In this paper, we establish the generalized Qi-type inequality involving conformable fractional integrals. The results presented here would provide extensions of those given in earlier works.

Sensory descriptive analysis was used to evaluate the aged Feng-flavored baijiu. The results indicated that there are notable differences in the samples of different ages. The samples with shorter storage times and fresh distilled Baijiu present bran flavor, and fresh green flavor. with the increase of storage time, the fragrance of honey, sweetness, flowers, and aging gradually increases. The samples of Feng-flavored baijiu were dected by Headspace solid-phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC–TOFMS) , in total, 496 sustances were identified in all samples, mainly containing 14 types of substances, such as esters, aldehydes etc., of which 42 substances were found in Feng-flavored baijiu for the first time. Chemometrics was used to analyze the key differential compounds. 143 differential compounds closely related to aging were preliminarily screened, and principal component analysis revealed that these samples were separated by year. 65 differential compounds were selected out by partial least squares discriminant analysis(PLS-DA). Furthermore, 43 key differential compounds were selected from the aged Feng-flavored baijiu combined with variable importance in projection and Pearson correlation coefficients. Partial least squares regression (PLSR) was used to research the correlation of sensory properties and key differential compounds, and the results indicated that most compounds were closely related to the aged Baijiu . This study afford theoretical basis and reference for flavor research of Feng-flavored baijiu.

Two novel core-shell composites SiO2@PMDA-Si-Tb, SiO2@PMDA-Si-Tb-phen with SiO2 as the core and terbium organic complex as the shell, were successfully synthesized. The terbium ion was coordinated with organic ligand forming terbium organic complex in the shell layer. The bi-functional organosilane ((HOOC)2C6H2(CONH(CH2)3Si(OCH2CH3)3)2 (abbreviated as PMDA-Si) was used as the first ligand and phen as the second ligand. Furthermore, the silica-modified SiO2@PMDA-Si-Tb@SiO2, SiO2@PMDA-Si-Tb-phen@SiO2 core-shell-shell composites were also synthesized by sol–gel chemical route. An amorphous silica shell was coated around the SiO2@PMDA-Si-Tb and SiO2@PMDA-Si-Tb-phen core-shell composites. The core-shell and core-shell-shell composites both exhibited excellent luminescence in solid state. The luminescence of core-shell-shell composites was stronger than that of core-shell composites. Meanwhile, an improved luminescence stability property for the core-shell-shell composites was found in the aqueous solution. The core-shell-shell composites exhibited bright luminescence, high stability, long lifetime, and good solubility, which may present potential applications in the field of bio-medical.

Dietary factors are one of the risk factors that can impact the brain chemistry, which leads to mental distress. Based on our data mining approach, we found that mental distress in men is associated with eating unhealthy food. Our aim in this paper is to apply results from our big data analytics approach to inform system dynamics (SD) modeling to investigate the causal relationships between brain structures, nutrients from food and dietary supplements, and mental health. We perform descriptive analysis based on a large data set to estimate the SD modeling parameters. Finally, we calibrate the model towards a time series data collected for individuals on their dietary and distress patterns. The results reveal that bridging these different methodologies leads to further insights from the SD model and decreases the error of calibrated parameter values. Future research is needed to validate our initial results for investigating the relationship between mental distress and dietary intake.

Color image binarization plays a pivotal role in image preprocessing work, significantly impacting subsequent tasks, particularly in text recognition. This paper concentrates on Document Image Binarization (DIB), aiming to separate a image into foreground (text) and background (non-text content). Through a thorough analysis of conventional and deep learning-based approaches, we conclude that prevailing DIB methods leverage deep learning technology. Furthermore, we explore the receptive fields pre- and post-network training to underscore the Transformer model's advantages. Subsequently, we introduce a lightweight model based on the U-Net structure, enhanced with the Mobile ViT module to better capture global information features in document images. Given its adeptness at learning both local and global features, our proposed model exhibits superior performance on two standard datasets (DIBCO2012 and DIBCO2017) compared to state-of-the-art methods. Notably, our proposed DIB method presents a straightforward end-to-end model devoid of additional image preprocessing or post-processing. Moreover, its parameter count is less than a quarter of the HIP'23 model, which achives best results on three datasets(DIBCO2012, DIBCO2017 and DIBCO2018). Finally, two sets of ablation experiments were conducted to verify the effectiveness of the proposed binarization model.

We introduce a full binary directed tree structure to represent the set of natural numbers, further categorizing them into three distinct subsets: pure odd numbers, pure even numbers, and mixed numbers. We adopt a binary string representation for natural numbers and elaborate on the composite methodology encompassing odd- and even-number functions. Our analysis focuses on examining the iteration sequence (or composition) of the Collatz function and its reduced variant, which serves as an analog to the inverse function, to scrutinize the validity of the Collatz conjecture. To substantiate this conjecture, we incorporate binary strings into an algebraic formula that captures the essence of the Collatz sequence. By this means, we transform discrete powers of 2 into continuous counterparts, ultimately culminating in the smallest natural number, 1. Consequently, the sequence generated through infinite iterations of the Collatz function emerges as an eventually periodic sequence, thereby validating an enduring 87-year-old conjecture.

We use binary string to represent a natural number and show the composite procedure of odd-number and even-number functions, thus we propose full binary directed tree to represent the set of natural numbers and give another partition the natural number set to three sets: pure odd, pure even and mixed number. For the Collatz conjecture we make use of the parity of a natural number to analyse the sequence of iteration (or composite) of Collatz function and reduced Collatz function analog to the inverse function. We give tabular and binary strings to the algebra expression to state the sequence of Collatz, this is the key topic to proof the conjecture: the discrete powers of 2 can be changed to ultimately continuous powers of 2, finally get to pure even number and to the smallest number 1. The sequence created by the infinite iterations of the Collatz function becomes the ultimately periodic sequence if any natural number is the beginning value, proving the conjecture that has been held for 87 years.

With the advances in industry and commerce, passengers have become more accepting of environmental sustainability issues; thus, more people now choose to travel by bus. Government administration constitutes an important part of bus transportation services as the government gives the right-of-way to transportation companies allowing them to provide services. When these services are of poor quality, passengers may lodge complaints. The increase in consumer awareness and developments in wireless communication technologies have made it possible for passengers to easily and immediately submit complaints about transportation companies to government institutions, which has brought drastic changes to the supply-demand chain comprised of the public sector, transportation companies, and passengers. This study proposed the use of big data analysis technology including systematized case assignment and data visualization to improve management processes in the public sector and optimize customer complaint services. Taichung City, Taiwan was selected as the research area. There, the customer complaint management process in public sector was improved, effectively solving such issues as station-skipping, allowing the public sector to fully grasp the service level of transportation companies, improving the sustainability of bus operations, and supporting the sustainable development of the public sector-transportation company-passenger supply chain.

The high Nb-containing TiAl-based alloy ingot beyond laboratory scale with a composition of Ti-46Al-8Nb (at. %) was prepared by a vacuum induction melting process based on BaZrO3 refractory. An ingot without macroscopic casting defects (such as pipe shrinkage and center line porosity) was finally obtained, and the chemical composition, solidification path, microstructure and tensile properties of the ingots were investigated. The results show that the deviations of Al and Nb content along a 430 mm long central part of the ingot are approximately \mathrm{\pm}0.39 at. % and \mathrm{\pm}0.14 at. %, and the oxygen content in the ingot can be controlled at around 1000 ppm. During the solidification process, the alloy suffered from peritectic reaction and formed columnar grains with anisotropy. In addition to Al segregation and Nb segregation, β-phase particles associated with γ phase at the triple junction of the colonies were observed. Moreover, the mechanical properties of the ingot in the transverse direction are significantly better than those in the longitudinal direction, with a tensile strength of up to high as 700 MPa and a corresponding fracture elongation of 1.1 %.

The transverse momentum distribution of J/ψ mesons produced in pp collisions at the center-of-mass energy 5 TeV, 7 TeV，and 13 TeV is described by the modified Hagedorn function which is based on the Tsallis function and Hagedorn function. The calculated results by the modified Hagedorn function are in accord with experimental data measured by the LHCb Collaboration at LHC. The related parameters are obtained and analyzed.

Based on 2010, 2013 and 2015 CGSS data, the impact of Internet use and social capital on the income gap among farmers in the past five years is assessed at three time points using the OLS method and a quantile regression method. The study finds that (1) the income gap among farmers increases continuously in the five-year period, while Internet use plays a positive impact on farmers’ income growth in all five quartiles; the coefficient differences are all significantly negative, indicating that Internet use plays a positive role in alleviating the income gap between high-income and low-income farmer subgroups, and (2) social capital plays a positive role in moderating the income gap among farmers and that Internet use by farmers expands the boundary of social capital, which in turn increases the income level of and alleviates the income gap among farmers.

Capacity Expansion Models (CEMs) are optimization models used for long-term energy planning on national to continental scale. They are typically computationally demanding, thus in need of simplification, where one such simplification is to reduce the temporal representation. This paper investigates how using representative periods to reduce the temporal representation in CEMs distorts results compared to a benchmark model of a full chronological year. The test model is a generic CEM applied to Europe, equipped with a novel formulation for storage in model versions with reduced temporal representation. We test the performance of reduced models at penetration levels of wind and solar of 90%. Three measures for accuracy are used: (i) system cost, (ii) total capacity mix and (iii) regional capacity. We find that: (i) the system cost is well represented (~5% deviation from benchmark) with as few as ten representative days, (ii) the capacity mix is in general fairly well (~20% deviation) represented with 50 or more representative days, and (iii) the regional capacity mix displays large deviations (>50%) from benchmark for as many as 250 representative days. We conclude that modelers should be aware of the error margins when presenting results on these three aspects.

Over the last decades, the energy market around the world has reshaped due to accommodating the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system are performed using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of simulation and statistical results of EO with other optimization techniques showed that EO is more effective and superior.

Over the last decades, the energy market around the world has reshaped due to accommodating the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus 13 voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ 14 constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources 15 on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar 16 PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system are performed 17 using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of 18 simulation and statistical results of EO with other optimization techniques showed that EO is more effective 19 and superior.

With an increased interest in applications that require a clean background image, such as video surveillance, object tracking, street view imaging and location-based services on web-based maps, multiple algorithms have been developed to reconstruct a background image from cluttered scenes. Traditionally, statistical measures and existing image quality techniques have been applied for evaluating the quality of the reconstructed background images. Though these quality assessment methods have been widely used in the past, their performance in evaluating the perceived quality of the reconstructed background image has not been verified. In this work, we discuss the shortcomings in existing metrics and propose a full reference Reconstructed Background image Quality Index (RBQI) that combines color and structural information at multiple scales using a probability summation model to predict the perceived quality in the reconstructed background image given a reference image. To compare the performance of the proposed quality index with existing image quality assessment measures, we construct two different datasets consisting of reconstructed background images and corresponding subjective scores. The quality assessment measures are evaluated by correlating their objective scores with human subjective ratings. The correlation results show that the proposed RBQI outperforms all the existing approaches. Additionally, the constructed datasets and the corresponding subjective scores provide a benchmark to evaluate the performance of future metrics that are developed to evaluate the perceived quality of reconstructed background images.

The receptor-type protein tyrosine phosphatases (RPTPs) are involved in a wide variety of physiological functions which are mediated via their diverse extracellular regions. They play key roles in cell-cell contacts, bind various ligands and are regulated by dimerization and other processes. Depending on the subgroup they have been described as everything from ‘rigid rods’ to ‘floppy tentacles’. Here we review current experimental structural knowledge on the extracellular region of RPTPs and draw on AlphaFold structural predictions to provide further insights into structure and function of these cellular signalling molecules.

To enhance the safety of power grid operations, this study proposes a high-precision short-term photovoltaic power prediction method that integrates information from surrounding pho-tovoltaic stations and the Conv-LSTM-ATT model. In the deep learning prediction model, not only is numerical weather prediction (NWP) data from the target photovoltaic station used as input features, but also highly correlated features from nearby photovoltaic stations are incor-porated. The research begins by analyzing the correlation between irradiance and power se-quences, along with distance factors, to calculate a composite similarity index between the target and other regional photovoltaic stations. Stations with high similarity indices are then selected as data sources. Subsequently, Bayesian optimization techniques are employed to find the optimal data fusion ratios. Ultimately, using the selected data, power prediction mod-eling is conducted via the Conv-LSTM-ATT deep neural network. Experimental results con-firm the superiority of the proposed model, which demonstrates higher predictive accuracy compared to three other classical models. The data fusion strategy determined by Bayesian optimization significantly enhances prediction accuracy, reducing the root mean square error (RMSE) of the test set by 20.04%, 28.24%, and 30.94% for three weather types, respectively.

Zinc cobalt oxide-zinc hydroxide (ZnCo2O4-Zn(OH)2) microspheres were successfully fabricated on carbon cloth via a sample hydrothermal method. The surface morphology of these microspheres and their efficacy in degrading methyl violet were further modulated by varying the thermal annealing temperatures. The manipulation of thermal annealing temperatures was pivotal in adjusting the porosity of ZnCo2O4-Zn(OH)2 microspheres to amplify their photocatalytic performance. Various analytical techniques were utilized to evaluate the physical and chemical properties of the ZnCo2O4-Zn(OH)2 microspheres, including field-emission scanning electron microscopy, energy-dispersive spectroscopy, X-ray diffraction, field-emission transmission electron microscopy, X-ray photoelectron spectroscopy, and UV-vis spectroscopy. Compared to untreated ZnCo2O4-Zn(OH)2 microspheres, those subjected to thermal annealing exhibited increased specific surface area and light absorption capacity, rendering them highly effective photocatalysts under UVC light exposure. Subsequent studies have confirmed the superior performance of ZnCo2O4-Zn(OH)2 microspheres as a reusable photocatalyst for degrading methyl violet and tetracycline. Additionally, trapping experiments during the photodegradation process involving ZnCo2O4-Zn(OH)2 microspheres have identified hydroxyl radicals (·OH) and superoxide radicals (·O2–) as the primary reactive species.

The threat of fine particulate matter concentration (PM2.5) is increasing globally, Tackling this issue requires an accurate understanding of its trends and drivers. The article investigates the PM2.5 characteristics of 285 prefecture-level cities in China from 2000-2018 based on multiscale geographically weighted regression(MGWR), and the results show that（1）previous studies based on classical MGWR models may be somewhat unstable, while MGWR can reflect the scale of influence of different variables on the dependent variable, and its regression results are more reliable.（2）PM2.5 is very sensitive to carbon emission(CE) factors, and there is a high degree of spatial heterogeneity, and the influence scale of location is the smallest among all variables, close to the municipal scale.（3）In 2000, the constant term all, IS, OFT, CE, and LT positively affect PM2.5, while GDP (jurisdiction) and UR negatively affect PM2.5; in 2010, the constant term all, GDP (jurisdiction), IS, OFT and LT positively affect PM2.5, while UR and CE negatively affect PM2.5; in 2018 the constant term all, IS, OFT and CE factors positively affect PM2.5, and GDP (jurisdiction), UR and LT negatively affect PM2.5.

:Peat substrate is made from peat from drained peatlands, which is a limited resource. A realistic estimate is that 50% of the world’s wetlands have been lost. Peat is used in horticulture, especially for the cultivation of vegetables in greenhouses. The consequences of peatland exploitation are an in-crease in the greenhouse effect and a decrease in carbon stocks. Wood fiber can be used as an al-ternative to peat. The chemical properties of the growing media interact and change continuously due to the small volume of the growing media, which is limited by the growing container. This study aims to gain new knowledge on the impact of nutrient changes in the microbial degradation of carbon compounds in wood fiber and mixtures with peat substrate on the content and uptake of nutrients required by plants. Cucumbers (Cucumis sativus L.) variety “Dirigent H” developed in the Netherlands, were cultivated in growing media of peat substrate and wood fiber: (1) peat substrate (PS); (2) wood fiber (WF); (3) wood fiber and peat substrate 50/50 v/v (WF/PS 50/50); (4) wood fiber and peat substrate 25/75 v/v (WF/PS 25/75). The rates of fertilization were the following: (1) con-ventional fertilization (CF); (2) N13; (3) N23; (4) N30. The experiment was carried out in three repli-cations. As the amount of wood fiber increased, the humidity and pH of the growing medium in-creased. Fertilization of cucumbers with different rates of nitrogen influenced the nutrient uptake. Plants grown in 50/50 and 25/75 growing media had the best Cu uptake when fertilized with N23. When the plants grown in the wood fiber media and the 50/50 media were fertilized with N13, N23, and N30, the Mn content in the growing media at the end of the growing season was significantly lower than the Mn content in the media with conventional fertilization. Thus, nitrogen improved the uptake of Mn by plants grown not only in the wood fiber but also in combinations with peat sub-strate. Growing plants in wood fiber and fertilizing them with N13 can result in optimum uptake of micronutrients. The number and mass of cucumber fruits per plant were influenced by the amount of wood fiber in the growing media and the application of nitrogen fertilizer. The highest number of fruits and mass of fruits per plant was obtained significantly higher when cucumbers were grown on WF/PS 50/50 growing media with additional N13 fertilization.

: Greenhouse plants are usually grown in containers filled with growing media. Peat is the main component of the growing media used in greenhouses. However, peat substrate is made from peat from drained peatlands, which is a limited resource. Wood fiber can be an alternative to use as a growing media for controlled-climate crops. The chemical properties of the growing media interact and change continuously due to the small volume of the growing media, which is limited by the vegetative container. Therefore, this study aims to gain new knowledge on the impact of nutrient changes in the microbial degradation of carbon compounds in wood fiber and mixtures with peat substrate on the content and uptake of nutrients required by plants. Cucumbers (Cucumis sativus L.) were cultivated in growing media of peat substrate and wood fiber: (1) peat substrate (PS); (2) wood fiber (WF); (3) wood fiber and peat substrate 50/50 v/v (WF/PS 50/50); (4) wood fiber and peat substrate 25/75 v/v (WF/PS 25/75). The rates of fertilization were the following: (1) conventional fertilization (CF); (2) N13; (3) N23; (4) N30. Fertilization of cucumbers with different rates of nitrogen influenced the nutrient uptake. Plants grown in WF/PS 50/50 and WF/PS 25/75 growing media had the best Cu uptake when fertilized with N23. When the plants grown in the wood fiber media and the 50/50 media were fertilized with N13, N23, and N30, the Mn content in the growing media at the end of the growing season was significantly lower than the Mn content in the media with conventional fertilization. Thus, nitrogen improved the uptake of Mn by plants grown not only in the wood fiber but also in combinations with peat substrate. Growing plants in wood fiber and fertilizing them with N13 can result in optimum uptake of micronutrients. The number and mass of cucumber fruits per plant were influenced by the amount of wood fiber in the growing media and the application of nitrogen fertilizer. The highest number of fruits and mass of fruits per plant was obtained significantly higher when cucumbers were grown on WF/PS 50/50 growing media with additional N13 fertilization.

This study examines whether information about the winners of the Sustainability Reporting Award (SRA) contributes to the usefulness of the information in the financial statements. This study used a sample consisting of 110 winners of SRA (SRA firms) and 110 companies that did not receive SRA (non-SRA firms) from 2008 to 2016. The study found that earnings per share (EPS), book value per share (BVPS), and earnings per share change (EPSC) are value relevant information. Results of comparison between SRA firms and non-SRA fimrs, this study found that EPS positive association with stock price and with returns for SRA firms is higher than that for non-SRA firms. Findings of this study also show that, value relevance of BVPS for non-SRA firms is higher than that for SRA firms. When mesures of Price and BVPS are transformed into natural logarithm, the value relevance of BVPS for SRA firms is higher than that for non-SRA firms. Thus, the results are sensitive to measures of the variables. The findings of this study indicate that information about the winners of SRA contributes to the usefulness of financial statements.

This paper addresses the input coupling problem for the shape memory alloy (SMA) actuated parallel platform with completely unknown nonlinear dynamics. The problem means that in a parallel platform with multiple SMA actuators acting together, the displacement of one of the actuators will simultaneously affect the remaining actuators to change. Due to the coupling problem and nonlinear characteristics of the SMA actuators, it is not easy to control the platform to achieve bi-directional swing with completely unknown nonlinear dynamics. Therefore, a model-free adaptive sliding mode control method is proposed to improve the control accuracy of the complex motion of the platform, avoiding the complex modeling process of the SMA actuated parallel platform. Based on the model-free adaptive control (MFAC) theory, a multiple input and multiple output (MIMO) dynamic linearized mathematical model of the parallel platform is established using the online input and output data of the system. Then, a sliding mode controller is designed based on the dynamic model. A rigorous theoretical analysis proves that the proposed model-free adaptive sliding mode controller is able to stably control the SMA actuated parallel platform, and its tracking error is uniformly ultimately bounded (UUB). Finally, experiments are conducted on the established SMA actuated parallel platform. The results show that the proposed model-free controller is feasible and effective, and can control the system well to achieve the complex motion of bi-directional swing.

Colombia is noteworthy as a biodiversity hotspot, featuring an extraordinary number of en-demic orchids, birds, and butterflies. This exploratory study examines the perceptions of desti-nation image considering the cognitive and affective image in predicting behavioral intentions of ecotourists through symmetric data analysis. Using Partial Least Squares (PLS), the author(s) analyzed 64 survey responses collected of rural areas, including a new 15 statement scale spe-cialized on birdwatching. The findings support the reliability of the model, symmetric analysis presents the higher influence of emotions and affections in increasing intentions of recommen-dation, considering birdwatching as based on personal relationships. Additionally, the cognitive image for the birders despite representing destination attributes or sets of destination resources of a mental picture does not have the same impact on behavioral intentions. Therefore, manag-ers should develop positioning strategies based on the generation of emotions, because bird-watching tourists seek to have more emotional experiences.

Since the COVID-19 caused by SARS-CoV-2 break out in Wuhan China from Dec. 2019, it has spread to hundreds of countries up to now. Scientists from all over the world have paid tremendous efforts to research and try to control the disease. Previous studies suggested that some of the wild animals could be intermediate hosts between humans and origination of SARS-CoV-2, and some companion animals of humans can be infected by SARS-CoV-2, which raised our curiosity about cross-infection of SARS-CoV-2 between animals and humans. Thus, we select some kinds of animals that might have contact with humans to estimate the susceptibility to SARS-CoV-2 in different animals by evolutionary analysis of their receptors for SARS-CoV-2. The results show that some companion animals of the Felidae family like the cat has a higher infection possibility while the species of the Rodent family like the rat and mouse having close contact with humans show an opposite result, which consist with recent animal experiments and researches. These should raise concerns about cross-infection between human and companion animals or animals having close contact with humans which might turn animals into depositaries of the coronavirus even after control of SARS-CoV-2 spreading and cause second or more waves of infections after social reopening. Another side of our results stands by the opinion that bioinformatic analysis can be consistent with experiments in some respects so that we can prevent unnecessary sacrifice of laboratory animals in future experiments.

In large-scale parallel computing and communication systems, an interconnect network structure is usually modeled as a graph, in which vertices and edges correspond to processors and communication links, respectively. In a graph, the vertices and edges are likely to fail, so we must think about the fault tolerance of a graph. Connectivity is an important parameter in the study of faulty tolerance for a graph. In this paper, we study a special class of connectivity: $m$-component connectivity, this is a natural generalization of the classical connectivity of graphs defined in terms of the minimum vertex-cut. Let $F$ is a vertex set of $G$ $(i.e, F\subseteq V(G))$, if the following conditions are satisfied, we say $F$ is a $m$-component cut: $(1)$ $G-F$ is disconnected; $(2)$ the number of components in $G-F$ is greater than or equal to $m$. In another word, the $m$-component connectivity $c\kappa_{m}(G)$ is defined as $min\{|F|~|~F\subseteq V(G)$ and $F$ is a $m$-component cut$\}$. Determining $m$-component connectivity is still unsolved in most interconnection networks even for small $m'$s. Leaf-sort graph is a special Cayley graph, it has many special properties that are different from other Cayley graphs. So we need to pay attention to some of it's special properties when we study it. In this paper, we can get the values: $c\kappa_{3}(CF_{n})=3n-6$ $(n$ is odd$)$ and $c\kappa_{3}(CF_{n})=3n-7$ $(n$ is even$)$ for $n\geq3$; $c\kappa_{4}(CF_{n})=\frac{9n-21}{2}$ $(n$ is odd$)$ and $c\kappa_{4}(CF_{n})=\frac{9n-24}{2}$ $(n$ is even$)$ for $n\geq4$; $c\kappa_{5}(CF_{n})=6n-16$ $(n$ is odd$)$ and $c\kappa_{5}(CF_{n})=6n-18$ $(n$ is even$)$ for $n\geq5$.

The study findings revealed significant variability in various wood properties among different genetic families, although the static modulus of elasticity did not exhibit significant differences between the chosen genetic families. All measured wood properties decreased from the bottom to the top of the model trees. Wood hardness displayed a moderately negative correlation with wood density and weak correlations with MOE and MOR. Given the weak correlations between wood hardness and other wood mechanical properties, it is suggested that the MOEdyn would be a more suitable trait for genetic studies.

Reservoir computing is a machine learning method that uses the response of a dynamical system to a certain input in order to solve a task. As the training scheme only involves optimising the weights of the responses of the dynamical system, this method is particularly suited for hardware implementation. Furthermore, the inherent memory of dynamical systems which are suitable for use as reservoirs mean that this method has the potential to perform well on time series prediction tasks, as well as other tasks with time dependence. However, reservoir computing still requires extensive task dependent parameter optimisation in order to achieve good performance. We demonstrate that by including a time-delayed version of the input for various time series prediction tasks, good performance can be achieved with an unoptimised reservoir. Furthermore, we show that by including the appropriate time-delayed input, one unaltered reservoir can perform well on six different time series prediction tasks at a very low computational expense. Our approach is of particular relevance to hardware implemented reservoirs, as one does not necessarily have access to pertinent optimisation parameters in physical systems but the inclusion of an additional input is generally possible.

Macula fovea detection is a crucial prerequisite towards screening and diagnosing macular diseases. Without early detection and proper treatment, any abnormality involving the macula may lead to blindness. However, with the ophthalmologist shortage and time-consuming artificial evaluation, neither accuracy nor effectiveness of the diagnose process could be guaranteed. In this project, we proposed a deep learning approach on ultra-widefield fundus (UWF) images for macula fovea detection. This study collected 2300 ultra-widefield fundus images from Shenzhen Aier Eye Hospital in China. Methods based on U-shape network (Unet) and Fully Convolutional Networks (FCN) are implemented on 1800 (before amplifying process) training fundus images, 400 (before amplifying process) validation images and 100 test images. Three professional ophthalmologists were invited to mark the fovea. A method from the anatomy perspective is investigated. This approach is derived from the spatial relationship between macula fovea and optic disc center in UWF. A set of parameters of this method is set based on the experience of ophthalmologists and verified to be effective. Results are measured by calculating the Euclidean distance between proposed approaches and the accurate grounded standard, which is detected by Ultra-widefield swept-source optical coherence tomograph (UWF-OCT) approach. Through a comparation of proposed methods, we conclude that, deep learning approach of Unet outperformed other methods on macula fovea detection tasks, by which outcomes obtained are comparable to grounded standard method.

In the paper, the author introduces the notions "multi-order logarithmic numbers" and "multi-order logarithmic polynomials", establishes an explicit formula, an identity, and two recurrence relations by virtue of the Faa di Bruno formula and two identities of the Bell polynomials of the second kind in terms of the Stirling numbers of the fi rst and second kinds, and constructs some determinantal inequalities, product inequalities, logarithmic convexity for multi-order logarithmic numbers and polynomials by virtue of some properties of completely monotonic functions.

Scientists who hope to obtain a faculty position at a primarily undergraduate institution (PUI) need a distinct skill set and outlook on their future teaching and research career. To obtain a position at a PUI, candidates should 1) design a strategy for obtaining a faculty position that suits each individual’s career goals and aspirations, 2) prepare for the application process, on-campus interview, and contract negotiations, and 3) plan a strategy for the probationary period leading up to tenure and promotion. Given the different types of PUIs, candidates need to consider whether they seek a position that consists of all or mostly all teaching, or both teaching and research. Candidates should educate themselves on the expectations at PUI’s, including current thought, practice, and aspirations for science pedagogy, and gain teaching experience prior to seeking a suitable position. If the candidate’s goal is a position with both teaching and research, it is important to discuss with the current research mentor what projects the candidate can take with them to their new position. The candidate should also consider what types of projects will be successful with undergraduate student researchers in a PUI research environment Importantly, candidates should clearly demonstrate a commitment to diversity and inclusion in their teaching, research, and outreach, and application materials should demonstrate this. On interviews, candidates should be knowledgeable about the mission, values, and resources of the institution and how the candidate will contribute to that mission. Once hired, new faculty should discuss a formal or informal mentoring plan during the probationary period that includes peer evaluations on a regular basis, and maintain communication with the department chair or designated mentor regarding teaching, research, and service activities.

Forest resources are renewable,rational exploitation and utilization of forest resources are not only conducive to sustainable development of population, but also can obtain higher economic benefits. Based on actual timber harvesting problems,a combined harvesting model of timber and non-timber with nonlinear harvesting term was established.Firstly, using the qualitative theory of ordinary differential equations, the dynamic behavior of the model is studied, and the existence and stability of the equilibrium point of the model are proved .Secondly, the optimal control solution is obtained by using the optimal control theory.Finally, the optimal harvesting strategy of timber and non-timber products is given based on the numerical simulation results, which provides a certain theoretical basis for the sustainable development of forestry ecological economy.

Background and aims: Despite recent advances in advanced prostate cancer treatments, there are no clinically useful biomarkers or treatments for men with such cancers. Targeted therapies have shown promise, but there remain fewer actionable targets in prostate cancer than in other cancers. This work aims to characterize BRD9, currently understudied in prostate cancer, and investigate its co-expression with other genes to assess its potential as a biomarker and therapeutic target in human prostate cancer. Materials and methods: Omics data from a total of 2053 prostate cancer patients across 11 independent datasets were accessed via Cancertool and cBioPortal. mRNA expression and co-expression, mutations, amplifications, and deletions were assessed with respect to key clinical parameters including survival, Gleason grade, stage, progression and treatment. Network and pathway analysis was carried out using Genemania, and heatmaps were constructed using Morpheus. Results: BRD9 is overexpressed in prostate cancer patients, especially those with metastatic disease. BRD9 expression did not differ in patients treated with second generation antiandrogens versus those who were not. BRD9 is co-expressed with many genes in the SWI/SNF and BET complexes, as well as those in common signaling pathways in prostate cancer. Summary and conclusions: BRD9 has potential as a diagnostic and prognostic biomarker in prostate cancer. BRD9 also shows promise as a therapeutic target, particularly in advanced prostate cancer, and as a co-target alongside other genes in the SWI/SNF and BET complexes, and those in common prostate cancer signalling pathways. These promising results highlight the need for wider experimental inhibition and co-targeted inhibition of BRD9 in vitro and in vivo, to build on the limited inhibition data available.

This study analyzed the CO2 capture potential for Parque Natural Regional Serrania de las Quinchas buffer area in Colombia. For this purpose, multitemporal analysis for land covering for years 1989, 2000, 2006, 2011, 2017 and 2021 was made using the Normalized Difference Vegetation Index (NDVI), and Corine Land Cover (CLC) methodology. In the same way, Aboveground Biomass (AGB) was measured for representative parcels by measuring tree’s diameters and heights and applying the adequate allometric models; carbon content in soils was measured too. Results show that dense forest has grown since 1989 and the carbon stock in all the vegetation covers increased by 14,3% from 1989 until 2021, using literature data for tropical humid forests. If measured AGB values obtained in this study are used, the carbon stock average is 3 times this value. Measured carbon average content in AGB was 374,3 Ton C/Ha, well above the average for the content reported for humid tropical forests in Colombia; carbon content in soils was 897,19 Ton/Ha, 2,4 times that found in the AGB. In total, an average of 1271,49 Ton C/Ha (AGB+ soil) was found and a pattern of dense forest recovery was found, but in a more dispersed way than in the past. A very interesting potential for existing forests recovery was found for this area. Strategies for this include the development of sustainable practices, land use management, everything pursuing biodiversity preservation and the participation and leading of the local communities.

The current SARS-CoV-2 pandemic is still threatening humankind. Despite first successes in vaccine development and approval, no antiviral treatment is available for COVID-19 patients. The success is further tarnished by the emergence and spreading of mutation variants of SARS-CoV-2, for which some vaccines are not effective anymore. This highlights the urgent need for antiviral therapies even more. This article describes how the Genome-Scale Metabolic Model (GEM) of the host-virus interaction of human alveolar macrophages and SARS-CoV-2 was refined by incorporating the latest information about the virus’s structural proteins and the mutant variants B.1.1.7 and B.1.351. We confirmed the initially identified guanylate kinase as a potential antiviral target with this refined model and identified further potential targets from the purine and pyrimidine metabolism. The model was further extended by incorporating the virus’ lipid requirements. This opened new perspectives for potential antiviral targets in the altered lipid metabolism. Especially the phosphatidylcholine biosynthesis seems to play a pivotal role in viral replication. The guanylate kinase is even a robust target in all investigated mutation variants currently spreading worldwide. These new insights can guide laboratory experiments for the validation of identified potential antiviral targets. Only the combination of vaccines and antiviral therapies will effectively defeat this ongoing pandemic.

A new quinazolinone alkaloid, named peniquinazolinone A (1), as well as eleven known com-pounds, 2-(2-hydroxy-3-phenylpropionamido)-N-methylbenzamide (2), viridicatin (3), viridicatol (4), (±)-cyclopeptin (5a/5b), dehydrocyclopeptin (6), cyclopenin (7), cyclopenol (8), methyl-indole-3-carboxylate (9), 2,5-dihydroxyphenyl acetate (10), methyl m-hydroxyphenylacetate (11), conidiogenone B (12), was isolated from the endophytic Penicillium sp. HJT-A-6. The chemical structures of all compounds were elucidated by comprehensive spectroscopic analysis, including 1D, 2D NMR, and HRESIMS. The absolute configuration at C-13 of peniquinazolinone A (1) was established by applying the modified Mosher’s method. Compounds 2, 3, and 7 exhibited an op-timal promoting effect on the seed germination of Rhodiola tibetica at a concentration of 0.01 mg/mL, while the optimal concentration for compounds 4 and 9 to promote Rhodiola tibetica seed germination was 0.001 mg/mL. Compound 12 showed optimal seed-germination-promoting activity at a concentration of 0.1 mg/mL. Compared with the positive drug 6-benzyladenine (6-BA), compounds 2, 3, 4, 7, 9, and 12 could extend the seed-germination period of Rhodiola tibetica up to the 11th day.

Coal is an important resource that is closely related to people’s lives and has an irreplaceable role. However, coal mine safety accidents occur from time to time in the process of working underground. To this end, this paper proposes a coal mine environmental safety early warning model to detect abnormalities and ensure worker safety in a timely manner by assessing the underground climate environment. In this paper, the support vector machine (SVM) parameters are optimized using an improved artificial hummingbird algorithm (IAHA), and its safety level is classified by combining various environmental parameters. To address the problems of insufficient global exploration capability and slow convergence of the artificial hummingbird algorithm during iterations, a strategy incorporating Tent chaos mapping and backward learning is used to initialize the population, a Levy flight strategy is introduced to improve the search capability during the guided foraging phase, and then the simplex method is introduced to replace the worst value before the end of each iteration of the algorithm. The IAHA-SVM safety warning model was established using the improved algorithm to classify and predict the safety of the coal mine environment into four classes. Finally, the performance of the IAHA algorithm and the IAHA-SVM model are simulated separately. The simulation results show that the convergence speed and the search accuracy of the IAHA algorithm are improved, and the performance of the IAHA-SVM model has a significant improvement.

Circulating extracellular microvesicles (cEVs) are characterised by presenting surface antigens of parental cells. Since their biogenesis involves the translocation of phosphatidylserine (PS) from the inner to the outer-leaflet of the plasma membrane, exposed PS has been considered as a recognition hallmark of cEVs. However, not all cEVs externalise PS. In this study we have phenotypically and quantitatively characterised cEVs by flow cytometry with special attention to the proportions of PS in chronic heart failure patients (cHF; n=119) and reference non-HF group (n=21). PS─-cEVs were predominantly found in both groups. Parental markers showed differential pattern depending on PS exposure. Endothelium-derived and connexin 43-rich cEVs were mainly PS─-cEVs and significantly increased in cHF. On the contrary, platelet-derived cEVs were mostly PS+ and were increased in non-HF. We observed similar levels of PS+- and PS─-cEVs in non-HF subjects when analysing immune cell-derived EVs, but there was a subset-specific difference in cHF patients. Indeed, those cEVs carrying CD45+, CD29+, CD11b+ and CD15+ were mainly PS+-cEVs, while those carrying CD14+, CD3+ and CD56+ were mainly PS─-cEVs. In conclusion, endothelial and red blood cells are stressed in cHF patients as detected by a high shedding of cEVs. Despite PS+-cEVs and PS─-cEVs represent two distinct cEV populations, their release and potential function as both biomarkers and shuttles for cell communication seem unrelated to PS content.

Buckling defect will appear on the outer surface of the deformed ring during constrained ring rolling (CRR) of aluminum alloy thin wall conical ring with inner high ribs (AATWCRIHR), if the geometrical dimension of the ribs doesn't match the wall thickness. To avoid the buckling defect, a quantitative method for characterizing the degree of the buckling defect is proposed using the area of buckling profile. Then an orthogonal experimental scheme was designed taking the width of the middle rib, thickness of wall, and height of the middle rib as design variables and defining the area of buckling profile as optimization objective. Subsequently, a quadratic polynomial response surface model was established by combining the optimization algorithm with the finite element method (FEM), and the geometrical dimension of the middle ribs of the deformed AATWCRIHR is optimized. Also the optimal parameter combination to minimize the area of buckling profile is obtained and verified using FE simulation. Results show that the AATWCRIHR after optimization doesn’t generate the buckling defect during constrained ring rolling, and it is proved that the quantitative buckling defect representation method and the optimization design method based on the response surface model and the finite element simulation results are feasible for the constrained ring rolling process of the AATWCRIHR.

The massive use of electronic equipment has raised concerns about electromagnetic (EM) pollution, leading to increased attention to EM shielding in both civil and military applications. EM absorption materials play a crucial role in reducing the energy of microwaves projected onto their surface. In this work, we propose a novel OTA (over-the-air) antenna test method to evaluate and analyze the functionality of EM absorption materials. This method offers a new and practical way to assess the effectiveness of these materials. Measured results indicate that the presence of the EM absorption material led to a decrease in antenna gain of approximately 2-3 dB, a reduction in efficiency of more than 10-15%, and a smaller radiation pattern during the actual testing process. These findings highlight the impact of EM absorption materials on antenna performance. Compared to the traditional S-parameter testing method, the gain comparison testing method exhibits the advantages of higher accuracy and simpler operation in the lower frequency experiment.

In recent years, Atherosclerotic Cardiovascular Disease (ACVD), Obesity and Diabetes, have increase exponentially worldwide. In the present work, we evaluate the genoprotective effect of consuming a flavonoids-rich chocolate and the improvement in the biochemical parameters related to the prevention and treatment of cardiovascular risk and metabolic syndrome in young Mexican adults. A randomized, placebo-controlled, double-blind study was undertaken in the Autonomous University of Baja California. The treatments were a daily intake of 2 grams of dark chocolate containing 70% cooca or milk chocolate. Total phenolic compounds and flavonoids were evaluated in both chocolates. Anthropometrical and Biochemical parameters were measured in the 84 participants before and after the study. Buccal epithelial genotoxicity was also evaluated from the beginning to the end of the experiment in the participants. Result suggested that flavonoids of cocoa intake have protective effects against DNA damage, and Biochemical parameters (total cholesterol, triglycerides, and LDL-cholesterol level in blood) and anthropometrical parameters (waist circumference) were also improved after six months of daily intake of 2 grams of dark chocolate with a 70% of cocoa.

This paper presents the results of a recent study that was conducted with a number of German municipalities/cities. Based on the obtained and briefly presented recommendations emerging from the study, the authors propose the concept of an Urban Data Space (UDS), which facilitates an eco-system for data exchange and added value creation thereby utilizing the various types of data within a smart city/municipality. Looking at an Urban Data Space from within a German context and considering the current situation and developments in German municipalities, this paper proposes a reasonable classification of urban data that allows to relate the various data types to legal aspects and to conduct solid considerations regarding technical implementation designs and decisions. Furthermore, the Urban Data Space is described/analyzed in detail, and relevant stakeholders are identified, as well as corresponding technical artifacts are introduced. The authors propose to setup Urban Data Spaces based on emerging standards from the area of ICT reference architectures for Smart Cities, such as DIN SPEC 91357 “Open Urban Platform” and EIP SCC. Thereby, the paper walks the reader through the construction of an UDS based on the above mentioned architectures and outlines all the goals, recommendations and potentials, which an Urban Data Space can reveal to a municipality/city.

In the paper, the author finds bounds of the sine and cosine along a circle on the complex plane in terms of two double inequalities for the norms of the sine and cosine along a circle on the complex plane.

In the paper, the author discusses and computes bounds of the sine and cosine along straight lines on the complex plane.

Construction using earth materials demonstrates ecological sustainability using locally sourced natural materials and environmentally friendly demolition methods. In this study, the environmental impact of adding cement to soil materials for rammed-earth farmhouse construction in rural China was investigated and comparatively simulated using the One Click LCA database, focusing on the conflict between sustainability objectives and the practical aspects of cement addition. By analyzing how the addition of cement aligns with local construction practices and by addressing the debate surrounding the inclusion of cement in rammed earth construction, our objective is to provide insights into achieving a balance between the environmental impact and the pragmatic considerations of using cement in earthen building practices. Three local structure scenarios are evaluated via simulations: a cement-stabilized rammed earth wall, a fired brick wall, and a localized reinforced concrete frame structure. The quantitative environmental impacts are assessed, and the qualitative differences in adaptation, economic sustainability, and other factors are examined in the context of present-day development in rural China. The results show that the use of cement-stabilized rammed earth wall-supported structures is associated with higher embodied carbon emissions compared to structures supported by reinforced concrete frames and enclosed by brick walls; however, these emissions are lower than those for brick wall-supported structures, while effectively meeting the structural requirements. In addition, the use of cement-stabilized earth for perimeter walls simplifies material management and disposal throughout the building's life cycle, and the cost-effectiveness of cement has been found to be substantially greater than that of reinforced concrete frames and brick structures, improving economic viability and social acceptability, especially among low-income communities in rural areas.

We hypothesized that reticuloruminal temperature and pH, as well as cow activity, can be used as biomarkers for the early diagnosis of clinical mastitis in dairy cows. Therefore, we aimed to detect the relationship between reticuloruminal temperature and pH, cow activity, and clinical mastitis in dairy cows. We randomly selected cows with clinical mastitis and clinical healthy cows (HG) out of 600 milking cows. We recorded the following parameters during the experiment: reticulorumen tem-perature (RR temp.), reticulorumen pH (RR pH), and cow activity. We used smaXtec boluses (smaXtec animal care technology®, Graz, Austria). In this investigation, reticulorumen data ob-tained seven days before diagnosis were compared to HG data from the same time period. CM cows were observed on the same days as the healthy cows. The healthy group’s RR pH was 7.32% higher than that of cows with CM. Reticulorumen temperature was also 1.25% higher in the CM group than in the control group. The healthy group had a higher average value for walking activity and was 17.37% higher than the CM group. The data of reticulorumen pH changes during 24 h showed that during the day, the pH changed from 5.53 to 5.83 in the CM group. By contrast, pH changed from 6.05 to 6.31 in the control group. The lowest reticulorumen pH in the CM group was detected on the third day before diagnosis. It was 15.76% lower than the highest reticulorumen pH detected on the sixth day before diagnosis. The lowest reticulorumen pH in CM cows was detected at 0 and 1 days before diagnosis. It was 1.45% lower than the highest reticulorumen pH detected on the second day before diagnosis. The lowest walking activity in the CM group was detected 0 days before diagnosis, 50.60% lower than on the fifth day before diagnosis. The lowest walking activity was detected 0 days before diagnosis, 39.57% lower than on the seventh day before diagnosis. In this study, we found that reticuloruminal temperature, reticuloruminal pH, and cow ac-tivity could be used as biomarkers for the early diagnosis of clinical mastitis in dairy cows.

The chemically synthesized polymer polyacrylamide (HPAM) in conventional reservoirs has achieved excellent oil displacement, but its oil displacement is poor in extreme reservoir environments. To develop biopolymer oil flooding agent under extreme reservoir conditions, the viscosity increasing and rheological properties of three biopolymers, diutan gum, xanthan gum, and scleroglucan, were studied under extreme reservoir conditions (high salt, high temperature, strong acid, and alkali), and the effects of temperature, mineralization, pH, and other factors on their viscosities and long-term stability properties were analyzed and compared. The results showed that under the temperature of 90℃ and below, the three kinds of biopolymers had the best viscosity-increasing ability. The viscosity of the three kinds of biopolymers was 80.94, 11.57, and 59.83mPa·s, respectively, when the concentration was 1500mg/L and the salinity was 220g/L. At the shear rate of 250s-1,100℃~140℃, scleroglucan has the best viscosification. At 140℃, the solution viscosity is 19.74mPa·s, and the retention rate can reach 118.27%. The results of the long-term stability study showed that the solution viscosity of scleroglucan with mineralization level of 220 mg/L was 89.54% viscosity retention in 40 days, and the diutan gum could be stabilized for 10 days, and the viscosity was maintained at 90 mPa·s. All three biopolymers are highly acid and alkali-resistant, with viscosity variations of less than 15% in the pH3~10 range. Rheological tests have shown that both of them have better viscoelastic properties than xanthan gum due to the peculiar double-helix structure of xanthan gum and the rigid triple-helix structure of scleroglucan. Therefore, the two biopolymers, diutan gum, and scleroglucan have the potential for extreme reservoir oil displacement applications, and it is recommended to use diutan gum for oil displacement in reservoirs up to 90℃ and scleroglucan for oil displacement in reservoirs between 100℃ and 140℃.

In the paper, by convolution theorem for the Laplace transforms and analytic techniques, the author finds necessary and sufficient conditions for complete monotonicity, monotonicity, and inequalities of several functions involving polygamma functions. By these results, the author derives a lower bound of a function related to the sectional curvature of the manifold of the beta distributions. Finally, the author poses several guesses and open problems related to monotonicity, complete monotonicity, and inequalities of several functions involving polygamma functions.

The 3x+1 problem asks the following: Suppose we start with a positive integer, and if it is odd then multiply it by 3 and add 1, and if it is even, divide it by 2. Then repeat this process as long as you can. Do you eventually reach the integer 1, no matter what you started with? Collatz conjecture (or 3n+1 problem) has been explored for about 85 years. In this paper, we convert an integer number from decimal to binary number, and convert the Collatz function to binary function, which is multiplication and division of two binary numbers. Finally the iternation of the Collatz function, eventually reach the integer 1, thus we solve the 3x+1 problem completely.

In recent years, with the development of the Internet of Things and distributed computing, the "server-edge device" architecture has been widely deployed. This study focuses on leveraging autoencoder technology to address the binary classification problem in network intrusion detection, aiming to develop a lightweight model suitable for edge devices. Traditional intrusion detection models face two main challenges when directly ported to edge devices: inadequate computational resources to support large-scale models and the need to improve the accuracy of simpler models. To tackle these issues, this research utilizes Extreme Learning Machine for its efficient training speed and compact model size to implement autoencoders. Two improvements over the latest related work are proposed: First, to improve data purity and ultimately enhance detection performance, this study partitions the data into multiple regions based on the prediction results of these autoencoders. Second, leveraging autoencoder characteristics to investigate further the data within each region. We used the public dataset NSL-KDD to test the behavior of the proposed mechanism. The experimental results show that when dealing with multi-class attacks, the model's performance was significantly improved, the accuracy and the F1-score are improved by 3.5% and 2.9%, respectively maintaining its lightweight nature.

Precision and accuracy estimation is an important index used to reflect the measurement performance and quality of a measurement system. To reveal the significance and connotations of the precision and accuracy estimation index of a close-range photogrammetry system, several common precision and accuracy estimation methods used in close-range photogrammetry are explained from a theoretical perspective, and the mechanism of the internal coincidence precision estimation and the external coincidence accuracy estimation are deduced, respectively. Through detailed experimental design and testing, the validity and reliability of the proposed precision and accuracy estimation methods are verified, which provides strong evidence for the quality control, optimisation, and evaluation of the measurement results from a close-range photogrammetry system. At the same time, it has significance for the further development of precision and accuracy estimation analysis of close-range photogrammetry systems.

Infrared dim and small target detection is a key technology of various detection tasks. However, due to the lack of shape, texture, and other information, it is a challenging task to detect dim and small targets. Recently, since many traditional algorithms ingore global information of infrared images, they generate some false alarms in complicated environments. To address this problem, in this paper, a coarse-to-fine deep learning-based method is proposed to detect dim and small targets. Firstly, a coarse-to-fine detection framework integrating deep learning and background prediction is applied for detecting targets. The framework contains of coarse detection module and fine detection module. In coarse detection stage, Region Proposal Network (RPN) is employed to generate masks in target candidate regions. Then, for further optimize the result, inpainting is utilized to predict the background by the global semnantic of images. In this paper, inpainting algorithm with a mask aware dynamic filtering module is incorporated into the fine detection stage to estimate background in candidate target areas. Finally, compared with existing algorithms, the experimental results indicate that the proposed framework have effective detection capability and robustness for complex surroundings.

Multi-cameras system is widely applied in 3D computer vision especially when multiple cameras are distributed on both sides of the measured object. The calibration methods of multi-cameras system are critical to the accuracy of vision measurement and the key is to find an appropriate calibration target. In this paper, a high-precision camera calibration method for multi-cameras system based on transparent glass checkerboard and ray tracing is described, which is used to calibrate multiple cameras distributed on both sides of the glass checkerboard. Firstly, the intrinsic parameters of each camera is obtained by Zhang’s calibration method. Then, multiple cameras capture several images from the front and back of the glass checkerboard with different orientations, and all images contain distinct grid corners. As the cameras on one side are not affected by the refraction of glass checkerboard, extrinsic parameters can be directly calculated. However, the cameras on another side are influenced by the refraction of glass checkerboard, and the direct use of projection model will produce calibration error. A multi-cameras calibration method using refractive projection model and ray tracing is developed to eliminate this error. Furthermore, both synthetic and real data are employed to validate the proposed approach. The experimental results of refractive calibration show that the error of the 3D reconstruction is smaller than 0.2 mm, the relative errors of both rotation and translation are less than 0.014%, and the mean and standard deviation of reprojection error of 4-cameras system are 0.00007 and 0.4543 pixel. The proposed method is flexible, high accurate, and simple to carry out.

Both bacteria product flagellin and macrophages are implicated in HIV infection/disease progression. However, the impact of their interaction on HIV infection and the associated mechanisms remain to be determined. We thus examined the effect of the flagellins on HIV infection of primary human macrophages. We observed that the pretreatment of macrophages with the flagellins from the different bacteria significantly inhibited HIV infection. The mechanistic investigation showed that the flagellin treatment of macrophages downregulated the major HIV entry receptors (CD4 and CCR5) and upregulated the CC chemokines (MIP-1α, MIP-1β, and RANTES), the ligands of CCR5. These effects of the flagellin could be compromised by a toll like receptor 5 (TLR5) antagonist. Given the important role of flagellin as a vaccine adjuvant in TLR5 activation-mediated immune regulation and in HIV infection of macrophages, future investigations are necessary to determine the in vivo impact of flagellin-TLR5 interaction on macrophage-mediated innate immunity against HIV infection and the effectiveness of flagellin adjuvant-based vaccines studies.

Europium (Eu)-doped fluorapatite (FA) nanorods has a similar biocompatibility with hydroxyapatite (HA) in terms, attracted much attention as cell imaging biomaterials due to their luminescent property. Here, we will discuss the new feature of europium doped fluorapatite (Eu-FA) nanorods as anticancer drug carrier. Eu-FA nanorods was prepared using a hydrothermal method. The morphology, crystal structure, fluorescence and composition are investigated. The specific crystal structure, enabling an effective loading of drug molecules. Doxorubicin (DOX), used as an anticancer model drug, was shown to be effectively loaded onto the surface of the nanorods. The DOX release was fairly pH-dependent, occurring more rapidly at pH 5.5 than pH 7.4 was observed. The intracellular penetration of the DOX-loaded Eu-FA nanorods (Eu-FA/DOX) can be imaged in situ due to the self-fluorescence property. Treatment of melanoma A375 cells with Eu-FA/DOX elicited a more effective apoptosis rate than direct DOX treatment. Overall, Eu-FA show great promise for tracking and treating tumor, may potentially useful as a multifunctional carrier system to effectively load and sustainably deliver drugs.

The characteristics of gap plasmon formed by nanoparticle-on-mirror (NPOM) structure composed of metal nanoparticles (MNP) and metal thin films have aroused the interest of various optoelectronic devices. The resonant spectrum obtained by the internal coupling effect of gap can be flexibly controlled by the polarization of incident light and the thickness of the dielectric layer between MNP and metal thin films. We have theoretically studied the resonance spectra of polarization-dependent gold ellipsoidal nanoparticles (GENP) and gold thin films in the gap region of NPOM structures. GENP and gold thin films are separated by a dielectric layer with a refractive index of 1.36. We observe that the intensity of the local electric field resonance peak in the gap region is inversely proportional to the polarization angle. Similarly, the intensity of the local electric field resonance peak in the gap region is inversely proportional to the thickness of the dielectric layer. We have obtained more than 2200 V/m local electric field intensity (dielectric layer thickness 0.3nm). Finally, the resonant peak wavelength of the electric field in the gap region of the NPOM structure is also controlled by the polarization angle of the incident light and the thickness of the dielectric layer.

The CuCrSn alloy is promising as high-strength and high-conductivity Cu alloy due to its relative low smelting requirement, while thus far reports on the CuCrSn alloy is still quite lacked. In this study, the microstructure and properties of Cu-0.20Cr-0.25Sn (wt%) specimens prepared under different rolling and aging combinations were comprehensively characterized, in order to reveal the effects of cold rolling and aging on the CuCrSn alloy. The results show that increasing the aging temperature from 400 ºC to 450 ºC can obviously accelerates the precipitation, and the cold rolling before aging significantly increases the initial microhardness and promotes the precipitation. Whereas, the deformation hardening will be eliminated during the aging process, making the microhardness even decrease monotonically when the aging temperature and the rolling ratio before aging are high. Performing the cold rolling after the aging can maximize the effects of precipitation strengthening and deformation strengthening, and its adverse impact on the conductivity is not serious. A tensile strength of 506.5 MPa and a conductivity of 70.33% IACS were obtained with such a treatment, only the elongation decreases. Different strength-conductivity combinations of the CuCrSn alloy can be achieved through appropriate combinations of the aging and post aging cold rolling conditions.

One of the most significant challenges that is facing urban-planning ,is the develop-ment of a transportation network, particularly in historical Syrian cities, which are characterized by their compact urban form. Historical Syrian cities, including historical city of Aleppo, present difficulties due to the essential balance required between saving cultural heritage and meeting the needs of a present-day population. This study basically addresses the city's key elements and planning issues, including traffic density, pedestrian safety, and the massive spreading of motor-ized vehicles. The objective of this study is to analyze the street structure, understanding its components and problems in order to develop a methodology that can be used to enhance urban mobility and to improve the structure of the historical city. for this purpose, two main methods were employed, method of analyzing geographical data based on Geographic Information Systems (GIS) and K-Means cluster analysis method. These two methods were employed to gain detailed and clear vision into mobility patterns of historical Aleppo. Which involved careful processing of data, such as street names, locations, components, quantities, and widths, based on the author’s observations and notes and a variety of local and international sources. This analysis process will not only reveal the current hierarchy of streets but also demonstrates the dynamical and complicated formation of transportation structures of the historical city. The findings of the study describe the challenges faced by historic city centers and highlight the interrelationship between the following: urban structure, objects of cultural heritage, tourism plans, and mobility patterns. The application of spatial analysis method serves as a technique that reveals the formulation of possible scenarios that helps to develop the transportation structure in the historical city of Aleppo. These generated scenarios will be used as typical solutions that can be generalized to all similar historic Syrian cities.

Background Obesity compromises the health of a woman's pregnancy and her newborn. Aim: To describe weight-gaining changes throughout pregnancy and evaluating outcomes for the mother and the baby. Methods A retrospective review of women who delivered singletons using Large Perinatal Registry. According to their BMI, patients were categorized into four categories: underweight, normal, overweight, and obese. Mode of delivery, gestational diabetes, hypertensive diseases, obstetric cholestasis, and postpartum hemorrhage were the main maternal outcome measures. The newborn outcome indicators were birth weight, NICU hospitalization, premature birth, and stillbirth. Results The study sample included 2,352 natives (25%) and 7,058 expatriates (75%). The majority of the sample (4726) were aged 20-29 years, 43.6% were aged 30-39 years, and 2.1% and 3.9% were aged 19 years and 40 years respectively. The incidence of hypertension, obstetric cholestasis, diabetes, postpartum hemorrhage, and cesarean section varied among the entire sample. In the underweight group, the incidence of CS was 15.7%, in the normal weight group (24.9%), in the overweight group (31.3%), and in the obese group (41%). Hypertensive disorders were 3 times more prevalent in obese women than in normal-weight women (2%), and 5.3% of obese women had PPH compared to 5. 6% of women of normal weight. The underweight groups gained the most weight during pregnancy, whereas the obese gained the least. Conclusions A significant proportion of pregnant women in our sample will become obese by the time of delivery. Obesity during pregnancy is associated with negative maternal and fetal outcomes.

The type III receptor tyrosine kinase FLT3 is a pivotal kinase for hematopoietic progenitor cell regulation, with significant implications in acute myeloid leukemia (AML) through mutations like internal tandem duplication (ITD). This study delves into the structural intricacies of FLT3, the roles of activation loop mutants, and their interaction with tyrosine kinase inhibitors. Coupled with this, the research leverages molecular contrastive learning and protein language modeling to examine interactions between small molecule inhibitors and FLT3 activation loop mutants. Utilizing the ConPLex platform, over 5.7 million unique FLT3 activation loop mutants-small molecule pairs were analyzed. The binding free energies of three inhibitors were assessed, and cellular apoptotic responses were evaluated under drug treatments. Notably, the introduction of the Xepto50 scoring system provides a nuanced metric for drug efficacy. The findings underscore the modulation of molecular interactions and cellular responses by Y842 mutations in FLT3-KD, highlighting the need for tailored therapeutic approaches in FLT3-ITD-related malignancies.

Background: Recommended CKD first-line diagnostics is based on GFR-determination by Creatinine. Cystatin C-use may provide better assessment. Methods: We compared creatinine- and cystatin C-derived eGFR determination in first-line di-agnostic of 112 hospital patients aged >60 years (median=76 years). Patients were judged kid-ney-sane according to first-line diagnostic recommendations (N=61, eGFR (CKD-EPI) ≥60ml/min/m2, total urine protein <150mg/g creatinine, urinary red and white blood cells not increased) or classified at-risk for kidney insufficiency due to aortic valve dysfunction (N=51). Plausibility of eGFR-values was evaluated retrospectively by final case diagnoses. Results: eGFR (CAPA) was found linearly correlated to eGFR (CKD-EPI) (R2=0.5, slope=0.69, p<0.0001). In 93/112 (>80%) cases, eGFR (CAPA) yielded lower values (on average ≈20%). In 55/112 (49%) cases CKD-stage decreased. CKD-reclassification from kidney-sane to kid-ney-insufficient state (i.e. CKD1/2 to CKD3a/b or 4) or reclassification to more severe kidney in-sufficiency (i.e. CKD3a3b/4 or 3b4) was found in 41/112 (37%) cases. Worsening of CKD-classification (kidney-sanekidney-insufficient) based on eGFR (CAPA) was in 30% of cases plausible in the light of final case-diagnoses. Conclusion: In elderly patients (>60 years), renal function appears systematically overestimated by creatinine-based eGFR (CKD-EPI) heralding for this group employment of cystatin C-based eGFR (CAPA) as first-line diagnostic.

Background. Artificial Intelligence (AI) is an advanced technology for the latest 20 years. Machine learning (ML) and deep learning (DL) are the major innovations for AI, which has been applied for multiple fields. Ophthalmology has become to be one of the most significant disciplines for human healthcare. Methodology. This study utilizes methods of text mining and bibliometric analysis to explore applications of AI to ophthalmology. 179 related articles from Web of Science (WOS) and 96 papers from China National Knowledge Infrastructure (CNKI) are explored during the period of 2000 to 2021. A descriptive analysis of major trends, journal releasing, topic mapping and quotation relationships is implemented in this paper. Leading authors, journals, institutions, nations and references in the related research are identified. Results. Findings show that the application of AI technologies in ophthalmologic diagnosis with optical coherence tomography (OCT) fundus images is the core topic for this area’s studies, especially for diabetic retinopathy (DR), aged macular degeneration (AMD) and glaucoma. It is also be predicted as the core direction over the recent years. Besides, The USA, England and China is the most competitive countries in this scientific filed. Journals of Ophthalmology, Investigative Ophthalmology and Visual Science, Eye, Acta Ophthalmologica and Scientific Reports are the top five journal related to the research area. There is a significant difference between WOS and CNKI databases pertaining to the application of Artificial Intelligence (AI) to ophthalmology, especially for the historic development, topic mapping and discipline category. Finally, the potential academic value of interdisciplinary subject of “AI in Ophthalmology” and tradition Chinese medicine (TRM) is discussed. Limitations and suggestions for the future research is indicated at the end of this paper.

Nowadays, brain signal processing is performed rapidly in various brain-computer interface (BCI) applications. Most researchers focus on developing new methods for the future or improving the basic implemented models to identify the optimum standalone feature set. Our research focuses on four ideas. One of them introduces future communication models, and the others are for improving old models or methods. These are: 1) new communication imagery model instead of speech imager using the mental task: Due to speech imagery is very difficult, and it is impossible to imagine sound for all of the characters in all of the languages. Our research introduces a new mental task model for all languages that call Lip-sync imagery. This model can use for all characters in all languages. This paper implemented two lip-sync for two sounds, characters or letters. 2) New combination Signals: Selecting an inopportune frequency domain can lead to inefficient feature extraction. Therefore, domain selection is so important for processing. This combination of limited frequency ranges proposes a preliminary for creating Fragmentary Continuous frequency. For the first model, two s intervals of 4 Hz as filter banks were examined and tested. The primary purpose is to identify the combination of filter banks with 4Hz (scale of each filter bank) from the 4Hz to 40Hz frequency domain as new combination signals (8Hz) to obtain well and efficient features using increasing distinctive patterns and decreasing similar patterns of brain activities.3) new supplement bond graph classifier for SVM classifier: When SVM linear uses in very noisy, the performance is decreased. But we introduce a new bond graph linear classifier to supplement SVM linear in noisy data. 4) a deep formula recognition model: it converts the data of the first layer into a formula model (formula extraction model). The main goal is to reduce the noise in the subsequent layers for the coefficients of the formulas. The output of the last layer is the coefficients selected by different functions in different layers. Finally, the classifier extracts the root interval of the formulas, and the diagnosis does based on the root interval. For all of the ideas achieved the results of implementing methods. The results are between 55% to 98%. Less result is 55% for the deep detection formula, and the highest result is 98% for new combination signals.

A millimeter-wave microstrip leaky-wave antenna array based on the substrate-integrated waveguide (SIW) and the complementary split-ring resonator (CSRR) is proposed in this paper. The slow wave characteristics of the SIW are enhanced by etching two rows of symmetrical CSRR-type slots on the surface of the SIW layer. The magnetic coupling between the CSRR-SIW layer and equally spaced circular patches array on the upper layer realizes the radiation of electromagnetic energy. In the 23~30 GHz (relative bandwidth 26.4%) operating frequency band, the horizontal polarization radiation beam scanning from -62° to -2° is realized, with a peak gain of 9.6~11.7 dBi, and the cross-polarization ratio is more than 43.8 dB.

Macrophages as a source and target of GDF-15

Ferrocenium (Fc+) inherits a number of molecular/electronic properties from the neutral counterparts’ ferrocene (Fc) including the high symmetry. Both Fc+ and Fc prefer the eclipsed structure (D5h) over the staggered structure (D5d) by an energy of 0.36 kcal·mol-1. The present study using the recently developed excess orbital energy spectrum (EOES) shows that the open shell Fc+ cation exhibits similar conformer dependent configurational changes to the neutral Fc conformer pair. A further energy decomposition analysis (EDA) discloses that the reasons for the preferred structures are different between Fc+ and Fc. The dominant differentiating energy between the Fc+ conformers is the electrostatic energy (EEstat), whereas in neutral Fc, it is the quantum mechanical Pauli repulsive energy (EPauli). Within the D5h conformer of Fc+, the EOES reveals that the -electrons of Fc+ experience more substantial conformer dependent energy changes than the -electrons (assumed the hole is in a β orbital).

In the paper, the authors survey integral representations (including the Lévy--Khintchine representations) and applications of some bivariate means (including the logarithmic mean, the identric mean, Stolarsky's mean, the harmonic mean, the (weighted) geometric means and their reciprocals, and the Toader--Qi mean) and the multivariate (weighted) geometric means and their reciprocals, derive integral representations of bivariate complex geometric mean and its reciprocal, and apply these newly-derived integral representations to establish integral representations of Heronian mean of power 2 and its reciprocal.

Although there are extensive literature reports on the use of gold nanoparticle (AuNP) based homogeneous assays for detection of biomolecules, very few experimental description and procedures involving their preparation are described. In this study, AuNPs conjugated to Bovine Serum Albumin or Envelope protein from Dengue II were developed as a homogeneous immunoassay for antibody detection. We report here optimization of key parameters to prepare an immunoassay like conjugation protein concentration, centrifugation time, electrolyte addition and assay temperature. We determined that saturating protein concentrations improved AuNPs surface coverage and uniformity of the assay and addition of sodium chloride improved sensitivity of the antibody detection method and assay stability. Furthermore, we showed that dynamic light scattering can be used to monitor changes in gold nanoparticles in the preparation and detection steps. Additionally, numerical simulations of the plasmonic optical response of AuNPs were carried out to scan for size-dependent response of the AuNPs. The AuNPs homogeneous immunoassay developed was further used in the detection of antibodies in vitro to detect Dengue virus infection.

In this perspective article, we ponder topographical enhancements of artificial neural networks. In our recent paper in JMLR, we proved a quasi-equivalence between the network width and depth and also discussed the power of intra-links, which can be viewed as network height. In 1982, Hopfield published a network to model human associative memory, which contains many loops for dynamic evolution toward fixed points. Based on noising-denoising loops, diffusion models are recently developed to enable Bayesian modeling and inference with big data. Furthermore, we envision development of multi-AI-agent systems through “netware” engineering as a quantum leap of software engineering for emergent behaviors and autonomous AI at individual and population levels. We believe that the novel use of links and loops in space and time via multi-scale coupling would catalyze the next-generation neural networks.

Evodiamine is a bioactive alkaloid that is specified as a biomarker for the quality assessment of Evodia rutaecarpa and for traditional Chinese medicines containing this plant. We previously reported that quantitative structure-activity modeling indicated that evodiamine may cause cardiotoxicity. However, previous investigations have indicated that evodiamine has beneficial effects in patients with cardiovascular diseases and there are no previous in vitro or in vivo reports of evodiamine-induced cardiotoxicity. The present study investigated the effects of evodiamine on primary cultured neonatal rat cardiomyocytes in vitro, and on zebrafish in vivo. Cell viability was reduced in vitro, where evodiamine had a 24-h 50% inhibitory concentration of 28.44 µg/mL. Cells exposed to evodiamine also showed increased lactate dehydrogenase release and maleic dialdehyde levels, and reduced superoxide dismutase activity. In vivo, evodiamine had a 10% lethal concentration of 354 ng/mL and induced cardiac malfunction, as evidenced by changes in heart rate and circulation, and pericardial malformations. This study indicated that evodiamine could cause cardiovascular side effects involving oxidative stress. These findings suggest that cardiac function should be monitored in patients receiving preparations containing evodiamine.

This paper presents a study to accurately evaluate defects in reinforced concrete decks using ultrasonic pulse-echo signals. Two validation specimens were designed and tested where reinforced concrete deck slab specimens included planned voids and defects. A commercial Ultrasonic Pulse-Echo (UPE) device obtains 2-D images of the void/defect locations of the reinforced concrete deck. The UPE is based on the ultrasonic shear-wave test method using dry-point-contact transmitting and receiving transducers and employing a synthetic aperture focusing technique. The authors analyzed the recorded UPE A-scan data to enhance the accuracy of estimating the defects' locations using the synthetic aperture focusing technique imaging method. The analysis benefitted from an advanced denoising approach and defect echo peak extraction based on empirical modal decomposition, Hurst exponent characterization, and Hilbert envelope estimation. While output from conventional UPC devices can only provide qualitative results, the new method provides quantitative information on the anomalies inside the reinforced concrete deck. The developed approach accurately assists with assessing the location and depth of the voids/defects in the reinforced concrete deck slabs.

In the paper, the authors survey integral representations of the Catalan numbers and the Catalan–Qi function, discuss equivalent relations between these integral representations, supply alternative and new proofs of several integral representations, collect applications of some integral representations, and present sums of several power series whose coefficients involve the Catalan numbers.

The undoped and tungsten (W)-doped vanadium dioxide (VO₂) thin films were prepared by electron beam evaporation associated with ion-beam assisted deposition (IAD). The influence of different W-doped contents (3%-5%) on the optical, electrical, structural, and thermos-mechanical properties of VO₂ thin films was investigated experimentally. Spectral transmittance results showed that with the increase of W-doped contents, the transmittance in the visible light range (400-750 nm) decreases from 60.2% to 53.9%, and the transmittance in the infrared wavelength range (2.5 μm to 5.5 μm) drops from 55.8% to 15.4%. As the W-doped content increases, the residual stress in the VO₂ thin film decreases from -0.276 GPa to -0.238 GPa, but the surface roughness increases. For temperature-dependent spectroscopic measurements, heating the VO2 thin films from 30°C to 100°C showed the most significant change in transmittance for the 5% W-doped VO₂ thin film. When the heating temperature exceeds 55°C, the optical transmittance drops significantly, and the visible light transmittance drops by about 11%. Finally, X-ray Diffraction (XRD) and scanning electron microscope (SEM) were used to evaluate the microstructure characteristics of VO₂ thin films.

This paper is concerned with developing an efficient numerical algorithm for fast implementation of the sparse grid method for computing the $d$-dimensional integral of a given function. The new algorithm, called the MDI-SG ({\em multilevel dimension iteration sparse grid}) method, implements the sparse grid method based on a dimension iteration/reduction procedure, it does not need to store the integration points, nor does it compute the function values independently at each integration point, instead, it reuses the computation for function evaluations as much as possible by performing the function evaluations at all integration points in a cluster and iteratively along coordinate directions. It is shown numerically that the computational complexity (in terms of CPU time) of the proposed MDI-SG method is of polynomial order $O(Nd^3 )$ or better, compared to the exponential order $O(N(\log N)^{d-1})$ for the standard sparse grid method, where $N$ denotes the maximum number of integration points in each coordinate direction. As a result, the proposed MDI-SG method effectively circumvents the curse of dimensionality suffered by the standard sparse grid method for high-dimensional numerical integration.

Snow-covered regions are the main source of reflection of incident shortwave radiation (ISR) on Earth’s surface. The deposition of light-absorbing particles (LAPs) on these regions increases the capacity of snow to absorb ISR and decreases surface snow albedo (SSA), which intensifies the radiative forcing leading to accelerated snowmelt and modifications of the hydrologic cycle. In this work we investigate changes in SSA and radiative forcing (RF) induced by LAPs in the Upper Aconcagua River Basin (Chilean central Andes) using remote sensing satellite data (MODIS), in-situ spectral SSA measurements, and the ISR (Chilean Solar Explorer platform) during the austral-winter months (May to August) for the 2004-2016 period. To estimate the changes in SSA and RF, we define two spectral ranges: i) an enclosed range (Ecr) between 841-876 nm, which isolates effects of Black-Carbon, an important LAP derived from anthropogenic activities, and ii) a broadband range (Bbr) between 300-2500 nm. Our results show that percent variations in SSA in the Ecr are higher than in the Bbr, regardless of the total amount of radiation received, which may be attributed to the presence of LAPs as these particles have a greater impact on SSA at wavelengths in the Ecr band than in the Bbr band.

In the paper, the authors find two explicit formulas and recover a recursive formula for the generalized Motzkin numbers. Consequently, the authors deduce two explicit formulas and a recursive formula for the Motzkin numbers, the Catalan numbers, and the restricted hexagonal numbers respectively.

In order to study the effect of explosion load on the flexural performance of RC beams, two RC beams of the same size were carried out explosion test and bearing capacity test successively. Piezoelectric intelligent aggregate was embedded in the beams in advance to monitor the damage state of the beams, which realized the whole process of damage monitoring of the concrete inside the structure from explosion damage to compression damage.Based on wavelet packet analysis and residual bearing capacity damage evaluation criteria, the beam damage was quantitatively evaluated, and the bending bearing capacity of RC beam after explosion damage was compared and analyzed.The results show that the change of concrete strain gauge signal, the phenomenon of crack development and the increase of internal crack development index indicate that the RC beam is damaged by explosion load.After explosion damage, the damage index of the beam increases and the residual bending capacity decreases, which proves that the piezoelectric intelligent aggregate sensor can effectively monitor the bending capacity change of the component after explosion damage.

Recent years have witnessed a boom of fashion bloggings sharing information about clothing and cosmetics on diverse social media platforms. Constant exposure to fashion-related digital information heavily impacts the cognition and behaviour of Chinese youth. Compared to the substantial studies on the impact of social media, scarce research has been conducted on how youth’s cognitive processing of fashion-related digital information interacts with motivational factors to determine the subsequent behaviour. This study made an initial attempt to address this issue by exploring the successive associations between clothing motivation (amotivation, controlled, and autonomous motivation), online critical thinking (for information credibility, objectivity, and relevance), and the subsequent behavioural intentions. A total of 1997 Chinese youths with diverse educational backgrounds voluntarily participated in the study. Results confirmed the direct links between clothing motivation and behavioural intentions, but these links were mediated by different online critical thinking skills. This study provides new insights for both practitioners and scholars in the fields of education, psychology, social media, and marketing.

Sparse reward long horizon task is a major challenge for deep reinforcement learning algorithm. One of the key barriers is data-inefficiency. Even in the simulation environment, it usually takes weeks to training the agent. In this study, a data-efficiency training framework is proposed, where a curriculum learning is design for the agent in the simulation scenario. Different distributions of the initial state are set for the agent to get more informative reward during the whole training process. A fine-tuning of the parameters in the output layer of the neural network for value function is conduct to bridge the gap between sim-to-real. An experiment of UAV maneuver control is conducted in the proposed training framework to verify the method more efficient. We demonstrate that data-efficiency is different for the same data in different training stages.

The Mara River basin (MRB) has a world-famous ecosystem, but the vegetation has been damaged due to economic development in recent years, and there is little known about the area that will experience severe vegetation damage in the future. Based on the vegetation vulnerability system, principal component analysis, and three CMIP6 scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5), vegetation vulnerability was calculated in the base period (2010-2019), near-term period (2020-2059) and long-term period (2060-2099) in the MRB. The spatial cluster of vegetation vulnerability was revealed by spatial correlation analysis, and the transition of vegetation vulnerability of different periods was analyzed by stochastic matrix. The results showed that in all periods, the vulnerability showed a high-high cluster in the east, and a low-low cluster midstream and downstream. From the stochastic matrix, the area of high vulnerability increased the least under the SSP1-2.6, while it increased the most under the SSP5-8.5. The vegetation vulnerability upstream increased the most from the base period to the near-term period and long-term period in the MRB. By comparing the vegetation vulnerability under different scenarios, and pointing out the areas with the highest vulnerability increase, this study can better provide comprehensive decision-making for vegetation protection in the MRB.

Abstract: A fertilisation experiment with aim to determine the effect of different potassium fertiliser rates and their interaction with nitrogen and phosphorus on field rotation productivity, potassium balance, fertiliser utilization and changes in content of potassium in soil was carried out in Lithuania between 1971 and 2020. The multi-factorial scheme with 45-treatment plots, where seven (including zero) rates of nitrogen, phosphorus and potassium fertilisers were studied. The experimental treatments during the study period included winter wheat, spring wheat, spring barley, sugar beet, spring rapeseed, annual and perennial grasses. It was found that potassium fertilisers was the most effective on agricultural crops when used in combination with other major plant nutrients – nitrogen and phosphorus. The balance of potassium (K2O) in soil, when nitrogen and phosphorus fertilisers were applied together, to compensate for potassium removal, when applying low nitrogen (N) 72 kg ha-1 and phosphorus (P2O5) 64 kg ha-1 fertiliser rates, 128 kg ha-1 of potassium fertilisers is required. When using high nitrogen 180 kg ha-1 and phosphorus 160 kg ha-1 fertiliser rates, 160 kg ha-1 of potassium is needed. The highest potassium uptake, reaching 51.6%, was achieved when plants had been fertilised with nitrogen 108 kg ha-1, phosphorus 96 kg ha-1, and potassium 96 kg ha-1. When fertilising with potassium fertilisers alone, the content of plant available K2O content in the soil increased, while fertilisation with nitrogen and phosphorus combined it’s decreased, except in the plots where the plants had been fertilised with potassium fertiliser at rates of 128 kg ha-1 and higher. Due to the influence of fertilizers, the amount of non-exchangeable potassium in the soil also increased, but relatively less compared to the amount of available potassium content.

Bearings are widely used in various types of electrical machinery and equipment. As their core components, failures will often cause serious consequences . At present, most methods of parameter adjustment are still manual adjustment of parameters. This adjustment method is susceptible to prior knowledge and easy to fall into the local optimal solution, failing to obtain the global optimal solution and requires a lot of resources.Therefore, this paper proposes a new method of bearing fault diagnosis based on wavelet packet transform and convolutional neural network optimized by simulated annealing algorithm.The experimental results show that the method proposed in this paper has a more accurate effect in feature extraction and fault classification compared with traditional bearing fault diagnosis methods. At the same time, compared with the traditional artificial neural network parameter adjustment, this paper introduces the simulated annealing algorithm to automatically adjust the parameters of the neural network, thereby obtaining an adaptive bearing fault diagnosis method. To verify the effectiveness of the method, the Case Western Reserve University bearing database was used for testing, and the traditional intelligent bearing fault diagnosis method was compared. The results show that the method proposed in this paper has good results in bearing fault diagnosis. Provides a new way of thinking in the field of bearing fault diagnosis in parameter adjustment and fault classification algorithms

With the intensification of population aging in rural areas, it becomes increasingly important to analyze the post-retirement migration intention of rural residents and the variables influencing these intentions. In this study, we focus on rural residents aged 45 to 60 and investigate the main variables that influence the post-retirement migration intention of rural residents, using survey data collected from 164 households in three different rural areas and the logistic regression model. From the result of this study, we found that gender, part-time employment, savings level, children's residence and occupation stability, and interest in urban living positively affect migration intention. In contrast, the number of rural companions, relationships with others in rural areas, and evaluation of rural living have a negative effect. In addition, we employ age and the proportion of mobile income as control variables to examine the variables that influence the post-retirement migration intention in different age groups and mobile income groups. The analysis reveals that, the variables influencing post-retirement migration intention varied across age groups and mobile income groups, and this variation can be attributed to the differences between groups' characteristics.

This study empirically examines the spatial spillover effect of various environmental regulations on green technology innovation using panel data from 284 county-level cities in China between 2007 and 2019. A geographical-economic spatial weight matrix is constructed, and the spatial Durbin model is employed to identify the specific characteristics of this spillover effect. The findings indicate that the spatial spillover effect of green technology innovation primarily occurs through geographical transmission. However, there is no significant spatial autocorrelation when using the economic distance weight matrix. Various types of environmental regulations influence the spatial spillover effect of green technology innovation in distinct ways. Specifically, Market-motivated environmental regulation exhibits a U-shaped relationship with the spatial spillover effect, while Command-controlled environmental regulation demonstrates an inverted U-shaped relationship, suggesting a complementary effect. Additional research shows that the upgrading of industrial structure acts as a mediator between command environmental regulation and the spatial spillover effect of green technology innovation. Government departments should comprehensively coordinate Market-motivated environmental regulation and Command-controlled environmental regulation, accurately assess the intensity of Command-controlled measures, and prevent the migration of green technology innovation elements caused by excessive regulatory measures within enterprises.

It has recently been shown that, contrary to the wide belief that a shift-enabled condition (necessary for any shift-invariant filter to be representable by a graph shift matrix) can be ignored because any non-shift-enabled matrix can be converted to a shift-enabled matrix, such a conversion in general may not hold for a directed graph with non-symmetric shift matrix. This paper extends this prior work, focusing on undirected graphs where the shift matrix is generally symmetric. We show that while, in this case, the shift matrix can be converted to satisfy the original shift-enabled condition, the converted matrix is not associated with the original graph, that is, it does not capture anymore the structure of the graph signal. We show via a counterexample, that a non-shift-enabled matrix cannot be converted to a shift-enabled one and still maintain the topological structure of the underlying graph, which is necessary to facilitate localized signal processing.

The transportation of feed pellets via pneumatic conveying plays an improtant role in feed industry. In recent years, many efforts are made both exprimentally and numerically to gain a better understanding of the underlying mechanism for pneumatic conveying. Though few of those research is directly related to feed pellets, it can be beneficial to draw a full picture of rencent development in pneumatic conveying, with emphasis on aspects extendable to feed transportation. This paper reviews first the major factors concerning feed pellets pneumatic conveying, such as particle breakage, pipe wear and electrostatic. Building on that, new advancement including emerging new technologies in experiments and simulations are discussed, with a focus on the experimental measurements and mathematical models, repectively. The needs for future research and the analogy to feed pellets tranportation is given lastly.

In the paper, by virtue of convolution theorem for the Laplace transforms, Bernstein's theorem for completely monotonic functions, and other techniques, the author finds necessary and sufficient conditions for a difference constituted by four derivatives of a function involving trigamma function to be completely monotonic.

The most cited evidence for (nonbaryonic) dark matter has been an apparent lack of visible mass to gravitationally support the observed orbital velocity of matters in rotating disk galaxies. Yet measurement of the mass of celestial objects cannot be straightforward, requiring theories derived from the known physical laws along with some empirically established semi-quantitative relationship. The most reliable means for determining the mass distribution in rotating disk galaxies is to solve a force balance equation according to Newton’s laws from measured rotation curves, similar to calculating the Sun’s mass from the Earth’s orbital velocity. Another common method to estimate galactic mass distribution is to convert measured brightness from surface photometry based on empirically established mass-to-light ratio. For convenience, most astronomers commonly assumed a constant mass-to-light ratio for estimation of the so-called “luminous” or “visible” mass, which should not be expected accurate. The mass determined from rotation curve typically exhibit an exponential-like decline with galactrocentric distance, qualitatively consistent with observed surface brightness. This fact scientifically suggests variable mass-to-light ratio of baryonic matter in galaxies without the need for dark matter.

Pneumatic nebulizers (as variations based on the Collison nebulizer) have been widely used for producing fine aerosol droplets from a liquid material. The basic working principle of those nebulizers has been qualitatively described as utilization of the negative pressure associated with an expanding gas jet to syphon liquid into the jet stream, then to blow and shear into liquid sheets, filaments, and eventually droplets. Detailed quantitative analysis based on fluid mechanics theory is desirable, to gain in-depth understanding of the liquid aspiration mechanism among other aspects of the Collison nebulizer behaviour. The purpose of present work is to investigate the nature of negative pressure distribution associated with compressible gas jet flow in the Collison nebulizer by a computational fluid dynamics (CFD) analysis, using an OpenFOAM® compressible flow solver. The value of the negative pressure associated with a gas jet flow is examined by varying geometric parameters of the jet expansion channel adjacent to the outlet of jet orifice. Such an analysis can provide valuable insights into fundamental mechanisms for liquid aspiration, helpful for designing improved pneumatic atomizer in the Aerosol Jet® direct-write system for micro-feature, high-aspect-ratio material deposition

In the paper, by induction and recursively, the author proves that the generating function of multivariate logarithmic polynomials and its reciprocal are a Bernstein function and a completely monotonic function respectively, establishes a Lévy-Khintchine representation for the generating function of multivariate logarithmic polynomials, deduces an integral representation for multivariate logarithmic polynomials, presents an integral representation for the reciprocal of the generating function of multivariate logarithmic polynomials, computes real and imaginary parts for the generating function of multivariate logarithmic polynomials, derives two integral formulas, and denies the uniform convergence of a known integral representation for Bernstein functions.

In the paper, by virtue of some properties for the Riemann zeta function, the author finds a double inequality for the ratio of two consecutive Bernoulli numbers with even indexes and analyzes the approximating accuracy of the double inequality.

In the paper, the author (1) presents an explicit formula and its inversion formula for higher order derivatives of generating functions of the Bell polynomials, with the help of the Faà di Bruno formula, properties of the Bell polynomials of the second kind, and the inversion theorem for the Stirling numbers of the first and second kinds; (2) recovers an explicit formula and its inversion formula for the Bell polynomials in terms of the Stirling numbers of the first and second kinds, with the aid of the above explicit formula and its inversion formula for higher order derivatives of generating functions of the Bell polynomials; (3) constructs some determinantal and product inequalities and deduces the logarithmic convexity of the Bell polynomials, with the assistance of the complete monotonicity of generating functions of the Bell polynomials. These inequalities are main results of the paper.

In the paper, the authors establish two identities to express the generating function of the Chebyshev polynomials of the second kind and its higher order derivatives in terms of the generating function and its derivatives each other, deduce an explicit formula and an identities for the Chebyshev polynomials of the second kind, derive the inverse of an integer, unit, and lower triangular matrix, present several identities of the Catalan numbers, and give some remarks on the closely related results including connections of the Catalan numbers respectively with the Chebyshev polynomials, the central Delannoy numbers, and the Fibonacci polynomials.

Fast-growing teak is widely cultivated in Indonesia to address the supply and demand of teak trees. However, efforts still need to be made to evaluate the condition of standing teak trees during their growth period. Studies on nondestructive testing (NDT) of wood based on electrical properties through dielectric spectroscopy (DS) are recently being developed, especially for standing tree evaluation. The study aimed to analyze the dielectric value of a fast-growing standing teak tree at frequency ranges 250 kHz – 60 MHz and to understand the relationships between physical and anatomical properties. Dielectric spectroscopy data were collected directly on the trees 4, 5, and 7 years old using a capacitance measurement system. Meanwhile, physical and anatomical samples were taken using a Ø 0.5 cm increment borer. The results showed that fiber length (FL), lumen diameter (LD), and fiber wall thickness (FWT) were significantly different at each tree age. This research found the optimal dielectric frequency to discriminate the wood properties in standing trees. There is a weak relationship (R= 0.2) in predicting the anatomical wood properties, while moderate to strong relationships (R= 0.4 to R= 0.8) are found in predicting wood density based on the selected frequency and moisture content variables. Further analyses and data processing can be improved by finding significant variables in the capacitance measurement system.

MicroRNA (miRNA) is a typical class of small RNAs that could modulate gene expression in trans at the post-transcriptional level. miRNAs bind to the miRNA binding sites (MBSs) in target mRNAs by sequence complementarity. Alternative splicing (AS) is another commonly occurred process in pre-mRNAs that changes the isoforms of a gene. It is hypothesized that there should be an interaction for gene regulation that involves both AS and miRNA targeting. Studies have verified this hypothesis in the model organism Arabidopsis thaliana. High-throughput sequencing data suggested that in Arabidopsis a considerably large fraction of MBSs are affected by AS events. The overlapping between MBS and AS exceeds the randomly simulated number. Functional experiments have indicated that the AS events are required for the gene expression changes of miRNA targets. Therefore, AS and MBS are mutually favored. The observed expression changes caused by miRNAs could also be contributed by AS events. In the present perspective article, we propose that the AS analysis should be incorporated in the differential-expression analysis of miRNA studies. When defining a differentially-expressed gene, it should be clarified whether the change in gene expression is caused by AS events or solely by miRNA targeting.

To generate a probability density function (PDF) for fitting probability distributions of real data, this study proposes a deep learning method which consists of two stages: (1) a training stage for estimating the cumulative distribution function (CDF) and (2) a performing stage for predicting the corresponding PDF. The CDFs of common probability distributions can be adopted as activation functions in the hidden layers of the proposed deep learning model for learning actual cumulative probabilities, and the differential equation of trained deep learning model can be used to estimate the PDF. To evaluate the proposed method, numerical experiments with single and mixed distributions are performed. The experimental results show that the values of both CDF and PDF can be precisely estimated by the proposed method.

The global environmental impact of plastic waste is significant, with only 9% being recycled, causing pollution and harming the environment and humans. Due to increased traffic, limited funding, and dwindling natural resources, Jordan's road network is deteriorating rapidly. Pavement performance can be improved through high-quality materials and sustainable construction practices. The research investigates using Polyethylene Terephthalate as a polymer additive in asphalt mixtures to enhance their properties. Basalt and limestone mixtures were applied to asphalt mixtures. The optimal binder content for the control mixture was 4.8% for basalt and 4.93% for limestone. When modified with 10% PET, the basalt mixture showed slightly better stability than the control mix, while higher PET proportions led to reduced strength. PET-modified mixtures consistently displayed higher flows and bulk densities, with a more pronounced impact on the basalt mixture. PET increased the air-void ratio in basalt but had minimal effect on VMA. PET offers economic and environmental advantages, saving 8.4% of the original bitumen cost. As a result, limestone mixture properties, which are inferior to basalt mixture properties, improved significantly compared to basalt mixture properties. PET has the potential to create sustainable and high-performing asphalt mixtures, providing valuable insights for road construction and environmental management.

The ZIPs (ZRT/IRT-like proteins) play critical roles in the absorption, transport, and intracellular balance of metal ions essential for various physiological processes in plants. However, little is known about the pan-genomic characteristics and properties of ZIP genes in cucumber (Cucumis sativus L.). In this study, we identified 10 CsZIP genes from the pan-genome of 13 C. sativus accessions. Among them, only CsZIP10 showed no variation in protein sequence length. We analyzed the gene structure, conserved domains, promoter cis-elements, and phylogenetic relationships of these 10 CsZIP genes derived from "9930". Based on phylogenetic analysis, the CsZIP genes were classified into three branches. Amino acid sequence comparison revealed the presence of conserved histidine residues in the ZIP proteins. Analysis of promoter cis-elements showed that most promoters contained elements responsive to plant hormones. Expression profiling in different tissues showed that most CsZIP genes were expressed at relatively low levels in C. sativus leave, stem, and tendril, and CsZIP7 and CsZIP10 were specifically expressed in root, indicating their potential involvement in the absorption and transport of metal ions. Transcriptomic data indicated that these 10 ZIP genes displayed responses to both downy mildew and powdery mildew, and CsZIP1 were significantly downregulated after both salt and heat treatments. In conclusion, this study deepens our understanding of the ZIP gene family and enhances our knowledge of the biological functions of CsZIP genes in C. sativus.

In wireless sensor networks (WSNs), each sensor node can estimate the global parameter from the local data in distributed manner. This paper proposed a robust diffusion estimation algorithm based on minimum error entropy criterion with self-adjusting step-size, which are referred to as diffusion MEE-SAS (DMEE-SAS) algorithm. The DMEE-SAS algorithm has fast speed of convergence and is robust against non-Gaussian noise in the measurements. The detailed performance analysis of the DMEE-SAS algorithm is performed. By combining the DMEE-SAS with diffusion minimum error entropy (DMEE) algorithms, an Improving DMEE-SAS algorithm is proposed, in non-stationary environment where tracking is very important. The Improving DMEE-SAS algorithm can avoid insensitivity of the DMEE-SAS algorithm due to the small effective step-size near the optimal estimator, and obtain a fast convergence speed. Numerical simulations are given to verify the effectiveness and advantages of these proposed algorithms.

Unmanned aerial vehicles (UAVs) have increasingly become integral to multi-access edge computing (MEC) due to their flexibility and cost-effectiveness, especially in the B5G and 6G eras. This paper aims to enhance the Quality of Experience (QoE) in large-scale UAV-MEC networks by minimizing the shrinkage ratio through optimal decision-making in computation mode selection for each user device (UD), UAV flight trajectory, bandwidth allocation, and computing resource allocation at edge servers. However, the interdependencies among UAV trajectory, binary task offloading mode, and computing/network resource allocation across numerous IoT nodes pose significant challenges. To address these challenges, we formulate the shrinkage ratio minimization problem as a mixed-integer nonlinear programming (MINLP) problem and propose a two-tier optimization strategy. To reduce the scale of the optimization problem, we first design a low-complexity UAV partition coverage algorithm based on the Welzl method and determine the UAV flight trajectory by solving a Traveling Salesman Problem (TSP). Subsequently, we develop a coordinate descent (CD) based method and an alternating direction method of multipliers (ADMM) based method for network bandwidth and computing resource allocation in the MEC system. The CD-based method is simple to implement and has a low computational complexity, while the ADMM-based method can further enhance the optimization result through joint optimization. Extensive simulations demonstrate that our proposed algorithms perform well in large-scale edge networks and outperform other representative benchmark methods.