Influence of Methane-Hydrogen Mixture Characteristics on Compressor Vibrations

A transition to clean hydrogen energy will not be possible until the issues related to its production, transportation,storage, etc., are adequately resolved. Currently, however, it is possible to use methane-hydrogen mixtures.Natural gas can be transported using a pipeline system with the required pressure being maintained by gascompression stations. This method, however, is affected by some problems too. Compressors emergency stopscan be induced by vibrations because in some cases, mechanical methods are not able to reduce the vibrationamplitude. As an example, it is known that a gas-dynamic flow effect in labyrinth seals can lead to increasedvibrations. This paper presents the numerical simulation of rotor oscillations taking into account a gas-dynamicload. The influence of a transported mixture on the oscillatory process is investigated. Mixtures consisting ofmethane and hydrogen in various proportions and an air mixture are considered. The results are discussed forvarious operating pressures and include the rotor motion trajectories and oscillation frequency spectra obtainednumerically. It is shown that the gas mixture composition has a significant effect on the oscillations and theiroccurrence. Hydrogen as a working fluid reduces the vibration amplitude. Operating a compressor with hydrogenleads to a decrease in the resonant frequency, bringing it closer to the operating one. However, the operatingpressure at which maximum oscillations are observed depends slightly on the gas mixture composition.

Retrieval of Volcanic Sulfate Aerosols Optical Parameters from AHI Radiometer Data

This paper presents a method for retrieving optical parameters from volcanic sulfate aerosols from the AHI radiometer on board the Himawari-8 satellite.The proposed method is based on optical models for various mixtures of aerosol components from volcanic clouds,including ash particles,ice crystals,water drops,and sulfate aerosol droplets.The application of multi-component optical models of various aerosol compositions allows for the optical thickness and mass loading of sulfate aerosol to be estimated in the sulfuric cloud formed after the Karymsky volcano eruption on 3 November 2021.A comprehensive analysis of the brightness temperatures of the sulfuric cloud in the infrared bands was performed,which revealed that the cloud was composed of a mixture of sulfate aerosol and water droplets.Using models of various aerosol compositions allows for the satellite-based estimation of optical parameters not only for sulfate aerosol but also for the whole aerosol mixture.

The medium-temperature dependence of jet transport coefficient in high-energy nucleus-nucleus collisions

The medium-temperature T dependence of the jet transport coefficient̂q was studied via the nuclear modification factor RAA(p_(T))and elliptical flow parameter v_(2)(p_(T))for large transverse momentum p_(T) hadrons in high-energy nucleus-nucleus collisions.Within a next-to-leading-order perturbative QCD parton model for hard scatterings with modified fragmentation functions due to jet quenching controlled by q,we check the suppression and azimuthal anisotropy for large p_(T) hadrons,and extract q by global fits to RAA(pT)and v_(2)(pT)data in A+A collisions at RHIC and LHC,respectively.The numerical results from the best fits show that q∕T^(3) goes down with local medium-temperature T in the parton jet trajectory.Compared with the case of a constant q∕T^(3),the going-down T dependence of q∕T^(3) makes a hard parton jet to lose more energy near T_(c) and therefore strengthens the azimuthal anisotropy for large pT hadrons.As a result,v_(2)(p_(T))for large pT hadrons was enhanced by approximately 10%to better fit the data at RHIC/LHC.Considering the first-order phase transition from QGP to the hadron phase and the additional energy loss in the hadron phase,v_(2)(p_(T))is again enhanced by 5-10%at RHIC/LHC.

Transverse momentum balance of dijets in Xe+Xe collisions at the LHC

We present a theoretical study of the medium modifications of the p_(T)balance (x_(J)) of dijets in Xe+Xe collisions at■.The initial production of dijets was carried out using the POWHEG+PYTHIA8 prescription,which matches the next-toleading-order (NLO) QCD matrix elements with the parton shower (PS) effect.The SHELL model described the in-medium evolution of nucleus–nucleus collisions using a transport approach.The theoretical results of the dijet xJin the Xe+Xe collisions exhibit more imbalanced distributions than those in the p+p collisions,consistent with recently reported ATLAS data.By utilizing the Interleaved Flavor Neutralisation,an infrared-and-collinear-safe jet flavor algorithm,to identify the flavor of the reconstructed jets,we classify dijets processes into three categories:gluon–gluon (gg),quark–gluon (qg),and quark–quark (qq),and investigated the respective medium modification patterns and fraction changes of the gg,qg,and qq components of the dijet sample in Xe+Xe collisions.It is shown that the increased fraction of qg component at a small x_(J)contributes to the imbalance of the dijet;in particular,the q_(1)g_(2)(quark-jet-leading) dijets experience more significant asymmetric energy loss than the g_(1)q_(2)(gluon-jet-leading) dijets traversing the QGP.By comparing the■of inclusive,■ dijets in Xe+Xe collisions,we observe■.Moreover,ρ_(Xe),P_(b),the ratios of the nuclear modification factors of dijets in Xe+Xe to those in Pb+Pb,were calculated,which indicates that the yield suppression of dijets in Pb+Pb is more pronounced than that in Xe+Xe owing to the larger radius of the lead nucleus.

Two-Body Hadronic Weak Decays of Bottomed Hadrons

The structure of light diquarks plays a crucial role in formation of exotic hadrons beyond the conventional quark model, especially with regard to the line shapes of bottomed hadron decays. We study the two-body hadronic weak decays of bottomed baryons and bottomed mesons to probe the light diquark structure and to pin down the quark–quark correlations in the diquark picture. It is found that the light diquark does not favor a compact structure. For instance, the isoscalar diquark [ud] in Λ_(b)^(0) can be easily split and rearranged to form ■via the color-suppressed transition. This provides a hint that the hidden charm pentaquark states produced in Λ_(b)^(0) decays could be the ■chadronic molecular candidates. This quantitative study resolves the apparent conflicts between the production mechanism and the molecular nature of these P_(c) states observed in experiment.

Comparative Study of Gut Microbiota in Breast Cancer Patients versus Controls in Abidjan, Côte d’Ivoire

Context: The gut microbiota represents a complex ecosystem encompassing all unicellular microorganisms residing in the digestive tract, primarily bacteria, fungi, archaea, and even viruses. The relationship between the host and the microbiota is symbiotic: bacteria benefit from a stable environment, while the host gains numerous capabilities in terms of digestion, metabolism, nutrition, and immunity. However, numerous studies suggest that the gut microbiota plays a crucial role in various non-communicable diseases, including obesity, chronic inflammatory bowel diseases, allergic and immune disorders, behavioral disorders, and even certain cancers. The objective of our study was to characterize the gut microbiota of a group of breast cancer patients by comparing it to that of control subjects in Côte d’Ivoire, using a metagenomic approach. Method: A case-control study was conducted from May 2020 to September 2023. A total of 85 women (39 cases and 46 controls) were recruited, and stool samples were collected from both breast cancer patients and healthy women. Among these, ten (10) samples from patients and ten (10) samples from healthy women were randomly selected for the study of the gut microbiota. The gut microbiota was characterized by sequencing the V4 region of 16S rRNA using metagenomic NGS technology, and bioinformatic analysis was performed using the mothur pipeline. Results: In women with breast cancer, we observed a reduction in the relative abundance of the phyla Firmicutes and Bacteroidetes, as well as an increase in the phyla Actinobacteria and Verrucomicrobia. Additionally, their microbiota exhibited lower Chao1 and Sobs diversities compared to the control women (p < 0.05). Molecular variance analysis (AMOVA) revealed a significant difference between the case and control groups (p < 0.001). This study has highlighted a significant difference in the relative abundance of major phyla within the gut microbiota of cases compared to healthy controls. It will contribute to enriching African and global data, thus promoting a better understanding of the role of gut microbiota in breast cancer.

Cooperative structure of Li/Ni mixing and stacking faults for achieving high-capacity Co-free Li-rich oxides

Co-free Li-rich layered oxides(LLOs)are emerging as promising cathode materials for Li-ion batteries due to their low cost and high capacity.However,they commonly face severe structural instability and poor electrochemical activity,leading to diminished capacity and voltage performance.Herein,we introduce a Co-free LLO,Li_(1.167)Ni_(0.222)Mn_(0.611)O_(2)(Cf-L1),which features a cooperative structure of Li/Ni mixing and stacking faults.This structure regulates the crystal and electronic structures,resulting in a higher discharge capacity of 300.6 mA h g^(-1)and enhanced rate capability compared to the typical Co-free LLO,Li_(1.2)Ni_(0.2)Mn_(0.6)O_(2)(Cf-Ls).Density functional theory(DFT)indicates that Li/Ni mixing in LLOs leads to increased Li-O-Li configurations and higher anionic redox activities,while stacking faults further optimize the electronic interactions of transition metal(TM)3d and non-bonding O 2p orbitals.Moreover,stacking faults accommodate lattice strain,improving electrochemical reversibility during charge/discharge cycles,as demonstrated by the in situ XRD of Cf-L1 showing less lattice evolution than Cf-Ls.This study offers a structured approach to developing Co-free LLOs with enhanced capacity,voltage,rate capability,and cyclability,significantly impacting the advancement of the next-generation Li-ion batteries.

Transcriptomic analysis of Andrias davidianus meat and experimental validation for exploring its bioactive components as functional foods

Andrias davidianus(Chinese giant salamander,CGS)is the largest and oldest extant amphibian species in the world and is a source of prospective functional food in China.However,the progress of functional peptides mining was slow due to lack of reference genome and protein sequence data.In this study,we illustrated full-length transcriptome sequencing to interpret the proteome of CGS meat and obtain 10703 coding DNA sequences.By functional annotation and amino acid composition analysis,we have discovered various genes related to signal transduction,and 16 genes related to longevity.We have also found vast variety of functional peptides through protein coding sequence(CDS)analysis by comparing the data obtained with the functional peptide database.Val-Pro-Ile predicted by the CDS analysis was released from the CGS meat through enzymatic hydrolysis,suggesting that our approach is reliable.This study suggested that transcriptomic analysis can be used as a reference to guide polypeptide mining in CGS meat,thereby providing a powerful mining strategy for the bioresources with unknown genomic and proteomic sequences.

Delay-Differentiated Scheduling in Optical Packet Switches for Cloud Data Centers

We consider differentiated timecritical task scheduling in a N×N input queued optical packet s w itch to ens ure 100% throughput and meet different delay requirements among various modules of data center. Existing schemes either consider slot-by-slot scheduling with queue depth serving as the delay metric or assume that each input-output connection has the same delay bound in the batch scheduling mode. The former scheme neglects the effect of reconfiguration overhead, which may result in crippled system performance, while the latter cannot satisfy users' differentiated Quality of Service(Qo S) requirements. To make up these deficiencies, we propose a new batch scheduling scheme to meet the various portto-port delay requirements in a best-effort manner. Moreover, a speedup is considered to compensate for both the reconfiguration overhead and the unavoidable slots wastage in the switch fabric. With traffic matrix and delay constraint matrix given, this paper proposes two heuristic algorithms Stringent Delay First(SDF) and m-order SDF(m-SDF) to realize the 100% packet switching, while maximizing the delay constraints satisfaction ratio. The performance of our scheme is verified by extensive numerical simulations.

Multi-core based parallel computing technique for content-based image retrieval

In this paper, we propose a parallel computing technique for content-based image retrieval （CBIR） system. This technique is mainly used for single node with multi-core processor, which is different from those based on cluster or network computing architecture. Due to its specific applications （such as medical image processing） and the harsh terms of hardware resource requirement, the CBIR system has been prevented from being widely used. With the increasing volume of the image database, the widespread use of multi-core processors, and the requirement of the retrieval accuracy and speed, we need to achieve a retrieval strategy which is based on multi-core processor to make the retrieval faster and more convenient than before. Experimental results demonstrate that this parallel architecture can significantly improve the performance of retrieval system. In addition, we also propose an efficient parallel technique with the combinations of the cluster and the multi-core techniques, which is supposed to gear to the new trend of the cloud computing.

Selected topics of quantum computing for nuclear physics

Nuclear physics,whose underling theory is described by quantum gauge field coupled with matter,is fundamentally important and yet is formidably challenge for simulation with classical computers.Quantum computing provides a perhaps transformative approach for studying and understanding nuclear physics.With rapid scaling-up of quantum processors as well as advances on quantum algorithms,the digital quantum simulation approach for simulating quantum gauge fields and nuclear physics has gained lots of attention.In this review,we aim to summarize recent efforts on solving nuclear physics with quantum computers.We first discuss a formulation of nuclear physics in the language of quantum computing.In particular,we review how quantum gauge fields(both Abelian and non-Abelian)and their coupling to matter field can be mapped and studied on a quantum computer.We then introduce related quantum algorithms for solving static properties and real-time evolution for quantum systems,and show their applications for a broad range of problems in nuclear physics,including simulation of lattice gauge field,solving nucleon and nuclear structures,quantum advantage for simulating scattering in quantum field theory,non-equilibrium dynamics,and so on.Finally,a short outlook on future work is given.

Review of emulsified asphalt modification mechanisms and performance influencing factors

In recent years,with the improvement of the requirements of road performance,modified emulsified asphalts with better performance has gradually replaced the emulsified asphalt and become the primary material for road maintenance.This paper introduces the modified emulsified asphalt materials commonly used in pavement maintenance projects,definitions and modified mechanisms of polymerized styrene butadiene rubber(SBR)modified emulsified asphalt,styrene butadiene styrene block polymer(SBS)modified emulsified asphalt and waterborne epoxy resin(WER)modified emulsified asphalt are summarized.The analysis focused on comparing the effects of modifiers,preparation process,auxiliary additives,and other factors on the performance of modified emulsified asphalt.In this paper,it is considered that the greatest impact on the performance of emulsified asphalt is the modifier,emulsifier mainly affects the speed of breaking the emulsion,stabilizers on the basic performance of emulsified asphalt evaporative residue is small;and when the modifier is distributed in the asphalt in a network,the dosage at this time is the recommended optimum dosage.Finally,this study recommends that in the future,the polymer-asphalt compatibility can be improved through composite modification,chemical grafting and other methods to continue to develop broader applicability and better performance of modified emulsified asphalt.

A review on evaluation of crack resistance of asphalt mixture by semi-circular bending test

Although there are many kinds of fracture tests to choose from in evaluating the crack resistance of asphalt mixture,the semi-circular bending(SCB)test has attracted a lot of attention in the academic road engineering community because of its simplicity,stability,and flexibility in testing and evaluation.The SCB test has become a common method to study the cracking resistance of asphalt mixture in recent years.This paper mainly summarizes the overview of the SCB test,summarizes some research results and common characterization parameters of the SCB test method in monotone test and fatigue test in recent years,and predicts and suggests the research direction of the SCB test in the future.It is found that the research on the monotonic SCB test is more comprehensive,and the research on the SCB fatigue test needs to be further improved in the aspects of loading mode,characterization parameter selection,and so on.Researchers can flexibly adjust the geometric dimensions and the test parameters of semi-cylindrical specimens,and conduct comprehensive analysis combined with the results of numerical simulation.The crack resistance of asphalt mixture can be comprehensively evaluated by fracture energy,fracture toughness,stiffness,flexibility index and other fracture indicators,combined with the crack propagation of the specimen.The analysis of numerical simulation can confirm the test results.In order to standardize the setting of fatigue parameters for future application,it is necessary to standardize the setting of bending performance.

Systematic Survey on Big Data Analytics and Artificial Intelligence for COVID-19 Containment

Artificial Intelligence(AI)has gained popularity for the containment of COVID-19 pandemic applications.Several AI techniques provide efficient mechanisms for handling pandemic situations.AI methods,protocols,data sets,and various validation mechanisms empower the users towards proper decision-making and procedures to handle the situation.Despite so many tools,there still exist conditions in which AI must go a long way.To increase the adaptability and potential of these techniques,a combination of AI and Bigdata is currently gaining popularity.This paper surveys and analyzes the methods within the various computational paradigms used by different researchers and national governments,such as China and South Korea,to fight against this pandemic.The process of vaccine development requires multiple medical experiments.This process requires analyzing datasets from different parts of the world.Deep learning and the Internet of Things(IoT)revolutionized the field of disease diagnosis and disease prediction.The accurate observations from different datasets across the world empowered the process of drug development and drug repurposing.To overcome the issues generated by the pandemic,using such sophisticated computing paradigms such as AI,Machine Learning(ML),deep learning,Robotics and Bigdata is essential.

An image segmentation method of pulverized coal for particle size analysis

An important index to evaluate the process efficiency of coal preparation is the mineral liberation degree of pulverized coal,which is greatly influenced by the particle size and shape distribution acquired by image segmentation.However,the agglomeration effect of fine powders and the edge effect of granular images caused by scanning electron microscopy greatly affect the precision of particle image segmentation.In this study,we propose a novel image segmentation method derived from mask regional convolutional neural network based on deep learning for recognizing fine coal powders.Firstly,an atrous convolution is introduced into our network to learn the image feature of multi-sized powders,which can reduce the missing segmentation of small-sized agglomerated particles.Then,a new mask loss function combing focal loss and dice coefficient is used to overcome the false segmentation caused by the edge effect.The final comparative experimental results show that our method achieves the best results of 94.43%and 91.44%on AP50 and AP75 respectively among the comparison algorithms.In addition,in order to provide an effective method for particle size analysis of coal particles,we study the particle size distribution of coal powders based on the proposed image segmentation method and obtain a good curve relationship between cumulative mass fraction and particle size.

Molecular Nature of X(3872)in B^(0)→K^(0)X(3872)and B^(+)→K^(+)X(3872)Decays

We investigate the decays of B^(0)→K^(0)X(3872)and B^(+)→K^(+)X(3872)based on the picture where the X(3872)resonance is strongly coupled to the DD*+c.c.channel.In addition to the decay mechanism where the X(3872)resonance is formed from the DD*pair hadronization with the short-distance interaction,we have also considered the DD*rescattering diagrams in the long-distance scale,where D andD*are formed from c andDD*separately.Because of the difference of the mass thresholds of charged and neutralDD*channels,and the rather narrow width of the X(3872)resonance,at the X(3872)mass,the loop functions ofD^(0)D*^(0)andD^(+)D*^(-)are much different.Taking this difference into account,the ratio of B[B^(0)→K^(0)X(3872)]/B[B+→K+X(3872)]■0.5 can be naturally obtained.Based on this result,we also evaluate the decay widths of B_s^(0)→η(η′)X(3872).It is expected that future experimental measurements of these decays can be used to elucidate the nature of the X(3872)resonance.

The genomic and epigenetic footprint of local adaptation to variable climates in kiwifruit

A full understanding of adaptive genetic variation at the genomic level will help address questions of how organisms adapt to diverse climates.Actinidia eriantha is a shade-tolerant species,widely distributed in the southern tropical region of China,occurring in spatially heterogeneous environments.In the present study we combined population genomic,epigenomic,and environmental association analyses to infer population genetic structure and positive selection across a climatic gradient,and to assess genomic offset to climatic change for A.eriantha.The population structure is strongly shaped by geography and influenced by restricted gene f low resulting from isolation by distance due to habitat fragmentation.In total,we identified 102 outlier loci and annotated 455 candidate genes associated with the genomic basis of climate adaptation,which were enriched in functional categories related to development processes and stress response;both temperature and precipitation are important factors driving adaptive variation.In addition to single-nucleotide polymorphisms(SNPs),a total of 27 single-methylation variants(SMVs)had significant correlation with at least one of four climatic variables and 16 SMVswere located in or adjacent to genes,several of whichwere predicted to be involved in plant response to abiotic or biotic stress.Gradient forest analysis indicated that the central/east populations were predicted to be at higher risk of future population maladaptation under climate change.Our results demonstrate that local climate factors impose strong selection pressures and lead to local adaptation.Such information adds to our understanding of adaptive mechanisms to variable climates revealed by both population genome and epigenome analysis.

Genome assembly of the snow lotus species Saussurea involucrata provides insights into acacetin and rutin biosynthesis and tolerance to an alpine environment

Dear Editor,Understanding the evolution and survival mechanisms of endangered wild medicinal herbs is crucial for their cultivation,utilization,and conservation.The snow lotus species Saussurea involucrata(Kar.&Kir.)Sch.Bip.(2n=32)(i.e.the well-known Tianshan snow lotus)which belongs to the eudicot family Asteraceae,is a famous traditional Chinese medicinal herb having anti-inflammatory.

三聚氰胺金属(Ⅱ)配合物的结构、紫外-可见光谱和反应活性

三聚氰胺是婴幼儿"肾结石事件"的重要前体.本文选取几个典型的二价金属离子与三聚氰胺(L)形成的三聚氰胺金属配合物ML2(OH)2(M=Ca,Mg,Zn,Cu,Ni,Fe),使用密度泛函理论(DFT)、含时DFT和概念DFT等工具,系统地计算和比较了ML2(OH)2的结构、紫外-可见光谱和反应性质的异同.模拟结果揭示了ML2(OH)2的结构、光谱及其反应性质是一类不同于其前体L,形成ML2(OH)2配合物后,将有较高的亲电指数和较低的化学硬度以及呈现红外吸收峰红移;在这些典型的二价金属配合物中,金属M离子电荷与配体O和N原子之间的电荷、以及与金属M离子和配体原子之间的二级微扰相互作用能,配合物最低空轨道能级与其亲电反应指数、最低空轨道能级与化学硬度指数等方面,存在着一系列定量的相关关系,相关系数(R2)达0.889-0.997;前线分子轨道模拟结果表明,ML2(OH)2体系反应活性的差异源于金属离子对前线轨道贡献有所不同,FeL2(OH)2、CuL2(OH)2、NiL2(OH)2等过渡金属离子的配合物中,金属离子贡献较多,共价性成分较多.这些结果将为进一步理解人体内三聚氰胺致结石的成因提供有益的启示.

双螺旋金属(Ⅱ)卟啉的结构、电子光谱及其反应活性

由两个拓展的卟吩环键合不同的金属离子形成的卟啉结分子是生命体系中DNA双螺旋分子最简单的金属扭结模型物,在仿酶催化反应等方面存在广阔的应用空间.本文选取8个典型的二价金属离子(M(Ⅱ),M=Ca,Mg,Mn,Zn,Cu,Ni,Fe,Co)与拓展卟吩结分子(1H)形成的单金属卟啉结配合物(1M)和双金属卟啉结配合物(2M),用密度泛函理论(DFT)、含时DFT和概念DFT等工具,在优化构型的基础上,通过自然键轨道(NBO)方法和前线轨道能级研究了它们的分子结构、光谱性质和反应活性.模拟结果显示1M、2M的结构、光谱及其反应性质不同于其前体1H:形成1M和2M金属配合物分子后,将有较高的亲电指数和较低的化学硬度以及呈现紫外吸收峰位移;形成2M双金属配合物后,绝大多数金属离子形成的2个四配位环境的对称性较1M体系有了提高,同时DFT反应指数也有显著的增强.但2M体系的调变能力也不尽相同:主簇金属和含饱和电子结构离子较弱,过渡金属离子强些,二元描述符(dual descriptor)结果支持了以上结论.在这些典型的二价金属配合物中,金属原子M和配体原子N之间的自然电荷分布,金属原子M和配体原子N之间的二级微扰相互作用能,配合物的前线轨道能级与其硬度指数、键的离解能与自然电荷等方面,存在着一系列定量的相关关系,相关系数(R2)在0.858-0.986之间.本研究对理解含有金属离子的重要生物物质在结构和反应性能上的差别将提供有益启示.