Changing the diameter of 3D printed tissue engineering scaffolds made via melt electrospinning writing

Introduction. Due to the structural complexity of the natural tissues, a production of anatomically accurate three-dimensional (3D) structures is a major challenge in tissue engineering. Previously a technology termed melt electrospinning writing (MEW), produced 3D constructs out of filaments sized from 0.8 μm up to 140 μm [1-3]. Here the fiber diameter control during MEW printing was investigated. Methods: Poly (ε-caprolactone) (PCL) fibers were printed with a custom-built MEW device [4] at 73 ± 1 °C temperature, 8.5 kV voltage difference and 6 mm distance between the nozzle and the collector. The polymer flowrate was controlled by the air pressure variation between 0.5 and 4 bar. For the different fiber stretching, collector speed was varied from 300 to 10000 mm/min. Results. Fiber diameter could be changed from 2.02±0.57 μm to 49.93±2.61 μm (Figure 1A). Multi-modal 3D printed structures, produced within a single print are shown in Figure 1B-D. Figure 1B demonstrates a grid pattern of 3 μm fibers overlaid with 30 μm fibers. Figure 1C and 1D shows that multidiameter fibers can be precisely stacked and rotated around each other. As an example of a 3D-printed construct, a tapered frame for spheroid capture is shown in Figure 1E; due to the different diameters, this construct has a larger pore size at the top compared to the bottom. Please click Additional Files below to see the full abstract

Corner contribution to cluster numbers in the Potts model

For the two-dimensional Q-state Potts model at criticality, we consider Fortuin-Kasteleyn and spin clusters and study the average number N_Gamma of clusters that intersect a given contour Gamma. To leading order, N_Gamma is proportional to the length of the curve. Additionally, however, there occur logarithmic contributions related to the corners of Gamma. These are found to be universal and their size can be calculated employing techniques from conformal field theory. For the Fortuin-Kasteleyn clusters relevant to the thermal phase transition we find agreement with these predictions from large-scale numerical simulations. For the spin clusters, on the other hand, the cluster numbers are not found to be consistent with the values obtained by analytic continuation, as conventionally assumed.Comment: 9 pages, 6 figure

Efficient simulation of the random-cluster model

The simulation of spin models close to critical points of continuous phase transitions is heavily impeded by the occurrence of critical slowing down. A number of cluster algorithms, usually based on the Fortuin-Kasteleyn representation of the Potts model, and suitable generalizations for continuous-spin models have been used to increase simulation efficiency. The first algorithm making use of this representation, suggested by Sweeny in 1983, has not found widespread adoption due to problems in its implementation. However, it has been recently shown that it is indeed more efficient in reducing critical slowing down than the more well-known algorithm due to Swendsen and Wang. Here, we present an efficient implementation of Sweeny's approach for the random-cluster model using recent algorithmic advances in dynamic connectivity algorithms.Comment: RevTeX 4.1, 14 pages, 8 figures, 3 tables, version as publishe

On the Coupling Time of the Heat-Bath Process for the Fortuin–Kasteleyn Random–Cluster Model

We consider the coupling from the past implementation of the random-cluster heat-bath process, and study its random running time, or coupling time. We focus on hypercubic lattices embedded on tori, in dimensions one to three, with cluster fugacity at least one. We make a number of conjectures regarding the asymptotic behaviour of the coupling time, motivated by rigorous results in one dimension and Monte Carlo simulations in dimensions two and three. Amongst our findings, we observe that, for generic parameter values, the distribution of the appropriately standardized coupling time converges to a Gumbel distribution, and that the standard deviation of the coupling time is asymptotic to an explicit universal constant multiple of the relaxation time. Perhaps surprisingly, we observe these results to hold both off criticality, where the coupling time closely mimics the coupon collector's problem, and also at the critical point, provided the cluster fugacity is below the value at which the transition becomes discontinuous. Finally, we consider analogous questions for the single-spin Ising heat-bath process

Cluster Monte Carlo and dynamical scaling for long-range interactions

Many spin systems affected by critical slowing down can be efficiently simulated using cluster algorithms. Where such systems have long-range interactions, suitable formulations can additionally bring down the computational effort for each update from O($N^2$) to O($N\ln N$) or even O($N$), thus promising an even more dramatic computational speed-up. Here, we review the available algorithms and propose a new and particularly efficient single-cluster variant. The efficiency and dynamical scaling of the available algorithms are investigated for the Ising model with power-law decaying interactions.Comment: submitted to Eur. Phys. J Spec. Topic

Of the importance of a leaf: the ethnobotany of sarma in Turkey and the Balkans

BACKGROUND: Sarma - cooked leaves rolled around a filling made from rice and/or minced meat, possibly vegetables and seasoning plants - represents one of the most widespread feasting dishes of the Middle Eastern and South-Eastern European cuisines. Although cabbage and grape vine sarma is well-known worldwide, the use of alternative plant leaves remains largely unexplored. The aim of this research was to document all of the botanical taxa whose leaves are used for preparing sarma in the folk cuisines of Turkey and the Balkans. Methods: Field studies were conducted during broader ethnobotanical surveys, as well as during ad-hoc investigations between the years 2011 and 2014 that included diverse rural communities in Croatia, Bosnia and Herzegovina, Serbia, Kosovo, Albania, Macedonia, Bulgaria, Romania, and Turkey. Primary ethnobotanical and folkloric literatures in each country were also considered. Results: Eighty-seven botanical taxa, mainly wild, belonging to 50 genera and 27 families, were found to represent the bio-cultural heritage of sarma in Turkey and the Balkans. The greatest plant biodiversity in sarma was found in Turkey and, to less extent, in Bulgaria and Romania. The most commonly used leaves for preparing sarma were those of cabbage (both fresh and lacto-fermented), grape vine, beet, dock, sorrel, horseradish, lime tree, bean, and spinach. In a few cases, the leaves of endemic species (Centaurea haradjianii, Rumex gracilescens, and R. olympicus in Turkey) were recorded. Other uncommon sarma preparations were based on lightly toxic taxa, such as potato leaves in NE Albania, leaves of Arum, Convolvulus, and Smilax species in Turkey, of Phytolacca americana in Macedonia, and of Tussilago farfara in diverse countries. Moreover, the use of leaves of the introduced species Reynoutria japonica in Romania, Colocasia esculenta in Turkey, and Phytolacca americana in Macedonia shows the dynamic nature of folk cuisines. Conclusion: The rich ethnobotanical diversity of sarma confirms the urgent need to record folk culinary plant knowledge. The results presented here can be implemented into initiatives aimed at re-evaluating folk cuisines and niche food markets based on local neglected ingredients, and possibly also to foster trajectories of the avant-garde cuisines inspired by ethnobotanical knowledge

The Effect of Complex Interventions on Depression and Anxiety in Chronic Obstructive Pulmonary Disease: Systematic Review and Meta-Analysis

Background Depression and anxiety are very common in people with chronic obstructive pulmonary disease (COPD) and are associated with excess morbidity and mortality. Patients prefer non-drug treatments and clinical guidelines promote non-pharmacological interventions as first line therapy for depression and anxiety in people with long term conditions. However the comparative effectiveness of psychological and lifestyle interventions among COPD patients is not known. We assessed whether complex psychological and/or lifestyle interventions are effective in reducing symptoms of anxiety and depression in patients with COPD. We then determined what types of psychological and lifestyle interventions are most effective. Methods and Findings Systematic review of randomised controlled trials of psychological and/or lifestyle interventions for adults with COPD that measured symptoms of depression and/or anxiety. CENTRAL, Medline, Embase, PsychINFO, CINAHL, ISI Web of Science and Scopus were searched up to April 2012. Meta-analyses using random effects models were undertaken to estimate the average effect of interventions on depression and anxiety. Thirty independent comparisons from 29 randomised controlled trials (n = 2063) were included in the meta-analysis. Overall, psychological and/or lifestyle interventions were associated with small reductions in symptoms of depression (standardised mean difference −0.28, 95% confidence interval −0.41 to −0.14) and anxiety (standardised mean difference −0.23, 95% confidence interval −0.38 to −0.09). Multi-component exercise training was the only intervention subgroup associated with significant treatment effects for depression (standardised mean difference −0.47, 95% confidence interval −0.66 to −0.28), and for anxiety (standardised mean difference −0.45, 95% confidence interval −0.71 to −0.18). Conclusions Complex psychological and/or lifestyle interventions that include an exercise component significantly improve symptoms of depression and anxiety in people with COPD. Furthermore, multi-component exercise training effectively reduces symptoms of anxiety and depression in all people with COPD regardless of severity of depression or anxiety, highlighting the importance of promoting physical activity in this population

XMLEase: A Novel Access- and Space-Efficiency Model for Maintaining XML Data in Relational Databases

Abstract- Representing XML data in terms of the rows and columns of a relational table is quite inefficient. Similarly, object-oriented databases cater for storage of objects but lack fast access. In these cases, a better technique is required to speedup representation and retrieval of hierarchical data in relational databases. This paper presents XMLEase, a new access- and store-efficient technique to keep XML data in relational databases. XMLEase keeps data node together with its successors down to a pre-defined level of hierarchy. This method has been implemented and evaluated; in comparison to other similar methods it is found to perform better. It shows a fair linear performance independent to the depth of hierarchy with superior data retrieval efficiency. Although it suffers of a bit of extra space usage for storing successor links, however this is much less than that of the other methods used for dealing with XML data. Present paper focuses on the access efficiency of the model in connection with run query processing. This method's best feature is its efficiency in operations to store and retrieve XML data requiring only one-run SQL query