Sexual Propagation of Pteris Vittata L. Influenced by pH, Calcium, and Temperature

National High-tech Program (863 Program) of China 2007AA061001;Foundation of the Ministry of Agricultural Key Laboratory of Plant Nutrition and Nutrient CyclingWe aimed to optimize germination and growth conditions of the arsenic hyperaccumulating fern, Pteris vittata L. Pot experiments were carried out to investigate the effects of soil pH, soil calcium (Ca) concentration, and temperature on the sexual propagation of P. vittata. At 25 degrees C, germination was both accelerated and increased by high soil pH and Ca concentration. Spores of P. vittata did not germinate on medium with a pH of 4.6. Amending strongly acid soils with 27.5 or 40 mol/g Ca(OH)2 significantly improved the growth rate during both the germination phase and the gametophyte phase. Amending strongly acid soils with NaOH (55 mol/g) promoted germination, but did not affect subsequent growth. Among the different temperature, germination and growth rates were higher at 25 degrees C than at 20 degrees C or 30 degrees C. The distribution of P. vittata in China might be influenced by its requirement for high pH and high Ca concentration in the soil, and appropriate growth temperature to complete sexual propagation. These results provided important information for improving breeding conditions of P. vitatta and will be helpful for extending the range of areas in which P. vittata can be used for phytoremediation

Homogeneous Cu-Fe super saturated solid solutions prepared by severe plastic deformation

A Cu-Fe nanocomposite containing 50 nm thick iron filaments dispersed in a copper matrix was processed by torsion under high pressure at various strain rates and temperatures. The resulting nanostructures were characterized by transmission electron microscopy, atom probe tomography and M\"ossbauer spectrometry. It is shown that alpha-Fe filaments are dissolved during severe plastic deformation leading to the formation of a homogeneous supersaturated solid solution of about 12 at.% Fe in fcc Cu. The dissolution rate is proportional to the total plastic strain but is not very sensitive to the strain rate. Similar results were found for samples processed at liquid nitrogen temperature. APT data revealed asymmetric composition gradients resulting from the deformation induced intermixing. On the basis of these experimental data, the formation of the supersaturated solid solutions is discusse

Ultrasensitive force and displacement detection using trapped ions

The ability to detect extremely small forces is vital for a variety of disciplines including precision spin-resonance imaging, microscopy, and tests of fundamental physical phenomena. Current force-detection sensitivity limits have surpassed 1 $aN/\sqrt{Hz}$ (atto $=10^{-18}$) through coupling of micro or nanofabricated mechanical resonators to a variety of physical systems including single-electron transistors, superconducting microwave cavities, and individual spins. These experiments have allowed for probing studies of a variety of phenomena, but sensitivity requirements are ever-increasing as new regimes of physical interactions are considered. Here we show that trapped atomic ions are exquisitely sensitive force detectors, with a measured sensitivity more than three orders of magnitude better than existing reports. We demonstrate detection of forces as small as 174 $yN$ (yocto $=10^{-24}$), with a sensitivity 390$\pm150$ $yN/\sqrt{Hz}$ using crystals of $n=60$ $^{9}$Be$^{+}$ ions in a Penning trap. Our technique is based on the excitation of normal motional modes in an ion trap by externally applied electric fields, detection via and phase-coherent Doppler velocimetry, which allows for the discrimination of ion motion with amplitudes on the scale of nanometers. These experimental results and extracted force-detection sensitivities in the single-ion limit validate proposals suggesting that trapped atomic ions are capable of detecting of forces with sensitivity approaching 1 $yN/\sqrt{Hz}$. We anticipate that this demonstration will be strongly motivational for the development of a new class of deployable trapped-ion-based sensors, and will permit scientists to access new regimes in materials science.Comment: Expanded introduction and analysis. Methods section added. Subject to press embarg

Robustness Verification of Support Vector Machines

We study the problem of formally verifying the robustness to adversarial examples of support vector machines (SVMs), a major machine learning model for classification and regression tasks. Following a recent stream of works on formal robustness verification of (deep) neural networks, our approach relies on a sound abstract version of a given SVM classifier to be used for checking its robustness. This methodology is parametric on a given numerical abstraction of real values and, analogously to the case of neural networks, needs neither abstract least upper bounds nor widening operators on this abstraction. The standard interval domain provides a simple instantiation of our abstraction technique, which is enhanced with the domain of reduced affine forms, which is an efficient abstraction of the zonotope abstract domain. This robustness verification technique has been fully implemented and experimentally evaluated on SVMs based on linear and nonlinear (polynomial and radial basis function) kernels, which have been trained on the popular MNIST dataset of images and on the recent and more challenging Fashion-MNIST dataset. The experimental results of our prototype SVM robustness verifier appear to be encouraging: this automated verification is fast, scalable and shows significantly high percentages of provable robustness on the test set of MNIST, in particular compared to the analogous provable robustness of neural networks

On Multi-objective Policy Optimization as a Tool for Reinforcement Learning

Many advances that have improved the robustness and efficiency of deep reinforcement learning (RL) algorithms can, in one way or another, be understood as introducing additional objectives, or constraints, in the policy optimization step. This includes ideas as far ranging as exploration bonuses, entropy regularization, and regularization toward teachers or data priors when learning from experts or in offline RL. Often, task reward and auxiliary objectives are in conflict with each other and it is therefore natural to treat these examples as instances of multi-objective (MO) optimization problems. We study the principles underlying MORL and introduce a new algorithm, Distillation of a Mixture of Experts (DiME), that is intuitive and scale-invariant under some conditions. We highlight its strengths on standard MO benchmark problems and consider case studies in which we recast offline RL and learning from experts as MO problems. This leads to a natural algorithmic formulation that sheds light on the connection between existing approaches. For offline RL, we use the MO perspective to derive a simple algorithm, that optimizes for the standard RL objective plus a behavioral cloning term. This outperforms state-of-the-art on two established offline RL benchmarks

Investigating the impact of poverty on colonization and infection with drug-resistant organisms in humans: a systematic review

Background Poverty increases the risk of contracting infectious diseases and therefore exposure to antibiotics. Yet there is lacking evidence on the relationship between income and non-income dimensions of poverty and antimicrobial resistance. Investigating such relationship would strengthen antimicrobial stewardship interventions. Methods A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, Ovid, MEDLINE, EMBASE, Scopus, CINAHL, PsychINFO, EBSCO, HMIC, and Web of Science databases were searched in October 2016. Prospective and retrospective studies reporting on income or non-income dimensions of poverty and their influence on colonisation or infection with antimicrobial-resistant organisms were retrieved. Study quality was assessed with the Integrated quality criteria for review of multiple study designs (ICROMS) tool. Results Nineteen articles were reviewed. Crowding and homelessness were associated with antimicrobial resistance in community and hospital patients. In high-income countries, low income was associated with Streptococcus pneumoniae and Acinetobacter baumannii resistance and a seven-fold higher infection rate. In low-income countries the findings on this relation were contradictory. Lack of education was linked to resistant S. pneumoniae and Escherichia coli. Two papers explored the relation between water and sanitation and antimicrobial resistance in low-income settings. Conclusions Despite methodological limitations, the results suggest that addressing social determinants of poverty worldwide remains a crucial yet neglected step towards preventing antimicrobial resistance

Engineering of a wheat germ expression system to provide compatibility with a high throughput pET-based cloning platform

Wheat germ cell-free methods provide an important approach for the production of eukaryotic proteins. We have developed a protein expression vector for the TNT® SP6 High-Yield Wheat Germ Cell-Free (TNT WGCF) expression system (Promega) that is also compatible with our T7-based Escherichia coli intracellular expression vector pET15_NESG. This allows cloning of the same PCR product into either one of several pET_NESG vectors and this modified WGCF vector (pWGHisAmp) by In-Fusion LIC cloning (Zhu et al. in Biotechniques 43:354–359, 2007). Integration of these two vector systems allowed us to explore the efficacy of the TNT WGCF system by comparing the expression and solubility characteristics of 59 human protein constructs in both WGCF and pET15_NESG E. coli intracellular expression. While only 30% of these human proteins could be produced in soluble form using the pET15_NESG based system, some 70% could be produced in soluble form using the TNT WGCF system. This high success rate underscores the importance of eukaryotic expression host systems like the TNT WGCF system for eukaryotic protein production in a structural genomics sample production pipeline. To further demonstrate the value of this WGCF system in producing protein suitable for structural studies, we scaled up, purified, and analyzed by 2D NMR two 15N-, 13C-enriched human proteins. The results of this study indicate that the TNT WGCF system is a successful salvage pathway for producing samples of difficult-to-express small human proteins for NMR studies, providing an important complementary pathway for eukaryotic sample production in the NESG NMR structure production pipeline

Phenotypic covariance of longevity, immunity and stress resistance in the Caenorhabditis nematodes

Background \ud Ageing, immunity and stresstolerance are inherent characteristics of all organisms. In animals, these traits are regulated, at least in part, by forkhead transcription factors in response to upstream signals from the Insulin/Insulin– like growth factor signalling (IIS) pathway. In the nematode Caenorhabditis elegans, these phenotypes are molecularly linked such that activation of the forkhead transcription factor DAF-16 both extends lifespan and simultaneously increases immunity and stress resistance. It is known that lifespan varies significantly among the Caenorhabditis species but, although DAF-16 signalling is highly conserved, it is unclear whether this phenotypic linkage occurs in other species. Here we investigate this phenotypic covariance by comparing longevity, stress resistance and immunity in four \ud Caenorhabditis species. \ud \ud Methodology/Principal Findings \ud We show using phenotypic analysis of DAF-16 influenced phenotypes that among four closely related Caenorhabditis nematodes, the gonochoristic species (Caenorhabditis remanei and Caenorhabditis brenneri) have diverged \ud significantly with a longer lifespan, improved stress resistance and higher immunity than the hermaphroditic species (C. elegans and Caenorhabditis briggsae). Interestingly, we also observe significant differences in expression levels between the daf-16 homologues in these species using Real-Time PCR, which positively correlate with the observed phenotypes. Finally, we provide additional evidence in support of a role for DAF-16 in regulating phenotypic coupling by using a combination of wildtype isolates, constitutively active daf-16 mutants and bioinformatic analysis. \ud \ud Conclusions \ud The gonochoristic species display a significantly longer lifespan (p < 0.0001)and more robust immune and stress response (p<0.0001, thermal stress; p<0.01, heavy metal stress; p<0.0001, pathogenic stress) than the hermaphroditic species. Our data suggests that divergence in DAF-16 mediated phenotypes may underlie many of the differences observed between these four species of Caenorhabditis nematodes. These findings are further supported by the correlative higher daf-16 expression levels among the gonochoristic species and significantly higher lifespan, immunity and stress tolerance in the constitutively active daf-16 hermaphroditic mutants

Phenotypic covariance of Longevity, Immunity and Stress Resistance in the Caenorhabditis Nematodes

Background: Ageing, immunity and stresstolerance are inherent characteristics of all organisms. In animals, these traits are regulated, at least in part, by forkhead transcription factors in response to upstream signals from the Insulin/Insulin–like growth factor signalling (IIS) pathway. In the nematode Caenorhabditis elegans, these phenotypes are molecularly linked such that activation of the forkhead transcription factor DAF-16 both extends lifespan and simultaneously increases immunity and stress resistance. It is known that lifespan varies significantly among the Caenorhabditis species but, although DAF-16 signalling is highly conserved, it is unclear whether this phenotypic linkage occurs in other species. Here we investigate this phenotypic covariance by comparing longevity, stress resistance and immunity in four Caenorhabditis species. \ud \ud Methodology/Principal Findings: We show using phenotypic analysis of DAF-16 influenced phenotypes that among four closely related Caenorhabditis nematodes, the gonochoristic species (Caenorhabditis remanei and Caenorhabditis brenneri) have diverged significantly with a longer lifespan, improved stress resistance and higher immunity than the hermaphroditic species (C. elegans and Caenorhabditis briggsae). Interestingly, we also observe significant differences in expression levels between the daf-16 homologues in these species using Real-Time PCR, which positively correlate with the observed phenotypes. Finally, we provide additional evidence in support of a role for DAF-16 in regulating phenotypic coupling by using a combination of wildtype isolates, constitutively active daf-16 mutants and bioinformatic analysis. \ud \ud Conclusions: The gonochoristic species display a significantly longer lifespan (p<0.0001) and more robust immune and stress response (p<0.0001, thermal stress; p<0.01, heavy metal stress; p<0.0001, pathogenic stress) than the hermaphroditic species. Our data suggests that divergence in DAF-16 mediated phenotypes may underlie many of the differences observed between these four species of Caenorhabditis nematodes. These findings are further supported by the correlative higher daf-16 expression levels among the gonochoristic species and significantly higher lifespan, immunity and stress tolerance in the constitutively active daf-16 hermaphroditic mutants