Spin and the honeycomb lattice: lessons from graphene

A model of electrons hopping from atom to atom in graphene's honeycomb lattice gives low-energy electronic excitations that obey a relation formally identical to a 2+1 dimensional Dirac equation. Graphene's spin equivalent, "pseudospin," arises from the degeneracy introduced by the honeycomb lattice's two inequivalent atomic sites per unit cell. Previously it has been thought that the usual electron spin and the pseudospin indexing the graphene sublattice state are merely analogues. Here we show that the pseudospin is also a real angular momentum. This identification explains the suppression of electron backscattering in carbon nanotubes and the angular dependence of light absorption by graphene. Furthermore, it demonstrates that half-integer spin like that carried by the quarks and leptons can derive from hidden substructure, not of the particles themselves, but rather of the space in which these particles live.     

Recommendations for oversight of nanobiotechnology: dynamic oversight for complex and convergent technology

Federal oversight of nanobiotechnology in the U.S. has been fragmented and incremental. The prevailing approach has been to use existing laws and other administrative mechanisms for oversight. However, this “stay-the-course” approach will be inadequate for such a complex and convergent technology and may indeed undermine its promise. The technology demands a new, more dynamic approach to oversight. The authors are proposing a new oversight framework with three essential features: (a) the oversight trajectory needs to be able to move dynamically between “soft” and “hard” approaches as information and nano-products evolve; (b) it needs to integrate inputs from all stakeholders, with strong public engagement in decision-making to assure adequate analysis and transparency; and (c) it should include an overarching coordinating entity to assure strong inter-agency coordination and communication that can meet the challenge posed by the convergent nature of nanobiotechnology. The proposed framework arises from a detailed case analysis of several key oversight regimes relevant to nanobiotechnology and is informed by inputs from experts in academia, industry, NGOs, and government.     

Learning lessons from five electrostatic incidents

It is well known that electrostatic discharges can ignite mixtures of flammable gases with air and suspensions of combustible dust in air. For this reason, the prevention of electrostatic discharges is an essential part of measures to prevent explosions and fires. Incendive electrostatic discharges occurred in five cases in various chemical plants.The incidents involved were:

• 1.Spark type electrostatic discharges from a leaking steam pipe.
• 2.Spark type electrostatic discharges inside a charging chute for a solid.
• 3.A spark type electrostatic discharge whilst transferring a solid powder from a bin, which led to ignition of the powder.
• 4.A propagating brush discharge during pneumatic transfer of solid, which caused a severe electric shock to a process operator.
• 5.A brush discharge inside an electrostatic precipitator which caused ignition of an aerosol of hydrocarbon.

To avoid explosions and fires it is important to prevent incendive electrostatic discharges from occurring in industrial facilities. To help managers of chemical plants to do this, the incidents above are presented in the form of learning lessons including:

• •the mechanism of the generation and separation of electrical charges,
• •the mechanism of the electrostatic discharge,
• •the root causes of the incident,
• •the safety measures which are necessary to avoid a repetition.

     

Invariant length scale in relativistic kinematics: lessons from Dirichlet branes

Dirac–Born–Infeld theory is shown to possess a hidden invariance associated with its maximal electric field strength. The local Lorentz symmetry O(1,n) on a Dirichlet-n-brane is thereby enhanced to an O(1,n)×O(1,n) gauge group, encoding both an invariant velocity and acceleration (or length) scale. The presence of this enlarged gauge group predicts consequences for the kinematics of observers on Dirichlet branes, with admissible accelerations being bounded from above. An important lesson is that the introduction of a fundamental length scale into relativistic kinematics does not enforce a deformation of Lorentz boosts, as one might assume naively. The exhibited structures further show that Moffat's non-symmetric gravitational theory qualifies as a candidate for a consistent Born–Infeld type gravity with regulated solutions.     

How can nanobiotechnology oversight advance science and industry: examples from environmental,health, and safety studies of nanoparticles (nano-EHS)

Nanotechnology has great potential to transform science and industry in the fields of energy, material, environment, and medicine. At the same time, more concerns are being raised about the occupational health and safety of nanomaterials in the workplace and the implications of nanotechnology on the environment and living systems. Studies on environmental, health, and safety (EHS) issues of nanomaterials have a strong influence on public acceptance of nanotechnology and, eventually, affect its sustainability. Oversight and regulation by government agencies and non-governmental organizations (NGOs) play significant roles in ensuring responsible and environmentally friendly development of nanotechnology. The EHS studies of nanomaterials can provide data and information to help the development of regulations and guidelines. We present research results on three aspects of EHS studies: physico-chemical characterization and measurement of nanomaterials; emission, exposure, and toxicity of nanomaterials; and control and abatement of nanomaterial releases using filtration technology. Measurement of nanoparticle agglomerates using a newly developed instrument, the Universal NanoParticle Analyzer (UNPA), is discussed. Exposure measurement results for silicon nanoparticles in a pilot scale production plant are presented, as well as exposure measurement and toxicity study of carbon nanotubes (CNTs). Filtration studies of nanoparticle agglomerates are also presented as an example of emission control methods.     

On the information expressed in enzyme primary structure: lessons from Ribonuclease A

The information expressed in an enzyme’s primary structure is investigated. Brownian computations are directed at Ribonuclease A (RNase A) so as to quantify the information at the atom/covalent bond level. The information content and distribution are crucial because the primary structure underpins the molecule’s chemical functions. Brownian computation data are illustrated for the native protein, mutants, and sequence isomers. The results identify signature features of the active protein on new information grounds. The same tools offer rapid screening of proteins and polypeptides whereby several examples are illustrated.     

On the information expressed in enzyme structure: more lessons from ribonuclease A

Brownian computations were directed at Ribonuclease A (RNase A) and variants in folded states so as to quantify information of the statistical type at the atom/covalent bond level. This advanced the research reported in this journal last year on the information properties of enzyme primary structure. Brownian computation data are illustrated for a sixteen-member library. The results identify signature traits that distinguish the folded wild type (WT) molecule from variants. The distinctions are explainable in terms of correlated information and dispersion energy. The Brownian tools used for this study can be directed at other protein families (e.g., kinases, isomerases, etc.) in rapid screening, QSAR, and design applications.     

Application of ultrasound to biotechnology: an overview.

Application of ultrasound to biotechnology is relatively new, but several processes that take place in the presence of cells or enzymes are activated by ultrasonic waves. High intensity ultrasonic waves break the cells and denaturize the enzymes. Low intensity ultrasonic waves can modify cellular metabolism or improve the mass transfer of reagents and products through the boundary layer or through the cellular wall and membrane. In the case of enzymes, the increase in the mass transfer rate of the reagents to the active site seems to be the most important factor. Immobilized enzymes are more resistant to thermal deactivation produced by ultrasound than native enzymes. Reverse micelles can be used to carry out synthesis using enzymes. Several applications of ultrasound to the biotechnology are discussed.     

Acoustic detection and classification of Microchiroptera using machine learning: lessons learned from automatic speech recognition

Current automatic acoustic detection and classification of microchiroptera utilize global features of individual calls (i.e., duration, bandwidth, frequency extrema), an approach that stems from expert knowledge of call sonograms. This approach parallels the acoustic phonetic paradigm of human automatic speech recognition (ASR), which relied on expert knowledge to account for variations in canonical linguistic units. ASR research eventually shifted from acoustic phonetics to machine learning, primarily because of the superior ability of machine learning to account for signal variation. To compare machine learning with conventional methods of detection and classification, nearly 3000 search-phase calls were hand labeled from recordings of five species: Pipistrellus bodenheimeri, Molossus molossus, Lasiurus borealis, L. cinereus semotus, and Tadarida brasiliensis. The hand labels were used to train two machine learning models: a Gaussian mixture model (GMM) for detection and classification and a hidden Markov model (HMM) for classification. The GMM detector produced 4% error compared to 32% error for a baseline broadband energy detector, while the GMM and HMM classifiers produced errors of 0.6 +/- 0.2% compared to 16.9 +/- 1.1% error for a baseline discriminant function analysis classifier. The experiments showed that machine learning algorithms produced errors an order of magnitude smaller than those for conventional methods.     

Addressing conflicts of interest in nanotechnology oversight: lessons learned from drug and pesticide safety testing

Financial conflicts of interest raise significant challenges for those working to develop an effective, transparent, and trustworthy oversight system for assessing and managing the potential human health and ecological hazards of nanotechnology. A recent paper in this journal by Ramachandran et al., J Nanopart Res, 13:1345–1371 (2011) proposed a two-pronged approach for addressing conflicts of interest: (1) developing standardized protocols and procedures to guide safety testing; and (2) vetting safety data under a coordinating agency. Based on past experiences with standardized test guidelines developed by the international Organization for Economic Cooperation and Development (OECD) and implemented by national regulatory agencies such as the U.S. Environmental Protection Agency (EPA) and Food and Drug Administration (FDA), we argue that this approach still runs the risk of allowing conflicts of interest to influence toxicity tests, and it has the potential to commit regulatory agencies to outdated procedures. We suggest an alternative approach that further distances the design and interpretation of safety studies from those funding the research. In case the two-pronged approach is regarded as a more politically feasible solution, we also suggest three lessons for implementing this strategy in a more dynamic and effective manner.     

从J.H. Schön的科学不端行为探讨防范对策

20世纪末和21世纪初世界科学行为的上空出现了三朵乌云,第一朵是科学前沿的原创活动中出现了实验数据的作假和虚构现象,严格地说出现了行为严重的科学不端事件;第二朵是一般科技研究人员中产生了为数不算少的范围不同的抄袭甚至剽窃的严重问题;第三朵是在研究生的习作和学位论文中出现了将互联网上的信息、资料和国内外披露或发表的论文片断予以摘引、拼凑或连接而构成"论文"的屡见不鲜的情况.这些利用信息技术和设施发展不平衡的背景,以授其奸的科学不端行为,严重违犯了国际科学界长期形成的周知科学准则和科学精神,引起了舆论的普遍贬斥和指责.文章仅就普世关注的、关系到近年来世界科学发展和影响最大的事件--舍恩(J. Hendrick Schn)博士的不端科学行为,作为一个案例予以分析."麻雀虽小,五脏俱全",通过这个分析可以从中得出一些对科学不端行为的防范和决策等有益的启示.     

Oscillations in the dark energy equation of state: New MCMC lessons

We study the possibility of detecting oscillating patterns in the equation of state (EoS) of the dark energy using different cosmological datasets. We follow a phenomenological approach and study three different oscillating models for the EoS, one of them periodic and the other two damped (proposed here for the first time). All the models are characterized by the amplitude, the center and the frequency of oscillations. In contrast to previous works in the literature, we do not fix the frequency to a fiducial value related to the time extension of chosen datasets, but consider a discrete set of values, so to avoid arbitrariness and try to detect any possible time period in the EoS. We test the models using a recent collection of SNeIa, direct Hubble data and Gamma Ray Bursts data. Main results are: I. even if constraints on the amplitude are not too strong, we detect a trend of it versus the frequency, i.e. decreasing (and even negatives) amplitudes for higher frequencies; II. the center of oscillation (which corresponds to the present value of the EoS parameter) is very well constrained, and phantom behavior seems statistically disfavored; III. the frequency is hard to constrain, showing similar statistical validity for all the values of the discrete set chosen, but the best fit of all the considered scenarios is associated with a period which is in the redshift range depicted by our cosmological data. The “best” oscillating models are compared with ΛCDM using different dimensionally consistent and Bayesian-based information criteria; the conclusion is reached that at present, data cannot discriminate between a cosmological constant and oscillating equation of state.     

Validity range of centrifuges for the regulation of nanomaterials: from classification to as-tested coronas

Granulometry is the regulatory category where the differences between traditional materials and nanomaterials culminate. Reported herein is a careful validation of methods for the quantification of dispersability and size distribution in relevant media, and for the classification according to the EC nanodefinition recommendation. Suspension-based techniques can assess the nanodefinition only if the material in question is reasonably well dispersed. Using dispersed material of several chemical compositions (organic, metal, metal-oxide) as test cases we benchmark analytical ultracentrifugation (AUC), dynamic light scattering (DLS), hydrodynamic chromatography, nanoparticle tracking analysis (NTA) against the known content of bimodal suspensions in the commercially relevant range between 20?nm and a few microns. The results validate fractionating techniques, especially AUC, which successfully identifies any dispersed nanoparticle content from 14 to 99.9?nb% with less than 5?nb% deviation. In contrast, our screening casts severe doubt over the reliability of ensemble (scattering) techniques and highlights the potential of NTA to develop into a counting upgrade of DLS. The unique asset of centrifuges with interference, X-ray or absorption detectors??to quantify the dispersed solid content for each size interval from proteins over individualized nanoparticles up to agglomerates, while accounting for their loose packing??addresses also the adsorption/depletion of proteins and (de-)agglomeration of nanomaterials under cell culture conditions as tested for toxicological endpoints.     

Nonlinear bivariate dependency of price-volume relationships in agricultural commodity futures markets: A perspective from Multifractal Detrended Cross-Correlation Analysis

Nonlinear dependency between characteristic financial and commodity market quantities (variables) is crucially important, especially between trading volume and market price. Studies on nonlinear dependency between price and volume can provide practical insights into market trading characteristics, as well as the theoretical understanding of market dynamics. Actually, nonlinear dependency and its underlying dynamical mechanisms between price and volume can help researchers and technical analysts in understanding the market dynamics by integrating the market variables, instead of investigating them in the current literature. Therefore, for investigating nonlinear dependency of price-volume relationships in agricultural commodity futures markets in China and the US, we perform a new statistical test to detect cross-correlations and apply a new methodology called Multifractal Detrended Cross-Correlation Analysis (MF-DCCA), which is an efficient algorithm to analyze two spatially or temporally correlated time series. We discuss theoretically the relationship between the bivariate cross-correlation exponent and the generalized Hurst exponents for time series of respective variables. We also perform an empirical study and find that there exists a power-law cross-correlation between them, and that multifractal features are significant in all the analyzed agricultural commodity futures markets.     

On interfacial free energy versus interfacial stress of fluids adsorbed on chemically patterned surfaces: lessons from the special case of striped substrates

The statistical mechanics of fluids adsorbed on chemically patterned surfaces is far from straightforward when attempting to develop virial theorems for the interfacial free energy. This is because in general one would have to devise new procedures to distinguish surface tension from surface stress, even for wall-fluid models where the substrate atoms are replaced by an effective external field. However, the distinction may be made explicit for the special case of striped walls. This paper makes use of striped wall-fluid models to discuss the significance of fluid interfacial stress to patterned inhomogeneous fluids. In particular, it considers the adsorption of hemicylindrical drops on an array of high energy stripes. For the planar stripe geometry it is also possible to make effective use of the pressure tensor formalism. Beyond the special case of striped patterns it is not possible to use standard procedures based on virial theorems to directly evaluate interfacial free energy. The lessons learnt from these exercises apply especially to computer simulation studies of patterned inhomogeneous fluids.     

Size controlled gold nanoparticle formation by <Emphasis Type="Italic">Avena sativa</Emphasis> biomass: use of plants in nanobiotechnology

Oat (Avena sativa) biomass was studied as an alternative to recover Au(III) ions from aqueous solutions and for its capacity to reduce Au(III) to Au(0) forming Au nanoparticles. To study the binding trend of Au(III) to oat and the possible formation of Au nanoparticles, the biomass and a solution of Au(III) were reacted for a period of 1 h at pH values ranging from 2 to 6. The results demonstrated that Au(III) ions were bound to oat biomass in a pH-dependent manner, with the highest adsorption (about 80%) at pH 3. HRTEM studies showed that oat biomass reacted with Au(III) ions formed Au nanoparticles of fcc tetrahedral, decahedral, hexagonal, icosahedral multitwinned, irregular, and rod shape. To our knowledge, this is the second report about the production of nanorods as a product of the reaction of a Au(III) solution with a biological material. These studies also showed that the pH of the reaction influenced the nanoparticle size. The smaller nanoparticles and the higher occurrence of these were observed at pH values of 3 and 4, whereas the larger nanoparticles were observed at pH 2.     

从J.H.Schn的科学不端行为探讨防范对策

20世纪末和21世纪初世界科学行为的上空出现了三朵乌云,第一朵是科学前沿的原创活动中出现了实验数据的作假和虚构现象,严格地说出现了行为严重的科学不端事件;第二朵是一般科技研究人员中产生了为数不算少的范围不同的抄袭甚至剽窃的严重问题;第三朵是在研究生的习作和学位论文中出现了将互联网上的信息、资料和国内外披露或发表的论文片断予以摘引、拼凑或连接而构成"论文"的屡见不鲜的情况.这些利用信息技术和设施发展不平衡的背景,以授其奸的科学不端行为,严重违犯了国际科学界长期形成的周知科学准则和科学精神,引起了舆论的普遍贬斥和指责.文章仅就普世关注的、关系到近年来世界科学发展和影响最大的事件--舍恩(J. Hendrick Schn)博士的不端科学行为,作为一个案例予以分析."麻雀虽小,五脏俱全",通过这个分析可以从中得出一些对科学不端行为的防范和决策等有益的启示.