A premise of statistical learning research is that learners attend to and learn the frequencies of repeating or co-occurring elements in the input. When the input is a series of words, participants readily learn the frequencies of phoneme sequences, that is, to learn phonotactic frequencies. Inherent to the concepts of both frequency and phonotactics is order, or the temporal structure of the input. Order is similarly inherent to statistical learning, yet the effect of order on statistical learning is not well understood. In the present study, adult participants learned the relative frequencies of eight item-medial consonant sequences, for example, the /mk/ in /nʌmkət/. Across five ordering conditions, both familiarization and test stimuli were independently ordered and randomized, thus allowing for a relatively broad search for order effects in an established statistical learning paradigm. Participants learned the target frequencies equivalently across the five ordering conditions, indicating no modulating effect of order. Nevertheless, participants also approached the task by applying idiosyncratic, structured orders to their responses. The result is an unexpected but robust effect of order. Both the results and the design of the study also allow for increased integration of statistical learning with memory and other aspects of cognition.

Mixed reality technology is being increasingly used in cultural heritage attractions to enhance visitors’ experience. However, how the characteristics of mixed reality affect satisfaction and brand loyalty has not been explored in previous research. The purpose of this study is to identify factors affecting satisfaction with mixed reality experiences at cultural and artistic visitor attractions and their influence on brand loyalty, which is connected with management performance. We propose a theoretical model based on brand equity theory in the context of mixed reality experience. Survey data were gathered from 251 respondents visiting a cultural and artistic visitor attraction in Seoul, Korea using a stratified sampling method. PLS-SEM was employed for the data analysis. The results suggest that the characteristics of mixed reality (interactivity, vividness) not only influence the affective aspects (perceived immersion, perceived enjoyment) of visitors’ experience, but also positively affect brand awareness, brand association, and brand loyalty.

Background: Since the advent of virtual reality (VR), it has been used in medical education for surgical training and anatomy teaching. Recently, other modalities of extended reality (XR) such as augmented reality (AR) and mixed reality (MR) has also made its way into medical education. Although there has been research validating XR’s use in medical education, there have been few studies on the research trends of the different XR modalities. The paper aims to compare the research trends of the XR modalities in general and in terms of the medical fields studied and outcomes measured. Methods: Web of Science was searched, and preliminary data was extracted to analyze the general trend. Inclusion and exclusion criteria were then applied, and finalized articles were analyzed and grouped based on the medical field studied and outcomes measured. Results: 31 articles on VR, eight on AR and one on MR were included in the final analysis. We found that there is increasing research in VR since 1990 and AR since 2008. The research in MR is constant. Most of the papers on VR studied endoscopic surgery and anatomy whereas AR studied mostly anatomy and endovascular procedures. Using Miller’s prism of clinical competence, the competency measured most for VR and AR is “show”. Discussion and conclusion: Advancement in computing, communication and display technologies since 1990 may contribute to the increase in research on VR whereas the ubiquity of smartphone since 2008 may explain the increase in research on AR. Although both VR and AR are used in surgical training and anatomy teaching, we found possible strengths of VR in counseling and AR in practical skills. The competency "show" was measured most as most of the papers were on surgery, and the XR simulators used can capture surgical parameters

Functional mobility assessments (i.e., Timed Up and Go) are commonly used clinical tools for mobility and fall risk screening in the aging population. In this work, we proposed a new Mixed Reality (MR)-based assessment that utilized a Microsoft HoloLens^TM headset to automatically lead and track the performance of functional mobility tests, and subsequently evaluated its validity in comparison with reference inertial sensors. Twenty-two healthy adults (10 older, 12 young) participated in this study. An automated functional mobility assessment app was developed based on the HoloLens platform. Mobility performance was recorded with the headset built-in sensor and validated with reference inertial sensor (Opal, APDM) taped on the headset and lower back. Results indicate vertical kinematic measures by HoloLens was in good agreement with the reference sensor (Normalized RMSE ~ 10%). Additionally, the HoloLens-based test completion time was in perfect agreement with clinical standard stopwatch measure. Overall, our preliminary investigation indicates that it is possible to use an MR headset to automatically guide users to complete common mobility tests with good measurement accuracy, thus it has great potential to provide objective and efficient sensor-based mobility assessment.

Scientific studies had shown that mixed forests of silver fir (Abies alba Mill.) and European beech (Fagus sylvatica L.) provide higher ecosystem services than monospecific forests. Mixed forests are known for their high resilience to climate change impacts and superior biodiversity compared to monospecific forests. In many countries, promotion of mixed forests in forest management is becoming a government policy since they can contribute to fulfill the Sustainable Development Goals set by the United Nation, respectively Goal 13 and 15. However, not much is known about public perceptions on mixed forests compared to monoculture forests. Our study on ecosystem services provided by mixed and monospecific forests in southwest Germany fill this gap. Based on a survey with 520 valid responses we analyzed people’s perception on 18 different supporting, cultural, regulating and provisioning ecosystem services measured by Likert scale. Stepwise regression analyses show relations between social profiles (gender, age, education, profession) and preferences on respondents’ perceptions. Our findings show that people perceive that mixed forests provide better cultural, regulating and supporting ecosystem services than monospecific forests of fir and beech whereas provisioning services were perceived as being equally or better provided by monospecific forests. Significant effects towards a positive perception on ecosystem services provided by mixed forests were mainly influenced by the perceived abundance of old trees, feeling of pleasantness in mixed forests, age, profession, and education. Our findings indicate that there is a high public support for the promotion of silver fir and beech mixed forests in Southwest Germany.

The streptavidin and biotin interaction is one of the strongest non-covalent interactions in nature. As a result, this non-covalent interaction has been of great interest when it comes to biochemical assays, diagnosis of diseases, and cell-targeted drug delivery. Past research has proven that biotin-streptavidin is useful in biosensor development to improve the detection of a system when conjugated to nanoparticles. This study aims to prove that streptavidin-coated nanoparticles can be conjugated with biotinylated antibodies using the primary-secondary method to non-invasively detect adenocarcinoma in-vitro. While the use of nanoparticles is not uncommon to the diagnostics area of scientific research, the technique this research aims to investigate is a non-invasive one, utilizing the primary-secondary method. Specifically, the increased stability of fluorophores when bound to antibodies as opposed to nanoparticles directly can be indicative of the particles conjugated through the primary-secondary method’s ability to specifically bind to overexpressed transferrin receptors in the A549 cell line. In this paper, streptavidin-coated nanoparticles were conjugated with biotinylated anti-transferrin receptor antibodies and AlexaFluor-488 secondary antibodies were used to enable fluorescence-based detection. The efficiency of these particles were observed quantitatively through a plate reader and qualitatively through a fluorescence microscope. I demonstrated that these nanoparticles are able to specifically bind to the target proteins in this study. These findings contribute to the field of nanoparticle diagnostics and can be extended to different diseases caused by overexpression of proteins in the future. While this was conducted in-vitro, conjugates can be prepared to detect cancer in-vivo and can be tested with magnetic relaxometry in the future.

The complexity of modern power grids, exacerbated by integrating diverse energy sources, espe-cially inverter-based resources (IBRs), presents a significant challenge to grid operation and plan-ning since linear models fail to capture the intricate IBR dynamics. This study employs the Sparse Identification of Nonlinear Dynamics (SINDy) method to bridge the gap between theoretical un-derstanding and practical implementation in power system analysis. It introduces the novel Volterra-based Nonlinearity Index (VNI) to examine system-level nonlinearity comprehensively. The distinction of dynamics into first-order linearizable terms, second-order nonlinear dynamics, and third-order noise elucidates the intricacy of power systems. The findings demonstrate a fundamental shift in system dynamics as power sources transit to IBRs, revealing system-level nonlinearity compared to module-level nonlinearity in conventional syn-chronous generators. The VNI quantifies nonlinear-to-linear relationships, enriching our comprehension of power system behavior and offering a versatile tool for distinguishing between different nonlinearities and visualizing their distinct patterns through the proposed VIN profile.

Artificial intelligence algorithms have gained widespread adoption in the field of air conditioning load prediction. However, their prediction accuracy is substantially influenced by the quality of training samples. Training samples that lack relevance to the predicted moments can introduce interference into the neural network's learning process, potentially leading to a state of local convergence during its iterative process. This, in turn, diminishes the robustness and generalization capabilities of the prediction model. To enhance the prediction accuracy of air conditioning load prediction models based on artificial intelligence algorithms, this study presents an artificial intelligence algorithm prediction model based on the method of sample similarity sample screening. Initially, the comprehensive similarity coefficient between samples is computed using the gray correlation analysis method, enriched with enhancements in information entropy. Subsequently, a subset of closely related samples is extracted from the original dataset and employed as the training dataset for the artificial intelligence prediction model. Finally, the trained artificial intelligence algorithm prediction model is deployed for air conditioning load prediction. The results illustrate that the method of screening training samples based on sample similarity effectively improves the prediction accuracy of BP neural network (BPNN) and extreme learning machine (ELM) prediction models. However, it is important to note that this approach may not be suitable for genetic algorithm BPNN (GABPNN) and support vector regression (SVR) models.

Deep eutectic solvents have emerged as a greener alternative and have attracted so much interest in the last two decades. This paper present alternative synthesis method to classical heating-stirring. The ultrasound method is one of the most promising syntheses DESs in terms of yield and energy. So, ultrasound synthesis method was studied to obtain hydrophobic (Aliquat 336: L-Menthol 3:7; Li-docaine: decanoic acid 1:2) and hydrophilic DESs based on Choline chloride and urea, ethylene glycol and oxalic acid. The physical characterization of DESs by comparison of FTIR spectra no show difference between DESs obtained by heating-stirring and ultrasound synthesis methods. The RMN spectra of the DESs obtained by heating-stirring revealed the DESs formation. Density and viscosity properties of DESs were evaluated. The density values are similar for both synthesis methods. However, lower viscosity values are obtained to the hydrophilic DESs prepared by ul-trasound methods.

Influence lines are indispensable tools for visualizing and analyzing the dynamic variations in force factors induced by external loads within structural systems. Among these methods, the energetic approach stands as a widely employed technique, rooted in the fundamental principle of work done by changing forces. It enables engineers to transform intricate structural analysis problems into manageable ones by exploring the first derivatives of the radius vector, which represent infinitesimal velocity or displacement. This methodology seamlessly interweaves concepts such as carrier motion, relative motion, and the construction of mechanisms, bringing fresh perspectives to the analysis of influence lines. In this article, we explore the nuances of these novel methods within the domain of mechanism theory. Through comprehensive elaboration and analysis, we elucidate the underlying principles and practical applications of Jacobian contours. Crucially, we introduce a straightforward, rapid, and programmable approach, promising to revolutionize influence line determination in structural engineering. This method bridges the gap between theory and practice, offering the potential to elevate the accuracy, efficiency, and adaptability of influence line analysis. As such, it represents a significant advancement in the field of structural and applied mechanics, with broad-reaching implications for engineering practice.

With the improvement in medical quality, cold mechanical rehabilitation equipment can no longer meet the psychological needs of the physically handicapped. Therefore, design for behaviour change should be viewed as a strategy for enabling lifestyle changes as soon as possible. Although how to use equipment to assist physically disabled people in hydrotherapy rehabilitation is the primary design goal, the psychological feelings of users are also one of the focuses of this study. Besides, coupled with the large-scale spread of the Coronavirus Disease (COVID-19) in the past two years. People's living habits are also forced to change, many activities that people are used to doing outdoors are being slowly completed at home. During the epidemic, it is very dangerous and inconvenient for users who need to go to institutional rehabilitation regularly. Hence, it is urgent to change past usage habits and places. In this study, a personal multi-functional hydrotherapy bucket is designed. In addition to not having to use a public spa with other people to reduce the risk of contracting the Coronavirus Disease, it can be easily placed at home by reducing its size. According to market research, it is known that the current domestic hydrotherapy buckets on the market usually only have a single function. The large medical hydrotherapy pools are not only rare in Taiwan, but this kind of equipment also takes up a lot of space. Various factors have resulted in a relatively low market share of hydrotherapy pools compared to other rehabilitation equipment. In order to take into account, the physical and psychological needs of the physically disabled, this research focus on the design of a multi-functional but small-sized hydrotherapy bucket. Taking the convenience of entering and leaving the bucket as the starting point to improve the shortcomings of the existing products, on the other hand, because most users are inconvenient to move, safety is also the focus of the design to reduce the occurrence of accidents and injuries. This study is based on the systematic design methodology of concurrent design to obtain product design results. Firstly, conduct market research and select products from different manufacturers for analysis and comparison. Through functional analysis and sorting out the problem points, the TRIZ theory and the morphological diagram method are used to find the solution to the problem. Finally, the best design scheme is obtained by the PUGH method. Besides, construct a 3D model to present the design concept that meets the design goals. The research results are hoped to be used as a reference for designing and developing related products, thereby increasing the home's multifunctional hydrotherapy buckets' market share.

In this lecture notes, we will introduce Asymptotics, then we will give a short glimpse on Perturbation theory (regular versus singular), which plays a crucial role especially in theoretical physics. Our goal is to find Asymptotic series that approximates the values of integrals depending on some parameter or the solutions of differential equations. These methods that lead to obtain more effective algorithms of numerical evaluation are called: Asymptotic Methods.

Video super-resolution, which utilizes the relevant information of several low-resolution frames to generate high-resolution images, is a challenging task. One possible solution called sliding window method tries to divide the generation of high-resolution video sequences into independent sub-tasks, and only adjacent low-resolution images are used to estimate the high-resolution version of the central low-resolution image. Another popular method named recurrent algorithm proposes to utilize not only the low-resolution images but also the generated high-resolution images of previous frames to generate the high-resolution image. However, both methods have some unavoidable disadvantages. The former one usually leads to bad temporal consistency and requires higher computational cost while the latter method always can not make full use of information contained by optical flow or any other calculated features. Thus more investigations need to be done to explore the balance between these two methods. In this work, a bidirectional frame recurrent video super-resolution method is proposed. To be specific, a reverse training is proposed that the generated high-resolution frame is also utilized to help estimate the high-resolution version of the former frame. With the contribution of reverse training and the forward training, the idea of bidirectional recurrent method not only guarantees the temporal consistency but also make full use of the adjacent information due to the bidirectional training operation while the computational cost is acceptable. Experimental results demonstrate that the bidirectional super-resolution framework gives remarkable performance that it solves the time-related problems when the generated high-resolution image is impressive compared with recurrent-based video super-resolution method.

Currently, electromagnetic and radar methods are the most common non-destructive tests for non-destructive rebar location in structures.. Both methods have some advantages, disadvantages and limitations. This article is an attempt to describe possibilities of particular methods with emphasizing their advantages and limitations. The first stage of tests included results from tests conducted on a lintel beam made of autoclaved aerated concrete (AAC) and reinforced with small-diameter rebars and rebars placed close to each other. The second stage consisted in testing nine lightweight concrete specimens, each with three bars having a diameter of 10, 16 and 20 mm at three different space arrangements, to determine the effect of bar diameter and spacing on the measurement accuracy. The reinforcement of lintels and specimens was tested with two different electromagnetic scanners and a ground-penetrating radar (GPR) device. Received results from direct tests were compared with results from non-destructive tests (NDT). NDT tests conducted in such an element were found to perform the correct assessment of the concrete cover, and at the same time to give ambiguous results with reference to shape and number of rebars.

This paper presents a theoretical evaluation of the prices of mixed briquettes produced from co-conut shells (CCS), banana peels (BNP), rattan waste (RWT), and sugarcane bagasse (SGC), and, on the other hand, an analysis of the economic viability of their use as a replacement for conventional household fuels (Liquefied Petroleum Gas, fuelwood, and wood charcoal) in house-holds in Cameroon. The investigation was carried out using the Life Cycle Cost method on a typical household over a ten-year period with annual cooking energy requirements of 950 kWhth. The SGC-CCS and SGC-RWT mixed briquettes with a ratio higher than 7.75% and 11.1%, respectively, have prices lower than 0.063 €/kWhth. The Present Value of the Net Benefit is posi-tive for the use of SGC-CCS and SGC-RWT mixed briquettes. The results show that by making the right mixes of residues, it is possible to obtain biomass briquettes that are less expensive than conventional fuels.

Nowadays, there are implemented devices whose purpose is to perform massive computations by saving resources at the time they reduce the latency of arithmetic operations. These devices are usually GPUs, FPGAs and other specialised devices such as "Coral". Neural networks, digital filters and numerical simulators take advantage of the massively parallel operations of such devices. One way to reduce the amount of resources used is to limit the size of the registers that store data. This has led to the proliferation of numeric formats with a length of less than 32 bits, known as short floating point or SFP. We have developed several SFP’s for use in our neural network accelerator design, allowing for different levels of accuracy. We use a 16-bit format for data transfer and different formats can be used simultaneously for internal operations. The internal operations can be performed in 16-bit, 20-bit and 24-bit. The use of registers larger than 16-bit allows the preservation of fractional information while increasing precision. By leveraging some of the FPGA’s arithmetic resources, our design outperforms designs implemented from scratch and is competitive with specialized arithmetic circuits already implemented in the FPGA.

Being able to complete the production of the product project on time is the prerequisite to win more tasks, many enterprises have begun to study intelligent scheduling algorithms to achieve dynamic control of the total project duration. However, the production operation time of products is highly volatile, and it is impossible to predict the possible operation time of future products. In the actual production environment, we often encounter extreme situations such as mixed production lines, multiple varieties, variable batches, etc. A dynamic optimization CPM model in the ERP/MES system with the attention mechanism (EMA-DCPM) will collect, extract and predict the operation time through artificial intelligence technology, and it can accurately predict the exact operation time of a batch of products that have not yet been produced. Through experiments, our algorithm can realize the production scheduling and get more than 200% better precision than former algorithms and realize dynamic optimization of complex projects.

In order to understand the impact of lithologic heterogeneity of continental mixed fine-grained sedimentary rocks on reservoir brittleness in western Qaidam basin, the mechanical properties of the rocks and their correlation with mineral composition and petrographic characteristics were studied by measns of mineralogy, petrography and triaxial stress test. The results show that the reservoir rocks can be divided into 5 different types according to the mechanical properties of the reservoir (characteristics of stress-strain curves), among them Type I and III belong to similar elastoplastic failure model, type II shows a special pulse failure mode for plastic material, type IV shows a failure mode of mixed characteristics, and type V exhibits a typical plastic failure model. The correlation between minerals and mechanical properties indicates that quartz and feldspar, which are often considered brittle minerals, do not contribute much to the brittleness of continental fine-grained sedimentary rocks. The main minerals affecting reservoir brittleness are dolomite and clay minerals, and their contributions to reservoir brittleness are positive and negative, respectively. The petrographic analysis results prove that the abnormal correlation between rock mechanical properties and quartz and feldspar is caused by the different rock fabrics. When dolomite forms a rock skeleton, it typically exhibits greater strength, brittleness and physical properties than other minerals. Based on the results, a brittleness evaluation standard for continental fine-grained sedimentary rock reservoir is proposed, and the validity of the standard is verified by the spatial correlation between the lithology probability model and the micro-seismic monitoring data, indicating that the spatial heterogeneity of dolomite-rich rock is the main controlling factor for the development of ‘sweet spot’ in the Cenozoic continental fine-grained sedimentary rock reservoir in the Western Qaidam Basin.

Research rarely explores LGBTQ+ youth bullying in the context of culture-specific outcomes (e.g., LGBTQ+ identity development) and what can mitigate the impact of peer stressors. This study used a concurrent mixed methods design to explore how experiences of peer victimization predicted LGBTQ+ youth’s identity development (i.e., stigma sensitivity, concealment motivation, and difficult process) and whether social support and outness served as protective, moderating factors. The mixed-methods approach provides a culture-specific context via qualitative inquiry to inform whether the quantitative findings align with how youth qualitatively discuss their experience of bullying, negative outcomes, and social support. Our sample consisted of 349 LGBTQ+ youth 14-17 years old who completed a survey (quantitative sample), and a subset of 39 LGBTQ+ youth who completed a semi-structured interview (qualitative sample). Our quantitative findings indicated that greater overall peer victimization was positively related to LGBIS-revised subscales of stigma sensitivity, concealment motivation, and difficult process, where both outness and social support moderated such relations. Qualitatively, victimized youth also reported stigma sensitivity and concealment motivation, while also endorsing how being out and having a support system played a role in their experience of being victimized. These qualitative findings align with our quantitative findings that classmate support mitigated the effects of peer victimization on difficulty of coming out. Implications for practitioners and researchers are provided.

The copper end paste used in multilayer ceramic capacitors sintered in nitrogen atmosphere will lead to carbon residue of organic vehicle, which will lead to the reduction of electrode conduc-tivity and high scrap rate. With an attempt to leave no residue in the sintering, the compatibility of solvents and thickeners should be improved because it has an important influence on the hi-erarchical volatilization and carbon residue of organic vehicles. In this work, the volatility of different solvents was compared and several solvents were mixed in a definite proportion to prepare an organic vehicle with polyacrylate resins. The hierarchical volatility and solubility parameters of mixed solvents were adjusted effectively by changing proportions of different components, the thermogravimetric curves of resins and organic vehicles were measured by thermogravimetric analyzer, the effect of solubility parameter on the dissolvability of resins in the solvent and the residual of organic vehicles were studied. Results showed that the hierar-chical volatilization of solvents can be obtained by mixing different solvents; the intrinsic vis-cosity of the organic vehicle is higher and the thermal decomposition residue of polyacrylate resins is lower when the solubility parameters of mixed solvents and polyacrylate resins are closer. The low residual sintering of organic vehicles can be achieved by using the mixed solvent with hierarchical volatility and approximate solubility parameters as resins.

Any photon, regardless of its origin, carries the same optical field profile. This feature and the quantum Rayleigh emissions generate temporally discrete groups of several photons in a resonant cavity incorporating one single quantum dot. A periodic stream of single photons is distorted by high-finesse optical cavities and the quantum Rayleigh spontaneous emission in a beam splitter. Groups of photons emerge from interferometric filters because of multiple internal reflections.

A novel geometric interpretation of the Minkowski metric is provided, which offers a different and more intuitive approach to phenomena in special relativity. First it is shown that a change of basis in Minkowski space is the equivalent of a change of basis in Euclidean space if a basis element is replaced by its dual element, constituting a mixed basis set. The methodology of the proof includes infinitesimal changes of basis using the Lie-algebras of the involved groups. As a consequence, a direct mapping between Euclidean and Minkowski space is defined. Second, a measuring device called a local, flat observer is defined in Euclidean space and it is shown, that this device uses a mixed basis when measuring distances. Combining these steps, it is concluded that a local, flat observer in a four-dimensional Euclidean spacetime measures a Minkowski spacetime.

In this contribution, a method based on a solid solution theory of clathrate hydrate for multiple cage occupancy, host lattice relaxation and guest-guest interactions has been presented to estimate hydrate formation conditions of binary and ternary gas mixtures. We have performed molecular modeling of structure, guest distribution, and hydrate formation conditions for the CO₂ + CH₄, and CO₂ + CH₄ + N₂ gas hydrates. In all considered systems with and without N₂, at high and medium content of CO₂ in the gas phase we have found that CO₂ is more favorable to occupy clathrate hydrate cavities than CH₄ or N₂. Addition of N₂ to the gas phase increases ratio concentration CO₂ in compressing with concentration CH₄ in clathrate hydrates and makes gas replacement more effective. The mole fractions of CO₂ in CO₂ + CH₄ + N₂ gas hydrate rapidly increases with the growth of its content in the gas phase. And the formation pressure of CO₂ + CH₄ + N₂ gas hydrate rises in comparison with the formation pressure of CO₂ + CH₄ gas hydrate. Obtained results agree with the known experimental data for simple CH₄, CO₂ gas hydrates and mixed CO₂ + CH₄ gas hydrate.

As part of the ongoing screening research for local edible plants in Thailand, Petroselinum crispum fruit oil was considered as a potential bioinsecticide with proven antimosquito activity against both the pyrethroid susceptible and resistant strains of Aedes aegypti. Due to the comparative mosquitocidal efficacy on these mosquitoes, this plant oil is promoted as a natural alternative and attractive candidate for further study in monitoring resistance of mosquito vectors. Therefore, the aim of this study was to evaluate the impact of P. crispum oil on the biochemical characteristics of the target mosquito larvae of Ae. aegypti, by determining quantitative changes of key enzymes responsible for xenobiotic detoxification, including glutathione-S-transferases (GSTs), α- and β-esterases (α-/β-ESTs), acetylcholinesterase (AChE), acid and alkaline phosphatases (ACP and ALP) and mixed-function oxidases (MFO). Three populations of Ae. aegypti, comprising the pyrethroid susceptible Muang Chiang Mai-susceptible (MCM-S) strain and the pyrethroid resistant Pang Mai Dang-resistant (PMD-R) and Upakut-resistant (UPK-R) strains, were used as test organisms. Biochemical study of Ae. aegypti larvae prior to treatment with P. crispum oil revealed that apart from AChE, the baseline activity of most defensive enzymes, such as GSTs, α-/β-ESTs, ACP, ALP and MFO, in resistant UPK-R or PMD-R, was higher than that determined in susceptible MCM-S. However, after 24-h exposure to P. crispum oil, the pyrethroid susceptible and resistant Ae. aegypti showed similarity in biochemical features, with alterations of enzyme activity in the treated larvae, as compared to the controls. A significant increase in the activity levels of GSTs, α-/β-ESTs, ACP and ALP was recorded in all strains of P. crispum oil-treated Ae. aegypti larvae, whereas MFO and AChE activity in these mosquitoes was decreased. The recognizable larvicidal capability on pyrethroid resistant Ae. aegypti, and the inhibitory effect on AChE and MFO, emphasized the potential of P. crispum oil as an attractive alternative application for management of mosquito resistance in current and future control programs.

In this paper we study the class of mixed-index time fractional differential equations in which different components of the problem have different time fractional derivatives on the left hand side. We prove a theorem on the solution of the linear system of equations, which collapses to the well-known Mittag-Leffler solution in the case the indices are the same, and also generalises the solution of the so-called linear sequential class of time fractional problems. We also investigate the asymptotic stability properties of this class of problems using Laplace transforms and show how Laplace transforms can be used to write solutions as linear combinations of generalisedMittag-Leffler functions in some cases. Finally we illustrate our results with some numerical simulations.

The aim of this work is to present a design approach of a Shock-Induced Combustion Ramjet (Shcramjet) inlet, and present its optimization in terms of the flow and geometrical parameters. The flow properties of mixed compression type inlet of a Shcramjet are examined using analytical and numerical techniques. The geometries obtained with variations in the wedge angles, length, height and cowl lip positions are used to study the flow characteristics of inlet, identifying bow shock temperature ratio as the optimization parameter. The two-dimensional geometries of two-shock and three-shock inlet models designed analytically for shock-on-lip condition at Mach 12.5 and an altitude of 32.5 km are numerically simulated in OpenFOAM CFD Toolbox. A density based compressible CFD solver based on central upwind schemes of Kurganov and Tadmore is used to solve 2D inviscid Euler equations. The inlet total pressure recovery is expressed as a function of temperature ratios of compression shocks, and is found to have a maxima at a bow shock temperature ratio at the design condition when the bow and external shocks have equal strengths. The effect of considering the flow to be calorically imperfect is studied numerically, and the deviation from the analytical design is presented.

Initial periods of adsorption kinetics play an important role in estimating the initial adsorption rate and rate constant of adsorption process. Several adsorption processes rapidly occur, and the experimental data of adsorption kinetics under the initial periods can contain potential errors. The pseudo-second-order (PSO) kinetic model has been popularly applied in the field of adsorption. The use of the nonlinear optimization method to obtain the parameters of the PSO model can minimize error functions during modelling compared to the linear method. However, the nonlinear method has limitations in that it cannot directly recognize potential errors in the experimental points of time-dependent adsorption, especially under the initial periods. In this study, for the first time, the different linear types (Types 1–6) of the PSO model are applied to discover the error points under the initial periods. The result indicated that the fitting method using its linear equations (Types 2–5) is really helpful for identifying the error (doubtful) experimental points from the initial periods of adsorption kinetics. The imprecise points lead to low adjusted R2 (adj-R2), high reduced χ2 (red-χ2), and high Bayesian information criterion (BIC) values. After removing those points, the experimental data were adequately fitted with the PSO model. statistical analyses demonstrated that the nonlinear method must be used for modelling the PSO model because its red-χ2 and BIC were lower than the linear method. Type 1 has been extensively applied in the literature because of its very high adj-R2 (0.9999) and its excellent fitting to experimental points. However, its application should be limited because the potential errors from experimental points were not identified by this type. For comparison, the other kinetic models (i.e., pseudo-first-order, pseudo-nth-order, Avrami, and Elovich) are applied. The modelling result using the nonlinear forms of those models indicated that the fault experimental points from the initial periods were not detected.

The Failure Mode and Effect Analysis (FMEA) is often used to improve a system's reli-ability. This paper proposes a new approach that aims to overcome the most critical defects of the traditional FMEA. This new methodology combines the Entropy and Best Worst Method (BWM) methodology with the EDas and System Dynamics, FMECA: The EN-B-ED Dynamic FMECA. The main innovation’s point of the proposed work is the presence of an unknown factor (Cost), that allows to obtain an objective weighted factor, a risk index when a machine failure occurs. The criticality analysis has been carried out using software (Vensim PLE x64) to simulate System Dynamics models to identify corrective actions and evaluating the possible implementation of these ac-tions. The methodology proposed is applied to a case study in a relevant Italian com-pany in the agri-food sector.

The development of computational acoustics allows simulation of sound generation and propagation in complex environment. In particular, meshfree methods are widely used to solve acoustics problems through arbitrarily distributed field points and approximation smoothness flexibility. As a Lagrangian meshfree method, smoothed particle hydrodynamics (SPH) method reduce the difficulty in solving problems with deformable boundaries, complex topologies, or multiphase medium. The traditional SPH method has been applied in acoustic simulation. This study presents the corrective smoothed particle method (CSPM), which is a combination of SPH kernel estimate and Taylor series expansion. The CSPM is introduced as a Lagrangian approach to improve accuracy in solving acoustic wave equations in the time domain. Moreover, a boundary treatment technique based on the hybrid meshfree and finite difference time domain (FDTD) method is proposed to represent different acoustic boundaries with particles. To model sound propagation in pipes with different boundaries, soft, rigid, and absorbing boundary conditions are built with this technique. Numerical results show that the CSPM algorithm is consistent and demonstrates convergence with exact solutions. Main computational parameters are discussed, and different boundary conditions are validated to be effective for benchmark problems in computational acoustics.

This article presents the possibilities of using ferrite absorption material for shielding rooms with medical devices in order to additionally protect them against the limits of the electric component of the E field, which are up to 61 V/m. These values may appear in connection with the currently launched 5G system operating in the high-band frequency range, i.e. 28 GHz and 38 GHz, and may cause negative effects on the operation of medical devices. The possibilities of using ferrite absorption material for shielding rooms with medical devices were determined based on the results of measurements of the electrical properties of the ferrite material performed using two methods: the reflection method and the free space method. In the article, the complex electrical permittivity and complex magnetic permeability were determined for a ferrite plate based on measurements of the reflection coefficient and the transmission (attenuation) coefficient. The presented calculation and measurement results were used to show the properties of the ferrite material in the frequency range from 15 GHz to 45 GHz and to show the possibility of using it for shielding rooms as a material absorbing electromagnetic waves in this frequency range.

Comparison with conventional reservoirs, the prediction of pressure in ultra-deep tight sandstone formations is difficult. The prediction of seismic pressure is more challenging than well logging pressure prediction. The main methods for seismic pressure prediction include equivalent depth method, Eaton method, Fillippone formula, and its modified versions. Among them, the Eaton method is widely used and has good effectiveness. However, this method relies on difficult-to-obtain normal compaction trend line, which leads to low prediction accuracy in space. To address this issue, a method combining the Eaton method and Collocated cokriging is proposed. The Eaton formula is used to predict formation pressure at the well, with compressional wave velocity as the covariate for predicting the main variable, formation pressure. By simulating the shear wave velocity based on seismic compressional wave velocity, the influence of various parameters on the prediction results is analyzed, and the accuracy of this method is verified by comparing it with other methods. The proposed method is then applied to predict formation pressure in the ultra-deep formations of the Junggar Basin. The simulation results show that the Collocated cokriging method achieves higher planar accuracy and better matches the experimental expectations in terms of prediction results. The application results also demonstrate the scientific effectiveness of the combined method, which has achieved good results in practical production applications.

Topological indices are invariant numerical fields of a graph that give facts about the structure of graphs and are found to be very helpful in predicting the physical properties of aluminophosphates. The characteristics of the aluminophosphates are similar to those of zeolites. Two examples of current applications are natural gas dehydration and humidity sensor. New frameworks are being synthesised by researchers in chemistry and materials science. There are many layers and holes in these substances. In this study, Vertex version of distance-based topological indices, the entropy of topological indices and their numerical analysis are explained.

Rail impedance directly affects the transmission performance of track circuit . Considering the condition of earth stratification, for the difficult to calculate the rail impedance due to the semi-infinite integration interval and the oscillation of the integrand by using the Carson formula, The truncation method is proposed to divide the impedance formula is divided into definite integral and tail integral. The integral is approximated by the spline function, and the tail integral is calculated by using the exponential integral and Euler formula. Based on it, the rail impedance calculation formula of track circuit is obtained. The electromagnetic field model of track circuit with earth stratification is simulated by finite element method, and the correctness of the method is verified. Based on the formula, the influence of current frequency, soil depth and conductivity on rail impedance is studied. The relative error between the calculated results of rail impedance and the simulation results of finite element is within 5%. It can be seen that the formula has high accuracy and correctly reflects the law of rail impedance variation with current frequency, soil depth and resistivity. It provides a reliable reference for the theoretical calculation of rail impedance of track circuit.

Due to the tremendous progress in the automotive industry, the growth of the urban population, the number of vehicles is increasing and this creates parking challenges. Intelligent parking management systems offer an optimal solution for finding empty parking space so that drivers can quickly find their car parking space. To solve these problems, it is necessary to design an intelligent parking system, in addition to providing comfort to drivers, which is also economically viable. This paper proposes an intelligent multi-storey car parking system with the help of RFID technology and examining user preferences that can effectively solve car parking problems. The proposed method is a multi-objective decision-making method to reduce the problem of car parking, which is called MODM-RPCP. Therefore, the proposed MODM-RPCP method can allocate the best space for their stopping place by using the decision-making system and based on the priorities considered by the users. The simulation results show that the MODM-RPCP reduces the average booking time more than 19.2% and 27.1%, and decreases the response time of central parking management server more than 20.1% and 29.78% compared to MOGWOLA and ODPP approaches.

In this paper, we introduce some basic idea of Variational iteration method for short (VIM) to solve the Volterra’s integro-differential equations. The VIM is used to solve effectively, easily, and accurately a large class of non-linear problems with approximations which converge rapidly to accurate solutions. For linear problems, it’s exact solution can be obtained by only one iteration step due to the fact that the Lagrange multiplier can be exactly identified. It is to be noted that the Lagrange multiplier reduces the iteration on integral operator and also minimizes the computational time. The method requires no transformation or linearization of any forms. Two numerical examples are presented to show the effectiveness and efficiency of the method. Also, we compare the result with the result from Homotopy perturbation method (HPM). Finally, we investigate the absolute difference between variational iteration method and homotopy perturbation method and draw the graph of difference function by using Mathematica.

In this paper, we consider the development of algorithms for the solution of first order initial value problems whose solution exhibits exponential behaviour. Method of interpolation and collocation of basis function to give system of nonlinear equations which is solved for the unknown parameters to give a continuous scheme. The discrete methods recovered from the continuous scheme are implemented in block form. The stability properties of the method is verified and numerical experiments show that our method is efficient in handling these problems

Optimal planning and design of microgrids is a priority for electrification of off-grid areas. Indeed, according to one of the Sustainable Development Goals (SDG) 7, the UN recommends universal access to electricity for all but, at the lowest cost. To achieve this goal, several optimization methods with different strategies have been proposed in the literature. This paper proposes a microgrid installation and planning model based on a combination of several techniques. Python 3.10, the programming language, has been used in conjunction with machine learning techniques such as unsupervised learning based on K-means clustering and deterministic optimization methods based on mixed linear programming. These methods were complemented by the open-source spatial method for optimal electrification planning: onsset. The results obtained enabled us to simulate the model obtained, with a cluster considered as a case study, based on the elbow and k-means clustering method; then, in a second phase, to size the microgrid with a capacity of 40 kW, by optimizing all the resources available on the site: the example of the various resources in the case of Togo was considered (solar, wind, hydropower). This study therefore highlighted the optimal resources obtained by integrating battery systems by the optimization model formulated on the basis of the various technology costs, such as investment, maintenance and operating costs, based on the technical limits of the various technologies. For the optimum results obtained, solar systems account for 80% of the maximum load considered, compared with 7.5% for wind systems and 12.5% for battery systems. Next, an optimal microgrid connection model was proposed, based on the constraints of a voltage stability limit estimated at 10% of the maximum voltage drop. The substation capacity limit was also taken into account. The results obtained from the case studied enabled us again, to present selective results for load nodes in relation to the substation node. And finally, the spatial technology planning tool made it possible to obtain results on the different strategies for the various technologies required for the electrification planning study of the Togo case. The various results obtained from the different techniques provide the leads needed for a feasibility study for optimal electrification of off-grid areas, using microgrid systems.

In this paper, we propose a system of nonlinear mixed variational inequality problems, which consists of two elliptic mixed variational inequality problems on Banach spaces. Under suitable assumptions, using the Kakutani-Ky Fan fixed point theorem and Minty techniques, we prove the solution set to the system of nonlinear mixed variational inequality problem is nonempty, weakly compact and unique. Additionally, we suggest a stability result for the system of nonlinear mixed variational inequality problem by perturbing the duality mappings. Furthermore, we present an optimal control problem governed by the system of nonlinear mixed variational inequality problems and establish a solvability result.

Malocclusions have a continuously increasing prevalence from a generation to another as a result of climate changes, soil, atmosphere and water pollution. All of these aspects have unfavorable consequences on the nutritional scheme. Thus, nutrition together with other etiopathogenic factors contribute to complex alterations in the somatic development of the entire organism and, implicitly, of the cephalic extremity. The study group included 4147 children from randomly selected schools from Vâlcea County, Romania. The aim of this study is to determine the prevalence of malocclusions in schoolchildren from Vâlcea County, Romania, according to the three main classes of malocclusions (according to Angle’s classification), age groups (from 6 to 10 years old and from 11 to 14 years old), gender (male and female) and place of origin (rural and urban). For Angle class I malocclusions we recorded the highest prevalence (48,78% from the total number of schoolchildren with malocclusions), followed by Angle class II malocclusions (45,85% from the total number of schoolchildren with malocclusions) and for Angle class III malocclusions we found the lowest prevalence (5,37% from the total number of schoolchildren with malocclusions).According to gender, we found the highest prevalence in female gender (29,90% from the total number of female subjects), while in male gender we recorded a prevalence of 27,70% from the total number of male subjects. Regarding the place of origin, there is a higher prevalence of malocclusions in the urban areas (29,16%). The study subgroup included 140 children randomly selected from the total number of subjects from the study group. They were included in a more advanced study. The aim is to find potential associations between the presence of malocclusions and various oral variables. Categorical variables were expressed as numerical values and percentages, and their association was evaluated with either the Chi-square test of association or homogeneity, or the Fisher Exact test. The acquired data were incorporated into a binomial logistic regression model to assess the likelihood of developing malocclusions in relation to the following variables: defective phonation, bruxism, frequency of teeth brushing, onychophagia, oral respiration, infantile deglutition, placing objects between the maxillaries, thumb sucking and salivary aspects. It is also aimed to compare the results obtained with similar ones from the specialized literature.

The present study describes the preparation of a composite material consisting of thermoplastic polyurethane-poly (n-isopropylacrylamide) (TPU-PNIPAM), which was employed for the se-lective adsorption separation of alcohol/water mixed solutions for the first time. The findings revealed that TPU and PNIPAM were interconnected through interchain hydrogen bonding, resulting in exposed hydrophobic isopropyl groups while covering the hydrophilic hydrogen bond sites. Selective separation of alcohols from alcohol/water mixed solutions occurred via London dispersion forces between alkyl groups. Increasing the PNIPAM load on the TPU surface led to a decrease in available hydrogen bond sites capable of bonding with water molecules, an increase in dispersible isopropyl groups interacting with alcohol alkyl groups, and enhanced selective adsorption capacity of TPU-PNIPAM towards alcohol/water mixed solutions. Moreover, TPU-PNIPAM exhibited a characteristic fast-slow-fast-equilibrium ad-sorption curve for different initial concentrations of alcohol/water mixtures, and its selective adsorption capacity increased when temperature reached 55℃. In addition to these general trends, under identical conditions, the selective adsorption capacity of TPU-PNIPAM gradually increased by methanol < ethanol < isopropyl alcohol < propyl alcohol, thus indicating a positive correlation between selectivity performance and hydrophobicity level.

The African continent has the highest prevalence of hypertension globally, with South Africa reporting the highest prevalence in Southern Africa. While the influence of genetic variability in the pathogenesis of hypertension is well described internationally, limited reports are available for African populations. This study aimed to assess the association of genetic variants and essential hypertension in a cohort of two ethnic South African population groups. Two hundred and seventy-seven hypertensive and one hundred and seventy-six normotensive individuals were genotyped for 79 variants. Genotyping was performed using the Illumina GoldenGate Assay and allele-specific polymerase chain reaction. The association of variants was assessed using the Fisher Exact test under the additive and allelic genetic models, while multivariate logistic regression was used to predict the development of hypertension. Five variants (CYP11B2 rs179998, AGT rs5051 and rs699, AGTR1 rs5186 and ACE rs4646994) were significantly associated with essential hypertension in the cohort under study. Furthermore, AGTR1 rs5186 and AGT rs699 were identified as risk factors for the development of hypertension in both ethnic groups. In two ethnic South African populations an association was observed between Renin-Angiotensin-Aldosterone System (RAAS) related genes and the development of hypertension.

Objective: The aim of this study was to optimize the fermentation process of Radix Ranunculi ternate via microbial fermentation and analyze the changes in the contents of the main components, the antioxidant and hypoglycemic capacities of the extract before and after fermentation. Methods: The solid-state fermentation process was optimized using single-factor tests and the response surface method, with the yield of the alcohol extract of R. ternate as an evaluation index. Results: The best fermentation process was optimized using solid-state endophytic fungus fermentation technology as follows: strain addition ratio of Chaetomium globosum/Fusarium equiseti =1:1, fermentation for 5 d, sieve size of 40 mesh, liquid/material ratio of 0.8:1 mL·g−1, fermentation temperature of 31 °C, and inoculation amount of 7.5%. Under the optimized conditions, the contents of the water-soluble extract and total polysaccharides decreased by 12.71% and 12.95%, respectively, in the fermentation, The contents of ethanol-soluble-extract, flavonoids, saponins, polyphenols, organic acids, and total amino acids of fermented R. ternate increased by 19.77%, 57.14%, 79.67%, 14.29%, 17.63% and 3.82%, respectively, and the scavenging rate for DPPH, ABTS+, ·OH free radicals and inhibitory rate for α-amylase also increased by 19.02%, 14.17%, 7.53% and 34.54%, respectively, compared with unfermented R. ternate. Conclusions: Solid-state fermentation opens new avenues for the development and application of R. ternate as natural antioxidant and hypoglycemic food.

This study examined the efficiency of a combined diagnostic approach in which bioamplification of Arizona 861 S1 citron was integrated with RT‒PCR to detect Citrus tristeza virus (CTV) and Hop Stunt Viroid (HSVd) in Citrus plants. The capacity of the combined method to diagnose mixed infections of CTV and HSVd, along with early single infections of both pathogens, was assessed by evaluating the incubation periods and differential detection capabilities between the combined and direct methods. The bioamplification method exhibited high sensitivity (100%) and specificity (100%) for CTV, enabling early detection even in patients with low-titer infections compared to direct RT‒PCR. However, for HSVd, the combined method achieved 50% sensitivity in early infections, highlighting the need for additional replicates to enhance diagnostic reliability. The relative concentrations of pathogens in mixed and simple infections were evaluated; the analysis revealed no significant differences, suggesting minimal interference between CTV and HSVd. This approach allows early detection of CTV but requires further refinement for HSVd diagnosis. These findings underscore the complementary roles of the cost-effectiveness of direct RT‒PCR and the sensitivity of the combined method in implementing effective disease control strategies in citrus crops.

Little is known about how the degree of mixing of forest-forming species affects forest floor hydrology. We evaluated the water storage capacity of the resulting litter layer by mixing litterfall of Scots pine and sessile oak and studying their decomposition time. We prepared 90 artificial samples containing pure pine litter, pure oak litter, and mixed pine-oak litter with varying shares of pine needles. These samples were subjected to 15 months of decomposition in soil. After every three months of decay, some samples were removed from the soil, and their water storage capacity, bulk density, and C:N ratio were evaluated. Our findings indicate that samples with the greatest water storage capacity had a low C:N ratio and a predominant share of oak leaves. Conversely, samples with a high C:N ratio and a predominant share of pine needles had the lowest water storage capacity. After 12 and 15 months of decomposition, the water storage capacity increased by more than 52% compared to the initial water capacity of the samples. The highest increase in water storage capacity (>40%) was observed in samples with a predominant share of oak leaves, while the lowest (approximately 28%) was recorded in samples with 80 and 100% of pine needles.

In this work, a modeling technique utilizing the P-Graph framework was used for a case 1 study involving biomass-based local energy production. In recent years, distributed energy systems 2 gained attention. These systems aim at satisfying energy supply demands, supporting the local 3 economy, decreasing transportation needs and dependence on imports, and in general obtaining a 4 more sustainable energy production process. Designing such systems is a challenge, for which novel 5 optimization approaches were developed to help decision-making. Previous work used the P-Graph 6 framework to optimize energy production in a small rural area, involving manure, intercrops, grass, 7 and corn silage as inputs, and fermenters. Biogas is produced in fermenters, and Combined Heat 8 and Power (CHP) plants provide heat and electricity. A more recent result introduced the concept of 9 operations with flexible inputs in the P-Graph framework. In this work, the concept of flexible inputs 10 was applied to model fermenters in the original case study. A new implementation of the original 11 decision problem was made both as a Mixed-Integer Linear Programming (MILP) model and as a 12 purely P-Graph model by using the flexible input technique. Both approaches provided the same 13 optimal solution, with a 31% larger profit than originally reported.

This paper presents a new low-voltage versatile mixed-mode filter which uses a multi-ple-input/output differential difference transconductance amplifier (MIMO-DDTA). The multi-ple-input of the DDTA is realized using a multiple-input bulk-driven MOS transistor (MI-BD-MOST) technique to maintain a single differential pair, thereby achieving simple structure with minimal power consumption. In a single topology, the proposed filter can provide five standard filtering functions (low-pass, high-pass, band-pass, band-stop, and all-pass) in four modes: voltage (VM), current (CM), transadmittance (TAM), and transimpedance (TIM). This provides the full capability of a mixed mode filter (i.e., twenty filter functions). Moreover, the VM filter offers high-input and low-output impedances and the CM filter offers high-output impedance; therefore, no buffer circuit is needed. The natural frequency of all filtering functions can be electronically controlled by a setting current. The voltage supply is 0.5 V and for a 4 nA setting current, the power consumption of the filter was 281 nW. The filter is suitable for low-frequency biomedical and sensor applications that require extremely low supply voltages and nano-watt power consumption. For the VM low-pass filter, the dynamic range was 58.23 dB @ 1 % total harmonic distortion. The proposed filter was designed and simulated in the Cadence Virtuoso System Design Platform using the 0.18 µm TSMC CMOS technology.

Art organizations are increasingly focusing on enhancing the visitor experience to attract a wider audience. The aim objective of this study was to explore the key factors that influence the visitor experience of offline art exhibitions and to use a mixed methods to data collection and analysis. The research process was divided into three stages. In the first stage, we conducted semi-structured interviews with 12 respondents by dividing the exhibition experience into three time periods: pre, during, and post-visit. We extracted seven factors affecting visitor experience through qualitative content analysis including marketing, motivation, physical environment, exhibit quality, participation, technology and service facilities; in the second stage, we developed an assessment scale and pretested it; in the third stage, we collected 725 questionnaires to validate the factors of visitor experience in art exhibitions. The results of linear regression analyses showed that all seven key factors had a significant impact on visitor experience. This study constructed a scale to assess the factors of art exhibition experience, which provides theoretical sup-port for in-depth study of art exhibition experience and useful guidance for planning and design-ing art exhibitions to improve the quality of visitors' experience of art exhibitions.

A major challenge of augmented and mixed reality applications is identifying the context and semantics of the real environment. Studies on object and action recognition were developed based on the improvement of machine learning techniques, allowing them to be annotated and recognized. This study aims to characterize current knowledge on the use of machine learning for recognizing objects and actions in augmented and mixed reality environments, increasing context awareness. Therefore, a systematic literature review of works related to these topics was made, using the Scopus and Web of Science knowledge bases. We searched articles and conference reviews or papers published between 2018 and 2022 and selected fifteen studies to be reviewed. The results indicate that there is a great demand for using machine learning to immersive technologies in factories, engineering, entertainment, education, health, among other application domains. However, these real-time interactive systems still have challenges and limitations to be solved, involving network communication, prediction time and the creation of a model that recognize objects and actions in broad contexts. Furthermore, additional research is needed to investigate how object and action recognition can increase context awareness in augmented reality applications.

Quality control is a critical component in industrial manufacturing, directly influencing efficiency, product reliability, and ultimately, customer satisfaction. In the dynamic environment of industrial manufacturing, traditional methods of inspection may not adequately meet the evolving complexity, necessitating innovative approaches to bolster precision and productivity. In this study, we explore the application of mixed reality (MR) technology for real-time quality control in the assembly process. Our methodology involved the integration of smart glasses with a server-based image recognition system, designed to conduct real-time component analysis. The innovative aspect of our study lies in the harmonization of MR and computer vision algorithms, providing immediate visual feedback to inspectors and thereby improving the speed and accuracy of defect detection. YOLOv8 have been adopted in this study for detection object model. The project implementation occurred in a controlled environment to enable a comprehensive evaluation of the system functionality, the identification of possible problems and improvements in the system performance. The results indicated the viability of mixed reality as a powerful tool for enhancing traditional inspection processes. The fusion of MR and computer vision offers possibilities for future advancements in industrial quality control, paving the way for more efficient and reliable manufacturing ecosystems.

The cutter structure and layout scheme of PDC (Polycrystalline Diamond Compact) bits are important factors in improving efficiency. To further improve the drilling efficiency of PDC bits, axe, triangular prism, and cylindrical PDC cutters were used as research objects. Based on the measured granite data, a finite element model of non-homogeneous granite was established and verified by uniaxial compression simulation. The rock-breaking process of different cutter combination schemes was compared using the finite element method, and the parameters in the best scheme were optimized using the Box-Behnken response surface method. The results show that the constructed model of non-homogeneous granite is consistent with the stress-strain relationship of real granite and is reliable. The axe PDC cutter is more aggressive than the other two cutters and is more suitable for the front row of the bit blade tooth arrangement, while the triangular prism cutter is the second most aggressive and is suitable for the rear row of tooth arrangement, and the best combination scheme is the front row of axe cutter and the rear row of triangular prism cutter arranged alternately with the axe cutter. The optimal transverse and longitudinal distances of the optimized triangular prism cutter from the front axe cutter are 10mm and 7mm, and the optimal transverse and longitudinal distances of the rear axe cutter from the front cutter are 10.06mm and 7mm. The drilling speed is more stable during drilling and the PDC bit with mixed tooth arrangement has 16.8% and 16.6% higher rate of penetration(ROP) compared with the bit with single axe cutter and triangular prism cutter, and the drilling speed is more stable during working, which can effectively improve the rock breaking efficiency of the PDC bit. The field application proves that the bit with mixed cutter arrangement is easier to break the complex formations, with more stable ROP and better efficiency. The study can provide theoretical support for the cutter layout of the PDC bit.

This article explores matter collineations (MCs) of static plane-symmetric spacetimes, considering the stress-energy tensor in its contravariant and mixed forms. We solve the MC equations in two cases: when the energy-momentum tensor is nondegenerate and degenerate. For the case of degenerate energy-momentum tensor, we employ a direct integration technique to solve the MC equations, which leads to an infinite-dimensional Lie algebra. On the other hand, when considering the nondegenerate energy-momentum tensor, the contravariant form results in a finite-dimensional Lie algebra with dimensions of either 4 or 10. However, in the case of the mixed form of the energy-momentum tensor, the dimension of the Lie algebra is infinite. Moreover, the obtained MCs are compared with those already found for covariant stress-energy.

The total tree height (h) and diameter at breast height (dbh) relationship is an essential tool in forest management and planning. The height—diameter (h-dbh) relationship had been studied with several approaches and for several species worldwide. The nonlinear mixed effect modeling (NLMEM) has been extensively used and lately the resilient backpropagation artificial neural network (RBPANN) approach has been a trend topic for modeling this relationship. The artificial neural network (ANN) is a computing system based in artificial intelligence and inspired in biological neural network for supervised learning. In this study the NLMEN and RBPANN approaches were used for modeling the h—dbh relationship for Durango pine species (Pinus durangensis Martínez) in mixed-species forest from Mexico. The total dataset considered 1,000 (11,472 measured trees) randomly selected from 14,390 temporary forest inventory plots and the dataset was randomly divided into two parts; 50% for training and 50% for testing. An unsupervised clustering analysis was used to grouped the dataset into 10 clusters based on k-means clustering method and plot-variables like density, basal area, mean dbh, mean h, quadratic mean diameter, altitude and aspect. The RBPANN was performed for tangent hyperbolicus (RBPANN-tanh), softplus (RBPANN-softplus), and logistic (RBPANN-logistic) activation functions for functions in cross product of the covariate or neurons and the weights for the ANN analysis. For both training and testing, 10 classical statistics (e.g., RMSE, R2, AIC, BIC, logLik) were computed for the residual values and assess the approaches for h—dbh relationship. For training and testing, the ANNs approach outperformed the NLMEM approach, and the RBPANN-tanh has the best performance in both training and testing phases.

This paper investigates the physical/virtual dynamics when constructing an immersive environ-ment for medieval courtyard houses in Historic Cairo. Using a VR Lab at a university campus, the paper analyzes a courtyard that symbolizes social resilience and community bonding at the newly rehabilitated Bayt Yakan. The courtyard is reconstructed as a Mixed Object through 3D documentation and scanning the space to develop a photogrammetry and VR experience. The results show that the sense of presence is perceived through a combination of factors and juxta-positions of the real and the virtual including: 1) architectural aesthetics, 2) intangible elements and 3) socio-cultural activities in space. Based on the pilot case study, the paper concludes with proposing a “Geospatial Framework for Immersive Environments and Social Sustainability” that is transdisciplinary, pluralistic and expansive in nature to encompass the multiple narratives of the contested past, and overlay the material and immaterial sustainable features embedded in historical contexts, where the Mixed Reality paradigm becomes an enabler for multiple voices, tools and mediums.

Since people spend most of their time in indoor environments, the objective of this work was to study indoor air quality perception and its effects on users’ thermal comfort. Based on previous data from a building with a central air-conditioning system and two mixed-mode buildings located in the humid subtropical climate of Florianópolis, southern Brazil, statistical analyses were performed. Each user subjective answer obtained through a questionnaire was combined with the corresponding environmental conditions – measured using microclimate stations, a portable thermo-anemometer and a CO2 analyser. Results showed that improvement in air quality was associated with the reduction of air temperature and humidity ratio. Also, there was a significant influence of thermal, air movement and humidity sensation and acceptability of air quality perception. Users felt more satisfied or neutral with air quality for being in thermal comfort, and not because of the CO2 level – which means that air quality perception is influenced by factors other than CO2. This study recommends the implementation of an air exchange device in split air-conditioners with air recirculation used in mixed-mode buildings in Brazil. It is important to provide suitable indoor ventilation to reduce pollutants concentration, ensure good air quality and prevent respiratory diseases.

Due to climate change, droughts have been occurring more frequently in Germany in recent years. More frequent and prolonged drought affects the health of trees and increases the risk of forest fires. A large-scale forest fire broke out near Treuenbrietzen, Brandenburg, in the summer of 2018 in pine monospecific forests. In addition to evaluating the damage caused, future reforestation is discussed, which is related mainly to the expectations of the forest owners. A telephone survey of seven affected forest owners was conducted using a semi-structured guided interview. The results from our interview demonstrated the support of private forest owners for mixed forests over monospecific pine forests. Most forest owners do not prioritize economic benefit with the forest land as forestry was not the primary source of income. Instead, the ownership of the forest tends to be linked to idealistic, cultural, and family values. The motives for reforestation vary but are often externally influenced. Different goals of forest owners lead to the challenge of finding consensus among them. We conclude that forestry advice by the federal and state governments is essential, especially on how climate change can affect local forests, to sensitize private forest owners to this problem.

Biofilms play a crucial role in the development of Candida-associated denture stomatitis. Inhibition of microbial adhesion to PMMA and phosphate containing PMMA has been examined in this work. C. albicans and mixed salivary microbial biofilms were compared on naked and salivary pre-conditioned PMMA surfaces in the presence or absence of antimicrobials (cetyl pyridinium chloride [CPC], KSL-W, histatin 5 [his 5]). Polymers with varying amounts of phosphate (0-25%) were tested using four C. albicans oral isolates as well as mixed salivary bacteria and 24 h biofilms were assessed for metabolic activity and confirmed using Live/Dead staining and confocal microscopy. Biofilm metabolism was reduced as phosphate density increased (15%: P=0.004; 25%: P=0.001). Loading of CPC on 15% phosphated disks showed a substantial decrease (P=0.001) in biofilm metabolism in the presence or absence of a salivary pellicle. Salivary pellicle on uncharged PMMA enhanced the antimicrobial activity of CPC only. CPC also demonstrated remarkable antimicrobial activity on mixed salivary bacterial biofilms under different conditions displaying the potent efficacy of CPC (350 µg/ml) when combined with an artificial protein pellicle (Biotene half strength).

Efficient alternatives in energy production and consumption are constantly investigated by increasingly strict policies. In this way, the pollutant emissions that contribute to the greenhouse effect reduce and sustainability of the electricity sector increase. With more than a third of the world's energy consumption, buildings have great potential to contribute these sustainability goals. Additionally, with growing incentives in the Distributed Generation (DG) and Electric Vehicle (EV) industry, it is believed that Smart Buildings (SBs) can be a key in the field of residential energy sustainability in the future. In this work, an energy management system in SBs are developed to reduce the power demanded of a residential building. In order to balance the demand and power provided by the grid, microgrids such as Battery Energy Storage System (BESS), EVs and Photovoltaic Generation panels (PV) are used. Here, a Mixed Binary Linear Programming formulation (MBLP) is proposed to optimize the charge and discharge scheduling of EVs and also BESS. In order to show the efficiency of the model, a case study involving three scenarios and an economic analysis is considered. The results point a 65% reduction in peak load consumption supplied by grid and a 28.4% reduction in electricity consumption costs.

The aim of this study is to introduce a novel method which can separate sand or gravel dominated bed load transport in rivers with mixed-size bed material. In engineering practice, the Shields-Parker diagram could be used for such purposes, however, the method has certain applicability limits, due to the fact that it is based on uniform bed material and provides information rather on river-scale, instead of reach or local scale. When dealing with large rivers with complex hydrodynamics and morphodynamics the bed load transport modes can also indicate strong variation even locally, which requires a more suitable approach to estimate the locally unique behavior of the sediment transport. Here, we suggest that the decision criteria utilizes the shear Reynolds number (Re*). The method was verified against field and laboratory measurement data, both performed at non-uniform bed material compositions. The comparative assessment of the results show that the shear Reynolds number based method operates more reliably than the Shields-Parker diagram and it is expected to predict the sand or gravel transport domination with a < 5% uncertainty. The introduced results can greatly contribute to the improvement of numerical sediment transport modeling as well as to the field implementation of bed load transport measurements.

Vibrations of plate structures placed in a supersonic flow is considered. The undisturbed fluid flow is parallel to the plate. Two specific problems are treated: in the first one the plate is in the form of an infinite strip and the flow is in the direction of its finite length. Rigid walls extend from the sides of the plate indefinitely. In the second problem, the plate is a finite rectangle and the flow is parallel to one of its sides. The first problem is a limiting case of the second problem. The flow is modeled by piston theory which assumes that the fluid pressure on the plate is proportional to local slope. This approximation is widely used at high speeds, and reduces the interaction between the fluid flow and the vibrations of the plate to an additional term in the vibration equation. The resulting problem can be solved by assumed mode methods. In this study, the solution is also carried out by using the collocation method. The main result is the flutter velocity of the free fluid flow under which the plate vibrations become unstable. Finally, simple expressions are proposed between the various non-dimensional parameters that allows quick estimation of flutter velocity.

Two-dimensional heat diffusion problem with heat source which is quasilinear parabolic problem is examined analytically and numerically. Periodic boundary conditions are used as a boundary conditions. Since the problem is not linear, Picard’s successive approximation theorem is used. Under certain conditions of natural regularity and consistency imposed on the input data, establish the existence, uniqueness and constant dependence of the solution on the data using the generalized Fourier method. As a numerical solution, implicit finite difference scheme is used. The results ob-tained from analytical and the numerical solutions are so close to each other.

Shear deflection effects are traditionally neglected in most structural system identification methods. Unfortunately, this assumption might lead to significant errors in some structures, like deep beams. Although some inverse analysis methods based on the stiffness matrix method including shear deformation effects have been presented in the literature, none of these methods is able to deal with actual rotations in their formulations. Recently, the observability techniques, one of the first methods for the inverse analysis of structures included the shear effects into the system of equations. In this approach, the effects of shear rotation are neglected. When actual rotations on site are used to estimate the mechanical properties in the inverse analysis, it can result in serious errors in the observed properties. This characteristic might be especially problematic in structures such as deep beams where only rotations can be measured. To solve this problem and increase the observability techniques' applicability, this paper proposes a new approach to include shear rotations into the inverse analysis by observability techniques. This modification is based on the introduction of a new iterative process. To illustrate the applicability and potential of the proposed method, the inverse analysis of several examples of growing complexity is presented.

This paper focuses on robust multi-criteria traffic network equilibrium problems with path capacity constraints. The concepts of robust vector equilibrium and robust vector equilibrium with respect to worst case are introduced, respectively. To generate a subset of robust vector equilibrium, an equivalent min-max optimization problem is constructed. In addition, a direct search algorithm, in which the step size without derivatives and redundant parameters, for solving this min-max problem is proposed. To find a subset of robust vector equilibrium with respect to worst case, an equivalent smoothing optimization problem based on a variant version of ReLU activation function is established. Numerical experiments are also presented to expound the advantages of the algorithms.

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

The main issue in this work is to study limit functions necessary for the reliability assessment of the structural steel with the use of the relative entropy apparatus. This would be done using a few different mathematical theories relevant to this relative entropy, namely those proposed by Bhattacharyya, Kullback-Leibler, Jeffreys, and Hellinger. Probabilistic analysis in the presence of uncertainty in material characteristics would be delivered using three different numerical strategies – Monte-Carlo simulation, stochastic perturbation method as well as the semi-analytical approach. All these methods are based on the Weighted Least Squares Method approximations of the structural response functions versus the given uncertainty source and they would allow efficient determination of the first two probabilistic moments of the structural responses including stresses, displacements, and strains. The entire computational implementation would be delivered using the Finite Element Method system ABAQUS and computer algebra program MAPLE, where relative entropies, as well as polynomial response functions, would be determined. This study would demonstrate that the relative entropies may be efficiently used in reliability assessment close to the widely engaged First Order Reliability Method (FORM).

The approach to the personal experience and previous ideas about Physical Education of future Primary Education teachers is a starting point of great interest for the teaching of the subject of Didactics of Physical Education. The study aims to investigate these prior beliefs and to verify to what extent this initial perception changes after taking the course on “Didactics of Physical Education”. A concurrent mixed-methods study was conducted, which included two data collection procedures: (1) a pre-experimental design with a single group featuring pre-test and post-test; (2) the analysis of students' autobiographical accounts of their school experience with physical education. The participants were students enrolled in the Bachelor’s degree program in Primary Education at the University of Santiago de Compostela (USC) who undertook the course last year. The results obtained reveal that after taking the subject of Didactics of Physical Education, students give greater value to more positive concepts of learning, socializing, participating, and playing, among others. Similarly, in the post-test, the assessment of concepts such as competitiveness and physical fatigue diminished. In their autobiographical memories, students associate good memories with relationships with classmates and the playful and socializing nature of the subject; and among the bad memories, they highlight the content related to physical performance, competitiveness, and lack of attention to the diversity of students and their individual characteristics.

Background and aims. Clinically significant delayed bleeding (CSDB) may complicate endoscopic colorectal submucosal dissection (ESD). Methods. We assessed the results of a prospective registry of colorectal ESD. We evaluated the effect of clip closure and PuraStat application for prevention of CSDB. Results. 40 patients with 41 colorectal ESD were included. ESD was successful in 38 lesions (92.7%), 35 with R0 resection (92.1%) and 33 with curative resection (86.8%). CSDB occurred in 3 out 38 lesions (7.9%, 95% CI [1.7 – 21.4%]), exclusively after rectal ESD (3 of 22 rectal lesions vs. 0 of 16 colonic lesions, p = 0.249). Clip closure was more frequently used after colonic ESD (12 of 16 colonic lesions vs. 2 of 22 rectal lesions, p < 0.001) and was not protective for CSDB in univariate analysis, even though no events occurred after clip closure (0 of 14 lesions with clip closure vs. 3 of 27 lesions without, p = 0.283). PuraStat was more frequently applied after ESD for rectal lesions (16 of 22 rectal lesions vs. 2 of 16 colonic le-sions, p < 0.001) and was not protective for CSDB, all three events occurring after PuraStat application (3 of 21 lesions with PuraStat application vs. 0 of 20 lesions without, p = 0.097). Conclusions. CSDB occurred exclusively after rectal ESD, and no predictive factors were identified in uni-variate analysis. Clip closure and PuraStat application were not protective for CSDB.

This study presents a critical literature review on the models of users' adoption of blockchain applications in supply chains. This review pertaining to blockchain technology adoption by supply chain stakeholders is significant as it is a pre-requisite for the technical sustainability of blockchain technology in supply chains. Through a critical literature review, the previous studies related to technology adoption models were analyzed to explore practices brought about by blockchain applications for supply chain management. This study examined the suitability of the existing models (e.g., the technology-organization-environment (TOE) framework, task technology fit (TTF), unified theory of acceptance and use of technology (UTAUT)) of technology adoption for blockchain applications in supply chains and came up with a new unified model, namely, TOE-TTF-UTAUT. This review provides implications for a more appropriate research design using mixed methods. When adopting the TOE-TTF-UTAUT model in a study, two phases of research using mixed methods can be performed. The first phase is an exploratory sequential design in which a qualitative approach to explore the TOE and supply chain task constructs is followed by a quantitative approach using a survey and quantitative analyses to investigate the factors affecting blockchain adoption in supply chains. The second phase adopts explanatory sequential design in which the quantitative findings from the first phase are reviewed for follow-up by qualitative interviews to obtain explanations.

Unmanned aerial vehicle (UAV), or drone is recognized for its potential to improve efficiency and address last-mile delivery issues. As a result, there has been a lot of activity in recent years in the field of drone scheduling and routing. Unlike the vehicle routing problem, drone route design is difficult due to several operational characteristics, such as speed optimization, multitrip operation, and energy consumption estimation. On the one hand, drone energy consumption is a complex nonlinear function of both speed and payload in practice. On the other hand, the high operating speed of drones can significantly curtail the drone range, thereby limiting the efficiency of drone delivery systems. Most of the existing drone delivery models either assume constant drone speed or do not consider the effect of drone speed and parcel weight on energy consumption, leading to costly or energy-infeasible routes. This paper addresses the trade-off between speed and flight range in a multi-trip drone routing problem with variable flight speeds (DRP-VFS), in which a team of homogeneous drones is employed for delivery services. We propose a new model to particularly consider energy constraints using a nonlinear energy consumption model and treat drone speeds as decision variables so that various drone speeds can be adopted in applications. The DRP-VFS is initially formulated as mixed-integer linear programming (MILP) to minimize total energy consumption. To solve large-scale instances, we propose a three-phase adaptive large neighborhood search (ALNS) algorithm. The experimental results demonstrate that suboptimal solutions can be found effectively in practical scenarios using the proposed method. Furthermore, results indicate that operating drones at variable speeds leads to about 21% of energy savings compared to fixed speeds, boasting advantages in cost-savings and range extensions.

New digital interventions have shown potential in managing asthma and improving patients' quality of life compared with conventional interventions. Our objective was to conduct an exhaustive survey of the application of digital health technologies in evaluating, treating, and self-managing psychological and psychopathological elements linked to asthma. We analyzed a compendium of research papers and systematic reviews pertaining to asthma, encompassing themes such as outdoor air pollution, early life wheezing disorders, atopic dermatitis, digital strategies for asthma self-management, psychiatric conditions and asthma, familial impacts on pediatric asthma, and the utilization of mobile health apps for managing asthma. We scrutinized eight chosen studies to evaluate the capacity of digital health technologies to enhance the man-agement and treatment outcomes of psychological factors related to asthma. The studies under review indicate that eHealth interventions, mixed reality instruments, mHealth technolo-gy-augmented nurse-led interventions, and smartphone apps incorporating Bluetooth-enabled sensors for asthma inhalers can markedly enhance self-management of symptoms, quality of life, and mental health outcomes, particularly in children and adolescents with asthma. Nonetheless, additional research is required to ascertain their efficacy and practicability across diverse populations and environments. Customized interventions that cater to the unique needs and preferences of asthma patients and associated psychological elements are vital to ensure the persistent and equitable adoption of these technologies. We underscore the significance of addressing psychological elements in the management and treatment of asthma and advocate for ongoing research and development in this domain.

Wave buoy measurements were carried out near the north-eastern Black Sea coast at the natural reserve Utrish in 2020-2021. In total, about 11 months of data records were collected during two stages of the experiment at 600 and 1500 meters offshore and depths of 18 and 42 meters. The measured waves propagate almost exclusively from the seaward directions. Generally, the waves do not follow the local wind directions, thus, implying a mixed sea state. Nevertheless, dimensionless wave heights and periods appears to be quite close to the previously established empirical laws for the wind-driven seas. The results of the wave turbulence theory are applied for estimates of spectral energy fluxes and their correspondence to the energy flux from the turbulent wind pulsations. These estimates are consistent with today's understanding of wind-wave interaction. It is shown that the main fraction of the wind energy flux goes to the direct Kolmogorov-Zakharov cascade to high wave frequencies and then to dissipation in small scales. Less than 1% of the wind energy flux is directed to low frequency band (the so-called inverse Kolmogorov-Zakharov cascade), thus, providing wave energy growth.

Establishment of mixed-forests has gained increasing attention as a way to optimize forest production, to improve ecological benefits and as a safety net for impacts of future climate uncertainties. However, practical knowledge about which species and what proportion of them should be mixed is still lacking. Thus, this study was conducted with the aim of identify suitable species for mixture with Acacia cincinnata. The mixture tested in the present study was A. cincinnata + Eucalyptus robusta (6:4), A. cincinnata + Acacia mangium (3:1) and monospecifc plantation of A. cincinnata established in 2014. After 7 years of growth, we analyzed the effects of species mixture on growth of tree species, understory vegetation and soil physico-chemical properties as well as bacterial community structure and diversity. The results showed that species mixture had no significant effect on growth characteristics, such as diameter and singletree volume of A. cincinnata. However, mixed-species planting increased the total stocking volume compered to monospecific plantation of A. cincinnata. Furthermore, stand mixture significantly increased species diversity, biomass and nutrient stocks in the understory vegetation. The soil of mixed stand of A. cincinnata and A. mangium had the highest C and N contents, whereas the soil of pure A. cincinnata stand had the highest P content. The diversity of soil bacterial community were the highest in the mixed stand of A. cincinnata and E- robusta, followed by pure A. cincinnata stand and A. cincinnata + A. mangium stand. The relative abundance of Proteobacteria and Actinobacteria was higher in soils of mixed stands. Furthermore, the relative abundance of Firmicutes was high in the soil of A. cincinnata + A. mangium while the relative abundance of Verrucomicrobia was high in A. cincinnata + E. robusta stand. As a whole, the study demonstrated that establishing mixed-species plantation enhance the diversity and composition of understory vegetation, soil physico-chemical and soils bacterial community; thereby increasing biodiversity, nutrient cycling and carbon sequestration in the biomass and soil. From the viewpoints of forest productivity and ecological benefits, it is advisable to establish a mixed plantation of A. cincinnata and A- mangium in southern China. As a whole, our work revealed that the sustainability of mixed-species plantation relies on the interactions between soil attributes, vegetation, and bacterial community.

[Co(AMPY)(DAPY)Cl2(H2O)].H2O (1) [Cu(AMPY)(DAPY)Cl2(H2O)].H2O (2) [Zn(AMPY)(DAPY)Cl2(H2O)] (3) were prepared from the ligands; AMPY = 2-amino-4-methylpyrimidine (L1), DAPY = 2,3-diaminopyridine (L2) and CoCl2.6H2O, CuCl2.2H2O and ZnCl2 in water/ethanol solutions and the three products characterized by elemental analysis, ultraviolet-visible spectroscopy (UV–Vis), Fourier-transform infrared spectroscopy (FT-IR), magnetic susceptibility, molar conductivity methods, and TGA analysis. The X-ray powder diffraction of the Co(II), Cu(II), and Zn(II) compounds showed that the geometry of monoclinic and SEM analysis revealed their morphology with a smooth surface. Molecular modeling was performed for all compounds using the density functional method DFT/B3LYP to study the structures and the frontier molecular orbitals (HOMO and LUMO). We have used Gaussian09 software for the calculations. In this study, different complexes were tested against Gram negative and Gram positive bacterial species to give insight into their broad-spectrum effects. The used pathogenic strains were two Gram positive species "Staphylococcus aureus and Micrococcus luteus" and two Gram negative species "Salmonella thyphimurium and Escherichia coli. The antifungal activity was evaluated against a pathogenic reference strain of the yeast Candida albicans. The antimicrobial and antioxidant assay results demonstrate that the tested compounds are effective against Gram positive and negative bacteria. Additionally, the compounds have an antifungal effect against Candida albicans with a maximum inhibitory zone of 2.5cm. The results demonstrated high antioxidant potential for the Zn(II) complex with a DPPH scavenging of 91.5%, however, the Cu(II) complex was low (16.5%). The data of docking with tyrosyl-tRNA synthetase presented that all compounds fit very well in the catalytic pockets of the proteins of the receptor.

Economic expedience of waste heat recovery systems (WHRS), especially for low temperature difference applications, is often questionable due to high capital investments and long pay-back periods. By its simple design isobaric expansion (IE) machines could provide a viable pathway to utilize otherwise unprofitable waste heat streams for power generation and particularly for pumping liquids and compression of gases. Different engine configurations are presented and discussed. A new method of modelling and calculation of the IE process and efficiency is used on IE cycles with various pure and mixtures as a working fluid. Some interesting cases are presented. It is shown in this paper, that the simplest non-regenerative IE engines are efficient at low temperature differences between a heat source and heat sink. Efficiency of non-regenerative IE process with pure working fluid can be very high approaching Carnot efficiency at low pressure and heat source/heat sink temperature differences. Regeneration permits to increase efficiency of the IE-cycle to some extent. Application of mixed working fluids in combination with regeneration permits to significantly increase the range of high efficiencies to much larger temperature and pressure differences.

Global use of single-use non-biodegradable plastics, like bottles made of polyethylene tereph-thalate (PET), have contributed to catastrophic levels of plastic pollution. Fortunately, microbi-al communities are adapting to assimilate plastic waste. Previously, our work showed a full consortium of five bacteria capable of synergistically degrading PET. Using omics approaches we identified key genes implicated in PET degradation within the consortium’s pangenome and transcriptome. This analysis led to the discovery of a novel PETase, EstB, discovered to hydrolyze oligomer BHET, and polymer PET. Besides genes implicated in PET degradation, many other biodegradation genes were discovered. Over 200 plastic and plasticizer degrada-tion related genes were discovered through the Plastic Microbial Biodegradation Database (PMBD). Diverse carbon source utilization was observed by a microbial community-based as-say, which paired with an abundant number of plastic and plasticizer degrading enzymes in-dicates a promising possibility for mixed plastic degradation. Using RNAseq differential analysis, several genes were predicted to be involved in PET degradation including aldehyde dehydrogenases and several classes of hydrolases. Active transcription of PET monomer me-tabolism was also observed, including the generation of polyhydroxyalkanoate (PHA) bi-opolymers. These results present an exciting opportunity for the bio-recycling of mixed plastic waste with upcycling potential.

Meloidogyne javanica causing root-knot nematode in soybean is an important problem in soybean areas, leading to several yield losses. Some accessions have been identified carrying resistance loci to this nematode specie. In this study, a set of 317 soybean accessions were characterized for resistance to M. javanica. Genome-wide association study (GWAS) was performed using SNPs from genotyping-by-sequencing (GBS), and a region of 29.2 Kbp on chromosome 13 was identified. The haplotype analysis showed that SNPs were able to discriminate susceptible and resistant accessions, leading to 25 accessions sharing the resistance locus. Furthermore, 5 accessions may be new M. javanica resistance sources. The screening of the SNPs in the USDA soybean germplasm showed that several accessions previous reported as resistance to other nematodes also showed the resistance haplotype on chromosome 13. High levels of concordance among the phenotypes of Brazilian cultivars and the SNPs in chromosome 13 were observed. A in silico analysis of the mapped region on soybean genome revealed a presence of 5 genes with structural similarity with major resistance genes. The expression levels of the candidate genes in the interval demonstrated a potential pseudogene, and other two model genes up-regulated in the resistance source after pathogen infection. The SNPs associated to the region conferring resistance is a important tool for introgression of the resistance by marker-assisted selection in soybean breeding programs.

We describe the direct formation of mixed-phase (1T and 2H) MoS2 layers on Si as a photocathode via atomic layer deposition (ALD) for application in the photoelectrochemical (PEC) reduction of water to hydrogen. Without typical series-metal interfaces between Si and MoS2, our p-Si/SiOx/MoS2 photocathode showed efficient and stable operation in hydrogen evolution reactions (HERs). The resulting performance could be explained by spatially genuine device architectures in three dimensions (that is, laterally homo and vertically heterojunction structures). The ALD-grown MoS2 overlayer with the mixed-phase 1T and 2H homojunction passivates light absorber and surface states and functions as a monolithic structure for effective charge transport within MoS2. It is also beneficial in the operation of p-i-n heterojunctions with inhomogeneous barrier heights due to the presence of mixed-phase cocatalysts. The effective barrier heights reached up to 0.8 eV with optimized MoS2 thicknesses, leading to a 670 mV photovoltage enhancement without employing buried Si p-n junctions. The fast-transient behaviors via light illumination show that the mixed-phase layered chalcogenides can serve as efficient cocatalysts by depinning the Fermi levels at the interfaces. A long-term operation of ~ 70 h was also demonstrated in a 0.5 M H2SO4 solution.

Hepatitis-C is one of the most common viral diseases caused by hepatitis C virus (HCV). It is responsible for millions of deaths each year in the developing world. The common dissemination paths of HCV include the use of contaminated water and transfusion of infected blood. Control of this virus has become a challenge for scientists and health professionals due to its versatility and adaptability in different host environments. Along with other problems, lack of efficient diagnosis, quantification and genotyping of viral strains are the major hindrances in a management of this notorious epidemic. The knowledge of HCV genotype and an amount of virus in patient’s blood are pre-requisites to determine the duration and method of treatment. In this review, we discuss the implications of HCV molecular diagnostic methods and their clinical applications. We conclude that while, several commercial and home-brewed methods are available for this purpose, and there is a visible vacuum for cost effective, robust, sensitive assays that can detect multiple viral genotypes in a single reaction. We are of the view that the level of sensitivity offered by Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) technique is unequivocal as compared to other techniques. Therefore, researchers may explore further possibilities using this technique in the management of HCV.

At present European buildings typically consume two to five times more energy than predicted at the design stage. An important cause of this performance gap is the discrepancies between the design specification and the As-Built condition. Such discrepancies are mainly due to the gaps in knowhow between design, production and construction professionals. Design is more and more contained into a virtual environment and loses touch with the physical production and construction sites. As the construction sector enters the Industry 4.0 era, Building Information Modelling (BIM) based Mixed Reality can intertwine virtual and real worlds to bridge the knowhow gaps.

We present a generalized state-space model formulation particularly motivated by an online scheduling perspective. Through these proposed generalizations, we enable a natural way to handle routinely encountered disturbances and a rich set of corresponding counter-decisions. Thereby, greatly simplifying and extending the possible application of mathematical programming based online scheduling solutions to diverse application settings.

The article presents a new scalable iterative method for linear programming called the “apex method”. The key feature of this method is constructing a path close to optimal on the surface of the feasible region from a certain starting point to the exact solution of linear programming problem. The optimal path refers to a path of minimum length according to the Euclidean metric. The apex method is based on the predictor-corrector framework and proceeds in two stages: quest (predictor) and target (corrector). The quest stage calculates a rough initial approximation of linear programming problem. The target stage refines the initial approximation with a given precision. The main operation used in the apex method is an operation that calculates the pseudoprojection, which is a generalization of the metric projection to a convex closed set. This operation is used both in the quest stage and in the target stage. A parallel algorithm using a Fejér mapping to compute the pseudoprojection is presented. An analytical estimation of the parallelism degree of this algorithm is obtained. Also, an algorithm implementing the target stage is given. The convergence of this algorithm is proven. An experimental study of the scalability of the apex method on a cluster computing system is described. The results of applying the apex method to solve problems from the Netlib-LP repository are presented.

In order to reduce the silique shattering loss of rapeseed mechanical harvesting process, based on the state of force on the silique during rapeseed harvesting reel branch, Ningza 1810, Zhenyou 8 and Fengyou 306 were used as research objects, and the experimental research on the factors affecting rapeseed siliques shattering was carried out using the swing impact method. The experimental analysis showed that: rapeseed varieties, silique moisture content, silique growth position, collision material, impact speed, force position and other factors had significant effects on silique shattering. The impact velocity was less than 1.5m·s-1, the difference on the effect of each factor on pod-shattering was not significant, it was not easy to shatter when the moisture content of rapeseed silique was higher. The impact resistance of the front side of rapeseed was 2 to 4 times that of the bonding surface of rapeseed petals, the shattering rate of the top rapeseed silique was twice that of the bottom siliques, when siliques were supported, they were more likely to shatter under external forces than when they were unsupported. The experimental study of the mechanical properties of rapeseed siliques was carried out using the impending fracture method, the experimental analyses showed that the support position and force position of the silique, the loading speed and the growth position of the silique had a significant effect on the mechanical properties of the silique. The maximum cracking force was higher and bending strength was stronger when the body of the silique was supported, which the range of the maximum cracking force were 3.05N to 4.16N, and the bending strength range were 8.48 MPa to 11.57 MPa. The maximum cracking force and bending strength of the silique was stronger when the front side of the silique petal was pressurized than when the bonding surface of the petal was pressurized. Based on Pearson's correlation and grey correlation analysis, the morphological characteristics of rapeseed siliques were ranked in order of their influence on the performance of siliques in terms of the angle between silique and stalk, stalk diameter, petal thickness, beak length, silique thickness, silique width and silique length. This study can be used as a reference for the design and optimization of the rapeseed harvesting reel branch mechanism and the selection of machine harvestable rapeseed varieties.

Magnetorheological fluids (MRFs) are smart materials consisting of micro-scale magnetizable particles suspended in a carrier fluid. The rheological properties of a MRF can be changed from a fluid-state to a solid-state upon the application of an external magnetic field. This study reports the development of a particle-level simulation code for magnetic solid spheres moving through an incompressible Newtonian carrier fluid. The numerical algorithm is implemented within an open-source finite-volume solver coupled with an immersed boundary method (FVM-IBM) to perform fully-resolved simulations. The particulate phase of the MRF is modeled using the discrete element method (DEM). The resultant force acting on the particles due to the external magnetic field (i.e., magnetostatic polarization force) is computed based on the Clausius-Mossotti relationship. The fixed and mutual dipole magnetic models are then used to account for the magnetic (MAG) interactions between particles. Several benchmark flows were simulated using the newly-developed FVM-IBM-DEM-MAG algorithm to assess the accuracy and robustness of the calculations. First, the sedimentation of two spheres in a rectangular duct containing a Newtonian fluid is computed without the presence of an external magnetic field, mimicking the so-called drafting-kissing-tumbling (DKT) phenomenon. The numerical results obtained for the DKT case study are verified against published data from the scientific literature. Second, we activate both the magnetostatic polarization and the dipole-dipole forces and resultant torques between the spheres for the DKT case study. Next, we study the robustness of the FVM-IBM-DEM-MAG solver by computing multi-particle chaining (i.e., particle assembly) in a two-dimensional (2D) domain for area volume fractions of 20% (260 particles) and 30% (390 particles) under vertical and horizontal magnetic fields. Finally, the fourth computational experiment describes the multi-particle chaining in a three-dimensional (3D) domain allowing to study fully-resolved MRF simulations of 580 magnetic particles under vertical and horizontal magnetic fields.

The paper presents the identification and classification of steel cord failures in the conveyor belt core based on an analysis of a two-dimensional image of magnetic field changes recorded using the Diagbelt system around scanned failures in the test belt. The obtained set of identified changes in images obtained for numerous devices parameters settings were the base for statistical analysis. It makes it possible to determine the Pearson’s linear correlation coefficient between the parameters being changed and the image of the failures. In the second stage of the research, artificial intelligence methods were applied to construct a multilayer neural network (MLP) and to teach its appropriate identification of damage. In both methods were used the same data sets, which made it possible to compare methods.

In this article, we present a comparative study between the Adomian Decomposition Method (ADM) and Variational Iteration Method (VIM). The study outlines the significant features of the two methods, for solving nonlinear Volterra-Fredholm integro-differential equations. From the computational viewpoint, the VIM is more efficient, convenient and easy to use. Moreover, we proved the existence and uniqueness results and convergence of the solution. Finally, an example is included to demonstrate the validity and applicability of the proposed techniques.

This paper presents a new numerical method for multiscale modeling of composite materials. The new numerical model, called DECM, consists in a DEM (Discrete Element Method) approach of the Cell Method (CM) and combines the main features of both the DEM and the CM. In particular, it offers the same degree of detail as the CM, on the microscale, and manages the discrete elements individually such as the DEM—allowing finite displacements and rotations—on the macroscale. Moreover, the DECM is able to activate crack propagation until complete detachment and automatically recognizes new contacts. Unlike other DEM approaches for modeling failure mechanisms in continuous media, the DECM does not require prior knowledge of the failure position. Furthermore, the DECM solves the problems in the space domain directly. Therefore, it does not require any dynamic relaxation techniques to obtain the static solution. For the sake of example, the paper shows the results offered by the DECM for axial and shear loading of a composite two-dimensional domain with periodic round inclusions. The paper also offers some insights into how the inclusions modify the stress field in composite continua.

Photoluminescent (PL) layers and electroluminescent (EL) systems have been extensively explored for constructing flat panels, screen monitors, and lighting systems. Due to their optical properties, our group is interested in the relationship between optical properties and dielectric constant is converted due to thermal change. In this study, we prepared a zinc sulfide (ZnS) fluorescent film on barium-calcium zirconium titanate ceramics. BCZT0.85 (Ba0.85Ca0.15Zr0.1Ti0.9O3) and BCZT0.9 (Ba0.9Ca0.1Zr0.1Ti0.9O3) were prepared using the solid-state reaction method for the dielectric layer. The BCZT powders were calcined at 1200 and 1250 °C and dwell times of 2 and 4h. The phase formation and microstructure characteristics were then determined using X-ray diffraction and scanning electron microscopy, respectively. The dielectric behavior and optical properties rela-tionship was then studied to determine the composition and optimal conditions for further use as thermal detectors in electric vehicle battery packs. All BCZT powders exhibited the tetragonal phase, which was confirmed by JCPDS No. 01-079-2265. The dielectric constant increased with increasing calcining temperature or dwell time. The dielectric properties showed the BCZT0.85 ceramic sintered had the maximum dielectric constant of 15342 at calcine temperature of 1250 °C for 4h. Therefore, in this study, this condition was optimal for preparing the dielectric film. The maximum dielectric constant film is 42. The electroluminescence intensity of the samples increased in a temperature-dependent manner, with the highest EL intensity at 80 °C. Moreover, the electroluminescence intensity value was enhanced with the increase of the dielectric constant. Our results show promise for developing applications for Opto-thermal sensors.

There exists a great potential for application in soil mechanics with the use of mechanistic models such as the finite element model, and other non-local models, such as the peridynamic model, since the soil mass can be modelled as a group of particles that interact with each other. In this work, we determine the bearing capacity of deep foundations where stresses are transmitted to deep deposits, which generally present better characteristics in terms of compressibility and shear strength. One of the main elements are driven piles, which must be previously designed, made and tested before their final use. In this work, a comparison with different methods is presented. The finite element method and the peridynamic model are used. Because the effect of consolidation was not taken into account, in these examples, the assumption is made that the structures are cemented in inert soil. Likewise, it is assumed that the water table has no influence on the simulations. Failure envelopes were observed where bonds between particles present high gradients of deformation and fracture. Bearing capacities were estimated and compared with those obtained from the Terzaghi and Meyerhof methods.

Determining the level of PE/VC market development and the way it operates is extremely difficult. Despite countless reports and analyses concerning the PE/VC market, there is a lack of study on that sector based on a synthetic index. The usage of taxonomic methods in the PE/VC market analysis may be extremely useful in its proper characterizing. An in-depth study allows the identification of weaknesses and strengths as well as opportunities and threats related to a specific stage of PE/VC market development in a given country, that gives the opportunity to determine public activities that could affect the acceleration of this market development in future. The main objective of the study was to conduct a taxonomic analysis of the level of PE/VC market development in Europe, in 2010–2015. It is worth mentioning that the term “level of development” does not refer only to the value of investment or its dynamics, but to a set of objectified features that create one synthetic indicator. The conducted analysis using the Hellwig method allowed to determine the ranking of European countries in terms of the level of PE/VC market development, which reveal some significant differences in the functioning of the this market within Europe. Further detailed analysis of the designated groups of countries made it possible to determine the characteristics of such clusters. The construction of the level of private equity/venture capital market development ranking over the years enabled defining the current status and indicating the direction of possible changes.

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

The digital elevation model (DEM) is one of the key geospatial datasets used in many fields of engineering and science for countless applications. In this contribution, we assess the vertical accuracy of the Advanced Land Observing Satellite (ALOS) World 3D-30m (AW3D30) DEM using the runway method (RWYM). The RWYM utilizes the longitudinal profiles of runways which are reliable and ubiquitous reference data. A reference dataset used in this project consists of 36 runways located at various points throughout the world. The same dataset was previously used to test the accuracy of WorldDEM^TM. Our study indicates that AW3D30 has a remarkably high RMSE of 1.78 m (one σ). However, while analyzing the results, it has become apparent that it also contains a widespread elevation anomaly. We conclude that this anomaly is the result of uncompensated sensor noise and the data processing algorithm (downsampling of the higher resolution data). We believe that this issue should be communicated to the user community. Also, we would like to note that the traditional accuracy assessment of a DEM, e.g., statistical assessment of the elevation differences = model – reference, does not allow for identification of these type of anomalies in a DEM.

This paper introduces an innovative approach to numerically model Structure-Soil-Structure Interaction (SSSI) by integrating the Boundary Element Method (BEM) and the Finite Element Method (FEM) in a coupled manner. To assess the accuracy of the proposed method, a comparative study is undertaken, comparing its outcomes with those generated by the conventional FEM technique. Alongside accuracy, the computational efficiency aspect is crucial for the analysis of large-scale SSSI problems. Hence, the computational performance of the coupled BEM-FEM method undergoes a thorough examination and is compared with that of the standalone FEM method. The results from these comparisons illustrate the superior capabilities of the proposed method in comparison to the FEM method. The novel approach provides more reliable results compared to traditional FEM methods, serving as a valuable tool for engineers and researchers involved in structural analysis and design.

Estimating the parameters of statistical distributions generally involves solving a system of nonlinear equations or a nonlinear equation, being a technical difficulty in their usual application in hydrology. This article presents improved approximations and, in some cases, new approximations for the estimation with the method of ordinary moments and the method of linear moments, which are useful for the direct calculation of the parameters, because the errors in the approximate estimation are similar to the use of iterative numerical methods. Thirteen statistical distributions of two and three parameters frequently used in hydrology are presented, for which parameter estimation was laborious. Thus, the approximate estimation of the parameters by the two methods is simple but also precise and easily applicable by hydrology researchers. The approximate forms characterized by very small errors are the result of the research conducted within the Faculty of Hydrotechnics to update the romanian normative standards in the hydrotechnical field.

The testing requirements of the active phased array antennas are very different from those of traditional passive antennas, due to its beam steering capability. Usually, each beam profile of the active phased array needs a separate radiation pattern test, which makes the overall testing time extremely long. Thus the traditional antenna test method can no longer meet the efficiency and cost requirements of new active phased array antennas test. In this paper, a fast test method tailored for phased array antennas is proposed that offers significantly reduced testing time at the expense of slight sacrifice of the accuracy. Using the simulated element pattern in array and ideal port excitation, the beam profile in any direction can be predicted by testing only a certain beam profile. Through theoretical derivation and experiments, the effectiveness of the method is verified, and the testing efficiency of the phased array antenna is demonstrated to be improved by ten times or even more.

DGJ (Daftardar-Gejii-Jafaris) method is used to obtain numerical solution of the third order fractional differential equation. Providing the DGJ method converges, the approximate solution is a good and effective numerical result which is close to the exact solution or the exact solution. For this,the examples of the explaning the method are presented. The proposed method is implemented for the approximation solution of the third order nonlinear fractional partial differential equations. The method was shown to be unsuitable and inconsistent for an example of a nonlinear fractional partial differential equation depend on initial-boundary value conditions. The fact that these numerical results are not consistent can be explained by the fact that the method is not convergent.

This study proposes a mobile positioning method which adopts recurrent neural network algorithms to analyze the received signal strength indications from heterogeneous networks (e.g., cellular networks and Wi-Fi networks) for estimating the locations of mobile statioThis study proposes a mobile positioning method which adopts recurrent neural network algorithms to analyze the received signal strength indications from heterogeneous networks (e.g., cellular networks and Wi-Fi networks) for estimating the locations of mobile stations. The recurrent neural networks with multiple consecutive timestamps can be applied to extract the features of time series data for the improvement of location estimation. In practical experimental environments, there are 4,525 records, 59 different base stations, and 582 different Wi-Fi access points detected in Fuzhou University in China. The lower location errors can be obtained by the recurrent neural networks with multiple consecutive timestamps (e.g., 2 timestamps and 3 timestamps); the experimental results can be observed that the average error of location estimation was 9.19 meters by the proposed mobile positioning method with 2 timestamps.

The paper presents an adaptation of numerical solution of first order linear differential equation in fuzzy environment. The numerical method is re-established and studied with fuzzy concept to estimate its uncertain parameters whose values are not precisely known. Demonstrations of fuzzy solutions of the governing methods are carried out by the approaches, namely Modified Runge Kutta method and Runge Kutta Merson method. The results are compared with the exact solution which is found using generalized Hukuhara derivative (gH-derivative) concepts. Additionally, different illustrative examples and an application in industry of the methods are also undertaken with the useful table and graph to show the usefulness for attained to the proposed approaches.

With the increasing of copper consumption, the in-use stock of copper tends to increase. This paper used the “average use life method” to quantify the amount of copper in-use stock, and calculated the average age of in-use stock. It was indicated that the total in-use stock had an overall smooth trends, and reached its peak in 2007 was about 68.9 Mt (million tons), in addition, in-use stock per capita reached its peak ,234 kg/capita in 2001. The results demonstrated that during the period 1992-2002, the average age of copper in-use stock was continually decreased, but gradually increased since the year 2003. The fixed assets depreciation method used in this paper is applied to analyze depreciated copper in-use stock, and to analyze the relationship with economic indicator (GDP). It is demonstrated that it was inconsistent with the theory of Environmental Kuznets Curve (EKC) before 2000, this might be the demand for copper in the service sector is greater than the reduced strength of alternatives. Finally, scenario analysis of future copper in-use stock and depreciated copper in-use stock per capita in the U.S. were presented. The corresponding average age of the in-use stock will have a slight rise in the next decade.

The development of mineral resources in China has gradually entered the stage of deep mining. Rock burst, collapse and other ground pressure disasters caused by deep high stress have become major hidden dangers restricting mine safety production. Microseismic monitoring technology is an important means of ground pressure risk prediction. In this paper, the wavelet coefficient threshold denoising method in time-frequency domain, STA/LTA method, AIC method, Skew and Kurtosis method are studied, and the automatic P-phase onset time picking model based on noise reduction and multiple detection indexes is established. Through the effect analysis of microseismic signals collected by microseismic monitoring system of coral Tungsten Mine in Guangxi, automatic P-phase onset time picking is realized. the reliability of the P-phase onset time picking method proposed in this paper based on noise reduction and multiple detection indexes is verified. The picking accuracy can still be guaranteed under the severe signal interference of background noise, power frequency interference and manual activity underground mine, Which is of great significance to the data processing and analysis of microseismic monitoring.

Soil management in orchards can have several economic and environmental implications. In this study, three different soil management systems were compared in a dry-farmed olive grove: conventional tillage (Tillage), glyphosate-based herbicide (Herbicide) and Sheep Walking. The experiment lasted eleven years (2011-2022) and was carried out after a previous trial conducted on the same plot with the same treatments and duration (2001-2011). However, in the earlier trial, the Herbicide and Sheep Walking treatments switched positions in the plot, while the tillage treatment remained in its original place. The average total accumulated olive yields between 2011 and 2022 were 225.1, 230.9, and 245.0 kg tree–1 for the Sheep Walking, Tillage, and Herbicide treatments, respectively. However, no significant differences were observed between the treatments. The levels of total organic carbon in the soil, measured in samples collected in the last year of the study, were 41.3, 33.7, and 37.3 g kg–1, respectively for the same treatments. These findings indicated that the Tillage treatment exhibited lower soil organic matter content and reduced bioavailability of some nutrients, which raises concerns about its sustainability. On the contrary, employing Sheep Walking with an appropriate stocking rate, effectively controlling vegetation in the spring, ensured favourable soil properties and olive yields comparable to the other treatments. Moreover, the Sheep Walking approach provides supplementary advantages to the farmer, including revenue from the sale of animal products and the opportunity to transition to organic farming systems, which better align with the preferences of contemporary societies.

In the context of carbon neutrality and carbon peaking, in order to achieve low carbon emissions and promote the efficient utilization of wind energy, hydrogen energy as an important energy carrier is proposed to mix hydrogen and natural gas to form hydrogen enriched compressed natu-ral gas (HCNG). It is also injected into the natural gas pipeline network to realize the transmission and utilization of hydrogen energy. At the same time, the participation of demand response is considered, the load peak and trough period is adjusted, and large-scale consumption of renewa-ble energy and the reduction of carbon emissions are realized. First of all, a fine model of hydro-gen production and hydrogen use equipment is established to analyze the impact of adding hy-drogen mixing on the economy and low-carbon of the system. With green certificates and demand response, the utilization rate of hydrogen energy is improved to further explore the energy utiliza-tion rate and emission reduction capacity of the system. Secondly, on the basis of modeling, the optimal scheduling strategy is proposed with the sum of energy purchase cost, equipment opera-tion cost, carbon emission cost, wind curtailment cost and green certificate income as the lowest objective function. Considering the constraints such as hydrogen blending ratio and flexible load ratio of the pipeline network, a low-carbon economic scheduling model of hydrogen mixed natu-ral gas was established. The model was linearized and solved by using MATLAB and CPLEX solver. By comparing different scenarios, the superiority of the model and the effectiveness of the strategy are verified.