Bioactive surface coatings have retained the attention of researchers and physicians due to their versatility and range of applications in orthopedics, particularly in infection prevention. Antibacterial metal nanoparticles (mNPs) are a promising therapeutic, with vast application opportunities on orthopedic implants. The current research aimed to construct a polyelectrolyte multilayer on a highly porous titanium implant using alternating thin film coatings of chitosan and alginate via the layer-by-layer (LbL) self-assembly technique, along with the incorporation of silver nanoparticles (AgNPs) or titanium dioxide nanoparticles (TiO2NPs), for antibacterial and osteoconductive activity. These mNPs were characterized for their physicochemical properties using quartz crystal microgravimetry with dissipation system, nanoparticle tracking analysis, scanning electron microscopy, and atomic force microscopy. Their cytotoxicity and osteogenic differentiation capabilities were assessed by AlamarBlue and alkaline phosphatase (ALP) activity assays, respectively. The antibiofilm efficacy of the mNPs tested against Staphylococcus aureus. The LbL polyelectrolyte coating was successfully applied to the porous titanium substrate. A dose-dependent relationship between nanoparticle concentration and ALP as well as antibacterial effects was observed. TiO2NP samples were also less cytotoxic than AgNP counterparts, although similarly antimicrobial. Together, these data serve as a proof-of-concept for a novel coating approach for orthopedic implants with antimicrobial and osteoconductive properties.

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.

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.

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.

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.

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 optimized design of catalyst layer (CL) plays a vital role to improve the performance of polymer electrolyte membrane fuel cells (PEMFCs). The need to improve transport and catalyst activity is especially important at low Pt loading, where local oxygen and ionic transport resistances decrease the performance due to an inevitable reduction of active catalyst sites. In this work, local oxygen and ionic transport are analyzed using direct numerical simulation on virtually reconstructed microstructures. Four morphologies are examined: (i) heterogeneous, (ii) uniform, (iii) uniform vertically-aligned, and (iv) meso-porous ionomer distributions. The results show that the local oxygen transport resistance can be significantly reduced, while maintaining good ionic conductivity, through the design of high porosity CLs (ε≃0.6−0.7) with low agglomerated ionomer morphologies. Ionomer coalescence into thick films can be effectively mitigated by increasing the uniformity of thin films and reducing the tortuosity of ionomer distribution (e.g., good ionomer interconnection in supports with a vertical arrangement). The local oxygen resistance can be further decreased by the use of blended ionomers with enhanced oxygen permeability and meso-porous ionomers with oxygen transport routes in both water and ionomer. In summary, achieving high performance at low Pt loading in next-generation CLs must be accomplished through a combination of high porosity, uniform and low tortuosity ionomer distribution, and oxygen transport through activated water.

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%).

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.

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.

In this paper, a further mathematical analysis of some previous results of the author’s ongoing investigation regarding Prandtl’s equations is accomplished. In particular, the objective of the present work is the performance of an approximate explicit solution to Prandtl’s system of equations for a laminar, isothermal, incompressible and steady boundary layer flow of a Newtonian fluid, over an infinite horizontal flat plate.

The deterioration of soil-cement in corrosive environment leads to the reduction of strength and the increase of permeability. Effective methods of determining deteriorated layer permeability coefficient of soil-cement are currently lacking. A laboratory test method for permeability coefficient of deteriorated layer was proposed using the modified permeability coefficient testing apparatus. According to the proposed method, the permeability coefficient of deteriorated layer can be obtained after testing the permeability coefficient of the soil-cement specimen in curing room and the equivalent permeability coefficient and deterioration depth of the soil-cement specimen in corrosion environment. Taking the marine dredger fill of Jiaozhou Bay for example, the deteriorated layer permeability coefficients of soil-cements with different cement contents were tested. It turned out that the permeability of deteriorated layer increases with the increase of age. At the beginning of curing age, larger cement content leads to smaller permeability coefficient of the deteriorated layer of soil-cement. As the curing age increases, the deteriorated layer permeability coefficient of the soil-cement with larger cement content becomes larger. The evolution of the permeability coefficient of deteriorated layer with age can be formulated as the Logistic function. This study provides a support for anti-permeability designs of soil-cement structures in corrosive environment.

Suppressing the charge recombination at the interface of photoanode/electrolyte is the crucial way to enhance the photovoltaic performance of quantum dot sensitized solar cells (QDSSCs). In this scenario, ZnS/SiO2 blocking layer was deposited on TiO2/CuInS2 QDs to inhibit the charge recombination at photoanode/electrolyte interface. As a result, the TiO2/CuInS2/ZnS/SiO2 based QDSSCs delivers a power conversion efficiency (η) value of 4.63%, which is significantly higher than the 2.15% and 3.23% observed for QDSSCs with a TiO2/CuInS2 device and TiO2/CuInS2/ZnS, respectively. Electrochemical impedance spectroscopy and open circuit voltage decay analyses indicate that ZnS/SiO2 passivation layer on TiO2/CuInS2 suppress the charge recombination at the photoanode/electrolyte interface and prolongs the electron lifetime.

Ventilation in cities is crucial for the well being of their inhabitants. Therefore, local governments require air ventilation assessments (AVAs) prior to the construction of new buildings. In a standard AVA, however, only neutral stratification is considered, although diabatic and particularly unstable conditions may be observed more frequently in nature. The results presented here indicate significant changes in ventilation within most of the area of Kowloon City, Hong Kong, included in the study. A new definition for calculating ventilation was introduced, and used to compare the influence of buildings on ventilation under conditions of neutral and unstable stratification. The overall ventilation increased due to enhanced vertical mixing. In the vicinity of exposed buildings, however, ventilation was weaker for unstable stratification than for neutral stratification. The influence on ventilation by building parameters, such as the plan area index, was altered when unstable stratification was considered. Consequently, differences in stratification were shown to have marked effects on ventilation estimates, which should be taken into consideration in future AVAs.

The paper proposes TOPSIS method for solving multi-objective multi-level programming problem (MO-MLPP) with fuzzy parameters via fuzzy goal programming (FGP). At first, - cut method is used to transform the fuzzily described MO-MLPP into deterministic MO-MLPP. Then, for specific , we construct the membership functions of distance functions from positive ideal solution (PIS) and negative ideal solution (NIS) of all level decision makers (DMs). Thereafter, FGP based multi-objective decision model is established for each level DM for obtaining individual optimal solution. A possible relaxation on decisions for all DMs is taken into account for satisfactory solution. Subsequently, two FGP models are developed and compromise optimal solutions are found by minimizing the sum of negative deviational variables. To recognize the better compromise optimal solution, the concept of distance functions is utilized. Finally, a novel algorithm for MO-MLPP involving fuzzy parameters is provided and an illustrative example is solved to verify the proposed procedure.

We develop an interactive likelihood (ILH) for sequential Monte-Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, AFL, and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (OSPA and CLEAR MOT). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

New TLC-densitometric method have been developed for the identification and quantification of paracetamol (PA), propyphenazone (PP) and caffeine (C) of Saridon tablets using the NP-TLC technique combined with densitometry. This method allows for the simultaneous determination of PA, PP, and C in the same sample. Among all tested chromatographic conditions, the mixture consisting of chloroform + toluene + ethyl acetate + ethanol + acetic acid (18:18:7.5:5.0:0.3, v/v) and silica gel 60F254 plate proved to be the most effective for the separation of three tested active pharmaceutical ingredients (APIs) and substances related to paracetamol. The fully validation of the proposed NP-TLC method proves that it is specific, precise, accurate, robust and sensitive. The percentage content in relation to the content declared by the manufacturer is for propyphenazone 99.8%, paracetamol 101.6% and caffeine 100.8%, which are in accordance with pharmacopoeial requirements. The results presented indicate the possibility of using the developed method in the routine control of pharmaceutical preparations containing these APIs. The proposed method is economical and more sensitive compared to the previously proposed planar methods for the simultaneously determination of PA, PP and CAPIs. Will be an What is more, the presented method may be anaxcellent excellent economical alternative when HPLC method is unavailable for such determination.

Several chemistry-climate models (CCM) underestimate the total column ozone (TCO) over the polar region in the Southern Hemisphere during wintertime. To evaluate potential causes of the problem, we exploit CCM SOCOLv3 to study the TCO over Antarctica sensitivity to the: (1) photo-dissociation rates of ozone for large solar zenith angles; (2) rates of the stratospheric heterogeneous reactions, and (3) intensity of the meridional flux into the polar regions due to sub-grid scale mixing processes in the model. Comparisons of the model results with the satellite-based IASI (Infrared Atmospheric Sounder Interferometer) sensor measurements showed that the most important processes for the improvement of the polar ozone simulation results are photolysis and horizontal mixing. The reasonable tuning of these factors has allowed us to improve the model representation of the ozone annual cycle over the southern polar region. The proposed increase of the horizontal mixing can be recommended for the CCMs with relatively low horizontal resolution.

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.

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

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.

During the long-term operation of the plasma reactor, decreases in the plasma concentration were noticed despite the constant maintenance of all parameters. One of the factors is the decrease of the nitrogen content on the surface of the electrode, in order to eliminate it, the supply voltage has been increased to 11 kV. The next decisive factor in the decrease of plasma concentration is the oxidation of the electrode surface, therefore two electrodes were used: first one with solid gold and the other one copper covered with galvanized gold with a thickness of 10 μm. During the experiment, a large decrease in plasma concentration was observed when the electrode coated by gold was used. High-energy electrons have knocked out the gold atoms from the electrode, as a result of which the gold evaporated and the raids layers formed. After a month of working of the electrodes, metallographic researches were carried out, the results of which are described in this publication.

Knowledge about laminar-turbulent transition on operating multi-megawatt wind turbine blades needs sophisticated equipment like hot-films or microphone arrays. Contrarily thermographic pictures can easily be taken from the ground and temperature differences indicate different states of the boundary layer. The accuracy however, still is an open question, so that an aerodynamic glove known from experimental research on aero-planes was used to classify the boundary-layer state of a 2 megawatt wind turbine blade operating in the orthern part of Schleswig-Holstein, Germany. State-of-the-art equipment for measurering static surface pressure was used for monitoring the lift distribution. To distinguish laminar and turbulent parts of the boundary layer (suction side only) 48 microphones were applied together with ground-based thermographic cameras from two teams. Additionally, an optical camera mounted on the hub was used to survey vibrations. During start-up (from 0 to 9 rpm) extended, but irregularly shaped regions of a laminar boundary layer were observed which had the same extension measured both with microphones and Thermography. When an approximately constant rotor rotation (9 rpm corresponding to approximately 6 m/s wind-speed) was achieved, a flow transition was visible at the expected position of 40 % chord length on the rotor blade, which was fouled with dense turbulent wedges and an almost complete turbulent state on the glove was detected. In all observations, quantitative determination of the flow transition positions from thermography and microphones agree well within their accuracy.

Carburizing of stainless steels at low temperatures (below 500°C) develops a high content carbon layer, known for its high hardness. X-ray Diffraction investigation indicates that carburization treatment does not impact the structure of substrate; however, introduced carbon causes expansion in the carburized layer through the increase in d-spacing. Characterization of carbon concentration and hardness profiles indicate that carbon content gradually decreases while moving further into the substrate; and the origin of the increased hardness of the expanded layer arises from the super-saturated carbon content, following the solid solution strengthening theory. An area that is not well understood is in regard to the carburized layer’s relation to the substrate and the significance in their differences. Using two grades of stainless steel, AISI 316L and PH 17-4, it was observed that the carburized layer is not a separate layer, but a higher carbon content version of the substrate,

In this study organic bulk heterojunction (BHJ) solar cell along with the spiro OMeTAD as a hole transport layer (HTL) and the PDINO as an electron transport layer (ETL) was simulated through the Solar Capacitance Simulator, one dimensional (SCAPS-1D) software to examine the performance of this type of polymer thin film organic solar cells. As an active layer the blend of polymer donor PBDB-T and non-fullerene acceptor ITIC-OE was used. Numerical simulation was performed by varying the thickness of HTL and active layer. Firstly, the HTL layer thickness was optimized to 50 nm, after that the active layer thickness varied up to 80 nm. These results of simulation demonstrated that the HTL thickness has rather little impact on efficiency while in the case of active layer thickness improves efficiency significantly. The temperature effect on the performance of solar cells was considered, by the simulation performed for temperature from 300 K up to 400 K and the efficiency of solar cell decreases with increasing temperature. Generally, polymer films usually are full of traps and defects, the density of defects (Nt) value was also introduced to the simulation, and it was confirmed that with the increasing of defect density (Nt), the efficiency of solar cell decreases. After thickness, temperature and defect density optimization, the reflection coating was also applied on it. It turned out that by introducing the reflection coating on the back side of solar cell, the efficiency increases by 2.5 %. Additionally, the positive effect of HTL and ETL doping on efficiency of this type of solar cells was demonstrated.

Large-scale crowd phenomena are complex to model because the behaviour of pedestrians needs to be described at both strategic, tactical, and operational levels and is impacted by the density of the crowd. Microscopic models manage to mimic the dynamics at low densities, whereas mesoscopic models achieve better performances in dense situations. This paper proposes and evaluates a novel agent-based architecture to enable agents to dynamically change their operational model based on local density. The ability to combine microscopic and mesoscopic models for multi-scale simulation is studied through a use case of pedestrians at the Festival of Lights, Lyon, France. Pedestrian outflow data is extracted from video recordings of exiting crowds at the festival. The hybrid model is calibrated and validated using a genetic algorithm that optimizes the match between simulated and observed outflow data. Additionally, a local sensitivity analysis is then conducted to identify the most sensitive parameters in the model. Finally, the performance of the hybrid model is compared to different models in terms of density map and computation time. The results demonstrate that the hybrid model has the capacity to effectively simulate pedestrians across varied density scenarios while optimizing computational performance compared to other models.

One of the most important applications in the wireless sensor networks (WSN) is to classify mobile targets in the monitoring area. In this paper, a multi-DBN weighted voting classification algorithm is proposed on the basis of the Deep Belief Network (DBN) classifier and combined with the idea of voting method, which is implemented on the nodes of the WSN monitoring system by means of "upper training, lower transplantation" appraoch. The performance of the algorithm is verified by using real-world experimental data, and the results show that the proposed method has a higher accuracy in classifying the target signal features, achieving an average classification accuracy of 84.63% across four different types of moving targets. The experiment reveals that the multi-DBN weighted voting algorithm enhances the target classification accuracy by approximately 5% in comparison to the single DBN classifier, but the memory and computation time required for the algorithm to run are also increased at the same time. Compared to the FFNN classifier, which exhibited the highest classification accuracy among the four selected methods, the algorithm achieves an improvement of approximately 8.8% in classification accuracy. However, it incurs greater time overhead to run.

Unmanned Aerial Vehicles (UAVs) image object detection has great application value in military and civilian fields. However, the objects in the captured images from UAVs have problems of large scale variation, complex backgrounds, and a large proportion of small objects. To resolve these problems, a multi-scale object detector based on coordinate and global information aggregation is proposed, named CGMDet. Firstly, a Coordinate and Global Information Aggregation Module (CGAM) is designed by aggregating local, coordinate, and global information, which can obtain features with richer context information. Secondly, a Multi-Feature Fusion Pyramid Network (MF-FPN) is proposed, which can better fuse features of different scales and obtain features containing more context information through repeated use of feature maps, to better detect multi-scale targets. Moreover, more location information of low-level feature maps is integrated to improve the detection results of small targets. Furthermore, we modified the bounding box regression loss of the model to make the model more accurately regress the bounding box and faster convergence. Finally, the proposed CGMDet was tested on VisDrone and UAVDT datasets and mAP0.5 of 50.9% and 48% was obtained, respectively. At the same time, our detector achieved the best results compared to other detectors.

Rapid assessment of maize yields in smallholder farming system is important to understand its spatial and temporal variability and for timely agronomic decision-support. Imageries acquired with unmanned air vehicles (UAV) offer opportunity to assess agronomic variables at field scale, however, it is not clear if this can be translated into reliable yield assessment on smallholder farms where field conditions, maize genotypes, and management practices vary within short distances. In this study, we assessed the predictability of maize grain yield using UAV-derived vegetation indices (VI), with(out) biophysical variables, in smallholder farms. High-resolution images were acquired with UAV-borne multispectral sensor at 4 and 8 weeks after sowing (WAS) on 31 farmers’ managed fields (FMFs) and 12 nearby Nutrient Omission Trials (NOT), all distributed across 5 locations within the core maize region of Nigeria. The NOTs included non-fertilized and fertilized plots (with and without micronutrients), sown with open-pollinated or hybrid maize genotypes. Acquired multispectral images were post-processed into several three (s) vegetation indices (VIs), normalized difference vegetation index (NDVI), normalized difference red-edge (NDRE), green-normalized difference vegetation index (GNDVI). Biophysical variables, plant height (Ht) and percent canopy cover (CC), were measured with the georeferenced plot locations recorded. In the NOTs, the nutrient status, not genotype, influenced the grain yield variability and outcome. The maximum grain yield observed in NOTs was 9.3 tha^-1, compared to 5.4 tha^-1 in FMF. Without accounting for between- and within-field variations, there was no relationship between UAV-derived VIs and grain yield at 4WAS (r<0.02, P>0.1), but significant correlations were observed at 8WAS (r≤0.3; p<0.001). Ht was positively correlated with grain yield at 4WAS (r=0.5, R²=0.25, p<0.001), and more strongly at 8WAS (r=0.7, R²=0.55, p<0.001), while relationship between CC and yield was only significant at 8WAS. By accounting for within- and between-field variations in NOTs and FMF (separately) through linear mixed-effects modeling, predictability of grain yield from UAV-derived VIs was generally (R²≤0.24), however, the inclusion of ground-measured biophysical variable (mainly Ht) improved the explained yield variability (R² ≥0.62, RMSEP≤0.35) in NOTs but not in FMF. We conclude that yield prediction with UAV-acquired imageries (before harvest) is more reliable under controlled experimental conditions (NOTs), than in actual farmer-managed fields where various confounding agronomic factors can amplify noise-signal within the vegetation canopy.

In this work, we show that a late fusion approach to multi-modality in sign language recognition improves the overall ability of the model in comparison to the singular approaches of Computer Vision (88.14%) and Leap Motion data classification (72.73%). With a large synchronous dataset of 18 BSL gestures collected from multiple subjects, two deep neural networks are benchmarked and compared to derive a best topology for each. The Vision model is implemented by a CNN and optimised MLP and the Leap Motion model is implemented by an evolutionary optimised deep MLP topology search. Next, the two best networks are fused for synchronised processing which results in a better overall result (94.44%) since complementary features are learnt in addition to the original task. The hypothesis is further supported by application of the three models to a set of completely unseen data where a multi-modality approach achieves the best results relative to the single sensor method. When transfer learning with the weights trained via BSL, all three models outperform standard random weight distribution when classifying ASL, and the best model overall for ASL classification was the transfer learning multi-modality approach which scored 82.55% accuracy.

An increased demand for natural products nowadays most specifically probiotics (PRO) is evident since it comes in conjunction with beneficial health effects for the consumers. In this regard, it is well known that encapsulation could affect positively the PRO's viability throughout food manufacturing and long-term storage. This paper aims to analyze and review various multilayer strategies for encapsulation of PRO. Double-layer encapsulation of PRO by electro-hydrodynamic atomization or electrospray technology has been reported along with layer-by-layer assembly and water-in-oil-in-water (W1/O/W2) double emulsions to produce multilayer PRO-loaded carriers. Finally, their applications in food products are presented. The resistance (cover material) and viability of (PRO) to mechanical damage, during gastrointestinal transit and shelf life of these trapping systems are also described. The PRO encapsulation in double and multiple-layer coatings combined with other technologies can be examined to increase the opportunities for new functional products with amended functionalities opening a novel horizon in food technology.

Opportunistic networks, an evolution of mobile Ad Hoc networks (MANETs), offer decentralized communication without relying on preinstalled infrastructure, enabling nodes to route packets through different mobile nodes dynamically. However, due to the absence of complete paths and rapidly changing connectivity, routing in opportunistic networks presents unique challenges. This paper proposes a novel probabilistic routing model for opportunistic networks, leveraging nodes' meeting probabilities to route packets towards their destinations. The model dynamically builds routes based on the likelihood of encountering the destination node, considering factors such as last meeting time and acknowledgment tables to manage network overload. Additionally, an efficient message detection scheme is introduced to alleviate high overhead by selectively deleting messages from buffers during congestion. Furthermore, the proposed model incorporates cross-layer optimization techniques, integrating optimization strategies across multiple protocol layers to maximize energy efficiency, adaptability, and message delivery reliability. Through extensive simulations, the effectiveness of the proposed model is demonstrated, showing improved message delivery probability while maintaining reasonable overhead and latency. This research contributes to the advancement of opportunistic networks, particularly in enhancing connectivity and efficiency for Internet of Things (IoT) applications deployed in challenging environments.

The ocean’s mixed layer depth (MLD) plays an important role in understanding climate dynamics, especially during extreme weather occurrences like hurricanes. This study investigates the effects of Hurricane Katrina (2005) on the MLD in the Gulf of Mexico, using the Delft3D modeling system. By integrating hydrodynamics and wave dynamics modules, we simulate the ocean’s response to extreme weather, focusing on temperature, salinity and MLD variations. Our analysis reveals significant cooling and mixing induced by Katrina, resulting in spatial and temporal fluctuations in temperature (~± 4°C) and salinity (~± 2.5 ppt). The MLD is estimated using a simple threshold method, revealing a substantial deepening to ~120 m on August 29th-30th during Hurricane Katrina in the middle of northern Gulf of Mexico, compared to an average MLD of ~20-40 m during pre-storm conditions. It took about 18-days to recover to ~84% of the pre-storm level after Katrina. Compared to the stand-alone FLOW model, the coupled FLOW+WAVE model yields a deeper MLD of ~5%. The MLD recovery and wave effect on the MLD provide insights from various scientific, environmental and operational perspectives, offering a valuable basis for ocean management, planning and applications, particularly during extreme weather events.

This paper proposes to combat active eavesdropping by intelligent reflecting surface (IRS) backscatter techniques. To be specific, the source (Alice) sends the confidential information to the intended user (Bob), while the eavesdropper (Willie) transmits jamming signal to interrupt the transmission for more data interception. To enhance the secrecy, an IRS is deployed and connected with Alice through fiber to transform the jamming signal into the confidential signal by employing backscatter techniques. Based on the considered model, an optimization problem is formulated to maximize signal-to-interference-plus-noise ratio (SINR) at Bob under the constraints of the transmit power at Alice, the reflection vector at the IRS and the allowable maximum SINR at Willie. To address the optimization problem, an alternate optimization algorithm is developed. The simulation results verify the achievable secrecy gain of the proposed scheme.

Electroluminescence (EL) is an innovative technology in the lighting area. The EL device's main structure consists of a phosphor layer sandwiched by two electrodes. In this work, several alternating current EL devices have been developed by applying a set of sequential layers with combinations of in-house prepared inks and commercially available ink as a phosphor layer. A flexible polyester textile substrate was functionalized with inks by spray coating technique, after knife-coated an interfacial layer directly on the surface. A thorough study was carried out on the phosphor layer composition to optimize the EL device performance, more precisely the illuminance intensity and the illuminance homogeneity. The developed phosphor layer was composed of zinc sulphide doped with copper (between 30.0 to 38.1 wt%) and diluted by using a diluent at different ratios (28.0 to 35.5 wt%). The best peak illuminance intensity of 61 lux was obtained when the phosphor ink presented 35.4% ZnS:Cu and was diluted with 33.0% diluent. The aim of this study to determine the best formulation of the phosphor layer, which can be highly promising for further developments of EL devices, taking in account different applications in market.

Wearing gloves while operating machinery in workshops is an essential precaution to prevent mechanical injuries and burns from high temperatures, among other potential hazards. Ensuring workers are properly equipped with gloves, which is a crucial measure in accident prevention. Glove images often occupy a minimal proportion of the frame and are easily obscured by cluttered backgrounds, especially with limited edge computing resources. Consequently, this study proposes a glove detection algorithm called YOLOv8-AFPN-M-C2f based on YOLOv8, offering swifter detection speeds, lower computational demands, and enhanced accuracy for workshop scenarios. This research innovates by substituting the head of YOLOv8 with the AFPN-M-C2f network, amplifying the pathways for feature vector propagation, and mitigating semantic discrepancies between non-adjacent feature layers. Additionally, the introduction of a superficial feature layer enriches surface feature information, augmenting the model's sensitivity to smaller objects. To assess the performance of the YOLOv8-AFPN-M-C2f model, we conducted multiple experiments using a factory glove detection dataset compiled for this study. The results indicate that the enhanced YOLOv8 model surpasses other network models. Compared to the baseline YOLOv8 model, the refined version shows a 2.6% increase in mAP@50%, a 90.1% rise in FPS, and a 13% reduction in the number of parameters. This research contributes an effective solution for the detection of glove adherence.

Calcium sulfate (CS) materials containing terbium ions at 0, 1.0, or 2.0 mol.% were obtained by mechanochemical synthesis. According to X-ray diffraction data, the powder materials are characterized by the presence of a CaSO4×0.5H2O phase, while Tb3+ is incorporated into the lattice at ≤1.0 mol.%. Specific surface area enlarged from 2.1 to 22.5 m2/g as crystallite size decreased from 68 to 31 nm and the Tb3+ concentration increased up to 1.0 mol.%. Thermal analysis showed that terbium slightly raises the temperature of CaSO4×2H2O-to-CaSO4 transition. The presence of Tb3+ did not affect the solubility of the CS cements. Furthermore, after 7 days of soaking of the materials in a simulated body fluid, a calcium phosphate layer formed corresponding to a hydroxyapatite phase, in contrast to the pure cements. Luminescent properties were studied by excitation at 276 nm. The recorded emission peaks of the CS materials indicated that the luminescence of the samples is green and blue, with the most intense luminescence observed for samples containing 1.0 mol.% Tb3+. The developed materials can find applications in medicine as bioimplants for the regeneration and restoration of bone tissue with a possibility of noninvasive monitoring of the bone restoration process.

This study focuses on the analyses of nano-twinned Copper (Cu) films deposited through magnetron sputtering on Silicon Carbide (SiC) chips. The investigation encompasses the utilization of Chromium (Cr) adhesive layer coupled with varying voltage bias conditions. The goal is to comprehensively examine the influence of adhesive layer and negative bias voltages, contributing to an enhanced understanding of materials engineering and bonding technologies for advanced applications. The formation of a nanotwinned structure and (111) surface orientation can be properly controlled by applied substrate bias. High density nanotwinned structures were introduced into Cu films sputtered on SiC substrates with 82.3% of (111)-orientation proportion at -150 V much higher than the Cu film sputtered with another substrate bias. It is concluded that the sputtered Cu nanotwinned film formed with -150 V bias voltage has the potential to be employed as the interlayer for low temperature direct bonding.

The flow around thick airfoils at low Reynolds numbers and the possibility of using energy methods to control flowfield, increase lift and reduce drag are considered. For calculations, a series of propulsion airfoils is used, obtained by a combination of solving the inverse problem of aerodynamics and stochastic methods of global optimization. The calculations take into account the transition from the laminar flow regime to the turbulent one, which has a significant effect on the lift and airfoil drag. The applicability of various turbulence models for airfoil modelling at low Reynolds numbers is discussed. The results of numerical simulation make it possible to determine the dependence of the lift coefficient on the angle of attack and the optimal flow rate of air taken from the airfoil surface for each angle of attack. The results of numerical simulation are compared with the data of a physical experiment, and conclusions are drawn about the accuracy of various turbulence models.

Nano- and micro-sized CeO2 surface layers based on titanium alloy TiAl6V4 were obtained by magnetron sputtering with or without subsequent annealing. The structure of the samples was determined using scanning electron microscopy, Auger electron spectroscopy, energy dispersive spectroscopy, and X-ray diffraction. Hardness was measured by sclerometry. A direct linear dependence of the thickness of the surface layers on the deposition time and an extreme dependence, passing through a maximum, on the power are shown. A decrease in hardness with an increase in the thickness of the cerium oxide coating was noted. An increase in surface roughness, delamination and loosening of the surface layer, presumably associated with annealing, were noted. In samples with a surface layer thinner than 715 nm without annealing and 750 nm after annealing, the formation of a sublayer of TiO2, Al2O3, and Ce(VO4) was found, and in annealed samples with a layer length of less than 300 nm, all cerium dioxide reacted with vanadium dioxide to form vanadate.

In the past decade, considerable efforts have been devoted to the development of semitransparent organic solar cells. Numerous materials and architectures have been proposed for the future commercialization of these devices. Among these, the use of ternary active layers demonstrated a great promise for the development of efficient semi-transparent organic solar cells with the potential for future applications including self-powered greenhouses and powered windows. Researchers seek alternative solutions to the trade-off between device power conversion efficiency (PCE) and average visible transmittance (AVT), with photoactive materials being the key parameters that govern both (PCE) and (AVT) as well as device stability. Several new organic materials, including polymers and small molecules, were synthesized, and used in conjunction with a variety of techniques to achieve semitransparent conditions. In this review paper, we will look at the working principle and key parameters of semi-transparent organic solar cells, as well as the methods that have been used to improve the performance of ternary-based semi-transparent organic solar cells. The main approaches were concluded to be spectral enhancement and transparency increment of the active layer through bandgap tuning, utilizing novel organic semiconductors, and design architecture of the active layers.

Graphene nanostructures (GNS) are among the most promising materials for creating supercapacitors. However, GNS are still not used in creating supercapacitors due to the impossibility of obtaining large volumes of high-quality material at an acceptable cost. In this work, we investigated the efficiency of using few-layer graphene (FLG) with the number of layers is not more than 5 synthesized under Self-propagating high-temperature synthesis (SHS) conditions as basic material for supercapacitors. Using the SHS process makes it possible to synthesize large volumes of FLG without Stone-Wales defects. It was found that the synthesized FLG makes it possible to obtain better results than using classical materials, namely activated carbon (AC). It was found that the sample based on FLG has a higher specific capacitance – 65 F×g-1 compared to the sample from AC, the specific capacitance of which is 35 F×g-1, for a speed of 5 mV×s-1 these values are 170 and 64 F×g-1, respectively. The drop in capacitance over 1000 cycles was 4%, which indicates a sufficiently high stability of FLG and allows us to consider FLG as perspective material for use in supercapacitors.

Delayed atomic layer deposition (ALD) of ZnO, i.e., area selective (AS)-ALD, was successfully achieved on silicon wafers (Si/SiO2) terminated with tris(dimethylamino)methylsilane (TDMAMS). This resist molecule was deposited in a home-built, near atmospheric pressure, flow-through , gas-phase reactor. TDMAMS has been shown to react with Si/SiO2 in a single cycle/reaction and to drastically reduce the number of silanols that remain at the surface. ZnO was deposited in a commercial ALD system using dimethylzinc (DMZ) as the zinc precursor and H2O as the coreactant. Deposition of TDMAMS was confirmed by spectroscopic ellipsometry (SE), X-ray photoelectron spectroscopy (XPS), and wetting. ALD of ZnO, including its selectivity on TDMAMS – terminated Si/SiO2 (Si/SiO2/TDMAMS), was confirmed by in situ ellipsometry, ex situ SE, XPS, and/or high sensitivity – low energy ion scattering (HS-LEIS). The thermal stability of the TDMAMS resist layer, which is an important parameter for AS-ALD, was investigated by heating Si/SiO2/TDMAMS in air and nitrogen at 330 ºC. ALD of ZnO takes place more readily on Si/SiO2/TDMAMS heated in the air than in N2, suggesting greater damage to the surface heated in the air. To better understand the in situ ALD of ZnO, the data were also plotted as the normalized growth per cycle and to show the selectivity. Even one, short pulse of TDMAMS effectively passivates Si/SiO2. TDMAMS can be an effective small molecule inhibitor of ALD of ZnO on Si/SiO2 surfaces.

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.

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: $u^+=\frac{1}{\kappa}\ln(2\kappa {y^+} +\sqrt{1+4\kappa^2{y^+} ^2})-\frac{2{y^+} }{1+\sqrt{1+4\kappa^2{y^+} ^2}}$.

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.

A method of solution to solve the compressible unsteady 3D Navier-Stokes Equations in cylindrical co-ordinates coupled to the continuity equation in cylindrical coordinates is presented in terms of an additive solution of the three principle directions in the radial, azimuthal and z directions of flow. A dimensionless parameter is introduced whereby in the large limit case a method of solution is sought for in the boundary layer of the tube. A reduction to a single partial differential equation is possible and integral calculus methods are applied for the case of a body force directed to the centre of the tube to obtain an integral form of the Hunter-Saxton equation. Also an extension for a more general body force is shown where in addition there is a rotational force applied.

The accumulation of high levels of lead or lead ions in a human body is harmful, particularly to children. Its neurotoxic effect is profound, damaging the central and peripheral nervous systems, resulting in stunted growth, behavioral problems and learning disabilities. The major source of lead or lead ions comes from the drinking water and tap water. The assessment of the water quality, including lead or lead ion content, is usually completed by a regional water department professional. This assessment is time-consuming and requires expensive instruments and skilled operators. Therefore, there is a need to produce a simple-use and relatively inexpensive method to detect lead or lead ions in water samples. This research has developed a simple-use, cost effective sensor system for the detection of lead ions in tap water. An under-potential deposited bismuth sub-layer on a thin gold film based electrochemical sensor was designed, manufactured and evaluated. Differential pulse voltammetry (DPV) measurement technique was employed in this detection. Tap water from the Cleveland, Ohio, USA regional water district was the test medium. Concentrations of lead ion in the range of 8 X 10^-8 M to 8 x 10^-4 M were evaluated. This DPV detection system required 3 -6 minutes to complete the detection measurement. A longer measurement time of 6 minutes was used for the lower lead ion concentration. The selectivity of this lead ion sensor was very good, and Fe III, Cu II, Ni II and Mg II at a concentration level of 5×10^-4 M did not interfere with the lead ion measurement.

Urgent environmental challenges and emerging additive manufacturing (AM) technologies push research towards more performant and new materials. In the field of metallurgy, high entropy alloys (HEAs) have recently represented a topic of intense research because of their promising properties, such as high temperature strength and stability. Moreover, this class of multi-principal element alloys (MPEAs) have opened up researcher community to unexplored compositional spaces, making prosper literature of high-throughput methodologies and tools for rapidly screening large number of alloys. However, none of the methods has been aimed to design new MPEAs for AM process known as selective laser melting (SLM) so far. Here we conducted nanoindentation testing on single scan tracks of elemental powder blends and pre-alloyed powders after ball milling of AlTiCuNb and AlTiVNb. Results show that nanoindentation can represent an effective technique to gain information about phase evolution during laser scanning, contributing to accelerate the development of new MPEAs.

Smart Internet of Vehicles (IoVs) combined with Artificial Intelligence (AI) will contribute to vehicle decision-making in the Intelligent Transportation System (ITS). Multi-Vehicle Pursuit games (MVP), a multi-vehicle cooperative ability to capture mobile targets, is becoming a hot research topic gradually. Although there are some achievements in the field of MVP in the open space environment, the urban area brings complicated road structures and restricted moving spaces as challenges to the resolution of MVP games. We define an Observation-constrained MVP (OMVP) problem in this paper and propose a Transformer-based Time and Team Reinforcement Learning scheme (T3OMVP) to address the problem. First, a new multi-vehicle pursuit model is constructed based on decentralized partially observed Markov decision processes (Dec-POMDP) to instantiate this problem. Second, by introducing and modifying the transformer-based observation sequence, QMIX is redefined to adapt to the complicated road structure, restricted moving spaces and constrained observations, so as to control vehicles to pursue the target combining the vehicle’s observations. Third, a multi-intersection urban environment is built to verify the proposed scheme. Extensive experimental results demonstrate that the proposed T3OMVP scheme achieves significant improvements relative to state-of-the-art QMIX approaches by 9.66%~106.25%. Code is available at https://github.com/pipihaiziguai/T3OMVP.

Abstract: Thermal desalination is yet a reliable technology in the treatment of brackish water and seawater; however, its demanding high energy requirements have lagged it compared to other non-thermal technologies such as reverse osmosis. This review provides an outline of the development and trends of the three most commercially used thermal or phase change technologies worldwide: Multi Effect Distillation (MED), Multi Stage Flash (MSF), and Vapor Compression Distillation (VCD). First, state of water stress suffered by regions with little fresh water availability and existing desalination technologies that could become an alternative solution are shown. The most recent studies published for each commercial thermal technology are presented, focusing on optimizing the desalination process, improving efficiencies, and reducing energy demands. Then, an overview of the use of renewable energy and its potential for integration into both commercial and non-commercial desalination systems is shown. Finally, research trends and their orientation towards hybridization of technologies and use of renewable energies as a relevant alternative to the current problems of brackish water desalination are discussed. This reflective and updated review will help researchers to have a detailed state of the art of the subject and to have a starting point for their research, since current advances and trends on thermal desalination are shown.

Water area segmentation in remote sensing is of great importance for flood monitoring. To overcome some challenges in this task, we construct the Water Index and Polarization Information (WIPI) multi-modality dataset and propose a multi-Modality Fusion and Gated multi-Filter U-Net (MFGF-UNet) convolutional neural network. The WIPI dataset enhances the water information and reduces the data dimension. In particular, the Cloud-Free label provided in the database effectively mitigates the issue of scarcity of labeled samples Since a single form or uniform kernel size cannot handle the variety in size and shape of water bodies, we proposed the gated multi-filter inception (GMF-Inception) module in our MFGF-UNet. Moreover, we utilize the attention mechanism by introducing the Gated Channel Transform (GCT) skip connection and integrating GCT into GMF- Inception to further improve model performance. Extensive experiments on three benchmarks, including WIPI, Chengdu and GF2020 datasets demonstrate that our method achieves favorable performance with lower complexity and better robustness against six competing approaches. For example, on WIPI, Chengdu and GF2020 datasets, the proposed MFGF-UNet model achieves F1 of 0.9191, 0.7410, and 0.8421, respectively, which average F1 on three datasets is 0.0045 higher than the U-Net model and reduces 62% average GFLOPs. New WIPI dataset, code and trained models have been released on GitHub

Real-world optimization problems are often governed by one or more constraints. Over the last few decades, extensive research has been performed in Constrained Optimization Problems (COPs) fueled by advances in computational intelligence. In particular, Evolutionary Algorithms (EAs) are a preferred tool for practitioners for solving these COPs within practicable time limits. We propose an ensemble of multi- method hybrid EA framework with four mutation operators, two crossover operators, multi-search [Differential Evolution (DE) & Gaining Sharing Knowledge (GSK)] optimization algorithm, and ensemble of constraint handling techniques to solve global real- world constrained optimization problem. The proposed frame- work FEPEA has an ascendancy of multiple adaptation strategies concerning the control parameters, search mechanisms, two sub-populations as well as uses knowledge sharing mechanism between junior and senior phases. The algorithm also combines the power of four popular constraint handling techniques (CHT) and uses a voting mechanism to select any particular CHT. On top of that, this algorithm also uses both linear and non- linear population size reduction in every step of the evolutionary process. We test our method on 57 real-world problems provided as part of the CEC 2020 special session & competition on real- world constrained optimization benchmark suite. Experimental results indicate that FEPEA is able to achieve state-of-the- art performance on real-world constrained global optimization when compared against other well-known real-world constrained optimizers.

The hybrid bond graph has been studied in depth for scalar bond graphs, but how does this translate to the multi-bond graph? Here, the controlled junction – used to model structural switching such as contact – is extended to the multi-bond case. This is a simple process, assuming that all bonds switch simultaneously (which makes physical sense). A controlled 0-junction is applied to multi-bond graph of a car, which can lose contact with the ground in cornering. Dynamic causality features, but this can be accommodated using an equational submodel in 20-Sim (in a manner similar to that used with scalar bond graphs). The junction is proposed for subsequent work to develop a validated multi-body dynamics car model in cornering.

The quality of digital elevation models (DEMs) is inevitably affected by the limitations of the imaging modes and the generation methods. One effective way to solve this problem is to merge the available datasets through data fusion. In this paper, a fusion-based global DEM dataset (82°S-82°N) is introduced, which we refer to as GSDEM-30. This is a 30-m DEM mainly reconstructed from the unfilled SRTM1, AW3D30, and ASTER GDEM v2 datasets combining the multi-source and multi-scale fusion techniques. A comprehensive evaluation of the GSDEM-30 data, as well as the 30-m ASTER GDEM v2 and AW3D30 DEM, was presented. Global ICESat GLAS data and the local National Elevation Dataset (NED) were used as the reference for the vertical accuracy validation, while GlobeLand30 was introduced for the landscape analysis. Furthermore, we employed the maximum slope approach to detect the potential artefacts in the DEMs. The results show that the GDEM data are seriously affected by noise and artefacts. With the advantage of the multiple datasets and the refined post-processing, the GSDEM-30 are contaminated with fewer anomalies than both ASTER GDEM and AW3D30. The fusion techniques used can also be applied to the reconstruction of other fused DEM datasets.

The framework of product life cycle (PLC) cost analysis is one of the most important evaluation tools for a contemporary high-tech company in an increasingly competitive market environment. The PLC-purchasing strategy provides the framework for a procurement plan and examines the sourcing strategy of a firm. The marketing literature emphasizes that ongoing technological change and shortened life cycles are important elements in commercial organizations. From a strategic viewpoint, the vendor has an important position between supplier, buyer and manufacturer. The buyer seeks to procure the products from a set of vendors to take advantage of economies of scale and to exploit opportunities for strategic relationships. However, previous studies have seldom considered vendor selection (VS) based on PLC cost (VSPLCC) analysis. The purpose of this paper is to solve the VSPLCC problems considering the situation of a single-buyer-multiple-supplier. For this issue, a new VSPLCC procurement model and solution procedure are derived by this paper to minimize net cost, rejection rate, late delivery and PLC cost subject to vendor capacities and budget constraints. Moreover, a real case in Taiwan is provided to show how to solve the VSPLCC procurement problem.

In this paper, a new approach to the sliding-mode control of single-phase inverters under linear and non-linear loads is introduced. The main idea behind this approach is to utilize a non-linear, flexible and multi-slope function in controller structure. This non-linear function makes the controller possible to control the inverter by a non-linear multi-slope sliding surface. In general, this sliding surface has two parts with different slopes in each part and the flexibility of the sliding surface makes the multi-slope sliding-mode controller (MSSMC) possible to reduce the total harmonic distortion, to improve the tracking accuracy, and to prevent overshoots leading to undesirable transient-states in output voltage which are occurred when the load current sharply rises. In order to improve the tracking accuracy and to reduce the steady-state error, an integral term of the multi-slope function is also added to the sliding surface. The improved performance of the proposed controller is confirmed by simulations and finally, the results of the proposed approach are compared with a conventional SMC and a SRFPI controller.

Purpose: The aim of the study is an approach to a nanocomposite with copper nanoparticles, constituting a bacteriostatic surface for maintaining the human lung cells' function. Methods: The polyelectrolyte layer coating with copper nanoparticles incorporated was designed. As a bacteriostatic factor, copper nanoparticles were applied as a colloidal solution of copper nanoparticles (ColloidCuNPs) and solution of copper nanoparticles (CuNPs). The influence of polyelectrolytes on selected Gram(+) and Gram(-) strains was examined. The function of the human adenocarcinoma A549 cell line of epithelial human lung cells cultured in the presence of nanocomposite layer coatings was analyzed, as well as their morphology using flow cytometry, fluorescence microscopy, and scanning electron microscopy. In addition, the material of layer coating was assessed using AFM and SEM-EDX characterization. Results: It was observed that polyelectrolytes polyethylenimine and poly-L-lysine do not induce proliferation of E.coli strain. On the other hand, it induces the proliferation of S. aureus strain. Due to CuNPs effectiveness against E.coli strain, CuNPs were selected for further research. The designed coatings at proper NPs share sustained the function of human lung cells cultured within 10 days of culture. The AFM and EDX characterization confirmed copper presence in the layer coating nanomaterial. The presence of CuNPs in polyethyleneimine-based nanocomposite deepens the bacteriostatic effect on E. coli compared with PEI alone. Meanwhile, incorporating CuNPs in PLL at share allowed A549 cell maintenance, did not exert a bacteriostatic influence on the examined strain.Conclusion: The platform based on polyelectrolytes incorporated with copper nanoparticles ensuring the growth and morphology of the human lung epithelial cells can be considered an element of the system components for medical devices for maintaining the human lung cells' function.

The establishment of an isolation layer in submarine mining has long presented an enduring challenge. In the context of this research, we conducted a similarity simulation test to preliminarily ascertain the interplay between the thickness and extent of the isolation layer. Subsequently, we introduce an innovative approach that integrates fractal theory and the bonded block model (BBM) to simulate undersea isolation layer mining. The validation of this method hinges on on-site borehole scanning and displacement monitoring, which serve to depict the intricate fractal evolution of fractures and predict the optimal thickness of the isolation layer. Our findings affirm the robustness and validity of this method. Evaluation of the fractal dimensions of fractures reveals that a critical threshold of 1.7 exists to prevent structural failure of the isolation layer, while a limit of 1.5 is necessary to avert significant water ingress. Remarkably, the correlation dimension of the settlement time series closely aligns with the fractal dimension of the fractures, underscoring the feasibility of ensuring the safety of isolation layer mining through real-time settlement monitoring.

OSI model used to be common network model for years. In the case of ad hoc networks with dynamic topology and difficult radio communications conditions, gradual departure is happening from the classical kind of OSI network model with a clear delineation of layers (physical, channel, network, transport, application) to the cross-layer approach. The layers of the network model in ad hoc networks strongly influence each other. Thus, the cross-layer approach can improve the performance of an ad hoc network by jointly developing protocols using interaction and collaborative optimisation of multiple layers. The existing cross-layer methods classification is too complicated, because it’s based on the whole manifold of network model layers combinations, regardless their importance. In this work, we review ad hoc networks cross-layer methods, propose the new useful classification of cross-layer methods, and show future research directions in ad hoc networks cross-layer methods development. The proposed classification can help to simplify the goal-oriented cross-layer protocol development.

The amount of heat transfer in gas turbine blades depends on cooling techniques and various flow phenomena. The effect of eddies, passing shock waves and free flow turbulence has been noticed by many researchers since the beginning. The focus of the upcoming work is on the numerical investigation of the effects of turbulence intensity and Reynolds number on the amount of heat transfer from the blade surface with internal cooling. The SST model has been used to solve this problem, which has been compared with the experimental work to ensure the correctness of the numerical simulation. In this regard, by changing the free flow turbulence intensity with values of 1, 5, 7, and 10% and at three Reynolds numbers of 150,000, 350,000, and 750,000, the changes in heat transfer coefficients have been investigated. The results show that with the increase of the turbulence intensity at different Reynolds numbers, due to the positive effect of the flow turbulence on the suppression of separation and promotion of the boundary layer transition, the blade surface heat transferincreases and this increase is more evident at higher Reynolds numbers.

The role of volume hydrogel holographic gratings as optical transducers in sensor devices for point-of-care applications is increasing due to their ability to be functionalized for achieving enhanced selectivity. The first step in the development of these transducers is the optimization of the holographic recording process. The optimization aims at achieving gratings with reproducible diffraction efficiency, which remains stable after reiterative washings, typically required when working with analytes of biological nature or several step tests. The recording process of volume phase transmission gratings within acrylamide/propargyl acrylate hydrogel layers reported in this work was successfully performed and the obtained diffraction gratings were optically characterized. Unslanted volume transmission gratings were recorded in the hydrogel layers and using the optimized conditions, diffraction efficiencies of up to 80% were achieved. Additionally, the recorded gratings demonstrated to be stable in water after multiple washings. The hydrogels, after functionalization with oligonucleotide probes yields specific hybridization response, recognizing the complementary strand as demonstrated by fluorescence. Analyte-sensitive hydrogel layers with holographic structures are a promising candidate for the next generation of in vitro diagnostic tests.

Hf1-xZrxO2 (HZO) thin films are versatile materials suitable for advanced ferroelectric semiconductor devices. Previous studies have shown that the ferroelectricity of HZO thin films, can be stabilized by doping them with group III elements at low concentrations. While doping with Y improves the ferroelectric properties, there has been limited research on Y-HZO thin films fabricated using atomic layer deposition (ALD). In this study, we investigated the effects of Y doping cycles on the ferroelectric and electrical properties of as-deposited Y-HZO thin films with vaying compositions fabricated through ALD. The Y-HZO thin films were stably crystallized without the need for post-thermal treatment and exhibited transition behavior depending on the Y-doping cycle and initial composition ratio of the HZO thin films. These Y-HZO thin films offer several advantages, including enhanced dielectric constant, leakage current density, and improved endurance. Moreover, the optimized Y-doping cycle induced a phase transformation that resulted in Y-HZO thin films with improved ferroelectric properties, exhibiting stable behavior without fatigue for up to 1010 cycles. These as-deposited Y-HZO thin films show promise for applications in semiconductor devices that require high ferroelectric properties, excellent electrical properties, and reliable performance with a low thermal budget.

The study presents the synthesis and characterization of dual-layer sulfonated polyphenylenesulfone (SPPSu) nanocomposite hollow fiber nanofiltration membranes incorporating titanium dioxide (TiO2) nanoparticles using the phase inversion technique. The newly developed membranes were systematically characterized using advanced tools and methods to evaluate their properties and performance. The study focused on investigating the effects of TiO2 addition in the SPPSu inner layer on pure water permeability, and salt rejection. The nanocomposite hollow fiber nanofiltration membranes exhibited a significant enhancement in pure water permeability, with a three-fold increase compared to the pristine membranes, achieving a flux of 5.4 L/m2h.bar. The addition of TiO2 also led to an improvement in the mechanical properties of the membranes, as evidenced by the increase in the expected tensile strength from 2.4 to 3.9 MPa. To evaluate the salt rejection performance, rejection tests were conducted using a laboratory-scale filtration setup in recycle mode. Aqueous solutions containing different divalent ions, specifically magnesium sulfate (Mg2SO4) and sodium sulfate (Na2SO4) at a concentration of 500 ppm, were used as the feed solution. The modified dual-layer hollow fiber nanocomposite membranes exhibited a maximal rejection of 95% for Mg2SO4, demonstrating their effective separation capabilities for divalent ions. The findings of this study highlight the successful synthesis and characterization of dual-layer SPPSu nanocomposite hollow fiber nanofiltration membranes incorporating TiO2 nanoparticles. The incorporation of TiO2 resulted in improved pure water flux, mechanical strength, and salt rejection performance. These enhanced properties make the developed nanocomposite membranes promising candidates for applications in nanofiltration processes, particularly for the selective separation of divalent ions from aqueous solutions.

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.

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.

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%.

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.

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.

In this paper, we have used magnetron sputtering to grow the high-quality GeSn layer on Ge (100) with Sn compositin up to 7%. The crystallinity of the GeSn layer is pretty good, and the strain relaxation degree of the GeSn layer is evaluated to be approximately 50%. The root mean square (RMS) value is 0.8 nm, and the averaged TDDs in the GeSn layer is 8.7×109 cm-2, which is obtained from the rocking curve of GeSn layer along (004) plane. PL measurement result shows the significant optical emission from the deposited high-quality GeSn layer, which also means that magnetron sputtering is an optional way to achieve the higher Sn composition GeSn luminescent material. To verify whether our deposited GeSn can used for optoelectronic devices, we fabricate the simple vertical p-i-n diode, and the room temperature current-voltage (I-V) characteristic was obtained. This result paves the way for future sputtered-GeSn optimization, which is critical for the optoelectronic application.

In this paper, we first investigate secure communications for a two-hop interference relay system in the wireless Internet of Things (IoT), where K source-destination pairs communicate in the presence of an eavesdropper. Explicitly, we jointly design source, relay and destination matrices upon minimizing total mean-squared error (MSE) of all legitimate destinations while keeping the MSE at eavesdropper above a certain threshold. We illuminate that the joint design of the source, relay and destination matrices subject to both secrecy and transmit power constraints. More specifically, we proposed an efficient iterative distributed algorithm to simplify the process of the joint design for optimal source, relay and destination matrices. Furthermore, the convergence of the iterative distributed algorithm is described. Additionally, the performances of the proposed algorithm, including both its secrecy rate and MSE, are characterized with the aid of simulation results. We demonstrate that our proposed algorithm outperforms the traditional approach. As a benefit, secure communications can be guaranteed by using the proposed algorithm for the multiple input multiple output (MIMO) interference relay IoT network in the presence of an eavesdropper.

The search for graphene or few layer graphene production methods that are simple, allow mass production and yield good quality material continues to provoke intense investigation. The present work contributes through the study of the aqueous exfoliation of four types of graphene sources, namely graphite and graphite nanoflakes with different morphologies and geographical origin. The exfoliation was achieved in an aqueous solution of a soluble pyrene derivative that was synthesized to achieve maximum interaction with the graphene surface at low concentration (5 x 10-5 M). The yield of bilayer and few layer graphene obtained was quantified by Raman spectroscopic analysis and the adsorption of the pyrene derivative on the graphene surface was studied by thermogravimetric analysis and X-ray diffraction. The whole procedure was rationalized with the help of molecular modeling.

Medical implants made of biodegradable materials could be of advantage for temporary applications such mechanical support during bone-healing or as vascular stents to keep blood vessels open. After completion of the healing process the implant would disappear, avoiding long-term side effects or the need for surgical removal. Various corrodible metal alloys based on magnesium, iron or zinc have been proposed as sturdier and potentially less inflammatory alternative to degradable organic polymers, in particular for load-bearing applications. Despite the recent introduction of magnesium-based screws the remaining hurdles to routine clinical applications are still challenging, such as limiting mechanical material characteristics or unsuitable corrosion characteristics. Here, salient features and clinical prospects of currently investigated biodegradable implant materials are summarized with a main focus on magnesium alloys. A mechanism of action for the stimulation of bone growth due to the exertion of mechanical force by magnesium corrosion products is discussed. To explain divergent in vitro and in vivo effects of magnesium a novel model for bacterial biofilm infections is proposed which predicts crucial consequences antibacterial implant strategies.

In wild habitats, fruit dehiscence is a critical strategy for seed dispersal; however, in cultivated crops it is one of the major sources of yield loss. Therefore, indehiscence of fruits, pods, etc., was likely to be one of the first traits strongly selected in crop domestication. Even with the historical selection against dehiscence in early domesticates, it is a trait still targeted in many breeding programs, particularly in minor or underutilized crops. Here, we review of this trait in pulse (grain legume) crops, which are of growing importance as a source of protein in human and livestock diets, and which have received less attention than cereal crops and the model plant Arabidopsis thaliana. We specifically focus on the i) history of indehiscence in domestication across legumes, ii) structures and the mechanisms involved in shattering, iii) the molecular pathways underlying this important trait, iv) an overview of the extent of crop losses due to shattering, and the effects of environmental factors on shattering, and, v) efforts to reduce shattering in crops. While our focus is mainly pulse crops, we also included comparisons to crucifers and cereals because there is extensive research on shattering in these taxa.

We report on the fabrication and electrical characteristics of zinc-oxide (ZnO) based metal-insulator-semiconductor (MIS) type Schottky barrier diodes (SBHs). ZnO thin layer on the p-type silicon substrate was fabricated by atomic layer deposition (ALD). The structure and surface properties of the thin film were characterized by X-ray diffraction (XRD), atomic force microscope (AFM) and secondary ion mass spectrometer (SIMS). The current-voltage (I-V) characteristics of Al/ALD-grown ZnO/p-Si diodes were measured under dark at room temperature. The electrical parameters such as ideality factor (n), series resistance (R_s) and barrier height (ϕ_b) of the diodes were analyzed using standard thermionic emission (TE) theory, Norde and Cheung method. The barrier height value obtained from I-V and Cheung method was found to be 0.73 eV and 0.76 eV, respectively. The interface state density (Dit) of the diodes was determined from the I-V characteristics. The nonideal behavior of measured parameters suggested the presence of interface states. The obtained results showed that the prepared diode can be used for NIR Schottky photodetector applications.

Presence and identity of secondary metabolites are two of the main components of lichen taxonomy. Aromatic compounds formed via the acetyl-polymalonate pathway are the most studied lichen substances. In addition, compounds derived from the mevalonic acid pathway (e.g., terpenes and steroids) are sometimes detected in the medulla. However, their identity and value as diagnostic characters in the genus Usnea are yet poorly understood despite the fact that they were mentioned in several taxonomical papers. We conclude that i) aside from the previously recognized polyphenolic compounds, carbohydrates and steroids are also detected in the medulla of some Usnea species; ii) the use of sulfuric anisaldehyde reagent greatly improves the detection of terpenes, carbohydrates and steroids compared with the sulfuric acid reagent routinely used in thin layer chromatography; iii) among carbohydrates, we detected arabitol and sucrose in the medulla; iv) steroids and terpenes remain unidentified and deserve further investigations.

Biomass materials have received attention for energy storagebecaused of the advantage of low-cost, easy-to-prepare, and eco-friendliness. Three-dimensional carbon materialswith abundant pore structure gradually becomeresearch hotspot in high-performance energy storage. In this study, an easy-to-prepare, green, light and elastic activated carbon was present using the biomass Juncus effusus (JCE) via high-temperature pyrolysis, followed by activation in air. Compared with previously reported bio-carbons, the proposed air-activated bio-carbon contributes in the fabrication of pores to preserve the interconnected, reticular and tubular structure. Moreover, the interconnected porous material also inherits the excellent tenacity of the original JCE such as the material can be bended to below 90^o under an external force while maintaining structural integrity. The activated porous carbon material exhibits an enhanced electric double-layer capacitance (~210 F g^-1 at 1 A g^-1), with capacitance retention of ~78.62% at 10 A g^-1. The interconnected porous carbon microtubes electrode as a double-layer symmetric capacitor exhibits considerable capacitance retention (84%) after 2000 cycles at 1 A g^-1. The improved energy storage performance was proposed to be attributed to the shortened ionic diffusion distance and sufficient contact between the interface of the carbon electrode and electrolyte, which is resulted from the elastic, undamaged structure and types of pores. These results demonstrated that as-preparedcarbon materials have potentional application in symmetric capacitors.

Fragmentation processes of multiply charged ions of C10H8 isomers produced in fast proton collision (velocity between 1.41 and 2.4 a.u.) is discussed in view of their fundamental molecular dynamics. Especially so in the mechanisms to produce a variety of carbon clusters from such ions. This aspect is assessed with the help of a multihit analysis of daughter ions in coincidence with elimination of H+ and CHn+ (n = 0 to 3). The elimination of H+/C+ was found to be very different from CH3+ loss. The loss of CH3+ was found to be accompanied with the formation of heavy ions like C9H5+, C9H5++ and C7H3+ by a cascade of momentum correlated dissociations. The most probable structures of large fragment ions in the CH3+ loss cascade are predicted with the help of computed electronic energy and the multihit ToF correlations of second and third hit. In addition, we report observation of super-dehydrogenation of naphthalene and azulene targets, with evidence of complete dehydrogenation in a single collision.

This paper proposes a multi-terminal adaptive collaborative operation method to solve the problem of unstable internal force tracking in clamping and handling unknown objects by multi-terminal robots. In the proposed method, the internal command force changes the complex internal force control problem into an internal force tracking problem from multi-slave to master. Moreover, we develop an algorithm for multi-slave setups to estimate object stiffness and motion uncertainty in the direction of the internal command force according to Lyapunov theory. Finally, the impedance control generates a reference trajectory for the multi-slave to maintain the desired internal force and track the master’s motion. Several experiments are conducted on a self-made robot equipped. The experimental results show that the oscillation amplitude of each slave end is less than 1 mm, the directional oscillation amplitude is less than 1 degree during the tracking of the desired commanded internal force. For objects with low stiffness, the error of the commanded internal force is less than 1 N (6%) per slave. The error in tracking the commanded internal force for objects with high stiffness is less than 2 N (8%). The results prove the feasibility and effectiveness of the proposed method.

In gravitational theory and astrophysical dynamics, singular initial value problems (IVPs) are frequently encountered. Finding the solutions to this class of IVPs can be challenging due to their complex nature. This study strives to circumvent the complexity by proposing a numerical method for solving such problems. The approach proposed in the current research seeks solutions to the IVP by partitioning the domain [0,L] of the problem into two intervals and solving the problem on each domain. The study seeks a closed-form solution to the IVP in the interval containing the singular point. A linearization technique and piecewise partitioning of the domain not containing the singularity are applied to the nonlinear IVP. The resulting linearized differential equation is solved using the Chebyshev spectral collocation method. Some examples are presented to illustrate the efficiency of the proposed method. Numerical analysis of the solution and residual errors are shown to ascertain convergence and accuracy. The results suggest that the technique gives accurate convergent solutions using a few collocation points.

Dracunculiasis (also known as Guinea worm disease) is caused by Dracunculus medinensis parasite and it spreads by drinking water containing Larvae of Guinea worm. The lack of safe water facilities, preventions and treatments resulted in highly dangerous consequences in its endemic regions. The economy of the affected regions totally falls down due to less production which is the result of agricultural field worker’s bad health. In this study, a multi epitope vaccine was designed against Dracunculus medinensis by using immune-informatics. The vaccine was designed by using T-Cell and B-Cell epitopes derived from Dracunculus medinensis proteins (Lactamase-B domain-containing protein, G-Domain containing protein and Ferrochelatase) in addition to Adjuvants and Linkers. The tertiary structure, physiochemical properties and immunogenic elements of vaccine were achieved. The validation of tertiary structure was accessed, and quality was achieved. In addition, the world coverage of parasite’s CTL and HTL epitopes is 95.61%. The stability of the chimeric vaccine was achieved through disulfide engineering. The molecular docking with Toll Like Receptor 4 (TLR-4) of vaccine showed its binding efficiency followed by Molecular Dynamic Simulation. The immune simulation suggested the mediated cell immunity and repeated antigen clearance. At the end, the optimized codon was used in in silico cloning to ensure vaccine’s higher exposure in bacterium E. coli strain K12. With further assessments, it is believed that the proposed multi epitope vaccine has strong immunogen to control Dracunculus medinensis which may result in better social and economic conditions of endemic regions.

Introduction Tuberculosis is common in Pakistan. Due to various factors including socioeconomic factors, compliance is poor to anti-tuberculosis drugs, leading to resistance. We aim to determine the prevalence of Multidrug resistance (MDR) tuberculosis in Pakistani population.Methods A prospective observational study was conducted from April 1, 2019, to December 31, 2019, in the Pulmonology department of a tertiary care hospital in Pakistan. Culture and sensitivity were assessed using a sputum sample or, in cases of an absent sputum sample, from Broncho alveolar lavage.ResultsApproximately 71.3% percent patients who had tuberculosis were found to be resistant to Isoniazid and around 48.6% did not respond to Rifampin. Multi-drug resistant was found in 29.4% participants.ConclusionMulti-drug resistance tuberculosis is very prevalent in Pakistan, which may increase burden on health care system and may lead to various complications of tuberculosis.

Phenotypic studies require large datasets for accurate inference and prediction. Collecting plant data in a farm can be very labor intensive and costly. This paper presents the design, architecture (hardware and software) and deployment of a distributed modular agricultural multi-robot system for row crop field data collection. The proposed system has been deployed in a soybean research farm at Iowa State University.

In the framework of maritime surveillance, vessel detection techniques based on spaceborne Synthetic Aperture Radar (SAR) images have promoted extensive applications for the effective understanding of unlawful activities at sea. The paper deal with this topic presenting a novel approach exploiting a cascade application of a pre-screening, and discrimination phase. The latter leverage the SAR spectrum by means of sub-looks analysis. For the first time, the method has been validated with experiments on multi-frequency (C-, X-, and L-band) SAR images. For a future syngergic exploitation of more SAR missions, the developed dataset, composed of Sentinel-1, SAOCOM and COSMO-SkyMed images, is comprehensive of multiple images gathered over the same area with short time lag (below 15 minutes). Finally, the diversified processing chains and the results for each mission product and scenarios are discussed. Being the first dataset of SLC (Single Look Complex) SAR multi-frequency data, the present work intends to encourage additional research in this promising field of research.

In our increasingly urbanized world, precise and up-to-date maps of human settlements are essential for sustainable urban development policies. The availability of open-access Sentinel-2 data from the Copernicus program presents an opportunity to create a comprehensive global map of human settlements, offering a detailed view of built areas on a large scale. This study estimates large-scale built-up fractions using encoder-decoder deep learning architectures like U-net, Res-U-net, and Attention-U-net in the large and complex urban area of Delhi, India. Openly available datasets like Open Street Map (OSM) and Microsoft building footprint datasets are used to derive built-up fractions at 10×10m resolution cells for over 34,000 km2. Our results show that Attention-U-net with the Huber loss function performs the best in different built-up densities (i.e., urban, semi-urban or rural) with an R2 score of 0.631, while Res-U-net and U-net obtained an R2 score of 0.623 and 0.612, respectively. The investigated networks significantly improve the accuracy over the latest Global Human Settlement Layer product (GHSL-S2), which uses a deep-CNN and reaches an R2 of 0.387 in our case study area. The result of this study yields a valuable spatial layer for examining the spatial distribution of human settlements across the entire spectrum from rural to urban areas.

Phosphorus is required by laying hens for a variety of biological functions. It is usually provided in excess, in a readily digestible inorganic form in diet formulations. However, this does not represent an efficient use of a finite resource and can result in water pollution. Plant bound phosphorus in phytate, is common in commercial poultry diets, and represents an alternate source of phosphorus, however poultry lacks the enzyme to digest it. By adding enzymes to their diets, the availability of this phytate-bound phosphorus can be increased allowing for the reduced inclusion of inorganic P in the diet formulation. Therefore, this study was conducted to examine the effect of a natural enzyme complex that contains phytase and xylanase in layer diets. Novogen Brown Classic layers (n=314) were fed one of two diets: (T1) control diet or (T2) control diet plus a natural mixed-enzyme product with both, phytase and xylanase. Experimental diets were provided for 12 days after which the excreta from each pen were collected for an additional three days to determine total retention and ileal digestibility of phosphorus and gross energy. At the end of the trial the birds were euthanized, and their ileal contents were collected. Productivity parameters were also recorded over the course of the study. The amount of phosphorus detected in the excreta of the control group was significantly higher than the amount detected in the enzyme-supplemented group (P<0.05). Both phosphorus retention and phosphorus ileal digestibility were significantly higher in the enzyme-supplemented birds (P<0.001). Gross energy digestibility was significantly higher in the enzyme-supplemented birds for both the total tract and ileal samples (P<0.001). There were only numerical improvements, not significant, in the layer productivity parameters. This study showed that the enzyme supplement can improve total retention and ileal digestibility of phosphorus and gross energy in older layers.

The cubic nonlinearity of graphene oxide (GO) monolayer was characterized by open and closed Z-scan using a nano-second laser of 10 Hz repetition rate with a Gaussian spatial beam profile. The reverse saturable absorption or positive nonlinearity from open Z-scan and valley-peak traces or positive nonlinearity from closed Z-scan was displayed. The reverse saturable absorption could be from a two-photon or two-step excitation process due to the larger absorption in the lower visible and upper UV wavelength region compared with the excitation source. The nonlinear absorption and nonlinear refraction coefficient were estimated to be ~ 2.62x10-8 m/W and 3.9x10-15 m2/W, respectively. This study also reveals the effect of nonlinear absorption on nonlinear refraction traces.

The aim of this work is to synthesis and characterize the Ta/TaN multilayer thin film coatings on 52100 tool steel under three different levels of N2 gas flow rate. The High Power Impulse Magnetron Sputtering (HiPIMS) technique was used for the deposition of Ta/TaN thin film multilayers on the substrate. Microstructure, coating thickness, composition, hardness and tribological properties of Ta/TaN multilayer coatings were characterized using scanning electron microscopy (SEM), Energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), microhardness tester and pin-on-disc tester, respectively. Adhesion property was evaluated via scratch testing of the thin film thin film layer. The lowest coefficient of friction was observed with the thin film layer of higher N2 gas flow rate due to the highest adhesion value of the coating on the surface. The obtained results on hardness, adhesion and coefficient of friction properties demonstrated that this Ta/TaN multilayer thin film coating can be used for tribological applications.

A structural study of the 6√3 reconstruction conversion on 4H-SiC substrate surface in an Ar medium with a short sublimation annealing time into quasi-free epitaxial graphene by means of hydrogen intercalation between the upper layer of SiC and the adjacent reconstructed layer was carried out using the technique of reflection high-energy electron diffraction (RHEED) characterizing the surface of a crystalline material. A slight violation of the 6√3 reconstruction layer formation uniformity was found. The results of the study of the crystal structure of quasi-free graphene and single-layer graphene comprising a buffer layer formed on 4H-SiC in the traditional way in an Ar atmosphere without intercalation were compared.

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.

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.

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.

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.

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.

Recently Li et al (2019 Nature 572 624) discovered a new type of oxide superconductor Nd_0.8Sr_0.2NiO₂ with T_c = 14 K. To classify superconductivity in this infinite-layer nickelate experimental upper critical field, B_c2(T), and the self-field critical current densities, J_c(sf,T), reported by Li et al (2019 Nature 572 624), are analysed in assumption of s-, d-, and p-wave pairing symmetries and single- and multiple-band superconductivity. Based on deduced the ground-state superconducting energy gap, Δ(0), the London penetration depth, λ(0), the relative jump in electronic specific heat at T_c, ΔC/C, and the ratio of 2Δ(0)/k_BT_c, we conclude that Nd_0.8Sr_0.2NiO₂ is type-II high-κ weak-coupled single-band s-wave superconductor.

The three-axes Doppler sodar Latan-3 operated on an oceanographic stationary platform in the coastal zone of the Black Sea in June 2015. The platform is located 450 meters offshore from the southern coast of the Crimea Peninsula in the region of Katsiveli (44.39°N, 33.99°E). The water depth at the site is about 30 meters. The atmospheric boundary layer (ABL) typical for the mediterranean seas was observed when the wind is from the sea. The physical processes typical for the coastal mountain terrain was observed when the wind was from the shore. Complex measurements of the ABL parameters were performed using a sodar. Auxiliary measurements of the ABL parameters were performed using a temperature profiler and an ultrasonic thermometer-anemometer. Observations were made mostly during a fair weather with a pronounced diurnal course of meteorological parameters. Sodar data analysis revealed a strong wave activity in the ABL. Internal gravity waves with amplitudes of up to one hundred meters were regularly observed in a layered turbulence structure under stable conditions. Various forms of Kelvin-Helmholtz billows were observed at the interface between the sea breeze and the return flow aloft and in the low level jets.

Permafrost hydrology is an emerging discipline, attracting increasing attention as the Arctic region is undergoing rapid change. However, the research domain of this discipline had never been explicitly formulated. Both 'permafrost' and 'hydrology' yield differing meanings across languages and scientific domains, hence 'permafrost hydrology' serves as an example of linguistic relativity. The differing views of permafrost as either an ecosystem class or a geographical region, and hydrology as a discipline concerned with either landscapes or generic water bodies, maintain a language-specific touch in the definition of permafrost hydrology. From this point of view, the English and Russian usage of this term is explained. A universal process-based definition is further proposed, developed on a specific process assemblage, including (i) water table dynamics caused by migration of an upper aquitard through freeze–thaw processes; (ii) water migration in soil matrix, driven by phase transitions in the active layer; (iii) transient water storage in solid state in the subsurface compartment. This definition is shown to fill the niche in existing vocabulary, and other definitions from northern hydrology field are revisited.