Critical evaluation of the computational methods used in the forced polymer translocation

In forced polymer translocation, the average translocation time, $\tau$, scales with respect to pore force, $f$, and polymer length, $N$, as $\tau \sim f^{-1} N^{\beta}$. We demonstrate that an artifact in Metropolis Monte Carlo method resulting in breakage of the force scaling with large $f$ may be responsible for some of the controversies between different computationally obtained results and also between computational and experimental results. Using Langevin dynamics simulations we show that the scaling exponent $\beta \le 1 + \nu$ is not universal, but depends on $f$. Moreover, we show that forced translocation can be described by a relatively simple force balance argument and $\beta$ to arise solely from the initial polymer configuration

Business process modelling and visualisation to support e-government decision making: Business/IS alignment

© 2017 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/978-3-319-57487-5_4.Alignment between business and information systems plays a vital role in the formation of dependent relationships between different departments in a government organization and the process of alignment can be improved by developing an information system (IS) according to the stakeholders’ expectations. However, establishing strong alignment in the context of the eGovernment environment can be difficult. It is widely accepted that business processes in the government environment plays a pivotal role in capturing the details of IS requirements. This paper presents a method of business process modelling through UML which can help to visualise and capture the IS requirements for the system development. A series of UML models have been developed and discussed. A case study on patient visits to a healthcare clinic in the context of eGovernment has been used to validate the models

Dynamics of forced biopolymer translocation

We present results from our simulations of biopolymer translocation in a solvent which explain the main experimental findings. The forced translocation can be described by simple force balance arguments for the relevant range of pore potentials in experiments and biological systems. Scaling of translocation time with polymer length varies with pore force and friction. Hydrodynamics affects this scaling and significantly reduces translocation times.Comment: Published in: http://www.iop.org/EJ/article/0295-5075/85/5/58006/epl_85_5_58006.htm

NEEDLE IN A HAYSTACK: FEASIBILITY OF IDENTIFYING SMALL SAFETY ASSETS FROM POINT CLOUDS USING DEEP LEARNING

Asset management systems are beneficial for maintaining building infrastructure and can be used to keep up-to-date records of relevant safety assets, such as smoke detectors, exit signs, and fire extinguishers. Existing methods for locating and identifying these assets in buildings primarily rely on surveys and images, which only provide 2D locations and can be tedious for large-scale structures. Indoor point clouds, which can be captured quickly for buildings using mobile scanning techniques, can provide us with 3D asset locations. In this paper, we study the feasibility of using 3D point clouds of buildings combined with deep learning techniques to identify safety-related assets, particularly small-sized assets like fire switches and exit signs. We adopt the state-of-the-art Deep Learning network, Kernel Point-Fully Convolutional Network (KP-FCNN), to identify these assets through semantic segmentation. Using the obtained results, we create a 3D-geometry model of the building with assets pinpointed, providing scene semantics and delivering more value. Our method is tested using three different point cloud datasets obtained from a depth camera, a mobile laser scanner, and an iPhone lidar sensor

Preregistration Classification of Mobile LIDAR Data Using Spatial Correlations

We explore a novel paradigm for light detection and ranging (LIDAR) point classification in mobile laser scanning (MLS). In contrast to the traditional scheme of performing classification for a 3-D point cloud after registration, our algorithm operates on the raw data stream classifying the points on-the-fly before registration. Hence, we call it preregistration classification (PRC). Specifically, this technique is based on spatial correlations, i.e., local range measurements supporting each other. The proposed method is general since exact scanner pose information is not required, nor is any radiometric calibration needed. Also, we show that the method can be applied in different environments by adjusting two control parameters, without the results being overly sensitive to this adjustment. As results, we present classification of points from an urban environment where noise, ground, buildings, and vegetation are distinguished from each other, and points from the forest where tree stems and ground are classified from the other points. As computations are efficient and done with a minimal cache, the proposed methods enable new on-chip deployable algorithmic solutions. Broader benefits from the spatial correlations and the computational efficiency of the PRC scheme are likely to be gained in several online and offline applications. These range from single robotic platform operations including simultaneous localization and mapping (SLAM) algorithms to wall-clock time savings in geoinformation industry. Finally, PRC is especially attractive for continuous-beam and solid-state LIDARs that are prone to output noisy data

Biometal Dyshomeostasis in Olfactory Mucosa of Alzheimer's Disease Patients

Olfactory function, orchestrated by the cells of the olfactory mucosa at the rooftop of the nasal cavity, is disturbed early in the pathogenesis of Alzheimer's disease (AD). Biometals including zinc and calcium are known to be important for sense of smell and to be altered in the brains of AD patients. Little is known about elemental homeostasis in the AD patient olfactory mucosa. Here we aimed to assess whether the disease-related alterations to biometal homeostasis observed in the brain are also reflected in the olfactory mucosa. We applied RNA sequencing to discover gene expression changes related to metals in olfactory mucosal cells of cognitively healthy controls, individuals with mild cognitive impairment and AD patients, and performed analysis of the elemental content to determine metal levels. Results demonstrate that the levels of zinc, calcium and sodium are increased in the AD olfactory mucosa concomitantly with alterations to 17 genes related to metal-ion binding or metal-related function of the protein product. A significant elevation in alpha-2-macroglobulin, a known metal-binding biomarker correlated with brain disease burden, was observed on the gene and protein levels in the olfactory mucosa cells of AD patients. These data demonstrate that the olfactory mucosa cells derived from AD patients recapitulate certain impairments of biometal homeostasis observed in the brains of patients.Peer reviewe

Interventions to prevent injuries in construction workers

Background Construction workers are frequently exposed to various types of injury-inducing hazards. A number of injury prevention interventions have been proposed, yet their effectiveness is uncertain. Objectives To assess the effects of interventions to prevent injuries in construction workers. Search methods We searched the Cochrane Injuries Group’s specialised register, CENTRAL,MEDLINE, EMBASE, PsycINFO,OSH-ROM(including NIOSHTIC and HSELINE), Scopus, Web of Science and EI Compendex to September 2011. The searches were not restricted by language or publication status. The reference lists of relevant papers and reviews were also searched. Selection criteria Randomised controlled trials, controlled before-after (CBA) studies and interrupted time series (ITS) of all types of interventions for preventing fatal and non-fatal injuries among workers at construction sites. Data collection and analysis Two review authors independently selected studies, extracted data and assessed study quality. For ITS, we re-analysed the studies and used an initial effect, measured as the change in injury-rate in the year after the intervention, as well as a sustained effect, measured as the change in time trend before and after the intervention

Associations of age and sex with brain volumes and asymmetry in 2–5-week-old infants

Information on normal brain structure and development facilitates the recognition of abnormal developmental trajectories and thus needs to be studied in more detail. We imaged 68 healthy infants aged 2–5 weeks with high-resolution structural MRI (magnetic resonance imaging) and investigated hemispheric asymmetry as well as the associations of various total and lobar brain volumes with infant age and sex. We found similar hemispheric asymmetry in both sexes, seen as larger volumes of the right temporal lobe, and of the left parietal and occipital lobes. The degree of asymmetry did not vary with age. Regardless of controlling for gestational age, gray and white matter had different age-related growth patterns. This is a reflection of gray matter growth being greater in the first years, while white matter growth extends into early adulthood. Sex-dependent differences were seen in gray matter as larger regional absolute volumes in males and as larger regional relative volumes in females. Our results are in line with previous studies and expand our understanding of infant brain development.</p