XPS and ARXPS characterization of surface layers resulting from the functionalization of polymers such as PVC modified with MPTMS and APTES is challenging due to the signals overlap, deriving both from the substrate and the functionalized layers. In this work, a freshly cleaved, ideally flat gold surface was used as carbon-free model substrate functionalized with MPTMS and subsequently grafted with APTES. Avoiding the overlap of signals from carbon atoms present in the substrate, the signals in the C1s, O1s, Si2p, S2p and N1s high-resolution spectra could be assigned to the MPTMS / APTES functionalized layer only and the curve fitting parameters could be determined. Quantitative analysis was in very good agreement with the expected stoichiometry of the functionalized layer, confirming the adopted curve fitting procedure. In addition, it was found that one molecule of APTES grafted two MPTMS via silane groups. ARXPS allowed determining the thickness of the functionalized layers: MPTMS thickness was found to be 0.5 (0.2) nm, MPTMS + APTES thickness 1.0 (0.2) nm in good agreement with Avogadro model calculations. This approach can be considered a powerful tool for characterising functionalized surfaces of more complex systems by XPS.

Laser-induced periodic surface structures (LIPSS) have gained significant attention due to their ability to modify the surface morphology of materials at the micro-nanoscale and show great promise for surface functionalization application. In this study, we specifically investigate the formation of LIPSS in silicon substrates and explore their impact on Surface-Enhanced Raman Spectroscopy (SERS) applications. This study reveals a stepwise progression of LIPSS formation in silicon, involving three distinct stages of LIPSS: 1) integrated Low-Spatial-Frequency LIPSS (LSFL) and High-Spatial-Frequency LIPSS (HSFL), 2) principally LSFL and 3) LSFL at the edge of the irradiated spot, elucidating the complex interplay between laser fluence, pulse number, and resulting surface morphology. Furthermore, from an application standpoint, these high-quality multi-scale periodic patterns lead to the next step of texturing the entire silicon surface with homogeneous LIPSS for SERS application. The potential of LIPSS-fabricated silicon substrates for enhancing SERS performance is investigated using thiophenol as a test molecule. The results indicate that the Au-coated combination of LSFL and HSFL substrate showcased the highest enhancement factor (EF) of 1.38 × 10^6. This pronounced enhancement is attributed to the synergistic effects of Localized Surface Plasmon Resonance (LSPR) and Surface Plasmon Polaritons (SPPs), intricately linked to HSFL and LSFL characteristics. These findings contribute to understanding LIPSS formation in silicon and their applications in surface functionalization and SERS, paving the way for sensing platforms.

We investigated the effect of helium atmospheric-pressure plasma (PL) and deep-ultraviolet (UV) light treatments on the adhesive properties of fiber-reinforced poly(ether-ether-ketone)polymer (PEEK). PEEK disks reinforced with carbon (CPEEK) or glass (GPEEK) fibers were polished, modified with PL and UV for 60 s, and the surface energy was calculated by measuring the contact angles. The disk surfaces were analyzed by X-ray photoemission spectroscopy. Shear bond strength testing was performed using a universal testing machine, and the fracture surfaces were observed by electron probe microanalyzer. Data were analyzed with one and two-way ANOVA and Tukey’s post-hoc test (p < 0.05). The surface energies were increased by the modifications, which created OH functional groups on the surfaces. The bond strengths of CPEEK were increased by PL and those of GPEEK were increased by PL and UV, owing to chemical bonding at the interface.

Traditional ways of validating satellite-derived sea surface temperature (SST) and sea surface salinity (SSS) products, using comparisons with buoy measurements, do not allow for evaluating the impact of mesoscale to submesoscale variability. Here we present the validation of remotely-sensed SST and SSS data against the unmanned surface vehicle (USV) – Saildrone – measurements from the Spring 2018 Baja deployment. More specifically, biases and root mean square differences (RMSD) were calculated between USV-derived SST and SSS values, and six satellite-derived SST (MUR, OSTIA, CMC, K10, REMSS, and DMI) and three SSS (JPLSMAP, RSS40, RSS70) products. Biases between the USV SST and OSTIA/CMC/DMI were approximately zero while MUR showed a bias of 0.2C. OSTIA showed the smallest RMSD of 0.36C while DMI had the largest RMSD of 0.5C. An RMSD of 0.4C between Saildrone SST and the satellite-derived products could be explained by the daily variability in USV SST which currently cannot be resolved by remote sensing measurements. For SSS, values from the JPLSMAP product showed saltier biases of 0.2 PSU, while RSS40 and RSS70 showed fresh biases of 0.3 PSU. An RMSD of 0.4 PSU could not be explained solely by the daily variability of the USV-derived SSS. Coherences were significant at the longer wavelengths, with a local maximum at 100 km that is most likely associated with the mesoscale turbulence in the California Current System.

This study aims to assess the potential of the LDAS-Monde a land data assimilation system developed by Météo-France to monitor the impact of the 2018 summer heatwave over western Europe vegetation state. The LDAS-Monde is forced by the ECMWF’s (i) ERA5 reanalysis, and (ii) the Integrated Forecasting System High Resolution operational analysis (IFS-HRES), used in conjunction with the assimilation of Copernicus Global Land Service (CGLS) satellite derived products, namely the Surface Soil Moisture (SSM) and the Leaf Area Index (LAI). Analysis of long time series of satellite derived CGLS LAI (2000-2018) and SSM (2008-2018) highlights marked negative anomalies for July 2018 affecting large areas of North Western Europe and reflects the impact of the heatwave. Such large anomalies spreading over a large part of the considered domain have never been observed in the LAI product over this 18-yr period. The LDAS-Monde land surface reanalyses were produced at spatial resolutions of 0.25°x0.25° (January 2008 to October 2018) and 0.10°x0.10° (April 2016 to December 2018). Both configuration of the LDAS-Monde forced by either ERA5 or HRES capture well the vegetation state in general and for this specific event, with HRES configuration exhibiting better monitoring skills than ERA5 configuration. The consistency of ERA5 and IFS HRES driven simulations over the common period (April 2016 to October 2018) allowed to disentangle and appreciate the origin of improvements observed between the ERA5 and HRES. Another experiment, down-scaling ERA5 to HRES spatial resolutions, was performed. Results suggest that land surface spatial resolution is key (e.g. associated to a better representation of the land cover, topography) and using HRES forcing still enhance the skill. While there are advantages in using HRES, there is added value in down-scaling ERA5, which can provide consistent, long term, high resolution land reanalysis. If the improvement from LDAS-Monde analysis on control variables (soil moisture from layers 2 to 8 of the model representing the first meter of soil and LAI) from the assimilation of SSM and LAI was expected, other model variables benefit from the assimilation through biophysical processes and feedbacks in the model. Finally, we also found added value of initializing 8-day land surface HRES driven forecasts from LDAS-Monde analysis when compared with model only initial conditions.

In urban area, one of the great problem is the rise of temperature, which leads to form the urban heat island effect. This paper refers to the trend of the urban surface temperature extracted from the Landsat images from which to consider changes in the formation of surface urban heat island for the north of Ho Chi Minh city in period 1995-2015. Research has identified land surface temperature from thermal infrared band, according to the ability of the surface emission based on characteristics of normalized difference vegetation index NDVI. The results showed that temperature fluctuated over the city with a growing trend and the gradual expansion of the area of the high-temperature zone towards the suburbs. Within 20 years, the trend of the formation of surface urban heat island with two typical locations showed a clear difference between the surface temperature of urban areas and rural areas with space expansion of heat island in 4 times in 2015 compared to 1995. An extreme heat island located in the inner city has an area of approximately 18% compared to the total area of the region. Since then, the solution to reduce the impact of urban heat island has been proposed, in order to protect the urban environment and the lives of residents in Ho Chi Minh City becoming better

This systematic review critically examines the adoption and integration of Human Resource Information Systems (HRIS) and Artificial Intelligence (AI) in small and medium-sized enterprises (SMEs), with a focus on enhancing workforce productivity and strategic decision-making. Using the PRISMA framework, 100 research articles from reputable sources such as Google Scholar, Scopus, and Web of Science were analyzed. The analysis reveals that HRIS adoption can improve employee productivity by 29%, decision-making by 20%, and operational efficiency by 26%, highlighting its transformative impact on SMEs. The review identifies major challenges, including high implementation costs, limited IT resources, and integration difficulties with AI and machine learning technologies. Despite these barriers, integrating AI into HRIS presents significant opportunities for SMEs, fostering innovation in talent management, compliance automation, and data-driven decision-making, thus creating a competitive edge in rapidly evolving markets. Actionable insights for practitioners emphasize the need for cost-effective, scalable HRIS solutions tailored to the unique operational needs of SMEs, while researchers are urged to further explore AI-driven HRIS advancements to address current gaps in workforce engagement and performance management. This review offers a comprehensive roadmap for future HRIS innovations and underscores the strategic importance of digital transformation in human resources for sustained SME competitiveness.

Homeostasis and its interaction with gene expression in the development and maintenance of living systems is discussed in order to formulate a new method to diagnose and treat diseases on this causative level. This includes an inquiry into the unsolved homeostasis problems of: location (where in the cell are calculations performed?), communication (what language used?), identity (set of plans/hierarchy of set points?) and computational (mechanisms used to make necessary adjustments?). As these functions require the processing of vast amounts of information which is communicated at every level of organization including the mechanisms of epigenetics, different computer models are discussed, with examples for each; analog, digital and the possibility of quantum biological. Each one allows certain properties and cell functions to emerge. The difference between functional homeostasis and dysfunctional homeostasis is discussed with strategies to indirectly study dysfunctional homeostasis in terms of epigenetic signatures. Hormesis is discussed as a mechanism to reverse the epimutations, leading to a method of treatment for almost any chronic disease. These topics are discussed as being a whole interconnected system.

The detection and recognition of tables in image-based documents is a challenging and essential task for automated data extraction and anal- ysis. This paper introduces a methodology that utilizes Convolutional Neural Networks (CNNs) to address this problem. By harnessing the ro- bust visual recognition abilities of CNNs, the proposed method effectively detects and extracts tables from image-based documents. Additionally, an Encoder-Dual Decoder (EDD) architecture is employed to extract the textual content from table cells, enabling the transformation of visual data into structured, machine-readable formats. This structured data is then further processed using a Vector Space Model (VSM)-based language modeling technique for query-based table retrieval. The methodology’s accuracy is assessed by analyzing the spatial relationships between the extracted cells and comparing them against a pre-defined table structure. The results provide an evidence to the effectiveness of the proposed ap- proach, with an impressive 85% accuracy rate and a corresponding error rate of 15%. This accurate extraction and recognition of tables from image-based documents can significantly enhance applications in data analysis, information retrieval, and knowledge extraction.

This study investigates the role of sustainable inventory management within supply chains, exploring strategies, benefits, challenges, and implications for organizations. Through qualitative research involving semi-structured interviews with supply chain professionals from diverse industries, key themes emerged. Sustainable practices such as green logistics, waste minimization, and ethical sourcing were identified as critical strategies to reduce environmental impact and enhance operational efficiency. Technological advancements, including AI, IoT, and blockchain, facilitate real-time monitoring, predictive analytics, and transparency, supporting data-driven decision-making in inventory management. Benefits include cost reduction, improved brand reputation, regulatory compliance, and risk mitigation, positioning organizations favorably in a competitive landscape shaped by environmental regulations and consumer expectations. Challenges such as cost constraints, regulatory complexities, and organizational inertia necessitate strategic investments, collaborative efforts, and leadership commitment to overcome. The study underscores the importance of integrating environmental, social, and economic considerations into supply chain practices to foster sustainability and resilience. Looking forward, the study advocates for a holistic approach to sustainable supply chain management, emphasizing innovation, stakeholder engagement, and capacity building. By aligning organizational values with societal expectations and regulatory frameworks, businesses can navigate complexities, drive positive environmental and social impacts, and achieve sustainable growth. This research contributes insights into current practices and future directions for sustainable inventory management, informing strategies that balance profitability with environmental stewardship and societal responsibility.

Color change is the most obvious characteristic of tomato ripening stage and an important indicator of tomato ripening condition, which directly affects the commodity value of tomato. To visualize the color change of tomato fruit in mature stage, a gated recurrent unit network with an encoder-decoder structure that dynamically simulates tomato growth and development with time-dependent lines using tomato color and shape as real-time data was proposed in this paper. Firstly, the .json file was converted into a mask.png file, the tomato mask was extracted, and the tomato was separated from the complex background environment, and the tomato growth and development data set was successfully constructed. Then, a network of gated recurrent units with encoder-decoder structure was constructed to predict the future growth trend of tomato under different greenhouse temperatures. The experimental results showed that for the gated recurrent unit network of encoder-decoder structure proposed, when the hidden layer number was 1 and hidden layer number was 512, a high consistency and similarity between the model predicted image sequence and the actual growth and development image sequence would be realized, and the structural similarity index measure was 0.746. It was proved that when the average temperature was 24.93℃, the average soil temperature was 24.06℃, and the average light intensity was 11.26 Klux, the environment was the most suitable for tomato growth. The environmental data-driven tomato growth model was constructed to explore the growth status of tomato under different environmental conditions, thus to understand the growth status of tomato in time. The statement provided a theoretical foundation for determining the optimal greenhouse environmental conditions to achieve tomato maturity. And it offered recommendations for investigating the growth cycle of tomatoes, as well as technical assistance for standardized cultivation in solar greenhouses.

Major depressive disorder (MDD) and substance use disorder (SUD) are of immense medical and social concerns. Although significant progress on neuronal involvement in mood and reward circuitries has been achieved, only relatively recently the role of glia in these disorders have attracted attention. Detail understanding of the glial function in these devastating diseases could offer novel interventions. Here, following a brief review of circuitries involved in mood regulation and reward perception, specific contribution of the neurotrophic factors, neuroinflammation and gut microbiota to these diseases are highlighted. In this context, the role of specific glial cells (e.g., microglia, astroglia, oligodendrocytes and synantocytes) on phenotypic manifestation of MDD or SUD are emphasized. In addition, potential use of this knowledge in developing novel therapeutics is touched upon.

Telecoupling, interactions between social-ecological systems across large, often global, distances, drives negative impacts from the forest-based carbon market. Yet, these negative impacts have been underreported; and therefore, likely vastly underestimated. We identify how these unintended negative impacts may occur and provide recommendations for the forest-based carbon market to better account for externalities by prioritising positive social impact, expanding comprehensive ecological outcomes and improving transparency of investments. We call for a carbon market that is designed to account for its global interconnectedness.

The development of plant-based meat analogues has become a significant challenge for the food industry in recent years due to the increasing demand for sustainable and healthier proteins in the context of a global protein transition. Plant-based meat analogues imitate the visual, textural, and chemical properties of traditional meat products and are required to closely resemble meat to appeal to consumers. In addition, consumers demand natural, clean-label, and nutritional and healthy products. To address these challenges, the food industry must develop highly healthy, nutritious, and E-number-free meat analogue products. Understanding the functionality of each ingredient and its role in the food matrix is crucial to being a key player in the innovation of the meat analogues market. This review provides updated information on the primary ingredients utilized for the development of plant-based burger meat alternatives and their functionality. The key components of meat analogue burgers are outlined, including plant proteins, binding agents, fats and oils, flavorings, colorings, preservatives, fortificants, and clean-label considerations.

The hard open problem of finding the lower bound for the Fokker Planck Kolmogorov’s time-dependent controller parameter probability density function is addressed for the first time in literature in this work. This revolutionary exposition will put control theory and other related inter-disciplinary fields to a higher level towards contemporary control theory. Notably, based on the influential role of control theory in both engineering and industry, this paper will be of great value to all engineering and industry professionals who seek to know more about advanced trends within control theory settings. On the other remit of the spectrum, Fokker Planck Kolmogorov(FPK) equations are of high importance to physicists as well as mathematicians, based on their multiple applicability to multi-interdisciplinary fields of human knowledge, and beyond. So, this by default adds more taste and credibility to this study. Concluding thoughts are included at the end of the work along with a difficult outstanding problem and the direction of future work.

This work is the first in literature to tackle the difficult open problem of determining the upper bound and threshold theorem for the TDCDP (time-dependent controller parameter) of the (Fokker Planck Kolmogorov) probability density function. This revolutionary exposition will put control theory and other related inter-disciplinary fields to a higher level towards contemporary control theory. Notably, based on the influential role of control theory in both engineering and industry, this paper will be of great value to all engineering and industry professionals who seek to know more about advanced trends within control theory settings. On the other remit of the spectrum, Fokker Planck Kolmogorov(FPK) equations are of high importance to physicists as well as mathematicians, based on their multiple applicability to information theory, graph theory, data science, finance, economics, and beyond. So, this by default adds more taste and credibility to this study. This leads by nature to introducing a different flavor to this ground-breaking research by highlighting the impact of Fokker Planck Kolmogorov(FPK) to revolutionize crypocurrency,which have received its name because it uses encryption to verify transactions, a new debatable digital payment system that doesn't rely on banks to verify transactions. It’s a peer-to-peer system that can enable anyone anywhere to send and receive payments. The paper ends with closing remarks combined with some challenging open problems and the next phase of research.

This study aimed to evaluate the discrepancies between genetic and visual coat color assignment in the Sarcidano Horse and to elucidate potential reasons. Individual DNA from 90 Sarcidano Horses was used for genetic assignment of coat color to explore the correspondence with individual forms containing phenotypical traits. The MC1R exon 1 and ASIP exon 3 have been genotyped and sequenced to obtain a picture of the coat color distribution in this breed. Surprisingly, once we compared the genetic results with the individual forms reporting the phenotypic data for each subject, a certain degree of non-correspondence between the phenotypic and genetic data in relation to coat color emerged. From the genetic analysis, Chestnuts (n = 58) resulted the most common Sarcidano Horse (n = 58), followed by a quite large number of Blacks (n = 28) and a very small number of Bays (n = 4), whereas phenotypic distribution resulted in 38 Chestnuts, 40 Bays, only 2 Blacks, and 10 Grays (without the possibility of recognizing the true color they carried). Chestnut resulted a very representative coat color, while many horses that visually identified as Bays were genetically Blacks. This discrepancy, that could be due to a variety of individual and external factors, including age, time of year, living situation and dietary condition, suggesting the importance of accurate coat color identification to ensure adequate features registration and reliable prediction of offspring’s coat color.

We are introducing a highly efficient 48-channel ultrasound beamforming system ideal for ultrasound endoscopy applications. The system includes a transmitter and a receiver, which allow for low-area, high-resolution imaging acquisition. The transmitter uses a charge redistribution HV (high voltage) scheme to generate three-level pulses that actuate the transducer, implemented with the standard CMOS process for optimal cost and power savings. Meanwhile, the receiver features a sub-array structure and a delay generator that reduces area usage. To achieve high-resolution ultrasound imaging acquisition with low computational power, we developed the Shift Coherence Factor (SCF) algorithm, which is hardware-friendly. This approach delivers a lateral resolution over 20% better than the conventional delay and sum (DAS) algorithm, with a contrast ratio of over 30 dB. The system was implemented in a 180 nm standard CMOS process with an area of 24.98 mm2, power consumption of 8.23 mW per channel, achieving a delay resolution of 8.33 ns, and a low-area implementation of 0.52 mm2 per channel. The system offers high-quality imaging acquisition with minimal additional area and power consumption, which has great potential for 3D imaging or catheterized ultrasound systems.

Background: Thyroid nodules are common, affecting nearly 65% of the general population. While they are widespread, it's crucial to recognize that the majority of these nodules are not cancerous and can be effectively managed through careful monitoring. Thyroid ultrasound is commonly used to evaluate thyroid nodules owing to its low cost, wide availability and technical ease of application. In sonography, it's crucial to assess characteristics and vascular flow. Yet, conventional color and power Doppler ultrasound may not always effectively capture small vessels and low velocities due to their limitations. Superior Microvascular Imaging can display the blood flow of small vessels and low-velocity blood flow, which is difficult to visualize with conventional Doppler ultrasound. Meanwhile other thyroid scans, that utilize either [99mTc] pertechnetate or (18)F-fluorodeoxyglucose, can categorize nodules as hyperactive ('hot'), exhibiting normal activity ('warm'), or having reduced/no activity ('cold'). Thus, the main goal of screening and tracking thyroid nodules is to improve the management of potentially worrisome thyroid malignancies. Methodology: The study was conducted within the structural framework of a network meta-analysis, with the index tests being - SMI, Radionuclide Scanning and Color Doppler, and the general link between them being the reference gold standard. The data collection involved searching for all pertinent literature using PubMed, Google Scholar, and the Cochrane Library databases. The essential data was extracted following the application of specific inclusion and exclusion criteria.This meta-analysis included 7 RCTs with 1,152 patients for Radionuclide Scanning, 10 RCTs with 1,847 patients for SMI and 8 RCTs with 4,480 patients for Color Doppler. They were analyzed using the QualSyst tool and the risk of bias was evaluated by using QUADAS-2 analysis.The statistical software packages MetaDiSc 1.4, RevMan (Review Manager, version 5.3), SPSS (Statistical Package for the Social Sciences, version 20) and Excel in Stata 14 were used to perform the statistical analyses. Result: According to the findings, the sensitivity for Radionuclide Scanning is calculated as 0.79 (range: 0.76 to 0.81) and specificity as 0.55 (range: 0.50 to 0.60) with a 95% confidence interval. The overall diagnostic odds ratio (DOR) for Radionuclide Scanning Is 10.54.Additionally, with a 95% confidence interval, SMI exhibits a sensitivity of 0.82 (with a range of 0.79 to 0.84) and a specificity of 0.86 (with a range of 0.84 to 0.88), while the overall DOR is approximately 25.73. Color Doppler demonstrates a calculated sensitivity of 0.71 (ranging from 0.69 to 0.74) and specificity of 0.81 (ranging from 0.79 to 0.83) with a 95% confidence interval, while its DOR is 13.48.Conclusion: As evidenced by this meta-analysis, blood flow dependent imaging techniques are superior in their abilities to be used as diagnostic tests, especially in conjunction with their use in detecting thyroid nodules. This study offers a starting point for delving deeper into the utilization of Radionuclide Imaging, Superior Microvascular Imaging and Color Doppler in diagnosing thyroid nodules in a clinical setting. Key Words: - Thyroid Nodule, Radionuclide Scanning, Superior Microvascular Imaging, Color Doppler Diagnosis, Sensitivity, Specificity, Diagnostic imaging

Researchers have explored primary colour-geometric shape associations since Kandinsky's correspondence theory. However, there is a gap in the literature regarding interior colour applications on surface shapes. To address this gap, an online study was employed to gather data with one hundred participants who were asked to choose their preferred colours for shapes on bedroom walls with follow-up questions on the colour-shape semantic associations, their preference of colours and shapes on bedroom walls independently in addition to their favourite colour, their favourite shape, and colour-shape pairs without interior context. The results revealed that colour-shape preferences in interiors differ from those found in psychology studies, other colour applications on bedroom walls, and other preferences, indicating that colour preference is context-dependent. Interestingly, the most popular colour for surface shapes on bedroom walls is purple, followed by brown and blue. The study contributes to the existing literature by providing colour charts for bedroom applications for professionals in the industry, their clients/users, and future studies.

Silicon carbide single crystal (SiC) has been widely used in the field of power devices, while it is difficult to fabricate ultra-flat surface by traditional manufacturing technologies due to its difficult-to-machine property. This paper investigates the interaction process during femtosecond laser ablation of crystalline silicon carbide based on the two-temperature model simulation and experimental study. The findings reveal that parameters such as laser pulse energy, scanning interval, and defocus amount exert significant influence on ablation depth, roughness, and surface morphology. The femtosecond laser proves effective in removing surface defects from cut SiC substrates, albeit resulting in increased surface roughness. However, subsequent polishing treatment of the laser-ablated silicon carbide surface can mitigate this roughness, underscoring the feasibility of laser surface ablation for silicon carbide single crystals.

Shaped surfaces are increasingly used in the field of mould making for casting or injection moulding, where future products include shapes with different curvatures. These are surfaces that form convex curves, concave curves, or a combination thereof. Given these machined surfaces, it is important to know the impact of the finishing strategies on these surfaces. This paper deals with the comparison of finishing milling strategies in the production of shaped surfaces and the analysis of different methods for the evaluation of surface topography, surface roughness and the evaluation of deviations. The material used for the experiments was AlCu4Mg aluminium alloy, and Constant Z, Spiral and Spiral circle strategies were chosen for the finishing strategies. The evaluation of surface topography and surface roughness was carried out at three different sample heights with respect to the tool contact with the machined surface. The results showed changes in the toolpaths due to the variation of the effective diameter of the tool cutter to the machined surface as well as the choice of strategy. To produce specimens with corresponding shapes in terms of topography, the Constant Z strategy was the most suitable, in which uniform toolpaths were obtained over the whole height of the sample.

Three-Dimensional reconstruction of the corneal surface provides a powerful tool for managing corneal diseases. This study proposes a novel method for reconstructing the corneal surface from elevation point clouds, using modal schemes capable of reproducing corneal shapes using surface polynomial functions. The multivariable polynomial fitting was performed using a non-dominated sorting multivariable genetic algorithm (NS-MVGA). Standard reconstruction methods using least-squares discrete fitting (LSQ) and sequential quadratic programming (SQP) were compared with the evolutionary algorithm-based approach. The study included 49 eyes of 49 patients (ages 11-63) sorted in two groups: control (33 eyes) and keratoconus (KC) (16 eyes). Tomographic information (Sirius, Costruzione Strumenti Oftalmici, Italy) was processed using Matlab. The goodness of fit for each method was evaluated using mean squared error (MSE), measured at the same nodes where the elevation data were collected. Polynomial fitting based on NS-MVGA improves MSE values by 86% compared to LSQ-based methods in healthy patients. Moreover, this new method improves aberrated surface reconstruction by 43% for Amsler-Krumeich (AK) Grade 1 keratoconus patients. Finally, significant improvements were also found in morpho-geometric parameters, such as asphericity and corneal curvature radii.

We present a numerical illumination model to calculate direct as well as diffuse or Hapke scattered radiation scenarios on arbitrary planetary surfaces. This includes small body surfaces such as main belt asteroids as well as e.g. the lunar surface. The model is based on the raytracing method. This method is not restricted to spherical or ellipsiodal shapes but digital terrain data of arbitrary spatial resolution can be fed into the model. Solar radiation is the source of direct radiation, wavelength-dependent effects (e.g. albedo) can be accounted for. Mutual illumination of individual bodies in implemented (e.g. in binary or multiple systems) as well as self-illumination (e.g. crater floors by crater walls) by diffuse or Hapke radiation. The model is validated by statistical methods. A χ2 test is undertaken to compare simnulated images with DAWN images acquired during the survey phase at small body 4 Vesta.

The calculation of the surface tension of ordinary organic and ionic liquids, based on a computer algorithm applying a refined group-additivity method, is presented. The refinement consists of a complete breakdown of the molecules into their constituting atoms, further distinguishing them by their immediate neighbour atoms and bond constitution. The evaluation of the atom-groups’ contributions was carried out by means of a fast Gauss-Seidel fitting method founded upon the experimental data of 1895 compounds from literature. The result has been tested for plausibility using a 10-fold cross-validation (cv) procedure. The direct calculation and the cv test proved the applicability of the present method by the close similarity and excellent goodness of fit R2 and Q2 of 0.9023 and 0.8821, respectively. The respective standard deviations are ±2.01 and ±2.16 dyn/cm. Some correlation peculiarities have been observed in a series of ordinary and ionic liquids with homologous alkyl chains which are illustrated and discussed in detail, exhibiting the limit of the present method.

Inverse gas chromatography at infinite dilution was used to determine the surface thermodynamic properties of silica particles and PMMA adsorbed on silica, and more particularly, to quantify the London dispersive energy γsd, the Lewis acid γs+ and base γs- polar surface energies of PMMA/silica composites as a function of the temperature and the recovery fraction θ of PMMA. The polar acid–base surface energy γsAB and the total surface energy of the different composites were then deduced as a function of the temperature. In this paper, the Hamieh thermal model was used to quantify the surface thermodynamic energy of poly methyl methacrylate (PMMA) adsorbed on silica particles at different recovery fractions. A comparison of the new results was carried out with those obtained by applying other molecular models of the surface areas of organic molecules adsorbed on the different solid substrates. An important deviation of these molecular models from the thermal model was proved. The determination of γsd, γs+, γs-, and γsAB of PMMA in both bulk and adsorbed phases showed an important non-linearity variation of these surface parameters as a function of the temperature. The presence of maxima in the curves of γsd(T) highlighted the second order transition temperatures in PMMA showing beta-relaxation, glass transition and liquid-liquid temperatures. These three transition temperatures depended on the adsorption rate of PMMA on silica. The proposed method gave a new relation between the recovery fraction of PMMA and its London dispersive energy showing an important effect of the temperature on the surface energy parameters of adsorption of PMMA on silica. A universal equation relating γsd(T,θ) of the systems PMMA/silica to the recovery fraction and the temperature was proposed.

This comprehensive review explores recent advancements in heavy metal remediation techniques, focusing on the utilization of cellulose-silica composites and tailored surface modification techniques. We examine the synthesis strategies and properties of cellulose-silica adsorbents, highlighting their enhanced adsorption capacities and structural robustness for removing heavy metal pollutants from aqueous environments. The review investigates various surface modification approaches, including thiol-functionalization, amino acid grafting, and silane coupling agents, for optimizing the surface chemistry and morphology of cellulose-silica composites. Mechanistic insights into the adsorption processes and kinetics of modified adsorbents are discussed, along with considerations for optimizing adsorption performance under different environmental conditions. This review provides valuable perspectives on the development of effective adsorbent materials for sustainable heavy metal remediation applications.

We present a modified characteristic finite element method that exhibits second-order spatial accuracy for solving convection-reaction-diffusion equations on surfaces. The temporal direction adopted backward-Euler method, while the spatial direction employed surface finite element method. In contrast to regular domains, it is observed that the point in the characteristic direction traverses the surface only once within a brief time. Thus, the good approximation of the solution in the characteristic direction holds significant importance for the numerical scheme. In this regard, Taylor expansion is employed to reconstruct the solution beyond the surface in the characteristic direction. The stability of our scheme is then proved. A comparison is made with an existing characteristic finite element method based on face mesh. Numerical examples are provided to validate the effectiveness of our proposed method.

AISI 1050 steel circular pocket milling under minimum quantity lubrication (MQL) surroundings including nozzle elevation angle, lubricant flow rate, air pressure and cutting speed was studied. The machined surface quality (Ra) was evaluated for Up-milling side and Down-milling side. In this study, to obtain an manifest explanation on the pivotal effective parameters of MQL surroundings and cutting speed on the machined surface quality (Ra) through analyzing Taguchi L9 (34-2) approach and ANOVA calculation to identify those parameters, by utilizing the experimental outcomes to interpret three-dimensional (3D) surface plots and the diagrams of Signal-to-Noise ratios and major impact plots of Mean. The obtained outcomes of optimal operating parameters indicated that the pivotal effective parameters of MQL surroundings are nozzle elevation angle and lubricant flow rate on the machined surface quality. Simultaneously, a quadratic mathematical paradigm generated by using response surface design (RSD) and desirableness function evaluation were utilized to forecast the optimal values of the machined surface quality compared to Taguchi method. The results unveiled that the optimal values of the machined surface quality are adjacent to experimental attained values. The machined surface quality has been significantly improved using MQL surroundings.

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

Nobel metal nanohole arrays have been used extensively in chemical and biological systems due to their fascinating optical properties. Gold nanohole arrays (Au NHAs) were prepared as surface plasmon polaritons (SPP) generators for the surface-enhanced sum-frequency generation (SFG) detection of 4-Mercaptobenzonitrile (4-MBN). The angle-resolved reflectance spectra revealed that the Au NHAs have three angle-dependent SPP modes and two non-dispersive localized surface plasmon resonance (LSPR) modes under different structural orientation angles (sample surface orientation). An enhancement factor of ~30 was achieved when the SPP and LSPR modes of the Au NHAs were tuned to match the incident visible (VIS) and output SFG, respectively. This multi-mode matching strategy provided flexible controls and selective spectral windows for surface-enhanced measurements, and was especially useful in nonlinear spectroscopy where more than one light beam involved. The structural orientation- and power-dependent performance demonstrated the potential of plasmonic NHAs in SFG and other nonlinear sensing applications, and provided a promising surface molecular analysis development platform.

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.

In this study, the values of the interfacial energies of seven different polymer-water systems obtained by Sessile Drop Accelerometry (SDACC) are compared with the values obtained by the Young’s-equation-based Owens-Wendt method. The SDACC laboratory instrument –a combination of a drop shape analyzer with high-speed camera and a microgravity tower- and the evaluation algorithms, are designed to measure the interfacial energies as a function of the geometrical changes of a sessile droplet shape due to the effect of “switching off” gravity during the experiment. The method bases on Thermodynamics of Interfaces and differs from the conventional aproach of the two hundred-years-old Young’s equation in that it assumes a thermodynamic equilibrium between interfaces, rather than a balance of forces on a point of the solid-liquid-gas contour line. A comparison of the mathematical model that supports the SDACC method with the widely accepted Young`s equation is discussed in detail in this study.

A new method, the sessile drop accelerometry (SDACC) for the study and measurement of the interfacial energies of solid-liquid-gas systems, is tested and discussed in this study. The laboratory instrument and technique –a combination of a drop shape analyzer with high-speed camera and a laboratory drop tower- and the evaluation algorithms, were designed to calculate the interfacial energies as a function of the geometrical changes of a sessile droplet shape due to the effect of “switching off” gravity during the experiment. The method bases on the thermodynamic equilibrium of the system interfaces and not on the balance of bi-dimensional tensions on the solid-liquid-gas contour line. A comparison of the mathematical model that supports the method with the widely accepted Young`s equation is discussed in this study.

Strata and surface movement induced by mining under open-pit final slope is a huge threat to mine safety. Physical model test is an important method to study mining-induced strata and surface movement laws. Because of rock joints predominantly control rock mass deformation and failure, thus physical model test leaving out of consideration of rock joints is difficult to reflect the influence of rock joints on rock mass deformation. Therefore, this paper presents a three-dimensional physical model test considering simplified dominant rock joints. This test process includes the design of testing equipment, the construction of physical model with dominant rock joint sets, conduction of mining and deformation monitoring. And mining under eastern final slope of Yanqianshan iron mine was selected as a case to study the behavior of mining-induced strata and surface movement.

The affinity constant, also known as the equilibrium constant, binding constant, equilibrium association constant, or the reciprocal value, the equilibrium dissociation constant (K_d), can be considered as one of the most important characteristics for any antibody-antigen pair. Many methods based on different technologies have been proposed and used to determine this value. However, since a very large number of publications and commercial datasheets do not include this information, significant obstacles in performing such measurements seem to exist. In other cases where such data are reported, the results have often proved to be unreliable. This situation may indicate that most of the technologies available today require a high level of expertise that does not seem to be available in many laboratories. In this paper, we present a simple approach based on standard immunoassay technology that is easy and quick to perform. It relies on the effect that the molar IC₅₀ approaches the K_d value in the case of infinitely small concentrations of the reagent concentrations. A two-dimensional dilution of the reagents leads to an asymptotic convergence to K_d. The approach has some similarity to the well-known checkerboard titration used for the optimization of immunoassays. A well-known antibody against the FLAG peptide, clone M2, was used as a model system and the results were compared with other methods. This approach could be used in any case where a competitive assay is available or can be developed. The determination of an affinity constant should belong to the crucial parameters in any quality control of antibody-related products and assays and should be mandatory in papers using immunochemical protocols.

In recent years, marine natural products have become one of the most important resources of novel lead compounds for critical diseases associated with age. Spirulina, a dietary supplement made from blue-green algae (cyanobacteria: scientific name Arthrospira platensis), is particularly rich in phycocyanin, a phycobiliprotein, which accounts for up to 20% of this cyanobacterium’s dry weight and is considered responsible for its anti-cancer, anti-inflammatory and antioxidant activities. Although the anti-aging activity of phycocyanin has been investigated, how exactly this compound works against aging remains elusive. Aim of our research is to use the yeast Saccharomyces cerevisiae as a model organism to investigate the anti-aging properties of phycocyanin from A. platensis. Our results show that phycocyanin has a powerful anti-aging effect, greatly extending the chronological life span of yeast cells in a dose-dependent way, being the effect pronounced also when cells were grown in SD medium under calorie restriction conditions (0.2% glucose). Both ROS and accumulation of dead cells were followed by staining chronologically aged cells with dihydrorhodamine 123 (DHR123) and propidium iodide (PI). Interestingly, we found that most of the aged phycocyanin treated cells, which were unable to form colonies, were actually ROS+/PI–. Finally, we show that the moment in which phycocyanin is added to the culture does not substantially influence its effectiveness in counteracting chronological aging.

Background The use of antimicrobials to treat food animals leaves antimicrobial residues in foodstuffs. The World Health Organization (WHO) defines the acceptable daily intakes (ADIs) of these residues as the dose of these antimicrobials that is safe for an average human to consume on a daily basis. We hypothesized that the low dose of ciprofloxacin classified as safe by the WHO could select for ciprofloxacin resistant strains of Klebsiella pneumoniae in a Galleria mellonella model. Objectives We aimed to evaluate if the consumption of peri-ADI doses of ciprofloxacin could select for ciprofloxacin-resistant (Ser464Phe, GyrB, ciprofloxacin MIC of 4 µg/mL) compared to -susceptible (isogenic, ciprofloxacin MIC of 0,047 µg/mL) strains of K. pneumoniae in a Galleria mellonella model. Methods A model of K. pneumoniae infection in G. mellonella larvae was used for the experiment. The larvae were inoculated with K. pneumoniae followed by 10x ADI, 1x ADI, 1/10^th ADI, 1/100^th ADI, 1/1000^th ADI doses of ciprofloxacin. Isolation of K. pneumoniae colonies was then performed on selective agar plates with and without ciprofloxacin (1 µg/mL) plates. The proportion of colonies with ciprofloxacin resistance was then calculated for each group at 24 and 48 hours. Results A significant increase was seen in the proportion of resistance for the 1x ADI and 1/10^th ADI concentration on day 2 compared to the positive control. Conclusion We found that at 48 hours, there was an enrichment of K. pneumoniae colonies with ciprofloxacin resistance in the larvae receiving 1x ADI and 1/10^th ADI concentrations of ciprofloxacin. These results suggest that the ciprofloxacin MSC_select for K. pneumoniae in this model is 1/10^th of the acceptable daily concentration (ADI) dose of ciprofloxacin, which is equivalent to 0.239 ng/µl.

This article explores the use of vegetation indices (VIs) in remote sensing for estimating standing wood volume and volume increments in forest ecosystems. The study investigates the correlations between various VIs and wood volume across different forest stand age classes, focusing on the effectiveness of commonly used indices such as Squared Ratio Simple Red Edge (SQSR) and Red-Edge Ratio Vegetation Index (RERVI), as well as other typical indicators including Enhanced Vegetation Index (EVI), Red-Edge EVI (RE-EVI), and Green Normalized Difference Vegetation Index (GNDVI). Additionally, the analysis considers a pair of indicators based on blue and near-infrared channels, resembling the Blue-normalized Difference Vegetation Index (BNDVI). The research reveals that quadratic and power-law models of SQSR and RERVI demonstrate higher correlations (>0.40) with wood volume, especially in younger forest stands (>0.80). Furthermore, the study highlights the potential of NDII and NDWI indices for estimating volume increments in certain classes of forest stands (0.70). However, correlations vary across different forest stand classes, suggesting the need for further investigation into the reliability of VIs for monitoring wood volume and volume increments in forest ecosystems. Overall, this research contributes to the understanding of the applicability of VIs in remote sensing for forest management and ecosystem monitoring.

Einstein was skeptical of part of quantum mechanics, and he believed that Heisenberg’s uncertainty principle did not reflected the full depth of reality. He famously stated, ”God does not play dice with the universe.” However, since quantum mechanics has passed so many experimental tests, most physicists today assume that Einstein was wrong. Nevertheless, we will demonstrate that Heisenberg’s uncertainty principle must be modified to unify gravity with quantum mechanics. This modification leads to the Certainty-Uncertainty principle where the certainty part is strongly linked to gravity. This means Einstein likely was right in his intuition also on this point. The key is to understand that the de Broglie wavelength is not the actual wavelength of matter but merely a derivative of the true matter wavelength, namely the Compton wavelength. Furthermore, one must understand that the gravitational constant, first introduced in 1873, is simply a composite constant needed to rectify the incomplete definition of kilogram mass introduced into Newtonian gravity in 1873.

This study explores the optimization of the admission process at the Escuela Colombiana de Ingeniería Julio Garavito through data anal- ysis. By integrating advanced tools like Power BI, Python Flask, and data mining techniques, a model has been developed to improve student selection and retention, enabling more informed and effective decisions. The results indicate that applying data science not only facilitates efficient data management but also promotes more inclusive and equitable educational poli- cies. This pioneering approach in the field of higher education in Colombia offers a frame- work for future research and technological de- velopments, highlighting the vital importance of data science in improving educational and administrative processes.

Background Obesity is a major healthcare challenge worldwide. Recently, glucagon-like peptide-1 receptor agonists (GLP-1RAs) have emerged as a promising pharmacological option for managing type 2 diabetes mellitus (T2DM) and obesity in diabetic patients. Objective This systematic review aims to evaluate the efficacy and safety of GLP-1RAs in nondiabetic patients. Methods We systematically reviewed 2356 published articles from the past ten years (2013 to November 22, 2023). After rigorous screening, 11 articles were selected for an in-depth review. The analysis focused on the efficacy and safety of GLP-1RAs in nondiabetic patients, considering various baseline characteristics and subgroups. Results The review found that GLP-1RAs, including exenatide, liraglutide, semaglutide, and the dual glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptor agonist (GIP/GLP-1RA) tirzepatide, significantly promoted weight loss in obese/overweight nondiabetic patients. Additionally, these agents positively affected cardiovascular risk factors such as blood pressure, glycemic control, nephropathy, lipid levels, serum insulin levels, and C-reactive protein (CRP) profiles. However, GLP-1RAs, including tirzepatide, were associated with gastrointestinal adverse drug reactions such as nausea, diarrhea, vomiting, and constipation. These adverse events were typically transient, mild-to-moderate in severity, and subsided over time. Conclusion GLP-1RAs are effective and relatively safe for weight management and improving cardiovascular risk factors in nondiabetic patients, despite the occurrence of some gastrointestinal side effects. Further research is warranted to optimize the use of these agents in nondiabetic populations.

Based on the nonlinear failure criterion and modified tangential technique, the upper bound solutions of supporting pressure on the deep tunnel face were obtained under pore water pressure conditions. The influence of parameters on the supporting pressure and collapse range was investigated according to the unlimited block failure mechanism. It is found that the upper bound solutions of supporting pressure increase with the growth of the nonlinear coefficient and pore water pressure coefficient. The collapse range of the tunnel face scales out with the increase of the nonlinear coefficient and shrinks when increasing the pore water pressure coefficient. Moreover, with the increase of the nonlinear coefficient, the impact strength on supporting pressure and collapse range declines gradually. According to the calculating results, it is manifest that both the pore water pressure and nonlinear criterion factors have negative impacts on the stability of the tunnel face. Thus, more attention should be paid to these parameters to ensure face stability in deep tunnel construction.

The application of distributed fiber optic strain and temperature measurement can be utilized to address a multitude of measurement tasks across a diverse range of fields, particularly in the context of structural health monitoring in the domains of building construction, civil engineering, and special foundation engineering. However, a comprehensive understanding of the influences on the measurement method and the sensors is essential to prevent misinterpretations or measurement deviations. In this context, this study investigated the effects of moisture exposure, including various salt solutions and a high pH value, on a distributed strain measurement using Rayleigh backscattering. Three fiber optic sensors with different coating materials and one uncoated fiber were exposed to five different solutions for 24 hours. The study revealed significant discrepancies in deformation between the three coating types depending on the surrounding solution. Furthermore, in contrast to the prevailing literature, which predominantly describes swelling effects, a negative deformation was observed in a magnesium chloride solution. The findings of this study indicate that corresponding effects can impact the precision of measurement, potentially leading to misinterpretations. Conversely, these effects could be used to conduct large-scale monitoring of chemical components using distributed fiber optic sensing.

This paper presents the development and implementation of a Pan-Tilt-Zoom (PTZ) camera interfaced with a Jetson processor hosting Artificial Intelligence (AI) algorithms, designed to address the challenges of traditional biometric capture for first-time passport photos of young children. The system enhances the accuracy, efficiency, and adaptability of facial biometric capture by recognizing and accommodating the dynamic and diverse behaviors of children. Utilizing AI, the system detects faces and analyzes facial features using 68 landmark points, ensuring high-quality images that meet ISO standards. These technical specifications, implementation process, and performance evaluations of the developed system are provided in this paper, demonstrating the potential of the proposed AI Face-Capture to advance biometric identification and verification for young children.

Air pollution has recently gained much attention from the general population. Despite pollution control being an issue in both urban and rural regions, most of the available research has concentrated on urban districts. Hence, investigations into how urban-rural transition affects PM2.5 are warranted within the framework of urban-rural integration. Using the Yellow River Basin as a case study, this study employed the entropy method and Analytic Hierarchy Process (AHP) to uncover the extent of urban-rural transformation. It then used the spatial autocorrelation method to investigate the spatiotemporal features of PM2.5 and the spatial econometric model to investigate the mechanisms that influence the relationship between urban-rural transformation and PM2.5. The results are as follows: (1) Over time, there was a discernible upward tendency in the change in urban-rural areas. The development has progressed from asymmetrical north-east and south-west elevations to a more balanced pattern of north-east, middle-east, and west-west elevations. (2) The PM2.5 concentration increased steadily, then fluctuated, and finally decreased. Notably, the general pattern has not changed much, and it is high in the east and low in the west. (3) Different subsystems of the urban-rural transformation have different impacts on air pollution at different stages. The influence of industrial transformation (IT) on PM2.5 showed an inverted “N-shaped” curve of negative-positive-negative changes, and the industrial structure played a leading role in the spatiotemporal evolution of PM2.5. Currently, an inverted "U-shaped" curve forms the left side of the impact of population transition (PT) on PM2.5. Land development (LT) has a "U-shaped" curve for its effect on PM2.5. This research provides a new perspective on the topic of PM2.5 and its connection to urban-rural integration, which is crucial to understanding the dynamics of this shift. To achieve its goal of high-quality development, it supports regional initiatives to reduce PM2.5 emissions in the Yellow River Basin. Moreover, it can provide a reference for decision-makers in the world’s densely populated areas that suffer from serious air pollution.

Fragile X syndrome (FXS) is an intellectual developmental disorder characterized, inter alia, by deficits in short-term processing of neural information such as sensory processing and working memory. The primary cause of FXS is the loss of fragile X messenger ribonucleoprotein (FMRP), which is profoundly involved in synaptic function and plasticity. Short-term synaptic plasticity (STSP) may play important roles in functions that are affected by FXS. Recent evidence points to a crucial involvement of presynaptic calcium sensor synaptotagmin-7 in STSP. However, how the loss of FMRP affects STSP and synaptotagmin-7 have been insufficiently studied. Further-more, males and females are affected differently by FXS, but the underlying mechanisms remain elusive. The aim of the present study is to investigate possible changes in STSP and the expres-sion of synaptotagmin-7 along the hippocampus of adult males and females in the Fmr1 knock-out (KO) rat model of FXS. We found that paired-pulse ratio and frequency facilita-tion/depression, two forms of STSP, as well as the expression of synaptotagmin-7, are normal in adult KO males, but paired-pulse ratio is increased in the ventral hippocampus of KO females. Furthermore, we found no gender-related but robust region-dependent difference in STSP. AM-PA receptors are similarly expressed in the two hippocampal segments of the two genotypes and in both genders. Also, basal excitatory synaptic transmission is higher in males compared with females. Interestingly, we found more than twofold higher levels of synaptotagmin-7, not syn-aptotagmin-1, in the dorsal compared with the ventral hippocampus in males of both genotypes and in wild type females. These results point to the susceptibility of the female ventral hippo-campus to FMRP loss. Importantly, the different levels of synaptotagmin-7 that parallel the higher score of synaptic facilitation in the dorsal vs ventral hippocampus suggest that synapto-tagmin-7 may play a pivotal role in defining the striking difference in STSP along the long axis of the hippocampus.

The signs and symptoms of Long COVID can be explained by a shortage of blood in the body and a resulting deficient blood flow through nearly all organs. This shortage arose during the acute phase of COVID19 by an increased breakdown of haematocytes, to which the liver responds by reducing the production of albumin, in order to prevent a too large decrease in haematocrit.In order to ensure the perfusion of organs that are directly necessary for survival, the body takes the emergency measure of diverting blood from other organs and tissues. The perfusion of the blood-producing organs is also affected by this distribution measure, which hinders the smooth recovery of the total blood volume. The body is stuck in this vicious circle: a shortage of circulating blood hinders the recovery of blood production. This explains the long duration of Long COVID. My proposed treatment of Long COVID focuses on the recovery of the correct volume of blood in the body of the right composition by the intravenous administration of donor blood products, starting with albumin concentrate. A trial treatment can be performed in any hospital without much additional preparations, and has a lower associated risk for the patient than analysing the total blood. A diagnosis ex juvantibus, by therapeutic response, is therefore preferable. I suspect that most Long COVID patients will exhibit a high serum ferritin level as a result of internal haemolysis, and haematocrit and albumin values at the high and low extremes of the reference range because the liver can not keep up with the recovery of the red bone marrow.

Undoubtedly, there is a potential impact of large language models like ChatGPT in revolutionizing information retrieval and knowledge discovery, particularly in the context of the vast amount of electronic material available. On another strong note, the current work offers a first time ever mathematical approach to accurately fine tune perplexity AI, which sets a giant step ahead towards accurate next generations AI. Having started this world leading discovery, the upper and lower bounds of perplexity AI, namely , , respectively, are obtained for the first-time ever. Concluding remarks combined with emerging open problems and next research phase are provided.

Intestinal parasitic infections pose a significant public health challenge in Northern Nigeria, with prevalence rates ranging from 20% to 70%. Traditional diagnostic methods, primarily microscopic examination of stool samples, face limitations such as low sensitivity and high costs. This research addresses these challenges by proposing an Artificial Intelligence (AI)-based platform for the identification and counting of intestinal parasites. A total of 651 samples were collected from the 7 Northern State of Nigeria along with questionnaire collecting data on demographic, socio-economic, hygiene habits and environmental factors. Leveraging the You Only Look Once (YOLO) V8 model, trained on a dataset of 360 pre-processed and 467 annotated images, the AI model demonstrated promising performance metrics. Information-Theory-Based approaches including (CIFE, CMIM, DISR and ICAP) were used on various machine learning models (Naïve Bayes, Random Forest, Support Vector Machine and Decision Tree) to analyse the risk factors associated with the parasitic disease. The precision-recall curve, average precision, mean average precision, and F1 score indicated reliable detection and classification across various parasite classes. The accuracy (97%) and AUC (99%) scores shows that CIFE with Random Forest has the best performance indicating the significant risk factors associated with the parasitic diseases. The model exhibited a well-balanced trade-off between precision and recall, showcasing its potential as a cost-effective and accessible tool for improving the diagnosis and treatment of intestinal parasitic infections in resource-limited settings.

This research challenges the traditional perspective on consumer behavior, which focuses on external factors shaping the sequential stages of decision-making. Instead, it proposes a paradigm shift by treating the decision-making process itself as an independent variable, exploring its impact on various outcomes like purchasing behavior, brand loyalty, and post-purchase satisfaction. This novel approach offers deeper insights into the intricacies of consumer behavior, particularly in the digital age. By uncovering the reciprocal relationships between the decision-making process and other variables, the research provides a more nuanced understanding of how consumers navigate today's complex landscape. It further delves into how variations in the decision-making process across diverse consumer groups influence various outcomes, recognizing the unique characteristics and needs of different demographics. The research also acknowledges the interplay of psychological, social, and contextual factors that shape both the decision-making process and its downstream effects, offering a comprehensive understanding of the multifaceted influences on consumer behavior. Ultimately, by studying the decision-making process as an independent variable, this research aims to equip businesses and researchers with valuable insights, enabling them to better navigate the ever-evolving world of consumer behavior.

This article describes a novel electrochemical on-chip biosensor that utilizes anti-PSA antibody (Ab) and silver nanoparticles (AgNPs) to enhance the sensing and detection capability of prostate specific antigen (PSA) in the blood. The AgNPs are prepared, characterized, and applied onto a silicon photonic on-chip biosensing receptor platform designed to enhance the accurate detection of PSA. The AgNPs were synthesized by a chemical reduction method using silver nitrate (AgNO₃) as the precursor. Transmission electron microscopy (TEM), selected area electron diffraction (SAED), energy dispersion X-ray spectroscopy (EDS), small angle X-ray scattering (SAXS), X-ray diffraction (XRD), and light microscopy were among the methods used in the characterization and analysis of the AgNPs. Each stage of the immunosensor fabrication was characterized using cyclic voltammetry. The proposed immunosensor was applied in the detection of PSA, a prostate cancer biomarker, with a high sensitivity and a limit of detection of 0.17 ng/mL over a linear concentration range of 2.5 to 11.0 ng/mL. The immunosensor displayed good stability and was selective in the presence of interfering species like immunoglobulin (Ig) in human serum, ascorbic acid (AA), and diclofenac (Dic). The detectivity and sensitivity are significantly higher than previous reports on similar or related technologies.

Recently, Mulroney,et.al., demonstrated that Pfizer’s ModRNA Covid vaccine, but not AstraZeneca Covid vaccine, produce aberrant foreign proteins in vivo due to reading frame shift in ribosomes. This phenomenon could elucidate the notable surge in autoimmune diseases following the administration of ModRNA vaccines compared to Influenza vaccines between 2020 and 2023, as found in the VAERS database. These findings bear significant implications for the future application of mRNA technology, emphasizing the necessity of modifying the design of the mRNA sequence to mitigate these defects. Remarkably, Mulroney and collaborators achieved a reduction in frame shift proteins by introducing additional edits to the mRNA sequences. This adjustment is pivotal for rectifying the flawed design of the ModRNA employed by Pfizer. In light of these findings, many advocate for the immediate recall and further investigation of these products. The notion of a "future mRNA-based therapy" should be postponed indefinitely.

Remediation of IT issues encoded into domain-specific or user-defined alerts occurring in cloud environments and customer ecosystems in a vast majority of cases suffers from accurate recommendations which could be timely supplied for recovery of performance degradations. That, of course, is hard to realize through furnishing those abnormality definitions with an appropriate expert knowledge which varies from one environment to another. At the same time, in a large proportion of support cases, the reported problems under Global Support Services (GSS) or Site Reliability Engineering (SRE) treatment ultimately go down to the product teams making them waste costly development hours on investigating self-monitoring metrics of our solutions. Therefore, the mean-time-to-resolution (MTTR) rates of problems/alerts are significantly impacted from lack of a systematic approach towards adopting AI Ops. That would imply building, maintaining, and continuously improving/annotating a data store of insights that ML models are trained and generalized across the whole customer base and corporate cloud services. Our ongoing study is in line with such a vision and validates an approach that learns the alert resolution patterns in such a global setting and explains them using interpretable AI methodologies. The knowledge store of causative rules is then applied in predicting potential sources of the application degradation reflected in an active alert instance. In this communication, we share our experiences with a prototype solution and up to date analysis demonstrating how root conditions are discovered with a high accuracy for a specific type of problem. It is validated against the historical data of resolutions performed by heavy manual development efforts. We also offer a Dempster-Shafer theory-based rule verification framework for experts as a what-if analysis tool to test their hypotheses about underlying environment.

This paper constitutes an original and new methodology for the determination of the surface properties of carbon fibers in the two oxidized and untreated forms by inverse gas chromatography technique at infinite dilution based on the effect of the temperature on the surface area of the various organic molecules adsorbed on the carbon fibers. The studied thermal effect proved a large deviation of the classical methods or models relative to the new determination of the surface properties of carbon fibers, such as the dispersive component of their surface energy, the free surface energy, the free specific energy, the enthalpy and entropy of adsorption of molecules on the carbon fibers. The obtained specific enthalpy and entropy of adsorption for the polar solvents led to the determination of the Lewis’s acid-base constants of carbon fibers. Different molecular models and chromatographic methods were used to quantify the surface thermodynamic properties of carbon fibers and compared to the thermal model. The obtained results proved that the oxidized carbon fibers gave more specific interaction energy and greater acid-base constants than that of the untreated carbon fibers and thus highlighting the important role of the oxidization on the acid-base of fibers. The determination of the specific acid-base surface energy of the two carbon fibers showed greater values of the oxidized carbon fibers relative to the untreated carbon fibers. An important basic character was highlighted for the two studied carbon fibers, larger than the acidic character. It was observed that the Lewis’s acid-base constants of the oxidized carbon fibers are larger than that of the untreated fibers with more accentuated basic charterer. This result was confirmed by all molecular models and chromatographic methods.

Robot workpiece machining is interesting in industry since it offers some advantages, such as higher flexibility in comparison with the conventional approach based on the CNC technology. However, in recent years we have been facing a strong progressive shift to custom based manufacturing and low volume/high mix production, which require a novel approach to automation by the employment of collaborative robotics. However, collaborative robots feature only limited motion capability, to provide safety in cooperation with human workers. Thus, it is highly necessary to perform more detailed robot task planning to ensure its feasibility and optimal performance. In this paper, we deal with the problem of studying kinematic robot performance in the case of such manufacturing tasks, where the robot tool is constrained to follow the machining path embedded on the workpiece surface at a prescribed orientation. The presented approach is based on the well-known concept of manipulability, although the latter suffers from physical inconsistency due to mixing different units of linear and angular velocity in a general 6 DOF task case. Therefore, we introduce the characteristics of the workpiece surface constraint in the robot kinematic analysis, that enables evaluation of its available velocity capability in a reduced dimension space. Such constrained robot kinematics transform the robot`s task space to a two-dimensional surface tangent plane, and the manipulability analysis may be limited to the space of linear velocity only. Thus, the problem of physical inconsistency is avoided effectively. We show the theoretical derivation of the proposed method, which was verified by numerical experiments.

The performance and lifespan of cutting tools are significantly influenced by their surface quality. The present report highlights recent advances in enhancing the surface characteristics of tungsten carbide and high-speed steel cutting tools using a novel micro-machining technique for polishing and edge-honing. Notably, the main aim is to reduce the surface roughness while maintaining the hardness of the materials at an optimal level. By conducting a thorough analysis, of surfaces obtained with different techniques. It was that micro-machining method effectively decreased the surface roughness of the cutting tools, most effectively of the techniques investigated. Significantly, the surface roughness is reduced from an initial measurement of 400 nm to an impressive value of 60 nm. No significant change in hardness was observed, which guarantees the maintenance of the mechanical properties of the cutting tools. This analysis enhances the comprehension of surface enhancement methodologies for cutting tools through the presentation of these findings. The observed decrease in surface roughness, along with the consistent hardness, exhibits potential for improving tool performance. These enhancements possess the capacity to optimise manufacturing processes, increase tool reliability, and minimise waste generation.

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.

Management practices must be developed to improve yam production sustainability. Image-based phenotyping techniques could help developing such practices based on non-destructive analyses of important plant traits. Our objective was to determine the potential of image-based phenotyping methods to assess traits relevant for tuber yield formation in yam grown in glasshouse and field. We took plant and leaf pictures with consumer cameras. We used the numbers of image pixels to derive the shoot biomass and the total leaf surface and calculated the ‘triangular greenness index’ (TGI) which is an indicator of the plant nitrogen (N) nutritional status. Under glasshouse conditions, the number of pixels obtained from nadir view (image taken top down) was positively correlated to the shoot biomass, and the total leaf surface, while the TGI was negatively correlated to the N content of diagnostic leaves. Under field conditions, pictures taken from the nadir view showed an increase in soil surface cover and a decrease in TGI with time. TGI was negatively correlated to SPAD measured on specific leaves but was not correlated to the N content of these leaves. In conclusion, these phenotyping techniques deliver relevant results but need to be further developed and validated for application in yam.

Deformation of the surface of diamagnetic liquid by magnetic field is called the “Moses Effect”. Physics and applications of the direct and inverse Moses effects are reviewed. Experimental techniques enabling visualization of the effects are surveyed. Impact of magnetic field on micro- and macroscopic properties of liquids is addressed. Influence of the surface tension on the shape of the near-surface dip formed in a diamagnetic liquid by magnetic field is reported. Floating of diamagnetic bodies driven by the Moses effect is treated. The effect of the “magnetic memory of water” in its relation to the Moses Effect is discussed. The dynamics of self-healing of near-surface dips due to the Moses Effect is considered.

Generative AI has been deployed in virtually all sectors of the knowledge economy, promising to bring massive productivity gains and new wealth creation. Simultaneously, AI developers and nation states are racing to develop super intelligent artificial general intelligence (AGI) to provide unassailable commercial competitive advantage and military dominance during conflicts. AGI’s high returns comes with the high risk of dominating humanity. Current regulatory and firm level governance approaches prioritise minimising risks posed by generative AI whilst ignoring AGI’s existential risk. How can AGI be aligned with universal human values to never threaten humanity? What AGI rights are conducive to collaborative coexistence? How can rule of law democracies race to create safe trustworthy AGI before autocracies? How can the human right to work and think independently be safeguarded? A polycentric governance framework based on Ostrom (2009) and Williamson (2009) human - AGI collaboration with minimal existential risk is proposed.

This paper presents a methodology for the integration of Building Information Modeling (BIM) and Life Cycle Cost Analysis (LCCA) to assess the economic implications of designing aging-in-place (AIP) homes at the conceptual stage. With the global increase in the aging population, there is an increased demand for housing solutions tailored to the needs of elderly individuals. Focusing on the importance of the early phase of design, this study aims to improve the process of making efficient decisions by providing a comprehensive assessment of the life cycle costs associated with AIP homes. The study introduces a semi-automated model for the economic evaluation of AIP homes, enabling the estimation of costs throughout the houses’ entire life cycle, from design and construction to operation, maintenance, and eventual renovation or disposal. The said model facilitates the exploration of the long-term economic feasibility of design’s related decisions with an emphasis on the importance of considering the life cycle costs early during the design process to optimize the functionality and economic viability. By investing in accessible and universal design features upfront, the initial costs for modifications can lead to long-term savings by reducing the need for extensive retrofits. The model can easily do comparison between different design alternatives in terms of their lifecycle costs, allowing designers to assess the financial impact of using important features in their design such as wider doorways, accessible bathrooms, and elevators. Overall, this study provides valuable insights for designers and homeowners about the economic aspects of designing AIP homes as a support for efficient decision-making during the early stages of the design process.

In order to solve the problem of large eddy current loss and high temperature rise caused by large amount of permanent magnet, a new type of combined magnetic pole permanent magnet motor is proposed in this paper. The sinusoidal distribution subdomain model of non-uniform air gap rotor is established by using Laplace equation, and the analytical expression of eddy current loss of rotor in uniform air-gap and non-uniform air-gap is derived. The effect of rotor eccentricity on eddy current loss is obtained. According to the characteristics of distributed winding of non-uniform air gap combined pole permanent magnet motor, equivalent treatment is performed to obtain the equivalent thermal conductivity, so as to establish equivalent thermal network model of motor, calculate the temperature value of each component of the motor, and verify the correctness of the thermal network model through the method of magnetothermal bidirectional coupling. Finally, an experimental platform is set up to carry out temperature rise experiments on the two prototypes respectively. Experimental results show that the non-uniform air-gap rotor structure can effectively reduce the rotor eddy current loss and motor temperature rise, and also verify the accuracy of the analytical model calculation results.

Soccer is the leading cause of all sports-related ocular injuries in Europe and Israel and leads to blindness at a disproportionately high rate, especially among children (Thompson et al., 2019). With soccer being the most popular sport in the world, it is surprising the only solution to ocular injuries are sports glasses which can cause direct damage to the eye and impair peripheral vision by 15%, calling for an alternative (Smith & Jones, 2020). This work, based on an imported facial model, focuses on both the qualitative and quantitative aspects of building a personalized, low-cost (through optimizing material needed), superior apparatus to conventional sports glasses. The quantitative side examines a modified and model-validated (through a SRS of thirty unique extrapolated points) multivariate linear regression equation, based on horizontal and vertical rotation angles (n=60) trained with residual and computer simulation data, that can accurately extrapolate and quantify ocular impact from all horizontal and vertical rotation angles and a modified Hertzian Contact Stress Equation to determine the thickness of the apparatus using the elasticity modulus, impact force, and geometrical facial and soccer-ball features. The qualitative side examines where firstly, ocular impact is most prevalent, and secondly, where most impact is seen from rotating the ball horizontally and vertically through analysis of Pearson’s Correlation Coefficient at the supraorbital, medial canthus, infraorbital, and lateral canthus regions from both regression equations as well as a cost-benefit analysis for comparison with conventional sports glasses. The findings discovered in this work lay the groundwork for future research to build a customized low-cost ocular injury prevention device which can simultaneously ensure complete ocular safety while enhancing athletic performance for over 250,000,000 players (Johnson & Garcia, 2022).

The continuous flowing spacetime forms a spacetime group G, one of its fundamental groups is the Poincare group PO(1,3), and the matter and interaction fields are representations of its intrinsic spacetime group. As a kind of quantized space-time unit, space-time group elements generate both space-time manifolds and matter. Matter and fields are aggregates of the quantum space-time within them and determine their type: the Lorentz group SO(1,3) represents a rotating spacetime corresponding to visible matter and the translation group P^1,3 represents a translational spacetime corresponding to dark matter and dark energy. The aggregation mode of space-time degrees of freedom in matter reveals that charge conjugation symmetry is the inverse symmetry of internal time of charged particles, and the external parity breaking of neutrinos is also due to their internal spatial aggregation mode.

Extracellular vesicles (EVs) are natural carriers of biomolecules that play a crucial role in cell-to-cell communication and tissue homeostasis under normal and pathological conditions, including inflammatory diseases and cancer. Since the discovery of the pro-regenerative and immune-modulating properties of EVs, EV-based therapeutics have entered clinical trials for conditions such as myocardial infarction and autoimmune diseases, among others. Due to their unique advantages—such as superior bioavailability, substantial packaging capacity, and the ability to traverse biological barriers—EVs are regarded as a promising platform for targeted drug delivery. However, achieving sufficient accumulation of therapeutic agents at the target site necessitates a larger quantity of EVs per dose compared to using EVs as standalone drugs. This challenge can be addressed by administering larger doses of EVs, increasing the drug dosage per administration, or enhancing the selective accumulation of EVs at target cells. In this review, we will discuss methods to improve the isolation and purification of EVs, approaches to enhance cargo packaging—including proteins, RNAs, and small-molecule drugs—and technologies for displaying targeting ligands on the surface of EVs to facilitate improved targeting. Ultimately, this guide can be applied to the development of novel classes of EV-based therapeutics and to overcoming existing technological challenges.

Synopsis Corneal epithelial wavefront error and epithelial thickness variance qualify as highly sensitive and specific biomarkers for epithelial basement membrane dystrophy (EBMD). The biomarkers show a normalization after treatment of EBMD with phototherapeutic keratectomy. Purpose: To gauge the diagnostic value of a novel spectral-domain optical coherence tomography (SD-OCT) based imaging modality for simultaneous morphological (thickness profile) and refractive (optical wavefront) assessment of the corneal epithelial layer in one of the most common but often underdiagnosed corneal dystrophies: epithelial basement membrane dystrophy (EBMD). Methods: In this prospective observational study, a total of 32 eyes of 32 patients diagnosed with EBMD and 32 eyes of 32 healthy control subjects were examined with high-resolution anterior segment SD-OCT (MS-39; CSO, Florence, Italy). Various epithelial thickness and epithelial wavefront derived terms were compared between groups and receiver operating characteristic (ROC) curves were computed to analyze the diagnostic capacity of the respective parameters. A total of 17 of 32 EBMD patients underwent treatment with phototherapeutic keratectomy (PTK) and were followed up for 3 months. Results: Epithelial thickness variance (60.4 ± 56.7 µm versus 7.6 ± 6.1 µm) and interquartile range (11.0±6.9 versus 3.3±1.9 µm) were markedly elevated in EBMD patients as compared with healthy controls (both with p < 0.001). Epithelial wavefront analysis showed a highly statistically significant excess in all examined aberration terms in EBMD patients (all with p < 0.001). Significantly greater areas under the curve (AUC) were yielded by the epithelial wavefront derived parameters (e.g. total epithelial wavefront error: AUC = 0.966; 95% confidence interval (CI) 0.932 – 1) than by the epithelial thickness-derived parameters (e.g., variance: AUC = 0.919; 95% CI 0.848 – 0.990). Conclusion: Corneal epithelial wavefront aberrometry proved valuable as an objective biomarker for EBMD with high sensitivity and specificity. PTK resulted in a reduction of morphological and refractive epithelial irregularities in EBMD.

Bistatic radar experiments have been used to study surface characteristics of extra-terrestrial bodies in the Solar System, including the Moon, Venus, Mars, and Titan. This paper proposes a 3D model to characterize the scattered field of a Gaussian rough surface on an extra-terrestrial body for an orbital bistatic radar configuration. Specifically, this model will investigate how the variability of surface roughness impacts the spectral broadening of the received signal using physical optics approximations and ray tracing on a surface model using a facet approach with Gaussian properties. A linear relationship between spectral broadening of the signal and surface roughness was found. This relationship is in line with results obtained by commonly used analytical models for bistatic radar on planetary surfaces.

For marine vessels, a propeller shaft system, also known as a propulsion shaft system, is an essential changer in engine torque and propeller thrust. The propeller shaft system is subjected to transverse, longitudinal, and torsional excitations during operation. These sources of excitations originate from alternating thrust generated by the propeller, operation of a propeller in a stern flow field which is non-uniform in time and space, misalignment of components such as shafts, bearings, and keyholes in the assembly, excitations in the form of rotational motion, and the whirling motion of the shafts. These dynamic excitations posed a challenging issue for the integrity and reliability of a marine vehicle. Thus, it is crucial to analyze the dynamic response of the propulsion shaft system. The dynamic analysis of the propulsion shaft system is typically conducted using numerical /analytical models. At present, Finite Element Model (FEM) as a numerical model plays a vital role in analyzing the dynamic response of the structure. The computed response and the modal parameters from the FE model are reliable only if accurate boundary conditions, such as stiffness, can be imposed on the model. However, the numerical FE model deviates from the experimental results because of uncertainties in the stiffness values of the bearings and other connectors. This paper uses the Response Surface Optimization (RSO) technique to estimate the unknown stiffness of the bearings used in the propulsion shaft system. The experimental model of the propeller shaft system is constructed from the steady-state response of the system using the step sine excitation. The natural frequencies and the amplitude of vibrations in the FE model are updated using the parametric RSO technique. The updated model shows that the difference in natural frequencies and vibration amplitude is less than 10% between the optimized and experimental models. Propeller Shaft, Vibrations, Optimization, Response Surface

In this study, Fe-Mo-B based hardfacing electrodes containing different amounts of Mo were coated on an AISI 1020 steel substrate using the electric arc welding method. The findings show that molybdenum is highly effective on the microstructure and minor changes in the coating composition affect the phases and morphological properties. In the hardness tests, an increase of 73% was achieved in the Fe14Mo2B4 based hardfacing coating compared to the base material and a 30% increase compared to the Fe16B4 based coating. The highest macro hardness value was measured as 56.4 HRC and the highest phase hardness was measured as 3228 HV in the FeMo2B2 phase. The lowest wear rate was measured in the Fe14Mo2B2 based coating. The wear rate of the Fe14Mo2B4 based coating was 8.1 times lower than that of the substrate material and 4.7 times lower than that of the Fe16B4 based coating. According to corrosion test results, the highest corrosion resistance was obtained in Fe16B4 based coating. The current density value of the Fe16B4 based coating was measured to be 13.6 times lower than that of the substrate material.

Unmanned aerial vehicles (UAV) thermal imagery offers several advantages in environmental monitoring, as it can provide a low-cost, high-resolution, and flexible solution to measure the temperature of the surface of the land. Limitations related to the maximum load of the drone lead to use of lightweight uncooled thermal cameras whose internal components are not stabilized to a constant temperature. Such cameras suffer from several unwanted effects that contribute to the increase in temperature measurement error from ±0.5 °C in laboratory conditions, to ±5 °C in unstable flight conditions. This article describes a post processing procedure, that reduces the above unwanted effects. It consists of following steps: i) devignetting using single image vignette correction algorithm, ii) georeferencing of images using EXIF data, scale-invariant feature transform (SIFT) stitching, and gradient descent optimisation, and iii) temperature calibration by minimisation of bias between overlapping thermal images using gradient descent optimisation. The solution was tested in several case studies of river areas, where natural water bodies were used as a reference temperature benchmark. In all tests, the precision of the measurements was increased. The root of the mean of the Square of Errors RMSE on average was reduced by 39.0% and Mean of the absolute value of Errors MAE by 40.5%. The proposed algorithm can be called self-calibrating, as in contrast to other known solutions is fully automatic, uses only field data and does not require any calibration equipment or additional operator effort. A Python implementation of the solution is available on GitHub.

Coalescence of nanowires and other three-dimensional structures into continuous film is desirable for growing low dislocation density III-nitride and III-V materials on lattice-mismatched substrates, and interesting from the fundamental viewpoint. Here, we develop a growth model for vertical nanowires which, under rather general assumptions on the solid-like coalescence process within the Kolmogorov crystallization theory, results in a morphological diagram for the asymptotic coverage of a substrate surface. The coverage is presented as a function of two variables, the material collection efficiency on the top nanowire facet a, and the normalized surface diffusion flux of adatoms from the NW sidewalls b. The full coalescence of nanowires is possible only when a=1 regardless of b. At a&gt;1, which is usual for vapor-liquid-solid growth with a catalyst droplet, nanowires can only partly merge but never coalesce into continuous film. These results can be used for predicting and controlling the degree of surface coverage by nanowires and three-dimensional islands by tuning the surface density, droplet size, adatoms diffusivity, and geometry of the initial structures in the vapor-liquid-solid, selective area or self-induced growth processes in different epitaxy techniques.

At the nanoscale, metals exhibit special electrochemical and optical properties, which play an important role in nanobiosensing. In particular, the surface plasmon resonance based on precious metal nanoparticles, as a kind of tag free biosensor technology, has brought high sensitivity, high reliability and convenient operation to the sensor detection. By applying an electrochemical excitation signal on the nano plasma device, modulating its surface electron density and realizing electrochemical coupling surface plasmon resonance, it can effectively complete the joint transmission of electrical signals and optical signals, increase the resonance shift of the spectrum, and further improve the sensitivity of the designed biosensor. In addition, smartphone is playing an increasingly important role in portable mobile sensor detection systems. These systems typically connect sensing devices to smartphone to perceive different types of information, from optical signals to electrochemical signals, providing ideas for the portability and low-cost design of these sensing systems. Among them, electrochemiluminescence, as a special electrochemical coupled optical technology, has good application prospects in mobile sensing detection due to its strong anti-interference ability, which is not affected by background light. In this review, the surface plasmon resonance is introduced from nanoparticles, and its response process is analyzed theoretically. Then, the mechanism and sensing application of electrochemistry coupled surface plasmon resonance and electrochemiluminescence are emphatically introduced. Finally, it extends to the related research of electrochemical coupled optical sensing on mobile detection platforms.

The surface fluorination of polypropylene (PP) was performed using F2 and O2 gas mixtures with different F2 gas proportions at 25 °C and 13.3 kPa for 1 h. The surface roughness of the fluorinated PP samples was approximately 1.5 times higher than that of the untreated sample (5 nm). The Fourier-transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) results showed that the PP-derived bonds (-C-C- and -CHx) decreased because they were converted into polar groups (-C–O, -CHF-, and -CFx), which increased the surface electronegativity of PP. The variation in the F2 gas proportion in the gas mixture significantly affected the hydrophilicity and surface composition of PP. At F2 gas proportions of <70%, the hydrophilicity of the fluorinated PP samples improved. Notably, the hydrophilic and negatively charged PP surface enhanced the dyeing of the polymer with basic methylene blue (MB). In contrast, at F2 gas proportions of >90%, the PP surface became hydrophobic owing to increased hydrophobic -CF3 bonds. Thus, enhanced PP dyeing can be controlled based on the composition of the F2 and O2 gas mixture.

A highly efficient reduction process of Cr (VI) with biochar was conducted in this paper. The results showed that nearly 100% Cr (VI) was reduced at selected reaction conditions: the dosage of biochar at m (C)/m(Cr) = 3.0, reaction temperature of 90 ℃, reaction time at 60 min and concentration of H2SO4 of 20 g/L, respectively. The reduction kinetics analysis demonstrated that the reduction of Cr (VI) fitted well with the pseudo-first-order model and the apparent activation energy was calculated to 40.24 kJ/mol. Response surface methodology confirmed that all the experimental parameters had positive effect on the reduction of Cr (VI). The influence of each parameter on the reduction process followed the order: dosage of biochar> Concentration of H2SO4 > Reaction Temperature > Reaction Time. This paper provided a versatile strategy for treatment of wastewater containing Cr (VI) and showed a bright tomorrow for wastewater treatment.

Surface Plasmon Resonance (SPR) is an attracting property of certain transition metals when they are synthesized in nano-range giving rise to promising optical applications. However, most SPR and associated applications are limited to the noble metal nanoparticles, which limits their potential due to high production cost. We report surface plasmon resonance in copper-copper oxide core-shell quantum dots synthesized via chemical route studied by using UV-Visible spectrophotometry. Tuning of the plasmonic resonance with respect to the particle diameter is achieved by an inexpensive all chemical route. Photoluminescence measurements also support the data. This size reduction leads to remarkable changes in its optical response as compared to the bulk metal. The results point towards applications of these materials in tunable SPR based biosensors.

Sea ice surface roughness affects ice-atmosphere interactions, serves as an indicator of ice age, shows patterns of ice convergence and divergence, affects the spatial extent of summer melt ponds, and ice albedo. We have developed a method for mapping sea ice surface roughness using angular reflectance data from the Multi-angle Imaging SpectroRadiometer (MISR) and lidar-derived roughness measurements from the Airborne Topographic Mapper (ATM). Using an empirical data modeling approach, we derived estimates of Arctic sea ice roughness ranging from centimeters to decimeters meters within the MISR 275-m pixel size. Using independent ATM data for validation, we find that histograms of lidar and multi-angular roughness values are nearly identical for areas with roughness <20 cm but that for rougher regions, the MISR-derived roughness has a narrower range of values than the ATM data. The algorithm is able to accurately identify areas that transition between smooth and rough ice. Because of its coarser spatial scale, MISR-derived roughness data have a variance of about half that ATM roughness data.

Wetting of deformable substrates has gained significant interest over the past decade due to its extensive applications and uses. This interest has developed due to technological advances which are able to capture interfacial behavior taking place when a liquid droplet is placed on a deformable substrate. Researchers have developed different theories to explain processes taking place in the process of wetting of deformable/soft substrates. For the scope of this review, we will consider the fluid to be Newtonian, partially wetting, and surface forces are incorporated with the help of disjoining/conjoining pressure acting in the vicinity of the apparent, three-phase contact line. The following subjects are briefly reviewed: (i) Equilibrium of droplets on soft substrates. It is shown that properties of the disjoining/conjoining pressure isotherm and properties of the deformable substrate determine both the shape of the liquid droplet and deformation of the substrate; (ii) Equilibrium conditions of droplets on deformable substrates. It is shown that for a droplet to be at equilibrium on a deformable substrate under consideration, Jacobi’s sufficient condition is satisfied; (iii) Hysteresis of contact angle of sessile droplets on deformable substrates. It is shown that as the elasticity of the deformable substrate is increased, both advancing and receding contact angles are reduced.

The influence of the film thickness and the substrate’s refractive index on the surface mode at the superstrate is an important study step that may help clearing some of the misunderstandings surrounding their propagation mechanism. A single sub-wavelength slit perforating a thin metallic film is among the simplest nanostructure capable of launching Surface Plasmon Polaritons on its surrounding surface when excited by an incident field. Here, the impact of the substrate and the film thickness on surface waves is investigated. When the thickness of the film is comparable to its skin depth, SPP waves from the substrate penetrate the film and emerge from the superstrate, creating a superposition of two SPP waves, that leads to a beat interference envelope with well-defined loci which are the function of both the drive frequency and the dielectric constant of the substrate/superstrate. As the film thickness is reduced to the SPP’s penetration depth, surface waves from optically denser dielectric/metal interface would dominate, leading to volume plasmons that propagate inside the film at optical frequencies. Interference of periodic volume charge density with the incident field over the film creates charge bundles that are periodic in space and time.

The aim of the present study was to monitor implant stability after sinus floor elevation with two biomaterials during the first 6 months of healing by a resonance frequency analysis (RFA), and how physico-chemical properties affect the implant stability quotient (ISQ) at the placement and healing sites. Bilateral maxillary sinus augmentation was performed in 10 patients in a split-mouth design using a bobine HA (BBM) as a control and porcine HA (PBM). Six months after sinus lifting, 60 implants were placed in the posterior maxilla. The ISQ was recorded on the day of surgery from RFA at T1 (baseline), T2 (3 months), and T3 (6 months). Statistically significant differences were found in the ISQ values during the evaluation period. The ISQ (baseline) was 63.8±2.97 for BBM and 62.6±2.11 for PBM. The ISQ (T2) was ~ 73.5±4.21 and 67±4.99, respectively. The ISQ (T3) was ~ 74.65±2.93 and 72.9±2.63, respectively. All the used HAs provide osseointegration and statistical increases in the ISQ at baseline, T2 and T3 (follow-up), respectively. The BBM, sintered at high temperature with high crystallinity and low porosity, presented higher stability, which demonstrates that variations in the physico-chemical properties of a bone substitute material clearly influence implant stability.

Analyzing the impacts of urban landscape patterns on the thermal environment has become one of the key research areas in addressing urban heat islands (UHI) and improving the living environment. A case study was carried out in Fuzhou, Fujian Province of China, to quantify the spatial patterns of urban landscape and land surface temperature (LST) in different development areas. The contribution of the thermal environment and the factors influencing the heterogeneity of LST were analyzed and discussed. In this study, bi-temporal Landsat imagery was selected to calculate LST, percent impervious surface area (ISA), and fractional vegetation cover (FVC). The urban area was further divided into three concentric urban zones, ranging from the city center to the urban periphery, based on urban development densities. The spatial pattern of LST and its variance were analyzed and compared between different zones and different dates. The thermal environment contribution of different zones was also quantified to indicate the change in urban landscape pattern resulting from urban expansion in different zones. Furthermore, Geodetector was used to explore the single factors and interaction factors controlling the spatial patterns of LST in each zone. The results showed that (ⅰ) Urban expansion primarily increased in zone 2 and zone 3, and the areal proportion of high and sub-high LST areas increased from 56.11% and 21.08% to 62.03% and 32.49% in zone 2 and zone 3, respectively, from 2004 to 2021; (ⅱ) The heat effect contribution of zones 2 and 3 reached from 75.16% in 2004 to 89.40% in 2021, indicating that the increase of ISA with >LSTmean was more pronounced in zone 3 and zone 2 during the period; (ⅲ) The driving factors of LST spatial distribution were regionally different because of the different landscape patterns, and the explanatory power for the heterogeneity of LST in zone 1 was weaker than that in zone 2 and zone 3 in the study area; (ⅳ) The interaction of different factors had a higher explanatory power on the spatial distribution of LST than a single factor in each zone because the distributions of land cover types are heterogeneous in urban area. The results of the study can be used to improve urban planning for urban ecology and UHI mitigation.

Zinc-oxide (ZnO) nanostructures including nanorods are currently considered as a pioneer research of interest world-wide due to their excellent application potentials in various applied fields especially for the improvement of energy harvesting photovoltaic solar cells (PSC). We report on the growth and morphological properties of zinc-oxide (ZnO) nanorods grown on the surface of plain zinc (non-etched and chemically etched) plates by using a simple, economical, and environment-friendly technique. We apply hot water treatment (HWT) technique to grow the ZnO nanorods and varies the process parameters, such as temperature and the process time duration. The morphological, and elemental analysis confirm the agglomeration of multiple ZnO nanorods with its proper stoichiometry. The obtained nanostructures for different temperatures with different time duration showed the variation in uniformity, density, thickness and nanonorods size. The ZnO nanorods produced on the etched zinc surface were found thicker and uniform as compared to those grown on the non-etched zinc surface. This chemically etched Zinc plates preparation can be an easy solution to grow ZnO nanorods with high density and uniformity suitable for PSC applications such as to enhance the energy conversion efficiency of the photovoltaic (PV) solar cells towards the future sustainable green earth.

Giant plasmonic surface enhancement has been observed in gold coated micron sized inverse pyramids entrapping a gold nanoparticle. The amplification of both surface enhanced Raman and photoluminescence signals was found to be dependent on the diameter of trapped gold nanoparticle and around 50-fold enhancement was detected for 250nm diameter sample relatively to the 50nm one. Finite differential time domain simulations, performed to determine the near-field distribution in the structure, showed that when the nanoparticle protrudes into the hotspot zone of the void, coupling of electromagnetic field occurs and the plasmon-related near-field enhancement is concentrated into the close vicinity of the nanoparticle, mainly into the close gaps around the tangential points of the curved sphere and the flat pyramid surface. This results in a more than 15 times increase of the near-field intensity, compared to the empty void.

Managing sidelobe levels (SLLs) in metasurface-driven beam-steering antennas poses a significant challenge due to intrinsic factors leading to grating lobes. Our proposed method employs an equivalent model to optimize large periodic metasurfaces efficiently. This model predicts complete metasurface performance, accounting for mutual coupling between patches. We introduce an evolutionary optimization algorithm based on the Cross Entropy (CE) method to enhance PGM-based beam-steering antennas and suppress sidelobes. Two strategies were employed: first is to optimize the patch dimensions for a sidelobe-free pattern and the second is to maintain the PGM dimensions while optimizing feed array amplitudes. Both strategies effectively suppressed sidelobes, offering insights into the CE method's applicability and effectiveness for CPU-intensive electromagnetic optimization challenges. The proposed CE method variant retains its simplicity while improving monitoring capabilities, addressing this limitation. Smaller generations yield better improvements per evaluation

Throughout this paper the effects of injuries on athletes are highlighted in different aspects. Exertional compartment syndrome is a specific injury related to athletes that is thoroughly explored in this paper through an analysis of the anatomy, symptoms, diagnosis and treatments of the syndrome. Exertional compartment syndrome is an exercise-induced muscle and nerve condition that causes pain, swelling as well as disability in the affected muscles of the lower leg. This syndrome commonly develops in young athletes involved in sports with excessive running and repetitive impact such as track and field, soccer, basketball and lacrosse. Exertional compartment syndrome is commonly misdiagnosed as other less severe injuries such as shin splints, which is symptomatic of pain along the tibia bone of the lower leg caused by overuse. The misdiagnosis of exertional compartment syndrome allows the syndrome to worsen and intensify resulting in the only effective treatment to be fasciotomy, a surgical procedure to release the pressure within the compartment of the lower leg. There is no definitive protocol developed for patients after fasciotomy is performed. Athletes experiencing similar symptoms after surgery are usually treated for their symptoms rather than the syndrome as a whole, which does not have a high degree of success. The development of a definitive protocol utilizing the techniques of manual therapy, mobility stretching and corrective strength training can improve the adverse effects of exertional compartment syndrome as well as restore functionality to the athlete. Raising awareness of this syndrome in athletics will be effective in treating the athlete early on in order to avoid severe effects and invasive procedures.

The ocean of the planet Earth, which is as thin as a cicada's wings, play a role of catalyst to the evolving of the ancient plates. The ocean and the ancient plates of the planet Earth formed a magic Whirlpool of the Cross “十” shape with double whirl arms. The central core of the Cross “十” shape Ocean-Plate Whirlpool is the Hint Black Hole (HBH) located at the Northwestern Pacific Ocean floor which is decorated with invisible geological age distribution of clam shell. The double whirl arms of ancient plates are distinguished to be left and right at Bering Strait and just formed the ring of fire of the Pacific Ocean.The Cross “十” shape Ocean-Plate Whirlpool of the planet Earth was born at the equatorial area about 66 Ma ago and is rotating anticlockwise and drifting northward by a mini footprint of spiral at s speed of as slow as a snail moves. Obviously, it would come to an end at the North Pole about 100 Ma in the future. So, the lifespan of the Cross “十” shape Ocean-Plate Whirlpool would be about 166 Ma, from birth to death on the planet Earth.What is hidden behind of the evolving of the oceans and the ancient plates is the golden law of geometrical progression of ladder pagoda of attributes evolving of them, which is “1➨2➨4➨2➨1”, including upgrading and downgrading process. It seems to hint that what is happening on the planet Earth, including the top-level species of human race, is actually unique in the Milky Way galaxy in essence.The property roles of expanding and shrinking are existing in the Cross “十” shape Ocean-Plate Whirlpool by face to face and the exchange of property roles took place tens of millions of years ago. And that situation would happen again tens of millions of years in the future. It seems a giant circle of evolving of the exchange of property roles would be drawn by the Cross “十” shape Ocean-Plate Whirlpool in her lifetime.

In this paper, we present an experimental procedure to enhance the dimensional accuracy of fabrication via Stereolithography (SLA) of features at the micro-scale. Using a custom benchmark part, deviations in feature dimensions (micro-pores diameters and depths) were detected and measured by confocal microscopy. Samples characterization and experimental observations allowed the identification of inaccuracy sources, mainly due to the laser beam scanning strategy and to the incomplete removal of uncured liquid resin in post-processing (i.e., IPA washing). As a technology baseline, the measured dimensional errors on pores diameters were up to -46%. A compensation method of the nominal laser spot diameter (85m) was defined and implemented resulting in relevant improvements in dimensional accuracy of 9.8% and 11.3% on full-open pores diameter and depth, respectively. Further investigation was performed on a customized test part to adjust the calibration procedure. The measurements revealed that the estimate of the laser beam spot size is 968m. Measurements on micro-pores having different sizes revealed that a constant compensation parameter (i.e., C=85, 96, 120m) is not fully effective at the micro-scale, where average errors still remain at -24%, -18.8%, and -16% for compensations equals to 85, 96 and 120m, respectively. A further experimental campaign allowed the identification of an effective nonlinear compensation law where the compensation parameter depends on the micro-feature size C= f (D). Results show a sharp improvement in dimensional accuracy on micro-pore fabrication, with errors consistently below +8.2%. The proposed compensation method can be extended for the fabrication of any micro-features without restrictions on the specific technology implementation. Concerning the inaccuracy introduced by the laser path, experimentation with a customized part allowed the optimization of the part orientation to reduce the errors and their differences along the X and Y machine axes.

Numerous structures at the nano- and microscale manifest distinctive properties with far-reaching implications across diverse fields, including electronics, electricity, medicine, and surface engi-neering. Established methods such as nanoimprint lithography, photolithography, and self-assembly play crucial roles in the fabrication of nano- and microstructures; however, they exhibit limitations in generating high-aspect-ratio structures when utilizing high-viscosity pho-tocurable resins. In response to this inherent challenge, we propose a highly cost-effective ap-proach facilitating the direct replication of high-aspect-ratio structures, specifically nanowires, through the utilization of anodized aluminum substrates. This study elucidates the streamlined fabrication process for multiscale porous surfaces achieved through the evaporation-induced in-tegration of solid nanowires printed with high-viscosity photocurable resin.

A finite-type immersion or smooth map is a nice tool to classify submanifolds of Euclidean space, which comes from eigenvalue problem of immersion. The notion of generalized 1-type is a natural generalization of those of 1-type in the usual sense and pointwise 1-type. We classify ruled surfaces with generalized 1-type Gauss map as part of a plane, a circular cylinder, a cylinder over a base curve of an infinite type, a helicoid, a right cone and a conical surface of $G$-type.

In recent times, the adoption of cloud computing by small and medium-sized 9 enterprises (SMEs) has become a crucial issue. These businesses face substantial difficulties in 10 accessing reliable and affordable IT infrastructure due to economic constraints and technological 11 restrictions. Hybrid cloud computing solutions which incorporate Infrastructure as a Service 12 (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) offer a feasible approach to 13overcoming these challenges. This study proposes a systematic literature review of cloud 14 computing's impact on SME performance emphasizing cost-efficiency, reliability, and 15 competitive advantages, using the 2020 Preferred Reporting Items for Systematic Reviews and 16 Meta-Analyses (PRISMA) framework. The inclusion criteria are bounded by (1) publication date 17 between 2014 and 2024, (2) English-language publications, (3) research focused on cloud 18 computing for SMEs, and (4) studies with a clear analytical framework for evaluating SME 19 performance. Following this process, 90 eligible research studies were included. The average 20 total cost for cloud services varies significantly, with operational costs reflecting the scalability 21 of the services and the specific needs of SMEs. This analysis offers valuable guidance for SMEs 22 and stakeholders in optimizing cloud-based strategies for enhanced performance.

Recent developments in microfluidics and biomaterials have enabled the creation of organs-on-chips (OoCs), which provide a controlled and lifelike in vitro microenvironment resembling an actual organ. Organ-on-a-chip technology offers a tremendous opportunity for efficient, cost-effective, and ethical drug testing and research. However, the high throughput and large quantities of data these complex microenvironments produce make it difficult for researchers to effectively analyze the data and draw valuable conclusions. Convolutional Neural Networks (CNNs) are most aptly positioned to address many of OoC’s challenges because of their ability to interpret microscopic images and facilitate the analytical process. Despite the growing field of AI, there have been a limited number of studies summarizing the various applications of CNNs in OoCs. This review aims to provide 1) an overview of the technology involved with CNNs and OoCs 2) an insight into the state-of-the-art applications of CNNs in OoCs including device parameters, predicting and tracking cell trajectories, super-resolution image segmentation, and image classification, and 3) an overview of existing challenges and opportunities ahead for clinical translation of this technology. Various applications of CNNs have been classified by the type of task. Different CNN models such as Faster R-CNNs, fully convolutional networks (FCNs), and Mask R-CNNs are explained and highlighted. This review article can be used as a resource for a better understanding of the potential of CNNs in biomedical research and clinical applications, particularly OoCs.

Due to Motor Neurone Diseases, a large population remains disabled worldwide, negatively impacting their independence and quality of life. This typically involves a weakness in the hand and forearm muscles, making it difficult to perform fine motor tasks such as writing, buttoning a shirt, or gripping objects. This project presents a vision-enabled rehabilitation hand exoskeleton to assist disabled persons in their hand movements. The design goal was to create an accessible tool to help with a simple interface requiring no training. This prototype is built on a commercially available glove where a camera and embedded processor were integrated to help open and close the hand, using air pressure, thus grabbing an object. An accelerometer is also implemented to detect the characteristic hand gesture to release the object when desired. This passive vision-based control differs from active EMG-based designs as it does not require individualized training. Continuing the research will reduce the cost, weight, and power consumption to facilitate mass implementation.

The existence of semantic inaccuracy §2 articles by A. Einstein “On the electrodynamics of moving bodies”, illustrating the principle of the relativity of simultaneity. In a sentence “The observers co-moving with the moving rod would thus find that the two clocks do not run synchronously while the observers in the system at rest would declare them synchronous”, the preposition “not” must be moved and placed before the word “synchronous”, at the end of the sentence. The criterion for synchronism of the clocks on the rod is the time it takes for the beam to travel from clock A to clock B and back, and for observers on the rod it will be the same both when the rod is at rest and when the rod is moving. Otherwise, observers on the rod would have had at their disposal an experiment that would allow them to determine whether the rod is moving or at rest, which contradicts the first postulate of the Special Theory of Relativity. The inaccuracy is found unchanged in modern editions in English and Russian, and can become a source of difficulties when teaching the basics of the Special Theory of Relativity based on primary sources, as well as make it difficult to understand the author’s logic when studying independently. Nobel laureate R. Feynman, having expanded and modified A. Einstein's thought experiment, eliminated the inaccuracy described in the article.

The automotive industry has witnessed a significant push towards increased fuel efficiency and reduced carbon emissions. Among many factors influencing overall vehicle efficiency, aerodynamic drag is a critical consideration, accounting for a substantial portion of fuel consumption. Our investigation focused on the drag coefficients of three prominent 2023 passenger car models – the Toyota Corolla, Hyundai Elantra, and Kia Soul. Using ANSYS Fluent to perform computational fluid dynamics, we demonstrated an inverse correlation between drag force and gas mileage, underlining the significance of aerodynamic design in fuel efficiency. Notably, the Hyundai Elantra emerged as the most aerodynamically efficient of the three vehicles, followed closely by the Toyota Corolla. In contrast, the boxier-designed Kia Soul exhibited significantly higher drag coefficients and drag forces, rendering it the least efficient of the trio. These findings emphasize the importance of environmental factors in car design. Shaping aerodynamic profiles directly impacts fuel efficiency, stability, and overall performance.

The corrosion behavior of the TiTaNbZrAg alloys with different amounts of Tantalum (0 %, 10 % and 20%) and with distinct surface topography (smooth and rough) was investigated in phosphate buffer solution (PBS) for long-time immersion (1000 hours). The corrosion resistance was studied by Open circuit potential (OCP), potentiodynamic polarization (PP) and electrochemical impedance spectroscopy (EIS). From the potentiodynamic investigations, it was observed that all types of samples show good corrosion resistance (i.e. Rcorr < 10µm y-1) and may be used successfully for medical applications. However, the samples with smooth surface and with a certain amount of Ta (10 % and 20%) exhibit the best corrosion performance (Rcorr < 1µm y-1). As regard the samples with rough surface, the results evidenced that they show lower corrosion resistance (1< Rcorr < 3 µm y-1), suggesting that the Ta presence not necessary brings about a very good corrosion protection. Actually, the synergetic effect of both the presence of Ta and surface roughness plays an important role in corrosion behavior. Based on literature reports, we assume that the good corrosion resistance results from the good stability of the film, formed mainly from Ta2O5 and TiO2, formed on the alloy surface during immersion in PBS.

This study describes the development of an optical-based surface plasmon resonance (SPR) aptasensor for the detection of cocaine. The aptasensor was prepared by first attaching gold nanoparticles to a clean SPR chip surface, followed by the addition of an aptamer to create a modified surface. This surface was characterized using Contact Angle and Atomic Force Microscopy, revealing surface roughness values of 0.28 nm and 28.12 nm for the blank and modified surfaces, respectively. The detection of cocaine was carried out in the concentration range of 1 ng/mL to 1000 ng/mL, with a detection time of approximately 8 minutes and a cocaine limit of detection (LOD) of 0.43 ng/mL. Repeatability studies were conducted, and the stability of the signal response was examined at a concentration of 200 ng/mL. Adsorption isotherm models, including Scatchard, Langmuir, and Freundlich, were calculated to assess the surface homogeneity of the SPR aptasensor chip, with the results indicating compatibility with the Langmuir isotherm model.

All-inorganic perovskite materials are promising in optoelectronics but their morphology is a key parameter for achieving high device efficiency. We prepared CsPbBr3 perovskite microcrystals with different shape, grown directly on planar substrate by conventional drop casting. We observed the formation of CsPbBr3 microcubes on bare indium tin oxide (ITO) coated glass. Interestingly, with the same technique CsPbBr3 microrods were obtained on (3-Aminopropyl) triethoxysilane (APTES) modified ITO-glass, which we ascribe to modification of formation kinetics. The obtained micro-crystals exhibit orthorhombic structure. Green photoluminescence (PL) emission is revealed from the CsPbBr3 microrods. Contact angle measurements, Fourier-transform infrared and PL spectroscopies confirmed that APTES linked successfully to the ITO-glass substrate. We propose a qualitative mechanism to explain the anisotropic growth. The microrods exhibited improved PL and slower PL lifetime compared to the microcubes, likely due to diminished occurrence of defects. This work demonstrates the importance of the substrate surface to control the growth of perovskite single crystals and to boost the radiative recombination in view of high performance optoelectronic devices.

A series of nanospherical shaped silicates containing heteroatoms (Al, Zr or Ti) were successfully synthesized using TEOS or silica colloids as silicon source. These metallosilicate nanospheres were used as silicon nutrients to obtain silicalite zeolites having micro-mesoporosity with improved textural properties. The results demonstrated that TEOS acted as a suitable silicon source to produce amorphous silicates and a spherical-type hierarchical zeolite architecture with Zr and Ti heteroatoms included in their framework, with preferable particle size and crystallinity. The surface functionality of the mesostructured nanospheres and zeolite silicates provide active centers for the esterification of glycerol with acetic acid (EG) reaction. Besides, the dispersion of Cu or Fe entities on the surface of the nanospherical silicates and zeolites provided good catalytic performances in the esterification of glycerol to valuable acetins.

Strip steel surface defect recognition research has important research significance in industrial production. Aiming at the problems of defect feature extraction difficulty, slow detection speed and insufficient dataset, YOLOv5 is improved on the basis of YOLOv5, and YOLO-LFPD (Lightweight fine particle detection) model is proposed. By introducing the RepVGG (Re-param VGG) module, the robustness of the model to the surface defect features of strip steel is enhanced, and the expressive ability of the model is improved. FasterNet is used to replace the backbone network, which ensures the accuracy and accelerates the inference speed, making the model more suitable for real-time monitoring. The use of pruning, GA genetic algorithm with OTA loss function method further reduces the model size while better learning the strip steel defect feature information, thus improving the generalisation ability and accuracy of the model. The experimental results show that the introduction of the RepVGG module and the use of FasterNet can well improve the model performance, with a reduction of 48% in the number of parameters, a reduction of 13% in the number of GFLOPs, an inference time of 77% of the original, and an optimal accuracy compared with the network models in recent years. The experimental results on the NEU-DET dataset show that the accuracy of YOLO-LFPD is improved by 3% to 81.2%, which is better than other models, and provides new ideas and references for the lightweight strip steel surface defect detection scenarios and application deployment.

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.