Miracle-dz/UniFAR-FTUs huggingface dataset:
Fabrication and characterization of magnetoresponsive electrospun nanocomposite membranes based on methacrylic random copolymers and magnetite nanoparticles

Magnetoresponsive polymer-based fibrous nanocomposites belonging to the broad category of stimuli-responsive materials, is a relatively new class of "soft" composite materials, consisting of magnetic nanoparticles embedded within a polymeric fibrous matrix. The presence of an externally applied magnetic field influences the properties of these materials rendering them useful in numerous technological and biomedical applications including sensing,magnetic separation, catalysis and magnetic drug delivery. This study deals with the fabrication and characterization of magnetoresponsive nanocomposite fibrous membranes consisting of methacrylic random copolymers based on methyl methacrylate (MMA) and 2-(acetoacetoxy)ethyl methacrylate (AEMA) (MMAco-AEMA) and oleic acid-coated magnetite (OAċFe3O4) nanoparticles. The AEMA moieties containing β-ketoester side-chain functionalities were introduced for the first time in this type of materials, because of their inherent ability to bind effectively onto inorganic surfaces providing an improved stabilization. For membrane fabrication the electrospinning technique was employed and a series of nanocomposite membranes was prepared in which the polymer content was kept constant and only the inorganic (OAċFe3O4) content varied. Further to the characterization of these materials in regards to their morphology, composition and thermal properties, assessment of their magnetic characteristics disclosed tunable superparamagnetic behaviour at ambient temperature.
Fusogenic-Oligoarginine Peptide-Mediated Delivery of siRNAs Targeting the CIP2A Oncogene into Oral Cancer Cells

Despite a better understanding of the pathogenesis of oral cancer, its treatment outcome remains poor. Thus, there is a need for new therapeutic strategies to improve the prognosis of this disease. RNA interference (RNAi) appears to be a promising therapeutic tool for the treatment of many diseases, including oral cancer. However, an obstacle for RNAi-mediated therapies has been delivery, in particular, the retention of small interfering RNAs (siRNAs) in endosomes and their subsequent degradation in lysosomes, resulting in inefficient gene silencing. Thus, the current study examined the feasibility of designing and utilizing a peptide, termed 599, consisting of a synthetic influenza virus-derived endosome-disruptive fusogenic peptide sequence and a stretch of cationic cell-penetrating nona(D-arginine) residues, to deliver siRNAs into oral cancer cells and induce silencing of the therapeutic target, CIP2A, an oncoprotein overexpressed in various human malignancies including oral cancer. Increasing the 599 peptide-to-siRNA molar ratio demonstrated a higher binding capacity for siRNA molecules and enhanced siRNA delivery into the cytoplasm of oral cancer cells. In fact, quantitative measurements of siRNA delivery into cells demonstrated that a 50∶1 peptide-to-siRNA molar ratio could deliver 18-fold higher amounts of siRNAs compared to cells treated with siRNA alone with no significant long-term cytotoxic effects. Most importantly, the 599 peptide-mediated siRNA delivery promoted significant CIP2A mRNA and protein silencing which resulted in decreased oral cancer cell invasiveness and anchorage-independent growth. Together, these data demonstrate that a chimeric peptide consisting of a fusogenic sequence, in combination with cell-penetrating residues, can be used to effectively deliver siRNAs into oral cancer cells and induce the silencing of its target gene, potentially offering a new therapeutic strategy in combating oral cancer.
Design and fabrication of single- and coupled-cavity thin film structures for optical switching and regeneration

All-optical switching and regeneration based on optical Kerr effect are feasible in single and coupled-cavity thin film structures comprised of high-index and low-index materials. In this report we will present a simulated Kerr effect nonlinear function switching from low to high transmissions at telecom wavelength using an optimized coupled cavity structure. This nonlinear transfer function has multiple high transmission peaks suitable for all-optical switching and regeneration detection at high transmission state. Successful fabrication of single and coupled-cavity dielectric thin film structures for 800 nm were achieved with low refractive index (n=1.46) SiO2 and high refractive index (n=1.90) SiN by RF PVD. The simulated transmissions of the samples match almost exactly with the measured transmissions by VASE ellipsometer. The strategy of precision control of central wavelength of the resonant structure was implemented and good results were attained. The RMS surface roughness of RF sputtered and pulsed DC sputtered thin films are investigated by AFM. Suitability of nonlinear materials for ultrafast optical Kerr effect nonlinear refractions will be briefly discussed.
Deresination options in sulphite pulping

Three methods for improved deresination of sulphite pulps were evaluated, namely, alkaline washing, enzyme treatment, and pulp fractionation. Alkaline washing appears to come at a high cost, because caustic is expensive and affects cellulose chain length, as indicated by lower viscosity of the pulps. Thus this is not a viable option for pulps that are sensitive to changes in viscosity. Enzyme treatment did not completely degrade the glycerides under the mill conditions used. Fibre fractionation studies showed that the fines fractions contained 8 to 13 times more residual lipophilic extractives than the whole pulps. Removing this fraction, which represents only a small percentage of the whole pulp, could reduce by about a half the amount of lipophilic extractives in the remaining pulp. Thus pulp fractionation appears to be a viable option to achieve further deresination of sulphite pulps.
Decomposition of Gene Expression State Space Trajectories

Representing and analyzing complex networks remains a roadblock to creating dynamic network models of biological processes and pathways. The study of cell fate transitions can reveal much about the transcriptional regulatory programs that underlie these phenotypic changes and give rise to the coordinated patterns in expression changes that we observe. The application of gene expression state space trajectories to capture cell fate transitions at the genome-wide level is one approach currently used in the literature. In this paper, we analyze the gene expression dataset of Huang et al. (2005) which follows the differentiation of promyelocytes into neutrophil-like cells in the presence of inducers dimethyl sulfoxide and all-trans retinoic acid. Huang et al. (2005) build on the work of Kauffman (2004) who raised the attractor hypothesis, stating that cells exist in an expression landscape and their expression trajectories converge towards attractive sites in this landscape. We propose an alternative interpretation that explains this convergent behavior by recognizing that there are two types of processes participating in these cell fate transitions—core processes that include the specific differentiation pathways of promyelocytes to neutrophils, and transient processes that capture those pathways and responses specific to the inducer. Using functional enrichment analyses, specific biological examples and an analysis of the trajectories and their core and transient components we provide a validation of our hypothesis using the Huang et al. (2005) dataset.
Potential Effects of Aggressive Decongestion During the Treatment of Decompensated Heart Failure on Renal Function and Survival

Background— Overly aggressive diuresis leading to intravascular volume depletion has been proposed as a cause for worsening renal function during the treatment of decompensated heart failure. If diuresis occurs at a rate greater than extravascular fluid can refill the intravascular space, the concentration of such intravascular substances as hemoglobin and plasma proteins increases. We hypothesized that hemoconcentration would be associated with worsening renal function and possibly would provide insight into the relationship between aggressive decongestion and outcomes. Methods and Results— Subjects in the Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness trial limited data set with a baseline/discharge pair of hematocrit, albumin, or total protein values were included (336 patients). Baseline-to-discharge increases in these parameters were evaluated, and patients with ≥2 in the top tertile were considered to have evidence of hemoconcentration. The group experiencing hemoconcentration received higher doses of loop diuretics, lost more weight/fluid, and had greater reductions in filling pressures (P<0.05 for all). Hemoconcentration was strongly associated with worsening renal function (odds ratio, 5.3; P<0.001), whereas changes in right atrial pressure (P=0.36) and pulmonary capillary wedge pressure (P=0.53) were not. Patients with hemoconcentration had significantly lower 180-day mortality (hazard ratio, 0.31; P=0.013). This relationship persisted after adjustment for baseline characteristics (hazard ratio, 0.16; P=0.001). Conclusion— Hemoconcentration is significantly associated with measures of aggressive fluid removal and deterioration in renal function. Despite this relationship, hemoconcentration is associated with substantially improved survival. These observations raise the question of whether aggressive decongestion, even in the setting of worsening renal function, can positively affect survival.
Building extraction from digital elevation models

To extract buildings from digital elevation models, we define a point process whose points represent buildings. We then define a density for this point process which is split into two parts, consisting in an "internal field" that allows us to model the prior knowledge we have on patterns of buildings in urban areas and an "external field" that makes the point process fit the data. We then use a metropolis Hastings Green sampler coupled with a simulated annealing that gives the configuration of buildings minimizing the energy we have defined. We present results on real data provided by the French Mapping Institute (IGN).
Carbonated Apatite, Type-A or Type-B?

Carbonated apatite, the basic mineral component in human hard tissues and an important bioceramic material, has been extensively studied. However, its atomic arrangements in apatite crystal structure and its experimental characterization are still not lack of debating. We analyzed infrared (IR) vibrational spectroscopy for carbonated apatite determinations, by comparatively studying the IR spectra of hydroxyapatite and of surface carbonate absorption, biological apatites (human enamel, human cortical bone, and two animal bones) and carbonated apatite. The carbonated apatite samples were sythesized by various methods, including precipitation method, hydrothermal reaction and solid-gas reaction at high temperature. The comparative study indicates that the bands at ~880 cm-1, ~1413 cm-1, and ~1450 cm-1 should not be used to identify carbonated apatite since they may result from carbonate absorption on surfaces of apatite crystals or separated carbonate phase present with apatite crystals. The IR characteristic bands of carbonate substitution in apatites should be: ν3 at ~1465 cm-1 for type-B (CO3 substituting for PO4) and ν3 band at ~1546 cm-1 for type A (CO3 substituting for OH). These signature IR bands are further confirmed by the ab initio simulations.
Dryad: distributed data-parallel programs from sequential building blocks

Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. A Dryad application combines computational "vertices" with communication "channels" to form a dataflow graph. Dryad runs the application by executing the vertices of this graph on a set of available computers, communicating as appropriate through flies, TCP pipes, and shared-memory FIFOs. The vertices provided by the application developer are quite simple and are usually written as sequential programs with no thread creation or locking. Concurrency arises from Dryad scheduling vertices to run simultaneously on multiple computers, or on multiple CPU cores within a computer. The application can discover the size and placement of data at run time, and modify the graph as the computation progresses to make efficient use of the available resources. Dryad is designed to scale from powerful multi-core single computers, through small clusters of computers, to data centers with thousands of computers. The Dryad execution engine handles all the difficult problems of creating a large distributed, concurrent application: scheduling the use of computers and their CPUs, recovering from communication or computer failures, and transporting data between vertices.
A 25-GHz 9-dB distributed amplifier in CMOS technology

A common source single-ended distributed amplifier using 0.18-µm CMOS technology is presented in this paper. The four-stage DA demonstrates a relatively flat gain of 9.0 dB from 3.1GHz to 12.5GHz with less than 1.0dB ripple and a unity-gain bandwidth of 25.5GHz while the minimum value of noise figure is 3.6dB at 6.9GHz. Staggering technique is used to prevent instability. The proposed amplifier dissipates 158mW with a 1.8 V power supply.
Retrieving reusable software by sampling behavior

A new method, called behavior sampling, is proposed for automated retrieval of reusable components from software libraries. Behavior sampling exploits the property of software that distinguished it from other forms of test: executability. Basic behavior sampling identifies relevant routines by executing candidates on a searcher-supplied sample of operational inputs and by comparing their output to output provided by the searcher. The probabilistic basis for behavior sampling is described, and experimental results are reported that suggest that basic behavior sampling exhibits high precision when used with small samples. Extensions to basic behavior sampling are proposed to improve its recall and to make it applicable to the retrieval of abstract data types and object classes.
11C-Methionine PET of Myocardial Inflammation in a Rat Model of Experimental Autoimmune Myocarditis

Myocarditis represents a major cause of dilated cardiomyopathy and sudden cardiac death in younger adults. Currently, definitive diagnosis of myocarditis requires endomyocardial biopsy, which is highly invasive and has the drawback of variable sensitivity due to inherent sampling error. Therefore, reliable noninvasive methods to detect and monitor cardiac inflammation are clinically relevant. In this study, we explored the potential of radiolabeled methionine to assess myocardial inflammatory activity in a rat model of experimental autoimmune myocarditis (EAM). Methods: Autoimmune myocarditis was induced by immunizing Lewis rats twice with porcine cardiac myosin and Freund complete adjuvant. Control animals were treated with adjuvant alone. Dual-tracer autoradiography was performed to assess 14C-methionine uptake and to compare the distributions of 14C-methionine versus 18F-FDG. Hematoxylin and eosin staining and anti-CD68 macrophage staining were performed for histologic analysis. Additionally, cardiac 11C-methionine PET was performed to evaluate the feasibility of in vivo imaging. 18F-FDG PET was also conducted to compare the in vivo uptake of 11C-methionine and 18F-FDG. Results: Multiple focal cardiac inflammatory lesions were histologically identified in myosin-immunized rats, whereas no cardiac lesions were observed in the controls. Autoradiographic images clearly showed a high-density accumulation of 14C-methionine in inflammatory lesions of EAM rats, whereas no significant uptake was observed in the control animals. 14C-methionine uptake was significantly higher in inflammatory lesions than in remote noninflammatory areas and control rat hearts. The distribution of 14C-methionine correlated well with that of 18F-FDG and with macrophage density. The contrast between inflammatory and noninflammatory areas was higher for 18F-FDG than for 14C-methionine (3.45 ± 0.68 vs. 2.07 ± 0.21, respectively; P < 0.05). In the PET imaging study, the regional 11C-methionine uptake (percentage injected dose per cubic centimeter) observed in EAM rats was significantly higher than the values obtained for control animals (0.64 ± 0.09 vs. 0.28 ± 0.02, respectively; P < 0.001). A good positive correlation between 11C-methionine and 18F-FDG uptake was found. Conclusion: In a rat model of autoimmune myocarditis, we demonstrated the colocalization of radiolabeled methionine accumulation with 18F-FDG uptake in histologically proven inflammatory lesions. These data suggest that 11C-methionine might represent a promising candidate for the noninvasive detection and monitoring of myocarditis.
Physically based morphing of point‐sampled surfaces

This paper presents an innovative method for naturally and smoothly morphing point‐sampled surfaces via dynamic meshless simulation on point‐sampled surfaces. While most existing literature on shape morphing emphasizes the issue of finding a good correspondence map between two object representations, this research primarily investigates the challenging problem of how to find a smooth, physically‐meaningful transition path between two homeomorphic point‐set surfaces. We analyze the deformation of surface involved in the morphing process using concepts in differential geometry and continuum mechanics. The morphing paths can be determined by optimizing an energy functional, which characterizes the intrinsic deformation of the surface away from its rest shape. As demonstrated in the examples, our method automatically produces a series of natural and physically‐plausible in‐between shapes, which greatly alleviates the shrinking, stretching, and self‐intersection problems that often occur when linear interpolation is employed for the morphing of two objects. We envision that our new technique will continue to broaden the application scope of point‐set surfaces and their dynamic animation. Copyright © 2005 John Wiley & Sons, Ltd.
Conductive carbon nanotube thermosetting polyester nanocomposites

A commercial unsaturated polyester resin has been used in combination with commercial multiwalled carbon nanotubes (MWNTs) to study the effects of this nanofiller on the electrical properties of the mix in the liquid state, during the cure and in the solid state. The level of addition of the nanotubes ranged from 0.05 to 0.3 wt%. The dispersion of the filler particles in the matrix was carried out combining triple roll milling, horn sonication and high shear mixing. Qualitative optical and electronic microscopy characterisation supports the development of novel techniques for real-time quantitative assessments of dispersion quality. Fitting of shear dependent viscosity, measured between 0.1 and 100 s−1, to Carreau’s model has been shown to provide an indicator of the state of nanotube dispersion in the mixture. Additionally, liquid electrical conductivity measurements offer the option of on-line monitoring, providing a promising tool for process optimisation. The formation of an effective conductive network of nanotubes during the cure was investigated by combining impedance spectroscopy measurements and equivalent circuit modelling with two parallel RC circuit in series with each other. This allows in-situ observation of the key phenomenon responsible for the electrical conductivity of the nanocomposite, namely the filler re-aggregation during cure. Optimisation of dispersion and cure parameters results in a nanocomposite showing conductive behaviour in the solid state, achieving DC conductivity of 0.13 S/m at 0.30 wt% loading. The percolation threshold was estimated to occur at 0.026 wt% filler loading. The conductivity achieved is comparable to state-ofthe-art epoxy thermosetting nanocomposites based on use of carbon nanotubes of equivalent quality. Successful laboratory scale trials demonstrated the suitability of the materials in copper electroplating and resistance heating. An industrial scale up trial of a 40 kg batch was carried out, using the dispersion and the monitoring techniques developed in the study. I love fools’ experiments. I am always making them. CHARLES ROBERT DARWIN Acknowledgments I wish to thank my supervisors for their support and guidance: Dr. Alex Skordos for continuously fuel my enthusiasm and Prof. Ivana Partridge for teaching me how important it is to slow down and think, among other things. I am particularly grateful to Neil Gray and Dr. Gavin Creech at Scott Bader, to let me work with them instead of for them. They have been more than supportive and I hope I learnt something that will help me in my future career. Thanks also, in no particular order, to Silvia Marson, Mehdi Asareh, Christian Knipprath, Jim Hurley, Beth Costa, David Ayre, Usama Attia, Gary Muir, Johannes Treiber, Denis Cartie, Bojan Boskovic, Ben Hopper, Ippokratis Sitaras, Mar Salinas Ruiz, James Lander, Marco Longana, Sharon McGuire and all the people that helped me during my PhD. A special thanks to all the new friends that I made during my time in Cranfield, luckily they are too many to name them all! Thanks to Fra’, for everything.
Electric Load Forecasting Based on Locally Weighted Support Vector Regression

The forecasting of electricity demand has become one of the major research fields in electrical engineering. Accurately estimated forecasts are essential part of an efficient power system planning and operation. In this paper, a modified version of the support vector regression (SVR) is presented to solve the load forecasting problem. The proposed model is derived by modifying the risk function of the SVR algorithm with the use of locally weighted regression (LWR) while keeping the regularization term in its original form. In addition, the weighted distance algorithm based on the Mahalanobis distance for optimizing the weighting function's bandwidth is proposed to improve the accuracy of the algorithm. The performance of the new model is evaluated with two real-world datasets, and compared with the local SVR and some published models using the same datasets. The results show that the proposed model exhibits superior performance compare to that of LWR, local SVR, and other published models.