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Despite the prevalence of corporate entrepreneurship, our understanding of its temporal horizon remains undeveloped. This study fills this gap by using stewardship theory to elaborate on how an entrepreneur's prior experience moderates the association between a firm's long-term orientation and corporate entrepreneurship. Using data based on a large-scale survey of private small and medium-sized firms in China, we find that long-term orientation plays a positive role in the corporate entrepreneurship of small and medium-sized firms. The evidence shows that the link between long-term orientation and corporate entrepreneurship is enhanced within firms where entrepreneurs have prior experience in the government or the military. However, the strength of this link is weakened within firms where entrepreneurs have overseas experience. This study contributes a fine-grained understanding of the temporal horizon and stewardship tendency that firms integrate when implementing entrepreneurial activities.

Graphene has attracted significant interest due to its unique properties. Herein, we built an adsorption structure selection workflow based on a density functional theory (DFT) calculation and machine learning to provide a guide for the interfacial properties of graphene. There are two main parts in our workflow. One main part is a DFT calculation routine to generate a dataset automatically. This part includes adatom random selection, modeling adsorption structures automatically, and a calculation of adsorption properties. It provides the dataset for the second main part in our workflow, which is a machine learning model. The inputs are atomic characteristics selected by feature engineering, and the network features are optimized by a genetic algorithm. The mean percentage error of our model was below 35%. Our routine is a general DFT calculation accelerating routine, which could be applied to many other problems. An attempt on graphene/magnesium composites design was carried out. Our predicting results match well with the interfacial properties calculated by DFT. This indicated that our routine presents an option for quick-design graphene-reinforced metal matrix composites.

A Co-free as-cast AlCrFe2Ni2 medium entropy alloy (MEA) with multi-phases was remelted by fiber laser in this study. The effect of laser remelting on the microstructure, phase distribution and mechanical properties was investigated by characterizing the as-cast and the remelted AlCrFe2Ni2 alloy. The laser remelting process resulted in a significant decrease of grain size from about 780 μm to 58.89 μm (longitudinal section) and 15.87 μm (transverse section) and an increase of hardness from 4.72 ± 0.293 GPa to 6.40 ± 0.147 GPa (longitudinal section) and 7.55 ± 0.360 GPa (transverse section). It was also found that the long side plate-like microstructure composed of FCC phase, ordered B2 phase and disordered BCC phase in the as-cast alloy was transformed into nano-size weave-like microstructure consisting of alternating ordered B2 and disordered BCC phases. The mechanical properties were evaluated by the derived stress-strain relationship obtained from nano-indentation tests data. The results showed that the yield stress increased from 661.9 MPa to 1347.6 MPa (longitudinal section) and 1647.2 MPa (transverse section) after remelting. The individual contribution of four potential strengthening mechanisms to the yield strength of the remelted alloy was quantitatively evaluated, including grain boundary strengthening, dislocation strengthening, solid solution strengthening and precipitation strengthening. The calculation results indicated that dislocation and precipitation are dominant strengthening mechanisms in the laser remelted MEA.

A new carbon allotrope, pentadiamond, was recently reported in the literature. Herein, we investigate its thermal expansion and thermoelastic properties by first principles. It is observed that the bulk modulus and hardness of pentadiamond are far less than those of diamond, but the thermal expansion of pentadiamond is lower than that of diamond in the range of 0 K to 2000 K, and even negative in the temperature range of 0-190 K. The negative thermal expansion at low temperature originates from the transverse vibrations of the edge-shared atoms in the coplanar double-pentagon. The low thermal expansion at high temperature is contributed by the strong bonds in pentadiamond. Benefiting from the low thermal expansion, the elastic constants of pentadiamond decrease very slowly with respect to temperature compared with those of diamond. The low sensitivity of thermodynamic and thermoelastic properties to temperature makes pentadiamond a promising material for high anti-thermal-shock and accurate electronic device applications.

In this paper, we present an efficient and effective method to predict the pressure dependence and temperature dependence of second-order elastic constants (SOECs) by introducing third-order elastic constants (TOECs) in the monocarbide ultrahigh temperature ceramics. The method is validated by comparing with experiments and previous calculations in four TMCs (TM = Nb, Ti, V, Zr). Using this method, we investigate the derivatives of SOECs against pressure and temperature as well as the anisotropic properties of polycrystalline modulus. In addition, we fit the SOECs with pressure and temperature under the framework of CALPHAD for practice usage.

To explain why some privately owned firms in emerging market settings benefit from government policies while others do not, this paper goes beyond the notion of political connections and emphasizes the role of entrepreneurial attention. Building upon the attention-based view (ABV), this study illuminates how entrepreneurial attention to government policies is translated into firm performance. Based on a dataset of 2386 Chinese privately owned firms, this study finds that entrepreneurial attention to government policies facilitates corporate venturing activities that lead to enhanced performance in the Chinese context. Additionally, the relationship between entrepreneurial attention to government policies and corporate venturing is conditioned by local government intervention. This study advances our understanding of the relationship between government policies and firm performance by unveiling the importance of entrepreneurial attention, all of which serve as the micro-foundations of the heterogeneous impacts of government policies on firms. This study also enriches the entrepreneurial attention literature and sheds new light on the antecedents of corporate venturing.

PurposeOne increasingly popular financing option for entrepreneurial ventures is to attract corporate venture capital (CVC) investments. Prior research tends to take a CVC-centric perspective assessing the benefits and contingencies for incumbent firms or corporate investors to engage with entrepreneurial ventures. Few studies have taken the opposite perspective of investigating factors that entrepreneurial ventures need to take into account when engaging with CVC investments. As such, this study aims to investigate pre- and post-IPO entrepreneurial venture performance that partners with CVC providers or corporate investors, as well as to assess organizational and environmental contingencies.Design/methodology/approachThis study draws on a sample of 631 entrepreneurial ventures from the CSMAR database ranging from 2009 to 2019, along with CVC financing data from the CVSource database and financial data in entrepreneurial ventures’ annual reports from the Juchao Network. This study applies multiple linear regression modelling and fixed effect panel data analyses to test the proposed hypotheses.FindingsThe results show that CVC investment contributes to entrepreneurial ventures’ financial performance, both pre- and post-IPO. However, while research and development (R&D) intensity and geographic proximity strengthen the positive relationship between CVC investment and entrepreneurial ventures’ performance pre-IPO, R&D intensity has a negative moderating effect on the relationship between CVC investment and entrepreneurial ventures’ performance post-IPO.Practical implicationsFirst, in emerging economies, adopting a CVC financing strategy is an important strategic choice for entrepreneurial ventures that have a great demand for external capital, resources and technology support. Second, leveraging the relationship between external financing and internal R&D investment is essential for them to maintain their core competitiveness and sustainable growth. Moreover, entrepreneurial ventures should deal with the coopetitive relationship with incumbent companies and manage their dependency on other market participants in the external environment.Originality/valueThis study focuses on the performance implications for entrepreneurial ventures engaging with CVC investments pre- and post-IPO. First, this study broadens and expands prior research on the mechanism of the relationship between CVC and entrepreneurial ventures’ financial performance. Second, the research conducts a comparative study of the moderating effects of different timings. Third, this study applies learning theory to the field of CVC in emerging economies.

This study investigates how firms’ social capital affects their access to informal finance. We argue that social capital helps reduce information asymmetry, increase trust between related parties and enforce lending contracts, so it has positive effects on firms’ access to informal finance. Using novel survey data of Chinese private firms, we find that firms with more social capital have more access to informal finance with lower costs. Further tests show that the effect of social capital is more significant when firms are located in regions with less developed market and lower community’s social capital and during the 2008 financial crisis.

Dilute magnetic semiconductors (DMSs), such as (In, Mn)As and (Ga, Mn)As prototypes, are limited to III–V semiconductors with Curie temperatures ( T c ) far from room temperature, thereby hindering their wide application. Here, one kind of DMS based on perovskite niobates is reported. BaM x Nb (1− x ) O 3− δ ( M = Fe, Co) powders are prepared by the composite-hydroxide-mediated method. The addition of M elements endows BaM x Nb (1− x ) O 3− δ with local ferromagnetism. The tetragonal BaCo x Nb (1− x ) O 3− δ nanocrystals can be obtained by Co doping, which shows strong saturation magnetization ( M sat ) of 2.22 emu g −1 , a remnant magnetization ( M r ) of 0.084 emu g −1 and a small coercive field ( H c ) of 167.02 Oe at room temperature. The ab initio calculations indicate that Co doping could lead to a 64% local spin polarization at the Fermi level ( E F ) with net spin DOS of 0.89 electrons eV −1 , this result shows the possibility of maintaining strong ferromagnetism at room temperature. In addition, the trade-off effect between the defect band absorption and ferromagnetic properties of BaM x Nb (1− x ) O 3− δ is verified experimentally and theoretically.

The unique high-temperature properties of refractory high entropy alloys (HEAs) are mainly depended on their phase formation. Therefore, a new approach to predict the phase formation has to be proposed, in order to accelerate the development of refractory HEAs. Here, we use machine learning to build classifiers to predict the phase formation in refractory HEAs. Our dataset containing 271 data only consists of as-cast refractory HEAs data. We simplify the input parameters to element content, and refine the phase formation outputs into five classes. Decision tree has been employed to build our phase classifier, due to its great advantages in solving classification problem. Both training and test accuracy of phase formation prediction achieve 90% using our classifier. The five single phase prediction accuracies are above 97%. Our phase classifier performs effectively in multi-phases classification and prediction of refractory HEAs, and establishes a direct relation between compositions and refractory phase formation.

Melting temperature has great influence on the high temperature properties and working temperature limits of ultra-high temperature ceramics (UHTCs) In order to bypass the challenge in the measurement of ultra-high melting points, this paper proposed a novel method to predict UHTCs melting temperature via machine learning. A dataset including more than ten thousand melting temperature data has been established, which covers 8 elements and most of the known non-oxide UHTCs. We built up an element to ceramic system framework by back propagation artificial neural network (BPANN) with the accuracy approaching to 90% and the correlation coefficients approaching to 0.95. Our work provides a probability to get the high accuracy melting temperature of UHTCs, and a more convenient way to develop novel materials with higher working temperature. The given case of melting temperature prediction of Hf-C-N ceramics proves the generality of the artificial neural network (ANN). An inter-validation of melting temperature prediction using our network with materials thermodynamics and density functional theory (DFT) has been demonstrated, indicating that our network is of powerful prediction ability.

What types of entrepreneurs are more likely to ‘stay tuned’ to government policies and does it pay? Integrating work on opportunity recognition and the institution-based view, this study examines t...

Quenching and partitioning (QP meanwhile, the number of experiments was reduced significantly. When treated by quenching at 180 °C followed by partitioning at 330 °C for 20 min, the steel reached the best combination between strength and ductility. In detail, the product of ultimate tensile strength and reduction in area was 1.36 times (from 64.9 to 88.8 GPa%) that treated by quenching and tempering. In addition, owing to the grain refinement, the strength and ductility increase simultaneously. Specifically, the reduction in area increased by 27.4% (from 35.8% to 45.6%) coupled with a little improvement in ultimate tensile strength (7.4%).

In this work, numerical modeling and simulation method was firstly used to obtain the hot-pressing sintering parameter of high entropy alloy (HEA). The finite element model was built to describe the consolidation process. Constitutive relation of powder material was applied assuming that metal powder is a kind of elasto-plastic material with an elliptical yield criterion. The change law of relative density for sintered bulk varying with pressure, time and temperature were obtained. Besides, the flow stress as well as relative density distributions were acknowledged with different sintering time. The simulation results indicate that the HEA would achieve a relative density of more than 95 % if the pressure above 45 MPa at 1150 ℃. The relative density from experiment is well agreement with that of simulation results when the sintering parameter are within the predicted range. This work is of great importance to the study of hot-press sintering of HEA.

Preparing transition-metal oxides in their two-dimensional (2D) form is the key to exploring their unrevealed low-dimensional properties, such as the p-type transparent superconductivity, topological Mott insulator state, existence of the condensed 2D electron/hole gas, and strain-tunable catalysis. However, existing approaches suffer from the specific constraint techniques and precursors that limit their product types. Here, we report a solution-based method to directly synthesize KNbO2 in 2D by an out-of-the-pot growth process at low temperature, which is observed directly in real time. The developed method can also be applied to other 2D ternary oxide syntheses, including CsNbO2 and composited NaxK1-xNbO2, and it can be extended to the preparation of self-assembled nanofilms. In addition, We demonstrate the emission of broadband photoluminescence (PL, λ ∼ 350-800 nm) from as-synthesized single-crystal 2D KNbO2 sheets down to a single unit cell thickness. The ultra-broadband emission is ascribed to the self-trapped excitation state (STEs) from the in-phase distortion of the NbO6 octahedrons in 2D NbO2- layers. Beyond the broader luminescent range and the robust material thermal stability of niobates, the absence of sample size restrictions and the large aspect ratio of the 2D oxide sheets will provide opportunities in miniaturizing and advancing 2D-materials integrated optoelectronic devices.

In this paper, we report the estimation of the minimum PMIs of two human corpses and two dog carcasses using entomological evidence. Corpses of an elderly couple and carcasses of four dogs were found scattered on different floors in a house. The scene was very dirty. In addition, there were 12 emaciated live dogs at the scene. The corpses had been eaten by the dogs to different degrees, but the damage was greater on the man’s corpse. After forensic examination, it was concluded that both individuals died of natural causes. The minimum PMIs of the two individuals and the two dogs were estimated using entomological evidence. The minimum PMIs of the other two dogs were not estimated because of the risk of contamination with the human corpses. Different insect species were found on each of the corpses and carcasses. The minimum PMIs were estimated as about 8.75 days for the woman, 4.17 days for the man, 3.13 days for the dog found in the stairwell and about 28.80 days for the dog found in the toilet. These estimations coincided with the time the woman stopped communicating with her daughter and when the electricity consumption at the house decreased significantly.

The influence of alloying elements on phase stability, elastic and thermodynamic properties of random Nb-Ti-V-Zr high entropy alloys was investigated by virtual crystal approximation (VCA) based on first principles calculation. The lattice constant, elastic constant and thermal expansion coefficient of equimolar NbTiVZr agree well with other calculations and experiments, which indicates that VCA scheme is suitable for random Nb-Ti-V-Zr system. The stable crystal structure was judged by energy criterion, which shows that BCC is the most stable structure except NbxTiVZr(x ≦ 0.4) and NbTiVZrx(x ≧ 1.6). Based on BCC structure, the dependence of elastic stiffness on composition was built using CALPHAD model, which fits well with the value calculated by first principles. Furthermore, the polycrystalline elastic modulus and anisotropy were estimated. In addition, the thermodynamic properties, such as thermal expansion coefficient, as a function of component and temperature were calculated using quasi-harmonic Debyeg-Gruneisen model.

To increase the understanding of entrepreneurship in China and contribute to the view that deregulation facilitates the rapid development of the private sector in transitional economies, we examine the positive relationship between entrepreneurial attention to deregulation (formal institution at the country level) and reinvestment by Chinese private firms. We supplement this main aim by identifying two moderating factors: the entrepreneurs’ political connections (informal institution) and the regional institution development (formal institution at the regional level). We also explore how the interaction of political connections and regional institution development moderate the “entrepreneurial attention to deregulation-reinvestment” link. We find support for our hypotheses from survey data on 3,284 private firms in China. This paper contributes to the research on the relationship between institution and entrepreneurship in general and the association of deregulation and reinvestment in particular by considering two categories of institutional arrangements (formal and informal institutions; national and regional institutions) simultaneously and by exploring the antecedent of reinvestment from a fresh perspective—the attention-based view, highlighting the importance of “noticed” or “perceived” deregulation that influences entrepreneurial decision-making.

The Polar discontinuity at heterointerface and the bare surface reconstructs the electronic phase of perovskite oxides. This gives rise to confined free electrons which intrinsically transit material from band insulator to metal. However, the insulator–metal transition induced by free holes has not been investigated so far due to the challenge in obtaining free hole state in oxides. Here, we propose a simple method whereby free holes can be obtained via polar facet reorientation. In the high polarity case, free holes can be supported by the lift up of O 2p subbands, which split into three independent subbands (one heavy hole subband and two light hole subbands) due to strong quantum confinement. Results show that both of the free electron and hole states are confined in a two dimensional quantum well, subjecting to the confined energy (E − EF) and occupied density of states around the Fermi level, indicating a finite thickness for preserving the metal states.

In this work, we present a software package in Python for high-throughput first-principles calculations of thermodynamic properties at finite temperatures, which we refer to as DFTTK (Density Functional Theory Tool Kit). DFTTK is based on the atomate package and integrates our experiences in the last decades on the development of theoretical methods and computational software. It includes task submissions on all major operating systems and task execution on high-performance computing environments. The distribution of the DFTTK package comes with examples of calculations of phonon density of states, heat capacity, entropy, enthalpy, and free energy under the quasi-harmonic phonon scheme for the stoichiometric phases of Al, Ni, Al3Ni, AlNi, AlNi3, Al3Ni4, and Al3Ni5, and the fcc solution phases treated using the special quasirandom structures at the compositions of Al3Ni, AlNi, and AlNi3., 50 pages, 18 figures

The effect of fabrication methods on microstructures, mechanical properties, and strengthening mechanisms of high-entropy alloys has been systematically studied. In this work, a non-equiatomic Fe0.25CrNiAl medium-entropy alloy (MEA) was selected and fabricated by arc-melting, spark plasma sintering (SPS), and hot-press sintering (HPS). The results indicate that the fabrication method has little effect on the main phase compositions of Fe0.25CrNiAl MEA while marked impacts on microstructures, mechanical properties, and strengthening mechanisms. All alloys mainly consist of a disordered body-centered cubic (BCC) phase and an ordered body-centered cubic (B2) phase. However, the arc-melted alloy possesses a typical dendritic structure, while a speckle-like microstructure for the SPS-ed and HPS-ed alloys. Particularly the grain is refined dramatically by powder metallurgical methods of SPS and HPS. The yield strength of powder metallurgical alloys is over 400 MPa higher than that of arc-melted alloy, and without sacrificing the ductility (~30%). The strengthening mechanism analysis demonstrates that precipitate strengthening plays a significant role for arc-melted alloy while grain boundary strengthening is the dominant strengthening mechanism for powder metallurgical alloys. The Fe0.25CrNiAl MEAs by powder metallurgy achieve a trade-off between high strength and strain-to-failure, which suggests that the method is available for improving the mechanical properties of high-entropy alloys.

In this letter, we study the higher-order effect on the third-order elastic constants (TOECs) of diamond using longitudinal stress-uniaxial strain (LSUS) approach based on density functional theory. The result shows that the higher-order effect on TOECs is not negligible in the shock wave experiments and similar calculations. By taking the higher-order elastic response (up to fifth order) into consideration, the convergence of TOECs against maximum stain gets improved significantly and resolves the discrepancy of several different theoretical methods and experiments., 9 pages, 3 figures, 2 tables

Drawing on imprinting theory and the attention-based view of strategy, this study extends previous literature on the implications of imprinting for opportunity selection by examining how Chinese entrepreneurs’ socialist imprinting from their formative experiences in the Danwei system guides them to pursue lucrative policy-induced opportunities arising from government deregulation, reform, and incentives in certain industries. Using data from 3803 privately owned enterprises in China, we find that (1) privately owned enterprises with entrepreneurs bearing the socialist imprint are more likely to act on policy-induced opportunities to make a quick profit; (2) the relationship between socialist imprinting and the selection of these opportunities is mediated by the entrepreneurs’ attention to government policies; (3) the positive association between socialist imprinting and the selection of these opportunities is less salient for privately owned enterprises located in regions with higher institutional development.

This paper investigates the association between dividend payouts and earnings quality for Chinese listed firms. The results show that dividend payouts are associated with more persistent earnings, higher accrual quality, and greater earnings informativeness, confirming the hypothesis on information content of dividends for Chinese firms. Further analyses show that the relationship between dividends and earnings could change with factors influencing the incentives to pay dividends. We find that the positive impact of dividend payouts on earnings quality is reduced for firms conducting equity refinancing. We also find evidence that the state ownership can reduce the information-conveying role of dividends.

The third-order elastic constants (TOECs) are fundamental to describe crystal’s nonlinear response to stress, and can be applied to explore anharmonic properties of crystals such as Gruneisen parameters, thermal expansion coefficient, and the effect of pressure on second-order elastic constants (SOECs). Here, we report an open-source python package, Elastic3rd, which is able to calculate the SOECs and TOECs using the strain–energy method for crystals with any symmetry from first-principles calculations. An algorithm to generate necessary strain modes and the corresponding coefficients for a given symmetry is proposed. These strain modes are then applied to the fully relaxed structure to generate the deformed structures. The total energies of the strained structures are calculated by a chosen first-principles code, and the SOECs and TOECs are determined by fitting the resulted strain–energy data. The present code has been validated by several case studies of C, Si and Mg, and the case of MnP4 shows the ability for low-symmetry crystals. Program summary Program title: Elastic3rd CPC Library link to program files: https://doi.org/10.17632/n54vr2kwx8.1 Developer’s repository link: https://github.com/hitliaomq/ELASTIC3rd Licensing provisions: GNU General Public License 3 Programming language: Python 2.7.X and Python 3.X. External routines/libraries: Numpy [1], Scipy [2], and Matplotlib [3]. Nature of problem: To automatically calculate the third-order elastic constants for crystals with any symmetry from first-principles calculations. Solution method: Firstly, the deformed patterns and the corresponding coefficients for the second- and third-order elastic constants are automatically generated according to the symmetry. Secondly, the deformed patterns are applied to the initial lattice and the corresponding input files for first-principles calculations are generated. Thirdly, the energies of the deformed structures are calculated by first-principles software such as CASTEP [4] and VASP [5]. Then, the parameters of strain–energy functions are obtained by fitting the strain and energy relationships. Finally, the third-order elastic constants are determined by solving the linear-independent equations, and the second-order elastic constants are calculated by solving the overdetermined equation using the least squares method. Addition comments including restrictions and unusual features: This code is well modularized. Thus, the energy can be calculated using energy-generated first-principles or other packages only by writing few functions. [1] S. Van Der Walt, S.C. Colbert, G. Varoquaux, Comput. Sci. Eng. 13(2011):22–30 [2] P. Virtanen, R. Gommers, T.E. Oliphant, et al., ArXiv:1907.10121 (2019). [3] J.D. Hunter, Comput. Sci. Eng. 9(2007):99–104. [4] S.J. Clark, M. D. Segall, C.J. Pickard, et al. Z. Kristallogr. 220(2005):567-570. [5] G. Kresse, J. Furthmuller, Phys. Rev. B 54 (1996) 11169.

The interfacial properties of graphene/Al composites are of critical important for exploring its high mechanical performance. To improve the mechanical properties, many experimental works have been done in past decades, however, the understanding of their physical mechanisms are limited. Here, the electronic structures and interfacial adhesion properties of pristine/virous deficient graphene(0 0 1)/Al(1 1 1) interfaces are calculated by first-principles method. Results show that single vacancy defective graphene (SVG)/Al interface has larger work of adhesion (Wad) of 5.62 J/m2 than the pristine (Wad of 1.03 J/m2) and other defective graphene/Al interfaces (Wad of 5.12 J/m2 for boron doped single vacancy defective graphene (BVG)/Al and Wad of 5.12 J/m2 for double vacancy defective graphene (DVG)/Al, respectively) due to the strong hybridization of Al-2p and C-2p orbits, which giving rise to the formation of polar covalent bonds with the bond populations of 0.62–0.72 at the deficient site The corresponding interface spacing decreasing from 2.72 A (Pristine Gra/Al) to 2.17 A (SVG/Al). And the defective graphene doped by B atoms could inhibit the interaction between Al and C atoms in the BVG/Al interface. Comparing with the SVG and BVG cases, the interface interaction strength of DVG/Al interface decreases due to the formation of octatomic ring, which could cape the carbon dangling bond and lead to a small structure deformation of graphene. However, it maintains a high Wad of 3.98 J/m2, indicating a better interface bonding strength than idea Gra/Al.

To predict the thermal deformation behavior in pearlitic steel, the stress–strain data from hot compression tests on a Gleeble-1500D thermo-simulation machine, with the strain rate range of 0.001–1 s−1 and the deformation temperature range of 1223–1373 K, were employed to develop the Arrhenius-type constitutive model and BP neural network model. Then a comparative study was carried out to further evaluate the predictability of the Arrhenius-type constitutive model and BP neural network model. The results show that the correlation coefficient (R) and average absolute relative error (AARE) for the improved Arrhenius-type constitutive equations were found to be 0.98884, 6.41%, respectively, while the R and AARE for BP neural network model were 0.99986, 0.5519%, respectively. The BP neural network model can accurately track the experimental data across the whole hot working process and exhibits better performance than improved Arrhenius-type constitutive equation. Then, the experimental results at 1323 K demonstrate the predictive capability of the developed BP neural network model. Finally, the processing maps suggests that the flow instability tends to occur at low deformation temperature and high strain rate. The optimum processing parameters of the pearlitic steel are in the temperature range of 1223–1293 K and strain rate range of 0.001–0.004 s−1.

This article investigates the effect of heterogeneous beliefs on firms’ mergers and acquisitions (M&A) decisions. Using data of China’s financial market, which is featured with great heterogeneity of belief, we find that heterogeneous beliefs are positively associated with the occurrence of M&A transactions, and firms with greater heterogeneous beliefs are more likely to pay the transactions with stock. Moreover, we show that government intervention, measured by state ownership, weakens the effect of heterogeneous beliefs on firms’ M&A decisions.

This paper examines how government intervention affects firms' investment and investment efficiency, focusing on the world's largest economic stimulus package (ESP) during the 2008 global financial crisis period. The RMB four trillion ESP aimed to restore the economy by promoting investment in priority areas. Thus it provided an exogenous shock to firms' investment environment and exacerbated the impact of government intervention on firms' investment and investment efficiency. We use propensity score matching to match government-intervened firms with their controls to reduce the endogeneity issue of government intervention. Our difference-in-differences analysis shows that government-intervened firms invested more than control firms. Further analysis shows that the source of funding for investment was mainly from bank loans rather than internal cash flows. However, the post-investment performance was poor. We find that the investment efficiency of government-intervened firms decreased and government-intervened firms overinvested after the ESP. Our results are robust to alternative model specifications and placebo tests. The findings suggest that government intervention can play a negative role in government-intervened firms.

A grain refined FeCrNiAlTi0.2 high entropy alloy (HEA) was firstly produced by powder metallurgy, and the alloy combines well with high strength, good ductility and low cost. The sintered HEA exhibits a major body-centered cubic (BCC) matrix and a minor ordered BCC (B2) phase. The alloy possesses an excellent properties, reaching the yield strength of 1877 MPa and plastic strain of 26.6% at room temperature. Compared with the current FeCrNi-based HEAs, the compressive strength is improved distinctly without sacrificing plastic strain. The analysis of strengthening mechanism suggests that the main strengthening contribution is the grain boundary strengthening.

Bridging both the edges and the center of multicomponent space, which have been widely investigated in traditional alloys and high entropy alloys respectively, is significant but difficult in the design of alloys. In this paper, the single-crystal elastic constant model of the quaternary BCC Nb-Ti-V-Zr system across full composition space was established using first principles combined with the CALPHAD model. The accuracy of the model was confirmed by comparing with previous calculations and experiments. Using the fitted model, the alloying effect on stability and polycrystalline elastic properties of the current research system was analyzed. We find that there exists an area where BCC becomes unstable, and all the instability is caused by breaking C11-C12 > 0. And all of the stable Nb-Ti-V-Zr is ductile. In addition, there lies a surface on which the alloys are completely isotropic in elasticity. Furthermore, some alloys promising in some special aspects are predicted, such as gum metal, directional auxetic properties and biomedical application materials.

In this study, we investigated the electronic and magnetic nature of the LiMgPdSn-type CoFeHfGe quaternary Heusler alloy in the bulk form as well as the (100) and (001) surfaces using density functional theory within the generalized gradient approximation scheme. The bulk CoFeHfGe alloy was predicted to exhibit half-metallic behavior with an electronic band gap of 0.37 eV and 100% spin-polarization at an equilibrium lattice parameter of 6.08 A. The elastic constants and phonon dispersion confirmed the mechanical and dynamical stability of the bulk form considered. The total magnetic moment was determined as 1μB/f.u. for the CoFeHfGe alloy. The atomic relaxation and surface energy were investigated for the (100) and (001) surfaces of the CoFeHfGe alloy, and the results indicated that the slabs are stable, where CoFe (001) has the lowest surface energy among all of the terminations. For (100) and (001) slabs of the CoFeHfGe alloy, we found that the half-metallicity is destroyed due to the surface states and the HfGe (100) slab has the highest spin polarization of 90.72%, and thus it can be used in giant magnetoresistance devices. The magnetic moments in the layers of the HfGe (100) slabs are similar to the corresponding bulk and magnetic moments of the surface atoms, where they tend to increase with depth in the CoFe (100) slab.

Murderers sometimes dispose of bodies in zipped suitcases in an attempt to conceal their crimes. In these cases, the species of insects found and their succession patterns are typically different from those found on exposed corpses due to hindrances or delays in colonization. Here we report a case in which an unidentified female corpse was found in a soft-shell suitcase in a wetland area among some reeds in Guangdong, China on 13 May 2018. The suitcase was unbroken and zippers were well-sealed. The victim was a young woman, naked, and curled up in the suitcase. The insect evidence we collected include (i) pupae and empty puparia of Chrysomya nigripes (Aubertin) (Diptera: Calliphoridae) and Fannia canicularis (Linnaeus) (Diptera, Muscidae), (ii) larvae, pupae and empty puparia of Megaselia scalaris (Loew) (Diptera: Phoridae) and Hermetia illucens (Linnaeus) (Diptera: Stratiomyidae). According to this insect evidence, we estimated the PMImin as 56 days. Bhadra et al. (2014) show that larvae of Calliphora vomitoria (Linnaeus) (Diptera: Calliphoridae) and Calliphora vicina (Robineau-Desvoidy) (Diptera, Calliphoridae) can colonize carcasses concealed in zipped suitcases. Although the size of the zipper (7mm) in this case is larger than that described in Bhadra et al. (4mm), we did not find Chrysomya megacephala (Fabricius) (Diptera: Calliphoridae), Chrysomya rufifacies (Macquart) (Diptera: Calliphoridae), or Lucilia sericata (Meigen) (Diptera: Calliphoridae) which usually colonize fresh corpses in this area. Therefore, we deduced that the victim may have been killed in winter. After the crime was solved, the murderer confessed that he killed the victim on 5 January.

In text-independent speaker identification, there are a large number of likelihood computations, especial in large population. To speed up the recognition, we proposed a lightweight algorithm called CBF (Codebook Filtering). CBF provides two phase of speaker pruning to accelerate the speaker recognition. To make CBF could process large population, this paper implements CBF on Map-Reduce framework. In this approach, we encountered some problems, such as how to balance accuracy and speed-up of algorithm. This paper provides a mechanism of parameter consulting to archieve satisfactory accuracy and speed-up factor. To verify algorithm, we implement it on Phoenix, a Map-Reduce framework on multi-core. As the result of experiment, this approach has increased the speed-up factor of CBF obviously. The speed-up factor reaches 40.2 when the accuracy keeps 94.98%.