Design of a five-axis ultra-precision micro-milling machine—UltraMill. Part 2: Integrated dynamic modelling, design optimisation and analysis

Using computer models to predict the dynamic performance of ultra-precision machine tools can help manufacturers to substantially reduce the lead time and cost of developing new machines. However, the use of electronic drives on such machines is becoming widespread, the machine dynamic performance depending not only on the mechanical structure and components but also on the control system and electronic drives. Bench-top ultra-precision machine tools are highly desirable for the micro-manufacturing of high-accuracy micro-mechanical components. However, the development is still at the nascent stage and hence lacks standardised guidelines. Part 2 of this two-part paper proposes an integrated approach, which permits analysis and optimisation of the entire machine dynamic performance at the early design stage. Based on the proposed approach, the modelling and simulation process of a novel five-axis bench-top ultra-precision micro-milling machine tool—UltraMill—is presented. The modelling and simulation cover the dynamics of the machine structure, the moving components, the control system and the machining process and are used to predict the entire machine performance of two typical configurations

Dynein structure and power stroke

Dynein ATPases are microtubule motors that are critical to diverse processes such as vesicle transport and the beating of sperm tails; however, their mechanism of force generation is unknown. Each dynein comprises a head, from which a stalk and a stem emerge. Here we use electron microscopy and image processing to reveal new structural details of dynein c, an isoform from Chlamydomonas reinhardtii flagella, at the start and end of its power stroke. Both stem and stalk are flexible, and the stem connects to the head by means of a linker approximately 10 nm long that we propose lies across the head. With both ADP and vanadate bound, the stem and stalk emerge from the head 10 nm apart. However, without nucleotide they emerge much closer together owing to a change in linker orientation, and the coiled-coil stalk becomes stiffer. The net result is a shortening of the molecule coupled to an approximately 15-nm displacement of the tip of the stalk. These changes indicate a mechanism for the dynein power stroke

Exponential Random Graph Modeling for Complex Brain Networks

Exponential random graph models (ERGMs), also known as p* models, have been utilized extensively in the social science literature to study complex networks and how their global structure depends on underlying structural components. However, the literature on their use in biological networks (especially brain networks) has remained sparse. Descriptive models based on a specific feature of the graph (clustering coefficient, degree distribution, etc.) have dominated connectivity research in neuroscience. Corresponding generative models have been developed to reproduce one of these features. However, the complexity inherent in whole-brain network data necessitates the development and use of tools that allow the systematic exploration of several features simultaneously and how they interact to form the global network architecture. ERGMs provide a statistically principled approach to the assessment of how a set of interacting local brain network features gives rise to the global structure. We illustrate the utility of ERGMs for modeling, analyzing, and simulating complex whole-brain networks with network data from normal subjects. We also provide a foundation for the selection of important local features through the implementation and assessment of three selection approaches: a traditional p-value based backward selection approach, an information criterion approach (AIC), and a graphical goodness of fit (GOF) approach. The graphical GOF approach serves as the best method given the scientific interest in being able to capture and reproduce the structure of fitted brain networks

Equivalent forms of Dirac equations in curved spacetimes and generalized de Broglie relations

One may ask whether the relations between energy and frequency and between momentum and wave vector, introduced for matter waves by de Broglie, are rigorously valid in the presence of gravity. In this paper, we show this to be true for Dirac equations in a background of gravitational and electromagnetic fields. We first transform any Dirac equation into an equivalent canonical form, sometimes used in particular cases to solve Dirac equations in a curved spacetime. This canonical form is needed to apply the Whitham Lagrangian method. The latter method, unlike the WKB method, places no restriction on the magnitude of Planck's constant to obtain wave packets, and furthermore preserves the symmetries of the Dirac Lagrangian. We show using canonical Dirac fields in a curved spacetime, that the probability current has a Gordon decomposition into a convection current and a spin current, and that the spin current vanishes in the Whitham approximation, which explains the negligible effect of spin on wave packet solutions, independent of the size of Planck's constant. We further discuss the classical-quantum correspondence in a curved spacetime based on both Lagrangian and Hamiltonian formulations of the Whitham equations. We show that the generalized de Broglie relations in a curved spacetime are a direct consequence of Whitham's Lagrangian method, and not just a physical hypothesis as introduced by Einstein and de Broglie, and by many quantum mechanics textbooks.Comment: PDF, 32 pages in referee format. Added significant material on canonical forms of Dirac equations. Simplified Theorem 1 for normal Dirac equations. Added section on Gordon decomposition of the probability current. Encapsulated main results in the statement of Theorem

Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset

Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics

Distribution of Capillary Transit Times in Isolated Lungs of Oxygen-Tolerant Rats

Rats pre-exposed to 85% O2 for 5–7 days tolerate the otherwise lethal effects of 100% O2. The objective was to evaluate the effect of rat exposure to 85% O2 for 7 days on lung capillary mean transit time (t¯c) and distribution of capillary transit times (h c(t)). This information is important for subsequent evaluation of the effect of this hyperoxia model on the redox metabolic functions of the pulmonary capillary endothelium. The venous concentration vs. time outflow curves of fluorescein isothiocyanate labeled dextran (FITC-dex), an intravascular indicator, and coenzyme Q1 hydroquinone (CoQ1H2), a compound which rapidly equilibrates between blood and tissue on passage through the pulmonary circulation, were measured following their bolus injection into the pulmonary artery of isolated perfused lungs from rats exposed to room air (normoxic) or 85% O2 for 7 days (hyperoxic). The moments (mean transit time and variance) of the measured FITC-dex and CoQ1H2 outflow curves were determined for each lung, and were then used in a mathematical model [Audi et al. J. Appl. Physiol. 77: 332–351, 1994] to estimate t¯c and the relative dispersion (RDc) of h c(t). Data analysis reveals that exposure to hyperoxia decreases lung t¯c by 42% and increases RDc, a measure h c(t) heterogeneity, by 40%

Predictive significance of the six-minute walk distance for long-term survival in chronic hypercapnic respiratory failure

Background: The 6-min walk distance ( 6-MWD) is a global marker of functional capacity and prognosis in chronic obstructive pulmonary disease ( COPD), but less explored in other chronic respiratory diseases. Objective: To study the role of 6-MWD in chronic hypercapnic respiratory failure ( CHRF). Methods: In 424 stable patients with CHRF and non-invasive ventilation ( NIV) comprising COPD ( n = 197), restrictive diseases ( RD; n = 112) and obesity-hypoventilation- syndrome ( OHS; n = 115), the prognostic value of 6-MWD for long- term survival was assessed in relation to that of body mass index (BMI), lung function, respiratory muscle function and laboratory parameters. Results: 6-MWD was reduced in patients with COPD ( median 280 m; quartiles 204/350 m) and RD ( 290 m; 204/362 m) compared to OHS ( 360 m; 275/440 m; p <0.001 each). Overall mortality during 24.9 (13.1/40.5) months was 22.9%. In the 424 patients with CHRF, 6-MWD independently predicted mortality in addition to BMI, leukocytes and forced expiratory volume in 1 s ( p <0.05 each). In COPD, 6-MWD was strongly associated with mortality using the median {[} p <0.001, hazard ratio ( HR) = 3.75, 95% confidence interval (CI): 2.24-6.38] or quartiles as cutoff levels. In contrast, 6-MWD was only significantly associated with impaired survival in RD patients when it was reduced to 204 m or less (1st quartile; p = 0.003, HR = 3.31, 95% CI: 1.73-14.10), while in OHS 6-MWD had not any prognostic value. Conclusions: In patients with CHRF and NIV, 6-MWD was predictive for long- term survival particularly in COPD. In RD only severely reduced 6-MWD predicted mortality, while in OHS 6-MWD was relatively high and had no prognostic value. These results support a disease-specific use of 6-MWD in the routine assessment of patients with CHRF. Copyright (C) 2007 S. Karger AG, Basel

Is a Severe Clinical Profile an Effect Modifier in a Web-Based Depression Treatment for Adults With Type 1 or Type 2 Diabetes? Secondary Analyses From a Randomized Controlled Trial.

Background: Depression and diabetes are two highly prevalent and co-occurring health problems. Web-based, diabetes-specific cognitive behavioral therapy (CBT) depression treatment is effective in diabetes patients, and has the potential to be cost effective and to have large reach. A remaining question is whether the effectiveness differs between patients with seriously impaired mental health and patients with less severe mental health problems. Objective: To test whether the effectiveness of an eight-lesson Web-based, diabetes-specific CBT for depression, with minimal therapist support, differs in patients with or without diagnosed major depressive disorder (MDD), diagnosed anxiety disorder, or elevated diabetes-specific emotional distress (DM-distress). Methods: We used data of 255 patients with diabetes with elevated depression scores, who were recruited via an open access website for participation in a randomized controlled trial, conducted in 2008-2009, comparing a diabetes-specific, Web-based, therapist-supported CBT with a 12-week waiting-list control group. We performed secondary analyses on these data to study whether MDD or anxiety disorder (measured using a telephone-administered diagnostic interview) and elevated DM-distress (online self-reported) are effect modifiers in the treatment of depressive symptoms (online self-reported) with Web-based diabetes-specific CBT. Results: MDD, anxiety disorder, and elevated DM-distress were not significant effect modifiers in the treatment of self-assessed depressive symptoms with Web-based diabetes-specific CBT. Conclusions: This Web-based diabetes-specific CBT depression treatment is suitable for use in patients with severe mental health problems and those with a less severe clinical profile

Study of Bc+B_c^+ decays to the K+K−π+K^+K^-\pi^+ final state and evidence for the decay Bc+→χc0π+B_c^+\to\chi_{c0}\pi^+

A study of $B_c^+\to K^+K^-\pi^+$ decays is performed for the first time using data corresponding to an integrated luminosity of 3.0 $\mathrm{fb}^{-1}$ collected by the LHCb experiment in $pp$ collisions at centre-of-mass energies of $7$ and $8$ TeV. Evidence for the decay $B_c^+\to\chi_{c0}(\to K^+K^-)\pi^+$ is reported with a significance of 4.0 standard deviations, resulting in the measurement of $\frac{\sigma(B_c^+)}{\sigma(B^+)}\times\mathcal{B}(B_c^+\to\chi_{c0}\pi^+)$ to be $(9.8^{+3.4}_{-3.0}(\mathrm{stat})\pm 0.8(\mathrm{syst}))\times 10^{-6}$. Here $\mathcal{B}$ denotes a branching fraction while $\sigma(B_c^+)$ and $\sigma(B^+)$ are the production cross-sections for $B_c^+$ and $B^+$ mesons. An indication of $\bar b c$ weak annihilation is found for the region $m(K^-\pi^+)<1.834\mathrm{\,Ge\kern -0.1em V\!/}c^2$, with a significance of 2.4 standard deviations.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2016-022.html, link to supplemental material inserted in the reference