In situ semi-quantitative analysis of polluted soils by laser-induced breakdown spectroscopy (LIBS)

Time-saving, low-cost analyses of soil contamination are required to ensure fast and efficient pollution removal and remedial operations. In this work, laser-induced breakdown spectroscopy (LIBS) has been successfully applied to in situ analyses of polluted soils, providing direct semi-quantitative information about the extent of pollution. A field campaign has been carried out in Brittany (France) on a site presenting high levels of heavy metal concentrations. Results on iron as a major component as well as on lead and copper as minor components are reported. Soil samples were dried and prepared as pressed pellets to minimize the effects of moisture and density on the results. LIBS analyses were performed with a Nd:YAG laser operating at 1064 nm, 60 mJ per 10 ns pulse, at a repetition rate of 10 Hz with a diameter of 500 μm on the sample surface. Good correlations were obtained between the LIBS signals and the values of concentrations deduced from inductively coupled plasma atomic emission spectroscopy (ICP-AES). This result proves that LIBS is an efficient method for optimizing sampling operations. Indeed, "LIBS maps" were established directly on-site, providing valuable assistance in optimizing the selection of the most relevant samples for future expensive and time-consuming laboratory analysis and avoiding useless analyses of very similar samples. Finally, it is emphasized that in situ LIBS is not described here as an alternative quantitative analytical method to the usual laboratory measurements but simply as an efficient time-saving tool to optimize sampling operations and to drastically reduce the number of soil samples to be analyzed, thus reducing costs. The detection limits of 200 ppm for lead and 80 ppm for copper reported here are compatible with the thresholds of toxicity; thus, this in situ LIBS campaign was fully validated for these two elements. Consequently, further experiments are planned to extend this study to other chemical elements and other matrices of soils.     

Matrix-implanted laser desorption/ionization mass spectrometry

The implantation of low-velocity massive gold clusters is shown to be a method of choice for homogeneous incorporation of a metallic matrix into the near-surface region of a solid biopolymer for subsequent laser desorption/ionization (LDI) MS analysis. Matrix implanted (MI)LDI spectra from cluster-implanted pure test peptide or tissue exhibit molecular ion peaks similar to those observed by matrix-assisted LDI. Moreover, the ion emission is very reproducible from any spot on the surface of these test samples. MILDI promises to be a powerful technique for mass spectrometric analysis of native biological samples as demonstrated by the first results on rat brain tissues.     

A reduced basis method for parametrized variational inequalities applied to contact mechanics

We investigate new developments of the reduced-basis method for parametrized optimization problems with nonlinear constraints. We propose a reduced-basis scheme in a saddle-point form combined with the Empirical Interpolation Method to deal with the nonlinear constraint. In this setting, a primal reduced-basis is needed for the primal solution and a dual one is needed for the Lagrange multipliers. We suggest to construct the latter using a cone-projected greedy algorithm that conserves the non-negativity of the dual basis vectors. The reduction strategy is applied to elastic frictionless contact problems including the possibility of using nonmatching meshes. The numerical examples confirm the efficiency of the reduction strategy.     

The Thinnest Light Disk: Rewritable Data Storage and Encryption on WS2 Monolayers

The thinnest light disk is demonstrated at the atomic level by developing an erasable method to directly write encrypted information onto WS₂ monolayers. The write-in is realized by precise control of photoluminescence emission by means of ozone functionalization and scanning focused laser beam. The visual decryption and reading-out of information are enabled by fluorescence contrast. The high encryption level is ensured by the threshold power upon which the data deletion will be triggered. Owing to the high spatial resolution and power sensitivity, the storage capacity within < 1 nm thickness can be up to ≈ 62.5 MB cm⁻², and the writing speed can reach ≈ 6.25 MB s⁻¹. Density functional theory calculations suggest that the disk formatting is realized by ozone molecule adsorption induced localized unoccupied states, while the read-in relies on the passivation of defects via substitution of the sulfur vacancies with oxygen atoms. The results of this study promote data storage and encryption on the atomic scale.     

SDN/NFV‐based handover management approach for ultradense 5G mobile networks

With the great increase of connected devices and new types of applications, mobile networks are witnessing exponential growth of traffic volume. To meet emerging requirements, it is widely agreed that the fifth‐generation mobile network will be ultradense and heterogeneous. However, the deployment of a high number of small cells in such networks poses challenges for the mobility management, including frequent, undesired, and ping‐pong handovers, not to mention issues related to increased delay and failure of the handover process. The adoption of software‐defined networking (SDN) and network function virtualization (NFV) technologies into 5G networks offers a new way to address the above‐mentioned challenges. These technologies offer tools and mechanisms to make networks flexible, programmable, and more manageable. The SDN has global network control ability so that various functions such as the handover control can be implemented in the SDN architecture to manage the handover efficiently. In this article, we propose a Software‐Defined Handover (SDHO) solution to optimize the handover in future 5G networks. In particular, we design a Software‐Defined Handover Management Engine (SDHME) to handle the handover control mechanism in 5G ultradense networks. The SDHME is defined in the application plane of the SDN architecture, executed by the control plane to orchestrate the data plane. Simulation results demonstrate that, compared with the conventional LTE handover strategy, the proposed approach significantly reduces the handover failure ratio and handover delay.     

Blind image inpainting quality assessment using local features continuity

Multimedia Tools and Applications - This paper deals with Blind Inpainted Image Quality Assessment BIIQA. Herein, we propose a new method that exploits the continuity of features around the...     

Deep-PHURIE: deep learning based hurricane intensity estimation from infrared satellite imagery

Hurricanes are among the most destructive natural phenomena on Earth. Timely prediction and tracking of hurricane intensity is important as it can help authorities in emergency planning. Several manual, semi and fully automated techniques based on different principles have been developed for hurricane intensity estimation. In this paper, a deep convolutional neural network architecture is proposed for fully automated hurricane intensity estimation from satellite infrared (IR) images. The proposed architecture is robust to errors in annotation of the storm center with a smaller root-mean-squared error (RMSE) (8.82 knots) in comparison to the previous state of the art methods. A web server implementation of Deep-PHURIE and its pre-trained neural network model are available at the URL: http://faculty.pieas.edu.pk/fayyaz/software.html#Deep-PHURIE.

     

A review on natural convective heat transfer of nanofluids

Nanofluids are considered to have great potential for heat transfer enhancement and are highly suited to application in practical heat transfer processes. Recently, several important studies were carried out to understand and explain the causes of the enhancement or control of heat transfer using nanofluids. The main aim upon which the present work is based is to give a comprehensive review on the research progress on the natural convective heat transfer characteristics of nanofluids for both single- and two-phase models. Both experimental and theoretical studies are reviewed for natural convection of nanofluids in different types of enclosures.     

Discontinued and alternative brominated flame retardants in the atmosphere and precipitation from the great lakes basin

Air (vapor and particle) and precipitation samples were collected at five sites (two urban, one rural, and two remote) around the Great Lakes during 2005-2009 as a part of the Integrated Atmospheric Deposition Network (IADN). The concentrations of polybrominated diphenyl ethers (PBDEs), decabromodiphenylethane (DBDPE), hexabromobenzene (HBB), pentabromoethylbenzene (PBEB), and 1,2-bis(2,4,6-tribromophenoxy)ethane (BTBPE) were measured in these samples. The highest concentrations of these compounds were generally observed at the two urban sites-Chicago and Cleveland-with a few exceptions: The remote site at Eagle Harbor had particularly high levels of PBEB in all three phases, and the rural Sturgeon Point site had the highest HBB concentrations in the vapor phase. The sources of HBB and PBEB to these sites are unknown. A multiple linear regression model was applied to the concentrations of these compounds in the vapor phase, particle phase, precipitation, and the three phases combined. This regression resulted in overall (three phases combined) halving times for total PBDE concentrations of 6.3 ± 1.1 years. The overall halving times for HBB and BTBPE were 9.5 ± 4.6 years and 9.8 ± 2.8 years, respectively. For PBEB and DBDPE, the regression was not statistically significant for the combined phases, indicating that the atmospheric concentrations of these compounds have not changed between 2005 and 2009.