Thermally-assisted-occupation density functional theory (TAO-DFT) has been an efficient electronic structure method for studying the ground-state properties of large electronic systems with multi-reference character over the past few years. To explore the time-dependent (TD) properties of electronic systems (e.g., subject to an intense laser pulse), in this work, we propose a real-time (RT) extension of TAO-DFT, denoted as RT-TAO-DFT. Besides, we employ RT-TAO-DFT to study the high-order harmonic generation (HHG) spectra and related TD properties of molecular hydrogen H2 at the equilibrium and stretched geometries, aligned along the polarization of an intense linearly polarized laser pulse. The TD properties obtained with RT-TAO-DFT are compared with those obtained with the widely used time-dependent Kohn-Sham (TDKS) method. In addition, issues related to the possible spin-symmetry breaking effects in the TD properties are discussed.

For the ground-state properties of gas-phase nanomolecules with multi-reference character, thermally-assisted-occupation density functional theory (TAO-DFT) has been recently found to outperform the widely used Kohn-Sham density functional theory, when the conventional exchange-correlation energy functionals are employed. Aiming to explore solvation effects on the ground-state properties of nanomolecules with multi-reference character at a minimal computational cost, we combine TAO-DFT with the polarizable continuum model (PCM). To show its usefulness, TAO-DFT-based PCM (TAO-PCM) is employed to study the electronic properties of linear acenes in three different solvents (toluene, chlorobenzene, and water). According to TAO-PCM, in the presence of these solvents, the smaller acenes should have nonradical nature, and the larger acenes should have increasing polyradical nature, showing remarkable similarities to the past findings in the gas phase.

The essence of cross-modal generation and retrieval modeling for image-text interactions lies in semantic consistency. Among these, cross-modal representation alignment serves as the foundational requirement for achieving cross-modal semantic consistency. The crux of our proposed method entails the collaborative training of an image captioning model(referred to as the ’captioner’) and a pair of contrastive encoders for image-text matching(referred to as the ’concoder’). This synergistic approach yields concurrent enhancements in concoder’s performance, captioner’s proficiency, and cross-modal semantic coherence. We coin the proposed method as ‘ReCap’. To begin, we initialize the concoder through knowledge distillation from a pre-trained model. During the training process, we use the output of the initialized concoder as input to a residual attention network, jointly training it with the captioner to achieve semantic consistency. Subsequently, we iteratively update the concoder during the image-text momentum encoding phase using the residual attention network, creating a closed-loop for semantic consistency resolution. Upon completion of training, the concoder and captioner modules can be used independently to perform tasks related to cross-modal retrieval and cross-modal generation of text and images. In order to substantiate the efficacy of our proposed method, we initially conducted empirical experiments encompassing image-text retrieval and image captioning tasks, employing a widely recognized benchmark dataset, MSCOCO. Subsequently, we assessed the fine-grained cross-modal alignment performance of the concoder through an image classification task on the iNaturalist 2018 dataset. The achieved performance metrics notably surpassed those achieved by several incumbent state-of-the-art models, thus validating the proficiency of our method. Finally, motivated by the practical requirements of handling the nature conservation image data, we performed caption annotation for the iNaturalist 2018 dataset. Subsequently, we trained the ReCap on this annotated data. Experimental results demonstrate that our proposed method can maintain semantic consistency between cross-modal retrieval and image caption generation for species with similar visual features but distinct semantics. This achievement signifies a meaningful exploration in the field of cross-modal semantic consistency representation, holding significant practical value in the domain of biological research.

Tao and Ming (name) or Tao and Yan (language or speech) is an inseparable pair of important concepts in traditional Chinese language philosophy. In LaoTze’s opinion, Tao could not be spoken out, and language or speech could not reach Tao’s essence. Yan and Tao are separated from each other, and they are paradoxical. All the confusion derives from Yan regardless of how delicate they are. Tao can be expressed in words, but it will never be expressed through common languages. In this article, Tao is regarded as a human being’s thoughts or intentions and is even considered to be the origin of the real world. Language can express people’s thought, although it has some limitations. There exist some contradictions between the real word and the world expressed in words. To enable people to better understand the existence of the real world from multiple perspectives at the language or linguistic level without being constrained by words, this article studies LaoTze’s linguistic philosophy reflected in his opinion on the relationship between Tao and Yan and makes a comparative analysis of modern Western language philosophers’ stand on language (or speech) and existence.

Background: Cigarette smoking (CS) is a global public health problem and a high-risk factor for various diseases. In December 2019, a novel coronavirus (HCoV-19) was identified in Wuhan, China. Because ACE2 has been identified as a receptor for HCoV-19, we hypothesize that CS affects the expression pattern of ACE2 in respiratory tract, causing differences in susceptibility to the virus. Methods: Three datasets (GSE994, GSE17913, and GSE18344), were downloaded from the Gene Expression Omnibus (GEO) database. Correlation and enrichment analysis were used to evaluate the function of ACE2. Also, the different expression of ACE2 in different groups of three datasets were analyzed. Results: Genes associated with ACE2 were enriched in important biological processes such as viral processes and immune response. Elevated ACE2 were found in intrapulmonary airways (GSE994) and oral epithelial cells (GSE17913) of smokers but not those of non-smokers or former smokers. Significant dose- and time-dependent relationships between CS and ACE2 expression were observed in mouse lung tissues, and long periods without smoking were found to significantly reduce ACE2 expression. Conclusions: Both human and rat data confirmed that CS could induce increased ACE2 in the respiratory tract, indicating that smokers have a higher susceptibility to HCoV-19.

Intercropping significantly improves land use efficiency and soil fertility. This study examines the impact of three cultivation systems (monoculture sugarcane, peanut-sugarcane and soybean-sugarcane intercropping) on soil properties and diazotrophs. Sugarcane rhizosphere soil was sampled from the farmers’ field. Soil properties and nifH gene abundance were analyzed by high throughput sequencing. Moreover, a total of 436,458 nifH gene sequences were obtained and classified into the 3201 unique operational taxonomic units (OTUs). Maximum unique OTUs resulted with soybean-sugarcane intercropping (<375). The dominant groups across all cultivation were Alpha-proteobacteria and Beta-proteobacteria. On the basis of microbial community structure, intercropping systems were more diverse than monoculture sugarcane. In the genus level, Bradyrhizobium, Burkholderia, Pelomonas, and Sphingomonas were predominant in the intercropping systems. Moreover, diazotrophic bacterial communities of these cultivation systems were positively correlated to the soil pH and soil enzyme protease. Moreover, low available P recovered from intercropping system showed a strong correlation with higher nutrient uptake activity of soil microbes. Based on the results, our investigation concluded that intercropping system caused a positive effect on the growth of diazotrophic bacterial communities and it might boost the soil fertility and this kind of study helps to develop an eco-friendly technology for sustainable sugarcane production.

The base excitation of mechanical equipment can result in pipeline system vibration which seriously affects the safe operation of the equipment. Particle damping technology is based on the particle collision dissipation principle to realize the structural vibration energy dissipation. This paper introduces the particle damping method into the vibration control of pipeline system. A particle damper has been designed for the structural characteristics of the pipeline. The influence of the material and structure of the pipeline particle damper, the external excitation and other parameters on the energy dissipation characteristics of particle damping are revealed. The energy dissipation mechanism of the pipeline particle collision damper under various parameter is analyzed. A pipeline vibration reduction test system with particle damping has been established. The effects of different excitation conditions, damper materials and number of unit structures of particle damper on the vibration damping effect of pipeline systems are investigated comparatively. The influence of damper parameters on the vibration suppression of pipeline system is obtained. The research in this paper can provide technical references for vibration suppression of pipeline systems.

Motivated by empirical observations, we propose a possible extension of Gibrat's law. By applying it into the random growth theory of income distribution (Gabaix, 2009), we find that the income distribution is described by a generalized Pareto-type distribution (GPD) with three parameters. We observe that there is a parameter /elta in the GPD that plays a key role in determining the shape of income distribution. By using the Kolmogorov-Smirnov test, we empirically show that, for typical market-economy countries, /elta is close to 0 significantly, such that the income distribution is characterized by a two-class pattern in which the bottom 90% of the population is approximated by an exponential distribution and the richest 1%~3% is approximated by an asymptotic power law. However, we empirically find that, for China both in planned economy period and in early stages of market reformation (from 1978 to 1990), /elta is significantly deviated from 0, such that the bottom of the population no longer conforms to an exponential distribution.

In this computational study, we investigate the electronic properties of zigzag graphene nano-parallelograms (GNPs), which are parallelogram-shaped graphene nanoribbons of various widths and lengths, using thermally-assisted-occupation density functional theory (TAO-DFT). Our calculations reveal a monotonic decrease in the singlet-triplet energy gap as the GNP length increases. The GNPs possess singlet ground states for all the cases examined. With the increase of GNP length, the vertical ionization potential and fundamental gap decrease monotonically, while the vertical electron affinity increases monotonically. Besides, as the GNP length increases, the symmetrized von Neumann entropy increases monotonically, denoting an increase in the degree of multi-reference character associated with ground-state GNPs. The occupation numbers and real-space representation of active orbitals indicate that there is a transition from the nonradical nature of the shorter GNPs to the increasing polyradical nature of the longer GNPs. In addition, the edge/corner localization of active orbitals is found for the wider and longer GNPs.

Scattering hyperspectral technology is a nondestructive testing method with many advantages. Here, we propose a method to improve the accuracy of egg freshness, research the influence of incident angles of light source on the accuracy and explain its mechanism. A variety of weak classifiers classify eggs based on the spectra after preprocessing and feature wavelength extraction to obtain three classifiers with the highest accuracy. The three classifiers are used as metamodels of stacking ensemble learning to improve the highest accuracy from 96.25% to 100%. Moreover, the highest accuracy of scattering, reflection, transmission and mixed hyperspectral of eggs are 100.00%, 88.75%, 95.00% and 96.25%, respectively, indicating that the scattering hyperspectral for egg freshness detection is better than that of the others. In addition, the accuracy is inversely proportional to the angle of incidence due that the smaller the incident angle, the camera collects a larger proportion of scattering light, which contains more biochemical parameters of an egg than that of reflection and transmission. These results are very important for improving the accuracy of non-destructive testing and selecting the incident angle of the light source, and have potential applications in online non-destructive testing.

Accompanied by increasing population growth and urban sprawl, most coastal cities are unprecedentedly vulnerable to climate change and its impacts, such as sea level rise, increasing extreme storm events, and coastal flooding. Coastal resilience and sustainable development are antidotes to vulnerability; they aim to enhance the adaptive capability of absorbing disturbances and resisting uncertainty. This study explores building a quantitative assessment framework to measure resilience and provide an objective and comparable method to understand the strengths and weaknesses in a given region. The proposed 25 resilience indicators incorporate the aspects of essential livelihood protection, infrastructure and natural resource maintenance, emergency facilities and institutions, floodplain management regulations, and adaptive planning process. Each indicator is assigned the resilience quality that includes robustness, resourcefulness, redundancy, and rapidity. The aggregated resilience quality scoring reflects the systematic performance of the city to cope with the coastal hazards. The innovative part of this framework is combining hazard mitigation measures, climate adaptation strategies, and sustainable development goals together to achieve a comprehensive assessment method. In the case of New Haven, the resilience assessment is taken as a practical monitoring tool and decision-making support.

Abstract In order to solve the problem that it is difficult to obtain the accurate trigger signal moment when using the time difference of UAV flight acoustic signals collected by acoustic sensors arranged in advance to locate the position of UAVs when they cannot be tracked by radar and are difficult to be observed by the human eye, an acoustic source localisation method with improved empirical modal decomposition (REMD) under an adaptive frequency window is proposed. Firstly, the collected UAV flight signals are smoothed and filtered, then the robust empirical modal decomposition (REMD) is used for IMF modal decomposition and spectral analysis of the collected signals, and a panning frequency window with variable bandwidth is introduced for corresponding frequency locking and extracting the IMFs; the GWO optimisation is used and the sliding metrics are set to determine the position of the panning frequency window automatically; finally, the extracted Finally, the extracted IMF components are reconstructed according to the criterion, and the trigger signal moments in the reconstructed IMF components are resolved and recorded, and the algorithm is used to calculate the difference between the reception moments of different sensors; for the traditional sound source localisation algorithms with a small detection range, which are prone to fall into the no-solution or false-solution, i.e., unable to achieve the localisation, a weighted least-squares-based Chan-Taylor algorithm is proposed for the localisation computation, and a weighted least-squares algorithm is proposed for the localisation computation, through the Inputting the sensor delay parameter and solving the linear equation system to get the target position information; finally, this paper verifies the robustness and performance of the design method with simulated and actual signals. The results show that the maximum positioning error is no more than 5% in an area with a side length of 15m in the measurement area. With the improved accuracy of time delay estimation, the positioning simulation results meet the positioning requirements even though the positioning error is further expanded when the measurement area is further expanded.

Existing research concerning the effects of the sitting birth position during the second stage of labour on maternal and neonatal outcomes remains controversial, and there is a lack of studies to explore its effect on the childbirth experience. The objective of this study is to explore whether the sitting birth position would influence maternal and neonatal outcomes, as well as the childbirth experience reported by Chinese women using the Childbirth Experience Questionnaire (CEQ). A total of 296 women (including primiparous women and multiparous women) were enrolled in our study, and they were divided into the sitting position cohort (n=106) or the lithotomy position cohort(n=116). The study found that primiparous women in the sitting position cohort had a shorter duration of the second stage of labour, higher spontaneous vaginal birth rates, lower episiotomy rates and better childbirth experience (p<0.01). There was no significant difference for perineal lacerations, 2h-postpartum haemorrhage (P>0.05) between the two cohorts of primiparous women. After adjusting for confounding factors through multiple linear and logistic regression analyses, the results remained consistent with those reported above. No neonate in each cohort had Apgar scores at 1min and 5 min postpartum less than 7 or the Cord artery pH less than 7.00, regardless of parity. In addition, among multiparous women, there was no significant difference in any maternal and neonatal outcomes and women’s CEQ scores (p>0.05) between two cohorts. Based on the findings, we recommend that women could take the sitting birth position into account when giving birth for a positive childbirth experience, especially for primiparous women. The study could also serve as a reference for healthcare providers in the management of childbirth positions and the development of high-quality maternal care.

Ledge formation presents a significant challenge in endodontic treatment. Yet, there is still a lack of educational tooth models for hands-on practice. This study aimed to create and evaluate a tooth model for ledge management practice. A natural tooth with curved roots was collected for scientific use under ethics committee approval. Following initial root canal preparation, the tooth was scanned using micro-computed tomography (μCT) and 3D reconstructed. A K-file, created via computer-aided design (CAD), was partly inserted into the root canal wall of the 3D-reconstructed tooth. By subtracting the K-file from the tooth, a tooth model with a root canal ledge was produced. The models were then 3D printed for a hands-on workshop. A seven-item Likert scale questionnaire was administered to 20 postgraduate students and 10 endodontists to assess the model's quality and training effectiveness. The feedback from both students and experts was positive, with no statistically significant differences found between the two groups (p &gt; 0.05). This novel tooth model is expected to address the existing gap in endodontic education and provide benefits for dental practitioners in future applications.

This paper presents a review on numerical and experimental methods to predict fracture of ad-vanced high strength steels (AHSS). AHSS are widely processed through sheet metal forming processes. Although being an excellent choice when lightweight, high strength and ductility are critical factors, their multi-phase microstructure accentuates forming challenges. To accurately model forming behavior, necking based failure criteria as well as direct fracture models require improvements. As a necking based failure model, the conventional forming limit diagram/curve (FLD/FLC) presents limitations such as in estimating direct fracture (surface cracks, edge cracks, shear cracks), as well as deformation histories under nonlinear strain paths. Thus, significant re-search efforts are being made towards the needs of advanced fracture constitutive models capa-ble of predicting fracture scenarios without necking, more frequently observed in the realm of AHSS. Scientific community research is divided into several directions aiming at improving the forming and fracture behavior accuracy of parts subjected to sheet metal forming operations. In this review paper, a comprehensive overview on ductile fracture modeling is presented. Firstly, the FLD/FLC limitations modeling fracture behavior in sheet metal forming operations are stud-ied. Followed by the recent trends in constitutive material modeling. Afterwards, material char-acterization methods advancements to cover a broad range of stress states are comprised. Final-ly, damage and fracture models predicting failure in AHSS are investigated. This review paper supplies relevant information on the current issues the sheet metal forming community is chal-lenged with due to the trend towards AHSS employment in the automotive industry.

The current management of colorectal cancer liver metastasis (CRCLM) patients involves a multidisciplinary approach with surgical resection remaining the primary curative option. The advances in liver surgery have improved outcomes, enabling more patients to undergo surgery successfully. In addition, the development of imaging software has improved the preoperative planning and patient selection for surgery and other interventions. Systemic therapies, such as targeted therapies and immunotherapies have enhanced the chances of complete resection. Targeted agents in combination with chemotherapy, have shown efficacy in downstaging tumors and increasing resectability.

This paper systematically examines Chinese academic discourse that concurrently addresses Indonesia and Timor-Leste, analysing 137 articles from the China National Knowledge Infrastructure (CNKI) and indexed by the Chinese Social Sciences Citation Index (CSSCI). The analysis reveals significant publication trends, particularly during periods of heightened geopolitical and economic engagement, such as the global expansion of the Belt and Road Initiative (BRI). It identifies predominant themes such as economic cooperation, security concerns, and historical-cultural dynamics. The findings highlight China’s strategic interests and leadership aspirations in Southeast Asia， providing insights into how Chinese scholars perceive and articulate China’s strategic interests and diplomatic efforts in the region involving Indonesia and Timor-Leste.

Hyperactivation of Janus kinase (JAK)/signal transducer and activator of transcription 3 (STAT3) signaling is an attractive therapeutic target for tumor therapy. Herein, forty-eight novel meridianin derivatives were designed and synthesized, and their anti-tumor activity were evaluated in vitro both for activity optimization and structure-activity relationship (SAR) study. The results indicated that most derivatives exhibited significantly improved anti-tumor activity, especially for compound 6e. The compound 6e contains an isothiouronium linked by an alkyl chain consisting of 6 carbon atoms with IC50 ranging from 1.11 to 2.80 μM on various cancer cell lines. Consistently, 6e dose dependently induced the apoptosis of A549 and DU145 cells, in which STAT3 are constitutively active. Western blotting assays indicated that the phosphorylation levels of JAK1, JAK2 and STAT3 were inhibited by 6e at 5 μM without significant change in total STAT3 level. Moreover, 6e also suppressed the expressions of STAT3 downstream genes, including c-Myc, Cyclin D1 and Bcl-XL at 10 μM. An additional in vivo study revealed that 6e at the dose of 10 mg/kg could potently inhibit the DU145 xenograft tumor without obvious body-weight loss. These results clearly indicate that 6e could be a potential anti-tumor agent by targeting JAK/STAT3 signaling pathway.

In order to realize rapid and nondestructive monitoring of wheat biomass in field, field experiments based on different densities, nitrogen fertilizer and variety treatments were studied. RGB images of wheat in the main growth stage were obtained by UAV, and wheat color and texture feature indices were obtained by image processing, and wheat biomass was obtained by field sampling in the same period. Then the relationship between different color and texture feature indices and wheat biomass was analyzed to select the color and texture feature index suitable for wheat biomass estimation. The results showed that there was a high correlation between image color index and wheat biomass in different stages, and most of them reached a very significant correlation level. However, the correlation between image texture feature index and wheat biomass was poor, only a few indexes reached significant or extremely significant correlation level. Based on the above results, the color indices with the highest correlation to wheat biomass or the combining indices of color and texture feature in different growth stage were used to construct estimation model of wheat biomass. The models were validated using independently measured biomass data, and the correlation between simulated and measured values reached the significant level, RMSE were smaller. This indicated that the estimated results by the models were reliable and accurate. It also showed that the estimation models of wheat biomass combined with color and texture feature indices of UAV image were better than the single color index models. The results would provide a new method for real-time monitoring of wheat field growth and biomass estimation.

The major histocompatibility complex (MHC) genes are the most polymorphic genes in vertebrates, and their proteins play a critical role in adaptive immunity for defense against a variety of pathogens. MHC diversity was lost in many species after experiencing a decline in size. To understand the variation and evolution of MHC genes in the Siberian ibex, Capra sibirica, which has undergone a population decline, we analyzed the variation of the second exon of MHC class II DRB genes in samples collected from five geographic localities in Xinjiang, China, that belong to three diverged mitochondrial clades. Consequently, we identified a total of 26 putative functional alleles (PFAs) with 260 bp in length from 43 individuals, and found one (for 27 individuals) to three (for 5 individuals) PFAs per individual, indicating the presence of one or two DRB loci per haploid genome. The Casi-DRB1*16 was the most frequently occurring PFA, Casi-DRB1*22 came after found in only seven individuals, 14 PFAs occurred once (7 PFAs twice), implying high frequency of rare PFAs. Interestingly, more than half of the (15) PFAs were specific to clade I, only one and three PFAs were specific to clades II and III, respectively. So, we assume that the polygamy and sextual segregation nature of this species likely contributed to the allelic diversity of DRB genes. Genetic diversity indices showed that PFAs of clade II were lower in nucleotide, amino acid, and supertype diversity compared to those of the other two clades. The way of allele sharing and FST values between three clades were to some extent in agreement with pattern observed in mitochondrial DNA divergence. In addition, recombination analyses revealed no evidence for significant signatures of recombination events. Alleles shared by clades III and the other two clades diverged 6 million years ago, and systematic neighbor grids showed cross-species polymorphisms. Together with the PAML and MEME analyses, the results indicated that the DRB gene in C. sibirica evolved under balancing and positive selection. However, by comparison, it can be clearly seen that different populations were under different selective pressures. Our results are valuable in understanding the diversity and evolution of the DRB gene in a mountain living C. sibirica and in making decisions on future long-term protection strategies.

This paper provides attempts to formalize Hayek’s theory of knowledge. It has been theoretically shown that exponential income distribution is a spontaneous order of the well-functioning market economy. We show that this theoretical result is supported by the empirical evidence from the United Kingdom and China. In particular, we empirically show how the income structure of China evolved towards an exponential distribution after the market-oriented economic reformation. Furthermore, we strictly prove that, if the income structure of an economy obeys an exponential distribution, the income summation over all households leads to an aggregate production function with Hicks-neutral-like technical progress, in which the technology factor is exactly equal to society’s information stock that is a result of combining all of decentralized decisions.

In this study, we investigate the behavior of randomly moving particles with a defined average energy, focusing on their biased motion around a specific point. These particles' velocity magnitudes follow a Maxwell distribution with a specific scale parameter. Our analysis derives the stochastic rotation rules for these particles and introduces the Ito equation conditions for biased stochastic rotation at a given curl value. We also consider the special relativistic-like effects in this context. The findings are validated through a representative example.

We show that an exponential income distribution will emerge spontaneously in a peer-to-peer economic network that shares the publicly available technology. Based on this finding, we identify the exponential income distribution as the benchmark structure of the well-functioning market economy. However, a real market economy may deviate from the well-functioning market economy. We show that the deviation is partly reflected as the invalidity of exponential distribution in describing the super-low income class that involves unemployment. In this regard, we find, theoretically, that the lower-bound u of exponential income distribution has a linear relationship with (per capita) unemployment compensation. In this paper, we test this relationship for the United Kingdom from 2001 to 2015. Our empirical investigation confirms that the income structure of low and middle classes (about 90% of populations) in the United Kingdom exactly obeys exponential distribution, in which the lower-bound u is exactly in line with the evolution of unemployment compensation.

In a particle swarm with a fixed kinetic energy, the constituent particles move randomly and their velocity magnitudes follow a Maxwell distribution characterized by specific parameters. Within a certain time frame, particles in a sub-swarm may exhibit a bias in their movement direction. Thus, the particles may exhibit a special characteristic (biased random motion), where the group velocity in a particular direction remains constant u. For this biased particle swarm, composed of randomly moving particles with a fixed average speed c, particles have a higher probability of moving in a specific direction. Conversely, their likelihood of moving in all other directions is equally reduced. This study starts from the perspective of biased random walks and using Mathematica software proves that the diffusion rate of particles (in the reference frame R_u observed from R₀) in all directions is slower than that of an unbiased particle swarm with the same average speed c. Specifically, the degree of reduction is determined by the Lorentz-like factor. Lastly, we present the Ito equation for this biased random motion and provide associated verification examples. This study aims to serve as a reference for comprehending the underlying principles of the special relativity effect.

This paper presents an optimized energy management strategy for Li-ion power batteries used on electric vehicles (EVs) at low temperatures. Under low-temperature environments, EVs suffer a sharp driving range loss resulted from the energy and power capability reduction of the battery. Simultaneously, because of Li plating, battery degradation becomes an increasing concern as temperature drops. All these factors could greatly increase the total vehicle operation cost. Prior to battery charging and vehicle operating, preheating battery to a battery-friendly temperature is an approach to promote energy utilization and reduce total cost. Based on the proposed LiFePO4 battery model, the total vehicle operation cost under certain driving cycles is quantified in the present paper. Then given a certain ambient temperature, a target temperature of preheating is optimized under the principle of minimizing total cost. As for the preheating method, a liquid heating system is also implemented on an electric bus. Simulation results show that the preheating process becomes increasingly necessary with a decreasing ambient temperature; however, the preheating demand declines as driving range grows. Vehicle tests verify that the preheating management strategy proposed in this paper is able to save total vehicle operation cost.

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

Open-vocabulary learning has recently gained prominence as a means to enable image segmentation for arbitrary categories based on textual descriptions. This advancement has extended the applicability of segmentation systems to a broader range of generally purpose scenarios. However, current methods often revolve around specialized architectures and parameters tailored to specific segmentation tasks, resulting in a fragmented landscape of segmentation models. In response to these challenges, we introduce OVAMTSeg, a versatile framework designed for Open-Vocabulary and Multitask Image Segmentation. OVAMTSeg harnesses adaptive prompt learning to empower the model to capture category-sensitive concepts, enhancing its robustness across diverse multi-task and scenario contexts. Text prompts are employed to effectively capture semantic and contextual features of the text, while cross-attention and cross-modal interactions enable the fusion of image and text features. Furthermore, a transformer-based decoder is incorporated for dense prediction. Extensive experimental results underscore the effectiveness of OVAMTSeg, showcasing its state-of-the-art performance and superior generalization capabilities across three segmentation tasks. Notable achievements include a 47.5 mIoU in referring expression segmentation, 51.6 mIoU on Pascal-VOC with four unseen classes, 46.6 mIoU on Pascal-Context in zero-shot segmentation, 65.9 mIoU on Pascal-5i, and 35.7 mIoU on COCO-20i datasets for one-shot segmentation.

We constrain two dynamical dark energy models that are parametrized by the logarithm form of $w(z)=w_{0}+w_{1}\left(\frac{\ln (2+z)}{1+z}-\ln 2\right)$ and the oscillating form of $w(z)=w_{0}+w_{1}\left(\frac{\sin(1+z)}{1+z}-\sin(1)\right)$. Comparing with the Chevallier-Polarski-Linder (CPL) model, the two parametrizations for dark energy can explore the whole evolution history of the universe properly. Using the current mainstream observational data including the cosmic microwave background data and the baryon acoustic oscillation data as well as the type Ia supernovae data, we perform the $\chi^2$ statistic analysis to global fit these models, finding that the logarithm parametrization and the oscillating parametrization are almost as well as the CPL scenario in fitting these data. We make a comparison for the impacts of the dynamical dark energy on the cosmological constraints on the total mass of active neutrinos. We find that the dark energy properties could significantly change the fitting results of neutrino mass. Looser constraints on $\sum m_{\nu}$ are obtained in the logarithm and oscillating models than those derived in the CPL model. Consideration of the possible mass ordering of neutrinos reveals that the most stringent constraint on $\sum m_{\nu}$ appears in the degenerate hierarchy case.

Soil amendments with composted organic materials are recommended to increase soil organic matter (SOM), promote soil fertility, and the Circular Economy. Growing areas of hedged olive groves in southern Iberia peninsula generate huge amounts of olive leaves whose potential as soil organic amendment is not fully studied. An experimental field trial in a hedged olive grove (cv. “Cobrançosa”) was set up near Portalegre, Portugal, to test a compost of olive leaves plus sheep manure (2:1) applied in the row, at soil surface. Three nominal rates (0 or control, 2.5 and 5.0 kg m-2) were used, in a complete randomized block setup (3 treatments, 3 replicas, 9 plots) and soil chemical properties of layers 0-5, 5-15, and 15-30 cm deep were annually monitored. Results (mainly in layer 0-5 cm) showed increases in total N, carbon of the particulate organic matter (POM-C), permanganate oxidizable carbon (POX-C), extractable phosphorus, and zinc, after one year, and increases in soil organic carbon (SOC), C-stock, pHKCl, extractable phosphorus, and zinc, after two years. POX-C was the most sensitive SOM-related indicator, showing increases up to 30 cm deep after one year. This compost improved soil fertility, but should be monitored over longer periods of time, namely for SOC and extractable zinc content.

MIMO (multiple-input multiple-output) radar provides much more flexibility than the traditional radar for its ability to realize far more observation channels than the actual number of T/R (transmit and receive) elements. Designing the array of MIMO imaging radar, the commonly used virtual array theory generally assumes that all elements are placed on the same line. However, due to the physical size of the antennas and coupling effect between T/R elements, a certain height difference between T/R arrays is essential, resulting in the defocusing of edge points of the scene. On the other hand, the virtual array theory implies far-field approximation, leading to inevitable high grating lobes in the imaging result of near-field edge points of the scene observed by common MIMO array. To tackle these problems, this paper derives the relationship between target’s PSF (point spread function) and pattern of T/R arrays, by which the design criterion of near-field imaging MIMO array is presented. Firstly, the proper height between T/R arrays is designed to focus the near-field edge points well. Secondly, the far-field array is modified to suppress the grating lobes in the near-field area. Finally, the validity of the proposed methods is verified by simulations and an experiment.

Time and space are fundamental concepts for characterizing and understanding our world. Despite of continuous curiosity and extensive studies, the nature of time and space remains elusive, and the underlying quantum structure is unclear. Here we propose a molecular model based on energy space decomposition to incorporate time and space synthetically in a unified framework. In the proposed model, the multipole expansion of action mapped to energy modules in scalar, vector, and matrix forms, results in the generators of time, space, and a material framework, cloud. And the invariance of time, space and cloud transformation corresponds to the conservation of energy, momentum, and mass, respectively. The classification of energy modules reveals a periodicity of energy elements, which constructs a hierarchical world in a molecular framework with dynamics represented by energy transformations. Here the role of time and space could switch from each other, and motion is attributed to the coupling of particle with intermediate bosons, corresponding to energy transformations among different energy modules. The application on Bohr model demonstrates that this picture provides a consistent classical interpretation to the foundation of quantum mechanics, and suggests an atomic model for gravitation.

In recent years, video anomaly detection technology , which can intelligently analyze massive video and quickly find abnormal phenomena, has attracted extensive attention with the wide application of video surveillance technology . To address the complex and diverse problem of abnormal human behavior detection in surveillance videos, a surveillance video abnormal behavior detection and localization supervised method based on the deep network model and the traditional method is proposed. Specifically, we combined AGMM and YOLACT methods to obtain more accurate foreground information by fusing the foreground maps extracted by each technique. To further improve the accuracy , we use the PWC-Net technique to extract features of the foreground images and input them into an anomaly classification model for classification. The proposed method effectively detects and locates the abnormal behavior in the monitoring scene. In addition to the aforementioned methods, this paper also employs YOLOV5 and DeepSORT networks for object detection and tracking in the video, which allows us to track the detected objects for better understanding of the scene in the video. Experiments on the UCSD benchmark dataset and the comparison with state-of-the-art schemes prove the advantages of our method.

By using the particle swarm optimization algorithm for crystal structure prediction, we reveal a newly orthorhombic Cmcm structure of HfB4, which is more energetically superior to the previously proposed YB4-, ReP4-, FeB4-, CrB4-, and MnB4-type structures in the considered pressure range. The phonon dispersion and elastic constants calculations confirm that the new phase is dynamically and mechanically stable. The calculated large shear modulus (240 GPa) and high hardness (45.7 GPa) imply that the predicted Cmcm-HfB4 is a potential superhard material. Meanwhile, the directional dependences of the Young's modulus, bulk modulus, and shear modulus for HfB4 are systematically investigated. Further analyses of the density of states and electronic localization function indicate that the strong B-B and B-Hf covalent bonds greatly contribute to its high hardness and stability.

In recent years, researchers have paid increasing attention on hyperspectral image (HSI) classification using deep learning methods. To improve the accuracy and reduce the training samples, we propose a double-branch dual-attention mechanism network (DBDA) for HSI classification in this paper. Two branches are designed in DBDA to capture plenty of spectral and spatial features contained in HSI. Furthermore, a channel attention block and a spatial attention block are applied to these two branches respectively, which enables DBDA to refine and optimize the extracted feature maps. A series of experiments on four hyperspectral datasets show that the proposed framework has superior performance to the state-of-the-art algorithm, especially when the training samples are signally lacking.

Flexible implementations of Monte Carlo Tree Search (MCTS), combined with domain specific knowledge and hybridization with other search algorithms, can be a very powerful for the solution of problems in complex planning. We introduce mctreesearch4j, a standard MCTS implementation written as a standard JVM library following key design principles of object oriented programming. We define key class abstractions allowing the MCTS library to flexibly adapt to any well defined Markov Decision Process or turn-based adversarial game. Furthermore, our library is designed to be modular and extensible, utilizing class inheritance and generic typing to standardize custom algorithm definitions. We demon- strate that the design of the MCTS implementation provides ease of adaptation for unique heuristics and customization across varying Markov Decision Process (MDP) domains. In addition, the implementation is reasonably performant and accurate for standard MDP’s. In addition, via the implementation of mctreesearch4j, the nuances of different types of MCTS algorithms are discussed.

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

This study investigated the adaptability of Dunaliella salina to different salinity levels, with emphasis on growth, pigment concentration, and desalination potential. It was found that among the 21 salinity levels, salinity 75 produced consistently favorable results in cell count (13.08 x 10³ ± 1.41 x 10³ cells/mL), dry biomass (2.46 ± 0.06 g/L), pigment content (chlorophyll a = 97.5 ± 0.1 µg/L, chlorophyll b = 123.6 ± 0.3 µg/L), and desalination (9.32 ± 0.47 reduction). Therefore, salinity 75 was selected for the final trial (scale-up), which revealed unanticipatedly high cell counts (58.96 x 10³ ± 535.22 cells/mL), with dry biomass weight being statistically different (higher) than the expected (4.21 ± 0.02 g/L) (p<0.0001), most likely due to high cell count and energy reserve storage for high salinity adaption in the form of bio-compounds. Pigment growth continued (chlorophyll a = 95.4 ± 2.2 µg/L, chlorophyll b = 128.1 ± 5.1 µg/L), indicating pigment production under salt stress. Notably, desalination did not occur in this stage, possibly due to the necessity for a bigger initial inoculate, prolonged exposure or bioaccumulation becoming the prevailing mechanism over desalination. Nevertheless, the trial highlights D. salina's strong adaptation to various salinity levels. This suggests a promising future in halophyte research, particularly in understanding the mechanisms that prevent salt accumulation in cells and how to overcome this barrier. Additionally, these results suggest that microalgae could be a viable resource in saline-rich environments unsuitable for conventional agriculture, promoting industrial adaptation to adverse conditions.

A macro network loading Model for multi-flow lines, time-varying and pedestrian congestion is proposed. The station hub is abstracted as a network of different types of nodes, and the flow of passengers at each node is calculated in real time for the purpose of simulating the hub's collection and distribution process. For correct transmission of passenger flow on heterogeneous networks, three types of indexes are proposed to distinguish the nodes, and then match the corresponding fundamental diagrams. This paper divides the update process of the dynamic network loading model into multiple processes by flow lines, and improves computational speed of DNL model. The proposed model is applied to the simulation of passenger flow collection and distribution in an actual hub station with multi-flow lines. The analysis results illustrate that the model can accurately reflect the realistic congestion facilities and explain the formation process of high-density areas. A rolling passenger flow control model based on optimal control theory is proposed. The effectiveness of the control model is verified based on simulation data.

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

A set of polymer composite bolted T-joints with novel configuration consisting of internal skeleton and external skin was fabricated using a prepreg-RTM co-curing molding process. Experiments were conducted to study their mechanical properties under bending load. A finite element model with a polymer resin area between the skin and skeleton was established and verified by the experimental results. Then, the damage propagation process and failure mechanism of the joint and the influence of three factors related to the layer characteristics of the skin and skeleton were investigated by the validated models. The results show that the bending stiffness and the yield limit load of the novel composite T-joint are 0.81 times and 1.65 times that of the 2A12 aluminum T-joint respectively, while at only 55.4% of its weight. The damage of the joint initiates within the resin area and leads to a degradation of the joint bending performances. The preferred stacking sequence of the skeleton is [0/+45/90/-45]ns when primarily subjected to bending loads. The decrease in bending performances is within 5% with the inclining angle of the skeleton less than 12 degrees. The more layers of 90° in the skin, the better bending performances of the joints, while the more layer of 0°, the poorer bending performances.

To solve the problem of smooth switching between car-following model and lane-changing model, the Intelligent Driver Model (IDM) for a single lane was used to study the driver's behavior switching mechanism of normally following, generating intentions to change lanes, creating space and speed gains, and performing lane change. In the case of sufficient lane-changing space and speed gains, the ego vehicle's intention to change lane was considered to solve the switching boundary between car-following behavior and lane-changing behavior, which is also the IDM failure point. In the event that there is no lane-changing gains, the IDM was optimized by incorporating the constraint components of the target lane vehicles in conjunction with the actual motion state of the ego vehicle, and the Stepless Switching Intelligent Driver Model (SSIDM) was constructed. Drivers' natural driving information was collected and scenario mining was performed on structured roads. On the basis of the collected data, an elliptic equation was used to fit the behavior switching boundary, and the two component balance coefficients of the front and rear vehicles on the target lane were identified. According to the test set verification results, the Mean Square Error (MSE) of the SSIDM is 2.172, which is 57.98% less than that of the conventional single-lane IDM. The SSIDM can accomplish stepless switching comparable to driver's behavior between the car-following behavior and the lane-changing behavior, with greater precision than IDM.

Purpose: The treatment of renal fibrosis caused by long-term obstructive nephropathy is limited. The purpose of this study was to establish a mouse model of renal fibrosis with unilateral ureteral obstruction (UUO) and to treat it with exosomes derived from SIRT6 transfected urine-derived stem cells (USCs), which will determine whether exosomes have the effect of anti-fibrosis Methods: The renal fibrosis model of UUO mice was established by ligating unilateral ureter. USCs were extracted from human urine and transfected with SIRT6 lentivirus plasmid. The SIRT6-USCs-exosomes(SIRT6-USCs-exos) were collected and identified by transmission electron microscope, nanoparticle tracking analysis and western blot. SIRT6-USCs-exos were injected into the tail vein of mice and the renal tissue of mice was stained with HE. The relative gene expressions of α-SMA, E-cadherin and TGF-β1 were analyzed by RT-qPCR. Results: In this study, we successfully constructed the renal fibrosis model of UUO mice and hUSCs with overexpression of SIRT6. The SIRT6-USCs-exos significantly improved the renal fibrosis in UUO mice. The relative mRNA expressions of fibrosis-related genes α-SMA, E-cadherin and TGF-β1 in renal tissue were significantly down-regulated after SIRT6-USCs-exos treatment. Conclusion: Our results indicate that SIRT6-USCs-exos can effectively alleviate renal fibrosis caused by long-term obstructive nephropathy. The findings may be promising for dealing with renal fibrosis.

It has been well known that the exponential distribution is the only continuous distribution that has the memoryless property. Here, we observe that, if the exponential distribution dominates an economy as a probability distribution of income acquisition, then the memoryless property imposes equal opportunities on agents in this economy to acquire earnings. Based on this observation, we propose to identify the emergence of an exponential income distribution as a potential necessary condition for guaranteeing the equality of opportunity. Together with other conditions (such as social and economic mobility), it would promote equal opportunities for income acquisition among citizens. Empirically, we employ the latest data available from four representative market-economy countries (the United Kingdom, the United States, Canada, and China) to demonstrate that the exponential distribution is a stylized feature of the income structure of the low- and middle-income class, which occupies the great majority of populations. By contrast, the top income classes in these countries obey the Pareto distribution. To validate the relationship between exponential distribution and equal opportunity, we empirically show how the income structure of the low- and middle-income class in China (from 1978 to 2015) evolved towards an exponential distribution after the market-oriented economic reformation.

Prior studies have focused on the overall behavior of randomly moving particle swarms. However, the characteristics of the stochastic-constrained particles that form ubiquitously within these swarms remain oblivious. This study demonstrates a generalized diffusion equation for stochastic-constrained particles that considers the velocity and location aggregation effects observed from their parent particle swarm (i.e., a completely random particle swarm). This equation can be approximated as the form of Schr\"odinger equation in the microcosmic case (low relative density) and describe the dynamics of the total mass distribution in the macrocosmic case (high relative density). The predicted density distribution of the particle swarm in the stable aggregation state is consistent with the total mass distribution of massive, relaxed galaxy clusters (at least in the range of r < r_s), preventing cuspy problems in the empirical Navarro-Frenk-White (NFW) profile. This study opens a window to observe the dynamics of stochastic-constrained particles from a third perspective, from which the aggregation effect of particles without gravitation can be saw.

Background Cancer is one of the most concerning public health issues in the world. One of cancer hallmarks wildly accepted is sustaining proliferative signaling, which involved most of the cell cycle biological activities. Centromeric histone, Centromere Protein A (CENPA), a variant of canonical histone H3, plays an essential role in selective chromosome segregation in the cell cycle. However, so far, a systematic pan-cancer bioinformatic analysis has not been done yet. Methods We accessed genome, transcriptome, and clinical information from open databases. The genetic alteration, mRNA expression, functional enrichment, stemness, mutation association, expression in cell populations and cellular locations, cell cycle association, survival association of CENPA, and immune association were analyzed. A prognostic model for glioma patients was constructed as an example application of CENPA as a biomarker. Drugs targeting CENPA in cancer cells were also screened and predicted by the CENPA correlation of drug sensitivity and protein-ligand docking. Results CENPA had low gene mutation in cancers. CENPA was overexpressed in almost all cancer types in TCGA compared to their normal control. CENPA was highly expressed in the nucleus of malignant cells. CENPA was associated with the cell cycle of cancer cells. CENPA is a biomarker for the cell cycle G2 phase in cancer cells. CENPA was a diagnostic and prognostic biomarker across multiple cancer types. The prognosis of glioma with CENPA was reliable and can be applied with other prognostic factors. CENPA was associated with the immune microenvironment. Drugs CD-437, 3-Cl-AHPC, Trametinib, BI-2536, and GSK461364 were predicted to target CENPA in cancer cells. Conclusion CENPA was a cell cycle biomarker in cancers with diagnostic and prognostic value.

Although Eulerian approaches are standard in computational acoustics, they are less effective for certain classes of problems like bubble acoustics and combustion noise. A different approach for solving acoustic problems is to compute with individual particles following particle motion. In this paper, a Lagrangian approach to model sound propagation in moving fluid is presented and implemented numerically, using three meshfree methods to solve the Lagrangian acoustic perturbation equations (LAPE) in the time domain. The LAPE split the fluid dynamic equations into a set of hydrodynamic equations for the motion of fluid particles and perturbation equations for the acoustic quantities corresponding to each fluid particle. Then, three meshfree methods, the smoothed particle hydrodynamics (SPH) method, the corrective smoothed particle (CSP) method, and the generalized finite difference (GFD) method, are introduced to solve the LAPE and the linearized LAPE (LLAPE). The SPH and CSP methods are widely used meshfree methods, while the GFD method based on the Taylor series expansion can be easily extended to higher orders. Applications to modeling sound propagation in steady or unsteady fluids in motion are outlined, treating a number of different cases in one and two space dimensions. A comparison of the LAPE and the LLAPE using the three meshfree methods is also presented. The Lagrangian approach shows good agreement with exact solutions. The comparison indicates that the CSP and GFD method exhibit convergence in cases with different background flow. The GFD method is more accurate, while the CSP method can handle higher Courant numbers.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

The dilatometer curves of continuous cooling transformation of 12Mn steel were measured with Formastor-FⅡthermal mechanical simulator．The steel's undercooled austenite phase continuous cooling transformation curves ( CCT curves) were established by means of the dilatometer method and the metallographic-hardness measurement method． The effect of cooling rate on microstructure and hardness of the steel was studied． CCT curve of test steel was simulated by JMatPro. The results show that the Ac1 and Ac3 of the experimental steel are 692 ℃ and 855 ℃ ; the microstructure obtained is made of ferrite，pearlite and bainite．The ferrite transformation and pearlite transformation occur at a slower cooling rate，in which the ferrite is dominant. When the cooling rate is greater than 4.25 ℃ / s bainite transformation happens．As the cooling rate increases，microstructure or grains become finer．The hardness of the tested steel with increasing cooling rate shows a trend of first fast increase and soon decrease．The simulation results are consistent with the measured CCT law. The high temperature mechanical properties of 12mn steel round billet were tested by gleeble-1500d thermal / mechanical simulator. The tensile strength, reduction of area and stress-strain curves of the billet were obtained in the range of 600-1300 ℃.

Compared with conventional methods of fault diagnosis for power transformers, which have defects such as imperfect encoding and too absolute encoding boundaries, this paper systematically discusses various intelligent approaches applied in fault diagnosis and decision making for large oil-immersed power transformers based on dissolved gas analysis (DGA), including expert system (EPS), artificial neural network (ANN), fuzzy theory, rough sets theory (RST), grey system theory (GST), swarm intelligence (SI) algorithms, data mining technology, machine learning (ML), and other intelligent diagnosis tools, and summarizes existing problems and solutions. From this survey, it is found that a single intelligent approach for fault diagnosis can only reflect operation status of the transformer in one particular aspect, causing various degrees of shortcomings that cannot be resolved effectively. Combined with the current research status in this field, the problems that must be addressed in DGA-based transformer fault diagnosis are identified, and the prospects for future development trends and research directions are outlined. This contribution presents a detailed and systematic survey on various intelligent approaches to faults diagnosing and decisions making of the power transformer, in which their merits and demerits are thoroughly investigated, as well as their improvement schemes and future development trends are proposed. Moreover, this paper concludes that a variety of intelligent algorithms should be combined for mutual complementation to form a hybrid fault diagnosis network, such that avoiding these algorithms falling into a local optimum. Moreover, it is necessary to improve the detection instruments so as to acquire reasonable characteristic gas data samples. The research summary, empirical generalization and analysis of predicament in this paper provide some thoughts and suggestions for the research of complex power grid in the new environment, as well as references and guidance for researchers to choose optimal approach to achieve DGA-based fault diagnosis and decision of the large oil-immersed power transformers in preventive electrical tests.

Under the development mode of deep blending of emerging technologies, major projects are important for enhancing China's comprehensive national strength and independent innovation capability. Based on the social benefits of major projects, and considering the influence of reputation factors, an evolutionary game model composed of a general contractor and subcontractor of major projects is established. This paper studies the influence of various factors including the income distribution coefficient of collaborative innovation, and MATLAB simulation software is analyzed the influence of factors on an evolutionary path. The results show that a reasonable income distribution coefficient can promote the game behavior of both parties to the direction of active collaborative innovation; The reduction of innovation cost and the improvement of spillover technology absorption capacity can make innovation subjects tend to choose active collaborative innovation strategies. In addition, reputation loss above a specific threshold can effectively inhibit free-riding behavior and encourage innovation subjects to choose active collaborative innovation strategies. The research results provide reference for promoting major projects' technology innovation.

Background: Diabetic retinopathy (DR) is one of the most prominent pathological microvascular complications in diabetes. A series of studies reported that vitamin D deficiency was associated with increased prevalence of retinopathy in diabetic patients but the results were inconsistent. In this study we focused on evaluating the relationship between vitamin D deficiency and DR by conducting a meta-analysis of observational studies. Methods: Systematic computerized searches were performed in PubMed, MEDLINE, and the Cochrane Library for relevant original articles till November 20, 2016. The pooled odds ratios (ORs) with corresponding confidence intervals (CIs) were calculated to assess the associated value of vitamin D deficiency to the risk of DR. 9 studies including 6332 participants were subjected to final analysis. Results: The results indicated that vitamin D deficiency increases the risk of DR (OR = 1.57, 95% CI 1.32-1.87) with a little heterogeneity (I2 = 23%). In addition, the subgroup analysis demonstrated that there were obvious heterogeneities in T2DM (I2 = 47.8%). Sensitivity analysis showed that the results were relatively stable and reliable. Conclusion: our meta-analysis demonstrated that vitamin D deficiency could increase the risk of DR.

The Doppler band compensated by the keystone transform (KT) is limited. Therefore, it needs to be used in conjunction with the Doppler ambiguity compensation function to correct the range migration (RM) caused by maneuvering targets with Doppler ambiguity. However, the KT implemented by sinc interpolation suffers from significant performance loss at boundaries of compensation Doppler bands. Additionally, in a multi-target scenario, KT implementation methods occupy high complexity when the Doppler range of targets spans over two compensation Doppler bands. To address aforementioned issues, this study presents a variable Doppler starting point keystone transform (VDSPKT) method, where a new form of ambiguity compensation function is constructed, turning the Doppler starting point of the compensation band in KT variable. Firstly, the position of the compensation Doppler band is changed from fixed to adjustable as needed, enhancing the flexibility of KT. Crucially, the connection points of the compensation Doppler bands in sinc interpolation are reset, avoiding the performance loss at their boundaries. Also, the compensation band is adjusted to cover the narrow Doppler frequency range caused by targets, significantly improving the computational efficiency. Finally, the simulation results demonstrate that the proposed approach effectively addresses the performance degradation and high computational complexity of KT in the aforementioned scenarios, resulting in a computational load reduced by approximately 50% compared to traditional methods.

Large-scale volumetric fracturing is generally used during shale gas development. The return rate of fracturing fluid is low, and a large amount of slickwater will be retained in the reservoir. The adsorption and desorption of partially hydrolyzed polyacrylamide (HPAM), an additive commonly used in slickwater, on the surface of shale was studied using Longmaxi Shale from the Sichuan Basin. The experimental results showed that the mass ratio of the HPAM solution to shale reached saturation adsorption at 20:1 when the concentration of HPAM solution was 1000 mg/L and 25:1 when the concentration of HPAM solution was 500 mg/L. The mass ratio of the HPAM solution to shale was fixed at 25:1, and the adsorption equilibrium was reached at a HPAM concentration of 1000 mg/L when the aqueous solution temperature was 30°C and 800 mg/L when the aqueous solution temperature was 60°C. The Langmuir adsorption model yielded a better fit than the Freundlich adsorption model. The adsorption equilibrium time at 30°C was at 60 min for a HPAM concentration of 500 mg/L, while for a concentration of 1000 mg/L, it was at 90 min. The adsorption equilibrium time at 60°C was 40 min for a HPAM concentration of 500 mg/L, whereas it was 60 min for a HPAM concentration at 1000 mg/L. The pseudo-second order kinetics model yielded better fits than the pseudo-first order kinetics model. The adsorption of HPAM on shale was strong, and the adsorbed HPAM resembled cobwebs adhering to the shale surface. HPAM on the surface of shale after adsorption could resist the desorption capacity of water. However, when the amount of adsorbed HPAM on shale increased significantly, the amount of residual HPAM on the surface of the shale decreased rapidly during desorption in deionized water. The desorption of HPAM on the shale surface followed a modified desorption model. The higher the concentration of HPAM adsorbed on the shale surface was, the easier it was to desorb, the easier it was to be removed from the shale.

Unpaid family caregivers might suffer losses in income as a result of care provision. Here we used data from the baseline survey of the China Health and Retirement Longitudinal Study to assess the relationship between hours of weekly caregiving provided to grandchildren/parents/parents-in-law and individual’s monthly employment income. Our study sample comprised 3,718 middle-aged Chinese adults who were of working age (45-60 years). For women and men separately, we used a likelihood-based method to determine a caregiving threshold in a two-stage Heckman selection procedure. Instrumental variables were used to rule out the endogeneity of caregiving hours. Our analysis revealed a negative association between caregiving and income for women that depended on a caregiving threshold of 63-hours per week. There was an absence of caregiving-income relationship among men. These results offer new insights into the opportunity costs of unpaid caregiving and support tailored policies to protect the financial well-being of female caregivers.

InGaN-based red micro light-emitting diodes (µLEDs) of different sizes prepared in this work. The red GaN epilayers were grown on a 4-inch sapphire substrate through metal organic chemical vapor deposition (MOCVD). Etching, sidewall treatment, and p- and n- contact deposition was involved in the fabrication process. Initially, the etching process would cause undesirable damages to the GaN sidewalls, which leads to an increase in leakage current. Hence, we employed KOH wet treatment to rectify the defects on the sidewalls and conducted a comparative and systematic analysis on electrical as well as optical properties. We observed that the µLEDs with a size of 5µm exhibited substantial leakage current, which was effectively mitigated by the application of KOH wet treatment. In terms of optical performance, the arrays with KOH demonstrated improved Light Output Power (LOP). Additionally, while photoelectric performance exhibited a decline with increasing current density, the devices treated with KOH consistently outperformed their counterparts in terms of optoelectronic efficiency. It is noteworthy that the optimized devices displayed enhanced photoelectric characteristics without significantly altering their original peak wavelength and FWHM. Our findings point to the elimination of surface non-radiative recombination by KOH wet treatment, thereby enhancing the performance of small-sized red µLEDs which has significant potential in realizing full-color micro-displays in near-eye projection applications.

Robotic systems have been widely used in various industries, so the security of communication between robots and their components has become an issue that needs to be focused on. As a framework for developing robotic systems, the security of ROS2 can directly affect the security of the upper-level robotic systems. Therefore, it is a worthwhile research topic to detect and analyze the security of ROS2. In this paper, we adopt a formal approach to analyze the security of the communication mechanism of ROS2. First, we use a state transition system to model the potential vulnerabilities of ROS2 based on the ROS2 communication mechanism and the basic process of penetration testing. Secondly, we introduce the CIA model on the basis of the established vulnerability model and use LTL to define its security properties. Then, we design and implement a vulnerability detection tool for ROS2 applications based on the vulnerability model and security properties. Finally, we experimentally test some ROS2-based applications, and the results show that ROS2 has vulnerabilities without additional protection safeguards.

As hematite ores become lower in grade, finer in grain size, and more complex in compositions, their beneficiation by froth flotation to produce the high Fe grade concentrate has become increasingly more difficult. A systematic and in-depth process mineralogy study based on the multi-element chemical and MLA analysis combined with other characterization techniques was conducted to explore the fundamental reasons for difficulties in refractory hematite flotation separation. The results show that the valuable mineral in the sample was mainly hematite and gangue mineral was primarily quartz. Hematite had a fine particle size distributed over a range of 0~45 μm with a degree of mineral liberation of 90.19%. The particle size of quartz was relatively coarse and was mainly distributed in the range of 20~150 μm with a liberation degree of only 67.72%. Unliberated quartz was mainly associated with hematite and the composite particle content was 36.44%. The rougher flotation tests produced a flotation concentrate of 66.71% TFe grade at a recovery of 65.47%. The screening analysis results with rougher flotation products indicated that the main reasons for the poor performance of rougher flotation were the serious entrainment of fine hematite particles and the difficulty in effective collection of coarse low-grade composite particles. Possible approaches for improving hematite flotation performance have been proposed based on the results from this study.

The propagation of electromagnetic waves beyond the line of sight can be caused by atmospheric ducts, which are a significant concerns in the fields of radar and communication. This paper utilizes data from seven automatic stations and five radio-sounding stations to statistically analyze the characteristics of the atmospheric ducts in the northwest region of the South China Sea (SCS). After verifying the practicality of numerical analysis data from NCEP CFSv2 and ERA5 in studying atmospheric ducts using measured data, we analyzed the space-time distribution characteristics of the height of the regional evaporation duct and the bottom height of the elevated duct. Using the parabolic equation model, we simulated electromagnetic propagation loss under different frequencies and radiation elevation angles in both uniform and non-uniform duct environments within a typical atmospheric duct structure. The study found that the NCEP CFSv2 data accurately captures the evaporation duct height and duct occurrence rate in the study area, and the elevated duct bottom height obtained from the inversion of ERA5 and the measured data has a good consistency. The occurrence rate and height of evaporation duct in coastal stations in the northwest of the SCS vary significantly by month, demonstrating clear monthly distribution patterns. Conversely, changes in the Xisha station are minimal, indicating good temporal uniformity. For lower atmospheric ducts, the difference in occurrence rates between 00:00 and 12:00 (UTC) is negligible. The occurrence probability of elevated ducts in the Beibu Gulf area is relatively high, mainly concentrated from January to April, and the Xisha area is dominated by surface ducts without foundation layer, mainly concentrated from June to August. The monsoon plays a critical role in the generation and evolution of atmospheric ducts in the northwest of the SCS, with the height of the evaporation duct increasing and the bottom height of the elevated duct decreasing after the onset of the summer monsoon. Electromagnetic propagation simulations demonstrate that higher frequency and lower elevation angles of radiation sources in the trapping layer of the evaporation duct make it easier to be trapped. As the evaporation duct height decreases, the amplitude of the "sinusoidal fluctuation" of the propagation loss also decreases. Frequency changes of the radiation source in the surface duct environment have minimal impact on electromagnetic propagation loss, but the elevation angle of the radiation source is a critical factor. The frequency of the "sinusoidal fluctuation" in propagation loss is higher in a hybrid duct environment compared to a uniform surface duct. Additionally, the propagation loss increases faster with distance at the height of the evaporation duct, resulting in greater electromagnetic propagation loss.

A (2,6)-fullerene F is a 2-connected cubic planar graph whose faces are only 2-length and 6-length. Furthermore, it consists of exactly three 2-length faces by Euler's formula. The (2,6)-fullerene comes from Do\v{s}li\'{c}'s (k,6)-fullerene, a 2-connected 3-regular plane graph with only k-length faces and hexagons. Do\v{s}li\'{c} showed that the (k,6)-fullerenes only exist for k = 2, 3, 4 or 5, and some of the structural properties of (k,6)-fullerene for k = 3, 4 or 5 are studied. In this paper, we study the properties of (2,6)-fullerene. We obtain that the edge-connectivity of (2,6)-fullerenes is 2. Every (2,6)-fullerene is 1-extendable, but not 2-extendable. F is said to be k- resonant (k>0) if the deleting of any i (0=< i<= k) disjoint even faces of F results in a graph with at least one perfect matching. We have that every (2,6)-fullerene is 1-resonant. An edge set S of F is called an anti-Kekule set if F-S is connected and has no perfect matchings, where F-S denotes the subgraph obtained by deleting all edges in S from F. The anti-Kekule number of F, denoted by ak(F), is the cardinality of a smallest anti-Kekule set of F. We have that every (2,6)-fullerene F with |V(F)|>6 has anti-Kekule number 4. Further we mainly prove that there exists a (2,6)-fullerene F having f_{F} hexagonal faces, where f_{F} is related to the two parameters n, m.

Unpaid family caregivers must consider the economic trade-off between caregiving and paid employment. Prior literature has suggested labour force participation (LFP) to decline with caregiving intensity, but no study has evaluated this relationship by accounting for the presence of both kinks and discontinuities. Here we used respondents of the China Health and Retirement Longitudinal Study baseline survey who were non-farming, of working-age (aged 45-60) and had a young grandchild and/or a parent/parent-in-law. For women and men separately, a caregiving threshold-adjusted probit model was used to assess the association between LFP and weekly unpaid caregiving hours. Instrumental variables were used to rule out the endogeneity of caregiving hours. Of the 3,718 respondents in the analysis, for men, LFP was significantly and inversely associated with caregiving that involved neither discontinuities nor kinks. For women, a kink was identified at the caregiving threshold of 8 hours per week such that before 8 hours, each caregiving hour was associated with an increase of 0.0257 in the marginal probability of LFP, but each hour thereafter was associated with a reduction of 0.0014 in the marginal probability of LFP. These results have implications for interventions that simultaneously advance policies of health, social care and labour force.

Inside hippocampal circuits, neuroplasticity events that individual cells may undergo during synaptic transmissions occur in the form of Long Term Potentiation (LTP) and Long Term Depression (LTD). The high density of NMDA receptors expressed on the surface of the dendritic CA1 spines confers to hippocampal CA3-CA1 synapses, the ability to easily undergo NMDA-mediated LTP and LTD, that is essential for some forms of explicit learning in mammals. Providing a comprehensive kinetic model that can be used for running computer simulations of the synaptic transmission process is currently a major challenge. Here, we propose a compartmentalized kinetic model for CA3-CA1 synaptic transmission. Our major goal was to tune our model in order to predict the functional impact caused by disease associated variants of NMDA receptors related to severe cognitive impairment. Indeed, for variants Glu413Gly and Cys461Phe, our model predicts negative shifts in the glutamate affinity and changes in the kinetic behavior, consistent with experimental data. These results pinpoint to the predictive power of this multiscale viewpoint, which aims to integrate the quantitative kinetic description of large interaction networks typical of system biology approaches with a focus on the quality of few, key, molecular interactions typical of structural biology ones.

The economic, social and environmental benefits generated by the use of urban public transportation infrastructure constitute a complex dynamic urban public transportation infrastructure utilization benefit system. This paper evaluates the coupling coordination among these three benefits taking four Chinese autonomous municipalities as an example. These four cities have large-scale urban public transportation infrastructures but their utilization has many serious problems. The basic function of urban public transportation infrastructure has not been fully played in these cities. Whether the different benefits of urban public transportation infrastructure have been developed in harmony or not is unclear. We analyzed the coordinated development among three benefits by constructing coupling coordination degree model and used Gini coefficient to study the difference of coordinated development among three benefits of four cities. The result shows that the levels of coordinated development among three benefits of urban public transportation infrastructure were lower in these four cities and have positive correlation with it of urban public transportation infrastructure utilization benefit. Raising the level of urban public transportation infrastructure utilization benefit is the most crucial solution of promoting the coordinated development among three benefits.

In recent years, the Chinese government pays more and more attention to agricultural development and ecological protection. While improving the cultivated land green use efficiency(CLGUE) is the key to promote the sustainable development of agriculture. This study aims to study the current situation and influencing factors of agricultural production from the perspective of green utilization efficiency of cultivated land. It takes 39 cities in the upper, middle and lower reaches of the Yangtze River basin in China as an example. The CLGUE values in those 39 cities from 2011 to 2020 were specifically measured, using the Super-SBM model, kernel density estimation and geographic detector method. Their temporal and spatial heterogeneity was described, and the influencing factors were detected at both single and interactive levels. The results showed that: （1）From 2011 to 2020, the green utilization efficiency value of cultivated land in the Yangtze River Basin showed an upward trend on the whole; （2）There is a clear spatial heterogeneity the CLGUE values in the Yangtze River Basin cities, as shown by: downstream region > midstream region > upstream region; (3) Cultivated land resource endowment, socioeconomic development, and agricultural production technology are important factors affecting the variability of CLGUE values. However, there are some differences in the degree and direction of influence of different influencing factors on different sample subgroups.

In this study, we discuss the thermospheric density response to the solar activity and QBO. By using the wavelet power spectrum method, the thermospheric density from 1967 to 2013 shows ~11-year period, semiannual and annual variations, while the seasonal variation is usually more significant under high solar activity conditions. Importantly, we investigate the possible link between the density and the QBO, with the aid of GAMDM model and different density residual method. As a result, the difference between the measured density and empirical model seemingly has QBO signal, but the ratio of them revels that the QBO signal does not exist in the thermospheric density. Comprehensively, we thought the stratospheric QBO cannot impact on the thermosphere, and more data and numerical modeling are needed for further validation.

Achieving eco-efficiency in agriculture production at low environmental costs is key to sustainable agriculture. Using the DEA-SBM model, this study evaluated the agricultural eco-efficiency of the 77 counties and districts in China’s Jiangsu province from 1999 to 2018 and analyzed its spatio-temporal evolution pattern and influencing factors. The mains conclusions were as follows: (1) The overall agricultural eco-efficiency and its decomposition terms, pure technology efficiency and scale efficiency, exhibited a fluctuating downward trend. The regional inequality in agricultural eco-efficiency had been widening and exhibited a strong positive spatial association. (2) The agricultural eco-efficiency in Jiangsu province presented a “high south and low north” spatial pattern. High-level agricultural eco-efficiency areas were in the Taihu Plain in Sunan, while low-level agricultural eco-efficiency zones are distributed across Subei City. The High-High-type spatial association pattern is concentrated in the Suzhou-Wuxi-Changzhou region, while the Low-Low areas are mainly in the coastal regions of Subei and Suzhong. (3) The spatial pattern of PTE and SE generally exhibited a “high south and low north” distribution. Areas with positive growth in agricultural eco-efficiency, PTE, and SE, were situated in Xuzhou, Nanjing city, and the bordering regions between Yangzhou and Huai’an, and Changzhou and Wuxi. (4) The excessive redundant use and application of pesticides, chemical fertilizer, agricultural diesel, labor, land, and agricultural carbon emission have been the primary factor affecting Jiangsu's agricultural eco-efficiency. Irrigation had also signficantly impacted agricultural eco-efficiency, while mechanical power and agricultural film had minimal effect. The majority of counties and districts in Subei, Suzhong, and Ningzhen Yang Hilly region have issues regarding their excessive usage of chemical fertilizer, pesticide, chemical fertilizer, agricultural diesel, labor, and land. The findings of this study can contribute towards a better understanding of agricultural eco-efficiency and spatial association effect and can help policymakers increase agricultural eco-efficiency.

Meshfree particle method, which is always regarded as a pure Lagrangian approach, is easily represented complicated domain topologies, moving boundaries, and multiphase media. Solving acoustic problems with the mesfree particle method forms a branch of the acoustic wave modeling field, namely, particle-based computational acoustics (PCA). The aim of this paper is to improve the accuracy of using the PCA method to solve two-dimensional acoustic problems, and realize the particle representation with a hybrid meshfree and finite-difference time-domain (FDTD) method for acoustic boundary conditions at both the plane and curved surface. As a widely used Lagrangian meshfree method, the smoothed particle hydrodynamics (SPH) based on the support domain and the kernel function has developed rapidly in recent years. The traditional SPH method is easily implements parallel processing and has been applied in sound wave simulation. As a corrective method with higher accuracy than SPH, the acoustic propagation and scattering in the time domain is simulated with the corrective smoothed particle method (CSPM). Moreover, a hybrid meshfree-FDTD boundary treatment technique is utilized to represent different acoustic boundaries in the Lagrangian approach. In this boundary treatment technique, the parameter value of virtual particles is obtained with the FDTD method, which concerns truncation errors based on the Tayler series expansion. Soft, rigid, and Mur’s absorbing boundary conditions are developed to simulate sound waves in finite and infinite domain. Results of modeling acoustic propagation and scattering show that CSPM is accurate and convergence with exact solutions, and different acoustic boundaries are validated to be effective in the computation.

This research provides a computationally efficient numerical tool for predicting 3-D turbulent flows over hydrofoils. It addresses a gap in existing numerical methods by extending the capabilities of the laminar VIScous Vorticity Equation (VISVE) solver to handle 3-D turbulent flow scenarios. The implementation integrates the k − ω SST model into the 3-D VISVE solver using the Finite Volume Method (FVM), extending its capability to handle turbulent flows. The turbulence model is also parallelized to improve computational efficiency. The application of the newly developed model to 3-D hydrofoil cases expands its scope and serves as preparatory work for future rotational propeller applications. Rigorous testing includes a convergence analysis concerning grid numbers and time step sizes, and validation against a Reynolds-Averaged Navier-Stokes (RANS) solver ensures the reliability and accuracy of the enhanced VISVE solver for turbulent flow simulations. The turbulent VISVE solver offers advantages such as reduced computational domain and costs through a vorticity-based approach. Turbulence concentration within boundary layers and free shear flows does not compromise the advantages of the small computational domain. The simplified meshing process, automatically generated by denoting the number of panels on the hydrofoil, makes the solver accessible for researchers and engineers.

The ZX Spectrum was a popular 8-bit home computer by Sinclair Research in the 80s. Even though some of these computers may still work, the audio tapes, the TV with an analog tuner and the micro-switch joystick, used with the original ZX Spectrum, nowadays are outdated and hard to find in good working order or replicate. Since many other old closed systems are also very difficult to update to support modern peripherals, there is a necessity to provide a methodology to adapt such systems to support new peripherals while being compatible with existing software. The work proposed in this paper is focused on recreating a ZX Spectrum+/48k computer and interface it with modern peripherals on an FPGA. This is accomplished by adding a co-processor to assist with the control of the new peripherals which would either require to complex architectural changes to the original system and in the end it would perform poorly due to the low performance of the Z80 CPU. This work distances from previous ones on emulating a ZX Spectrum since it focuses on the use of different upgraded peripherals and the use of a NIOS II soft-processor as a co-processor to manage the SD Card accesses. A demonstration of the proposed modernized architecture was made by successfully running a diagnostics ROM and playing original ZX Spectrum games from an SD card for game with a PS/2 keyboard and a pair of joysticks.

This article explores the relationship between green energy and cryptocurrencies in the sustainable energy finance sector. The research findings contribute to our understanding of the application of green economy practice, enabling investors in financial markets, policymakers, and stakeholders to make informed decisions and develop specific strategies. Adopting the green economy paradigm makes it possible to promote collaboration and innovation by integrating ethical and responsible principles that can improve the overall quality of processes and boost sustainable growth. Cryptocurrencies have been widely used as financial instruments over the last decade. Given the development of the cryptocurrency market and the growing awareness of greener and more energy-efficient tokens, the green economy has become a popular topic for understanding economic and political issues. However, the literature still lacks clear evidence on how cryptocurrencies interact with green energies. Therefore, this study examines the long- and short-term relationships between dirty cryptocurrencies such as Bitcoin (BTC), Ethereum (ETH), clean cryptocurrencies such as Cardano (ADA), Ripple (XRP), Stellar (XLM), and green energies such as ISE Clean Edge Global Wind Energy, S&amp;P Global Clean Energy, S&amp;P TSX Renewable Energy and Clean Technology, Solactive China Clean Energy, in the period from January 2020 to September 2023. The results show that diversification is key, with clean cryptocurrencies such as ADA, XLM and XRP offering diversification opportunities alongside "dirty" cryptocurrencies such as BTC and ETH. Although sustainable energy indices show mixed evidence in the long and short term, they remain relevant for those who focus on clean energy investments. It is also becoming increasingly relevant for investors in sustainable portfolios to assess their environmental impact, especially for energy-intensive cryptocurrencies, and it is advisable to explore sustainable blockchain technologies.

As a stimulus signal, coded electrical signals can control the motion behavior of animals, which has been widely used in the field of animal robots. In current research, most of the stimulus signals used by researchers are traditional waveform, such as square waves. To enrich the stimulus waveform, a wireless animal robot stimulation system based on neuronal electrical signal characteristics is presented in this paper. The stimulator uses the CC1101 wireless module to control animal behavior through brain stimulation. The LabVIEW-based graphical user interface(GUI) can manipulate brain stimulation remotely while the stimulator powered by battery. Additionally, the spikes of animals have been simulated by this system through Direct Digital Synthesizer(DDS) algorithm. The GUI enable users to customize the combination of these analog spike signals. The recombined signals are sent to the stimulator through CC1101 as stimulus signals. In vivo experiments conducted on five pigeons verified the efficacy of the stimulation mechanism. The analog spike signal with an amplitude of 3-5V successfully caused the pigeon’s turning behavior. The feasibility of the analog spike signals as stimulus signals was successfully verified. Increased the diversity of stimulus waveform in the field of animal robots.

The utilization of primary school buildings is multifaceted, primarily due to the high occupancy density, varying thermal preferences among occupants, diverse indoor activities (such as walking, sports, and conversation), and a constant flow of individuals entering and exiting the building. This results in frequent opening and closing of external windows and doors and fluctuations in internal heat gain. Consequently, frequent interactions between the indoor and outdoor microenvironments lead to energy losses. This study conducts a comprehensive literature review on building energy loss stemming from occupant behavior and the interactions between indoor and outdoor microenvironments. Furthermore, it proposes a dynamic real-time monitoring system based on a computer data capture and visualization platform foundation for building energy loss. The research methods include data crawling, data association rule mining, and data association analysis. The research findings yield a universally applicable and informative building energy-saving design theory based on extensive data analysis. Additionally, the system presents information on occupants' behavior and the microclimate data of indoor and outdoor environments on a computer screen, facilitating human-machine communication and enabling timely adjustments to design strategies for new buildings and operation and maintenance strategies for existing buildings.

Policy induced decline of human mobility has been recognised to be effective in controlling the COVID-19 spread especially in the initial stage of the outbreak, although the relationship among mobility, policy implementation, and virus spread remains contentious. Coupling data of confirmed COVID-19 cases with Google mobility data in Australia, we present a state-level empirical study to: 1) inspect the temporal variation of COVID-19 spread and the change of mobility adherent to social restriction policies; 2) examine the extent that different types of mobility are associated with the COVID-19 spread in eight Australian states/territories; and 3) analyse the time-lag effect of mobility restriction on the COVID-19 spread. We find that social restriction policies implemented in the early stage of the pandemic controlled the COVID-19 spread effectively; the restriction of human mobility has a time-lag effect on growth rates, and the strength of the mobility-spread correlation increases up to seven days after policy implementation but decreases afterwards. The association between mobility and COVID-19 spread varies across space and time, and subjects to the types of mobility. Thus, it is important for governments to consider the degree to which lockdown conditions can be eased by accounting for this dynamic mobility-spread relationship.

After sperm enter the female reproductive tract, the physicochemical and biochemical microenvironment undergoes significant changes. Thus, the response of sperm to environmental factors is vital for successful fertilization. The cation channel of sperm (CatSper) is a sperm-specific, pH-sensitive, and Ca2+-permeable ion channel. It is responsible for the predominant Ca2+ entry in mammalian sperm and is involved in nearly every event of sperm to acquire fertilizing capability. CatSper also serves as a pivotal polymodal chemosensor in mammalian sperm by responding to multiple chemical cues. Physiological ligands (such as progesterone, prostaglandins, β-defensins, and odorants) provoke Ca2+ entry into sperm by activating CatSper and thus triggering sperm functions including hyperactivation, capacitation, the acrosome reaction, and chemotaxis. Additionally, synthetic and natural chemicals (such as medicines, endocrine disrupting chemicals, drugs of abuse, and antioxidants) affect sperm functions by regulating CatSper-dependent Ca2+ signaling. Therefore, understanding the interactions between CatSper and extracellular ligands sheds light on the mechanisms underlying male infertility and offers innovative diagnostic and treatment approaches. This underscores the importance of CatSper as a crucial regulatory target in male reproduction, linking sperm function with the extracellular environment. This review comprehensively summarizes the relevant studies describing the environmental factors that affect CatSper in humans and rodents.

Reasonable trajectory planning is the precondition for the parafoil airdrop system to achieve autonomous accurate homing and safe landing. In order to successfully realize the self-homing of the parafoil airdrop system, a new trajectory optimization design scheme is proposed in this paper. The scheme is based on the parafoil's unique flight and control characteristics and adopts a segmented homing design. Compared with the current common trajectory design method, its core feature is to avoid the problem that the straight-line flight distance before landing is limited by the radius of the height-reducing area and ensure landing accuracy and safety. Firstly, the different starting states of the parafoil airdrop system and the landing requirements were comprehensively considered, and the homing trajectory is reasonably segmented. Based on the requirements of energy control, stable flight, and landing accuracy, the optimal objective function of the trajectory was established, and the trajectory parameters, calculation methods, and constraints were given. Secondly, the cuckoo search algorithm was applied to optimize the objective function to obtain the final home trajectory. Finally, the trajectory planning under different airdrop conditions was simulated and verified. The results showed that the planned trajectories could reach the target point accurately and meet the flight direction requirements, proving the proposed scheme's correctness and feasibility.

Given the documented wave-induced damage of elevated coastal decks during extreme natural hazards (e.g. hurricanes) in the last two decades, it is of utmost significance to decipher the wave-structure-interaction of complex deck geometries and quantify the associated loads. Therefore, this study focuses on the assessment of solitary wave impact on open-girder decks that allow the air to escape from the sides. To this end, an arbitrary Lagrangian-Eulerian (ALE) numerical method with a multi-phase compressible formulation is used for the development of three-dimensional hydrodynamic models, which are validated against a large-scale experimental dataset of a coastal deck. Using the validated model as a baseline, a parametric investigation of different deck geometries with a varying number of girders Ng and three different widths, was conducted. The results reveal that the Ng of a superstructure has a complex role and that for small wave heights the horizontal and uplift forces increase with the Ng, while for large waves the opposite happens. If the Ng is small the wave particles accelerate after the initial impact on the offshore girder leading to a more violent slamming on the onshore part of the deck and larger pressures and forces, however, if Ng is large then unsynchronized eddies are formed in each chamber, which dissipate energy and apply out-of-phase pressures that result in multiple but weaker impacts on the deck. The decomposition of the total loads into slamming and quasi-static components, reveals surprisingly consistent trends for all the simulated waves, which facilitates the development of predictive load equations. These new equations, which are a function of Ng and are limited by the ratio of the wavelength to the deck width, provide more accurate predictions than existing empirical methods, and are expected to be useful to both engineers and researchers working towards the development of resilient coastal infrastructure.

Detailed built-up area information is valuable for mapping complex urban environments. Although a large number of classification algorithms about built-up areas have been developed, they are rarely tested from the perspective of feature engineering and feature learning. Therefore we launched a unique investigation to provide a full test of the OLI imagery for 15-m resolution built-up area classification in 2015, in Beijing, China. Training a classifier requires many sample points, and we propose a method based on the ESA's 38-meter global built-up area data of 2014, Open Street Map and MOD13Q1-NDVI to achieve rapid and automatic generation of a large number of sample points. Our aim is to examine the influence of a single pixel and image patch under traditional feature engineering and modern feature learning strategies. In feature engineering, we consider spectra, shape and texture as the input features, and SVM, random forest (RF) and AdaBoost as the classification algorithms. In feature learning, the convolution neural network (CNN) is used as the classification algorithm. In total, 26 built-up land cover maps were produced. Experimental results show that: (1) the approaches based on feature learning are generally better than those based on feature engineering in terms of classification accuracy, and the performance of ensemble classifiers e.g., RF, is comparable to that of CNN. Two dimensional CNN and the 7 neighborhood RF have the highest classification accuracy of nearly 91%. (2) Overall, the classification effect and accuracy based on image patches are better than those based on single pixels. The features that can highlight the information of the target category (for example, PanTex and EMBI) can help improve classification accuracy.

Recent advances in open data initiatives allow us to free access to a vast amount of open LiDAR data in many cities. However, most of these open LiDAR data over cities are acquired by airborne scanning, where the points on façades are sparse or even completely missing due to the viewpoint and object occlusions in the urban environment. Integrating other sources of data, such as ground images, to complete the missing parts is an effective and practical solution. This paper presents an approach for improving open LiDAR data coverage on building façades by using point cloud generated from ground images. A coarse-to-fine strategy is proposed to fuse these two different sources of data. Firstly, the façade point cloud generated from terrestrial images is initially geolocated by matching the SFM camera positions to their GPS meta-information. Next, an improved Coherent Point Drift algorithm with normal consistency is proposed to accurately align building façades to open LiDAR data. The significance of the work resides in the use of 2D overlapping points on the outline of buildings instead of limited 3D overlap between the two point clouds and the achievement to a reliable and precise registration under possible incomplete coverage and ambiguous correspondence. Experiments show that the proposed approach can significantly improve the façades details of buildings in open LiDAR data and improving registration accuracy from up to 10 meters to less than half a meter compared to classic registration methods.

With the great development of intelligent transportation systems (ITS), travel time prediction has attracted the attentions of many researchers and a large number of prediction methods have been developed. However, as an unavoidable topic, the predictability of travel time series is the basic premise for travel time prediction has received less attention than the methodology. Based on the analysis of the complexity of travel time series, this paper defines travel time predictability to express the probability of correct travel time prediction and proposes an entropy-based method to measure the upper bound of travel time predictability. Multiscale entropy is employed to quantify the complexity of travel time series, and the relationships between entropy and the upper bound of travel time predictability are presented. Empirical studies are made with vehicle trajectory data in an express road section. The effectiveness of time scales, tolerance, and series length to entropy and travel time predictability are analysis, and some valuable suggestions about the accuracy of travel time predictability are discussed. Finally, the comparisons between travel time predictability and actual prediction results from two prediction models, ARIMA and BPNN, are conducted. Experimental results demonstrate the validity and reliability of the proposed travel time predictability.

Climate warming profoundly affect vegetative growth, flowering phenology and sexual reproduction of plants, therefore the ornamental value of wild flowers. Despite this, the extent and mechanism of the impact remain unclear. Here, we conducted warming experiment for two growing seasons (1.89 ℃ in 2017 and 2.37 ℃ in 2018 increases) with infrared heaters to examine the effects of warming on ornamental value of wild flower I. oxyanthera, endemic to China, in Mount Emei. We fitted generalized linear mixed models (GLMMs) and generalized linear model (GLM) to examine how warming affected plant morphology and floral traits. We evaluated comprehensive ornamental value based on plant morphology and flowering characteristics using Analytic Hierarchy Process (AHP) and disentangled the impact of the two traits on ornamental value using principal component analysis (PCA) and partial least squares structural equation model (PLS-SEM) under the ambient and warming treatments. Warming decreased significantly plant height and crown width, while increased branch number and single leaf area. Warming also decreased vexillum length, corolla tube length, nectar spur length and pedicel length. In addition, warming shortened flowering duration per plant and reduced flower number, while there was no significant effect on flower longevity, flower color at full-bloom stage between the control and warming treatment. Therefore, comprehensive ornamental value under warming was lower than that under the control. Pedicel length, flower color, flower longevity and flowering duration per plant were the main factors of affecting comprehensive ornamental value. PLS-SEM showed that warming had an indirect negative effect on ornamental value via direct negative effects on flowering traits. Collectively, these results indicate that although promoting vegetative growth, short-term warming decreased significantly ornamental value of I. oxyanthera due to warming-caused smaller flowers and shorter flowering duration.

Lactobacillus plantarum has been observed to play a crucial role in shaping the sensory properties of chili sauce. However, the specific taste-active metabolites responsible for the desirable flavor profile of chili sauce remain inadequately characterized. This study employed a combination of metabolomics and web-based computational tools analysis to investigate the dynamic changes in taste-active metabolites during chili sauce fermentation. Initially, metabolites were rapidly annotated using a feature-based molecular network, leading to the tentative annotation of 206 metabolites, of which a significant proportion had not been previously reported. Subsequently, the VirtualTaste tool identified dihydrosphingosine, lactic acid, isoleucine, phytosphingosine, and gluconic acid as potential taste markers for quality control. Finally, pathway enrichment analysis revealed that these components were primarily associated with amino acid tRNA, phenylalanine, tyrosine, and tryptophan biosynthesis, as well as sphingolipid metabolism. This study provides valuable insights into the mechanisms underlying the formation of the distinctive flavor of chili sauce.

Sracocystis cruzi in cattle (Bos taurus) and Sarcocystis poephagicanis in yaks (Bos grunniens) are morphologically indistinguishable. However, the relationship of the two parasites is still un-clear. Here, muscular tissues of the two domestic animals collected from abattoirs in China were examined for sarcocysts of S. cruzi and S. poephagicanis. The sarcocysts isolated from the samples were processed for light microscopy (LM), transmission electron microscopy (TEM), and DNA analysis. Sarcocysts of S. cruzi and S. poephagicanis were found in 405 of 950 (42.6%) cattle and 304 of 320 (95.0%) yaks, respectively. By LM and TEM, the sarcocysts of the two parasites showed similar morphologically characteristics. The thin-walled sarcocysts had hair-like protrusions on the surface. Ultrastructures exhibited the primary cyst wall contained irregularly folded, hirsute or bone-like protrusions. Four genetic markers, 18S rDNA, 28S rDNA, mitochondrial cox1, and apicoplast rpl6 of the two parasites were sequenced and analyzed. The sequences of the four loci presented an interspecific identity of 97.9−98.6%, 97.2−98.1%, 89.5−90.4%, and 96.9−97.2%, respec-tively. Phylogenetic analysis using 28S rDNA and cox1 sequences indicated that both species were placed into a group encompassing Sarcocystis spp. in ruminants with canid as known or putative definitive hosts. Sarcocystis cruzi and S. poephagicanis should represent separated species, and cox1 and rpl6 was suitable for distinguishing between them.

To investigate the impact of electrode structure on Electrical Stimulation Therapy (EST) for chronic wound healing, this study designed three variants of flexible microelectrodes (FMs) with Ag-Cu coverings (ACCs), each exhibiting distinct geometrical configurations: hexagonal, cross-shaped, and serpentine. These were integrated with PPY@PDA/PANI (3/6) hydrogel dressings. Comprehensive animal studies, coupled with detailed electrical and mechanical modeling and simulations, were conducted to assess their performance. Results indicated that the serpentine-shaped FM outperformed its counterparts in terms of flexibility and safety, exhibiting minimal thermal effects and a reduced risk of burns. Notably, FMs with metal coverings under 3% demonstrated promising potential for optoelectronic self-powering capabilities. Additionally, simulation data highlighted the significant influence of hydrogel non-uniformity on the distribution of electrical properties across the skin surface, providing critical insights for optimizing EST protocols when employing hydrogel dressings.

A Chinese superalloy GH4099 (~20 vol.% γ' phase), which can operate for long periods of time at temperatures of 1173-1273 K, was fabricated by electron beam melting (EBM). Argon gas atomized (AA) and plasma rotation electrode process (PREP) powders with the similar composition and size distribution were used as raw materials for comparison. Microstructure and mechanical properties of both the as-EBMed and post-treated alloy samples were investigated. The results show that the different powder characteristics resulted in the different build temperatures for AA and PREP samples, which were 1253 K and 1373 K, respectively. With increasing the building temperature, the EBM processing window shifted towards the higher scanning speed direction. Furthermore, intergranular cracking was observed for the as-fabricated PREP sample as a result of local enrichment of Si at grain boundaries. The cracks were completely eliminated by hot isostatic pressing (HIPing) and did not re-open during subsequent solution treatment and aging (STA). Fine spherical γ' phase precipitated uniformly after STA. The tensile strength of the HIP+STA samples was ~920 MPa in the building direction and ~850 MPa in the horizontal direction, comparable with that of the wrought alloy.

Brain-stimulation reward, also known as intracranial self-stimulation (ICSS), is a commonly used procedure for studying brain reward function and drug reward. In electrical ICSS, an electrode is surgically implanted into the medial forebrain bundle in the lateral hypothalamus or the ventral tegmental area in the midbrain. Operant lever responding leads to the delivery of electrical pulse stimulation. The alteration in the stimulation frequency-lever response curve is used to evaluate the impact of pharmacological agents on brain reward function. If a test drug induces a leftward or upward shift in the ICSS response curve, it implies a reward-enhancing or abuse-like effect. Conversely, if a drug causes a rightward or downward shift in the functional response curve, it suggests a reward-attenuating or aversive effect. A significant drawback of electrical ICSS is the lack of cellular selectivity in understanding the neural substrates underlying drug reward versus aversion. Excitingly, recent advancements in optical ICSS (oICSS) have facilitated the development of at least three cell type-specific oICSS models – dopamine-, glutamate-, and GABA-dependent oICSS. In these new models, a comparable frequency-rate response curve has been established and employed to study the substrate-specific mechanisms underlying brain reward function and a drug's rewarding versus aversive effects. In this review article, we summarize recent progress in this exciting research area. The findings in these new behavioral models have not only increased our understanding of the neural mechanisms underlying drug reward and addiction but have also introduced a novel experimental approach in preclinical medication development for treating substance use disorders.

Using co-precipitation to synthesize (CeO2)0.95(Y2O3)0.05 (YDC) and solid reaction method to synthesize (CeO2)0.75(ZrO2)0.25 (ZDC), and the characterization for both crystal structure and micro-structure of the two materials was conducted with X-ray diffraction (XRD) and scanning electron microscope (SEM) methods. Prepare the YDC and ZDC based limited current O2 sensor by employing platinum pasting bonding method. Sensing characteristics of the sensor were obtained at different conditions and study on the impact of temperature, O2 concentration as well as water vapor pressure on the sensing characteristics had been conducted. XRD results show that the phase structure of both YDC and ZDC is cubic phase. SEM results show that both YDC and ZDC layers are dense layers, which are then qualified to be the composition materials of the sensor. This limited current O2 sensor shows good sensing performance and conforms to the Knudsen model. Log(IL•T) depends linearly on 1000/T with R2 of 0.9904, IL depends linearly on x(O2) with R2 of 0.9726 and sensing characteristics are not affected by p(H2O).

Base on building information modeling(BIM) plus with Robotic process automation (RPA) technology is rapid development in smart building operations and maintenance (O&M). RPA is a workflow-based automated execution tool that is particularly well suited for replacing manual execution of simple and repetitive tasks using computer systems. The use of RPA technology can saves man-hours and increases productivity, which is important for the automation of building operations and maintenance operations.. The BIM technology, as an advanced technology in the construction industry, it can provide new ideas and methods for building operation and maintenance based on its visualization characteristics. That’s integrating RPA with BIM technology which will enhance the digitalization and virtualization of smart building operation and management. In this article will first introduce the features of RPA and BIM technology and then discuss the technical roadmap for remote automated operation and maintenance of smart building equipment room to implemention a low-cost and high efficient building equipment room operation and maintenance solution.

Considering the significance of thermodynamic cycles in the global energy system, it is necessary to develop new general classes of thermodynamic cycles to relieve current energy and environmental problems. Inspired by the relationship between power cycles and refrigeration cycles, we realize that general classes of thermodynamic cycles should occur in pairs with opposite functions. Here we reverse class 1 heating cycles to obtain another new general class of thermodynamic cycles named class 2 heating cycles (HC-2s). HC-2s have two basic forms, and each contains six thermodynamic processes. HC-2s present the simplest and most general approach to utilizing the temperature difference between a medium-temperature heat source and a low-temperature heat sink to achieve efficient high-temperature heating. HC-2s fill the gaps that have existed since the origin of thermal science, and they will play significant roles in the global sustainable energy system.

Thermodynamic cycles are not only the core concepts of thermal science, but also key approaches to energy conversion and utilization. So far, power cycles and refrigeration cycles have been the only two general classes of thermodynamic cycles. While diverse types of systems have been developed to perform thermodynamic cycles, no new general classes of thermodynamic cycles have been proposed. Based on the basic principles of thermodynamics, here we propose and analyze a new general class of thermodynamic cycles named class 1 heating cycles (HC-1s). Two basic forms of HC-1s are obtained by connecting six essential thermodynamic processes in the proper order and forming a thermodynamic cycle. HC-1s present the simplest and most general approach to utilizing the temperature difference between a high-temperature heat source and a medium-temperature heat sink to achieve efficient medium-temperature heating and/or low-temperature cooling. HC-1s fill the gaps that have existed since the origin of thermal science, and they will play significant roles in energy conservation and emission reduction.

The growing shortage of human resources to manage landscape in the water environment has led to problems concerning preservation of the landscape in Japan. To cultivate people with awareness about preserving the landscape, it is important to understand the process of how a region’s residents develop an attachment toward the water environment in their area. This paper identified factors influencing the attachment of residents toward the Fukushima-gata lagoon, Niigata prefecture, Japan, as a case study while focusing on changes in the lifestyle of the regional residents. The findings are as follows: (1) The target households frequently used Fukushima-gata lagoon for “fishing and for picking edible wild plants” and “gathering reeds to make thatched roofs” before “the reclamation project was carried out by the government in Fukushima-gata lagoon.” They also frequented Fukushima-gata lagoon for “walking and cherry blossom viewing” after “the reclamation project” was implemented. (2) Even the fact that distance from the lagoon to their place of residence increased after the project did not lose their attachment to the lagoon. (3) It was suggested that the project contributed to increase the attachment of regional residents towards Fukushima-gata lagoon because of multiple factors such as “playing in the water,” “livelihood opportunity,” “recreational use,” and so on. (4) Changes in the attachment of regional residents toward Fukushima-gata lagoon before and after the reclamation project was carried out by the government corresponded to “changes in the lifestyle of the local residents” before and after the project.

Pancreatic neuroendocrine tumors (PNETs) are characterized by dysregulated signaling pathways that are crucial for tumor formation and progression. The efficacy of traditional therapies is limited, particularly in treatment of PNETs at advanced stage. Epigenetic alterations profoundly impact the activity of signaling pathways in cancer development, offering potential opportunities for drug development. There is currently a lack of extensive research on epigenetic regulation in PNETs. To fill this gap, we first summarize major signaling events which are involved in PNET development. Then, we discuss the epigenetic regulation of these signaling pathways in the context of both PNET and commonly occurring, and therefore more extensively studied, malignancies. Finally, we will offer perspective on the future research direction of PNET epigenome and its potential applications in patient care.

CoCrFeNiMn high-entropy alloy coatings were prepared on compacted graphite iron（CGI） through plasma cladding to strength the CGI substrate. The effects of heat treatment temperatures and times on the microstructure and mechanical properties of the CoCrFeNiMn coatings were investigated. After heat treatment, a single FCC phase was remained in the coating as compared to the deposited one, with smaller dendrites, larger dendritic spacing and more Cr-rich compounds precipitated between dendrites. The coatings’ microhardness was increased after heat treatment. After heat treated at 660°C for 90 minutes, the coating had the highest microhardness of 563±6.9 HV0.2, the lowest frictional coefficient of 0.71 and the smallest wear mass loss of 1.12 mg, and it had the best wear resistance.

Strangeness flavor is abundant and in chemical equilibrium in the primordial Quark-Gluon Plasma(QGP) filling the early Universe. Upon hadronization near to T=150 MeV one may think that relatively short lived massive strange hadrons decay rapidly and strangeness disappears. However, we show using detailed balance considerations for inverse decay reactions that the back reaction repopulate strangeness keeping it in chemical equilibrium at least to the time when strange antibaryons annihilate near T≃30-50 MeV. However, our present study is focused on the meson sector of the hadronic Universe. Specifically, we establish here the temperature range in which the expansion of the Universe becomes faster compared to the production processes which balance natural strangeness decay: In the temperature interval 33MeV&lt;T&lt;20MeV: μ±+νμ→K±, π+π→K and l−+l+→ϕ reactions in sequence become slower compared to the characteristic Hubble time.

It is a challenging issue to provide a secure and conditional anonymous authentication scheme in vehicle ad hoc networks(VANETs) with low storage space and computational cost. In 2008, Lu et al. [8] proposed an conditional privacy preservation scheme called ECPP protocol. The ECPP protocol provides conditional privacy preservation to vehicles in VANETs, that is, on one hand vehicles can achieve anonymous authentication in the network, on the other hand allow to be traced and revoked if necessary. However, ECPP scheme suffers from large storage and high computational cost. In our scheme, an improved protocol based on the concept of ECPP protocol has been proposed, which uses minimal interaction steps, little storage space and less computation overhead to achieve more efficiency conditional privacy preservation(MECPP) scheme in VANETs.

Micro/Nano Robot is an intelligent and efficient microrobot that can perform specific tasks under the influence of external stimuli. Depending on the application scenarios, the microrobot can adaptively transform into appropriate functional forms under different external stimuli, thus perfectly matching the needs. To date, microbots have been widely used in targeted therapy, drug delivery, tissue engineering, environmental remediation, and other fields. Although the applications of microrobots are promising, there are only a few reviews that can focus on the preparation methods and driving mechanisms. Therefore, it is necessary to outline the current status of the development of these microrobots in order to provide some new insights for the further development of the field. Therefore, this paper reviews the research progress of microrobots in terms of preparation methods, stimulus response mechanisms and applications, and highlights the applicability of different preparation methods and stimulus types. Finally, the current challenges faced by microrobots are highlighted and possible solutions are proposed to facilitate the practical application of microrobots.

High dimensional statistical analysis for the yield of large-scale circuits is quite difficult due to expensive simulations, especially for the memory circuits with high sigma requirement (e.g., SRAM). In this paper, we developed an efficient sparse additive model to substitute simulations. To fit high sigma region accurately, the modeling center is moved to near failure boundary searched by scaling the shape of sampling function. To solve the model efficiently, the process variables are grouped by standard cells so that the model can be solved by our developed blockwise greedy algorithm. The experiments on the 28nm memory circuits validate that our method achieves high accuracy and efficiency compared with other state-of-art works.

To explore the relevant factors that affect the efficacy of consciousness-regaining therapy (CRT)for prolonged disorder of consciousness(pDOC),a retrospective analysis was conducted on the case data of 114 patients with pDOC admitted to department of functional neurosurgery of Tianjin Huanhu Hospital from January 2019 to January 2022. Basic information on the cases,data on pDOC disease assessment, consciousness-regaining therapy methods, and efficacy evaluation were collected. A total of 114 patients were grouped and compared based on the efficacy at the end of treatment. Among them, there were 61 cases in the ineffective group and 53 cases in the effective group. There was no statistically significant difference (P&gt;0.05) between the two groups in terms of gender, age, etiology, acute cerebral herniation, emergency craniotomy surgery, emergency decompressive craniectomy, time from onset to start of consciousness-regaining therapy , and duration of consciousness-regaining therapy(P&gt;0.05). However, there were statistically significant differences (P&lt;0.05) in terms of secondary hydrocephalus, , consciousness-regaining therapy methods, CRS-R grading before treatment, and GOSE score at 6 months after treatment. Binary logistic regression analysis showed that the type of therapy (OR=0.169, 95% CI: 0.057-0.508) was a related factor affecting the efficacy of consciousness-regaining therapy (P&lt;0.05).Compared with non-invasive therapy, personalized awakening therapy using various invasive consciousness-regaining therapy methods can help improve the efficacy of therapy for pDOC.

Commercial classification is essential to spatially describe commerce. Although most of the proposed classifications have been classic functional analyses, rooted on qualitative studies, some recent classifications efforts are found to rely heavily on more quantitative methods, due eventually to increasing data availability and technological advancements. In this paper, a classification is proposed, using k-means clustering and a minimal set of variables (density, diversity and clustering) to derive the commercial structure of Lisbon. The classification is implemented for 1995, 2002 and 2010, using a 150m-sided square grid. The cross-sectional analysis of the results shows the rise of shopping-malls against city centre decline and gentrification, along with changes in cluster composition considering 9 different commercial categories (6 categories of retail, and restaurants, cafes and bars). These findings are in line with literature, thus supporting the obtained classification. Since the classification can be used to accurately describe the commercial structure of the city in different time periods, it is implied that it may also be generalized to different cities. Furthermore, the potential use of cluster membership in retail location models, which is an advantage of the proposed classification, could help strengthen the relationship between location modelling and commercial classification, thus reinforcing the role of commercial studies in urban planning and policymaking.

Using the 2011-2020 digital inclusive finance data released by Peking University and the index system constructed by the Blue Book of China Rural Revitalization and Development Index (2018), this paper analyzes the dynamic evolution of the digital inclusive finance and the rural revitaliza-tion from time and space dimensions with the help of kernel density estimation, Markov chain and Moran index. Using The Gini coefficient decomposition method to analyze the source of differ-ences in digital inclusive finance, and then using the spatial autoregressive (SAR) model and ge-ographically weighted regression (GWR) model to study the boosting effect of digital inclusive finance on rural revitalization from the perspective of spatial aggregation and spatial differentia-tion, respectively. The results show that: (1) The growth rate of China's digital inclusive finance slows down year by year, and the inter-provincial differences increase year by year and show gradient characteristics, indicating that there may be a trend of multipolar differentiation. The overall level of Rural Revitalization shows an increasing trend, and the gap between provinces is still apparent. (2) The evolution of digital inclusive finance and rural revitalization is a slow ad-justment process, and there has been no cross-level jump in the past ten years. In digital inclusive finance, the liquidity from the highest and lowest levels to the medium level is high. However, the liquidity in the states of rural revitalization development level is not high. (3) Rural revitalization has a positive spatial spillover effect. The level of rural revitalization in the western area is signif-icantly lower than in the eastern area. At the same time, there is no significant difference between the east and central areas. The depth of the use of digital inclusive finance has a significant positive impact on the revitalization and development of rural areas, indicating that the further promotion of digital inclusive finance business in rural areas can substantially boost the revitalization of rural areas. (4) The boosting effect of digital inclusive finance on rural revitalization shows prominent spatial differentiation characteristics. The depth of use and the degree of digitization generally show a positive impact. The central and eastern coastal cities have the highest impact, decreasing toward the southwest and northeast. The areas with the lowest usage depth impact are clustered in the northeast, and the areas with the lowest digitization impact are clustered in the southwest.

Bacterial biofilms can cause widespread infection. In addition to causing urinary tract infections and pulmonary infections in patients with cystic fibrosis, biofilms can help microorganisms adhere to the surfaces of various medical devices, causing biofilm-associated infections on the surfaces of biomaterials such as venous ducts, joint prostheses, mechanical heart valves, and catheters. Biofilms provide a protective barrier for bacteria and provide resistance to antimicrobial agents, which increases the morbidity and mortality of patients. This review introduces the formation process and drug resistance mechanism of biofilms in detail, and further summarizes the main characteristics of clinical persistent infection caused by biofilms and the many methods of treating biomaterial-related biofilm. This provides ideas and directions for the development of new biofilm infection strategies related to therapeutic materials.

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.