To expand the application area of the reference group and enrich exercise theoretical research, based on Stimulus-Organism-Response (S–O-R) framework, this study examines the factors that motivate for adherence to exercise from the external. Taking reference group and strategy and cultural fit as the main stimulus, and personal investment and life satisfaction as mediating variables, this study try to explore the influence of external stimulus on residents’ exercise behavior. In order to enrich the sample size, two surveys of 734 Chinese residents in two cities (Xiamen vs. Fuzhou) were conducted using factor analyses, regression analysis, and T-test analysis. The results indicated that the reference group and strategic and cultural fit as external stimulus have impact on residents’personal investment, life satisfaction and exercise adherence, personal investment and life satisfaction as the organism has impact on residents’ exercise adherence. Personal investment and life satisfaction play a chain mediating role between the reference group and exercise adherence, strategy and cultural fit, and exercise adherence. Moreover, the T-test determined the differences between Xiamen and Fuzhou residents’ exercise adherence and life satisfaction. Residents’ surroundings affect their exercise behavior and life satisfaction. These findings have implications for policymaking aimed at promoting national exercise, which could gradually improve residents’ physical fitness, particularly in light of the current coronavirus emergency.

Nutrients are the driving force of plant and herbivore interactions. Different elements and fertilization levels in soil, or artificially fertilized substrates can have a direct impact on plant defense responses. Meanwhile, nutrient levels mediated by root associated microbes can indirectly affect plant-herbivore interactions. Nutrient uptake promoted by beneficial mycorrhizal fungi or rhizobacteria interacting with roots can stimulate plant tolerance to herbivore attack, as evidenced by herbivore performance, plant nutrient status, plant biomass allocation and compensatory growth. In return, herbivory affects nutrient fluxes between plants and their associated beneficial microbes. Furthermore, aboveground and belowground herbivory can affect the nutrient exchange between plants and soil microbial communities, mainly for carbon-and nitrogen-based resources supporting herbivores´ life cycles. These ecological interactions are governed by jasmonic acid (JA) and key enzymes on the molecular level. This review summarizes the current scientific literature on the role of nutrients in plant-herbivore interactions. This will support efforts to optimize plant defense strategy via managing nutrient variance.

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.

During deep-sea mining, the heavy metals pollutants can cause contamination in the marine environment. In this paper, the multiphasic coupling model is established to describe the heavy metal migration process during deep-sea mining, which takes the effects of convection-diffusion, adsorption-desorption and sedimentation-resuspension of heavy metals in the aquatic environment into full consideration. Due to the advantages of Lattice Boltzmann method, it is adopted to numerically solve the multiphasic coupling model and achieve the simulation for heavy metal migration process during deep-sea mining. In addition, taking Cadmium as an example, the concentration variations are discussed and analyzed in detail. Based on the established model and Lattice Boltzmann method, the concentration distribution of heavy metals can be accurately described to provide the reasonable bases for the evaluation of marine environmental protection.

Fire is a serious security threat that can lead to casualties, property damage, and environmental damage. However, despite the availability of object detection algorithms, challenges persist in detecting fires and smoke. These challenges include slow convergence speed, poor performance in detecting small targets, and high computational cost limiting deployments. In this paper, Fire smoke and human detection based on ConvNeXt and Mixed encoder (FCM-DETR), an end-to-end object detection algorithm based on Deformable DETR, is proposed. Firstly, we introduce ConvNeXt to take the place of Resnet, which greatly reduces the amount of computation and improves the ability to extract irregular flame features. Secondly, to effectively process multi-scale features, the original encoder is decoupled into two modules. Then Mixed encoder, an innovative encoder structure, is proposed, resulting in excellent performance of multi-scale fire and smoke features fusion. What can’t be overlooked is that the encoder block is compatible with any DETR-based models. Finally, the convergence speed is accelerated and the mean of average precision is improved by applying a novel loss function called Powerful IoU v2. The experimental results indicate that our model achieves the best detection accuracy compared to other models, with mAP reaching 66.7%, mAPs and Accuracyfire achieving impressive 50.2% and 98.05%, respectively.

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.

We explored the dynamics of the two interacting information systems. We show that for the Markovian marginal systems the driving force for information dynamics is determined by both the information landscape and information flux. While the information landscape can be used to construct the driving force to describe the equilibrium time reversible information system dynamics, the information flux can be used to describe the nonequilibrium time-irreversible behaviours of the information system dynamics. The information flux explicitly breaks the detailed balance and is a direct measure of the degree of the nonequilibriumness or time irreversibility. We further demonstrate that the mutual information rate between the two subsystems can be decomposed into the equilibrium time-reversible and nonequilibrium time-irreversible parts respectively. This decomposition of the mutual information rate (MIR) corresponds to the information landscape-flux decomposition explicitly when the two subsystems behave as Markov chains. Finally, we uncover the intimate relationship between the nonequilibrium thermodynamics in terms of the entropy production rates and the time-irreversible part of the mutual information rate. We found that this relationship and MIR decomposition still hold for the more general stationary and ergodic cases. We demonstrate the above features with two examples of the bivariate Markov chains.

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

In this paper, mineralogical and elemental geochemical characteristics of massive sulfide samples collected from Jade hydrothermal field, located in the Izena depression in the central graben of Okinawa Trough, were analyzed by means of optical microscopy, scanning electron microscopy and electron probe. The results show that the sulfide in Jade hydrothermal area can be divided into Zn-Cu-Pb rich massive sulfide and Zn-Fe rich massive sulfide. The former is composed of sphalerite, galena, anglesite, chalcopyrite and pyrite, and its formation stage can be divided into pyrite stage, sphalerite-chalcopyrite stage, anglesite stage and colloidal pyrite stage. The latter is mainly composed of sphalerite, pyrite, marcasite and a small amount of galena, which can be divided into galena stage, pyrite stage, sphalerite stage, pyrite and marcasite stage. Cu and Zn in pyrite may exist in the form of microinclusions, while Ag and Pb may exist in pyrite in the form of fine galena inclusions containing Ag. Fe and Cu may enter sphalerite in the form of ion replacement. Zn may enter chalcopyrite in the form of ion replacement, and As and Pb may be inclusions in chalcopyrite as As-bearing galena inclusions. Consistent with the previous understanding, the metal elements in the hydrothermal liquid system in Jade hydrothermal field mostly migrate with the hydrothermal fluid as sulfur complexes, and when the hydrothermal fluid mixes with seawater, the physical and chemical conditions of the fluid change, resulting in sulfide mineral precipitation. However, the chemical structure of chalcopyrite is still controversial, which restricts the understanding of the substitution mechanism of trace elements during chalcopyrite precipitation.

High-quality rice (Oryza sativa L.) is increasingly widely planted in China with the improvement of people's living standards and the achievement of rice breeding efforts in recent years. However, the agronomic and physiological performances of high-quality indica rice (HQIR) under different nitrogen(N) application conditions in southern China are little known. Two-year consecutive field experiments were conducted with two HQIR and two ordinary-quality indica rice (OQIR) varieties under moderate and high N application rates, with yield and yield components, biomass, N up-take, and their related traits investigated. We found that grain yields of HQIR were slightly de-creased, but grain yields of OQIR were significantly increased by 6.60%-8.88% under high N rate compared with moderate N rate in both years. Thereby, OQIR produced 8.34%-11.87% and 22.00%-22.50% higher grain yield than HQIR under moderate and high N rates, respectively. The different responses of grain yield to N application rates were mainly due to decreased grain set-ting rate in HQIR and increased spikelets m-2 in OQIR under high N rate. Furthermore, high N rate significantly reduced pre-anthesis AE and improved grain-leaf area ratio, while did not in-crease post-anthesis DM compared with moderate N rate in HQIR, which might result in carbon metabolic deterioration and imbalance of source-sink relationship and subsequently lower supply of carbohydrate to panicle. Our results suggest that a moderate N rate (165 kg N ha-1) is beneficial for HQIR varieties to balance the maximum grain yield and high quality in southern China

. In this paper, we introduce a series of definitions of generalized affine functions for vector-valued functions. We prove that our generalized affine functions have some similar properties with generalized convex functions. We present examples to show that our generalized affinenesses are different from one another, and also provide an example to show that our definition of presubaffinelikeness is non-trivial; presubaffinelikeness is the weakest generalized affineness introduced in this article. We work with optimization problems that are defined and taking values in linear topological spaces. We devote to the study of constraint qualifications, and derive some optimality conditions as well as a strong duality theorem. Our optimization problems have inequality constraints, equality constrains and abstract constraints; our inequality constraints are generalized convex functions and equality constraints are generalized affine functions.

In this paper, we prove that the sub convexlikeness introduced by V. Jeyakumar [1], and the subconvexlikeness defined in V. Jeyakumar [2] are equivalent in loccallly convex topological spaces. And then, we work with set-valued vector optimization problems and obtain some vector saddle-point theorems and vector Lagrangian theorems.

General wisdom thinks that the central of blackholes are singular and featured by mass, charge and spin exclusively; the microstate reflected in the Bekenstein-Hawking entropy can be accounted for only in some quantum gravity. We challenge this wisdom with two exact solution families to the sourceful Einstein equation which describe dust ball with oscillatory inner structure and variety of mass profiles. We attribute the matter content's oscillation across the central point of the system to the forward scattering domination in high energy collisions induced by inter-gravitating acceleration and provide their Penrose-Carter diagram representation and quantum description briefly. Our solution family provides a very simple semi-classic picture for the micorstate definition of black holes.

Genetic engineering technology offers opportunities to improve many important agronomic traits in crops, including insect-resistance. However, genetically modified (GM) exogenous proteins in edible tissues of transgenic crops has become an issue of intense public concern. To advance the application of GM techniques in maize, a Cre/loxP-based strategy was developed for manipulating the transgenes in green tissues while locking it in non-green tissues. In the strategy, the site-specific excision can be used to switch on or off the expression of transgenes at specific tissues. In this work, two basic transgenic maize named KEY carrying the Cre gene and LOCK containing the Vip3A gene with a blocked element, were obtained based on their separate fusion gene cassettes. The expression level and concentration of Vip3A were observed with high specific accumulation in green tissues (leaf and stem), and only a small amount in root and kernel tissues in the KEY × LOCK hybrids. The insect-resistance of transgenic maize against two common lepidopteran pests, Ostrinia furnacalis and Spodoptera frugiperda, was assessed in the laboratory and field. The results indicated that the hybrids possessed high resistance levels against the two pests, with mortality rates above 73.6% and damage scales below 2.4 compared with the control group. Our results suggested that the Cre/loxP-mediated genetic engineering approach has a competitive advantage in GM maize. Overall, findings from this study are significant for providing a feasible strategy for transgenes avoiding expression in edible parts and exploring novel techniques toward the biosafety of GM plants.

High temperature titanium alloys are widely used in aerospace hot parts, however, the thermal barrier temperature of 600 oC limits its service temperature. In this paper, a two-step hot-dip plating method is proposed to prepare the composite coating containing Ce on the surface of titanium alloy, which can make the oxidation resistance temperature of titanium alloy reach 800 oC The microstructure, phase composition and element distribution of Ce-containing Ti-Al-Si hot-dip coating, Ce-containing Ti-Al-Si pre-oxidation coating and Ce-containing Ti-Al-Si high-temperature oxidation coating were studied by X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS), respectively. The results show that the Ti-Al-Si hot-dip coating containing Ce is mainly composed of (Ti,Ce)(Al,Si)3 alloy phase layer, and the Ti-Al-Si pre-oxidation coating containing Ce is mainly composed of Ti-Al binary system phase layer and dense Al2O3 layer rich in CeO2. Ce in the high temperature oxidation coating of Ti-Al-Si containing Ce is mainly distributed in Ti3Al, TiAl, TiAl3+Ti5Si3 mixed phase layer and Al2O3. The addition of Ce can promote the formation of continuous Al2O3 layer, improve the uniformity of composite coating, prevent the spread of cracks, and improve the high temperature oxidation resistance of Ti-Al-Si coating.

Artificial Intelligence (AI) is a breakthrough technology that has been widely applied in many fields and its use in pharmacy is also gaining increasing attentions. Recently, ChatGPT, a newly developed virtual assistant and large language model, is showing strong ability in writing, which makes it a potential tool for review writing. Here in our study, we employ the public available ChatGPT and try to instruct it to generate a mini review on the topic of “lipid-based drug delivery systems” by conversation. Our results showed that ChatGPT can give reasonable outline for this topic and give seemingly sentences with concluding wording, which can give useful information to the readers. However, the accuracy and consistence of the review are not fully guaranteed and there is lack of reliable citations. Therefore, it is concluded that ChatGPT can only give general knowledge on the selected topic, but not capable of giving in-depth discussion. The generated review article can be a useful but occasionally unprecise electronic encyclopedia instead of rigorous scientific literature, which can give benefit for pharmaceutical education and interchange to some extent.

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.

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.

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.

The average working person can spend between 35-60 hours a week in the workplace, making it an influential place for mental well-being while also being a place for socio-economic contribution. Workplace incivility can diminish positive mental health outcomes and negatively impact work engagement through increased social anxiety. To investigate this, 118 working adults aged between 19 to 67 years old in Singapore were recruited for a survey comprising of demographics questions, the Workplace Incivility Scale, Brief DSM-5 Social Anxiety Disorder Severity Scale, Utrecht Work Engagement Scale-9 over the period of November 2022 to April 2023. Correlational, regression and mediation analysis showed workplace incivility scale scores to significantly pre-dict social anxiety after controlling for covariates, supporting our hypothesis that employees exposed to work-place incivility would have higher levels of social anxiety that mediated work engagement after controlling for age and gender. The findings here show workplace incivility to be a possible intervention target for social anx-iety to reduce negative impacts on work engagement in order to improve employee experience and retention for organizations.

A fluorescent probe, N'-((3-methyl-5-oxo-1-phenyl-4, 5-dihydro-1H-pyrazol-4-yl) methylene)-2-oxo-2H-chromene-3-carbohydrazide (MPMC), was synthesized and characterized. Characterizations of the synthetic MPMC were conducted by proton nuclear magnetic resonance (1HNMR) spectroscopy and carbon-13 nuclear magnetic resonance spectroscopy (13C NMR). The fluorescence emission behaviors of probe MPMC towards diverse metal ions were detected and the probe exhibited high sensitivity and selectivity towards Cu2+ over other metal ions via quenching of its fluorescence. Furthermore, the existence of other metal actions made no difference on the fluorescence intensity of the MPMC-Cu2+ system apparently, that is, MPMC displayed a good anti-interference ability. Job’s plot of MPMC and copper ions indicated the detection limit was 15.16 nM (R2=0.9612) for the assayed actions, with a stoichiometric ratio of 1:1 for MPMC and Cu2+. Additionally, the color of MPMC probe solution changed from nearly colorless to yellow in the presence of Cu2+ in visible light, which the color change could be observed by the naked eye. Similarly, the color resolved bright yellow into blue in ultraviolet light. Also reusability studies indicated that MPMC probe was reusable. The pH effect of probe MPMC to Cu2+ had a broad range of pH detection 4.0 to 11.0. The response time of MPMC probe for determining Cu2+ was within 1 min. The recognition of Cu2+ by MPMC performed on pre-treated paper under sunlight and UV light both had a distinct colour change. Thus, the solid-state method for detecting Cu2+ with the naked-eye, was both economical and convenient.

Although the positive relationship between religion and environmental behavior is well-argued, empirical research about the relationship between religion and public pro-environmental behavior is relatively lacking. This paper aims to explore the group differences in the influence of religion on public pro-environmental behavior and the mediating role of environmental risk perception in religion and public pro-environmental behavior. Using the Chinese General Social Survey data in 2013 for empirical analysis, this study’s results show that there are group differences in the impact of religion on public pro-environmental behavior. Women with religious beliefs are more willing to engage in public pro-environmental behavior than those without religious beliefs. Religious believers over the age of 45 are more willing to participate in public pro-environmental behavior than those without religious beliefs. Political participants with religious beliefs are more willing to practice public pro-environmental behavior than those without religious beliefs. In addition, we found that environmental risk perception can act as partial mediation in religious and public pro-environmental behavior. In other words, religious beliefs are deeply embedded in local political and social culture. In order to correctly understand the relationship between religion and public pro-environmental behavior, it is necessary to consider religion in a specific cultural background.

These years have witnessed growing research on applying rheology in grinding and flotation treatment of finely disseminated ores. The slurry rheology has long been identified as the comprehensive effect of inter-particle interactions, including their aggregation (coagulation and flocculation) and dispersion states in slurry, which are more impactive under the fine-particle effect. In this regard, rheology has the potential to play a significant role in interpreting the flowing and deforming phenomenon of inter-particle aggregates, particle-bubble aggregates, and flotation froth. Though much attention has been paid to the rheological effect in industrial suspension, this has not been the case for mineral grinding and flotation for fine particles. The influential mechanism of rheology on the sub-processes of mineral processing has not been systemically concluded and revealed thoroughly, without which the underpinning mechanism for enhancing the processing efficiency has been difficult to discover. This paper reviews the current application and importance of rheology in the fine mineral processing, and the potential research direction in the field is proposed.

The model internal year-to-year variability (hereafter, internal variability) is a significant source of uncertainty when estimating anthropogenic aerosol effective radiative forcing (ERF). In this study, we investigate the impact of internal variability using large ensemble simulations (600 years in total) with the same climate model under prescribed anthropogenic aerosol forcings. A comparison of the magnitudes (i.e., standard deviation, Std) of these influences confirms that internal variability has negligible impacts on the instantaneous radiative forcing (RF) diagnosed by double radiation calls but has considerable impacts on estimating ERF through rapid adjustments (ADJ). Approximately half of the model grids exhibit strong internal variability influence on ERF (Std > 5 W m−2). These strong internal variabilities lead to a 50% probability that 30-year linear change can reach 2 W m−2, and 10-year linear change can reach 4 W m−2. A 50-year simulation can provide a relatively stable annual mean map of ERF (ERF = ADJ + RF), but it fails for ADJ. The statistically significant areas in the annual mean maps of both ERF and ADJ from a 10-year simulation exhibit instability with evident chaotic features. These analyses contribute to the setup of comparative experiments and a more comprehensive understanding of the modeled anthropogenic aerosol ERF.

The Marchenko method is a data-driven way which makes it possible to calculate Green's functions from virtual points in the subsurface by the reflection data at the surface, only requiring a macro velocity model. This method requires collocated sources and receivers. However, in practice, subsampling of sources or receivers will cause gaps and distortions in the obtained focusing functions and Green's functions. To solve this problem, this paper proposes to integrate sparse inversion into the iterative Marchenko scheme. Specifically, we add sparsity constraints to the Marchenko equations and apply sparse inversion during the iterative process. Our work not only reduces the strict requirements on acquisition geometries, but also avoids the complexity and instability of direct inversion for Marchenko equations. This new method is applied to a two-dimensional numerical example with irregular sampled data. The result shows that it can effectively fill gaps of the obtained focusing functions and Green's functions in the Marchenko method.

Chicken infectious anemia (CIA) poses a significant threat to the chicken industry in China. De-spite its non-specific symptoms, the disease is often overlooked. This study aimed to conduct a comprehensive analysis of the etiology and pathology of CIA in Guangxi Province, China. Three strains of the chicken infectious anemia virus (CIAV) were isolated from liver samples of diseased 20-week-old chickens. The complete genomes of these strains were sequenced, and experiments on specific pathogen-free (SPF) chicks revealed that the GX21121 strain exhibited high virulence. Histopathological examination of the deceased chicks showed liver cell necrosis, fibrous-serous exudation, inflammatory cell infiltration, hemorrhage in liver tissues, as well as congestion in lung and renal tissues. Phylogenetic analysis of the genome revealed that the three strains had a close genetic relationship to the Heilongjiang wild-type (GenBank KY486144). The genetic evolu-tion of their VP1 genes indicated that all three CIAV isolates belonged to genotype IIIc. In sum-mary, this study demonstrated the genomic diversity of three CIAV strains in adult layer hens. The isolation and characterization of the GX21121 strain as a highly virulent isolate provide val-uable information for further investigations into the etiology, molecular epidemiology, and viral evolution of CIAV.

The majority of existing numerical simulations of the effect of bridge piers on water movement are based on a limited number of bridge piers at a laboratory scale. Furthermore, some 2D numerical simulations for actual bridge projects have deficiencies, including the use of overly large mesh sizes and an inadequate treatment of bridge piers. In this study, we compare three methods of structural mesh encryption, suspension mesh, and nonstructural mesh based on Delft3D, and apply the optimization scheme to a real bridge project. It is demonstrated that optimal results can be achieved by utilising a grid size comparable to the pier diameter (Dp) in the region away from the piers. In the vicinity of the piers, the grid cell size should be no larger than 1/9 Dp. The suspended grid technique (DD Boundary) can yield results consistent with those obtained using a full-area high-resolution grid, provided that the total number of grids can be reduced and the computational time is considerably reduced. In this study, the unstructured mesh (Deflt3D Flexible Mesh) scheme was unable to capture the oscillations of the wake flow behind the bridge piers. However, the application of the optimized scheme in bridge engineering has demonstrated its practical value. The findings of this study on mesh resolution and suspension mesh scheme can be applied to the Delft3D software and are also useful for other numerical simulation work.

At present, in the field of aviation industry, titanium alloy is mainly used to manufacture parts such as compressor disc, blade and casing of aircraft engine. When working, titanium alloy parts produce high temperature due to high-speed running friction, which makes the high temperature oxidation resistance and friction resistance of titanium alloy greatly reduced. When their working environment contains salt, titanium alloys are subjected to thermal corrosion, which limits their wider practical applications. This paper introduce the aluminide coating and its preparation methods. The characteristics and functional mechanism of three functional coatings for service environment, such as high temperature resistant alumina-based coating, thermal corrosion resistant alumina-based coating and wear-resistant alumina-based coating are summarized. Finally, the development direction of composite coatings of titanium and titanium alloys for complex service environment is prospected.

We found an important fact that the beam footprint line of Ping will intersect with the real water depth when the initial incidence angle is about 45°, and sound velocity error hardly has an effect on it. This is contrary to our previous experience that the soundings of the central beam of multi-beam bathymetric system (MBS) is the most accurate. Firstly, the influence of sound velocity errors on central beam and seafloor topography distortion was analyzed. Secondly, the process of proving this fact was given, and the topography correction method was proposed by compensating the sound velocity profile area (SVP area). Finally, we showed in the first simulation of four type errors in SVPs that this fact is verified. The topography correction method used in the second simulation to correct the topography distortion of the first simulation is also verified.

Gibberella ear rot (GER) caused by Fusarium graminearum (teleomorph Gibberella zeae) is one of the most destructive diseases in maize that severely reduces grain yield and contaminates several potential mycotoxins. However, few efforts had been devoted to dissect the genetic basis of maize GER resistance. In the present study, a genome-wide association study (GWAS) was conducted in a maize association panel consisting of 303 diverse inbred lines. The phenotypes of GER severity were evaluated using kernel bioassay across multiple time points in the laboratory. Then, three models including fixed and random model circulating probability unification model (FarmCPU), general linear model (GLM) and mixed linear model (MLM), were conducted simultaneously in GWAS to identify single-nucleotide polymorphisms (SNPs) significantly associated with GER resistance. A total of four individual significant association SNPs with the phenotypic variation explained (PVE) ranging from 3.51 to 6.42% were obtained. Interestingly, the peak SNP (PUT-163a-71443302-3341) with the greatest PVE value, was co-localized in all models. Subsequently, 12 putative genes were captured from the peak SNP that several of these genes were directly or indirectly involved in disease resistance. Overall, these findings contribute to understand the complex plant-pathogen interactions in maize GER resistance. The regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the kernel bioassay that can be used for evaluating and selecting elite germplasm resources with GER resistance in maize.

Hydrological connectivity plays a major role in solving water resource and eco-environmental problems. However, this phenomenon has not been afforded the attention it deserves. Detailed analysis of connectivity in river systems could provide considerable insight into structural and functional attributes of riverine landscapes. The current study used graph theory approach and associated connectivity indicators to explore the characteristics and evolution of river systems and hydrological connectivity in a large catchment (Poyang Lake, China). The results revealed that the structure of the river system tended to be complex during 1990-2020, characterized by a dynamic evolution of tributaries in certain northern areas. Both river density and complexity exhibited an increasing trend by up to 15%, with the change rate after 2000 approximately twice as high as that of the preceding period. Overall, human activities across the catchment are more likely to play a key role in leading to significant changes in the quantity, morphometric, and structure characteristics of the river system. Additionally, the functional connectivity analysis indicated that the index of connectivity (IC) in the downstream catchment is stronger than that of the upstream vegetation areas, suggesting a strong contribution to the runoff-sediment transport (r=0.6-0.7). This study highlights the spatial and temporal evolution of both the structural and functional connectivity in the large Poyang Lake catchment. The findings of this work will bene-fit future water resource management and applications by providing a strategy for protecting the surface hydrology and mass transport of large river basins under climate and land-use changes.

This study examined the tourism spatial distribution of nine cities in the Fujian province and assessed the impacts of COVID-19. The modified gravity model found that it was widely dispersed, with uneven and relatively independent tourism development in different cities. The social network analysis showed that tourism connections across cities were significantly reduced after the pandemic. The impacts of brand awareness and transport accessibility on spatial networks were positive in pre-pandemic but became negative during the pandemic. In contrast, tourist volume had negative impacts on spatial networks in pre-pandemic but had positive ones during the pandemic. Tourism resources and market performance had significantly positive impacts in the post-pandemic era. These findings provide advice on tourism recovery and destination management in coping with future critical events. It also contributes to the theoretical gravity framework in tourism and the research scope of the social networks analysis at the city level.

Due to the lack of theoretical research on the amount of spatio-temporal information in the high-speed photography technologies, obtaining an optimized system with a best amount of spatio-temporal information remains a challenge, resulting in insufficient effective information and observation accuracy for ultrafast events. The paper presents an ultrafast raster imaging (URI) system with a large amount of spatio-temporal information based on the all-optical raster principle in single-shot. Specifically, we derive the optimal equation of spatial resolution and the expression for the maximum amount of spatio-temporal information that can achieve excellent performance for an URI system. It serves as a general guideline for getting a large amount of information design in the URI system. Compared to the existing URI systems, the advanced URI system exhibits an improvement of nearly 1 order of magnitude in the amount of spatio-temporal information, and more than twofold in spatial resolution. It shows a great potential for capturing intricate and non-repetitive ultrafast events on the femtosecond time scale.

Drug-target affinity (DTA) prediction is crucial for understanding molecular interactions and aiding drug discovery and development. While various computational methods have been proposed for DTA prediction, their predictive accuracy remains limited, failing to delve into the structural nuances of interactions. With increasingly accurate and accessible structure prediction of targets, we developed a novel deep learning model, named S2DTA, to accurately predict DTA by fusing sequence and structural knowledge of drugs, targets, and pockets using heterogeneous models based on graph and semantic networks. Experimental findings underscored that complex feature representations imparted negligible enhancements to the model’s performance. However, the integration of heterogeneous models demonstrably bolstered predictive accuracy. In comparison to three state-of-the-art methodologies, the supremacy of S2DTA became strikingly apparent. It showcased a noteworthy 25.2% reduction in Mean Absolute Error (MAE) and an impressive 20.1% decrease in Root Mean Square Error (RMSE). Furthermore, S2DTA exhibited substantial advancements in other pivotal metrics, including Pearson Correlation Coefficient (PCC), Spearman, Concordance Index (CI), and R2. These metrics experienced remarkable increments of at least 19.6%, 17.5%, 8.1%, and a remarkable 49.4%, respectively. Finally, we conducted interpretability analysis on the effectiveness of S2DTA by bidirectional self-attention mechanism, fully proving that S2DTA is a valuable and accurate tool for predicting DTA. For further exploration, the source data and code repository can be accessed at https://github.com/dldxzx/S2DTA.

As a widely used plastic, the aging and degradation of polyethylene (PE) are inevitable problems, whether the goal is to prolong the life of PE products or address the issue of white pollution. Molecular simulation is a vital scientific tool in elucidating the mechanisms and processes of chemical reactions. To obtain the distribution and evolution process of PE's thermal oxidation products, this work employs the self-consistent charge density functional tight binding (SCC-DFTB) method to perform molecular simulations of the thermal oxidation of PE with different crystallinity and branched structures. We discovered that crystallinity does not affect the thermal oxidation mechanism of PE, but higher crystallinity makes PE more susceptible to cross-linking and carbon chain growth, reducing the degree of PE carbon chain breakage. The branched structure of PE results in differences in pore size between the carbon chains, with larger pores leading to a concentrated distribution of O2 and free radicals subsequently formed. The breakdown of PE is slowed down when free radicals are localized in low-density regions of the carbon chain. The specifics and mechanism of PE's thermal oxidation are clearly revealed in this paper, which is essential for understanding the process in-depth and for the development of anti-aging PE products.

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.

Privacy and information insurance have consistently been a priority for the European Union lawmaker. This paper presents whether the NIS prevails in its underlying endeavors to remain the congruity among residents and companies. It distinguishes current difficulties that specific business structures may experience while conforming to the Regulation. The exploration traces certain reasons which could impede the opportune reception of the new lawful ideas inside the system of the organizations. The exploration incorporates what is unique about the NIS; how it overlaps with existing frameworks; and how security requirements in the GDPR influence the NIS Directive. This paper furnishes different point of views of experts with the aim of setting up an entire examination

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.

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

As the number of end-of-life vehicles continues to grow, the field of separation technology for broken copper and aluminium parts of end-of-life vehicles has emerged as a significant area of research. As a key technology for the separation of non-magnetic non-ferrous metals, such as copper and aluminium, eddy current separation can achieve efficient separation of non-magnetic non-ferrous metals according to their differing conductivity and density. Nevertheless, further research is required in the separation of large-scale broken copper and aluminium parts of end-of-life vehicles. This paper presents a novel magnetic roller model comprising circumferential and axial periodic arrangements of permanent magnets. A single permanent magnet was constructed as an equivalent current model, and the magnetic scalar potential equations were solved using simulation tools. This allowed the distribution of the magnetic field outside the magnetic roller to be studied. The results demonstrate that the novel permanent magnet array magnetic roller can enhance the magnetic field intensity and action distance of the external magnetic field, which is more conducive to the separation of large-scale broken copper and aluminium parts of scrap cars. The findings of this research provide a theoretical foundation for the separation of scrap car broken copper and aluminium parts.

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.

To obtain a cost-effective and high-performance composite material of polybutylene adipate-terephthalate (PBAT), for this study we selected microcrystalline cellulose, which is inexpensive and easily available, as the reinforcing medium. Hexadecyl trimethoxysilane (HDTMS) containing a long carbon chain was chosen to silanize the microcrystalline cellulose (MCC) to obtain silanized cellulose (SG). Three types of SGs with different degrees of silanization were obtained by controlling the reaction ratio. Characterization of these three types of SGs was conducted using FTIR, TEM, and water absorption analysis. Subsequently, PBAT/SG composites were prepared through a sol-gel method, and the effects of these three types of SGs on the thermal stability, compatibility, mechanical properties, and dynamic thermomechanical properties of PBAT were evaluated. Furthermore, the mechanism behind enhancing the mechanical properties of the composite was analyzed. The results demonstrated successful synthesis of SG. As the reaction ratio between HDTMS and MCC increased, the nanoparticle size increased, while the water absorption decreased significantly. After SG was added to the PBAT composites, the yield stress increased while maintaining good thermal stability. Both the SEM and DMA results indicated good compatibility of the PBAT/SG composites. Analysis of the mechanical properties revealed that the tensile strength initially increased and then decreased with increasing blending ratio for all three composites tested; among them, the PBAT/SG2 composites exhibit superior performance, with a maximum tensile strength reaching 22 MPa at an 85/15 blending ratio—nearly 30% higher than that of pure PBAT alone. The addition of SG significantly improved the strength of the PBAT, and we speculated as to the underlying mechanism involved. This study provides a new idea for the industrial-scale development of degradable polyesters with low cost and good mechanical properties.

Mineral identification is an important part of geological analysis. Traditional identification methods rely on either the experiences of the appraisers or the various measuring instruments and the methods are either easily influenced by the experiences or need too much work. To solve the above problems, there have been studies using image recognition and intelligent algorithms to identify minerals. But the current studies can not identify many minerals, and the accuracy is low. To increase the number of identified mineral categories and the accuracy, we proposed the method that uses both the mineral images and the Mohs hardness in the deep neural networks to identify the minerals. The experimental results showed that the method can reach 94.0% Top-1 accuracy and 99.9% Top-5 accuracy for 28 common minerals. The model that combines image and Mohs hardness together can identify more minerals and increase the accuracy using less training data.

In this work, an novel flow-electric field coupling configuration for enhanced Zn-Cd cementation was designed and utilized. A series of tests were conducted to explore the optimization of Zn-Cd cementation process and its mechanism.Firstly, the various characterisations of the cadmium sponge at different locations in the device were compared and it was concluded that the purity of the cadmium sponge was optimal from the anode surface. The generation and stripping of cadmium sponge was revealed for the first time by cross-sectional electron microscopy. The four stages of the apparent reaction in the system were analysed in relation to the pH, cadmium concentration and cadmium sponge flaking at each flow rate. It was proved that the separation of cadmium sponge mainly occurred in the third phase. Secondly, by comparing the morphology and specific surface area of cadmium sheep at different flow rates, the optimum flow field velocity was identified as 30 ml/s. Six flow field configurations were compared and preferred. The results demonstrate that the LCAH modulation results in a more sparse structure of the cadmium sponge, which is more easily exfoliated from the zinc anode surface by fluid impact. This was considered to be the most beneficial flow field configuration for improving the cadmium cementation rate and reducing the cost of the reaction. Further, the reaction steps of the system were analysed. The diffusion process under different flow field configurations was confirmed by calculations to follow first order kinetics. The diffusion coefficient of LACH proved to be the highest in the comparative tests and this result was also supported by the apparent experimental results.

Following the occurrence of a typhoon, quick damage assessment related to residents can facilitate quick dispatch of house repair and disaster insurance works. Employing a deep learning method, this study used aerial photos of the Chiba prefecture obtained following the Typhoon Faxai in 2019 to automatically detect and evaluate the roof damage. This study comprised three parts: training deep learning model, detecting the roof damage using trained model, and classifying the level of roof damage. The detection object comprised roof outline, blue tarps, and roof completely destroyed. The roofs were divided into three categories: roof without damage, roof with blue tarps and roof completely destroyed. the F value obtained using the proposed method was higher than those obtained using other methods. In addition, it can be further divided into 5 levels from level 0 to 4. Finally, the spatial distribution of the roof damage was analyzed using ArcGIS tools. The proposed method is expected to provide certain reference for the real-time detection of the roof damage after the occurrence of a typhoon.

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.

This research focussed on utilisation of salmon protein and lipid to manipulate pasta glycaemic index and protein digestibility. Salmon fish (Oncorhynchus tschawytscha) powder (SFP) supplemented pasta flour at the from 5% to 20% (w/w). Inclusion of SFP lead to a significant reduction in starch digestibility and hence the potential glycaemic values of pasta (experimental pasta being up to 143% lower than control values). SFP addition to pasta increased the release of phenolic compounds from pasta during both a gastric digestion (179%) and pancreatic digestion ( 133%) in comparison to the control sample. At the same time, the antioxidant activity of the digested pasta was increased by up to 263% (gastric) and 190% (pancreatic) in comparison to durum wheat pasta alone. Interestingly, although protein levels increased with incorporation of SFP, the digestibility values of the protein decreased from 86.41% for the control pasta to 81.95% for 20% SFP pasta. This may indicate that there are interactions between phenolic and protein in the pasta samples which affect overall protein digestibility levels.

The analysis of high-temperature physicochemical properties of theK₃AlF₆-Na₃AlF₆-AlF₃ molten salt system is crucial for practical production of electrolytic aluminum. In this paper, the physicochemical properties of the K₃AlF₆-Na₃AlF₆-AlF₃ molten salt electrolyte system at 1173 K and standard atmospheric pressure were simulated using molecular dynamics calculations. The effects of Zr、B、C、W、Ti、Hf、Nb、and Ta on the radial distribution function, coordination number, viscosity and conductivity of the electrolyte system are discussed in detail. The simulation results show that the coordination number between Al-F and the conductivity is decreasing as the content of B²- increases. And the coordination number between Al-F and the viscosity is decreasing as the content of Zr⁴⁺ increases. With the addition of impurity elements such as C, W, Ti, Hf, Nb, and Ta, the data show that C has no significant effect on this electrolyte system, while the presence of W will decrease the coordination number between Al-F in the system. The presence of Ti, Hf, Nb, and Ta may intensify the decomposition reaction between one of the Al-F ligands, which increases the coordination number between Al-F and the number of ions in the electrolyte. This work provides theoretical support for the subsequent study of inert anodes containing Zr, B, Ti, Hf, Nb, and Ta.

Wearable touch sensors, which can convert force or pressure signals into quantitative electronic signals, have emerged as an essential smart sensing devices and played an important role in various cutting-edge fields, including wearable health monitoring, soft robots, electronic skin, artificial prosthetics, AR/VR, and the Internet of Things. Flexible touch sensors have made significant advancements, while construction of novel touch sensors via mimicking the unique properties of biological materials and biogenetic structures always remains a hot research topic and significant technological pathway. This review provides a comprehensive summary of the research status of wearable touch sensors constructed by imitating the material and structural characteristics in nature, and also summarizes the scientific challenges and development tendency of this aspect. Firstly, the research status for constructing flexible touch sensors based on biomimetic materials is summarized, including hydrogel materials, self-healing materials, and other bioinspired or biomimetic materials with extraordinary properties. Then, design and fabrication of flexible touch sensors based on bionic structures for performance enhancement are fully discussed. These bionic structures include special structures in plants, special structures insects/animal, and special structures in human body. Moreover, a summary of the current issues and future prospects for developing wearable sensors based on bioinspired materials and structures is discussed.

Here, we present a series of novel block copolymers (BCP) from bio-derived monomers, poly(lactic acid)-block-poly(2,5-furandimethylene succinate) (PLA-b-PFS), in which the furan groups from PFS block can be crosslinked with bis(maleimido) triethylene glycol (M2) through a Diels-Alder reaction. This dynamic crosslinking reaction leads to a network structure for enhancing the mechanical properties compared to their linear BCP analogous. Decreasing the crosslinking density leads to a decrease of glass transition temperature of BCPs and a transition from glassy to rubbery-like behavior at room temperature. This allows a wide tunablity of both elastic moduli and yields of the materials. For the lowest crosslinking density. the material exhibits an over 50% self-healing efficiency at room temperature after five days, attributed to the low Tg (15.2 C) from the introduction of PFS block, allowing sufficient chain mobility for structure re-organization. Moreover, with the appropriate selection of crosslinking density (PLA-b-PFS/M2 (6/1)), it also shows an excellent shape memory property with a high recovery rate of 96.3% and a fixity rate of 97.3%. The permanent shape can be rewriteable due to the reversibility of Diels-Alder reaction. With these advanced functionalities and ease in large-scale fabrication, the PLA-b-PFS/M2 shows great promises for self-healing coatings or films with shape memory properties in a wide variety of applications such as packaging materials

Aiming to investigate the impact of strategic knowledge disclosure on the continuous realization of digital innovation in enterprises, this study examines data from 168 listed companies across three high-tech industries in China from 2012 to 2021. By examining investor trust, consumer trust, worker trust, and rival trust as mediating variables within the market trust dimension, this research explores the impact mechanism of strategic knowledge disclosure on the sustainability of input and output in digital innovation. The findings reveal that strategic knowledge disclosure significantly promotes both input and output sustainability in digital innovation. Specifically, investor trust positively mediates the relationship between strategic knowledge disclosure and the sustainability of digital innovation input. Similarly, consumer trust and worker trust positively mediate the association between strategic knowledge disclosure and both input and output sustainability in digital innovation. However, it is important to note that rival trust negatively mediates the link between strategic knowledge disclosure and both input and output sustainability in digital innovation. The research findings possess significant theoretical value and provide valuable guidance for promoting the sustainable development of digital innovation in enterprises.

As one of the common techniques for measuring coseismic deformations, optical image correlation techniques are capable of overcoming the drawbacks of inadequate coherence and phase blurring which can occur in radar interferometry, as well as the problem of low spatial resolution in radar pixel offset tracking. However, the scales of the correlation window in optical image correlation techniques typically influence the results, the conventional SAR POT method faces a fundamental trade-off between the accuracy of matching and the preservation of details in the matching window size. This study regards co-seismic deformation as a two-dimensional vector, and develops a new post-processing workflow called VACI-OIC to reduce the dependence of shift estimation on the size of the matching window. This paper takes the coseismic deformations in both the east-west and north-south directions into account at the same time, treating them as vectors, while also considering the similarity of displacement between adjacent points on the surface. Herein, the angular continuity index of the coseismic deformation vector was proposed as a more reasonable constraint condition to fuse the deformation field results obtained by optical image correlation across different matching window. Taking the earthquake of 2021 in Maduo, China, as the study area, the deformation with the highest spatial resolution in the violent surface rupture area was determined (which could not be provided by SAR data). Compared to the results of single-scale optical correlation, the presented results were more uniform (i.e., more consistent with published results). At the same time, the proposed index also detected the strip fracture zone of the earthquake with impressive clarity.

Epilepsy is characterized by repeated spontaneous reactions caused by hyper-excitability and neurons firing in high synchronization in the central nervous system. It seriously affects the quality of life of epileptic patients and nearly 30% of individuals are refractory to treatment of antiepileptic drugs. Therefore, there is an urgent need to develop new medicines to manage and control the refractory epilepsy. Cannabinoid ligands including selective cannabinoid receptor subtype (CB1 or CB2 receptor) ligands and non-selective cannabinoid (synthetic and endogenous) ligands may serve as the novel candidates for this need. Cannabinoid systems appear to regulating seizure activity in the brain through the activation of CB1 and CB2 cannabinoid receptors (CB1R and CB2R). An abundant series of cannabinoid analogues have been tested in various animal models, including a rat pilocarpine model of acquired epilepsy, in vitro hippocampal neuronal culture models of acquired epilepsy and status epilepticus, a pentylenetetrazole model of myoclonic seizures in mice and a penicillin-induced model of epileptiform activity in the rats. The accumulating lines of evidence show that cannabinoid ligands exhibit significant benefits to control seizure activity in different epileptic models. For this reason, we summarize the relationship between brain CB2 receptors and seizures, and emphasize the potential mechanisms of their therapeutic effects involving affecting neurons, astrocytes, and microglia cells. The unique features of CB2Rs, such as lower expression levels under physiological conditions and high inducibility under epileptic conditions, make it an important target for future research on drug-resistant epilepsy.

Hand and arm gesture recognition using radio frequency (RF) sensing modality proves valuable in man-machine interface and smart environment. In this paper, we use time series analysis method for accurately measuring the similarity of the micro-Doppler (MD) signatures between the training and test data, thus providing improved gesture classification. We characterize the MD signatures by the maximum instantaneous Doppler frequencies depicted in the spectrograms. In particular, we apply the dynamic time warping (DTW) method and compare its performance with that of the long short-term memory (LSTM) network. Both methods take into account the values as well as the temporal evolution and trends of time series data. It is shown that the DTW method achieves high gesture classification rates and is robust to time misalignment.

List-only entity linking is the task of mapping ambiguous mentions in texts to target entities in a group of entity lists. Different from traditional entity linking task, which leverages rich semantic relatedness in knowledge bases to improve linking accuracy, list-only entity linking can merely take advantage of co-occurrences information in entity lists. State-of-the-art work utilizes co-occurrences information to enrich entity descriptions, which are further used to calculate local compatibility between mentions and entities to determine results. Nonetheless, entity coherence is also deemed to play an important part in entity linking, which is yet currently neglected. In this work, in addition to local compatibility, we take into account global coherence among entities. Specifically, we propose to harness co-occurrences in entity lists for mining both explicit and implicit entity relations. The relations are then integrated into an entity graph, on which Personalized PageRank is incorporated to compute entity coherence. The final results are derived by combining local mention-entity similarity and global entity coherence. The experimental studies validate the superiority of our method. Our proposal not only improves the performance of list-only entity linking, but also opens up the bridge between list-only entity linking and conventional entity linking solutions.

Connected and Autonomous Vehicle (CAV) combines technologies of autonomous vehicle (AV) and connected vehicles (CV) to develop quicker, more reliable and safer traffic. Artificial Intelligence (AI) based CAV solutions play significant roles in sustainable city. The convergence imposes stringent security requirements for CAV safety and reliability. In practice, vehicles are developed with increased automation and connectivity. Increased automation increases the reliance on the sensor-based technologies and decreases the reliance on driver; increased connectivity increases the exposures of vehicles vulnerability and increases the risk for an adversary to implement a cyber-attack. Much work has been dedicated to identifying the security vulnerabilities and recommending mitigation techniques associated with different sensors, controllers, and connection mechanisms, respectively. However, there is an absence of comprehensive and in-depth studies to identify how the cyber-attacks exploit the vehicles vulnerabilities to negatively impact the performance and operations of CAV. In this survey, we set out to thoroughly review the security issues introduced by AV and CV technologies, analyze how the cyber-attacks impact the performance of CAV, and summarize the solutions correspondingly. The impact of cyber-attacks on the performance of CAV is elaborated from both viewpoints of intra-vehicle system and inter-vehicle system. We pointed out that securing the perception and operations of CAV would be the top requirement to enable CAV to be applied safely and reliably in practice. Also, we suggested to utilize cloud and new AI methods to defend against smart cyber-attacks on CAV.

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.

The deployment of a manufacturing execution system (MES) holds promising potential in facilitating the accumulation of a substantial amount of inspection data. Low quality levels in discrete manufacturing environments are the result of multi-factor coupling and failure to find quality issues in a timely manner within manufacturing settings may trigger the propagation of defects downstream. Currently, most of the inspection quality methods are direct measurement followed by manual judgment. The integration of deep learning methods provides a feasible way to identify defects in a timely manner, thus improving the acceptance rate of factories. This paper focuses on the design of a data-driven quality prediction and control model around discrete manufacturing characteristics, and use fuzzy theory to evaluate the quality level of production stages. Building Multivariate Long and short-term memory learning hidden quality representations to extract predictions from multi-level inspection data in manufacturing systems. Finally, by validating the data of actual produced water dispensers according to three evaluation indexes, RMSE, MAE, MAPE, the results show that Multivariate Long and short-term memory has better prediction performance.

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.

Based on the analysis of the spatial distribution of uranium grade in 348 boreholes of a uranium deposit in Xinjiang, the enrichment and spatial variation of uranium ore in two stopes of the deposit are discussed by using multifractal theory. The distribution characteristics of uranium ore of the two stopes are studied by multifractal parameters: the scaling exponent of mass , the scaling exponent of each sub-set and its corresponding fractal dimension , the fractal dimension D0 and information dimension D1. The differences of uranium distribution in two stopes can be well quantified by multifractal spectrum and multifractal parameters( , , ).10m×10m is defined as a fence unit, and the window sizes are respectively set, the singularity exponent of the two stopes are calculated by this element concentration-area(C-A) method. The results show that the multifractal theory and model can organically combine spatial structure information, scale change information and anisotropy information to obtain low-grade and weak mineral resources information, and can effectively distinguish complex and superimposed anomalies. This will provide a basis for local concentration and spatial variation rules of uranium distribution and the design of the parameters of leaching uranium mining well site.

Background: Coronavirus Disease 2019 (COVID-19) has been demonstrated to be the cause of pneumonia. Nevertheless, it has not been reported as the cause of acute myocarditis or fulminant myocarditis. Case presentation: A 63-year-old male was admitted with pneumonia and cardiac symptoms. He was genetically confirmed as having COVID-19 according to sputum testing on the day of admission. He also had elevated troponin I (Trop I) level (up to 11.37 g/L) and diffuse myocardial dyskinesia along with a decreased left ventricular ejection fraction (LVEF) on echocardiography. The highest level of interleukin-6 was 272.40 pg/ml. Bedside chest radiographs showed typical ground-glass changes indicative of viral pneumonia. Laboratory test results for viruses that cause myocarditis were all negative. The patient conformed to the diagnostic criteria of the Chinese expert consensus statement for fulminant myocarditis. After receiving antiviral therapy and mechanical life support, Trop I was reduced to 0.10 g/L, and interleukin-6 was reduced to 7.63 pg/ml. Moreover, the LVEF of the patient gradually recovered to 68%. The patient died of aggravation of secondary infection on the 33^rd day of hospitalization. Conclusion: COVID-19 patients may develop severe cardiac complications such as myocarditis and heart failure. This is the first report of COVID-19 complicated with fulminant myocarditis. The mechanism of cardiac pathology caused by COVID-19 needs further study.

Urban vitality is an important reflection of a city's development potential and urban quality. This study uses exploratory spatio-temporal big data such as social media check-ins to portray the spatio-temporal evolution of urban vitality at the subdistrict scale in Changsha, a city in central China, from 2013-2021, and finds that urban vitality in Changsha exhibits central agglomeration and outward circling expansion over time; and then use Geodetector and spatial regression analyses are used to explain the interactive effects and spatio-temporal heterogeneity of the spa-tial elements of subdistrict form, subdistrict function and subdistrict economy on urban vi-tality. The results show the following: (1) The subdistrict form and subdistrict function dimen-sions have a significant effect on urban vitality, and the effect of the economic dimension of the subdistrict is not significant. (2) The interaction effect of the density of entertainment and leisure facilities and the density of business office facilities in subdistrict function is the dominant factor in the change of urban vitality. (3) Under the spatio-temporal effect, land use diversity and park facility density have the strongest positive effect on urban vitality; road density and shopping facility density have the weakest effect. The study aims to provide a reference for the optimization and allocation of spatial elements of subdistricts in sustainable urban development and urban renewal, to achieve the purpose of urban vitality creation and enhancement.

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.

The study's motivation is to gauge the nexus between economic policy uncertainty and financial innovation for the period 2004M1 to 2018M12 in BRIC nations. For establishing a long-run cointegration study applied Autoregressive Distributed Lagged (ARDL) and asymmetry effects of economic policy uncertainty investigated following nonlinear framework known as NARDL. Furthermore, directional causality is established by performing a non-granger causality test. Cointegration test results of Fpss, Wpss, and tBDM confirmed the long-run association between EPU and financial innovation. On the other hand, the Wald test results proved asymmetry effects furring from EPU to financial innovation both in the long-run and short-run. Referring to asymmetry effects that positive and negative shocks in financial innovation, the study revealed that negative linkage between shocks in EPU and financial innovation in the long-run but short-run effects are insignificant. Furthermore, financial innovation measured by R&D investment exhibits positive linked with shocks in EPU, implying that uncertainty induces innovation in the economy. Refers to directional causality estimation, the study revealed evidence supporting the feedback hypothesis between EPU and financial innovation in all sample countries.

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.

In this study, we investigate the magnetization behavior of coaxial nanowires fabricated through the sol-gel electrospinning method. Our analysis uncovers a significant reduction in coercivity for CoFe2O4 nanowires when BaTiO3 is used as the shell material, effectively transforming them from hard to soft magnetic. This intriguing behavior is attributed to the magnetization reversal effect at the interface between ferromagnetic and paramagnetic regions, and it is also observed in NiFe2O4 and Fe2O3 nanowires. Surprisingly, introducing a GdBa2Cu3O7 shell induces a similar effect. Additionally, we employ magnetic impedance measurements on the coaxial nanowires, unveiling their potential for magnetic field sensing applications.

Artificial intelligence provides a new research concept for digital image processing. However, at present, artificial intelligence is rarely introduced into the teaching of digital image processing in colleges and universities, and there are problems such as obsolete teaching content, single teaching methods, and simple course experiments, which affect the teaching effect and are not conducive to the cultivation of comprehensive and innovative talents. Digital image processing technology brings more possibilities to communication engineering and makes communication more convenient. For example, video calls and photo transmission make people's communication methods in daily life more and more diversified. Time and space limitations allow people to meet online, creating more communication possibilities. However, there are still many problems and methods worthy of in-depth exploration. Therefore, this paper has a comprehensive understanding and mastery of the traditional and deep learning methods of digital image processing to improve the relevant project practice and scientific research exploration ability and refer for similar research conclusions.

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.

In the pursuit of China’s dual carbon goals, identifying spatio-temporal changes in industrial carbon emission efficiency and their influencing factors in cities at different stages of development is the key to effective formulation of countermeasures to promote the low-carbon transformation of Chinese national industry and achieve high-quality economic development. In this study, we used balanced panel data of 270 Chinese cities from 2005 to 2020 as a research object: (1) to show spatio-temporal evolution patterns in urban industrial carbon emission efficiency; (2) to analyze the aggregation characteristics of industrial carbon emission efficiency in Chinese cities using Global Moran's I statistics; and (3) to use the hierarchical regression model for panel data to assess the non-linear impact of the digital economy on the industrial carbon emission efficiency of cities. The results show the following: (1) the industrial carbon emission efficiency of Chinese cities exhibited an upward trend from 2005 to 2020, with a spatial distribution pattern of high in the south and low in the north; (2) China's urban industrial carbon emission efficiency is characterized by significant spatial autocorrelation, with increasing and stabilizing correlation, and a relatively fixed pattern of spatial agglomeration; (3) there is a significant inverted-U-shaped relationship between the digital economy and the industrial carbon emission efficiency of cities. The digital economy increases carbon emissions and inhibits industrial carbon-emission efficiency in the early stages of development, but inhibits carbon emissions and promotes industrial carbon emission efficiency in mature developmental stages. Therefore, cities at all levels should reduce pollution and carbon emissions from high-energy-consuming and high-polluting enterprises, gradually reduce carbon-intensive industries, and accelerate the digital transformation and upgrading of enterprises. Western, central and eastern regions especially should seek to promote the sharing of innovation resources, strengthen exchanges and interactions relating to scientific and technological innovation, and jointly explore coordinated development routes for the digital economy.

The heritage of ancient buildings is an important part of the world's history and culture, which has an extremely rich historical-cultural value and artistic research value. Beijing has a large number of palace ancient buildings, and because of the age of their construction, many of them have problems of varying degrees of peeling and mold on the inner surfaces of the envelope. To solve the problems of the damp and moldy interior of palace buildings, a mathematical model of indoor heat and moisture transfer was established based on a wooden palace ancient building in Beijing. Through the indoor mold distribution validation model, the effects of outdoor humidity, soil moisture, wall humidity, and other factors on the indoor heat and moisture transfer of ancient buildings were simulated and analyzed by using the control variables method. The results showed that the molds were distributed at the indoor corners and floors, and the simulation of indoor humidity match the measured humidity. Thus, the simulation results were consistent with the actual situation. The variable trend of the relative humidity of the indoor environment with the outdoor humidity is inconsistent from plane to plane, i.e. it increases or remains constant with the increase of the outdoor humidity. The indoor ambient relative humidity increased with increasing the wall humidity. And the indoor average temperature is 23.3 ℃ and indoor relative humidity ranged between 90.9 % to 92.44 %. Soil moisture and wall humidity were the main factors affecting the indoor environmental relative humidity.

The promotion of plant growth and suppression of plant disease using beneficial microorganisms is considered an alternative to the application of chemical fertilizers or pesticides in the field. In this study, a coconut-scented antagonistic Trichoderma strain LZ42, previously isolated from Genoderma lucidum-cultivated soil, was investigated for biostimulatory and biocontrol functions in tomato seedlings. Morphological and phylogenetic analyses suggested that strain LZ42 is closely related to T. atroviride. Tomato plants showed increased aerial and root dry weights in greenhouse trials after treatment with T. atroviride LZ42 formulated in talc, indicating the biostimulatory function of this fungus. T. atroviride LZ42 effectively suppressed Fusarium wilt disease in tomato seedlings, with an 82.69% control efficiency, which is similar to that of fungicide treatment. The volatile organic compounds (VOCs) emitted by T. atroviride LZ42 were found to affect the primary root growth direction and promote the root growth of tomato seedlings in root Y-tube olfactometer assays. The fungal VOCs from T. atroviride LZ42 were observed to significantly inhibit F. oxysporum in a sandwiched Petri dish assay. SPME-GC-MS analysis revealed several VOCs emitted by T. atroviride LZ42; the dominant compound was tentatively identified as 6-pentyl-2H-pyran-2-one (6-PP). 6-PP exhibited a stronger ability to influence the direction of the primary roots of tomato seedlings but not the length of the primary roots. The inhibitory effect of 6-PP on F. oxysporum was the highest among the tested pure VOCs, showing a 50% effective concentration (EC50) of 5.76 μL mL-1 headspace. In conclusion, T. atroviride LZ42, which emits VOCs with multiple functions, is a promising agent for the biostimulation of vegetable plants and integrated management of Fusarium wilt disease.

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

Uridine diphosphate (UDP)-glycosyltransferases (UGTs) are major phase II detoxification enzymes involved in glycosylation of lipophilic endobiotics and xenobiotics, including phytoalexins. Nicotine, one of the most abundant secondary plant metabolites, is highly toxic to herbivorous insects. Plant-herbivore competition has been the major impetus for evolution of large superfamilies of UGTs and other detoxification enzymes. However, UGT functions in Myzus persicae adaptation have remained unknown. In this study, UGT inhibitors (sulfinpyrazone and 5-nitrouracil) significantly increased nicotine toxicity in M. persicae nicotianae, suggesting UGTs may be involved in nicotine tolerance. One hundred one UGT transcripts identified from the M. persicae genome/transcriptome were renamed according to UGT Nomenclature Committee guidelines and clustered into 11 families: UGT329, UGT330, UGT339, UGT341-UGT345, and UGT348-UGT350. UGT344 contained the most UGTs (fifty-seven). Ten UGTs (UGT330A3, UGT339A2, UGT341A6, UGT342B3, UGT343C3, UGT344D5, UGT344D8, UGT348A3, UGT349A3 and UGT350A3) were overexpressed in M. persicae nicotianae compared with M. persicae sensu stricto. UGT330A3/UGT344D5/UGT348A3/UGT349A3 knockdown significantly increased M. persicae nicotianae nicotine sensitivity, suggesting UGT upregulation in this subspecies may be associated with nicotine tolerance and thus host adaptation. This study reveals possible UGTs relevant to nicotine adaptation in tobacco-consuming M. persicae nicotianae and might facilitate further validation of the roles of these UGTs in nicotine tolerance.

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.

Crash prediction of the sharp horizontal curve segment (SHCS) of a freeway is an important tool in analyzing safety of SHCSs and in building a crash prediction model (CPM). The design and crash report data of 88 SHCSs from different institutions were surveyed and three negative binomial (NB) regression models and three generalized negative binomial (GNB) regression models were built to prove that the interactive influence of explanatory variables plays an important role in fitting goodness. The study demonstrates the effective use of the GNB model in analyzing the interactive influence of explanatory variables and in predicting freeway basic segments. Traffic volume, highway horizontal radius, and curve length have been formulated as explanatory variables. Subsequently, we performed statistical analysis to determine the model parameters and conducted sensitivity analysis. Among the six models, the result of model 6, which considered interactive influence, is much better than those of the other models by fitting rules. We also compared the actual results from crashes of 88 SHCSs with those predicted by models 1, 3, and 6. Results demonstrate that model 6 is much more reasonable than models 1 and 3.

Lunar grabens are the largest tensional linear structures on the Moon. In this paper, 17 grabens were selected to investigate the dips and displacement-length ratios (γ) of graben-bounding faults. Several topographic profiles were generated from selected grabens to measure their rim elevation, width and depth through SLDEM2015 (+LOLA) data. The differences in rim elevation (∆h) and width (∆W) between two topographic profiles on each graben were calculated, yielding 146 sets of data. We plotted ∆h versus ∆W for each and calculated the dip angle (α) of graben-bounding faults. A dip of 39.9° was obtained using the standard linear regression method. In order to improve accuracy, large error data was removed based on error analysis. The results 49.4° and 52.5° were derived by the standard linear regression and mean methods, respectively. Based on the depth and length of grabens, the γ value of the graben-bounding normal fault is also studied in this paper. The γ value is 3.6×10-3 for lunar normal faults according to the study of grabens and the Rupes Recta normal fault. After obtaining the values of α and γ, the increase in lunar radius caused by the formation of grabens was estimated. We suggest that the lunar radius has increased by around 130 m owing to the formation of grabens. This study could aid in the understanding of normal fault growth and provide important constraints on the thermal evolution of the Moon.

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.

In this study, the generality and prediction accuracy of a generalised series model for large eddy simulation of premixed and non-premixed turbulent combustion is explored. The model is based on Taylor series expansion of the chemical source term in scalar space and implemented into OpenFOAM. The mathematical model does not depend on the combustion regimes, and has the correct limiting behaviour. The numerical error sources are outlined and analysed. The model is first applied to a piloted methane/air non-premixed jet flame (Sandia Flame D). The statistical (time-averaged and RMS) results agree well with experimental measurements, particularly with regard to the mixture fraction, velocity, temperature, and concentrations of major species CH4, CO2, H2O, and O2. The concentrations of intermediates CO and H2 are over-predicted, due to the limitations of the reduced reaction mechanism employed. Then, a Bunsen piloted flame is simulated. Most of the statistical properties of both reactive species and progress variable are well reproduced. The only major discrepancy evident is in the temperature, which is attributed to the experimental uncertainties of temperature fields in the pilot stream. These findings have demonstrated the model`s generality for both premixed and non-premixed combustion simulation, as well as the accuracy of prediction of reactive species distribution.

This study aimed to evaluate the effects of a palygorskite-based antibacterial agent (PAA) as an alternative to antibiotics on growth performance, blood parameters, rumen fermentation, and rumen microbiota in sheep. A total of 120 sheep were randomly divided into five groups of six replicates with four sheep each. Sheep were fed a basal diet, an antibiotic diet supplemented with 500 g/t chlortetracycline (CTC), and a basal diet supplemented with 500, 1,000, and 2,000 g/t PAA for 80 d, respectively. Supplementation with 2,000 g/t PAA and 500 g/t CTC increased the average daily gain (ADG) of sheep compared with the control group (P < 0.05). Diets supplemented with 2,000 g/t PAA and 500 g/t CTC reduced (P < 0.05) the feed: gain (F/G ratio) in the overall periods. Dietary Supplementation with 1,000 g/t PAA significantly increased albumin and total protein (P < 0.05). A significant positive correlation was found between growth hormone concentration and PAA supplementation (P < 0.05). In addition, compared to the control group, the CTC group had higher growth hormone concentration and lower lipopolysaccharide concentration (P < 0.05). No dif-ference was observed between the five groups in terms of rumen fermentation characteristics (P > 0.05). At the phylum level, the relative abundance of Proteobacteria was lower in the PAA 2000 and CTC 500 groups than that in the control and PAA 500 groups (P < 0.05). At the genus level, a sig-nificant decrease (P < 0.05) in the relative abundance of RuminococcaceaeUCG-010 was observed in the PAA 1000, PAA 2000, and CTC 500 groups compared with that in the control group. In addition, the relative abundance of Prevotella1 (P < 0.05) was higher in the PAA 2000 group than that in the control group. These findings indicate that dietary supplementation with PAA has ameliorative effects on growth performance, blood parameters, and rumen microbiota, with an optimal dosage of 2,000 g/t for sheep.

Hippophae is a tree species with ecological, economic and social benefits. In this study, we assembled and annotated chloroplast genomes of sympatric Hippophae gyantsensis and H. rhamnoides subsp. yunnanensis. Their full-length are 155260 and 156415 bp, respectively. Each of them has 131 genes, comprising 85 protein-coding genes, 8 ribosomal RNA genes and 38 transfer RNA genes. After comparing the chloroplast genomes, we found 1302 base difference loci, and 63.29% are located in the intergenic region or intron sequences and 36.71% are located in the coding sequences. The SSC region has the highest mutation rate, followed by the LSC region; the IR regions have the lowest mutation rate. Among the protein-coding genes, three had a ratio of nonsynonymous to synonymous substitutions (Ka/Ks) >1 (but P values were non-significant) and 66 had Ka/Ks <1 (46 were significant). In general, the chloroplast protein-coding genes may be subject to purification selection. Among H. gyantsensis and H. rhamnoides subsp. yunnanensis chloroplast protein-coding genes, there are 20 and 16 optimal codons, respectively. Most of the optimal codons were ending with A or U, which indicates significant AT preference. It is an important reference for studies on the general characteristics and evolution of the Hippophae chloroplast genome.

There are various types of charged particles in the space environment, which can cause different types of radiation damage to materials and devices, leading to on-orbit failures and even accidents of spacecraft. Developing lightweight and efficient radiation shielding materials is an effective approach to improve the inherent protection of spacecraft. The protective performance of different materials against proton and electron spectra in the Earth’s radiation belts is evaluated by Geant4 simulation. Based on the simulation results, suitable hardening components are selected to design composite materials, and B4C/PEEK composites with different B4C content were successfully prepared. Experimental results demonstrate that the simulated and experimental results for the electron, proton and neutron shielding performance of B4C/PEEK composites are consistent. These composites exhibit excellent radiation shielding capabilities against electrons, protons and neutrons, and the radiation protection performance improves with increasing B4C content in the B4C/PEEK composite materials.

Osteosarcoma (OSA) is the most common primary malignant bone tumor. More than 40% of patients with OSA have poor prognoses. We aimed to discover a biomarker for patient stratification and therapeutic targets for these high-risk patients. Using Single Sample Gene Set Enrichment Analysis (ssGSEA) and univariate Cox analysis, six hallmarks were identified as significant prognostic factors for overall survival (OS). Three were selected to construct a multivariate Cox model. Then, WGCNA, univariate Cox regression, Kaplan-Meier (KM) survival analyses, and multivariate Cox analyses were combined to filter promising candidates and establish a seven-gene signature to predict OS, whose prognostic value was validated internally and externally. Subsequently, Differential Expression Analysis was conducted between high- and low-risk patients, and the Robust Rank Aggregation algorithm was used to determine the robust DEGs. Metascape was used to perform pathway and process enrichment analyses as well as construct protein-protein interaction (PPI) networks. Finally, RPS28 was identified as an independent risk factor by using univariate and multivariate Cox regression, which was preliminarily validated as a promising therapeutic target by using RNA interference. In conclusion, we might contribute to optimizing risk stratification and an excellent therapeutic target for high-risk patients with OSA.

In order to investigate the relationship between government policy, the service and design of rural crowdsourcing spaces, the self-efficacy of returning youth, and the innovation performance of businesses, this study focuses on gathering data by distributing questionnaires to returning youth in rural crowdsourcing spaces and developing a structural model. The results demonstrate how important government policies are in encouraging youth entrepreneurship in their local communities. It has the potential to enhance both the development of rural crowdsourcing spaces and the self-efficacy of young entrepreneurs, thereby enhancing the innovative capabilities of local entrepreneurial businesses. Therefore, in order to encourage economic development in rural areas, the government should improve pertinent support measures.

In this study, we evaluated the effects of Cyclosporine A (CsA) on Lipopolysaccharide (LPS)-induced cytokine production in the genital tract of female rabbits. Twelve sexually mature and healthy female rabbits were randomly divided into four groups (n = 3 each). The rabbits in the LPS group were given an intrauterine infusion of Escherichia coli LPS (4 mg/kg body weight (BW)). Rabbits in the CsA group were given CsA (20 mg/kg BW). Rabbits in the LPS + CsA group were given LPS (4 mg/kg BW) and CsA (20 mg/kg BW). The control group received only LPS and CsA carrier. The gene expression and protein levels of pro- and anti-inflammatory cytokines were observed using qRT-PCR and immuno-histochemical (IHC) assay, respectively. Our study showed that IL-1β, IL-6, IL-8, TNF-α, IFN-γ, IL-4, IL-10, IL-13, and TGF-β were expressed in female genital organs. The LPS challenge increased the mRNA expression of IL-6 and TNF-α in the uterine body and IL-1β in the uterotubal junction compared to the control group. CsA increased the basal mRNA expression of anti-inflammatory cytokines (i.e., IL-4 in the uterine body, uterotubal junction, and oviductal ampulla; IL-10 in the cervix, oviductal isthmus, and ampulla; and TGF-β in the uterotubal junction and oviductal ampulla) and pro-inflammatory cytokines (i.e., IL-6 and IL-8 in the cervix; IL-1β in the oviductal isthmus; TNF-α in the oviductal ampulla; and IFN-γ in the uterine body compared to the control group). In addition, CsA inhibited the mRNA expression of pro-inflammatory cytokines, such as IL-6 in the uterine body, uterotubal junction, and oviductal isthmus; TNF-α in the uterine body; and IFN-γ in the uterotubal junction and oviductal isthmus induced by the LPS challenge. The IHC assay showed the LPS-induced increase in protein production of IL-6 in the uterine body and oviductal isthmus. CsA increased the protein production of IL-10 in the cervix, uterine body, oviductal ampulla, and isthmus. Moreover, CsA decreased the protein production of IL-6 in the uterine body and oviductal isthmus induced by LPS.

Flexible capacity applications demands to large energy storage density and high breakdown electric field strength of flexible films. Here, P(VDF-HFP) with ultra-thin Al2O3 nanosheets composite films were designed and fabricated through an electrospinning process followed by hot-pressing in sandwich structured. The results show that the insulating ultra-thin Al2O3 nanosheets and the sandwich structure can enhance the composites' breakdown field (by 24.8%) and energy density (by 30.6%) remarkedly to P(VDF-HFP) polymer matrix. An energy density of 23.5 J/cm3 at the ultrahigh breakdown field of 740kV/mm can be therefore realized. Insulating test and phase-field simulation results reveal that ultra-thin nanosheets insulating buffer layers can reduce the leakage current in composites, thus it effects the electric field spatial distribution to enhance breakdown strength. Our research provides a feasible method to increase the breakdown strength of ferroelectric polymers, which is comparable to those of non-ferroelectric polymers.

Chinese investors are easily affected by hot topics on the media and Internet and likely take irrational behavior. They tend to consume rationally and invest emotionally. This research aims to analyze the Baidu index’s effect on share price of solar power industry in China. Three main models are established to identify the correlation between Baidu index and stock price of solar industry. The media index and searching index of Baidu are chosen as an independent variable to measure the influence from media and Internet, and stock price as the dependent variable. To improve and complete the analysis, Hexun index is taken into consideration as mediator variable. This study applied Multiple Linear Regression Model and VAR (Vector auto-regression) Model. The research mainly uses the tools of SPSS, Eviews and Excel to conduct data analysis. The test is based on the theories of Granger Causality, unit root test, F-test, and t-test. The research proves the relationship between the close price of stock and Baidu index, and it also created a model for further forecasting.

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.

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.

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.

(1) Background: Since the pandemic, adolescent girls have increasingly faced mental health challenges. We examined prevalence trends and associated risk factors for depression among adolescent girls. 2) Methods: Data for girls aged 12 to 17 years (N=4346) from the 2021 cross-sectional National Survey on Drug Use and Health were analyzed. Factors associated with depression were examined using multiple regression analysis. (3) Results: Rates of severe depression were significantly higher (p&lt;.001) in older girls (adjusted odds ratio [AOR]: 1.63, 1.61, those who did not have authoritative parents (AOR: 3.40), and those with negative school experiences (AOR: 4.03). Black and Asian/Native Hawaiian or other Pacific Islanders were less likely to report severe depression than white girls. As previously reported, non-White girls were significantly less likely to receive treatment for depression (p&lt;.05). Parents’ characteristics and school experiences had no effect on the likelihood of receiving mental health treatment. (4) Conclusion: Depression has become increasingly common among American adolescent girls, who are now three times as likely as adolescent boys to have had recent experiences with depression. Our results show that family structure, parenting style, and negative school experiences significantly contribute to the rate of depression and that treatment disparities exist with regard to race and ethnicity.

Chlorophyll-a (Chla) is a crucial pigment in phytoplankton, playing a vital role in determining phytoplankton biomass and water nutrient status. However, in optically complex water bodies, Chla concentration is no longer the primary factor influencing remote sensing spectral reflectance signals, leading to significant errors in traditional Chla concentration estimation methods. With advancements in in-situ measurements, synchronized satellite data, and computer technology, machine learning algorithms have become popular in Chla concentration retrieval. Nevertheless, when using machine learning methods to estimate Chla concentration, abrupt changes in Chla values can disrupt the spatiotemporal smoothness of the retrieval results. Therefore, this study proposes a two-stage approach to enhance the accuracy of Chla concentration estimation in optically complex water bodies. In the first stage, a one-dimensional convolutional neural network (1DCNN) is employed for precise Chla retrieval, and in the second stage, the regression layer of the 1DCNN is replaced with Support Vector Regression (SVR). The research findings are as follows: (1) In the first stage, the performance metrics (R², RMSE, RMLSE, Bias, MAE) of the 1DCNN outperform state-of-the-art algorithms (OCI, SVR, RFR) on the test dataset. (2) After the second stage, the performance further improves, with the metrics achieving values of 0.892, 11.243, 0.052, 1.056, and 1.444, respectively. (3) In mid-to-high latitude regions, the inversion performance of 1DCNN\SVR is superior to other algorithms, exhibiting richer details and higher noise tolerance in nearshore areas. (4) 1DCNN\SVR demonstrates high inversion capabilities in water bodies with medium to high nutrient levels.

For W-band long-range mm-wave wireless transmission systems, nonlinearity issues resulting from photoelectric devices, optical fiber, and wireless power amplifiers can be handled by deep learning equalization algorithms. Besides, the PS technique is considered an effective measure to further increase the capacity of the modulation-constraint channel. However, since the proba-bilistic distribution of m-QAM varies with the amplitude, there have been difficulties in learning valuable information from the minority class. This limits the gain of nonlinear equalization. To overcome the imbalanced machine learning problem, we propose a novel two-lane DNN (TLD) equalizer with the random over-sampling (ROS) technique in this paper. The combination of PS at the transmitter and ROS at the receiver improves the overall performance of the W-band wireless transmission system, and our 4.6-km ROF delivery experiment verifies its effectiveness for the W-band mm-wave PS-16QAM system. Based on our proposed equalization scheme, we realize single-channel 10-Gbaud W-band PS-16QAM wireless transmission over 100 m optical fiber link and 4.6-km wireless air-free distance. The results show that compared with the typical TLD without ROS, the TLD-ROS can improve the receiver sensitivity by 1dB. Furthermore, a reduction of 45.6% in complexity is realized, and training samples can be reduced by 15.5%. Considering the actual wireless physical layer with its requirements, there is much to be gained from the joint use of deep learning and balanced data pre-processing techniques.

Manipulation of radiation pattern control is challenging, especially at low frequencies. In this paper, we demonstrate that acoustic metamaterials as an effective array of quadrupoles can remarkably improve the directionality of acoustic radiation at low frequencies, compared with previous metamaterials as monopole and dipole structures. The directivity of the acoustic radiation can be adjusted by changing the characteristic parameter and the symmetry of the structure, which provide a flexible method of adjustable radiation di-rections. The directionality can be further improved by constructing linear array of structure. Our work opens an approach of acoustic radiation control via quadrupolar metamaterials.

Solar assisted hybrid cooling systems are promising for the energy saving of refrigeration systems. In most cases, the solar thermal gain is only able to power the heat-driven process of facilities in part of the working period. Therefore, the reduction of compressor power strongly depends upon the duration of heat-driven processes, which has not been addressed properly. Motivated by such knowledge gap, the thermodynamic understanding of solar assisted hybrid cooling systems is deepened through considering the duration in heat-driven processes. Three absorption-compression integrated cooling cycles were taken as examples. It is found that optimal parameters, e.g., inter-stage pressure and temperature, corresponding to various performance indicators trend to be identical, as the duration of heat-driven processes is taken into account. Furthermore, the optimal parameter for different working conditions was obtained. It is displayed that the dimensionless optimal intermediate temperature of layout with the cascade condensation process varies slightly, e.g., 4%, for different conditions. Moreover, the fall of compressor power in entire working periods is nearly independent upon the intermediate temperature. The paper is favorable for the efficient design and operation of solar assisted hybrid cooling systems.

An increasingly large quantity of primary mineral resource is being converted into manufactured products and destined for solid waste disposal. This material can be reclassified as “anthropogenic mineral reserves” and be a potential source of metals for a range of manufacturing uses. China is implementing a range of policy interventions which can lead to such a classification that will raise the profile of recycling programs as a means of metal supply. China is not only a major producer of consumer products and importer of secondary metals, but also has a major urban infrastructure footprint. Here we consider three product groups, 30 products, and imports, and map the recycling potential of anthropogenic mineral and 23 types of the capsulated materials by targeting their evolution from 2010 to 2050. Total weight of anthropogenic mineral on average in China reached 39 Mt in 2010, but it will double in 2022 and quadruple in 2045. Stocks of precious metals and rare earths will increase faster than most base materials. The total economic potential in yearly-generated anthropogenic mineral is anticipated to grow markedly from 100 billion US$ in 2020 to 400 billion US$ in 2050. Anthropogenic mineral of around 20 materials will be able to meet projected consumption of three product groups by 2050, due to high availability of recycled content and gradual saturation of consumption. Durability of material usage and the concomitant stock of the anthropogenic mineral remain major challenges in determining the viability of this supply in the second half of the coming century.

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.

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.