Effect of shear-induced contact area and aperture variations on nonlinear flow behaviors in fractal rock fractures

This study experimentally analyzes the nonlinear flow characteristics and channelization of fluid through rough-walled fractures during the shear process using a shear-flow-visualization apparatus.A series of fluid flow and visualization tests is performed on four transparent fracture specimens with various shear displacements of 1 mm,3 mm,5 mm,7 mm and 10 mm under a normal stress of 0.5 MPa.Four granite fractures with different roughnesses are selected and quantified using variogram fractal dimensions.The obtained results show that the critical Reynolds number tends to increase with increasing shear displacement but decrease with increasing roughness of fracture surface.The flow paths are more tortuous at the beginning of shear because of the wide distribution of small contact spots.As the shear displacement continues to increase,preferential flow paths are more distinctly observed due to the decrease in the number of contact spots caused by shear dilation;yet the area of single contacts in-creases.Based on the experimental results,an empirical mathematical equation is proposed to quantify the critical Reynolds number using the contact area ratio and fractal dimension.

Development of glioblastoma organoids and their applications in personalized therapy

Glioblastomas(GBMs)are the brain tumors with the highest malignancy and poorest prognoses.GBM is characterized by high heterogeneity and resistance to drug treatment.Organoids are 3-dimensional cultures that are constructed in vitro and comprise cell types highly similar to those in organs or tissues in vivo,thus simulating specific structures and physiological functions of organs.Organoids have been technically developed into an advanced ex vivo disease model used in basic and preclinical research on tumors.Brain organoids,which simulate the brain microenvironment while preserving tumor heterogeneity,have been used to predict patients’therapeutic responses to antitumor drugs,thus enabling a breakthrough in glioma research.GBM organoids provide an effective supplementary model that reflects human tumors’biological characteristics and functions in vitro more directly and accurately than traditional experimental models.Therefore,GBM organoids are widely applicable in disease mechanism research,drug development and screening,and glioma precision treatments.This review focuses on the development of various GBM organoid models and their applications in identifying new individualized therapies against drug-resistant GBM.

Permeability evolution and gas flow in wet coal under non-equilibrium state:Considering both water swelling and process-based gas swelling

Accurate knowledge of gas flow within the reservoir and related controlling factors will be important for enhancing the production of coal bed methane.At present,most studies focused on the permeability evolution of dry coal under gas adsorption equilibrium,gas flow and gas diffusion within wet coal under the generally non-equilibrium state are often ignored in the process of gas recovery.In this study,an improved apparent permeability model is proposed which accommodates the water and gas adsorption,stress dependence,water film thickness and gas flow regimes.In the process of modeling,the water adsorption is only affected by water content while the gas adsorption is time and water content dependent;based on poroelastic mechanics,the effective fracture aperture and effective pore radius are derived;and then the variation in water film thickness for different pore types under the effect of water content,stress and adsorption swelling are modeled;the flow regimes are considered based on Beskok’s model.Further,after validation with experimental data,the proposed model was applied to numerical simulations to investigate the evolution of permeability-related factors under the effect of different water contents.The gas flow in wet coal under the non-equilibrium state is explicitly revealed.

Shear behaviours and roughness degeneration based on a quantified rock joint surface description

The asperity wear of rock joints significantly affects their shear behaviour.This study discusses the wear damage of the asperities on the joint surface,highlighting the roughness degradation characteristics during the shear process.The direct shear experiment of artificial specimens containing rock joints was conducted under different normal stresses based on three-dimensional scanning technology.These experimental results showed the contribution of joint wear to roughness degeneration,such as the height,zone,and volume of asperity degeneration.The wear coefficient of the rock joint was obtained based on the volume wear of asperities in the laboratory experiment.The functional relationship between the friction coefficient and wear coefficient is subsequently determined.To quantitatively analyse the wear damage of a joint surface,a calculation method for determining the wear depth of the rock joint after shearing was proposed based on wear theory.The relationship between the ultimate dilation and wear depth was analysed.A coefficient m,which can describe the damage degree of the joint surface,and a prediction method of joint surface roughness after shearing are established.Good agreement between analytical predictions and measured values demonstrates the capability of the developed model.Lastly,the sensitivity factors on the wear depth are explored.

An improved apparent permeability model considering full pore pressure range,variable intrinsic permeability and slippage coefficient

Although the slippage effect has been extensively studied,most of the previous studies focused on the impact of the slippage effect on apparent permeability within a low pore pressure range,resulting in the inability of matching the evolution of permeability in the remaining pressure range.In this paper,a new apparent permeability model that reveals the evolution of permeability under the combined action of effective stress and slippage in the full pore pressure range was proposed.In this model,both intrinsic permeability and slippage coefficient are stress dependent.Three experimental tests with pore pressure lower than 2 MPa and a test with pore pressure at about 10 MPa using cores from the same origin under constant confining stress and constant effective stress are conducted.By comparing experimental data and another apparent permeability model,we proved the fidelity of our newly developed model.Furthermore,the contribution factor of the slippage effect Rslip is used to determine the low pore pressure limit with significant slippage effect.Our results show that both narrow initial pore size and high effective stress increase the critical pore pressure.Finally,the evolutions of the slippage coefficient and the intrinsic permeability under different boundary conditions were analyzed.

Recent progress in the machine learning-assisted rational design of alloys

Alloys designed with the traditional trial and error method have encountered several problems,such as long trial cycles and high costs.The rapid development of big data and artificial intelligence provides a new path for the efficient development of metallic materials,that is,machine learning-assisted design.In this paper,the basic strategy for the machine learning-assisted rational design of alloys was introduced.Research progress in the property-oriented reversal design of alloy composition,the screening design of alloy composition based on models established using element physical and chemical features or microstructure factors,and the optimal design of alloy composition and process parameters based on iterative feedback optimization was reviewed.Results showed the great advantages of machine learning,including high efficiency and low cost.Future development trends for the machine learning-assisted rational design of alloys were also discussed.Interpretable modeling,integrated modeling,high-throughput combination,multi-objective optimization,and innovative platform building were suggested as fields of great interest.

Structural and Magnetic Properties of Nanocomposite Nd Fe BPrepared by Rapid Thermal Processing

Nanoscale permanent magnetic materials,which possess excellent magnetic and mechanical properties,thermal stability,and corrosion resistance,have become a research hotspot for permanent magnets.In reality,however,the obtained maximum energy product,(BH)max,is not satisfactory in comparison with the theory limit,especially for exchange-coupled nanocomposite magnets.The construction of an ideal microstructure still remains a challenge in the synthesis and preparation of nanoscale permanent magnets.This work reported the impact of rapid thermal process(RTP)with electron-beam heating on the microstructures of Nd12.5-xFe80.8+xB6.2Nb0.2Ga0.3(x=0,2.5)nanocomposites.It was found that the crystallization time was greatly reduced,from 15 min under the conventional annealing conditions to 0.1 s under the RTP.For Nd2Fe14B single-phase materials,the crystallization temperature of the RTP ribbons decreased by about 248 C compared with that of the ribbons produced by the conventional annealing method.A synergetic crystallization of the Nd2Fe14B and a-Fe phases was observed under the RTP,which restrained not only the shape,size distribution,and compositions of the hard and the soft phases,but also the interface between them.This modification effect became more obvious as the fraction of Fe increased.Due to the improvement in the uniformity of the Nd2Fe14B and a-Fe phases,and their grain size distribution,better magnetic properties were achieved using RTP in comparison with the conventional annealing method.

Conceptual Modular Design of Auto Body Frame Based on Hybrid Optimization Method

This article presents a systematic research methodology of modular design for conceptual auto body frame by hybrid optimization method.A modified graph-based decomposition optimization algorithm is utilized to generate an optimal BIW assembly topo model composed of“potential modules”.The consistency constraint function in collaborative optimization is extended to maximize the commonality of modules and minimize the performance loss of all car types in the same product family simultaneously.A novel screening method is employed to select both“basic structures”and“reinforcement”modules based on the dimension optimization of the manufacturing elements and the optimal assembly mode;this allows for a more exhaustive modular platform design in contrast with existing methods.The proposed methodology is applied to a case study for the modular design of three conceptual auto body types in the same platform to validate its feasibility and effectiveness.

Analysis of Changing Factors on Airborne Allergenic Pollens Distribution in Taiyuan Downtown, North China

To study and analyse 2 surveys on airborne allergenic pollens distribution in Taiyuan Downtown, North China 30 years apart, the surveys focused on the phenomenon and the influence factors on types, counts, drift patterns, growth and decline rhythm and distribution features of airborne pollen with the same methods in the region in March 1977 to February 1978 and July 2008 to June 2009, respectively. The data of two airborne pollens surveys were treated with statistics, comparation and analysis, and the influence factors of pollen distribution in Taiyuan Downtown were explored. In the 2 surveys, 24 species and 35 species of pollen were collected in the region, respectively. Two pollen drift peaks were formed in spring and autumn in the two surveys. Artemisia L. is still the absolute dominant allergy airborne pollen. The types, counts, drift patterns and composition of pollen in air could be changed by the plants variation. Climate warming might affect pollen peak appearing time and lasting time, climate warming and Poplar & Willow contents changes in spring and autumn reversed the airborne pollen peak. It was found that Humulus L. had become the region’s main allergic pollen. Invasive strong allergen ragweed was spread to the inland city Taiyuan. Allergists should focus on exotic invasive harmful plants in the region.

Superplastic Solid-Phase Welding of 40 Cr-T10A Steel

The microstructure of 40Cr and T10A steel sample and its surface to be welded is ultra-fined through salt-bath cyclic quenching and high frequency hardening, then the surface is cleaned. Under non-vacuum and no shielded gas, the welding parameter of isothermal superplastic solidphase welding and the effect of surface microstructure prior to pressure welding on the quality of joint are studied. At the temperature of 730~750℃ and at initial strain rate of (2~4) × 10-4 s-l, the strength of the joint is up to or close to that of 40Cr base metal in 3-5 min pressure welding

Magnetic and Magnetocaloric Properties of Polycrystalline and Oriented Mn2-δSn

Mn-based Heusler alloys have attracted significant research attention as half-metallic materials because of their giant magnetocr.ystalline anisotropy and magnetocaloric properties.We investigate the crystal structure and magnetic properties of polycrystalline,[101]-oriented,and[100]-oriented Mn2-δ Sn prepared separately by arc melting,the Bridgeman method,and the flux method.All of these compounds crystallize in a Ni2 In-type structure.In the Mn2-δSn lattice,Mn atoms occupy all of the 2 a and a fraction of the 2 d sites.Site disorder exists between Mn and Sn atoms in the 2 c sites.In addition,these compounds undergo a re-entrant spin-glass-like transition at low temperatures,which is caused by frustration and randomness within the spin system.The magnetic properties of these systems depend on the crystal directions,which means that the magnetic interactions differ significantly along different directions.Furthermore,these materials exhibit a giant magnetocaloric effect near the Curie temperature.The largest value of maximum of magnetic entropy change(-△SM)occurs perpendicular to the[100]direction.Specifically,at 252 K,maximum-△SM is 2.91 and 3.64 J-kg-1K-1 for a magnetic field of 5 and7 T,respectively.The working temperature span over 80 K and the relative cooling power reaches 302 J/kg for a magnetic field of 7 T,which makes the Mn2-δSn compound a promising candidate for a magnetic refrigerator.

Magnetic van der Waals materials:Synthesis,structure,magnetism,and their potential applications

As the family of magnetic materials is rapidly growing,two-dimensional(2D)van der Waals(vdW)magnets have attracted increasing attention as a platform to explore fundamental physical problems of magnetism and their potential applications.This paper reviews the recent progress on emergent vd W magnetic compounds and their potential applications in devices.First,we summarize the current vd W magnetic materials and their synthetic methods.Then,we focus on their structure and the modulation of magnetic properties by analyzing the representative vd W magnetic materials with different magnetic structures.In addition,we pay attention to the heterostructures of vd W magnetic materials,which are expected to produce revolutionary applications of magnetism-related devices.To motivate the researchers in this area,we finally provide the challenges and outlook on 2D vd W magnetism.

A Paraquat Tolerance Mutant in Rice (<i>Oryza sativa</i>L.) Is Controlled by Maternal Inheritance

Paraquat (1,1’-dimethyl-4,4’-bipyridinium) tolerance is an important trait in the weed control during crop production. The paraquat tolerant (Pq72) and susceptible (Pq1192) mutants are pure lines derived from the mutation pool of rice cultivar TNG67. Two reciprocal crosses, Pq72/Pq1192 and Pq1192/Pq72, were conducted between Pq72 and Pq1192 mutant lines for studying the genetic of paraquat tolerance by investigations of physiological characteristics related to paraquat tolerance including leaf injury index, leaf chlorophyll fluorescence (Fv/Fm) and electrolyte leakage in the F2 populations of two reciprocal crosses after paraquat treatment. The results suggested that a maternal inheritance of paraquat tolerance is existed in these mutants. Further analysis found that the F2 population of Pq72/Pq1192 segregated 3:1 (tolerant to susceptible) in both Fv/Fm and electrolyte leakage, respectively. This result implies that the paraquat tolerance of the Pq72 mutant is controlled by a single dominant gene.

Radio Coverage Mapping in Wireless Sensor Networks

Radio coverage directly affects the network connectivity, which is the foundational issue to ensure the normal operation of the network. Many efforts have been made to estimate the radio coverage of sensor nodes. The existing approaches (often RSSI measurement-based), however, suffer from heavy measurement cost and are not well suitable for the large-scale densely deployed WSNs. NRC-Map, a novel algorithm is put forward for sensor nodes radio coverage mapping. The algorithm is based on the RSSI values collected by the neighbor nodes. According to the spatial relationship, neighbor nodes are mapping to several overlapped sectors. By use of the least squares fitting method, a log-distance path loss model is established for each sector. Then, the max radius of each sector is computed according to the path loss model and the given signal attenuation threshold. Finally, all the sectors are overlapped to estimate the node radio coverage. Experimental results show that the method is simple and effectively improve the prediction accuracy of the sensor node radio coverage.

Exact geometry based quasi-conforming analysis for Euler-Bernoulli beam

The problem of quick analysis using exact geometry data was proposed by Hughes et al. and the isogeometric analysis framework was introduced as a solution. In this letter, the exact geometry concept is combined into the quasi-conforming framework and a novel method, i.e., the exact geometry based quasi-conforming analysis is proposed. In present method the geometry is exactly described by non-uniform rational B-spline bases, while the solution space by traditional polynomial bases. Present method combines the merits of both isogeometric analysis and quasi-conforming finite element method. In this letter Euler-Bernoulli beam problem is solved as an example and the results show that the present method is effective and promising.

Rice functional genomics:decades'efforts and roads ahead

Rice(Oryza sativa L.)is one of the most important crops in the world.Since the completion of rice reference genome sequences,tremendous progress has been achieved in understanding the molecular mechanisms on various rice traits and dissecting the underlying regulatory networks.In this review,we summarize the research progress of rice biology over past decades,including omics,genome-wide association study,phytohormone action,nutrient use,biotic and abiotic responses,photoperiodic flowering,and reproductive development(fertility and sterility).For the roads ahead,cutting-edge technologies such as new genomics methods,high-throughput phenotyping platforms,precise genome-editing tools,environmental microbiome optimization,and synthetic methods will further extend our understanding of unsolved molecular biology questions in rice,and facilitate integrations of the knowledge for agricultural applications.

Discovery of aluminum alloys with ultra-strength and high-toughness via a property-oriented design strategy

Aluminum alloys with ultra-strength and high-toughness are fundamental structural materials applied in the aerospace industry.Due to the intrinsic restriction between strength and toughness,optimizing a desirable combination of these conflicting properties is always challenging in material development.In this study,171 sets of data were curated based on the characteristics of high-strength and high-toughness aluminum alloys in the literature.Then,a machine learning design system(MLDS)with a property-oriented design strategy was established to rapidly discover novel aluminum alloys with ductility and toughness indexes(with elongationδ=8%–10%and fracture toughness K_(IC)=33–35 MPa·m^(1/2))comparable to those of current state-of-the-art AA7136 aluminum alloys when the ultimate tensile strength(UTS)exceeded approximately 100 MPa,with values reaching 700–750 MPa.With the MLDS for experimental verification,three typical candidate alloys show satisfactory performance with UTS of 707–736 MPa,δof 7.8%–9.5%,and K_(IC)of 32.2–33.9 MPa·m^(1/2).The high contents of Mg and Zn alloying elements in the novel alloys form abundantη'phases,which produce a significant hardening effect,while the reasonable matching of Cr,Mn,Ti and Zr dispersoids refines the grain size.The decreased Cu content compared with that in the AA7136 alloy inhibits the formation of theσphase and S phase,so that the alloys show high toughness.

A property-oriented design strategy for high performance copper alloys via machine learning

Traditional strategies for designing new materials with targeted property including methods such as trial and error,and experiences of domain experts,are time and cost consuming.In the present study,we propose a machine learning design system involving three features of machine learning modeling,compositional design and property prediction,which can accelerate the discovery of new materials.We demonstrate better efficiency of on a rapid compositional design of high-performance copper alloys with a targeted ultimate tensile strength of 600–950 MPa and an electrical conductivity of 50.0%international annealed copper standard.There exists a good consistency between the predicted and measured values for three alloys from literatures and two newly made alloys with designed compositions.Our results provide a new recipe to realize the property-oriented compositional design for highperformance complex alloys via machine learning.

Twenty years of rice genomics research: From sequencing and functional genomics to quantitative genomics

Since the completion of the rice genome sequencing project in 2005,we have entered the era of rice genomics,which is still in its ascendancy.Rice genomics studies can be classified into three stages:structural genomics,functional genomics,and quantitative genomics.Structural genomics refers primarily to genome sequencing for the construction of a complete map of rice genome sequence.This is fundamental for rice genetics and molecular biology research.Functional genomics aims to decode the functions of rice genes.Quantitative genomics is large-scale sequence-and statistics-based research to define the quantitative traits and genetic features of rice populations.Rice genomics has been a transformative influence on rice biological research and contributes significantly to rice breeding,making rice a good model plant for studying crop sciences.

Frequency-modulated continuous-wave dual-frequency LIDAR based on a monolithic integrated two-section DFB laser

We demonstrate a high-resolution frequency-modulated continuous-wave dual-frequency LIDAR system based on a monolithic integrated two-section(TS) distributed feedback(DFB) laser. In order to achieve phase locking of the two lasers in the TS-DFB laser, the sideband optical injection locking technique is employed. A high-quality linear frequency-modulated signal is achieved from the TS-DFB laser. Utilizing the proposed LIDAR system, the distance and velocity of a target can be measured accurately. The maximum relative errors of distance and velocity measurement are 1.6% and 3.18%, respectively.