Scaling regimes for wormlike chains confined to cylindrical surfaces under tension.

We compute the free energy of confinement [Formula: see text] for a wormlike chain (WLC), with persistence length [Formula: see text], that is confined to the surface of a cylinder of radius R under an external tension f using a mean field variational approach. For long chains, we analytically determine the behavior of the chain in a variety of regimes, which are demarcated by the interplay of [Formula: see text], the Odijk deflection length ([Formula: see text]), and the Pincus length ([Formula: see text], with [Formula: see text] being the thermal energy). The theory accurately reproduces the Odijk scaling for strongly confined chains at [Formula: see text], with [Formula: see text]. For moderate values of f, the Odijk scaling is discernible only when [Formula: see text] for strongly confined chains. Confinement does not significantly alter the scaling of the mean extension for sufficiently high tension. The theory is used to estimate unwrapping forces for DNA from nucleosomes.

Correlation functions for confined wormlike chains.

Polymer models describing the statistics of biomolecules under confinement have applications to a wide range of single-molecule experimental techniques and give insight into biologically relevant processes in vivo. In this paper, we determine the transverse position and bending correlation functions for a wormlike chain confined within slits and cylinders (with one and two confined dimensions, respectively) using a mean-field approach that enforces rigid constraints on average. We show the theoretical predictions accurately capture the statistics of a wormlike chain from Monte Carlo simulations in both confining geometries for both weak and strong confinement. We also show that the longitudinal correlation function is accurately computed for a chain confined to a slit and leverages the accuracy of the model to suggest an experimental technique to infer the (often unobservable) transverse statistics from the (directly observable) longitudinal end-to-end distance.

Crystal Structures and Property Measurements of Rare Earth Magnesium Thiosilicates Synthesized via Flux Crystal Growth Utilizing the Boron Chalcogen Mixture (BCM) Method.

Nine new rare earth magnesium-containing thiosilicates of the formula RE3Mg0.5SiS7 (Ln = Ce, Pr, Nd, Sm, Gd, Tb, Dy, Ho, Er) were synthesized in an alkali halide flux using the boron chalcogen mixture (BCM) method. Crystals of high quality were produced, and their structures were determined by single-crystal X-ray diffraction. The compounds crystallize in the hexagonal crystal system in the P63 space group. Phase pure powders of the compounds were used for magnetic susceptibility measurements and for second-harmonic generation (SHG) measurements. Magnetic measurements indicate that Ce3Mg0.5SiS7, Sm3Mg0.5SiS7, and Dy3Mg0.5SiS7 exhibit paramagnetic behavior with a negative Weiss temperature over the 2-300 K temperature range. SHG measurements of La3Mg0.5SiS7 demonstrated SHG activity with an efficiency of 0.16 times the standard potassium dihydrogen phosphate (KDP).

Compression-induced buckling of a semiflexible filament in two and three dimensions.

The ability of biomolecules to exert forces on their surroundings or resist compression from the environment is essential in a variety of biologically relevant contexts. For filaments in the low-temperature limit and under a constant compressive force, Euler buckling theory predicts a sudden transition from a compressed state to a bent state in these slender rods. In this paper, we use a mean-field theory to show that if a semiflexible chain is compressed at a finite temperature with a fixed end-to-end distance (permitting fluctuations in the compressive forces), it exhibits a continuous phase transition to a buckled state at a critical level of compression. We determine a quantitatively accurate prediction of the transverse position distribution function of the midpoint of the chain that indicates this transition. We find that the mean compressive forces are non-monotonic as the extension of the filament varies, consistent with the observation that strongly buckled filaments are less able to bear an external load. We also find that for the fixed extension (isometric) ensemble, the buckling transition does not coincide with the local minimum of the mean force (in contrast to Euler buckling). We also show that the theory is highly sensitive to fluctuations in length in two dimensions and the buckling transition can still be accurately recovered by accounting for those fluctuations. These predictions may be useful in understanding the behavior of filamentous biomolecules compressed by fluctuating forces, relevant in a variety of biological contexts.

Short-term renewable energy consumption and generation forecasting: A case study of Western Australia.

Peer-to-Peer (P2P) energy trading has gained much attention recently due to the advanced development of distributed energy resources. P2P enables prosumers to trade their surplus electricity and allows consumers to purchase affordable and locally produced renewable energy. Therefore, it is significant to develop solutions that are able to forecast energy consumption and generation toward better power management, thereby making renewable energy more accessible and empowering prosumers to make an informed decision on their energy management. In this paper, several models for forecasting short-term renewable energy consumption and generating are developed and discussed. Real-time energy datasets were collected from smart meters that were installed in residential premises in Western Australia. These datasets are collected from August 2018 to Apr 2019 at fine time resolution down to 5 s and comprise energy import from the grid, energy export to the grid, energy generation from installed rooftop PV, energy consumption in households, and outdoor temperature. Several models for forecasting short-term renewable energy consumption and generating are developed and discussed. The empirical results demonstrate the superiority of the optimised deep learning-based Long Term Short Memory (LSTM) model in forecasting both energy consumption and generation and outperforms the baseline model as well as the alternative classical and machine learning methods by a substantial margin.

Effects of Protein Crowders and Charge on the Folding of Superoxide Dismutase 1 Variants: A Computational Study.

The neurodegenerative disease amyotrophic lateral sclerosis (ALS) is associated with the misfolding and aggregation of the metalloenzyme protein superoxide dismutase 1 (SOD1) via mutations that destabilize the monomer-dimer interface. In a cellular environment, crowding and electrostatic screening play essential roles in the folding and aggregation of the SOD1 monomers. Despite numerous studies on the effects of mutations on SOD1 folding, a clear understanding of the interplay between crowding, folding, and aggregation in vivo remains lacking. Using a structure-based minimal model for molecular dynamics simulations, we investigate the role of self-crowding and charge on the folding stability of SOD1 and the G41D mutant where experimentalists were intrigued by an alteration of the folding mechanism by a single point mutation from glycine to charged aspartic acid. We show that unfolded SOD1 configurations are significantly affected by charge and crowding, a finding that would be extremely costly to achieve with all-atom simulations, while the native state is not significantly altered. The mutation at residue 41 alters the interactions between proteins in the unfolded states instead of those within a protein. This paper suggests electrostatics may play an important role in the folding pathway of SOD1 and modifying the charge via mutation and ion concentration may change the dominant interactions between proteins, with potential impacts for aggregation of the mutants. This work provides a plausible reason for the alteration of the unfolded states to address why the mutant G41D causes the changes to the folding mechanism of SOD1 that have intrigued experimentalists.

Insights from graph theory on the morphologies of actomyosin networks with multilinkers.

Quantifying the influence of microscopic details on the dynamics of development of the overall structure of a filamentous network is important in a number of biologically relevant contexts, but it is not obvious what order parameters can be used to adequately describe this complex process. In this paper we investigated the role of multivalent actin-binding proteins (ABPs) in reorganizing actin filaments into higher-order complex networks via a computer model of semiflexible filaments. We characterize the importance of local connectivity among actin filaments, as well as the global features of actomyosin networks. We first map the networks into local graph representations and then, using principles from network-theory order parameters, combine properties from these representations to gain insight into the heterogeneous morphologies of actomyosin networks at a global level. We find that ABPs with a valency greater than 2 promote filament bundles and large filament clusters to a much greater extent than bivalent multilinkers. We also show that active myosinlike motor proteins promote the formation of dendritic branches from a stalk of actin bundles. Our work motivates future studies to embrace network theory as a tool to characterize complex morphologies of actomyosin detected by experiments, leading to a quantitative understanding of the role of ABPs in manipulating the self-assembly of actin filaments into unique architectures that underlie the structural scaffold of a cell relating to its mobility and shape.

Generalized Erdos numbers for network analysis.

The identification of relationships in complex networks is critical in a variety of scientific contexts. This includes the identification of globally central nodes and analysing the importance of pairwise relationships between nodes. In this paper, we consider the concept of topological proximity (or 'closeness') between nodes in a weighted network using the generalized Erdos numbers (GENs). This measure satisfies a number of desirable properties for networks with nodes that share a finite resource. These include: (i) real-valuedness, (ii) non-locality and (iii) asymmetry. We show that they can be used to define a personalized measure of the importance of nodes in a network with a natural interpretation that leads to new methods to measure centrality. We show that the square of the leading eigenvector of an importance matrix defined using the GENs is strongly correlated with well-known measures such as PageRank, and define a personalized measure of centrality that is also well correlated with other existing measures. The utility of this measure of topological proximity is demonstrated by showing the asymmetries in both the dynamics of random walks and the mean infection time in epidemic spreading are better predicted by the topological definition of closeness provided by the GENs than they are by other measures.

On Economic Complexity and the Fitness of Nations.

Complex economic systems can often be described by a network, with nodes representing economic entities and edges their interdependencies, while network centrality is often a good indicator of importance. Recent publications have implemented a nonlinear iterative Fitness-Complexity (FC) algorithm to measure centrality in a bipartite trade network, which aims to represent the 'Fitness' of national economies as well as the 'Complexity' of the products being traded. In this paper, we discuss this methodological approach and conclude that further work is needed to identify stable and reliable measures of fitness and complexity. We provide theoretical and numerical evidence for the intrinsic instability in the nonlinear definition of the FC algorithm. We perform an in-depth evaluation of the algorithm's rankings in two real world networks at the country level: the global trade network, and the patent network in different technological domains. In both networks, we find evidence of the instabilities predicted theoretically, and show that 'complex' products or patents tend often to be those that countries rarely produce, rather than those that are intrinsically more difficult to produce.

Disambiguation of patent inventors and assignees using high-resolution geolocation data.

Patent data represent a significant source of information on innovation, knowledge production, and the evolution of technology through networks of citations, co-invention and co-assignment. A major obstacle to extracting useful information from this data is the problem of name disambiguation: linking alternate spellings of individuals or institutions to a single identifier to uniquely determine the parties involved in knowledge production and diffusion. In this paper, we describe a new algorithm that uses high-resolution geolocation to disambiguate both inventors and assignees on about 8.5 million patents found in the European Patent Office (EPO), under the Patent Cooperation Treaty (PCT), and in the US Patent and Trademark Office (USPTO). We show this disambiguation is consistent with a number of ground-truth benchmarks of both assignees and inventors, significantly outperforming the use of undisambiguated names to identify unique entities. A significant benefit of this work is the high quality assignee disambiguation with coverage across the world coupled with an inventor disambiguation (that is competitive with other state of the art approaches) in multiple patent offices.

Aging in complex interdependency networks.

Although species longevity is subject to a diverse range of evolutionary forces, the mortality curves of a wide variety of organisms are rather similar. Here we argue that qualitative and quantitative features of aging can be reproduced by a simple model based on the interdependence of fault-prone agents on one other. In addition to fitting our theory to the empiric mortality curves of six very different organisms, we establish the dependence of lifetime and aging rate on initial conditions, damage and repair rate, and system size. We compare the size distributions of disease and death and see that they have qualitatively different properties. We show that aging patterns are independent of the details of interdependence network structure, which suggests that aging is a many-body effect, and that the qualitative and quantitative features of aging are not sensitively dependent on the details of dependency structure or its formation.

The Image Gently pediatric digital radiography safety checklist: tools for improving pediatric radiography.

Transition from film-screen to digital radiography requires changes in radiographic technique and workflow processes to ensure that the minimum radiation exposure is used while maintaining diagnostic image quality. Checklists have been demonstrated to be useful tools for decreasing errors and improving safety in several areas, including commercial aviation and surgical procedures. The Image Gently campaign, through a competitive grant from the FDA, developed a checklist for technologists to use during the performance of digital radiography in pediatric patients. The checklist outlines the critical steps in digital radiography workflow, with an emphasis on steps that affect radiation exposure and image quality. The checklist and its accompanying implementation manual and practice quality improvement project are open source and downloadable at www.imagegently.org. The authors describe the process of developing and testing the checklist and offer suggestions for using the checklist to minimize radiation exposure to children during radiography.

Image gently campaign back to basics initiative: ten steps to help manage radiation dose in pediatric digital radiography.

OBJECTIVE: The purpose of this review is to summarize 10 steps a practice can take to manage radiation exposure in pediatric digital radiography. CONCLUSION: The Image Gently campaign raises awareness of opportunities for lowering radiation dose while maintaining diagnostic quality of images of children. The newest initiative in the campaign, Back to Basics, addresses methods for standardizing the approach to pediatric digital radiography, highlighting challenges related to the technology in imaging of patients of widely varying body sizes.

Discovering communities through friendship.

We introduce a new method for detecting communities of arbitrary size in an undirected weighted network. Our approach is based on tracing the path of closest-friendship between nodes in the network using the recently proposed Generalized Erds Numbers. This method does not require the choice of any arbitrary parameters or null models, and does not suffer from a system-size resolution limit. Our closest-friend community detection is able to accurately reconstruct the true network structure for a large number of real world and artificial benchmarks, and can be adapted to study the multi-level structure of hierarchical communities as well. We also use the closeness between nodes to develop a degree of robustness for each node, which can assess how robustly that node is assigned to its community. To test the efficacy of these methods, we deploy them on a variety of well known benchmarks, a hierarchal structured artificial benchmark with a known community and robustness structure, as well as real-world networks of coauthorships between the faculty at a major university and the network of citations of articles published in Physical Review. In all cases, microcommunities, hierarchy of the communities, and variable node robustness are all observed, providing insights into the structure of the network.

Compaction and tensile forces determine the accuracy of folding landscape parameters from single molecule pulling experiments.

We establish a framework for assessing whether the transition state location of a biopolymer, which can be inferred from single molecule pulling experiments, corresponds to the ensemble of structures that have equal probability of reaching either the folded or unfolded states (P(fold)=0.5). Using results for the forced unfolding of a RNA hairpin, an exactly soluble model, and an analytic theory, we show that P(fold) is solely determined by s, an experimentally measurable molecular tensegrity parameter, which is a ratio of the tensile force and a compaction force that stabilizes the folded state. Applications to folding landscapes of DNA hairpins and a leucine zipper with two barriers provide a structural interpretation of single molecule experimental data. Our theory can be used to assess whether molecular extension is a good reaction coordinate using measured free energy profiles.

Changes in falls risk factors for geriatric diagnostic groups across inpatient, outpatient and domiciliary rehabilitation settings.

PURPOSE: To compare falls event rates and risk factors for falls across three rehabilitation settings. METHODS: A multi-centre prospective longitudinal cohort study was conducted of 1682 participants referred for rehabilitation from 18 sites (across two Australian states) and receiving physiotherapy treatment. Falls risk factors across multiple domains (rehabilitation settings, medical diagnoses, age, gender, standing balance, functional capacity, cognition, prior living arrangements, pre-admission use of gait aid and past history of falls) were collected by treating physiotherapists on admission to rehabilitation. Falls were measured by incident reporting and review of medical histories in the inpatient settings and by weekly interviews in the outpatient and domiciliary settings. RESULTS: Overall, outpatient and domiciliary settings demonstrated lower falls event rates compared to inpatient [IRR (95% CI): 0.58 (0.36-0.93) and 0.35 (0.24-0.51)], respectively. Cognitive status, functional ability and past history of falls were consistent risk factors across settings. However medical diagnoses of stroke, other neurological conditions, elective orthopaedic and other orthopaedic together with standing balance were inconsistent as risk factors or protective factors across settings. CONCLUSIONS: Risk factors for falls, including medical diagnosis, are not necessarily universal across settings. Balance performance was a significant risk factor for outpatient and domiciliary settings but was not a risk factor for inpatients. Cognitive status and a previous history of falls were, however, consistent risk factors across all settings. This suggests that different approaches for the prevention of falls may be required for the same diagnostic group of patients depending on the location of the rehabilitation setting.

Dose-response relationship between physiotherapy resource provision with function and balance improvements in patients following stroke: a multi-centre observational study.

RATIONALE, AIMS AND OBJECTIVES: Inpatient rehabilitation of patients following stroke can be resource intensive, with optimal models of service delivery unclear. This study investigates the dose-response curves between physiotherapy service delivery variables and balance and function clinical outcomes. METHOD: This was a multi-centre (15 sites), prospective, cohort study involving patients (n = 288) admitted for rehabilitation following stroke conducted across two states in Australia. Physiotherapy department resource provision variables were collected and examined for association with change in patient function and balance outcomes (Functional Independence Measure, step test, functional reach test) measured at admission and discharge from inpatient care. RESULTS: A greater amount of log-transformed physiotherapy department resource provision was associated with greater improvement in the functional independence measure [Regression coefficient (95% CI): 4.05 (1.15, 6.95)] and functional reach test [46.43 (17.03, 75.84)], while physiotherapist time provided to patients was associated with greater improvement for the step test [0.15 (0.03, 0.28)], and functional reach [0.35 (0.19, 0.52)]. CONCLUSION: Receiving a higher rate of physiotherapist input is an important factor in attaining a greater amount of recovery in function and balance outcomes; however, the improvement by patients who received the greatest amount of input was highly variable.