The production of municipal solid waste incineration bottom ash (MSWIBA) is very massive and has the potential to replace cement despite the problems of complex composition, uneven particle size distribution, and low reactivity. This paper adopts sodium silicate activation of MSWIBA-slag to improve the reactivity to prepare composite cementitious materials. It explores the hydration performance study of the composite cementitious materials by isothermal calorimetric analysis, Fourier Transform Infrared (FTIR) spectroscopy, XRD physical diffraction analysis, and SEM/EDS tests. SEM/EDS tests will be used to explore the hydration properties of the composite gelling. The results showed that with the increase of MSWIBA doping, the porosity between the materials increased, the degree of Hydration decreased, and the compressive strength decreased with the rise of MSWIBA. When sodium silicate increased from 25% to 35%, too much alkaline material occurred over the alkaline effect, which inhibited the Hydration of the particles, and the degree of hydration reaction decreased, and the compressive strength decreased accordingly; the exothermic process of Hydration can be mainly divided into five stages, quartz and calcite did not participate in the hydration reaction completely, and sexual aluminum participated in the hydration reaction. The vibrational peaks of Si-O-Ti (T = Si and Al) were present in the material. The vibrational peaks of XRD, FTIR, and SEM-EDS all indicate the presence of silica-aluminate network structures in the hydration products, mainly N-A-S-H and C-A-S-H gels.

To investigate the effects of plant polysaccharides combined with boric acid on digestive function, immune function, and harmful gas and heavy metal contents in faeces of finishing pigs, for this study, 90 healthy three-way cross-bred pigs were selected and randomly divided into five groups: Con) A control, fed basic feed; BA) fed basic feed supplemented with 40 mg/kg of boric acid; BA+APS) fed basic feed supplemented with 40 mg/kg of boric acid and 400 mg/kg of Astragalus polysaccharides; BA+GLP) fed basic feed supplemented with 40 mg/kg of boric acid with 200 mg/kg of Ganoderma lucidum polysaccharides; and BA+EPS) fed basic feed supplemented with 40 mg/kg of boric acid and 500 mg/kg of Echinacea polysaccharides. Compared with the Con, the average daily gain (ADG) and trypsin activity were higher in BA, along with there being increased glutathione peroxidase (p < 0.05); furthermore, lower malondialdehyde content and harmful substance emissions from manure were observed (p < 0.05). Compared with BA, increases in ADG, gain-to-feed ratio (G/F), trypsin, and maltase activities were observed in BA+EPS (p < 0.05), as well as a lower NH3 emissions (p < 0.05). Compared with BA, BA+APS exhibited higher ADG, average daily feed intake (ADFI), G/F, trypsin, and maltase activities (p < 0.05), while H2S emissions were lower (p < 0.05). And Taken together, our findings reveal that supplementation with boric acid and plant polysaccharides in the diet of finishing pigs synergistically improved their growth performance, trypsin and maltase activities, and immune function, while also discovered the intestinal digestive enzymes, serum inflammatory factors, oxidative stress responseand emissions of harmful gases and heavy metals from feces and urine were tightly related, further reducing the impact of fecal pollution generated by modern animal husbandry on the environment.

Fractional calculus is defined by expanded integer order integration and differentiation. In this paper, multiple mathematical models of a nonlinear dual tank device are precisely formulated by fractional calculus. Using the accurate model, multivariable Fractional-Order Controller is designed for the nonlinear device. The merits of the fractional-order design include: 1) Control of multivariable nonlinearities, 2) Compensation of uncertainties, 3) Elimination of coupling effects. Simulations and experiments are conducted to verify the precision of the fractional order models and the effectiveness of the multivariable fractional-order control design.

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

The anthropogenic deterioration of aquatic ecosystems affects water resources due to agricultural malpractices, pollution from domestic septic tanks, recreational activities, and poor watershed management, among others. This study examines the management of Las Curias Reservoir (176,974 m2), San Juan, Puerto Rico, post the 2016 arrival of the invasive aquatic fern Salvinia molesta. In December 2019, a community-led initiative introduced the Cyrtobagous salviniae weevil, an effective biological control agent for S. molesta, and commenced a mechanical removal campaign using an aquatic harvester. Limnological sampling (September 2019 to March 2022) and drone flights were employed to measure physicochemical and floating plant cover changes, respectively, in the reservoir. Monitoring of weevils in the reservoir demonstrated a rapid establishment and dispersal, which resulted in visible damage including browning of plants and eventually sinking of entire mats. By January 29, 2021, 71% (125,652 m2) of the reservoir surface was covered by salvinia. In 2022, the reservoir recorded an average dissolved oxygen concentration of 2.38 mg/L -1 (± 0.021, n = 144), the highest in the study period and indicative of ecosystem recovery. After three years of control efforts, dissolved oxygen, pH, and specific conductance returned to levels recorded prior to Salvinia molesta introduction. This ecosystem recovery, a first in Puerto Rico, could be attributed to an early use of mechanical control and a long-term impact of biological control.

Background: Atopic dermatitis is a chronic condition that significantly affects the daily life of those who suffer from it, requiring complex and personalized management with active participation of the patient in the management of their disease. Objective: to describe the design and development process of a mobile application, using the Design Thinking method, for the follow-up of patients with atopic dermatitis. Methods: User-centered design and prototype creation method, differentiating the phases of the empathize, define, idea, prototype, and test. A purposive snowball sampling was used to recruit patients with atopic dermatitis, family members, and health professionals. Three two-hour workshops were held, attended by 25 people. Results: the parameters to be monitored will include objective data (physical, behavioral, treatments, environmental, integration of daily routines) and subjective data (user experience). On the other hand, it will figure out behavior patterns, set up rewards, foster a feeling of community, and use notifications and a chatbot. Conclusion: The active integration of all stakeholders at each stage of the design and development of the digital solution has improved its relevance and acceptance, resulting in a tool that is expected to significantly improve the management of atopic dermatitis.

Vertex-degree-based (VDB) topological indices have been applied in QSPR/QSAR. As an important category, the general logarithmic VDB topological index $T_{lnf}(G)$, is defined as the summation of $ln{f(d(u),d(v))}$, where the summation over all $uv\in E(G)$. In this paper, we give the sufficient conditions for that (1) the path $P_{n}$ is the only tree with the minimal $T_{lnf}$; (2) the star $S_n$ is the only tree with the maximal and the minimal $T_{lnf}$, respectively. As applications, the minimal and maximal trees of some logarithmic VDB indices are determined.

In this work, we discuss a newly proposed scalar-tensor theory in Minkowski spacetime. The basic frame in Minkowski spacetime is obtained. Consider a charged particle in the electromagnetic field, we make an attempt to connect this theory with conventional quantum theory. Two specific models are chosen to calculate values of the time delay.

Metastasis is a major cause factor for breast cancer (BC)-associated mortality. During the metastatic process, disseminated tumor cells (DTCs) detach from the primary sites, and enter the bloodstream and establish the secondary colonies. Recent studies have provided substantial evidence for the importance of Notch signaling in BC metastasis. Therefore, this review focuses on the mechanisms by which Notch contributes to the origin of BC DTCs, increases their motility, regulates their intravasation and extravasation, protects them from host surveillance, and finally facilitates colonization. Identification of the mechanisms underlying Notch-related BC metastasis will lead to the development of novel Notch-targeted therapeutic strategies to reduce metastasis and significantly improve outcomes.

The accompanying mechanical behavior during the flow of ore-rock dispersion is an important factor leading to the instability and failure of the orepass in the ore storage section. It is of great significance to accurately understand the instability characteristics of the well wall in the ore section, during the ore drawing process by understanding the flow characteristics and internal mechanical transfer mechanism of ore-rock dispersion. Using the discrete element method to analyze the flow characteristics, contact compactness, stress distribution characteristics and contact force probability distribution of the ore-rock dispersion, it realizes the quantitative characterization of the damage degree of ore-rock flow, and reveals the damage mechanism of mine storage wall. The results show that: (1) The friction between ore-rock particles, between ore-rock and well wall is an important reason for the change of the macroscopic flow form of ore-rock from “one” to “V” type. (2) The compactness and stress concentration of ores are increasing with the increase of storage depth, which is shown that with the increase of storage depth, the greater the probability of well wall instability. (3) The probability distribution of contact force strength between particles decreases exponentially in the whole process of ore drawing, in which the strong chain plays a major role in the stability of the dispersion system. (4) The number of overpressure and the overpressure coefficient can be used to quantitatively characterize the wall damage degree under the action of ore-rock flow. The dynamic side pressure decreases periodically in the form of exponential fluctuations, and the dynamic load formed by the ore-rock flow mainly played a role in the lower area of the ore storage section.

In this paper, we propose an assumption of which the relation between electron and phonon is discussed and investigated based on the experiment of γ photon and electric interconverting with each other. We calculated the charge of a particular standing wave topology with Maxwell’s equation rotated in accordance space with the SO3 transformation. The derived charge value is 1.6035 × 10E−19C around 0.0826% different from the experimental data, indicating the proposal is a promising theory to explain the origin of charge and spin of electron particle. Electron spin angular momentum comes from the orbital angular momentum of photon rotation (electromagnetic field rotation), and electron charge comes from photon, that is, the space-time rotation effect of electromagnetic wave.

This paper designed a new type of generator, transgenerator, that integrates the wind turbine and flywheel into one system, aiming to make the flywheel distributed energy storage (FDES) more modular and scalable than the conventional FDES. The transgenerator is a three-member dual-mechanical-port (DMP) machine with two rotating members (inner and outer rotors) and one stationary member (stator). The transgenerator-flywheel system is introduced with the system configuration, transgenerator overview, flywheel operation principle and power management strategies, and control system. Simulations are performed in MATLAB/ Simulink to verify the system viability, including control system verification and the flywheel storage performance evaluation. Results show that the inner and outer rotors can be controlled independently with accurate and fast control response, and the grid-side control works properly. The flywheel performs well with considerable charging power and storage capacity.

3D Zernike moments based on 3D Zernike polynomials have been successfully applied to the field of voxelized 3D shape retrieval and have attracted more attention in biomedical image processing. As the order of 3D Zernike moments increases, both computational efficiency and numerical accuracy decrease. Due to this phenomenon, a more efficient and stable method for computing high-order 3D Zernike moments was proposed in this study. The proposed recursive formula for computing 3D Zernike radial polynomials combines the recursive calculation of spherical harmonics to develop a voxel-based algorithm for the calculation of 3D Zernike moments. The algorithm was applied to the 3D shape Michelangelo's David with a size of 150×150×150 voxels. As compared to the method without additional acceleration, the proposed method uses a group action of order sixteen orthogonal group and saving unnecessary iterations, the factor of speed-up is 56.783±3.999 when the order of Zernike moments is between 10 and 450. The proposed method also obtained an accurate reconstructed shape with the error rate (normalized mean square error) of 0.00 (4.17×10^-3) when the reconstruction was computed for all moments up to order 450.

In this work, we try to find a way to describe the physical law of micro-world under the frame of a space-time theory. By introducing the scalar fields $\mathcal{D}\left( x\right)$ and $\zeta\left( x\right) $, we rewrite the action of conventional field theory and the Lagrangian describing the motion of the particle, where a modified space-time relation is obtained. To test the correctness of this attempt, we demonstrate the Klein-Gordon equation by the Hamilton-Jacobi method in four dimensional form and present a time delay for the ground state of hydrogen atom.

Purpose: Physical activity (PA) is likely the most important modifiable element for the growth of skeletal muscle. However, a detailed investigation of PA’s impact on preschoolers’ of skeletal muscle development is lacking. This study aimed to determine whether PA level is related to skeletal muscle thickness among preschool children. Methods: 275 healthy preschoolers between the ages 4–6 were instructed to wear an accelerometer for 4 consecutive days. The daily steps and minutes spent in moderate-to-vigorous PA (MVPA) and total PA (TPA) were examined. Muscle thickness (MT) was measured by B-mode ultrasonography. The MT was measured at the anterior (AT) and posterior thigh (PT) and the anterior (AL) and posterior lower leg (PL). Results: Boys were more physically active and engaged in significantly more TPA and MVPA on weekdays compared with girls. Compared with that on the weekends, more physical activity, and significantly greater number of daily steps and higher TPA and MVPA were recorded for both boys and girls on the weekdays. Multivariable regression analyses, after adjusting for daylight duration, indicated that a daily increase in the TPA and MVPA would lead to higher muscle size in AT (β=1.11 and β=1.37, p<0.05), and PL (β=1.18 and β=0.94, p<0.05) among preschool children. Conclusions: The time spent involved in most of the different categories of MVPA was significantly higher for boys than for girls on the weekdays and weekends. MVPA was positively correlated with greater skeletal muscle development in the lower body.

In polymer-based dental composites, wear is a three-body wear system mainly abrasive, because of the food particles and wear products suspended in the oral cavity, which are transferred to the microcavities of the surface of the replacements. Due to this fact, the incorporation of nanodiamond as reinforcement in these polymer matrix composites, which promotes the creation of a solid lubricant tribofilm surface could be advantageous. When nanodiamond is added in contents of 0.8, 1.6 and 3.2 wt %, an increase in microhardness from 95 up to 420 %, compared to the one of neat BisGMA/TEGDMA, is observed. Additionally, the incorporation of a content of 1.6 wt % is enough to cause a diminution of ~78 % in the friction coefficient and a reduction of the specific wear rate and Archard’s coefficient of ~50 %. Nevertheless, the addition of relatively high contents reduces the effectiveness of photoinitiation and UV-curing, which is related to the scattering and absorption of UV radiation by ND.

Solid polymer electrolytes and composite polymer electrolytes serve as crucial components in all-solid-state energy storage devices. Structural batteries and supercapacitors present a promising alternative for electric vehicles, integrating structural functionality with energy storage capability. However, despite their potential, these applications are hampered by various challenges, particularly in the realm of developing new solid polymer electrolytes that require more investigations. In this study, novel solid polymer electrolytes and composite polymer electrolytes were synthesized using epoxy resin blends, ionic liquid, lithium salt, and alumina nanoparticles, and subsequently characterized. Among the formulations tested, the optimal system, designated as L70P30ILE40Li1MAl2 and containing 40 wt.% of ionic liquid and 5.7 wt.% of lithium salt, exhibited exceptional mechanical properties. It displayed a remarkable storage modulus of 1.2 GPa and reached ionic conductivities of 0.085 mS/cm at 60°C. Furthermore, a proof-of-concept supercapacitor was fabricated, demonstrating the practical application of the developed electrolyte system.

Positioning based on wireless signals such as mobile communication networks has become an important means to provide high-precision location services in environments where satellite signals are blocked. In complex environments such as indoor and underground, wireless signal propagation is obstructed and non-line-of-sight (NLOS) phenomena appears due to serious occlusion and reflection. The time delay caused by NLOS effects has little impact on communication system but can significantly increase positioning errors in positioning systems. Therefore, effective suppression of NLOS errors is crucial to improving 5G positioning accuracy. To address the insufficient feature extraction of existing NLOS error suppression methods, the neglect of residual NLOS measurement errors, and poor stability of position estimation results, this paper innovatively proposes a NLOS mitigation and location estimation method for 5G positioning terminals. Simulation and experimental test results demonstrate that the proposed method outperforms the comparative methods both theoretically and practically, achieving an average positioning accuracy of 1.85 meters in complex indoor NLOS environments. The method proposed in this paper provides a new strategy for NLOS error suppression in indoor 5G positioning, which can significantly contribute to high-precision location services based on commercial 5G networks.

The aim of this work was to classify the business incubators in Spain according to the four phases of the startup’s incubation process. Considering that the graduation rate implies greater survival and business success of the incubated companies, they have been identified at each stage of the incubation (spread of entrepreneurship, pre-incubation, advanced incubation, and graduation). The activities that present higher impacts on the success of the incubated companies and the activities carried out by the business incubator that have a greater relevance on the graduation of the companies have concretely been considered. Principal component (PC) cluster analysis has been applied. All the incubation variables were used simultaneously, reducing their number, and grouping them into factors. Finally, the cases were grouped according to these latent variables. Principal components analysis reduced dimensionality to 8 factors with a 74 % of explained variance. Factor 1 was positively related to pre-incubation variables, factor 2 was linked to training and collaboration variables within the entrepreneurship diffusion phase. Factor 3, named activity monitoring and control, was related to phase 3 or basic incubation variables. Cluster analysis facilitates the grouping of business incubators into three clusters: Group 1 (16 % of the total), incubators with strong deficits in incubation phases 1, 2 and 3. They are small sized business incubators, often located in rural areas or cities and low graduation rate. Group 2 (30 %), business incubators with very high graduation rate, and strongly positive values in factors 1 and 2. Factor 3, although positive, it is susceptible to improvement. They are the largest group of business incubators and usually located in industrial and technological parks. Group 3 (54 %) is the majority, with values close to cluster 2 and 3.

The aim of this work was to classify the business incubators in Spain according to the four phases of startups incubation. Taking into account that the graduation rate implies greater survival and business success of the incubated companies, they have been identified at each stage of the incubation (spread of entrepreneurship, pre-incubation, advanced incubation, and graduation). The activities that present higher impacts on the success of the incubated companies and the activities carried out by the incubator that have a greater relevance on the graduation of the companies have concretely been considered. Principal component (PC) cluster analysis have been applied. All the incubation variables were used simultaneously, reducing their number, and grouping them into factors, finally the cases were grouped according to these latent variables. Principal components analysis reduced dimensionality to 8 factors with a 74 % of explained variance. Factor 1 was positively related to pre-incubation variables, factor 2 was linked to training and collaboration variables within the entrepreneurship diffusion phase. Factor 3 called activity monitoring and control and was related to phase 3 or basic incubation variables. Clusters analysis facilitates the grouping of incubators into three clusters: Group 1 (16 % of the total), incubators with strong deficits in incubation phases 1, 2 and 3. They are small Business Incubators, often located in rural areas or cities and low graduation rate. Group 2 (30 %), business incubators with very high graduation rate, and strongly positive values in factor 1 and 2. Factor 3 although positive is susceptible to improvement. They are the largest incubators and usually located in industrial and technological parks. Group 3 (54 %) is the majority, with values close to cluster 2 and 3.

Landslides are serious geological hazards that become a disaster worldwide, causing a large number of casualties and economic losses every year. There are many factors affecting landslide susceptibility, such as rainfall, soil and slope. Each of them has an important role in the process of slope losing stability. In this paper, the effects of rainfall intensity, rainfall pattern, slope gradient and soil type on landslide susceptibility are studied. In the process of rainfall-induced landslide, the relevant physical quantities of soil changes continuously. Their values and processes are closely related to the time of landslide occurrence. Hence, the variation of soil volumetric water content, matrix suction, pore water pressure and total stress throughout the rainfall are measured. As the results, soil type, slope gradient and rainfall intensity have a large influence on landslide susceptibility. The occurrence of landslides has a prerequisite that the slope is greater than or equal to 15°. The rainfall intensity needs to be not less than 80 mm/h. The difference of rainfall pattern also affects the landslide susceptibility. The rainfall pattern with rainfall intensity peak at the later stage is more likely to induce landslide. Coarser soils with gravels are prone to landslides when other conditions are the same. Steeper slopes, stronger rainfall, and coarser soils can all increase the amount of sediment yield.

A face serum composed of a combination of biologically active compounds was evaluated for safety and efficacy in vitro, in a repeat insult patch test and in a human clinical efficacy trial. The serum inhibited tyrosinase activity modestly, decreased collagenase activity and exhibited notable free radical scavenging activity in vitro. It is gentle to the skin, as the serum did not irritate the skin or produce symptoms of allergic contact dermatitis in the 55 healthy adults that participated in the repeat insult patch test. In the efficacy trial, daily application of the face serum for 30 days significantly increased skin hydration, with all 35 volunteers experiencing improvement. Substantial improvements in skin elasticity, roughness (fine lines and wrinkles), and brightness also occurred during the trial. Dermatological examination also revealed a trend for reduced comedone count with use of the serum. Self-assessment responses revealed that all volunteers experienced improvements in multiple skin quality parameters and that participant perceptions are consistent with the results of the instrumental analyses. These findings indicated that the measured improvements in skin quality are not only statistically significant but are also clinically relevant as they were great enough for users of the face serum to feel and recognize.

NongXiangXing Baijiu (NBJ) is produced using a solid-state fermentation system, but the impact of stratified fermented grains on fermentation remains unclear. Therefore, in a typical distillery plant, we evaluated the physical and chemical composition, volatile compound profile, and microbial community of fermented grains in NBJ both above (FG-A) and below (FG-B) the Huangshui line. Significant differences in fermentation parameters between FG-A and FG-B were observed after 30 days of fermentation (P < 0.05). Additionally, the partial least squares projection to latent structure discriminant analysis (PLS-DA) revealed distinct differences in volatile compounds between FG-B and FG-A, identifying 26 discriminant markers. The diversity of short-chain fatty acids (SCFAs) and their esters was higher in FG-B compared to FG-A. Furthermore, microbial diversity and abundance differed significantly between the two layers of fermented grains (P < 0.05). Correlation and pathway enrichment analyses indicated that the higher SCFA content in FG-B could be attributed to the greater abundance of acid-producing microorganisms compared to FG-A. This study highlights the differences between the two layers of fermented grains in NBJ fermentation, offering new insights into solid-state fermentation and expanding the current understanding of the traditional NBJ fermentation process.

In this nano era, nanomaterials and nanostructures are popular in developing novel functional materials. However, the combinations of nanoproducts with materials at micro and macro scale can open new routes for conceiving novel materials with an improved or even new functional performances. In this study, a brand-new hybrid, containing both nanofibers and particles having a microsize, was fabricated using a sequential electrohydrodynamic atomization (EHDA) process. Firstly, the microparticles loaded with drug (berberine hydrochloride, BH) molecules in the cellulose acetate (CA) were fabricated using a solution electrospraying process. Later, these microparticles were suspended into a co-dissolved solution containned BH and a hydrophilic polymer (polypyrrolidone, PVP), and were co-electrospun into the nanofiber/microparticle hybrids. The EHDA processes were clearly recorded, and the resultant products showed a typical hybrid topography, with microparticles distributed all over the nanofibers, which was demonstrated by SEM assessments. FTIR and XRD demonstrated that the components within the hybrids were presented in an amorphous state and have fine compatibility with each other. In vitro dissolution tests verified that the hybrids were able to provide the designed dula-step drug release profiles, a combination of the fast release step of BH from the hydrophilic PVP nanofibers through an erosion mechanism and the sustained release step of BH from the insoluble CA microparticles via a typical Fickian diffusion mechanism. The present protocols pave a new way for developing trans-scale functional materials.

In this study, three new demountable joints consisting of reinforced concrete columns and steel beams were proposed and their seismic performance was investigated using cyclic loading tests. The test results demonstrated that the three demountable RCS joints had good seismic performance. Using the finite element software ABAQUS, the influence of parameters such as beam flange thickness, bolt strength, and connector steel strength on the seismic performance of each joint was analyzed, and the influence of different parameters on the seismic behavior of the joint was determined. The results also showed that the three demountable RCS joints were sensitive to changes in the thickness of the steel beam flange, while the connector steel strength and bolt type had little impact on the joint's capacity. Additionally, shear capacity calculation formulas for the joint core area provided by different codes and researchers were compared with test and finite element results. The results showed that the calculation results of the ASCE guidance method, the Nishiyama method, and the CECS 347-2013 method were higher than the test values, while the calculation results of the Para method were lower because it did not consider the contribution of the cylindrical steel plate to the shear capacity of the joint core area.

Toxoplasma gondii, a protozoan parasite with the ability to infect various warm-blooded vertebrates, including humans, is the causative agent of toxoplasmosis. This infection poses significant risks, leading to severe complications in immunocompromised individuals and potentially affecting the fetus through congenital transmission. A comprehensive understanding of the intricate molecular interactions between T. gondii and its host is pivotal for the development of effective therapeutic strategies. This review emphasizes the crucial role of proteomics in T. gondii research, with a specific focus on host-parasite interactions, post-translational modifications (PTMs), PTM crosstalk, and ongoing efforts in drug discovery. Additionally, we provide an overview of recent advancements in proteomics techniques, encompassing interactome sample preparation methods such as BioID, APEX, and Y2H, as well as various proteomics approaches, including single-cell analysis, DIA, targeted, top-down, and plasma proteomics. Furthermore, we discuss the integration of proteomics with other omics technologies, highlighting its potential in unraveling the intricate mechanisms of T. gondii pathogenesis and identifying novel therapeutic targets.

The purpose of this study is to investigate and validate the influencing factors of audiences’ attitude toward virtual concerts. To address this issue, the current study proposes a conceptual model integrating player experiences’ factors (autonomy, relatedness, and engagement) and the technology acceptance model (perceived usefulness, perceived ease of use, and perceived enjoyment). An online questionnaire on virtual concert experiences was distributed to Chinese audiences who had attended virtual concerts. Structural equation modeling was then used to establish the relationship between variables. The results suggested autonomy, relatedness and engagement positively impacted perceived usefulness, perceived ease of use, and perceived enjoyment. Furthermore, the perceived usefulness, perceived ease of use, and perceived enjoyment were significant predictors of audiences’ attitude. The findings of this study can provide a reference for relevant virtual entertainment providers and can also serve as a point of development and exploration for technology acceptance model and player experience in the field of virtual concerts.

A long-term forecast study on the electricity demand of Taoussa of Mali is conducted in this paper, with various scenarios of socioeconomic and technological conditions. The analysis tool, which is applied in scenarios simulation, is the Model for Analysis of Energy Demand from the International Atomic Energy Agency. The analysis results are annual electricity demand and peak load forecast for the electrification from the period 2020 to 2035. During the planning period, the analysis results show that the electricity demand will increase to 49.40 MW (332.57 GWh) for the low scenario (LS), 66.46 MW (472.61 GWh) for the reference scenario (RS), and 89.47 MW (635 GWh) for the high scenario (HS). In addition, the total electricity demand increased at an average rate of 8.13% in the LS, 10.31% in the RS and 12.56% in the HS in all sectors. The electricity peak demand is expected to grow at 7.92%, 10.53% and 12.91% corresponding to the three scenarios; in this case, the system peak demand in 2035 will increase to 64.88 MW for the LS, 92.2 MW for the RS and 126.22 MW, the days of peak load are between 17th -23rd in May. The Industry sector will be the biggest electricity consumer of Taoussa area.

With the changing relationship between urban and rural areas in China, the rural areas are experiencing rapid social transformation. To ensure successful implementation of the rural revitalization strategy, land consolidation has become a major measure of rural economic reform. Existing research focuses on quantitative studies exploring the relationship between land consolidation and rural economic development, but there is a lack of studies on the relationship between land consolidation and social change. In this study, Jin’an Village is selected as the research area, using semi-structured interviews and semi-participatory observation to obtain original materials, aiming to make a detailed description of the specific practice of land consolidation, and to analyze the impact of land consolidation on the transformation of rural social consciousness. The study found that rural land consolidation involves villagers in the land consolidation process, which can effectively stimulate villagers’ participation in public affairs. Concurrently, the interaction between villagers and outside investors disrupts the conventional socialization model in rural areas and motivates villagers to act in accordance with contractual agreements. The conclusion is that land consolidation in rural areas can enhance the political democracy and legal consciousness of local villagers, which can lead to a change in local social consciousness. Our findings also emphasize the crucial necessity to grant rural villagers with improved accessibility to professional services and information, coupled with the continued promotion of land consolidation to advance modernization in these areas.

Chinese texts often feature a substantial volume of normative content, and their analysis has increasingly become a focal point in recent semantic analysis endeavors. Enhancing the effectiveness of text classification and clustering is pivotal in unveiling the intricate semantics within extensive textual data. Empirical research within the realm of computational social science has underscored the need for improved explanatory power when it comes to general text clustering methods applied to normative texts. This study introduces an innovative hierarchical clustering method that incorporates part-of-speech (POS) features and pioneers a novel semantic network model. It achieves this by amalgamating a POS-based feature weight calculation method with hierarchical clustering techniques. To assess its efficacy, the method is rigorously evaluated across three diverse text datasets, encompassing normative reports, news articles, and social media content. The experimental results unequivocally demonstrate the superior performance of the POS-HC method, surpassing the traditional TF and TF-IDF feature extraction methods in terms of clustering accuracy, and surpassing some existing clustering methods. Furthermore, its classification effectiveness exhibits notable advantages, particularly in the semantic classification of normative texts.

Currently, active and intelligent packaging have been developed to solve the spoilage problem for rich protein foods during storage, especially by adding anthocyanin extracts. In such film system, the antioxidant and antibacterial properties were dramatically increased by adding anthocyanins. The physicochemical properties were enhanced through interactions between active groups in anthocyanins and reactive groups in polymer chains. Additionally, active and intelligent film could monitor the spoilage of rich protein foods in response to pH change. Therefore, this film could monitor the sensory acceptance, and extending the shelf life of rich protein foods simultaneously. In this paper, the structure and functional properties of anthocyanins, the composite actions of anthocyanin extracts and biomass materials, and their reinforced properties of active and intelligent film were discussed. Also, the applications of this film in quality maintenance, shelf-life extension and quality monitoring for fresh meat, aquatic product and milk were summarized. The film that achieves high stability and continuous release of anthocyanins on demand will become an underlying trend in packaging applications for rich protein foods.

There is a noticeable absence of health education among college students. This study aimed to evaluate the extent of general nutrition knowledge among Chinese university students and explore its association with eating attitudes. Data were collected from a group of 273 students in Spring of 2023, using a valid and reliable research instrument consisting of three sections: demographic variables, the General Nutrition Knowledge Questionnaire (GNKQ), and the Eating Attitudes Test (EAT-26). The results were analyzed using SPSS, with correlations and t-tests to examine the relationships between nutritional knowledge and dietary attitudes. Furthermore, the present study employed the Random Forest (RF) algorithm, a machine learning technique, utilizing the Mean Decrease Impurity (MDI) method to investigate the influence of various features on participants' eating attitudes. The findings revealed that Chinese university students had an average accuracy of over 60% in their nutritional knowledge, but their understanding of the relationship between diet and disease still needs improvement. Moreover, male students had significantly lower nutritional knowledge than female students, and there was a positive correlation between nutritional knowledge and parents’ income. The study also found a significant correlation between the level of nutritional knowledge and eating attitudes. RF results indicated that family income level exhibited the most substantial impact on the eating attitudes of the participants. The study highlights the need for nutrition education curriculum developers to focus more on improving students' nutritional knowledge, with particular attention given to male students, low-income individuals, and those with an abnormal BMI.

Wind power generation is one of the mainstream renewable energy resources. Voltage stability is as important as the frequency stability of a power system with a high penetration of wind power generation. The advantages of high-voltage direct current (HVDC) transmission systems become more significant with the increase of both installed capacity and transmission distance in offshore wind farms. Therefore, this study discusses about various voltage control methods for wind turbines and HVDC transmission systems. First, various voltage control methods of a wind farm were introduced, and they include QV control and voltage droop control. The reactive power of a wind turbine varies with active power, while the active power from each wind turbine may be different owing to wake effects. Thus, QV and voltage droop control with varying gain values were also discussed in this paper. Next, the voltage control methods for a HVDC transmission system, such as power factor control, voltage control, and Vac-Q control, are also summarized and tested in this study. When a three-phase short circuit fault occurs or a suddan reactive power load increases, the system voltage would drop immediately. Thus, various voltage control methods for wind turbines or HVDC can make the system's transient response more stable. Therefore, this study implemented the simulation scenarios, including a three-phase short circuit fault at the point of common coupling (PCC) or a sudden increase of reactive power load, and adopted various voltage control methods, which aims to verify whether additional voltage control methods are effective to improve the performance of transient voltage.

This article focuses on generating an alternative in order to identify traffic officers during driving. This research employed the latest You Only Look Once (YOLO) model, using a six-phase methodology: data collection, data preparation involving resizing and labeling, implementation of various filters to avoid overfitting, model training, prediction evaluation, and result interpretation. The YOLO model was applied across three iterations using a dataset of 1862 images. To enhance training efficiency and detection speed, the graphics processing unit (GPU) acceleration was utilized, further enhancing the experimental process. The results of this study revealed that the YOLOv8x variant produced the most promising results. This proposed model attained a remarkable F1 score of 0.95, bolstered by a confidence score of 0.631, with the potential for an increase to 0.80 in confidence without significantly compromising the F1-score. These findings are poised to make a substantial contribution to the broader research landscape, particularly in advancing the effectiveness of detection models for traffic officers.

Objective. To test the hypothesis that a session of unilateral tSMS over the dominant primary motor cortex (M1) in healthy subjects produces a transient decrease in manual dexterity. Methods. A triple-blinded randomized control trial was conducted in 40 healthy participants who were allocated to real- or sham-tSMS group. Each participant underwent one session of tSMS and were assessed before, immediately after, 15 minutes, and 40 minutes after stimulation. Outcome measures were Finger Tapping Test (FTT), 5-seconds FTT, nine Hole Peg Test, and the hand grip assessment. Results: Significant differences were found between groups 15 minutes after stimulation in favor of the tSMS group in the FTT (2.2 ± 0.99; CI= .18-4.22; d= .84p=.034), and 5-second FTT (4.2 ± 1.98; CI= .199-8.2, d= .68; p=.04). In the intragroup analysis, a significantly lower number of taps 15 minutes after stimulation was observed in sham group (3.3 ± 1.01; CI= .47-6.13; d= .42; p=.015), but not in the real stimulation group. Conclusion: A unilateral session of tSMS in the M1 of the dominant hemisphere of healthy individuals does not reduce manual dexterity or grip strength. This technique could have benefits on the motor performance of the arm contralateral to the stimulated motor cortex

Technology has transformed aeroponics, providing numerous advantages over traditional soil-based agriculture. However, there remains a need for comprehensive information on the types of technology employed in aeroponics and their impact on the growing process. This paper presents a literature review of 47 studies published between 2012 and 2023 in peer-reviewed journals and conference proceedings. As a result, it identifies the status and tendencies in the usage of technology in aeroponics as well as the main opportunities and challenges. Furthermore, this paper introduces the Technology Adoption and Integration in Sustainable Agriculture (TAISA) model. TAISA is a model that identifies the degree of technology integration in any sustainable agriculture system to determine how technology affects production and quality. Overall, the systematic review suggests that technology can play a vital role in improving the efficiency and sustainability of aeroponic farming. However, careful consideration must be given to the costs and technical requirements associated with using these technologies. Moreover, the TAISA model reveals that technology has primarily been employed in creating new processes that are not possible to implement without the help of technology. Therefore, we conclude that technology use has taken root in aeroponics and can be promoted to improve sustainable agriculture.

Background: Although confirmed cases of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been declining since late 2020 due to general vaccination, little research has been done regarding the impact of vaccines against SARS-CoV-2 in Spain in terms of hospitalizations and deaths. Objective: Our aim was to identify the reduction in severity and mortality of coronavirus disease 2019 (COVID-19) at a nationwide level due to vaccination. Methods: We designed a retrospective, population-based study to define waves of infection and to describe the characteristics of the hospitalized population. We also studied the rollout of vaccination and its relationship with the decline in hospitalizations and deaths. Finally, we developed two mathematical models to estimate non-vaccination scenarios using machine learning modeling (with the ElasticNet and RandomForest algorithms). The vaccination and non-vaccination scenarios were eventually compared to estimate the number of averted hospitalizations and deaths. Results: In total, 498,789 patients were included, with a global mortality of 14.3%. We identified six waves or epidemic outbreaks during the observed period. We established a strong relationship between the beginning of vaccination and the decline in both hospitalizations and deaths due to COVID-19 in all age groups. We also estimated that vaccination prevented 170,959 hospitalizations (CI 95% 77,844–264,075) and 24,546 deaths (CI 95% 2,548–46,543) in Spain between March 2021 and December 2021. We estimated a global reduction of 9.19% in total deaths during the first year of COVID-19 vaccination. Conclusions: Demographic and clinical profiles changed over the first months of the pandemic. Patients over 80 years old and other age groups obtained clinical benefit from early vaccination. The severity of COVID-19, in terms of hospitalizations and deaths, decreased due to vaccination.

The availability of multiple sequenced genomes from a single species made it possible to explore intra- and inter-specific genomic comparisons at higher resolution and build clade-specific pangenomes of several crops. The pan-genomes of crops constructed from various cultivars/accessions, landraces, and wild ancestral species represent a compendium of genes and structural variations and allow researchers to search for the novel genes and alleles that were inadvertently lost in domesticated crops during the historical process of crop domestication or in the process of extensive plant breeding. Fortunately, many valuable genes and alleles associated with desirable traits like disease resistance, abiotic stress tolerance, plant architecture, and nutrition qualities exist in landraces, ancestral species, and crop wild relatives. The novels genes from the wild ancestors and landraces can be introduced back to high-yielding varieties of modern crops by implementing classical plant breeding, genomic selection, and transgenic/gene editing approaches. Thus, pan-genomic represents a great leap in plant research and offers new avenues for targeted breeding for mitigating the impact of global climate change. Here we summarize the tools used for pangenome assembly and annotations, web-portals hosting plant pangenomes. Furthermore, we highlight a few discoveries made in crops using the pan-genomic approach and its future potential.

BACKGROUND: Qu-aroma is a critical quality indicator for medium-high temperature Daqu (MT-Daqu), significantly influencing the aroma profile of strong-aroma Baijiu (SAB). SAB is produced across various regions in China, each with unique environmental conditions and production techniques. These regional differences are likely to cause variations in the Qu-aroma of MT-Daqu. Despite this, comprehensive research on the variations in Qu-aroma across different regions has been lacking. This study aims to address this gap by utilizing Gas Chromatography-Olfactometry-Mass Spectrometry (GC-O-MS) and electronic nose (E-nose) technology, combined with sensory evaluation, to analyze the differences in Qu-aroma characteristics and volatile compound profiles of MT-Daqu from seven distinct production areas.RESULTS: Sensory analysis identified seven broad aroma categories and 25 specific aromas characterizing the Qu-aroma of MT-Daqu samples. Chen aroma and roasted aroma were notably more prevalent in MT-Daqu samples from Sichuan compared to those from other regions (P < 0.05), while the fermentation aroma was less prominent in Sichuan samples. In total, 123 volatile compounds were detected in MT-Daqu, with 46 classified as aroma-active compounds. Among these, 21 aroma-active compounds were identified as markers distinguishing Sichuan MT-Daqu from those produced in non-Sichuan regions, showing significant differences in their concentrations (P < 0.05). Additionally, six major aroma-active compounds-ethyl isovalerate, ethyl heptanoate, hexanal, 1-nonanal, (E)-2,4-decadienal, and 2,3-dimethyl-5-ethylpyrazine-were found to significantly contribute to the aroma differences between Sichuan and non-Sichuan MT-Daqu.CONCLUSION: This study delineates the distinct Qu-aroma characteristics of MT-Daqu from various SAB production areas and identifies the aroma-active compounds responsible for these differences. The insights gained from this research offer valuable guidance for optimizing flavor profiles in MT-Daqu production, potentially enhancing the overall quality and regional distinctiveness of the product.

Gaussian mixture models (GMMs) are powerful tools specifically suited for problems where data distributions are multi-modal. Inspired by Fourier expansion, we propose a concept called GMM expansion to approximate arbitrary densities. A simple learning method is introduced under this framework. Theoretical and numerical analyses are provided to show that densities under GMM expansion are able to approximate arbitrary densities with certain accuracy. The proposed learning algorithm demonstrates better accuracy and time efficiency compared to classic density approximation methods such as the Expectation Maximization (EM) algorithm and Bayesian variational inference (BVI) for Gaussian mixture models. The proposed framework also shows better accommodation of neural networks. Three neural network applications are built to demonstrate its usability. The accuracy of density estimation in neural networks is reported to be significantly improved in one of the applications. Another application shows that latent variables can be easily turned into random variables. This user-friendly method opens up more possibilities in terms of latent manipulation, embedding techniques, and many other potential uses.

The log data generated during the operation of a software system contains information about the system, and using logs for anomaly detection can detect system failures in a timely manner. Most of the existing log anomaly detection methods are specific to a particular system, have cold start problems, and are sensitive to updates in log format. In this paper, we propose a log anomaly detection method LogBD based on pre-training model and domain adaptation, which uses the pre-training model BERT to learn the semantic information of logs, and can solve the problems caused by multiple meaning words and log statement updates. An anomaly detection method LogBD based on distance to determine anomalies is constructed based on domain adaptation, using TCN networks to extract common features of different system logs and map them to the same hypersphere space. Finally, experiments are conducted on two publicly available datasets to evaluate the method, and the experimental results show that the method can better solve the log instability problem and has some improvement in the cross-system log anomaly detection effect.

The development and utilization of wind energy is of great significance to the sustainable development of China's economy and the realization of the goal of "dual carbon". Under the typhoon system, the randomness and volatility of wind speed become an important basis for affecting the energy efficiency utilization and design of wind turbines. Therefore, based on wind speed and wind direction data at 10m, 30m, 50m and 70m heights of a wind power tower in Yancheng, Jiangsu Province, this paper analyzes the change characteristics of wind speed and wind direction by using BFAST method and Hurst index. Based on typhoon body data, topographic data and mesoscale system wind direction data, the causes of the occurrence and development of wind speed and wind direction of wind tower are further analyzed, and a conclusion is drawn: (1) In BEAST method, there are 5, 5, 6 and 6 change points at the height of 10m, 30m, 50m and 70m respectively. Among them, the change points at the height of 10m, 30m and 50m all change before and after node 325, and the change time point at the height of 70m is inconsistent with other heights. Hurst index results show that the inconsistency at 70m altitude is stronger than that at other altitudes. (2) The wind direction sequence at 10m, 30m, 50m and 70m altitude is fitted by stages, and the direction of wind direction is SE-E-SE-SW-W-NW, where, At the height of 70m, the deviation of the fitting trend line from other altitudes is larger in the wind speed strengthening stage and weakening stage. (3) The wind speed at the height of 10m and 70m has different response degrees to the typhoon body. The correlation between the wind speed and the distance between the wind measurement tower and the typhoon near the center is stronger at the height of 10m than at the height of 70m. The surface type and the wind direction of the mesoscale system also have certain effects on the wind speed and direction. In this paper, the change characteristics and influencing factors of wind speed and direction of wind tower are studied, which provides methods and theoretical support for the study of short-term wind speed when typhoon passes through, and provides reliable support for the selection of wind power forecast indicators and the selection and design of wind turbines under extreme gale weather systems.

A co-curing resin system consisting of 9368 epoxy resin for prepreg and 6808 epoxy resin for resin transfer molding (RTM) was developed. A corresponding preparation method of novel polymer composite bolted T-joint with internal skeleton and external skin was proposed based on prepreg-RTM co-curing process, and novel T-joints were fabricated. A series of conventional configuration T-joints based on RTM process and T-joints made of 2A12 aluminum alloy were prepared simultaneously. Bending performances were studied on these T-joints experimentally. The results indicate that 9368 epoxy resin and 6808 epoxy resin exhibit good compatibility in rheological and thermophysical properties. The novel T-joints prepared with prepreg-RTM co-curing process show no obvious fiber local winding or resin-rich regions inside, and the interface quality between internal skeleton and external skin is excellent. The main failure modes of the novel T-joint under bending load include separation of skin and skeleton and fracture along the thickness on the base panel; the skeleton carries the main bending load, but there is still load transfer between external skin and internal skeleton through their interface. The internal damages of the novel T-joint are highly consistent with surface damages observed visually, facilitating the detection and timely discovery of damages. The initial stiffness, damage initiation load, and ultimate load of the novel T-joint are 1.65 times, 5.89 times, and 3.45 times that of conventional T-joint, respectively. When considering the influence of density, the relative initial stiffness and relative ultimate load of the novel T-joint are 1.44 times and 2.07 times that of aluminum alloy T-joint, respectively.

The research on the distribution of rural buildings is one of the fundamental works of urban-rural development in Vietnam. Adopting Mask R-CNN deep learning framework and collecting sub-meter remote sensing images, this research used a remote sensing interpretation model of rural buildings trained based on East Asian characteristics of rural buildings and successfully recognized about 2.87 million rural buildings in 34 Vietnamese provincial administrative districts with a total area of rural buildings of 2,492 million square meters. The reliability of the identification results was verified by manual detection and quantitative statistics, and a multi-scale database of rural buildings in Vietnam based on individual rural buildings was created. Based on the database, this paper analyzes the distribution characteristics of rural buildings and summarizes characteristics of rural buildings distribution at the country, regional, and provincial scales. The identification results lay the foundation for the next study of urban-rural relations in Southeast Asia and the construction of a basic database on villages.

This preprint is focused in the presence of plastics and microplastics in food. We will discuss how many we eat, and how they arrive to the food, and why. We will treat many other things, such as the waste treatment in Europe and in Spain, with updated data; how much plastic waste is generated; what are microplastics and how they are analyzed, I will tell about the experience we have at the University of Alicante (UA); how they can be removed and we will estimate how many we eat over the course of a year.

Previous studies on the water-energy nexus mainly focused on the calculation and comparison of resource consumption at the national or regional level, lacking interprovincial sector-sector transfer analysis. In this study, the intensity of water and energy consumption of various sectors in China were calculated, the key nodes and paths of resource networks were identified, and countermeasures for resource conservation were proposed from the new perspective of the “dual saving” and “bidirectional saving” of water and energy. The results showed that the metallurgical industry (Me) in Jiangsu and the chemical industry (Ch) in Hebei and Jiangsu had high node strength in the water and energy network and were key sectors in China with “dual saving” effects of water and energy. The construction industry, Ch, Me in Jiangsu, electricity and hot water production and supply industry in Beijing, and Me in Hebei had high node strength in the water-related energy network and energy-related water network, significantly supporting the “bidirectional saving” effect of water and energy in China. The electrical equipment industry (El) in Jiangsu→El in Zhejiang, El in Zhejiang→El in Shanghai frequently appeared in key paths, which could effectively reduce the resource consumption of the entire network.

China faces a persistent deficiency in feed protein resources. Enhancing the utilization efficiency of indigenous feed protein resources emerges as a viable strategy to alleviate the current deficit in protein feed supply. Corn gluten meal (CGM), characterized by high proportion of crude protein and glutamine, is predominantly employed in animal feed. Nonetheless, the water-insolubility of CGM protein hampers its protein bioavailability when utilized as feed material. This study aimed to augment protein bioavailability, liberate glutamine peptides from CGM, and produce gluta-mine-enriched CGM fermented feed. We executed a co-fermentation protocol using Bacillus subtilis A5, Lactobacillus 02002, and acid protease to generate the CGM fermented feed. Subsequent in vivo experiment with broilers were conducted to assess the efficacy of the fermented product. Findings revealed that the soluble protein, glutamine, small peptides, and lactic acid contents in the fer-mented feed increased by 69.1%, 700%, 47.6%, and 125.9%, respectively. Incorporating CGM fermented feed into the diet markedly enhanced the growth performance and intestinal health of broilers, positively modulated the cecal microbiota structure, and augmented the population of beneficial bacteria, specifically Lactobacillus. These results furnish both experimental and theoretical foundations for deploying CGM fermented feed as an alternative protein feed resource.

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.

The electroencephalogram (EEG) is a record of brain activity. Brain Computer Interface (BCI) technology formed by the EEG signal has become one of the hotspots at present. How to extract the feature signal of EEG is the most basic research of BCI technology. In this paper, A new method of recognizing fatigue, conscious, concentrated state of human brain is proposed by the combination of discrete wavelet transform and the neural network based on EEG signal. First of all, the law signal is preprocessed by the wavelet denoising method because the law EEG signal contains a large number of high frequency noise, which is decomposed into multi-layer high frequency signal and low frequency signal. thus, δ wave, θ wave, α wave, β wave are obtained by the wavelet transform. And then, frequency band energy of the different wave is regards as the feature signal of EEG. In the experiment, the feature signal is classified by radial basic function (RBF) and annealed chaotic competitive learning network (ACCLN). RBF and ACCLN networks are trained with 500 sets of sample data and are tested by 100 sets of samples in different mental states. The experimental results show that the average accuracy of RBF network under three conditions are 88.75%, 88.25%, 88.5%, respectively, and the correct rate of ACCLN network is 97%, 98%, 98%, respectively.

Air quality is a topic of growing relevance on the global agenda. Two key indicators of air quali-ty, nitrogen dioxide (NO2) and carbon monoxide (CO), represent significant hazards to human health and the environment putting the sustainability of natural resources at risk. Therefore, it is imperative to regularly monitor and reduce atmospheric pollutant concentrations to mitigate their harmful consequences. This study presents an analysis of NO2 total and CO emissions in Argentina, utilizing remote sensing data. The research aims to determine the spatiotemporal distribution of NO2 and CO emissions in Argentina from 2019 to 2021. Subsequently, it seeks to establish the influence of land uses and land cover on the emission of NO2 and CO through dif-ferent climatic, anthropic, and natural indicators. The study was carried out in Argentina during the period 2019-2021, where random points were placed for the different land covers with a total of 800 points surveyed. The year with the highest CO concentration (mol/m-2) was 2020. The values were highest for tree covers and herbaceous wetland coverage in the northern part of the country. For total NO2, the highest concentrations were reached during the years 2020 and 2021. Regarding its distribution, throughout the evaluated period, the highest concentrations of total NO2 were found in the built-up and cropland coverages, with the capital of the country and the northern region of the Buenos Aires province being the most affected areas. In addition, the concentration of CO was influenced by climatic variables (atmospheric pressure, wind speed, maximum environment temperature, Palmer index), natural (height, humidity, NDVI), and ur-ban variables (distances to mining extraction, airports, power plants, urban index) for the differ-ent uses and land covers. Finally, the concentrations of total NO2 were influenced by climatic variables (Palmer index and wind speed), natural (height and NDVI), and urban variables (dis-tance to airports, power plants, industries, service stations, and open dumpsites) for the differ-ent uses and land cover. This study contributes to sustainable environmental management, ena-bling the formulation of effective strategies for mitigating emissions and promoting the long-term health and well-being of communities.

With global warming, arable land in boreal regions is tending to expand into high latitude regions in the northern hemisphere. This entails certain risks; such that inappropriate management could result in previously stable carbon sinks becoming sources. Agroecological models are an important tool for assessing the sustainability of long-term management, yet applications of such models in boreal zones are scarce. We collated eddy-covariance, soil climate and biomass data to evaluate the simulation of GHG emissions from grassland in eastern Finland using the process-based model DNDC. We simulated gross primary production (GPP), net ecosystem exchange (NEE) and ecosystem respiration (Reco) with fair performance. Soil climate, soil temperature and soil moisture at 5 cm were excellent, and soil moisture at 20 cm was good. However, the model overestimated NEE and Reco following crop termination and tillage events. These results indicate that DNDC can satisfactorily simulate GHG fluxes in a boreal grassland setting, but further work is needed, particularly in simulated second biomass cuts, the (>20 cm) soil layers and model response to management transitions between crop types, cultivation, and land use change.

As e-commerce services and Internet technology have rapidly developed in recent years, many services and applications integrating these technologies can now be completed online. These commercial activities include online auctions, online ticketing and online payments. The client shops from the store online, andthe store delivers the goods to the client. The goods can be divided into digital products without entities, as well as actual entities. If it is a physical product, the store will deliver the package to the client through itslogistics. However, there have been many cases of switched goods purchased by clients in recent years. Earlier, some scholars proposed a security mechanism with a subliminal channel for E-cash and digital content. Only the sender and the receiver would know that the secret information was hidden in the signature. So the privacy of this subliminal message couldbe ensured. We apply this concept to the logistics environment to design secure logistics architecture with subliminal messages. The client can check the subliminal message of the received package, and know whether the package has been switched by malicious people. In addition, the proposed scheme also applies sensor technology;the client can check the GPS location, the temperature and humidity at any time during the delivery process. So intelligent logisticswouldthereby be achieved. This paper proposes an intelligent and secure package sensoring logistics system based on a subliminal channel. The proposed architecture uses the related mechanisms tosolve the problems of a logistics system, including how to achieve mutual authentication, data integrity, anti-switch package, package location and status tracing, resisting replay attacks, forward and backward secrecy, and non-repudiation issues.

Link prediction is to complete the missing links in the network or to predict the generation of new links according to the current network structure information, which is very important for mining and analyzing the evolution of the network such for construction and analysis of logical architecture in 6G network. Link prediction algorithms based on node similarity need predefined similarity functions, which is highly hypothetical and only applies to specific network structures without generality. To solve this problem, this paper proposes a link prediction algorithm based on the subgraph of the target node pair. In order to automatically learn the graph structure characteristics, the algorithm firstly extracts the h-hop subgraph of the target node pair, and then predicts whether the target node pair will be linked according to the subgraph. Experiments on seven real data sets show that the link prediction algorithm based on target node pair subgraph is suitable for various network structures and superior to other link prediction algorithms.

The heat release response of the flame to acoustic excitation is a critical factor for understanding combustion instability. In the present work, the nonlinear heat release response of a methane-air non-premixed flame to the low frequency acoustic excitations is experimentally investigated. The flame describing function (FDF) was measured based on the overall CH* chemiluminescence intensity and the velocity fluctuations obtained by two-microphone method. The CH* chemiluminescence images and the schlieren images were analyzed to reveal the mechanism of nonlinear response. The excitation frequency ranges from 10Hz to 120Hz. The forced relative velocity fluctuation amplitude ranges from 0.10 to 0.50. The corresponding flame Strouhal number (Stf) ranges from 0.43 to 4.67. The study has shown that the flame length responds more sensitively to changes in excitation amplitude when subjected to relatively high frequency excitations. The normalized flame length (Lf/D) decreases from 3.79 to 2.37 with the increase of excitation amplitude at excitation frequency of 100Hz. The number of oscillation zones along the flame increases with increasing excitation frequency, which is consistent with the increase of the Stf. The low-pass filtering characteristic of FDF is caused by the dispersion of multiple oscillation zones, as well as the cancellation effect of the adjacent oscillation zones under relatively high frequency excitation. The cancellation effect of the positive and negative oscillation zones with various Stf is main mechanism for the local gain peak and valley. When two adjacent oscillation regions have approximate amplitudes, the overall phase-lag becomes more sensitive to changes in excitation frequency and amplitude. This sensitivity leads to nonlinear anomalous changes in the phase-lag near the frequency corresponding to the gain valley. The calculated disturbance convection time is consistent with the measured time delay in the short flame scenario. Future research is necessary to establish whether the observed agreement occurs due to the oscillation zone consistently occurring proximate to the flame's center of mass, coupled with a precise determination of the average convective velocity.

Based on data from the Yunnan Province farm household survey, we examine the effect of rural land rights policy on farmers’ income. The regression results show that right significantly raises the total income of farmers, with farm income serving as the primary source of total income. After performing numerous robustness tests, using instrumental variables to handle endogeneity and arriving at the same conclusion, the result is still valid. According to the heterogeneity analysis, in the sample of households with long-term migrant workers, the confirmation of rural land rights significantly increases total and nonfarm income while decreasing farm income. Furthermore, total income includes nonfarm income, which reflects the effect of different farmers' optimal labor allocation based on the external market environment. According to the impact mechanism anal-ysis, right can increase farmers' total income by promoting land transfer, and farmers in less developed areas are more willing to increase their income by land transfer out.

Wi-Fi based localization has become one of the most practical methods for mobile users in location-based services. However, due to the interference of multipath and high-dimensional sparseness of fingerprint data, the localization system based on received signal strength (RSS) is hard to obtain high accuracy. In this paper, we propose a novel indoor positioning method, named JLGBMLoc (Joint denoising auto-encoder with LightGBM Localization). Firstly, because the noise and outliers may influence the dimensionality reduction on high-dimensional sparseness fingerprint data, we propose a novel feature extraction algorithm, named joint denoising auto-encoder (JDAE), which reconstructs the sparseness fingerprint data for a better feature representation and restores the fingerprint data. Then, the LightGBM is introduced to the Wi-Fi localization by scattering the processed fingerprint data to histogram, and dividing the decision tree under leaf-wise algorithm with depth limitation. At last, we evaluated the proposed JLGBMLoc on UJIIndoorLoc dataset and Tampere dataset, experimental results show that the proposed model increases the positioning accuracy dramatically comparing with other existing methods.

An adaptive spatial clustering (ASC) algorithm is proposed in this present study, which employs sweep-circle techniques and a dynamic threshold setting based on the Gestalt theory to detect spatial clusters. The proposed algorithm can automatically discover clusters in one pass, rather than through the modification of the initial model (for example, a minimal spanning tree, Delaunay triangulation or Voronoi diagram). It can quickly identify arbitrarily-shaped clusters while adapting efficiently to non-homogeneous density characteristics of spatial data, without the need of prior knowledge or parameters. The proposed algorithm is also ideal for use in data streaming technology with dynamic characteristics flowing in the form of spatial clustering in large data sets.

A construction for the systems of natural and real numbers is presented in Zermelo-Fraenkel Set Thoery, that allows for simple proofs of the properties of these systems, and practical and mathematical applications. A practical application is discussed, in the form of a Simple and Linear Fast Adder (Patent Pending). Applications to finite group theory and analysis are also presented. A method is illustrated for finding the automorphisms of any finite group $G$, which consists of defining a canonical block form for finite groups. Examples are given, to illustrate the procedure for finding all groups of $n$ elements along with their automorphisms. The canonical block form of the symmetry group $\Delta_4$ is provided along with its automorphisms. The construction of natural numbers is naturally generalized to provide a simple and sound construction of the continuum with order and addition properties, and where a real number is an infinite set of natural numbers. A basic outline of analysis is proposed with a fast derivative algorithm. Under this representation, a countable sequence of real numbers is represented by a single real number. Furthermore, an infinite $\infty\times\infty$ real-valued matrix is represented with a single real number. A real function is represented by a set of real numbers, and a countable sequence of real functions is also represented by a set of real numbers. In general, mathematical objects can be represented using the smallest possible data type and these representations are calculable. In the last section, mathematical objects of all types are well assigned to tree structures in a proposed type hierarchy.

Taking a certain type of test centrifuge as the research object, the finite element model of the test centrifuge is established, the vibration characteristics and aerodynamic performance of the test centrifuge are analyzed, and the structural optimization design of the test centrifuge is carried out. In this paper, the load is applied according to the actual working condition of a certain type of test centrifuge. The vibration of the mounting seat of the test centrifuge is analyzed and the structure of the mounting seat is optimized. After optimization, the vibration of the mounting seat is 77.38 % lower than that of the original mounting seat. Then, the aerodynamic analysis of the test centrifuge is carried out. The analysis results show that the test centrifuge moves more smoothly under the whole package shell and the steady flow shell, and the resistance decreases and the shaft load decreases. Finally, the steady flow shell of the test centrifuge is optimized. The analysis shows that the increase of the width of the steady flow shell can reduce the resistance coefficient, which is helpful to the stability of the test centrifuge during operation and reduces the unbalanced response of the system caused by air resistance.

SARS-CoV2 (corona virus) has spread globally at an unprecedented rate; so far, increasing SARS-CoV2-infected individuals have been identified. Although the situation in China is improving and is currently under control, the outbreak in other countries and its pandemic management is only beginning to develop. Based on 154 SARS-CoV2 genome sequence analyses, we used receptor–ligand docking to identify one potential point mutation (V354F) on the spike structure which enhances spike binding to ACE2 receptors underlying potential super infection. Importantly, the V354F site on spike S1 had been identified in 5/10 infected French patients living in Paris, who sharing 100% identical SARS-CoV2 genomes. With Covid-19 cases increasing rapidly in France that could lead to a new explosion, we suggest that the French government should identify all potential super spreaders and treat them accordingly. In summary, our study provides on of the measures to avoid the potential second worldwide explosion of SARS-CoV2.

Recurrent Pregnancy Loss (RPL) affects 1-2% of women, and its triggering factors are unclear. Several studies have shown the vaginal, endometrial, and gut microbiota may play a role in RPL. A decrease in the quantity of Lactobacillus crispatus in local microbiota has been associated with an increase in local (vaginal and endometrial) inflammatory response and immune cell activation that leads to pregnancy loss. The inflammatory response may be triggered by gram-negative bacteria, lipopolysaccharides (LPS), viral infections, mycosis, or atypia (tumor growth). Bacterial structures and metabolites produced by microbiota could be involved in immune cell modulation and may be responsible for immune cell activation and molecular mimicry. Gut microbiota metabolic products may increase the amount of circulating pro-inflammatory lymphocytes, which, in turn, will migrate into vaginal or endometrial tissues. Local proinflammatory Th1 and Th17 subpopulations along with a decrease in Treg and tolerogenic NK cells are accountable for the increase in pregnancy loss. Local microbiota may modulate the local inflammatory response increasing pregnancy success. Analyzing local and gut microbiota may be necessary to characterize some RPL patients. Although oral supplementation of probiotics has not been shown to modify vaginal or endometrial microbiota, the metabolites produced by it may benefit patients. Lactobacillus crispatus transplantation into the vagina may enhance the required immune tolerogenic response to achieve a normal pregnancy. The effect of hormone stimulation and progesterone to maintain early pregnancy on microbiota has not been adequately studied, and more research is needed in this area. Well-designed clinical trials are needed to ascertain the benefit of microbiota modulation in RPL.

Seasonal precipitation variance significantly alters soil water content, potentially inducing water stress and affecting plant transpiration in semiarid deserts. This study explored the effects of environmental variables and hydraulic conductance on whole-tree transpiration (ET) in Mongolian pines (Pinus sylvestris var. mongolica) across different forest stages in the semiarid deserts of northern China. We measured ET using sap flow in mature (MMP), half-mature (HMP), and young (YMP) Mongolian pine plantations. Measurements included soil-leaf water potential difference (ΔΨ), atmospheric conditions, and soil moisture contents on sunny days, both in dry and wet periods. Seasonally variable rainfall distinctly affected soil moisture, correlating ET with photosynthetically active radiation (PAR) and vapor pressure deficit (VPD). Notable nocturnal sap flow occurred during the growing season. During the dry periods, both stomatal and hydraulic conductance influenced ET, whereas during the wet periods, stomatal conductance primarily regulated it. Discrepancies between predicted and measured ET were noticed: compared to the predicted ET, measured ET was lower during dry periods while higher during wet periods. Hydraulic conductance (KT) increased with tree height (H) and ΔΨ, although tall trees exhibited lower KT rates, suggesting that hydraulic compensation had occurred. This compensation, observed between 11:00 and 13:00, aligned with increased hydraulic resistance during dry periods. Decreasing hydraulic conductance intensified leaf water stress in dry periods, especially during the time when PAR and VPD were heightened, potentially increasing stomatal sensitivity to drought, promoting water conservation and plant survival. A linear relationship between predawn and midday leaf water potentials was noticed, indicating extreme anisohydric behavior across forest stages during both dry and wet periods. Although both stomatal and hydraulic conductance influenced ET during the dry period, MMP and YMP were more susceptible to drought conditions. Understanding these dynamics could help evaluate semiarid desert ecological functions for water conservation amidst uneven seasonal precipitation in Northern China.

Two secondary waste materials, municipal incinerator bottom ash (MIBA) and sewage sludge ash (SSA), were mixed with clay for ceramic manufacturing in this study. Specimens with 5 different MIBA replacement amount of 0%, 5%,10%, 15%, and 20%(wt) and 3 different SSA replacement amount of 0%, 10%, and 20%(wt) were prepared and then a series of tests and analysis were conducted to investigate how the two materials affect the quality of the final product and to what extent. It concludes that a mix with up to 20% of SSA and 5% of MIBA could result in quality tiles complying with specifications for interior or exterior flooring applications at certain kiln temperatures.

The application of Explainable AI (XAI) to improve understanding of complex non-linear SST teleconnections and gain predictive skills is at the frontier of climate research. In this study, we attempt to refine the applications of XAI advancements to ENSO prediction by including SSTA in the western North Pacific (WNP) as a precursor. Our analyses indicate that the baseline accuracy increases from the 60% threshold previously reported for ENSO to &gt;85% for moderate warm, cold, and neutral ENSO states one year in advance when WNP SSTA is included. Precision increases to over 90% for higher magnitude El Niños and La Niñas. Experiments conducted at 4-year lead times yield a strong WNP SSTA signal. A moderate SSTA signal is observed at 3-year lead time with no predictability; however, predictability spikes to over 80% when stratospheric zonal winds are included with WNP SSTA. While additional scientific work is required to make robust connections between XAI and dynamical processes, our results demonstrate a potential to improve long term predictability of ENSO through the ability of XAI in capturing SST patterns evolving at extended spatial and temporal scales.

Objective: To explore the hot spots and development trends of community public health research. Methods: The literature related to this topic was searched in CNKI and PubMed databases, and the trend map of the number of articles was drawn according to the obtained data. The included literature were analyzed with Vosviewer software for keyword and author co-occurrence, and CiteSpace 6.3.R1 Basic software was used for mechanism co-occurrence, key emergence and clustering analysis, and timeline distribution map drawing. Results: 189 Chinese literature and 77 English literature were selected. The Chinese literature focused on “community public health service, emergency management, and community governance”, and the research trend was “community public health emergency management and community governance”; English literature focuses on “nursing education, health education, human qualitative research”. Conclusion: Although the Chinese and English literature shows that scholars in this field have different emphases, the primary community health is the key and difficult point to realize the national public health service project, and improving the basic public health service in the primary community is related to the health of all the people, so it is very important.

A facilitative transport system exists on the blood brain barrier (BBB) that has been tacitly assumed to be a path for glutamate entry to brain. But glutamate is a non-essential amino acid whose brain content is much greater than plasma, and studies in vivo show that glutamate does not enter brain in material quantities except in those small regions with fenestrated capillaries (circumventricular organs). The situation became understandable when luminal (blood facing) and abluminal (brain facing) membranes were isolated and studied separately. Facilitative transport of glutamate and glutamine exist only on the luminal membranes whereas Na+-dependent transport systems for glutamate, glutamine and some other amino acids are present only on the abluminal membrane. The Na+-dependent cotransporters of the abluminal membrane are in a position to actively transport amino acids from the extracellular fluid (ECF) into the endothelial cells of the BBB. These powerful secondary active transporters couple the energy of the Na+-gradient to move glutamate and glutamine into the ECF whereupon glutamate can exit to blood on the luminal facilitative glutamate transporter. Glutamine may also exit brain on a separate facilitative transport system that exists on the luminal membranes or glutamine can be hydrolyzed to glutamate within the BBB thereby releasing ammonia that is freely diffusible. The γ-glutamyl participate cycle participates indirectly by producing oxoproline (pyroglutamate) that stimulates almost all secondary active transporters yet discovered in the abluminal membranes of the BBB.

An eight-sided prism sample, obtained from a hot-rolled AZ31 magnesium alloy sheet, was compressed at room temperature along the transverse direction to investigate the influence of local strain on twinning behavior using electron backscatter diffraction (EBSD) measurements. The octagonal surface of the sample was divided into distinct regions based on hardness distribution and metallographic observations. The EBSD maps of different areas show significant variations, suggesting that these areas experienced different local strain conditions. The EBSD measurements provided detailed data from three distinct regions, with the strain state known in two regions and uncertain in the third. The combined analysis of the Schmid factor (SF) and the strain compatibility factor (m') was employed to study twin variant selection. The comparison of twinning behavior in different regions showed that the strain compatibility factor offered a more comprehensive explanation for the observed twinning pattern in the region with local shear strain.

YG-13A represents the highest level of Chinese SAR satellites to date. In this paper, we report on experiments conducted to improve and validate ranging accuracy with YG-13A. We analyze the error sources in the YG-13A ranging system, such as atmospheric path delay, and transceiver channel delay. A real-time atmospheric delay correction model is established to calculate the atmospheric path delay, considering the troposphere delay and ionosphere delay. Six corner reflectors (CRs) were set up to ensure the accuracy of validation methods. Pixel location accuracies of up to 0.479-m standard deviation can be achieved after a complete calibration. We further demonstrate that the adjustment of the CRs can cause a marginal loss of ranging precision. After eliminating this error, the ranging accuracy is improved to 0.237 m. For YG-13A, a single frequency GPS receiver is used and the orbital nominal accuracy is 0.3 m, which is the biggest factor restricting its ranging accuracy. Our results show that the ranging accuracy of YG-13A can achieve decimeter-level, which is lower than centimeter-level accuracy with TerraSAR-X loading a dual frequency GPS. YG-13A has great convenience in terms of access to control points and target location that does not depend on ground equipment.

While digitization can make the health industry faster and more efficient, there are many financial, social and organizational obstacles and barriers to its implementation. This article offers a systematic review of the main troubles detected from the literature review. Also there is a proposal of new kind of restrictions to pay attention. Finally, its offer an heterodox reading about the problem analyzed.

In the present work, a predictive modelling and optimization with the adaptive network based fuzzy inference system(ANFIS) modelling of mechanical properties of laser-coated NB/SiC/Ni welds was studied based on Taguchi design by laser cladding. An ANFIS model based on a Sugeno type fuzzy inference system was developed for predicting the hardness properties of SiC/BN/Ni welds by laser cladding with experimental data required for network training and prediction. Based on analysis of variance, three important factors were taken as inputs for the fuzzy logic inferences, while the hardness properties was taken as the output of the ANFIS. The microstructure of welds were analysed using scanning electron microscopy with an energy dispersive X-Ray spectrometer. Highly developed leaf-like dendrites and eutectic crystals were found in some areas of the melting zone for the BN/SiC/Ni weld, which was significantly hardened. The ANFIS model based on Taguchi's design provides a better pattern of response because the predicted and experimental values were highly similar. As a result, a satisfactory result was achieved between the predicted and experimental values of hardness in laser-coated NB/SiC/Ni welds, whereby the success and validity of the method was verified.

Infrared small target detection (ISTD) plays a crucial role in both civilian and military applications. The detection of small targets against dense cluttered backgrounds remains a challenging task, requiring the collaboration of false alarm source elimination and target detection. Existing approaches primarily focus on modeling targets while often neglecting false alarm sources. To address this limitation, we propose a Target and False Alarm Collaborative Detection Network to leverage the information provided by false alarm sources and the background. Firstly, we introduce a False Alarm Source Estimation Block (FEB) that estimates potential interferences present in the background by extracting features on multiple scales and employing stepwise upsampling for feature fusion. Subsequently, we propose a framework that employs multiple FEBs to eliminate false alarm sources across multiple scales. Finally, a Target Segmentation Block (TSB) is introduced to accurately segment the targets to produce the final detection result. Experiments on public datasets demonstrate that, compared to other methods, our model achieves high accuracy in segmenting targets while being able to extract false alarm sources which can be used for further studies.

In this paper, a distributed algorithm is proposed to solve a consensus convex optimization problem. It is a Jacobi-proximal alternating direction method of multipliers with a damping parameter $\gamma$ in the iteration of multiplier. Compared with existing algorithms, it has the following nice properties: (1) The restriction on proximal matrix is relaxed substantively, thus alleviating the weight of the proximal term. Therefore, the algorithm has a faster convergence speed. (2) The convergence analysis of the algorithm is established for any damping parameter $\gamma\in(0,2]$, which is larger ones in the literature. In addition, some numerical experiments and an application to a logistic regression problem are provided to validate the effectiveness and the characteristics of the proposed algorithm.

This article is about school evaluation. The objective was to explain critically the mediating relationships between educational evaluation and the production of school knowledge from the perspective of the Dialectical Historical Materialism. With this interest, a documentary analysis was made, obtaining as result four explanatory categories: production, subsumption, distribution and exchange of knowledge, which form a concrete totality with distinctions and antagonistic relationships between them, limited by their opposite. It is concluded that the evaluation as a mediating form lacks antagonistic pair and consequently of control by opposition, emerging from the school daily as autonomous and sovereign entity, oppressive of school subjects.

Today's city needs more than ever methodological devices that ensure a specific urbanism, in keeping with the complexity of relationships that occur in the urban space. Networks or systems of diverse nature must be activated to achieve a certain success of the city, even more so in its fragile central fabrics. The study is focused on the historic neighborhoods of the city of Jaén (Spain), which have a high vulnerability index. The aim is to establish a strategy to revitalize their urban and social capital and improve their articulation with the rest of the urban and territorial structure. A methodological proposal for the analysis of vulnerability factors and an urban and cartographic analysis of the public space is addressed through an interweaving of a triple network: environmental, social, and urban. For this purpose, the configuration of this overlapping network of analysis and formulation of criteria is presented, which considers the urban multiplicity and promotes new dynamics for the integrated urban regeneration of the area and for the activation of public and collective urban spaces.

The fatigue delamination damage is one of the most important fatigue failure modes of laminated composite structures. However, the developments of the theoretical framework, mathematical/physical model and numerical simulation of fatigue delamination are still challenging issues, and there is a lack of systematic classification. This article reviews the experimental phenomena of the onset and propagation stage of delamination under fatigue loading, and summarizes the commonly used phenomenological models for laminated composite structures. The research methods, general modeling formulas and development prospects of the phenomenological models are presented in detail. In the light of the analysis of finite element model (FEM) for the laminated composite structures, a number of simulation methods of fatigue delamination crack propagation damage model are carefully classified. Furthermore, within the theoretical framework of strength theory model (SM), fracture mechanics model (FM), damage mechanics model (DM) and hybrid model (HM), the complete procedure, application, capability assessment, advantages and limitations of the models are also discussed in detail. Finally, several valuable suggestions are given for the research interests, and challenging technical problems that need to be overcome on the fatigue delamination prediction of laminated composite structures in the future.

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

The development of one technology can be portrayed by common methods like Gartner’s hype cycle or S-curve, however, there is no method to characterize the feature distributions of multiple technologies within a specific domain. This study proposes a big data-based method in terms of four proposed features, namely versatility, significance, commerciality, and disruptiveness, to characterize the technologies within a given domain. The features of technologies are quantitively portrayed using the representative keywords and volumes of returned search results from Google and Google Scholar in two-dimensional analytical spaces of technique and application. We demonstrate the applicability of this method using 452 technologies in the domain of intelligent robotics. The results of our assessment indicate that the versatility values are normally distributed, while the values of significance, commerciality, and disruptiveness follow power-law distributions, in which few technologies possess higher feature values. We also show that significant technologies are more likely to be commercialized or causing potential disruption, as such technologies have higher scores in these features. Further, we validly prove the robustness of our approach via comparing historical trends with literature and characterizing technologies in reduced analytical spaces. Our method can be widely applied in analyzing feature distributions of technologies in different domains, and it can potentially be exploited in decisions like investment, trade, and science policy.

In this work,the wave behaviour propagation of single-walled fluid conveying carbon nanotubes (SWCNT) under longitudinal magnetic fields and elastic foundations is studied, based on the nonlocal strain gradients theory(NSGT). With considertion of surface effect, the governing differential equation are obtained utilising Timoshenko beam theory and Hamilton's variational principle. The influence of small-scale parameters, fluid density, magnetic flux, surrounding elastic medium and surface effects on wave behaviour characteristics of carbon nanotubes are discussed in detail. The numerical results illustrated that with the magnetic flux increase，the phase velocities of the carbon nanotube will increase. When the fluid effects inside the carbon nanotube, the wave frequencies of the system reduces with increase in the non-local coefficient, while promotes with increase in the strain gradient coefficient. In addition, fluid density, surrounding elastic medium and surface effects have meaningful influence on the phase velocity of the system.

The anti-inflammatory effect of ginsenoside Rh2 (GRh2) is one of the most important ginsenosides. The purpose of this study is to identify the anti-inflammatory and antioxidant effects of GRh2 after LPS challenge lung injury animal model. GRh2 reduced LPS-induced NO, TNF-α, IL-1, IL-4, IL-6 and IL-10 productions in lung tissues. GRh2 treatment decreased the histological alterations in the lung tissues and BALF protein content and total cells number also diminished in LPS-induced lung injury mice. Moreover, GRh2 blocked iNOS, COX-2, the phosphorylation of IκB-α, ERK, JNK, p38, Raf-1 and MEK protein expression which is corresponded to the growth of HO-1, Nrf-2, catalase, SOD and GPx expressions in LPS-induce lung injury. An experimental study has suggested that GRh2 has provided with anti-inflammatory effects in vivo, and its potential therapeutic efficacy in major anterior segment lung diseases.

The one-dimensional MoS₂/carbon nanofibers (1D MoS₂/CNFs) are synthesized by electrospinning using exfoliated MoS₂ nanosheets and polyacrylonitrile as raw materials. The exfoliated MoS₂ nanosheets with size of about 150 nm are encapsulated in carbon nanofibers, and the free-standing MoS₂/CNFs can be easily cut into flexible tablet and directly used as binder-free anode for lithium storage. The resultant 1D MoS₂/CNFs exhibit a very high reversible capacity of 700 mAh g^-1 at 100 mA g^-1 after 50 cycles, high rate capacity (450 mAh g^-1 at 1000 mA g^-1 after 200 cycles) and good cycle stability.

As two commonly-used non-selective herbicides, glyphosate (GP) and diquat (DQ) are easily co-resided in lateritic paddy soil due to the rich iron/aluminum oxides, nevertheless there is limited information on their co-impact on microbial diversity and community structure in this type soil. In this study, the short-term effects of combined GP and DQ on soil microbial diversity and community structure shifts were investigated in lateritic paddy soil from a tropical agricultural region (Hainan, China) based on 16S rRNA and ITS high-throughput sequencing technology. The results showed that mixed herbicides promoted the abundance of Streptomyces in bacteria (0.45-1.84%) and Curvularia in fungi (0.01-5.85%), while GP and DQ had inhibitory effects on the abundance of Streptomyces (0.13-2.21%) and Curvularia (0.03-1.13%), which were significantly different with their single exposure (p < 0.05); the combined application of the two herbicides aggravate the adverse effect on the diversity of soil fungal community (p < 0.05), although their mixture did not have a greater impact on the soil bacteria abundance/diversity and fungi abundance (p > 0.05). Results suggested that the combined application of GP and DQ affected the fungal diversity although they did not cause other significant negative effects on soil microorganisms, hinting that more attention should be paid to the mixed effect caused by GP and DQ on specific fungal populations in lateritic paddy soil.

The utilization of dual-potential mode of integrated array (IDA) electrodes and other two-electrode systems has revolutionized electrochemical detection by enabling the simultaneous and independent detection of two species, accompanied by the exhibition of unique characteristics. In contrast to conventional dual-potential electrodes, the rotating ring disk electrodes (RRDE), IDA electrodes demonstrate analogous yet vastly improved performance metrics, characterized by remarkable collection efficiency and sensitivity. Notably, due to the distinctive microscale structure of IDA electrode, the special “feedback” effect makes IDA a unique signal amplifier. In recent decades, the research surrounding IDA electrodes has garnered escalating interest due to their attractive attributes. This review centers its focus on the fabrication and applications of IDA electrodes. In the realm of fabrication, two critical breakthroughs are poised for realization: the achievement of reduced dimensions and the diversification of materials. Established fabrication methods for IDA electrodes encompass photolithography, inkjet printing, and direct laser writing, each affording distinct advantages in terms of size and precision in IDA construction. Predominantly employed materials for IDA electrodes include gold, platinum, and carbon, with the selection of fabrication methods guided by considerations such as material properties, desired dimensions, cost-efficiency, and specific application requisites. Within the domain of applications, IDA electrodes, capitalizing on their distinctive attributes, have found utility in diverse fields. This review summarizes the applications of IDA electrodes based on their fundamental working principles, encompassing redox cycling, resistance modulation, capacitance variations, and more. The potential for further development of this specialized tool to exhibit enhanced properties holds substantial promise.

Microglial cells are highly specialized central nervous system (CNS) cells that can promote the inflammation and neurodegeneration seen in Multiple Sclerosis (MS). MS is a neurodegenerative autoimmune disease characterized by inflammation, demyelination, and axonal degeneration. In MS patients, demyelination is associated with activated microglia. Endothelin-1 (ET-1) is a potent vasoconstrictor that induces severe and prolonged cerebral vasoconstriction and inflammation. However, the mechanism of how ET-1 activates a proinflammatory response in the CNS is unknown. To investigate ET-1’s role in microglia activation, HMC3 cells were treated with ET-1 in the presence or absence of endothelin receptor B antagonist, BQ788. TNFα and IL-6 levels were measured using ELISA. Nitric Oxide (NO) production was measured using Griess Reagent. Reactive oxygen species (ROS) production was measured using the MUSE Oxidative Stress kit. ET-1 increases TNFα levels by 56% (p= 0.0003) and IL-6 levels by 86% (p= 0.0111) in HMC3 cells, and it was decreased to basal levels in the presence of BQ788. NO and ROS production is induced by ET-1 (p&lt;0.05), and treatment with BQ788 was able to decrease them. ET-1 increases STAT-1 activation by 3.5 folds compared to control (p &lt;0.0001) in microglia cells. Moreover, to study ET-1 levels in MS, we used C57BL/6 mice brains with or without induced experimental autoimmune encephalomyelitis (EAE). The brain ET-1 levels were measured by qPCR and ELISA. We found that the ET-1 gene and protein were upregulated by 1.5 folds (p= 0.0199) in EAE mice compared to the control. These data suggest that in vitro administration of ET-1-activated microglia significantly increased inflammatory cytokine levels and NO and ROS formation. This novel mechanism of microglial cell activation will provide key information to understand MS pathogenesis.

The subtilase family is the second largest family of serine proteases. Some fungi including Trichoderma species can capture and kill nematodes by secreting hydrolytic enzymes or toxins, among which serine proteases are important enzymes that allow fungi to infect nematodes. Subtilase can degrade nematode and insect body walls. In this study, subtilase family genes were identified from the Trichoderma harzianum genome database, and bioinformatics analysis of the characteristics and evolutionary status of these genes, along with structural and functional analyses of their proteins, was performed. Gene structure analysis revealed that all the 41 subtilase genes contained introns, while some did not have upstream or downstream regions. Chromosome localisation showed that subtilase family members were unevenly distributed in 22 Trichoderma chromosomes, and 3 clusters were present, indicating that they may be hot spots of subtilase genes. Conserved motif analyses showed these proteins contained a commonly conserved motif, and motifs belonging to the same subfamily remained highly similar. The upstream region of the subtilase genes were enriched with different type and numbers of cis-elements, indicating that subtilase genes are likely to play a role in the response to diverse stresses. Transcription of 31 genes was increased after 5 days of infection with nematodes, whereas that of 10 genes decreased. In these subtilase genes, ThSBT4, ThSBT5, ThSBT12, ThSBT27, ThSBT34, ThSBT35, ThSBT38, and ThSBT40 showed significantly upregulated expression with a log2 fold change value of more than 4, and ThSBT35 showed the highest peak. These results laid a theoretical foundation for further research on the function of the subtilase genes and the mechanism of the resistance response.

A study of cryogenic drilling in sandwich composites has been carried out. Materials used have been carbon fiber reinforced polymer sandwich sheets with inner foamed polyvinyl chloride core, composites with aerospace, marine, construction and automotive applications, including protec-tion structure of Polar engineering equipment. Experimental tests have been performed in lam-inates with 12 mm and 6 mm of thickness, drilling with liquid nitrogen as refrigerant to reach temperatures below -120ºC under different cutting conditions, in particular, drill rotation speeds between 2000 rpm and 6000 rpm and feed rates between 200 mm/min and 600 mm/min. Variables as thrust forces and circularity error have been measured, due to the importance of its effect on the hole quality, as an operation prior to a possible assembly. A design of experiments has been allowed determining relationships between variables, identifying the influence of cutting condi-tions on the thrust force and the circularity at inlet and outlet holes.

Aimed to obtain purple garlic varieties, 360 bolting bulbs from the Protected Geographical Indication (PGI) “Las Pedroñeras” were selected for their size, and the presence of abundant external scales. After a further selection, 243 out of the 360 bulbs were discarded due to undesired characteristics, as light purple color, high number of small cloves, cloves affected by Fusarium spp. and mites, among other. It was stablished that each bulb would give rise to a family. Thus, 117 families were planted under a random design during season 2021-2022. Either physiological, morphological and phenological traits were assessed for each family, and the affectations by pest and pathogens were also controlled. After the assessment of this trial, 103 out 117 families remained in the program, and were used for the establishment of a second trial the next season. Unlike the first trial, after the evaluations only 23 families remained in the program. There was observed a high variability for most of traits, with a great influence of families. The phenotypic behavior of families was significative influenced by environment, highlighting the need of their assessment under different environmental conditions. The high variability registered for the target sample, opens the possibility to select new garlic varieties from this PGI.

In the context of freshwater ecosystems, turbidity and suspended solids play crucial roles, with their levels significantly influenced by anthropogenic activities. This study focuses on assessing and monitoring these parameters in Albufera de Valencia using Sentinel-2 imagery. The primary aim is to establish reliable estimation algorithms that can contribute to effective ecosystem management. The study calibrated and validated algorithms for estimating turbidity and suspended solids. The R783×R705/R490 model proved to have the best performance for estimating turbidity and total solids in the Albufera. However, R783/R490 obtained a higher coefficient of de-termination for the organic part, while the R705 band was selected for the inorganic part. However, to achieve better estimates of turbidity and inorganic matter, more research is needed in the future. The implications of excessive suspended solids are underscored, including the depletion of dissolved oxygen, and reduced primary productivity due to limited light penetration and habitat availability. Collaboration between disciplines such as limnology, optics and water chemistry are crucial to advance water quality estimation models in lakes and lagoons such as Albufera. By integrating expertise and approaches from these diverse fields, new knowledge can be gained and the basis for more effective management and conservation strategies can be laid.

The characteristics of biogenic aerosols in urban area were explored by determining the composition, temporal distribution of saccharides in PM_2.5 in Shanghai. The total saccharides showed a wide range of 15.2 ng/m³ to 1752.8 ng/m³, with the averaged concentrations were 169.8 ng/m³，300.5 ng/m³，288.4 ng/m³，688 ng/m³ in spring, summer, autumn, and winter, respectively. The concerned saccharides include anhydrosaccharides (levoglucosan and mannosan), which were higher in cold seasons due to the increased biomass burning, saccharide alcohols (mannitol, arabitol, sorbitol) and monosaccharides (fructose, glucose), which showed more abundant in warm seasons attributed to the biological emissions. By PMF analysis, four emission sources of saccharides were demonstrated, including biomass burning, fungal spores, soil suspension and plant pollens. Resolution of backward trajectory and fire points showed a process of high concentrations of levoglucosan. We found that concentrations of anhydrosaccharides showed relatively stable under different pollution levels while saccharide alcohols exhibited an obvious decrease, indicated that biomass burning was not the core reason of the heavy haze pollution, however, and high level PM_2.5 pollution might inhibit effects of biological activities.

According to official sources, the numbers of children-to-parent violence (CPV) in the most advanced countries have been on an increasing trend for more than a decade, which generates great social concern. This phenomenon has also aroused enormous interest among researchers, who have identified risk and protective factors related to adolescent CPV in numerous studies. To contribute to a better explanation of CPV, the aim of the present study was to analyze the relationship between family communication problems and CPV, through psychosocial adjustment variables -psychological distress and positive attitude toward the transgression of social norms- in schooled adolescents. The sample consisted of 8115 adolescents enrolled in schools in the State of Nuevo León (Mexico) (51.5% boys, 49.5% girls), whose ages ranged from 11 to 16 years (M = 13.34, SD = 1.04). Structural equation modeling was performed using Structural Equation Modeling Software (EQS). The results showed that family communication problems have a direct and signif-icant relationship with CPV. It was also observed that there is an indirect relationship between both variables, through the relationships of psychological distress and positive attitude towards the transgression of social norms. The multigroup analysis performed showed gender differences in some of these relationships. Finally, the results and their implications in the field of family intervention are discussed.

The research aims to present an innovative methodology to execute the Heritage conservation processes in a collaborative and interdisciplinary BIM project, with an effective management of the deterioration suffered over time, emphasizing the structures and coatings. The research begins with the architectural survey using scanning techniques (TLS) and terrestrial photogrammetry (SfM) and taking as a study the Duomo of Molfetta (Italy), a unique Romanesque architecture of Puglia (Italy). The methodological process is mainly aided by the precise semantic segmentation of global point clouds, a semi-automatic process assisted by classification algorithms implemented in the post-processing software, and which has allowed the classification of the unstructured information provided by the remote sensing equipment when identifying the architectural-structural systems of a building with high historical values. Subsequently, it has been possible to develop an efficient Scan-to-HBIM workflow, where the Heritage-BIM (HBIM) project has fulfilled the function of a database by incorporating and organizing all the information (graphic and non-graphic) to optimize the tasks of auscultation, identification, classification, quantification and, in turn, facilitating the parametric modeling of unique structures and architectural elements. The results have shown great effectiveness in the processes of characterization of architectural and artistic heritage, focusing on the deformations and deterioration of the masonry in columns, and making multidisciplinary conservation work in an HBIM project more flexible. But there are still some difficulties for the automatic interpretation of 3D point cloud data, related to specific systems of the historical architecture. In conclusion, human action and interpretation continues to be a fundamental pillar to achieve precise results in a heritage environment.

Helicobacter pylori infection constitutes a silent pandemic of global concern. In the last decades, the alarming increase of multidrug resistance evolved by this pathogen has led to a marked drop in the eradication rates of traditional therapies worldwide, encouraging scientific community to discover and develop new antimicrobial strategies. In the present work, we identified a battery of novel drug-like HsrA inhibitors with MIC values ranging from 0.031 to 4 mg/L against antibiotic-resistant strains of H. pylori. Most of these novel antimicrobials exhibited minor effects against both Gram-negative and Gram-positive species of human microbiota. The most potent anti-H. pylori candidate demonstrated a high therapeutic index, additive effect in combination with metronidazole and clarithromycin, as well as a strong antimicrobial action against Campylobacter jejuni, another clinically relevant pathogen of phylum Campylobacterota. Transcriptomic analysis suggested that in vivo inhibition of HsrA triggered lethal global disturbances in H. pylori physiology, including the arrest of protein biosynthesis, malfunction of respiratory chain, detriment in ATP generation, and oxidative stress. The novel drug-like HsrA inhibitors described here constitute valuable candidates to a new family of narrow-spectrum antibiotics that allow overcoming the current resistome, protecting from dysbiosis, and increasing therapeutic options for novel personalized treatments against H. pylori.

Current effort with light field displays is mainly concentrated on the widest possible viewing angle, while a single viewer only needs to view the display in a specific viewing direction. To make light field display a practical practice, a super multi-view light field display is proposed to compress the information in the viewing zone of a single user by reducing the redundant viewpoints. A quasi-directional backlight is proposed and a lenticular lens array is applied to achieve the restricted viewing zone. Eye-tracking technique is applied to extend the viewing area. Experimental results show that the proposed scheme can present vivid 3D scene with smooth motion parallax. Only 16.7% conventional light field display data are required to achieve 3D display. Furthermore, an illumination power of 3.5 watt is sufficient to lighten a 31.5-inch light field display，which takes up 1.5% of the illumination power required for planar display of similar configuration.

Huge amounts of chitin and chitosans can be found in the biosphere as important constituent of the exoskeleton of many organisms, as well as waste by worldwide seafood companies. Nowadays, politicians, environmentalists, and industrialists encouraged the use of these marine polysaccharides as renewable source, particularly when developed by alternative eco-friendly processes, especially in the production of regular cosmetics. The aim of this review is to outline the physicochemical and biological properties and the different bioextraction methods of chitin and chitosans sources, focusing on enzymatic deproteinization, bacteria fermentation, and enzymatic deacetylation methods. Thanks to their biodegradability, non-toxicity, biocompatibility, and bioactivity, the application of these marine polymers is widely used in the contemporary manufacturing of biomedical and pharmaceutical products. In the end, advanced cosmetic products based on chitin and chitosans are presented, analyzing different therapeutic aspects about skin, hair, nail, and oral care. The innovative formulations described can be considered as excellent solutions regarding problems in the various body anatomical sectors.

Background: The Hengduan Mountains are one of the most species–rich mountainous areas in the world. The origin and evolution of such a remarkable biodiversity are likely to be associated with geological or climatic dynamics, as well as taxon-specific biotic processes (e.g., hybridization, polyploidization, etc.). Here, we investigate the mechanisms fostering the diversification of the endemic Himalopsyche martynovi complex, a poorly known group of aquatic insects. Methods: We used multiple allelic datasets generated from 691 AHE loci to reconstruct species and RaxML phylogenetic trees. We selected the most reliable phylogenetic tree to perform network and gene flow analyses. Results: Phylogenetic reconstructions and network analysis identified three clades, including H. epikur, H. martynovi sensu stricto and H. cf. martynovi. Himalopsyche martynovi sensu stricto and H. cf. martynovi present an intermediate morphology between H. epikur and H. viteceki, the closest known relative to the H. martynovi–complex. The gene flow analysis revealed extensive gene flow among these lineages. Conclusion: Our results suggest that H. viteceki and H. epikur are likely to have contributed to the evolution of H. martynovi sensu stricto and H. cf. martynovi via gene flow, and thus, our study provides insights in the diversification process of a lesser–known ecological group, and hints at the potential role of gene flow in the emergence of biological novelty in the Hengduan Mountains.

(1) In order to study the influence of chaotic system on wheat image encryption, a method to find the optimal chaotic system encryption based on wheat image is proposed. (2) 10 different chaotic system schemes are combined to encrypt wheat images by 13 common chaotic maps, respectively. The best chaotic system scheme is obtained by considering the anti-attack capability of these encryption schemes, which analyzes 8 commonly used image encryption performance evaluation indexes. (3) The experimental results show that the new four-dimensional chaotic system has the best encryption effect, which is suitable for wheat image encryption. (4) The proposed scheme of wheat image encryption based on chaotic system provides a reference for other crop image encryption.

The heat generated during the startup process of dry gas seals, such as the friction heat of the asperities, viscous shear heat, and the expansion heat of the gas film, easily leads to seal failure and endangers the stable operation of turbomachinery. This study combines the statistically modified contact model and the average Reynolds equation by considering the adiabatic index and the microscale effects of dry gas seals to explore the heat generation characteristics of dry gas seals formed in series at multiple times. In particular, the change laws and influencing factors among the components, including the friction heat of asperities and the shear heat and expansion heat of the gas film and total heat, are investigated. A comparative analysis indicates that the slip flow effect increases the total heat during the startup process. The friction heat is much greater than expansion heat and shear heat. Despite constant acceleration, exponential acceleration, or Harrision acceleration, the heat changes are uneven during the startup process. In particular, the heat changes sharply in the early stage and gently in the later stage. The Harrision acceleration mode is the most conducive to sealing stability.

Experimental methodologies for fatigue lifetime prediction are time-intensive and susceptible to environmental variables. While the cohesive zone model is popular for predicting adhesive fatigue lifetime, entropy-based methods have also shown promise. This study aims to provide an understanding of the durability characteristics of CFRP adhesive joints by incorporating an entropy damage model within the context of the finite element method (FEM), examined the effects of different adhesive layer thicknesses on SLS models. As the adhesive layer increased in thickness, DAMAGE VARIABLES initially rose and then declined, peaking at 0.3mm. This finding provides crucial understanding into the stress behavior at the resin-CFRP interface and the resin's fatigue mechanisms.

The inherent non-smoothness of vibroimpact system leads to complex behaviors as well as strong sensitive dependence on parameter changes. Unfortunately, uncertainties and errors in system parameters are inevitable in mechanical engineering. Therefore, the investigations of dynamical behaviors for vibroimpact systems with stochastic parameters are highly essential. The present study aims to analyze the dynamical characteristics of the three-degree-of-freedom vibroimpact system with an uncertain parameter by means of the Chebyshev polynomial approximation method. Specifically, the vibroimpact system model considered is one with unilateral constraint. Firstly, the three-degree-of-freedom vibroimpact system with an uncertain parameter is transformed into an equivalent deterministic form by the Chebyshev orthogonal approximation. Then, the ensemble means responses of the stochastic vibroimpact system are derived. Numerical simulations are performed to verify the effectiveness of the approximation method. Furthermore, the periodic and chaos motions under different system parameters are investigated, and the bifurcations of the vibroimpact system are analyzed by the Poincaré map. The results demonstrate that both the restitution coefficient and the random factor can induce the appearance of the periodic bifurcation. It is worth noting that the bifurcations fundamentally differ between the stochastic and deterministic systems. The former has a bifurcation interval, while the latter occurs at a critical point.

Pedestrian multi-target tracking technology plays an important role in artificial intelligence, driverless, virtual reality and other fields. The pedestrian multi-target tracking algorithm DeepSORT based on detection is widely used in industry. It mainly tracks multiple pedestrian targets continuously and keeps their ID unchanged. In order to improve the applicability and tracking accuracy of DeepSORT algorithm, this paper improved the IOU distance measurement in the matching process. At the same time, ResNet50 is used as the feature extraction backbone network, and combined with FPN (Feature Pyramid Network), the appearance features of multi-layer pedestrians are fused to improve the tracking accuracy of DeepSORT algorithm. The proposed algorithm is verified on the public data set MOT-16 and it’s tracking accuracy is enhanced to 4.1%.

Statistics modules are included in most university degrees, independent of the degree area. They have an important role in preparing students for the real world. The overall goal of this paper is to identify the common statistical issues students face during the transition from secondary education to tertiary education. Drawing upon data from the University College Dublin (UCD) Math Support Center (MSC) and Universidad Rey Juan Carlos (URJC), our approach aims to optimize learning experiences while advancing sustainability objectives. In this paper, we conducted a categorization of statistical concepts taught in university (based on URJC). Using this categorization, UCD MSC tutor comments were categorized and validated, and subsequently descriptive analyses and text mining were used on the UCD MSC comments to achieve a deeper understanding of the statistical issues. Building on this study, we plan to develop a suite of evidence-based sustainable educational applications and games to support undergraduate students internationally in first-and second-year statistical modules. Our findings on students’ main statistical issues contribute to the cultivation of lasting statistical literacy among students. This research advances the sustainability agenda within statistical education.