Scanning tunneling microscopy simulations of poly(3-dodecylthiophene) chains adsorbed on highly oriented pyrolytic graphite

We report on a novel scheme to perform efficient simulations of Scanning Tunneling Microscopy (STM) of molecules weakly bonded to surfaces. Calculations are based on a tight binding (TB) technique including self-consistency for the molecule to predict STM imaging and spectroscopy. To palliate the lack of self-consistency in the tunneling current calculation, we performed first principles density-functional calculations to extract the geometrical and electronic properties of the system. In this way, we can include, in the TB scheme, the effects of structural relaxation upon adsorption on the electronic structure of the molecule. This approach is applied to the study of regioregular poly(3-dodecylthiophene) (P3DDT) polymer chains adsorbed on highly oriented pyrolytic graphite (HOPG). Results of spectroscopic calculations are discussed and compared with recently obtained experimental datComment: 15 pages plus 5 figures in a tar fil

Frontiers of beam diagnostics in plasma accelerators: measuring the ultra-fast and ultra-cold

Advanced diagnostics are essential tools in the development of plasma-based accelerators. The accurate measurement of the quality of beams at the exit of the plasma channel is crucial to optimize the parameters of the plasma accelerator. 6D electron beam diagnostics will be reviewed with emphasis on emittance measurement, which is particularly complex due to large energy spread and divergence of the emerging beams, and on femtosecond bunch length measurements

Neurite Orientation Dispersion and Density Imaging Color Maps to Characterize Brain Diffusion in Neurologic Disorders

Purpose: Neurite orientation dispersion and density imaging (NODDI) has recently been developed to overcome diffusion technique limitations in modeling biological systems. This manuscript reports a preliminary investigation into the use of a single color-coded map to represent NODDI-derived information. Materials and methods: An optimized diffusion-weighted imaging protocol was acquired in several clinical neurological contexts including demyelinating disease, neoplastic process, stroke, and toxic/metabolic disease. The NODDI model was fitted to the diffusion datasets. NODDI is based on a three-compartment diffusion model and provides maps that quantify the contributions to the total diffusion signal in each voxel. The NODDI compartment maps were combined into a single 4-dimensional volume visualized as RGB image (red for anisotropic Gaussian diffusion, green for non-Gaussian anisotropic diffusion, and blue for isotropic Gaussian diffusion), in which the relative contributions of the different microstructural compartments can be easily appreciated. Results: The NODDI color maps better describe the heterogeneity of neoplastic as well inflammatory lesions by identifying different tissue components within areas apparently homogeneous on conventional imaging. Moreover, NODDI color maps seem to be useful for identifying vasogenic edema differently from tumor-infiltrated edema. In multiple sclerosis, the NODDI color maps enable a visual assessment of the underlying microstructural changes, possibly highlighting an increased inflammatory component, within lesions and potentially in normal-appearing white matter. Conclusion: The NODDI color maps could make this technique valuable in a clinical setting, providing comprehensive and accessible information in normal and pathological brain tissues in different neurological pathologies

Longitudinal phase-space manipulation with beam-driven plasma wakefields

The development of compact accelerator facilities providing high-brightness beams is one of the most challenging tasks in field of next-generation compact and cost affordable particle accelerators, to be used in many fields for industrial, medical and research applications. The ability to shape the beam longitudinal phase-space, in particular, plays a key role to achieve high-peak brightness. Here we present a new approach that allows to tune the longitudinal phase-space of a high-brightness beam by means of a plasma wakefields. The electron beam passing through the plasma drives large wakefields that are used to manipulate the time-energy correlation of particles along the beam itself. We experimentally demonstrate that such solution is highly tunable by simply adjusting the density of the plasma and can be used to imprint or remove any correlation onto the beam. This is a fundamental requirement when dealing with largely time-energy correlated beams coming from future plasma accelerators

Evidence for European presence in the Americas in ad 1021

Transatlantic exploration took place centuries before the crossing of Columbus. Physical evidence for early European presence in the Americas can be found in Newfoundland, Canada(1,2). However, it has thus far not been possible to determine when this activity took place(3–5). Here we provide evidence that the Vikings were present in Newfoundland in ad 1021. We overcome the imprecision of previous age estimates by making use of the cosmic-ray-induced upsurge in atmospheric radiocarbon concentrations in ad 993 (ref. (6)). Our new date lays down a marker for European cognisance of the Americas, and represents the first known point at which humans encircled the globe. It also provides a definitive tie point for future research into the initial consequences of transatlantic activity, such as the transference of knowledge, and the potential exchange of genetic information, biota and pathologies(7,8)

Focusing of high-brightness electron beams with active-plasma lenses

Plasma-based technology promises a tremendous reduction in size of accelerators used for research, medical, and industrial applications, making it possible to develop tabletop machines accessible for a broader scientific community. By overcoming current limits of conventional accelerators and pushing particles to larger and larger energies, the availability of strong and tunable focusing optics is mandatory also because plasma-accelerated beams usually have large angular divergences. In this regard, active-plasma lenses represent a compact and affordable tool to generate radially symmetric magnetic fields several orders of magnitude larger than conventional quadrupoles and solenoids. However, it has been recently proved that the focusing can be highly nonlinear and induce a dramatic emittance growth. Here, we present experimental results showing how these nonlinearities can be minimized and lensing improved. These achievements represent a major breakthrough toward the miniaturization of next-generation focusing devices

Overview of Plasma Lens Experiments and Recent Results at SPARC_LAB

Beam injection and extraction from a plasma module is still one of the crucial aspects to solve in order to produce high quality electron beams with a plasma accelerator. Proper matching conditions require to focus the incoming high brightness beam down to few microns size and to capture a high divergent beam at the exit without loss of beam quality. Plasma-based lenses have proven to provide focusing gradients of the order of kT/m with radially symmetric focusing thus promising compact and affordable alternative to permanent magnets in the design of transport lines. In this paper an overview of recent experiments and future perspectives of plasma lenses is reported

fMRI-Targeted High-Angular Resolution Diffusion MR Tractography to Identify Functional Language Tracts in Healthy Controls and Glioma Patients

Background MR Tractography enables non-invasive preoperative depiction of language subcortical tracts, which is crucial for the presurgical work-up of brain tumors; however, it cannot evaluate the exact function of the fibers. Purpose A systematic pipeline was developed to combine tractography reconstruction of language fiber bundles, based on anatomical landmarks (Anatomical-T), with language fMRI cortical activations. A fMRI-targeted Tractography (fMRI-T) was thus obtained, depicting the subsets of the anatomical tracts whose endpoints are located inside a fMRI activation. We hypothesized that fMRI-T could provide additional functional information regarding the subcortical structures, better reflecting the eloquent white matter structures identified intraoperatively. Methods Both Anatomical-T and fMRI-T of language fiber tracts were performed on 16 controls and preoperatively on 16 patients with left-hemisphere brain tumors, using a q-ball residual bootstrap algorithm based on High Angular Resolution Diffusion Imaging (HARDI) datasets (b = 3000 s/mm(2); 60 directions); fMRI ROIs were obtained using picture naming, verbal fluency, and auditory verb generation tasks. In healthy controls, normalized MNI atlases of fMRI-T and Anatomical-T were obtained. In patients, the surgical resection of the tumor was pursued by identifying eloquent structures with intraoperative direct electrical stimulation mapping and extending surgery to the functional boundaries. Post-surgical MRI allowed to identify Anatomical-T and fMRI-T non-eloquent portions removed during the procedure. Results MNI Atlases showed that fMRI-T is a subset of Anatomical-T, and that different task-specific fMRI-T involve both shared subsets and task-specific subsets - e.g., verbal fluency fMRI-T strongly involves dorsal frontal tracts, consistently with the phonogical-articulatory features of this task. A quantitative analysis in patients revealed that Anatomical-T removed portions of AF-SLF and IFOF were significantly greater than verbal fluency fMRI-T ones, suggesting that fMRI-T is a more specific approach. In addition, qualitative analyses showed that fMRI-T AF-SLF and IFOF predict the exact functional limits of resection with increased specificity when compared to Anatomical-T counterparts, especially the superior frontal portion of IFOF, in a subcohort of patients. Conclusion These results suggest that performing fMRI-T in addition to the 'classic' Anatomical-T may be useful in a preoperative setting to identify the 'high-risk subsets' that should be spared during the surgical procedure

Modeling of Acoustic Emission Failure Mechanism Data from a Unidirectional Fiberglass/Epoxy Tensile Test Specimen

The purpose of this work was to model the acoustic emission (AE) flaw growth data that resulted from the tensile test of a unidirectional fiberglass/epoxy specimen. The data collected and stored during the test were the six standard AE quantification parameters for each event. A classification neural network was used to sort the data into five failure mechanism clusters. The resulting frequency histograms of the sorted data were then mathematically modeled herein using the three types of Johnson distributions: bounded, lognormal, and unbounded. These provided a reasonably good fit for all six AE parameter distributions for each of the five failure mechanisms