Recently, we studied CR-slant warped products B1×fM⊥, where B1=MT×Mθ is the Riemannian product of holomorphic and proper slant submanifolds and M⊥ is a totally real submanifold in a nearly Kaehler manifold. In the continuation, in this paper, we study B2×fMθ, where B2=MT×M⊥ is a CR-product of a nearly Kaehler manifold and establish Chen’s inequality for the squared norm of the second fundamental form. Some special cases of Chen’s inequality are given.

In this paper, we introduce the notion of pointwise hemi-slant submanifolds of nearly Kaehler manifolds. Further, we study their warped products and prove the necessary and sufficient condition that a pointwise hemi-slant submanifold to be a warped product manifold. Also, we prove that every pointwise hemi-slant warped product submanifold $M=M_\perp\times_fM_\theta$ which is mixed totally geodesic in an arbitrary nearly Kaehler manifold $\tilde M$ satisfies $\|h\|^2\geq\frac{2p}{9}\cos^2\theta\|\nabla(\ln f)\|^2,$ where $\|h\|$ is the length of the second fundamental form of $M$ and $2p=\dim M_\theta$; while $\nabla(\ln f)$ is the gradient of $\ln f$ along $M_\perp$. The equality case of this inequality is also given.

Litsea martabanica root's antioxidant and AChE activity showed promise as a pesticide detoxification agent in our previous study. In addition to roots, its leaves can help mitigate pesticide exposure, although there is limited scientific evidence supporting their efficacy. However, the use of roots in many countries, such as Thailand, could contribute to environmental degradation, as highland communities traditionally cut down whole trees to obtain them. This study aims to evaluate the antioxidant activity and anti-pesticide potential of water extracts from L. martabanica leaves instead of its roots through in vitro and in vivo investigations. The findings showed that L. martabanica water extracts and fractions demonstrated varied antioxidant activity. The water extract, obtained using traditional extraction methods, was chosen for in vivo experiments. Rats received the extract followed by chlorpyrifos exposure for 16 days. Results indicated reduced acetylcholinesterase activity in chlorpyrifos-exposed rats, while treatment with leaf extract led to increased activity, suggesting its potential as a detoxifying agent. Histopathological examination revealed no liver cell necrosis and showed liver cell regeneration, indicating potential protection against free radical-induced liver damage without affecting rat liver weight or biochemical profiles. Utilizing L. martabanica leaves for healthcare purposes holds promise without negative environmental impact.

Addressing the pressing challenge of global warming, reducing greenhouse gas emissions in the transportation sector is a critical imperative. Battery and fuel-cell electric vehicles have emerged as promising solutions for curbing emissions in this sector. In this study, we conducted a comprehensive life cycle assessment (LCA) for typical passenger vehicles, heavy duty trucks and city buses using either proton-exchange membrane fuel cells or Li-ion batteries with different cell chemistries. To ensure accuracy, we supplemented existing studies with data from the literature, particularly for the recycling phase, as database limitations were encountered. Our results highlight that fuel cell and battery systems exhibit large emissions in the production phase. Recycling can significantly offset some of these emissions, but a comparison of the technologies examined revealed considerable differences. Overall, battery electric vehicles consistently outperform fuel cell electric vehicles regarding absolute greenhouse gas emissions. Hence, we recommend prioritizing battery electric over fuel cell vehicles. However, deploying fuel cell electric vehicles could become attractive in a hydrogen economy scenario where other factors, e. g. the conversion and storage of surplus renewable electricity via electrolysis, become important.

The last decade has seen a significant growth in low-cost air quality monitoring systems (LCAQMS) adoption, mostly driven by the spatial density limitations of traditional regulatory grade networks which restrict their effectiveness in several settings. The EU's regulatory framework advise for deploying one air quality monitoring unit per roughly 170,000 people or 15 square kilometers which is insufficient for capturing high spatio-temporal variance in complex urban scenarios. Often these settings are characterized by distributed emissions in small roads subjected to intense cars traffic, house heating driven emissions and frequently subjected to canyon effects. The Air Heritage project in Portici, funded by the EU's Urban Innovative Actions (UIA) program, addressed these challenges by integrating low-cost sensors with traditional monitoring systems and engaging the community in pervasive measurement strategies. The project highlights the importance of individualized sensor calibration and frequent recalibrations to maintain accuracy. It also showcases the benefits of citizen science approaches, IoT infrastructures, AI components, and geostatistical sensor fusion algorithms for mobile and opportunistic air quality measurements. This paper reports on the lessons learned and experiences from the Air Heritage project, aiming to guide future implementations in similar contexts. By sharing these insights along with the gathered datalake, we aim to inform stakeholders, including researchers, public authorities, and citizens, about effective strategies for deploying and utilizing LCAQMS to enhance air quality monitoring and public awareness.

In this paper thermo-mechanical behavior of 4D printed Polylactic Acid (PLA) was investigated, focusing on its response to varying strain rates and temperatures below the glass transition temperature. Dynamic mechanical analysis and uniaxial tensile tests confirmed PLA's dependency on strain rate, showcasing its sensitivity to external stimuli. Stress-strain curves exhibited typical thermoplastic behavior, with yield stresses varying with strain rates, underscoring PLA's responsiveness to different deformation speeds. Clear strain rate dependence was observed, particularly at quasi-static rates, with temperature and strain rate fluctuations significantly influencing PLA's mechanical properties, including yield stress and deformation behavior. Isothermal compression tests demonstrated predictable stress-strain curves with distinct yield points, while adiabatic tests reveal additional complexities such as heat accumulation leading to further softening. Thermal imaging revealed temperature increase during deformation, highlighting the material's thermo-sensitive nature. These findings provide the basis for future research with the focus on advanced modeling techniques and mitigation strategies for self-heating effects, aiming to enhance PLA-based product reliability and performance in applications with deformations at higher strain rates, while also developing models to simulate shape recovery in 4D printed PLA structures at both cold and hot programming temperatures.

Automated charging technologies are becoming increasingly important in the electrification of heavy road freight transport, especially in combination with autonomous driving. This study provides a comprehensive analysis of automated charging technologies for electric heavy-duty vehicles (HDVs). It encompasses the entire spectrum of feasible technologies, including static and dynamic approaches, with each charging technology evaluated for its advantages, potentials, challenges, and technology readiness level (TRL). Static conductive charging methods such as charging robots, underbody-couplers or pantographs show good potential, with pantographs being the most mature option. These technologies are progressing towards higher TRLs, with a focus on standardization and adaptability. While static wireless charging is operational for some prototype solutions, it encounters challenges related to implementation and efficiency. Dynamic conductive charging through an overhead contact line or contact rails holds promise for high-traffic HDV routes with the overhead contact line being the most developed option. Dynamic wireless charging, although facing efficiency challenges, offers potential for seamless integration into roads and minimal wear and tear. Battery swapping is emerging as a practical solution to reduce downtime for charging, with varying levels of readiness across different implementations. To facilitate large-scale deployment further standardization efforts are required. The study emphasizes the necessity for continued research and development to enhance efficiency, decrease costs, and ensure seamless integration into existing infrastructures. Technologies that achieve this best will have the highest potential to significantly contribute to the creation of an efficiently automated and environmentally friendly transport sector.

Vertical Indoor Farming (VIF) with hydroponics offers a promising perspective for sustainable food production. Intelligent control of VIF system components plays a key role in reducing operating costs and increasing crop yields. Modern machine vision (MV) systems use Deep Learning (DL) in combination with camera systems for various tasks in agriculture, such as disease and nutrient deficiency detection, and flower and fruit identification and classification for pollination and harvesting. This study presents the applicability of MV technology with DL modelling to detect the growth stages of chilli plants using YOLOv8 networks. The influence of different bird’s eye and side view datasets and different YOLOv8 architectures was analysed. To generate the image data for training and testing the YOLO models, chilli plants were grown in a hydroponic environment and imaged throughout their life cycle using four camera systems. The growth stages were divided into growing, flowering and fruiting classes. All trained YOLOv8 models showed reliable identification of growth stages with high accuracy. The results indicate that models trained with data from both views show better generalisation. YOLO’s middle architecture achieved the best performance.

Properties of time domain parameters of the vibration signal have been extensively studied for the fault diagnosis of rolling element bearings (REB). Parameters like kurtosis and Envelope Harmonic-to-Noise Ratio are most widely applied in this field and some important progress has been made. However, since only one-sided information is contained in these parameters respectively, problems still exist in practice when the signals collected are of complicated structure and/or contaminated by strong background noises. A new parameter, named Shock pulse index (SPI), is proposed in this paper. It integrates the mutual advantage of both parameters above and can help effectively identify fault related impulse components under the interference of strong background noises, unrelated harmonic components and random impulses. The SPI optimizes the parameters of Maximum Correlated Kurtosis Deconvolution (MCKD), which is used to filter the signals under consideration. Finally, the interested transient information contained in the filtered signal can be highlighted through demodulation with Teager Energy Operator (TEO). Fault related impulse components can therefore be extracted accurately. Simulations and experiment analyses verify the effectiveness and correctness of the SPI.

Wireless Sensor networks (WSNs) are gaining more and more research interest due to their ability to monitor large areas more or less independent. However, their reliability is an important issue, since their system reliability is influenced from a hardware, a data and an energetic point of view due to different factors like loading conditions, signal attenuation and battery lifetime. Regarding these issues, the positions of sensor nodes have to be chosen correctly to maximize the system reliability, which has to be considered during the development of new products equipped with WSNs. In this paper, an approach to estimate a WSNs system reliability during the development phase based on the analysis of the measurements on the example of strain measurements in finite elements (FE) models is presented. For that, the part under consideration is divided into regions with similar strains by the use of a Region Growing Algorithm (RGA). Afterwards, the WSN’s configuration is analyzed regarding its reliability in accordance to the data paths and measurement redundancy due to the sensor positions in the found measuring regions. This methodology is tested on an exemplary WSN configuration at an aircraft wing box under bending load and was found to work very well regarding the estimation of the hardware perspective on the system reliability. Therefore, the methodology and the developed algorithm show potentials for optimizations in sensor node positions for better reliability results.

For a long time, a company's Product Development Process (PDP) was seen as supporting the operations department, although PDP decisions and mistakes have a considerable impact on market performance. This is critical even in agriculture where bad habits and practices in the PDP can lead rural producers to great losses. Therefore, this research investigated the effect on the market performance of rural products (banana) in the southern region of Brazil, based on two analyses: (i) how sustainability practices support the PDP phases and (ii) how the phases of the Product Life Cycle Assessment (LCA) mediate sustainability practices and PDP phases. This study presents a quantitative analysis using Confirmatory Factor Analysis (CFA) and hierarchical ordinary least squares (OLS) regression of data obtained from a survey of 110 rural producers who directly participate in the banana production and planning process in southern Brazil. Our results shows that sustainability practices support the PDP, and we confirm that the product development and post-development phase has an effect on market performance. In addition, we identified that in the pre-development phase of the PDP, dealing with rural products (bananas), the maturity stage of the LCA mediates sustainability. In the PDP development phase, we concluded that rural families that develop economic and environmental practices with their products in the market growth phase may have reduced results. As for the post-development phase of the PDP, we conclude that when companies invest in environmental and social practices, there is a complete mediation of the effect, where these practices lose strength if the product is in the introduction and maturity phases in the market. As originality, our study contributed to demonstrate value on the product life cycle for the product development process in agriculture using sustainability practices through a systemic approach, filling the gap in the literature due to the lack of research on these areas seen in an integrated way.

A class of models for non-Gaussian spatial random fields is explored for spatial field reconstruction in environmental and sensor network monitoring. The family of models explored utilises a class of transformation functions known as the Tukey g-and-h transformations to create a family of warped spatial Gaussian process models which can support various desirable features such as flexible marginal distributions, which can be skewed, leptokurtic and/or heavy-tailed. The resulting model is widely applicable in a range of spatial field reconstruction applications. To utilise the model in applications in practice, it is important to carefully characterise the statistical properties of the Tukey g-and-h random fields. In this work, we both study the properties of the resulting warped Gaussian processes as well as using the characterising statistical properties of the warped processes to obtain flexible spatial field reconstructions. In this regard, we derive five different estimators for various important quantities often considered in spatial field reconstruction problems. These include the multi-point Minimum Mean Squared Error (MMSE) estimators; the multiple point Maximum A-Posteriori (MAP) estimators; an efficient class of multiple-point linear estimators based on the Spatial-Best Linear Unbiased (S-BLUE) estimators; and two multi-point threshold exceedance based estimators, namely the Spatial Regional and Level Exceedance estimators. Simulation results and real data examples show the benefits of using the Tukey g-and-h transformation as opposed to standard Gaussian spatial random fields in a real data application for environmental monitoring.

We show that the Einstein field equations for a five-dimensional warped spacetime, where only gravity can propagate into the bulk, determine the dynamical evolution of the warp factor of the four-dimensional brane spacetime. This can be explained as a holographic manifestation. The warped 5D model can be reformulated by considering the warp factor as a dilaton field ($\omega$) conformally coupled to gravity and embedded in a smooth $M_4 \otimes R$ manifold. On the brane, where the U(1) scalar-gauge fields live, the dilaton field manifests itself classically as a warp factor and enters the evolution equations for the metric components and matter fields. We write the Lagrangian for the Einstein-scalar-gauge fields in a conformal invariant setting. However, as expected, the conformal invariance is broken (trace-anomaly) by the appearance of a mass term and a quadratic term in the energy-momentum tensor of the scalar-gauge field, arising from the extrinsic curvature terms of the projected Einstein tensor. These terms can be interpreted as a constraint in order to maintain conformal invariance. By considering the dilaton field and Higgs field on equal footing on small scales, there will be no singular behavior, when $\omega\rightarrow 0$ and one can deduce constraints to maintain regularity of the action. Our conjecture is that $\omega$, alias warp factor, has a dual meaning. At very early times, when $\omega \rightarrow 0$, it describes the small-distance limit, while at later times it is a warp (or scale) factor that determines the dynamical evolution of the universe. We also present a numerical solution of the model and calculate the (time-dependent) trace-anomaly. The solution depends on the mass ratio of the scalar and gauge fields, the parameters of the model and the vortex charge $n$.

Surface acoustic wave (SAW) is effective for the manipulation of fluids and particles in microscale. The current approach of integrating interdigitated transducers (IDTs) for SAW generation into microfluidic channels involves complex and laborious microfabrication steps. These steps often require the full access to clean room facilities and hours to align the transducers to the precise location. This work presents an affordable and innovative method for fabricating SAW-based microfluidic devices without the need of clean room facilities and alignment. The IDTs and microfluidic channels are fabricated in the same process and thus precisely self-aligned in accordance with the device design. With the use of the developed fabrication approach, a few types of different SAW-based microfluidic devices have been fabricated and demonstrated for particle separation and active droplet generation.

The Ionian Sea is a crucial intersection for various water masses in the Mediterranean. Its hydrography and dynamics play a significant role in the seawater budgets and biogeochemistry of the neighboring sub-basins. Multiple theories have been formulated to gain a better understanding of the Ionian dynamics. These theories primarily attribute the variability of the near-surface Ionian circulation to internal processes. Here, we utilize horizontal currents and temperature-salinity profiles from the Copernicus reanalysis to examine the contribution of baroclinic modes to the variability of the basin horizontal circulation. Our findings demonstrate that, although the basin vertical structure is characterized by three layers, the primary patterns of the Ionian circulation can be attributed to the first baroclinic mode. This mode, along with the barotropic mode, accounts for over 85% of the overall variability in the Ionian circulation, suggesting that only one of the three interfaces separating the different water masses in the basin is dynamically active. We estimate the depth of this interface to be about 490 m. Additionally, our analysis shows that more than 90% of the kinetic energy over the water column is localized above this interface, indicating that the deep layer of the Ionian is dynamically nearly inert.

This paper proposes a product design model for internalising users’ positive experiences through attachment. First, the research commences with a literature review to define the concepts and research status of positive experience design (PED) and product attachment. Subsequently, the design model is constructed, accompanied by relevant formulas for concept generation. Finally, the model’s validity is verified through a workshop, and its effectiveness is evaluated and discussed using the USE questionnaire. This study incorporates the seven factors of product attachment to activate positive states within the user–product relationship and facilitate the cultivation of positive thinking. Grounded in theories of PED and embracing a product attachment perspective, the attachment-driven PED model offers a systematic approach for generating design concepts that are relevant to user experience.

In the present study, the new biological sources in the form of lichen Usnea orientalis Motyka was screened for its antidermatophytic potential. Six species of dermatophytes were chosen on the basis of their prevalence for antidermatophytic assays, and the Clinical Laboratory Standard Institute (CLSI)-recommended broth microdilution procedure was used to detect the efficacy of extract against dermatophytes. Thin layer chromatography of lichen extracts reveals the presence of two secondary metabolites viz. salazinic acid and usnic acid. U. orientalis extract exhibited promising antidermatophytic activity against all tested pathogens. Amongst all tested pathogens, E. floccosum exhibited most susceptibility towards extract, whereas T. mentagrophytes exhibited the least susceptibility. Topical application of U. orientalis extract might be helpful in the cure of dermal infections.

A solution of general relativity is presented that describes an Alcubierre propulsion system in which it is possible to travel at superluminal speed while reducing the energy, by an arbitrary value.

As a method of lightweight design, multi-material design aims to make targeted use of materials in order to reduce CO2 emissions. In this context, it can be described as one of the product development methods used to meet the challenges of climate change. However, since the design of structures in multi-material design is complex, topology optimization can be used to support the product developer. In this article, a multi-material topology optimization method is developed that combines the Velocity Field Level Set method with the Reconciled Level Set method. Furthermore, the current design is explicitly resolved in each iteration by means of multi-material remeshing. The edge collapse phase in the remeshing process is achieved by applying the producer consumer pattern. The developed method is then validated using known examples from the state of research and the influence of parameters of the method on the result is analyzed by means of studies.

Taekwondo has evolved from a traditional martial art into an official Olympic sport. This study introduces a novel action recognition model tailored for Taekwondo unit actions, utilizing joint motion data acquired via wearable inertial measurement unit (IMU) sensors. The utilization of IMU sensor-measured motion data facilitates the capture of the intricate and rapid movements characteristic of Taekwondo techniques. The model, underpinned by a conventional convolutional neural network (CNN)-based image classification framework, synthesizes action images to represent individual Taekwondo unit actions. These action images are generated by mapping joint motion profiles onto the RGB color space, thus encapsulating the motion dynamics of a single unit action within a solitary image. To further refine the representation of rapid movements within these images, a time-warping technique was applied, adjusting motion profiles in relation to the velocity of the action. The effectiveness of the proposed model was assessed using a dataset compiled from 40 Taekwondo experts, yielding remarkable outcomes: an accuracy of 0.998, precision of 0.983, recall of 0.982, and an F1-score of 0.982. These results underscore the time-warping technique's contribution to enhancing feature representation, as well as the proposed method's scalability and effectiveness in recognizing Taekwondo unit actions.

In this study, 10%PTFE/PEEK blend were modified by potassium titanate whisker (PTW) and chopped glass fiber (GF), respectively. The blends were prepared by three-screw extruder. Through the investigation of thermal stability, tribological properties, mechanical properties and rheological behavior, the effects of reinforcing agents were determined. The results illustrated that the mechanical properties of 10%PTFE/PEEK blend can be dramatically improved by adding reinforcing agent of PTW or GF, and the reinforcing effect of GF was especially obvious. As for tribological properties, 1% addition was the best proportion. The friction coefficient and wear rate of the blend with 1% PTW were 0.283 and 4.97 × 10^-6 mm³/N · m, which decreased by 7.2% and 21% compared with those of the blend without reinforcing agent.

Fiber coupling efficiency is one of the key technical indicators of atmospheric laser communication, which directly affects the communication system BER. According to the optical fiber coupling efficiency model, the optical fiber coupling model under atmospheric slant link is established, and the relationship between wavelength, zenith angle, receiving aperture, altitude and coupling efficiency is studied through numerical simulation. Based on the principle of adaptive optics turbulence correction, the relationship between fiber coupling efficiency and adaptive optics order is established. A fast method for estimating the coupling efficiency based on Strehl ratio is proposed. According to the principle of laser communication system, the semi-physical simulation experimental system of atmospheric slant-range channel coupling efficiency is constructed, and the coupling efficiency test and analysis are completed.

Background: Circulating rare cells participate in breast cancer evolution as systemic components of the disease and thus, are a source of theranostic information. Exploration of cancer-associated rare cells is in its infancy. We determined the validity of a rare-cell detection platform and demonstrated the usefulness of a certain rare cell subset as a novel approach to characterize the breast cancer system. Methods: Linearity of the Rarmax® platform was established using a spike-in approach. The platform includes red blood cell lysis, leukocyte depletion and high-resolution fluorescence image recording. Rare cell analysis was conducted on 28 samples (before and after surgery) from 14 patients with breast cancer, 20 healthy volunteers and 9 non-cancer control volunteers. In-depth identification of rare cells, including circulating tumor cells, endothelial-like cells, erythroblasts and inflammation-associated cells, was performed using a phenotype and morphology-based classification system. Results: The platform performed linearly over a range of 5-950 spiked cells, with an average recovery of 84.6%. Circulating epithelial and endothelial-like cell subsets have been demonstrated to be associated with or independent of cancer with tumor presence. Furthermore, certain cell patterns may be associated with treatment-related adverse effects. The sensitivity in detecting tumor-presence and cancer-associated abnormality before surgery was 50% and 85.7%, respectively and the specificity was 100% and 96.6%, respectively. Conclusion: The present study supports the idea of a cancer-associated rare cell abnormality to represent tumor entities as well as systemic cancer. The latter is independent of the apparent clinical cancer.

This bibliographic study addresses key aspects related to fishing, product safety, and climate change in the Adriatic Sea region. The examination of product safety focuses on the assessment of contaminants originating from human activities such as industry, mining, agriculture, and household waste disposal. The contamination of the aquatic environment has emerged as a pressing global concern, extending to the Adriatic subbasin. Aquatic organisms, including fish, are prone to accumulating pollutants directly from polluted water sources and indirectly through the food web. The bio-accumulation of potentially hazardous substances, particularly heavy metals, pesticides, PCBs, PAHs, and antibiotic resistance in aquatic organisms, poses a significant threat to human health. Climate change effects will deplete our seafood supply in terms of quantity and safety owing to negative consequences such as higher levels of pollution, parasites, viruses, infections, acidification, and toxicities such as shellfish poisoning. Global food safety strategies should be developed to reduce greenhouse gas emissions and promote environmentally friendly technology, which indirectly affects seafood quality and microbiological safety, especially for Adriatic Sea, which is part of the Mediterranean Sea, characterized by the most polluted waters in the world.

This paper addresses the mixed convective flow and heat transfer in combustible third grade fluid through a slant channel that is filled with a permeable materials. The fluid layer in contact with the lower plate is exposed to convective heating with the ambient while at the upper plate, a constant heat flux is experienced. We employ the spectral quasilinearisation method (SQLM) to the coupled nonlinear flow governing equations. Fluid velocity and temperature profiles, local entropy generation and irreversibility ratio are computed and analysed quantitatively and qualitatively. A residual error analysis demonstrated high accuracy and convergence of the numerical method. The results on flow and thermal effects, entropy generation rate and Bejan number revealed fascinating manifestations that have profound implications in design of thermo-mechanical systems. In particular, the results of the thermal analysis are pertinent to optimal designs of systems that achieve efficient energy utilization.

A large core size and bending resistance are very important properties of mid-infrared energy transfer fibers, but large core sizes usually lead to a deterioration of bending properties. A negative-curvature nested node-free anti-resonant hollow-core fiber (AR-HCF) based on quartz is proposed. It was made by adding a nested layer to a previous AR-HCF design to provide an additional anti-resonance region while keeping the gap between adjacent tubes strictly correlated to the core diameter to produce a node-free structure. These features improve the fiber’s bending resistance while achieving a larger core diameter. The simulation results show that the radial air-glass anti-resonant layer is increased by the introduction of the nested anti-resonant tube, and the weak interference overlap between the fiber core and the cladding mode is reduced, so the fiber core’s limiting loss and the sensitivity to bending are effectively reduced. When the capillary wall thickness t of the fiber is 0.71 μm, the core diameter D is 70 μm, the ratio of the inner diameter of the cladding capillary to the core diameter d/D is 0.62, and the diameter of the nested tube is d0=29 μm, the fiber has a lower limiting loss at the wavelength of 2.79 μm, and the limiting loss is 3.28×10-4 dB/m. At the same time, the optimized structure also has good bending resistance. When the bending radius is 30 mm, the bending loss is only 4.72×10-2 dB/m. To our knowledge, this is the first research to achieve an anti-bending low-loss micro-structure hollow fiber with a bending radius of less than 30 mm in the 2.79 μm band. An anti-bending low-loss anti-resonant hollow-core fiber with this structure constitutes a reliable choice for the light guiding system of a 2.79 μm band erbium laser therapy instrument.

Fe-(9, 19, 28, 37)wt.% Cr alloys were corroded at 700 and 800 ^oC for 70 h under 1 atm of N₂, 1 atm of N₂/3.2%H₂O-mixed gas, and 1 atm of N₂/3.1%H₂O/2.42%H₂S-mixed gas. The corrosion rate of Fe-9Cr alloy increased with the addition of H₂O, and furthermore with the addition of H₂S in N₂ gas. Fe-9Cr alloy was always nonprotective. In contrast, Fe-(19, 28, 37) wt.%Cr alloys were protective in N₂ and N₂/H₂O-mixed gas because of formation of the Cr₂O₃ layer. They were, however, nonprotective in N₂/H₂O/H₂S-mixed gas because sulfidation dominated to form the outer FeS layer and the inner Cr₂S₃ layer containing some FeCr₂S₄.

Ultra-short 230 fs laser pulses of 515 nm wavelength were tightly focused into 700 nm focal spots and utilised in opening ~ 400 nm nano-holes in a Cr etch mask that was tens-of-nm thick. Nano-holes ablated at slightly above the threshold of ablation irradiance became nano-disks and nano-rings at slightly lower pulse energies. Subtle sub-1 nJ pulse energy control was harnessed to pattern large surface areas with controlled nano-alloying of Si and Cr. This technique is extendable to vacuum-free large area patterning of nanolayers by alloying them at distinct locations with sub-diffraction resolution. Such metal masks with nano-hole opening can be used for formation of random patterns of nano-needles with sub-100 nm separation when applied to dry etching of Si.

In this paper, several classes of rough Marcinkiewicz integral operators along surfaces of revolution on product spaces are investigated. We prove the Lp boundedness of these operators when their kernels functions belong to a class of functions related to a class of functions introduced by Grafakos-Stefanov. The results in this paper extend and improve several known results on Marcinkiewicz integrals.

This research investigates the impact of Al and Ti elements on the formation of self-generated ordered phase in high-entropy alloys (HEA), which have been receiving widespread concentration in present times thanks to their remarkable multifunctional properties and wide range of component selection. By adjusting the dual elements of Al and Ti, the study explores the regulation of quantity and distribution of the in-situ self-generated ordered phases in the alloy. The results of the annealing heat treatment process demonstrated that, through accession Al and Ti elements, the Cr-Fe-Ni medium-entropy alloy transfer from BCC phase to BCC+FCC phase and the precipitation of new phases such as B2, L21, and σ. This led to a synergistic impact of second phase strengthening, and also of solid solution strengthening, resulting in improved compressive properties of HEA.

In this review, we address issues that relate to the rapid “Warp Speed” development of vaccines to counter the COVID-19 pandemic. We review the antibody response that is triggered by SARS-CoV-2 infection of humans, and how it may inform vaccine research. The isolation and properties of neutralizing monoclonal antibodies from COVID-19 patients provide additional information on what vaccines should try to elicit. The nature and longevity of the antibody response to coronaviruses are relevant to the potency and duration of vaccine-induced immunity. We summarize the immunogenicity of leading vaccine candidates tested to date in animals and humans, and discuss the outcome and interpretation of virus-challenge experiments in animals. By far the most immunogenic vaccine candidates for antibody responses are recombinant proteins, which are not included in the initial wave of “Warp Speed” immunogens. A substantial concern for SARS-CoV-2 vaccines is adverse events, which we review by considering what was seen in studies of SARS-CoV-1 and MERS-CoV vaccines. We conclude by outlining the possible outcomes of the “Warp Speed” vaccine program, which range from the hoped-for rapid success to a catastrophic adverse influence on vaccine uptake generally.

Fiscal control and monitoring of public management are issues of great importance and relevance, as they focus on preventing and mitigating corruption, thus benefiting governments in their management and performance, and thus citizens. Given the large amount of data involved in the management and functioning of a government, it is pertinent to apply data analysis methods to contribute to fiscal control. This paper aims to investigate data management for this purpose, starting with a bibliometric study to demonstrate the relevance and pertinence of the current study. It examines existing data collection techniques that may facilitate such control, data storage considering its nature and the possibilities that contribute to this end, and data processing through techniques that allow obtaining adequate information for further analysis and decision making. The necessary architecture and interoperability between systems is also discussed, as the existence of large amounts and types of data in governments makes it crucial to promote these practices for accurate and truthful analysis. Finally, data visualization is addressed since this topic is highly relevant as it allows for the identification of anomalies, where proper visualization promotes appropriate analysis and thus informed decision making. This work is useful for modern audit and fiscal control entities, since data capture, storage, processing, interoperability, and visualization are crucial elements that collectively enhance the ability to supervise public expenditure effectively, ensuring that public funds are managed with the highest standards of transparency, accountability, and efficiency.

For the purpose of improve the sustainability of products sold in the EU, Digital Product Passports is a mandatory solution. These passports would systematically gather information about products, such as detailing the materials involved to aid recycling and remanufacturing efforts, or recording the emissions produced throughout the manufacturing process. The overall goal is the establishment of a circular economy in the EU. Current research on Digital Product Passports is focused on collating content for sector-specific applications. However, achieving sustainability goals through Digital Product Passports will require new methods and technical solutions for digital collaboration between supply chain participants, especially in the manufacturing sector. Collaborative work on Digital Product Passports requires trust and traceability in data and access management to ensure privacy over the data contained. One way to enable this securely and confidentially is through the use of blockchain technology, in which stored data cannot be concealed, which is key to the traceability of digital product data documentation. This paper therefore presents a concept for the implementation of generically applicable cross-industry blockchain-based digital product passports. To this end, generic supply chain processes have been abstracted and condensed into the architecture of smart contracts. Great attention is paid to the establishment of traceability as well as privacy through the selection of the blockchain technology Secret Network in combination with Gaia-X functionalities. An illustrative use case for digital product passports in manufacturing is used to demonstrate the applicability of the presented concept. In this use case information about the digital nameplate and carbon footprint is exchanged securely and confidentially in a multi-tenant supply chain network based on the Industry 4.0 infomation model of the Asset Administration Shell.

Ultramafic rocks become promising candidates for carbon sequestration by enhanced carbon dioxide (CO2) mineralization strategies due to their highly CO2-reactive mineral composition and its abundant availability. This study reports a mineralogy and microtextures of a representative ultramafic rock from the Ma-Hin Creek in northern Thailand and observes evidence of CO2 mineralization occurring through the interaction between CO2 and the rock with the existence of water under ambient conditions. After sample collection, rock description was determined by optical petrographic analysis. The rock petrography reveals a cumulated wehrlite comprising over 50% olivine and minor amounts of clinopyroxene, plagioclase, and chromian spinel. Approximately 25% of the wehrlite has altered to serpentine and chlorite. A series of CO2 batch experiments were conducted on six different rock sizes at a temperature of 40°C and pressure of 1 atm over five consecutive days. The post-experimental products were dried, weighed, and geochemically analyzed to detect changes in mineral species. Experimental results showed that product weight and the presence of calcite increased with reducing grain size. Additionally, the modal mineralogy of the wehrlite theoretically suggests a potential CO2 uptake of up to 53%, which is higher than the average uptake values of mafic rocks. These findings support the suitable rock investigation approach and the preliminary assessment of carbon mineralization potential, contributing to enhanced rock weathering techniques for CO2 removal that could be adopted by mining and rock supplier industries.

Batch and transport experiments were used to investigate the remediation of a loamy sand soil contaminated with Cr(VI) using zero valent iron nanoparticles (nZVI) stabilized by the carboxy methyl cellulose (CMC-nZVI). The effect of pH, ionic strength (IS), and flow rate on the removal efficiency of Cr(VI) were investigated under equilibrium (uniform transport) and non-equilibrium (Two-site sorption) transport using the Hydrus-1D model. The overall removal efficiency ranged from 70 to over 90% based on the chemical characteristics of the CMC-nZVI suspension and the transport conditions. The concentration and pH of the CMC-nZVI suspension had the most significant effect on the removal efficiency and transport of Cr(VI) in the soil. The average removal efficiency of Cr(VI) was increased from 24.1 to 75.5% when the concentration of CMC-nZVI nanoparticles was increased from 10 to 250 mg L-1, mainly because of the increased total surface area at larger particle concentration. Batch experiments showed that removal efficiency of Cr(VI) was much larger under acidic conditions. The average removal efficiency of Cr(VI) reached 90.1 and 60.5 % at pH 5 and 7, respectively. The Two-site sorption model described quite well (r2 = 0.96-0.98) the transport of Cr(VI) in soil as compared to the uniform transport model (r2 = 0.81-0.98). The average retardation of Cr(VI) was 3.51 and 1.61 at pH 5 and 7, respectively, indicating earlier arrival for the breakthrough curves and shorter time to reach maximum relative concentration at lower pH. The Hydrus-1D model has proven to be an efficient tool for assessing the removal of Cr(VI) pollutants, offering innovative, cost-effective, and environmentally friendly remediation methodologies.

The influence of short term water absorption on the mechanical properties of halloysite nanotubes-multi layer graphene reinforced polyester hybrid nanocomposites has been investigated. The addition of nano-fillers significantly increased the flexural strength; tensile strength and impact strength in dry and wet conditions. After short term water exposure; the maximum microhardness; tensile; flexural and impact toughness values were observed at 0.1 wt% MLG. The microhardness increased up to 50.3%; tensile strength increased up to 40% and flexural strength increased up to 44%. Compared to dry samples; the fracture toughness and surface roughness of all types of produced nanocomposites were increased that may be attributed to plasticization effect. Scanning electron microscopy revealed that the main failure mechanism is caused by the weakening of nano-filler-matrix interface induced by water absorption. It was further observed that synergistic effects were not effective at concentration of 0.1 wt% to produce considerable improvement in mechanical properties of produced hybrid nanocomposites.

Cohesion in the refractory metals Cr, Mo, and W is phenomenologically described in this work via a n-body energy functional with a set of physically motivated parameters that were optimized to reproduce selected experimental properties characteristic of perfect and defective crystals. The functional contains four terms accounting for the hard-core repulsion, the Thomas-Fermi kinetic energy repulsion and for contributions to the binding energy of s and d valence electrons. Lattice dynamics, molecular statics, and molecular dynamics calculations show that this model describes satisfactorily thermodynamic properties of the studied metals whereas, unlike other empirical approaches from the literature, predictions of phonon dispersion relations and of surface and point defect energetics reveal in fair good agreement with experiments. These results suggest that the present model is well adapted to large-scale simulations and whenever total energy calculations of thermodynamic properties are unfeasible

Aluminum base alloys containing chromium (Cr) and zinc (Zn) were produced using extrusion and heat treated powder metallurgy. Cr addition ranged between 5 to 10 wt. % while Zn was added in an amount between 0 to 20 wt. %. Heat treatment processes were performed during powder metallurgy process at different temperatures followed by water quenching. Similar alloys were extruded, with an extrusion ratio of 4.6 to get proper densification. Optical microscopy was used for microstructure investigations of the produced alloys. The element distribution microstructure study was carried out using the Energy Dispersive X-ray analysis method. Hardness and tensile properties of the investigated alloys have been examined. Wear resistance tests were carried out and the results were compared with these of the Al-based bulk alloys. Results showed that the aluminum base alloys containing 10wt. % Chromium and heat treated at 500°C for one hour followed by water quenching exhibited the highest wear resistance and better mechanical properties.

mRNA-lipid nanoparticle (LNP) medicinal products can be considered a platform technology because the development process is similar for different diseases and conditions, with similar noncoding mRNA sequences and lipid nanoparticles and essentially unchanged manufacturing and analytical methods utilised often for different products. It is critical not to lose the momentum built using the platform approach during the development, regulatory approval and rollout of vaccines for SARS-CoV-2 and its variants. This Review proposes a set of modifications to existing regulatory requirements for mRNA products, based on a platform perspective for quality, manufacturing, preclinical and clinical data. For the first time, we address development and potential regulatory requirements when the mRNA sequences and LNP composition vary in different products as well. In addition, we propose considerations for self-amplifying mRNA, individualised oncology mRNA products and mRNA therapeutics. Providing a predictable development pathway for academic and commercial groups, so they can know in detail what product characterisation and data are required to develop a dossier for regulatory submission, has many potential benefits. These include reduced development and regulatory costs; faster consumer/patient access and more agile development of products in the face of pandemics; and for rare diseases where alternatives may not exist or to increase survival and the quality of life in cancer patients. Therefore, achieving consensus around platform approaches is both urgent and important. This approach with mRNA can be a template for similar platform frameworks for other therapeutics and vaccines to enable more efficient development and regulatory review.

This study proposed the combination system consisting of biogas dry reforming reactor and solid oxide fuel cell (SOFC). Since a biogas dry reforming is an endothermic reaction, this study adopted a membrane reactor operated due to the non-equilibrium state with H2 separation from the reaction space. This study aimed to clarify the characteristics of Ni/Cr/Ru catalyst using for a biogas dry reforming membrane reactor. Additionally, this study also investigated the comparison of the characteristics of Ni/Cr/Ru catalyst with that of Ni/Cr catalyst. The impact of operation temperature, the molar ratio of CH4 : CO2, the differential pressure between the reaction chamber and the sweep chamber and the introduction of sweep gas on the characteristics of the biogas dry reforming membrane reactor using Pd/Cu membrane and Ni/Cr/Ru catalyst was examined. The concentration of H2 using Ni/Cr/Ru catalyst was larger than that using Ni/Cr catalyst by 2871 ppmV for the molar ratio of CH4 : CO2 = 1.5 : 1 at the reaction temperature of 600 ℃ and the differential pressure of 0 MPa without a sweep gas, especially. Under this condition, CH4 conversion, H2 yield and thermal efficiency were 67.4 %, 1.77×10-2 % and 0.241 %, respectively.

Business-to-business (B2B) manufacturing companies are increasingly confronted with transformative trends such as sustainability, digitalization, and servitization. These trends are changing how product portfolios are developed, and value contributions are assessed, and therefore have disruptive potential. Dealing with these disruptive factors in Product Portfolio Management (PPM) is a largely unexplored topic. This study presents an empirical-qualitative exploration that contributes significantly to the field. The aim is to clarify the extent to which disruptive factors influence the evaluation and shaping of the product portfolio in B2B manufacturing companies. The Gioia method was used to evaluate 21 semi-structured interviews with experts from leading B2B manufacturing companies. Eight overarching challenges in PPM resulting from the disruptive factors were identified. Based on the eight overarching challenges and their associated causal relationships, two aggregated dimensions of action were derived: (1) increasing speed and flexibility by using generative artificial intelligence (AI) in a defined PPM process and (2) adjusting the product portfolio evaluation to consider various strategic drivers. These two dimensions of action call for future research to overcome the disruptive factors in PPM.

In this paper, some mixed type bounds on the spectral radius $\rho(A\circ B)$ for the Hadamard product of two nonnegative matrices ($A$ and $B$) and the minimum eigenvalue $\tau(C\star D)$ of the Fan product of two $M$-matrices ($C$ and $D$) are researched. These bounds complement some corresponding results on the simple type bounds. In addition, a new lower bound on the minimum eigenvalue of the Fan product of several $M$-matrices is also presented: $$ \tau(A_{1}\star A_{2}\cdots\star A_{m})\geq \min_{1\leq i\leq n}\{\prod^{m}_{k=1}A_{k}(i,i)-\prod^{m}_{k=1}[A_{k}(i,i)^{P_{k}}-\tau(A_{k}^{(P_{k})})]^\frac{1}{P_{k}}\}, $$ where $A_{1},\ldots, A_{k}$ are $n\times n$ $M$-matrices and $P_{1},\ldots, P_{k}>0$ satisfy $\sum^{m}_{k=1}\frac{1}{P_{k}}\geq 1$. Some special cases of the above result and numerical examples show that this new bound improves some existing results.

The success of near-infrared spectroscopy (NIRS) analysis hinges on the precision and robustness of the calibration model. Shallow learning (SL) algorithms like partial least squares discriminant analysis (PLS-DA) often fall short in capturing interrelationships between adjacent spectral variables, and the analysis results are easily affected by spectral noise, which dramatically limits the breadth and depth application of NIRS. Deep learning (DL) methods, with their capacity to discern intricate features from limited samples, are progressively integrated into NIRS. In this paper, two discriminant analysis problems including wheat kernels and Yali pears were used as examples, and several representative calibration models to research the robustness and effectiveness of the model. Additionally, this article proposed a near-infrared calibration model, which is based on gramian angular difference field and coordinate attention convolutional neural networks (G-CACNN). The research results show that, compared with SL, spectral preprocessing has a smaller impact on the analysis accuracy of consensus learning (CL) and DL, and the latter has the highest analysis accuracy in the modeling results of using the original spectrum. The accuracy of G-CACNN in two discrimination tasks is 98.48% and 99.39%, respectively. Finally, This research compared the performance of various models under noise to evaluate the robustness and noise resistance of the proposed method.

We investigate and discuss in detail the structure of the restricted singular value decomposition for a tensor triplet under t-product (T-RSVD). The algorithm is provided with a numerical example illustrating the main result. For applications, we consider color image watermarking processing with T-RSVD.

Several bio-actors are involved in the occurrence of leishmaniasis, which is made too complex for prevention and control options. Currently, all forms of leishmaniasis are being treated with chemical drugs, which have limitations and adverse effects on patients. Searching the bioactive molecules from plant sources allows the development of a novel drug. The essential oil and solvent extract of the roots of E. kebericho showed antileishmanial activity. But looking for biological activities of the isolated active ingredient from tubers of E. kebericho was scant. Thus, the isolation of the leishmanicidal compound from the roots of E. kebericho through a bioassay-guided technique was an aim of this work. Dehydrocostus lactone showed doubled potent than the standard drug miltefosine on leishmanicidal activities against L. major and L. tropica. Besides, the broad-spectrum biological activities of dehydrocostus lactone could be a potential drug candidate for co-infected patients caused by an association of leishmania and another pathogen.

In this paper we introduce the hypo-q-norms on a Cartesian product of inner product spaces. A representation of these norms in terms of inner products, the equivalence with the q-norms on a Cartesian product and some reverse inequalities obtained via the scalar Shisha-Mond, Birnacki et al., Grüss type inequalities, Boas-Bellman and Bombieri type inequalities are also given.

Tea (Camellia sinenesis) is a health beneficial beverage and is also a source for extracting bioactive components such as theanine, tea polyphenols (TPP) and tea polysaccharides (TPS). TPS is a group of hetero-polysaccharides bounded with proteins. There were tests showing that TPS had various bioactivities, such as antioxidant, antitumors, antihyperglycemia, anti-inflammation and improving immunity. However, inconsistent results concerning chemical composition and bioactivity of TPS were published in recent years. The advances in chemical composition and bioactivities of TPS were reviewed in the present paper. The inconsistent and controversial results regarding composition and bioactivities of TPS were also discussed.

Compared to other 2D materials, MBenes are at an early stage in both experimental and theoretical approaches. However, the wide range of possible 2D structures leads to novel and challenging properties and their consequent applications. From all the possible stoichiometries, we have performed a theoretical study of orthorhombic and hexagonal M2B2 MBenes in the framework of the Density Functional Theory. We have found that both symmetries of Cr2B2, Fe2B2, and Zr2B2 show a metallic behavior and could be grown under certain conditions, as they are demonstrated to be dynamically stable. Moreover, the values of the magnetic moment, in specific ferromagnetic cases exceeding 2.5 μB/M2B2, make them suitable as robust 2D magnets. All our findings represent an important step in the understanding of MBenes and open several windows to future research in fields like energy conversion and storage, sensing, catalysis, biochemistry, or nanotechnology, among others.

Jerusalem artichoke juice is valued for its nutritional content and health benefits. Spontaneous fermentation enhances its flavor, quality, and functional components through microbial metabolic activities. This study used high-throughput sequencing to analyze microbial community changes and LC-MS and GC-MS to detect secondary metabolites and flavor compounds during fermentation. During the natural fermentation, beneficial bacteria like Lactobacillus and Pediococcus increased, promoting lactic acid production and inhibiting harmful bacteria, while environmental bacteria decreased. Similarly, fungi shifted from environmental types like Geosmithia and Alternaria to fermentation-associated Pichia and Penicillium. A total of 1, 666 secondary metabolites were identified, with 595 upregulated and 497 downregulated. Key metabolic pathways included phenylpropanoid biosynthesis, with significant increases in phenylalanine, tryptophan, and related metabolites. Lipid and nucleotide metabolism also showed significant changes. Flavor compounds, including 134 identified alcohols, esters, acids, and ketones, mostly increased in content after fermentation. Notable increases were seen in Phenylethyl Alcohol, Ethyl Benzenepropanoate, 3-Methylbutyl Butanoate, Ethyl 4-Methylpentanoate, 5-Ethyl-3-Hydroxy-4-Methyl-2(5H)-Furanone, Ethyl Decanoate, Hexanoic Acid, 1-Octanol. γ-aminobutyric acid (GABA) and other functional components enhanced the health value of the juice. This study provides insights into microbial and metabolic changes during fermentation, aiding in optimizing processes and improving the quality of fermented Jerusalem artichoke juice for functional food development.

The Double Diaphragm Forming (DDF) process uses vacuum pressure and heat to pre-shape composite reinforcements between flexible diaphragms. Accurate modelling of heat transfer within DDF requires knowledge of the thermophysical properties of the constituent materials. This study investigates the specific heat and thermal conductivity of silicone diaphragms, carbon fibers (chopped and powdered), thermoplastic veils, and their combinations. Experiments measured the specific heat of each material using differential scanning calorimetry and the thermal conductivity of silicone and carbon fabric preforms using the transient plane source method and modified transient plane source method respectively. The influence of reheating cycles on specific heat of carbon fiber-veil samples and the effect of compaction on thermal conductivity of silicone and carbon fabrics were explored. While silicone exhibited linear specific heat behavior, the thermoplastic veil showed non-linearity due to phase change. The combined carbon fiber-veil samples demonstrated slight non-linear specific heat variations depending on reheating cycles. Thermal conductivity of the fabric preforms decreased with the addition of thermoplastic veil and under vacuum-compaction conditions. The established temperature-dependent property relationships provide valuable data for optimizing DDF preforming parameters and enhancing energy efficiency in composite manufacturing.

Background: A new coronavirus (SARS-CoV-2) that emerged from Wuhan, Hubei Province, China, has spread throughout the world and is declared a pandemic by the World Health Organization (WHO). A lot remains to be understood of SARS-CoV-2 and the disease (COVID-19). SARS-CoV-2 has until recently been identified as responsible for both asymptomatic and serious life-threatening infections. The unavailability of specific therapeutic agents is a major hurdle in the treatment and management of COVID-19 patients. The present review attempts to evaluate the immunobiochemical aspects of the pathogenesis, diagnosis, and management of SARS-CoV-2 infection. Main Body: This review is a comprehensive evaluation of the data collected through various sources, including Google Scholar, PubMed, and Scopus. The articles were searched and selected using key words such as “Coronavirus disease (COVID-19)”, “Diagnosis of COVID-19”, Pathogenesis of Covid-19”, “management of COVID-19”, “Immunology of COVID-19”, and “Complications of COVID-19”. The study noted that the novel Coronavirus infection could result in an exaggerated immune response, causing a cytokine storm and damaging several organs of the body. The infected patients develop several complications, including immunological, hematological, and biochemical alterations. Consequently, COVID-19 patients may develop cardiovascular, liver, renal, and neurological complications, among others. Conclusion: An increased understanding of the immunobiochemical aspects of the disease may contribute to better management of SARS-CoV-2-infected persons, as evidenced from the available literature. A holistic approach to the management of COVID-19 patients taking into consideration the effect of COVID-19 infection on various organs of the body assumes increased significance in patient management.

Nickel-base superalloys like VDM 780 may possess a high content of Cr and Co. This influences solution energies of phase-forming elements like Al and Ta (γ′-phase), Nb (γ′′- and δ-phase), and Ti (η-phase). We perform density functional theory studies of a nickel matrix at 0 K with high concentrations of either Co and Cr and calculate the influence of these elements on solution energies. In the case of Co, the solution energy can be predicted well by the nearest-neighbor interaction in the Co-rich matrix. For Cr, the effect is more complicated because Cr has a larger ionic radius and changes the magnetic state of the material. The effect of a Cr-rich matrix on the energy of Co is dominated by magnetic effects, interactions with the other elements by elastic deformation of the lattice.

Optical characterization and thermal aging tests are performed on a sputter-deposited coating, consisting of SiO₂/Cr₂O₃/Cr/Cr₂O₃ layers, designed and developed as a selective solar absorber to be used for unconcentrated solar thermal applications. Both measurements are performed by using a home-made apparatus, which mimics a flat plate collector under high vacuum. A Performance Criterion (PC_η(T)), based on absorber efficiency is proposed, and a forecast of service lifetime is obtained. As a result of the thermal aging tests, the selective solar absorber under study appears to be highly efficient at mid temperatures (up to 573 K) and thermally stable at temperatures (up to 690 K).

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.

In this work, we investigated the effects of heat treatment on the microstructure, hydrogen storage characteristics and corrosion rate of a Ti₃₄V₄₀Cr₂₄Fe₂ alloy. The arc melted alloy was divided into three samples, two of which were separately quartz-sealed under vacuum and heated to 1000 °C for 1 h; one of these samples was quenched and the other furnace cooled to ambient temperature. The crystal structures of the samples were studied via X-ray diffractometry and scanning electron microscopy. Absorption/desorption characteristics were investigated using a Sievert apparatus. Potentiostat corrosion tests on the alloys were performed using an AutoLab^® corrosion test apparatus and electrochemical cell. All samples exhibited a mixture of body-center-cubic (BCC) and Laves phase structures. The corrosion rate, maximum absorption, and useful capacities increased after both heat treatments. The annealed sample had the highest absorption and reversible capacity. The plateau pressure of the as-cast alloy increased after quenching. The corrosion rate increased from 0.0004 mm/y in as-cast sample to 0.0009 mm/y after annealing and 0.0017 mm/y after quenching, due to a decrease in the Cr-content of the C14 phase.

The overarching vision of Society 5.0 seeks to integrate technology to enhance the quality of life and address social issues, with the primary goal of creating human-centered communities, which nowadays represent the inhabitants of Smart Cities. In this context, this work addresses the design of a modular strategic platform for the smart supervision of public expenditure, to be used by the Directorate of Information, Analysis, and Immediate Reaction (DIARI) of the General Comptroller of the Republic (CGR) of Colombia as a significant contribution towards the country’s transition into the Society 5.0. The design was performed by conducting a detailed literature review on fiscal control; a comprehensive analysis of the legal, organizational, and technological aspects of the country and the CGR; and developing six functional modules focused on topics such as continuous learning, strategic decision-making, distinctive value, strategic achievements, capacity building, and organization, within a three-year implementation plan, through a participatory approach. This plan aims to integrate the platform to enable real-time monitoring, early detection of irregularities, and increased transparency in the management of data and public resources. The strategic platform for the DIARI of the CGR is useful for Smart Cities and the transition into Society 5.0 since it ensures efficient public expenditure management, enhancing transparency and citizen empowerment through modern technologies, data analytics, and active participation in governance processes.

A useful perioperative nutritional therapy for highly invasive esophageal cancer surgical cases needs to be developed. We clarified the usefulness of amino acid-enriched nutritional therapy using glutamine (Gln)/arginine (Arg)/calcium β-hydroxy-β-methylbutyrate (HMB) products on the short-term postoperative outcomes of minimally invasive esophagectomy for esophageal cancer. Altogether, 114 patients (Gln/Arg/HMB group) received perioperative nutritional therapy with Gln/Arg/HMB products, and we retrospectively investigated the change in nutritional parameters including skeletal muscle mass, occurrence of postoperative complications, and short-term postoperative outcomes in this group. The results were compared between the Gln/Arg/HMB and control groups (79 patients not receiving the Gln/Arg/HMB products). The incidence of all postoperative complications, sputum expectoration disorder, and pleural effusion of grade ≥III was significantly lower in the Gln/Arg/HMB group (62.0% vs. 38.6%, p = 0.001; 44.3% vs. 28.1%, p = 0.020; 27.8% vs. 13.2%, p = 0.011, respectively). The psoas muscle area and postoperative body weight was significantly higher at 1 month and 1 year after surgery in the Gln/Arg/HMB group than in the control group (93.5% vs. 99.9%, p < 0.001; 92.0% vs. 95.4%, p = 0.006). Perioperative amino acid-enriched nutritional therapy may improve the short-term postoperative outcomes, nutritional status, and skeletal muscle mass of esophageal cancer surgical patients.

Product Development Process is widely known among industry and automobile companies. With the advance of technology and the need to improve product efficiency, many companies have been applying Lean Thinking principles. Their benefits lead those companies to implement their concepts and tools, like Value Stream Design in Indirect Areas, Obeya, Just-in-time (JIT) which is based on the production control system developed and implemented by Toyota. This article describes the case study of the implementation of Lean Product & Process Development (LPPD) on the current Product Development Process (PDP) in an automotive company. The PDP was created by the organization and adapted from Advanced Product Quality Planning (APQP). The main findings were a Value Stream Design model of an improved PDP as a useful and successfully contribution for the company. These improvements reduced the product development lead time from 700 days to 369 days. The process efficiency increased from 68% to 85%. The communication and transparency between the cross-functional team (CFT) was improved and show promise for achieving a successful launch of new products.

Natural products (NPs) are a rich source of structurally novel molecules, and the chemical space they encompass is far from being fully explored. Over history, NPs have represented a significant source of bioactive molecules and have served as a source of inspiration for developing many drugs on the market. On the other hand, computer-aided drug design (CADD) has contributed to drug discovery research, mitigating costs and time. In this sense, compound databases represent a fundamental element for the CADD. This work reviews the progress toward developing compound databases of natural origin, particularly databases developed in Latin America, and their practical applications in the drug discovery area. We also survey the computational methods, emphasizing chemoinformatic approaches to profile natural product databases.

This paper is devoted to the study of reproducing kernels on 2-inner product Hilbert spaces. We focus on a new structure to produce reproducing kernel Hilbert and Banach spaces. According to multi-variable computing, this structures can be useful in electrocardiographs, machine learning and economy

This research investigated high-temperature corrosion (500 °C) of Cr-Mo steel processed using water jet peening or multifunction cavitation (MFC), and the suitability of such steel for high-temperature boilers and reaction vessels. High-temperature corrosion was induced using an embedment test and a coating test using sulfide-type K2SO4-Na2SO4 powder. To measure the relaxation of the residual stress due to the decrease in work hardening caused by an increase in specimen temperature and the difference in thermal shrinkage between the surface and interior of the specimen, a thermal cycling test was conducted. For the MFC-processed specimen, the oxide film that formed on the surface suppressed mass loss, prevented crack formation, and reduced the compressive residual stress caused by high-temperature corrosion. MFC-processed Cr-Mo steel is thus suitable for a high-temperature corrosion environment.

The main objective of our study was to understand the rheological behavior of various types of cheeses with mold subjected to multiple stresses during processing/handling, transport, or storage, aiming to maintain or even improve product quality, using computer-assisted penetration methods, and advanced regression algorithms. Uniaxial penetration tests with a cone at a constant speed were conducted using a universal Hounsfield HK1S testing equipment connected to a computer to analyze the texture behavior (tangential stress, flow index, apparent viscosity) of four of the most common types of cheese with mold, depending on the cone's tip angle (9, 19, and 90°) and penetration speed (12, 30, and 60 mm/min). From the results obtained for the four categories of mold cheeses (Brie, Camembert, Dorblue, or Roquefort), the amplitude of the speed and angle of penetration were considered as the main influencing factors for the shear deformation (τc), flow index (Kf), and apparent viscosity (ηa). The moisture and firmness of the mold cheeses are closely linked and depend on the type of mold, the maturation process, or storage conditions. Careful control of these factors is essential to achieve the desired texture and taste characteristics in cheeses with mold.

A wide variety of bacteria, fungi and plants can produce bioactive secondary metabolites, which are often referred to as natural products. With the rapid development of DNA sequencing technology and bioinformatics, a large number of putative biosynthetic gene clusters have been reported. However, only a few natural products can be detected when isolated species are grown under conventional laboratory conditions, as most biosynthetic gene clusters are not expressed or are expressed at extremely low levels at these conditions. With the rapid development of synthetic biology, advanced genome mining and modification strategies have been reported, and they provide new opportunities for discovery of natural products. This review discusses advances in recent years that can accelerate the design, build, test, and learn (DBTL) cycle of natural product discovery, and prospects trends and key challenges for future research directions.

Ocean surface heat fluxes play a significant role in the genesis and evolution of various marine-based atmospheric phenomena, from the synoptic scale down to the microscale. While in-situ measurements from buoys and flux towers will continue to be the standard in regards to surface heat flux estimates, they commonly have significant gaps in temporal and spatial coverage. Previous and current satellite missions have filled these gaps; though they may not observe the fluxes directly, they can measure the variables needed (wind speed, temperature, and humidity) to estimate latent and sensible heat fluxes. However, current remote sensing instruments have their own limitations, such as infrequent coverage, signals attenuated by precipitation, or both. The Cyclone Global Navigation Satellite System (CYGNSS) mission overcomes these limitations over the tropical and subtropical oceans by providing improved coverage in nearly all weather conditions. While CYGNSS (Level 2) primarily estimates surface winds, when coupled with observations or estimates of temperature and humidity from reanalysis data, it can provide estimates of latent and sensible heat fluxes along its orbit. This paper describes the development of the Surface Heat Flux Product for the CYGNSS mission, its current results, and expected improvements and changes in future releases.

We discuss further details on the concepts of “drug-likeness”, “lead-likeness”, and “natural product-likeness”. The discussion will first focus on natural products as drugs, then a discussion of previous studies in which the complexities of the scaffolds and chemical space of naturally occurring compounds have been compared with synthetic, semi-synthetic compounds and FDA-approved drugs. This is followed by guiding principles for designing “drug-like” natural product libraries for lead compound discovery purposes. We end up by presenting a tool for measuring “natural product-likeness” of compounds and a brief presentation of machine learning approaches and a binary quantitative structure-activity relationship (QSAR) for classifying drugs from non-drugs and natural compounds from non-natural ones, respectively.

(1) Background: Although diagnostic criteria for massive hemorrhage with organ dysfunction such as disseminated intravascular coagulation associated with delivery have been empirically established based on clinical findings, strict logic has yet to be used to establish numerical criteria. (2) Methods: A dataset of 107 deliveries with ≥2,000 g of blood loss, among 13,368 deliveries from nine national perinatal centers in Japan between 2020 and 2023 was obtained. Twenty-three patients had fibrinogen levels <170 mg/dl, which is the initiation of coagulation system failure per our previous reports. Three of these patients had hematuria. We used six machine learning methods to identify the borderline criteria dividing the fibrinogen/fibrin/fibrinogen degradation product (FDP) planes, using 15 coagulation fibrinolytic factors. (3) Results: The boundaries of hematuria development on a two-dimensional plane of fibrinogen and FDP were obtained. If the FDP–fibrinogen/3–60 (mg/dl) value is positive, this indicates hematuria; otherwise, the case is non-hematuria, as demonstrated by the support vector machine method that seemed the most appropriate. (4) Conclusions: The borderline criterion dividing the fibrinogen/FDP plane for patients with hematuria that could be considered organ dysfunction in massive hemorrhage during delivery was obtained using artificial intelligence, and this method seemed to be useful.

This study investigates the synthesis and characterization of zirconium oxide (ZrO₂)-based metal-composites doped with cerium (Ce) and yttrium (Y), using chromium (Cr) and nickel (Ni) as base metals. These constituents were selected for their superior mechanical properties and compatibility with the ceramic phase. High-purity powders were homogenized via high-energy ball milling, followed by cold isostatic pressing (CIP) and sintering in a controlled atmosphere. The sintering process was conducted at various temperatures (850°C to 1350°C) to examine densification, grain growth, and microstructure evolution. Scanning Electron Microscopy (SEM) revealed a homogeneous distribution of phases, with distinct microstructural features attributed to each element at different sintering temperatures. Density measurements using the water immersion method and theoretical calculations demonstrated increased density and reduced porosity with higher sintering temperatures. Vickers hardness testing indicated that hardness improved with increased sintering temperature, peaking around 1150°C due to cerium and yttrium reinforcement within the matrix. Flexural strength tests showed the highest value at 1350°C, with a significant drop in porosity, suggesting enhanced mechanical properties due to efficient doping and phase transformations. Overall, the incorporation of cerium and yttrium significantly improved the mechanical behavior and phase stability of the ZrO₂-Cr-Ni composites, highlighting their potential for advanced engineering applications.

The effects of chemical composition and solidification rate on the solidification behavior of high-Cr white irons were investigated through directional solidification. Increasing the solidi-fication rate in hypoeutectic alloys caused the finer dendrite arm spacing as expected. The eutec-tic structure which formed in the interdendritic region comprised of M7C3 and austenite, how-ever, secondary dendrite arms of hypoeutectic alloys contained a few M7C3 particles that solidi-fied prior to the eutectic structure. The transition from cellular to dendritic solidification oc-curred at a solidification rate between 50 µm/s and 100 µm/s in a near eutectic alloy. In the near eutectic alloy with cellular solidification, a directionally arrayed in-situ composite of M7C3/austenite formed within the cell. Speckle-like feature appeared in the intercellular region due to M23C6 carbide precipitation during subsequent cooling after freezing. Like dendrite arm spacing in hypoeutectic alloys, the inter-speckle spacing and the inter-fibre spacing became finer with increasing solidification rate in the cellular solidification range.

This study investigates the effect of Re addition on the microstructure evolution and oxidation resistance of Co-Cr-Ta-Ti-C alloys. The alloys tested in this study consist of a Co-rich matrix with mixed HCP and FCC phases, together with TaTiC2 and Ti-based carbides. The addition of Re promotes the precipitation and growth of a CoCr-rich σ phase. Differential thermal analysis (DTA) showed that the melting temperatures did not change drastically up to 10 at% Re addition, whereas 15 at% Re addition significantly increased the melting temperature of the alloys. Oxidation tests in air at 1200°C showed that excessive Re content could lead to deterioration in oxidation resistance, mainly due to the accelerated formation of volatile Re oxides.

With the rapid development of industry, Cr has become one of the major heavy metal pollutants in soil, which has caused serious effects on the soil's ecological environment. However, the effects of Cr stress on bacterial communities in plant rhizosphere soils remain unclear. In this study, I. tectorum was selected as the research object, and 16S rRNA high-throughput sequencing technology was used to analyze the effects of Cr stress on the structure and diversity of the bacterial community in the rhizosphere soil of I. tectorum. The results showed that I. tectorum had strong tolerance and enrichment to Cr. However, under Cr stress, the diversity and abundance index of rhizosphere bacteria decreased by 8.5% and 6.8% on average, and the Sobs index decreased by 7.6%. Moreover, the bacterial community changed by 20.1% due to the addition of Cr, further leading to a 15.9% decrease in the common species of the bacterial community, among which Proteobacteria, Actinobacteria, Chloroflexi and Acidobacteriota accounted for more than 74.8% of the total sequence. According to the symbiosis network diagram, it was found that under a two-cultivated pattern, the synergizing effect between dominant bacteria was significantly enhanced, and the soil microenvironment was improved. Redundancy analysis showed that C, N, and P nutrient elements and Cr contents in uncontaminated and contaminated soils were the primary driving factors for the succession of I. tectorum rhizosphere bacterial community, and the response was stronger after Cr(Ⅵ) was added. In conclusion, the results of this study will provide insights into the response of rhizosphere bacterial communities to heavy metal Cr and the interactions between wetland plants and rhizosphere bacteria in wetland phytoremediation.Keywords: Cr stress; rhizosphere bacterial community; Iris tectorum; 16S rRNA sequencing technology; Phytoremediation

Heavy metals are non-biodegradable and have a high toxicity effect to living things which makes their presence in the environment extremely dangerous. The method of handling heavy metals waste by photocatalysis techniques using TiO2/SiO2 composite showed a good performance in reducing harmful pollutants. In this study, SiO2 from Bengkulu beach sand was used as a support material for TiO2 photocatalyst to reduce Cr(VI) and Pb(II) concentrations. SiO2 was obtained through leaching techniques using NaOH as a solvent. The TiO2/SiO2 composite photocatalyst were synthesized using a solvothermal method at 130 °C and then characterized using XRD, FTIR, SEM and PSA. Based on the XRD diffractogram, the synthesized TiO2 showed the anatase structure while the SiO2 showed the amorphous structure. Ti-O-Si bond is defined in the IR spectra, which indicates that the relationship between TiO2 and SiO2 is a chemical interaction. The results of SEM and PSA characterizations show agglomerated spherical (round) particles with a mean particle size of 616.9 nm. The TiO2/SiO2 composite of 7:1 ratio showed the highest photocatalytic activity after 180 minutes of UV irradiation, with a concentration-decrease percentage of 93.77% and 93.55% for for Cr(VI) and Pb(II), respectively.

Dental caries is a public health problem worldwide according to WHO data. Among treatments in pediatric dentistry, prefabricated metal crowns (PMCs) have been one of the most successful options since they were introduced in cases of considerable tooth destruction. Our objective was to detect the presence and concentration of iron (Fe), chromium (Cr), and nickel (Ni) in saliva of patients who require rehabilitation with PMCs, before and after their placement. A quasi-experimental study was performed in 32 patients who attended dental care in a pediatric dentistry clinic at a public university and who required rehabilitation with PMCs. Parametric tests (ANOVA and Pearson correlation) were performed, and a p ≤ 0.05 was considered statistically significant. Statistically significant differences were found when comparing the Ni release before, 1 week, and 1 month after placing the crowns. Similarly, we observed a positive correlation between the number of crowns and Ni release. No tests were performed for Fe and Cr because the amounts of these metals were less than 0.1 ppb, which was not detectable by inductively coupled plasma optical emission spectrometry (ICP-OES). The levels of Fe, Cr, and Ni released were below toxic health levels. Studies are required to evaluate whether this release has negative effects at cellular levels.

Institutional sustainability is a dynamic and multifaceted concept that relies on the contributions of various institutions, including the legal and the scientific system. On the other side, consumers boycotts are an expression of political consumerism by which consumers can use their market power to attain sustainability objectives. This article explores institutional trust on the legal system and trust on scientists as potential drivers for consumers’ boycotts. Using data retrieved from the European Social Survey covering twenty-five countries, the study employs binary logistic regression to assess the importance of institutional trust and other potential drivers of product boycotts in Europe. Results confirm that boycotting behaviour is affected by institutional trust, as well as other individual variables including gender, age and life-cycle effects, education, interest in politics and level of satisfaction with the political system, generalized trust, personal well-being, and consumers’ use and perceptions of information and communication technologies. The results of this study enrich the literature on consumer boycotts and have implications for policymakers involved in sustainability initiatives.

The current paper has examined the effect of both export product diversification and poverty on non-resource tax revenue in developing countries. The analysis has used an unbalanced panel dataset of 111 countries over the period 1980-2014. Based on the Blundell and Bond two-step system Generalized Methods of Moments technique, the empirical analysis has shown interesting findings. Export product concentration and poverty influence negatively non-resource tax revenue over the full sample, but this effect varies across countries in the sample. Furthermore, the effect of export product diversification on non-resource tax revenue performance depends on the level of poverty. It appears that export product diversification influences positively non-resource tax revenue performance in countries that experience lower poverty rates. From a policy perspective, these findings show that policies in favour of diversifying export product baskets and reducing poverty would contribute to enhancing non-resource tax revenue performance in developing countries.

The accuracy of sales prediction models based on the big data of online word-of-mouth (eWOM) is still not satisfied. We argue that eWOM contains heat and sentiments of different product dimensions, which can improve the accuracy of these models. In this paper, we propose a dynamic topic analysis (DTA) framework in order to extract heat and sentiments of product dimensions from the big data of eWOM. Finally, we propose an autoregressive-heat-sentiment (ARHS) model, which integrates heat and sentiments of dimensions into the baseline predictive model. The empirical study in movie industry confirms that heat and sentiments of dimensions can improve the accuracy of sales prediction model. ARHS model is better for movie box-office revenue prediction than other models.

Epigallocatechin gallate (EGCG), the principal catechin in green tea, exhibits diverse therapeutic properties. However, its clinical efficacy is hindered by poor stability and low bioavailability. This study investigated solid particle-in-oil-in-water (S/O/W) emulsions stabilized by whey protein isolate (WPI) and sodium caseinate (NaCas) as carriers to enhance the bioavailability and intestinal absorption of EGCG. Molecular docking revealed binding interactions between EGCG and these macromolecules. The emulsions exhibited high encapsulation efficiencies and augmented EGCG bioaccessibility by 64% compared to free EGCG in a simulated gastrointestinal digestion model. EGCG-loaded emulsions demonstrated minimal cytotoxicity towards Caco-2 cells and facilitated EGCG transport across the intestinal epithelial layer without compromising tight junction integrity. Notably, EGCG-loaded emulsions protected Caco-2 cells against oxidative stress by suppressing intracellular reactive oxygen species generation. The results demonstrate the potential of WPI- and NaCas-stabilized S/O/W emulsions to enhance the bioavailability, intestinal absorption, and bioactivity of EGCG, expanding its applications in functional foods and nutraceuticals.

A two-layer Fe-Cr-Al-Zr surface alloy was synthesized on a zirconium substrate by magnetron sputtering and subsequent low-energy high-current electron-beam (LEHCEB) processing. Thicknesses of the top Fe69Cr20Al11 (at.%) relatively large-grained (~1 µm) and transition Fe-Zr Cr-Al amorphous layers were about 0.7 and 0.6 µm, respectively. In turn, the amorphous layer consisted of two Fe64–54Zr8–22Cr21–17Al8–7 and Fe40–16Zr42–78Cr12–4Al6–2 (at.%) sublayers, differing in both zirconium and iron concentrations in wide ranges, which were separated by another nanocrystalline interlayer. The Fe-Cr-Al-Zr surface alloy serve as a diffusion barrier, preventing interaction of the zirconium substrate with oxygen from an environment. It was thermally stable up to ≈1173 K.

Alternating TiB2-dcMS and Cr-HiPIMS layers are used to fabricate TiB2/Cr multilayer films. In-troducing a 5-nm-thick Cr interlayer deposited under a substrate bias of -60 V produces slight increases of both film hardness and elastic modulus. The TEM observation indicates that the Cr grains favor epitaxially growth on TiB2 interlayer, forming a coherent TiB2/Cr interface. This produces the hardness increasement. Mechanic measurement by using AFM illustrates that the coherent interface increases the elastic modulus of the Cr up to ~280 GPa, which is significantly higher than bulk material.

In this article, we prove an orthogonal decomposition theorem for real inner product gyrogroups, which unify some well-known gyrogroups in the literature: Einstein, M\"{o}bius, Proper Velocity, and Chen's gyrogroups. This leads to the study of left (right) coset partition of a real inner product gyrogroup induced from a subgyrogroup that is a finite-dimensional subspace. As a result, we obtain gyroprojectors onto the subgyrogroup and its orthogonal complement. We construct also quotient spaces and prove an associated isomorphism theorem. The left (right) cosets are characterized using gyrolines (cogyrolines) together with automorphisms of the subgyrogroup. With the algebraic structure of the decompositions, we study fiber bundles and sections inherited by the gyroprojectors. Finally, the general theory is exemplified for the aforementioned gyrogroups.

Technological advancements in the Internet of Things (IoT), unmanned aerial vehicles (UAVs), and novel technological tools have transformed disaster management practices from localized approaches to a global framework. These innovations necessitate a unified understanding and application of diverse methodologies at an international level, ensuring they are accessible and operational across different sectors. This integration is crucial not only for technical personnel but also for medical teams, who play a pivotal role in disaster response and management. By fostering a comprehensive grasp of these methods, we can enhance coordination, efficiency, and effectiveness in addressing disasters on a global scale. The authors aimed to provide a comprehensive overview of emerging techniques that are driving shifts in strategic approaches and treatment technologies. Recognized as a domain of continuous research and development, this overview, by necessity, remains an incomplete snapshot of an evolving field. It highlights the dynamic nature of technological and strategic advancements, underscoring the importance of ongoing investigation and innovation to stay abreast of current trends and future directions. The article also highlights the importance of international collaboration beyond societal and national boundaries A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

(1) Background: Grapes and their associated by-products (as grape pomace, GP) stand out for their polyphenol content, which makes them a source of bioactive compounds with antioxidant capacity. The aim of this research was to determine if the inclusion of 50 g/kg of GP in the diet of hens could enrich egg with antioxidants and to study its effect on internal and external egg quality parameters. (2) Methods: A trial was conducted with two genetic lines of hens, which were fed either a control diet or a diet containing 50 g/kg of GP. Performance, internal and external egg quality, and egg yolk content of vitamins E and A, and gallic acid were determined; (3) Results: In eggs laid by hens fed GP diet, Haugh units and yolk colour score were enhanced, and eggshell became thinner, but without affecting the breaking strength. No dietary effect was observed on vitamin contents in yolk. Higher gallic acid content was observed in yolk of eggs laid by hens fed the GP diet, suggesting that some dietary phenolic compounds could be transferred to the eggs. Hen genetics influenced egg weight, albumen Haugh units, shell thickness and α- and γ-tocopherol concentration in yolks; (4) Conclusions: Dietary inclusion of GP improved the internal quality of eggs, enriching yolks with a phenolic compound, but reduced shell thickness.

In this paper, Fe-Cr-C-N-Al-Y wear-resistant surfacing alloy was prepared by open arc surfacing with self-shielded flux-cored wire. The wear properties of the surfacing alloy were analyzed by MLS-23 rubber wheel wet sand wear tester. The phase composition and microstructure of the surfacing alloy were analyzed by XRD, SEM, EBSD and TEM, and the strengthening mechanism and wear mechanism of the alloy were discussed. The results show that the microstructure of Fe-Cr-C-N-Al-Y surfacing alloy is composed of M + γ-Fe + M7C3 + AlN. When the content of nano-Y2O3 is 0.456wt. %, the formability of the surfacing alloy is the best and the wetting angle is the smallest, which is 50.8°, AlN and M7C3 precipitate the most, and the microstructure grain is the smallest. At this time, the hardness value of the surfacing alloy is up to 62.3 HRC, which is 11.8 % higher than that of the unmodified surfacing alloy. The minimum wear weight loss is 0.125 g, and the wear resistance is increased by 41.86 %. The wear mechanism of surfacing alloy is mainly plastic deformation mechanism, and the material removal process is micro cutting and furrow wear.

Cationised hemp cellulose was prepared by etherification with two quaternary ammonium salts: 3-chloro-2-hydroxypropyl trimethyl ammonium chloride (CHPTAC) and glycidyltrimethylammonium chloride (GTMAC) and examined for (i) the efficiency of Cr(VI) removal under acid mine-drainage (AMD) conditions, and (ii) antibacterial activity. Adsorbents were characterised by electron microscopy, Fourier transform infrared (FTIR), CP-MAS ¹³C nuclear magnetic resonance (NMR) spectroscopy, elemental composition and surface charge. FTIR and solid state ¹³C NMR confirmed the introduction of quaternary ammonium moieties on cellulose. ¹³C NMR also showed that cationisation decreased the degree of crystallisation and lateral dimensions of cellulose fibrils. Nevertheless, 47 % - 72% of Cr(VI) ions were removed from solutions at pH 4, by 0.1 g of CHPTAC and GTMAC-cationised cellulose, respectively. Adsorption kinetics followed the pseudo-second order model and isotherms were best described by the Freundlich and Dubinin-Radushkevich models. When GTMAC-modified cellulose was applied to AMD contaminated water (pH 2.7), however, Cr(VI) uptake removal decreased to 22% likely due to competition from Al and Fe ions. Nevertheless, cationised materials displayed considerable antibacterial effects, reducing the viability of Escherichia coli by up to 45 % after just 3 hours of exposure. Together, these results suggest that cationised cellulose can be applied in the treatment of Cr(VI)-contaminated mine water particularly if pre-treatments to reduce Fe and Al concentrations are applied.

The wealth of data obtained during the past 20 years using Laser-Induced Breakdown Spectroscopy (LIBS) indicates that the technique is very promising to detect small chemical contents of alloying elements. The potential of LIBS was looked more seriously during the past two decades or so as more data were obtained on Aluminum and steel to study the phenomena in the condition of local thermodynamic equilibrium and time-delay between a Q-switch laser and an intensified CCD camera. Since the past decade, some data on compounds were also shown to be useful in determining small concentrations of harmful elements. This manuscript is intended to show that the technique of LIBS performance is very promising in fields such as micro-machining, in alloying element analysis, surface cleaning and environmental applications even with lightweight spectrometers having a relatively low resolution, which can potentially be air-borne.

The fourth industrial revolution, also known as Industry 4.0, has led to an increased transition towards automation and reliance on data-driven innovations and strategies. Companies in the manufacturing sector are heavily integrating Industry 4.0 technologies, including cloud compu-ting, cyber-physical systems (CPS), big data analytics, horizontal and vertical system integration, the internet of things (IoT), and additive manufacturing (3d printing). The interconnected systems and processes have significantly increased operational efficiency, enhanced organizational capacity to monitor and control functions, reduced costs, and improved product quality. One significant way that companies have achieved these benefits is by integrating diverse sensor technologies within these innovations, allowing critical data collection on products, equipment performance, and maintenance. The sensors connect systems and machines, allowing them to communicate and track operations for enhanced operations. While numerous research has been conducted to show the role of sensors in industry 4.0, limited studies show how these innovations can leverage product design to maximize benefits and opportunities. Given the rapidly changing market conditions, Industry 4.0 requires new products and business models to ensure companies adjust to the current and future changes. These requirements call for the evolutions in product design processes to accommodate design features and principles applicable in the current dynamic business environment. This research paper employs a systematic bibliometric literature review (LRSB) methodology to explore and synthesize data on how Industry 4.0 and sensors can leverage product design. The results show that various product design features create opportunities to be leveraged to guarantee the success of Industry 4.0 and sensor technologies. However, the research also identifies numerous challenges that undermine the ongoing transition towards intelligent factories and products.

The electronics industry is a significant contributor to environmental challenges, generating approximately 50 million tons of electronic waste annually and high levels of carbon dioxide emissions throughout the production and disposal of devices. This paper investigates the interplay between reliability and sustainability by analyzing how degraded components affect the environmental footprint of electronic products. Using a board with 215 components as a baseline, we calculate the mean time between failures (MTBF) and compare it to scenarios involving degraded components. Our findings demonstrate that degraded components can reduce MTBF by up to 50%, resulting in higher failure rates, increased electronic waste, and up to 30% more CO2 emissions due to shortened product lifespans. This study underscores the crucial importance of component quality control in the production process to improve both reliability and sustainability. Additionally, the broader economic and environmental impacts of using unchecked components are highlighted, showing their contribution to elevated failure rates, shortened product lifespans, and an estimated 20% increase in e-waste. By adopting a 100% inspection protocol, leveraging advanced technologies, and enforcing stringent material quality controls, manufacturers can significantly enhance the reliability of electronic products while reducing their environmental impact, thus fostering a more sustainable electronics industry.

This qualitative research explores the dynamics of collaborative marketing and supply chain strategies for enhanced product lifecycle management. Through in-depth interviews with industry stakeholders, key themes, challenges, and implications of collaboration emerge. Trust, communication, technology, strategic alignment, and sustainability are identified as critical factors driving successful collaboration. The study highlights the transformative potential of collaboration in driving innovation, efficiency, and customer satisfaction. Despite challenges such as aligning objectives and ensuring data security, collaborative strategies offer significant opportunities for value creation and differentiation. The findings underscore the importance of building trust, leveraging technology, and integrating sustainability considerations in collaborative efforts. Strategic alignment and cultural fit among partners are essential for overcoming differences and achieving common goals. The implications of the research extend to practitioners seeking to enhance collaboration in their organizations and researchers exploring collaborative practices in different industries and contexts. Future research could further explore the impact of collaboration on stakeholder perspectives and outcomes. By addressing challenges and leveraging opportunities, organizations can maximize the benefits of collaborative marketing and supply chain strategies to drive sustainable growth and competitive advantage in today's dynamic business landscape.

Regular regimes of oil and oil products pipelines are studied. The problem is to develop an algorithm of effective pipeline system control that ensures the fulfillment of specified boundary conditions at the system boundaries. The product is pumped in batches, the flow is characterized by a change in temperature and pressure flow parameters over time. The developed solution method uses the principle of decomposition in the sense that each computational iteration is im-plemented in 3 stages, in three nested loops. The inner cycle is connected with the material bal-ance relations, at the next cycle the flow equations are introduced and the fulfillment of the 2nd Kirchhoff's law is monitored. If the flow process is significantly affected by temperature, then an external cycle is also implemented, correcting the solution so that the energy conservation equa-tion is satisfied. In the calculation procedure, some computational difficulties may arise, which consist in choosing an appropriate optimization method. On a specific example, the possibility of using various library programs to solve the problem was checked. The developed method is suita-ble for the analysis of systems of arbitrary topology. Since the method is not time-consuming, it can be recommended for online control of oil and oil products supply systems. The paper opens a new direction in the theory of hydraulic circuits. It uses both traditional methods of continuum mechanics and stochastic models.

The main goal of the Soil Moisture and Ocean Salinity (SMOS) mission over land surfaces is the production of global maps of soil moisture (SM) and vegetation optical depth (τ) based on multi-angular brightness temperature (TB) measurements at L-band. The operational SMOS Level 2 and Level 3 soil moisture algorithms account for different surface effects, such as vegetation opacity and soil roughness at 4 km resolution, in order to produce global retrievals of SM and τ. In this study, we present an alternative SMOS product which was developed by INRA (Institut National de la Recherche Agronomique) and CESBIO (Centre d’Etudes Spatiales de la BIOsphère). This SMOS-INRA-CESBIO (SMOS-IC) product provides daily SM and τ at the global scale and differs from the operational SMOS Level 3 (SMOSL3) product in the treatment of retrievals over heterogeneous pixels. Specifically, SMOS-IC is much simpler and does not account for corrections associated to the antenna pattern and the complex SMOS viewing angle geometry. It considers pixels as homogeneous to avoid uncertainties and errors linked to inconsistent auxiliary data sets which are used to characterize the pixel heterogeneity in the SMOS L3 algorithm. SMOS-IC also differs from the current SMOSL3 product (Version 300, V300) in the values of the effective vegetation scattering albedo (ω) and soil roughness parameters. An inter-comparison is presented in this study based on the use of ECMWF (European Center for Medium range Weather Forecasting) SM outputs and NDVI (Normalized Difference Vegetation Index) from MODIS (Moderate-Resolution Imaging Spectroradiometer). A 6 year (2010-2015) inter-comparison of the SMOS products SMOS-IC and SMOSL3 SM (V300) with ECMWF SM yielded higher correlations and lower ubRMSD (unbiased root mean square difference) for SMOS-IC over most of the pixels. In terms of τ, SMOS-IC τ was found to be better correlated to MODIS NDVI in most regions of the globe, with the exception of the Amazonian basin and of the northern mid-latitudes.

This study reports on the assessment of the growth potential of five edible vegetables which were grown in Cr (VI) spiked soils. The vegetable plants that were used in this study were Vigna angularis, Cicer arietinum, Spinacia oleracea, Amaranthus dubius Thell and Phaseolus vulgaris. Dried ground samples from roots, stems and leaves were analysed for various oxidation states of Cr. The daily intake of chromium (DIC), hazard quotient (HQ) and hazard index (HI) methods were employed to assess the potential human health risks posed by these Cr oxidation states through vegetable consumption. The results showed that Vigna angularis was the only vegetable that germinated in highly concentrated Cr (VI) in the simulated soil (456 mg/kg). The highest bioaccumulation factor of CrT in the roots was found in Cicer arietinum at 3.5 ± 0.51 mg/kg DW. The highest translocation factor in stem was that of Cicer arietinum and Vigna angularis at 1.0 ± 0.00, while Cicer arietinum and Spinacia oleracea translocated highest Cr to the leaf at 2.1 ± 0.21. A child or an adult consuming such contaminated Cicer arietinum were likely to take in between 508 -785 mg/kg/day of total Cr which were above the World Health Organisation guidelines of 220 and 340 mg/kg/day, respectively. The highest HQ was found in Cicer arietinum at 8.7 and 13.4 for adults and children, respectively. The same species of plants had also high HI at 17.4 and 27.2 for adults and children respectively. This indicated that consumers of the edible vegetables grown in Cr (VI) rich soil may be exposed to health risks and the children were more likely to be vulnerable to these adverse effects than the adult.

Seawater contamination is a global challenge due to its hazardous effects on marine organisms and human health. Twenty-three surface seawater samples were collected from Al Lith intertidal area along the Saudi Red Sea coast to evaluate the ecological risks and document the potential sources of Cr, Cd, Fe, Zn, and Pb. Contamination factor (CF), contamination degree (Cd), water quality index (WQI), and heavy metal pollution index (HPI), as well as multivariate tools were applied. The averages of HMs (μg/L) had the following order: Zn (6.616) > Pb (0.284) > Cd and Cr (0.268) > Fe (0.197). Results of CF showed moderate contamination of seawater with Cd and low contamination for Cr, Fe, Zn, and Pb. However, 26.09% of the samples showed considerable contamination for Cd. Average Cd values revealed low contamination for HMs, while 17.39% of the samples showed moderate contamination. HPI average values indicated medium pollution for Al Lith seawater, meanwhile 13 samples reported high pollution. The higher HPI values were reported in samples characterized by higher concentration of HMs, particularly Cd and Zn. Correlation matrix and principal component analysis suggested anthropogenic sources for Pb and Zn, mostly from industrial and agricultural effluents, landfilling and domestic wastewaters, apart from their natural sources.

This qualitative study explores supplier collaboration in e-commerce product development, examining motivations, challenges, strategies, outcomes, and ethical considerations. Through in-depth interviews with stakeholders from diverse e-commerce sectors, the study identifies key themes shaping collaboration dynamics. Motivations include innovation, operational efficiency, and strategic partnerships, driving companies to integrate supplier expertise early in product development. Challenges such as global supply chain complexities, goal misalignment, and communication barriers underscore the need for robust governance and cultural sensitivity. Strategies for success include technology adoption, supplier development programs, and collaborative decision-making, enhancing supply chain visibility and mutual benefits. Effective collaboration yields improved product quality, cost efficiencies, and enhanced customer satisfaction, supporting competitive advantage. Ethical sourcing practices and sustainability initiatives are crucial for maintaining trust and regulatory compliance. Cultural and organizational factors, including leadership support and change management, significantly influence collaboration outcomes. The study concludes with implications for theory and practice, emphasizing the role of innovative strategies and continuous improvement in supplier relationships. Future research could explore digital transformation, sustainability trends, and technological impacts on supplier collaboration in e-commerce. Practical applications include optimizing supply chain strategies to navigate complexities and capitalize on market opportunities.

To remain competitive in the current market, an enterprise must differentiate itself based on higher value propositions. For this purpose, since improving the product or service performance can reach some limits, one potential solution is to move towards new combinations of products and services. This evolution, called servitization, leads to the generation of Product-Service Systems (PSS). Servitization requires not only a clear understanding of enterprise core business but also a clear vision on the prevailing trends and challenges of PSS development from both business and technological points of view. In addition, the evolution path should be aligned with the enterprise strategy. This paper first highlights the notion of symbiotic PSS where Product Systems and Service Systems, and their stakeholders, interoperate seamlessly based on a win-win approach. Then it proposes a PSS Conceptual Framework (PSS-CF) which can be applied in the early stages of servitization to increase the understating of PSS dimensions and to facilitate the prioritization of the servitization investments. The framework dimensions were discussed in several iterations, from both academic and industrial points of view, in the frame of a European research project. Moreover, the applicability of the framework was studied in four different industrial Use-Cases.

Servitization or productization, indicating evolution from product to service economy or vice-versa, can be considered as a successful strategy to gain competitiveness based on novel combination of products and services. To decrease the risks of servitization and to support the sustainable development of its main outcome, being Product Service System (PSS), it is required not only to have a clear and common understanding of the core business and processes but also to share the same definitions on (PSS) concepts as the main outcome of servitization. For this purpose, managers could be supported by abstract models with a limited number and high ratio of known concepts in the early stages of PSS development. Through an extensive literature review on this subject, followed by a structured conceptualization approach and discussions with domain experts, this paper proposes a Conceptual Model (PSS-CM). To validate the results, PSS-CM and its elements were discussed in several iterations, from both academic and industrial points of view, in the frame of a European research project. In the frame of this project, a case study was also performed to illustrate the instantiation of PSS-CM.

Heavy metal contamination is listed among the most alarming threats to the environment and human health. The detrimental effects of heavy metals in the natural environment span from a reduction of biodiversity to toxic effects on marine life - through microplastic born heavy metals -, to impairment of microbial activity in the soil, and to detrimental effects on animal reproduction. A host of different chemical and biological technologies have been proposed to alleviate environmental contamination by heavy metals. Relatively less attention has been paid to the microbial precipitation of heavy metals, as a side mechanism of the most general process of microbially induced calcite precipitation (MICP). This process is currently receiving a great deal of interest from both a theoretical and practical standpoint, because of its possible practical applications in concrete healing and soil consolidation, and its importance in the more general framework of microbial induced mineral precipitation. In this study, we analyse the ability of the marine bacteria Vibrio harveyi in co-precipitating CaCO3 minerals, together with Cd, Cr, Pb, and Zn added in form of nitrates, from solutions containing CaCl2. The precipitated carbonatic minerals were a function of the different heavy metals present in the solution. The process of co-precipitation appears to be rather effective and fast, as the concentrations of the 4 heavy metals were reduced in 2 days by 97.2%, on average, in the solutions.

Mining-induced water contamination remains a significant concern in many regions of the world due to the high concentrations of toxic ions often associated with it. In this study, cellulose-supported ferrihydrite composites (CNF-Fe) were prepared by seeding of ferrihydrite nanoparticles on cellulose nanofibres (CNFs) and employed for the removal of As(III), As(V) and Cr(VI) from contaminated water. The adsorbent was characterized by electron microscopy, gas adsorption, point of zero charge (pH_PZC), X-ray diffractometry (XRD), as well as infrared and Raman spectroscopy. Compared to parent CNFs, CNF-Fe adsorbents had lower crystallinity and a higher surface area: 218.76 m² g^-1. Further, with a pH_PZC of 6.3, CNF-Fe was positively charged at low pH and suitable for adsorption of anions at acidic conditions characteristic of acid mine drainage. In single-ions solutions, the removal efficiency of CNF-Fe was in the order Cr(VI)>As(V)>As(III) (i.e. 0.15, 0.12 and 0.11 mg g^-1 respectively). Adsorption kinetics followed the pseudo second-order model and isotherms were best fitted by the Freundlich, Dubinin-Radushkevich, and Temkin models. However, when CNF-Fe was applied to AMD-contaminated water (pH 2.7), Cr(VI) uptake decreased to ~39% which was likely due to competition from sulphate and selenium ions. Nevertheless, the adsorbent displayed regeneration capabilities with ~98% As and ~45% Cr desorbed after 24 hours of treatment. Together, these results suggest that cellulose supported ferrihydrite composites can be applied in treatment of mine drainage-contaminated water in conjunction with pre-treatments that limit SO₄^2- and selenium concentrations.

This study addresses the urgent need for sustainable protein sources in aquaculture due to the depletion of marine resources and rising costs. Animal protein sources, particularly poultry by-product meal (PBM) and insect exuviae meal, are investigated as viable alternatives to fishmeal (FM). Research confirms the successful replacement of FM with a combination of PBM and insect exuviae meal (up to 50%) in the diet of European seabass without compromising growth, feed conversion, gut health and liver fat content. In particular, growth performance was robust with both PBM formulations, with the 25% PBM diet showing better results. Histological examinations showed good gut and liver health, contradicting the concerns of previous studies. The study emphasizes the importance of holistic analyzes that go beyond growth parameters and include histomorphological investigations. The results show that PBM in combination with insect/exuviae meal is well tolerated by seabass, which is consistent with literature reports of mitigating negative effects on gut health. A detailed analysis of the microbiota revealed a decrease in the Firmicutes/Proteobacteria ratio due to an increase in potentially pathogenic bacteria. However, the formulation containing insect exuviae partially counteracted this effect by preserving the beneficial Lactobacillus and promoting the synthesis of short-chain fatty acids (SCFA), particularly butyrate. Chitin-rich components from insect exuviae were associated with improved gut health, which was supported by increased production of SCFA, which are known for their anti-inflammatory properties. The study concludes that a combination of PBM and insect/exuviae meal can replace up to 50% of FM in the diet of seabass, supporting sustainable aquaculture practices. Despite some changes in the microbiota, the negative effects are mitigated by the addition of insect exuviae, highlighting their potential as a prebiotic to increase fish productivity and contribute to a circular economy in aquaculture.

We present a new method of estimating fitness of countries and complexity of products by exploiting a non-linear non-homogeneous map applied to the publicly available information on the goods exported by a country. The non homogeneous terms guarantee both convergence and stability. After a suitable rescaling of the relevant quantities, the non homogeneous terms are eventually set to zero so that this new method is parameter free. This new map reproduces the findings of the method proposed by Tacchella et al. [1], and allows for an approximate analytic solution in case of actual binarized matrices based on the Revealed Comparative Advantage (RCA) indicator. This solution is connected with a new quantity describing the neighborhood of nodes in bipartite graphs, representing in this work the relations between countries and exported products. Moreover, we define the new indicator of country net-efficiency quantifying how a country efficiently invests in capabilities able to generate innovative complex high quality products. Eventually, we demonstrate analytically the local convergence of the algorithm.

The effect of transition metal substitution for Fe and the structural and magnetic properties of Gd2Fe16Ga0.5TM0.5 (TM=Cr, Mn, Co, Ni, Cu, and Zn) compounds were investigated. Rietveld analysis of X-ray diffraction indicates that all the samples crystallize in the hexagonal Th2Ni17 structure. The lattice parameters: a, c and unit cell volume show TM ionic radii dependence. Both Ga and TM atoms show preferred site occupancy for 12j and 12k sites. The saturation magnetization at maximum room temperature was observed for Co, Ni, and Cu of 69, 73, and 77 emu/g, respectively while minimum value was observed for Zn (62emu/g) doping Gd2Fe16Ga0.5TM0.5. Highest Curie temperature of 590 K was observed for Cu doping which is 15% and 5% and thesehigher than Gd2Fe17 and Gd2Fe16Ga compounds, respectively. The hyperfine parameters viz. hyperfine field and isomer shift, show systematic dependence on the TM atomic number. The observed magnetic and Curie temperature behavior in Gd2Fe16Ga0.5TM0.5 is explained on the basis of Fe(3d)-TM(3d) hybridization. The superior Curie temperature and magnetization value of Co, Ni, and Cu doped Gd2Fe16Ga0.5TM0.5 compounds as compared to pure Gd2Fe17 or Gd2Fe16Ga makes Gd2Fe16Ga0.5TM0.5 a potential candidate for high-temperature industrial magnet applications.

Numerous goods and services are now offered through online platforms due to the recent growth of online transactions like e-commerce. Users have trouble locating the product that best suits them from the numerous products available in online shopping. Many studies in deep learning-based recommender systems (RSs) have focused on the intricate relationships between the attributes of users and items. Deep learning techniques have used consumer or item-related traits to improve the quality of personalized recommender systems in many areas, such as tourism, news, and e-commerce. Various companies, primarily e-commerce, utilize sentiment analysis to enhance product quality and effectively navigate today's business environment. Customer feedback regarding a product is gathered through sentiment analysis, which uses contextual data to split it into separate polarities. The explosive rise of the e-commerce industry has resulted in a large body of literature on e-commerce from different perspectives. Researchers have made an effort to categorize the recommended future possibilities for e-commerce study as the field has grown. There are several challenges in e-commerce, such as fake reviews, frequency of user reviews, advertisement click fraud, and code-mixing. In this review, we introduce an overview of the preliminary design for e-commerce. Second, the concept of deep learning, e-commerce, and sentiment analysis are discussed. Third, we represent different versions of the commercial dataset. Finally, we explain various difficulties facing RS and future research directions.