In order to study the surface settlement law of subway tunnel engineering site overlying soft soil layer under the action of earthquake, ABAQUS finite element analysis software was used to study the surface settlement law of subway tunnel construction site overlying soft soil layer under the action of three different seismic waves, including El-Centro wave, Kobe wave, and artificial seismic wave with exceedance probability of 10%, based on the Dalian Metro Line 5 with overlying soft soil layer as the engineering background, and the law was analyzed theoretically. Then, the surface settlement law of tunnel top was studied based on El-Centro wave and soft soil parameters, and the sensitivity analysis of soft soil parameters on surface settlement of tunnel top was carried out by orthogonal test method. The results show that under earthquake action, the settlement of the strata within a certain range of the tunnel roof is significantly greater than that of the surrounding strata, forming a settlement trough with a width of about 8 to 20 meters. The width of the settlement trough under the El-Centro wave is the largest, about 19.6 meters, surpassing the artificially synthesized seismic waves with a probability of 10%, which is about 15.6 meters, while the width of the settlement trough under the Kobe wave is the smallest, about 8.5 meters. The ground surface within a range of about 20 meters above the tunnel roof is most strongly affected by the seismic waves and the special lithology of the overlying soft soil layer, and the settlement is the largest. The settlement law of the settlement trough in the overlying strata of the tunnel conforms to the Peck formula. Increasing the elastic modulus of the silty soil can reduce the settlement of the ground surface above the tunnel roof, increasing the Poisson's ratio of the silty soil will increase the settlement of the ground surface above the tunnel roof, increasing the cohesive force of the silty soil to 20 kPa will basically stabilize the settlement of the ground surface above the tunnel roof, and increasing the internal friction angle of the silty soil will basically not change the settlement of the ground surface above the tunnel roof. The sensitivity of the soft soil parameters to the settlement of the ground surface above the tunnel roof is in the order of Poisson's ratio, elastic modulus, cohesive force, and internal friction angle.

In permafrost regions, ground surface deformations induced by freezing and thawing threaten the integrity of the built environment. Mapping the frost susceptibility of the ground at a high spatial resolution is of practical importance for the construction and planning sectors. We processed Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) data from thawing seasons 2015 to 2019, acquired over the area of Ilulissat, West Greenland. We used a least-squares inversion scheme to retrieve the average seasonal displacement (S) and long-term deformation rate (R). We secondly investigated two different methods to extrapolate active layer thickness (ALT) measurements, based on their statistical relationship with remotely-sensed surface characteristics. A Generalized Linear Model (GLM) was first implemented, but the model was not able to fit the data and represent the ALT spatial variability over the entire study domain. ALT were alternatively averaged per vegetation class, using a land cover map derived by supervised classification of Sentinel-2 images. We finally estimated the active layer ice content and used it as a proxy to map the frost susceptibility of the ground at the community scale. Fine-grained sedimentary basins in Ilulissat were typically frost susceptible and subject to average seasonal downward displacements of 3 to 8 cm. Areas following a subsiding trend of up to 2.6 cm/yr were likely affected by permafrost degradation and melting of ground ice below the permafrost table. Our approach enabled us to identify frost-susceptible areas subject to severe seasonal deformations, and/or long-term subsidence induced by degrading permafrost. Used in combination with traditional site investigations, InSAR maps provide valuable information for risk management and community planning in the Arctic.

Chronoamperometric curves of the oxidation of a ferrocenyl derivative by the potential step showed diffusion controlled-like currents less than the Cottrell's equation at a platinum wire electrode. The lower deviation cannot be explained by the Butler-Volmer heterogeneous kinetics, but was ascribed to the negatively capacitive current associated with the redox reaction. The deviation at the fully oxidized potential corresponds to the non-zero concentration at the electrode surface, which cannot be predicted from the Nernst equation. The Nernst equation expresses the relationship of the potential with the activity at the electrode surface rather than the concentration. The diffusion equation provides the relation of the current with the surface concentration rather than the activity. The negative capacitance or the non-zero concentration may arise from structure formation on the electrode owing to the dipole-dipole interaction, which is similar to the generation of the double layer capacitance including frequency dispersion. On this concept, we derive here expressions for the lowered diffusion-controlled current and the time-dependent surface concentration. The negatively capacitive current shows the time-dependence of t-0.9, which is similar to the decay of the double layer capacitive currents. The surface concentration decays with the t-0.4-dependence.

In this study novel recommendations are presented and substantiated for selecting the number of modes and optical thicknesses of flat lattice slabs that make up the microreliefs, which minimize the computational complexity of the rigorous coupled-wave analysis calculation of the diffraction efficiency (DE) of a sawtooth two-layer two-relief microstructure, while maintaining the specified reliability of the calculation results. The computational complexity can be controlled by allowing one or another level of oscillation of the DE curves depend on the angle of incidence of the radiation incident on the microstructure. In particular, the complexity of the multi-thousand DE calculations in the optimization process can be reduced by using the proposed methodology as well as increased computational complexity to certify the accuracy of the solution obtained as a result of implemented optimization.

In this study the formation of thin-film barrier coatings based on a highly-conducting Bi1.60Er0.4O3 (EDB) solid electrolyte on supporting Ce0.8Sm0.2O1.9 (SDC) electrolyte substrates is implemented for the first time using electrophoretic deposition (EPD). Electrokinetic properties of EDB-based suspensions in a non-aqueous dispersion medium of isopropanol modified with small additions of polyethyleneimine (PEI, 0.26 g/L) and acetylacetone (0.15 g/L), as well as in a mixed isopropanol/acetylacetone (70/30 vol.%) medium are studied. The dependences of the thickness of EDB coatings on voltage and deposition time are obtained using deposition on a model Ni-foil electrode. Preliminary synthesis of a conductive polypyrrole (PPy) polymer film is used to create surface conductivity of non-conductive SDC substrates. The efficiency of using a modified dispersion medium based on isopropanol to obtain a continuous EDB coating 12 μm thick, sintered at a temperature of 850 °C for 5 h, is shown. The microstructure and morphology of the surface of the EDB coating are studied. Pt/SDC/EDB/Pt cell is used to characterize the coating conductivity. The EPD method is shown to be promising for the formation of barrier coatings based on doped bismuth oxide. The developed method can be used for creating cathode barrier layers in SOFC technology.

This study investigates the Hagen–Poiseuille pipe flow of viscoplastic fluids, focusing on analytical predictions of concrete pumping using the shear-stress-dependent parabolic model. Research highlights encompass solving the steady laminar pipe flow for viscoplastic fluids described by the parabolic model, extending analytical studies to a nonlinear rheological model with easily accessible experimental parameters, presenting detailed results for the two-fluid parabolic model, and introducing computational apps implementing theoretical findings. The parabolic model outperforms linear models, such as the Bingham model, in accuracy by accounting for the nonlinearity in the shear stress and shear rate relations. The influence of rheological parameters on these relations is analyzed, and their versatility is demonstrated by a Wolfram Mathematica-based application program. This approach is adaptable for other models with shear stress as the independent variable, offering valuable insights into viscoplastic fluid flows.

The use of interleaving material with viscoelastic properties is one of the most effective solutions to improve the damping capacity of CFRP laminates. Improving composite damping without threatening mechanical performance is challenging and the use of nanomaterials should lead to the target. In this paper, the effect of a nanostructured interlayer based on Graphite Nanoplatelets (GNPs) on the damping capacity and fracture toughness of CFRP laminates has been investigated. High-content GNP/Epoxy (70wt/30wt) coating was sprayed on the surface of CF/Epoxy prepregs at two different areal weight (10 and 40 g/m2) and incorporated at the middle-plane of a CFRP laminate. The effect of the GNP areal weight on viscoelastic and the mechanical behaviour of the laminates was investigated. Coupons with low-areal weight GNP interlayer showed a 25% increase in damping capacity with a trivial reduction of the elastic modulus. Moreover, a reduction in interlaminar shear strength (ILSS) and fracture toughness (both mode I and mode II) was observed in the composites with GNPs interlayer. GNPs alignment and degree of compaction reached during process were found as key parameters on material performances. By increasing the areal weight a mitigation on the mechanical performances drop was achieved (-15%).

A new three-dimensional numerical model of a polymer electrolyte fuel cell (PEFC) with a single straight channel has been developed to primarily investigate the important impact of the double-sided microporous layer (MPL) coating on the overall performance of the fuel cell and the distribution of the current and the oxygen concentration within the cathode gas diffusion layers (GDLs). Realistic experimentally estimated interfacial contact resistance values between the gas diffusion layer and each of the bipolar plates and the catalyst layer values were incorporated into the model, and parametric studies were performed. The results showed that the double-sided MPL coating could significantly improve the fuel cell performance by up to 30%. Also, it was shown that the neglect of the contact resistance between the MPL and the catalyst layer could overestimate the fuel cell performance by up to 6%. In addition, the results showed that the fuel cell performance and the distribution of the current and oxygen are more sensitive to the porosity of the MPL facing the bipolar plate than the porosity of the MPL facing the catalyst layer. All the above results are presented and critically discussed in detail.

The influence of small-scale processes at the ocean-atmosphere boundary layer such as spray and foam on the surface waves prediction is studied. Estimates of the effect of including the exact number of specific fragmentation "parachute" type in the spray on the resulting drag coefficient is shown. For the estimates, the numerical simulations within WAVEWATCH III wave model are performed. The parameterizations of wind input were tested within WAVEWATCH III wave model: default ST4 and ST6 parameterizations and the ST1 and ST6 parameterizations used together with the implemented drag coefficient parameterization. The proposed parameterization takes into account the presence of foam and spay. The obtained results are compared with the NDBC buoys data. The importance of small-scale processes for waves at hurricane winds prediction and the prospects for their inclusion in modern numerical wave models is shown.

Internet of Things (IoT) is a massive network of tiny devices connected internally and to the in-ternet. It is uniquely identified in the network (i.e. dedicated IP) and can share the information with other devices. However, the low power and low resources that distinguish IoT devices render them unsecure and targeted by different kinds of attacks since IoT devices cannot toler-ate heavy security models. Also, due to the heavy nature of famous protocols such as HyperText Transport Protocol (HTTP), it is costly to be used with IoT devices, and alternatively, different lightweight protocols are implemented to fit IoT devices. One of the prevailing protocols used over IoT networks is the Constrained Application Protocol (CoAP). Therefore, CoAP is popular, and that makes it targeted by different types of attacks. One of the major attacks that target CoAP is distributed denial of service (DDoS) attacks. DDoS aims to overwhelm the resources of the target and make them unavailable to legitimate users. As a result, different kinds of meth-ods were used to secure CoAP against DDoS attacks such as Datagram Transport Layer Secu-rity (DTLS) and Lightweight and Secure Protocol for Wireless Sensor Networks (LSPWSN). However, the existing models suffer from two issues: DTLS is not designed for constrained devices and is considered a heavy protocol. Besides, LSPWSN is working over the network layer, not in the application layer that CoAP works on. In this paper, we build a machine learn-ing model that can detect the DDoS attacks against CoAP with an accuracy of 98%. The CIDAD dataset is extended from ~11000 to 100,000 samples using GANs because it has fewer samples of malware (less than 0.2% of the total dataset). Our model outperforms the existing models that target securing CoAP in the application layer and obtains 93% of accuracy.

In the era of big data, feature engineering has proved its efficiency and importance in dimensionality reduction and useful information extraction from original features. Feature engineering can be expressed as dimensionality reduction and is divided into two types of methods such as feature selection and feature extraction. Each method has its pros and cons. There are a lot of studies to combine these methods. Sparse autoencoder (SAE) is a representative deep feature learning method that combines feature selection with feature extraction. However, existing SAEs do not consider the feature importance during training. It causes extracting irrelevant information. In this paper, we propose a parallel guiding sparse autoencoder (PGSAE) to guide the information by two parallel guiding layers and sparsity constraints. The parallel guiding layers keep the main distribution using Wasserstein distance which is a metric of distribution difference, and it suppresses the leverage of guiding features to prevent overfitting. We perform our experiments using four datasets that have different dimensionality and number of samples. The proposed PGSAE method produces a better classification performance compared to other dimensionality reduction methods.

The paper focuses on two unconventional magnetic field-based treatment regimes applied to an alloyed steel before applying a thermochemical treatment. This study was conducted in order to improve the behavior of the chosen material during the wear process. Increasing the wear resistance and the micro-hardness of the superficial layer obtained from the treatments are a priority, as well as improving the mechanical properties of a Cr-Mo alloyed steel. Thermomagnetic treatment, applied before plasma nitriding treatment, improves the mechanical properties of the base material, especially in the case of a steel with a considerable chromium content (1,02%). This paper is a review of my own researches in the last years.

Abstract- Cognitive radio (CR) play an important role in improving spectral efficiency (SE) of wireless communication, meanwhile, intelligent reflecting surface (IRS) is an effective technology to improve the secrecy performance of wireless communication system by adjusting the phase shift and amplitude of channel. Thus, we consider an IRS-aided multiple-input single-output (MISO) CR systems to enhance secrecy rate, which is consists of a single eavesdropping link, a primary network containing the primary receiver (PR), and secondary network including secondary receiver (SR) and the SR transmitter (SR-TX). Specifically, we minimize the transmit power of SR subject to secrecy capacity constraint and interference temperature (IT) constraint on PR, by jointly optimizing the beamforming vector and artificial noise (AN) constraints matrix at SR-TX as well as the phase shift matrix of IRS. Numerical results show that the different values of transmit antennas at the SR-TX and the number of IRS elements can significantly decrease the transmit power under the condition of ensuring secure communication.

The problem of health status prediction of insulated-gate bipolar transistors (IGBTs) gains a lot of attention in the field of health management of power electronic equipment. The performance degradation of IGBT gate oxide layer is one of the important failure modes. In view of failure mechanism analysis and easy implementation of monitoring circuit, this paper selects the gate leakage current of IGBT as the precursor parameter of gate oxide degradation, and uses time domain characteristic analysis, gray correlation degree, Mahalanobis distance, Kalman filter and other methods to carry out feature selection and fusion, and finally obtains a health indicator characterizing the degradation of IGBT gate oxide. Based on the Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) network, this paper constructs an IGBT gate oxide degradation prediction model, and performs experimental analysis on the dataset released by NASA-Ames Laboratory, and the average absolute error of performance degradation prediction is as low as 0.0216. Compared with Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), Support Vector Regression (SVR) and CNN-LSTM models, CNN-LSTM network has the highest prediction accuracy. These results show the feasibility of gate leakage current as a precursor parameter of IGBT gate oxide layer failure, as well as the accuracy and reliability of the CNN-LSTM prediction model.

This study provides, to our knowledge, the first detailed analysis of how surface oil modifies air-sea interaction in a two-way coupled model, i.e., the coupled-ocean-atmosphere-wave-sediment-transport (COAWST) model modified to account for oil-related changes to air-sea fluxes. This study investigates the effects of oil on surface roughness, surface wind, surface and near surface temperature differences, and boundary-layer stability, and how those conditions ultimately affect surface stress. We first conducted twin coupled modeling simulations with and without the influence of oil over the Deepwater Horizon (DWH) oil spill period (April 21 to May 5, 2010) in the Gulf of Mexico. Then we compared the results by using a modularized flux model with parameterizations selected to match those selected in the coupled model adapted to either ignore or account for different atmospheric/oceanic processes in calculating surface stress. When non-oil inputs to the bulk formula treated as unchanged by oil, the surface stress changes are always negative due to oil-related damping of surface roughness alone. However, the oil-related changes to 10-m wind speed and boundary-layer stability are found to play a dominant role in surface stress changes relative to those due to the oil-related surface roughness changes, highlighting that most of the changes in surface stress are due to the oil-related changes in wind speed and boundary-layer stability. Finally, the oil-related changes to surface stress due to the combined oil-related changes in surface roughness, surface wind, and boundary-layer stability are not large enough to have a major impact on the surface current and surface oil transport, indicating that the feedbacks from the surface oil to the surface oil movement itself are minor for forecasting the surface oil transport unless the fractional oil coverage is much larger than found in this study.

We re-inventoried red wood ant nests (RWA) in 12 study sites (≈1281 ha) in the Westeifel Volcanic Field, Germany, in an area-wide and integrated ecosystem approach after 12 years. Combined with the re-identification of previously mapped nests using a photo database, this approach leads to more accurate nest counts in (re)inventories. A total increase of nests from 1144 (2009) to 1252 (2021), and a dramatic one for the Heidberg site by 52-fold (2009) and 85-fold (2021) compared to a 1984 inventory was observed, contrasting with earlier postulations of a decline in RWA. Early to medium mature (41-80 years) and mature (³81–140 years) spruce forests were the preferred habitat. Large increase in small nest sizes suggests an increase in new nest settlements also in clearings, despite climate-induced forest dieback over the past decade. A decline in biodiversity in the herbaceous layer was observed; highly proliferating blackberries had no negative impact on RWA nests. Monitoring of woodpecker cavities in RWA nests is suggested as an indirect indicator tool for evaluating populations in forests. Positive ground movement rates caused by the Eifel plume are suggested another factor favoring nest settlements. This study contributes to the urgent update of statistically valid data required to a) effectively substantiate the status-quo of RWA occurrences, b) protect RWA as ecosystem engineers, c) advance understanding of Geo-Bio-Interactions in the wake of climate change, and c) contribute to the German government's Insect Conservation Action Program.

Membrane-based beverage dealcoholization is a successful process for producing low- and non-alcoholic beer and represents a fast-growing industry. Polyamide NF and RO membranes are commonly applied for this process. Polyelectrolyte multilayer (PEM) NF membranes are emerging as industrially relevant species and their unique properties (usually hollow fiber geometry, high and tunable selectivity, low fouling) underlines the importance of testing them in the food industry as well. To test PEM NF membranes for beer dealcoholization, at small pilot scale we dealcoholized filtered and unfiltered lager beer with the tightest available commercial polyelectrolyte multilayer NF membrane (NX Filtration dNF40), which has a MWCO=400Da which is quite high for these purposes. Dealcoholization is possible with a reasonable flux (10 LMH) at low pressures (5-8.6 bar) with a real extract loss of 16-18% and an alcohol passage of ~100%. Inorganic salt passage is high (which is typical for PEM NF membranes), which greatly affected beer flavor. During the dealcoholization process, the membrane underwent changes which substantially increased its salt rejection values (MgSO4 passage decreased 4-fold) while permeance loss was minimal (less than 10%). According to our sensory examination, the process yielded an acceptable flavored beer which could be greatly enhanced by the addition of the lost salts and glycerol.

Titanium dioxide (TiO2) thin films have been widely used in transparent optoelectronic devices owing to their excellent optical properties also is used in photocatalysis, cosmetics, and many other biomedical applications. However, a lack of studies was published on microstructure and adherence comparison of the TiO2 deposited on both AISI substrates. In this work, TiO2 thin films were deposited onto AISI 304 and AISI 316L stainless steel (SS) substrates via atomic layer deposition. Its heterostructure, morphology, and adhesion were compared in both substrates looking for synergistic and multifunctional properties. Raman spectroscopy mapping and X-ray diffraction using the Rietveld refinement method showed that the films are composed of anatase and rutile phases in different percentages. Scratching tests were used to analyze the film adher-ence and friction between a diamond tip and TiO2 film, showing well adhered in both substrates.

Precise monitoring of different environmental parameters and contaminations during food processing and storage is a key factor for maintaining its safety and nutritional value. Thus, developing reliable, efficient, cost-effective sensor devices for these purposes is of utmost importance. In this paper, we show that Poly-(diallyl-dimethylammonium chloride)/reduced Graphene oxide (PDAC/rGO) films produced by a simple Layer-by-Layer deposition can be effectively used to monitor temperature, relative humidity and the presence of volatile organic compounds as indicators for spoilage odors. At the same time, they show potential for electrochemical detection of organophosphate pesticide dimethoate. By monitoring the resistance/impedance changes during temperature and relative humidity variations or upon the exposure of PDAC/rGO films to methanol, good linear responses were obtained in the temperature range of 10-100 °C, 15-95 % relative humidity, and 35 ppm - 55 ppm of methanol. Moreover, linearity in the electrochemical detection of dimethoate is shown for the concentrations in the order of 102 µmol dm−3. The analytical response to different external stimuli and analytes depends on the number of layers deposited, affecting sensors’ sensitivity, response and recovery time, and long-term stability. The presented results could serve as a starting point for developing advanced multimodal sensor devices and sensor arrays with high potential for analytical applications in food safety and quality monitoring.

The results of studying the effect of particles of few-layer graphene (FLG) synthesized by self-propagating high-temperature synthesis (SHS) on the complex of strength and thermo physical properties of polymer composite products obtained by DLP 3D printing are presented. It has been discovered to achieve an increase in thermo physical and strength parameters of polymers modified by FLG compared with samples made on the unmodified base resin. This result was achieved due to low defectiveness, namely the absence of Stone-Wales defects in the structure of FLG due to the homogeneous distribution of FLG over the volume of the polymer in the form of highly dispersed aggregates. It was possible to increase hardness by 120 %, bending strength by 102 %, Charpy impact strength by 205 %, and thermal conductivity at 25 °C by 572 % at concentrations of few-layer graphene of no more than 2 wt. %.

This work focused on the evaluation of some machine learning (ML) models and their application in e-health, using intermediate nodes within an Internet of Things (IoT) platform used for heartbeat anomaly detection. For the evaluation of ML models, a set of statistical validation metrics was selected. These metrics were applied in the training, testing and validation phases of the models. The results obtained can determine relevant factors for the selection of ML models, either based on the statistical and intrinsic efficiency of the ML models, or on their suitability to be implemented in intermediate nodes within an IoT platform. the more Lightweight models such as Simple Linear Regression, Logistic Regression, and K Nearest Neighbors, could easily operate in intermediate nodes, and they are models that require low processing and storage to work. In conclusion, the approach for intermediate nodes of Internet of Things platforms using cognitive networks decreases the processing cost in cloud computing and transfers it to the fog layer.

Recent studies have proven that synthetic aperture radar (SAR) automatic target recognition (ATR) models based on deep neural networks (DNN) are vulnerable to adversarial examples. However, existing attacks are easily failed in the case where adversarial perturbations cannot be fully fed to victim models. We call this situation perturbation offset. Moreover, since background clutter takes up most of the areas in SAR images and has low relevance to recognition results, fooling models with global perturbations is quite inefficient. This paper proposes a semi-whitebox attack network, called Universal Local Adversarial Network (ULAN), to generate universal adversarial perturbations (UAP) for the target regions of SAR images. In the proposed network, we calculate the model’s attention heatmaps through layer-wise relevance propagation (LRP), which is used to locate the target regions of SAR images that have high relevance to recognition results. In particular, we utilize a generator based on the U-Net to learn the mapping from noise to UAPs and craft adversarial examples by adding the generated local perturbations to target regions. Experiments indicate that the proposed method fundamentally prevents perturbation offset and achieves comparable attack performance to conventional global UAPs by perturbing only a quarter or less of SAR image areas.

Herein we foremost detailed the numerical modeling of the double absorber layer- methyl ammonium lead iodide– carbon nitride layer solar cell and subsequently provided in-depth insight on the active layer associated with dominant radiative and non-radiative recombination losses limiting the efficiency ( ) of the solar cell. Under recombination kinetics phenomena, we explored the influence of Radiative recombination, Auger recombination, Shockley Read Hall recombination, the energy distribution of defects; Band Tail recombination (Hoping Model), Gaussian distribution, metastable defect states including single donor (0/+), single acceptor (-/0), Double Donor (0/+/2+), double acceptor (2/-/0-), and the interface layer defects on the output characteristics of the solar cell. Setting defect (or trap) density to with uniform energy distribution of defects for all the layers, we achieved the of 24. 16 %. A considerable enhancement in power conversion efficiency was perceived as we reduced the trap density to for the absorber layers. Further, it was observed that for the absorber layer with double donor defect states, the active layer should be carefully synthesized to reduce crystal order defects to keep the total defect density as low as to achieve efficient device characteristics

This research program investigated the effects of layer thickness (50 and 100 microns) on the microstructure and mechanical properties of electron beam powder bed fusion (EBPBF) additive manufacturing of Inconel 625 alloy. The as-built 50 and 100 micron layer thickness components were also heat treated at temperatures above 1100 oC, which produced a recrystallized grain structure containing annealing twins in the 50 micron layer thickness components, and a duplex grain structure consisting of islands of very small equiaxed grains dispersed in a recrystallized, large-grain structure containing annealing twins. The heat treated component microstructures and mechanical properties were compared with the as-built components in both the build direction (vertical) and perpendicular (horizontal) to the build direction. Vickers microindentation hardness (HV) values for the vertical and horizontal geometries averaged 227 and 220 for the as-built 50 and 100 micron layer components, and 185 and 282 for the corresponding heat treated components. The yield stress values were 387 MPa and 365 MPa for the as-built layer horizontal and vertical 50 micron layer geometries, and 330 MPa and 340 MPa for the as-built 100 micron layer components. For the heat treated 50 micron components, the yield stress values were 340 and 321 MPa for the horizontal and vertical geometries, and 581 and 489 MPa for the 100 micron layer components, respectively. The elongation for the 100 micron layer as-built horizontal components was 28% in contrast to 65% for the corresponding 100 micron heat treated layer components, an increase of 132% for the duplex grain structure. However, the coarse grains containing annealing twins and the equiaxed small grain islands in the duplex structure for the heat treated components contained continuous carbides in the grain boundaries, and this may indicate sensitization and a reduction in corrosion resistance. These findings point to the potential mechanical property advantage for heat treatment of Inconel 625 alloy 100 micron layer thickness components fabricated by EBPBF.

At present, nanomaterials (NMs) show extreme potential for a wide range of applications ranging from aerospace to energy storage applications owing to a number of properties which, in a number of contexts have been reported to be superior as compared to those of bulk counterparts. However, the high surface area to volume ratio which yields extraordinary properties to NMs also turns out to be the major limitation in a number of different contexts. For instance, the high surface area to volume ratio in these materials leads to a high reactivity, especially in electrochemical environments which are prevalent during energy storage applications. In this context, it is worthwhile mentioning that processing of NMs play a crucial role in influencing their mechanical properties. On the other hand, surface engineering has emerged as a powerful tool to deconvolute bulk properties from surface characteristics and has been reported to exhibit tremendous potential for overcoming the aforementioned limitation of NMs. The present review therefore, is aimed at highlighting the present status of research in the field of processing and applications of surface engineered NMs. Moreover, challenges and future perspectives in the aforementioned avenue have been discussed.

new subsonic blower wind tunnel design has been studied both numerically and experimentally, it is also referred to as “blower” wind tunnel. This paper, is initially aimed to address each sequential stage of the wind tunnel design process. Rather than applying the standard method of modelling solely the flow in the test section, a large-scale CFD model of the whole wind tunnel was employed. The loss of every constituent element was calculated and then all the losses are added up to determine the power needed for the wind tunnel operation which is used as “intake fan” boundary conditions in the CFD model. Then, flow uniformity and turbulent intensity measurements in an empty test section using a Pitot-static tube and hot wire anemometer (HWA) were introduced to validate the CFD results. The results showed that flow quality was significantly affected by boundary layer controllers (honeycomb and mesh screens) in the settling chamber and wide-angle diffuser. Investigations were also conducted to evaluate the flow deficit in the wake area behind a convex hump model using HWA. This was additional experimental tests carried out to validate the suitability of the wind tunnel flow aerodynamic research.

This paper presents work done as part of a transformation effort towards a greener and more sustainable Aluminium manufacturing plant. The effort includes reducing the carbon footprint by minimising waste and increasing operational efficiency. The contribution of this work includes the reduction of waste through the implementation of autonomous, real-time quality measurement and classification at an Aluminium casthouse. Data is collected from the MV20/20 which uses ultrasound pulses to detect molten Aluminium inclusions, which degrade the quality of the metal and cause subsequent metal waste. The sensor measures cleanliness, inclusion counts and distributions from 20 - 160 microns. The contribution of this work is in the development of business analytics to implement condition-based monitoring through anomaly detection, and to classify inclusion types for samples that failed. For anomaly detection, multivariate K-Means and DBSCAN algorithms are compared as they have been proven to work in a wide range of datasets. For classification, a two-stage classifier is implemented. The first stage classifies the success or failure of the sample, while the second stage classifies the inclusion responsible for the failed sample. The algorithms considered include logistic regression, support vector machine, multi-layer perceptron and radial basis function network. The multi-layer perceptron offers the best performance using k-fold cross-validation, and is further tuned using grid search to explore the possibility of an even better performance. The results reveal that the model has achieved a global maximum in performance. Recommendations include the integration of additional sensor systems and the improvements in quality assurance practices.

Single-layer core corrugated sandwich panels generally consist of a corrugated core and two layers of panels, while multi-layer core corrugated sandwich panels are formed by stacking multiple layers of panels with multiple layers of core layers. In this study, integrated multilayer core corrugated sandwich panels with different shapes of corrugated cores (triangular, trapezoidal, and rectangular) and the different number of core layers were fabricated using 3D printing technology, and the mechanical behavior of such multilayer core corrugated sandwich panels under quasi-static three-point bending was investigated using experiments and numerical simulations. The effects of core shape and number of core layers on the bending deformation process, damage mode, load carrying capacity, and bending energy dissipation capacity of multilayer core sandwich panels are discussed. Parametric design of multilayer triangular core corrugated sandwich panels was also carried out by finite element software ABAQUS. It was found that a new multilayer corrugated sandwich panel with a multi-layer core is better than the single core shape multilayer corrugated sandwich panel in terms of bending load capacity, energy dissipation capacity and deformation capacity can be obtained through the combination design of different core shapes.

This brief review introduces some general properties of lower atmospheric motions that may be exploited by birds, linking historical findings and current knowledge from both observational and modeling perspectives. The relative importance of turbulent mixing resulting from wind shear and that from buoyant thermals is emphasized as well as the determinants of the geometry of the resulting vertical motions.

Copper indium gallium selenide (CIGS) is an inexpensive material that has the potential to dominate the next-generation photovoltaic (PV) industry. Here we detail computational investigation of CIGS solar cell with encouragement of adopting cuprous dioxide (Cu₂O) as a Hole Transport Layer (HTL) for efficient fabricated CIGS solar cells. Although Cu₂O as a HTL has been studied earlier for perovskite and other organic/inorganic solar cell yet no study has been detailed on potential application of Cu₂O for CIGS solar cells. With the proposed architecture, recombination losses are fairly reduced at the back contact and contribute to enhanced photo-current generation. With the introduction of Cu₂O, the overall cell efficiency is increased to 26.63%. The wide-band of Cu₂O pulls holes from the CIGS absorber which allows smoother extraction of holes with experiencing lesser resistance. Further, it was also inferred that, HTL also improves the quantum efficiency (QE) for photons with large wavelengths thus increases the cell operating spectrum.

Steam boiler has a significant role in the industrial sector. The failure in boiler tubes significantly reduces the availability of the plant. Furthermore, deposits on the inner tube wall contribute to such failure by changing the thermal resistance of the wall, which causes a significant increase in the tube wall's temperature and, consequently, lower allowable stress. The presented thermal-fluid model is developed for the water tube. The model is implemented using ANSYS FLUENT to estimate the wall maximum water tube wall temperature considering the deposits layer and then determine the minimum thickness of the tube wall via ASME standards to assure safe operation. The model is verified via a mesh independence test. The minimum tube thickness is recommended and justified given the thermo-mechanical performance of the water tubes at several operating loads of 50, 75, and 100 %. These loads are implemented by different convective heat transfer coefficients of flue gases under different deposit thicknesses, thermal conductivity, and flue gas temperature. The present work contributes to the literature by recommending the minimum thickness of the water wall tubes and highlighting the thermo-mechanical effect of the deposits on water tube resilience under different operating conditions.

The Chebyshev collocation method (ChC) implemented as Chebfun is used in order to solve a class of second order one-dimensional singular and genuinely nonlinear boundary value problems. Efforts to solve these problems with conventional ChC have generally failed, and the outcomes obtained by finite differences or finite elements are seldom satisfactory. We try to fix this situation using the new Chebfun programming environment. However, for toughest problems we have to loosen the default Chebfun tolerance in Newton's solver as the ChC runs into trouble with ill-conditioning of the spectral differentiation matrices. Although in such cases the convergence is not quadratic the Newton updates decrease monotonically. This fact, along with the decreasing behaviour of Chebyshev coefficients of solutions, suggests that the outcomes are trustworthy, i.e., the collocation method has exponential (geometric) rate of convergence or at least an algebraic rate. We consider first a set of problems that have exact solutions or prime integrals and then another set of benchmark problems that do not possess these properties. Actually, for each test problem carried out we have determined how Chebfun solution converges, its length, the accuracy of the Newton method and especially how well the numerical results overlap with the analytical ones (existence and uniqueness).

A century-old scientific conundrum is solved in this paper. The Prandtl mixing length modelled plane boundary turbulent flow is described by: $\frac{du^+}{d{y^+} }+\kappa^2{y^+} ^2\left( \frac{du^+}{d{y^+} }\right)^2=1$, together with boundary condition $ {y^+} =0:\, u^+=0$. Only an approximate solution to this nonlinear ordinary differential equation (ODE) has been sought so far, however, the exact solution to this ODE has not been obtained. By introducing a transformation, $2\kappa y^+=\sinh \xi$, I successfully find the exact solution of the ODE as follows: $u^+=\frac{1}{\kappa}\ln(2\kappa {y^+} +\sqrt{1+4\kappa^2{y^+} ^2})-\frac{2{y^+} }{1+\sqrt{1+4\kappa^2{y^+} ^2}}$.

The study of long-term average weather patterns is known as climatology. It is a distinct field of study from meteorology and can be broken down into several subdivision. In order to predict the future, the knowledge of climatology is essential. In other words, with the help of climatology, we can figure out how likely it is that snow and hail will fall to the ground, and how much solar thermal radiation can reach a certain location etc. Climatology often focuses on how the climate has changed over time and how it has affected people and events. Both meteorology and climatology fall under the general term "meteorology", in particular, they are subdivision of research in the same field. In case of predicting the weather, meteorologists use variables such as humidity, air pressure, and temperature. This article's primary objective is to familiarize engineers with the fundamentals of climate and its processes so that they can effectively apply this knowledge to comprehend the climatic impact on water resources systems.

Laser irradiation of metals is widely used in research and applications. In this work, we study how the material geometry affects electron-phonon coupling in nano-sized gold samples: an ultrathin layer, nano-rod, and two types of gold nanoparticles: cubic and octahedral. We use the combined tight-binding molecular dynamics Boltzmann collision integral method implemented within XTANT-3 code to evaluate the coupling parameter in irradiation targets at high electronic temperatures (up to Te~20,000 K). Our results show that the electron-phonon coupling in all objects with the same fcc atomic structure (bulk, layer, rod, cubic and octahedral nanoparticles) is nearly identical at electronic temperatures above Te~7000 K, independently of geometry and dimensionality. At low electronic temperatures, reducing dimensionality reduces the coupling parameter. Additionally, nano-objects under ultrafast energy deposition experience nonthermal damage due to expansion caused by electronic pressure, in contrast to bulk metal. Nano-object ultrafast expansion leads to ablation/emission of atoms, and disorder inside of the remaining parts. These nonthermal atomic expansion and melting are significantly faster than electron-phonon coupling, forming a dominant effect in nano-sized gold.

Strained layer superlattice (SLS) material system is being considered for large format, small-pitch and low-cost focal plane arrays for different applications. To address difficulties associated to focal plane arrays fabrication arising from mesa-isolation etching or complex surface treatment/ passivation process, planar structures have been considered. In this work, the recent progress on planar SLS photodetector using ion-implantation for device isolation is presented. The devices are presented here are nBn and pBn heterostructure InAs/InAsSb SLS photodetector, where Zn and Si were chosen as the ion implants, respectively. The electrical and optical performance of the devices were compared along with comparison with mesa-etched device, to give deeper view of the device performance.

This review summarises the main numerical models of fuel droplet heating and evaporation (DHE) in combustion engines across the different scales by accessing the nano/micro, meso and macroscopic fluid elements. The phenomena of multi-physics, multi-scale and multi-phase fluid flow and heat transfer are fully investigated when the fuel droplet (dodecane) is heating and evaporated into a background gas (nitrogen) crossing the liquid-vapour (LV) interface, kinetic region (i.e., Knudsen layer) and the bulk regions of liquid and gas in terms of molecular dynamics (MD) simulations, kinetic theory modelling (i.e., direct numerical solutions of Boltzmann equations) and convectional fluid dynamics approach, respectively. The evaporation coefficient of fuel evaporating molecules and their velocity distributions at the LV interface derived from MD simulations formulate a new kinetic boundary condition (KBC). Moreover, a novel kinetic model considering the inelastic collision between fuel molecules alongside the new KBC enables us to describe the non-equilibrium gas dynamics of fuel vapour and gas mixture in Knudsen layer (KL). Heat and mass flux analysis of the fuel droplet under combustion engine conditions can be accurately assessed by implementing the inelastic collision between fuel molecules in KL and a temperature-dependent evaporation coefficient at the LV interface into DHE. The surface temperature of fuel droplet and its evaporation time, which play a significant role in resolving the ignition delay and hence the combustion phasing in engines, can also be well estimated. The multi-scale modelling of fuel DHE will make significantly potential input into the cleaner engine targeting the low-carbon emissions and enhance the capability of the existing computational fluid dynamics (CFD) solvers.

Archie model is the basis of calculating oil saturation, but there are some limitations when using this model to calculate oil saturation in water-flooded layer. The main reason is that the main parameters, such as rock resistivity and formation water resistivity, are constantly changing dynamic parameters in the underground with the influence of injected water. Considering that water-flooded layers changes with injection waters, influence factors of rock resistivity and formation water resistivity of primary parameters are analyzed. Considering the dynamic data of water cut is the most reactive underground fluid characteristics of real information, combined with dynamic and static, and the “double ratio” model of later development by the same sedimentary layer is established, which realizes the inversion of rock resistivity and formation water resistivity, then modified Archie model relating to water-flooded layers of the same sedimentary explaining formation. The explanation of actual data indicates that the “double ratio” model well considers the dynamic variation of production data, which makes the inversion of the flooded rock resistivity relatively accurate, besides, the modified Archie model can accurately calculate the oil saturation of water-flooded layers with a reasonable result, which offers scientific basis for the predicting of remaining oil distribution rules.

This paper studies the performance improvement of the IEEE 802.15.4 nonbeacon-enabled mode originated by the inclusion of the Request-To-Send/Clear-To-Send (RTS/CTS) handshake mechanism resulting in frame concatenation. Under IEEE 802.15.4 employing RTS/CTS, the backoff procedure is not repeated for each data frame sent but only for each RTS/CTS set. The maximum throughput and minimum delay performance are mathematically derived for both the Chirp Spread Spectrum and Direct Sequence Spread Spectrum Physical layers for the 2.4 GHz band. Results show that the utilization of RTS/CTS significantly enhances the performance of IEEE 802.15.4 applied to healthcare in terms of bandwidth efficiency.

Soil temperature is a fundamental parameter in water resources and engineering. A cost-effective model which can forecast soil temperature accurately is extensively needed. Recently, many studies have applied artificial intelligence (AI) at both surface and underground levels for soil temperature prediction. However, there is no comprehensive and detailed assessment of the performance of different AI approaches in soil temperature estimation, and primarily limited atmospheric variables are used as input data for AI models. In the present study, great varieties of various land and atmospheric variables are applied to evaluate the performance of a wide range of AI methods on soil temperature prediction. Herein, thirteen approaches, from classic regressions to well-established methods of random forest and gradient boosting to advanced AI techniques like multi-layer perceptron and deep learning are taken into account. The results show that AI is a promising approach in climate parameter forecast and deep learning demonstrates the best performance among other models. It has the highest R-squared ranging from 0.957 to 0.980, the lowest NRMSE ranging from 2.237% to 3.287% and the lowest MAE, ranging from 0.510 to 0.743 in predicting soil temperature. The prediction is repeated for different sizes of data, and prediction outcomes confirm the conclusion mentioned above.

Computer network attacks are evolving in parallel with the evolution of hardware and neural network architecture. Despite major advancements in Network Intrusion Detection System (NIDS) technology, most implementations still depend on signature-based intrusion detection systems, which can’t identify unknown attacks. Deep learning can help NIDS to detect novel threats since it has a strong generalization ability. The deep neural network’s architecture has a significant impact on the model’s results. We propose a genetic algorithm based model to find the optimal number of hidden layers and the number of neurons in each layer of the deep neural network (DNN) architecture for the network intrusion detection binary classification problem. Experimental results demonstrate that the proposed DNN architecture shows better performance than classical machine learning algorithms at a lower computational cost.

The design of multifunctional microcarriers has attracted significant attention because they combine various functions within a single system. In this study, we developed a set of multi-layered hydrogel microcarriers, which were first loaded with chemotherapeutic curcumin (CUR), then using the layer-by-layer (LbL) technique, coated through a polyelectrolyte shell consisting of chitosan (CHIT) or poly(allylamine hydrochloride) (PAH). As an outer layer with antimicrobial function, newly synthesised alkylene quaternary ammonium salt functionalised polyelectrolytes (A-QAS-PEs) were applied. For this purpose, poly(acrylic acid) (PAA) was decorated with dif-ferent hydrophobic side chains (n-hexane and n-dodecane side entities) and different degrees of substitution (m) of quaternary ammonium groups (abbreviated as PAA-C(O)O-(CH2)n-N+(CH3)3(m); n=6,12; m=8-14%). The grafting approach of PAA with the al-kylene quaternary ammonium salt moiety was performed under mild reaction conditions using Steglich esterification followed by quaternisation. The structure of antimicrobial decorated PAA was confirmed by 1H NMR and FTIR, and the mean diameter of all multifunctional microparticles was characterised by SEM. The viscoelastic properties of the functional layers were studied using QCM-D. The release of CUR from the microcarriers was described using a hybrid model, i.e., a combination of first-order kinetics and the Korsmeyer-Peppas model. The antimicrobial activity of functionalised PAA and multilayered CUR-loaded hydrogel microcarriers with quaternary am-monium function was assessed against Staphylococcus aureus and Serratia marcescens by the agar diffusion assay method. Only a limited inhibition zone of PAA was observed, but in the case of both antimicrobial decorated PAA and the corresponding multilayered nanocarriers, the inhibi-tory activity increase was achieved against both strains of bacteria.

A better study of the postnatal retinal development is not only essential for the in-depth understanding of the nature of the vision system but also may provide insights for treatment developments of eye conditions, such as retinopathy of premature (ROP). To date, quantitative analysis of postnatal retinal development is primarily limited to endpoint histological examination. This study is to validate in vivo optical coherence tomography (OCT) for longitudinal monitoring of postnatal retinal development in developing mouse eyes. Three-dimensional (3D) frame registration and super averaging were adopted to investigate the fine structure of the retina. Interestingly, a hyporeflective layer (HRL) between the nerve fiber layer (NFL) and inner plexiform layer (IPL) was observed in developing eyes and gradually disappeared with aging. To interpret the observed retinal layer kinetics, a model based on eyeball expansion, cell apoptosis, and retinal structural modification was proposed.

A quantitative method is proposed to determine of Stone-Wales defects for carbon nanostructures with sp2 hybridization of carbon atoms. The technique is based on the diene synthesis reaction (Diels-Alder reaction). The proposed method was used to determine Stone-Wales defects in the few-layer graphene (FLG) nanostructures synthesized by the self-propagating high-temperature synthesis (SHS) process, in reduced graphene oxide (rGO) synthesized based on the method of Hammers and in the single-walled carbon nanotubes (SWCNT) TUBAL trademark, Russia. Our research has shown that the structure of FLG is free of Stone-Wales defects, while the surface concentration of Stone-Wales defects in TUBAL carbon nanotubes is 1.1×10-5 mol/m2 and 3.6×10-5 mol/m2 for rGO.

For the first time, few-layer graphene (FLG) nanosheets were synthesized by the method of self-propagating high-temperature synthesis (SHS) from biopolymers (starch and lignin). We suggested that biopolymers (lignin, tree bark) and polysaccharides, in particular starch, could be an acceptable source of native cycles for the SHS process. The carbonization of biopolymers under the conditions of the SHS process was chosen as the basic method of synthesis. Chemical reactions, under the conditions of the SHS process, proceed according to a specific mechanism of nonsothermal branched-chain processes, which are characterized by the joint action of two fundamentally different process-accelerating factors - avalanche reproduction of active intermediate particles and self-heating. The method of obtaining FLG nanosheets included the thermal destruction of hydrocarbons in a mixture with an oxidizing agent. We used biopolymers as hydrocarbons and ammonium nitrate as an oxidizing agent. Thermal destruction was carried out in the mode of SHS, heating the mixture in a vessel at a speed of 20–30 oC/min to 150-200 oC and keeping at this temperature for 15–20 min with the discharge of excess gases into atmosphere. A combination of spectrometric research methods, supplemented by electron microscopy data, has shown that the particles of the carbonated product powder in their morphometric and physical parameters correspond to FLG nanosheets. An X-ray diffraction analysis of the indicated FLG nanosheets was carried out, which showed the absence of formations with a graphite crystal structure in the final material. The surface morphology was also studied and the features of the IR absorption of FLG nanosheets were analyzed. It is shown that the developed SHS method makes it possible to obtain FLG nanosheets with linear dimensions of tens of microns and a thickness of not more than 1-5 graphene layers (several graphene layers).

We have suggested earlier a new sustainable method for permafrost thermal stabilization that combines passive screening of solar radiation and precipitation with active solar-powered cooling of the near-surface soil layer thus preventing heat penetration in depth. Feasibility of this method has been shown by calculations, but needed experimental proof. In this article, we are presenting the results of soil temperature measurements obtained at the experimental implementation of this method outside of the permafrost area which actually meant higher thermal loads than in Polar Regions. We have shown that near-surface soil layer is kept frozen during the whole summer, even at air temperatures exceeding +30°C. Therefore, the method has been experimentally proven to be capable of sustaining soil frozen even in more extreme conditions than expected in permafrost areas. In addition to usual building and structure thermal stabilization, the method could be used to prevent the development of thermokarst, gas emission craters, and landslides; greenhouse gases, chemical, and biological pollution from the upper thawing layers at least in the area of human activities; protection against coastal erosion; and permafrost restoration after wildfires. Using commercially widely available components, the technology can be scaled up for virtually any size objects.

Retinal findings may change in patients with obstructive sleep apnea syndrome (OSAS). The present study aims to evaluate several retinal findings such as macula layer thickness, peripapillary retinal nerve fiber layer, and the optic nerve head in patients with OSAS using optical coherence tomography (OCT) and monitor the result of several types of treatment of OSAS with OCT. A prospective comparative study was designed. Patients were recruited at a Sleep Unit of a University Hospital and underwent comprehensive ophthalmological examinations. Following exclusion criteria, fifty-two patients with OSAS were finally included. Patients were examined by OCT twice: first, before treatment; secondly, after six months of treatment. In mild-moderate patients, where retinal swelling has been demonstrated, retinal thicknesses decreased [fovea (p=0.026), as well as inner ring macula (p=0.007), outer ring macula (p=0.015), and macular volume (p=0.015)]. In severe patients, where retinal atrophy had been observed, retinal thickness increased [fovea (p<0.001)]. No statistically significant differences in efficacy between treatments were demonstrated. In conclusion, OCT can evaluate the retina in patients with OSAS and help monitor results after treatment. In severe OSAS, retinal thickness increased six months after treatment.

An explanation of aerodynamic lift still is under controversial discussion as can be seen, for example, in a recent published article in Scientific American [1]. In contrast to an approach via integral conservation laws we here review an approach via the classical Kutta-Condition and its relation to boundary layer theory. Thereby we summarize known results for viscous correction to the lift coefficient for thin aerodynamic profiles and try to remember the work on triple-deck or higher order Boundary Layer theory, its connection to interactive boundary layer theory, viscous/inviscid coupling as implemented to well-known engineering code Xfoil. Finally we compare its findings to simple 2D numerical solution of full Navier Stokes equations (CFD)models. As a conclusion, a clearer definition of terms like understanding and explanation applied to the phenomenon of aerodynamic lift will be given.

This article describes in detail the numerical modeling of a CZTS (copper zinc tin sulfide) based kesterite solar cell. The Solar Cell Capacitance Simulator -one-dimension (SCAPS-1D) software was used to simulate MO/CZTS/CdS/ZnO/FTO structured solar cells. The parameters of different photovoltaic thin-film solar cells are estimated and analyzed using numerical modeling. The effects of various parameters on the performance of the photovoltaic cell and the conversion efficiency are discussed. Since the response of the solar cell is also contingent on its internal physical mechanism, J-V characteristic measures are insufficient to characterize the behavior of a device. Different features, as well as different potential conditions, must be considered for simulation, disregarding the belief in the modeling of a solar cell. With a conversion efficiency of 25.72%, a fill factor of 83.75%, a short-circuit current of 32.96436 mA/cm2 and an open-circuit voltage of 0.64V, promising optimized results have been achieved. The findings will be useful in determining the feasibility of fabricating high-efficiency CZTS-based photovoltaic cells. The efficiency of a CZTS-based experimental solar cell is also discussed. First, the effects of experimentally developed CZTS solar cells are simulated in the SCAPS-1D environment. The experimental results are then compared to the SCAPS-1D simulated results. The conversion efficiency of an optimized system increases after cell parameters are optimized. Using one-dimensional SCAPS-1D software, the effect of system parameters such as the thickness, acceptor and donor carrier concentration densities of absorber and electron transport layers, and the effect of temperature on the efficiency of CZTS-based photovoltaic cells is investigated. The proposed results will greatly assist engineers and researchers in determining the best method for optimizing solar cell efficiency, as well as in the development of efficient CZTS-based solar cells.

The planetary boundary layer height (PBLH) is one of the key factors in influencing the dispersion of the air pollutants in the troposphere and hence the air pollutant concentration on ground level. For this reason, accurate air pollutant concentration depends on the performance of PBLH prediction. Recently, ceilometer, a lidar instrument to measure cloud base height, has been used by atmospheric scientists and air pollution control authorities to determine the mixing level height (MLH) in improving forecasting and understanding the evolution of aerosol layers above ground at a site. In this study, ceilometer data at an urban (Lidcombe) and a rural (Merriwa) location in the New South Wales, Australia was used to validate the PBLH prediction from two air quality models (CCAM-CTM and WRF-CMAQ) as well as to understand the aerosol transport from sources to receptor point at Merriwa for the three case studies where high PM10 concentration was detected in each of the three days. The results show that the PBLH prediction by the two air quality models corresponds reasonably well with observed ceilometer data and the cause and source of high PM10 concentration at Merriwa can be found by using ceilometer MLH data to corroborate with back trajectory analysis of transport of aerosols to the receptor point at Merriwa. Of the three case studies, one had aerosol source from north and north west of Merriwa in remote NSW where windblown dust is the main source, and the other two had sources from south and south east of Merriwa where anthropogenic sources dominate,

Cadmium telluride (CdTe), a metallic dichalcogenide material, has been utilized as an absorber layer for thin film-based solar cells with appropriate configurations, and the SCAPS-1D structures program has been used to evaluate the results. In both known and developing thin film photovoltaic systems, a CdS thin film buffer layer has been frequently employed as a traditional n-type heterojunction partner. In this study, numerical simulation was used to find a suitable non-toxic material for the buffer layer instead of CdS, among various types of buffer layers (ZnSe, ZnO, ZnS, and In2S3), and carrier concentrations for the absorber layer (NA) and buffer layer (ND) were varied to determine the optimal simulation parameters. carrier concentrations (NA from 2 x 1012 cm-3 to 2 x 1017 cm-3 and ND from 1 x 1016 cm-3 to 1 x 1022 ??−3) have been differed. The results showed that the CdS as buffer layer based CdTe absorber layer solar cell has the highest efficiency (?%) of 17.43%. Furthermore, high conversion efficiencies of 17.42% and 16.27% have been found for ZnSe and ZnO based buffer layers, respectively. As a result, ZnO and ZnSe are potential candidates for replacing the CdS buffer layer in thin-film solar cells. Here, the absorber (CdTe) and buffer (ZnSe) layers were chosen to improve the efficiency by finding the optimal density of the carrier concentration (acceptor and donor). The simulation findings above provide helpful recommendations for fabricating high-efficiency metal oxide-based solar cells in the lab.

The electrical performance of the back-channel etched Indium–Gallium–Zinc–Oxide (IGZO) thin-film transistors (TFTs) with copper (Cu) source and drain (S/D) which are patterned by a selective etchant was investigated. The Cu S/D were fabricated on molybdenum (Mo) layer to prevent the Cu diffusion to the active layer (IGZO). We deposited the Cu layer using thermal evaporation and performed the selective wet etching of Cu using non-acidic special etchant without damaging the IGZO active layer. We fabricated the IGZO TFTs and compare the performance in terms of linear and saturation region mobility, threshold voltage and ON current (ION). The IGZO TFTs with Mo/Cu S/D exhibits good electrical properties as the linear region mobility is 12.3 cm2/V-s, saturation region mobility is 11 cm2/V-s, threshold voltage is 1.2 V and ION is 3.16 x 10-6 A. We patterned all the layers by photolithography process. Finally, we introduced SiO2-ESL layer to protect the device from the external influence. The results show that the prevention of Cu and introduced ESL layer enhances the electrical properties of IGZO TFTs.

The method of regularized stokeslets is widely-used to model microscale biological propulsion. The method is usually implemented with only the single layer potential, with the double layer potential being neglected, despite this formulation often not being justified a priori due to non-rigid surface deformation. We describe a meshless approach enabling inclusion of the double layer which is applied to several Stokes flow problems in which neglect of the double layer is not strictly valid: the drag on a spherical droplet with partial slip boundary condition, swimming velocity and rate of working of a force-free spherical squirmer, and trajectory, swimmer-generated flow and rate of working of undulatory swimmers of varying slenderness. The resistance problem is solved accurately with modest discretization on a notebook computer with the inclusion of the double layer ranging from no-slip to free slip limits; neglect of the double layer potential results in up to 24% error, confirming the importance of the double layer in applications such as nanofluidics, in which partial slip may occur. The squirming swimmer problem is also solved for both velocity and rate of working to within a few percent error when the double layer potential is included, but the error in the rate of working is above 250% when the double layer is neglected. The undulating swimmer problem by contrast produces a very similar value of the velocity and rate of working for both slender and non-slender swimmers, whether or not the double layer is included, which may be due to the deformation’s `locally rigid body’ nature, providing empirical evidence that its neglect may be reasonable in many problems of interest. Inclusion of the double layer enables us to confirm robustly that slenderness provides major advantages in efficient motility despite minimal qualitative changes to the flow field and force distribution.

The behavior of convective boundary conditions is studied to delineate their role in heat and mass relegation in the presence of radiation, chemical reaction, and hydromagnetic forces in three-dimensional Powell-Eyring nanofluids. Implications concerning non-Fourier’s heat flux and non-Fick’s mass flux with respect to temperature nanoparticle concentration were examined to discuss the graphical attributes of the principal parameters. An efficient optimal homotopy analysis method is used to solve the transformed partial differential equations. Tables and graphs are physically interpreted for significant parameters

Alcoholism is attributed to regular or excessive drinking of alcohol and leads to the disturbance of the neuronal system in the human brain. This results in certain malfunctioning of neurons that can be detected by an electroencephalogram (EEG) using several electrodes on a human skull at appropriate positions. It is of great interest to be able to classify an EEG activity as that of a normal person or an alcoholic person using data from the minimum possible electrodes (or channels). Due to the complex nature of EEG signals, accurate classification of alcoholism using only a small data is a challenging task. Artificial neural networks, specifically convolutional neural networks (CNN), provide efficient and accurate results in various pattern-based classification problems. In this work, we apply CNN on raw EEG data, and demonstrate how we achieved 98% average accuracy by optimizing a baseline CNN model and outperforming its results in a range of performance evaluation metrics on the UCI-KDD EGG dataset. This article explains the step-wise improvement of the baseline model using the dropout, batch normalization, and kernel regularization techniques, and provides a comparison of the two models that can be beneficial for aspiring practitioners who aim to develop similar classification models in CNN. A performance comparison is also provided with other approaches using the same dataset.

Different approaches for digital workflows have already been presented for their use in palatal plates for newborns and infants. However, there is no evidence on the accuracy of CAD/CAM manufactured orthodontic appliances for this kind of application. This study evaluates trueness and precision provided by different CAM technologies and materials for these appliances. Samples of a standard palatal stimulation plate were manufactured using stereolithography (SLA), direct light processing (DLP) and subtractive manufacturing (SM). The effect of material (for SM) and layer thickness (for DLP) were also investigated. Specimens were digitized with a laboratory scanner (D2000, 3Shape) and analyzed with a 3D inspection software (Geomagic Control X, 3D systems). For quantitative analysis, differences between 3D datasets were measured using root mean square (RMS) error values for trueness and precision. For qualitative analysis, color maps were generated to detect locations of deviations within each sample. SM showed higher trueness and precision than AM technologies. Reducing layer thickness in DLP did not significantly increase accuracy, but prolonged manufacturing time. All materials and technologies met the clinically acceptable range and are appropriate for their use. DLP with 100µm layer thickness showed the highest efficiency, obtaining high trueness and precision within the lowest manufacturing time.

Highly-correlated electrons – electrons that engage in strong electron-electron interactions – have been observed in transition metal oxides and quantum dots and can create unusual material behavior that is difficult to model, such as switching between a low resistance metal state and a high resistance Mott insulator state. Tests of devices using a layer-by-layer deposition process for forming multilayer arrays of ferritin (a transition metal (iron) oxide storage protein) have been previously reported that indicate that highly-correlated electron transport is occurring, consistent with models of electron transport in quantum dots. This paper reports the results of the effect of various degrees of structural homogeneity on the electrical characteristics of these ferritin arrays, as well as demonstrating that these structures can provide a switching function associated with the circuit that they are contained within, consistent with the observed behavior of highly-correlated electrons.

Abstract: Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development processes and for the assessment of coupled nature-human systems, e.g., the dynamics of the wildland-urban interface. Herein, we propose a framework that jointly uses remote sensing derived human settlement data (i.e., the Global Human Settlement Layer, GHSL) and scanned, georeferenced historical maps to automatically generate historical urban extents for the early 20th century. By applying unsupervised color segmentation to the historical maps, spatially constrained to the urban extents derived from the GHSL, our approach generates historical settlement extents for seamless integration with the multi-temporal GHSL. We apply our method to study areas in countries across four continents, and evaluate our approach for two U.S. study sites against historical settlement extents derived from the Historical Settlement Data Compilation for the US, HISDAC-US, achieving Area-under-the-Curve values >0.9. Our results are largely in agreement with model-based urban areas from the HYDE database, and demonstrate that the integration of remote sensing derived observations and historical cartographic data sources opens up new, promising avenues for assessing urbanization, and long-term land cover change in countries where historical maps are available.

In this paper, we propose a lightweight physical layer aided authentication and key agreement (PL-AKA) protocol in the internet of things (IoT). Conventional evolved packet system AKA (EPS-AKA) used in long-term evolution (LTE) systems may suffer from congestions in core networks by the large signaling overhead as the number of IoT devices increases. Thus, in order to alleviate the overhead, we consider a cross-layer authentication by integrating physical layer approaches to cryptography-based schemes. To demonstrate the feasibility of the PL-AKA, universal software radio peripheral (USRP) based tests are conducted as well as numerical simulations. The proposed scheme shows a significant reduction in signaling overhead compared to the conventional EPS-AKA in both simulation and experiment. Therefore, the proposed lightweight PL-AKA has the potential for practical and efficient implementation of large-scale IoT networks.

Surface passivation, which has been intensively studied recently, is essential for the perovskite solar cells (PSCs), due to the intrinsic defects in perovskite crystal. A series of chemical or physical methods have been published for passivating the defects of perovskite, which effectively suppressed the charge recombination and enhanced the photovoltaic performance. In this study, the n-type semiconductor of [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) is dissolved in chlorobenzene (CB) for the surface passivation during the spin-coating process for depositing the two-dimensional (2D) perovskite film. This approach simplifies the fabrication process of 2D PSCs and benefits the film quality. As a result, the defects of perovskite film are effectively passivated by this method. A better perovskite/PCBM heterojunction is generated, exhibiting an increased film coverage and improved film morphology of PCBM. It is found that this technology results in an improved electron transporting performance as well as suppressed charge recombination for electron transport layer. As a result, PSCs based on the one-step formed perovskite/PCBM heterojunctions exhibit the optimized power conversion efficiency of 15.69% which is about 37% higher than that of regular perovskite devices. The device environmental stability is also enhanced due to the quality-improved electron transport layer.

In this study, an investigation on the influence of In-situ tribo-oxide-layer on non-lubricated tribological behaviours of LM27/SiCp composites was carried out at different applied loads. The variations in wear performance and microstructure of brake lining friction material (LM27) with the addition of different amounts and sizes of SiCp are explored. For this purpose, LM27/SiCp composite materials were manufactured by stir casting route varying the amount of particle reinforced from 3wt.% to 12wt.% with a different size range (fine: 1-20µm and coarse: 106-125µm). Non-lubricated dry wear tests of LM27/SiCp composites samples were trialled at different loads from 9.8N to 49N by using a pin-on-disc machine system. At a contact pressure of 0.2-1 MPa, LM27/SiCp composites with 12wt.% reinforcement showed a lower coefficient of friction than other composites. In-situ formation of oxide layers on the contact region of the specimen supports the self-lubrication during the wear test, which is responsible for better wear performance of LM27/SiCp composites. However, these study portraits that composite with 12wt. % fine size SiCp exhibits better wear performance in comparison to the other developed composites.

Deep convolutional neural network (CNN) has shown their great advantages in the single image deraining task. However, most existing CNN-based single image deraining methods still suffer from residual rain streaks and details lost. In this paper, we propose a deep neural network including the Multi-scale feature extraction module and the channel attention module, which are embed in the feature extraction sub-network and the rain removal sub-network respectively. In the feature extraction sub-network, the Multi-scale feature extraction module is constructed by a Multi-layer Laplacian pyramid, and is then integrated multi-scale feature maps by a feature fusion module. In the rain removal sub-network, the channel attention module, which assigns different weights to the different channels, is introduced for preserving image details. Experimental results on visually and quantitatively comparison demonstrate that the proposed method performs favorably against other state-of-the-art approaches

Electrochemical-mechanical interactions, in particular pressure-induced ones, have been identified to be a cause for lithium-plating in lithium-ion cells. Mechanically-induced porosity inhomogeneities in the separator layers due to electrode expansion during charging especially lead to cell internal balancing currents and can cause localized plating. To identify cell-format and cell-material dependent mechanical weak spots, a layer-resolved mechanical simulation of different cell types and cell-material combinations is presented in this work. The simulation results show distinctive layer strain patterns for different cell-types that coincide with localized lithium-plating found in post-mortem cells. Additionally, the effects of cell bracing in battery modules is investigated and a method to mitigate the increased layer strain due to bracing counterforces is proposed that also increases cell energy density for hardcase-type automotive cells.

Obesity and overweight is a foremost concern around the globe for each group of age. This can be accelerated by the current imposed lockdown. However, excessive weight gain may result in other chronic diseases. This study has been considering the age group of 25 to 55 years as the sample populations and monitoring them from July, 2020 to November, 2020. The lifestyle of this population, food habit, mental health conditions are explored using deep learning based framework. All these parameters need to be monitored as these have close relation with currently imposed constraints due to COVID-19. A predictive model is constructed using deep learning techniques to predict the risk of gaining weight. The predictive model hybridizes the convolutional layer and gated recurrent neural networks as a unified entity for achieving the objective of early weight gain prediction. The result obtained by this model exhibits an encouraging predictive efficiency of 93.7%.

Background: Central serous chorioretinopathy (CSC) is a common macular condition characterized by detachment of the neuroretina and is a frequent cause of central vision loss in adults. Among the various therapeutic strategies, subthreshold microsecond pulsed laser (SML) treatment has become a useful option. Despite the suggested involvement of choroidal circulatory disturbances in CSC, effects of this treatment on macular microperfusion have not been fully evaluated yet. Herein, we report the impact of SML on retinal and choroidal microvascular flow using non-invasive optical coherence tomography (OCT) angiography (OCTA). Methods: In this study, CSC patients with persistent subretinal fluid (SRF) with or without secondary choroidal neovascularization (CNV) were included (referred to as pachychoroid neovasculopathy (PNV) group and CSC group, respectively). SML was conducted using a yellow (577 nm) laser with duty cycle of 10%, spot size of 200 µm and duration of 200 ms. Best corrected visual acuity (BCVA) as well as OCT and OCTA images were evaluated at baseline and 4 weeks after SML. OCTA parameters of interest included full retinal perfusion (FRP), choriocapillaris perfusion (CCP), Sattler’s layer perfusion (SLP), and Haller’s layer perfusion (HLP), which were evaluated longitudinally and compared to unaffected fellow eyes. Results: 27 affected eyes and 17 fellow eyes from 27 patients were included. Before treatment, central retinal thickness (CRT) and subfoveal choroidal thickness (SFCT) of affected eyes were significantly larger than in fellow eyes. Four weeks after SML, CRT decreased significantly, whereas perfusion parameters did not change. In subgroup analyses, the CSC group showed a significant decrease of SFCT, whereas the PNV group did not despite the decrease of CRT. Conclusion: Our results suggest that the SML may SFCT of CSC, but not of PNV patients at least within four weeks following treatment. This effect seems to be independent of the change in choroidal perfusion measured with OCTA.

The accuracy of wind field simulation and prediction is one of the most significant parameters in the field of atmospheric science and wind energy. Limited by the observation data, there are few researches on wind energy development. A 3D Doppler wind lidar (DWL) providing the high-vertical-resolution wind data over the urban complex underlying surface in February 2018 was employed to evaluated the accuracy of vertical wind field simulation systematically for the first time. 11 PBL schemes of the Weather Research and Forecasting Model (WRF) were employed in simulation. The model results were evaluated in groups separated by weather (sunny days, haze days and windy days), observation height layers, and various observation wind speeds. The test results presented that the vertical layer altitude of the observation point position was the most important factor. The simulation is fairly well at a height of 1000-2000m, as most of the relative mean bias of wind speed and wind direction are less than 20% and 6% respectively. Below 1000 m, the wind speed and direction biases are about 30%-150% m.s-1 and 6%-30% respectively. Moreover, when the observed wind speed was lower than 5 m.s-1, the bias were usually large, and the wind speed relative mean bias is up to 50-300%. In addition, the accuracy of simulated wind profile is better in 10-15m.s-1 than other speed ranges, and is better up 1000m than below 1000m in the boundary layer. We see that the WRF boundary layer schemes have different applicability to different weather conditions. The WRF boundary layer schemes have significant differences in wind field simulation with larger error under the complex topography. A PBL scheme is not likely to maintain its advantages in the long term under different conditions including altitude and weather conditions.

Drug repositioning (also called drug repurposing) is a strategy for identifying new therapeutic targets for existing drugs. This approach is of great importance in pharmacology as it is a faster and cheaper way to develop new medical treatments. In this paper, we present, to our knowledge, the first application of multiplex-heterogeneous network embedding to drug repositioning. Network embedding learns the vector representations of nodes, opening the whole machine learning toolbox for a wide variety of applications including link prediction, node labelling or clustering. So far, the application of network embedding for drug repositioning focused on heterogeneous networks. Our approach for drug repositioning is based on multiplex-heterogeneous network embedding. Such method allows the richness and complexity of multiplex and heterogeneous networks to be projected in the same vector space. In other words, multiplex-heterogeneous networks aggregate different multi-omics data in the same network representation. We validate the approach on a task of link prediction and on a case study for SARS-CoV2 drug repositioning. Experimental results show that our approach is highly robust and effective for finding new drug-target associations.

Time-domain spectroscopy (TDS) in the Terahertz (THz) frequency range is gaining in importance in nondestructive testing of dielectric materials. One application is the layer thickness measurement of a coating layer. To determine the thickness from the measurement data, the refractive index of the coating layer must be known in the surveyed frequency range. For perpendicular incidence of the radiation, methods exist to extract the refractive index from the measurement data itself without prior knowledge. This paper extends these methods for non-perpendicular incidence, where the polarization of the radiation becomes important. Furthermore, modifications considering effects of surface roughness of the coating are introduced. The new methods are verified using measurement data of a sample of Inconel steel coated with yttria-stabilized zirconia (YSZ) and with COMSOL simulations of the measurement setup. To validate the thickness measurements, scanning electron microscopy (SEM) images of the layer structure are used. The results show good agreement with an average error of 1% for the simulation data and under 4% for the experimental data compared to reference measurements.

The modulation instability of surface capillary-gravity water waves is analysed in a shear flow model with a tangential discontinuity of velocity. It is assumed that air blows along the surface of the water with a uniform profile in the vertical direction. Such a model, despite its simplicity, plays an important role in hydrodynamics as the reference model for investigating basic physical phenomena of wave-current interactions and acquiring insights into a series of complex phenomena. In certain cases where the wavelength of interfacial perturbations is much bigger than the width of the shear fow profile, the model with the tangential discontinuity in the velocity is adequate for describing physical phenomena at least within limited spatial and temporal frameworks. A detailed analysis of the air-flow conditions under which modulation instability sets in is presented. It is also shown that the interfacial waves are subject to dissipative or radiative instability when negativeenergy waves appear at the interface.

We utilized laser irradiation as a potential technique in tuning the electrical performance of NiOx/SiO2 thin film transistors (TFTs). By optimizing the laser fluence and the number of laser pulses, the TFT performance is evaluated in terms of mobility, threshold voltage, on/off current ratio and subthreshold swing, all of which were derived from the transfer and output characteristics. The 500 laser pulses irradiated NiOx/SiO2 TFT exhibited an enhanced mobility of 3 cm2/V-s from a value of 1.25 cm2/V-s for as-deposited NiOx/SiO2 TFT. The laser-irradiated NiOx material likely has a significant concentration of defect gap states, which could also be involved in light absorption processes. Second, and more importantly, the excess energy that the photogenerated charge carriers possess (due to the significant difference between the photon energy and the bandgap of NiOx), combined with the very high light intensity, would result in complex thermal and photo thermal changes thus resulting in an enhanced electrical performance of p-type NiOx/SiO2 TFT structure.

Spatiotemporal dynamics of the atmospheric kinetic energy and its components caused by the ordered and turbulent motions of air masses are estimated from minisodar measurements of three velocity vector components and their variances within the lowest 5–200 m layer of the atmosphere, with a particular emphasis on the turbulent kinetic energy. The layered structure of the total atmospheric kinetic energy has been established. From the diurnal hourly dynamics of the altitude profiles of the turbulent kinetic energy (TKE) retrieved from minisodar data, four layers are established by the character of the altitude TKE dependence, namely, the near-ground layer, the surface layer, the layer with a linear TKE increase, and the transitive layer above. In the first layer, the most significant changes of the ТКЕ were observed in the evening hours. In the second layer, no significant changes in the TKE values were observed. A linear increase in the TKE values with altitude was observed in the third layer. In the fourth layer, the TKE slightly increased with altitude and exhibited variations during the entire observation period. The altitudes of the upper boundaries of these layers depended on the time of day. The MKE values were much less than the corresponding TKE values, they did not exceed 50 m²/s². From two to four MKE layers were distinguished based on the character of its altitude dependence. The two-layer structures were observed in the evening and at night (under conditions of the stable atmospheric boundary layer). In the morning and daytime, the four-layer MKE structures with intermediate layers of linear increase and subsequent decrease in the MKE values were observed. Our estimates demonstrated that the ТКЕ contribution to the total atmospheric kinetic energy considerably (by a factor of 2.5–3) exceeded the corresponding МКЕ contribution.

The aim of this articles is to investigate the entropy optimization in unsteady MHD flow Darcy-Forchheimer nanofluids towards a stretchable sheet. The surface we tend to think about is porous and stretchy under acceleration. Flow occurs due to the stretching of the surface. Four distinct types of aqueous nanostructures are taken in this examination where copper oxide ( ), copper ( ), titanium dioxide ( ) and aluminum oxide ( ) are the nanoparticles. Irreversibility analysis are discussed through second law of thermodynamics. The expression of energy is mathematically designed and discussed according to heat generation / absorption, dissipation, thermal radiation, and joule heating. The nonlinear PDE (partial differential conditions) is first changed to ODE (normal differential conditions) through appropriate similarity variables. Here we used the numerically embedded solution technique to develop a numerical result for the obtained nonlinear flow expression. Influence of various flow parameter velocity temperature distribution and entropy generation are discussed. Reduction occurs in velocity profile for larger porosity and magnetic parameters. An enhancement in entropy generation and temperature distribution is seen for Brinkman number. An opposite effect is noticed in velocity and temperature through solid volume friction.

Background: Inadequate meibomian glands (MGs) secretion can lead to dry eye signs and symptoms. Tear film lipid layer (TFLL) secreted by MGs protects and prevents rapid evaporation of tear film. Our purpose was to assess TFLL alteration and function in patients with evaporative dry eye (EDE) using tear interferometry after optimal pulse light technology (OPT) intense pulsed light (IPL). Methods: This prospective randomized examiner-masked sham- controlled study included 86 participants (142 eyes) with DED. IPL or sham procedure was performed on day 0, 21, and 42. Ocular Surface Disease Index (OSDI), non-invasive breakup time (NITBUT), interferometric fringe pattern determined TFLL quality, fluorescein staining (FS), and meibum gland (MG) were assessed at day 0, 21, 42 and 3-month. Results: At 3-month, TFLL, NITBUT, MG drop-out, MG quality, MG expressibility, FS and OSDI improved significantly (P<0.05) in the IPL group, while the sham group had no significant improvements. All DE parameters significantly correlated with the improvement in TFLL following IPL treatment. Additionally, artificial tears usage was significantly less in the IPL group from D-42 onwards. Conclusion: IPL treatment demonstrated the ability to improve TFLL quality and clinically reduced sign and symptoms of DED thereby reducing the frequency of artificial tears usage.

This study presents of the microsphere-based fiber-optic sensor with the ZnO ALD coating thickness of 100 nm and 200 nm for temperature measurements. Metrological properties of the sensor were investigated over the temperature range of 100°C to 300°C, with a 10°C step. The interferometric signal is used to control whether the microstructure is intact. Spectrum shift of a reflected signal is used to conclude changes in measured parameter for the sensor with a 100 nm coating, while the reflected signal intensity is an indicator during measurements executed by a sensor with a 200 nm coating. With changing temperature, the peak position or intensity of a reflected signal also changes. The R2 coefficient of the presented sensors indicates a linear fit of over 0.99 to the obtained data. The sensitivity of the sensors, investigated in this study, equals 103.5 nW/°C and 0.019 nm/°C for ZnO thickness of 200 nm and 100 nm, respectively.

In this study, the effect of hot stamping forming process on the properties change of compound layer in Al–Si coated high-strength steel sheet with different thickness was investigated. The coating layer in hot stamped high-strength steel sheet was composed of a diffusion layer and a compound layer. As the hot stamping temperature and holding time for forming increased, the thickness of the compound layer in the Al–Si coated high-strength steel sheet increased. The thickness of coating layer with the hot stamping for 500 sec at 890, 910 and 950 °C was obtained 8.9, 11.8, and 20.6 micrometer, respectively. The thickness of coating layer with hot stamping for 180, 500 and 550 sec at 910 ^oC was obtained 5.7, 11.8, and 17.8 micrometer, respectively. The compound layer in hot stamped high-strength steel sheet with Al–Si coating layer consists of Al_5.4Fe₂ and Fe₂Si phases. In the compound layer, Al and Si were irregularly distributed.

Transport Layer Security (TLS) is a cryptographic protocol that provides communications security between two peers and it is widely used in many applications. To reduce the latency in TLS handshake session resumption using pre-shared key (PSK) had been used. But current methods in PSK mode handshake uses a fixed session key multiple times for the lifetime of session ticket. Reuse of fixed session key should be very careful in the point of communications security. It is vulnerable to replay attacks and there is a possibility of tracking users. Paired token (PT) is a new secondary credential scheme that provides pre-shared key in stateless way in client-server environment. Server issues paired token (public token and secret token) to authenticated client. Public token represents signed identity of client and secret token is a kind of shared secret between client and server. Once client is equipped with PT, it can be used for many symmetric key based cryptographic applications such as authentication, authorization, key establishment, etc. It was also shown that it can be used for one-time authenticated key establishment using the time-based one-time password (TOTP) approach. In this paper we apply the PT and TOTP approach to TLS to achieve stateless one-time authenticated session resumption. Server executes full handshake of TLS 1.3 and issues PT to authenticated client. Then client and server can execute one-time authenticated session resumption using PT in stateless way in server side. In every runs of session resumption distinct session keys are established that the same PT can be used safely for longer lifetime. If anonymous PT is used with renewal issuing, user privacy, untraceability and forward security can be achieved easily. It will provide a huge performance gain in large-scale distributed services.

While L-PBF offers advantages in terms of geometrical freedom or lightweight construction, its use is often limited by economic constraints or currently achievable part costs. With an anticipated increase of L-PBF machine productivity during the next years, an increase of the share of material costs and the share of non-productive time for powder layer application process is to be expected. This results in a demand for less expensive powder materials and advanced processing strategies for the short-and medium-term advancement of L-PBF. As one possible approach, the processing of gas- and water atomized stainless steel (316L) powders with different morphology and particle size distribution as well as their impact on L-PBF productivity is investigated. The actual powder applicability in L-PBF systems and the L-PBF processability determines the minimum necessary powder quality. The main focus of the presented work is put on the interaction between powder quality, powder layer properties, part quality and cost-effectiveness of the L-PBF process. To this end, the influence of the gas and water-atomized powder properties (particle size and morphology) during the powder layer application process at highest possible powder recoater speeds and the resulting powder bed properties (powder layer density, powder bed density, powder demixing) and part properties (part density and tensile strength) is investigated.

Defect detection in ferromagnetic substrates is often hampered by non-magnetic coating thickness variation when using conventional eddy current testing technique. The lift-off distance between the sample and the sensor is one of the main obstacles for the thickness measurement of non-magnetic coatings on ferromagnetic substrates when using the eddy current testing technique. Based on the eddy current thin-skin effect and the lift-off insensitive inductance (LII), a simplified iterative algorithm is proposed for reducing the lift-off variation effect using a multi-frequency sensor. Compared to the previous techniques on compensating the lift-off error (e.g., the lift-off point of intersection) while retrieving the thickness, the simplified inductance algorithms avoid the computation burden of integration, which are used as embedded algorithms for the online retrieval of lift-offs via each frequency channel. The LII is determined by the dimension and geometry of the sensor, thus eliminating the need for empirical calibration. The method is validated by means of experimental measurements of the inductance of coatings with different materials and thicknesses on ferrous substrates (dual-phase alloy). The error of the calculated coating thickness has been controlled to within 3 % for an extended lift-off range of up to 10 mm.

In this work we have critically reviewed the processes in high-temperature sublimation growth of graphene in Ar atmosphere using enclosed graphite crucible. Special focus is put on buffer layer formation and free charge carrier properties of monolayer graphene and quasi-freestanding monolayer garphene on 4H-SiC. We show that by introducing Ar at different temperatures, TAr one can shift to higher temperatures the formation of the buffer layer for both n-type and semi-insulating substrates. A scenario explaining the observed suppresed formation of buffer layer at higher TAr is proposed and discussed. Increased TAr is also shown to reduce the sp3 hybridization content and defect densities in the buffer layer on n-type conductive substrates. Growth on semi-insulating substrates results in ordered buffer layer with significantly improved structural properties, for which TAr plays only a minor role. The free charge density and mobility parameters of monolayer graphene and quasi-freestanding monolayer graphene with different TAr and different environmental treatment conditions are determined by contactless terahertz optical Hall effect. An efficient annealing of donors on and near the SiC surface takes place in intrinsic monolayer graphene grown at 2000∘C, and which is found to be independent of TAr. Higher TAr leads to higher free charge carrier mobility parameters in both intrinsically n-type and ambient p-type doped monolayer graphene. TAr is also found to have a profound effect on the free hole parameters of quasi-freestanding monolayer graphene. These findings are discussed in view of interface and buffer layer properties in order to construct a comprehensive picture of high-temperature sublimation growth and provide guidance for growth parameters optimization depending on the targeted graphene application.

Three kinds of Ni based alloy cladding coatings were prepared on 316L stainless steel at different power. The microstructure of the cladding layer was observed and analyzed by XRD, metallographic microscope and SEM. The hardness of the cladding layer was measured, and the wear resistance of the cladding layer was tested by friction instrument. The results show that the effect of laser cladding is good and the cladding layer has a good metallurgical bonding with the substrate. Different microstructures such as dendritic and equiaxed grains can be observed in the cladding layer. With the increase of laser power, more equiaxed and columnar dendrites can be observed. The phase composition of the cladding layer is mainly composed of γ - Ni solid solution and some intermetallic compounds such as Ni3B, Cr5B3 and Ni17Si3. The results of EDS show that there are some differences in the distribution of C and Si between dendrites. The hardness of the cladding layer is about 600 HV0.2, which is about three times of the substrate (~ 200 HV0.2). Through the analysis of the wear morphology, the substrate wear is serious, there are serious shedding, mainly adhesive wear and abrasive wear. However, the wear of cladding layer is slight, which is abrasive wear, and there are some grooves on the surface.

A field theoretic representation of the classical partition function is derived for a system composed of a mixture of anisotropic and isotropic mobile charges that interact via long range Coulomb and short range nematic interactions. The field theory is then solved on a saddle-point approximation level, leading to a coupled system of Poisson-Boltzmann and Maier-Saupe equations. Explicit solutions are finally obtained for a calamitic counterion-only system in proximity of a charged planar wall. The nematic order parameter profile, the counterion density profile and the electrostatic potential profile are interpreted within the framework of a nematic-isotropic wetting phase with a Donnan potential difference.

With the latest advances in information and communication technologies, greater amounts of sensitive user and corporate information are constantly shared across the network making it susceptible to an attack that can compromise data confidentiality, integrity and availability. Intrusion Detection Systems (IDS) are important security mechanisms that can perform a timely detection of malicious events through the inspection of network traffic or host-based logs. Throughout the years, many machine learning techniques have proven to be successful at conducting anomaly detection but only a few considered the sequential nature of data. This work proposes a sequential approach and evaluates the performance of a Random Forest (RF), a Multi-Layer Perceptron (MLP) and a Long-Short Term Memory (LSTM) on the CIDDS-001 dataset. The resulting performance measures of this particular approach are compared with the ones obtained from a more traditional one, that only considers individual flow information, in order to determine which methodology best suits the concerned scenario. The experimental outcomes lead to believe that anomaly detection can be better addressed from a sequential perspective and that the LSTM is a very reliable model for acquiring sequential patterns in network traffic data, achieving an accuracy of 99.94% and a f1-score of 91.66%.

The progressive impairment analysis in gait from neurological diseases patients such as Hereditary Ataxias (HA) has been carried out using gait data collected with movement sensors. This research is focused on finding the minimum amount required of gait features to recognize efficiently and less intrusive way, HA patients based on data collected with iPhone movement sensors placed on the ankles from 14 HA patients and 14 healthy people. A twofold proposal is made , first a local minimum prominent peak criterion to find out the starting point of each stride, to get 10-stride window about which 56 spatial-temporal features are derived; second a search strategy based on Hill Climbing algorithm to reduce the number of gait features and sensors. The main results were the findings that with two gait patterns a 96% of classification accuracy was achieved by using K-Nearest Neighbors (KNN) and Multi-Layer Perceptron (MLP) algorithms, but in addition, MLP only right ankle sensor patterns were required which also allows to reduce the intrusion.

This article is devoted to the issues of thermal softening of materials in the surface layer of forging tools. The research covers numerical modeling of the forging process, laboratory tests of tempering of nitrided layers and the analysis of tempering of the surface layer of tools in the actual forging process. Numerical modeling was supported by measuring the temperature inside the tools with a thermocouple inserted into the tool to measure the temperature as close to the surface as possible. The modeling results confirmed the possibility of tempering the die material. The results of laboratory tests made it possible to determine the influence of temperature on tempering at different surface layer depths. Numerical analysis and measurement of surface layer microhardness of tools revealed the destructive effect of temperature during forging on the tempering of the nitrided layer and on the material layers located deeper below the nitrided layer.

In this study, we improved the photovoltaic (PV) properties and storage stabilities of inverted perovskite solar cells (PVSCs) based on methylammonium lead iodide (MAPbI3) by employing bathocuproine (BCP)/poly(methyl methacrylate) (PMMA) and BCP/polyvinylpyrrolidone (PVP) as hole-blocking and electron-transporting interfacial layers. The architecture of the PVSCs was indium tin oxide/poly(3,4-ethylenedioxythiophene):polystyrenesulfonate/MAPbI3/[6,6]-phenyl-C61-butyric acid methyl ester/BCP:PMMA or BCP:PVP/Ag. The presence of PMMA and PVP affected the morphological stability of the BCP and MAPbI3 layers. The storage-stability of the BCP/PMMA-based PVSCs was enhanced significantly relative to that of the corresponding unmodified BCP-based PVSC. Moreover, the PV performance of the BCP/PVP-based PVSCs was enhanced when compared with that of the unmodified BCP-based PVSC. Thus, incorporating hydrophobic polymers into BCP-based hole-blocking/electron-transporting interfacial layers can improve the PV performance and storage stability of PVSCs.

In roll-to-roll (R2R) processing, uniformity of the web is a crucial factor that can guarantee high coating quality. To understand web defects due to thermal deformation, we analyzed the effects of web unevenness on the coating quality of an yttria-stabilized zirconia (YSZ) layer, a brittle electrolyte of solid oxide fuel cells (SOFCs). We used finite element analysis to analyze the thermal and mechanical deformations at different drying temperatures. A YSZ layer was also coated using R2R slot-die coating to observe effects of web unevenness on the coating quality. It was seen that web unevenness was generated by thermal deformation due the conduction and convection heat from the dryer. Owing to varying web unevenness with time, the YSZ layer developed cracks. At higher drying temperatures, more coating defects having larger widths were generated. Results indicated that web unevenness at the coating section led to coating defects, which could damage the SOFC and decrease its yield in the R2R process. From this study, we suggest that coating defects, generated by the web unevenness owing to the convection and conduction heat, should be considered for the high-volume production of brittle electrolytes using the R2R process.

Height assignment is an important problem for satellite measurements of Atmospheric Motion Vectors (AMVs) that are interpreted as winds by forecast and assimilation systems. Stereo methods assign heights to AMVs from the parallax observed between observations from different vantage points in orbit while tracking cloud or moisture features. In this paper, we fully develop the stereo method to jointly retrieve wind vectors with their geometric heights from geostationary satellite pairs. Synchronization of observations between observing systems is not required. NASA and NOAA stereo-winds codes have implemented this method and we have processed large datasets from GOES-16, -17, and Himawari-8. Our retrievals are validated against rawinsonde observations and demonstrate the potential to improve forecast skill. Stereo winds also offer an important mitigation for the loop heat pipe anomaly on GOES-17 during times when warm focal plane temperatures cause infra-red channels that are needed for operational height assignments to fail. We also examine several application areas, including deep convection in tropical cyclones, planetary boundary layer dynamics, and fire smoke plumes, where stereo methods provide insights into atmospheric processes. The stereo method is broadly applicable across the geostationary ring where systems offering similar Image Navigation and Registration (INR) performance as GOES-R are deployed.

Traditional potential transformers have problems of large volume, difficulty in insulation, iron core saturation, ferroresonance overvoltage and poor transient response characteristics. The voltage sensor based on the principle of electric field coupling and differential input structure does not need to contact the measured object or ground, and can avoid the above problems. However, it requires a sufficiently high capacitance between the differential electrodes to obtain sufficient accuracy and a high voltage division ratio. The existing method of using mutual capacitance between the differential electrodes will cause many problems and fail to meet the practical needs. To solve the above problems, this paper innovatively uses multi-layer ceramic capacitor to replace the mutual capacitance and designs a new type of voltage sensor. In addition, by using single bypass small resistance grounding method to increase the input impedance of the differential signal processing circuit, error of the sensor is further reduced. The experimental results show that the sensor has excellent accuracy and great transient response characteristics. The ratio error under power frequency is within ±0.5% and the phase error is within 1. The ratio error in the range of 500 Hz∼30 kHz is within ±5% and the phase error is within 5. Moreover, it has the advantages of low cost, miniaturization, flexible shape and easy to adjust the voltage division ratio. These characteristics indicate that the sensor has good voltage measurement and sensor network potential.

The human mind is multimodal. Yet most behavioral studies rely on century-old measures of behavior—task accuracy and latency (response time). Multimodal and multisensory analysis of human behavior creates a better understanding of how the mind works. The problem is that designing and implementing these experiments is technically complex and costly. This paper introduces versatile and economical means of developing multimodal-multisensory human experiments. We provide an experimental design framework that automatically integrates and synchronizes measures including electroencephalogram (EEG), galvanic skin response (GSR), eye-tracking, virtual reality (VR), body movement, mouse/cursor motion and response time. Unlike proprietary systems (e.g., iMotions), our system is free and open-source; it integrates PsychoPy, Unity and Lab Streaming Layer (LSL). The system embeds LSL inside PsychoPy/Unity for the synchronization of multiple sensory signals—gaze motion, electroencephalogram (EEG), galvanic skin response (GSR), mouse/cursor movement, and body motion—with low-cost consumer-grade devices in a simple behavioral task designed by PsychoPy and a virtual reality environment designed by Unity. This tutorial shows a step-by-step process by which a complex multimodal-multisensory experiment can be designed and implemented in a few hours. When conducting the experiment, all of the data synchronization and recoding of the data to disk will be done automatically.

A solution for the Prandtl-Blasius equation is essential to all kinds of boundary layer problems. This paper revisits this classic problem and presents a general Maple code as its numerical solution. The solutions were obtained from the Maple code, using the Runge-Kutta method. The study also considers convergence radius expanding and an approximate analytic solution is proposed by curve fitting. Similarly, the study resolves some boundary layer related problems and provide relevant Maple codes for these.

Whether there is any inclination between structures and functions of antimicrobial peptides (AMPs) is a mystery yet to be unraveled. AMPs have various structures associated with many different antimicrobial functions, including antibacterial, anticancer, antifungal, antiparasitic and antiviral activities. However, none has yet reported any antimicrobial functional tendency within a specific category of protein/peptide structures nor any structural tendency of a specific antimicrobial function with respect to AMPs. Here we examine the relationships between structures categorized by three structural classification methods (CATH, SCOP and TM) and seven antimicrobial functions with respect to AMPs using an enrichment analysis. The results show that antifungal activities of AMPs were tightly related to two-layer sandwich structure of CATH, knottin fold of SCOP, and the first structural cluster of TM. The associations with knottin and TM cluster 1 even sustained through the AMPs with a low sequence identity. Besides, another significant mutual enrichment was observed between the third cluster of TM and anti-gram-positive-bacterial/anti-gram-negative-bacterial activities. The findings of the structure-function inclination further our understanding of AMPs and could help us design or discover new therapeutic potential AMPs.

Climate change and rapid urbanization are adversely affecting the urban environment by exacerbating the widely reported Urban Heat Island effect in Dhaka, Bangladesh. Two wetland areas with variable riparian shadings in the warm-humid conditions of urban Dhaka had been investigated through field campaigns on microclimatic parameters for their cooling potential on the surrounding urban fabric. It was observed that an inversion layer of fully saturated air develops over the water surface of wetland, suppressing evaporation from the wetland water surface layer, which was effectively reducing the heat exchange between the water surface and the air layer above it through its action as an insulating vapor blanket. Because of this effect, the wetland was unable to render as a source of coolth for the surrounding overheated urban area. This effect of the inversion layer was more pronounced in the urban wetland without riparian shading either by urban form or tree canopy. A Multiphysics simulation study conducted on the selected urban wetlands indicates the effect of differential shading pattern on the relation between fetch and inversion layer thickness. This research hypothesizes that the wetland can act as an urban adaption measure against the urban heat island effect by potentially transforming them into Urban Cooling Island (UCI) towards a favorable urban bioclimate.

The most extensive urban growths in the next 30 years are expected to occur in developing countries. Lagos, Nigeria - Africa’s second most populous megacity- is a prime example. To achieve more sustainable and resilient cities, there is a need for modeling the urban growth patterns of major cities and analyzing their implications. In this study, the urban growth of Lagos state was modeled using the Multi-Layer Perceptron (MLP) neural network for the transition modeling and the Markov Chain analysis for the change prediction, achieving a model accuracy of 81.8%. An innovative visual validation of the model results using the ArcGIS was combined with kappa correlation statistics. The results show that by 2031, built-up areas will be the most spatially extensive LULC class in the study area with percentage coverage of 34.1% as opposed to 9% in 1986. The coverage of bare areas is also expected to increase by 53% between 2016 and 2031. Conversely, 24.9% and 68.3% loss of forestlands and wetlands respectively, are expected between 2016 and 2031. In view of the 11^th goal of SDGs which focuses on achieving sustainable cities and communities, the objectives of African Union’s Agenda 2063, and based on the urban growth trends observed, the study recommends a prioritization of vertical expansion as opposed to the current horizontal urban growth trends in the study area.

The boundary layer height (BLH) distinguishes the interface between the lower and free atmosphere, which is a key variable in numerical simulation, aerosol, and environmental pollution studies. Thus, the goal of this work is to propose a novel method conjuncting with numerical regularization to analyze climate characteristics of the marine boundary layer height (MBLH) using 2007-2011 GPS-RO data from the COSMIC mission. While traditionally, the difference method has been used to achieve this aim, herein, we propose an innovative method, in which the bending angle profile gradient was calculated using the numerical regulation method where the regulation parameters are determined by the double-parameter model function method. Then, the MBLH was determined by employing the maximum gradient method to ascertain the height corresponding to the smallest gradient. The results show a correlation between currents and the MBLH—a relationship that has not been previously demonstrated. A low MBLH is associated with seasons and regions where cold ocean currents are prevailing; whereas a high MBLH is observed in the seasons and places where warm currents are prevailing. This correlation was validated by comparing the obtained results with different occultation data—i.e., atmprf and echprf—which also established that atmprf is more sensitive to convective cloud top capture. In seas with active convection, the armprf calculated bending angle is higher than that from echprf. Subsequently, the standard deviation was used to express the MBLH confidence level. The results show that the MBLH standard deviation is highest in low latitudes and lowest in the middle and high latitudes. Furthermore, we analyzed the interannual MBLH variation trend, which displayed a seasonal variation and spatial distribution corresponding with the current and subsolar point. Finally, we conducted a case study in the South China Sea, and identified a distinctive seasonal change and downward trend.

The stele concept is one of the oldest enduring concepts in plant biology. This paper reviews the concept and its foundations, and builds an argument for an updated view of steles and their evolution. The history of studies of stelar organization has generated a widely ranging array of definitions of the stele that determine the way we classify steles and construct scenarios about the evolution of stelar architecture. Because at the level of the organism biological evolution proceeds by, and is reflected in, changes in development, concepts of structure need to be grounded in development in order to be relevant in an evolutionary perspective. For the stele, most of the traditional definitions that incorporate development have viewed it as the totality of tissues that either originate from procambium – currently the prevailing view – or are bordered by a boundary layer (e.g., endodermis). A definition of the stele that would bring consensus between these perspectives recasts the stele as a structural entity of dual nature. Here, I review briefly the history of the stele concept, basic terminology related to stelar organization, and traditional classifications of the steles. I then revisit boundary layers from the perspective of histogenesis as a dynamic mosaic of developmental domains. I use classic and recent anatomical and molecular data to reaffirm and explore the importance of boundary layers for stelar organization. Drawing on data from comparative anatomy, developmental regulation, and the fossil record, I offer a model for a stele concept that integrates both the boundary layer and the procambial perspective, consistent with a dual nature of the stele. The dual stele model posits that stelar architecture is determined in the apical meristem by two major cell fate specification events: a first one that specifies a provascular domain and its boundaries, and a second event that specifies a procambial domain (which will mature into conducting tissues) from cell subpopulations of the provascular domain. If the position and extent of the developmental domains defined by the two events are determined by different concentrations of the same morphogen (most likely auxin), then the distribution of this organizer factor in the shoot apical meristem, as modulated by changes in axis size and the effect of lateral organs, can explain the different stelar configurations documented among tracheophytes. This model provides a set of working hypotheses that incorporate assumptions and generate implications that can be tested empirically. The model also offers criteria for an updated classification of steles that is in line with current understanding of plant development. In this classification, steles fall into two major categories determined by the configuration of boundary layers – boundary protosteles and boundary siphonosteles, each with subtypes defined by the architecture of the vascular tissues. Validation the dual stele model and, more generally, in-depth understanding of the regulation of stelar architecture, will necessitate targeted efforts in two areas: (i) the regulation of procambium, vascular tissue, and boundary layer specification in all extant vascular plants, considering that most of the diversity in stelar architecture is hosted by seed-free plants, which are the least explored in terms of developmental regulation; (ii) the configuration of vascular tissues and, especially, boundary layers, in as many extinct species and lineages as possible.

The famous Toms effect (1948) consists of a substantial increase of the critical Reynolds number when a small amount of soluble polymer is introduced into water. The most noticeable influence of polymer additives is manifested in the boundary layer near solid surfaces. The goal of the present paper is a group analysis of the boundary layer equations in two mathematical models of the flow of aqueous polymer solutions: the second grade fluid (Rivlin and Ericksen, 1955) and the model derived by Pavlovskii (1971). The equations of the unsteady two-dimensional boundary layer in the Pavlovskii and Rivlin-Ericksen models are analyzed for the first time here. These equations have no definite type so that finding their exact solutions is very important in order to understand the mathematical nature of the above mentioned models. The problem of group classification with respect to the arbitrary function of the longitudinal coordinate and time present in the equations, which sets the pressure gradient of the external flow, arises. All functions for which an extension of the admitted Lie group occurs are found. The task includes the ratio of two characteristic length scales. One of them is the Prandtl scale, and another is defined as the square root of the normalized coefficient of relaxation viscosity (Frolovskaya and Pukhnachev, 2018) and does not depend on the characteristics of the motion. The paper contains a number of exact solutions in the Pavlovskii model including a solution describing the flow near a critical point. Among the solutions of the new model of the boundary layer, a special place is taken by the solution of the stationary problem of flow around a rectilinear plate. Within the framework of the Prandtl theory of the boundary layer, such a solution was constructed by Blasius (1908). As is well-known, this solution has a non-removable defect: the transverse velocity near the edge of the plate increases without bound. The introduction of a relaxation term into the model makes it possible to eliminate this singularity.

Construction and demolition waste (CDW) represents 1/3 of the weight of all-waste produced. Increasing their recycling and reutilization with recycled aggregates (RA) means closing the life cycle of construction materials. Research has been carried out on artificial aggregates from the exclusive crushing of structural concrete waste in selective demolitions (CDWRConc). This study analyses the use of recycled concrete as graded aggregate (GARConc) and in cement soil (CSRConc). The material complies with the requirements as a road base, although due to the low values of resistance to fragmentation these materials are adequate for use in sensitive road systems and other places such as urban roads and car parks. The sensitive road systems are infrastructures in places of great natural wealth and low traffic intensity, with an annual average of heavy vehicle traffic (AADTh) below 50 vhp/d. As soluble salt contents have been detected, additional waterproofing or drainage measures must be adopted to prevent water infiltration into the layers made up of CDWRHorm. Finally, the high initial values of UCS allow the temporary passage of light vehicles over CSRConc after 3 days.

Studies on the detection of layers with elevated black carbon aerosol (BC) concentrations and the formation conditions of these layers help understand the vertical distribution of BC concentrations, which will provide a basis for the assessment of climate effects and early BC pollution warnings. By using the Weather Research and Forecasting with Chemistry (WRF-Chem) numerical model, we performed a numerical simulation analysis on the authenticity of strong elevated BC concentration layers that were detected by an aircraft in the mixing layer over Harbin, China, which is a high-emission area, on a clear sunny afternoon in the early heating period of 2016. We then discuss possible problems and solutions when non-vertical paths are used to detect the vertical distribution of BC concentrations. Finally, we discuss the favorable conditions for the formation of elevated BC concentration layers by weak vertical flow. The results show that the horizontal variability of BC concentration in the mixing layer in the observation area in Harbin was sufficiently large during the measurement. This produced a false elevated layer, as detected by the aircraft during one round of spiral flight in the mixing layer. The root mean square of the horizontal distribution of BC concentration did not change with height in the mixing layer during the daytime, but it decreased with the thickness of the mixing layer and was higher in the mixing layer than in the free atmosphere. Therefore, the thinner the mixing layer, in which the vertical distribution of the BC concentration is detected in an inclined path, the stronger interference of the horizontal variability on the detected results. When a spiral flight detection path is used, the aircraft should fly at least two rounds in the mixing layer. In the daytime, due to strong turbulence in the mixing layer, weak vertical uplift is not favorable for the occurrence of elevated BC concentration layers in the mixing layer. In the nighttime, if weak vertical uplift is well matched with the BC concentration or its vertical gradient, elevated BC concentration layers can be formed in the atmosphere. Compared with upper layers far from the ground, nighttime elevated layers are easier to form in lower layers near the ground because high BC concentrations or large vertical gradients are more likely to occur in the lower layers. Both cases facilitate the occurrence of large vertical upward transport rates of BC.

Through the Internet of Things (IoT) the internet scope is established by the aid of physical objects integration to classify themselves to mutual things. A physical object can be created by this inventive perception to signify itself in the digital world. Regarding the physical objects that are related to the internet, it is worth to mention that considering numerous theories and upcoming predictions, they mostly require protected structures, moreover, they are at risk of several attacks. IoTs are endangered by particular routing disobedience called physical layer attack owing to their distributed features. The physical layer attack as a security warning makes possible for the invader to abuse the resources and bandwidth of the network through overloading the network via unimportant packets. This protocol is called LSFA-IoT consisting of two key sections of the physical layer detection system and misbehavior detection system. The first section is utilized in stabilizing the status of the network. The second section is in charge of discovering the misbehavior sources within the IoT network through , the Average Packet Transmission RREQ. By detecting a malicious node, the status of the node is checked by LSFA-IoT prior to sending a data packet and in case detecting the node as malicious, no packet is sent to that node and that node is added to the detention list. Here, the technique is assessed through wide simulations performed within the NS-3 environment. Based on the results of the simulation, it is indicated that the IoT network behaviour metrics are enhanced based on the detection rate, false-negative rate, false-positive rate, and packet delivery rate.

The surface enhanced fluorescence（SEF）detection bases by plasmonic nanopillars array with nanoparticles has opened up a new gate in the application of biological imaging and sensing. The fluorescence enhancement of the probe molecule depends on its position in equilibrium, which is close to the hot spot leading to the electromagnetic field enhancement, but not too close to the metal surface resulting in quenching. Here, a large scale SiO₂-Ag-cicada wing SEF substrate was fabricated by magnetron sputtering with correction enhancement factor of 797.6. Thereinto the cicada wing provides the skeleton of the nanopillars array structure, the deposited Ag constructs two kinds of hot spots, and SiO₂ forms a separation layer to prevent quenching. Moreover, the substrate exhibited good reproducibility, high sensitivity with low limits of detection (LOD) and high stability for oxidation resistance. We propose that SEF substrate with modification of SiO₂ can not only improve the enhancement performance, but also expanding its application in the biological investigations.