Preparation and characterization of a specialized lunar regolith simulant for use in lunar low gravity simulation

Lunar in-situ resource utilization(ISRU)has been put on the agenda by many countries.Due to the special material nature and low gravity environment,the lunar regolith demonstrates significantly different behavior from terrestrial geomaterials.However,the systematic understanding of its geotechnical behavior is now seriously restricted by the scarcity of lunar regolith and the difficulty in simulating lunar gravity.A new lunar regolith simulant,termed as China University of Mining and Technology Number One(CUMT-1),has been developed to recover properties of the lunar regolith and simulate the lunar gravity by adopting the recently advanced geotechnical magnetic-similitude-gravity model testing(GMMT)method.The CUMT-1 simulant was prepared by reproducing the in-situ formation and fragmentation of the lunar matrix,which plays a key role in the irregular particle morphology.The mineralogical compositions,particle morphology and gradation,specific gravity,bulk density,void ratio,shear strength,and compressibility were determined.After quantifying the magnetization and magnetic-similitude-gravity characteristics,an application of the cone penetration resistance under low gravity was further given.The obtained results are compared to the values known for lunar regolith samples and other simulants,which demonstrates promising characteristics for use in geotechnical engineering-based and scientificbased applications,especially considering the influence of lunar gravity.

Behaviour of granular matter under gravity-induced stress gradient:A two-dimensional numerical investigation

Gravity is the most important load source in mining and geotechnical engineering,which causes both the stress level and stress gradient inside geomaterials.Different from the stress level,the influence of gravity-induced stress gradient on the behaviour of the material is still unknown.An in-deep study on it will help to promote the understanding of material behaviour,especially for those cases related to unconventional gravity such as terrestrial ng physical modelling and extraterrestrial resource exploitation(g is the terrestrial gravitational acceleration).In this study,a high-order homogenization for granular materials is proposed at first,in which the stress gradient is drawn into the constitutive representation by adopting a representative volume element(RVE).The consolidation and shear strength behaviour of RVE are then investigated by performing numerical biaxial tests.The results show that all the compressibility,shear strength,shear stiffness,volumetric deformation,and critical state behaviour show a stress gradient dependence.A coupling between stress gradient,stress level,and material properties is also observed.These observations suggest that,besides the stress level,extra attention needs to be paid to material responses related to stress gradient during engineering practices.

Bearing capacity of surface circular footings on granular material under low gravity fields

Low gravity fields have been simulated through magnetic acceleration to conduct experimental study on bearing capacity of circular footings on a type of crushable planetary regolith simulant,which has comparable density and particle size distribution of lunar soil.The loadesettlement responses of surface spread footings are obtained by investigating the relative density,footing size and gravity effects.Applying the hyperbolic asymptote method,normalised foundation stiffness and ultimate bearing capacity are obtained by curve fitting and predicted by power functions using multivariate nonlinear regression.The results show that the nonlinear gravity effect is not negligible,related to stress condition,soil dilatancy and mobilised friction angle.A cone penetration test(CPT)-based method for prediction of bearing capacity is proposed with correlations between ultimate bearing capacity of footings and shallow penetration stiffness of CPTs,avoiding the uncertainties of soil property estimations.Analyses of allowable bearing capacity and footing influence zone in consideration of footing size and gravity effects could therefore improve the design of shallow foundations on the Moon and Mars,and provide new understandings and potential implications to the bearing capacity of shallow foundations on crushable granular material in both terrestrial and extraterrestrial geotechnical engineering.

The Influences of Energy Price Variation on the Prices of Other Industries: A Study Based on Input-Output Price Model

Energy has laid material foundation for human society during its development. Meanwhile, any change of price in the energy industry may influence social production and people’s life at all levels via an input-output mechanism under which the change related to energy is surely transmitted to other industries. The price change thus incurred in all industries may adversely affect the realization of macroeconomic objective-maintaining prices at a stable level. It is, therefore, needed to conduct an empirical research related to the impact of price change in energy industry on that in other industries. According to the data coming from “China’s 2015 Input-Output Extension Table (42 Departments)” and four hypothetical basis, this article focuses on four energy sectors and analyzes how deeply the price change of them, by use of input-output model, affects that of other industrial products under five conditions where each of their price rises by 10% individually or simultaneously, and why such an influence occurs. The results show that the price rising of the energies in question leads to an upward growth in the prices of other industrial products, especially when their prices go up simultaneously. Besides, the price increase in the four energy sectors doesn’t influence other industries in an accumulation form but actually leads to a rollback in some of other industries. It is recommended to adopt diversified pricing strategies for different energy products, thus maximizing the value of each specific energy, and meanwhile achieving the goals of energy consumption reduction and price equilibrium.

Transmission electron microscopy of synaptic ultrastructural white matter damage in neonatal rats

BACKGROUND： To date, animal models of white matter damage remain controversial. Mild grey matter damage should be the basis for animal models to investigate white matter disease. OBJECTIVE： To establish white matter damage in neonatal rats and evaluate feasibility of the established model by observing myelination and synaptic ultrastructure. DESIGN, TIME AND SETTING： A randomized, controlled, animal experiment was performed at the Laboratory of Histology and Embryology of Guangzhou Medical College from December 2008 to May 2009. MATERIALS： H600 transmission electron microscopy was provided by Hitachi, Japan. METHODS： A total of 39 neonatal, Sprague Dawley rats were randomly assigned to normal control （n = 12）, sham-surgery （n = 12）, and white matter damage （n = 15） groups. White matter damage rats were subjected to right common carotid artery ligation, followed by inhalation of nitrogen oxygen gas mixture （6% oxygen） for 4 hours. MAIN OUTCOME MEASURES： Myelin sheath and synaptic ultrastructure in the injured （right） hippocampal CA1 region in 1-month-old rats were observed through the use of transmission electron microscopy, and pathological changes in the cerebral cortex and corpus callosum of the right hemisphere were detected by hematoxylin-eosin staining. RESULTS： Obvious tissue loss was observed in the corpus callosum of the injured （right） hemisphere. Injured oligodendrocytes and disrupted myelination were observed in the white matter damage group. However, synaptic length in the active zones, width of synaptic cleft, thickness of postsynaptic density, and curvature of the synaptic interface remained unchanged following injury, compared with the control and sham-surgery groups （P 〉 0.05）. CONCLUSION： The established white matter damage model resulted in changes in myelination and slightly altered synaptic ultrastructures. The model could function as an ideal model for white matter damage in neonatal rats.

Hypothermic intervention for 3 hours inhibits apoptosis in neonatal rats with hypoxic-ischemic brain damage

A neonatal rat model of hypoxic-ischemic brain damage was designed and implemented in this study. Rats were subjected to hypothermia at 31℃ immediately following hypoxia-ischemia for either 3, 6 or 15 hours. TdT-mediated dUTP nick end labeling demonstrated that the number of apoptotic cells was reduced in the rat cerebral cortex, hippocampus and periventricular white matter following hypothermia. Immunohistochemistry revealed that Bcl-2 and p16 expression were decreased. Inhibition of apoptosis was greatest with the 3 hour hypothermic treatment, followed by hypothermia for 6 hours. In contrast, hypothermia for 15 hours led to a decrease in neuronal number in the cerebral cortex. The results demonstrate that hypothermic intervention at 31℃ protects brain tissue against hypoxic-ischemic brain damage by inhibiting apoptosis, and that the optimal length of treatment is 3 hours.

Automated detection on the security of the linked-list operations

1 Introduction As measures taken by OS(operation system)to mitigate exploit getting more perfect,the stack-related vulnerabilities are reduced gradually and heap-related vulnerabilities have become increasingly prominent in most C/C++memory vulnerabilities.As is known,software program is a fusion of data structures and algorithms.Therefore,if unsafe operations are performed on data,unintended results may occur.

Comparative genomic and transcriptomic analyses uncover the molecular basis of high nitrogen-use efficiency in the wheat cultivar Kenong 9204

Studying the regulatory mechanisms that drive nitrogen-use efficiency(NUE)in crops is important for sustainable agriculture and environmental protection.In this study,we generated a high-quality genome assembly for the high-NUE wheat cultivar Kenong 9204 and systematically analyzed genes related to nitrogen uptake and metabolism.By comparative analyses,we found that the high-affinity nitrate transporter gene family had expanded in Triticeae.Further studies showed that subsequent functional differentiation endowed the expanded family members with saline inducibility,providing a genetic basis for improving the adaptability of wheat to nitrogen deficiency in various habitats.To explore the genetic and molecular mechanisms of high NUE,we compared genomic and transcriptomic data from the high-NUE cultivar Kenong 9204(KN9204)and the low-NUE cultivar Jing 411 and quantified their nitrogen accumulation under high-and low-nitrogen conditions.Compared with Jing 411,KN9204 absorbed significantly more nitrogen at the reproductive stage after shooting and accumulated it in the shoots and seeds.Transcriptome data analysis revealed that nitrogen deficiency clearly suppressed the expression of genes related to cell division in the young spike of Jing 411,whereas this suppression of gene expression was much lower in KN9204.In addition,KN9204 maintained relatively high expression of NPF genes for a longer time than Jing 411 during seed maturity.Physiological and transcriptome data revealed that KN9204 was more tolerant of nitrogen deficiency than Jing 411,especially at the reproductive stage.The high NUE of KN9204 is an integrated effect controlled at different levels.Taken together,our data provide new insights into the molecular mechanisms of NUE and important gene resources for improving wheat cultivars with a higher NUE trait.

Gclust:A Parallel Clustering Tool for Microbial Genomic Data

The accelerating growth of the public microbial genomic data imposes substantial burden on the research community that uses such resources.Building databases for non-redundant reference sequences from massive microbial genomic data based on clustering analysis is essential.However,existing clustering algorithms perform poorly on long genomic sequences.In this article,we present Gclust,a parallel program for clustering complete or draft genomic sequences,where clustering is accelerated with a novel parallelization strategy and a fast sequence comparison algorithm using sparse suffix arrays(SSAs).Moreover,genome identity measures between two sequences are calculated based on their maximal exact matches(MEMs).In this paper,we demonstrate the high speed and clustering quality of Gclust by examining four genome sequence datasets.Gclust is freely available for non-commercial use at https://github.com/niu-lab/gclust.We also introduce a web server for clustering user-uploaded genomes at http://niulab.scgrid.cn/gclust.

How Big Data and High-performance Computing Drive Brain Science

Brain science accelerates the study of intelligence and behavior,contributes fundamental insights into human cognition,and offers prospective treatments for brain disease.Faced with the challenges posed by imaging technologies and deep learning computational models,big data and high-performance computing(HPC)play essential roles in studying brain function,brain diseases,and large-scale brain models or connectomes.We review the driving forces behind big data and HPC methods applied to brain science,including deep learning,powerful data analysis capabilities,and computational performance solutions,each of which can be used to improve diagnostic accuracy and research output.This work reinforces predictions that big data and HPC will continue to improve brain science by making ultrahigh-performance analysis possible,by improving data standardization and sharing,and by providing new neuromorphic insights.

Pusher:an augmented fuzzer based on the connection between input and comparison operand

Coverage based fuzzing is a widespread vulnerability detection technique,and it has exposed many bugs in many real-world programs.However,its attention is to eliminate the testing on the repeated paths,yet it still employs random mutation to generate inputs,which is blind to penetrate complex comparisons in the program.As a result,the testing coverage is limited.Despite some solution proposals are presented,this problem is still partially solved.This paper argues that random mutation is mainly limited by two challenges,the sizable search space and the lack of a useful feedback to direct the search.Then we present an augmented fuzzing technique by addressing these two challenges.First of all,we point out a black relationship between input contents and comparison operands,which is dubbed connection.Second,we present a novel method to collect the comparison operands during execution,which is leveraged to infer the connections.Based on the connections,the fuzzer can learn about which input byte affects on which comparison instruction to establish a smaller search space.Third,the connection provides a useful feedback to direct the search.We resort to a modern metaheuristic algorithm to satisfy this searching requirement.We developed a prototype Pusher and evaluated its performance on several benchmarks and four real-world programs.The experimental results demonstrate that Pusher works better than some other state-of-the-art fuzzers on bug detection,and can achieve a higher testing coverage.Moreover,we take a detailed statistic about the execution overhead in Pusher,and the results indicate that the execution overhead introduced by our approach is within an acceptable scope.