ALBERT

Description: A deformed exponential family is a generalization of exponential families. Since the useful classes of power law tailed distributions are described by the deformed exponential families, they are important objects in the theory of complex systems. Though the deformed exponential families are defined by deformed exponential functions, these functions do not satisfy the law of exponents in general. The deformed algebras have been introduced based on the deformed exponential functions. In this paper, after summarizing such deformed algebraic structures, it is clarified how deformed algebras work on deformed exponential families. In fact, deformed algebras cause generalization of expectations. The three kinds of expectations for random variables are introduced in this paper, and it is discussed why these generalized expectations are natural from the viewpoint of information geometry. In addition, deformed algebras cause generalization of independences. Whereas it is difficult to check the well-definedness of deformed independence in general, the κ-independence is always well-defined on κ-exponential families. This is one of advantages of κ-exponential families in complex systems. Consequently, we can well generalize the maximum likelihood method for the κ-exponential family from the viewpoint of information geometry.

Description: We consider the problem of learning a Bayesian network structure given n examples and the prior probability based on maximizing the posterior probability. We propose an algorithm that runs in O(n log n) time and that addresses continuous variables and discrete variables without assuming any class of distribution. We prove that the decision is strongly consistent, i.e., correct with probability one as n ! 1. To date, consistency has only been obtained for discrete variables for this class of problem, and many authors have attempted to prove consistency when continuous variables are present. Furthermore, we prove that the “log n” term that appears in the penalty term of the description length can be replaced by 2(1+ε) log log n to obtain strong consistency, where ε > 0 is arbitrary, which implies that the Hannan–Quinn proposition holds.

Description: Background: In 2012, a pilot health policy of contractual service relations between general practitioners and patients was implemented in China. Due to the decline in body and cognitive function, as well as the lack of family care and narrow social support networks, the demand of health services among the elderly is much higher than that among the general population. This study aims to probe into the empty nesters’ willingness-to-pay for general practitioners using a contractual service policy, investigating empty nesters’ payment levels for the service, and analyze the main factors affecting the willingness of empty-nesters’ general practitioners using contractual service supply cost. Methods: This cross-sectional study adopted a multistage stratified sampling method to survey 865, city empty nesters (six communities in three districts of one city) aged 60–85 years. A condition value method was used to infer the distribution of the willingness-to-pay; Cox’s proportional hazards regression model was used to analyze the influencing factors of willingness-to-pay. Results: More than seventy percent (76.6%) of the empty nesters in this city were willing to pay general practitioners using contract service in Chongqing. The level of willingness-to-pay for the surveyed empty nesters was 34.1 yuan per year. The median value was 22.1 yuan per year, which was below the Chongqing urban and rural cooperative medical insurance individual funding level (60 yuan per year) in 2013. Cox’s proportional hazards regression model analysis showed that the higher the education level was, the worse the self-reported health status would be, accompanied by higher family per capita income, higher satisfaction of community health service, and higher willingness-to-pay empty nesters using a contract service. Women had a higher willingness-to-pay than men. Conclusions: The willingness-to-pay for general practitioners by contractual service is high among city empty nesters in Chongqing, thus, individual financing is feasible. However, people are willing to pay less than half of the current personal financing of cooperative medical insurance of urban and rural residents. Education level, family per capita income, and self-reported health status are the main factors affecting the cost sharing intention for general practitioners using contract service supply. According to the existing situation of different empty nesters, it is important to perfect the design of general practitioners using a contractual service policy system, according to differentiated personal financing levels.

Description: Lightweighting in the transportation industry is today recognized as one of the most important strategies to improve fuel efficiency and reduce anthropogenic climate-changing, environment-damaging, and human death-causing emissions. However, the structural applications of lightweight alloys are often limited by some inherent deficiencies such as low stiffness, high wear rate and inferior strength. These properties could be effectively enhanced by the addition of stronger and stiffer reinforcements, especially nano-sized particles, into metal matrix to form composites. In most cases three common strengthening mechanisms (load-bearing effect, mismatch of coefficients of thermal expansion, and Orowan strengthening) have been considered to predict the yield strength of metal matrix nanocomposites (MMNCs). This study was aimed at developing a unified model by taking into account the matrix grain size and porosity (which is unavoidable in the materials processing such as casting and powder metallurgy) in the prediction of the yield strength of MMNCs. The Zener pinning effect of grain boundaries by the nano-sized particles has also been integrated. The model was validated using the experimental data of magnesium- and titanium-based nanocomposites containing different types of nano-sized particles (namely, Al2O3, Y2O3, and carbon nanotubes). The predicted results were observed to be in good agreement with the experimental data reported in the literature.

Description: In order to achieve process intensification for adsorption chillers and heat pumps, a new composite material was developed based on sintered aluminum fibers from a melt-extraction process and a dense layer of silico-aluminophosphate (SAPO-34) on the fiber surfaces. The SAPO-34 layer was obtained through a partial support transformation (PST) process. Preparation of a composite sample is described and its characteristic pore size distribution and heat conductivity are presented. Water adsorption data obtained under conditions of a large pressure jump are given. In the next step, preparation of the composite was scaled up to larger samples which were fixed on a small adsorption heat exchanger. Adsorption measurements on this heat exchanger element that confirm the achieved process intensification are presented. The specific cooling power for the adsorption step per volume of composite is found to exceed 500 kW/m3 under specified conditions.

Description: An ultrasonic technique, invariant to temperature changes, for a density measurement of different liquids under in situ extreme conditions is presented. The influence of geometry and material parameters of the measurement system (transducer, waveguide, matching layer) on measurement accuracy and reliability is analyzed theoretically along with experimental results. The proposed method is based on measurement of the amplitude of the ultrasonic wave, reflected from the interface of the solid/liquid medium under investigation. In order to enhance sensitivity, the use of a quarter wavelength acoustic matching layer is proposed. Therefore, the sensitivity of the measurement system increases significantly. Density measurements quite often must be performed in extreme conditions at high temperature (up to 220 °C) and high pressure. In this case, metal waveguides between piezoelectric transducer and the measured liquid are used in order to protect the conventional transducer from the influence of high temperature and to avoid depolarization. The presented ultrasonic density measurement technique is suitable for density measurement in different materials, including liquids and polymer melts in extreme conditions. A new calibration algorithm was proposed. The metrological evaluation of the measurement method was performed. The expanded measurement uncertainty Uρ = 7.4 × 10−3 g/cm3 (1%).

Description: The relationship between soil fauna and different fertilizer management practices is of growing concern. The aim of this research was to investigate the response of soil fauna to fertilization regimes, to explore the relationships among the community of soil animals, soil moisture and crop yields. The application of organic fertilizers (i.e., sheep manure or crop residues) increased crop yields and promoted the number of individuals and species of soil fauna owing to the exogenous organic matter that fertilizers provided for the survival and development of soil fauna. Furthermore, the treatments that applied sheep manure (i.e., sheep manure only or nitrogen, phosphorus, potassium and sheep manure plus) were significantly beneficial for increasing crop yields and diversity of soil fauna compared to treatments with crop residues returned (i.e., crop residues returned only or nitrogen, phosphorus, potassium and crop residues returned to the field) (p 〈 0.05) due to the response of soil fauna to diverse exogenous nutrients and the effect of soil fertility. Therefore, the finding that soil fauna abundance is significantly positively correlated with soil moisture and crop yield may mean the effects of fertilizer applications on soil animals were partly masked by the soil moisture and crop yield.

Description: Urban areas are one of the most important components of human society. Their extents have been continuously growing during the last few decades. Accurate and timely measurements of the extents of urban areas can help in analyzing population densities and urban sprawls and in studying environmental issues related to urbanization. Urban extents detected from remotely sensed data are usually a by-product of land use classification results, and their interpretation requires a full understanding of land cover types. In this study, for the first time, we mapped urban extents in the continental United States using a novel one-class classification method, i.e., positive and unlabeled learning (PUL), with multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) data for the year 2010. The Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) night stable light data were used to calibrate the urban extents obtained from the one-class classification scheme. Our results demonstrated the effectiveness of the use of the PUL algorithm in mapping large-scale urban areas from coarse remote-sensing images, for the first time. The total accuracy of mapped urban areas was 92.9% and the kappa coefficient was 0.85. The use of DMSP-OLS night stable light data can significantly reduce false detection rates from bare land and cropland far from cities. Compared with traditional supervised classification methods, the one-class classification scheme can greatly reduce the effort involved in collecting training datasets, without losing predictive accuracy.

Description: The knowledge about impacts of changes in precipitation regimes on terrestrial ecosystems is fundamental to improve our understanding of global environment change, particularly in the context that heavy precipitation is expected to increase according to the 5th Intergovernmental Panel on Climate Change (IPCC) assessment. Based on observed climate data and the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) satellite-derived normalized difference vegetation index (NDVI), here we analyzed the spatio-temporal changes in grassland NDVI, covering 1.64 × 106 km2, in northern China and their linkages to changes in precipitation and temperature during the period 1982–2011. We found that mean growing season (April–October) grass NDVI is more sensitive to heavy precipitation than to moderate or light precipitation in both relatively arid areas (RAA) and relatively humid areas (RHA), whereas the sensitivities of grass NDVI to temperature are comparable to total precipitation in RHA. Heavy precipitation showed the strongest impacts in more than half of northern China (56%), whereas impacts of light precipitation on grass NDVI were stronger in some areas (21%), mainly distributed in northwestern China, a typical arid and semi-arid area. Our findings suggest that responses of grasslands are divergent with respect to changes in precipitation intensities.

Description: The worldwide Sensor Web comprises observation data from diverse sources. Each data provider may process and assess datasets differently before making them available online. This information is often invisible to end users. Therefore, publishing observation data with quality descriptions is vital as it helps users to assess the suitability of data for their applications. It is also important to capture contextual information concerning data quality such as provenance to trace back incorrect data to its origins. In the Open Geospatial Consortium (OGC)’s Sensor Web Enablement (SWE) framework, there is no sufficiently and practically applicable approach how these aspects can be systematically represented and made accessible. This paper presents Q-SOS—an extension of the OGC’s Sensor Observation Service (SOS) that supports retrieval of observation data together with quality descriptions. These descriptions are represented in an observation data model covering various aspects of data quality assessment. The service and the data model have been developed based on open standards and open source tools, and are productively being used to share observation data from the TERENO observatory infrastructure. We discuss the advantages of deploying the presented solutions from data provider and consumer viewpoints. Enhancements applied to the related open-source developments are also introduced.

Description: In recent years, IoT (Internet of Things) technologies have seen great advances, particularly, the IPv6 Routing Protocol for Low-power and Lossy Networks (RPL), which provides a powerful and flexible routing framework that can be applied in a variety of application scenarios. In this context, as an important role of IoT, Wireless Sensor Networks (WSNs) can utilize RPL to design efficient routing protocols for a specific application to increase the ubiquity of networks with resource-constrained WSN nodes that are low-cost and easy to deploy. In this article, our work starts with the description of Agricultural Low-power and Lossy Networks (A-LLNs) complying with the LLN framework, and to clarify the requirements of this application-oriented routing solution. After a brief review of existing optimization techniques for RPL, our contribution is dedicated to a Scalable Context-Aware Objective Function (SCAOF) that can adapt RPL to the environmental monitoring of A-LLNs, through combining energy-aware, reliability-aware, robustness-aware and resource-aware contexts according to the composite routing metrics approach. The correct behavior of this enhanced RPL version (RPAL) was verified by performance evaluations on both simulation and field tests. The obtained experimental results confirm that SCAOF can deliver the desired advantages on network lifetime extension, and high reliability and efficiency in different simulation scenarios and hardware testbeds.

Description: The aim of this randomized clinical trial was to evaluate whether a recently described multi-sensor approach called BIONOTE® is accurate enough to verify the efficacy of treatment of patients with halitosis. A treatment with Lactobacillus brevis (CD2)–containing lozenges, compared with placebo was tested. The BIONOTE® was compared with traditional techniques used to detect halitosis: OralChroma™ and two calibrated odor judges enrolled for the organoleptic assessments. Twenty patients (10 treated and 10 placebo), suffering from active phase halitosis were included in the study. Treatment consisted of Lactobacillus brevis (CD2)—containing lozenges or placebo, 4 tablets/day for 14 days. t0 was before the beginning of the study; t1 was day 7 and t2 was day 14. The effectiveness of treatment was assessed through: (1) Rosenberg score; (2) Winkel tongue coating index (WTCI) anterior and posterior; (2) OralChroma™; (3) the new developed multi-sensor approach, called BIONOTE® (test technique). Only the WTCI anterior revealed statistically significant changes between t0 and t2 data (p = 0.014) in the treated group. Except for the WTCI anterior, all diagnostic methods revealed the lack of effectiveness for halitosis of a 14-days treatment with Lactobacillus brevis (CD2)–containing lozenges. The BIONOTE® multisensor system seems accurate in addition to OralChroma™ to assess the initial condition of halitosis and its mitigation during treatment.

Description: We examine a distributed detection problem in a wireless sensor network, where sensor nodes collaborate to detect a Gaussian signal with an unknown change of power, i.e., a scale parameter. Due to power/bandwidth constraints, we consider the case where each sensor quantizes its observation into a binary digit. The binary data are then transmitted through error-prone wireless links to a fusion center, where a generalized likelihood ratio test (GLRT) detector is employed to perform a global decision. We study the design of a binary quantizer based on an asymptotic analysis of the GLRT. Interestingly, the quantization threshold of the quantizer is independent of the unknown scale parameter. Numerical results are included to illustrate the performance of the proposed quantizer and GLRT in binary symmetric channels (BSCs).

Description: This paper presents a multipurpose and low cost sensor for the simultaneous monitoring of temperature and ullage of wine in barrels in two of the most important stages of winemaking, that being fermentation and maturation. The distributed sensor subsystem is imbedded within the bung of the barrel and runs on battery for a period of at least 12 months and costs around $27 AUD for all parts. In addition, software was designed which allows for the remote transmission and easy visual interpretation of the data for the winemaker. Early warning signals can be sent when the temperature or ullage deviates from a winemakers expectations so remedial action can be taken, such as when topping is required or the movement of the barrels to a cooler cellar location. Such knowledge of a wine’s properties or storage conditions allows for a more precise control of the final wine quality.

Description: A fast and effective wound healing process would substantially decrease medical costs, wound care supplies, and hospitalization significantly improving the patients’ quality of life. The search for effective therapeutic approaches seems to be imperative in order to avoid the aggravation of chronic wounds. In spite of all the efforts that have been made during the recent years towards the development of artificial wound dressings, none of the currently available options combine all the requirements necessary for quick and optimal cutaneous regeneration. Therefore, technological advances in the area of temporary and permanent smart dressings for wound care are required. The development of nanoscience and nanotechnology can improve the materials and designs used in topical wound care in order to efficiently release antimicrobial, anti-inflammatory and regenerative compounds speeding up the endogenous healing process. Nanostructured dressings can overcome the limitations of the current coverings and, separately, natural origin components can also overcome the drawbacks of current antibiotics and antiseptics (mainly cytotoxicity, antibiotic resistance, and allergies). The combination of natural origin components with demonstrated antibiotic, regenerative, or anti-inflammatory properties together with nanostructured materials is a promising approach to fulfil all the requirements needed for the next generation of bioactive wound dressings. Microbially compromised wounds have been treated with different essential oils, honey, cationic peptides, aloe vera, plant extracts, and other natural origin occurring antimicrobial, anti-inflammatory, and regenerative components but the available evidence is limited and insufficient to be able to draw reliable conclusions and to extrapolate those findings to the clinical practice. The evidence and some promising preliminary results indicate that future comparative studies are justified but instead of talking about the beneficial or inert effects of those natural origin occurring materials, the scientific community leads towards the identification of the main active components involved and their mechanism of action during the corresponding healing, antimicrobial, or regenerative processes and in carrying out systematic and comparative controlled tests. Once those natural origin components have been identified and their efficacy validated through solid clinical trials, their combination within nanostructured dressings can open up new avenues in the fabrication of bioactive dressings with outstanding characteristics for wound care. The motivation of this work is to analyze the state of the art in the use of different essential oils, honey, cationic peptides, aloe vera, plant extracts, and other natural origin occurring materials as antimicrobial, anti-inflammatory and regenerative components with the aim of clarifying their potential clinical use in bioactive dressings. We conclude that, for those natural occurring materials, more clinical trials are needed to reach a sufficient level of evidence as therapeutic agents for wound healing management.

Description: Multiple stable states are established in coastal tidal wetlands (marshes, mangroves, deltas, seagrasses) by ecological, hydrological, and geomorphological feedbacks. Catastrophic shifts between states can be induced by gradual environmental change or by disturbance events. These feedbacks and outcomes are key to the sustainability and resilience of vegetated coastlines, especially as modulated by human activity, sea level rise, and climate change. Whereas multiple stable state theory has been invoked to model salt marsh responses to sediment supply and sea level change, there has been comparatively little empirical verification of the theory for salt marshes or other coastal wetlands. Especially lacking is long-term evidence documenting if or how stable states are established and maintained at ecosystem scales. Laboratory and field-plot studies are informative, but of necessarily limited spatial and temporal scope. For the purposes of long-term, coastal-scale monitoring, remote sensing is the best viable option. This review summarizes the above topics and highlights the emerging promise and challenges of using remote sensing-based analyses to validate coastal wetland dynamic state theories. This significant opportunity is further framed by a proposed list of scientific advances needed to more thoroughly develop the field.

Description: As internet technologies make their way into developing areas, so too does the possibility of education and training being delivered to the people living in those previously unserved areas. The growing catalogue of free, high quality courseware, when combined with the newly acquired means of delivery, creates the potential for millions of people in the developing world to acquire a good education. Yet a good education obviously requires more than simply delivering information; students must also receive high quality feedback on their assessments. They must be told how their performance compares with the ideal, and be shown how to close the gap between the two. However, delivering high quality feedback is labor-intensive, and therefore expensive, and has long been recognized as a problematic issue by educators. This paper outlines a case study that uses a Learning Management System (LMS) to efficiently deliver detailed feedback that is informed by the principles of best practice. We make the case that the efficiencies of this method allow for large-scale courses with thousands of enrolments that are accessible to developing and developed areas alike. We explore the question; is computer-mediated feedback delivery efficient and effective and might it be applied to large-scale courses at low-cost?

Description: This paper provides an overview of the main manufacturing technologies of displays, focusing on those with low and ultra-low levels of power consumption, which make them suitable for current societal needs. Considering the typified value obtained from the manufacturer’s specifications, four technologies—Liquid Crystal Displays, electronic paper, Organic Light-Emitting Display and Electroluminescent Displays—were selected in a first iteration. For each of them, several features, including size and brightness, were assessed in order to ascertain possible proportional relationships with the rate of consumption. To normalize the comparison between different display types, relative units such as the surface power density and the display frontal intensity efficiency were proposed. Organic light-emitting display had the best results in terms of power density for small display sizes. For larger sizes, it performs less satisfactorily than Liquid Crystal Displays in terms of energy efficiency.

Description: Model selection is an integral, yet contentious, component of epidemiologic research. Unfortunately, there remains no consensus on how to identify a single, best model among multiple candidate models. Researchers may be prone to selecting the model that best supports their a priori, preferred result; a phenomenon referred to as “wish bias”. Directed acyclic graphs (DAGs), based on background causal and substantive knowledge, are a useful tool for specifying a subset of adjustment variables to obtain a causal effect estimate. In many cases, however, a DAG will support multiple, sufficient or minimally-sufficient adjustment sets. Even though all of these may theoretically produce unbiased effect estimates they may, in practice, yield somewhat distinct values, and the need to select between these models once again makes the research enterprise vulnerable to wish bias. In this work, we suggest combining adjustment sets with model averaging techniques to obtain causal estimates based on multiple, theoretically-unbiased models. We use three techniques for averaging the results among multiple candidate models: information criteria weighting, inverse variance weighting, and bootstrapping. We illustrate these approaches with an example from the Pregnancy, Infection, and Nutrition (PIN) study. We show that each averaging technique returns similar, model averaged causal estimates. An a priori strategy of model averaging provides a means of integrating uncertainty in selection among candidate, causal models, while also avoiding the temptation to report the most attractive estimate from a suite of equally valid alternatives.

Description: The widespread, intentional and increasingly frequent chemical emplacement in the troposphere has gone unidentified and unremarked in the scientific literature for years. The author presents evidence that toxic coal combustion fly ash is the most likely aerosolized particulate sprayed by tanker-jets for geoengineering, weather-modification and climate-modification purposes and describes some of the multifold consequences on public health. Two methods are employed: (1) Comparison of 8 elements analyzed in rainwater, leached from aerosolized particulates, with corresponding elements leached into water from coal fly ash in published laboratory experiments, and (2) Comparison of 14 elements analyzed in dust collected outdoors on a high-efficiency particulate air (HEPA) filter with corresponding elements analyzed in un-leached coal fly ash material. The results show: (1) the assemblage of elements in rainwater and in the corresponding experimental leachate are essentially identical. At a 99% confidence interval, they have identical means (T-test) and identical variances (F-test); and (2) the assemblage of elements in the HEPA dust and in the corresponding average un-leached coal fly ash are likewise essentially identical. The consequences on public health are profound, including exposure to a variety of toxic heavy metals, radioactive elements, and neurologically-implicated chemically mobile aluminum released by body moisture in situ after inhalation or through transdermal induction.

Description: The impacts of climate change on human health have been documented globally and in the United States. Numerous studies project greater morbidity and mortality as a result of extreme weather events and other climate-sensitive hazards. Public health impacts on the U.S. Gulf Coast may be severe as the region is expected to experience increases in extreme temperatures, sea level rise, and possibly fewer but more intense hurricanes. Through myriad pathways, climate change is likely to make the Gulf Coast less hospitable and more dangerous for its residents, and may prompt substantial migration from and into the region. Public health impacts may be further exacerbated by the concentration of people and infrastructure, as well as the region’s coastal geography. Vulnerable populations, including the very young, elderly, and socioeconomically disadvantaged may face particularly high threats to their health and well-being. This paper provides an overview of potential public health impacts of climate variability and change on the Gulf Coast, with a focus on the region’s unique vulnerabilities, and outlines recommendations for improving the region’s ability to minimize the impacts of climate-sensitive hazards. Public health adaptation aimed at improving individual, public health system, and infrastructure resilience is urgently needed to meet the challenges climate change may pose to the Gulf Coast in the coming decades.

Description: This study forecasts the liquidity gap in China’s pension scheme for urban workers in the context of an ageing population and the possible effects of recent governmental policies by constructing a basic pension model, including “old people”, “middle people” and “new people” and a simulation method. We find, firstly, that China’s liquidity gap of pension will reach its peak of approximately 13.11 trillion yuan in 2038. Subsequently, this gap will gradually decrease with growth in the mortality rate. Secondly, reasonable intervals for the replacement and contribution rates should be set at [0.417, 0.604] and [0.189, 0.262], respectively, to sustain China’s pension system. Thirdly, compared to increasing fiscal subsidies, an income doubling plan, raising the contribution rate, lowering the replacement rate and delaying the retirement age can significantly reduce the liquidity gap, although the policy costs are relatively high. A policy permitting families to have two children will increase the rate of reduction of the liquidity gap, but it cannot effectively narrow the gap at the peak moment.

Description: More and more hybrid electric vehicles are driven since they offer such advantages as energy savings and better active safety performance. Hybrid vehicles have two or more power driving systems and frequently switch working condition, so controlling stability is very important. In this work, a two-stage Kalman algorithm method is used to fuse data in hybrid vehicle stability testing. First, the RT3102 navigation system and Dewetron system are introduced. Second, a modeling of data fusion is proposed based on the Kalman filter. Then, this modeling is simulated and tested on a sample vehicle, using Carsim and Simulink software to test the results. The results showed the merits of this modeling.

Description: The aim of this study was to investigate how atmospheric air pollutants and meteorological conditions affected atmospheric visibility in the largest Polish agglomeration. The correlation analysis, principal component analysis (PCA) and generalized regression models (GRMs) were used to accomplish this objective. The meteorological parameters (temperature, relative humidity, precipitation, wind speed and insolation) and concentrations of the air pollutants (PM10, SO2, NO2, CO and O3) were recorded in 2004–2013. The data came from the Ursynów-SGGW, MzWarszUrsynów and Okęcie monitoring stations, located in the south of Warsaw (Poland). It was shown that the PM10 concentration was the most important parameter affecting the visibility in Warsaw. The concentration, and indirectly the visibility, was mainly affected by the pollutant emission from the flat/building heating (combustion of various fuels). It changed intensively during the research period. There were also periods in which this emission type did not have a great influence on the pollutant concentrations (mainly PM10) and visibility. In such seasons, the research revealed the influence of the traffic emission and secondary aerosol formation processes on the visibility.

Description: Aquatic vegetation serves many important ecological and socioeconomic functions in lake ecosystems. The presence of floating algae poses difficulties for accurately estimating the distribution of aquatic vegetation in eutrophic lakes. We present an approach to map the distribution of aquatic vegetation in Lake Taihu (a large, shallow eutrophic lake in China) and reduce the influence of floating algae on aquatic vegetation mapping. Our approach involved a frequency analysis over a 2003–2013 time series of the floating algal index (FAI) based on moderate-resolution imaging spectroradiometer (MODIS) data. Three phenological periods were defined based on the vegetation presence frequency (VPF) and the growth of algae and aquatic vegetation: December and January composed the period of wintering aquatic vegetation; February and March composed the period of prolonged coexistence of algal blooms and wintering aquatic vegetation; and June to October was the peak period of the coexistence of algal blooms and aquatic vegetation. By comparing and analyzing the satellite-derived aquatic vegetation distribution and 244 in situ measurements made in 2013, we established a FAI threshold of −0.025 and VPF thresholds of 0.55, 0.45 and 0.85 for the three phenological periods. We validated the accuracy of our approach by comparing the results between the satellite-derived maps and the in situ results obtained from 2008–2012. The overall classification accuracy was 87%, 81%, 77%, 88% and 73% in the five years from 2008–2012, respectively. We then applied the approach to the MODIS images from 2003–2013 and obtained the total area of the aquatic vegetation, which varied from 265.94 km2 in 2007 to 503.38 km2 in 2008, with an average area of 359.62 ± 69.20 km2 over the 11 years. Our findings suggest that (1) the proposed approach can be used to map the distribution of aquatic vegetation in eutrophic algae-rich waters and (2) dramatic changes occurred in the distribution of aquatic vegetation in Lake Taihu during the 11-year study.

Description: Diffuse Correlation Spectroscopy (DCS) is a well-established optical technique that has been used for non-invasive measurement of blood flow in tissues. Instrumentation for DCS includes a correlation device that computes the temporal intensity autocorrelation of a coherent laser source after it has undergone diffuse scattering through a turbid medium. Typically, the signal acquisition and its autocorrelation are performed by a correlation board. These boards have dedicated hardware to acquire and compute intensity autocorrelations of rapidly varying input signal and usually are quite expensive. Here we show that a Raspberry Pi minicomputer can acquire and store a rapidly varying time-signal with high fidelity. We show that this signal collected by a Raspberry Pi device can be processed numerically to yield intensity autocorrelations well suited for DCS applications. DCS measurements made using the Raspberry Pi device were compared to those acquired using a commercial hardware autocorrelation board to investigate the stability, performance, and accuracy of the data acquired in controlled experiments. This paper represents a first step toward lowering the instrumentation cost of a DCS system and may offer the potential to make DCS become more widely used in biomedical applications.

Description: Wind tunnels are a key experimental tool for the analysis of airflow parameters in many fields of application. Despite their great potential impact on agricultural research, few contributions have dealt with the development of automatic control systems for wind tunnels in the field of greenhouse technology. The objective of this paper is to present an automatic control system that provides precision and speed of measurement, as well as efficient data processing in low-speed wind tunnel experiments for greenhouse engineering applications. The system is based on an algorithm that identifies the system model and calculates the optimum PI controller. The validation of the system was performed on a cellulose evaporative cooling pad and on insect-proof screens to assess its response to perturbations. The control system provided an accuracy of 〈0.06 m·s‾1 for airflow speed and 〈0.50 Pa for pressure drop, thus permitting the reproducibility and standardization of the tests. The proposed control system also incorporates a fully-integrated software unit that manages the tests in terms of airflow speed and pressure drop set points.

Description: A new application of utilizing ultra-wideband (UWB) technology to sense wind turbine blade deflections is introduced in this paper for wind energy cost reduction. The lower UWB band of 3.1–5.3 GHz is applied. On each blade, there will be one UWB blade deflection sensing system, which consists of two UWB antennas at the blade root and one UWB antenna at the blade tip. The detailed topology and challenges of this deflection sensing system are addressed. Due to the complexity of the problem, this paper will first realize the on-blade UWB radio link in the simplest case, where the tip antenna is situated outside (and on the surface of) a blade tip. To investigate this case, full-blade time-domain measurements are designed and conducted under different deflections. The detailed measurement setups and results are provided. If the root and tip antenna locations are properly selected, the first pulse is always of sufficient quality for accurate estimations under different deflections. The measured results reveal that the blade tip-root distance and blade deflection can be accurately estimated in the complicated and lossy wireless channels around a wind turbine blade. Some future research topics on this application are listed finally.

Description: A method for measuring shaft diameters is presented using structured light vision measurement. After calibrating a model of the structured light measurement, a virtual plane is established perpendicular to the measured shaft axis and the image of the light stripe on the shaft is projected to the virtual plane. On the virtual plane, the center of the measured shaft is determined by fitting the projected image under the geometrical constraints of the light stripe, and the shaft diameter is measured by the determined center and the projected image. Experiments evaluated the measuring accuracy of the method and the effects of some factors on the measurement are analyzed.

Description: Understanding the relationship between land use and surface water quality is necessary for effective water management. We estimated the impacts of catchment-wide land use on water quality during the dry and rainy seasons in the Dongjiang River basin, using remote sensing, geographic information systems and multivariate statistical techniques. The results showed that the 83 sites can be divided into three groups representing different land use types: forest, agriculture and urban. Water quality parameters exhibited significant variations between the urban-dominated and forest-dominated sites. The proportion of forested land was positively associated with dissolved oxygen concentration but negatively associated with water temperature, electrical conductivity, permanganate index, total phosphorus, total nitrogen, ammonia nitrogen, nitrate nitrogen and chlorophyll-a. The proportion of urban land was strongly positively associated with total nitrogen and ammonia nitrogen concentrations. Forested and urban land use had stronger impacts on water quality in the dry season than in the rainy season. However, agricultural land use did not have a significant impact on water quality. Our study indicates that urban land use was the key factor affecting water quality change, and limiting point-source waste discharge in urban areas during the dry season would be critical for improving water quality in the study area.

Description: The morphological properties of kaolin flocs were investigated in a Couette-flow experiment at the steady state under seven shear flow conditions (shear rates of 5.36, 9.17, 14, 24, 31, 41 and 53 s−1). These properties include a one-dimensional (1-D) fractal dimension (D1), a two-dimensional (2-D) fractal dimension (D2), a perimeter-based fractal dimension (Dpf) and an aspect ratio (AR). They were calculated based on the projected area (A), equivalent size, perimeter (P) and length (L) of the major axis of the floc determined through sample observation and an image analysis system. The parameter D2, which characterizes the relationship between the projected area and the length of the major axis using a power function, , increased from 1.73 ± 0.03, 1.72 ± 0.03, and 1.75 ± 0.04 in the low shear rate group (G = 5.36, 9.17, and 14 s−1) to 1.92 ± 0.03, 1.82 ± 0.02, 1.85 ± 0.02, and 1.81 ± 0.02 in the high shear rate group (24, 31, 41 and 53 s−1), respectively. The parameter D1 characterizes the relationship between the perimeter and length of the major axis by the function  and decreased from 1.52 ± 0.02, 1.48 ± 0.02, 1.55 ± 0.02, and 1.63 ± 0.02 in the low shear group (5.36, 9.17, 14 and 24 s−1) to 1.45 ± 0.02, 1.39 ± 0.02, and 1.39 ± 0.02 in the high shear group (31, 41 and 53 s−1), respectively. The results indicate that with increasing shear rates, the flocs become less elongated and that their boundary lines become tighter and more regular, caused by more breakages and possible restructurings of the flocs. The parameter Dpf, which is related to the perimeter and the projected area through the function , decreased as the shear rate increased almost linearly. The parameter AR, which is the ratio of the length of the major axis and equivalent diameter, decreased from 1.56, 1.59, 1.53 and 1.51 in the low shear rate group to 1.43, 1.47 and 1.48 in the high shear rate group. These changes in Dpf and AR show that the flocs become less convoluted and more symmetrical and that their boundaries become smoother and more regular in the high shear rate group than in the low shear rate group due to breakage and possible restructuring processes. To assess the effects of electrolyte and sediment concentration, 0.1 mol/L calcium chloride (CaCl2) and initial sediment concentration from 7.87 × 10−5 to 1.57 × 10−5 were used in this preliminary study. The addition of electrolyte and increasing sediment concentration could produce more symmetrical flocs with less convoluted and simpler boundaries. In addition, some new information on the temporal variation of the median size of the flocs during the flocculation process is presented.

Description: Accurate state of charge (SoC) estimation of batteries plays an important role in promoting the commercialization of electric vehicles. The main work to be done in accurately determining battery SoC can be summarized in three parts. (1) In view of the model-based SoC estimation flow diagram, the n-order resistance-capacitance (RC) battery model is proposed and expected to accurately simulate the battery’s major time-variable, nonlinear characteristics. Then, the mathematical equations for model parameter identification and SoC estimation of this model are constructed. (2) The Akaike information criterion is used to determine an optimal tradeoff between battery model complexity and prediction precision for the n-order RC battery model. Results from a comparative analysis show that the first-order RC battery model is thought to be the best based on the Akaike information criterion (AIC) values. (3) The real-time joint estimator for the model parameter and SoC is constructed, and the application based on two battery types indicates that the proposed SoC estimator is a closed-loop identification system where the model parameter identification and SoC estimation are corrected mutually, adaptively and simultaneously according to the observer values. The maximum SoC estimation error is less than 1% for both battery types, even against the inaccurate initial SoC.

Description: This is the second part of a study conducted to model the aerothermodynamic impact of suction parameters and gas properties on a multi-stage centrifugal compressor’s performance. A new iterative method has been developed in the first part to derive the equivalent performance at various operating conditions. This approach has been validated to predict the compressor map at different suction pressures and temperatures using the design characteristics as reference values. A further case is included in this paper in order to emphasize the validity of the developed approach to obtain the performance characteristics at various gas compositions. The provided example shows that the performance parameters at different gas mixtures can be predicted to within ±1.34%. Furthermore, the conducted optimization in this paper reveals that the proposed method can be applied for the compressor design evaluation corresponding to the expected variation in suction conditions. Moreover, the examined case study demonstrates the effect of gas properties’ variation on the operating point and aerodynamic stability of the entire compression system. In order to achieve that, a simple approach has been established to assess the contribution of gas properties’ variation to the inefficient and unstable compressor performance based on the available operational data.