Damage and fibre misalignment of woven fabrics during discontinuous polymer processing remain challenging. To overcome these, a promising switchable elastomeric adherence gripper is introduced here. The inherent surface tackiness is utilized for picking and placing large sheets. Due to the elastomer’s viscoelastic material behavior, the surface properties depend on loading speed and temperature. Different peeling speeds result in different adherence strength of an interface between the gripper and the substrate. This feature is mechanically characterized and the viscoelastic behavior of the stamp is examined. Based on this experimental characterization, an empirical model is proposed. Furthermore, a discussion of the applicability and limitation of the elastomeric gripper is given.

In 1895, Korteweg and de Vries (KdV), derived their celebrated equation describing the motion of waves of long wavelength in shallow water. In doing so they made a number of quite reasonable assumptions, incompressibility of the water and irrotational fluid. The resulting equation, the celebrated KdV equation, has been shown to be a very reasonable description of real water waves. However there are other phenomena which have an impact on the shape of the wave, that of vorticity and viscosity. This paper examines how a constant vorticity affects the shape of waves in electrohydrodynamics. For constant vorticity, the vertical component of the velocity obeys a Laplace equation and also has the usual lower boundary condition. In making the vertical component of the velocity take central stage, the Burns condition can be thus bypassed.

The conventional method used for calculating pavement condition index (PCI) has two major drawbacks: safety problems during pavement inspection, and human error. This paper proposes a method for removing these problems. The proposed method uses surface deflection data in falling weight Deflectometer test to estimate PCI. The data used in this study were derived from 236 pavement segments taken from Tehran-Qom freeway in Iran. The data set was analyzed using multi layers perceptron (MLP) and radial basis function (RBF) neural networks. These neural networks were optimized by levenberg-marquardt (MLP-LM), scaled conjugate gradient (MLP-SCG), imperialist competitive (RBF-ICA), and genetic (RBF-GA) algorithms. After initial modeling with four neural networks mentioned, the committee machine intelligent systems (CMIS) method was adopted to combine the results and improve the accuracy of the modeling. The results of analysis have been verified by the four criteria of average percent relative error (APRE), average absolute percent relative error (AAPRE), root mean square error (RMSE) and standard error (SD). The best reported results belonged to CMIS, including APRE=2.3303, AAPRE=11.6768, RMSE=12.0056, and SD=0.0210.

The sublimation enthalpies of four highly energetic materials (HEMs): triacetone triperoxide (TATP), 2,4-dinitrotoluene (DNT), 2,4,6-trinitrotoluene (TNT) and 1,3,5-trinitrohexahydro-s-triazine (RDX) deposited on stainless steel (SS) substrates were determined by optical fibre coupled-grazing angle probe (GAP) FTIR spectroscopy and thermogravimetric analysis (TGA) for bulk crystaline HEMs samples. The desorption energy of RDX on SS was also studied using grazing angle FTIR microscopy. Metastable phases of 2,4-DNT and TNT were observed when deposited on SS, and their sublimation enthalpies values were obtained by GAP measurements and compared with those for the crystalline phases. The sublimation enthalpies for the alpha phase RDX was also determined by TGA measurements. A layer of crystalline beta phase RDX was observed on SS, and it's sublimation enthalpies was determinate by GAP. PLS calibration curves for the surface concentrations of RDX on SS were generated using GAP to determinate the surface concentration with time at different temperatures.

Extraction of high-resolution surface waves is essential in surface-wave survey. Because reflections usually interfere with surface waves on X component in a multicomponent seismic exploration, it is difficult to extract dispersion curves of surface waves. The situation goes more serious when the frequencies and velocities of higher-mode surface waves are close to those of PS-waves. A method for surface-wave extraction is proposed based on the morphological differences between reflections and surface waves. Frequency-domain high-resolution linear Radon transform (LRT) and time-domain high-resolution hyperbolic Radon transform (HRT) are used to represent surface waves and reflections respectively. Then, the sparse representation problem based on the morphological component analysis (MCA) is built and optimally solved to obtain high-fidelity surface waves. An advantage of our method is its ability to extract surface waves when their frequencies and velocities are close to those of reflections. Furthermore, results of synthetic and field examples confirm that the proposed method can attenuate the distortion of surface-wave dispersive energy caused by reflections, which contributes to extracting accurate dispersion curves.

Small unmanned aerial systems (UAS) represent a cost-effective strategy for topographic surveys. These low-cost drones can provide useful information for 3D reconstruction even if they are equipped with a low-quality navigation system. To ensure the production of high-quality topographic models, careful consideration of flight mode and proper distribution of ground control points is required. To this end a commercial drone has been adopted to monitor a small earthen dam using different combinations of flight configurations and adopting a variable number of ground control points (GCPs). Results highlighted that both choice and combination of flight plans can reduce the relative error of the 3D model up to a few meters without the need of including GCPs. The use of GCPs allows the quality of topographic survey to be greatly improved, reducing error to the order of a few centimeters. In particular, the combined use of images extracted from two flights, one with a camera mounted at nadir and the second with a 20° angle, proves extremely beneficial to increase the overall accuracy of the 3D model and especially of the vertical precision.

Given the rise in the number of cases and their recurrences, Urinary Tract Infections (UTI) are one of the major burdens on public healthcare worldwide. Rapid, inexpensive and selective detection of Uropathogenic E. coli (UPEC), a major contributor to UTIs, is the need of the hour for effective treatment, given the rise of antibiotic-resistant bacteria due to improper diagnosis. Here we present a rapid, real-time, selective and label-free detection of UPEC using an integrated sensing platform based on Crossed Surface Relief Gratings (CSRGs) as nanoplasmonic sensors. Detection is achieved due to the unique Surface Plasmon Resonance (SPR)-based light energy exchange attributed to the CSRGs, allowing real-time sensing in a very narrow bandwidth of the incident light to pass where the SPR energy conversion occurs. The sensing ability of the platform is experimentally demonstrated by the detection of bulk Refractive Index (RI) changes, with a bulk sensitivity of 382.2 nm/RIU and a resolution in the order of 10-6 RIU. We demonstrate selective capture and detection of clinical concentration of UPEC, as opposed to other gram-negative bacteria, in real-time, a first for CSRGs. This work is particularly important for effective treatment of UTIs, allowing point-of-care diagnosis for economically disadvantaged regions around the world.

In this paper a novel type of a highly sensitive gas sensor device based on the surface photovoltage effect is described. The developed surface photovoltage gas sensor is based on a reverse Kelvin probe approach. As the active gas sensing electrode the porous ZnO nanostructured thin films are used deposited by the direct current (DC) reactive magnetron sputtering method exhibiting the nanocoral surface morphology combined with an evident surface nonstoichiometry related to the unintentional surface carbon and water vapor contaminations. Among others, the demonstrated SPV gas sensor device exhibits a high sensitivity of 1 ppm to NO₂ with a signal to noise ratio of about 50 and a fast response time of several seconds under the room temperature conditions.

A simple fabrication method in the surface modification of electroosmotic silicon microchannel using thermal dry oxidation is presented. The surface modification is done by coating the silicon surface with a silicon dioxide (SiO₂) layer using thermal oxidation process. The process is aimed not only to improve the surface quality of the channel to be suitable for electroosmotic fluid transport but also to reduce the channel width using a simple technique. Initially, the parallel microchannel array with dimensions of 0.5 mm length and width ranging from 1.8 µm to 2 µm are created using plasma etching on the 2x2 cm <100> silicon substrate. The oxidation of silicon channel in a thermal chamber is then conducted to create the SiO₂ layer. The layer properties and the quality of the surface are analyzed using SEM and surface profiler, respectively. The results show that the maximum oxidation growth rate occurs in the first 4 hours of oxidation time and the rate decreases by time as the oxide layer becomes thicker. It is also found that the surface roughness is reduced with the increase of process temperature and oxide thickness. The scallop effect on the vertical wall due to plasma etching process also improved with the presence of the oxide layer. After the oxidation, the channel width is reduced by ~40%. The demonstrated method is suggested for the fabrication of a uniform channel cross section with high aspect ratio in sub-micro and nanometer scale that will be useful for the electroosmotic flow (EOF) manipulation of the biomedical fluid sample.

Plasma treatment of soft polymers is the promising technique to improve biomedical properties. The response to the deformation of such materials is not yet clear. Soft elastic polyurethane treated with plasma immersion ion implantation is subjected to fatigue uniaxial loading (50000 cycles, frequency – 1 Hz, strain amplitude – 10, 20, 40%). The influence of the strain amplitude and the plasma treatment regime on damage character is discussed. Surface defects are studied in unloaded and stretched states of the material. As a result of fatigue loading, transverse cracks (with closed overlapping edges as well as with open edges deeply propagating into the polymer) and longitudinal folds which are break and bend inward, appear on the surface. Hard edges of cracks cut the soft polymer which is squeezed from the bulk to the surface.

Marine cold air outbreaks (MCAOs) are large-scale phenomena in which cold air masses are advected over open ocean. It is well-known that these events are linked to the formation of polar lows and other mesoscale phenomena associated with high wind speeds, and that they therefore in some cases represent a hazard to maritime activities. However, it is still unknown whether MCAOs are generally conducive to higher wind speeds than normal. Here this is investigated by comparing the behaviour of ocean surface wind speeds during MCAOs in three atmospheric reanalysis products with different horizontal grid spacings, along with case studies using a convection-permitting numerical weather prediction model. The study regions are the Labrador Sea and the Greenland–Iceland–Norwegian (GIN) Seas, where MCAOs have been shown to be important for air–sea interaction and deep water formation. The main findings are: 1) Wind speeds during the most extreme MCAO events are stronger than normal and higher than wind speeds during less severe events; 2) The peak times of MCAO usually occur when baroclinic waves pass over the regions; and 3) Reanalyses with grid spacings of more than 50 km appear to underestimate winds driven by the large ocean–atmosphere energy fluxes during MCAOs. It is also shown that while the strong wind episodes during MCAOs generally last for just a few days, MCAOs can persist for up to 50 days. These findings demonstrate that it would be worthwhile to forecast MCAOs, and that it might be possible to do this beyond the standard weather forecasting range of up to 10 days.

The paper examines the possibility of increasing the wear and corrosion resistance of a CP-Ti surface by duplex plasma electrolytic treatment (borocarburizing and polishing). The structure and composition of diffusion layers, their microhardness, surface morphology and roughness, wear resistance during dry friction and corrosion resistance in Ringer's solution were studied. The formation of a surface hardened layer up to 200 m thick with a microhardness of up to 950 HV, including carbides and a solid solution of boron and carbon, is shown. Subsequent polishing makes it possible to reduce surface roughness and remove weak areas of the porous oxide layer, which is formed during high-temperature oxidation in aqueous electrolyte vapor during borocarburizing. Changing the morphology and structural-phase composition of the CP-Ti surface helps reduce weight wear by 3 times (the mode of frictional interaction changes from microcutting to oxidative wear) and corrosion current density by 4 times after borocarburizing in a solution of boric acid, glycerin and ammonium chloride at 950 °C for 5 minutes and subsequent polishing in an ammonium fluoride solution at a voltage of 250 V for 3 minutes.

Relevant observations suggest that in geothermal power resources and volcanic regions in Earth the mean heat flow is either comparable or greater than the current global mean heat flow of this planet. We have inferred that critical or minimum heat flow required to sustain geothermal provinces (T >150⁰C) is at least 90 mWm^-2 and the same required to sustain active volcanoes in Earth is at least 100 mWm^-2.The volcanism in Venus is found have declined significantly during the past 300 Ma. It is suggested that Earth may lose significant part of its current active volcanoes and geothermal power resources in the next 300-500 Ma if the global mean heat flow in Earth is decreasing at a rate of 5.76 mW per 100 Ma. At the current inferred maximum rate of mantle cooling (20^o C per 100 Myrs) the plate tectonics in Earth is likely to cease within 750 Myrs from now. The critical mean surface heat flux for sustaining plate tectonics in Earth is inferred to be around 50-55 mW/m².

This paper is devoted to an accurate determination of the London dispersive and polar free energy of adsorption, the two Lewis acid γs+ and base γs- components of polar surface energy γsAB of 2D single-crystalline and polycrystalline covalent organic frameworks such as TAPPy-TPA-COFs. Inverse gas chromatography (IGC) at infinite dilution was used to quantify the different surface parameters of the different materials. From IGC measurements, one determined the net retention time of the adsorption of n-alkanes and several polar solvents on single-crystalline and polycrystalline covalent organic frameworks. The free surface Gibbs energy of adsorption was obtained for the various organic molecules at different temperatures from their net retention volume values. The separation between the London dispersive energy and the polar energy of adsorbed molecules was carried out by using a new thermodynamic parameter PSX chosen as new indicator variable and taken into account the deformation polarizability and the harmonic mean of the ionization energies of solvents and solid materials, derived from London dispersion equation. The obtained results are very promising for the accurate determination of the surface thermodynamic parameters of adsorption of organic solvents on solid surfaces.

Deforestation is an important environmental problem in México and a key promoter of regional climate change through modifying the surface albedo. The objective of this research was to characterize the impact of deforestation and land use changes on surface albedo (α) and climate patterns in the Municipality of Tapalpa, Jalisco, México between the years 2014 and 2021. The main land cover types are coniferous forests (CF), oak and gallery woodlands (OGW), and annual agriculture (AA); which represent more than 88% of the regional territory (1066.03 km2). We used 2014 and 2021 Landsat 8 OLI images with topographic and atmospheric correction, in order to develop an inventory of albedo values for each land cover type in both time scenarios. Albedo images were generated by using the equation proposed by Liang in 2001, which is based on the reflectance of the bands 2, 3, 4, 5, and 7. Differences in albedo values were calculated between the years 2014 and 2021, and those differences were correlated with variations in climate parameters, for which we used climate data derived from the WRF model. In addition, the different land use changes found were classified in terms of triggers for increasing or decreasing surface albedo. Results showed that between 2014 and 2021, at least 38 events of land use change or deforestation occurred, with albedo increments between 1 and 11%, which triggered an average increment of 0.57% of the regional surface albedo in comparison to 2014 scenario. From 2014 to 2021, the albedo for CF, OGW, and AA, increased significantly (p&lt;0.001; Mann-Whitney U Test) by 79, 12, and 9%, respectively. In addition, the regional albedo increment was found to be significant and negatively correlated (p&lt;0.01 Spearman’s coefficient) with relative humidity (RH), maximum temperature (Tmax), minimum temperature (Tmin), and diurnal thermal range (DTR). The decrease in the regional values of relative humidity in 2021, occurred even when in that year the annual precipitation levels were higher than those of 2014, hence, reinforcing the fact of a possible climatic effect of the regional albedo changes. Conversion of CF and OGW into AA, perennial agriculture (PA), or grassland (GR) always yielded an albedo increment, whilst the conversion of AA to irrigation agriculture or PA triggered a decrease in albedo, and finally, the pass from GR or AA to protected agriculture caused albedo increase or decrease, depending on the greenhouse covers materials. Reducing deforestation of CF and OGW, conversion of AA or GR into PA, and selecting adequate greenhouse covers could help to mitigate regional climate change.

Analysis of water resources of this area was carried out in order to assessing the water quality by determining the concentrations of Cations, Anions, Heavy metals, Trace elements, PH, Alkalinity, Total Dissolved Solids and microbial loads in water samples. Ten (10) water samples were collected from the study area - samples each of rain water, two pond waters - 1 and 2, stream water, four (4) hand-dug wells, hand pump water and a motorized borehole. The results obtained were compared with WHO standards and it showed that all the cations in water samples are within the limits. The water samples at locations B, E, F, G, H, I, and J have high alkalinity and HC0^-₃ content. The heavy metals (Pb, Ni and Cd) and trace elements (Fe and Cu) are dominantly high in the surface waters. Microbiological substances in the water samples from the study area revealed indicator organisms higher than the WHO standard for drinking water. Samples obtained from location G, I and J recorded an absence of E. coli and are fit for human consumptions but needed to be treated due to high MPN (Most Probable Number) index of viable microorganisms as against WHO standard. This research showed that the water resources of the study area are gradually polluted and in the near future may not be good for drinking.

Titanium dioxide (TiO₂) micro and nano architectures have been intensively studied in the past years because of many varied applications in environmental, energy conversion, and storage fields, such as heterogeneous catalysis, dye-sensitized solar cells, lithium/sodium ion batteries, lithium-sulfur (Li-S) batteries, and bio-nanotechnology, etc. Especially the surface and interface structures in the TiO₂ structures play important roles in those applications. This mini review article focuses on TiO₂ micro and nano architectures with the prevalent crystal structures (anatase, rutile, brookite, and TiO₂(B)), and summarizes major advances in the surface and interface engineering and applications in environmental and electrochemical applications. We present the principles and growth mechanisms of TiO₂ nanostructures via different strategies, with an emphasis on rational control of the surface and interface structures. We further discuss the applications of TiO₂ micro and nano architectures in photocatalysis, lithium/sodium ion batteries, and Li-S batteries. Throughout the discussion, the relationship between the device performance and the surface structures of TiO₂ micro/nano structures will be highlighted. Then we discuss the phase transitions of TiO₂ nanostructures and possible strategies of improving the phase stability. The review concludes with a perspective on the current challenges and future research directions.

Metal-catalyzed lipid oxidation is a major factor in food waste, as it reduces shelf life. Addressing this issue, our study investigates the potential of hydrolysates derived from potato protein, a by-product of potato starch production, as metal chelating antioxidants. Through sequential enzymatic hydrolysis using Alcalase or Trypsin combined with Flavourzyme, we produced various hydrolysates, which were then fractionated via ultrafiltration. Using a combination of peptidomics and bioinformatics, we predicted the presence of metal-chelating and free radical scavenging peptides across all hydrolysate fractions, with a trend indicating a higher content of antioxidant peptides in lower molecular weight fractions. To validate these predictions, we utilized Surface Plasmon Resonance (SPR) and a 9-day emulsion storage experiment. While SPR demonstrated potential in identifying antioxidant activity, it faced challenges in differentiating between hydrolysate fractions due to significant standard errors. In the storage experiment, all hydrolysates showed lipid oxidation inhibition, though not as effectively as EDTA. Remarkably, one fraction (AF13) was not significantly different (p < 0.05) from EDTA in suppressing hexanal formation. These results highlight SPR and peptidomics/bioinformatics as promising yet limited methods for antioxidant screening. Importantly, this study reveals the potential of potato protein hydrolysates as antioxidants in food products, warranting further research.

The exceptional performance of graphene has driven the advancement of its preparation technique and application. Laser-induced graphene (LIG), as a novel graphene preparation technique, has been applied in various fields. Graphene periodic structures created by LIG technique exhibit superhydrophobic characteristics and can be used for deicing and anti-icing applications, which are significantly influenced by the laser parameters. The laser surface treatment process was simulated by a finite element software analysis (COMSOL Multiphysics) to optimize the scanning parameter range, and the linear array surface structure were subsequently fabricated by the LIG technique. The generation of graphene was confirmed by Raman spectroscopy, and energy-dispersive X-ray spectroscopy. The periodic linear array structure were observed by Scanning electron microscopy (SEM) and confocal laser imaging (CLSM). In addition, CLSM testings, contact angle measurements, and delayed icing experiments were systematically performed to investigate the effect of scanning speed on surface hydrophobicity. The results show that the high quality and uniform graphene can be achieved using the laser scanning speed of 125 mm/s. The periodic linear array structures can obviously increase the contact angle and suppress delayed icing. Furthermore, these structures have the enhanced ability of the electric heating deicing, which can reach 100°C and 240°C within 15 s and within 60 s under the DC voltage power supply ranging from 3 to 7 V, respectively. These results indicate that the LIG technique can be developed to provide an efficient, economical, and convenient approach for preparing graphene and the hydrophobic surface array structure based on LIG has considerable potential for deicing and anti-icing applications.

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.

The perovskite solar cells (PSCs) have been significantly improved by utilizing inorganic hole transporting layer (HTL), such as nickel oxide. Despite the promising properties, there are still limitations due to defects. Recently, research on self-assembled monolayers (SAM) is being actively conducted, which show promise in reducing defects and enhancing device performance. In this study, we successfully engineered a p-i-n perovskite solar cell structure utilizing HC-A1 and HC-A4 molecules. These SAM molecules were found to enhance the grain morphology and uniformity of the perovskite film, which are critical factors in determining optical properties and device performance. Notably, HC-A4 demonstrated superior performance due to its distinct hydrophilic properties with a contact angle of 50.3°, attributable to its unique functional groups. Overall, the HC-A4 applied film exhibited efficient carrier extraction properties, attaining a carrier lifetime of 117.33 ns. Furthermore, HC-A4 contributed the superior device performance with its favorable band alignment, achieving the highest device efficiency of 20%.

Minerals are the chief constituents of rocks and they have varied properties such as surface area, surface charge, site densities etc. Hence, numerous interactions are bound to occur in the reservoir during rock-fluids (i.e., rock, crude oil and brine) interactions. This study seeks to assess the role of mineralogical composition on the wettability of Sandstone Rocks (SR) and Mineral Mixture (MM) using both Surface Complexation Modelling (SCM) and flotation test. From the considered sandstone rocks, both the experimental results and its simulated counterpart revealed that, the SR were preferentially hydrophilic. For the MM, when the mass fraction of the hydrophobic mineral was increased, the affinity of the MM became slightly hydrophobic and vice-versa. For the dominant sandstone reservoir rock minerals with predominantly negatively charged surfaces, negligible oil adsorption took place due the interfacial repulsive forces at the oil-brine and mineral-brine interfaces. For the MM with low calcite content, the wetting preference was influenced by the mineral with prominent surface area. Our developed model portrayed that the main mechanism for oil adhesion onto sandstone minerals was divalent cations bridging. Nonetheless, adhesion of carboxylate (&gt;COO-) onto the illite, montmorillonite and calcite sites also took place with the latter being more pronounced.

Zirconium dioxide (ZrO2) possesses numerous advantages such as high mechanical strength, low friction coefficient, excellent optical properties, and extended lifespan. Consequently, ZrO2 has a broad research foundation and practical significance in functional films and wear-resistant coatings. However, it suffers from brittleness and low ductility when used as a bio-coating material. In this study, a Ta/ZrO2 film was fabricated on Si (100) and titanium alloy substrates using a magnetron sputtering system, with tantalum (Ta) serving solely as a transition layer. Subsequently, Zr and Nb ions were implanted into the film at varying doses but with consistent energy levels. The analysis focused on the film's microstructure, mechanical properties, hydrophilicity, and corrosion resistance. The results demonstrated a significant improvement in the hydrophilicity and corrosion resistance of the ZrO2 film following the implantation of Zr and Nb ions. First-principles calculations based on density functional theory (DFT) principles indicated that, with increasing doping concentrations of Zr and Nb in the ZrO2 model, the stability of the model increased gradually, thereby enhancing its corrosion resistance.

Evaporating liquid sessile drop deposited on horizontal surface is an important object of applications (printing technologies, electronics, sensorics, medical diagnostics, hydrophobic coatings, etc.) and theoretical investigations (microfluidics, self-assembly of nanoparticle, crystallization of the solute, etc.). The arsenal of formulas for calculating the slow evaporation of an axisymmetric drop of capillary dimensions deposited on a flat solid surface is reviewed. Such characteristics as vapor density, evaporation flux density, total evaporation rate are considered. Exact solutions obtained in the framework of the Maxwellian model, in which the evaporation process of the drop is limited by vapor diffusion from the drop surface to the surrounding air, are presented. The summary covers both well-known results obtained during the last decades and new results published by us in the last few years, but practically unknown to the wide scientific community. The newest formulas, not yet published in refereed publications, concerning exact solutions for a number of specific contact angles are also presented. In addition, new approximate solutions are presented for the first time (total evaporation rate and mass loss per unit surface area per unit time in the whole range of contact angles ), which can be used in modeling without requiring significant computational resources.

Pollution of urban surface dust with hazardous elements (HEs) is a serious environmental issue due to its toxicity and potential hazardous effects. Surface dust samples were collected from core urban, urban, and suburban gradients in the Urumqi city of the arid NW China, and the concentrations of six HEs, such as arsenic (As), cadmium (Cd), nickel (Ni), lead (Pb), mercury (Hg), and chromium (Cr), were determined. The pollution load index (PLI) and the US EPA health risk assessment model were applied to analyze and compare the pollution levels and potential health risk of HEs in surface dusts in different urbanization gradients. The obtained results indicate that the average concentrations of Hg, Cd, and Ni in surface dust decrease in the order of core urban > urban > suburban, whereas the average concentrations of As, Cr, and Pb decrease in the order of urban > core urban > suburban. The PLI of HEs in surface dust decreased in the order of core urban > urban > suburban. The concentrations of HEs in the core urban and urban gradients are relatively higher than in the suburban gradient. Furthermore, the total non-carcinogenic and carcinogenic risk index of investigated HEs in surface dust decrease in order of urban > core urban > suburban, for both adults and children. In addition, the pollution of surface dust with HEs in all urbanization gradients is more harmful to the children's health than to the adults. Overall, the potential non-carcinogenic and carcinogenic health risks of the investigated HEs, instigated primarily by oral ingestion of surface dust, are found to be within the acceptable range. However, urbanization can effects the accumulation of HEs in surface dust, and Cr is the main non-carcinogenic risk factor, whereas Cd is the main carcinogenic risk factor among the analyzed HEs in surface dust in all urbanization gradients.

This study compares the action of different handpieces (turbine, high-speed electric handpiece and piezoelectric device) on surface roughness of enamel and dentin when using diamond-coated working tips and burs of the same grit size. Experiment was conducted on 15 extracted first molars from patients aged 45 to 60 years. The occlusal portion was removed using a diamond-coated water wheel and then refined with a 120-130 μm grit bur in order to obtain a flat surface with an adequate exposition of the dentin core. Each surface was divided into three portions and every portion was finished with one of the three tested instruments. Rotary burs and piezoelectric tips had the same grit size (60 μm) and load on handpiece during preparation never exceeded 150 g. Surface roughness parameters (Ra, Rsk, Rku) were recorded with an optical profilometer and SEM analysis of treated surfaces and working tips was conducted. Ra and Rsk differed significantly between enamel and dentin only after using turbine (p=0.004 and p=0.007, respectively). No significant differences were observed in Ra, Rsk, and Rku between enamel and dentin when using high-speed electric handpiece or piezoelectric device. Turbine produced higher Ra and Rsk values on dentin than the other devices, while no significant differences were found between piezoelectric handpiece and high-speed electric contra-angle on both substrates. Summarizing, the findings of the present study demonstrated that turbine generated rougher surfaces on dentin compared to the other handpieces. Moreover, the turbine produced more asymmetrical surface profiles on both enamel and dentin. However, it should be considered that these differences in roughness (Ra) were within the range of 0.25-0.30 μm: it is still unclear if these variations, although statistically significant, will influence final clinical outcomes.

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.

A series of LaF₃:Ce³⁺ phosphors for the application in photodynamic therapy is synthesized using a one-stage solvothermal synthesis. The conditions providing the maximum intensity of UV- and X-ray-excited luminescence, lowest size and highest colloidal stability of the phosphor nanoparticles are found to respectively include cerium content 5% mol., use of ethanol as the reaction medium for the solvothermal synthesis and addition of polyvinylpyrrolidone as a stabilizer in an optimized amount.

This note makes available five years of data gathered in a measurement site equipped with a micrometeorological station and two monitoring wells. Series of data of hydrological and atmospheric variables allow to estimate the flux of water across the atmosphere-land interface and to calculate the water budget, that are crucial topics in climate and environmental sciences. The measures of water-table began during 2017, one of the driest year of the whole instrumental period of climate history for the Central Mediterranean. Data from the micrometeorological station have been used to construct two more datasets of daily and monthly cumulative values of different terms of the surface water budget, from which the groundwater infiltration has been estimated. A significant decreasing trend characterizes both the data time series of piezometric heights and estimated infiltration in the considered period. All the data are collected in 2017-2022 datasets that are available in the supplementary material.

The purpose of this study was to clarify the attachment types of the tibialis anterior tendon (TAT) in Japanese fixed cadavers and to determine the attachment site area in three dimensions. We examined 100 feet from 50 Japanese cadavers. The TAT was classified according to differences in the number of fiber bundles as: Type I, with one fiber bundle; Type II, with two fiber bundles; and Type III, with three fiber bundles. The attachment site area of the TAT was measured using a three-dimensional scanner. Cases were Type II in 95% and Type III in 5%, with no cases of Type I identified. In Type II, mean attachment site areas were 85.2 ± 18.2 mm2 for the medial cuneiform bone (MCB) and 72.4 ± 19.0 mm2 for the first metatarsal bone (1MB), showing a significantly larger area for MCB than for 1MB. These findings suggest the possibility of ethnic differences in TAT attachment types and suggest that TAT attachments in Japanese individuals are highly likely to be Type II, with rare cases of Type III. Accurate measurement of attachment site areas is possible with appropriate three-dimensional measurements.

Electron beam treatment of ZnS:Cu,Br (Cu activator content 0…0.6%wt.) radioluminescent phosphors as well as charge mixture with the electron energy 900 keV and absorbed dose of 600 kGy resulted in a enhancement of brightness up to 80%. The increased brightness is due to increase of content of wurtzite phase relative to sphalerite one with formation of wurtzite/sphalerite nanocomposite structure. Transformation of crystal structure is accompanied with corresponding change in content of active surface centers characteristic for sphalerite and wurtzite phases. A model describing surface centers of ZnS:Cu,Br radioluminescent phosphor is suggested.

Mapping and prediction of inundated areas is increasingly important for climate change adaptation and emergency preparedness. Flood forecasting tools and flood risk models have to be compared to observed flooding patterns for training, calibration, validation and benchmarking. At regional to continental scale, satellite earth observation is the established method for surface water extent (SWE) mapping and several operational global-scale data products are available. However, the spatial resolution of satellite-derived SWE maps remains a limiting factor, especially in low-lying areas with complex hydrography, such as Denmark. We collected thermal imagery using an unmanned airborne system (UAS) for three areas in Denmark shortly after major flooding events. We combined the thermal imagery with an airborne lidar-derived high-resolution digital surface model of the country to retrieve high-resolution (40 cm) SWE maps. The resulting SWE maps were compared to low-resolution SWE maps derived from satellite earth observation (EO). We conclude that UAS have significant potential for SWE mapping at intermediate scales, can bridge the scale gap between ground observations and satellite EO and can be used to benchmark and validate SWE mapping products derived from satellite EO as well as models predicting inundation.

The athletic performance and safety of racehorses is influenced by hoof-surface interactions. This intervention study assessed the effect of eight horseshoe-surface combinations on hoof acceleration patterns at impact and foot-off in 14 galloping Thoroughbred racehorses retired from racing. Aluminium, barefoot, GluShu (aluminium-rubber composite) and steel shoeing conditions were trialled on turf and artificial (Martin Collins Activ-Track) surfaces. Shod conditions were applied across all four hooves. Tri-axial accelerometers (SlamStickX, range ±500 g, sampling rate 5000 Hz) were attached to the dorsal hoof wall (x: medio-lateral, medial=positive; y: along dorsal hoof wall, proximal=positive; z: perpendicular to hoof wall, dorsal=positive). Linear mixed models assessed whether surface, shoeing condition or stride time influenced maximum (most positive) or minimum (most negative) accelerations in x, y and z directions, using ≥40,691 strides (significance at p&lt;0.05). Day and horse-rider pair were included as random factors and stride time as a covariate. Collective mean accelerations across x, y and z axes were 22–98 g at impact and 17–89 g at foot-off. Mean stride time was 0.48 ± 0.07 s (mean ± 2 s.d.). Impact accelerations were larger on turf in all directions for forelimbs and hindlimbs (p≤0.015), with the exception of forelimb z-minimum, and in absolute terms maximum values were typically double minimum values. Surface-type affected all foot-off accelerations (p≤0.022), with the exception of hindlimb x-maximum; for example, there was an average increase of 17% in z-maximum across limbs on the artificial track. Shoe-type influenced all impact and foot-off accelerations in forelimb and hindlimb datasets (p≤0.024), with the exception of hindlimb impact y-maximum. Barefoot hooves generally experienced the lowest accelerations. Stride time affected all impact and foot-off accelerations (p<0.001). Identifying factors influencing hoof vibrations on landing and hoof motion during propulsion bears implication for injury risk and racing outcomes.

Inverse problems of recovering surface fluxes on the boundary of a domain from pointwise observations are considered. Sharp conditions on the data ensuring existence and uniqueness of solutions in Sobolev classes are exposed. They are smoothness conditions on the data, geometric conditions on the location of measurement points, and the boundary of a domain. The proof relies on asymptotics of fundamental solutions to the corresponding elliptic problems and the Laplace transform. The problem is reduced to a linear algebraic system with a nondegerate matrix.

Linear elastic fracture modeling coupled with empirical material tension data result in good quantitative agreement with experimental measurements of fracture failure for both brittle and tough epoxy nanocomposites. The nanocomposites comprise diglycidyl ethers of bisphenol A cured with O,O’ bis (2-aminopropylpropylene glycol) (Jeffamine D230) and doped with rubber nanoparticles of varying concentrations. Toughness, critical load, and critical displacement in quasi-static single edge-notched three-point bending are predicted accurately using both surface-based cohesive zone (CZS) and extended finite element (XFEM) methods implemented in Abaqus software. Fracture initiation within a crack is taken at the yield stress from uniaxial tension data. Prediction of fracture processes using a generalized truncated linear traction-separation law was significantly improved by considering the case of a linear softening function. There are no adjustable parameters in the XFEM model. The CZS model requires only optimization of the element displacement at fracture parameter. Thus, these continuum methods describe these materials in mode I fracture with a minimum number of independent parameters.

Eastern boundary upwelling systems feature strong zonal gradients of physical and biological ocean properties between cool, productive coastal oceans and warm, oligotrophic subtropical gyres. Zonal currents and jets (striations) are therefore likely to contribute to the transport of water properties between coastal and open oceanic regions. Multi-sensor satellite data are used to characterize the signatures of striations in sea surface temperature (SST), salinity (SSS), and chlorophyll-a (Chl-a) in subtropical eastern North/South Pacific (ENP/ESP) upwelling systems. In the ENP, tracers exhibit striated patterns extending up to ~2500 km offshore. Striations in SST and SSS are highly correlated with quasi-zonal jets, suggesting that these jets contribute to SST/SSS mesoscale patterns via zonal advection. Chl-a striations are collocated with sea surface height (SSH) bands, a possible result of mesoscale eddy trains trapping nutrients and forming striated signals. In the ESP, striations are only found in SST and coincide with SSH bands, consistently with quasi-zonal jets located outside major zonal tracer gradients. An interplay between large-scale SST/SSS advection by the quasi-zonal jets, mesoscale SST/SSS advection by the large-scale meridional flow and eddy advection may explain the persistent ENP hydrographic striations. These results underline the importance of quasi-zonal jets for surface tracer structuring at the mesoscale.

Heterogeneous distribution of delivery or treatment modalities within the tumor mass is a crucial limiting factor for a vast range of theranostic applications. Understanding the interactions between a nanomaterial and the tumor microenvironment will help to overcome challenges associated with tumor heterogeneity as well as the clinical translation of nanotheranostic materials. This study aims to evaluate the influence of protein surface adsorption on gold nanoparticle (GNP) biodistribution using high resolution Computed Tomography (CT) preclinical imaging in C57BL/6 mice harboring Lewis Lung Carcinoma (LLC) tumors. LLC provides a valuable model for study due to its highly heterogenous nature which makes drug delivery to the tumor challenging. By controlling the adsorption of proteins on the GNP surface, we hypothesize that we can influence the intratumoral distribution pattern and particle retention. We performed an in vitro study to evaluate the uptake of GNPs by LLC cells and an in vivo study to assess and quantify the GNP biodistribution by injecting concentrated GNPs citrate stabilized or passivated with Bovine Serum Albumin (BSA) intratumorally into LLC solid tumors. Quantitative CT and Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) results both confirm the presence of particles in the tumor 9 days post-injection (n=8 mice/group). Significant difference is highlighted between citrate-GNP and BSA-GNP groups (**p < 0.005, Tukey’s multiple comparisons test), confirming the protein corona of GNPs modifies intratumoral distribution and retention of the particles. In conclusion, our investigations show that the surface passivation of GNPs influences the mechanism of cellular uptake and intratumoral distribution in vivo highlighting the spatial heterogeneity of the solid tumor.

Although the concept of additive manufacturing has been proposed for several decades, momentum of selective laser melting (SLM) is finally starting to build. In SLM, density and surface roughness, as the important quality indexes of SLMed parts, are dependent on the processing parameters. However, there are few studies on their collaborative optimization in SLM to obtain high relative density and low surface roughness simultaneously in the previous literature. In this work, the response surface method was adopted to study the influences of different processing parameters (laser power, scanning speed and hatch space) on density and surface roughness of 316L stainless steel parts fabricated by SLM. The statistical relationship model between processing parameters and manufacturing quality is established. A multi-objective collaborative optimization strategy considering both density and surface roughness is proposed. The experimental results show that the main effects of processing parameters on the density and surface roughness are similar. It is noted that the effects of the laser power and scanning speed on the above objective quality show highly significant, while hatch space behaves an insignificant impact. Based on the above optimization, 316L stainless steel parts with excellent surface roughness and relative density can be obtained by SLM with optimized processing parameters.

The assimilation of Soil Moisture and Ocean Salinity (SMOS) data into the ECMWF (European Centre for Medium Range Weather Forecasts) H-TESSEL (Hydrology revised - Tiled ECMWF Scheme for Surface Exchanges over Land) model is presented. SMOS soil moisture (SM) estimates have been produced specifically by training a neural network with SMOS brightness temperatures as input and H-TESSEL model SM simulations as reference. This can help the assimilation of SMOS information in several ways: (1) the neural network soil moisture (NNSM) data have a similar climatology to the model, (2) no global bias is present with respect to the model even if regional differences can exist. Experiments performing joint data assimilation (DA) of NNSM, 2 metre air temperature and relative humidity or NNSM-only DA are discussed. The resulting SM was evaluated against a large number of in situ measurements of SM obtaining similar results to those of the model with no assimilation, even if significant differences were found from site to site. In addition, atmospheric forecasts initialized with H-TESSEL runs (without DA) or with the analysed SM were compared to measure of the impact of the satellite information. Although, NNSM DA has an overall neutral impact in the forecast in the Tropics, a significant positive impact was found in other areas and periods, especially in regions with limited in situ information. The joint NNSM, T2m and RH2m DA improves the forecast for all the seasons in the Southern Hemisphere. The impact is mostly due to T2m and RH2m, but SMOS NN DA alone also improves the forecast in July- September. In the Northern Hemisphere, the joint NNSM, T2m and RH2m DA improves the forecast in April-September, while NNSM alone has a significant positive effect in July-September. Furthermore, forecasting skill maps show that SMOS NNSM improves the forecast in North America and in Northern Asia for up to 72 hours lead time.

Dispersed silver nanoparticles (AgNPs) on the surface of titanium alloy (Ti6Al4V) and titanium alloy modified by titania nanotube layer (Ti6Al4V/TNT) substrates were produced by chemical vapor deposition method (CVD) using novel precursor of the formula [Ag₅(O₂CC₂F₅)₅(H₂O)₃]. The structure and volatile properties of this compound were determined using single crystal X-ray diffractometry, variable temperature IR spectrophotometry (VT IR), and electron inducted mass spectrometry (EI MS). The morphology and the structure of the produced Ti6Al4V/AgNPs, and Ti6Al4V/TNT/AgNPs composites were characterized by scanning electron microscopy (SEM) and atomic force microscopy (AFM). Moreover, measurements of hardness, Young’s modulus, adhesion, and surface free energy have been carried out. The ability to release silver ions from the surface of produced nanocomposite materials immersed in PBS solution has been estimated using inductively coupled plasma mass spectrometry (ICP MS). The wettability and the surface free energy of samples were estimated on the base of contact angle studies with the use of water and diiodomethane. Among the studied surface-modified titanium alloy implants, the best nano-mechanical properties were noticed for the Ti6Al4V/TNT15/AgNPs composite. The location of silver nanoparticles inside of titania nanotubes caused their lowest release rate, which may indicate on suitable properties above mentioned type of the composite for the construction of implants with a long term of antimicrobial activity.

Zinc is mostly extracted from zinc oxide and sulfide minerals, and this process involves flotation as a key step. While it is easier to float the sulfide mineral, its consumption and depletion has led to an increased reliance on zinc oxide minerals, including smithsonite; hence the development of efficient ways of collecting smithsonite by flotation is an important objective. Herein, we describe the use of 2-(hexadecanoylamino)acetic acid (HAA), a novel surfactant, as a collector during smithsonite flotation. The mechanism and flotation performance of HAA during smithsonite flotation were investigated by total organic carbon (TOC) content studies, zeta potential measurements, FTIR spectroscopy, and XPS analyses, combined with micro-flotation experiments. The flotation results revealed that HAA is an excellent collector in pulp over a wide pH range (9–12) and at a relatively low concentration (2 × 10^‒4 mol/L), at which a recovery of close to 90% of the smithsonite mineral was obtained. TOC-content studies reveal that the good flotation recovery is ascribable to large amounts of collector molecule adsorbed on the smithsonite surface, while zeta potential measurements show that the HAA is chemically adsorbed onto the smithsonite. FTIR and XPS analyses reveal that the HAA-collector molecules adsorb onto the smithsonite surface as zinc-HAA complexes involving carboxylate moieties and Zn sites on the smithsonite surface in alkaline solution.

An analysis of workplace accidents in the mining sector has been done using the database from the Spanish administration between the period 2005-2015 and applying data mining techniques. Data has been processed by means of the software Weka. Two scenarios were chosen regarding the accidents database, surface and underground mining. The most important variables involved in occupation accidents and their association rules have been determined. These rules are formed by several predictor variables that cause an accident, defining its characteristics and context. This study exposes the 20 most important association rules of the sector, either surface or underground mining, based on statistical confidence levels of each rule obtained by Weka. The outcomes display the most typical immediate causes with the percentage of accident basis of each association rule. The most typical immediate cause is body movement with physical effort or overexertion and type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident change in both scenarios. Data mining techniques have been proved as a very powerful tool to find out the root of the accidents, apply corrective measures and verify their effectiveness, either for public or private companies.

Background: Lithium di-silicate dental ceramics bonding, realized by using different resins, is strictly dependent on micro-mechanical retention and chemical adhesion. The aim of this in vitro study was to investigate the capability of a 1070 nm fiber laser for their surface treatment. Methods: Samples were irradiated by a pulsed fiber laser at 1070 nm with different parameters (Peak Power from 5 kW to 5 kW, RR 20 kHz, speed from 10 to 50 mm/s, total Energy Density from 1.3 to 27 kW/cm²) and the thermal elevation during the experiment was recorded by a Fiber Bragg Grating (FBG) temperature sensor. Subsequently, the surface modifications were analysed by optical microscope, Scanning Electron Microscope (SEM) and Energy Dispersive X-ray Spectroscopy (EDS). Results: With a Peak Power of 5 kW, RR of 20 kHz and speed of 50 mm/s, the microscopic observation of the irradiated surface showed increased roughness with small areas of melting and carbonization. EDS analysis revealed that, with these parameters, there are no evident differences between laser-processed samples and controls. Thermal elevation during laser irradiation ranged between 5 °C and 9 °C. Conclusions: 1070 nm fiber laser can be considered as a good device to increase the adhesion of Lithium di-silicate ceramics.

Development of the self-cleaning and anti-fogging superhydrophobic coating for aluminum surfaces which is durable in the aggressive conditions has raised tremendous interest in materials science. In this work, by employing chemical etching technique with mixture of hydrochloric and nitric acid, followed by passivation with lauric acid, superhydrophobic aluminum surface was synthesized. The surface morphology analysis reveals the presence of rough microstructures on coated aluminium surface. Superhydrophobicity with water contact angle of 170 ± 3.9° and sliding angle of 4 ± 0.5° is achieved. Surface bounces off the high speed water jet, indicating excellent water-repellent nature of coating. It is also continuously floated on water surface for several weeks, showing excellent buoyancy nature. Additionally, coating maintains its superhydrophobicity after undergoing 100 cycles of adhesive tape peeling test. Its superhydrophobic nature withstands 90° and 180° bending, and repeated folding and de-folding. Coating exhibits the excellent self-cleaning property. In low temperature condensation test, almost no accumulation of water drops on the surface, showing the excellent anti-fogging property of coating. This approach can be applied to any size and shape of aluminium surface and hence has great industrial applications.

This article presents, for the first time, the kinetics and the general conversion features of free radical polymerization (FRP) in a 3-component system (A/B/N), with [A] being the initiator, and [B] and [N] are additives, based on the proposed mechanism of Rahal et al. Higher FRP can be achieved by additives [B] and [N], via the dual function of (i) regeneration [A], and (ii) generation of extra radicals (R) via the radicals (S' and S) produced by N.The initiator (coumarin) shows a dual photo-oxidation and photo-reduction character for high efficacy. The FRP conversion efficacy (CE) depends not only on the property of the initiator [A], the additives [B] and [N}, but also the types of monomers. For example, when [A]=CoumC, [A]/NPG is more efficient than [A]/Iod, but revserse trend occurs in some monomers. However, 2-component systems (with CE=0% to 80%) are always less efficient than that of 3-component systems (with CE=70% to 86%, in TMPTA). Specific systems with [A]=coumarins, [B]=Iodonium salt, and N=NPG are analyzed. Analytical formulas for the role of each component concentration, light intensity and coupling rates on the conversion efficacy are derived.

Background: Understanding the physicians’ knowledge, attitudes and antimicrobial prescribing behaviour is a crucial step towards designing strategies for optimal use of these agents. Methods: A cross-sectional online survey was conducted among clinicians across India between “May to July 2022” using a self-administered questionnaire in English comprising of 35 questions pertaining to demographic characteristics, knowledge, attitude and practices domains. Results. A total of 544 responses were received from 710 physicians contacted. 60 percent participants were males with mean age of 34.7 years. Mean ± SD scores for knowledge, attitude and practices domains were 8±1.6, 20.2±3.5 and 15.3±2.1, respectively. Higher scores were associated with basic [odds ratio (95% C.I.), P value: 2.95 (1.21, 7.2), 0.02], medical and allied sciences [2.71 (1.09, 6.67), 0.03] and central zone [3.75 (1.39, 10.12), 0.009]. A substantial proportion of dissatisfactory responses were found regarding hospital antibiograms, antibiotics effective against anaerobes, WHO AWaRe classification of antibiotics, and role of infection prevention and control (IPC) measures in containment of antimicrobial resistance (AMR). Conclusions. There is a need to sensitize and educate clinicians on various issues related to antimicrobial use such as antibiograms, double anaerobic cover, IPC practices and guideline-based recommendations to curb the AMR pandemic.

Molecular descriptors are essential in mathematical chemistry for studying quantitative structure-property relationships (QSPR), and topological indices are a valuable source of information about molecular properties such as size, cyclicity, branching degree, and symmetry. Graph theory has played a crucial role in the development of topological indices and dominating parameters for molecular descriptors. The molecule graph, under graph isomorphism conditions, represents an invariant number, and the graph theory approach considers dominating sets, which are subsets of the vertex set where every vertex outside the set is adjacent to at least one vertex inside the set. The dominating sigma index, a topological index that incorporates the mathematical principles of domination topological indices and the sigma index, is applicable to some families of graphs, such as book graphs, windmill graphs, and some graph operations, which have exact values for this new index. To evaluate the effectiveness of the domination sigma index in QSPR studies, a comparative analysis was conducted to establish an appropriate domination index that correlates with the physicochemical properties of octane and its isomers. Linear and non-linear models were developed using the QSPR approach to predict the properties of interest, and the results showed that both the domination forgotten and domination first Zagreb indices exhibited satisfactory performance in comparison testing. Further research into QSAR/QSPR domination indices is required to build more robust models for predicting the physicochemical properties of organic compounds while maintaining the importance of symmetry.

Trauma is one of the most common causes of death or permanent disability in young people, so a timely diagnostic approach is crucial. In polytrauma patients, CEUS has been shown to be more sensitive than US for the detection of solid organ injuries, improving the identification and grading of traumatic abdominal lesions with levels of sensitivity and specificity similar to those seen with MDCT. CEUS is recommended for the diagnostic evaluation of hemodynamically stable patients with isolated blunt moderate-energy abdominal traumas and for the diagnostic follow-up of conservatively managed abdominal traumas. In this pictorial review we illustrate the advantages and disadvantages of CEUS and the procedure details with tips and tricks during investigation of blunt moderate-energy abdominal trauma as well as during follow-up in non-operative management.

Almond (Prunus dulcis (Mill.) D.A.Webb) is one of the largest nut crops in the world. Recently, phenolic compounds, mostly stored in almond skin, have been associated with much of the health-promoting behavior associated with their intake. The almond skin enriched fraction obtained from cold-pressed oil residues of the endemic Moroccan Beldi ecotypes is particularly rich in chlorogenic acid. In this study, both almond skin extract (AE) and chlorogenic acid (CHL) supplements, similar to traditional positive control resveratrol, significantly increased the replicative life-span of yeast compared to the untreated group. Our results showed that AE and CHL significantly reduced the production of reactive oxygen and nitrogen species (ROS/RNS), most likely due to their ability to maintain mitochondrial function during aging, as indicated by the maintenance of normal mitochondrial membrane potential in treated groups. This may be associated with the observed activation of the anti-oxidative stress response in treated yeast, which results in activation at both gene expression and enzymatic activity levels for SOD2 and SIR2, the latter being an upstream inducer of SOD2 expression. Interestingly, the differential gene expression induction of mitochondrial SOD2 gene at the expense of the cytosolic SOD1 gene confirms the key role of mitochondrial function in this regulation. Furthermore, AE and CHL have contributed to the survival of yeast under UV-C-induced oxidative stress, by reducing the development of ROS / RNS, resulting in a significant reduction in cellular oxidative damage as evidenced by decreased membrane lipid peroxidation, protein carbonyl content and 8-oxo-guanine formation in DNA. Together, these results demonstrate the interest of AE and CHL as new regulators in the replicative life-span and control of the oxidative stress response of yeast.

To understand functions of biomolecules such as proteins, not only structures but their conformational change and kinetics are important to be characterized but its atomistic details are hard to obtain both experimentally and computationally. We review our recent computational studies using novel enhanced sampling techniques for conformational sampling of biomolecules and calculations of their kinetics. For efficiently characterizing the free energy landscape of a biomolecule, we introduce the multiscale enhanced sampling method, which uses a combined system of atomistic and coarse-grained models. Based on the idea of Hamiltonian replica exchange, we can recover the statistical properties of the atomistic model without any biases. We next introduce the string method as a path search method to calculate the minimum free energy pathways along a multidimensional curve in high dimensional space. Finally we introduce novel methods to calculate kinetics of biomolecules based on the ideas of path sampling: One is the Onsager-Machlup action method, and the other is the weighted ensemble method. Some applications of above methods to biomolecular systems are also discussed and illustrated.

A time-sequential working, spatially multiplexed autostereoscopic 3D display design consisting of a fast switchable RGB-color filter array is presented. The wavelength-selective filter barrier emits the light from a display over a larger active area than common autostereoscopic barrier displays. An optical modelling of wavelength-selective barriers has been used for instance to calculate the light ray distribution properties of that arrangement. To find well working display designs, automated searches by simulation and computational evaluation has been proceeded. Wavelength-selective filter barrier arrangements exhibit characteristics different from common barrier displays with similar barrier pitch and ascent. In particular, these constructions show strong angular luminance dependency under barrier inclination specified by correspondent slant angle. In time-sequential implementation it is important to avoid that quick eye or eyelid movement lead to visible color artifacts. In the millisecond regime tunable liquid crystal Fabry-Pérot color filters for the colors red, green and blue are presented. They consist of a sub-micrometer thick nematic layer sandwiched between dielectric mirrors and ITO-electrodes. These cells shall switch narrow-banding light of red, green or blue. An array for a glasses-free 3D display has to be equipped with several thousand switchable filter elements having different color apertures. The newly introduced design is usable as a multi user display as well as a single user system with user adaptive control.

To study the spatial accessibility of healthcare services in cities on the Tibetan Plateau, this paper proposes an improved 3SFCA method in the main urban area of Xining City. The improved 3SFCA method incorporates both selection weights from the Huff model and the M2SFCA approach to addressing suboptimal allocation of supply resources. Results show that the accessibility of healthcare for the main urban area of Xining City decreases in a circle to four axes, with good accessibility in the east and center but poor accessibility in the north. And there is a positive spatial relationship between population and accessibility. Besides, this paper proposes a framework for studying the spatial accessibility of healthcare on the Tibetan Plateau.

Text CAPTCHAs are crucial security measures employed on global websites to deter unauthorized intrusions. The presence of anti-attack features incorporated into text CAPTCHAs limits the effectiveness of breaking them, despite CAPTCHA recognition being an effective method for assessing their security. This study introduces a novel color augmentation technique called Variational Color Shift (VCS) to boost the recognition accuracy of different networks. VCS generates a color shift range of every input image and then resamples the image within that range to generate a new image, thus expanding the number of samples of the original dataset to improve training effectiveness. In contrast to Random Color Shift (RCS) which treats the color offsets as hyperparameters, VCS uses the estimated offsets to reparametrize the points sampling from the unit uniform distribution to reconstruct new image pixels, which makes the offsets learnable. To reduce the computational effort of VCS, we also propose two variants of VCS: Sim-VCS and Dilated-VCS. In addition, to solve the overfitting problem caused by many disturbances in CAPTCHAs, we propose an Auto Encoder (AE) based on a Large Separable Kernel Attention (AE-LSKA) to replace the convolutional module in the text CAPTCHA recognizer. This new module employs an AE) to compress the interference while expanding the receptive field using Large Separable Kernel Attention (LSKA), which reduces the impact of local interference on the model training and improves the overall perception of characters. The experimental results show that the recognition rate of the model after integrating the AE-LSKA module is improved by at least 15 percentage points on both M-CAPTCHA and P-CAPTCHA datasets. In addition, experimental results demonstrate that color augmentation using VCS is more effective in enhancing recognition.

The Latin American Giant Observatory (LAGO) is a ground-based extended cosmic rays observatory designed to study transient astrophysical events, the role of the atmosphere on the formation of secondary particles, and space-weather-related phenomena. With the use of a network of Water Cherenkov Detectors, LAGO measures the secondary particle flux, a consequence of the interaction of astroparticles impinging on the Earth with the atmosphere. These interactions yield a flux of secondary particles that can be grouped into three distinct basic constituents: the electromagnetic, muonic, and hadronic components. In this work we extend our previous research by using detailed simulations of the expected atmospheric response to the primary flux and the corresponding response of our WCDs to atmospheric radiation. After implemented OPTICS, a density-based clustering algorithm, to identify patterns in data collected by a single WCD, we have further refined our approach by implementing a method that categorizes and differentiates particle groups using advanced unsupervised machine learning techniques. Our analysis demonstrates that applying our enhanced methodology can accurately identify the originating particle with a high degree of confidence on a single-pulse basis, highlighting its precision and reliability. These promising results suggest the feasibility of implementing machine-learning-based models throughout LAGO distributed detection network and other astroparticles observatories for semi-automated, onboard and real-time data analysis. When a particle enters a Water Cherenkov Detector (WCD), it generates a measurable signal characterized by unique features correlating to the particle’s type and the detector’s specific response. The resulting charge histograms from these signals provide valuable insights into the flux of primary astroparticles and their key characteristics. However, this data is insufficient to effectively distinguish between the contributions of different secondary particles. This research extends our previous investigations, wherein we implemented OPTICS, a density-based clustering algorithm, to identify patterns in data collected by a single WCD. We have further refined our approach by implementing a method that categorizes and differentiates particle groups using advanced unsupervised machine learning techniques. This methodology facilitates the differentiation among particle types and utilizes the detector’s nuanced response to each particle type, thus pinpointing the principal contributors within each group. In this work, we utilize OPTICS to analyze simulated data, further validating the proposed method. We created a simulated dataset by combining the outputs of the ARTI and MEIGA frameworks. This dataset simulates the expected WCD signals produced by the flux of secondary particles during one day at the LAGO site in Bariloche, Argentina, situated at 865 meters above sea level. To achieve this, real-time magnetospheric and local atmospheric conditions for February and March of 2012 were analyzed, and the resultant atmospheric secondary-particle flux was integrated into a specific MEIGA application featuring a comprehensive Geant4 model of the WCD at this LAGO location. The output from MEIGA was modified for effective integration into our machine learning pipeline. Our analysis demonstrates that applying our enhanced methodology can accurately identify the originating particle with a high degree of confidence on a single-pulse basis, highlighting its precision and reliability. These promising results suggest the feasibility of implementing machine-learning-based models throughout the LAGO distributed detection network for semi-automated, onboard and real-time data analysis. Our analysis demonstrates that OPTICS can accurately identify the originating particle with a high degree of confidence on a single-pulse basis, highlighting its precision and reliability. These promising results suggest the feasibility of implementing machine-learning-based models throughout the LAGO distributed detection network for semi-automated, onboard data analysis.

Computational rhinology is a specialized branch of biomechanics leveraging engineering techniques for mathematical modelling and simulation to complement the medical field of rhinology. Computational rhinology has already contributed significantly to advancing our understanding of the nasal function, including airflow patterns, mucosal cooling, particle deposition, and drug delivery, and is foreseen as a crucial element in e.g. the development of virtual surgery as a clinical, patient-specific decision support tool. The current paper delves into the field of computational rhinology from a nasal airflow perspective, highlighting the use of computational fluid dynamics to enhance diagnostics and treatment of breathing disorders. The paper consists of three distinct parts – an introduction to and review of the field of computational rhinology, a review of published literature on in vitro and in silico studies of nasal airflow, and the presentation and analysis of previously unpublished high fidelity CFD simulation data of in silico rhinomanometry. While the two first parts of the paper summarize the current status and challenges in the application of computational tools in rhinology, the last part addresses the gross disagreement commonly observed when comparing in silico and in vivo rhinomanometry results. It is concluded that this discrepancy cannot readily be explained by CFD model deficiencies caused by poor choice of turbulence model, insufficient spatial or temporal resolution, or neglecting transient effects. Hence, alternative explanations such as nasal cavity compliance or drag effects due to nasal hair should be investigated.

This study explores the application of numerical analysis and material models to predict ice impact loads on ships and offshore structures operating in polar regions. An explicit finite element analysis (FEA) approach was employed to simulate an ice and steel plate collision experiment conducted in a cold chamber. The pressure and strain history during the ice collision were calculated and compared with the experimental results. Various material model configurations were applied to the FEA to account for the versatile behavior of ice—whether ductile or brittle—its elastic-plastic yield criteria, and its dynamic strain rate dependency. In addition to the standard linear elastic perfectly plastic and linear elastic-plastic relationships, this study incorporated the crushable foam and Drucker-Prager models, based on the specific ice yield criteria. Considering the ice’s strain rate dependency, collision simulations were conducted for each yield criteria model to compute the strain and reaction force of the plate specimens. By comparing the predicted pressures for each material model combination with the pressures from ice collision experiments, our study proposes material models that consider the yielding, damage, and behavioral characteristics of ice. Lastly, our study proposes a combination of ice material properties that can accurately predict collision force.

One of the fastest growing customer service delivery platforms is online banking. However, the increasing number of attacks on online banking platforms is driving the banks to constantly review their security. This study developed an enhanced Multi-factor authentication scheme with a track and trace capability to reduce these threats. Five modalities of authentication were incorporated in the proposed scheme: The traditional username, password, personal identification number (PIN) and one-time PIN (OTP), augmented with fingerprints or facial scans, registered smart devices, and a time locked user's location. One of the scheme's most impressive accomplishments is its capacity to seamlessly detect undesired activities and send alerts in the form of secretly obtained photographs and location triangulation.

The emerging whitefly-transmitted crinivirus Tomato chlorosis virus (ToCV) causes substantial economic losses by inducing yellow leaf disorder in tomato crops. This study explores potential resistance mechanisms by examining early-stage molecular responses to ToCV. A time-course transcriptome analysis compared naïve, mock and ToCV-infected plants at 2, 7, and 14 days post-infection (dpi). Gene expression changes were most notable at 2 and 14 dpi, likely corresponding to whitefly feeding and viral infection. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed key genes and pathways associated with ToCV infection, including those related to plant immunity, flavonoids and steroids biosynthesis, photosynthesis, and hormone signalling. Additionally, virus-derived small interfering RNAs (vsRNAs) originating from ToCV predominantly came from RNA2 and were 22 nucleotides in lengt. To confirm these findings, two genes involved in plant immunity, Hsp90 (heat shock protein 90) and its co-chaperone Sgt1 (suppressor of the G2 allele of Skp1) were targeted through viral-induced gene silencing (VIGS), showing potential contribution to basal resistance against viral infections since their reduction correlated with increased ToCV accumulation. This study provides insights into tomato plants responses to ToCV, with potential implications for developing effective disease control strategies.

Dissolved organic matter (DOM) derived from organic fertilizers may increase soil phosphorus (P) availability. However, the frequently observed correlation between soil P availability and dissolved organic carbon (DOC) content has led to an excessive focus on DOC content at the expense of DOM properties. The present study investigated the influence of DOM characteristics on soil P availability by using a 6-year field experiment and microcosms of P sorption in paddy soil. Our results showed that partial replacement of chemical P fertilizer with manure or crop straw increased P fertilizer-use efficiency, even when decreasing chemical P input by 34 %, compared to normal chemical fertilization. The microcosm experiment demonstrated that DOM properties, rather than total DOC content, determine soil P sorption capacity, despite the significant correlation between DOC content and P availability observed in the field experiment. Manure-DOM exerted stronger inhibitory effects on P sorption than straw-DOM, and high molecular weight (HMW)-fractionated DOM exerted stronger inhibitory effects on P sorption than low-molecular-weight-fractionated DOM by 16-20%. The mechanism was rooted in the HMW DOM with unique characteristics (e.g., strong aromaticity, hydrophobicity, abundant humic-like components, carboxyl groups, and benzene ring structures) competing for soil P sorption sites (e.g., reduction in specific surface area and micropore volume), decreasing the soil surface charge (e.g., zeta potential), and thereby suppressing P sorption in paddy soil. Our study points out a promising avenue for regulating organic matter properties with organic fertilization to improve P use efficiency in agricultural soils.

This study aimed to compare the efficacies and safety of enhanced and standard monofocal intraocular lenses (IOLs) in eyes with early glaucoma. Patients with concurrent cataracts and open-angle glaucoma (OAG) were enrolled. They underwent cataract surgery with IOL implantation. Manifest refraction; monocular uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), uncorrected intermediate visual acuity (UIVA), and uncorrected near visual acuity (UNVA); visual field (VF); contrast sensitivity (CS); defocus curves and questionnaires were assessed three months postoperatively. Thirty-four and 38 patients had enhanced and standard monofocal IOLs, respectively. The enhanced monofocal IOL provided better UIVA than the standard monofocal IOL (p = 0.003) but similar UDVA, CDVA and UNVA. The enhanced monofocal IOL had more consistent defocus curves than the standard monofocal IOL, especially at -1 (p = 0.042) and -1.5 (p = 0.026) diopters. The enhanced monofocal IOL provided better satisfaction (p = 0.019) and lower spectacle dependence (p = 0.004) than the standard monofocal IOL for intermediate vision, with similar VF and CS. In conclusion, the enhanced monofocal IOL is recommended for patients with OAG because they provide better intermediate vision, higher satisfaction, and lower dependence on spectacles than standard monofocal IOL, without worsening other visual outcomes.

Polymers are one of the most widely used chemicals in the oil and gas industry. They are used for mobility control in enhanced oil recovery, in conformance control as a crosslinked plugging agent, as a fracking fluid for fracture propagation and proppant transportation, and in drilling fluids as an additive for drilling mud enhancement. In the majority of its applications in the petroleum industry, the polymer needs to be injected under high pressures and temperatures. This can impact the polymer structure significantly and compromises the possibility of reusing the injected polymer for cost reduction and material sustainability. This research characterizes the polymer injectivity in different pore sizes under different conditions and evaluates the polymer conditions after injection. Based on this, the ability to reinject the polymer in the porous media is discussed. The factors studied include the pore size, the polymer concentration, the polymer injection flowrate, and polymer injectivity. Results showed that the polymer usually undergoes four main degradations during injection including dehydration, syneresis, shearing, and excessive hydrolysis. The experimental results showed that one or more of the polymer degradations resulted in the inability to reinject the polymer in most cases.

This article presents, for the first time, comprehensive model based on the proposed mechanism of Rahal et al [17], Bonardi {20], Tar et al [20], and Mau et al [24], for 3-component systems of G1/Iod/EDB, G1/Iod/amine (in gold chloride), and Iod/Benzoic/Borate (for reduced oxygen inhibition) for the hybri free radical (FRP) and cationic (CP) photopolymerization of interpenetrated polymer network (IPN) systems. Analytic formulas are developed to explore the new features including: (i) conversion efficacy(CE) of FRP is an increasing function of the light intensity (I), the effective absorption coefficient (b), for transient state, whereas, CE at steady-state is independent to the light intensity; (ii) initiator regeneration (RGE)
provides a catalytic cycle for improved CE for FRP and CP; (iii) in the IPN system, the synergic effects due to the co-exist of FRP and CP include: (i) CP can increase the medium viscosity limiting the diffusional oxygen replenishment, such that OIH is reduced; (ii) the cationic monomer also acts as a diluting agent for the radical polymer network, and (iii) the exothermic property of the CP polymerization. We have proposed ascaling law for the transient and steady-state dependence of CE on the key parameter P=bIC₀, given by a an m-order power law of P^m, with m = 0.5 to 1.5, depending on various conditions. The CE also has an optimal value for maximum CE. The presented comprehensive model (with minimum mathematics) focusing on the enhancement mechanisms/pathways, provides analytic formulas which can be used to analyze reported data, and, more importantly, serves as guidance for exploring new functional materials or new kinetic schemes for improved conversion or procedures for both industrial and medical applications such as additive manufacturing (AM), 3D and 4D bioprinting. Finally, we have proposed new directions/experiments based on our theoretical predictions.

The detection performance of small objects in remote sensing images has not been satisfactory compared to large objects, especially in low-resolution and noisy images. A generative adversarial network (GAN)-based model called enhanced super-resolution GAN (ESRGAN) showed remarkable image enhancement performance, but reconstructed images usually miss high-frequency edge information. Therefore, object detection performance showed degradation for small objects on recovered noisy and low-resolution remote sensing images. Inspired by the success of edge enhanced GAN (EEGAN) and ESRGAN, we applied a new edge-enhanced super-resolution GAN (EESRGAN) to improve the quality of remote sensing images and used different detector networks in an end-to-end manner where detector loss was backpropagated into the EESRGAN to improve the detection performance. We proposed an architecture with three components: ESRGAN, EEN, and Detection network. We used residual-in-residual dense blocks (RRDB) for both the ESRGAN and EEN, and for the detector network, we used a faster region-based convolutional network (FRCNN) (two-stage detector) and a single-shot multibox detector (SSD) (one stage detector). Extensive experiments on a public (car overhead with context) dataset and another self-assembled (oil and gas storage tank) satellite dataset showed superior performance of our method compared to the standalone state-of-the-art object detectors.

We report on the study of energy-harvesting performance in medium-size (400 cm²) glass-based semitransparent solar concentrators employing edge-mounted photovoltaic modules. Systems using several different types of glazing system architecture and containing embedded diffractive structures are prepared and characterized. The technological approaches to the rapid manufacture of large-area diffractive elements suitable for use in solar window-type concentrators are described. These elements enable the internal deflection and partial trapping of light inside glass-based concentrator windows. We focus on uncovering the potential of pattern-transfer polymer-based soft lithography for enabling both the improved photon collection probability at solar cell surfaces, and the up-scaling of semitransparent solar window dimensions. Results of photovoltaic characterization of several solar concentrators employing different internal glazing-system structure and diffractive elements produced using different technologies are reported and discussed.

Machine learning methods used for classification can face challenges due to class imbalance, where a certain class is underrepresented. Over/under-sampling of minority/majority class observations, or model selection for ensemble methods alone, may not be effective if the class imbalance ratio is very high. To address this issue, this paper proposes a method called enhance tree ensemble (ETE) based on generating synthetic data for minority class observations in conjunction with tree selection based on their performance on the training data. The proposed method first generates minority class instances to balance the training data and then uses the idea of tree selection by leveraging out-of-bag (〖ETE〗_OOB) and sub-samples (〖ETE〗_SS) observations, respectively. The efficacy of the proposed method is assessed using twenty benchmark problems for binary classification with moderate to extreme class imbalance, comparing it against other well-known methods such as optimal tree ensemble (OTE), SMOTE random forest (〖RF〗_SMOTE), over-sampling random forest (〖RF〗_OS), under-sampling random forest (〖RF〗_US), k-nearest-neighbor (k-NN), support vector machine (SVM), tree, and artificial neural network (ANN). Performance metrics such as classification error rate and precision are used for evaluation purposes. The analyses of the study revealed that the proposed method, based on data balancing and model selection, yielded better results than the other methods.

Attention Deficit Hyperactivity Disorder (ADHD) diagnosis poses significant challenges due to its heterogeneous nature and reliance on subjective assessments. This study leverages deep learning to develop a robust diagnostic model by integrating a comprehensive set of EEG biomarkers. We incorporate parameters such as theta/beta ratio, coherency measures, delta power, event-related potentials (ERPs), power spectral density (PSD), microstates, entropy measures, fractal dimension, and source localization. Our convolutional neural network (CNN) model, designed to process these diverse features, demonstrates high accuracy and stability in distinguishing ADHD patients from controls, from all ages. The model's architecture includes convolutional layers for spatial feature extraction, followed by dense layers that integrate additional EEG parameters. The results indicate that deep learning, coupled with a rich feature set, can significantly enhance the predictive accuracy of ADHD diagnosis, offering a promising tool for clinical application.

Covalent organic frameworks (COFs) have garnered significant interest within the scientific community due to their distinctive ability to act as organic semiconductors responsive to visible light. This unique attribute makes them up-and-coming candidates for facilitating photocatalytic organic reactions. Herein, two donor-acceptor COFs, TPE-BSD-COF and TPE-BD-COF, have been designed and synthesized by incorporating electron-rich tetraphenylethylene and electron-deficient benzoselenadiazole and benzothiadiazole units into the framework through a Schiff-base polycondensation reaction. Both COFs exhibits exceptional crystallinity and enduring porosity. TPE-BSD-COF and TPE-BD-COF exhibit broad light absorption capabilities, narrow optical band gap, and low electrochemical impedance spectrum (EIS) levels, indicating that the two COFs are effective heterogeneous photocatalysts for the reductive dehalogenation of benzoyl bromide derivatives under blue LED irradiation. TPE-BSD-COF and TPE-BD-COF achieved a high photocatalytic yield of 98% and 95%, respectively, within only one hour.

This paper presents a repository of image databases where the image features are augmented with embedded vector field (VF) features to enhance the machine learning (ML) and increase classification statistics. Six VFs are formulated and used for the purpose of embedding. Three of them generate real shaped singular points (SPs): springing, sinking and saddle. The other three VFs generate seven kinds of SPs which include the real shaped SPs and four complex shaped SPs: repealing and attracting (out and in) spirals; clockwise and counterclockwise orbits (center). Also, the paper describes the VF singularities, their shapes, and locations according to the image objects. Then, the present work defines the mappings between the SPs’ shapes if the VFs are separately embedded into the same image. Thus, the paper infers which VFs are most appropriate for embedding into a particular image database such that the augmented SPs shapes enhance the ML classification. Examples of images with different embedded VFs are shown, in the text, to support and validate the theoretical conclusions. The contributions of the paper are: a description of the SPs location in an image; the mappings between the SPs of the different VFs; the definition of an imprint of an image in a VF; the generation of databases’ imprints. The advantage of classifying an image database with embedded VFs is that the new database enhances ML and improves the classification statistics if compared to the classification of the original image database with the same ML classifier. Furthermore, images with embedded SPs create a useful augmentation to the original image databases.

The Global Navigation Satellite Systems (GNSS) software-defined receivers offer greater flexibility, cost-effectiveness, customization, and integration capabilities compared to traditional hardware-based receivers, making them essential for a wide range of applications. The continuous evolution of GNSS research and the availability of new features require these software-defined receivers to upgrade continuously to facilitate the latest requirements. The Finnish Geospatial Research Institute (FGI) has been supporting the GNSS research community with its open-source implementations, such as a MATLAB-based GNSS software-defined receiver ’FGI-GSRx’ and a Python-based implementation ’FGI-OSNMA’ for utilizing Galileo’s Open Service Navigation Message Authentication (OSNMA). In this context, longer datasets are crucial for GNSS software-defined receivers to support adaptation, optimization and facilitate testing to investigate and develop future-proof receiver capabilities. In this paper we present an updated version of FGI-GSRx, namely FGI-GSRx-v2.0.0, which is also available as an open-source resource for the research community. FGI-GSRx-v2.0.0 offers improved performance as compared to its previous version, especially for the execution of long datasets. This is carried out by optimizing the receiver’s functionality and offering a newly added parallel processing feature to ensure faster capabilities to process the raw GNSS data. This paper also presents an analysis of some key design aspects of previous and current versions of FGI-GSRx for a better insight into the receiver’s functionalities. The results show that FGI-GSRx-v2.0.0 offers about 40% run time execution improvement over FGI-GSRx-v1.0.0 in case of sequential processing mode and about 59% improvement in case of parallel processing mode with 17 GNSS satellites from GPS and Galileo. In addition, an attempt is made to execute v2.0.0 with MATLAB’s own parallel computing toolbox. A detail performance comparison reveals an improvement of about 43% in execution time over v2.0.0 parallel processing mode for the same GNSS scenario.

Objectives: This study assessed the performance of a novel fluoride dentifrice containing micro- fibrillated cellulose (MFC) and 7% silica (Protegera™) versus common fluoride dentifrices. Methods: Removal of extrinsic stains was assessed using the pellicle cleaning ratio (PCR) method, and radioactive dentin abrasivity (RDA) was measured, to calculate a cleaning efficiency index (CEI). Fluoride efficacy was evaluated using widely used remineralization and fluoride uptake methods. Results: The MFC dentifrice removed stained pellicle significantly more effectively than the ADA reference material, Crest Cavity Protection™ and Sensodyne Pronamel™, and had equal performance to three known marketed stain-removing dentifrices (Arm & Hammer™ Advanced Whitening, Crest ProHealth™, and Colgate Optic White™). The MFC dentifrice vehicle had a low RDA (88), which was significantly less than Crest ProHealth (166) and Crest 3D-White™ (183). Based on PCR and RDA data, the CEI was 31% greater for the MFC product than for Crest ProHealth. In a 10-day pH cycling study, the fluoride efficacy of the MFC product was superior to a non-fluoridated control and was not significantly different from Sensodyne Pronamel and Crest Cavity Protection. The MFC dentifrice was superior for promoting fluoride uptake into incipient enamel lesions than the USP reference dentifrice. Conclusion: The low dentin abrasivity MFC dentifrice is highly effective in removing stained pellicle, and is an efficacious fluoride source when compared to other relevant commercially available fluoride dentifrices with high dentin abrasivity. Clinical Significance: Including micro-fibrillated cellulose into a fluoride dentifrice may enhance cleaning performance for the removal of external stain, while lowering abrasivity, and providing an effective fluoride source. This combination of benefits seems well suited to enamel protection and caries prevention.

This paper presents a novel framework for Collaborative Learning Networks (CLNs) in classrooms, aiming to optimize resource utilization and enhance educational services. The study addresses the inefficiencies of traditional education models, particularly the underutilization of computational resources and limited access to specialized software. The proposed framework employs a mix of task-based and random allocation strategies to distribute computational tasks within the CLN, considering each device’s capabilities and task requirements. The findings show significant improvement in resource utilization, facilitated by device-to-device collaboration and task sharing, thus enriching students’ learning experiences. This work contributes to optimizing resource utilization in education, advancing the field of CLNs.

Background and Objectives: The healing of bone defects is a serious challenge worldwide. One branch of dentistry deals with bone defects. capsaicin has anti-inflammatory, anti-oxidative and cholesterol-reducing effects. The aim of this study is to evaluate the effects of systemic capsaicin administered at different doses on bone healing. Materials and Methods: A total of 32 male wistar rats was used, their weight varying between 250 and 300 g. The rats were randomly divided into four groups of eight rats each. The analyses served to evaluate the effect on healing of different doses of capsaicin and grafts. A significant increase was observed in the number of osteoblasts in the capsaicin-applied groups compared to the control group. Conclusions: As a result of the analyses, positive effects on bone healing were observed when capsaicin 0.25 mg/kg and 0.50 mg/kg was administered intraperitoneally. However, more studies are needed for more accurate information.

Background: In today’s competitive market, predicting customer churn with high accuracy is crucial for enterprises to maintain growth and profitability. Traditional predictive models often lack in accuracy due to the complexity of customer behavior.Objective: This research aims to improve the accuracy of predicting customer churn by utilizing the Particle Swarm Optimization (PSO) algorithm for optimizing the hyperparameters of a composite deep learning model. The performance of this enhanced model is evaluated against traditional models such as LSRM_GRU, LSTM, GRU, and CNN_LSTM to demonstrate the effectiveness of PSO in hyperparameter tuning.Methods: A composite deep learning approach was employed, integrating various neural network architectures to leverage their strengths in modeling complex customer interactions. The PSO algorithm was used to optimize the model’s hyperparameters. Customer transaction and interaction data from different business operations served as the dataset for testing and analyzing the model’s performance. Evaluation metrics including accuracy, precision, recall, F1 score, and ROC AUC were utilized for a detailed comparison with established models.Findings: The PSO-enhanced composite deep learning model showed superior performance across all metrics, significantly outperforming the LSRM_GRU, LSTM, GRU, and CNN_LSTM models. Notably, improvements in ROC AUC and F1 score highlight the robustness and balanced precision-recall trade-off of the proposed model, demonstrating its effectiveness in identifying potential churners.Conclusion: The integration of PSO for hyperparameter optimization in composite deep learning models for customer churn prediction has proven to significantly enhance predictive accuracy and performance metrics over conventional models. This underscores the potential of evolutionary algorithms in improving deep learning applications. Future research should explore the scalability of this approach across various sectors and further refine predictive accuracy with evolving customer data.

Photocatalytic decomposition of ethylene was performed under UV-Led irradiation at the presence of nanocrystalline TiO2 (anatase, 15 nm) supported on the porous nickel foam. Process was carried out in the high temperature chamber with regulated temperature from ambient to 125°C under flow of reacted gas (ethylene in a synthetic air, 50 ppm) with simultaneous FTIR measurements of sample surface. Ethylene was decomposed with higher efficiency in elevated temperatures with maximum of 28% at 100-125°C. The nickel foam used as support for TiO2 allowed to enhance the ethylene decomposition at the temperature of 50°C. However, at 50°C the stability of ethylene decomposition was not retained within the following reaction run, but it was at 100°C. Performed photocatalytic measurements at the presence of some radicals scavengers indicated that higher efficiency of ethylene decomposition was obtained due to the improved separation of charge carriers and increased formation of superoxide anionic radicals, which were formed at the interface of thermally activated nickel foam and TiO2.

The sustainability of cities often changes as rapid urban developments and population growth affect the carrying capacity. Understanding the dynamics of carrying capacity then becomes crucial for tourist-oriented cities. This study focused on Baguio City, the "Summer Capital of the Philippines," attracting large crowds on holidays and actively promoting various events on non-holidays, thereby having temporal context variations classified as regular days, days with events, and holidays. Using the enhanced urban carrying capacity load number (EUCCLN) model, load number (LN) changes for different temporal contexts are calculated based on spatial indicators grouped into air, traffic, economy, and waste. The city experiences the worst pressures on air quality during holidays with $99.23\%$ districts under very high to critical levels followed by regular and days with events. However, the total LN is balanced by favorable economic conditions with only $9.23\%$ at critical. EUCCLN effectively pinpoints areas experiencing critical states at any time, advocating targeted government monitoring. We demonstrate that Night Time Light, for places with no economic data available, can be used as a proxy to highlight areas requiring improved urban vibrancy. This work suggests that EUCCLN monitoring urban pressures can easily be expanded to nowcasting with real-time data.

Temporal downscaling of gridded geophysical data is essential for improving climate models, weather forecasting, and environmental assessments. However, existing methods often could not accurately capture multi-scale temporal features, affecting their accuracy and reliability. To address this issue, we introduce an Enhanced Residual U-Net architecture for temporal downscaling. The architecture, which incorporates residual blocks, allows for deeper network structures without the risk of overfitting or vanishing gradients, thus capturing more complex temporal dependencies. The U-Net design inherently could capture multi-scale features, making it ideal for simulating various temporal dynamics. Moreover, we implement a flow regularization technique with advection loss to ensure that the model adheres to physical laws governing geophysical fields. Our experimental results across various variables within the ERA5 dataset demonstrate an improvement in downscaling accuracy, outperforming other methods.

Numerous reservoirs that play a significant role in worldwide petroleum production and reserves contain fractures. Typically, the fractures must form a connected network for a reservoir to be classified as naturally fractured. Characterizing the reservoir with a focus on its fracture network is crucial for modeling and predicting production performance. To simplify the solution, dual continuum modeling techniques are commonly employed. However, to use continuum-scale approaches, properties such as average aperture, permeability, and matrix fracture interaction parameters must be assigned, making it necessary to improve fracture depiction and modeling methods. This study investigates a fractured reservoir with a low matrix permeability and a well-connected fracture network. The focus is on the impact of the hyrachical fracture network on the production performance of gas-based enhanced oil recovery methods. The Discrete Fracture Model (DFN) was utilized to create comprehensive two-dimensional models for three processes: Gas Injection (GI), Water Alternating Gas (WAG), and Foam Assisted Water Alternating Gas (FAWAG). Moreover, dimensionless numbers were employed to establish connections between properties across the entire fracture hierarchy, spanning from minor to major fractures and encompassing the fracture intensity. The results indicate that the FAWAG is more sensitive to fracture types and networks than the WAG and GI processes. Hence, the sensitivity of the individual EOR method to the fracture network requires a respective depth of description of the fracture network. However, other factors, such as reservoir fluids properties and fracture properties, might influence the recovery when the minor fracture networks are excluded. This study has determined that, among the enhanced oil recovery (EOR) techniques examined, the significance of the hyrachical depth of fracture networks diminishes as the ratio of major (primary fracture) aperture to the aperture of medium and minor fractures increases. Additionally, the impact of the assisted-gravity drainage method was greater with increased reservoir height; however, as the intensity ratio increased, the relative importance of medium and minor fracture networks decreased.

Embryo quality evaluation during in vitro development is vital for the success of assisted reproductive technologies (ART). However, the subjective morphological assessment by embryologists may result in inconsistencies that affect the selection of the best embryo for transfer. To provide a more comprehensive evaluation of embryo quality, we performed the integration of embryo metabolomics with standardized morphokinetic classification. The culture medium of 55 embryos (from 21 couples undergoing ICSI) was collected at two timepoints (day 3 and 5). Samples were split into Good (n=29), Lagging (n=19) and Bad (n=10) according to embryo morphokinetic evaluation. Embryo metabolic performance was assessed by 1H-NMR, monitoring the variation of specific metabolites (pyruvate, lactate, alanine, glutamine, acetate, formate). Adjusted metabolite differentials were observed during the first three days of culture and found to be discriminative of embryo quality at the end of day 5. Pyruvate, alanine, glutamine, and acetate were major contributors to this discrimination. Good and Lagging embryos were found to export and accumulate pyruvate and glutamine in the 3 first days of culture, while Bad embryos consumed them. This suggests that Bad embryos have a less active metabolism than Good and Lagging embryos and these two metabolites as putative biomarkers for embryo quality. This study provides a more comprehensive evaluation of embryo quality and can lead to improvements in ART by enabling the selection of the best embryos. By combining morphological assessment and metabolomics, the selection of high-quality embryos with the potential to result in successful pregnancies may become more accurate and consistent.

News recommendation schemes utilize features of the news itself and information about users to suggest and recommend relevant news items to the users towards the interest they have. However, the effectiveness of the existing news recommendation scheme is limited in the occurrence of new user cold start problems. Therefore, we designed a news recommender system using hybrid approaches to address new user cold start problems to ease and suggest more related news articles for new users. To achieve the objective mentioned above, user demographic data with a hybrid recommendation system that contains the scheme of both content-based and collaborative filtering approaches is proposed. To evaluate the effectiveness of the proposed model, an extensive experiment is conducted using a dataset of news articles with user rating value and user demographic data. The performance of the proposed model is done by two ways of experiment. So, the performance of the proposed model performs around 68.05% of Precision, 42.46% of Recall and 52.1% of the average F1 score for the experiment based on individual user similarity in the system. And also performs around 93.75% of precision, 40.25% of recall and 56.31% F1-score for the similarity of users based on the similarity of users within the same category which is better than the first experiment.

This study presents a tri-layer broadband metamaterial absorber which operates in the GHz range. The absorber was composed of a polyhedral iron-cobalt alloy/graphite nanosheet material arranged in a flat sheet with two punched-in rings for the top layer, a continuous FR-4 layer at the middle, and a continuous copper layer at the bottom. For the normal incidence of electromagnetic wave, the proposed absorber demonstrated an exceptional broadband absorption in a frequency range of 7.9-14.6 GHz, revealing an absorption exceeding 90%. The absorption magnitude remains to be above 90% in a frequency range of 8-11.1 GHz for transverse-electric-polarized waves at incident angles up to 55°. For both transverse-magnetic- and electric-polarized waves, the absorption exceeds 90% in a frequency range of 9.5-14.6 GHz. The physical mechanism behind the absorption properties is analyzed thoroughly through the electric- and magnetic-field distributions. The obtained results could contribute potentially to the development of microwave applications based on metamaterial absorbers, such as radar-stealth technology, electromagnetic shielding for health safety and reduced electromagnetic interferences for high-performance communications and electronic devices.

Chitooligosaccharides (COS) are -1,4-linked homo-oligosaccharides of N-acetylglucosamine (GlcNAc) or glucosamine (GlcN), and also include hetero-oligosaccharides composed of GlcNAc and GlcN. These sugars are of practical importance because of their various biological activities, such as anti-microbial, anti-inflammatory, anti-oxidant and anti-tumor activities, as well as triggering the innate immunity in plants. The reported data on bioactivities of COS used to contain some uncertainties or contradictions, because the experiments were conducted with poorly characterized COS mixtures. Recently, COS have been satisfactorily characterized with respect to their structures, especially the degree of polymerization (DP) and degree of N-acetylation (DA); thus, the structure-bioactivity relationship of COS has become more unambiguous. To date, various green-chemical strategies involving enzymatic synthesis of COS with designed sequences and desired biological activities have been developed. The enzymatic strategies could involve transglycosylation or glycosynthase reactions using reducing end-activated sugars as the donor substrates and chitinase/chitosanase and their mutants as the biocatalysts. Site-specific chitin deacetylases were also proposed to be applicable for this purpose. Furthermore, to improve the yields of the COS products, metabolic engineering techniques could be applied. The above-mentioned approaches will provide the opportunity to produce tailor-made COS, leading to the enhanced utilization of chitin biomass.

A full connected world is expected to gain in the 6th generation mobile network (6G). As a typi-cal fully connected scenario, the internet of vehicle (IoV) enables intelligent vehicle operations via artificial intelligence (AI) and edge computing technologies. In the future of vehicular net-works, wide variety of services need powerful computing resources and higher quality of ser-vice (QoS). Existing resources are insufficient to match these requirements. Aim to this problem, An intelligent service offloading framework is provided. Based on the framework, an Algorithm of Improved Gradient Descent (AIGD) is created to accelerate the speed of iteration. So, the con-vergence of convolutional neural network (CNN) based on AIGD is able to be accelerated too. Then, an Algorithm of convolutional long short-term memory (CN_LSTM) Based Traffic Predic-tion (ACLBTP) is designed to gain the predicted number of vehicles belonged to the edge node. At last, an Algorithm of Service Offloading Based on CN_LSTM (ASOBCL) is conducted to of-fload these services to the vehicles belonged to the edge node. In ASOBCL, sorting technique is adopted to speed up the offloading work. Simulation results demonstrate the fact that the pre-diction strategy designed in this paper has high accuracy. The low offloading time and main-taining stable load balance is gained via running ASOBCL. Low offloading time means short response time. And, the QoS is guaranteed. So, these strategies designed in this paper are effec-tive and valuable.

Developing advanced carbon materials by utilizing biomass waste has attracted much attention. Herein, a N-doped carbon material (RSM-0.33-550) was prepared by directly pyrolyzing reed straw and melamine. The as-prepared RSM-0.33-550 possessed a N content of 6.02% and a specific surface area of 547.1 m2 g-1. As the anode for supercapacitors (SCs), in 6 M KOH, such RSM-0.33-550 exhibited a capacitance of 202.8 F g-1 at a current density of 1 A g-1. At a high current density of 20 A g-1, it still remained a capacitance of 158 F g-1. Notably, it delivered an excellent stability with capacity retention of 96.3% at 20 A g-1 after 5000 cycles. This work not only offer a new electrode material for SCs, but also gives a new insight for rationally utilizing the biomass waste for energy storage.

Design has often been interpreted as a practice of creating novel objects. However, the relationships between objects analysed upstream the process of creation have been under-studied. Here it is presented a model for enhancing the design practice by fostering a deep work on the relationships of mundane objects. The Three-dimensional Narratives (TdN) model comprises a stepwise five phases work package that facilitates a varied range of analyses to improve the creativity and innovation of any project led by any type of participants. One particular feature of the TdN model is the appropriation of concepts coming from non-design fields such physics and biology to both developing the work of the model and to improve the comprehension and outcomes of the enrolled participants. During three Case Studies with children, youngsters, and older participants the TdN model was validated, and its usability was successfully assessed. The TdN model shows that there is a need for a deeper design practice and that it is relevant to improve the lexicon of designers in order to facilitate a broader and design practice, irrespectively of the aim of the proposed project and nuances of the audience.

We study the performance of an endoreversible magnetic Otto cycle with a working substance composed of a single quantum dot described using the well-known Fock-Darwin model. We find that tuning the intensity of the parabolic trap (geometrical confinement) impacts the proposed cycle’s performance, quantified by the power, work, efficiency, and parameter region where the cycle operates as an engine. We demonstrate that a parameter region exists where the efficiency at maximum output power exceeds the Curzon-Ahlborn efficiency, the efficiency at maximum power achieved by a classical working substance.

Sphingosine-1-phosphate (S1P) synthesized by sphingosine kinase (SPHK) is a signaling molecule, involved in cell proliferation, growth, differentiation, and survival. Indeed, a sharp increase of S1P was linked to the pathological outcome with inflammation, cancer metastasis or angiogenesis etc. In this regard, the SPHK/S1P axis regulation has been a specific issue in anticancer strategy to turn accumulated sphingosine (SPN) into cytotoxic ceramides (Cers). For these purposes, there have been numerous chemicals synthesized for SPHK inhibition. In this study, we investigated the comparative efficiency of dansylated PF-543 (DPF-543) on the Cers synthesis along with PF-543. DPF-543 deserved attention in strong cytotoxicity, due to the cytotoxic Cers accumulation by ceramide synthase (CerSs). DPF-543 exhibited dual actions on Cers synthesis by enhance the serine palmitoyltransferase (SPT) activity, and by inhibiting SPHKs which eventually induced an unusual environment of the high amount of 3-ketosphinganine and sphinganine (SPA). SPA in turn was consumed to synthesize Cers via de novo pathway. Interestingly, PF-543 increased only the SPN level, but not for SPA. In addition, DPF-543 mildly activates acid sphingomyelinase (aSMase) that contributes a partial increase on Cers. Collectively, a dansyl-modified DPF-543 relatively en-hanced Cers accumulation via de novo pathway which was not observed in PF-543. Our results demonstrated that the structural modification on SPHK inhibitors is still an attractive anticancer strategy by regulating sphingolipid metabolism.

We evaluated the change in water dispersibility of lactic acid bacteria (LAB, Enterococcus faecalis KH2) upon powderization and its influence on their efficacy. When cultured LAB are washed, heat-killed, and powdered, adhesion between LAB occurs and they form aggregation (non-treated LAB, n-LAB). However, a dispersed LAB (d-LAB) powder with less aggregates can be prepared by treating them with a high-pressure homogenizer and adding an excipient during powdering. n-LAB or d-LAB was administered to mice and the Peyer's patches in the small intestine were observed. n-LAB administration showed a high amount of aggregated LAB drifting in the intestinal mucosa, whereas d-LAB reached the Peyer's patches and was taken up into the Peyer's patches. Evaluation in a mouse influenza virus infection model showed that d-LAB was more effective than n-LAB in influenza yield of bronchoalveolar lavage fluids (BALFs) on day 3 post-infection, neutralizing antibody titers of sera and influenza virus-specific IgA in the feces on day 14 post-infection. Thus, the physical properties of LAB affect their efficacy; controlling their water dispersibility can improve their effectiveness.

Layered 2D graphene oxide (GO) films are integrated with silicon nitride (SiN) waveguides to experimentally demonstrate an enhanced Kerr nonlinearity via four-wave mixing (FWM). Owing to the strong light–matter interaction between the SiN waveguides and the highly nonlinear GO films, the FWM performance of the hybrid waveguides is significantly improved. SiN waveguides with both uniformly coated and patterned GO films are fabricated based on a transfer-free, layer-by-layer GO coating method together with standard photolithography and lift-off processes, yielding precise control of the film thickness, placement and coating length. Detailed FWM measurements are carried out for the fabricated devices with different numbers of GO layers and at different pump powers. By optimizing the trade-off between the nonlinearity and loss, we obtain a significant improvement in the FWM conversion efficiency of ≈7.3 dB for a uniformly coated device with 1 layer of GO and ≈9.1 dB for a patterned device with 5 layers of GO. We also obtain a significant increase in FWM bandwidth for the patterned devices. A detailed analysis of the influence of pattern length and position on the FWM performance is performed. Based on the FWM measurements, the dependence of GO’s third-order nonlinearity on layer number and pump power is also extracted, revealing interesting physical insights about the 2D layered GO films. Finally, we obtain an enhancement in the effective nonlinear parameter of the hybrid waveguides by over a factor of 100. These results verify the enhanced nonlinear optical performance of SiN waveguides achievable by incorporating 2D layered GO films.

The continuous development in the field of industrial automation and electric mobility has led to the need for more efficient electrical machines with high power density. The improvement of electrical machines slot filling factors is one of the measures to satisfy these requirements. In recent years, this topic has aroused greater interest in the industrial sector, since the evolution of the winding technological manufacturing processes allows an economically sustainable realization of ordered winding arrangements, rather than random ones. Moreover, the manufacture of electrical machines windings must be preceded by an accurate design phase in which it is possible to evaluate the maximum slot filling factor obtainable for a given wire shape and for its dimensions. For this purpose, this paper presents an algorithmic approach for the evaluation of maximum slot filling factors in electrical machines under ideal geometric premise. In particular, this algorithm has a greater degree of flexibility with respect to the algorithm approaches found in the literature, since the study has been extended to round, rectangular and hexagonal wire sections. Furthermore, the slot filling factor calculation was carried out both for standard and non-standard slots. The algorithmic approach proposed can be considered as an additional useful tool for the fast design of electrical machine windings.

DNA vaccines are stable, safe, cost effective to produce and relatively quick and easy to manufacture. However, to date DNA vaccines have shown relatively poor immunogenicity in humans despite promising preclinical results. Consequently, a number of different approaches have been investigated to improve the immunogenicity of DNA vaccines. These include the use of improved delivery methods, adjuvants, stronger promoters and enhancer elements to increase antigen expression, and codon optimization of the gene of interest. This review describes the creation and use of a DNA vaccine vector containing a porcine circovirus (PCV-1) enhancer element that significantly increases recombinant antigen expression and immunogenicity and allows for dose sparing. A 172bp region containing the PCV-1 capsid protein promoter (Pcap) and a smaller element (PC; 70 bp) within this were found to be equally effective. DNA vaccines containing the Pcap region expressing various HIV-1 antigens were found to be highly immunogenic in mice, rabbits and macaques, at 4 to 10-fold lower doses than normally used and to be highly effective in heterologous prime-boost regimens. By lowering the amount of DNA used for immunization, safety concerns over injecting large amounts of DNA into humans can be overcome.

Electrically conductive polymer composites are in high demand for modern technologies, however, the intrinsic brittleness of conducting conjugated polymers and the moderate electrical conductivity of engineering polymer/carbon composites have highly constrained their applications. In this work, super high electrical conductive polymer composites were produced by a novel hot embossing design. The polydimethylsiloxane (PDMS) composites containing short carbon fiber (SCF) exhibited an electrical percolation threshold at 0.45 wt%, and reached a saturated electrical conductivity of 49 S/m at 8 wt% of SCF. When reduced the sample thickness from 1.0 mm to 0.1 mm by the hot embossing process, a compression-induced percolation threshold occurred at 0.3 wt%, while the electrical conductivity was further enhanced to 378 S/m at 8 wt% SCF. Furthermore, the additional of a second nanofiller of 1 wt%, such as carbon nanotube or conducting carbon black further increased the electrical conductivity of the PDMS/SCF (8 wt%) composites to 909 S/m and 657 S/m, respectively. The synergy of the densified conducting filler network by the mechanical compression and the hierarchical micro-/nanoscale filler approach has realize super high electrical conductive yet mechanical flexible polymer composites for modern flexible electronics applications.

With quick improvement in the field of network, everything becomes online. Remote user authentication is a mechanism in which remote server verify the correctness of user over common or public channel. Remote user authentication can be Single server authentication or Multi server authentication. The disadvantage of single server authentication is that the user needs to recall user id and password for each service, he/she need to utilize, however it can overcome by Multi-server authentication in which user needs to register himself with Registration Center (RC) for the first run through and after that onwards he can utilize each service (which are given by servers, associated with RC) by recollecting only one user id and password. In this paper, we analyze Chen's authentication scheme (based on multi server authentication) and show that this scheme is vulnerable to password guessing attack, replay attack, RC spoofing attack, session key verification attack and perfect forward secrecy attack. In this Paper, we propose a biometric based remote user authentication scheme in multi-server environment. Proposed scheme is more secure and efficient as compared to chen's scheme\cite{23}.

Here we performed a comparative experimental analysis by EPR spectroscopy of the intensity of nitric oxide (NO) production and copper content in the injured and uninjured areas of the frontal lobes and the hippocampus of the brain of male Wistar rats, after modeling of combined brain and spinal cord injury. Brain and spinal cord injury were modelled by local destruction of the left precentral region of the brain using a stylet followed by hemorrhage injury at the level of the first lumbar vertebra of the spinal cord. We found a significant decrease in NO production 7 days after injury modeling in the injured and uninjured (contralateral) brain regions, but the copper content remained unchanged one week after injury modeling. Thus, combined brain and spinal cord injury is not accompanied by a radical change in the activity of the antioxidant system in the brain, which is also confirmed by the absence of changes in NO production and copper content in the hippocampus.

Gestational diabetes mellitus (GDM) is a hyperglycemia state that is typically diagnosed by an oral glucose tolerance test (OGTT), which is unpleasant, time-consuming, poorly reproducible, and tardy. The machine learning (ML) predictive models that have been proposed to improve GDM diagnosis are usually based on instrumental methods that take hours to get a result. Near-infrared (NIR) spectroscopy, a simple, fast and low-cost analytical technique has never been assessed for the prediction of GDM. This study aims to develop ML predictive models for GDM based on NIR spectroscopy, and to evaluate their potential as early detection or alternative screening tools according to their predictive power and time of analysis. Serum samples from the first (before GDM diagnosis) and the second (at the time of GDM diagnosis) trimester of pregnancy were analyzed by NIR spectroscopy. Four spectral ranges were considered, and 80 pretreatments were tested for each. NIR data-based models were built with single- and multi-block ML techniques. Every model was subjected to double cross-validation. The best first and second trimester models got areas under the receiver operating characteristic curve of 0.5768 ± 0.0635 and 0.8836 ± 0.0259, respectively. This is the first study reporting NIR spectroscopy-based methods for the prediction of GDM. The developed methods allow to predict GDM from 10 µL of serum in only 32 minutes. They are simple and fast, and have a great potential to be applied in clinical practice, especially as alternative screening tools to the OGTT at the time of GDM diagnosis.

Purpose Isocitrate dehydrogenase (IDH) mutation has become one of the most important prognostic biomarkers in glioma management, indicating better treatment response and prognosis. IDH mutations confer neomorphic activity leading to the conversion of alpha-ketoglutarate (α-KG) to 2-hydroxyglutarate (2HG). The purpose of this study was to investigate the clinical potential of proton MR spectroscopy (1H-MRS) in identifying IDH-mutant gliomas by detecting characteristic resonances of 2HG and its complex interplay with other clinically relevant metabolites. Materials and Methods Thirty-two patients with suspected infiltrative glioma underwent single-voxel (SVS, n=17) and/or single-slice multivoxel (1H-MRSI, n=15) proton MR spectroscopy (1H-MRS) sequence with an optimized echo-time (97ms) on 3T-MRI. Spectroscopy data were analyzed using linear combination (LC) model. Cramer-Rao lower bound (CRLB) values of <40% were considered acceptable for detecting 2HG and <20% for other metabolites. Immunohistochemical analyses for determining IDH mutational status were subsequently performed from resected tumor specimens, and findings were compared with the results from spectral data. Mann-Whitney and Chi-squared tests were performed to ascertain differences in metabolite levels between IDH-mutant and IDH-wild-type gliomas. Receiver operating characteristics (ROC) curve analyses were also performed. Results Data from eight cases were excluded due to poor spectral quality or non-tumor-related etiology, and final data analyses were performed from 24 cases. Of these cases, 9/12 (75%) were correctly identified as IDH-mutant or IDH-wildtype gliomas by SVS and 10/12 (83%) by 1H-MRSI with an overall concordance rate of 79% (19/24). The sensitivity, specificity, positive predictive value, and negative predictive values were 80%, 77%, 86%, and 70%, respectively. The metabolite 2HG was found to be significant in predicting IDH-mutant gliomas by Chi-squared test (p<0.01). The IDH-mutant gliomas also showed significantly higher NAA/Cr ratio (1.20 ± 0.09 versus 0.75 ± 0.12 p= 0.016) and lower Glx/Cr ratio (0.86±0.078 versus 1.88±0.66; p=0.029) than those with IDH wild-type gliomas. The areas under the ROC curves for NAA/Cr and Glx/Cr were 0.808 and 0.786, respectively. Conclusion 1H-MRS may be useful in detecting IDH mutational status in gliomas by detecting 2HG and characteristic patterns of other metabolite ratios (NAA/Cr and Glx/Cr). This has significant clinical implications for prognostication and response assessment to novel targeted therapies in gliomas.

Digital skills are essential in today’s digital age, which means that students must gain technology-enhanced skills from higher education for their future careers. Studies in Art & Design (A&D) programs in this university surveyed three faculties’ perspectives and nineteen students’ experiences. During the COVID-19 pandemic, this university changed its teaching and learning strategies by offering courses online during autumn 2020 and spring 2021 during mandatory quarantine. However, the A&D program was not entirely based online. As a result, it is important to take a closer look at the A&D programs offered in order to assess the faculties’ perspectives and students’ experiences during the two online semesters. The study included online surveys from instructors’ perspectives and with regard to students’ experiences about the quality of studio learning, traditional studio learning opportunities, and online studio learning opportunities via either live (on-campus) or online studios. Using relationship-based research design, posttest data surveys were collected to ascertain the differences in the mean scores, standard deviations, and percentages of some forms of agreement between the faculties’ perspectives and students’ experiences of the quality of studio learning, traditional studio learning opportunities, and online studio learning opportunities in these Art & Design (A&D) programs. This quantitative research aimed to develop formative assessments and suggestions while establishing whether it would be possible to hold all A&D courses online in a higher education setting.

This is an exercise to explore the concentration of Lithium, Lithium-7 isotope and the possible presence of black dirty ice in the lunar surface using spectral data obtained from the Clementine mission. The main interest in tracing the lithium and presence of dark ice in the lunar surface are closely related to future human settlement missions in the Moon. We investigate the distribution of Lithium and 7 Li isotope on the Lunar surface, employing spectral data from the Clementine images. We utilized Visible (VIS-NIR) imagery at wavelengths of 450, 750, 900, 950, and 1000 nm, along with Near-Infrared (NIR-SWIR) at 1100, 1250, 1500, 2000, 2600, and 2780 nm, encompassing 11 bands in total. This dataset offers a comprehensive coverage of about 80% of the lunar surface, with resolutions ranging from 100 to 500 meters, spanning latitudes from 80°S to 80°N. In order to extract quantitative abundance of Lithium, ground truth sites were used to calibrate the Clementine images. Samples (12045, 15058, 15475, 15555, 62255, 70035, 74220 and 75075) returned from Apollo missions 12, 15, 16 and 17 have been correlated to the Clementine VIS-NIR bands and five spectral ratios. The 5 spectral ratios calculated synthesize the main spectral features of sample spectra that were grouped by their Lithium and 7 Li content using Principal Component Analysis. The ratios spectrally characterize substrates of anorthosite, silica-rich basalts, olivine-rich basalts and High-T mare basalts and Orange soils. Our findings reveal a strong linear correlation between the spectral parameters and the lithium content in the 8 Apollo samples. With the values of the 11 Clementine bands and the 5 spectral ratios for each of the 8 lunar soils we performed linear regression models to estimate the concentration of Lithium and 7 Li. Also, we calculated Digital Terrain Models (DTMs; Altitude, Slope, Aspect, DirectInsolation and WindExposition) from LOLA-DTM to discover relations between relief and spatial distribution of the extended models of lithium and 7 Li. The analysis was conducted in a mask polygon extracted from Lunar Orbiter Laser Altimeter (LOLA) and located around the Apollo 15 landing site. This analysis seeks to uncover potential 7 Li enrichment through spallation processes, influenced by varying exposure to solar wind. To explore the possibility of find ice mixed with regolithe (black ice) we used a spectral library (350-2500nm) form ices dirty with different concentration of volcanic particles.

For centuries, humans have relied on natural products to prevent and treat numerous health issues. However, biologically active compounds from natural sources, such as polyphenols, face significant challenges, including low solubility, rapid metabolism, and instability, which hinder their effectiveness. Advances in science and nanotechnology have provided solutions to overcoming these problems through the use of porous silica materials. These materials possess unique properties, such as a high specific surface area, adjustable particle and pore sizes, and a surface that can be easily and selectively modified. In this review, we summarize and discuss findings on how the pore and particle size, structure, and surface modification of silica materials influence the preparation of efficient delivery systems for biologically active polyphenols from natural sources. The available data demonstrate how parameters such as adsorption capacity, release and antioxidant properties, bioavailability, solubility, stability, etc. of the studied delivery systems could be affected by the structural and chemical characteristics of the porous silica carriers.

Climate change and over-exploitation are imposing unprecedented threats to the groundwater resource. Globally, groundwater reserves have depleted to the extent that well yield have decreased, pumping cost have risen, and land have irreversibly subsided. In Malawi, groundwater quantity is a national problem, specifically in Mzimba district due to severe droughts. In this study, the spatial and temporal trends of groundwater depletion was assessed using Gravity Recovery and Climate Experiment (GRACE) data and Land Surface Models (LSM) from Global Land Data Assimilation System (GLDAS) and Global Surface Water Explorer (GSWE). The results show that 1. Groundwater storage is depleting at an average rate of-1.0 ± 0.06 cm yr-1(0.1043 km3yr-1) in the study area with high rate of up to -1.2 cm yr-1(0.12516 km3 yr-1) in the western side and as low as –0.4 cm yr-1(0.04172 km3 yr-1) in the eastern part. 2. Groundwater storage increases from -13 cm in November up to 15 cm between May and April. 3. Drought is the primary cause of such depletion trends with correlation between active evapotranspiration and groundwater depletion, and downward surface shortwave radiation and groundwater depletion, at -0.577 and -0.678 respectively. The results from the study reveals the need for the scientific community and the general public to consider groundwater recharge strategies specifically by mitigating climate change to reduce prolonged droughts. The study suggests the need to establish a stand-alone groundwater assessment and monitoring authority for enhanced conservation efforts of the water resource in the country.

The beta-galactoside-binding mammalian lectin galectin-1 can bind, via its carbohydrate recognition domain (CRD), various cell surface glycoproteins and has been implicated in a range of cancers. As a consequence of binding to sugar residues on cell surface receptors it has been shown to have a pleiotropic effect across many cell types and mechanisms resulting in immune system modulation and cancer progression. As a result, it has started to become a therapeutic target for both small and large molecules. In previous studies, we have used fluorescence polarisation (FP) assays to determine KD values to screen and triage small molecule glycomimetics that bind to the galectin-1 CRD. In this study surface plasmon resonance (SPR) was used to compare human and mouse galectin-1 affinity measures with FP as SPR has not been applied for compound screening against this galectin. Binding affinities for a selection of mono- and di-saccharides covering a 1,000-fold range correlated well between FP and SPR assay formats for both human and mouse galectin-1. It was shown that slower dissociation drove the increased affinity at human galectin-1 whilst faster association was responsible for the effects at mouse galectin-1. This study demonstrates that SPR is a sound alternative to FP for early drug discovery screening and determining affinity estimates. Consequently, it also allows association and dissociation constants to be measured in a high throughput manner for small molecule galectin-1 inhibitors.