Cellulose based materials to accelerate the transition towards sustainability

Several significant sectors use cellulose, including paper manufacturing, cellophane, textiles (including rayon and viscose), and food and medicine additives. It can be utilised as a raw materials in production of fuel sources like cellulosic ethanol. Crystalline cellulose possesses a tensile strength of about 7.5 GPa, Young’s modulus of 110-220 GPa and as the most abundantly available natural polymer, with excellent biocompatibility, good degradation and regeneration properties, it is considered as a remarkable biomaterial. Cellulose-based materials can be fabricated with tuneable magnetic properties, electrical conductivity, photosensitivity, sensing abilities, catalytic activity, and other specific properties by incorporating nanoparticles. These qualities make cellulose a sustainable multifunctional material. To harness such properties, strenuous efforts are being made to manufacture cellulose based materials through a wide number of manufacturing processes. This review provides an overview of the current readiness in producing cellulose-based functional materials by surveying the manufacturing procedures, characteristics and their potential applications for the end users. Future directions and opportunities of work are suggested and the limitations inherent with every process and the challenges that needs to be overcome in scalable manufacturing of cellulose-based materials are also discussed

Monthly average daily global and diffuse solar radiation based on sunshine duration and clearness index for Brasov, Romania

The main objective of this study is to develop single location appropriate models for the estimation of the monthly average daily global and diffuse horizontal solar radiation for Brasov, Romania. The study focuses particularly on models based on the sunshine duration and clearness index. The data used for the calibration of the models were collected during a period of 4 yr, between November 2008 and October 2012, at the Transilvania University of Brasov. The testing and validation of the models was carried out using data from the online SoDa database for Brasov for the year 2005. Different statistical error tests were applied to evaluate the accuracy of the models. The predicted values are also compared with values from three other known models concerning the global and diffuse solar radiation. A new mixed model was developed for the estimation of monthly average daily global horizontal solar radiation. The data processing was performed by means of a real-time interface developed with LabVIEW graphical programming language. The parameters taken into account were the relative sunshine, the clearness index, the extraterrestrial radiation, the latitude and the longitude. The methodology is simple and effective and may be applied for any region. Its effectiveness was proven through comparison with global models

Optical extinction in a single layer of nanorods

We demonstrate that almost 100 % of incident photons can interact with a monolayer of scatterers in a symmetrical environment. Nearly-perfect optical extinction through free-standing transparent nanorod arrays has been measured. The sharp spectral opacity window, in the form of a characteristic Fano resonance, arises from the coherent multiple scattering in the array. In addition, we show that nanorods made of absorbing material exhibit a 25-fold absorption enhancement per unit volume compared to unstructured thin film. These results open new perspectives for light management in high-Q, low volume dielectric nanostructures, with potential applications in optical systems, spectroscopy, and optomechanics

HLA, infections and inflammation in early stages of atherosclerosis in children with type 1 diabetes

This prospective study focuses on risk factors for arterial damage in children with type 1 diabetes (T1D). Eighty children and adolescents with T1D were investigated twice, approximately 2 years apart, for carotid artery intima-media thickness (cIMT) and compliance (CAC), flow-mediated dilatation (FMD) of the brachial artery, and plasma levels of matrix metalloproteinase (MMP)-8. All subjects were genotyped for HLA. The number of respiratory tract infections (RTI) during the past year was obtained by a questionnaire in 56 patients. cIMT progression, defined as percentage (%) change of cIMT from baseline, correlated inversely with the % changes of both CAC (p = 0.04, r = - 0.3; n = 62) and FMD (p = 0.03, r = - 0.3; n = 47). In multivariate analysis, RTI frequency correlated significantly with cIMT progression irrespective of age, diabetes duration, BMI, and HbA1c (p = 0.03, r = 0.3). When patients were divided in relation to RTI, the association of DQ2/8 with cIMT progression remained significant in patients with over three infections/year (p = 0.04, r = 0.3). During follow-up, the group of DQ2/8 patients with hsCRP > 1 mg/l showed significantly higher levels of plasma MMP-8 than the non-DQ2/8 group. The diabetes-risk genotype DQ2/8 and systemic inflammation contribute to pro-atherosclerotic vascular changes in children and adolescents with T1D.Peer reviewe

Schedulability-Driven Frame Packing for Multi-Cluster Distributed Embedded Systems

We present an approach to frame packing for multi-cluster distributed embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. In our approach, the application messages are packed into frames such that the application is schedulable. Thus, we have also proposed a schedulability analysis for applications consisting of mixed event-triggered and time-triggered processes and messages, and a worst case queuing delay analysis for the gateways, responsible for routing inter-cluster traffic. Optimization heuristics for frame packing aiming at producing a schedulable system have been proposed. Extensive experiments and a real-life example show the efficiency of our frame-packing approach

Equation of motion approach to the solution of Anderson model

Based on an equation of motion approach the single impurity Anderson model(SIAM) is reexamined. Using the cluster expansions the equations of motion of Green functions are transformed into the corresponding equations of motion of connected Green functions, which provides a natural and uniform truncation scheme. A factor of two missing in the Lacroix's approximation for the Kondo temperature is gained in the next higher order truncation beyond Lacroix's. A quantitative improvement in the density of states at the Fermi level is also obtained.Comment: 4 pages, 2 figure

Content aware multi-focus image fusion for high-magnification blood film microscopy

Automated digital high-magnification optical microscopy is key to accelerating biology research and improving pathology clinical pathways. High magnification objectives with large numerical apertures are usually preferred to resolve the fine structural details of biological samples, but they have a very limited depth-of-field. Depending on the thickness of the sample, analysis of specimens typically requires the acquisition of multiple images at different focal planes for each field-of-view, followed by the fusion of these planes into an extended depth-of-field image. This translates into low scanning speeds, increased storage space, and processing time not suitable for high-throughput clinical use. We introduce a novel content-aware multi-focus image fusion approach based on deep learning which extends the depth-of-field of high magnification objectives effectively. We demonstrate the method with three examples, showing that highly accurate, detailed, extended depth of field images can be obtained at a lower axial sampling rate, using 2-fold fewer focal planes than normally required

Detection of acute promyelocytic leukemia in peripheral blood and bone marrow with annotation-free deep learning

While optical microscopy inspection of blood films and bone marrow aspirates by a hematologist is a crucial step in establishing diagnosis of acute leukemia, especially in low-resource settings where other diagnostic modalities are not available, the task remains time-consuming and prone to human inconsistencies. This has an impact especially in cases of Acute Promyelocytic Leukemia (APL) that require urgent treatment. Integration of automated computational hematopathology into clinical workflows can improve the throughput of these services and reduce cognitive human error. However, a major bottleneck in deploying such systems is a lack of sufficient cell morphological object-labels annotations to train deep learning models. We overcome this by leveraging patient diagnostic labels to train weakly-supervised models that detect different types of acute leukemia. We introduce a deep learning approach, Multiple Instance Learning for Leukocyte Identification (MILLIE), able to perform automated reliable analysis of blood films with minimal supervision. Without being trained to classify individual cells, MILLIE differentiates between acute lymphoblastic and myeloblastic leukemia in blood films. More importantly, MILLIE detects APL in blood films (AUC 0.94 ± 0.04) and in bone marrow aspirates (AUC 0.99 ± 0.01). MILLIE is a viable solution to augment the throughput of clinical pathways that require assessment of blood film microscopy

Eliashberg-type equations for correlated superconductors

The derivation of the Eliashberg -- type equations for a superconductor with strong correlations and electron--phonon interaction has been presented. The proper account of short range Coulomb interactions results in a strongly anisotropic equations. Possible symmetries of the order parameter include s, p and d wave. We found the carrier concentration dependence of the coupling constants corresponding to these symmetries. At low hole doping the d-wave component is the largest one.Comment: RevTeX, 18 pages, 5 ps figures added at the end of source file, to be published in Phys.Rev. B, contact: [email protected]