Surface Characterisation Based Tool Wear Monitoring in Peripheral milling

The progress of surface metrology in the last decade has led to improved 3D characterisation of surfaces which offers the possibility of monitoring manufacturing operations to give highly detailed information regarding the machine tool condition. This paper presents a case study where areal surface characterisation is used to monitor tool wear in peripheral milling. Due to the fact that tool wear has a direct effect on the machined workpiece surface, the machined surface topography contains much information concerning the machining conditions including the tool wear state. Through analysing the often subtle changes in the surface topography the tool wear state can be highlighted. This paper utilises areal surface characterization, areal auto-correlation function (AACF) and pattern analysis to illustrate the effect of tool wear on the workpiece surface. The result shows that: (1) tool wear, previously difficult to detect will influence almost all of the areal surface parameters; (2) the pattern features of AACF spectrum can reflect the subtle surface texture variation with increasing tool wear. The authors consider that, combined analysis of the surface roughness and its AACF spectrum are a good choice for monitoring the tool wear state especially with the latest developments in on-machine surface metrology

In situ interface engineering for probing the limit of quantum dot photovoltaic devices.

Quantum dot (QD) photovoltaic devices are attractive for their low-cost synthesis, tunable band gap and potentially high power conversion efficiency (PCE). However, the experimentally achieved efficiency to date remains far from ideal. Here, we report an in-situ fabrication and investigation of single TiO2-nanowire/CdSe-QD heterojunction solar cell (QDHSC) using a custom-designed photoelectric transmission electron microscope (TEM) holder. A mobile counter electrode is used to precisely tune the interface area for in situ photoelectrical measurements, which reveals a strong interface area dependent PCE. Theoretical simulations show that the simplified single nanowire solar cell structure can minimize the interface area and associated charge scattering to enable an efficient charge collection. Additionally, the optical antenna effect of nanowire-based QDHSCs can further enhance the absorption and boost the PCE. This study establishes a robust 'nanolab' platform in a TEM for in situ photoelectrical studies and provides valuable insight into the interfacial effects in nanoscale solar cells

Circumstellar discs: What will be next?

This prospective chapter gives our view on the evolution of the study of circumstellar discs within the next 20 years from both observational and theoretical sides. We first present the expected improvements in our knowledge of protoplanetary discs as for their masses, sizes, chemistry, the presence of planets as well as the evolutionary processes shaping these discs. We then explore the older debris disc stage and explain what will be learnt concerning their birth, the intrinsic links between these discs and planets, the hot dust and the gas detected around main sequence stars as well as discs around white dwarfs.Comment: invited review; comments welcome (32 pages

Spectral catalogue of bright gamma-ray bursts detected with the BeppoSAX/GRBM

The emission process responsible for the so-called "prompt" emission of gamma-ray bursts is still unknown. A number of empirical models fitting the typical spectrum still lack a satisfactory interpretation. A few GRB spectral catalogues derived from past and present experiments are known in the literature and allow to tackle the issue of spectral properties of gamma-ray bursts on a statistical ground. We extracted and studied the time-integrated photon spectra of the 200 brightest GRBs observed with the Gamma-Ray Burst Monitor which flew aboard the BeppoSAX mission (1996-2002) to provide an independent statistical characterisation of GRB spectra. The spectra were fit with three models: a simple power-law, a cut-off power law or a Band function. The typical photon spectrum of a bright GRB consists of a low-energy index around 1.0 and a peak energy of the nuFnu spectrum E_p~240 keV in agreement with previous results on a sample of bright CGRO/BATSE bursts. Spectra of ~35% of GRBs can be fit with a power-law with a photon index around 2, indicative of peak energies either close to or outside the GRBM energy boundaries. We confirm the correlation between E_p and fluence, with a logarithmic dispersion of 0.13 around the power-law with index 0.21+-0.06. The low-energy and peak energy distributions are not yet explained in the current literature. The capability of measuring time-resolved spectra over a broadband energy range, ensuring precise measurements of parameters such as E_p, will be crucial for future experiments (abridged).Comment: 28 pages, 20 figures, 3 tables, accepted to A&

Analytic philosophy for biomedical research: the imperative of applying yesterday's timeless messages to today's impasses

The mantra that "the best way to predict the future is to invent it" (attributed to the computer scientist Alan Kay) exemplifies some of the expectations from the technical and innovative sides of biomedical research at present. However, for technical advancements to make real impacts both on patient health and genuine scientific understanding, quite a number of lingering challenges facing the entire spectrum from protein biology all the way to randomized controlled trials should start to be overcome. The proposal in this chapter is that philosophy is essential in this process. By reviewing select examples from the history of science and philosophy, disciplines which were indistinguishable until the mid-nineteenth century, I argue that progress toward the many impasses in biomedicine can be achieved by emphasizing theoretical work (in the true sense of the word 'theory') as a vital foundation for experimental biology. Furthermore, a philosophical biology program that could provide a framework for theoretical investigations is outlined

Factors that affect proliferation of Salmonella in tomatoes post-harvest: the roles of seasonal effects, irrigation regime, crop and pathogen genotype

MAIN OBJECTIVES: Fresh fruits and vegetables become increasingly recognized as vehicles of human salmonellosis. Physiological, ecological, and environmental factors are all thought to contribute to the ability of Salmonella to colonize fruits and vegetables pre- and post-harvest. The goal of this study was to test how irrigation levels, fruit water congestion, crop and pathogen genotypes affect the ability of Salmonella to multiply in tomatoes post-harvest. EXPERIMENTAL DESIGN: Fruits from three tomato varieties, grown over three production seasons in two Florida locations, were infected with seven strains of Salmonella and their ability to multiply post-harvest in field-grown tomatoes was tested. The field experiments were set up as a two-factor factorial split plot experiment, with the whole-plot treatments arranged in a randomized complete-block design. The irrigation treatment (at three levels) was the whole-plot factor, and the split-plot factor was tomato variety, with three levels. The significance of the main, two-way, and three-way interaction effects was tested using the (type III) F-tests for fixed effects. Mean separation for each significant fixed effect in the model was performed using Tukey's multiple comparison testing procedure. MOST IMPORTANT DISCOVERIES AND SIGNIFICANCE: The irrigation regime per se did not affect susceptibility of the crop to post-harvest proliferation of Salmonella. However, Salmonella grew significantly better in water-congested tissues of green tomatoes. Tomato maturity and genotype, Salmonella genotype, and inter-seasonal differences were the strongest factors affecting proliferation. Red ripe tomatoes were significantly and consistently more conducive to proliferation of Salmonella. Tomatoes harvested in the driest, sunniest season were the most conducive to post-harvest proliferation of the pathogen. Statistically significant interactions between production conditions affected post-harvest susceptibility of the crop to the pathogen. UV irradiation of tomatoes post-harvest promoted Salmonella growth

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Study of B -> \rho \pi decays at Belle

This paper describes a study of B meson decays to the pseudoscalar-vector final state \rho\pi using 31.9\times 10^6 B\bar{B} events collected with the Belle detector at KEKB. The branching fractions B(B^+ \to \rho^0\pi^+) = (8.0^{+2.3+0.7}_{-2.0-0.7}) \times 10^{-6} and B(B^0 -> \rho^{+-} \pi^{-+}) = (20.8^{+6.0+2.8}_{-6.3-3.1}) \times 10^{-6} are obtained. In addition, a 90% confidence level upper limit of B(B^0 \to \rho^0\pi^0) < 5.3 \times 10^{-6}is reported.Comment: 14 pages, 3 figures, to be submitted to Phys. Lett.

Impact Factor: outdated artefact or stepping-stone to journal certification?

A review of Garfield's journal impact factor and its specific implementation as the Thomson Reuters Impact Factor reveals several weaknesses in this commonly-used indicator of journal standing. Key limitations include the mismatch between citing and cited documents, the deceptive display of three decimals that belies the real precision, and the absence of confidence intervals. These are minor issues that are easily amended and should be corrected, but more substantive improvements are needed. There are indications that the scientific community seeks and needs better certification of journal procedures to improve the quality of published science. Comprehensive certification of editorial and review procedures could help ensure adequate procedures to detect duplicate and fraudulent submissions.Comment: 25 pages, 12 figures, 6 table

Artificial Neural Network Inference (ANNI): A Study on Gene-Gene Interaction for Biomarkers in Childhood Sarcomas

Objective: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI). Method: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs) dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. Results: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS); FCGRT and OLFM1 in Ewing’s sarcoma (EWS)) suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. Conclusions: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas