bluuebunny/crossref_metadata_2025 huggingface dataset:
Elucidation of Spatial Distribution of Hydrophobic Aromatic Compounds Encapsulated in Polymer Micelles by Anomalous Small-Angle X-ray Scattering
Authors: Sasaki Shota , Machida Ginpei , Nakanishi Ryosuke , Kinoshita Masaki , Akiba Isamu
Published: February 2018

Spatial distribution of bromobenzene (BrBz) and 4-bromophenol (BrPh) as hydrophobic aromatic compounds incorporated in polymer micelles with vesicular structure consisting of poly(ethylene glycol)-b-poly(tert-butyl methacrylate) (PEG-b-PtBMA) in aqueous solution is investigated by anomalous small-angle X-ray scattering (ASAXS) analyses near Br K edge. Small-angle X-ray scattering (SAXS) intensities from PEG-b-PtBMA micelles containing BrBz and BrPh were decreased as the energy of incident X-ray approached to Br K edge corresponding to the energy dependence of anomalous scattering factor of Br. The analysis for the energy dependence of SAXS profiles from the PEG-b-PtBMA micelles containing BrBz revealed that BrBz molecules were located in hydrophobic layer of PEG-b-PtBMA micelles. On the contrary, it was found by ASAXS that BrPh existed not only in the hydrophobic layer but also in the shell layer. Since ASAXS analysis successfully accomplished to visualize the spatial distribution of hydrophobic molecules in polymer micelles, it should be expected to be a powerful tool for characterization of drug delivery vehicles.
Incorporation of Stem Water Content into Vegetation Optical Depth for Crops and Woodlands
Authors: Hunt E. , Li Li , Friedman Jennifer , Gaiser Peter , Twarog Elizabeth , Cosh Michael
Published: February 2018

Estimation of vegetation water content (VWC) by optical remote sensing improves soil moisture retrievals from passive microwave radiometry. For a variety of vegetation types, the largest unknown for predicting VWC is stem water content, which is assumed to be allometrically related to the water content of the plant canopy. For maize and soybean, measured stem water contents were highly correlated to canopy water contents, so VWC was calculated directly from the normalized difference infrared index (NDII), which contrasts scattering at near-infrared wavelengths with absorption of shortwave infrared wavelengths by liquid water. Woodland tree height is linearly related to woody stem volume, and hence to stem water content. We hypothesized that tree height is positively correlated with canopy water content, and thus with NDII. Airborne color-infrared imagery was acquired at two study areas in a mixed agricultural and woodland landscape, and photogrammetric structure-from-motion point clouds were derived to estimate tree heights. However, estimated tree heights were only weakly correlated with measured data acquired for validation. NDII was calculated from Landsat 8 Operational Line Imager (30-m pixel) and WorldView-3 (7.5 m pixel); but contrary to the hypothesis, NDII was not correlated with woodland tree height. Lastly, the interaction of woodland and crops stem water contents on total VWC in a mixed landscape were simulated for 2 days, one in the early summer and one in the late summer. VWC for the region varied from 2.5 to 3.0 kg m−2, which was just under a threshold for accuracy for soil moisture retrievals using Coriolis WindSat. Woodland tree height should be included as an ancillary data set along with land cover classification for soil moisture retrieval algorithms.
A Deconvolution Technology of Microwave Radiometer Data Using Convolutional Neural Networks
Authors: Hu Weidong , Zhang Wenlong , Chen Shi , Lv Xin , An Dawei , Ligthart Leo
Published: February 2018

Microwave radiometer data is affected by many factors during the imaging process, including the antenna pattern, system noise, and the curvature of the Earth. Existing deconvolution methods such as Wiener filtering handle this degradation problem in the Fourier domain. However, under complex degradation conditions, the Wiener filtering results are not accurate. In this paper, a convolutional neural network (CNN) model is proposed to solve the degradation problem. The deconvolution procedure is defined as a regression problem in the spatial domain that can be solved with deep learning. For the real inverse process of microwave radiometer data, the CNN model has a more powerful reconstruction ability than Wiener filtering due to the multi-layer structure of the CNN, which enables the multiple feature transform of the data. Additionally, the complex degradation factor during the imaging process of a microwave radiometer can be solved with general framework-based learning. Experimental results demonstrated that the CNN model gains about 5 dB at the peak signal-to-noise ratio compared to the Wiener filtering deconvolution method, and can better distinguish the measured data.
Object-Based Change Detection in Urban Areas from High Spatial Resolution Images Based on Multiple Features and Ensemble Learning
Authors: Wang Xin , Liu Sicong , Du Peijun , Liang Hao , Xia Junshi , Li Yunfeng
Published: February 2018

To improve the accuracy of change detection in urban areas using bi-temporal high-resolution remote sensing images, a novel object-based change detection scheme combining multiple features and ensemble learning is proposed in this paper. Image segmentation is conducted to determine the objects in bi-temporal images separately. Subsequently, three kinds of object features, i.e., spectral, shape and texture, are extracted. Using the image differencing process, a difference image is generated and used as the input for nonlinear supervised classifiers, including k-nearest neighbor, support vector machine, extreme learning machine and random forest. Finally, the results of multiple classifiers are integrated using an ensemble rule called weighted voting to generate the final change detection result. Experimental results of two pairs of real high-resolution remote sensing datasets demonstrate that the proposed approach outperforms the traditional methods in terms of overall accuracy and generates change detection maps with a higher number of homogeneous regions in urban areas. Moreover, the influences of segmentation scale and the feature selection strategy on the change detection performance are also analyzed and discussed.
Flow Control in Wells Turbines for Harnessing Maximum Wave Power
Authors: Lekube Jon , Garrido Aitor , Garrido Izaskun , Otaola Erlantz , Maseda Javier
Published: February 2018

Oceans, and particularly waves, offer a huge potential for energy harnessing all over the world. Nevertheless, the performance of current energy converters does not yet allow us to use the wave energy efficiently. However, new control techniques can improve the efficiency of energy converters. In this sense, the plant sensors play a key role within the control scheme, as necessary tools for parameter measuring and monitoring that are then used as control input variables to the feedback loop. Therefore, the aim of this work is to manage the rotational speed control loop in order to optimize the output power. With the help of outward looking sensors, a Maximum Power Point Tracking (MPPT) technique is employed to maximize the system efficiency. Then, the control decisions are based on the pressure drop measured by pressure sensors located along the turbine. A complete wave-to-wire model is developed so as to validate the performance of the proposed control method. For this purpose, a novel sensor-based flow controller is implemented based on the different measured signals. Thus, the performance of the proposed controller has been analyzed and compared with a case of uncontrolled plant. The simulations demonstrate that the flow control-based MPPT strategy is able to increase the output power, and they confirm both the viability and goodness.
A Railway Track Geometry Measuring Trolley System Based on Aided INS
Authors: Chen Qijin , Niu Xiaoji , Zuo Lili , Zhang Tisheng , Xiao Fuqin , Liu Yi , Liu Jingnan
Published: February 2018

Accurate measurement of the railway track geometry is a task of fundamental importance to ensure the track quality in both the construction phase and the regular maintenance stage. Conventional track geometry measuring trolleys (TGMTs) in combination with classical geodetic surveying apparatus such as total stations alone cannot meet the requirements of measurement accuracy and surveying efficiency at the same time. Accurate and fast track geometry surveying applications call for an innovative surveying method that can measure all or most of the track geometric parameters in short time without interrupting the railway traffic. We provide a novel solution to this problem by integrating an inertial navigation system (INS) with a geodetic surveying apparatus, and design a modular TGMT system based on aided INS, which can be configured according to different surveying tasks including precise adjustment of slab track, providing tamping measurements, measuring track deformation and irregularities, and determination of the track axis. TGMT based on aided INS can operate in mobile surveying mode to significantly improve the surveying efficiency. Key points in the design of the TGMT’s architecture and the data processing concept and workflow are introduced in details, which should benefit subsequent research and provide a reference for the implementation of this kind of TGMT. The surveying performance of proposed TGMT with different configurations is assessed in the track geometry surveying experiments and actual projects.
A Maximum Feasible Subsystem for Globally Optimal 3D Point Cloud Registration
Authors: Yu Chanki , Ju Da
Published: February 2018

In this paper, a globally optimal algorithm based on a maximum feasible subsystem framework is proposed for robust pairwise registration of point cloud data. Registration is formulated as a branch-and-bound problem with mixed-integer linear programming. Among the putative matches of three-dimensional (3D) features between two sets of range data, the proposed algorithm finds the maximum number of geometrically correct correspondences in the presence of incorrect matches, and it estimates the transformation parameters in a globally optimal manner. The optimization requires no initialization of transformation parameters. Experimental results demonstrated that the presented algorithm was more accurate and reliable than state-of-the-art registration methods and showed robustness against severe outliers/mismatches. This global optimization technique was highly effective, even when the geometric overlap between the datasets was very small.
Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR
Authors: Li Jincheng , Chen Jie , Wang Pengbo , Li Chunsheng
Published: February 2018

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.
Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network
Authors: Li Yuexiang , Shen Linlin
Published: February 2018

Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is very useful to increase the accuracy and efficiency of pathologists. In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1), lesion dermoscopic feature extraction (task 2) and lesion classification (task 3). A deep learning framework consisting of two fully convolutional residual networks (FCRN) is proposed to simultaneously produce the segmentation result and the coarse classification result. A lesion index calculation unit (LICU) is developed to refine the coarse classification results by calculating the distance heat-map. A straight-forward CNN is proposed for the dermoscopic feature extraction task. The proposed deep learning frameworks were evaluated on the ISIC 2017 dataset. Experimental results show the promising accuracies of our frameworks, i.e., 0.753 for task 1, 0.848 for task 2 and 0.912 for task 3 were achieved.
Big Geospatial Data Analytics for Global Mangrove Biomass and Carbon Estimation
Authors: Tang Wenwu , Zheng Minrui , Zhao Xiang , Shi Jiyang , Yang Jianxin , Trettin Carl
Published: February 2018

The objective of this study is to estimate the biomass and carbon of global-level mangroves as a special type of wetland. Mangrove ecosystems play an important role in regulating carbon cycling, thus having a significant impact on global environmental change. Extensive studies have been conducted for the estimation of mangrove biomass and carbon stock. However, this estimation at a global level has been insufficiently investigated because the spatial scale of interest is large and most existing studies are based on physically challenging fieldwork surveys that are limited to local scales. Over the past few decades, high-resolution geospatial data related to mangroves have been increasingly collected and processed using remote sensing and Geographic Information Systems (GIS) technologies. While these geospatial data create potential for the estimation of mangrove biomass and carbon, the processing and analysis of these data represent a big data-driven challenge. In this study, we present a spatially explicit approach that integrates GIS-based geospatial analysis and high-performance parallel computing for the estimation of mangrove biomass and carbon at the global level. This integrated approach provides support for enabling and accelerating the global-level estimation of mangrove biomass and carbon from existing high-resolution geospatial data. With this integrated approach, the total area, biomass (including above- and below-ground), and associated carbon stock of global mangroves are estimated as 130,420 km2, 1.908 Pg, and 0.725 Pg C for the year of 2000. The averaged aboveground biomass density of global mangroves is estimated as 146.3 Mg ha−1. Our analysis results demonstrate that this integrated geospatial analysis approach is efficacious for the computationally challenging estimation of global mangrove metrics based on high-resolution data. This global-level estimation and associated results are of great assistance for promoting our understanding of complex geospatial dynamics in mangrove forests.
Sustainable Development, Wellbeing and Material Consumption: A Stoic Perspective
Authors: Whiting Kai , Konstantakos Leonidas , Carrasco Angeles , Carmona Luis
Published: February 2018

Since the introduction of neoclassical economic theory, material wealth and accumulation have been linked to hedonic wellbeing. In turn, Utilitarian notions have generated the belief that infinite growth is not only good but necessary for society to prosper. Unsurprisingly, this belief system has supported the considerable depletion of natural resources and has not always led to social equitability or environmental justice, two pillars of sustainable development. Given these limitations, this paper looks into eudaimonic wellbeing, as defined by Stoicism. The latter originating in Classical Greece and Ancient Rome, has been used throughout the centuries to discuss and support the flourishing of individuals, but has rarely been applied to collective wellbeing. Consequently, we explore whether, and to what extent, this virtue-based philosophy can answer questions regarding the value and the role of material acquisition in societal development, as directed by sustainable policy. We propose the idea that the Stoic emphasis on prudence, self-control, courage and justice, as the only means to achieve “happiness”, is intrinsically linked to sustainable wellbeing and that its principles can be used to demonstrate that society does not require limitless growth to flourish.
Effects of Irrigation Regime and Nitrogen Fertilizer Management on CH4, N2O and CO2 Emissions from Saline–Alkaline Paddy Fields in Northeast China
Authors: Tang Jie , Wang Jingjing , Li Zhaoyang , Wang Sining , Qu Yunke
Published: February 2018

Irrigation regime and fertilizer nitrogen (N) are considered as the most effective agricultural management systems to mitigate greenhouse gas (GHG) emissions from crop fields, but few studies have involved saline–alkaline paddy soil. Gas emitted from saline–alkaline paddy fields (1-year-old and 57-year-old) was collected during rice growing seasons by the closed chamber method. Compared to continuous flooding irrigation, lower average CH4 flux (by 22.81% and 23.62%), but higher CO2 flux (by 24.84% and 32.39%) was observed from intermittent irrigation fields. No significant differences of N2O flux were detected. Application rates of N fertilizer were as follows: (1) No N (N0); (2) 60 kg ha−1 (N60); (3) 150 kg ha−1 (N150); and (4) 250 kg ha−1 (N250). The cumulative emissions of GHG and N fertilizer additions have positive correlation, and the largest emission was detected at the rate of 250 kg N ha−1 (N250). Global warming potential (GWP, CH4 + N2O + CO2) of the 57-year-old field under the N250 treatment was up to 4549 ± 296 g CO2-eq m−2, approximately 1.5-fold that of N0 (no N application). In summary, the results suggest that intermittent irrigation would be a better regime to weaken the combined GWP of CH4 and N2O, but N fertilizer contributed positively to the GWP.
Joint Pricing and Product Carbon Footprint Decisions and Coordination of Supply Chain with Cap-and-Trade Regulation
Authors: Cheng Yonghong , Xiong Zhongkai , Luo Qinglin
Published: February 2018

The implementation of cap-and-trade regulation worldwide is bound to have some effects on supply chain decision-making. This paper investigates optimal pricing and product carbon footprint decisions of the supply chain consisting of a manufacturer and a retailer under cap-and-trade regulation by applying optimization and game theory. By comparing the optimal results between the centralized and decentralized decision-making models, we find that the optimal product carbon footprint and selling price not only depend on the carbon trading price and carbon cap allocated by the government, but also relate to the initial carbon footprint of the product and the decision-making methods in the supply chain. It is found that there is also a “double marginalization” in the decentralized situation, thus we coordinate the supply chain using a two-part tariff contract. Specifically, only the manufacturer adjusts dynamically the wholesale price and fixed fee within the coordinating contract according to different initial carbon footprint and the range of the carbon cap reduction by the government. Finally, we obtain several interesting conclusions from the numerical examples and provide managerial insights and policy implications from the analytical results.
Simulation of Weak Signals of Nanotechnology Innovation in Complex System
Authors: Yoo Sun , Won DongKyu
Published: February 2018

It is especially indispensable for new businesses or industries to predict the innovation of new technologies. This requires an understanding of how the complex process of innovation, which is accomplished through more efficient products, processes, services, technologies, or ideas, is adopted and diffused in the market, government, and society. Furthermore, detecting “weak signals” (signs) of change in science and technology (S&T) is also important to foretell events associated with innovations in technology. Thus, we explore the dynamic behavior of weak signals of a specific technological innovation using the agent-based simulating tool NetLogo. This study provides a deeper understanding of the early stages of complex technology innovation, and the models are capable of analyzing initial complex interaction structures between components of technologies and between agents engaged in collective invention.
Identifying Factors Reinforcing Robotization: Interactive Forces of Employment, Working Hour and Wage
Authors: Cho Joonmo , Kim Jinha
Published: February 2018

Unlike previous studies on robotization approaching the future based on the cutting-edge technologies and adopting a framework where robotization is considered as an exogenous variable, this study considers that robotization occurs endogenously and uses it as a dependent variable for an objective examination of the effect of robotization on the labor market. To this end, a robotization indicator is created based on the actual number of industrial robots currently deployed in workplaces, and a multiple regression analysis is performed using the robotization indicator and labor variables such as employment, working hours, and wage. The results using the multiple regression considering the triangular relationship of employment–working-hours–wages show that job destruction due to robotization is not too remarkable yet that use. Our results show the complementary relation between employment and robotization, but the substituting relation between working hour and robotization. The results also demonstrate the effects of union, the size of the company and the proportion of production workers and simple labor workers etc. These findings indicate that the degree of robotization may vary with many factors of the labor market. Limitations of this study and implications for future research are also discussed.
Remote Care Technology: A Systematic Review of Reviews and Meta-Analyses
Authors: Queirós Alexandra , Alvarelhão Joaquim , Cerqueira Margarida , Silva Anabela , Santos Milton , Pacheco Rocha Nelson
Published: February 2018

Objectives—To identify the technologies that are being used in the remote care of patients with chronic conditions, and their most relevant outcomes. Methods—A systematic review of reviews and meta-analyses. Results—Fifty-one systematic reviews and meta-analyses related to diabetes, congestive heart failure, chronic obstructive pulmonary disease, mental and behavioral diseases, cancer, hypertension, asthma, multiple sclerosis, chronic renal disease, and obesity were retrieved; these studies compared the use of remote care technology with usual care. Conclusion—Remote care technology has positive effects in various health-related outcomes, but further research is required to allow its use in clinical practice.
Geometric Modeling of the Machine for Cutting Cane and Other Aquatic Plants in Navigable Waterways by Agustín de Betancourt y Molina
Authors: Rojas-Sola José , De la Morena-De la Fuente Eduardo
Published: February 2018

This article presents the steps followed to obtain a three-dimensional model of one of the most recognized historical inventions of Agustín de Betancourt y Molina from the scant documentation found about it. Specifically, this was a machine for cutting cane and other aquatic plants in navigable waterways, presented in London in 1795. The study is based on computer-aided design (CAD) techniques using Autodesk Inventor Professional, from the information provided by the only two sheets that exist from the machine, one with specifications in English and the other in French, both very similar. In order to obtain a functional result on which to carry out further studies, it has been necessary to make some geometrical hypotheses on the models, aimed to find the correct dimension of each element. In addition, it has also been necessary to define the relationship of each element with those that set up its environment, defining movement restrictions, so that the final model, behaves as real as possible.
The Effect of Botulinum Neurotoxin Serotype a Heavy Chain on the Growth Related Proteins and Neurite Outgrowth after Spinal Cord Injury in Rats
Authors: Wang Ya-Fang , Liu Fu , Lan Jing , Bai Juan , Li Xia-Qing
Published: February 2018

(1) Background: The botulinum toxin A (BoNT-A) heavy chain (HC) can stimulate the growth of primary motor neurites. (2) Methods: A recombinant BoNT/A HC was injected locally plus interval intrathecal catheter of BoNT/A HC to rats with ipsilateral semi-dissociated lumbar spinal cord injuries (SCIs). First, 2D gel with a silver nitrate stain was applied to detect the general pattern of protein expression. Growth associated protein 43 (GAP-43) and superior cervical ganglion 10 (SCG10) were chosen to represent the altered proteins, based on their molecular weight and pI, and were used to further detect their expression. Meanwhile, the neuronal processes were measured. The measurements of thermal hyperalgesia and grasp power at the ipsilateral hindlimb were used to evaluate spinal sensory and motor function, respectively. (3) Results: The local injection of BoNT/A HC followed by its intrathecal catheter intervally altered the spinal protein expression pattern after an SCI; protein expression was similar to normal levels or displayed a remarkable increase. The changes in the expression and distribution of phosphorylated growth associated protein 43(p-GAP 43) and superior cervical ganglion 10 (SCG 10) indicated that the administration of BoNT/A HC to the SCI significantly amplified the expression of p-GAP43 and SCG10 (p < 0.05). Meanwhile, the positive immunofluorescent staining for both p-GAP43 and SCG10 was mainly present near the rostral aspect of the injury, both in the cytoplasm and the neuronal processes. Moreover, the outgrowth of neurites was stimulated by the BoNT/A HC treatment; this was evident from the increase in neurite length, number of branches and the percentage of cells with neuronal processes. The results from the spinal function tests suggested that the BoNT/A HC did not affect sensation, but had a large role in improving the ipsilateral hindlimb grasp power (p < 0.05). (4) Conclusions: The local injection with the intermittent intrathecal administration of BoNT/A heavy chain to rats with SCI increased the local expression of GAP-43 and SCG 10, which might be affiliated with the regeneration of neuronal processes surrounding the injury, and might also be favorable to the relief of spinal motor dysfunction.
Multiple Mycotoxins in Rice: Occurrence and Health Risk Assessment in Children and Adults of Punjab, Pakistan
Authors: Majeed Saima , De Boevre Marthe , De Saeger Sarah , Rauf Waqar , Tawab Abdul , Fazal-e-Habib  , Rahman Moazur , Iqbal Mazhar
Published: February 2018

Mycotoxin contamination in rice can create a health risk for the consumers. In this study, the measurement of 23 mycotoxins in rice samples (n = 180) was performed using a validated LC–MS/MS method. A food frequency questionnaire was used to get rice consumption data for the assessment of mycotoxin dietary exposure, before calculating the health risk in adults and children of north and south regions of the Pakistani Punjab province. The prevalence of aflatoxin B1 (56%), aflatoxin B2 (48%), nivalenol (28%), diacetoxyscirpenol (23%), fumonisin B1 (42%), zearalenone (15%), HT-2 toxin (10%), deoxynivalenol (8%), and ochratoxin A (6%) was estimated in samples with a mean concentration range between 0.61 and 22.98 µg/kg. Aflatoxin degradation by traditional Pakistani cooking recipes was evaluated and observed to be 41–63%. The dietary exposure to aflatoxins exceeded the tolerable daily intake at all levels, and ochratoxin A and zearalenone posed health risk at high contamination and high consumption levels. The margin of aflatoxin B1 exposure ranged between 10 and 69 in adults and 10 and 62 in children. The mean cancer risk by aflatoxin B1 exposure was 0.070 (adults) and 0.071 (children) cases/year/100,000 people in South Punjab population, and 0.122 (adults) and 0.127 (children) cases/year/100,000 people in North Punjab population. This study will provide new insights for the planning and management of mycotoxins in Pakistan.
Geometric Aspects and Some Uses of Deformed Models of Thermostatistics
Authors: Gavrilik Alexandre
Published: February 2018

We consider diverse deformed Bose gas models (DBGMs) focusing on distributions and correlations of any order, and also on deformed thermodynamics. For so-called μ -deformed Bose gas model ( μ -DBGM), main thermodynamic aspects are treated: total number of particles, deformed partition function, etc. Using a geometric approach, we confirm the existence of critical behavior—Bose-like condensation; we find the critical temperature T c ( μ ) depending on μ so that T c ( μ ) > T c ( Bose ) for μ > 0 . This fact and other advantages of μ -DBGM relative to the usual Bose gas, e.g., stronger effective inter-particle attraction (controlled by the parameter μ ), allow us to consider the condensate in μ -DBGM as a candidate for modeling dark matter. As another, quite successful application we discuss the usage of the two-parameter ( μ ˜ , q )-deformed BGM for effective description of the peculiar (non-Bose like) behavior of two-pion correlations observed in the STAR experiment at RHIC (Brookhaven). Herein, we point out the transparent role of the two deformation parameters μ ˜ and q as being responsible for compositeness and (effective account of) interactions of pions, respectively.
Prospects of Constraining the Dense Matter Equation of State from Timing Analysis of Pulsars in Double Neutron Star Binaries: The Cases of PSR J0737 ‒ 3039A and PSR J1757 ‒ 1854
Authors: Bagchi Manjari
Published: February 2018

The Lense-Thirring effect from spinning neutron stars in double neutron star binaries contributes to the periastron advance of the orbit. This extra term involves the moment of inertia of the neutron stars. The moment of inertia, on the other hand, depends on the mass and spin of the neutron star, as well as the equation of state of the matter. If at least one member of the double neutron star binary (better the faster one) is a radio pulsar, then accurate timing analysis might lead to the estimation of the contribution of the Lense-Thirring effect to the periastron advance, which will lead to the measurement of the moment of inertia of the pulsar. The combination of the knowledge on the values of the moment of inertia, the mass and the spin of the pulsar will give a new constraint on the equation of state. Pulsars in double neutron star binaries are the best for this purpose as short orbits and moderately high eccentricities make the Lense-Thirring effect substantial, whereas tidal effects are negligible (unlike pulsars with main sequence or white-dwarf binaries). The most promising pulsars are PSR J0737 − 3039A and PSR J1757 − 1854. The spin-precession of pulsars due to the misalignment between the spin and the orbital angular momentum vectors affect the contribution of the Lense-Thirring effect to the periastron advance. This effect has been explored for both PSR J0737 − 3039A and PSR J1757 − 1854, and as the misalignment angles for both of these pulsars are small, the variation in the Lense-Thirring term is not much. However, to extract the Lense-Thirring effect from the observed rate of the periastron advance, more accurate timing solutions including precise proper motion and distance measurements are essential.
Climate Change Demands Adaptive Management of Urban Lakes: Model-Based Assessment of Management Scenarios for Lake Tegel (Berlin, Germany)
Authors: Ladwig Robert , Furusato Eiichi , Kirillin Georgiy , Hinkelmann Reinhard , Hupfer Michael
Published: February 2018

Lakes are known to be strongly affected by climate change as a result of their sensitivity to atmospheric forcing. The combined response of urban lakes to climatic changes and to urbanization of the catchment may be further altered by water quality management measures. We studied Lake Tegel in Berlin, Germany as a representative urban lake profoundly influenced by intense water management measures and a resulting complex hydrodynamic situation: Lake Tegel is fed by nutrient-rich river discharges and effluents from a phosphorus elimination plant (PEP). We estimated changes in water temperatures, the Wedderburn number, and the buoyancy frequency, as well as concentrations of dissolved oxygen and phosphate under climate change using a one-dimensional vertical hydrodynamic model coupled to a water quality model. Further, we investigated how four management scenarios with varying discharges of the PEP could affect the lake system. In all simulations, water temperatures increased and summer stratification extended. The modeling results demonstrated that the water management system buffers the high nutrient supply from the river inflow and can effectively mitigate negative effects of climate change on Lake Tegel, thus highlighting its importance for the lake ecosystem.
Phosphorus Solubilizing and Releasing Bacteria Screening from the Rhizosphere in a Natural Wetland
Authors: Cao Ying , Fu Dafang , Liu Tingfeng , Guo Guang , Hu Zhixin
Published: February 2018

Inorganic phosphorus (P)-solubilizing bacteria (IPSB) and organic P-mineralizing bacteria (OPMB) were isolated from bacteria that were first extracted from the rhizosphere soil of a natural wetland and then grown on either tricalcium phosphate or lecithin medium. The solubilizing of inorganic P was the major contribution to P availability, since the isolated bacteria released much more available P from inorganic tricalcium phosphate than lecithin. IPSB No. 5 had the highest P release rate, that is, 0.53 mg·L−1·h−1 in 96 h, and R10′s release rate was 0.52 mg·L−1·h−1 in 10 days. The bacteria were identified as Pseudomonas sp. and Pseudomonas knackmussii, respectively. R10 released as much as 125.88 mg·L−1 dissolved P from tricalcium phosphate medium, while R4 released the most dissolved P from organic P medium among the isolates, with a concentration of 1.88 mg·L−1 and a releasing rate of 0.0078 mg·L−1·h−1 in ten days. P releasing increased with a pH decrease only when it was from inorganic P, not organic lecithin, and there was no significant correlation between the culture pH and P solubilizing. High-throughput sequencing analysis revealed that the dominant phylum in the studied wetland rhizosphere consisted of Acidobacteria, Proteobacteria, Bacteroidetes and Chloroflexi, accounting for 34.9%, 34.2%, 8.8% and 4.8%, respectively.
Resilient Governance of Water Regimes in Variable Climates: Lessons from California’s Hydro-Ecological Zones
Authors: Romm Jeff , Conrad Esther , Måren Inger
Published: February 2018

Highly variable water regimes, such as California’s, contain distinctive problems in the pursuit of secure timing, quantities and distributions of highly variable flows. Their formal and informal systems of water control must adapt rapidly to forceful and unpredictable swings on which the survival of diversified ecosystems, expansive settlement patterns and market-driven economies depends. What constitutes resilient water governance in these high-variability regimes? Three bodies of theory—state resource government, resilience and social mediation—inform our pursuit of governance that adapts effectively to these challenges. Using evidence drawn primarily from California research and participation in the policy and practice of water governance, we identify two stark barriers to learning, adaptation and resilience in high-variability conditions: (1) the sharp divide between modes of governance for ecological (protective) and for social (distributive) resilience and (2) the separation between predominant paradigms of water governance in “basins” (shared streamflow) and in “plains” (minimized social risk). These sources of structural segregation block adaptive processes and diminish systemic resilience, creating need for mediating spaces that increase permeability, learning and adaptation across structural barriers. We propose that the magnitude and diversity of need are related directly to the degree of hydro-climatic variability.
Ultralight super-hydrophobic carbon aerogels based on cellulose nanofibers/poly(vinyl alcohol)/graphene oxide (CNFs/PVA/GO) for highly effective oil–water separation
Authors: Xu Zhaoyang , Zhou Huan , Tan Sicong , Jiang Xiangdong , Wu Weibing , Shi Jiangtao , Chen Peng
Published: February 2018

With the worsening of the oil-product pollution problem, oil–water separation has attracted increased attention in recent years. In this study, a porous three-dimensional (3D) carbon aerogel based on cellulose nanofibers (CNFs), poly(vinyl alcohol) (PVA) and graphene oxide (GO) was synthesized by a facile and green approach. The resulting CNF/PVA/GO aerogels were synthesized through an environmentally friendly freeze-drying process and then carbonized to yield CNF/PVA/GO carbon aerogels with low density (18.41 mg cm−3), high porosity (98.98%), a water contact angle of 156° (super-hydrophobic) and high oil absorption capacity (97 times its own weight). The carbonization treatment of the CNF/PVA/GO aerogel not only improved the hydrophobic properties but also enhanced the adsorption capacity and specific surface area. Given the many good performance characteristics and the facile preparation process of carbon aerogels, these materials are viable candidates for use in oil–water separation and environmental protection.
Resistance profiles and biofilm formation of coagulase negative staphylococci isolated from clinical specimens in a tertiary care hospital in Palestine
Authors: Al Laham Dr. Nahed Ali , Abou Elkhair Emad , Bashir Abdallah , Abdelateef Nahed
Published: February 2018

Background: Coagulase-negative staphylococci (CoNS) represent one of the major resistant nosocomial pathogens where its biofilm-related infections often fail to respond to antibiotic chemotherapy. Here, we studied the resistance profiles and biofilm formation in CoNS isolates from clinical specimens at Al Shifa hospital in Gaza, Palestine.

Methods: This study was carried out from March to July 2016 and included 81 clinical isolates. Identification and antibiotic susceptibility testing were performed using VITEK-2 system. The presence of nuc and mecA genes was performed using multiplex PCR. Qualitative and quantitative biofilm assays were performed using standard methods.

Results: Of the 81 clinical CoNS isolates, S. haemolyticus was the most common species (34, 42%), followed by S. epidermidis (26, 32.1%) and S. saprophyticus (13, 16%). The majority of isolates (83.9%) were from surgery, ICUs, pediatrics and medicine wards and the most common source was pus (28, 34.6%). Antibiotic resistance was highest against aminoglycosides, β-lactams, carbapenems, cephalosporins, fluoroquinolones, fosfomycin and macrolides. Though, no resistance was detected against rifampicin, vancomycin, teicoplanin, nitrofurantoin, linezolid and mupirocin. The antibiotic resistance among MR-CoNS was significantly higher than that among MS-CoNS. Nearly 88.9% of isolates were multidrug resistant with higher percentage among MR-CoNS. Most S. epidermidis (76.9%) isolates were biofilm producer, with statistically significant association between methicillin resistance and biofilm production.

Conclusions: High rates of antibiotic resistance were found among CoNS to commonly used antibiotics and the majority were methicillin and multidrug resistance. Most S. epidermidis isolates were biofilm producer. These results justified the necessity for national programs and measures to monitor and manage the usage of antibiotics in the Palestinian hospitals and community.
Sickness Benefit Rules and Work Absence: An Empirical Study Based on European Data
Authors: Chaupain-Guillot Sabine , Guillot Olivier
Published: February 2018

A partir des données de l’ European Working Conditions Survey de 2010, cette étude s’intéresse aux déterminants des absences au travail pour raisons de santé dans les pays européens. L’accent est mis sur l’impact des règles d’indemnisation des arrêts maladie. Cinq paramètres du système d’indemnisation sont pris en compte : l’obligation ou non de fournir un certificat médical dès le premier jour d’absence, la durée minimale d’affiliation au régime d’assurance sociale, l’existence ou non d’un délai de carence, le niveau d’indemnisation et la durée maximale de versement des indemnités maladie. Les comportements d’absence des salariés sont analysés à l’aide de régres sions logistiques multiniveaux. Les résultats montrent que les écarts entre pays dans la probabilité d’absence au travail peuvent en partie s’expliquer par les différences de législation en matière d’indemnisation des arrêts maladie. Le fait que le salaire soit intégralement maintenu par l’employeur en cas de maladie est l’élément le plus déterminant. Comme attendu, dans les pays où cette règle s’applique, la propension à s’absenter est significativement plus élevée.
Social and Nonlinear Tariffs on Drinking Water: cui bono? Empirical Evidence from a Natural Experiment in France
Authors: Mayol Alexandre
Published: February 2018

Cette contribution empirique teste les propriétés incitatives et redistributives des tarifs progressifs dans l’eau potable en France. En utilisant un panel de consommateurs collecté dans le cadre d’une expérience naturelle française, nous analysons économétriquement l’impact du passage d’un tarif linéaire à un tarif progressif sur la consommation. Nous montrons que ce changement réduit la consommation agrégée des ménages. Toutefois, nous observons que les petits consommateurs (<75 m 3 ) ont augmenté leur consommation, tandis que les autres l’ont réduit. De plus, la taille du foyer semble jouer sur la capacité des consommateurs à réagir aux tarifs progressifs. Dans une perspective de politiques publiques, ces résultats impliquent de discuter le design tarifaire pour en réduire le caractère distorsif et accroître leur efficacité.
Sex Offenders: General Information and Treatment
Authors: Sorrentino Renee , Brown Adam , Berard Brooke , Peretti Kaitlyn
Published: February 2018

Sex offenders are often neglected by psychiatrists due to a deficiency in training and a lack of knowledge in the area of sexual offenders. Many sex offenders have a comorbid psychiatric illness, including paraphilic disorders. Research has established that sex offenders can be treated with evidence-based principles. Psychiatrists can serve a pivotal role in the evaluation and biological treatment of sex offenders. Together, psychiatrists can work toward primary prevention of sexual violence by learning the requisite skills to identify and treat risk factors of sexual abuse.

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Psychiatr Ann.
2018;48(2):120–128.]
The Insanity Defense: Historical Precedent and Modern Application
Authors: VanDercar Ashley H. , Resnick Phillip J.
Published: February 2018

Mental health professionals need a basic understanding of the insanity defense. This article provides an overview of the historical origins of the defense and current application. The word “insanity” has a special meaning in the judicial system, one that is different than that used by medical professionals. A successful insanity defense allows a defendant to be found “not guilty by reason of insanity.” Although this verdict is an acquittal, it almost always leads to commitment to a psychiatric facility. Courts give considerable weight to the opinions of psychiatric experts when assessing an insanity plea. To provide such an opinion, a psychiatrist must understand their jurisdiction's insanity standard, review the facts of the case, and perform detailed interviews. Using this information, a psychiatrist can offer an opinion on a defendant's state of mind at the time of the crime.

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Psychiatr Ann.
2018;48(2):95–101.]
Sur quelques polémiques du XIXe siècle à propos de la définition et des rapports de l’homme et de l’animal
Authors: Jacquet Jean
Published: February 2018

En 1863, quand Littré, qui venait de faire paraître le premier tome de son Dictionnaire de la langue française, se présenta à l'Académie française, il se heurta à une campagne virulente déclenchée par Dupanloup. Il lui était reproché, entre autres positions positivistes, la définition matérialiste de l'âme et surtout le classement de l'homme parmi les mammifères, contenus dans le Dictionnaire de médecine, pharmacie et art vétérinaire (dit à tort de Nysten) dont la onzième édition venait d'être révisée par lui-même et Robin. Ce fut l'occasion d'une énorme prolifération de caricatures et de libellés.

Parmi ceux-ci, se trouve le livre de Jean Grange intitulé : «Lettres d’un vétérinaire à M. Littré, membre de l'Académie française».

En réalité, Littré était loin d’être le premier à avoir rangé l'homme parmi les mammifères ; par ailleurs, les substantifs âme, animal et anémome ont, en français, la même étymologie, dérivant de ανεµoζ souffle de vie, le sens des mots ayant beaucoup varié au cours des siècles.

Darwin, de son côté, eut à faire face à des polémiques analogues, sans compter le grand nombre de fois où ils furent en France rassemblés dans les mêmes attaques.
Leucoses à Mastocytes chez un chien
Authors: Jeanmonod Ph. , Groulade Paul
Published: February 2018

La leucose à mastocytes est exceptionnelle chez le chien comme chez l'homme. Le cas rapporté est caractérisé par une apparition subite d'une hypertrophie ganglionnaire sous-maxillaire accompagnée d'oedème périphérique, avec présence de mastocytes d’aspect malin dans le sang, la moelle, la rate, le ganglion, et l’absence de masse tumorale externe ou interne.
Prophylaxie de la brucellose bovine. Etude comparée du Test de l’anneau (Ring-test) et du Test Elisa sur les laits
Authors: Durand Maurice P. , Chatagnon G. , Le Jardinier J.-C.
Published: February 2018

En matière de recherche de la Brucellose dans le lait par la sérologie, nous avons, après avoir défini arbitrairement un seuil de positivité pour la méthode Elisa, comparé nos résultats sur laits de mélange entre Ring-test et Elisa. Sur 176 laits d'une région indemne, il y a une parfaite corrélation entre les deux méthodes ; sur 496 laits d’une région non indemne, il y a une distorsion importante dans les résultats, seulement 20% des laits trouvés positifs donnent une réaction positive commune. Compte tenu de la sensibilité de la méthode Elisa qui est au moins 100 fois supérieure au Ring-test, on peut s'interroger sur la signification de certains Ring-tests positifs et Elisa négatifs. Si après vérification de ces cas aberrants, la méthode Elisa peut être envisagée sur les laits de mélange, celle-ci est d'utilisation beaucoup plus délicate sur les laits individuels.
Étude du pouvoir antitumoral d’un Corynebactérium aérobie Corynebacterium catarrhalis. Effet des germes entiers et de ses fractions sur révolution de la tumeur de Lewis chez la souris
Authors: Métianu Tibérius
Published: February 2018

Une nouvelle espèce de Corynebacterium aérobie a été isolée et identifiée. Cette bactérie dénommée Corynebacterium catarrhalis possède un pouvoir immunostimulant et antitumoral hautement significatif. L'administration à la dose unique de 500 µg de bactéries entières délipidées, CBA-GD et surtout la fraction soluble appelée CBAp40 à la dose de 250 µg exercent un net effet inhibiteur sur lé développement de la tumeur de Lewis (3LL) chez les souris B6.D2.F1. Les résultats obtenus sont statistiquement très significatifs (test de Student = 0,001). Ce Corynebacterium catarrhalis augmente la défense non spécifique et ouvre de nouvelles perspectives dans la thérapeutique des tumeurs cancéreuses.