Consumption smoothing and vunerability in Russia

Applying bootstrapped quantile regression to the Russian Longitudinal Monitoring Survey (RLMS) data, we examine the channels through which individuals experience and seek to cope with changes in consumption. We find that married individuals living in small households, with educated heads in urban areas are better equipped to smooth consumption. Investigating the impact of idiosyncratic shocks, we find that the labour market is an important transmission mechanism allowing households to smooth their consumption but also exposing them to risk, mainly through job loss. Outside of pension payments the formal social safety net does not facilitate consumption smoothing, thus heightening the importance of informal coping institutions. It transpires that both support from relatives/friends and home production act as important insurance mechanisms for the most vulnerable

High Temperature Deformation Behavior of in-situ Bulk Metallic Glass Matrix Composites

Macroscopic ductility is promoted in bulk metallic glasses by both composite reinforcements (at low temperatures) and by the activation of viscous flow mechanisms (at high temperatures). It is of fundamental interest to understand deformation physics when both of these strategies are employed at the same time. Despite the quickly growing literature around the room-temperature mechanical properties of metallic glass matrix composites (MGMCs), the deformation behavior of MGMCs over a wide range of temperatures and strain rates has yet to be systematically investigated, especially at high temperatures close to Tg. Here the high temperature compressive behavior of Zr-based MGMCs with in-situ reinforcements is explored systematically over a series of strain rates. Additionally, the volume fraction of second-phase reinforcements was tailored to explore its effect on both inhomogeneous and homogeneous deformation modes.Singapore-MIT Alliance (SMA

High Temperature Deformation Behavior of Bulk Metallic Glass and Its Composites

The homogeneous deformation of Zr-based bulk metallic glass composites is studied near the glass transition temperature, at various levels of reinforcement volume fraction. Through examination of the constitutive response, it is seen that the presence of in-situ reinforcements increases the flow resistance of the glass dramatically. This strengthening effect is shown to arise from two separate contributions: load transfer from the amorphous matrix to the reinforcements, and changes to the glass composition and structure upon in-situ precipitation of reinforcements.Singapore-MIT Alliance (SMA

Internuclear gene silencing in Phytophthora infestans is established through chromatin remodelling

In the plant pathogen Phytophthora infestans, nuclear integration of inf1 transgenic DNA sequences results in internuclear gene silencing of inf1. Although silencing is regulated at the transcriptional level, it also affects transcription from other nuclei within heterokaryotic cells of the mycelium. Here we report experiments exploring the mechanism of internuclear gene silencing in P. infestans. The DNA methylation inhibitor 5-azacytidine induced reversion of the inf1-silenced state. Also, the histone deacetylase inhibitor trichostatin-A was able to reverse inf1 silencing. inf1-expression levels returned to the silenced state when the inhibitors were removed except in non-transgenic inf1-silenced strains that were generated via internuclear gene silencing, where inf1 expression was restored permanently. Therefore, inf1-transgenic sequences are required to maintain the silenced state. Prolonged culture of non-transgenic inf1-silenced strains resulted in gradual reactivation of inf1 gene expression. Nuclease digestion of inf1-silenced and non-silenced nuclei showed that inf1 sequences in silenced nuclei were less rapidly degraded than non-silenced inf1 sequences. Bisulfite sequencing of the endogenous inf1 locus did not result in detection of any cytosine methylation. Our findings suggest that the inf1-silenced state is based on chromatin remodelling

Cancellous bone from porous Ti6A|4V by multiple coating technique

A highly porous T{i}6Al4V with interconnected porous structure has been developed in our previous study. By using a so-called “Multiple coating” technique, the porous T{i}6Al4V can be tailored to resemble cancellous bone in terms of porous structure and mechanical properties. A thin layer of T{i}6Al4V slurry was coated on the struts of base porous T{i}6Al4V to improve the pore structure. After two additional coating, pore sizes ranged from 100 μm to 700 μm, and the porosity was decreased from ∼90% to ∼ 75%, while the compressive strength was increased from 10.3 ± 3.3 MPa to 59.4 ± 20.3 MPa and the Young's modulus increased from 0.8 ± 0.3 GPa to 1.8 ± 0.3 GPa. The pore size and porosity are similar to that of cancellous bone, meanwhile the compressive strength is higher than that of cancellous bone, and the Young's modulus is between that of cancellous bone and cortical bone. Porosity, pore size and mechanical properties can be controlled by the parameters in such multiple coating processes. Therefore the porous T{i}6Al4V with the characteristics of cancellous bone is expected to be a promising biomaterial for biomedical applications

A convergence and diversity guided leader selection strategy for many-objective particle swarm optimization

Recently, particle swarm optimizer (PSO) is extended to solve many-objective optimization problems (MaOPs) and becomes a hot research topic in the field of evolutionary computation. Particularly, the leader particle selection (LPS) and the search direction used in a velocity update strategy are two crucial factors in PSOs. However, the LPS strategies for most existing PSOs are not so efficient in high-dimensional objective space, mainly due to the lack of convergence pressure or loss of diversity. In order to address these two issues and improve the performance of PSO in high-dimensional objective space, this paper proposes a convergence and diversity guided leader selection strategy for PSO, denoted as CDLS, in which different leader particles are adaptively selected for each particle based on its corresponding situation of convergence and diversity. In this way, a good tradeoff between the convergence and diversity can be achieved by CDLS. To verify the effectiveness of CDLS, it is embedded into the PSO search process of three well-known PSOs. Furthermore, a new variant of PSO combining with the CDLS strategy, namely PSO/CDLS, is also presented. The experimental results validate the superiority of our proposed CDLS strategy and the effectiveness of PSO/CDLS, when solving numerous MaOPs with regular and irregular Pareto fronts (PFs)

Factors of having influence on the rheological properties of Ti6A14V slurry

A highly porous Ti6Al4V could be produced with a porous polymeric sponge and Ti6Al4V slurry. However, the rheological properties of Ti6Al4V slurry appeared to be the key issue in the preparation of porous Ti6Al4V. In this study, factors having influence on the rheological properties of Ti6Al4V slurry were addressed in detail. Ti6Al4V powders, organic thickening agents (binders), dispersants, concentration of powder and pH values were optimised with regard to the rheological properties of Ti6Al4V slurry. The results show that Ti6Al4V powder with a mean diameter of 45 μm and spherical shape is beneficial for the preparation of Ti6Al4V slurry. Meanwhile binders with two ingredients, which decompose at different temperatures, have the advantage to keep the shape after debinding. The optimised procedure, based on the findings, made it possible to produce highly porous Ti6Al4V with reticulate porous structure. Porous Ti6Al4V produced by this way is expected to be a promising biomaterial for tissue engineering scaffolds and orthopaedic implant applications

The transition of Chinese S&T institutes since 1980s: policy, performance and implication

In 1985 China began its reform on the Science & Technology (S&T) sector which was inherited from a planned economy. The reform over the past 20 years is deemed to be a decisive factor in China’s science and technology progress. The paper first argues that two fundamental tasks of China’s S&T sector reform are to enhance scientific productivity and strengthen the industry-academic relationships. Subsequently, the reform policies are outlined within three categories: 1) reforming the funding system, 2) improving R&D management 3) strengthening industry-academic relationships. The evolution of S&T institutes such as the Chinese Academy of Science is examined to provide micro-level evidence of policy impacts. The scientific output of China’s S&T sector did achieve the remarkable improvement in the reform period, but we also observe the rapidly growing investment from the governments flew into the sector. The evaluation of the performance of the reform needs to examine the scientific productivity of the sector. Therefore, we proceed to measure the scientific productivity of China’s S&T institutes based on the R&D input and output data in the aggregate and provincial level. The Polynomial Distributed Lag model is utilized to uncover the structure of the lag between R&D input and output. The findings based on the aggregate data and provincial data confirm that the scientific productivity of China’s S&T institutes has been decreasing since 1990s. These results call for the future actions that can contribute to enhancing the scientific productivity of China’s S&T institutes

Potential energy landscape-based extended van der Waals equation

The inherent structures ({\it IS}) are the local minima of the potential energy surface or landscape, $U({\bf r})$, of an {\it N} atom system. Stillinger has given an exact {\it IS} formulation of thermodynamics. Here the implications for the equation of state are investigated. It is shown that the van der Waals ({\it vdW}) equation, with density-dependent $a$ and $b$ coefficients, holds on the high-temperature plateau of the averaged {\it IS} energy. However, an additional ``landscape'' contribution to the pressure is found at lower $T$. The resulting extended {\it vdW} equation, unlike the original, is capable of yielding a water-like density anomaly, flat isotherms in the coexistence region {\it vs} {\it vdW} loops, and several other desirable features. The plateau energy, the width of the distribution of {\it IS}, and the ``top of the landscape'' temperature are simulated over a broad reduced density range, $2.0 \ge \rho \ge 0.20$, in the Lennard-Jones fluid. Fits to the data yield an explicit equation of state, which is argued to be useful at high density; it nevertheless reproduces the known values of $a$ and $b$ at the critical point

A self-organizing weighted optimization based framework for large-scale multi-objective optimization

The solving of large-scale multi-objective optimization problem (LSMOP) has become a hot research topic in evolutionary computation. To better solve this problem, this paper proposes a self-organizing weighted optimization based framework, denoted S-WOF, for addressing LSMOPs. Compared to the original framework, there are two main improvements in our work. Firstly, S-WOF simplifies the evolutionary stage into one stage, in which the evaluating numbers of weighted based optimization and normal optimization approaches are adaptively adjusted based on the current evolutionary state. Specifically, regarding the evaluating number for weighted based optimization (i.e., t1), it is larger when the population is in the exploitation state, which aims to accelerate the convergence speed, while t1 is diminishing when the population is switching to the exploration state, in which more attentions are put on the diversity maintenance. On the other hand, regarding the evaluating number for original optimization (i.e., t2), which shows an opposite trend to t1, it is small during the exploitation stage but gradually increases later. In this way, a dynamic trade-off between convergence and diversity is achieved in S-WOF. Secondly, to further improve the search ability in the large-scale decision space, an efficient competitive swarm optimizer (CSO) is implemented in S-WOF, which shows efficiency for solving LSMOPs. Finally, the experimental results have validated the superiority of S-WOF over several state-of-the-art large-scale evolutionary algorithms