-weeks detection (skill = 0.986) and capture of the upper soil moisture temporal dynamic (r = 0.652), implying that the SWDIS could be used to track agricultural droughts. Furthermore, SWDIS shows poor performance at sites located in mountains regions affected by severe droughts (−0.10 ≤ r ≤ 0.10). It is also noted that the vegetal cover/use, climate regime, and soil texture have little influence on the AWD-SWDIS coupling.
Optimising Fuzzy Neural Network Architecture for Dissolved Oxygen Prediction and Risk Analysis
Authors: Khan Usman , Valeo Caterina
Published: May 2017

A fuzzy neural network method is proposed to predict minimum daily dissolved oxygen concentration in the Bow River, in Calgary, Canada. Owing to the highly complex and uncertain physical system, a data-driven and fuzzy number based approach is preferred over traditional approaches. The inputs to the model are abiotic factors, namely water temperature and flow rate. An approach to select the optimum architecture of the neural network is proposed. The total uncertainty of the system is captured in the fuzzy numbers weights and biases of the neural network. Model predictions are compared to the traditional, non-fuzzy approach, which shows that the proposed method captures more low DO events. Model output is then used to quantify the risk of low DO for different conditions.
2017 National Institute of Justice Forensic Science Research and Development Symposium
Authors: Jones Nicole S. , LaPorte Gerald
Published: May 2017

The 2017 National Institute of Justice (NIJ) Forensic Science Research and Development (R&D) Symposium is intended to promote collaboration and enhance knowledge transfer of NIJ-funded research. The NIJ Forensic Science R&D Program funds both basic or applied R&D projects that will (1) increase the body of knowledge to guide and inform forensic science policy and practice or (2) result in the production of useful materials, devices, systems, or methods that have the potential for forensic application. The intent of this program is to direct the findings of basic scientific research; research and development in broader scientific fields applicable to forensic science; and ongoing forensic science research toward the development of highly discriminating, accurate, reliable, cost-effective, and rapid methods for the identification, analysis, and interpretation of physical evidence for criminal justice purposes.
OPTIMIZATION OF SIGNAL-TIMING PARAMETERS FOR THE INTERSECTION WITH HOOK TURNS
Authors: Bie Yiming , Cheng Shaowu , Liu Zhiyuan
Published: May 2017

A Hook Turn (HT) traffic control scheme has been successfully implemented in urban Melbourne (Australia) ever since 1950s, for the regulation of right-turning vehicles at the intersections (in traffic system where driving is on the left). This paper addresses the optimal signal-timing of the HT scheme, which is still an open question in the literature. Under the HT scheme, right-turning vehicles should enter the intersection and stop at a waiting area. Hence, it is common to have a spillback from these vehicles if the right-turning volume is high. This paper provides an in-depth analysis of the spillback phenomenon on the traffic movements and the average delays, and proposes the models for the calculation of average delay in different cases. With the aim of minimizing the average delay of all the vehicles, a nonlinear integer-programming model is proposed for the optimal signal-timing problem of HT scheme. A Genetic Algorithm (GA) is used to solve this model, considering the complexity of its objective function. A realistic example developed based on one intersection with HT in urban Melbourne is adopted to assess the proposed methodology. Based on real survey data in morning peak and nonpeak hours, we compare the existing signal plan and optimal plan. The numerical test shows that compared with the existing plan, the optimal plan can reduce the average delay for 12.05% in peak hour and 19.96% in nonpeak hour. Sensitive analysis is also conducted to investigate the variation of right-turning ratio on the intersection operational performance.
RESEARCH ON SHIP AUTONOMOUS STEERING CONTROL FOR SHORT-SEA SHIPPING PROBLEMS
Authors: Jakovlev Sergej , Andziulis Arūnas , Daranda Andrius , Voznak Miroslav , Eglynas Tomas
Published: May 2017

Today most ship rotation angle (steering control during movement) increase or decrease is done using an operator on deck or the auxiliary system in the ships engine room. Formal regulations suggest using manual inspection of the ship rotation and the work effectiveness of the engine during manoeuvring in ports and in the open sea regions. The accuracy of this procedure is very low and depends on the personnel of the deck. Therefore, automation and computer control systems are constantly required to assist the human eye. This problem becomes clearly visible when dealing with full ship autonomy in the open sea in the short-sea shipping regions. The trend of maritime technology development will only increase in the area of human interaction decrease with the physical operations and the shipping procedures, which will lead to the future full ship autonomy in the open sea regions around the globe. With the growing automation technologies, predictive control can prove to be a better approach than the traditionally applied visual inspection policy and linear control models. Ship full autonomy is also linked to the ship’s machinery regular repair and maintenance that has to be carried out for delivering satisfactory performance and minimizing downtime during transportation operations. In this paper, current stages of development of the intelligent transportation system concept are discussed for the ship autonomy in manoeuvring control and a robust ships’ systems integration and communication system concept is presented for several normal and abnormal situations: high-traffic, potentially dangerous situations or port approaching or ship maintenance, with the capability to solve problems with the limited human interface and with a remote control possibility. Then, simplified ship steering motor system for the main pump is analysed for rotation control using control voltage from the converters. Retrieved data from a small experimental control motor is used for the predictive control approach using two different methods: a neural network trained with Basic Levenberg– Marquardt Method and a Linear Model.
Intersectionality and the Construction of Inclusive Schools
Authors: Petersen Amy J.
Published: May 2017

This chapter explores the educational experiences of an African American woman labeled with a disability and from a low socioeconomic group. Grounded in a social and historical context, this chapters uses qualitative research and intersectional theory to understand her experiences in a holistic manner. Subsequent implications for educators are discussed, including the need to: 1) understand students through the social model, 2) acknowledge the intersection of multiple marginalized identities, and 3) assist students in advocacy and empowerment.
Cultivating Communities of Inclusive Practice
Authors: Curran Christina M. , Hawbaker Becky Wilson
Published: May 2017

Significant disparities in educational outcome, opportunity, and achievement endure for students with disabilities and those from culturally and linguistically diverse groups. A need for effective, responsive, and inclusive practices in schools is imperative. Educators are at the heart of providing the challenging, responsive education that each child and adolescent deserves. Professional development is the lever of change, but can or help or hinder educators in improving instructional and school practices that result in improved outcomes for all students. This chapter examines the evidence base surrounding professional development and inclusive practice. Four approaches to professional development supporting more transformative professional learning and change are featured: inquiry groups (teacher study groups and lesson study); coaching, Professional Learning Communities; and Professional Development Schools. Snapshots to practice are included with each approach to provide integrated descriptive examples of varied inclusive professional development practices.
Creating Inclusive Classroom Communities Through Social and Emotional Learning to Reduce Social Marginalization Among Students
Authors: Preast June L. , Bowman Nicky , Rose Chad A.
Published: May 2017

A student's social and emotional skills are related to how well equipped they are to address and adapt to the academic, behavioral, and functional demands of the classroom. With the increased attention on academic outcomes, the opportunities to teach social and emotional learning (SEL) are limited. However, SEL approaches have demonstrated increases in functional, behavioral, and academic outcomes for school aged youth. This chapter is designed to identify the key components of SEL, provide guidance in implementation, and describe how SEL can help reduce the social marginalization among youth with disabilities and those at-risk for disability identification.
Inclusive Recreation as Part of the IEP Process
Authors: Davison Amy M. , Scholl Kathleen G.
Published: May 2017

Individuals with disabilities have a long history of exclusion from both education and recreation settings. Until the 1970s, parents caring for their child with a disability was a private, isolated activity and an extreme hardship. Today, children with disabilities are usually included in general education classrooms with their typically developing peers. For inclusive education to be successful, the IEP team must focus on the collaborative aspects and possible community-wide solutions for the child's best interests by looking outside the classroom to examine the array of community supports that interconnect with the child's education and long-term transition outcomes over multiple seasons, including summer months. This chapter provides background on inclusive recreation services, including suggestions for how a multidisciplinary IEP team can incorporate existing recreation services and community programs as extended supports within a child's IEP or transition plan, using Bronfenbrenner's ecological systems framework.
The Role of Bibliotherapy and Therapeutic Storytelling in Creating Inclusive Classroom Communities
Authors: Mihić Sanja Skočić , Maich Kimberly , Belcher Christina , Perrow Susan , Barišić Ana , Ramić Nadia Novak
Published: May 2017

This chapter reviews the literature of using the bibliotherapy as a strategy to provide empathy and understanding for diverse behaviors and emotions. Since diverse learners may have difficulties in developing social skills and emotional regulation, the development of a positive and respectful social climate is critical in encouraging all students to be more accepting of individual differences and challenges. Using the Lessac bio-dynamic approach and verbal intonation and dynamic articulation of the text, enriches students' experience and allows students with difficulties to recognize the intention of the character and to interactively participate with movements. The unique model of therapeutic storytelling with Lessac Kinestetis is presented as a teaching strategy for the development of the skills of diverse learners, as well all students in the inclusive classroom.
Creating Inclusive Classroom
Authors: Li Jiacheng , Li Yan , Huang Ying , Huang Liujuan , Zheng Binyao
Published: May 2017

From the 1980s, there are three steps to understand and adopt the inclusive education belief and theory in China. In today's Chinese schools, the typical inclusive education is implemented at the classroom level, but with unique context and content compared with the practices in the Western world. Banzhuren, a very special role in Chinese school, has witnessed the development of each child and plays a very important role in student development. Banzhuren creates the inclusive atmosphere for all students, engages every student in the classroom-based activities, and works with other teachers and parents to develop the classroom community. Authors surveyed students in two classes on their experience, values, understanding and expectation on inclusive education in the classroom. Based on the data, the authors found that the banzhurens involved have fulfilled their potentials to achieve the inclusive classroom by multiple ways. The authors discussed the practical application, the limitations of the research, and future research directions about the inclusive classroom in China as well.
Data System-Embedded Analysis Support's Implications for Latino Students and Diverse Classrooms
Authors: Rankin Jenny Grant
Published: May 2017

Urban school populations are particularly diverse, requiring teachers to see to a broad spectrum of student needs. Latinos are the largest and fastest growing racial/ethnic minority group of students in the U.S., and the majority of Latino students live in urban areas. Data can be a powerful tool when used by teachers to target specific student needs, especially those of subgroups with a history of academic struggle. Latino students are commonly featured in not just one, but three large subgroups that typically struggle academically when compared to peers outside these subgroups: the Hispanic, Socio-economically Disadvantaged, and English Learner subgroups. It is vital teachers use data to better understand and meet these students' needs. However, such data use can only benefit students if teachers understand its meaning and implications. This chapter highlights study findings that can significantly improve teachers' ability to use data to help Latinos and other students in diverse classrooms.
Which primary care model? A qualitative analysis of ward-based outreach teams in South Africa
Authors: Marcus Tessa S. , Hugo Jannie , Jinabhai Champak C.
Published: May 2017

Abstract: Globally, models of extending universal health coverage through primary care are influenced by country-specific systems of health care and disease management. In 2015 a rapid assessment of the ward-based outreach component of primary care reengineering was commissioned to understand implementation and rollout challenges.Aim: This article aims to describe middle- and lower-level managers’ understanding of ward-based outreach teams (WBOTs) and the problems of authority, jurisdiction and practical functioning that arise from the way the model is constructed and has been operationalised.Setting: Data are drawn from a rapid assessment of National Health Insurance (NHI) pilot sites in seven provinces.Methods: The study used a modified version of CASCADE. Peer-review teams of public health researchers and district/sub-district managers collected data in two sites per province between March and July 2015.Results: Respondents unequivocally support the strategy to extend primary health care services to people in their homes and communities both because it is responsive to the family context of individual health and because it reaches marginal people. They, however, identify critical issues that arise from basing WBOTs in facilities, including unspecific team leadership, inadequate supervision, poorly constituted teams, limited community reach and serious infrastructural and material under-provision.Conclusion: Many of the shortcomings of a facility-based extension model can be addressed by an independently resourced, geographic, community-based model of fully constituted teams that are clinically and organisationally supported in an integrated district health system. However, a community-oriented primary care approach will still have to grapple with overarching framework problems.
Foundation phase teachers’ interpretation of the life skills programme with regard to the teaching of natural science
Authors: Beni Saritha , Stears Michele , James Angela
Published: May 2017

Scientific literacy should be promoted through the teaching of science from Grade R and for this to happen, teachers need to understand what science should be taught and how it should be taught. This interpretive, qualitative study explores the degree to which four foundation phase teachers interpret the life skills programme with regard to the teaching of natural science by using an adapted version of a theory of implementation. Analyses of a questionnaire, documents (Revised National Curriculum Statement and lesson plans) and interviews enabled us to build a picture of how each teacher interpreted the curriculum with regard to a number of constructs. The findings show that foundation phase teachers have great difficulty interpreting the curriculum because the foundation phase curriculum does not give clear guidance with regard to the teaching of science. Their poor content knowledge, the poor understanding of what integration of science in numeracy and literacy entails, as well as their poor understanding of the instructional methods used to teach science exacerbate the problem.
Patient and provider attitudes to emergency department-based HIV counselling and testing in South Africa
Authors: Hansoti Bhakti , Hill Sarah E. , Whalen Madeleine , Stead David , Parrish Andy , Rothman Richard , Hsieh Yu-Hsiang , Quinn Thomas C.
Published: May 2017

Background: The national South African HIV Counselling and Testing (HCT) guidelines mandate that voluntary counselling and testing (VCT) should be offered in all healthcare facilities. Emergency departments (EDs) are at the forefront of many healthcare facilities, yet VCT is not routinely implemented in this setting.Methods: We conducted a cross-sectional study that surveyed patients and healthcare providers at a tertiary care ED in the spring and summer of 2016 to ascertain their attitudes to VCT in the ED. We also used two previously validated survey instruments to gather data on patients’ HIV knowledge and providers’ stigma against patients living with HIV, as we anticipated that these may have an impact on providers’ and patients’ attitudes to the provision of HIV testing within the ED, and may offer insights for future intervention development.Results: A total of 104 patients and 26 providers were enrolled in the study. Overall, patients responded more favourably to ED-based HIV testing (92.3%) compared to providers (only 40% responded favourably). When asked about potential barriers to receiving or providing HIV testing, 16.4% of patients and 24% of providers felt that the subject of HIV was too sensitive and 58.7% of patients and 80% of providers indicated that privacy and confidentiality issues would pose major barriers to implementing ED-based HIV testing.Conclusion: This study shows that while ED-based HIV testing is overall highly acceptable to patients, providers seem less willing to provide this service. The survey data also suggest that future development of ED-based testing strategies should take into consideration privacy and confidentiality concerns that may arise within a busy emergency care setting. Furthermore, every effort should be made to tackle HIV stigma among providers to improve overall attitudes towards HIV-positive individuals that present for care in the ED.
Couples-based interventions in the context of HIV discordance
Authors: Mashaphu Sibongile , Burns Jonathan K.
Published: May 2017

No abstract available.
Alcohol use disorder and tuberculosis treatment: A longitudinal mixed method study in Thailand
Authors: Laprawat Samai , Peltzer Karl , Pansila Wirat , Tansakul Chalermpol
Published: May 2017

Objective: The relationship between tuberculosis (TB) treatment and alcohol use disorders over time is under-researched. The aim of this investigation was to study alcohol use and TB medication adherence and its predictors among TB patients over a period of 6 months.Methods: A longitudinal investigation was carried out with new TB and TB retreatment patients systematically selected from two hospitals and had screened positive for hazardous or harmful alcohol use in Sisaket Province in Thailand. Alcohol use disorders were measured with Alcohol Use Disorder Identification Test (AUDIT)-C at baseline, 3 months and 6 months.Results: Of the 295 TB patients who were screened with AUDIT-C, 72 (24.4%) tested positive for hazardous or harmful alcohol use. At 6 months, 72 TB patients had completed the follow- up. At the 6-month follow-up, hazardous or harmful drinking was reduced by 84.7%. Multivariate logistic regression analysis using generalised estimation equation modelling found that alcohol use significantly reduced over time, whereas there was no change in current tobacco use.Conclusion: The prevalence of alcohol use disorders significantly reduced over a period of 6 months.