Enzymatic treatments to improve mechanical properties and surface hydrophobicity of jute fiber membranes

Fiber membranes prepared from jute fragments can be valuable, low cost, and renewable. They have broad application prospects in packing bags, geotextiles, filters, and composite reinforcements. Traditionally, chemical adhesives have been used to improve the properties of jute fiber membranes. A series of new laccase, laccase/mediator systems, and multi-enzyme synergisms were attempted. After the laccase treatment of jute fragments, the mechanical properties and surface hydrophobicity of the produced fiber membranes increased because of the cross-coupling of lignins with ether bonds mediated by laccase. The optimum conditions were a buffer pH of 4.5 and an incubation temperature of 60 °C with 0.92 U/mL laccase for 3 h. Laccase/guaiacol and laccase/alkali lignin treatments resulted in remarkable increases in the mechanical properties; in contrast, the laccase/2,2-azino-bis-(3-ethylthiazoline-6-sulfonate) (ABTS) and laccase/2,6-dimethoxyphenol treatments led to a decrease. The laccase/ guaiacol system was favorable to the surface hydrophobicity of jute fiber membranes. However, the laccase/alkali lignin system had the opposite effect. Xylanase/laccase and cellulase/laccase combined treatments were able to enhance both the mechanical properties and the surface hydrophobicity of jute fiber membranes. Among these, cellulase/laccase treatment performed better; compared to mechanical properties, the surface hydrophobicity of the jute fiber membranes showed only a slight increase after the enzymatic multi-step processes.

Processing and properties of alumina reinforced mullite ceramics

Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2013

Verbreitung des Bibers (Castor fiber LINNAEUS 1758) im Biosphärenreservat Oberlausitzer Heide- und Teichlandschaft

Die Arbeit zeichnet die Verbreitung des Bibers (Castor fiber LINNEAUS 1758) im Biosphärenreservat Oberlausitzer Heide- und Teichlandschaft für das Jahr 2014 nach. Auf Grundlage der zwei wöchigen Feldarbeit im Februar 2014 wurden Aktivitätsspuren gesichtet und mit einem GPS Gerät registriert und fotografisch dokumentiert. Daraus werden Verbreitungskarten mit genauer Lage und Umfang der einzelnen Reviere dargestellt. Insgesamt wurden sieben Reviere entdeckt. Davon befinden sich vier Reviere an der Spree und ein Revier am Schwarzen Schöps. Die restlichen zwei Reviere wurden in Teichgruppen, die sich in der unmittelbaren Nähe der Spree befinden, verzeichnet. Des Weiteren erfolgte der Kontakt zu unterschiedlichen Akteuren die sich mit der Verbreitung des Bibers in Ost-Sachsen befassen. Zu den ermittelten Ergebnissen wurden die anderen Standorte eingebunden und kartografisch in einer Verbreitungskarte dargestellt.

Sparse regularization for fiber ODF reconstruction: from the suboptimality of ℓ2 and ℓ1 priors to ℓ0.

Diffusion MRI is a well established imaging modality providing a powerful way to probe the structure of the white matter non-invasively. Despite its potential, the intrinsic long scan times of these sequences have hampered their use in clinical practice. For this reason, a large variety of methods have been recently proposed to shorten the acquisition times. Among them, spherical deconvolution approaches have gained a lot of interest for their ability to reliably recover the intra-voxel fiber configuration with a relatively small number of data samples. To overcome the intrinsic instabilities of deconvolution, these methods use regularization schemes generally based on the assumption that the fiber orientation distribution (FOD) to be recovered in each voxel is sparse. The well known Constrained Spherical Deconvolution (CSD) approach resorts to Tikhonov regularization, based on an ℓ(2)-norm prior, which promotes a weak version of sparsity. Also, in the last few years compressed sensing has been advocated to further accelerate the acquisitions and ℓ(1)-norm minimization is generally employed as a means to promote sparsity in the recovered FODs. In this paper, we provide evidence that the use of an ℓ(1)-norm prior to regularize this class of problems is somewhat inconsistent with the fact that the fiber compartments all sum up to unity. To overcome this ℓ(1) inconsistency while simultaneously exploiting sparsity more optimally than through an ℓ(2) prior, we reformulate the reconstruction problem as a constrained formulation between a data term and a sparsity prior consisting in an explicit bound on the ℓ(0)norm of the FOD, i.e. on the number of fibers. The method has been tested both on synthetic and real data. Experimental results show that the proposed ℓ(0) formulation significantly reduces modeling errors compared to the state-of-the-art ℓ(2) and ℓ(1) regularization approaches.

Quantitative comparison of reconstruction methods for intra-voxel fiber recovery from diffusion MRI.

Validation is arguably the bottleneck in the diffusion magnetic resonance imaging (MRI) community. This paper evaluates and compares 20 algorithms for recovering the local intra-voxel fiber structure from diffusion MRI data and is based on the results of the "HARDI reconstruction challenge" organized in the context of the "ISBI 2012" conference. Evaluated methods encompass a mixture of classical techniques well known in the literature such as diffusion tensor, Q-Ball and diffusion spectrum imaging, algorithms inspired by the recent theory of compressed sensing and also brand new approaches proposed for the first time at this contest. To quantitatively compare the methods under controlled conditions, two datasets with known ground-truth were synthetically generated and two main criteria were used to evaluate the quality of the reconstructions in every voxel: correct assessment of the number of fiber populations and angular accuracy in their orientation. This comparative study investigates the behavior of every algorithm with varying experimental conditions and highlights strengths and weaknesses of each approach. This information can be useful not only for enhancing current algorithms and develop the next generation of reconstruction methods, but also to assist physicians in the choice of the most adequate technique for their studies.

PGC1alpha expression is controlled in skeletal muscles by PPARbeta, whose ablation results in fiber-type switching, obesity, and type 2 diabetes.

Mice in which peroxisome proliferator-activated receptor beta (PPARbeta) is selectively ablated in skeletal muscle myocytes were generated to elucidate the role played by PPARbeta signaling in these myocytes. These somatic mutant mice exhibited a muscle fiber-type switching toward lower oxidative capacity that preceded the development of obesity and diabetes, thus demonstrating that PPARbeta is instrumental in myocytes to the maintenance of oxidative fibers and that fiber-type switching is likely to be the cause and not the consequence of these metabolic disorders. We also show that PPARbeta stimulates in myocytes the expression of PGC1alpha, a coactivator of various transcription factors, known to play an important role in slow muscle fiber formation. Moreover, as the PGC1alpha promoter contains a PPAR response element, the effect of PPARbeta on the formation and/or maintenance of slow muscle fibers can be ascribed, at least in part, to a stimulation of PGC1alpha expression at the transcriptional level.

A dynamic assessment of medication-taking behavior during pregnancy and postpartum: should cART adherence be reinforced during postpartum?

This study compared adherence (persistence and execution) during pregnancy and postpartum in HIV-positive women having taken part in the adherence-enhancing program of the Community Pharmacy of the Department of Ambulatory Care and Community Medicine in Lausanne between 2004 and 2012. This interdisciplinary program combined electronic drug monitoring and semi-structured, repeated motivational interviews. This was a retrospective, observational study. Observation period spread over from first adherence visit after last menstruation until 6 months after childbirth. Medication-taking was recorded by electronic drug monitoring. Socio-demographic and delivery data were collected from Swiss HIV Cohort database. Adherence data, barriers and facilitators were collected from pharmacy database. Electronic data were reconciled with pill-count and interview notes in order to include reported pocket-doses. Execution was analyzed over 3-day periods by a mixed effect logistic model, separating time before and after childbirth. This model allowed us to estimate different time slopes for both periods and to show a sudden fall associated with childbirth. Twenty-five pregnant women were included. Median age was 29 (IQR: 26.5, 32.0), women were in majority black (n_17,68%) and took a cART combining protease and nucleoside reverse transcriptase inhibitors (n_24,96%). Eleven women (44%) were ART-naı¨ve at the beginning of pregnancy. Twenty women (80%) were included in the program because of pregnancy. Women were included at all stages of pregnancy. Six women (24%) stopped the program during pregnancy, 3 (12%) at delivery, 4 (16%) during postpartum and 12 (48%) stayed in program at the end of observation time. Median number of visits was 4 (3.0, 6.3) during pregnancy and 3 (0.8, 6.0) during postpartum. Execution was continuously high during pregnancy, low at beginning of postpartum and increased gradually during the 6 months of postpartum. Major barriers to adherence were medication adverse events and difficulties in daily routine. Facilitators were motivation for promoting child-health and social support. The dramatic drop and very slow increase in cART adherence during postpartum might result in viral rebound and drug resistance. Although much attention is devoted to pregnant women, interdisciplinary care should also be provided to women in the community during first trimester of postpartum to support them in sustaining cART adherence.

Recent development in optical fiber biosensors

Remarkable developments can be seen in the field of optical fibre biosensors in the last decade. More sensors for specific analytes have been reported, novel sensing chemistries or transduction principles have been introduced, and applications in various analytical fields have been realised. This review consists of papers mainly reported in the last decade and presents about applications of optical fiber biosensors. Discussions on the trends in optical fiber biosensor applications in real samples are enumerated.

A Monte Carlo-Based Fiber Tracking Algorithm using Diffusion Tensor MRI

Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach

Response to comment on "the geometric structure of the brain fiber pathways".

In response to Catani et al., we show that corticospinal pathways adhere via sharp turns to two local grid orientations; that our studies have three times the diffusion resolution of those compared; and that the noted technical concerns, including crossing angles, do not challenge the evidence of mathematically specific geometric structure. Thus, the geometric thesis gives the best account of the available evidence.

Acoustic properties of polypropylene composites reinforced with stone groundwood

Currently, acoustic isolation is one of the problems raised with building construction in Spain. The publication of the Basic Document for the protection against noise of the Technical Building Code has increased the demand of comfort for citizens. This has created the need to seek new composite materials that meet the new required acoustical building codes. In this paper we report the results of the newly developed composites that are able to improve the acoustic isolation of airborne noise. These composites were prepared from polypropylene (PP) reinforced with mechanical pulp fibers from softwood (Pinus radiata). Mechanical and acoustical properties of the composites from mechanical pulp (MP) and polypropylene (PP) have been investigated and compared to fiberglass (FG) composites. MP composites had lower tensile properties compared with FG composites, although these properties can be improved by incorporation of a coupling agent. The results of acoustical properties of MP composites were reported and compared with the conventional composites based on fiberglass and gypsum plasterboards. Finally, we suggest the application of MP composites as a light-weight building material to reduce acoustic transmitions

Universality class of fiber bundles with strong heterogeneities

We study the effect of strong heterogeneities on the fracture of disordered materials using a fiber bundle model. The bundle is composed of two subsets of fibers, i.e. a fraction 0 ≤ α ≤ 1 of fibers is unbreakable, while the remaining 1 - α fraction is characterized by a distribution of breaking thresholds. Assuming global load sharing, we show analytically that there exists a critical fraction of the components αc which separates two qualitatively diferent regimes of the system: below αc the burst size distribution is a power law with the usual exponent Ƭ= 5/2, while above αc the exponent switches to a lower value Ƭ = 9/4 and a cutoff function occurs with a diverging characteristic size. Analyzing the macroscopic response of the system we demonstrate that the transition is conditioned to disorder distributions where the constitutive curve has a single maximum and an inflexion point defining a novel universality class of breakdown phenomena

Avalanche dynamics of fiber bundle models

We present a detailed analytical and numerical study of the avalanche distributions of the continuous damage fiber bundle model CDFBM . Linearly elastic fibers undergo a series of partial failure events which give rise to a gradual degradation of their stiffness. We show that the model reproduces a wide range of mechanical behaviors. We find that macroscopic hardening and plastic responses are characterized by avalanche distributions, which exhibit an algebraic decay with exponents between 5/2 and 2 different from those observed in mean-field fiber bundle models. We also derive analytically the phase diagram of a family of CDFBM which covers a large variety of potential avalanche size distributions. Our results provide a unified view of the statistics of breaking avalanches in fiber bundle models

Impairment of mossy fiber long-term potentiation and associative learning in pituitary adenylate cyclase activating polypeptide type I receptor-deficient Mice

The pituitary adenylate cyclase activating polypeptide (PACAP) type I receptor (PAC1) is a G-protein-coupled receptor binding the strongly conserved neuropeptide PACAP with 1000-fold higher affinity than the related peptide vasoactive intestinal peptide. PAC1-mediated signaling has been implicated in neuronal differentiation and synaptic plasticity. To gain further insight into the biological significance of PAC1-mediated signaling in vivo, we generated two different mutant mouse strains, harboring either a complete or a forebrain-specific inactivation of PAC1. Mutants from both strains show a deficit in contextual fear conditioning, a hippocampus-dependent associative learning paradigm. In sharp contrast, amygdala-dependent cued fear conditioning remains intact. Interestingly, no deficits in other hippocampus-dependent tasks modeling declarative learning such as the Morris water maze or the social transmission of food preference are observed. At the cellular level, the deficit in hippocampus-dependent associative learning is accompanied by an impairment of mossy fiber long-term potentiation (LTP). Because the hippocampal expression of PAC1 is restricted to mossy fiber terminals, we conclude that presynaptic PAC1-mediated signaling at the mossy fiber synapse is involved in both LTP and hippocampus-dependent associative learning.