Molecular Dynamics Study of the Conformation, Ion Adsorption, Diffusion and Water Structure of Soluble Polymers in Saline Solutions

Polymers have interesting physicochemical characteristics such as charge density, functionalities, and molecular weight. Such attributes are of great importance for use in industrial purposes. Understanding how these characteristics are affected is still complex, but with the help of molecular dynamics (MD) and quantum calculations (QM), it is possible to understand the behavior of polymers at the molecular level with great consistency. This study was applied to polymers derived from polyacrylamide (PAM) due to its great use in various industries. The polymers studied include hydrolyzed polyacrylamide (HPAM), poly (2-acrylamido-2-methylpropanesulfonate) (PAMPS), polyacrylic acid (PAA), polyethylene oxide polymer (PEO), and guar gum polysaccharide (GUAR). Each one has different attributes, which help in understanding the effects on the polymer and the medium in which it is applied along a broad spectrum. The results include the conformation, diffusion, ion condensation, the structure of the water around the polymer, and interatomic polymer interactions. Such characteristics are important to selecting a polymer depending on the environment in which it is found and its purpose. The effect caused by salinity is particular to each polymer, where polymers with an explicit charge or polyelectrolytes are more susceptible to changes due to salinity, increasing their coiling and reducing their mobility in solution. This naturally reduces its ability to form polymeric bridges due to having a polymer with a smaller gyration radius. In contrast, neutral polymers are less affected in their structure, making them favorable in media with high ionic charges.

Advanced design of Close-Proximity (CPX) trailer enclosure acoustics on tyre/road noise measurement

The PolyU Mark II Twin-wheeled CPX trailer was developed for the measurement of tyre/road noise in Hong Kong urban environment according to a standard methodology (ISO/CD 11819-2) - the Close-Proximity (CPX) method. Numerical simulations of the acoustics of PolyU Mark II CPX enclosure were conducted and a good agreement between numerical and experimental results was obtained. In order to extend the capacity of the Mark II CPX trailer and enhance the acoustic performance within the enclosure for future tyre/road noise studies, the validated numerical simulations were carried on to design the next generation of the PolyU CPX system. Through analyzing the acoustic performance within the enclosures of different dimensions and the distributions of sound pressure level (SPL) inside the anechoic chamber, the geometry of the PolyU Mark III CPX enclosure was finally determined. With newly designed enhanced interior wall absorption, the new PolyU Mark III CPX enclosure design was delivered into numerical simulations for acoustic analysis. Fewer room modes and high uniformity of SPL distributions were observed within the new enclosure design. The PolyU Mark III CPX enclosure was fabricated based on the corresponding dimensions and the specific absorption layers. Great consistency was achieved between the numerical and measured results of the Mark III CPX enclosure. In addition, the PolyU Mark III CPX enclosure shows an improved acoustic property with a lower background noise level during road tests than Mark II CPX enclosure. The outcome of this study firmly establishes the feasibility of designing advanced CPX enclosure with numerical simulations with results that can be realized in realistic CPX measurement.

Doris adrianae sp. nov. (Heterobranchia; Nudibranchia; Doridina) from the Galician coasts (NW Iberian Peninsula).

A new species of dorid nudibranch, Doris adrianae sp. nov. is described, from the Ría de Ferrol (NW Iberian Peninsula) on rocky bottoms, between 11 and 20 m deep, where the sponge Polymastia boletiformis (Lamarck, 1815) on which it feeds is common. The new species is oval-shaped and yellow to yellow-orange in colour, with the back covered by rounded tubercles of various sizes, reinforced by tegumentary spicules. It is characterised by numerous integumentary and fusiform calcareous spicules, mainly grouped in multispicular bundles that give it a complex and very dense skeletal structure, giving the animal great consistency without losing flexibility. In addition, it differs from other known species of the genus Doris Linnaeus, 1758 by various external and internal characters, mainly by the colouring and tubercles of the body, characters of the radula and of the digestive and reproductive systems. Doris adrianae sp. nov. also presents a marked genetic distance in the barcode fragment (cox1-5') with other species of the genus Doris.

Automatic input variable selection for analog methods using genetic algorithms

<p>Analog methods (AMs) are statistical downscaling methods often used for precipitation prediction in different contexts, such as operational forecasting, past climate reconstruction of climate change impact studies. It usually relies on predictors describing the atmospheric circulation and the moisture content of the atmosphere to sample similar meteorological situations in the past and establish a probabilistic forecast for a target date. AMs can be based on outputs from numerical weather prediction models in the context of operational forecasting or outputs from climate models in climatic applications.</p><p>AMs can be constituted of multiple predictors organized in different subsequent levels of analogy that refines the selection of similar situations. The development of such methods is usually a manual process where some predictors are assessed in different structures. As most AMs use multiple predictors, a comprehensive assessment of all combinations becomes quickly impossible. The selection of predictors in the application of the AM often builds on previous work and does not evolve much. However, the climate models providing the predictors evolve continuously and new variables might become relevant to be considered in AMs. Moreover, the best predictors might change from one region to another or for another predictand of interest. There is a need for a method to automatically explore potential variables for AMs and to extract the ones that are relevant for a predictand of interest.</p><p>We propose using genetic algorithms (GAs) to proceed to an automatic selection of the predictor variables along with all other parameters of the AM. We even let the GAs automatically pick the best analogy criteria, i.e. the metric that quantifies the analogy between two situations. The first test consisted of letting the GAs select the single best variable to predict daily precipitation for each of 25 selected catchments in Switzerland. The results showed great consistency in terms of spatial patterns and the underlying meteorological processes. Then, different structures were assessed by varying the number of levels of analogy and the number of variables per level. Finally, multiple optimizations were conducted on the 25 catchments to identify the 12 variables that provide the best prediction when considered together.</p>

Comparing the Characteristics and Predicting the Survival of Head and Neck Melanoma versus Body Melanoma: A Population-based Study

Background: Previous studies have reported poorer survival in head and neck melanoma (HNM) than in body melanoma (BM). Individualized tools to predict the prognosis for patients with HNM or BM remain insufficient. We aim to compare the characteristics of HNM and BM, and establish and validate the nomograms for predicting the 3-, 5- and 10-year survival of patients with HNM or BM.Methods: We studied patients with HNM or BM from 2004 to 2015 in the Surveillance, Epidemiology, and End Results (SEER) database. The HNM group and BM group were randomly divided into training and validation cohorts. We performed the Kaplan-Meier method for survival analysis, and used multivariate Cox proportional hazards models to identify independent prognostic factors. Nomograms for HNM patients or BM patients were developed via the rms package, and were measured by the concordance index (C-index), the area under the receiver operator characteristic (ROC) curve (AUC) and calibration plots.Results: Of 70605 patients acquired, 21% (n=15071) had HNM and 79% (n=55534) had BM. The HNM group contained more older patients, male patients, and lentigo maligna melanoma, and more frequently had thicker tumors and metastases than the BM group. The 5-year CSS and OS rates were 88.1±0.3% and 74.4±0.4% in the HNM group and 92.5±0.1% and 85.8±0.2% in the BM group, respectively. Eight independent prognostic factors (age, sex, histology, thickness, ulceration, stage, metastases, and surgery) were identified to construct nomograms for HNM patients or BM patients. The performance of the nomograms were excellent: the C-index of the CSS prediction for HNM patients and BM patients in the training cohort were 0.839 and 0.895, respectively; in the validation cohort, they were 0.848 and 0.888, respectively; the AUCs for the 3-, 5- and 10-year CSS rates of HNM were 0.871, 0.865 and 0.854 (training), and 0.881, 0.879 and 0.861 (validation), respectively; of BM, the AUCs were 0.924, 0.918 and 0.901 (training) and 0.916, 0.908 and 0.893 (validation), respectively; and the calibration plots showed great consistency.Conclusions: The characteristics of HNM and BM are heterogeneous, and we constructed and validated specific nomograms as practical prognostic tools for patients with HNM or BM.

Comparing the Characteristics and Predicting the Survival of Head and Neck Melanoma versus Body Melanoma: A Population-based Study

Background Previous studies have reported poorer survival in head and neck melanoma (HNM) than in body melanoma (BM). Individualized tools to predict the prognosis for patients with HNM or BM remain insufficient. Objectives To compare the characteristics of HNM and BM, and to establish and validate the nomograms for predicting the 3-, 5- and 10-year survival of patients with HNM or BM. Methods We studied patients with HNM or BM from 2004 to 2015 in the Surveillance, Epidemiology, and End Results (SEER) database. The HNM group and BM group were randomly divided into training and validation cohorts. We performed the Kaplan-Meier method for survival analysis, and used multivariate Cox proportional hazards models to identify independent prognostic factors. Nomograms for HNM patients or BM patients were developed via the rms package, and were measured by the concordance index (C-index), the area under the receiver operator characteristic (ROC) curve (AUC) and calibration plots. Results Of 70605 patients acquired, 21% (n = 15071) had HNM and 79% (n = 55534) had BM. The HNM group contained more older patients, male patients, and lentigo maligna melanoma, and more frequently had thicker tumors and metastases than the BM group. The 5-year CSS and OS rates were 88.1 ± 0.3% and 74.4 ± 0.4% in the HNM group and 92.5 ± 0.1% and 85.8 ± 0.2% in the BM group, respectively. Eight independent prognostic factors (age, sex, histology, thickness, ulceration, stage, metastases, and surgery) were identified to construct nomograms for HNM patients or BM patients. The performance of the nomograms were excellent: the C-index of the CSS prediction for HNM patients and BM patients in the training cohort were 0.839 and 0.895, respectively; in the validation cohort, they were 0.848 and 0.888, respectively; the AUCs for the 3-, 5- and 10-year CSS rates of HNM were 0.871, 0.865 and 0.854 (training), and 0.881, 0.879 and 0.861 (validation), respectively; of BM, the AUCs were 0.924, 0.918 and 0.901 (training) and 0.916, 0.908 and 0.893 (validation), respectively; and the calibration plots showed great consistency. Conclusions The characteristics of HNM and BM are heterogeneous, and we constructed and validated specific nomograms as practical prognostic tools for patients with HNM or BM.

Visualization and measurement of supersonic jet flow field evolution issuing from a rectangular nozzle with aft-deck

An experimental study is reported of supersonic jet surface flow structure visualization and wall shear stress field measurement issuing from a rectangular nozzle with aft-deck. The near-field surface flow structures evolution from over-expansion to under-expansion with the increase of nozzle pressure ratio (NPR) are successfully captured by surface oil flow visualization and shear sensitive liquid crystal coating (SSLCC) technique. The quantitative measurement result of shear stress vector field obtained by SSLCC shows that shear stress directions change significantly across the shock wave and expansion fans, while the magnitudes of shear stress have no obvious changes. Surface streamlines calculated by SSLCC image keep great consistency with the streamlines visualized using oil flow technique, which demonstrates the accuracy and potential application of SSLCC in supersonic jet surface flow visualization.

The VIIRS-Based RST-FLARE Configuration: The Val d’Agri Oil Center Gas Flaring Investigation in Between 2015–2019

The RST (Robust Satellite Techniques)-FLARE algorithm is a satellite-based method using a multitemporal statistical analysis of nighttime infrared signals strictly related to industrial hotspots, such as gas flares. The algorithm was designed for both identifying and characterizing gas flares in terms of radiant/emissive power. The Val d’Agri Oil Center (COVA) is a gas and oil pre-treatment plant operating for about two decades within an anthropized area of Basilicata region (southern Italy) where it represents a significant potential source of social and environmental impacts. RST-FLARE, developed to study and monitor the gas flaring activity of this site by means of MODIS (Moderate Resolution Imaging Spectroradiometer) data, has exported VIIRS (Visible Infrared Imaging Radiometer Suite) records by exploiting the improved spatial and spectral properties offered by this sensor. In this paper, the VIIRS-based configuration of RST-FLARE is presented and its application on the recent (2015-2019) gas flaring activity at COVA is analyzed and discussed. Its performance in gas flaring characterization is in good agreement with VIIRS Nightfire outputs to which RST-FLARE seems to provide some add-ons. The great consistency of radiant heat estimates computed with both RST-FLARE developed configurations allows proposing a multi-sensor RST-FLARE strategy for a more accurate multi-year analysis of gas flaring.

Geodetic deformation forecasting based on multi-variable grey prediction model and regression model

Purpose The purpose of this paper is to examine the effectiveness of the multivariable grey prediction model in deformation forecasting. Design/methodology/approach Deformation in a dam can be seen because of many factors but without any doubt, the most influential factor is the water level. In this study, the deformation level of a point in the Keban Dam crest has been tried to be forecasted depending on the water level by the multivariable grey model GM(1,N). Regression analysis was used to test the accuracy of the prediction results obtained using the grey prediction model. Findings The results show that there is a great consistency between the grey prediction values and the actual values, and that the GM(1,N) produces more reliable results than the regression analysis. Based on the results, it can be concluded that the GM(1,N) is a very reliable estimation model for limited data conditions. Originality/value Different from the other studies in the literature, this study investigates deformation in a dam subject to the water level in the dam reservoir. The main contribution of the study to the literature is to suggest a relatively new procedure for estimating the deformation in the dams based on the water level.

Low-frequency perfect sound absorption achieved by a modulus-near-zero metamaterial

We have analytically proposed a mechanism for achieving a perfect absorber by a modulus-near-zero (MNZ) metamaterial with a properly decorated imaginary part, in which the perfect absorption (PA) is derived from the proved destructive interference. Based on the analysis, an ultrathin acoustic metamaterial supporting monopolar resonance at 157 Hz (with a wavelength about 28 times of the metamaterial thickness) has been devised to construct an absorber for low-frequency sound. The imaginary part of its effective modulus can be easily tuned by attentively controlling the dissipative loss to achieve PA. Moreover, we have also conducted the experimental measurement in impedance tube, and the result is of great consistency with that of analytical and simulated ones. Our work provides a feasible approach to realize PA (>99%) at low frequency with a deep-wavelength dimension which may promote acoustic metamaterials to practical engineering applications in noise control.