bluuebunny/crossref_metadata_2025 huggingface dataset:
Aptitude of Oxidative Enzymes for Treatment of Wastewater Pollutants: A Laccase Perspective
Authors: Unuofin John O. , Okoh Anthony I. , Nwodo Uchechukwu U.
Published: May 2019

Natural water sources are very often contaminated by municipal wastewater discharges which contain either of xenobiotic pollutants and their sometimes more toxic degradation products, or both, which frustrates the universal millenium development goal of provision of the relatively scarce pristine freshwater to water-scarce and -stressed communities, in order to augment their socioeconomic well-being. Seeing that both regulatory measures, as regards the discharge limits of wastewater, and the query for efficient treatment methods remain unanswered, partially, the prospects of enzymatic treatment of wastewater is advisable. Therefore, a reconsideration was assigned to the possible capacity of oxidative enzymes and the respective challenges encountered during their applications in wastewater treatment, and ultimately, the prospects of laccase, a polyphenol oxidase that oxidizes aromatic and inorganic substrates with electron-donating groups in treatment aromatic contaminants of wastewater, in real wastewater situations, since it is assumed to be a vehicle for a greener community. Furthermore, the importance of laccase-driven catalysis toward maintaining mass-energy balance, hence minimizing environmental waste, was comprehensibly elucidated, as well the strategic positioning of laccase in a model wastewater treatment facility for effective treatment of wastewater contaminants.
Quality by Design Approach Using Multiple Linear and Logistic Regression Modeling Enables Microemulsion Scale Up
Authors: Herneisey Michele , Lambert Eric , Kachel Allison , Shychuck Emma , Drennen James K. , Janjic Jelena M.
Published: May 2019

The development of pharmaceutical nanoformulations has accelerated over the past decade. However, the nano-sized drug carriers continue to meet substantial regulatory and clinical translation challenges. In order to address some of these key challenges in early development, we adopted a quality by design approach to develop robust predictive mathematical models for microemulsion formulation, manufacturing, and scale-up. The presented approach combined risk management, design of experiments, multiple linear regression (MLR), and logistic regression to identify a design space in which microemulsion colloidal properties were dependent solely upon microemulsion composition, thus facilitating scale-up operations. Developed MLR models predicted microemulsion diameter, polydispersity index (PDI), and diameter change over 30 days storage, while logistic regression models predicted the probability of a microemulsion passing quality control testing. A stable microemulsion formulation was identified and successfully scaled up tenfold to 1L without impacting droplet diameter, PDI, or stability.
A Review of Augmented Reality Applications for History Education and Heritage Visualisation
Authors: Challenor Jennifer , Ma Minhua
Published: May 2019

Augmented reality is a field with a versatile range of applications used in many fields including recreation and education. Continually developing technology spanning the last decade has drastically improved the viability for augmented reality projects now that most of the population possesses a mobile device capable of supporting the graphic rendering systems required for them. Education in particular has benefited from these technological advances as there are now many fields of research branching into how augmented reality can be used in schools. For the purposes of Holocaust education however, there has been remarkable little research into how Augmented Reality can be used to enhance its delivery or impact. The purpose of this study is to speculate regarding the following questions: How is augmented reality currently being used to enhance history education? Does the usage of augmented reality assist in developing long-term memories? Is augmented reality capable of conveying the emotional weight of historical events? Will augmented reality be appropriate for teaching a complex field such as the Holocaust? To address these, multiple studies have been analysed for their research methodologies and how their findings may assist with the development of Holocaust education.
Recovery of Rare Earth Elements by Carbon-Based Nanomaterials—A Review
Authors: Cardoso Celso E. D. , Almeida Joana C. , Lopes Cláudia B. , Trindade Tito , Vale Carlos , Pereira Eduarda
Published: May 2019

Modern societies depend strongly on electronic and electric equipment (EEE) which has a side effect result on the large production of electronic wastes (e-waste). This has been regarded as a worldwide issue, because of its environmental impact—namely due to non-adequate treatment and storage limitations. In particular, EEE is dependent on the availability of rare earth elements (REEs), considered as the “vitamins” of modern industry, due to their crucial role in the development of new cutting-edge technologies. High demand and limited resources of REEs in Europe, combined with potential environmental problems, enforce the development of innovative low-cost techniques and materials to recover these elements from e-waste and wastewaters. In this context, sorption methods have shown advantages to pre-concentrate REEs from wastewaters and several studies have reported the use of diverse nanomaterials for these purposes, although mostly describing the sorption of REEs from synthetic and mono-elemental solutions at unrealistic metal concentrations. This review is a one-stop-reference by bringing together recent research works in the scope of the application of carbon nanomaterials for the recovery of REEs from water.
Effect of 1 Year Krill Oil Supplementation on Cognitive Achievement of Dutch Adolescents: A Double-Blind Randomized Controlled Trial
Authors: van der Wurff Inge S.M. , von Schacky Clemens , Bergeland Trygve , Leontjevas Roeslan , Zeegers Maurice P. , Jolles Jelle , Kirschner Paul A. , de Groot Renate H.M.
Published: May 2019

Long-chain polyunsaturated fatty acids (LCPUFA) are important for brain development and function, maybe especially during adolescence. Observational studies have demonstrated an association between fish consumption (a source of LCPUFA) and cognition in adolescents, but intervention trials are lacking. The goal of the current study was to investigate the effect of one year of krill oil (a source of LCPUFA) supplementation on the cognitive performance of adolescents with a low Omega-3 Index (O3I ≤ 5%). A double-blind, randomized, and placebo-controlled supplementation trial with repeated measurements (baseline (T0), three months (T1), six months (T2), and 12 months (T3)) in adolescents (267 randomized) was executed. Participants were randomized to 400 mg eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) per day in Cohort I or placebo and 800 mg EPA + DHA per day in Cohort II or placebo. O3I was monitored by a finger prick at all time points. At T0, T2, and T3, participants executed a neurocognitive test battery. Covariate corrected mixed models were run with either condition (krill or placebo) or O3I as predictors. Krill oil supplementation led to a small but significant increase in mean O3I, but few participants increased to the intended O3I range (8–11%). There was no significant effect of supplementation on the neurocognitive tests, nor a relationship between O3I and neurocognitive test scores. The increase in O3I was small in most participants, probably due to non-compliance. Possibly the increase in O3I was too small to demonstrate an effect. More research on the influence of LCPUFAs on cognition in adolescents is needed.
Treadmill Exercise before and during Pregnancy Improves Bone Deficits in Pregnant Growth Restricted Rats without the Exacerbated Effects of High Fat Diet
Authors: Anevska Kristina , Mahizir Dayana , Briffa Jessica F. , Jefferies Andrew J. , Wark John D. , Grills Brian L. , Brady Rhys D. , McDonald Stuart J. , Wlodek Mary E. , Romano Tania
Published: May 2019

Growth restriction programs adult bone deficits and increases the risk of obesity, which may be exacerbated during pregnancy. We aimed to determine if high-fat feeding could exacerbate the bone deficits in pregnant growth restricted dams, and whether treadmill exercise would attenuate these deficits. Uteroplacental insufficiency was induced on embryonic day 18 (E18) in Wistar Kyoto (WKY) rats using bilateral uterine vessel ligation (restricted) or sham (control) surgery. The F1 females consumed a standard or high-fat (HFD) diet from 5 weeks, commenced treadmill exercise at 16 weeks, and they were mated at 20 weeks. Femora and plasma from the pregnant dams were collected at post-mortem (E20) for peripheral quantitative computed tomography (pQCT), mechanical testing, histomorphometry, and plasma analysis. Sedentary restricted females had bone deficits compared to the controls, irrespective of diet, where such deficits were prevented with exercise. Osteocalcin increased in the sedentary restricted females compared to the control females. In the sedentary HFD females, osteocalcin was reduced and CTX-1 was increased, with increased peak force and bending stress compared to the chow females. Exercise that was initiated before and continued during pregnancy prevented bone deficits in the dams born growth restricted, whereas a HFD consumption had minimal bone effects. These findings further highlight the beneficial effects of exercise for individuals at risk of bone deficits.
Validation of an Inverse Fitting Method of Diffuse Reflectance Spectroscopy to Quantify Multi-Layered Skin Optical Properties
Authors: Wang Chiao-Yi , Kao Tzu-Chia , Chen Yin-Fu , Su Wen-Wei , Shen Hsin-Jou , Sung Kung-Bin
Published: May 2019

Skin consists of epidermis and dermis layers that have distinct optical properties. The quantification of skin optical properties is commonly achieved by modeling photon propagation in tissue using Monte Carlo (MC) simulations and iteratively fitting experimentally measured diffuse reflectance spectra. In order to speed up the inverse fitting process, time-consuming MC simulations have been replaced by artificial neural networks to quickly calculate reflectance spectra given tissue geometric and optical parameters. In this study the skin was modeled to consist of three layers and different scattering properties of the layers were considered. A new inverse fitting procedure was proposed to improve the extraction of chromophore-related information in the skin, including the hemoglobin concentration, oxygen saturation and melanin absorption. The performance of the new inverse fitting procedure was evaluated on 40 sets of simulated spectra. The results showed that the fitting procedure without knowing the epidermis thickness extracted chromophore information with accuracy similar to or better than fitting with known epidermis thickness, which is advantageous for practical applications due to simpler and more cost-effective instruments. In addition, the melanin volume fraction multiplied by the thickness of the melanin-containing epidermis layer was estimated more accurately than the melanin volume fraction itself. This product has the potential to provide a quantitative indicator of melanin absorption in the skin. In-vivo cuff occlusion experiments were conducted and skin optical properties extracted from the experiments were comparable to the results of previously reported in vivo studies. The results of the current study demonstrated the applicability of the proposed method to quantify the optical properties related to major chromophores in the skin, as well as scattering coefficients of the dermis. Therefore, it has the potential to be a useful tool for quantifying skin optical properties in vivo.
Dual Responsive Polymersomes for Gold Nanorod and Doxorubicin Encapsulation: Nanomaterials with Potential Use as Smart Drug Delivery Systems
Authors: DiazDuarte-Rodriguez Melissa , Cortez-Lemus Norma A. , Licea-Claverie Angel , Licea-Rodriguez Jacob , Méndez Eugenio R.
Published: May 2019

In the present study, poly(ethylene glycol)-b-poly(N,N-diethylaminoethyl methacrylate) (PEG-b-PDEAEM) amphiphilic block copolymers were synthetized by reversible addition-fragmentation chain transfer (RAFT) polymerization using two different macro chain transfer agents containing PEG of 2000 and 5000 g/mol and varying the length of the PDEAEM segment. From the obtained block copolymers, polymersome type nanometric aggregates were obtained by two different techniques. By direct dispersion, particle diameters around 200 nm were obtained, while by solvent exchange using THF and water, the obtained diameters were around 100 nm. These block copolymers were used to encapsulate gold nanorods and doxorubicin (DOX) with good efficiencies to obtain nanomaterials with potential use as dual stimuli-sensitive drug delivery systems for combined anticancer therapies. Drug delivery studies showed that the release rate of DOX was accelerated when the pH was lowered from 7.4 to 5.8 and also when the systems were irradiated with a NIR laser at pH 7.4. The combination of lower pH and near infrared (NIR) irradiation resulted in higher drug release only in the case of polymersomes with lower molecular weight PEG.
British Muslims Navigating between Individualism and Traditional Authority
Authors: Amin Hira
Published: May 2019

According to some sociologists, one of the hallmarks of modernity is the end of ‘pre-determined’ identities and its replacement with bricolage projects in which people literally create ‘do-it-yourself’ identities. This has also significantly impacted the religious sphere, where it has been argued that traditional authorities are constantly undermined by individualistic cultures, print media, rising literacy rates and, more recently, the internet. Through analysing online discussions, this article explores how some young, devout British Muslims navigate between individualism and their own personal understanding of Islam on the one hand and following traditional religious authority figures on the other. This article argues that British Muslims who are consciously trying to practise their faith are neither following traditional religious authoritative figures or institutions blindly nor fully rationalising and individualising their faith. Rather, they are involved in a complex process of choosing and self-restricting themselves to certain scholars that they believe are representative of Islam and thereafter critically engaging with the scholar and his or her verdicts by adding in their own opinions, experiences and even Islamic textual evidence. While this illustrates how religious authority is transforming in the age of new media, the persistent engagement with scholars also indicates how they still play a significant role in the shaping of Islam in Britain.
Identifying a Slums’ Degree of Deprivation from VHR Images Using Convolutional Neural Networks
Authors: Ajami Alireza , Kuffer Monika , Persello Claudio , Pfeffer Karin
Published: May 2019

In the cities of the Global South, slum settlements are growing in size and number, but their locations and characteristics are often missing in official statistics and maps. Although several studies have focused on detecting slums from satellite images, only a few captured their variations. This study addresses this gap using an integrated approach that can identify a slums’ degree of deprivation in terms of socio-economic variability in Bangalore, India using image features derived from very high resolution (VHR) satellite images. To characterize deprivation, we use multiple correspondence analysis (MCA) and quantify deprivation with a data-driven index of multiple deprivation (DIMD). We take advantage of spatial features learned by a convolutional neural network (CNN) from VHR satellite images to predict the DIMD. To deal with a small training dataset of only 121 samples with known DIMD values, insufficient to train a deep CNN, we conduct a two-step transfer learning approach using 1461 delineated slum boundaries as follows. First, a CNN is trained using these samples to classify slums and formal areas. The trained network is then fine-tuned using the 121 samples to directly predict the DIMD. The best prediction is obtained by using an ensemble non-linear regression model, combining the results of the CNN and models based on hand-crafted and geographic information system (GIS) features, with R2 of 0.75. Our findings show that using the proposed two-step transfer learning approach, a deep CNN can be trained with a limited number of samples to predict the slums’ degree of deprivation. This demonstrates that the CNN-based approach can capture variations of deprivation in VHR images, providing a comprehensive understanding of the socio-economic situation of slums in Bangalore.
A New Application of Random Forest Algorithm to Estimate Coverage of Moss-Dominated Biological Soil Crusts in Semi-Arid Mu Us Sandy Land, China
Authors: Chen Xiang , Wang Tao , Liu Shulin , Peng Fei , Tsunekawa Atsushi , Kang Wenping , Guo Zichen , Feng Kun
Published: May 2019

Biological soil crusts (BSCs) play an essential role in desert ecosystems. Knowledge of the distribution and disappearance of BSCs is vital for the management of ecosystems and for desertification researches. However, the major remote sensing approaches used to extract BSCs are multispectral indices, which lack accuracy, and hyperspectral indices, which have lower data availability and require a higher computational effort. This study employs random forest (RF) models to optimize the extraction of BSCs using band combinations similar to the two multispectral BSC indices (Crust Index-CI; Biological Soil Crust Index-BSCI), but covering all possible band combinations. Simulated multispectral datasets resampled from in-situ hyperspectral data were used to extract BSC information. Multispectral datasets (Landsat-8 and Sentinel-2 datasets) were then used to detect BSC coverage in Mu Us Sandy Land, located in northern China, where BSCs dominated by moss are widely distributed. The results show that (i) the spectral curves of moss-dominated BSCs are different from those of other typical land surfaces, (ii) the BSC coverage can be predicted using the simulated multispectral data (mean square error (MSE) < 0.01), (iii) Sentinel-2 satellite datasets with CI-based band combinations provided a reliable RF model for detecting moss-dominated BSCs (10-fold validation, R2 = 0.947; ground validation, R2 = 0.906). In conclusion, application of the RF algorithm to the Sentinel-2 dataset can precisely and effectively map BSCs dominated by moss. This new application can be used as a theoretical basis for detecting BSCs in other arid and semi-arid lands within desert ecosystems.
Sparsity Based Full Rank Polarimetric Reconstruction of Coherence Matrix T
Authors: Aghababaee Hossein , Ferraioli Giampaolo , Ferro-Famil Laurent , Schirinzi Gilda , Huang Yue
Published: May 2019

In the frame of polarimetric synthetic aperture radar (SAR) tomography, full-ranks reconstruction framework has been recognized as a significant technique for fully characterization of superimposed scatterers in a resolution cell. The technique, mainly is characterized by the advantages of polarimetric scattering pattern reconstruction, allows physical feature extraction of the scatterers. In this paper, to overcome the limitations of conventional full-rank tomographic techniques in natural environments, a polarimetric estimator with advantages of super-resolution imaging is proposed. Under the frame of compressive sensing (CS) and sparsity based reconstruction, the profile of second order polarimetric coherence matrix T is recovered. Once the polarimetric coherence matrices of the scatterers are available, the physical features can be extracted using classical polarimetric processing techniques. The objective of this study is to evaluate the performance of the proposed full-rank polarimetric reconstruction by means of conventional three-component decomposition of T, and focusing on the consistency of vertical resolution and polarimetric scattering pattern of the scatterers. The outcomes from simulated and two different real data sets confirm that significant improvement can be achieved in the reconstruction quality with respect to conventional approaches.
Climate Change, Land Use/Land Cover Change, and Population Growth as Drivers of Groundwater Depletion in the Central Valleys, Oaxaca, Mexico
Authors: Ojeda Olivares Edwin Antonio , Sandoval Torres Sadoth , Belmonte Jiménez Salvador Isidro , Campos Enríquez José Oscar , Zignol Francesco , Reygadas Yunuen , Tiefenbacher John P.
Published: May 2019

Groundwater depletion is an important problem driven by population growth, land use and land cover (LULC) change, climate change, and other factors. Groundwater depletion generates water stress and encourages unstainable resource use. The aim of this study is to determine how population growth, LULC change, and climate change relate to groundwater depletion in the Alto Atoyac sub-basin, Oaxaca, Mexico. Twenty-five years of dry season water table data from 1984 to 2009 are analyzed to examine annual groundwater depletion. Kriging is used to interpolate the region’s groundwater levels in a geographic information system (GIS) from mapped point measurements. An analysis of remotely sensed data revealed patterns of LULC change during a 34-year (1986–2018) period, using a supervised, machine-learning classification algorithm to calculate the changes in LULC. This analysis is shown to have an 85% accuracy. A global circulation model (GFDL-CM3) and the RCP4.5 and RCP8.5 scenarios were used to estimate the effects of climate change on the region’s groundwater. Estimates of evapotranspiration (using HELP3.5 code) and runoff (USDA-SCS-CN), were calculated. Since 1984, the region’s mean annual temperature has increased 1.79 °C and urban areas have increased at a rate of 2.3 km2/year. Population growth has increased water consumption by 97.93 × 106 m3/year. The volume of groundwater is shrinking at a rate of 284.34 × 106 m3/year, reflecting the extreme pressure on groundwater supply in the region. This research reveals the nature of the direct impacts that climate change, changing LULCs, and population growth have in the process of groundwater depletion.
Dual Learning-Based Siamese Framework for Change Detection Using Bi-Temporal VHR Optical Remote Sensing Images
Authors: Fang Bo , Pan Li , Kou Rong
Published: May 2019

As a fundamental and profound task in remote sensing, change detection from very-high-resolution (VHR) images plays a vital role in a wide range of applications and attracts considerable attention. Current methods generally focus on the research of simultaneously modeling and discriminating the changed and unchanged features. In practice, for bi-temporal VHR optical remote sensing images, the temporal spectral variability tends to exist in all bands throughout the entire paired images, making it difficult to distinguish none-changes and changes with a single model. In this paper, motivated by this observation, we propose a novel hybrid end-to-end framework named dual learning-based Siamese framework (DLSF) for change detection. The framework comprises two parallel streams which are dual learning-based domain transfer and Siamese-based change decision. The former stream is aimed at reducing the domain differences of two paired images and retaining the intrinsic information by translating them into each other’s domain. While the latter stream is aimed at learning a decision strategy to decide the changes in two domains, respectively. By training our proposed framework with certain change map references, this method learns a cross-domain translation in order to suppress the differences of unchanged regions and highlight the differences of changed regions in two domains, respectively, then focus on the detection of changed regions. To the best of our knowledge, the idea of incorporating dual learning framework and Siamese network for change detection is novel. The experimental results on two datasets and the comparison with other state-of-the-art methods verify the efficiency and superiority of our proposed DLSF.
GOCE-Derived Coseismic Gravity Gradient Changes Caused by the 2011 Tohoku-Oki Earthquake
Authors: Xu Xinyu , Ding Hao , Zhao Yongqi , Li Jin , Hu Minzhang
Published: May 2019

In contrast to most of the coseismic gravity change studies, which are generally based on data from the Gravity field Recovery and Climate Experiment (GRACE) satellite mission, we use observations from the Gravity field and steady-state Ocean Circulation Explorer (GOCE) Satellite Gravity Gradient (SGG) mission to estimate the coseismic gravity and gravity gradient changes caused by the 2011 Tohoku-Oki Mw 9.0 earthquake. We first construct two global gravity field models up to degree and order 220, before and after the earthquake, based on the least-squares method, with a bandpass Auto Regression Moving Average (ARMA) filter applied to the SGG data along the orbit. In addition, to reduce the influences of colored noise in the SGG data and the polar gap problem on the recovered model, we propose a tailored spherical harmonic (TSH) approach, which only uses the spherical harmonic (SH) coefficients with the degree range 30–95 to compute the coseismic gravity changes in the spatial domain. Then, both the results from the GOCE observations and the GRACE temporal gravity field models (with the same TSH degrees and orders) are simultaneously compared with the forward-modeled signals that are estimated based on the fault slip model of the earthquake event. Although there are considerable misfits between GOCE-derived and modeled gravity gradient changes (ΔVxx, ΔVyy, ΔVzz, and ΔVxz), we find analogous spatial patterns and a significant change (greater than 3σ) in gravity gradients before and after the earthquake. Moreover, we estimate the radial gravity gradient changes from the GOCE-derived monthly time-variable gravity field models before and after the earthquake, whose amplitudes are at a level over three times that of their corresponding uncertainties, and are thus significant. Additionally, the results show that the recovered coseismic gravity signals in the west-to-east direction from GOCE are closer to the modeled signals than those from GRACE in the TSH degree range 30–95. This indicates that the GOCE-derived gravity models might be used as additional observations to infer/explain some time-variable geophysical signals of interest.
In Situ Hyperspectral Remote Sensing for Monitoring of Alpine Trampled and Recultivated Species
Authors: Kycko Marlena , Zagajewski Bogdan , Lavender Samantha , Dabija Anca
Published: May 2019

Vegetation, through its condition, reflects the properties of the environment. Heterogeneous alpine ecosystems play a critical role in global monitoring systems, but due to low accessibility, cloudy conditions, and short vegetation periods, standard monitoring methods cannot be applied comprehensively. Hyperspectral tools offer a variety of methods based on narrow-band data, but before extrapolation to an airborne or satellite scale, they must be verified using plant biometrical variables. This study aims to assess the condition of alpine sward dominant species (Agrostis rupestris, Festuca picta, and Luzula alpino-pilosa) of the UNESCO Man&Biosphere Tatra National Park (TPN) where the high mountain grasslands are strongly influenced by tourists. Data were analyzed for trampled, reference, and recultivated polygons. The field-obtained hyperspectral properties were verified using ground measured photosynthetically active radiation, chlorophyll content, fluorescence, and evapotranspiration. Statistically significant changes in terms of cellular structures, chlorophyll, and water content in the canopy were detected. Lower values for the remote sensing indices were observed for trampled plants (about 10–15%). Species in recultivated areas were characterized by a similar, or sometimes improved, spectral properties than the reference polygons; confirmed by fluorescence measurements (Fv/Fm). Overall, the fluorescence analysis and remote sensing tools confirmed the suitability of such methods for monitoring species in remote mountain areas, and the general condition of these grasslands was determined as good.
Channel Imbalances and Along-Track Baseline Estimation for the GF-3 Azimuth Multichannel Mode
Authors: Shang Mingyang , Qiu Xiaolan , Han Bing , Ding Chibiao , Hu Yuxin
Published: May 2019

Azimuth multichannel (AMC) synthetic aperture radar (SAR), which contains multiple receiving antennas along the azimuth, can prevent the minimum antenna area constraint and provide high-resolution and wide-swath (HRWS) SAR images. Channel calibration and along-track baseline estimation are important topics in an AMC SAR system, since they have a great impact on image quality. Based on the signal model for stationary target of AMC SAR, this paper first analyses the influence of the along-track baseline and channel imbalances on SAR images by simulation. Then, a novel method to simultaneously estimate the along-track baseline, phase imbalance and range sample time imbalance (RSTI) based on the azimuth cross-correlation in the two-dimensional frequency domain is addressed. In addition, with the help of simulations and real data acquired by Gaofen-3 (GF-3), the effectiveness of this method is verified by comparing with some existing methods. Finally, this paper analyzes the estimation accuracy of this method under different scenarios and signal-to-noise ratios (SNRs), and points out the direction for future research.
A New Deep Learning Algorithm for SAR Scene Classification Based on Spatial Statistical Modeling and Features Re-Calibration
Authors: Chen Lifu , Cui Xianliang , Li Zhenhong , Yuan Zhihui , Xing Jin , Xing Xuemin , Jia Zhiwei
Published: May 2019

Synthetic Aperture Radar (SAR) scene classification is challenging but widely applied, in which deep learning can play a pivotal role because of its hierarchical feature learning ability. In the paper, we propose a new scene classification framework, named Feature Recalibration Network with Multi-scale Spatial Features (FRN-MSF), to achieve high accuracy in SAR-based scene classification. First, a Multi-Scale Omnidirectional Gaussian Derivative Filter (MSOGDF) is constructed. Then, Multi-scale Spatial Features (MSF) of SAR scenes are generated by weighting MSOGDF, a Gray Level Gradient Co-occurrence Matrix (GLGCM) and Gabor transformation. These features were processed by the Feature Recalibration Network (FRN) to learn high-level features. In the network, the Depthwise Separable Convolution (DSC), Squeeze-and-Excitation (SE) Block and Convolution Neural Network (CNN) are integrated. Finally, these learned features will be classified by the Softmax function. Eleven types of SAR scenes obtained from four systems combining different bands and resolutions were trained and tested, and a mean accuracy of 98.18% was obtained. To validate the generality of FRN-MSF, five types of SAR scenes sampled from two additional large-scale Gaofen-3 and TerraSAR-X images were evaluated for classification. The mean accuracy of the five types reached 94.56%; while the mean accuracy for the same five types of the former tested 11 types of scene was 96%. The high accuracy indicates that the FRN-MSF is promising for SAR scene classification without losing generality.
A WASN-Based Suburban Dataset for Anomalous Noise Event Detection on Dynamic Road-Traffic Noise Mapping
Authors: Alsina-Pagès Rosa Ma , Orga Ferran , Alías Francesc , Socoró Joan Claudi
Published: May 2019

Traffic noise is presently considered one of the main pollutants in urban and suburban areas. Several recent technological advances have allowed a step forward in the dynamic computation of road-traffic noise levels by means of a Wireless Acoustic Sensor Network (WASN) through the collection of measurements in real-operation environments. In the framework of the LIFE DYNAMAP project, two WASNs have been deployed in two pilot areas: one in the city of Milan, as an urban environment, and another around the city of Rome in a suburban location. For a correct evaluation of the noise level generated by road infrastructures, all Anomalous Noise Events (ANE) unrelated to regular road-traffic noise (e.g., sirens, horns, speech, etc.) should be removed before updating corresponding noise maps. This work presents the production and analysis of a real-operation environmental audio database collected through the 19-node WASN of a suburban area. A total of 156 h and 20 min of labeled audio data has been obtained differentiating among road-traffic noise and ANEs (classified in 16 subcategories). After delimiting their boundaries manually, the acoustic salience of the ANE samples is automatically computed as a contextual Signal-to-Noise Ratio (SNR) together with its impact on the A-weighted equivalent level ( Δ L A e q ). The analysis of the real-operation WASN-based environmental database is evaluated with these metrics, and we conclude that the 19 locations of the network present substantial differences in the occurrences of the subcategories of ANE, with a clear predominance of the noise of sirens, trains, and thunder.
The Challenges for Gender Equity and Women in Leadership in a Distributed University in Regional Australia
Authors: Thomas Janelle , Thomas Cate , Smith Kirsty
Published: May 2019

The barriers to women’s achievement and career progression in the higher education sector have been well researched. It has long been acknowledged that career breaks for child-rearing, and women’s self-beliefs about their abilities can impact negatively on their careers, and many programs and policies have been implemented to redress these around the world. This article is focussed around a regional Australian university, with multiple campuses distributed over 1000 km across two states. Courses, schools, and work teams are often spread across multiple campuses, and travel between campuses is sometimes a necessity; one that is time-consuming and requires time away from family. For some women, travelling is not possible due to family and other commitments or constraints. This paper explores how working in a regional university, with distributed campuses, has an additional impact on women’s career progression. Through auto-ethnographic accounts of four female staff members, we explore the intersection of gender and location through case studies of personal experiences, investigating the effects that distance and travel limitations can have on participation in work team and networking events, access to professional development opportunities, and career progression within the institution.
Wisdom for Traveling Far: Making Educational Travel Sustainable
Authors: Hale Brack W.
Published: May 2019

Educational travel has been demonstrated to be an effective means of education to develop sustainable and pro-environmental behaviors. However, as this paper reviews, recent scholarship has revealed that educational travel may harm the communities that host it even while it is achieving gains for students. This paper encourages educational travel providers (institutions, staff, and faculty) to leverage the need for a broader perspective towards sustainability in educational travel programs so that their host communities also benefit. The programs can accomplish this by engaging students in the process of making the programs and their participants more sustainable. The paper ends with several examples from the author’s own experience as an educational travel leader and several recommendations to reduce the negative impacts on host communities.
Dynamic Environmental Efficiency Assessment of Industrial Water Pollution
Authors: Zhang Ronggang , Lu Ching-Cheng , Lee Jen-Hui , Feng Ying , Chiu Yung-Ho
Published: May 2019

In the face of severe water pollution, all provinces and cities in China have actively invested in water environment management funds driven by the goals of national energy conservation and emissions reduction. However, due to differences in natural environment, economic and technological levels, industrial structure, and other aspects in provinces and cities, their water environment management effects are also different across time and space. Under economic development and environmental regulation policies, it can be seen that the change in industrial GDP is not completely consistent with that of industrial wastewater discharge. How to improve desirable outputs and reduce undesirable outputs under the limited investment in water pollution control are key issues when investigating the efficiency of industrial water pollution control. This study uses the Dynamic SBM (Slacks-Based Measure) model to assess wastewater resources for research samples covering the 30 regions of China. There are two output variables, two input variables, and one carry-over variable. The output variables are industrial wastewater treatment and industrial output, the two input variables are industrial water consumption and facility operation cost, and the carry-over variable is industrial waste. This study concludes with implications for theory research, as these variables may lead to a better understanding and merging with the input variables, output variables, and carry-over variable of recent studies. The empirical results show that from the efficiency rank changes of the 30 regions for 2011–2015, regions with higher industrial output do not appear to have improved versus other regions, such as for Shandong, Guangdong, Jiangsu, Qinghai, and Zhejiang. The 30 regions’ efficiency scores show some volatility, with 13 regions’ efficiency score volatility clustering close to 0, like Beijing, Chongqing, Shandong, Guangdong, and Sichuan. In contrast, for Anhui, Inner Mongolia, Zhejiang, and Xinjiang, their efficiency scores fell more than other regions in this period and thus should adjust their input/output variables to increase their efficiency scores. This study further presents that many lower-/middle-/high-industrial output regions do not achieve a balance between industrial output and industrial wastewater treatment. How to find a balance between these two factors for any region is a vitally important issue for industrial wastewater treatment policy makers. Under such a circumstance, an industrial output region may not actually be highly efficient at doing this.
Using Static Concentrator Technology to Achieve Global Energy Goal
Authors: Alamoudi Abdullah , Saaduddin Syed Muhammad , Munir Abu Bakar , Muhammad-Sukki Firdaus , Abu-Bakar Siti Hawa , Mohd Yasin Siti Hajar , Karim Ridoan , Bani Nurul Aini , Abubakar Mas’ud Abdullahi , Ardila-Rey Jorge Alfredo , Prabhu Radhakrishna , Sellami Nazmi
Published: May 2019

Solar energy has demonstrated promising prospects in satisfying energy requirements, specifically through solar photovoltaic (PV) technology. Despite that, the cost of installation is deemed as the main hurdle to the widespread uptake of solar PV systems due to the use of expensive PV material in the module. At this point, we argue that a reduction in PV cost could be achieved through the usage of concentrator. A solar concentrator is a type of lens that is capable of increasing the collection of sun rays and focusing them onto a lesser PV area. The cost of the solar module could then be reduced on the assumption that the cost of introducing the solar concentrator in the solar module design is much lower than the cost of the removed PV material. Static concentrators, in particular, have great promise due to their ability to be integrated at any place of the building, usually on the building facade, windows and roof, due to their low geometrical concentration. This paper provides a historic context on the development of solar concentrators and showcases the latest technological development in static PV concentrators including non-imaging compound parabolic concentrator, V-trough, luminescent solar concentrator and quantum dot concentrator. We anticipated that the static low concentrating PV (LCPV) system could serve to enhance the penetration of PV technology in the long run to achieve the Sustainable Development Goal (SDG) 7—to open an avenue to affordable, reliable, sustainable, and modern energy for all by 2030.
Sustainability Evaluation of Process Planning for Single CNC Machine Tool under the Consideration of Energy-Efficient Control Strategies Using Random Forests
Authors: Zhang Chaoyang , Jiang Pingyu
Published: May 2019

As an important part of industrialized society, manufacturing consumes a large amount of raw materials and energy, which motivates decision-makers to tackle this problem in different manners. Process planning is an important optimization method to realize the object, and energy consumption, carbon emission, or sustainability evaluation is the basis for the optimization stage. Although the evaluation research has drawn a great deal of attention, most of it neglects the influence of state control of machine tools on the energy consumption of machining processes. To address the above issue, a sustainability evaluation method of process planning for single computer numerical control (CNC) machine tool considering energy-efficient control strategies has been developed. First, four energy-efficient control strategies of CNC machine tools are constructed to reduce their energy consumption. Second, a bi-level energy-efficient decision-making mechanism using random forests is established to select appropriate control strategies for different occasions. Then, three indicators are adopted to evaluate the sustainability of process planning under the consideration of energy-efficient control strategies, i.e., energy consumption, relative delay time, and machining costs. Finally, a pedestal part machined by a 3-axis vertical milling machine tool is used to verify the proposed methods. The results show that the reduction in energy consumption considering energy-efficient control strategies reaches 25%.
Power Relationship in the Governance of Regional Tourism Organizations in Brazil
Authors: Conceição Calidon Costa , Dos Anjos Francisco Antonio , Gadotti dos Anjos Sara Joana
Published: May 2019

Objective: The development of tourism is one the main objectives of managers seeking a greater competitive advantage for destinations. To achieve this objective, the political-institutional structure related to public and private organizations involved in the Brazilian scenario of tourism activities deliberately operate in the format of Regional Tourism Organizations—RTOs, which started in 2004. In this context, the aim of this study arose, which is to analyze the power relations of Regional Tourism Organizations of tourist regions. Design/Methodology: This research adopted a qualitative and quantitative approach, with data collection through documents, laws, reports and information about the RTOs and questionnaires in forms applied to 27 representatives of the public sector, 14 representatives of private sector and six representatives of the third sector, from a total population of 89 active members of the Regional Tourism Organizations: Costa Verde e Mar (state of Santa Catarina), Hortênsias (state of Rio Grande do Sul), and Costa das Dunas (state of Rio Grande do Norte). During the application of the forms, interviews were carried out, totaling 47 interviews with members of the RTOs. Quantitative analyses were generated by mean, mode, absolute and relative frequencies, multiple responses and dispersion graph, with the use of descriptive analyses. The qualitative analyses involving documents were descriptive, and those involving oral information were carried out using analysis of content of Bardin (1977). The different methods that were used in an interrelated manner and helped in the analysis of the data coming from the application of forms (quantitative), official documents (laws/decrees, regulations and statutes), and interviews with actors of the regional tourism organizations (qualitative), enabled the measurement of the effectiveness of the process of management of RTOs in relation to the dimension Power Relationship and the variables analyzed Representativeness, Harmony, Trust and Decision-Making Power. Results: As a result, it was seen that the regional tourism organizations of the tourist regions operate in an effective manner in the public or private sectors and that they involve the management of shared practices by the regional tourism organizations in the destinations studied in terms of representativeness, harmony, trust and decision-making power. Novelty/Value: This research theoretically deepened for the academy the theme of regional governance and power relationship between public and private actors in tourism who are important for the competitive performance of a tourist destination. It also analyzes how the management and governance of regional tourism organizations behaves in terms of power relationships.
Is Voluntary Product Stewardship for E-Waste Working in New Zealand? A Whangarei Case Study
Authors: Blake Vicktoria , Farrelly Trisia , Hannon Jonathon
Published: May 2019

New Zealand currently manages its annually-generated 99,000 tonnes of e-waste via voluntary product stewardship schemes. Limited data is available to determine the success of this approach. This lack of data is cited as the logic preventing the declaration of e-waste as a priority product by the Minister for the Environment which would trigger the enforcement of mandatory product stewardship. This case study involved an online survey of 264 Whangarei District householders asking questions about e-waste creation and management, as well as analyses of local services, and local and national policy. It found that only 1.8% of the estimated e-waste created in the district is recycled by municipal services, with the ‘cost to recycle’ and ‘a lack of knowledge’ presenting barriers to engagement in these services. The ‘lack of ability to repair/the cost to repair’ was found to be the most significant driver for e-waste creation. The adoption of mandatory product stewardship for e-waste was recommended to ensure robust and transparent data collection, see recycling services become more accessible, and raise awareness of these services, thus reducing the value-action gap. Mandatory e-waste management would also impact product design to ensure affordable repair-ability, further supporting a circular economy for electronic goods.