More than 110 countries including 500 cities worldwide have set the goal of reaching carbon neutrality. Heating contributes to most of the residential energy consumption and carbon emissions. The green energy transition of fossil-based heating systems is needed to reach the emission goals. However, the heating systems vary in energy source, heating technology, equipment location, and these complexities make it challenging for households to compare heating systems and make decisions. Hence, a decision support tool that provides a generalized ranking of individual heating alternatives is proposed for households as decision-makers to identify the optimal choice. This paper presents an analysis of 13 heating alternatives and 19 quantitative criteria in technological, environmental, and financial aspects, combines ideal solution based Multi-Criteria Decision Making with 6 weighting methods and 4 normalization methods, and introduces ensemble learning with a fuzzy membership function derived from Cauchy distribution to finalize the final ranking. The robustness of the proposed method is verified by 3 sensitive analyses from different aspects. Air to water heat pump, solar heating and direct district heating are the top three rankings in the final result under Danish national average data. A framework is designed to guide the decision-makers apply this ranking guideline with their practical feasible situations.

For the problem of poor accuracy of the existing multi-rate simulation methods, this paper proposes a multi rate real-time simulation method based on the Norton equivalent, compared with multi-rate simulation method based on the ideal source equivalent. After the Norton equivalence of the fast subsystem and the slow subsystem, they are obtained simultaneously at the junction nodes. In order to reduce the amount of simulation calculation, the Norton equivalent circuit is obtained by incremental calculation. The data interface between the fast subsystem and the slow subsystem is realized by extrapolation method. For ensuring the real-time performance of the simulation, the method that the slow subsystem calculates ahead of the fast subsystem is given for the slow subsystem with a large amount of calculation. Finally, the AC/DC hybrid power system was simulated on the real-time simulation platform (FRTDS), and the simulation results were compared with the single-rate simulation, which verified the correctness and accuracy of the method.

In the paper, we develop some numerical schemes including finite difference scheme and finite volume scheme for the fractional Laplacian operator, and apply the resulted numerical schemes to solve some fractional diffusion equations. First, the fractional Laplacian operator can be characterized as the weak singular integral by a integral operator with zero boundary condition. Second, because of the solution of fractional diffusion equation is usually singular near the boundary, we apply finite difference scheme to discrete fractional Laplacian operator and fractional diffusion equation by fractional interpolation function. Moreover, it is find that the differential matrix of the above scheme is symmetric matrix, and strictly row-wise diagonally dominant in special fractional interpolation function. Third, we show finite volume scheme to discrete fractional diffusion equation by fractional interpolation function, and analyze the properties of differential matrix. Finally, the numerical experiments are given, and verify the correctness of theoretical results and the efficiency of the schemes.

Abstract: Laryngoscopy for tracheal intubation has been developed for many decades. Among various conventional laryngoscopes, videolaryngoscopes (VL) have been applied in different patient populations, including difficult airways. The safety and effectiveness of VL have been repeatedly studied in both normal and difficult airways. The superiority of VL then has been observed and is advocated as the standard of care. In contrast to laryngoscopy, the development of video-assisted intubating stylet (VS, also named as styletubation) has been noticed two dec-ades ago. Since then, sporadic clinical experiences of use have appeared in literature. In this re-view article, we presented our vast use experiences of the styletubation (more than 55,000 pa-tients since 2016). We found this technique is swift (the time to intubate: from 3 s to 10 s), smooth (first-attempt success rate: 100%), safe (no airway complications), and easy (high subjective satis-faction and fast learning curve for the novice trainees) in both normal and difficult airway sce-narios. We therefore propose styletubation technique can be feasibly applied as universal rou-tine use for tracheal intubation.

In this study, we explore the potential of using a straightforward neural network inspired by the retina model to efficiently restore low-light images. The retina model imitates the neurophysiological principles and dynamics of various optical neurons. Our proposed neural network model reduces the computational overhead compared to traditional signal-processing models while achieving results similar to complex deep learning models from a subjective perceptual perspective. By directly simulating retinal neuron functionalities with neural networks, we not only avoid manual parameter optimization but also lay the groundwork for constructing artificial versions of specific neurobiological organizations.

To address the expression pattern of the SARS-CoV-2 receptor ACE2 and the viral priming protease, TMPRSS2, in the respiratory tract, this study investigated RNA sequencing transcriptome profiling of samples of airway and oral mucosa. As shown, ACE2 has medium levels of expression in both small airway epithelium and masticatory mucosa, and high levels of expression in nasal epithelium. The expression of ACE2 is low in mucosal associated invariant T (MAIT) cells, and can’t be detected in alveolar macrophages. TMPRSS2 is highly expressed in small airway epithelium and nasal epithelium, and has lower expression in masticatory mucosa. Our results provide the molecular basis that the nasal mucosa is the most susceptible locus in the respiratory tract for SARS-CoV-2 infection and consequently for subsequent droplet transmission and should be the focus for protection against SARS-CoV-2 infection.

Kidney disease is a significant health problem worldwide, affecting an estimated 10% of the global population. Kidney disease encompasses a diverse group of disorders that vary in their underlying pathophysiology, clinical presentation, and outcomes. These disorders include acute kidney injury (AKI), chronic kidney disease (CKD), glomerulonephritis, nephrotic syndrome, polycystic kidney disease, diabetic kidney disease, and many others. Despite their distinct etiologies, these disorders share a common feature of immune system dysregulation and metabolic disturbances. The immune system and metabolic pathways are intimately connected and interact to modulate the pathogenesis of kidney diseases. The dysregulation of immune responses in kidney diseases includes a complex interplay between various immune cell types, including resident and infiltrating immune cells, cytokines, chemokines, and complement factors. These immune factors can trigger and perpetuate kidney inflammation, causing renal tissue injury and progressive fibrosis. In addition, metabolic pathways play critical roles in the pathogenesis of kidney diseases, including glucose and lipid metabolism, oxidative stress, mitochondrial dysfunction, and altered nutrient sensing. Dysregulation of these metabolic pathways contributes to the progression of kidney disease by inducing renal tubular injury, apoptosis, and fibrosis. Recent studies have provided insights into the intricate interplay between immune and metabolic pathways in kidney diseases, revealing novel therapeutic targets for the prevention and treatment of kidney diseases. Potential therapeutic strategies include modulating immune responses through targeting key immune factors or inhibiting pro-inflammatory signaling pathways, improving mitochondrial function, and targeting nutrient-sensing pathways such as mTOR, AMPK, and SIRT1. This review highlights the importance of the interplay between immune and metabolic pathways in kidney diseases and the potential therapeutic implications of targeting these pathways.

As the natural resources are getting exhausted, the concept of sustainable development of region has received increasing attentions, especially for resource-dependent cities. In this paper an innovative method that emergy analysis and IPAT (Human Impact Population Affluence Technology) model were combined in order to analyze the quantitative relationship of economic growth and energy consumption and further to evaluate its overall sustainability level. Taiyuan, a traditional, resource-dependent city in China, is selected as the case study region. The main results show that total emergy of Taiyuan increased from 9.023× 1023 sej in 2007 to 9.116× 1023sej in 2014, with 38% reduction on non-renewable emergy and 125% growth on imported emergy. Regional emergy money ratio (RMB) was reduced by 48% from 5.31× 1013sej/$ in 2007 to 2.74× 1013sej/$ in 2014, indicating that the increasing speed of consuming resources and energy was faster than the increase of GDP, and that Taiyuan’s money purchasing power declined. The lower emergy sustainability index (ESI) indicates that Taiyuan was explored and produced large quantities of mineral resources, which puts more stress on the environment as a consequence, and that this is not sustainable in the long run. The IPAT analysis demonstrates that Taiyuan sticks to the efforts of energy conservation and environmental protection, in order to promote regional sustainable development, it is necessary to take an integrated effort. Policy insights suggest that resourceful regions should improve include energy and resource efficiency, optimizing energy and resourceful structure.

Long noncoding RNAs (lncRNAs) of virus origin accumulate in cells infected by many positive strand (+) RNA viruses to bolster viral infectivity. Their biogenesis mostly utilizes exoribonucleases of host cells that degrade viral genomic or subgenomic RNAs in the 5’-to-3’ direction until being stalled by well-defined RNA structures. Here we report a viral lncRNA that is produced by a novel replication-dependent mechanism. This lncRNA corresponds to the last 283 nucleotides of the turnip crinkle virus (TCV) genome, hence is designated tiny TCV subgenomic RNA (ttsgR). ttsgR accumulated to high levels in TCV-infected Nicotiana benthamiana cells when the TCV-encoded RNA-dependent RNA polymerase (RdRp), also known as p88, was overexpressed. Both (+) and (-) strand forms of ttsgR were produced in these cells in a manner dependent on the RdRp functionality. Strikingly, templates as short as ttsgR itself were sufficient to program ttsgR amplification, as long as the TCV-encoded replication proteins, p28 and p88, were provided in trans. Consistent with its replicational origin, ttsgR accumulation required a 5’ terminal G₃(A/U)₄ motif shown by others to be crucial for the replication of a TCV satellite RNA. More importantly, introducing a new G₃(A/U)₄ motif elsewhere in the TCV genome was alone sufficient to cause the emergence of another lncRNA. Collectively our results unveil a replication-dependent mechanism for the biogenesis of viral lncRNAs, thus suggesting that multiple mechanisms, individually or in combination, may be responsible for viral lncRNA production.

Pipeline conflicts arising from data dependencies are a common issue encountered in the hardware implementation of layered QC-LDPC decoders. This paper proposes an efficient layered decoding architecture to reduce pipeline conflicts without introducing stall cycles, by reordering the processing order offline and using the patch method based on variable-to-check message. The experimental results on the LDPC code of the IEEE802.16 standard in the OFDM-PON system demonstrate that the proposed architecture has a sensitivity improvement of 0.125 dBm and 0.375 dBm, respectively, compared with our previous work and the method described in the other work.

Geminiviruses possess single-stranded, circular DNA genomes, and control the transcription of their late genes, including BV1 of many bipartite begomoviruses, through transcriptional activation by the early expressing AC2 protein. DNA binding by AC2 is not sequence-specific, hence the specificity of AC2 activation is thought to be conferred by plant transcription factors (TFs) recruited by AC2 in infected cells. However, the exact TFs AC2 recruits are not known for most viruses. Here we report a systematic examination of the BV1 promoter (PBV1) of mungbean yellow mosaic virus (MYMV) for conserved promoter motifs. We found that MYMV PBV1 contains three abscisic acid (ABA)-responsive elements (ABREs) within its first 70 nucleotides. Deleting these ABREs, or mutating them all via site-directed mutagenesis, abolished the capacity of PBV1 to respond to AC2-mediated transcriptional activation. Furthermore, ABRE and other related ABA-responsive elements were prevalent in more than a dozen Old World begomoviruses we inspected. Together these findings suggest that ABA-responsive TFs may be recruited by AC2 to BV1 promoters of these viruses to confer specificity to AC2 activation. These observations are expected to guide the search for the actual TF(s), furthering our understanding of the mechanism of AC2 action.

In this paper, a new method by combining cold drawing and martensitic transformation was proposed to produce ultrahigh-strength steel wire, and the effect of austenitizing heating rate on microstructure and mechanical properties was studied. Compared with Muffle furnace heating, salt bath heating has a much higher austenitizing heating rate, which is beneficial to obtain ultrafine-grained martensite for steel wire with a larger section. By salt bath hardening and low-temperature tempering, an ultrahigh strong (strength of 2.48 GPa) and tough (elongation of 6.0%) steel wire was produced. Moreover, to explore whether is it possible to replace long-time low-temperature tempering with short-time tempering at elevated temperatures to improve the tempering efficiency, the effect of tempering time on the evolution of microstructure and mechanical properties of the steel wires tempered at 350 °C was systematically studied. The results demonstrate that tempering at 350 °C for 30 s can endow the steel wire with comparable mechanical properties to that of the one tempered at 250 °C for 2 h. With tempering time prolonging, the strength decreases gradually with the precipitated phase transition from χ-Fe5C2 carbide into θ-Fe3C carbide and coarsening, which plays a major role in the strength decrease.

Reproductively lethal mutations (RLMs) are mutations that, upon expression of the encoded lethal phenotypes, cause individuals carrying them to die or to be sterile. An underappreciated fact is that loss-of-function RLMs in protein-coding genes can be phenotypically shielded by favorable environments rendering these genes conditionally non-essential, or by their sister alleles in diploid organisms. Absent of rigorous mitigation, such phenotype-shielding causes the number of genes incurring RLMs to increase over time, and simultaneously allows each RLM to reach high allele frequencies in a conspecific population. Over-accumulation of RLMs then sets the population up for eventual concurrent expression of large numbers of RLMs, and massive deaths in rapid succession, possibly even population-level extinction. This hypothetical scenario in turn predicts that organismal lineages that evolved means to minimize the allele frequencies of phenotypically shielded RLMs are favored by natural selection. We argue that bottlenecking the genome copies destined for reproduction is a universal strategy adopted by all living beings to compel phenotype-based RLM purging. We further postulate that primitive RNA replicons must first evolve bottlenecked reproduction before evolving the capacity to encode diffusible products. In more complex, multicellular organisms, RLM management through bottlenecked reproduction gains additional reinforcement through sexual reproduction. In short, the evidence chronicled in this essay strongly suggest that the Bottleneck, Isolate, Amplify, Select (BIAS) principle, originally proposed to explain intracellular evolutionary dynamics of viruses, may be universally applicable to all living beings.

(1) Background: Investigating the characteristics of photosynthetic physiological changes of leaves in Mangifera indica L. cv. 'GuIfei' under enhanced UV-B radiation, natural light exposed trees were regarded as control, and 96 kJ·m-2·d-1enhanced UV-B radiation was artificially simulated in the field; (2) Methods: The changes of fruit maturity and fruit quality, leaf net photosynthetic rate (Pn), photosynthetic pigments contents, photochemical reaction, activities of photosynthetic enzymes and their genes expressions were determined; (3) Results: Compared with CK, the percentage of mature fruits of the treatment was significantly increased, and fruit quality was better. The net photosynthetic rate (Pn), the contents of photosynthetic pigment, Hill reaction activity and photochemical quenching coefficient (qP) of the treatment leaves showed a significantly higher trend than CK. The activities of Rubisco and RCA, and the expression of Rubisco genes rbcL and rbcS were significantly increased; (4) Conclusions: 96 kJ·m-2·d-1 enhanced UV-B radiation treatment improved Rubisco activity through increasing the expression of Rubisco genes rbcL and rbcS, thereby enhancing the CO2-fixing capacity and dark reaction capacity of leaves. Based on this, it raised the net photosynthetic rate of leaves, which promoted the early maturity of 'Guifei' mango by the fast accumulating photosynthetic products.

Many positive sense RNA viruses, especially those infecting plants, are known to experience stringent, stochastic population bottlenecks inside the cells they invade, but exactly how and why these populations become bottlenecked are unclear. A model proposed ten years ago advocates that such bottlenecks are evolutionarily favored because they cause the isolation of individual viral variants in separate cells. Such isolation in turn allows the viral variants to manifest the phenotypic differences they encode. Recently published observations lend mechanistic support to this model, and prompt us to refine the model with novel molecular details. The refined model, designated Bottleneck, Isolate, Amplify, Select (BIAS), postulates that these viruses impose population bottlenecks on themselves by encoding bottleneck-enforcing proteins (BNEPs) that function in a concentration-dependent manner. In cells simultaneously invaded by numerous virions of the same virus, BNEPs reach the bottleneck-ready concentration sufficiently early to arrest nearly all internalized viral genomes. As a result, very few (as few as one) viral genomes stochastically escape to initiate reproduction. Repetition of this process in successively infected cells isolate viral genomes with different mutations in separate cells. This isolation prevents mutant viruses encoding defective viral proteins from hitchhiking on sister genome-encoded products, leading to the swift purging of such mutants. Importantly, genome isolation also ensures viral genomes harboring beneficial mutations accrue the cognate benefit exclusively to themselves, leading to the fixation of such beneficial mutations. Further interrogation of the BIAS hypothesis promises to deepen our understanding of virus evolution, and inspire new solutions to virus disease mitigation.

On the basis of the force and safety factor analysis of traditional retaining wall, a new analytical method of force and displacement of slope is suggested, the numerical theoretical solution of the stress distribution of the sliding body can be obtained under the conditions, which the stresses distribution are satisfied with the differential equilibrium equations, the boundary conditions, the compatibility equation and the macroscopic equilibrium equations. The interface stresses between the sliding body and the retaining wall are continuous, the theoretical solution of retaining wall stress distributions can be gotten, while the stress differential equilibrium equation, the compatibility equation, macroscopic force and moment balance equations are satisfied. The strain and displacement solutions can be obtained by using Duncan Chang and Hooke constitutive equations for the slope and the retaining wall respectively. The transfer station of landfill in the Guandukou Town of Badong County is taken as an example, the results of the sliding body and retaining wall analysis show: The stress and strain solutions of a slope and a retaining wall can be obtained by the proposed method, the forces between the retaining wall and the sliding body include shear stress and normal stress, and the stress distributions change with the deformation of the sliding body, the shape and material of retaining wall can be optimized according to the calculation results，it is feasible for the proposed analysis method of slope with retaining wall design to be run many years.

In this paper, the physical station of space network was extended in time dimension by combining the train diagram information and station technical operation standard time. At the same time, the topology of railway space-time network which considered the secondary operation process of train was constructed and an improved A* algorithm based on car flow routing was proposed to generate feasible path sets. On this basis, a dynamic car flow organization optimization model was built to simulate the railway car flow organization process under abnormal conditions, and the results of solving the model could be used to obtain the real-time quantity of cars at each station.This paper can identify the dynamic bottleneck by comparing the real-time quantity of cars with the maximum quantity of cars at the station. Finally, the feasibility of this method was analyzed and verified by a case.

We review recent progress in high-speed orbital angular momentum (OAM) multiplexed free-space optical communication systems. The outdoor atmospheric turbulence is emulated by an indoor turbulence emulator, which is based on split-step beam propagation method. Adaptive optics, channel coding, Huffman coding combined with LDPC coding, and spatial offset are used for turbulence mitigation; while OAM multiplexing and wavelength-division multiplexing (WDM) are applied to boost aggregate capacity.

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

Selenium is a trace metal essential to human health, and its deficiency has been related to, for instance, cardiovascular and myodegenerative diseases, infertility and osteochondropathy Kashin-Beck disease. It is incorporated as selenocysteine to selenoproteins, which protect against reactive oxygen and nitrogen species. They also participate in the activation of thyroid hormone, and play a role in immune system functioning. The synthesis and incorporation of selenocysteine occurs via a special mechanism, which differs from the one used for standard amino acids. The codon for selenocysteine is the regular in-frame stop codon, which can be passed by specific complex machinery participating in translation elongation and termination. This includes the presence of selenocysteine insertion sequence (SECIS) in the 3’-untranslated part of the selenoprotein mRNAs. Selenium deficiency is known to control both selenoprotein and non-selenoprotein transcriptomes. Nonsense-mediated decay is involved in the regulation of selenoprotein mRNA levels, both other mechanisms are also possible.

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

OsNRAMP5—a member of the same family as the iron, manganese (Mn), and cadmium (Cd) transporter OsNRAMP1—is responsible for the transport of Mn and Cd from soil in rice. Knockout of OsNRAMP5 markedly reduces both Cd and Mn absorption; therefore, in low -Mn environments, such plants would exhibit Mn deficiency and suppressed growth. Amino acid mutations in IRT1 alter its metal selectivity. We generated random mutations in OsNRAMP5 via error-prone PCR, and used yeast to screen for the retention of Mn absorption and inhibition of Cd absorption. The results showed ththat alanine 512th is the most important amino acid residue for Cd absorption, and that its substitution resulted in the absorption of Mn but not Cd.

Approximately 240 million people are chronically infected with hepatitis B virus (HBV), despite four decades of an effective HBV vaccine. During chronic infection, HBV forms two distinct templates responsible for viral gene transcription: (1) episomal covalently closed circular (ccc)DNA and (2) host-genome integrated viral templates. Multiple ubiquitous and liver-specific transcription factors are recruited onto these templates and modulate viral gene transcription. This review details the latest developments in antivirals that inhibit HBV gene transcription, and their impact on the stability of viral transcripts. Notably, nuclear receptor agonists exhibit potent inhibition of viral gene transcription from cccDNA, small molecule inhibitors repress HBV X protein-mediated transcription from cccDNA and small interfering RNAs and single-stranded oligonucleotides result in transcript degradation from both cccDNA and integrant templates. These antivirals mediate their effects by reducing viral transcripts abundance, eventually leading to loss of surface antigen expression, and can potentially be added to the arsenal of drugs with demonstrable anti-HBV activity. Thus, these candidates deserve special attention for future repurposing or further development as anti-HBV therapeutics.

In this paper, the experimental study of heating in 2 h lunch mode of air-conditioned bed system is carried out. The results show that the power consumption of heat conduction heating is only 0.34 kW·h, and the average heat dissipation is 81.3 W, while the power consumption of convection heating is 1.43 kW·h, with an average heat dissipation of 748.7 W. Regardless of power consumption or heat dissipation, convection heating is significantly higher than heat conduction heating, resulting in the room air temperature of the former increased from 12.3 °C to 17.3 °C, while the latter only increased from 14.4 °C to 15.2 °C. The study found that the water temperature of heat conduction heating can meet the thermal comfort needs of the human body in the range of 38~40 °C, while convection heating requires a higher temperature range, In contrast, the grade of hot water required for heat conduction heating is lower. Through the experiment, it is also found that the temperature of convection heating rises fast, but it is easy to appear dry feeling after a long time, while heat conductive heating has a slow temperature rise. there is a cool feeling within 20 min after the heating starts, and then the thermal comfort is better. The air conditioning system in this paper is used for the heating experiment in the winter lunch break mode, compared with convection heating, the overall thermal comfort of heat conduction heating is better and more energy efficient. it is suggested to adopt heat conduction heating mode in the winter heating of this system.

The diverse physical appearances and wide density range of polymer bead foams offer immense potential across various applications and future advancements. The multi-scale and multi-level structural features of bead foams involve many fundamental scientific topics. This review presents a comprehensive overview of recent progress in bead foams preparation and molding techniques. Initially, a comparative analysis is conducted among bead foam characteristics of distinct polymers, based on their unique properties. Subsequently, a summary and comparison of molding processes employed for fabricating bead foam parts are provided. Beyond traditional methods like steam-chest molding (SCM) and adhesive-assisted molding (AAM), emerging techniques like in-mold foaming and molding (IMFM) and microwave selective sintering (MSS) are highlighted. Lastly, the bonding mechanisms behind the diverse molding methods are discussed.

The physical properties of coal reservoirs are the main restrictions to exploration and development of CBM. The study of the physical characteristics of coal reservoirs and their controlling factors is of great significance to the safe and efficient development and utilization of CBM resources in the mining area. The Pingdingshan No. 10 coal mine was chosen for this study because of its better gas production effect at the test wells. The reservoir properties of the main coal seams of the No. 10 coal mine were tested and analyzed to comprehensively evaluate the reservoir properties. The results indicate that (1) The gas content and methane purity of the No. 4 coal seam are significantly higher than the No. 2 seam, and therefore they have better development potential than the No. 2 seam; (2) The average adsorption time of the No. 2 coal seam is less than that of the No. 4 seam, making it easier to reach the peak production capacity of CBM wells in the short term, but is not conducive to long-term stable production of CBM. The Langmuir volume of the No. 2 coal seam samples was significantly greater than for the No. 4 coal seam; however, the No. 4 coal seam contains about three times the amount of gas in the No. 2 seam; (3) All three coal seams have high porosity, which is favorable for large amounts of CBM adsorption and storage. Micropores predominate, transitional pores are less frequent, and a few mesopores occur; macropores are the least common. Samples from the No. 4 seam contained the highest proportion of micropores; (4) Organic pores were common in the all coal samples, with pore diameters not more than 30 µm, mainly concentrated between 50.5 and 1000 nm. Microfractures with aperture less than 70 nm were relatively frequent, mainly in the 50–65 nm range. A large number of the nanoscale microfractures were curved or jagged; (5) Fractures in the No. 2 and No. 4 coal seam samples with widths of 50 nm to 20 µm were more developed, and many were filled with kaolinite, quartz and other minerals; (6) The samples contained mostly layered silicate minerals (kaolinite), with hard granular minerals (quartz) next, and a very small quantity of iron-type minerals such as siderite and pyrite in dendritic form. The results of this study can provide a reference basis for the large-scale development and utilization of subsequent CBM wells.

ozone-based chemiluminescence detection (CLD) has been widely applied for determining nitric oxide (NO) and its derived species in many different fields, such as environmental monitoring and biomedical research. In humans CLD was applied to determine exhaled NO and NO metabolites in biological samples. The main advantages of CLD are high sensitivity and selectivity for quantitative analysis in a wide dynamic range. Combining CLD with analytical separation techniques like gas or liquid chromatography allows the analytes to be quantified with less disturbance from matrix components or impurities. Sampling techniques like microdialysis and flow injection analysis may be coupled to CLD with the possibility of real-time monitoring of NO. However, details and precautions in experimental practice need to be addressed and clarified to avoid wrongly estimating. Therefore, using CLD as a detection tool requires a deep understanding of sample preparation procedure and chemical reactions used for liberating NO from its derived species. In this review, we discuss the advantages and pitfalls of CLD for determining NO species, the different applications and combinations with other analytical techniques, and provide general practical notes for sample preparation. These guidelines should help other researchers understand CLD data and select the best procedure for detecting NO species.

In the fifth generation communication system, millimeter wave (mmWave) networks will coexist with traditional micro wave (μWave) networks, which allows for higher data transmission rate and better user experience. In this paper, we give a comprehensive framework of mathematical models and analytical methods for multi-tier mmWave and μWave hybrid caching networks based on stochastic geometry. We propose an association strategy by assuming average biased-received power association and Rayleigh fading. Accordingly, by using a D-ball approximating blockage model of mmWave networks, expressions of the cell association probability and the coverage probability of the hybrid networks are derived. Also, we use the average successful delivery probability as the performance metric to analyze the existing caching placement strategies. Simulation results validate the accuracy of our analytical conclusions.

Environmental responsibility and economic benefits have promoted the development of closed-loop supply chain (CLSC), and shortages and channels are considered to be two important issues in CLSC. This paper explores ordering and channel decisions in CLSC with new and differentiated remanufactured products, and considers the price and sales effort-dependent demands, as well as the proportion of emergency orders determined by emergency order costs and backorder losses, and establishes an integrated and decentralized CLSC game models. We introduce a stochastic sales effort, which affects two types of products. Numerical results show that sales effort and the order quantity of new and remanufactured products exhibit concave and convex functions, respectively. Wherein, the upper limit of sales effort has a greater impact on supply chain decisions. High sales efforts can serve as a means of coordinating dispersed supply chains. Moreover, in different cases, decisions of integrated channel are better than those of decentralized channel. Finally, whether the supply chain adopts an emergency order strategy depends on the relative cost of emergency orders and out of stock costs. According to the research in this article, some management insights are also provided.

Silicon anodes have been considered one of the most promising anode candidates for the next generation of high-energy density lithium-ion batteries due to the high theoretical specific capacity (4200 mAh g-1) of Si. However, high lithiation capacity endows silicon anodes with severe volume expansion effects during the charge/discharge cycling. The repeated volume expansions not only lead to the pulverization of silicon particles and the separation of electrode materials from the current collector, but also brings rupture/formation of solid electrolyte interface (SEI) and also continuous electrolyte consumption, which seriously hinders the commercial application of silicon anodes. Structural design and optimization is the key to improving the electrochemical performances of silicon anodes, which has attracted wide attention and research in recent years. This paper mainly summarizes and compares the latest research progress for the structural design and optimization of silicon anodes.

Defect recognition in ballastless track structures, based on distributed acoustic sensors (DASs), was researched in order to improve detection efficiency and ensure the safe operation of trains on high-speed railways. A line in southern China was selected, and equipment was installed and debugged to collect the signals of trains and events along it. Track vibration signals were extracted by identifying a train track, denoising, framing and labeling to build a defect dataset. Time–frequency-domain statistical features, wavelet packet energy spectra and the MFCCs of vibration signals were extracted to form a multi-dimensional vector. An XGBoost model was trained and its accuracy reached 89.34%. A time-domain residual network (ResNet) that would expand the receptive field and test the accuracies obtained from convolution kernels of different sizes was proposed, and its accuracy reached 94.82%. In conclusion, both methods showed good performance with the built dataset. Additionally, the ResNet delivered more effective detection of DAS signals compared to conventional feature engineering methods.

Personalized recommendation is an important part of ecommerce platform. In the recommendation system, the neural network is used to enhance collaborative filtering to accurately capture user preferences, so as to obtain better recommendation performance. Traditional recommendation methods focused on the results of a single user behavior, ignoring the modeling of multiple interactive behaviors of users, such as click, add to cart and purchase. Although many studies had also focused on Multi-Behavior modeling, two important challenges remained. 1)Since multiple behavioral context information was ignored, it was still a challenge to identify the multimodal relationships of behaviors. 2) Surveillance signals were still sparse. In order to solve this problem, this paper proposes Two-path Multi-behavior Sequence Modeling(TP_MB). First, a two-path learning strategy is introduced to maximize the multiple interaction information of user items learned by the two paths, which effectively enhances the robustness of the model. Second, a multi-behavior dependent encoder is designed. Contextual information is obtained through behavior dependencies in the interaction of different user. In addition, three contrastive learning methods are designed, which not only obtain additional auxiliary supervision signals, but also alleviate the problem of sparse supervision signals. Extensive experiments on two real datasets demonstrate that our method outperforms state-of-the-art multi-behavior recommendation methods.

Owing to the advantages of cost-effectiveness, compactness, and the avoidance of complicated camera synchronization, single-camera three-dimensional (3D) digital image correlation (DIC) techniques have gained increasing attention for deformation measurement of materials and structures. In the traditional single-camera 3D-DIC system, the left and right view images can be recorded by a single camera using a diffraction grating, a bi-prism or a set of planar mirrors. To further improve the measurement accuracy of single-camera 3D-DIC, this paper introduces a single-camera four-view imaging technique by installing a pyramidal prism in front of the camera. The 3D reconstruction of the measured points before and after deformation is realized with eight governing equations induced by four views, and the strong geometric constraints of four views can help to improve the measurement accuracy. A static experiment, a rigid body translation experiment and a four-point bending experiment show that the proposed single-camera 3D-DIC method can achieve higher measurement accuracy than the dual-view single-camera 3D-DIC techniques and has advantages in reducing both random error and systematic error.

Some biologically active compounds isolated from sea cucumbers stimulate the body’s immune response through activating immune cells. Immune function is closed related to the integrity intestinal barrier and balanced gut microbiota. However, it is unknown whether daily administration of holothurian wall hydrolysates (HWH) ameliorated intestinal dysbiosis and barrier injury induced by immunodeficiency. This study aimed to investigate the immunomodulatory effect and the underlying mechanism of HWH in cyclophosphamide (CTX)-induced immunocompromised mice. BALB/c mice received CTX (80 mg/kg, intraperitoneally) once a day for 3 days to induce immunodeficiency, and then oral administration of HWH (80 or 240 mg/kg), levamisole hydrochloride (LH, 40 mg/kg, positive control) respectively once a day for 7 days. We utilized 16S rRNA sequencing for microbial composition alterations, histopathological analysis for splenic and colonic morphology, Western blotting for expressions of tight junction proteins (TJs), and quantitative real-time (qRT-PCR) for measurements of pro-inflammatory cytokines. HWH attenuated the immune organ damage induced by CTX, increased the secretions of interleukin (IL)-6, IL-1β and tumor necrosis factor (TNF)-α, and promoted the recovery of goblet cells and the productions of TJs (claudin-1, occludin, and ZO-1) in the colon of the immunocompromised mice. Moreover, HWH promoted the growth of beneficial microorganisms such as Lactobacillus, Lachnospiraceae, Christensenellaceae, and Bifidobacterium, while suppressed the populations of Ruminococcus, Staphylococcus, and Streptococcus. These results demonstrate that HWH elicits intestinal mucosal immunity, repairs the damage to intestinal mucosal integrity, and normalizes the imbalanced intestinal microbial profiles in immunocompromised mice. It may be helpful to identify the biological activities of HWH, and supports the potential as new prebiotics, immunomodulatory agents, and medical additive for intestinal repair.

In this paper, the methods and their analysis for estimating the location of three dimension (3-D) single source buried in lossy medium are presented with uniform circular array (UCA). The mathematical model of the signal in the lossy medium is proposed. Using location information in the covariance matrix obtained by sensors’ output, the equations of the source location (azimuth angle, elevation angle and range) are obtained. The phase and amplitude of the covariance matrix function are used to process these equations respectively. Then, the phase and amplitude of the covariance matrix function are used to process the source localization in the conductive medium together. By analyzing the characteristics of the proposed methods and MUSIC method, the computational complexity and the valid range of these methods are given. From the results, whether the loss is known, we can choose the appropriate method to process the issues (localization in lossless medium or lossy medium).

In this paper, we first discuss the research status and application progress of the finite element method and the smoothed particle method. By analyzing the advantages of the smoothed particle method and the finite element method, a new coupling algorithm, namely FEM-SPH algorithm, is proposed. By the method of comparison, it shows that finite element method and SPH method in the simulation of large deformation problems each have advantages and disadvantages, the finite element method smoothed particle coupling algorithm is effective to achieve the performance of high computational efficiency and can naturally simulate large deformation problems across. In the process of calculation, the large deformation unit can be freely into an algorithm to facilitate the calculation accuracy and efficiency of three methods of numerical simulation. Through the study found, FEM-SPH algorithm not only overcome the defect of smooth particle tensile instability, but also overcomes the problem of low efficiency of finite element computation. To further test the FEM-SPH algorithm has advantages in the practical engineering, we have carried out the actual test to the example of the super high speed collision, concluded that, since the target of most of the computational domain is always finite element, smoothed particle focused only in contact with the projectile and target of local area, particle number is not much, the whole calculation process just ten minutes, computational efficiency has been greatly improved, at the same time in the simulation of large deformation, the advantage is very obvious .This provides a criterion for the actual project, depending on the specific material deformation mode and choose a more appropriate conversion algorithm.

The current study aimed to investigate the antitumor effects and potent mechanism of cytokine-induced killer (CIK) cells combined with irreversible electroporation (IRE) via an in vitro function assay in an in vivo Panc02 cell–bearing mouse model. We established an in vitro culture assay for CIK cells and determined the proportions of different peripheral lymphocytes. The antitumor effect of the combination of IRE and CIK cells in a Panc02 pancreatic-cancer (PC) subcutaneous-xenograft model was investigated; tumor size and mouse survival rates were recorded. We used flow cytometry (FCM) to analyze the proportion of intratumoral lymphocytes, the expression of chemokine receptors, and the proliferative activity of CIK cells. The proportion of cells that were positive for clusters of differentiation 3 and 8 (CD3+CD8+) and the proportion of CD3+CD56+ cells were both significantly increased after 21 days of in vitro culture. Combined IRE/CIK cell treatment significantly inhibited tumor growth and increased the survival rate of Panc02 cell–bearing mice. Furthermore, infiltration of lymphocytes into tumor tissue was significantly increased by this combination therapy compared with the untreated group or monotherapy group. In addition, IRE significantly enhanced the expression of chemokine receptors elicited by, and the proliferative activity of, CIK cells. In conclusion, IRE combined with CIK cells showed superior antitumor efficacy in a PC subcutaneous-xenograft model, which we attributed to the promotion of lymphocytic infiltration, as well as to upregulation of chemokine receptor expression and of regulators of CIK cell proliferation.

The prediction of drug-target interactions plays a fundamental role in facilitating drug discovery, where the goal is to find prospective drug candidates. With the increase in the number of drug-protein interactions, machine learning techniques, especially deep learning methods, have become applicable for drug-target interaction discovery because they significantly reduce the required experimental workload. In this paper, we present a spontaneous formulation of the drug-target interaction prediction problem as an instance of multi-instance learning. We address the problem in three stages, first organizing given drug and target sequences into instances via a private-public mechanism, then identifying the predicted scores of all instances in the same bag, and finally combining all the predicted scores as the output prediction. A comprehensive evaluation demonstrates that the proposed method outperforms other state-of-the-art methods on three benchmark datasets.

Polymeric composites such as Poly-ether-ether-ketone (PEEK)/carbon fiber (CF) have been widely utilized due to outstanding performances such as high specific strength and specific modulus. The PEEK/CF components via powder-bed fusion additive manufacturing usually show brittle fracture behaviors induced by their poor interfacial affinity and inner voids. These defects are strongly associated with powder packing quality upon deposition. The particle dynamic model has been widely employed to study the interactions of particle motions. Powder property, bulk material property, and interfacial features of composite powders are key factors in the particle dynamic model. In this work, an efficient and systematic material evaluation is developed for composite powders to investigate their deposition mechanism. The discrete element method is utilized to simulate the dynamic behaviors of PEEK/CF composite powders. The powder properties, bulk material properties, and interfacial features of powders are calibrated and justified by experimental measurement, numerical simulation, and design of experiments. The particle dynamic model can well explain the powder flow behaviors and interactions. It reveals that the addition of short CF particles can assist the flow of PEEK powders and improve the packing quality of the composite powders.

(1) Background: Heat stress detrimentally restricted the economic in dairy farming production, therefore, this study was designed to investigate how automatic spraying method on alleviating heat stress on cows. (2) Methods: A total of 1208 multiparous dairy cows were randomly allocated into 6 barns, three barns were equipped with automatic sprinklers (SP), each barn was considered as a replicate. The other three barns were considered as control treatments (CON). Each barn was considered as a replicate. (3) Results: body temperature and milk somatic cell count were significantly decreased, while DMI, milk yield, and milk fat content significantly increased with spraying treatment. ICR was improved from 30% to 35%. Rumen fermentation was enhanced by the increased levels of total VFA, acetate, propionate, and butyrate with the spraying treatment. Rumen microbiota results showed at the phylum level, rumen Fibrobacters abundance significantly increased by the spraying treatment. At the genus level, Eubacterium, Shuttleworthia, Saccharofermentans, Lachnospira, Pseudobutyrivibrio, Selenomonas, and Succinivibrio abundance were significantly increased, while Ruminococcaceae and Rikenellaceae abundance were significantly decreased in the rumen with spraying treatment. (4) Conclusion: this study demonstrated automatic spraying modulated the rumen microbiota composition and fermentation function, and effectively meliorated side-effects of heat stress on dairy cows.

Abstract: The promotion and development of healthy cities are vital for enhancing human habitats and fostering sustainable economic growth. Based on the core database of Web of Science and the knowledge graph software, this paper makes a quantitative analysis of the literature related to attention recovery abroad. It is found that in recent years, the research on attention recovery has developed rapidly, the number of related literature has been increasing, and the research content presents the characteristics of interdisciplinary integration. By further analyzing the characteristics of research literature, research context, and knowledge basis, this paper summarizes the empirical research based on the existing quantitative analysis, reviews the research field based on the mechanism of attention recovery, and analyzes the development process and trend based on the research basis of attention recovery. Due to the change of modern life style, human health problems are becoming more and more prominent. Attention restoration design provides a new research idea and method to balance the relationship between humans and the urban environment.

The prevalence of antiviral drugs (AVTs) has seen a substantial increase in response to the COVID-19 pandemic, leading to heightened concentrations of these pharmaceuticals in wastewater systems. The hydrophilic nature of AVTs has been identified as a significant factor contributing to the low degradation efficiency observed in wastewater treatment plants. This characteristic often necessitates the implementation of additional treatment steps to achieve complete degradation of AVTs. Semiconductor-based photocatalysis has garnered considerable attention due to its promising potential in achieving efficient degradation rates and subsequent mineralization of pollutants, leveraging the inexhaustible energy of sunlight. However, in recent years, there have been few comprehensive reports that have thoroughly summarized and analyzed the application of photocatalysis for the removal of AVTs. This review commences by summarizing the types and occurrence of AVTs. Furthermore, it places a significant emphasis on delivering a comprehensive summary and analysis of the characteristics pertaining to the photocatalytic elimination of AVTs. Ultimately, the review sheds light on the identified research gaps and key concerns, offering invaluable insights to steer future investigations in this field.

Seniors safety is a compelling need, which necessitates 24/7 real-time monitoring and timely dangerous action recognition. Being able to mirror characteristics of physical objects (PO) to corresponding logical objects (LO) and seamlessly monitor their footprints thus detect anomaly parameters, Digital Twins (DT) has been considered a practical way to provide virtual health services for seniors safety. Meanwhile, widely adopted Internet of Medical Things (IoMT) consisting of wearable sensors and non-contact optical cameras for self and remote health data monitoring also raises concerns on information security and privacy violation. Therefore, security of POs, LOs and reliable data sharing among healthcare professionals are challenging as constructing trust and privacy-preserving virtual health services. Thanks to characteristics of decentralization, traceability and unalterability, Blockchain is promising to enhance security and privacy properties in many areas like data analysis, finance and healthcare. This paper envisions a lightweight authentication framework (LAF) to enable secure and privacy-preserving virtual healthcare services. Leveraging Non-Fungible Token (NFT) technology to tokenize LOs and data streams on blockchain, anyone can certify the authenticity of a digital LO along with its synchronized data between PO without relying on a third-party agency. In addition, the NFT-based tokenization not only allows owners fully control their IoMT devices and data, but it also enables verifiable ownership and traceable transferability during data sharing process. Moreover, NFT only contains references to encrypted raw data that are saved on off-chain storage like local files or distributed databases, such a hybrid storage strategy ensures privacy-preservation for sensitive information. A proof-of-concept prototype is implemented and tests are conducted on a case study of seniors safety. The experimental evaluation shows the feasibility and effectiveness of the proposed LAF solution.

Endophytic bacteria, especially those participate in nitrogen fixation, play critical roles in supplying essential nutrients for legume plant growth. Compared to the numerous bacterial microbiome reports targeting legume roots and nodules, little is known about embryonic bacteria that facilitate plant nutrient utilization after seed germination. Here, we collected and investigated endophytic bacterial microbiomes in edible pea (Pisum sativum) embryos using five representative cultivars and a pea sprout control. Twenty-six nitrogen-fixing bacteria (NFBs) were isolated from pea embryos, with three strains found in fresh pea (FGP) and snow pea (SP) exhibiting the strongest nitrogenase activity. Some NFB isolates are also potassium-solubilizing bacteria (KSBs) or phosphorus-solubilizing bacteria (PSBs) utilizing inorganic and/or organic phosphorus. All 26 NFBs showed variable levels of indole-3-acetic acid (IAA) secretion. The nutrient-solubilizing NFBs identified in our research are valuable resources for biofertilizer development. At the microbiome level, high-throughput 16S ribosomal RNA (rRNA) sequencing of 40 bacterial collections from pea embryos revealed similar community structures and species abundances and diversities in most samples. Our embryo-derived endophytic bacterial pool provides a microbiome platform for seed dormancy and germination research of edible peas.

As an important support for power system with high penetration of renewable energy, energy storage system (ESS) has changed the traditional model of simultaneous implementation of electricity production and consumption, and its installed capacity under the source-grid-load scenario is rising year by year, but it faces the problems of insufficient utilization and benefits. This study analyzes the functional combination of ESS under the source-grid-load scenarios, and proposes a comprehensive benefit evaluation method of energy storage projects based on fuzzy decision-making trial and evaluation laboratory (DEMATEL) and super efficiency data envelopment analysis (DEA) model, which considers the perspective of economic and social environment. Firstly, the functional requirements of energy storage on the source-grid-load scenarios are explored respectively, and the characteristics of various functions are analyzed to form functional combination schemes. Secondly, index modeling is carried out from three aspects: the whole life cycle cost, functional combination benefit and social environmental benefit, and the comprehensive benefit evaluation index system of energy storage project is proposed, which includes both economic and social environment. Then, the intuitionistic trapezoidal fuzzy number is combined with DEMATEL to form an effective analysis method for the input-output relationship of the indexes, and the comprehensive evaluation is realized based on the super efficiency DEA model. Finally, the effectiveness of the proposed evaluation method and the rationality of the functional combination are verified under source-grid-load scenarios respectively.

Cooperative Non-Orthogonal Multiple Access (NOMA) with Simultaneous Wireless Information and Power Transfer (SWIPT) communication can effectively improve the spectrum efficiency and energy efficiency of the wireless networks with extend coverage. An important design issue is to incentivize a relaying center user to participate in the cooperative process and achieve a win-win situation to both the BS and the center user. Some private information of the center users are hidden from the BS in the networks. We apply a contract theory-based incentive mechanism under such asymmetric information scenario to incentives center user to join the cooperative communication to maximize the BS profit utility and to guarantee the center user’s expect payoff. A match theory-based Gale-Shapley algorithm is proposed to obtain the optimal strategy with low computation complexity. Simulation results indicated the network performance of our proposed cooperative transmission is much better than the conventional NOMA transmission and the benefit utility of the BS with the stable match strategy is nearly close to the complete channel state information multi-users scenario while the center users get the satisfied expect payoffs.

This paper analyzes the measurement error, caused by the position of the current-carrying conductor, of circular array of magnetic sensors for current measurement. The circular array of magnetic sensors is an effective approach for AC or DC non-contact measurement, as its low cost, large linear range, wide bandwidth, light weight and low noise. Especially it has claimed that such structure has the excellent reduction ability for the errors caused by the position of the current-carrying conductor, crosstalk current interference, shape of the conduction cross section and the earth magnetic field. However, the positions of the current-carrying conductor, including un-center and un-perpendicularity, has not analyzed in detail until now. In this paper, the theoretical analysis has been proposed based on vector inner and exterior product. In the presented mathematical model of relative error, the un-center offset distance, the un-perpendicular angle, the radius of the circle and the number of the magnetic sensor are expressed in one equation. The comparison of the relative error caused by the position of the current-carrying conductor between four and eight sensors is conducted. The Tunnel Magnetoresistance (TMR) sensors are used in the experimental prototype to verify the mathematical model. The analysis results can be the reference to design the detail of circular array of magnetic sensors for current measurement in practical situation.

Land cover segmentation, a fundamental task within the domain of remote sensing, boasts a broad spectrum of application potential. In this article, we focus on the land cover segmentation tasks and complete the following research work: Firstly, to address the issues of uneven distribution of foreground and background and significant differences in target scales in remote sensing images, we propose a decoder called MDCFD based on multi-dilation rate convolution fusion. The decoder utilizes dilated convolution to expand the receptive field, enhancing the model's ability to capture global features and thus improving the model's ability to distinguish between foreground and background. Meanwhile, we design a multi-dilation rate convolution fusion module (MDCFM), which fuses the outputs of different dilation rate convolution layers. Secondly, aiming at the problems of diverse scenes, significant differences between categories, and many background interferences in remote sensing images, we propose a hybrid attention module called LKSHAM based on large kernel convolution. This module combines spatial attention and channel attention mechanisms and combines the two attention modules in series. By introducing large kernel convolution, the model's ability to extract contextual information is improved. At the same time, we adopt a strategy of decomposing large kernel convolution into multiple depthwise convolutions to reduce computational complexity. The improved network models designed by this paper can achieve an improvement of over 1.1% in the mIoU metric on segmentation tasks on the Potsdam and Vaihingen datasets.

This paper proposes a new battery balancing control strategy based on state of charge (SOC) for addressing the problem of cell-to-cell differences in lithium-ion battery systems. The strategy utilizes a reconfigurable converter system to transfer energy from high-SOC battery modules to low-SOC battery modules and allows balancing the battery modules while they are powering the load. A MATLAB/Simulink simulation model with five batteries was built to validate the effectiveness of the proposed balancing strategy under unloaded and loaded conditions. The simulation results demonstrate that the proposed strategy achieves more efficient and accurate battery module balancing compared to the previous balancing modes, thus increasing the overall lifespan and safety of the battery pack.

The ultrasonic vibration assisted pressing process can improve the fluidity, the uneven distribution of density and particle size of WC-Co powder. However, the microscopic mechanism of ultrasonic vibration on the powder remains unclear. In this paper, WC and Co particles are simulated by three-dimensional spherical models of two particle sizes with the aide of the secondary development of Python. At the same time, the forming process of powder at mesoscale is simulated in the virtue of the finite element analysis software ABAQUS. The influence of vibration amplitude on the fluidity, the filling density and the stress distribution of WC-Co powder is investigated when the ultrasonic vibration is applied to the conventional pressing process. From simulation results, the ultrasonic vibration amplitude has great influences on the density of the compact. With the increase of the ultrasonic amplitude, the compact density also increases gradually. At the initial stage of the compaction, the particles move violently under the action of ultrasonic vibration, the fluidity is obviously enhanced, the arch bridge effect between particles is destroyed, the fine particles quickly fill the pores between the large particles, which increase the density, and the residual stress in the billet decreases after the compaction. From the experimental results, the size distribution of the billet is more uniform, the elastic aftereffect is reduced, the dimensional instability is improved, and the density curves obtained by experiment and simulation are within a reasonable error range.

Survival models have become popular for credit risk estimation. Most current credit risk survival models use an underlying linear model. This is beneficial in terms of interpretability but is restrictive for real-life applications since it cannot discover hidden nonlinearities and interactions within the data. This study uses discrete time survival models with embedded neural networks as estimators of time to default. This provides flexibility to express nonlinearities and interactions between variables, and hence allows for models with better overall model fit. Additionally, the neural networks are used to estimate Age-Period-Cohort (APC) models so that default risk can be decomposed into time components for loan age (maturity), origination (vintage) and environment (e.g., economic, operational and social effects). These can be built as general models, or as local APC models for specific customer segments. The local APC models reveal special conditions for different customer groups. The corresponding APC identification problem is solved by a combination of regularization and fitting the decomposed environment time risk component to macroeconomic data, since the environmental risk is expected to have a strong relationship with macroeconomic conditions. Our approach is shown to be effective when tested on a large publicly available US mortgage data set. This novel framework can be adapted by practitioners in the financial industry to improve modelling, estimation and assessment of credit risk.

The Loess Plateau is an important region for vegetation restoration in China, however, changes in soil organic carbon (SOC), soil nutrients, and stoichiometry after restoration in this vulnerable ecoregion are not well understood. Typical restoration types, including orchardland (OL), grassland (GL), shrubland (SL), and forestland (FL) were chosen to examine changes in the stocks and stoichiometry of SOC, soil total nitrogen (TN), and soil total phosphorus (TP) at different soil depths and recovery times. Results showed that SOC stocks first increased and then stabilized in OL, GL, and SL at 0–30 cm depth, while in FL, stocks gradually increased. Soil TN stocks first increased and then decreased in OL, SL, and FL with vegetation age at 0–30 cm depth, while soil TP stocks showed little variation between restoration types. In the later stages of restoration, the stocks of SOC and soil TN at 0–30 cm soil depth were still lower than those in natural grassland (NG) and natural forest (NF). The overall C:N, C:P, and N:P ratios increased with vegetation age. Additionally, the SOC, soil TN and soil TP stocks, and C:N, C:P, and N:P ratios decreased with soil depth. The FL had the highest rate of change in SOC and soil TN stocks, at 0-10 cm soil depth. These results indicate a complex response of SOC, soil TN, and soil TP stocks and stoichiometry to vegetation restoration, which could have important implications for understanding C, N, and P changes and nutrient limitations after vegetation restoration.

Ground-level ozone (O3) increases in the northeastern part of Eurasia, where larch species are dominant trees and have been planted intensively. The Japanese larch (Larix kaempferi; hereafter larch) is classified as the tree species most of its sensitive to O3 based on data from long-shoot needles of seedlings. This criterion should be reconsidered based on O3 uptake, which is strongly depended on stomatal conductance (Gs) of adult trees through the difference in relevant needle traits. Because Gs is closely correlated with photosynthetic activity, we measured the in situ seasonal and yearly change in photosynthetic function, needle mass per area (LMA) and nitrogen (N) content of both short- and long-shoot needles of the canopy of larch trees over successive 3 years. No difference was observed in the in light saturated photosynthetic rate at ambient CO2 (Psat) between needles of hetero types of shoot in the latter part of the growing season, but clear differences were found within a specific year, indicating that seasonal changes in climatic factors determine Psat in the long term. The Psat-N relations differed significantly between the needle types. However, Psat at saturated CO2 (Pmax)-N was quite similar, implying that the CO2 diffusion difference between short- and long-shoots is responsible for the differing Psat -N. In conclusion, seasonal and yearly variations in photosynthetic capacity are mainly determined mainly by climatic variations, whereas shoot type determined the traits of photosynthetic N utilization as well as Gs regulation.

Direct laryngoscope and videolaryngoscope are the dominant endotracheal intubation tools. Styletubation technique (using a video-assisted intubating stylet) has shown its advantages regarding in short intubation time, high success rate, less stimulation, and operator’s satisfaction. The learning curve can be steep but easy to overcome if the technical pitfalls could be avoided. Conditions make styletubation challenging include secretions/blood, short/stiff neck, restricted mouth opening and cervical spine mobility, anatomical abnormalities over head and neck regions, and obesity, etc. In this clinical report, we present the effectiveness and efficiency of routine use of the styletubation for tracheal intubation in a super-super obese patient (BMI 103 kg/m2) undergoing bariatric surgery with laparoscopic sleeve gastrectomy.

With superior optical properties, high flexibility in engineering its material properties, and strong capability for large-scale on-chip integration, graphene oxide (GO) is an attractive solution for on-chip integration of two-dimensional (2D) materials to implement functional integrated photonic devices capable of new features. Over the past decade, integrated GO photonics, representing an innovative merging of integrated photonic devices and thin GO films, has experienced significant development, leading to a surge in many applications covering almost every field of optical sciences. This paper reviews the recent advances in this emerging field, providing an overview of the optical properties of GO as well as methods for the on-chip integration of GO. The main achievements made in GO hybrid integrated photonic devices for diverse applications are summarized. The open challenges as well as the potential for future improvement are also discussed.

Four angucycline glycosides including three new compounds landomycin N (1), galtamycin C (2) and vineomycin D (3), and a known homologue saquayamycin B (4), along with two alkaloids 1-acetyl-β-carboline (5) and indole-3-acetic acid (6), were identified from the fermentation broth of an intertidal sediments derived Streptomyces sp. Their structures were mainly established by IR, HR-ESI-MS, 1D and 2D NMR techniques. Among the isolated angucyclines, saquayamycin B displayed potent cytotoxic activity against hepatoma carcinoma cells HepG-2, SMMC-7721 and plc-prf-5, with IC50 values 0.135, 0.033 and 0.244 μM respectively, superior to positive drug doxorubicin. Saquayamycin B treatment to SMMC-7721 cells led to the typical morphological signs of apoptosis in 4',6-diamidino-2-phenylindole (DAPI) staining experiment.

Livestock farming plays a crucial role in agriculture and is important in meeting people's needs for a better life in the new era. However, due to China's "double carbon" target, the development of animal husbandry has been affected by the level of carbon emissions. To study the spatial dis-tribution and dynamic evolution of livestock carbon emissions in Shandong Province, we used panel data from 16 prefecture-level cities in Shandong Province from 2001 to 2022 to determine the spatial differentiation of livestock carbon emissions in Shandong Province and their dynamic evolution by combining spatial and non-parametric estimation methods based on livestock carbon emissions and livestock emission intensity measured by city. The results of the study show that the distribution of carbon emissions from animal husbandry in Shandong Province is in a "dis-persed-aggregated" pattern, and the intensity of carbon emissions shows a gradual downward trend, with a ladder-like distribution characterized by high in the west and low in the east. Through the analysis of the dynamic evolution of nuclear density, we observe that the regional differences of animal husbandry carbon emissions in Shandong Province are expanding, showing the characteristics of polarization. The difference of carbon emissions in the peninsula is gradually narrowing, and the phenomenon of polarization is weakening. The carbon emissions of animal husbandry in the central and western regions of Shandong are polarized.

African swine fever virus (ASFV), a highly contagious pathogen characterized by a complex structure and a variety of immunosuppression proteins, causes hemorrhagic, acute, and aggressive infectious disease that severely injure the pork product and industry. However, there is no effective vaccine or treatment. The main reasons are not only the complex mechanisms that lead to immunosuppression, but also the unknown functions of various proteins. This review summarizes the interaction between ASFV and host immune system, along with the involvement of virulence related genes and proteins, as well as the corresponding molecular mechanism of immunosuppression of ASFV, encompassing pathways such as cGAS-STING, NF-κB, JAK/STAT, apoptosis, and other modulation. The aim is to summarize the dynamic process during the ASFV infection and entry into host cell, provide a rational insight into development of vaccine and a better clear knowledge of how ASFV impacts host.

In order to study the adsorption process and adsorption characteristics of shale oil at the macro scale, the isothermal adsorption experiments of illite and kerogen on heptadecane (oil phase) solution were carried out by infrared spectrophotometry and gas chromatography-mass spectrometry. The reaction mechanism of alkane solution concentration and temperature in the adsorption process was investigated. The adsorption characteristics of heptadecane on the surface and pores of illite and kerogen were elucidated by adsorption isotherm model and adsorption thermodynamic model. The results show that: The concentration of alkane solution contributes to the adsorption of illite and kerogen. As the concentration of the solution continues to increase, the adsorption rate gradually slows down. However, the temperature hardly affects the adsorption rate. At 25℃, 50℃ and 60℃, the adsorption process of illite on alkane solution is more consistent with Langmuir model and Freundlich model, respectively. The difference is that Langmuir model is suitable for describing the whole adsorption process of kerogen on alkane solution. 3) The adsorption process of illite and kerogen to heptadecane solution is an endothermic reaction. Heating helps to accelerate the migration rate of alkanes, which is conducive to the adsorption reaction. The research results clarify the adsorption characteristics of shale oil heavy components from the macro level, and fill the research gap in the application of solid-liquid isothermal adsorption physical experiments to the adsorption and occurrence of shale oil.

In response to the issues of sensor noise and accumulated motion errors that lead to low positioning accuracy and insufficient robustness during large maneuvers or continuous flight of small unmanned aerial vehicles (UAVs) in complex environments, this paper proposes a multi-source and multimodal data fusion method. Initially, it employs a multimodal data fusion of various sensors including GPS (Global Positioning System), IMU (Inertial Measurement Unit), and visual sensors to complement the strengths and weaknesses of each hardware component, thereby eliminating motion errors to enhance accuracy. To mitigate the impact of sudden changes in sensor data, the method introduces a digital twin UAV data source. By utilizing the Extended Kalman Filter algorithm, it fuses data from both the real UAV and its digital twin, and the filtered positional information is fed back into the control system of the real UAV. This enables real-time correction of UAV positional deviations caused by sensor noise and environmental disturbances. The multi-source multimodal fusion Kalman filter method proposed in this paper significantly improves the positioning accuracy of UAVs in complex scenarios and the overall stability of the system. This method holds significant value in maintaining high-precision positioning in variable environments and has important practical implications for enhancing UAV navigation and application efficiency.

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.

Abstract: Tumor-targeting and blood-brain barrier (BBB)-penetrating are highly desirable for the treatment of glioma. In this study, we developed Pep-1&borneol-bifunctionalized carmustin-loaded micelles (Pep-1/Bor/CMS-M) capable of targeting to IL-13 receptor-overexpressed glioma and penetrating the brain microvascular endothelial cells-associated physiologic barriers. Pep-1/Bor/CMS-M were nearly spherical particles with a dimeter of 32.6 ± 1.1 nm and zeta potential of -21.3 ± 3.1 mV. Carmustine (CMS) released from Pep-1/Bor/CMS-M in pH 7.4 was significantly faster than in acidic environments. In human glioma BT325 cellular studies, Pep-1/Bor/CMS-M remarkably increased the cytotoxicity, notably improved the internalization and effectively induced the cell apoptosis. Likewise, in human brain microvascular endothelial cells (HBMEC) cells, Pep-1/Bor/CMS-M obviously promoted the cellular uptake, rapidly decreased the transepithelial electrical resistance (TEER) and thereby of enhancing the ability of penetration. In orthotopic Luc-BT325 glioma tumor-bearing nude mouse models, the stronger fluorescence signal and longer retention were observed in brain tissues compared with other controls, after single administration of DiD-labelled Pep-1/Bor/M (DiD/Pep-1/Bor/M). Importantly, Pep-1/Bor/CMS-M displayed the strongest inhibition of tumor growth, the longest survival period and low systemic toxicity in treating orthotopic glioma tumor-bearing nude mice. Simultaneous functionalization of Pep-1 and borneol offers a novel strategy for designing CMS-based nanomedicine and precisely treating glioma.

Age-related Macular Degeneration (AMD) is the major cause of elders’ vision loss, early screening and treatment are the most efficient way to reduce the rate of blindness. AI-based methods based on ophthalmic images play great potential for AMD diagnosis. However, low levels of accuracy, robustness, and explainability are challenges for AI approaches applied in clinics. Thus, this study proposed a multi-type of data source fusion method and a multi-model fusion approach for AMD detection. Typical unsupervised (Hierarchical Clustering and K-Means), typical supervised (SVM, VGG-16, and ResNet) methods, and proposed methods (multi-source data fusion-based method and multi-model fusion-based approach) are compared based on Optical Coherence Tomography (OCT), Fundus Autofluorescence (FAF), regular color fundus photography (CFP) and Ultra-Wide field Fundus (UWF) images. Data preprocessing and enhancements of each type of data are discussed. A feature extraction based on unsupervised ML models, feature combination and normalization, and multi-layer perception (MLP) algorithm are involved in the proposed multi-source data fusion-based method. Supervised ML and DL models and a voting mechanism are involved in the multi-model fusion-based approach. Findings show that the proposed methods present a high performance of accuracy and robustness. A real-world UWF database is involved from Shenzhen Aier Hospital. Practical and theoretical contributions are delivered. A reference value for medical diagnosis based on multiple digital images is contributed.

Rationale: The 14-3-3 protein family is known to interact with many proteins in non-cardiac cell types to regulate multiple signaling pathways, particularly those relating to energy and protein homeostasis; and the 14-3-3 network is a therapeutic target of critical metabolic and proteostatic signaling in cancer and neurological diseases. Although the heart is critically sensitive to nutrient and energy alterations, and multiple signaling pathways coordinate to maintain the cardiac cell homeostasis, neither the structure of cardiac 14-3-3 protein interactome, nor potential functional roles of 14-3-3 protein-protein interactions (PPIs) in heart has been explored. Objective: To establish the comprehensive landscape and characterize the functional role of cardiac 14-3-3 PPIs. Methods and Results: We evaluated both RNA expression and protein abundance of 14-3-3 isoforms in mouse heart, followed by co-immunoprecipitation of 14-3-3 proteins and mass spectrometry in left ventricle. We identified 52 proteins comprising the cardiac 14-3-3 interactome. Multiple bioinformatic analyses indicated that more than half of the proteins bound to 14-3-3 are related to mitochondria; and the deduced functions of the mitochondrial 14-3-3 network are to regulate cardiac ATP production via interactions with mitochondrial inner membrane proteins, especially those in mitochondrial complex I. Binding to ribosomal proteins, 14-3-3 proteins likely coordinate protein synthesis and protein quality control. Localizations of 14-3-3 proteins to mitochondria and ribosome were validated via immunofluorescence assays. The deduced function of cardiac 14-3-3 PPIs is to regulate cardiac metabolic homeostasis and proteostasis. Conclusions: Thus, the cardiac 14-3-3 interactome may be a potential therapeutic target in cardiovascular metabolic and proteostatic disease states, as it already is in cancer therapy.

If given the correct remotely sensed information, machine learning can accurately describe soil moisture conditions in a heterogeneous region at the large scale based on soil moisture readings at the small scale through rule transference across scale. This paper reviews an approach to increase soil moisture resolution over a sample region over Australia using the Soil Moisture Active Passive (SMAP) sensor and Landsat 8 only and a validation experiment using Sentinal-2 and the Advanced Microwave Scanning Radiometer (AMSR-E) over Nevada. This approach uses an inductive localized approach, replacing the need to obtain a deterministic model in favor of a learning model. This model is adaptable to heterogeneous conditions within a single scene unlike traditional polynomial fitting models and has fixed variables unlike most learning models. For the purposes of this analysis, the SMAP 36 km soil moisture product is considered fully valid and accurate. Landsat bands coinciding in collection date with a SMAP capture are down sampled to match the resolution of the SMAP product. A series of indices describing the Soil-Vegetation-Atmosphere Triangle (SVAT) relationship are then produced, including two novel variables, using the down sampled Landsat bands. These indices are then related to the local coincident SMAP values to identify a series of rules or trees to identify the local rules defining the relationship between soil moisture and the indices. The defined rules are then applied to the Landsat image in the native Landsat resolution to determine local soil moisture. Ground truth comparison is done via a series of grids using point soil moisture samples and air-borne L-band Multibeam Radiometer (PLMR) observations done under the SMAPEx-5 campaign. This paper uses a random forest due to its highly accurate learning against local ground truth data yet easily understandable rules. The predictive power of the inferred learning soil moisture algorithm did well with a mean absolute error of 0.054 over an airborne L-band retrieved surface over the same region.

In this paper, a polyacrylic elastomer latex with butyl acrylate (BA) as the core and methyl methacrylate (MMA) copolymerized with glycidyl methacrylate (GMA) as the shell, named poly(BA-MMA-GMA) (PBMG), was synthesized by seeded emulsion polymerization. Cellulose nanocrystal (CNC) was dispersed in the polyacrylic latex to prepare PBMG/CNC dispersions with different CNC contents. The dried product was mixed with polylactic acid (PLA) to fabricate PLA/PBMG/CNC blends. The addition of PBMG and PBMG/CNC improved the mechanical properties of the PLA matrix. Differential scanning calorimetry (DSC) was used to investigate the non-isothermal crystallization kinetics. The Avrami equation modified by Jeziorny, and the Ozawa, and Mo’s equations were used to analyze the nonisothermal crystallization kinetics of PLA and its blends. Analysis of crystallization halftime of nonisothermal conditions indicated that the overall rate of crystallization increased significantly at 1 wt% content of CNC. This seemed to result from the increase of nucleation density and the acceleration of segment movement in the presence of CNC component. This phenomenon was verified by polarizing microscope observation.

The Koka gold deposit is located in the Elababu shear zone between the Nakfa terrane and the Adobha Abiy terrane, NW Eritrea. Based on the paragenetic study two main stages of gold mineralization were identified in the Koka gold deposit: 1) an early stage of pyrite-chalcopyrite-sphalerite-galena-gold-quartz vein; and 2) a second stage of pyrite-quartz veins. NaCl-aqueous inclusions, CO2-rich inclusions, and three-phase CO₂-H₂O inclusions occur in the quartz veins at Koka. The ore-bearing quartz veins formed at 268℃, from NaCl-CO₂-H₂O(-CH₄) fluids averaging 5 wt% NaCl eq. The ore-forming mechanisms include fluid immiscibility during stage I, and mixing with meteoric water during stage II. Oxygen, hydrogen and carbon isotopes suggest that the ore-forming fluids originated as mixtures of metamorphic water, meteoric water and magmatic water, whereas sulfur isotope suggest an igneous origin. Features of geology and ore-forming fluid at Koka deposit are similar to those of orogenic gold deposits, suggesting the Koka deposit might be an orogenic gold deposit related to granite.

Examining the soil microbiome structure has a great significance in exploring the mechanism behind plant growth changes due to maize (Zea mays L.) and soybean (Glycine max Merr.) crop rotation. This study explored the effects of soil microbial community structure after soybean and maize crop rotation by designing nine treatments combining three crop rotations (continuous cropping maize or soybean; and maize after soybean) with three fertility treatments (organic compound fertilizer, chemical fertilizer, or without fertilizer). Soil was sampled to 30 cm depth the second year at approximately the middle of the growing season, and was analyzed for physical, chemical, and phospholipid fatty acid (PLFA) profiles. Bacteria was found to be the predominant component of soil microorganisms, which mainly contain the PLFAs i15:0, 16:1 ω 7c, 16:0, 10Me16:0, and 18:1 ω 7c. The concentration of soil gram-negative bacteria from the soybean and maize rotation was less than in soybean continuous cropping when organic fertilizer was applied to both. Crop rotation reduced the percentage of fungi in the soil, among which the effect of organic compound fertilizer application was significantly reduced 24%. The combined crop rotation with organic fertilizer can reduce maximum the percentage of fungi/bacteria. In addition, the content of soil aggregate and organic matter had great influence on gram-positive bacteria and actinomyces, and soil pH had a greater impact on other fungi.

How to improve plant tolerance and yield under salt stress is critical for ensuring sufficient food supply since plant survival and agricultural productivity are both affected by salinity. Some evidence has showed that beneficial microorganisms have a high ability to improve plant salt tolerance and increase crop yield. But few studies were involved in effects of halotolerant yeasts on plants under salt stress. In this present research, Meyerozyma guilliermondii, a halotolerant yeast, was inoculated with tomato plants followed by salt treatment of four different NaCl concentrations (0, 100, 200, and 300 mM). Our results showed that inoculation of M. guilliermondii increased the chlorophyll biosynthesis and photosynthetic machinery effectiveness under salt stress, contributing to biomass accumulation. Under salt treatment of 300 mM NaCl, the yeast inoculation significantly increased ascorbate concentrations in leaves, yet showed no effects on levels of glutathione and proline. Antioxidant enzymes were affected differently by the yeast inoculation. It was found that the yeast inoculation increased superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) activities under 300, 100, and 200 mM NaCl, respectively. Total soluble sugar levels increased in inoculated tomato plant leaves; however, there were no significant differences between different NaCl concentrations. Under 300 mM NaCl, the yeast inoculation significantly decreased H2O2 levels and reduced malondialdehyde levels. All together, our results showed that halotolerant yeast M. guilliermondii inoculation might be a strong candidate for regulating tomato growth under salt stress by increasing ability to scavenge reactive oxygen species and chlorophyll intactness, and by strengthening photosynthetic machinery.

Blockchain technology has been recognized as a promising solution to enhance the security and privacy of Internet of Things (IoT) and Edge Computing scenarios. Taking advantage of the Proof-of-Work (PoW) consensus protocol, which solves a computation intensive hashing puzzle, Blockchain assures the security of the system by establishing a digital ledger. However, the computation intensive PoW favors members possessing more computing power. In the IoT paradigm, fairness in the highly heterogeneous network edge environments must consider devices with various constraints on computation power. Inspired by the advanced features of Digital Twins (DT), an emerging concept that mirrors the lifespan and operational characteristics of physical objects, we propose a novel Miner-Twins (MinT) architecture to enable a fair PoW consensus mechanism for blockchains in IoT environments. MinT adopts an edge-fog-cloud hierarchy. All physical miners of the blockchain are deployed as microservices on distributed edge devices, while fog/cloud servers maintain digital twins that periodically update miners’ running status. By timely monitoring miner’s footage that is mirrored by twins, a lightweight Singular Spectrum Analysis (SSA) based detection achieves to identify individual misbehaved miners that violate fair mining. Moreover, we also design a novel Proof-of-Behavior (PoB) consensus algorithm to detect byzantine miners that collude to compromise a fair mining network. A preliminary study is conducted on a proof-of-concept prototype implementation, and experimental evaluation shows the feasibility and effectiveness of proposed MinT scheme under a distributed byzantine network environment.

In this study, Li-Al-OH layered double hydroxide (LDH), which was prepared by solvent-free one-step mechanochemical reaction of LiOH and Al(OH)₃, was applied to remove boron from aqueous solution. Dry-grinding for 3 h at a rotational speed of 500 rpm, Li/Al molar 1/2 was the optimum condition to prepare highly crystalline of Li-Al LDH phase with no evident impure phases. Two milling products with Li/Al molar ratio at 1/2 and 2/2 were evaluated for boron adsorption. The results confirmed that Li/Al molar ratio 2/2 sample showed high boron adsorption capacity due to the physical adsorption of Li-Al-OH LDH and chemical synergism of phase gel Al(OH)₃. The adsorption isotherms, described by the Langmuir model, indicated maximum monolayer boron uptake capacity 45.45 mg/g, implying competitive adsorption capacity of the material in our experiment.

Background: Atherosclerosis (AS) is a chronic progressive disease caused by lipometabolic disorder. However, the pathological characteristics and mechanism of AS have not been fully clarified. By high fat and cholesterol diet induction, Tibetan minipig could be developed to the AS model animal which had a very similar pathogenesis to human AS. Methods: Here, we built the AS model of Tibetan minipigs and identified the differential abundance metabolites in the development of AS based on untargeted metabolomics. Results: We found that the sphingolipid metabolism and glucose oxidation were enriched in the AS group and the phenylalanine metabolism was reduced in the AS group. Moreover, in the development of AS, gluconolactone was enriched in the late stage of AS whereas biopterin was enriched in the early stage of AS. Conclusion: Gluconolactone and biopterin could be potential biomarkers for indicating the development of AS. Our research provides novel clues for the metabolic mechanism of AS from the perspective of metabolomics.

Plastic materials have revolutionized modern life, particularly in the domain of food packaging, owing to their versatility, lightweight nature, and ease of processing. However, the environmental ramifications of non-degradable plastics have raised concerns. Polylactic acid (PLA), derived from renewable sources, presents a sustainable alternative due to its biodegradability and exceptional barrier, mechanical, and safety properties. Nevertheless, the high UV transmittance of PLA limits its use for photosensitive food and pharmaceutical packaging, where UV radiation can lead to nutritional loss and spoilage. Various methods have been explored to enhance the UV-blocking capabilities of PLA, including the integration of inorganic nanoparticles and surface coatings. Despite advancements, these approaches often compromise the inherent transparency of PLA. Incorporating large conjugated groups can maintain transparency but introduces additional challenges. This paper reviews modification methods to enhance PLA's UV-barrier properties and anticipates its expanded utility in food and drug packaging, promoting UV resistance and diversifying PLA's applications.

Unmanned agricultural tractor (UAT) represents the advanced stage of autonomous navigation and serves as a core technology in agricultural production. It reduces the operator’s workload, and improves operational accuracy and efficiency. This article reviews three aspects of key autonomous navigation technologies for UATs: perception, path planning and tracking, and motion control. The advantages, and shortages of these key technologies on UATs are clarified by analyzing technical principles and the current research status. We conducted summaries and analyses of existing unmanned navigation solutions for different application scenarios in order to identify current bottleneck issues. Based on the analysis of the applicability of key autonomous navigation technologies on UATs, it can be seen that fruitful research progresses have been achieved. The review also summarizes the common problems in current technologies. The application research on sharing and integrating multi-source data for autonomous navigation are relatively weak. There is an urgent need of high-precision, and high-stability sensing equipment. The universality of path planning methods, and the efficiency and precision of path tracking need to be improved. It is necessary to develop high reliability electrical control modules to enhance motion control performance. Overall, advanced sensors, high-performance intelligent algorithms, and reliable electrical control hardware are key factors in promoting the development of UAT technology.

Litsea cubeba, an important medicinal plant, is widely used as traditional Chinese medicine and spice. Using cytotoxicity-guided fractionation, nine new lignans (1-9) and eleven known analogues (10-19) were obtained from the EtOH extract of the twigs of L. cubeba. Their structures were assigned by extensive 1D and 2D NMR experiments, and the absolute configurations were resolved by specific rotation and a combination of experimental and theoretically calculated electronic circular dichroism (ECD) spectra. In the cytotoxicity assay, 7',9-epoxylignans with feruloyl or cinnamoyl group (7-9, 13 and 14) were selectively cytotoxic against NCI-H1650 cell line, while the dibenzylbutyrolactone lignans (17-19) exerted cytotoxicities against HCT-116 and A2780 cell lines. The results highlighted the structure-activity relationship importance of a feruloyl or a cinnamoyl moiety at C-9′ or/and C-7 ketone in 7',9-epoxylignans. Furthermore, compound 11 was moderate active toward protein tyrosine phosphatase 1B (PTP1B) with an IC50 value of 13.5 μM, and compounds 4-6, 11 and 12 displayed inhibitions against LPS-induced NO production in RAW264.7 macrophages, with IC50 values of 46.8, 50.1, 58.6, 47.5, and 66.5 μM, respectively.

An adaptive operation strategy for on-demand control of DMFC system is proposed as an alternative method to enhance the voltage stability. Based on a single-cell DMFC stack, a newly simplified semi-empirical model is developed from the uniform-designed experimental results to describe the I-V relationship. Integrated with this model, the multi-objective optimization method is utilized to develop an adaptive operation strategy. Although the voltage instability is frequently encountered in unoptimized operations, the voltage deviation is successfully decreased to a required level by adaptive operations with operational adjustments. Moreover, the adaptive operations are also found to be able to extend the range of operating current density or to decrease the voltage deviation according to ones requirements. Numerical simulations are implemented to investigate the underlying mechanisms of the proposed adaptive operation strategy, and experimental adaptive operations are also performed on another DMFC system to validate the adaptive operation strategy. Preliminary experimental study shows a rapid response of DMFC system to the operational adjustment, which further validates the effectiveness and feasibility of the adaptive operation strategy in practical applications. The proposed strategy contributes to a guideline for the better control of output voltage from operating DMFC systems.

The increasing amount of municipal sludge in China requires safe and effective management to protect human health and ensure environmental sustainability. Pyrolysis is a thermochemical process that that decompose organic matter at elevated temperature and under anaerobic conditions, and it has attracted an increasing attention in sludge treatment in the recent years. However, comprehensive environmental and economic assessment of sludge pyrolysis in China's context is rare, due to the small quantities of full-scale sludge pyrolysis plant. In this paper, we applied our design and operation parameters of full-scale sludge pyrolysis plants to generate the material and energy consumptions of the pyrolysis system under various of conditions, including sludge organic content and moisture content, system size, system energy distribution, and whether or not heat substitution is applied. Life cycle assessment and techno-economic assessment were then applied to investigate the environmental and economic performance of the system Our results demonstrate the significant environmental and economic impacts associated with sludge properties and system size. Generally, sludge with higher organic content and lower moisture content requires less natural gas consumption, which leads to a simultaneous improvement of the system environmental and economic performance. The system economic performance is more sensitive to the system size, and centralized sludge handling using a larger pyrolysis is more economic favorable. In the most ideal case, the average global warming potential and minimum sludge handling price of sludge pyrolysis could be as low as -32.5 kg CO₂-Eq/t DS and 188.8 $/t DS, respectively. Based on these results, we discussed the pathways that could be taken to further optimize the environmental and economic performances of the pyrolysis system.

Results showed that mulberry leaves could significantly reduce backfat thickness (P<0.05) and increase intramuscular fat (IMF) content (P<0.05). Lipidomics analysis showed that mulberry leaves improved lipid profile composition and increased the proportion of triglycerides (TG). Interestingly, IMF content was positively correlated with acyl C18:2 and negatively correlated with C18:1 of differential TGs. In addition, cecal microbiological analysis showed that mulberry leaves could increase the abundance of bacteria such as UCG−005, Muribaculaceae_norank, Prevotellaceae_NK3B31_group, Limosilactobacillus, and so on. At the same time improve the L-tyrosine-baton rouge ester, Oleic acid methyl ester, 21-deoxycortisol, N-acetyldihydrosphingosine, Mulberrin relative abundance. In this study, we found that mulberry leaves could extremely significantly increasing the mRNA relative expression of lipoprotein lipase (LPL), fatty acid-binding protein 4 (FABP4) and peroxisome proliferators-activated receptor γ (PPARγ) in muscle (P＜0.01), significantly increasing mRNA relative expression of diacylglycerol acyltransferase 1 (DGAT1) (P＜0.05) and significantly decreasing the mRNA relative expression of acetyl CoA carboxylase (ACC) (P＜0.05), and aignificantly upregulated hormone-sensitive triglyceride lipase (HSL), peroxisome proliferators-activated receptor α (PPARα) mRNA relative expression (P＜0.05) in backfat. In addition mulberry leaves could increased serum leptin and adiponectin (P＜0.01). Ultimately lead to up-regulation of IMF and down-regulation of backfat.

The development of solid-state forms of drugs is an effective mean of solubility enhancement. In this study, two polymorphs named form C, form D, and two co-crystals of sorafenib (SF) with oxalic acid (SF-OA) and malonic acid (SF-MA), by evaporation and slurry method, have been developed and characterized. The single-crystal X-ray diffraction results showed that the structure of form C was similar to of form I. It had similar cellular parameters, but different arrangement of stacking due to π-π conjugation. The drug molecules in SF-OA underwent torsional folding through four hydrogen bonds of intermolecular and intramolecular. The solubility performance of solid-state forms improved significantly. Compared with form I, form C and form D were 1.59, 1.49 times at pH 1.2 HCl, 1.59, 1.87 fold at pH 6.8 PBS. In particular, the SF-OA and SF-MA increased the apparent solubility of SF at pH 1.2 by 8.3 and 6.4 times, at pH 6.8 by 4.0 and 4.5 times respectively. The dissolution mechanisms were analyzed. New solid-state forms showed strong stability at storage conditions of 40 °C/75% RH and 60 °C/0% RH. Notably, the crystal of SF preferred to transform in mixed solvents, and the formation of co-crystals confirmed the ∆pKa rule.

Genomics involving tens of thousands of genes is a complex system determining phenotype. An interesting and vital issue is that how to integrate highly sparse genetic genomics data with a mass of minor effects into prediction model for improving prediction power. We find that deep learning method can work well to extract features by transforming highly sparse dichotomous data to lower dimensional continuous data in a non-linear way. This idea may provide benefits in risk prediction based on genome-wide data associated e.g. integrating most of the information in the genotype data. Hence, we developed a multi-stage strategy to extract information from highly sparse binary genotype data and applied it for risk prediction. Specifically, we first reduced the number of biomarkers via a univariable regression model to a moderate size. Then a trainable auto-encoder was used to extract compact representations from the reduced data. Next, we performed a LASSO problem process over a grid of tuning parameter values to select the optimal combination of extracted features. Finally, we applied such feature combination to two prognostic models, and evaluated predictive effect of the models. The results of simulation studies and real data applying indicated that these highly compressed transformation features could better improve predictive performance and did not easily lead to over-fitting.

Severe respiratory syncytial virus (RSV) infections in early life have been linked to the development of chronic airway disease. RSV is a potent inducer of reactive oxygen species (ROS) which contributes to inflammation and enhanced clinical disease. NF-E2-related factor 2 (Nrf2) is an evolutionary conserved redox-responsive protein that helps to protect cells and whole organisms from oxidative stress and injury. The role of Nrf2 in the context of viral-mediated chronic lung injury is not known. Herein, we show that RSV experimental infection of adult Nrf2 deficient BALB/c mice (Nrf2-/-; Nrf2 KO) is characterized by enhanced disease, increased inflammatory cell recruitment to the bronchoalveolar compartment, and a more robust upregulation of innate and inflammatory genes and proteins, compared to wild type Nrf2+/+ competent mice (WT). These events that occur at very early time points, lead to increased peak RSV replication in Nrf2 KO compared to WT mice (day 5). To evaluate longitudinal changes of the lung architecture, mice were scanned weekly by high-resolution micro-computed tomography (micro-CT) imaging up to 28 days after initial viral inoculation. Based on micro-CT qualitative 2D imaging and quantitative reconstructed histogram-based analysis of lung volume and density, we found that RSV infected Nrf2 KO mice developed significantly greater and prolonged fibrosis compared to WT mice. Results of this study underscore the critical role of Nrf2-mediated protection from oxidative injury not only in acute pathogenesis of RSV infection, but also in its long-term consequences of chronic airway injury.

The aim of this case-series report article is to provide a new topical view of the styletubation (video intubating stylet technique) in obese patients undergoing bariatric surgeries. In contrast to various conventional direct laryngoscopes (DLs), videolaryngoscopes (VLs) have been applied in such obese population with potentially difficult airway populations. The safety and effectiveness of VLs have been repeatedly studied and the superiority of VLs then has been observed and is advocated as a routine use. In this article, among our vast use experiences of the styletubation (more than 54,998 patients since 2016) for routine tracheal intubation, we present such unique experience to apply such intubating technique in obese patient undergoing bariatric surgery. Consistent with the experiences applied in other patient populations, we found the styletubation technique to be swift (the time to intubate from 5 s to 24 s), smooth (first-attempt success rate: 100%), safe (no airway complications), and easy (high subjective satisfaction). The learning curve can be steep but is easily overcome if technical pitfalls are avoided. We, therefore, propose that the styletubation technique can be feasibly applied for tracheal intubation in obese patients undergoing bariatric surgery.

Numerical simulations of turbulent flows in a stirred dead-end membrane bioreactor are performed by the RNG k-ε model based on finite volume method using Fluent codes. Comparisons of numerical and experimental results confirm the reliability and feasibility of the constructed model. Flow structures such as wake flows and circulation loops in stirred flows were well simulated. An increase of stirring speed is proposed to use to minimize the low velocity region. The single vane stirrer is found to be beneficial for biological separations. Results reveal that the increase of vane number can enhance the mixing effect in flow domains. However, a circular disk stirrer goes against the formation of vertical circulations. The six-vane stirrer is found to be able to provide a uniform distribution of high shear stress.

Plant leaf area index (LAI) is a key characteristic affecting field canopy microclimate. In addition to traditional professional measuring instruments, smartphone camera sensors have been used to measure plant LAI. However, when smartphone methods were used to measure conifer forest LAI, very different performances were obtained depending on whether the smartphone was held at the zenith angle or at a 57.5° angle. To validate further the potential of smartphone sensors for measuring conifer LAI and to find the limits of this method, this paper reports the results of a comparison of two smartphone methods with an LAI-2000 instrument. It is shown that both methods can be used to reveal the conifer leaf-growing trajectory. However, the method with the phone oriented vertically upwards always produced better consistency in magnitude with LAI-2000. The bias of the LAI between the smartphone method and the LAI-2000 instrument was explained with regard to four aspects that can affect LAI: gap fraction, leaf projection ratio, sensor field of view (FOV), and viewing zenith angle (VZA). It was concluded that large FOV and large VZA cause the 57.5° method to overestimate the gap fraction and hence underestimate conifer LAI, especially when tree height is greater than 2.0 m. For the vertically upward method, the bias caused by the overestimated gap fraction is compensated for by an underestimated leaf projection ratio.

Carbon nanomaterial is widely used in structural health monitoring due to the advantage of sensitivity and good mechanical properties. This study presents a novel approach employing carbon nanocomposite materials (CNM) to characterize deformation and damage evolution in physical modelling. As the primary measurement method, the CNM is used to investigate the deformation characteristics of a 200-400 m thick sandstone bed at a 1 km deep longwall mine. The sandstone unit is identified as an ultra-thick key stratum (UTKS), with its thicknesses varying across different mining panels of the UTKS. The results of CNM monitoring show that the UTKS remains stable even after a consecutive excavation of 900 m in width. This stability impedes the upward propagation of overlying strata failure, leading to minimal surface subsidence. The study demonstrates the huge potential of CNM in the mining area, which can be useful for investigating material damage in physical modelling studies. The findings suggest that the cumulative extraction width in individual mining areas of the mine should be controlled to avoid a sudden collapse of the UTKS, and that special attention should be paid to where the UTKS's thickness changes substantially. The substantial variation in UTKS thickness significantly impacts the pattern of overburden subsidence.

The Kerr nonlinear optical performance of silicon nanowire waveguides integrated with 2D layered graphene oxide (GO) films is theoretically studied and optimized based on experimentally measured linear and nonlinear optical parameters of the GO films. The strong mode overlap between the silicon nanowires and highly nonlinear GO films yields a significantly enhanced Kerr nonlinearity for the hybrid waveguides. A detailed analysis for the influence of waveguide geometry and GO film thickness on the propagation loss, nonlinear parameter, and nonlinear figure of merit (FOM) is performed. The results show that the effective nonlinear parameter and nonlinear FOM can be increased by up to ≈52 and ≈79 times relative to bare silicon nanowires, respectively. Self-phase modulation (SPM)-induced spectral broadening of optical pulses is used as a benchmark to evaluate the nonlinear performance, examining the trade-off between enhancing Kerr nonlinearity and minimizing loss. By optimizing the device parameters to balance this, a high spectral broadening factor of 27.6 can be achieved ‒ more than 6 times that achieved in previous experiments. Finally, the influence of pulse chirp, material anisotropy, and the interplay between saturable absorption and SPM is also discussed. These results provide useful guidance for optimizing the Kerr nonlinear optical performance of silicon waveguides integrated with 2D layered GO films.

In recent years, laser engraving has received widespread attention as a convenient, efficient, and programmable method, which has enabled the obtaining of high-quality porous graphene from various precursors. Laser engraving is often used to fabricate the dielectric layer with micro-structure for capacitive pressure sensors, however, the usual choice of electrodes remains poorly flexible metal electrodes, which greatly limits the overall flexibility of the sensors. In this work, we propose a flexible capacitive pressure sensor made entirely of thermoplastic polyurethane (TPU) and laser-induced graphene (LIG) derived from wood. The capacitive pressure sensor consisted of a flexible LIG/TPU electrode (LTE), a LIG/TPU electrode with micro hole array, and dielectric layer of TPU with micro-cone array molded from laser-engraved hole array on wood, which provided high sensitivity (0.11 kPa-1), ultra-wide pressure detection range (100Pa to 1.4MPa), fast response (~300 ms) and good stability (>4000 cycles, at 0-35 kPa). We believe that our research makes a significant contribution to the literature because the easily available materials derived from wood and overall consistent flexibility meet the requirements of flexible electronic devices.

In this paper, an intelligent blind guide system based on 2D LiDAR and RGB-D camera sensing is proposed, and the system is mounted on the smart cane. The intelligent guide system relies on 2D LiDAR, RGB-D camera, IMU, GPS, Jetson nano B01, STM32 and other hardware. The main advantage of the intelligent guide system proposed by us is that the distance between the smart cane and obstacles can be measured by 2D LiDAR based on Cartographer algorithm, thus achieving Simultaneous localization and mapping (SLAM). At the same time, through the improved yolov5 algorithm, pedestrians, vehicles, pedestrian crosswalks, traffic lights, warning posts, stone piers, tactile paving and other objects in front of the visually impaired can be quickly and effectively identified. Laser SLAM and improved yolov5 obstacle identification tests were carried out inside a teaching building on the campus of Hainan Normal University and on a pedestrian crossing on Longkun South Road in Haikou City, Hainan Province. The results show that the intelligent guide system developed by us can drive the wheels and omnidirectional wheels at the bottom of the smart cane, and give the smart cane a self-leading blind guide function like a "guide dog", which can effectively guide the visually impaired to avoid obstacles and reach the predetermined destination, and can quickly and effectively identify the obstacles on the way out. The laser SLAM speed of this system is 25~31FPS, which can realize the short-distance obstacle avoidance and navigation function both in indoor and outdoor envionments. The improved yolov5 helps to identify 86 types of objects, the recognition rate for pedestrian crosswalks and for vehicles are 84.6% and 71.8%, respectively; the overall recognition rate for 86 types of objects is 61.2%, and the obstacle recognition rate of the intelligent guide system is 25-26FPS.

Oxygen evolution reaction (OER) is a key half-reaction in electrocatalytic water splitting. Large-scale water electrolysis is hampered by the commercial precious metal-based OER electrocatalysts owing to their high cost and slow kinetics. To address these issues, we present a facile one-pot room-temperature coprecipitation method to quickly synthesize carbon nanotubes-interconnected amorphous NiFe-layered double hydroxides (NiFe-LDH@CNT) as low-cost, efficient and stable OER electrocatalyst. NiFe-LDH@CNT hybrid catalyst delivers outstanding OER performance with a low onset overpotential of 255 mV and a small Tafel slope of 51.2 mV dec-1, as well as outstanding long-term stability. The terrific catalytic capability of NiFe-LDH@CNT can be associated with the synergistic effects of its room-temperature synthesized amorphous structure, bi-metallic modulation, and conductive CNT skeleton. The room-temperature synthesis can not only offer economic feasibility, but also obtain amorphous NiFe-LDH without crystalline boundaries, facilitating long-term stability during OER process. The bi-metallic nature of NiFe-LDH guarantees a modified electronic structure, providing additional catalytic sites. Simultaneously, the highly conductive CNT network fosters a nanoporous structure, facilitating electron transfer, O2 release and enriching catalytic sites. This study presents a strategy to purposefully design nanoarchitecture and facilely synthesize amorphous transition metal-based OER catalysts, ensuring the cost effectiveness, production efficiency, and long-term stability.

The development of novel porous composite materials for organic dye degradation and removal has received increasing attention due to water contamination problem. In this paper, hydrothermal synthesized nano zeolite A have been encapsulated with porous periodic mesoporous organosilica (PMO) through a simple modified StÖber method an organosilane-directed growth-induced etching strategy, the obtained yolk-shell structured sample was further functionalized by the impregnation of copper, realizing the composite material with hierarchical porous and catalytic properties. The morphology, porosity and metal content of the zeolite Cu/A and Cu/A@Et-PMO were fully characterized. As compared to the parent material, the composite Cu/A@Et-PMO have an efficient adsorption and catalytic degradation performance on methylene blue (MB), the removal efficiency reached as high as 95% of 60 mg/L MB with 10min. These novel structured porous composites may have great potential for adsorption and degradation application including waste effluents.

Silicon is an essential trace nutrient for plant growth and is frequently employed to remediate soils contaminated with heavy metals in agriculture. However, silicon’s role and mechanism in reducing heavy metal toxicity have not been well understood, especially for multi-heavy metals. In this study, the effects of silicon-rich materials (silicate, rice husk biochar (RHB), and bentonite) on growth trait, antioxidant response, and heavy metal accumulation and distribution of wheat grown in two soils polluted by multiple heavy metals (Cd, Zn, Pb, and As) were investigated. The results revealed that the addition of silicon-rich materials enhanced plant growth, improved the photosynthetic attributes in leaf tissues, and decreased the contents of Cd, Zn, Pb, and As in wheat shoots and grains. The examination of the subcellular distribution of heavy metals in plants implied that silicon-rich materials transferred heavy metals as intracellular soluble fractions to the cell walls, indicating the reduction of mobility and toxicity of heavy metals in the plants. In addition, the application of the silicon-rich materials reduced oxidative damage in plants by downregulating plant antioxidant response systems and decreasing the production of malondialdehyde (MDA), ascorbic acid (AsA), and glutathione (GSH). Moreover, fractionation analysis of soil heavy metals showed that silicon-rich amendments could convert bioavailable heavy metals into immobilized forms. The results indicated that silicon-rich materials could remediate multi-heavy metal-polluted soils and promote wheat production.

. Manufacturers are increasingly adopting mixed-flow manufacturing models to meet the growing customized, diverse, and dynamic customer demand. In such an environment, material distribution scheduling optimization is vital for smooth operations and is integral to production management. However, manufacturers frequently encounter problems like disordered and delayed material distribution. Traditional scheduling methods suffer from problems like inadequate transparency, delayed decision directives, and suboptimal results, impacting performance. To this end, this study proposes a dynamic material distribution scheduling optimization model and strategy based on digital twin (DT) to address these problems. Firstly, we introduce workstation satisfaction and establish a material distribution path optimization model minimizing total distribution cost while maximizing workstation satisfaction. Subsequently, we present a cloud-edge computing-based decision framework and explain the DT-based material distribution system's components and operation. Furthermore, a dynamic material distribution scheduling optimization mechanism based on DT is designed. By incorporating a savings method and incentive, penalty strategies, improvements are made to the path node selection probabilities and the information pheromone update rules of the traditional ant colony optimization (ACO) algorithm. Finally, a numerical case study, using real data from collaborating enterprises, validates the proposed algorithm and strategy. This research offers valuable insights into logistics management and algorithm design in smart manufacturing environments.

Recent studies have discovered that functional connections are impaired in patients with Parkinson's disease (PD) accompanied by hallucinations(PD-H), even at the preclinical stage. The cerebellum has been implicated as playing a role in cognitive processes. However, the functional connectivity (FC) between cognitive sub-regions of the cerebellum of PD patients with hallucinations needs to be further clarified. Resting-state functional magnetic resonance imaging (rs-fMRI) data from three groups (17 PD-H, 13 no hallucinations accompanying the (PD-NH), and 26 healthy controls (HC) ) was collected in this study to explore the role of cerebellar FC changes in the cognitive performance. Additionally, we define cerebellar FC as a training feature for classifying all subjects using Support Vector Machine(SVM). We found that PD-H patients' cerebellum(Vermis_4_5 ) FC had increased within the left side of the precuneus(PCUN) compared to HC, cerebellum(Vermis_1_2) had increased within bilateral opercular part of the inferior frontal gyrus(IFGoprec) and triangular part of the inferior frontal gyrus(IFCtriang), left side of postcentral gyrus(PoCG), Inferior parietal lobe(IPL), and PCUNs compared to PD-NH. In the training results of machine learning, cerebellar FC has also been proven to be an effective biomarker feature, with a recognition rate of over 90% for PD-H. These findings indicate that cortico-cerebellar FC in PD-H and PD-NH patients were significantly disrupted with different distributions. The proposed pipeline offers a promising low-cost alternative for the diagnosis of preclinical PD-H and can be useful for other degenerative brain disorders.

In order to reduce the influence of ground vibration generated by tractor during driving and operation on driving stability and driver ride comfort, this paper proposes a control method of tractor active seat suspension based on model predictive control. By establishing a 3-degree of freedom tractor active seat suspension model and a ground excitation input model, a new model predictive controller for the active seat suspension system is designed. The vertical acceleration of the seat center of mass, the seat suspension stroke and the tire dynamic displacement are optimized by limiting the dynamic deflection of the seat suspension and the active force output of the actuator. The control model of MPC tractor active seat suspension system is built and its performance is simulated and verified. The results show that compared with the passive seat suspension and the PID seat suspension, the tractor active seat suspension based on model predictive control (MPC) has better damping characteristics and improves ride comfort.

We experimentally demonstrate enhanced spectral broadening of femtosecond optical pulses after propagation through silicon-on-insulator (SOI) nanowire waveguides integrated with two-dimensional (2D) graphene oxide (GO) films. Owing to the strong mode overlap between the SOI nanowires and the GO films with a high Kerr nonlinearity, the self-phase modulation (SPM) process in the hybrid waveguides is significantly enhanced, resulting in greatly improved spectral broadening of the femtosecond optical pulses. A solution-based, transfer-free coating method is used to integrate GO films onto the SOI nanowires with precise control of the film thickness. Detailed SPM measurements using femtosecond optical pulses are carried out, achieving a broadening factor of up to ~4.3 for a device with 0.4-mm-long, 2 layers of GO. By fitting the experimental results with theory, we obtain an improvement in the waveguide nonlinear parameter by a factor of ~3.5 and the effective nonlinear figure of merit (FOM) by a factor of ~3.8, relative to the uncoated waveguide. Finally, we discuss the influence of GO film length on the spectral broadening and compare the nonlinear optical performance of different integrated waveguides coated with GO films. These results confirm the improved nonlinear optical performance for silicon devices integrated with 2D GO films.

We theoretically investigate and optimize four-wave mixing (FWM) in silicon nitride (SiN) waveguides integrated with two-dimensional (2D) layered graphene oxide (GO) films. Based on extensive previous measurements of the material parameters of the GO films, we perform detailed analysis for the influence of device parameters including waveguide geometry, GO film thickness, length, and coating position on the FWM conversion efficiency (CE) and conversion bandwidth (CB). The influence of dispersion and photo-thermal changes in the GO films is also discussed. Owing to the strong mode overlap between the SiN waveguides and the highly nonlinear GO films, FWM in the hybrid waveguides can be significantly enhanced. We obtain good agreement with previous experimental results and show that by optimizing the device parameters to balance the trade-off between Kerr nonlinearity and loss, the FWM CE can be improved by as much as ~20.7 dB and the FWM CB can be increased by ~4.4 folds, relative to the uncoated waveguides. These results highlight the significantly enhanced FWM performance that can be achieved in SiN waveguides by integrating 2D layered GO films.

Layered two-dimensional (2D) GO films are integrated with silicon-on-insulator (SOI) nanowire waveguides to experimentally demonstrate an enhanced Kerr nonlinearity, observed through self-phase modulation (SPM). The GO films are integrated with SOI nanowires using a large-area, transfer-free, layer-by-layer coating method that yields precise control of the film thickness. The film placement and coating length are controlled by opening windows in the silica cladding of the SOI nanowires. Owing to the strong mode overlap between the SOI nanowires and the highly nonlinear GO films, the Kerr nonlinearity of the hybrid waveguides is significantly enhanced. Detailed SPM measurements using picosecond optical pulses show significant spectral broadening enhancement for SOI nanowires coated with 2.2-mm-long films of 1−3 layers of GO, and 0.4-mm-long films with 5−20 layers of GO. By fitting the experimental results with theory, the dependence of GO’s n₂ on layer number and pulse energy is obtained, showing interesting physical insights and trends of the layered GO films from 2D monolayers to quasi bulk-like behavior. Finally, we show that by coating SOI nanowires with GO films the effective nonlinear parameter of SOI nanowires is increased 16 fold, with the effective nonlinear figure of merit (FOM) increasing by about 20 times to FOM > 5. These results reveal the strong potential of using layered GO films to improve the Kerr nonlinear optical performance of silicon photonic devices.

Selective hydrogenation of nitrobenzene was carried out under solvent-free conditions using supported AuPd nanoparticles catalyst, prepared by modified impregnation method (MIm), as efficient catalyst. >99% yield of aniline (AN) was obtained after 15 hours at 90 °C, 3 bar H2 that can be used without any further purification or separation, therefore reducing cost and energy input. Supported AuPd nanoparticles catalyst, prepared by MIm, was found to be active and stable even after 4 recycle experiments whereas the same catalyst prepared by SIm deactivated during the recycle experiments. The most effective catalyst was tested for the chemoselective hydrogenation of 4-chloronitrobenzene (CNB) to 4-chloroaniline (CAN). The activation energy of CNB to CAN was found to be 25 kJ mol-1, while that of CNB to AN was found to be 31 kJ mol-1. Based on this, the yield of CAN was maximized (92%) by lowering the reaction temperature to 25 °C.

Due to the non-degradability of petroleum-based packaging materials, serious environmental pollution and the depletion of non-renewable resources have become pressing issues. In order to actively promote green production and address these concerns, there is an urgent need for new packaging materials to replace traditional plastic products. Starch-based packaging materials, composed of starch, fiber, and plasticizers, offer a degradable and environmentally friendly alternative. Starch alone cannot undergo thermoplastic processing due to its inherent structural characteristics. Therefore, researchers have explored modifications by incorporating plasticizers to create processable thermoplastic starch (TPS). However, there are challenges related to the high crystallinity and poor compatibility between TPS and fibers, resulting in decreased mechanical properties. To address these challenges, a novel approach combining plasticizer optimization and response surface method (RSM) optimization has been proposed to enhance the mechanical properties of starch-based packaging materials. This method leverages the advantages of composite plasticizers and process parameters. The findings demonstrate that the composite plasticizer effectively disrupt the hydrogen bonding and granule morphology of starch, leading to a significant reduction in crystallinity. Based on these findings, the optimal process parameters are determined using the RSM, resulting in a forming temperature of 198 °C, forming time of 5.4 minutes, and AC content of 0.84 grams. Compared with the non-optimized values, the tensile strength increases by 12.2% and the rebound rate increases by 8.1%.

Gravel packing completion method for horizontal wells has the advantages of maintaining high oil production for a long time, maintaining wellbore stability and preventing sand production, so it has become the preferred completion method for horizontal wells. At present, this technology still faces the problems of high sand bed height and poor gravel migration. In order to improve the efficiency of gravel packing in horizontal wells, pulsed gravel packing technology for horizontal wells is proposed for the first time. Based on the mechanism of hydraulic pulse, the Eularian model, RNG K-ε model and CFD model are used to simulate the solid-liquid two-phase flow. By optimizing the parameters such as frequency and amplitude of pulse waveform, the optimal pulse waveform of pulsed gravel packing in horizontal wells is determined. The effects of parameters such as sand-carrying fluid displacement, sand-carrying fluid viscosity, sand-carrying ratio, gravel particle size and string eccentricity on pulsed gravel packing in horizontal wells are studied, and the distribution law of gravel migration velocity and volume fraction in horizontal wells is obtained. According to the results, it can be seen that with the increase of displacement and viscosity of carrier fluid, the volume fraction of fixed bed and moving bed decreases gradually, while that of suspension bed increases gradually. With the increase of sand-carrying ratio, gravel particle size and string eccentricity, the volume fraction of fixed bed and moving bed increases gradually, while that of suspended bed decreases gradually. Comparing the effects of conventional gravel packing and pulsed gravel packing in horizontal wells, it can be concluded that the efficiency of pulsed gravel packing in horizontal wells is higher. The volume fraction of fixed bed and moving bed decreased by 30% and 40% respectively, while the volume fraction of suspended bed increased by 20%. The migration velocity of moving bed and suspended bed increased by 40% and 25% respectively. And the migration ability of gravel improved obviously.