The petroleum industry produces thousands of barrels of oilfield waters from the initial stage driven by primary production mechanisms to the tertiary stage. These produced waters contain measurable amounts of oil in water emulsions, the exact amounts being determined by the chemistry of the crude oil. To meet strict environmental regulations governing the disposal of such produced waters, demulsification to regulatory permissible levels is required. Within the electric double layer theory, coupled with the analytical solutions to the Poisson Boltzmann Equation, continuum electrostatics approaches can be used to describe the static and electrokinetic properties of such emulsion systems. Therefore, theoretical understanding of the stability of oil in water emulsions within such fundamental concepts provides reliable approaches to demulsification. In this paper, we have used theoretical approaches, based on zeta potential and surface charge density models to determine the stability of oil in water emulsions for different crude oil samples. Accordingly, we have used literature based data on the chemistry of the crude oils, and have ranked the order of emulsion stability based on criterial established by zeta potential plots for the oil. Our theoretical calculations show that where the isoelectric points of crude oil samples are closer to each other, the degree of ionization plots versus pH indicate close tends for salinities at varying pH of oilfield waters. Based on the chemistry of crude oil samples, the most efficient and cost-effective means of demulsification is by reducing produced water pH to values closer to the average point of zero charge pH values

The application of warm-mixing technology brings considerable economical and environment benefits by decreasing the mixing temperature during warm asphalt mixture(WMA) production. However, the possible water residue also generates concerns in moisture susceptibility. For deep investigation on the influencing factors and mechanism of the moisture susceptibility of WMA, surface free energy(SFE) test and laboratory tests are applied in this research. A novel indicator based on SFE namely effective adhesion work is proposed to assess the asphalt-aggregate adhesion with different moisture contents. Then, given the mixing procedure of dry mixing method, an advanced three-phase model as form of asphalt-aggregate-warm mixing additive is introduced improving from the conventional two-phase asphalt-aggregate model for better reflecting the separate addition of warm mixing additive during mixing. Afterwards, the influence of aggregate types, asphalt type, aggregate moisture contents, warm-mixing agent types and warm-mixing process on the moisture susceptibility of WMA is analyzed utilizing the models and indicators proposed. Finally, the validity of the SFE indicator is verified by comparing the calculation of effective adhesion work with freeze-thaw splitting test result. The results show that all of the above factors impact the moisture susceptibility of WMA by influencing the interfacial adhesion, with the effect of moisture content being the most significant. Meanwhile, effective adhesion work and the three-phase model brought out in this research are proven to be feasible to characterize the adhesion properties of WMA, offering theoretical support to the research on warm mixing technology.

The appropriate maintenance of highway roads is critical for the safe operation of road networks and conserves maintenance costs. Multiple methods have been developed to investigate the surface of roads for various types of cracks and potholes, among other damage. Like road surface damage, the condition of expansion joints in concrete pavement is important to avoid unexpected hazardous situations. Thus, in this study, a new system is proposed for autonomous expansion joint monitoring using a vision-based system. The system consists of the following three key parts: (1) a camera-mounted vehicle, (2) indication marks on the expansion joints, and (3) a deep learning-based automatic evaluation algorithm. With paired marks indicating the expansion joints in a concrete pavement, they can be automatically detected. An inspection vehicle is equipped with an action camera that acquires images of the expansion joints in the road. You Only Look Once (YOLO) automatically detects the expansion joints with indication marks, which has a performance accuracy of 95%. The width of the detected expansion joint is calculated using an image processing algorithm. Based on the calculated width, the expansion joint is classified into the following two types: normal and dangerous. The obtained results demonstrate that the proposed system is very efficient in terms of speed and accuracy.

Typically, a diesel generator on the merchant ship, composed of a wound rotor synchronous generator and a four-stroke diesel engine, supplies electrical power to various loads. Recently, shaft generators for merchant vessels are increasingly replacing diesel generators to reduce CO2 emissions through fuel efficiency improvement. In particular, permanent magnet generators replace induction generators due to their high-efficiency characteristics at light loads. The surface-mounted permanent magnet can be a suitable rotor topology due to the relatively short constant power range. This generator can also operate as a motor according to the propulsion mode, so minimizing the harmonics of the induced voltage and the torque ripple is necessary. This paper proposes an alternative NdFeB magnet pole topology combined with the modular step-skewed rotor. The step-skewed rotor affects to reduce higher-order harmonics, and the modular pole reduces the permanent magnet assembly process and harmonics in voltage and torque. A 2-D finite element method is used to evaluate the harmonics of induced voltage and torque pulsation for the proposed topology. The topology shows harmonic minimization effect by comparing the characteristics of three flatted-bottom magnets. Compared to the tapered bread-loaf magnet, voltage harmonics to the 100th component are almost the same, and the torque ripple is reduced by more than 12% at the same residual flux density. The analysis method is verified by comparing test and analysis results for prototype machines with similar specifications.

The central coast is one of the importantly livable regions in China, and green land plays a meaningful role in improving human settlements through regulating ecosystem services. However, the research on spatiotemporal heterogeneity of green land in different urbanized areas are still lacking in this region, which limits the timeliness of reporting on the land-surface thermal properties of residential environment from green land perspective. To address this issue, the synergistic methodology of “artificial numerical technology -- urban interior mixed pixel classification -- surface radiation energy balance model” was applied to investigate the green land change and its impact on human settlements in Rizhao region, which is known for its coastal ecology and greenery in China and obtained the United Nations habitat award. Main conclusions of this study are below: (1) Although total green land decreased by 474.05 km2, resulting in a decrease of 9.17% in its share of the entire study area from 2000-2022 during the urbanization process, but the greening levels improved within the built-up area, with the greening proportion of 25.34% in 2000 and 42.98 km2 in 2022. (2) Differences in green land at different urbanized regions were first observed, namely, urban greening rate was 37.78% in the old urban areas of 2022, while it was up to 46.43% in new urban areas. More attention was paid to the construction of urban green space during urban expansion, which will inevitably bring better visual and comfort experience to residents. (3) Thermal comfort indicators for urban residents were evaluated in latent heat flux (0-457.83 W/m2), sensible heat flux (0-645.09 W/m2), total available energy (254.07-659.42 W/m2) and others. (4) The lowered cooling temperature effect in the middle, high green land density region was 1.05 ℃ and 2.12 ℃ compared to the low-density region, and the average air temperature was 25.86 ℃. Also, spatial patterns of hot and cold uncomfortable areas were displayed in this study. Overall, this study provides the meaningfully practical reference for exploring the spatiotemporal heterogeneity of green land and its impact on residents' environments from the perspective of land-surface thermal properties in coastal areas of China and around the world.

Surface defect detection is one of the most widely used research areas in the field of image processing and machine vision. Detection of surface defects is used in visual inspection systems and medical image analysis. In this manuscript, an innovative method for detecting surface defects based on energy changes in co-occurrence matrices is presented in several directions. The method presented in this manuscript includes two stages of learning and testing. In the learning phase, to extract texture features, the gray level co-occurrence matrix operator is applied on the healthy image of the desired level. Then the energy value of the output matrix is ​​calculated. In the following, changes in the amount of energy are considered as statistical characteristics that are a good representative of the image of a healthy surface. Finally, with its help, a suitable threshold for the health of the images is obtained. Then, in the test phase, with the help of the calculated quorum, the defective windows that have suffered from non-normality are distinguished from the healthy surface sections. In the results section, the efficiency of the mentioned method has been measured on medical images and stone and ceramic images, and its detection accuracy has been compared with some previous effective methods. The advantages of the presented method include high accuracy, low calculations and compatibility with all types of levels due to the use of the learning stage. The proposed approach can be used in medical applications to diagnose abnormalities such as diseases. All extracted features are statistical, so its detection speed is higher than deep neural networks.

To investigate the dynamics of land surface temperature (LST) in Afghanistan in the period 2000-2021 and to assess the impact of such factors as soil moisture, precipitation, and vegetation coverage on it, remotely sensed soil moisture data from Land Data Assimilation System (FLDAS), precipitation data from Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS), and NDVI and LST from Moderate Resolution Imaging Spectroradiometer (MODIS) were downloaded and correlations between them were analyzed using the regression method. The result shows that the LST in Afghanistan has a slightly decreasing, but insignificant trend during the study period (R=0.2, p-value=0.25), while vegetation coverage, precipitation, and soil moisture had an increasing trend. It was revealed that soil moisture has the highest impact on LST (R=0.7, p-value=0.0007), and the soil moisture, precipitation, and vegetation coverage explain almost 80% of spring (R2=0.73) and summer (R2=0.76) LST variability in Afghanistan. The LST variability analysis done separately for Afghanistan’s rivers subbasins shows that the LST of the Amu Darya subbasin had an upward trend in the study period, while for the Kabul subbasin the trend was downward.

Among the thermophysical properties, the surface / interfacial tension, viscosity and density / molar volume of liquid alloys are the key properties for the modelling of microstructural evolution during solidification. Therefore, only reliable input data can yield accurate predictions preventing the error propagation in numerical simulations of solidification related processes. Due to experimental difficulties related to reactivity of metallic melts at high temperatures, the measured data are often unreliable or even lacking. The application of containerless processing techniques either leads to a significant improvement of the accuracy or makes the measurement possible at all. On the other side, accurate model predicted property values could be used to compensate the missing data; otherwise, the experimental data are useful for the validation of theoretical models. The choice of models is particularly important for the surface, transport and structural properties of liquid alloys representing the two limiting cases of mixing, i.e. ordered and phase separating alloy systems. To this aim, the thermophysical properties of the Fe-Si and Cu-Pb systems were analysed and the connections with the peculiarities of their mixing behaviours are highlighted.

Metal nanoparticles supporting plasmons are widely used to enhance electromagnetic fields, resulting in strong light-matter interactions at the nanoscale in a diverse range of applications. Recently, it has been shown that when metal nanorods are periodically arranged with proper lattice periods, surface lattice resonances (SLRs) can be excited and near fields can be greatly enhanced over extended volumes. In this work, we report significant near field enhancement over even larger volumes by placing the metal nanorod array within a Fabry-Pérot (F-P) microcavity. Results show that taking advantage of strong coupling between the SLR and the photonic F-P resonances, the electric field intensity of the bonding split mode can be enhanced by up to 1935 times, which is about three times of the enhancement of the SLR, and the greatly enhanced field can extend over most of the F-P microcavity. We further show that the F-P resonances of both odd and even orders can strongly couple to the SLR by varying the nanorods position from the middle of the microcavity. We expect that the proposed plasmonic-photonic coupling system will find promising applications in nanolasers, nonlinear optics and sensing.

Transparent, flexible, biaxially oriented polyethylene terephthalate (PET) sheets were modified by bioactive polymer-fibronectin top layers for the attachment of cells and growth of muscle fibers. Towards this end, PET sheets were grafted with 4-(dimethylamino)phenyl (DMA) groups from the in situ generated corresponding diazonium compound. The arylated sheets served as macro-hydrogen donors for benzophenone and the growth of poly(2-hydroxy ethyl methacrylate) (PHEMA) top layer by surface-confined free radical photopolymerization. The PET-PHEMA sheets were further grafted with fibronectin (FBN) through the 1,1-carbonyldiimidazole coupling procedures. The bioactive PET-PHEMA-I-FBN was then employed as a platform for the attachment, proliferation and differentiation of eukaryotic cells which after a few days gave remarkable muscle fibers, of ~120 µm length and ~45 µm thickness. We demonstrate that PET-PHEMA yields a fast growth of cells followed by muscle fibers of excellent levels of differentiation compared to pristine PET or standard microscope glass slides. The positive effect is exacerbated by crosslinking PHEMA chains with ethylene glycol dimethacrylate at initial HEMA/EGDMA concentration ratio = 9/1. This works conclusively shows that in situ generated diazonium salts provide aryl layers for the efficient UV-induced grafting of biocompatible coating that beneficially serve as platform for cell attachment and growth of muscle fibers. Beyond this work, diazonium coupling agents constitute the corner stone of next generation processes for building flexible platforms for cell adhesion and uses thereof.

This work shows a correlation between light reflectance, absorption, and morphologies of series of (1-x) BM–x PT, (x = 0.0, 0.02, 0.04, 0.08, 0.12, 0.16, 0.24) ceramics composite. The (1-x) BM–x PT showed features of a black mirror with a low optical energy gap. The measured Vis-NIR diffused reflectance enabled the calculation of the energy gap using the modified Kubelka-Munk function. The estimated energy gap was lower than 1.5 eV related to low reflectance in the Vis-NIR range. Moreover, obtained histograms of grains, using scanning electron microscope, enabled the correlation between grains size and amount of lead titanate. We deduced from the ceramics surface morphology that marked porosity also induced reflectivity of low magnitude. We correlated the magnitude of the energy gap with phases of the BM-PT composite and with the electrical conductivity activation energy reported in the literature. Our results findings opened prospect studied materials for optical applications.

In this work epitaxial Au islands have been grown on epitaxial α-Fe2O3 thin film by pulsed laser deposition on SrTiO3(111) substrate. Both Au and α-Fe2O3 layer show an island-type growth with an average particle size of 40 and 62 nm, respectively. The crystallographic coupling of lattices is confirmed with a rotation of 30º between the in-plane crystallographic axes of α-Fe2O3(0001) structure and those of SrTiO3(111) substrate and between the in-plane crystallographic axes of Au(111) and those of α-Fe2O3(0001) structure. α-Fe2O3 is the only phase of iron oxide identified before and after its functionalization with Au nanoparticles. In addition, its structural character-istics are also preserved after Au deposition, with minor changes at short-range order. The func-tional character of the complex systems as gas sensor has been proven at room temperature. Con-ductance measurements of Au(111)/α-Fe2O3(0001)/ SrTiO3(111) system show that the incorpora-tion of Au islands on top of the α-Fe2O3(0001) layer induces an enhancement of the gas-sensing ac-tivity for CO and CH4 gas in comparison to a bare α-Fe2O3(0001) layer grown on SrTiO3(111).

With global warming and accelerated degradation of permafrost, the engineering problems caused by the formation of weak zones between the shallow and permafrost layers of soil–rock mixture (S-RM) slopes in permafrost regions have become increasingly prominent. To explore the influence of rock content on the shear strength of the S-RM freezing–thawing interface, the variation in the shear strength for different rock content is studied herein using direct shear tests. In addition, a 3D laser scanner is used for obtaining the topography of the shear failure surface. Combined with the analysis results of the shear band-particle calculation model, the influence of the rock content on the shear strength of the interface is explored. It was found that the impact threshold of the rock content on the interface strength and failure mode is approximately 30%, when the rock content (R) is > 30% and that the shear strength increases rapidly with increasing rock content. When R ≤ 30%, the actual shear plane is similar to waves; when R > 30%, the shear plane appears as gnawing failure. The shear strength of S-RM freezing–thawing interface mainly comes from the bite force and friction between particles. The main reason for the increase in shear strength with increasing rock content is the increase in bite force between particles, which makes the ratio of bite force to friction force approximately 1:1.

Ocean surface waves have been utilized as fundamental information in various fields of oceanic research. In this paper, we suggest a simulation and modelling technique for generating an ocean surface wave using an inverse Fast Fourier Transform (iFFT), and we subsequently verify the wave’s accuracy. The conventional method, linear superposition, requires recursive calculation because of the double summation and the time variable; to circumvent this issue, the new algorithm is presented. The Joint North Sea Wave Project (JONSWAP) spectrum is utilized for the ocean surface wave simulation example, and the parameters are the significant wave height (HS) and the zero-crossing wave period (TZ). A coordinate transform for the wavenumber domain was used to apply the inverse FFT algorithm. To verify the accuracy of the simulation result, the relative error between the input condition and the analysis result was calculated. The result for TZ is below 4% relative error, and the maximum relative error for HS is 7%. To avoid the Nyquist frequency for wave-field analysis and simulation, the minimum grid size was calculated by twice applying the maximum wavenumber.

Elevated levels of oxidative stress in the corneal epithelium contribute to the progression of dry eye disease pathology. Previous studies have shown that antioxidant therapeutic intervention is a promising avenue to reduce disease burden and slow disease progression. In this study, we evaluated the pharmacological efficacy of Xanthohumol in preclinical models for dry eye disease. Xanthohumol is a naturally occurring prenylated chalconoid that promotes the transcription of phase II antioxidant enzymes. Xanthohumol exerted a dose-response in preventing tert-butylhydroxide-induced loss of cell viability in human corneal epithelial (HCE-T) cells and resulted in a significant increase in expression of nuclear factor erythroid 2-related factor 2 (Nrf2), the master regulator of the endogenous antioxidant system. Xanthohumol-encapsulating poly(lactic-co-glycolic acid) nanoparticles (PLGA NP) were cytoprotective against oxidative stress in vitro, and significantly reduced corneal fluorescein staining in the mouse desiccating stress/ scopolamine model for dry eye disease in vivo by reducing oxidative stress-associated DNA damage in corneal epithelial cells. PLGA NP represent a safe and efficacious drug delivery vehicle for hydrophobic small molecules to the ocular surface. Optimization of NP-based antioxidant formulations with the goal to minimize instillation frequency may represent future therapeutic options for dry eye disease and related ocular surface disease.

Study of gross alpha (GA) and gross beta (GB) activity in road and surface deposited sediments were performed in various geographical areas in three Russian cities. To perform radiation measurements, new methods were applied which allow dealing with low mass and low volume dust size (2-100μm) samples obtained after the size fractionation procedure. The 2-10 μm fraction size has the highest gross beta activity concentration (GB)– 1.32Bq/g in Nizhny Novgorod (NN) and Rostov-On-Don (RND) while the 50-100 μm fraction size in Ekaterinburg. This is maybe associated with the subsistence of radionuclides that conveyed through natural processes and anthropogenic applications. The highest gross alpha activity concentration (GA) in fraction sizes was found in Rostov-on-Don city within the 50-100 μm– 0.22Bq/g. The fraction size 50-100 μmhas a higher gross alpha activity concentration than 2-10 and 10-50 μmfraction sizes due to natural partitioning of the main minerals constituting the urban surface deposited sediment (USDS). The geochemical processes that occur during the formation and transportation of USDS are reflected in the observed dependencies.Developed experimental methods of radiation measurements allowed to the extent the methodological base of urban geochemical studies.

The potential of the Additive Manufacturing technologies is impeded by the surface finish obtained on the as-manufactured material. Therefore, the influence of various surface treatments, commonly applied to space hardware, on the mechanical properties of three selected metallic alloys (SS316L, AlSi10Mg, Ti6Al4V) prepared by using Selective Laser Melting (SLM) and Electron Beam Melting (EBM) additive manufacturing processes have been investigated. Within this study, SLM using EOS M400 and EOS M280 equipment and in addition EBM using an ARCAM Q20 machine have been applied for sample manufacturing. A half-automated shot-peening process followed by a chemical and/or electrochemical polishing or Hirtisation® process has been applied in order to obtain lower surface roughness compared to their as-received states. Special emphasize has been taken on their tensile, fatigue, and fracture toughness properties. In addition, their stress corrosion cracking (SCC) behaviour including microstructural analysis using HR-SEM have been investigated.

The current study investigated the use of two-dimensional spatial distribution mapping representing the chlorophyll-a level in a river generated via an unmanned aerial vehicle (UAV) and an unmanned surface vehicle (USV). A domestically developed UAV (Remo-M, Uconsystem Inc., Korea) and a USV developed by our research team were used to collect data from the Nae Seong stream in Korea. An adaptation of the “Data Cleaner” tool was developed and used for USV data processing and analysis. The operation of the autonomous USV was successful. Four previously described indices for quantifying algal blooms in rivers were utilized to create chlorophyll-a images, the normalized difference vegetation index (NDVI), the normalized green red difference index, the green normalized difference vegetation index (GNDVI), and the normalized difference red edge index. The suitability of the linear regression analysis of the correlation between the spectral indices obtained using the UAV and the in situ chlorophyll-a data obtained using the USV was evaluated with the coefficient of determination (R2) at a significance level of p &lt; 0.001. In field application and correlational analysis the NDVI was strongly correlated with chlorophyll-a (R2 = 0.88, p < 0.001), and the GNDVI was moderately correlated with chlorophyll-a (R2 = 0.74, p < 0.001). The map of chlorophyll-a was successfully quantified using the UAV and USV hybrid platforms.

Abstract: Polylactic acid (PLA) is brittle in nature with extensive deformation property. For improvement of the end-use quality, it is of significant importance to enhance the producibility of fused deposition modeling (FDM)-printed objects in PLA. The purpose of this investigation is to boost toughness and to reduce the production cost of the FDM-printed tensile test samples with the desired part thickness. To attain the research purpose number of experiments are designed and analyzed by the Response Surface Method (RSM). The statistical analysis is performed to deal with this concern considering layer thickness, infill percentage, and extruder temperature as controlled factors. The tensile test specimens are printed based on the designed experiments, and the tensile strength tests are conducted by SANTAM 150 universal testing machine based on ASTM D638. The honeycomb internal fill pattern is applied for the production of light-weight and high-strength specimens. The area under Force- Extension curve up to fracture is acquired as the toughness of the printed specimens. This study also developed a modeling process using ANN and ANN-GA techniques for developing an accurate estimation for toughness, part thickness, and production cost as dependant variables. Results were evaluated by correlation coefficient and RMSE values. According to the modeling results, ANN-GA as a hybrid ML technique could successfully improve the accuracy of modeling about 7.5, 11.5 and 4.5 % for toughness, part thickness, and production cost, respectively, in comparison with those for the single ANN method. In the other side, the optimization results confirm that the optimized specimen is cost-effective and able to comparatively undergo deformation, which develops the usability of printed PLA objects. The research is accomplished under the constraints of PLA compatibility with existing fused deposition modeling setup without changing the functional hardware/software of the machine. Although the mechanical properties and dimensional accuracy of PLA have already been studied, there is little literature on the toughness of the printed PLA with honeycomb internal fill pattern.

Geopolymer cement has been popularly studied nowadays compared to ordinary Portland cement because it demonstrated superior environmental advantages due to its lower carbon emissions and waste material utilization. This paper focuses on the formulation of geopolymer cement from nickel-laterite mine waste (NMW) and coal fly ash (CFA) as geopolymer precursors, and sodium hydroxide (SH) and sodium silicate (SS) as alkali activators. Different mix formulations of raw materials are synthesized to produce a geopolymer based from an I-optimal design and obtained different compressive strengths. A mixed formulation of 50% NMW and 50% CFA, SH-to-SS ratio of 0.5, and an activator-to-precursor ratio of 0.429 yielded the highest 28-day unconfined compressive strength (UCS) of 22.10 ± 5.40 MPa. Furthermore, using an optimized formulation of 50.12% NMW, SH-to-SS ratio of 0.516, and an activator-to-precursor ratio of 0.428, a UCS value of 36.30 ± 3.60 MPa was obtained. The result implies that the synthesized geopolymer material can be potentially used for concrete structures and pavers, pedestrian pavers, light traffic pavers, and plain concrete.

The influence of the type and amount of oxygen (O), nitrogen (N), and/or phosphorus (P) heteroatoms on the surface of carbon nanotube (CNT) on stability and catalytic activity in the oxygen reduction reaction (ORR) was investigated in alkaline media. It is shown that the functionalization of CNT leads to the growth of the electrochemically active surface and to an increase in the activity in ORR. At the same time, a decrease in stability is observed after the functionalization of CNT under accelerated corrosion testing in an alkaline media. These results are most significant on CNT after functionalization in HNO3 due to the formation of a large number of structural defects. However, the subsequent doping by N and / or P atoms provides a further activity increase and enhances the corrosion stability of CNT. Thus, as shown by the studies of characteristic parameters (SEAS, E1/2, corrosion stability), CNT doped with N and NP are a promising catalytic system that can be recommended for use as fuel cell cathodes. An important condition for effective doping is the synthesis of carboxyl and carbonyl oxygen containing group on the surface of CNT.

A portable urea sensor for use in the fast flow condition was fabricated using porous polytetrafluoroethylene (PTFE) membranes coated with amine-functionalized parylene, parylene-A, by vapor deposition. To generate a specific electrochemical sensor signal from urea, the urea-hydrolyzing enzyme urease was immobilized on the parylene-A-coated PTFE membranes via chemical crosslinking using glutaraldehyde. The urease-immobilized membranes were assembled in a polydimethylsiloxane (PDMS) fluidic chamber, and a screen-printed carbon three-electrode system was used for electrochemical measurements. The success of urease immobilization was confirmed using fluorescence microscopy, scanning electron microscopy, and Fourier-transform infrared spectroscopy. The optimum concentration of urease for immobilization on the parylene-A-coated PTFE membranes was determined to be 48 mg/mL, and the optimum number of membranes in the PDMS chamber was found to be 8. Using these optimized conditions, we fabricated the urea biosensor and monitored urea samples under various flow rates ranging from 0.5 to 10 mL/min in the flow condition using chronoamperometry. To test the applicability of the sensor for physiological samples, we used it for monitoring urea concentration in the waste peritoneal dialysate of a patient with chronic renal failure, at a flow rate of 0.5 mL/min.

The effect of γ-ray irradiation on surface plasmon resonance (SPR) sensing capability of refractive index (n = 1.418–1.448) of the silica glass optical fiber comprised of germano-silicate glass cladding embedded with Au nano-particles (NPs) was investigated. As the γ-ray irradiation increased from 1 hour to 3 hours with the dose rate of 1,190 Gy/h, the morphology of the Au NPs and the SPR spectrum were found to change. The average diameter of Au NPs increased with the aspect ratio from 1 to 2 and the nano-particles became grown to the clusters. The SPR peak wavelength shifted towards longer wavelength with the increase of total dose of γ-ray irradiation regardless of the corresponding refractive indices. The SPR sensitivities (wavelength/refractive index unit, nm/RIU) also increased from 407 nm/RIU to 3,553 nm/RIU, 1,483 nm/RIU, and 2,335 nm/RIU after the γ-ray irradiation at the total dose of 1,190 Gy, 2,380 Gy, and 3,570 Gy, respectively.

The incorporation of plastic matrix composite materials into structural elements of the aeronautical industry requires contour machining and drilling processes along with metallic materials prior to final assembly operations. These operations are usually performed using conventional techniques, but they present problems derived from the nature of each material that avoid implementing One Shot Drilling strategies that work separately. In this work, the study focuses on the evaluation of the feasibility of Abrasive Waterjet Machining (AWJM) as a substitute for conventional drilling for stacks formed of Carbon Fiber Reinforced Plastic (CFRP) and aluminum alloy UNS A97050 through the study of the influence of abrasive mass flow rate, traverse feed rate and water pressure in straight cuts and drills. For the evaluation of the straight cuts, Stereoscopic Optical Microscopy (SOM) and Scanning Electron Microscopy (SEM) techniques are used inspection techniques have been used. In addition, the kerf taper through the proposal of a new method and the surface quality in different cutting regions have been evaluated. For the study of holes, the macrogeometric deviations of roundness, cylindricity and straightness have been evaluated. Thus, this experimental procedure reveals the conditions that minimize deviations, defects, and damage in straight cuts and holes obtained by AWJM.

An investigation was made to determine the effects of tungsten surface coating on the coefficient of friction of sliding contact between lubricated steel surfaces. The four-ball test was modified, using a tungsten carbide ball bearing in the spindle to cause sliding contact onto three hard steel ball bearings coated with tungsten disulfide lamellar dry lubricant coating, with a coating of grease lubrication applied to the ball bearings. The coatings, loads, speed, and grease level was varied to best understand the impact of different conditions to the friction coefficient.

Polluted rivers are a primary problem in Changhua County, Taiwan, due to rapid and massive developments in agriculture and industry. In this study, samples consisted of water influent from the Yangzi-Cuo River, Ci-Tong Jiao, Changhua County. Ecology technology, a combination of gravel contact oxidation and surface flow constructed wetlands, was employed to enhance the water quality. Ecology technology is a useful and ordinary process that focuses on original treatment of pollution through chemical, physical, and biological procedures based on the mediums of soil, plant, water, and microorganisms from pure environments. Moreover, this study aimed to minimize the river pollution index (RPI) of the Yangzi-Cuo River by using combinations of gravel contact oxidation and surface flow constructed wetlands. The inflow volume of the water samples in situ was found to be 1534–2261 cubic meters per day (CMD). The pollution in the water sample mostly involved suspended solid (SS), ammoniacal nitrogen (NH₃–N), total phosphorus (TP), total nitrogen (TN), and biochemical oxygen demand (BOD), and the values of the above indexes were found to be 10.0–26.7 mg/L, 0.9–14.0 mg/L, 1.2–14.1 mg/L, 11.1–18.2 mg/L, and 0.5–3.6 mg/L, respectively. Efficiencies of pollution elimination in SS, NH₃–N, TP, TN, and BOD were found to be 24.2–93.1%, 58.3–86.2%, 5.2–85.0%, 59.4–77.2%, and 46.3–76.4%, correspondingly, after purification treatment via ecology technology. Thus, ecology technology is a valid means of purification treatment for polluted rivers.

In the present work a novel, portable and innovative eNose composed of a surface acoustic wave (SAW) sensor array based ZIF-8, and ZIF-67 nanocrystals (pure and combined with gold nanoparticles) as sensitive layers has been tested as a non-invasive system to detect and differentiate disease markers, such as acetone, ethanol and ammonia, related with early diagnosis of diabetes mellitus through exhaled breath. The sensors have been prepared by spin coating, achieving continuous and homogenous sensitive layers. Low concentrations (5 ppm, 10 ppm and 25ppm) of the marker analytes were measured, obtaining high sensitivities, good reproducibility, short time response and fast signal recovery.

High-resolution laboratory-based thermal infrared spectroscopy is an up-and-coming tool in the field of geological remote sensing. Its spatial resolution allows for detailed analyses at centimeter to sub-millimeter scale. However, this increase in resolution creates challenges with sample characteristics such as grain size, surface roughness and porosity that can influence the spectral signature. This research explores the effect of rock sample surface preparation on the TIR spectral signatures. We applied three surface preparation methods (split, saw and polish) to determine how the resulting differences in surface roughness affects both the spectral shape as well as the spectral contrast. The selected samples are a pure quartz sandstone, a quartz sandstone containing a small percentage of kaolinite, and an intermediate-grained gabbro. To avoid instrument or measurement type biases we conducted measurements on three TIR instruments, resulting in directional hemispherical reflectance spectra, emissivity spectra and bi-directional reflectance images. Surface imaging and analyses were performed with scanning electron microscopy and profilometer measurements. We demonstrate that surface preparation affects the TIR spectral signatures influencing both the spectral contrast as well as the spectral shape. The results show that polished surfaces predominantly display a high spectral contrast while the sawed and split surfaces display up to 25% lower reflectance values. Furthermore, the sawed and split surfaces display spectral signature shape differences at specific wavelengths, which we link to mineral transmission features, surface orientation effects and multiple reflections in fine-grained minerals. Hence, the influence of rock surface preparation should be taken in consideration to avoid an inaccurate geological interpretation.

Within the task of replacing bronze journal bearings with aluminum the processes taking part on friction surface of high-alloyed aluminum alloys working with steel are investigated. The surface and subsurface layer of experimental aluminum bearings were studied before and after tribological tests by scanning electron microscopy including energy-dispersive analysis. Both structural and composition changes in surface layer are shown. It has been revealed that secondary structures are formed on the surface during friction process and include all the chemical elements of the tribosystem which is a consequence of its self-organization. The interaction behavior of some chemical elements of tribological system is discussed.

Detection of early stage corrosion on slender steel members is crucial for preventing buckling failures of steel structures. An active photoacoustic fiber optic sensors (FOS) system has been reported for early stage steel corrosion detection of steel plates and rebars using surface ultrasonic waves. The objective of this paper is to investigate the surface corrosion/rust detection problem on steel rods using numerically simulated surface ultrasonic waves. The finite element method (FEM) is applied in simulating the propagation of ultrasonic waves on steel rod models. Transmission mode of damage detection is adopted, in which one source (transmitter) and one sensor (receiver) are considered. In this research, radial displacements at the receiver were simulated and analyzed by short-time Fourier transform (STFT) for detecting, locating, and quantifying a surface rust located between the transmitter and the receiver. From our time domain and frequency domain analyses, it is found that the presence, location, and dimensions (length, width, and depth) of surface rust can be estimated by ultrasonic waves propagating through the surface rust.

Maritime Continent (MC) positions in between Asian and Australian summer monsoons zone. Its complex topography and shallow seas around it is a major challenge for the climate researchers to model and understand it. Monsoon in this area is affected by inter-scale ocean-atmospheric interactions like El-Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Madden-Julian Oscillation. Monsoon rainfall in MC (especially in Indonesia and Malaysia) profoundly exhibits its variability dependency on ocean-atmospheric phenomena in this region. This monsoon shift often introduces to dreadful events like biomass burning (BB) in Southeast Asia (SEA) which sometimes leads to severe trans-boundary haze pollution. In this study, the episode of BB in 2015 of SEA is highlighted and discussed. Observational satellite datasets are tested by performing simulations with numerical weather prediction (NWP) model using WRF-ARW (Advanced research WRF). Observed and model datasets are compared to study the sea surface temperature (SST) and precipitation (rainfall) anomalies influenced by ENSO, IOD and MJO. Correlations have been recognised which explains the delayed rainfall of regular monsoon in MC due to the influence of ENSO, IOD and MJO during 2015 BB episode, eventually leading to intensification of fire and severe haze.

Degradation of environment quality is currently the prime cause of the recent occurrence of natural disasters; it also contributes in the increase of the area that is prone to natural disasters. This research is aimed to map the potential of areas around Pesanggrahan river in DKI Jakarta by segmenting the Digital Elevation Model derived from LIDAR data. The objective of this segmentation is to find the watershed lines of the DEM image. Data processing in this research is using LIDAR data which take the ground surface data, which is overlaid with Jakarta river map and subsequently, the data is then segmented the image. The expected result of the research is the flood potential area information, especially along the Pesanggrahan river in South Jakarta.

The properties of rubber are strongly influenced by the distribution of filler within the polymer matrix. Here we introduce a Monte Carlo-based morphology generator. The basic elements of our model are cubic cells, which, in the current version, can be either silica filler particles or rubber volume elements in adjustable proportion. The model allows the assignment of surface free energies to the particles according to whether a surface represents, for instance, 'naked' silica or silanised silica. The amount of silanisation is variable. We use a nearest-neighbour site-exchange Monte Carlo algorithm to generate filler morphologies, mimicking flocculation. Transmission electron micrographs (TEM) as well as small angle scattering (SAS) intensities can be calculated along the Monte Carlo trajectory. In this work we demonstrate the application of our morphology generator in terms of selected examples. We illustrate its potential as a tool for screening studies, relating interface tensions between the components to filler network structure as characterized by TEM and SAS.

Nowadays, the study of preparing silica/rubber composites, which can be used in “green tire”, in energy saving method is fast-growing. In our work, silica modified by using alcohol polyoxyethylene ether (AEO) and 3-Mercaptopropyltriethoxysilane (K-MEPTS) together were investigated. Thermal gravimetric analyzer (TGA) result indicated that both AEO and K-MEPTS could be grafted on the silica surface. Raman spectroscopy confirmed that the AEO could generate a certain steric hindrance for the mercaptopropyl group on K-MEPTS. Silica modified by using AEO and K-MEPTS together can be completely co-coagulated with the rubber in preparing silica/natural rubber (NR) composites by latex compounding method. AEO can form a physical interface between silica and rubber; meanwhile, K-MEPTS can form a chemical interface between silica and rubber. The effects of chemical and physical interface between silica and rubber on dynamic and mechanical performances of silica/NR composites were also given in this research. A proper combination of physical and chemical interface between silica and NR can improve performances of silica/NR composites.

The epidermal growth factor receptor (EGFR) plays vital roles in cellular processes including cell proliferation, survival, motility and differentiation. Dysregulated activation of the receptor is often implicated in human cancers. EGFR is synthesized as a single-pass transmembrane protein, which consists of an extracellular ligand-binding domain and an intracellular kinase domain separated by a single transmembrane domain. The receptor is activated by a variety of polypeptide ligands such as epidermal growth factor and transforming growth factor α. It has long been thought that EGFR is activated by ligand-induced dimerization of the receptor monomer, which brings intracellular kinase domains into close proximity for trans-autophosphorylation. An increasing number of diverse studies, however, demonstrate that EGFR is present as a pre-formed, yet inactive, dimer prior to ligand binding. Furthermore, recent progress in structural studies has provided insight into conformational changes during the activation of a pre-formed EGFR dimer. Upon ligand binding to the extracellular domain of EGFR, its transmembrane domains rotate or twist parallel to the plane of the cell membrane, resulting in reorientation of the intracellular kinase domain dimer from a symmetric inactive configuration to an asymmetric active form (the “rotation model”). This model is also able to explain how oncogenic mutations activate the receptor in the absence of ligand without assuming that the mutations induce receptor dimerization. In this review, we discuss mechanisms underlying ligand-induced activation of the preformed EGFR dimer, as well as how oncogenic mutations constitutively activate the receptor dimer, based on the rotation model.

The present study propose an innovative turn-boring operation method and focuses on finding optimal turn-boring process parameters for Ti-6Al-4V by considering multiple performance characteristics using Taguchi orthogonal array with the grey relational analysis, the effect of machining variables such as, feed rate, depth of cut and cutting speed are optimized with considerations of multiple performance characteristics namely surface roughness, roundness error, material removal rate and power consumption the optimal values were found out from the Grey relational grade. The result of the Analysis of Variances (ANOVA) is shown that the most significant factor is cutting speed, followed by feed rate, radial depth of cut. Finally, confirmation tests were carried out to make a comparison between the experimental results. Experimental results have shown that machining performance in the turn-boring process can be improved effectively through this approach.

Land Surface Temperature (LST) is routinely retrieved from remote sensing instruments using semi-empirical relationships between top of atmosphere (TOA) radiances and LST, using ancillary data such as total column water vapor or emissivity. These algorithms are calibrated using a set of forward radiative transfer simulations that return the TOA radiances given the LST and the thermodynamic profiles. The simulations are done in order to cover a wide range of surface and atmospheric conditions and viewing geometries. This work analyses calibration strategies, considering some of the most critical factors that need to be taken into account when building a calibration dataset, covering the full dynamic range of relevant variables. A sensitivity analysis of split-windows and single channel algorithms revealed that selecting a set of atmospheric profiles that spans the full range of surface temperatures and total column water vapor combinations that are physically possible seems beneficial for the quality of the regression model. However, the calibration is extremely sensitive to the low-level structure of the atmosphere indicating that the presence of atmospheric boundary layer features such as temperature inversions or strong vertical gradients of thermodynamic properties may affect LST retrievals in a non-trivial way. This article describes the criteria established in the EUMETSAT Land Surface Analysis – Satellite Application Facility to calibrate its LST algorithms applied both for current and forthcoming sensors.

A method for estimating river water surface elevation (WSE) from Landsat imagery using the river inundation area - water surface elevation (RIA-WSE) rating curve constructed from the U.S. Geological Survey Topobathymetric Elevation Model (TEM) data was developed and tested at six gauging stations along the upper Mississippi River. The Otsu's automatic threshold selection algorithm was employed for the image classification and estimation of inundation areas within each pre-defined polygon around each gauging station. In addition to the commonly used green-band based water indices, Landsat 8 and 9 OLI's ultra-blue, blue, and red band-based water indices were also tested in this study, which resulted in twenty different water indices: NDWIv (Normalized Difference Water Index), MNDWI1v and MNDWI2v (Modified Normalized Difference Water Index), AWEIsv (Automatic Water Extraction Index with shadow), and AWEInsv (AWEI without shadow), where v represents the visible light band used in the water index. At each station, about 60-80 Landsat 8 or 9 images during 2013-2023 were used for assessing the performances of the twenty water indices through comparing the estimated WSEs with the measured WSEs. Results showed that the ultra-blue or red band-based AWEIs yielded the most accurate estimations of WSEs among the twenty tested water indices.

In a previous companion study, satellite data were used to describe peculiar characteristics of ocean surface wave fields, generated by two extra-tropical cyclones (ETCs) rapidly propagating in the North Atlantic. Based on a 2D parametric wave model, further details are now provided to analyse and interpret the spatio-temporal evolution of ETC very intense generated waves. Significant wave height and wavelength values are shown to reach extreme values, 18 m and 500 m, respectively. Resulting energetic swell systems waves then radiate in the whole eastern part of North Atlantic, and more particularly in the Norwegian sea region. Moving to higher latitudes, wind forcing characteristics of ETCs evolve, with the shape of the wind field changing from quasi-cyclonic to "air jets/Icelandic lows". In this paper, the resulting swell generation and propagation, after the deformation of an individual ETC, are studied, as well. Confirmed with comparisons with multi-satellite observations, the application of the parametric-2D wave-ray model is demonstrated to provide robust and highly detailed information on wave generation under very complex wind regime changes.

Gold nanoparticles (NPs) are among the most commonly employed metal NPs in biological applications, with their distinctive physicochemical features. Their extraordinary optical properties, stemming from the strong localized surface plasmon resonance (LSPR), contribute to the devel-opment of novel approaches in the areas of bioimaging, biosensing, and cancer research, especially for photothermal and photodynamic therapy. The ease of functionalization with various lig-ands provides a novel approach to the precise delivery of these molecules to targeted areas. Gold NPs ability to transfer heat and electricity positions them as valuable materials for advancing thermal management and electronic systems. Moreover, their inherent characteristics, such as in-ertness, give rise to the synthesis of novel antibacterial and antioxidant agents as they provide a biocompatible and low-toxic approach. Chemical and physical synthesis methods are utilized to produce gold NPs. The pursuit of more ecologically sustainable and economically viable large-scale technologies, such as environmentally benign biological processes referred to as green/biological synthesis, has garnered increasing interest among global researchers. Green synthesis methods are favorable among other synthesis techniques as they minimize the necessity for hazardous chemicals in the reduction process due to their simplicity, cost-effectiveness, energy efficiency, and biocompatibility. This article discusses the importance of gold NPs, their optical and conductivity properties, antibacterial, antioxidant, and anticancer properties, synthesis methods, contemporary uses, and biosafety, emphasizing the need to understand toxicology principles and green commercialization strategies.

Welding spot defect detection using deep learning methods provides an effective way of body-in-white quality monitoring. Based on the existing Faster R-CNN model, this paper proposed an improved faster R-CNN model for resistance welding spot surface defect inspection to improve inspection efficiency and accuracy. The model contains the following improvements. Firstly, the improved algorithm uses anchor box with higher confidence output by the RPN network to locate welding spots. When a defect is detected and the detection system is in a suspended state, the Fast R-CNN network is used to confirm the defect category and details. Secondly, a new pruning model is proposed to replace the entire backbone neural network, which unnecessary convolutional layers and connection layers are deleted, and some parameters of each hidden layer are further reduced. On the premise of ensuring detection accuracy, the parameter quantity is extremely reduced, and the speed is improved. Experiments show that the model proposed in this paper took about 15ms for one single image test, and both the detection accuracy and recall rate reached over 90% according to the test on our dataset. This deep learning model meets the requirements of welding spot defect detection.

Additive Manufacturing (AM), also know as 3D Printing (3DP), is a widely used layer-by-layer manufacturing process, it is evolving rapidly both in research and industry. Among all AM methods, Material Extrusion (ME) is one of the most popular techniques. Based on ME, another new AM method is developed, which is Low-cost Metal Material Extrusion (LCMME). In this newly developed process, pure metallic parts could be fabricated after sintering the metal infused additively manufactured parts. Both AM and sintering process parameters will have influence on the quality of the final pure metallic parts. In this research, several statistics methods were used to analyze the data gotten from the experiment. Then two Machine Learning (ML) algorithms were used to predict the Surface Roughness (SR) of the final specimens. Additionally, the results show that the neural network (NN) is more accurate than the support vector regression (SVR) on prediction.

The lack of access to drinking water is a problem that affects many towns in the Province of Santa Fe. Many people affected by this situation use groundwater for consumption, cooking, and irrigation. In this work, a colorimetric analytical technique is used to quantify arsenic. It is sufficiently sensitive, simple, and economical to apply to the towns of interest. This work synthesized a hybrid sorbent in the form of magnetite-chitosan spheres (M-Q). The sorption capacity of this new sorbent for As removal was 270% greater than that of chitosan spheres (Q), which was 30%. Another advantage of this hybrid sorbent is the capability of being sep-arated by its magnetic properties. The work was done with groundwater (Andino, Province of Santa Fe) with high conductivity (12.1 µS/cm), hardness (1125 mg/L CaCO3), and an As(V) concentration of 265 µg/L. The removal capacity from groundwater was optimized using a composite factorial design, and for the conditions of mass 0.49 g, pH 5.24, and contact time of 81.23 min, it was found to be 81%.

Deflectometry is a key component in the precise measurement of specular (mirrored) surfaces, however traditional methods often lack an end-to-end approach that performs 3D reconstruction in a single shot with high accuracy and generalizes across different free-form surfaces. This paper introduces a novel deep neural network (DNN)-based approach for end-to-end 3D reconstruction of free-form specular surfaces using single-shot deflectometry. Our proposed network, VUDNet, innovatively combines discriminative and generative components to accurately interpret orthogonal fringe patterns and generate high-fidelity 3D surface reconstructions. By leveraging a hybrid architecture integrating a Variational Autoencoder (VAE) and a modified U-Net, VUDNet excels in both depth estimation and detail refinement, achieving superior performance in challenging environments. Extensive data simulation using Blender, leading to a dataset which we are making available, ensures robust training and enables the network to generalize across diverse scenarios. Experimental results demonstrate the strong performance of VUDNet, setting a new standard for 3D surface reconstruction. The implementation of VUDNet is available on GitHub at https://github.com/hadious/VUDNet.

The term ‘photocatalysis’ has recently gained high popularity, and various products using photocatalytic functions have been commercialized. Of all the materials that may be used as photocatalysts, TiO₂ is virtually the only one that is now and most likely will remain appropriate for industrial application. Water and air purification systems, sterilization, hydrogen evolution, self-cleaning surfaces, and photoelectrochemical conversion are just a few of the products and applications in the environmental and energy domains that make extensive use of TiO₂ photocatalysis. This is due to the fact that TiO₂ has the lowest cost, most stability, and most effective photoactivity. Furthermore, history attests to its safety for both people and the environment because it has been used as a white pigment since antiquity. This review discusses some important aspects and issues concerning different synthesis methods and their influence on the structure and properties of TiO₂, as well as the concept of photocatalysis based on it as a promising biocompatible functional material that has been widely used in recent years. The advantages of TiO₂ applications in various fields of science and technology are discussed, including environmental protection, photocatalysis including self-cleaning surfaces, water and air purification systems, hydrogen liberation, photovoltaic energy, cancer diagnosis and therapy, coatings and dental products, etc. Information on the structure and properties of TiO₂ phases, as well as modern methods of synthesis of functional materials based on them are presented. This is followed by a detailed review of the basic principles of TiO₂ photocatalysis with a brief introduction to the modern concept of TiO₂ photocatalysis. Finally, the challenges and prospects of TiO₂ photocatalysis for various applications are briefly discussed. Recent advances in the fundamental understanding of TiO₂ photocatalysis at the atomic-molecular level are highlighted, and important recent advances in TiO₂ photocatalysis are summarized in terms of the design and engineering of new materials.

In this study, a novel and efficient method was developed for the extraction of total flavonoids from Flos Sophorae Immaturus (FSI) using ultrasound-assisted deep eutectic solvent (UAE-DES). Different DES formulations were first investigated and choline chloride/1,2-propanediol (ChCl/PD) was identified as the optimal solvent due to its highest flavonoid yield. The extraction process was optimized through single factor experiments and response surface methodology (RSM). An extraction temperature of 68 °C, a sonication time of 41 minutes, a water content of 21% and a liquid-solid ratio of 21 mL/g were identified as the optimal conditions. Under these conditions, a maximum flavonoid yield of 378.77 mg RE/g DW was achieved. The crude extract was further purified using a macroporous D-101 resin, resulting in a flavonoid extract with a purity of 83.11 ± 3.54%. The antioxidant activity of the purified extract (FSPE) was evaluated using DPPH and ABTS radical scavenging assays, showing significant antioxidant properties with IC50 values of 52.50 μg/mL and 49.47 μg/mL, respectively. The UAE-DES method developed in this study not only significantly improves the extraction yield of flavonoids from FSI, but is also in line with sustainable and environmentally friendly practices. This method offers an environmentally friendly, efficient and scalable approach for the extraction of bioactive compounds from medicinal plants and has potential applications in the food, pharmaceutical and dietary supplement industries.

Exosomes are small extracellular vesicles produced by almost all cell types in the human body and exosomal microRNAs (miRNAs) are small non-coding RNA molecules that are known to serve as important biomarkers for diseases such as cancer. Given that the upregulation of miR-106b is closely associated with several types of malignancies, the sensitive and accurate detection of miR-106b is important but difficult. In this study, a surface acoustic wave (SAW) biosensor was developed to detect miR-106b isolated from the cancer cells based on immunoaffinity separation technique using our unique paddle screw device. Our novel SAW biosensor could detect a miR-106b concentration as low as 0.024 pM in a linear range from 0.1 pM to 1.0 μM with a correlation coefficient of 0.9939. Additionally, we were able to successfully detect miR-106b in total RNA extracted from the exosomes isolated from the MCF-7 cancer cell line, a model system for human breast cancer, with performance comparable to commercial RT-qPCR methods. Therefore, the exosome isolation by paddle screw method and the miRNA detection using the SAW biosensor has the potential to be used in basic biological research and clinical diagnosis as an alternative to RT-qPCR.

Improving photobioreactor performance for microalgae cultivation has attracted many researchers over the past years. One of the primary challenges associated with existing photobioreactors is the light penetration. An effective photobioreactor design should maximize light penetration, ensuring uniform illumination throughout the reactor. This study aims to assess the impact of light intensity on microalgal growth from the perspective of energy efficiency and productivity in two photobioreactors. A novel cactus-like and a cylindrical photobioreactor were designed and fabricated using 3D printing technology. These two photobioreactors were used to cultivate two strains of microalgae. The novel photobioreactor achieved a maximum biomass productivity of 0.99 g/L/d and a maximum energy efficiency of 0.3139 g/d/kWh. The cylindrical photobioreactor reached a maximum biomass productivity of 0.74 g/L/d and 0.2199 g/d/kWh of energy efficiency. The increase in biomass productivity can be linked to enhancements in the photobioreactor's surface-to-volume ratio and better light utilization.

In this investigation, the impact of reducing agent concentration on the synthesis of zinc oxide nanoparticles was examined. During the synthesis, an assessment of ionic conductivity was carried out, revealing a significant increase in conductivity prior to the introduction of the reducing agent, followed by a sharp decrease upon its addition. Characterization of the ZnO NPs involved UV-visible spectroscopy, scanning electron microscopy, Fourier Infrared Spectroscopy, and X-Ray Diffraction analysis. The outcomes suggest that the characteristics of the ZnO NPs are influenced by the concentration of the reducing agent during the synthesis process. Notably, the ZnO NPs synthesized with a higher concentration of reducing agent exhibited a narrower optical band gap and increased surface energy. Furthermore, employing a concentration of 0.5 v/v resulted in the rapid production of nanoparticles with relatively uniform sizes. Conversely, concentrations below 0.5 v/v lead to slow formation, while concentrations exceeding 0.5 v/v yielded non-uniform nanoparticles.

The aim of this study is to develop a software solution for real-time recognition of sign language words using two arms. This will enable communication between hearing-impaired individuals and those who can hear. Several sign language recognition systems have been developed using different technologies, including cameras, armbands, and gloves. The system developed in this study utilizes surface electromyography (muscle activity) and inertial measurement unit (motion dynamics) data from both arms. Other methods often have drawbacks, such as high costs, low accuracy due to ambient light and obstacles, and complex hardware requirements, which have prevented their practical application. A software has been developed that can run on different operating systems using digital signal processing and machine learning methods specific to the study. For the test, we created a dataset of 80 words based on their frequency of use in daily life and performed a thorough feature extraction process. We tested the recognition performance using various classifiers and parameters and compared the results. The Random Forest algorithm was found to have the highest success rate with 99.875% accuracy, while the Naive Bayes algorithm had the lowest success rate with 87.625% accuracy. Feedback from a test group of 10 people indicated that the system is user-friendly, aesthetically appealing, and practically useful. The new system enables smoother communication for people with hearing disabilities and promises seamless integration into daily life without compromising user comfort or lifestyle quality.

We investigated the micro-threaded stem taper surface and the impact on premature failures, aseptic loosening, and infection. We have focused on the fretting, and crevice corrosion of micro-threaded tapers, as well as the characterization of microstructure and surface properties of two new and three retrieved Zweymüller stem tapers of cementless hip endoprostheses selected from a set of 45 stems. The retrievals examined were those in which the sole source of modularity with a metallic component was the head-stem taper interface between the Ti alloy taper stem and the ceramic head. To determine the surface chemistry and microstructures of both new and retrieved hip endoprostheses stem taper titanium alloy, scanning electron microscopy (SEM) was employed for morphological and microstructural analyses. At the same time, energy dispersive spectroscopy (EDS) was utilized for characterizing chemical element distribution, and electron backscattered diffraction (EBSD) was used for phase analysis. The micro-threated stem taper’s roughness for different manufacturers was investigated using an optical profilometer. Standard roughness pa-rameters Ra (average surface roughness) and Rz (mean peak to valley height of the roughness pro-file) were used in this investigation.Additionally, profile depth and peak spacing for different samples were investigated. The surface roughness results indicate no significant difference in roughness associated with varying survivorship times, ranging from 3 to 239 months, and across different manufacturers. Electrochemical studies revealed no fretting corrosion in retrieved stem tapers (ceramic head) that prematurely failed due to aseptic loosening after 239 months, infection after 3 months, and low-grade infection after a 32-month lifetime. Therefore, three retrieved ta-pers and two new ones for comparison underwent potentiodynamic measurements in Hank’s so-lution to ascertain the corrosion rate of new and retrieved stem taper surfaces. The results show a low corrosion rate for both new and retrieved samples that failed prematurely due to aseptic loosening. However, the corrosion rate of infected and low-grade infected tapers was higher. In conclusion, our study aligns with existing literature, suggesting that the use of ceramic heads de-creases the problem of taper corrosion and subsequently reduces premature failures in total hip arthroplasty.

Friction stir welding (FSW) is a solid state welding process for joining metallic alloys and dissimilar metals. It has emerged as an alternative technology for welding high strength alloys that are difficult to join with conventional techniques. FSW is used to produce products with better mechanical properties. Now a days aluminum alloys have been widely used in several industrial applications such as aerospace, marine, automobile and commercial applications due to their light weight structure, better mechanical properties and high corrosion resistance.In this work, three welding parameters such as spindle speed, welding speed and plunge depth were considered for friction stir welding. FSW was carried out between dissimilar aluminum alloy plates (AA6061 and AA 8011) to produce butt joint.A Box-Behnken design with three factors and three levels was chosen to minimize the number of experimental conditions .The tensile strength and hardness of the welded regions were evaluated. The optimum level settings and the major parameters that influence the joint strength were obtained by Box-Behnken design.

EV transmissions operate at high speeds, upto 30,000 rpm. High speed operation puts higher demands on bearings, seals, and gears. Bearings in EV transmissions are prone to electrically induced bearing damage and may exhibit signs of pitting and fluting. Surface-initiated rolling contact fatigue is another common problem gaining increased attention lately. Most EV transmissions require a coupling between an oil-lubricated gearbox to an electrical motor that runs with minimal lubrication at very high rpm. High mechanical and thermal stresses the seals are exposed to under starved lubrication conditions have a detrimental impact on their service life. Hence, proper lubrication is critical. In general, EV transmission fluids call for a somewhat different spectrum of properties compared to conventional ATF. Gear tribology simulations open new ways to the design and optimization of lubrication for EV transmissions. Additionally, such simulations can also provide valuable insights into the effects of different oil properties on cooling and lubrication efficiencies, thereby helping in matching the lubricant and hardware characteristics for optimal performance. In the present communication, we demonstrate the effects of different lubricants and surface finishing technologies on the tribology of high-speed gears using tribological tests and advanced thermal elastohydrodynamic (TEHD) simulations. Important roles of lubricity additives and surface finish optimization are highlighted in conjunction with a move towards ultralow viscosity EV transmission fluids.

Measurements of temperature and salinity in the Amazon River plume in the open ocean of the western tropical North Atlantic are considered. The measurements were carried out using the AML CTD probe in the upper layer and a flow-through system that measures salinity and turbidity of seawater while the vessel is on the way. Additionally, archive oceanographic data from the WOD18 database, data of satellite altimetry measurements (AVISO), and satellite salinity data from Aquarius and SMOS were used. It is shown that the width of the Amazon plume is about 300–400 km, the depth of desalination is from 50 to 100 m. Surface salinity decreases compared to the background (36 PSU) by 0.5 PSU in February and more than by 3 PSU in September during the period of maximum development of the plume, which is determined from satellite measurements of surface salinity. Lagrangian modeling of the back-in-time advection of passive markers simulating freshwater particles was carried out. It was shown that the source of fresh water in the measurement area is the discharge of the Amazon.

Surface roughness prediction is a pivotal aspect of the manufacturing industry, as it directly influences product quality and process optimization. This study introduces a predictive model for surface roughness in the turning of complex-structured workpieces, utilizing Gaussian Process Regression (GPR) informed by vibration signals. The model captures parameters from both the time and frequency domains of the turning tool, encompassing the mean, median, standard deviation (STD), and root mean square (RMS) values. The signal is from the time to frequency domain is executed using Welch's method, complemented by time-frequency domain analysis employing three levels of Daubechies Wavelet Packet Transform (WPT). The selected features are then utilized as inputs for the GPR model to forecast surface roughness. Empirical evidence indicates that the GPR model can accurately predict the surface roughness of turned complex-structured workpieces. This predictive strategy has the potential to improve product quality, streamline manufacturing processes, and minimize waste within the industry.

Per- and polyfluoroalkyl substances (PFAS), a large group of developing contaminants, have recently become the subject of increased concern due to their potentially hazardous effects. They are classified as poisonous substances that can be found in a variety of aquatic situations. The widespread usage of PFAS across numerous industries has resulted in a high environmental and biological accumulation of the substance. Identification and elimination of PFAS from the environment is crucial since they are tenacious and have the potential to cause cancer. Traditional methods of PFAS content assessment, while useful in some cases, are often inadequate for continuing environmental control and monitoring. Within academia, there is a noticeable desire for rapid, cost-effective, durable, and readily transportable techniques targeted at detecting PFAS compounds in field settings. As a result, environmental labs and other governmental and non-governmental bodies may start testing more often as mandated by legislation. PFAS-detecting sensors, which offer an innovative solution that can be applied in situ and is affordable and simple to use, have emerged as a promising method for assessment based on the existing research. In addition, it may give administrators and users of water worldwide useful information they can use. This article provides a thorough summary of recent developments, limitations, and performance considerations in PFAS detection sensors. The Surface-enhanced Raman scattering (SERS) method has also been covered because of its excellent sensitivity and specificity for detecting pollutants, making it a potential solution for sensing PFAS. Intelligent sensing systems for PFAS detection should benefit from this research.

The rapid development of electric vehicles, unmanned aerial vehicles, and wearable electronic devices has led to a high interest in research related to the synthesis of graphene with a high specific surface area for energy applications. However, the problem of graphene synthesis scalability, as well as the lengthy duration and high energy intensity of the activation processes of carbon materials, are significant disadvantages. In this study, a reactor was developed for the green, simple, and scalable electrochemical synthesis of graphene oxide with a low oxygen content of 14.1 %. The resulting material was activated using a fast joule heating method. The processing of mildly oxidized graphene with a high–energy short electrical pulse (32 ms) made it possible to obtain a graphene–based porous carbon material with a specific surface area of up to 1984.5 m2/g. The low energy intensity, simplicity, and use of environmentally friendly chemicals render the proposed method scalable.

Literature review indicates that the basic microstructure of Ti-6Al-4V is bimodal which consist of two phases: α + β, and it occurs after the fabrication in conventional methods such as casting, plastic forming or machining processes. After the additive manufacturing methods, there could be significant changes in the microstructure. Due to the rapid heat exchange during heat-treatment process, bimodal microstructure transforms into lamellar microstructure which consists of two phases α′ + β. Despite applying optimum printing parameters, 3D-printed products exhibit typical surface defects and discontinuities. Recently, two of the primary technologies for the improvement of surface layer properties of titanium alloys are shot peening and electropolishing. Literature review signalizes that shot peening and electropolishing processes have positive impact on the corrosion behaviour, mechanical properties and the condition of the surface layer of titanium alloy. Furthermore, there is a lack of studies about combining shot peening and electropolishing in one hybrid process on titanium alloys, which could synthesize the benefits of both processes. The scope of future investigation is also included in this review.

Chromium-nickel austenitic stainless steels are widely used due to their high corrosion resistance, good weldability and deformability. To some extent, their application is limited by their mechanical characteristics. As a result of their austenitic structure, increasing the static and dynamic strength of the components can be achieved by surface cold work. Due to the tendency of these steels to undergo intercrystalline corrosion, another approach to improve their mechanical characteristics is the use of low-temperature thermo-chemical diffusion processes. This article proposes a new combined process based on sequentially applied diamond burnishing (DB) and low-temperature gas nitriding (LTGN) to optimally improve the fatigue strength of 304 steel. The essence of the proposed approach is to combine the advantages of the two processes (DB and LTGN) to create a zone of residual compressive stresses in the surface and subsurface layers–the enormous surface residual stresses (axial and hoop) introduced by LTGN, with the significant depth of the compressive zone characteristic of static surface cold working processes. DB (both smoothing and single-pass hardening), in combination with LTGN, achieves a fatigue limit of 600 MPa, an improvement of 36.4% compared to untreated specimens. Individually, smoothing DB, single-pass DB and LTGN achieve 540 MPa, 580 MPa and 580 MPa, respectively. It was found that as the degree of plastic deformation of the surface layer introduced by DB increases, the content of the S-phase in the nitrogen-rich layer formed by LTGN decreases, with resultant increased content of -phase, and a new (also hard) phase: stabilized nitrogen-bearing martensite.

Because the including of human anatomy forms the foundation for clinical medicine, it has contributed a pivotal role in medical education for many centuries. Thus with advancements in the science of modern, current day medicine, its continued place in the medical school curriculum deserves careful attention. In an attempt to provide guidance to decision-makers involved in clinical anatomy curriculum development at the medical school level, the Educational Affairs Committee of the American Association of Clinical Anatomists (AACA) developed this document, which defines the contours of a gross anatomy curriculum leading to the M.D. or D.O. degree. The main body of the document sets forth the anatomical concepts as well as the subject matter a student should master prior to graduation from medical school. Gross anatomy dissection is still a crucial topic in graduate and medical school. The nature and content of gross anatomy, which was historically regarded as a core course in the first year of medical education in MBBS, MD, DO, and some PhD and Graduate curricula as well as in other disciplines of selective graduate education and non-allopathic medical programs, have been significantly impacted by emerging challenges in the pedagogy of delivering medical education in the past ten years. A seemingly ever-increasing emphasis on additional modules in molecular biology, emerging pharmacotherapeutics and pathophysiology content have resulted in a condensation and apparent erosion of previously allotted classroom and laboratory hours in the gross anatomy curriculum. In addition, an imposition of financial constraints and a decreasing availability of sufficient cadaver donations to support gross anatomy dissection labs has also occurred in some locations. An innovative clinically focused cadaveric anatomy program is described which has improved the delivery and content retention of medical and graduate students and has become one of the most sought-after modules in the revised clinically oriented curriculum and has been deemed highly relevant to current medical education and graduate studies.

A unique method for synthesizing a surface modifier for metallic hydrogen permeable mem-branes based on non-classic bimetallic pentagonally structured Pd-Pt nanoparticles has been de-veloped. It was found that nanoparticles had unique hollow structure. This significantly reduces the cost of their production due to economical use of metal. According to the results of electro-chemical studies, synthesized bimetallic Pd-Pt/Pd-Ag modifier showed excellent catalytic activi-ty (up to 60.72 mA cm–2), long-term stability and resistance to COads poisoning in alkaline oxida-tion reaction of methanol. The membrane with pentagonally structured Pd-Pt/Pd-Ag modifier showed the highest hydrogen permeation flux density up to 27.3 mmol s–1 m–2. Obtained hy-drogen flux density were 2 times higher than that for membranes with classic Pdblack/Pd-Ag modifier and an order of magnitude higher than that for unmodified membrane. Since the rate of transcrystalline hydrogen transfer through a membrane increased, while the speed of transfer through defects remained unchanged, a one and a half times rise in selectivity of the developed Pd-Pt/Pd-Ag membranes was recorded and it amounted to 3514. Achieved results are due to both the synergistic effect of the combination of Pd and Pt metals in the modifier composition and the large number of available catalytically active centers, which are present as a result of non-classic morphology with high-index facets. The specific faceting, defect structure and unusual properties provide great opportunities for the application of nanoparticles in the areas of membrane reac-tors, electrocatalysis, petrochemical and hydrogen industries.

Tropical sea surface temperature (SST) variability, mainly driven by the El Niño–Southern Oscillation (ENSO), influences the atmospheric circulation and hence the transport of heat and chemical species in both the troposphere and stratosphere. This paper uses Met Office, ERA5 and MERRA2 reanalysis data to examine the impact of SST variability on the dynamics of the polar stratosphere and ozone layer over the period 1980 to 2020. Particular attention is paid to studying the differences in the influence of different types of ENSO (East Pacific (EP) and Central Pacific (CP)) for the El Niño and La Niña phases. It is shown that during the EP El Niño, the zonal wind weakens more strongly and changes direction more often than during the EP El Niño, and the CP El Niño leads to a more rapid decay of the polar vortex (PV), an increase in stratospheric air temperature and an increase in the concentration and total column ozone than during EP El Niño. For the CP La Niña, the PV is more stable, which often leads to a significant decrease in Arctic ozone. During EP La Niña, powerful sudden stratospheric warmings are often observed, which lead to the destruction of PV and an increase in column ozone.

Mechanical engineering plays an important role in the design and manufacture of medical devices, implants, prostheses, and other medical equipment, where the machining of bio-compatible materials have a special place. There are a lot of different conventional and non-conventional types of machining of biocompatible materials. One of the most frequently used methods is milling. The first part of this paper considers the optimization of machining parameters for minimizing surface roughness in milling biocompatible alloy Ti-6Al-4V. With four factors (cutting speed, feed rate, depth of cut, and cooling/lubricating method), each having three levels, the full factorial design implies 81 experiments have to be carried out. Using the Taguchi method, the experiment number was reduced from 81 to 27 runs through an orthogonal design. According to the analysis of variance (ANOVA), the most significant parameter for surface roughness is feed rate. In the second part possibilities of different ML techniques to create a predictive model for average surface roughness using previously created small dataset are explored. Several ML technologies and techniques that can deal successfully with small dataset were explored. The best results show commonly used machine learning algorithm Random Forest that is widely used in regression problems.

Optimizing input parameters not only improves production efficiency and processing quality but also plays a crucial role in the development of green manufacturing engineering practices. The aim of the present study is to conduct a comparative evaluation at cutting performance and machinability process during the turning of AISI 4340 steel under different cooling conditions. The study analyses cutting operations during turning using dry, minimum quantity lubrication (MQL), and nano-MQL. As control parameters in the experiments, three different cooling types, cutting speed (100, 150, 200 m/min), and feed rate (0.1, 0.15, 0.20 mm/rev) levels were applied. The experiment results present that the optimal output values are found as Vb=0.15 mm, Ra=0.81µm, 88.1 dB for sound intensity, and I=4.18 A for current. Moreover, variance analysis (ANOVA) was performed to determine the effects of input parameters on response values. Under dry, MQL, and nano-MQL processing conditions, parameters affecting tool wear, surface roughness, current by the motor shaft, and sound level were examined in detail, along with the chip morphology. The responses obtained were optimized according to the Taguchi S/N method. As a result of optimization, it was concluded that the optimum values for cutting conditions (A3B1C1) were nano-MQL cooling and V=100 m/min, f=0.1 mm/rev cutting. Last but not least, it was observed that there was a 13% improvement in tool wear, 7% in current, 9% in surface roughness, and 8% in sound intensity compared to the standard conditions. In conclusion, it was determined that nano-MQL and the lowest level of cutting and feed rate values provided the optimum results.

In order to solve the problem of many constraints and complex navigation environment in the path planning of unmanned surface vehicle(USV), an improved Sparrow search algorithm com-bining Cubic chaotic map and Gaussian random walk strategy was proposed to plan it. Firstly, in the population initialization stage, Cubic chaotic map was used to replace the random generation method of the traditional sparrow search algorithm to optimize the uneven initial distribution of the population and improve the global search ability of the population. Secondly, in the late it-eration of the algorithm, the standard deviation of fitness is introduced to determine whether the population is trapped in the local optimum. If true, the Gaussian random walk strategy is used to perturb the optimal individual and assist the algorithm to escape the local optimum. Thirdly, the chosen water environment is modeled, and the navigation information of the original inland electronic navigation chart(ENC) is preprocessed, gridized, and the obstacle swelling is processed. Finally, the path planning experiments of USV are carried out in inland ENC grid environment. The experimental results show that, compared with the traditional sparrow search algorithm, the average fitness value of the path planned by improved sparrow search algorithm is reduced by 14.8%, and the variance is reduced by 49.9%. The path planned by the algorithm is of good quality and high stability, and combined with ENC, it can provide a reliable path for USV.

A novel approach based on response surface methodology (RSM) was developed to predict and apply the best extraction conditions for the isolation of various-type polyphenolic antioxidants from the dried flower buds of Magnolia x soulangeana Soul.-Bod. var. ‘Lennei’ (Magnoliaceae). As a method of choice, ultrasound-assisted extraction was used and the optimized extraction parameters (temperature, time of extraction, the composition of aqueous-ethanolic extractants and solvent to solid ratio) have been determined using a central composite design factorial analysis, followed by appropriate spectrophotometric methods (with Folin–Ciocalteu and 2,2-diphenyl-1-picrylhydrazyl reagents) to determine the antioxidant and antiradical potential of extracts, respectively. The use of 66.8% (V/V) ethanol, as the extraction solvent during the 55.2 min extraction protocol, and the ratio of extractant volume to herbal substance of 46.8 mL/g gave the highest total yield of bioactive antioxidant phenolics in the extract obtained. For this herbal preparation, qualitative and quantitative analysis was performed using combined chromatographic (LC), spectroscopic (PDA) and tandem mass spectrometric (ESI-QTOF–MS/MS) techniques. A detailed phytochemical profiling, conducted for the first time, documented substantial amounts of polyphenolic antioxidants, especially phenylethanoids and flavonoids in the flower buds of M. soulangeana ‘Lennei’. Their average total content exceeded 30.3 and 36.5 mg/g dry weight, respectively.

Due to the non-degradability of petroleum-based packaging materials, serious environmental pollution and the depletion of non-renewable resources have become pressing issues. In order to actively promote green production and address these concerns, there is an urgent need for new packaging materials to replace traditional plastic products. Starch-based packaging materials, composed of starch, fiber, and plasticizers, offer a degradable and environmentally friendly alternative. Starch alone cannot undergo thermoplastic processing due to its inherent structural characteristics. Therefore, researchers have explored modifications by incorporating plasticizers to create processable thermoplastic starch (TPS). However, there are challenges related to the high crystallinity and poor compatibility between TPS and fibers, resulting in decreased mechanical properties. To address these challenges, a novel approach combining plasticizer optimization and response surface method (RSM) optimization has been proposed to enhance the mechanical properties of starch-based packaging materials. This method leverages the advantages of composite plasticizers and process parameters. The findings demonstrate that the composite plasticizer effectively disrupt the hydrogen bonding and granule morphology of starch, leading to a significant reduction in crystallinity. Based on these findings, the optimal process parameters are determined using the RSM, resulting in a forming temperature of 198 °C, forming time of 5.4 minutes, and AC content of 0.84 grams. Compared with the non-optimized values, the tensile strength increases by 12.2% and the rebound rate increases by 8.1%.

In this study, we considered the structural stability, electronic properties, and phonon dispersion of the cubic (c-ZrO₂), tetragonal (t-ZrO₂), and monoclinic (m-ZrO₂) phases of ZrO₂. We found that the monoclinic phase of zirconium dioxide is the most stable among the three phases in terms of total energy, lowest enthalpy, highest entropy, and other thermodynamic properties. The smallest negative modes were found for m-ZrO₂. Our analysis of the electronic properties showed that during the m–t phase transformation of ZrO₂, the Fermi level first shifts by 0.125 eV toward higher energies and then decreases by 0.08 eV in the t–c cross-section. The band gaps for c-ZrO₂, t-ZrO₂, and m-ZrO₂ are 5.140 eV, 5.898 eV, and 5.288 eV, respectively. Calculations based on the analysis of the influence of doping 3.23, 6.67, 10.35, and 16.15 mol. %Y₂O₃ onto the m-ZrO₂ structure showed that the enthalpy of m-YSZ decreases linearly, which accompanies further stabilization of monoclinic ZrO₂ and an increase in its defectiveness. The doping-induced and concentration-dependent phase transition of zirconium dioxide under the influence of yttrium oxide was studied, after which the position of the Fermi level changes and the energy gap decreases. It has been established that, not only for pure systems but including those doped with Y₂O₃, the main contribution to the formation of the conduction band is made by the p-states of electrons. The t-ZrO₂ (101) and t-YSZ (101) surface models were selected as optimal surfaces for water adsorption based on a comparison of their surface energies. An analysis of the mechanism of water adsorption on the surface of t-ZrO₂ (101) and t-YSZ (101) showed that H₂O on unstabilized t-ZrO₂ (101) is adsorbed dissociatively with an energy of -1.22 eV, as well as by the method of molecular chemisorption with an energy of -0.69 eV and the formation of a hydrogen bond with a bond length of 1.01 Å. In the case of t-YSZ (101), water is molecularly adsorbed onto the surface with an energy of -1.84 eV. Dissociative adsorption of water occurs at an energy of -1.23 eV, near the yttrium atom. The calculations showed that ab initio research methods are capable of describing the mechanism of phase transitions of materials under the influence of alloying. That is, by optimizing the parameters of DFT calculations, it is possible to observe the effects of doping on other physical and chemical properties of materials, which are still beyond the scope of quantum chemical modeling. The obtained results complement the database of research works carried out in the field of the application of biocompatible zirconium dioxide crystals and ceramics in green energy generation and can be used in designing humidity-to-electricity converters and creating solid oxide fuel cells based on ZrO₂.

: (1) Background: Hepatitis B core antibodies (anti-HBc) are a marker of hepatitis B virus (HBV) exposure; hence a normal HBV serology profile is characterized by HBV surface antigen (HBsAg) and anti-HBc positivity. However atypical HBV serologies occur and we aimed to determine the prevalence of an atypical profile (HBsAg+/anti-HBc-) in a cohort of people with HIV-1 (PWH) in Botswana. (2) Methods: Plasma samples from an HIV-1 cohort in Botswana (2013-2018) were used. Samples were screened for HBsAg and anti-HBc. Next generation sequencing was done using the GridION platform. Wilcoxon rank-sum test and Chi-squared tests were used for comparison of continuous and categorical variables respectively. (3) Results: HBsAg+/anti-HBc- prevalence was 13.7% (95% CI 10.1 – 18.4) (36/263). HBsAg+/anti-HBc- participants were significantly younger (p&lt;0.001), female (p=0.02), ART naïve (p=0.04) and had detectable HIV viral load (p=0.02). There were no mutational differences in sequences isolated from participants with HBsAg+/anti-HBc- versus those with HBsAg+/anti-HBc+ serology. (4) Conclusions: We report a high HBsAg+/anti-HBc– atypical serology profile prevalence among PWH in Botswana. We caution against HBV testing algorithms that consider only anti-HBc+ samples for HBsAg testing as they are likely to underestimate HBV prevalence. Studies to elucidate the mechanisms and implications of this profile are warranted.

In response to reducing the energy cost of unmanned surface vehicles (USVs) while overcoming the low accuracy problem in surface target detection, a lightweight detection algorithm with multi-scale feature fusion is proposed. Based on the popular one-stage lightweight Yolov7-tiny target detection model, a lightweight extraction module is designed first by introducing the multiscale residual module to reduce the number of parameters and computational complexity while improving accuracy. The Mish and SiLU activation functions are used to enhance network feature extraction. Second, the path aggregation network employs coordinate convolution to strengthen spatial information perception. Finally, the dynamic head, which is based on the at-tention mechanism, improves the representation ability of object detection heads without any computational overhead. According to the experimental findings, the proposed model has 22.1% fewer parameters than the original model, 15% fewer GFLOPs, a 6.2% improvement in mAP@0.5, a 4.3% rise in mAP@0.5:0.95, and it satisfies the real-time criteria. According to the research, the suggested lightweight water surface detection approach includes a lighter model, a simpler computational architecture, more accuracy, and a wide range of generalizability. It performs bet-ter in a variety of difficult water surface circumstances.

Temporary streams are a key component of the hydrological cycle in arid and semi-arid regions, but their flow is highly variable and difficult to measure. In this paper, we present a novel approach that could be used to assess the flow of temporary streams and characterize their environmental status. Specifically, we apply the Image Velocimetry method to estimate surface velocity in temporary streams using unmanned aerial vehicles (UAVs) equipped with optical sensors (IV-UAV method). The IV-UAV method enables the easy, safe and quick estimation of the velocity on the water’s surface. This method was applied in different temporary streams in Lesvos Island, Greece. The produced results show that the IV-UAV can be implemented at low discharges, at temporary streams and at small streams. However, there were many occasions that measurements were unable due to various reasons such as dense vegetation or archaeological sites. Despite of this, the proposed methodology could be incorporated in optical protocols which are used to assess the environmental status of temporary streams of Mediterranean conditions. Finally, this would become a valuable tool for understanding the dynamics of these eco-systems and monitoring changes over time.

Saltwater intrusion in the rapidly developing city of Da Nang in central Vietnam is currently causing various water-related challenges, including inadequate water supply and water pollution. An integrated SWAT-MODFLOW numerical model was used to investigate the origin and mechanism of saltwater in Holocene and Pleistocene aquifers. Geophysical and isotopic approaches were used to validate the SEAWAT model applied for simulating saltwater intrusion. The results suggest that the ebb and flow of tides, as well as water levels in rivers primarily impact coastal aquifers. However, effective water resource planning and management, along with maintaining the natural recharge of fresh water from local rain during the rainy season, could enable the rational and efficient utilization of groundwater, reducing saltwater intrusion in many areas. During the dry season, groundwater is recharged from higher altitude areas. The current saltwater intrusion mainly occurs along the rivers up to the hydraulic dam. Simulated models, using scenarios of stop abstracting groundwater, but changing to the use of surface water for drinking water, show that the area of saline water shrinks quickly after 30 years, reducing from 59.6 km2 to 39.5 km2 and from 40.2 km2 to 28.6 km2 in Holocene and Pleistocene, respectively.

During submerged laser peening using a pulsed laser, a bubble that behaves like cavitation is generated after laser ablation (LA). The bubble is referred to as laser cavitation (LC). The amplitude of the shock-wave in LA water is larger than that of LC; however, the impact passing through the target metal during LC is larger than that of LA. Thus, submerged laser peening is referred to as “laser cavitation peening”, as the peening method using the cavitation impact is known as “cavitation peening”. The impact induced by a hemispherical bubble is more aggressive than that of a spherical bubble with a microjet. Laser cavitation peening can improve the fatigue strength of metallic materials by producing work-hardening and the introduction of compressive residual stress. Three-dimensional additive manufactured metals (3D metals) such as titanium alloy are attractive materials for aviation components and medical implants; however, the fatigue strength of as-built components is nearly half that of bulk metals, and this is an obstacle for the applications of 3D metals. In the present study, published research papers were reviewed to identify the key factors of laser cavitation peening, with additional visualization of LC and data. Then, improvements in the fatigue strength of metallic materials, including 3D metals produced by laser cavitation peening, were summarized.

In this study, a numerical simulation of fluid flow through railway ballast in the time domain is presented, providing a model for unsteady-state flow. It is demonstrated that the position of the free surface with respect to time can also be used to solve the steady flow case. The effect of ballast fouling is included in the model to capture the realistic behavior of railway ballast, which is critical to understanding the impact of flooding. A thorough comparison with a range of previous studies, including theoretical and experimental approaches, is made and very close agreement is obtained. The significant impact of ballast fouling on fluid flow and its potential consequences for railway infrastructure are highlighted by the simulation. Valuable insights into the behavior of water flow through porous media and its relevance to railway ballast management are offered by this study.

Surfaces of additively manufactured metal parts from powder-based processes typically show powder particle agglomerations and other features, resulting in high surface roughness. Proper characterization of those surfaces is necessary in order to assess part quality with respect to coatability, mechanical performance or corrosion resistance for use in aerospace, automotive, medical and more industrial applications. Optical surface texture measurement allows for collection of areal surface data, while the established contact stylus method only captures line profile data. When applying optical methods for surface topography measurements, proper data acquisition and post-processing in order to assess surface texture may be complex. A number of variables can be adjusted, such as different measurement settings, approaches to outlier removal, evaluated area size or form removal. This work shows the influence of selected z-range prior to measurement and the influence of choosing pre-defined outlier removal settings in MountainsMap 9.2 on selected ISO 25178-2:2022 parameters calculated from data obtained from confocal microscopy for as-built Ti6Al4V from laser powder bed fusion. The aim is to show the influence of variation in measurement and post-processing on calculated surface texture parameters and stress the importance of proper documentation in order to achieve reproducibility of data for quality management.

Controlling the selectivity of detonation initiation reaction of explosive is a Holy Grail, and it seems to be an “idiot's daydream”, by strengthening external electric field, to reduce the explosive sensitivity. The effects of external electric fields on the initiation reactions in NH2NO2∙∙∙NH3, a model system of the nitroamine explosive with alkaline additive, were investigated at the MP2/6-311++G(2d,p) and CCSD/6-311++G(2d,p) level. The concerted effect in the intermolecular hydrogen exchange is characterized by an index of the imaginary vibrations. Due to the weakened concerted effects by the electric field along the −x-direction opposite to the “reaction axis”, the dominant reaction changes from the hydrogen exchange to 1,3-intramolecular hydrogen transference with the increase of the field strengths. Furthermore, the stronger the field strengths, the higher the barrier heights become, indicating the lower sensitivities. Therefore, by strengthening the field strength and adjusting the orientation between the field and “reaction axis”, not only can the reaction selectivity be controlled, but also the sensitivity can be reduced, in particular under a super-strong field. Thus, a traditional concept, which the explosive is dangerous under the super-strong external electric field, is broken theoretically. Compared to the neutral medium, the low sensitivity of the explosive with alkaline can be achieved under the stronger field. Employing atoms in molecules, reduced density gradient and surface electrostatic potentials, the origin of the reaction selectivity and sensitivity change is revealed. This work provides a new idea to the technical improvement for adding the external electric field into the explosive system.

Continuous rigid frame bridges across valleys are often at the risk of rockfalls caused by heavy rainfalls, earthquakes and debris flows in a mountainous country. Hollow thin-walled bridge piers (HTWBP) in valleys are exposed to the threat of the impact of accidental rockfalls. In the current research, ANSYS/LS-DYNA is used to establish a high-precision rockfall-HTWBP model. The rockfall-HTWBP model is verified against a scaled impact test of a previous research. A mesh independence test is also performed to obtained an appropriate mesh size. Based on the rockfall-HTWBP model, the impact force, damage and dynamic response characteristics of HTWBP under the rockfall impact are studied. In addition, a damage assessment criteria is proposed based on the response surface model combined with Central Composite Design method and Box-Behnken Design method. The main conclusions are as follows: 1）The impact force of rockfall has a substantial impulse characteristic, and the duration of the impulse load is approximately 0.01s. 2）The impacted surface of the pier is dominated by the final elliptic damage with the conical and strip damage areas as the symmetry axis. The cross-sectional damage mode is compression failure in the impact area and shear failure at the corner. 3）The maximum displacement occurs in the middle height of the pier. The maximum displacement increases with impact height, impact velocity and rockfall diameter and decreases with the uniaxial compressive strength of the concrete. 4) The initial impact velocity and diameter of the rockfall are the most significant parameters affecting the damage indices. In addition, a damage assessment method with a damage zoning diagram based on the response surface method is established for the fast assessment of the damage level of impacted HTWBP.

Seyfe Lake is an important part of the natural ecosystem of Central Anatolia and lies within a 1487 km² closed basin. Groundwater withdrawal for irrigation and recent climatic change have caused lake area to decrease for decades and to completely disappear briefly in August 2008. Groundwater quality is crucial for sustainable irrigation in the Seyfe Basin. A key finding of this study is the difference in the Hardie-Eugster alkalinity-to-calcium ratio of the lake water and that of most groundwater wells in the basin. This difference in the chemical signature of Seyfe Lake and basin groundwater means the evaporative salinization pathway of most groundwater discharged into the lake cannot account for the composition of Seyfe Lake. The ratio of actual evapotranspiration to precipitation will increase under current climate change projections. A second finding, with implications for soil salinization, is that most groundwater in Seyfe Basin has a Hardie-Eugster alkalinity-tocalcium ratio greater than unity, meaning soil alkalization will accompany soil salinization.

Three-Dimensional mesoporous TiO2 scaffolds of anatase phase possess inherent eximious optical behavior that are beneficial in designing photoelectrodes for solar energy conversion applications. However, substantial efforts have been devoted in maximizing the UV and/or visible light absorption efficiency, and suppressing the annihilation of photogenerated charged species in pristine mesoporous TiO2 structure for improved solar illumination conversion efficiencies. This study provides the fundamental insights into Mxene functionalized mesoporous TiO2 as photoelectrode for the first time. This novel combination of Mxene functionalized TiO2 electrodes with and without TiCl4 treatments have been successfully optimized to intensify the process of photon absorption, charge segregation and photocurrent, resulting in superior photoelectrode performance. The photocurrent measurements of prepared photoelectrodes are significantly enhanced upon increased contents of Mxene due to improved absorption efficiency within the visible region as verified by UV–Vis absorption spectroscopy. Moreover, as evident through structural analysis, the anatase phase of TiO2 is well grown due to increased contents of Mxene and post-deposition heat treatments. Consequently, an appreciable coverage of well-developed grains on FTO surface observed in SEM images. Thereby, the newly fabricated conductive mesoporous TiO2 photoelectrodes are potential candidates for photoinduced energy conversion and storage purposes.

We reveal the significance of plasmonic nanoparticle’s (NP) shape and its surface morphology en route to an efficient self-assembled plasmonic nanoparticle cluster. A simplified model is simulated in the form of free-space dimer and trimer nanostructures (NPs in shape of sphere, cube, and disk). A ~ 200 % to ~ 125% raise in near field strength (gap mode enhancement) is observed for spherical NPs in comparison with cubical NPs (from 2 nm to 8 nm gap sizes). Full-width three-quarter maximum reveals better broad-spectral optical performance in a range of ~ 100 nm (dimer) and ~ 170 nm (trimer) from spherical NPs as compared to a cube (~ 60 nm for dimer and trimer). These excellent properties for sphere-based nanostructures are merited from its dipole mode characteristics.

This paper consists of two parts. In part I some new relations for a field theory with time intervals are derived. One concept of field theory evaluated is complementarity, another is field operators both defined within a time interval description. Part II includes specific results and commentary. Discussed are time interval dependent wave propagation surfaces for star source emission waves and derived is a metric propagation surface area requirement. The results allow to consider one same field that like gravitation within General Relativity applies to both non zero and zero mass. The associated field energy is space time dependent for non zero mass, and is related to a space time dependent metric tensor for zero mass wave particles. Defined is internal energy transfer where wave particle numbers increase linearly and mass and momentum diminish, decrease inversely with the distance from the wave emission source. The commentary are applications related to cosmological overall volume and temperature dependence.

Electromagnetic eddy current sensors are commonly used to identify and quantify the surface notches of metals. However, the unintentional tilt of eddy current sensors affects results of size profiling, particularly for the depth profiling. In this paper, based on the eddy current thin-skin regime, a revised algorithm has been proposed for the analytical voltage or impedance of a tilted driver–pickup eddy current sensor scanning across a long ideal notch. Considering the resolution of the measurement, the bespoke driver–pickup, also termed as transmitter-receiver (T-R) sensor is designed with a small mean radius of 1 mm. Besides, the T-R sensor is connected to the electromagnetic instrument and controlled by a scanning stage with high spatial travel resolution , with a limit of 0.2 μm and selected as 0.25 mm. Experiments have been out on the voltage imaging of an aluminium sheet with 7 machined long notches of different depths using T-R sensor under different tilt angles. By fitting the measured voltage (both real and imaginary part) with proposed analytical algorithms, the depth profiling of notches is less affected by the tilt angle of sensors. From the results, the depth of notches can be retrieved within a deviation of 10 % for tilt angles up to 60 degrees.

A new approach to fabricate TiNi surfaces combining the advantages of both monolithic and porous materials for implants is used in this work. New materials were obtained by depositing a porous TiNi powder onto monolithic TiNi plates followed by sintering at 1200°C. Then, further modification of the material surface with a high-current-pulsed electron beam (HCPEB) was carried out. Three materials obtained (one after sintering and two after subsequent beam treatment by 20 and 30 pulses, respectively) were studied by XRD, SEM, EDX, EIS methods, profilometry and OCP measurements. Structural and compositional changes caused by HCPEB treatment were investigated. Surface properties of the samples during their storage in saline for 10 days were studied and a model experiment with cell growth (MCF-7) was carried out for the sample unmodified with electron beam to detect cell appearance on different surface locations.

Sea surface partial pressure of CO2 (pCO2) is a critical parameter in the quantification of air-sea CO2 flux, which plays an important role in calculating the global carbon budget and ocean acidification. In this study, we use chlorophyll-a concentration (Chla), sea surface temperature (SST), absorption due to dissolved and particulate detrital matter (Adg), diffuse attenuation coefficient of downwelling irradiance at 490nm (Kd) and mixed layer depth (MLD) as input data for retrieving the sea surface pCO2 in the North Atlantic based on a remote sensing empirical approach with the Categorical Boosting (CatBoost) algorithm. The results show that the root mean square error (RMSE) is 8.25μatm, the mean bias error (MAE) is 4.92μatm and the coefficient of determination (R2) can reach 0.946 in the validation set, which mean that the CatBoost model makes an improvement compared to other models in the published studies. In the further analysis of the spatial and temporal distribution of the sea surface pCO2 in the North Atlantic, it can be found that the North Atlantic sea surface pCO2 has a clear trend with latitude variations and have strong seasonal changes. Furthermore, the sea surface pCO2 in this area is mainly affected by sea temperature and salinity, and influenced by biological activities in some sub-regions.

In this work, we propose simple and robust technique for the retrieval of underlying surface spectral albedo using spaceborne observations. It can be used to process both multispectral moderate resolution satellite data and also multi - zone high spatial resolution data. The technique can work automatically for different types of land surfaces without using huge databases accumulated in advance. The new cloud discrimination and retrieval of the water vapor content in atmosphere procedures are presented. The key point of the proposed atmospheric correction technique is the suggested single-wavelength method for determining the atmospheric aerosol optical thickness without reference to a specific type of underlying surface spectrum. The retrievals of spectral albedo for various land surfaces with developed technique, performed using computer simulation and experimental data, have demonstrated a high retrieval accuracy.

The Kummer surface was constructed in 1864. It corresponds to the desingularisation of the quotient of a 4-torus by 16 complex double points. Kummer surface is kwown to play a role in some models of quantum gravity. Following our recent model of the DNA genetic code based on the irreducible characters of the finite group G5:=(240,105)≅Z5⋊2O (with 2O the binary octahedral group), we now find that groups G6:=(288,69)≅Z6⋊2O and G7:=(336,118)≅Z7⋊2O can be used as models of the symmetries in hexamer and heptamer proteins playing a vital role for some biological functions. Groups G6 and G7 are found to involve the Kummer surface in the structure of their character table. An analogy between quantum gravity and DNA/RNA packings is suggested.

Recent studies investigated the detectability of ship wake signatures on SAR imagery using a large number of SAR images collocated with Automatic Identification System data for training machine learning models. These detectability models are in agreement with oceanographic expectations from preceding studies and can therefore be used for comparing the performance of different SAR sensors in terms of wake detectability. Previous model comparisons showed better wake detection performance of TerraSAR-X (TS-X) than of RADARSAT-2 (RS2) and Sentinel-1 (S1). A comparison between CosmoSkymed (CSK) and RS2 is performed here, to examine the hypothesis that X-Band is generally better for wake detection than C-Band. Finally, this hypothesis is not confirmed, as the detectability models for TS-X, CSK and RS2 reveal similar performances. A comparison of wake detection performance should take the individual wake components into account separately.

Land Surface Temperature is a one of the key variable of Global climate changes and model which estimate radiating budget in heat balance as control of climate model. It is a major influenced factor by the ability of the surface emissivity. In this study, were used Landsat 8 satellite image that have Operational Land Imager and Thermal Infrared Sensor to calculate Land Surface Temperature through geospatial technology over Ampara district, Sri Lanka. The Land Surface Temperature was estimated with respect to Land Surface Emissivity and Normalized Difference Vegetation Index values determined from the Red and Near Infrared channels. Land Surface Emissivity was processed directly by the thermal Infrared bands. Pixels based calculation were used to effort at LANDSAT 8 images that thermal Band 10 various dates in this study. The results were achievable to compute Normalized Difference Vegetation Index, Land Surface Emissivity, and Land Surface Temperature with applicable manner to compare with land use/ land cover data. It determines and predicts the changes of surface temperature to favorable to decision making process for the society. Study area faces seasonal drought in Sri Lanka, the prediction method that how land can be efficiently used with the present condition. Therefore, the Land Surface Temperature estimation can prove whether new irrigation systems for agricultural activities or can transformed source of energy into useful form that introducing solar hubs for energy production in future.

The selection of biomaterials for biomedical application is a significant challenge. In the last few decades, various bioabsorbable and stable biopolymers have been applied for use as biomedical devices in orthopedic applications. Ultra-high molecular weight polyethylene (UHMWPE) has been extensively used in medical implants, notably in the bearings of hip, knee, and other joint prostheses, owing to its biocompatibility and high wear resistance. For the ACL graft, synthetic UHMWPE is an ideal candidate due to its biocompatibility and its extremely high tensile strength. Despite the appeal of new advanced materials such as carbon fiber, poly-ether-ether ketone, and other load-bearing materials, UHMWPE remains a primary load-bearing candidate material for ACL reconstructions because of its extremely high strength, the simplicity of the fabrication process, its biocompatibility, and low friction. However, some significant problems are observed in UHMWPE based implants, such as wear debris, and oxidative degradation due to the generation of free radicals when exposed to irradiation with gamma rays for grafting or sterilization. Various innovative methodologies have been developed to resolve those problems and enhance the properties of UHMWPE. In this review, we will explore in detail the methods for surface functionalization of UHMWPE and will apply these findings to the case study of UHMWPE for Anterior Cruciate Ligament repair.

This study was aimed at investigating the protective effects of glass ionomer cement (GIC) and surface pre-reacted glass ionomer (S-PRG) fillers used as dental restorative materials on demineralization of bovine enamel. GlasIonomer FX ULTRA (FXU), Fuji IX GP Extra (FIXE), CAREDYNE RESTORE (CDR) were used as GICs. PRG Barrier Coat (BC) was used as the S-PRG filler. They were incubated in a lactic acid solution (pH = 4.0) for 6 d at a temperature of 37 °C. The mineral was etched from the enamel surface, and a large number of Ca and P ions were detected in solution. The Al, F, Na, Sr, and Sr ions were released in GICs and S-RPG fillers. The Zn ion was released only in CDR and the B ion was released only in BC. The presence of apparent enamel prism peripheries was observed after 6 d of treatment for the group containing only enamel blocks. pH values for the FXU, FIXE, CDR, BC, and enamel block groups after 6 d were 6.5, 6.6, 6.7, 5.9, and 5.1, respectively. Therefore, the observed pH neutralization effect suppressed progression of caries due to the release of several ions from the restoratives.

Since its introduction, the Triangulation number has been the most successful and ubiquitous scheme for classifying spherical viruses. However, despite its many successes, it fails to describe the relative angular orientations of proteins, as well as their radial mass distribution within the capsid. It also fails to provide any insight into critical sites of stability, modifications or possible mutations. We show how classifying spherical viruses using icosahedral point arrays, introduced by Keef and Twarock, unveils new geometric rules and constraints for understanding virus stability and key locations for exterior and interior modifications. We present a modified fitness measure which classifies viruses in an unambiguous and rigorous manner, irrespective of local surface chemistry, steric hinderance, solvent accessibility or triangulation number. We then utilize these point arrays to explain the immutable surface loops of bacteriophage MS2, the relative reactivity of surface lysines in CPMV and the non-quasiequivalent flexibility of the HBV dimers. We explain how using sister and double point arrays can function as predictive tools for site directed modifications in other systems. This success builds on our previous work showing that viruses place their protruding features along the great circles of the asymmetric unit, demonstrating that viruses indeed adhere to these geometric constraints.

The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing (http://step.esa.int/main/toolboxes/snap/). In this work we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A/B measurements over clean and polluted snow fields. Using OLCI spectral reflectance measurements in the range 400-1020nm, we derive important snow properties such as spectral and broadband albedo, snow specific surface area, snow extent and grain size on the spatial grid of 300m. The algorithm also incorporates cloud screening and atmospheric correction procedures over snow surfaces. We present validation results using ground measurements from Antarctica, the Greenland ice sheet and the French Alps. We find the spectral albedo retrieved with accuracy of better than 3% on average, making our retrievals sufficient for a variety of applications. Broadband albedo is retrieved with the average accuracy of about 5% over snow. Therefore, the uncertainties of satellite retrievals are close to experimental errors of ground measurements. The retrieved surface grain size shows good agreement with ground observations. Snow specific surface area observations are also consistent with our OLCI retrievals. We present snow albedo and grain size mapping over the inland ice sheet of Greenland for areas including dry snow, melted/melting snow and impurity rich bare ice. The algorithm can be applied to OLCI Sentinel-3 measurements providing an opportunity for creation of long – term snow property records essential for climate monitoring and data assimilation studies - especially in the Arctic region, where we face rapid environmental changes including reduction of snow/ice extent and, therefore, planetary albedo.

Mediterranean coastal lagoons and their peripheral areas often provide a collection of habitats for many species, and they often face significant threats from anthropogenic activities. Diverse human activities in such areas directly affect the spatio-temporal dynamic of surface water and its ecological characteristics. Monitoring the surface water dynamic, and understanding the impact of human activities are of great significance for coastal lagoon conservation. The Regional Natural Park of Narbonne includes a typical Mediterranean lagoon complex where surface water dynamic and its potential link with local diverse human activities has not yet been studied. In this context, based on all the available Landsat images covering the study area during 2002-2016, this study identified the water and non-water classes for each satellite observation by comparing three widely used water indices (i.e., NDVI, NDWI and MNDWI) and using the Otsu method. The yearly water frequency index was then computed to present the spatio-temporal dynamic of surface water for each year, and three water dynamic scenarios were also identified for each year: permanent water (PW), non-permanent water (NPW) and non-water (NW). The spatial and inter-annual variation in the patterns of the three water scenarios were characterized by computing the landscape metrics at scenario-level quantifying area/edge, shape, aggregation and fragmentation. Finally, the quantitative link between different land use and land cover (LULC) types derived from the LULC maps of 2003, 2012 and 2015 and the surface water dynamic scenarios was established in each of the 300 m x 300 m grid cells covering the study area to determine the potential impact of human activities on the surface water dynamic. In terms of the inter-annual variation during 2002-2016, PW presented an overall stability, and NPW occupied only a small part of the water surface in each year and presented an inter-annual fluctuation. NPW had a smaller patch size, with lower connectivity degree and higher fragmentation degree. In terms of spatial variation during 2002-2016, NPW often occurred around PW, and its configurational features varied from place to place. Moreover, PW mostly corresponded to natural lagoon, and salt marsh (as a part of lagoons), and NPW had a strong link with arable land (agricultural irrigation) and salt marsh (salt production), sand beach/dune, coastal wetlands and lagoon for the LULC maps of 2003, 2012 and 2015. However, more in-depth analysis is required for understanding the impact of sand beach/dune, coastal wetlands and lagoon on surface water dynamics. This study covers the long-term variations of surface water patterns in a Mediterranean lagoon complex having intense and diverse human activities, and the potential link between LULC types and the water dynamic scenarios was investigated on different dates. The results of the study should be useful for environmental management and protection of coastal lagoons.

Aluminum profile surface defects can greatly affect the performance, safety and reliability of products. Traditional human-based visual inspection is low accuracy and time consuming, and machine vision-based methods depend on hand-crafted features which need to be carefully designed and lack robustness. To recognize the multiple types of defects with various size on aluminum profiles, a multiscale defect detection network based on deep learning is proposed. Then, the network is trained and evaluated using aluminum profile surface defects images. Results show 84.6%, 48.5%, 96.9%, 97.9%, 96.9%, 42.5%, 47.2%, 100%, 100%, 43.3% average precision(AP) for the ten defect categories, respectively, with a mean AP of 75.8%, which illustrate the effectiveness of the network in aluminum profile surface defects detection. In addition, saliency maps also show the feasibility of the proposed network.

Satellite-based remote sensing technologies are utilized extensively to investigate urban thermal environments under rapid urban expansion. Current MODIS data is, however, unable to adequately represent the spatially detailed information because of its relatively coarser spatial resolution, while Landsat data can’t explore temporally the refined analysis due to the low temporal resolution. In order to resolve this situation, we used MODIS and Landsat data to generate “Landsat-like” data by using the flexible spatiotemporal data fusion method (FSDAF), and then studied spatiotemporal variation of land surface temperature (LST) and its driving factors. The results showed that 1) The estimated “Landsat-like” data have high precision; 2) By comparing 2013 and 2016 datasets, LST increases ranging from 1.8°C to 4°C were measurable in areas where the impervious surface area (ISA) increased, while LST decreases ranging from -3.52°C to -0.70°C were detected in areas where ISA decreased; 3) LST has a strongly negative relationship with the Normalized Difference Vegetation Index (NDVI), and a strongly positive relationship with Normalized Difference Built Index (NDBI) in summer; and 4) LST is well correlated with Building density (BD), in a complex conic mode, and LST may increase by 0.460°C to 0.786°C when BD increases by 0.1. Our findings can provide information useful for mitigating undesirable thermal conditions and for long-term urban thermal environmental management.

This paper aims to study the surface homogenization and integrity of Ti-6Al-4V alloy by longitudinal-torsional coupled ultrasonic vibration assisted ball-end milling. A method of continuous processing between the flat surface and freeform surface connection is proposed by using ultrasonic vibration assisted ball-end precision milling, during this process, it is not necessary to exchange the cutting tool. The way has been explored for changing the homogenization of surface on Ti-6Al-4V by ultrasonic vibration-assisted milling (UVAM). Cutting experiments employing three parameters, cutting speed, feed rate and depth of cut and two types of machining forms using ball-end milling with UVAM and conventional milling (CM) respectively. The high frequency cutting force, finished surface roughness, topography and residual stresses on the surface and tool wear have been measured by advanced instruments. Particularly, adopting the high frequency cutting force measurement system, it is concluded cutting force in ball-end milling decreased significantly using UVAM as against CM. Moreover, the surface roughness by UVAM with ball-end milling is much better than the CM at a high cutting speed. However, an opposite trend is observed at a low cutting speed. Especially, there is a steep decrease from Ra 0.828 μm average value at 4000 rpm to Ra 0.129 μm average value at 5000 rpm. At the same time, the homogenization of surface roughness and residual stresses decrease significantly in UVAM as compared to which in CM when taking the transversal-longitudinal ratio into consideration. Cutting experiments and measuring results are demonstrated the validity and feasibility of UVAM with ball-end milling, and this method enjoys significant advantages compared to CM process.

A potassium bromide KBr material, which has been widely used as the key element in the Fourier spectrometers and as the output window of the IR-lasers, has been studied with good advantage via applying the carbon nanotubes in order to modify the potassium bromide surface. The laser oriented deposition method has been used to place the carbon nanotubes at the matrix material surface in the vertical position at the different electric field varied from 100 to 600 V×cm-1. The main idea of the improvement of the spectral properties of the potassium bromide structure is connected with the fact that the refractive index of the carbon nanotubes is substantially less than the refractive index of the studied material, and the small diameter of the carbon nanotubes allows one to embed these nano-objects in the voids of the lattice of the model matrix systems. Moreover, the mechanical characteristics and wetting features of the potassium bromide structures have been investigated under the condition mentioned above. Analytical and quantum-chemical simulations have supported the experimental results.

Conventional flame retardant (FR) application processes for textiles involve aqueous processing which is resource intensive in terms of energy and water usage. Recent research using sol-gel and layer-by-layer chemistries, while claimed to be based on more environmentally-sustainable chemistry, still require aqueous media with the continuing problem of water management and drying processes being required. This paper outlines the initial forensic work to characterise commercially produced viscose/flax, cellulosic furnishing fabrics which have had conferred upon them durable flame retardant (FR) treatments using a novel, patented atmospheric plasma/UV excimer laser facility for processing textiles with the formal name - Multiplexed Laser Surface Enhancement (MLSE) system. This system (MTIX Ltd., UK), is claimed to offer the means of directly bonding of flame retardant precursor species to the component fibres introduced either before plasma/UV exposure or into the plasma/UV reaction zone itself, thereby eliminating a number of wet processing cycles. Nine commercial fabrics, pre-impregnated with a semi-durable, proprietary FR finish and subjected to the MLSE process have been analysed for their flame retardant properties before and after a 40 °C 30 min water soak. For one fabric, the pre-impregnated fabric was subjected to a normal heat cure treatment which conferred the same level of durability as the plasma/UV-treated analogue. TGA and LOI were used to further characterise their burning behaviour and the effect of the treatment on surface fibre morphologies were assessed. Scanning electron microscopy indicated that negligible changes had occurred to surface topography of the viscose fibres occurred during plasma/UV excimer processing.

In common model testing practise, the measured values of the self propulsion test are split into the characteristics of the hull, the propeller and into the interaction factors. These coefficients are scaled separately to the respective full scale values and subsequently reassembled to give the power prediction. The accuracy of this power prediction depends {\em inter alia} on the accuracy of the measured values and the scaling procedure. An inherent problem of this approach is, that it is virtually impossible to verify each single step, because of the complex nature of the underlying problem. In recent years the scaling of the open-water characteristics of propeller model tests attracted a renewed interest, fuelled by competitive tests, which became the norm due to requests of the customer. This paper will show the influence of different scaling procedures on the predicted power. The prediction is compared to the measured trials data and the quality of the prediction will be judged. The procedures examined are the standard ITTC~1978 procedure plus derivatives of it: the Meyne, the strip method and the βᵢ-method.

A radial basis function network (RBFN) method is proposed to reconstruct daily Sea surface temperatures (SSTs) with limited SST samples. For the purpose of evaluating the SSTs using this method, non-biased SST samples in the Pacific Ocean (10°N–30°N, 115°E–135°E) are selected when the tropical storm Hagibis arrived in June 2014, and these SST samples are obtained from the OISST products according to the distribution of AVHRR L2p SST and in-situ SST data. Furthermore, an improved nearest neighbor cluster (INNC) algorithm is designed to search the optimal hidden knots for RBFNs from both the SST samples and the background fields. Then the reconstructed SSTs from the RBFN method are compared with the results from the optimum interpolation (OI) method. The statistical results show that the RBFN method has a better performance of reconstructing SST than the OI method in the study, and the average RMSE is 0.48°C for the RBFN method, which is quite smaller than the value of 0.69°C for the OI method. Additionally, the RBFN methods with different basis functions and clustering algorithms are tested, and we discover that the INNC algorithm with multi-quadric function is quite suitable for the RBFN method to reconstruct SSTs when the SST samples are sparsely distributed.