Miracle-dz/UniFAR-FTUs huggingface dataset:
Additive Manufacturing of Soft Polysiloxane-based Bio-structures with Heterogeneous Properties

This thesis is concerned with the development of novel additive manufacturing (AM) systems and methodologies for high speed fabrication of complex material-graded silicone structures with controllable internal features consistently. To this end, two AM systems were developed, each pertaining to a specific phase of silicone rubber. The first system integrates material extrusion and material jetting AM systems. This system is designed to process the paste-like silicone rubbers at high viscosity levels (> 400,000mPa.s at 10 s−1). In this system, the outer frame of each layer is made by extruding a highly uniform silicone strand at 5 mm/s printhead velocity. Once the perimeter is laid down on the substrate or the previous layer, a piezoelectric-based printhead with a translational speed of over 100 mm/s covers the internal section of layer by depositing uniform droplets of silicone at predefined locations. The printing parameters for both extrusion and jetting techniques were tuned using statistical optimization tools in order to minimize the surface waviness of printed parts. The optimized surface waviness values obtained are 8 μm and 3 μm for jetting and extrusion, respectively. Moreover, parts with solid density of over 99% and mechanical performance similar to the bulk material were manufactured by tailoring the rheology of silicone ink. A combination of powder-bed binder-jetting (PBBJ) system and micro-dispensing material extrusion form the second hybrid AM system. The three-dimensional (3D) shape forming of silicone powder is made possible for the first time using this system. The tomography results for the fabricated parts reveal a porous structure (∼ 8% porosity). This AM process is introduced as a the proof-of-concept. The porosity of structures can be tuned by improving the silicone binder delivery method so that binder droplets with pico-liter volumes can be dispensed. The characterization techniques used for materials and additively manufactured parts include confocal-laser profilometry for investigating the surface quality of printed parts, differential scanning calorimetry (DSC) for investigating the curing mechanism of heatcurable silicone inks, Fourier transform infrared (FTIR) spectroscopy for controlling the curing kinetics and surface cohesion of UV-curable silicones, dynamic mechanical analysis (DMA) tests for tuning the rheological properties of silicone inks under different shear stresses, rheometry for establishing the viscosity threshold for jetting of silicone inks at different temperatures, scanning electron microscopy (SEM), particle size analysis, and powder rheometry for establishing guidelines for the size, shape, cohesiveness, flow, and shear stress resistance of silicone powders, uniaxial tensile test, tearing test, and durometry for identifying the mechanical characteristics of 3D printed parts, and computed-tomography (CT) scanning for quantifying the porosity of parts.
Prospective real‐time correction for arbitrary head motion using active markers

Patient motion during an MRI exam can result in major degradation of image quality, and is of increasing concern due to the aging population and its associated diseases. This work presents a general strategy for real‐time, intraimage compensation of rigid‐body motion that is compatible with multiple imaging sequences. Image quality improvements are established for structural brain MRI acquired during volunteer motion. A headband integrated with three active markers is secured to the forehead. Prospective correction is achieved by interleaving a rapid track‐and‐update module into the imaging sequence. For every repetition of this module, a short tracking pulse‐sequence remeasures the marker positions; during head motion, the rigid‐body transformation that realigns the markers to their initial positions is fed back to adaptively update the image‐plane—maintaining it at a fixed orientation relative to the head—before the next imaging segment of k‐space is acquired. In cases of extreme motion, corrupted lines of k‐space are rejected and reacquired with the updated geometry. High‐precision tracking measurements (0.01 mm) and corrections are accomplished in a temporal resolution (37 ms) suitable for real‐time application. The correction package requires minimal additional hardware and is fully integrated into the standard user interface, promoting transferability to clinical practice. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.
Infrared and Raman Spectroscopic Studies of Optically Transparent Zirconia (ZrO2) Films Deposited by Plasma-Assisted Reactive Pulsed Laser Deposition

Plasma-assisted pulsed laser deposited zirconia (ZrO2) films were studied by Fourier transform infrared (FT-IR) and Raman spectroscopy for structural characterization and thermal stability in combination with optical characterization by spectroscopic ellipsometry and optical transmission measurements. Only the monoclinic ZrO2 phase was positively identified from the infrared and Raman spectra of the as-deposited ZrO2 films, which show excellent optical transparency from the ultraviolet to the near infrared as revealed by optical characterization. The as-deposited ZrO2 films are free of any SiOx interfacial layer when deposited on silicon. The prepared ZrO2 films exhibit good thermal stability in their structural, optical, and interfacial properties up to 900 °C. Upon annealing above 1100 °C, a silicon oxide interfacial layer forms due to the oxidation of the silicon substrate surface by the oxygen diffused from the oxide film to the silicon substrate at high temperatures.
Pathogenicity of four blue-stain fungi associated with aggressive and nonaggressive bark beetles.

ABSTRACT The pathogenicity of two isolates of each of four bark beetle-associated blue-stain fungi was evaluated after mass inoculation of about 40-year-old Norway spruce trees (Picea abies). Trees were inoculated with a different isolate of each fungus in 1995 and 1996 at a density of 400 inoculations per m(2) in a 1.2-m-wide band on the lower bole (about 270 inoculations per tree). Trees were felled 15 weeks after inoculation. In 1995, Ceratocystis polonica was the only fungus that had stained the sapwood (56.3% of cross-sectional sapwood area). It induced five times longer phloem necroses, 21 times more dead cambium, and 11 times more dead phloem than any other fungus. In 1996, C. polonica induced less extensive host symptoms and an unidentified Ambrosiella sp. induced comparable symptoms to C. polonica in the phloem and cambium. No trees showed any foliar symptoms 15 weeks after inoculation, but six out of eight trees inoculated with C. polonica in 1995 had only 0 to 25% functional sapwood and probably would have died if felling had been delayed. This study confirms that C. polonica, an associate of the aggressive bark beetle Ips typographus, is pathogenic to Norway spruce. The pathogenicity of the Ambrosiella sp. , which is associated with a nonaggressive bark beetle, seems moderate and varies between isolates. The two remaining fungi included in this study (Ophiostoma piceae and a dark fungus with sterile mycelium), which are associated with nonaggressive bark beetles, were nonpathogenic in both experiments. These results are consistent with the hypothesis that aggressive bark beetle species vector virulent fungi that may help them kill trees, but the results also show that some nonaggressive bark beetles may vector phytopathogenic fungi.
A Matrix Factorization Approach for Learning Semidefinite-Representable Regularizers

Regularization techniques are widely employed in optimization-based approaches for solving ill-posed inverse problems in data analysis and scientific computing. These methods are based on augmenting the objective with a penalty function, which is specified based on prior domain-specific expertise to induce a desired structure in the solution. We consider the problem of learning suitable regularization functions from data in settings in which precise domain knowledge is not directly available. Previous work under the title of `dictionary learning' or `sparse coding' may be viewed as learning a regularization function that can be computed via linear programming. We describe generalizations of these methods to learn regularizers that can be computed and optimized via semidefinite programming. Our framework for learning such semidefinite regularizers is based on obtaining structured factorizations of data matrices, and our algorithmic approach for computing these factorizations combines recent techniques for rank minimization problems along with an operator analog of Sinkhorn scaling. Under suitable conditions on the input data, our algorithm provides a locally linearly convergent method for identifying the correct regularizer that promotes the type of structure contained in the data. Our analysis is based on the stability properties of Operator Sinkhorn scaling and their relation to geometric aspects of determinantal varieties (in particular tangent spaces with respect to these varieties). The regularizers obtained using our framework can be employed effectively in semidefinite programming relaxations for solving inverse problems.
Remote cognitive assessments for patients with multiple sclerosis: a feasibility study

Background: measuring cognitive function in patients with multiple sclerosis (MS) can be challenging given the obstacles faced when traveling to testing centers. Objective: the purpose of this study was to evaluate the feasibility of remote cognitive assessment in patients with MS using the automated neuropsychological assessment metrics (ANAM–MS) and the symbol digit modalities test (SDMT). Methods: patients meeting the McDonald criteria for MS (n = 24) were randomized to complete the live-in-office condition or a remote-in-office condition first, with all patients completing both sessions. Patients (n = 20) then completed a final remote-in-home testing session. Both remote sessions were proctored by a psychologist using a secure telehealth connection. Results: scores on the live SDMT differed from scores in the two remote settings F(2, 38) = 4.46, p = 0.018. However, summary scores on the ANAM–MS were similar across the three settings, F(2, 36) = 2.21, p = 0.124. Satisfaction with telehealth testing was high on the part of the examiner and patients. Each telehealth testing session saved more than $144.00 in travel costs and lost wages. Conclusion: this study demonstrated that valid results can be obtained when evaluating patients remotely using ANAM–MS. Some differences were noted for the SDMT that suggest that either specific norms or a different implementation approach may be needed for telehealth.
Complications following Incident Stroke Resulting in Readmissions: An Analysis of Data from Three Scottish Health Surveys

Background and aims Stroke is widely recognized as the major contributor to morbidity and mortality in the United Kingdom. We analyzed the data obtained from the three consecutive Scottish Health Surveys and the Scottish Morbidity records, with the aim of identifying risk factors for, and timing of, common poststroke complications. Methods There were 19434 individuals sampled during three Scottish Health Surveys in 1995, 1998, and 2001. For these individuals their morbidity and mortality outcomes were obtained in 2007. Incident stroke prevalence, risk factors for a range of poststroke complications, and average times until such complications in the sample were established. Results Of the total of 168 incident stroke admissions (0·86% of the survey), 16·1% people died during incident stroke hospitalization. Of the remaining 141 stroke survivors, 75·2% were rehospitalized at least once. The most frequent reason for readmission after stroke was a cardiovascular complication (28·6%), median time until event 1412 days, followed by infection (17·3%, median 1591 days). The risk of cardiovascular readmission was higher in those with ‘poor’ self-assessed health (odds ratio 7·70; 95% confidence interval 1·64–43·27), smokers (odds ratio 4·24; 95% confidence interval 1·11–21·59), and doubled with every five years increase in age (odds ratio 1·97; 95% confidence interval 1·46–2·65). ‘Poor’ self-assessed health increased chance of readmission for infection (odds ratio 14·11; 95% confidence interval 2·27–276·56). Conclusions Cardiovascular events and infections are the most frequent poststroke complications resulting in readmissions. The time period until event provides a possibility to focus monitoring on those people at risk of readmission and introduce preventative measures, thereby reducing readmission-associated costs.
Filling the gap between Software Defined Networking and Wireless Mesh Networks

Software Defined Networking (SDN) has emerged as a new paradigm that highly increase the network management flexibility through simple but powerful abstractions. The key idea is decoupling the control plane, which makes the forward decisions, from the data plane, which effectively makes the forward. However, the OpenFlow, the main SDN enabler, is designed mainly by wired networks characteristics. As consequence, Wireless Mesh Networks (WMNs) is not suitable for operating as control plane and many wireless networks features are neglected in the OpenFlow, e.g.: power control and network ID. In addition, there are few effort research to extend SDN to wireless networks and these existing works focus on very specific issues of this integration. In this paper, we propose an architecture to extent the OpenFlow functionalities in order to proper deal with wireless networks, including an approach for transporting the control plane over wireless multihop networks. The extensions include new rules, actions, and commands, which bring the network management flexibility to the wireless context. We validated our proposal by implementing and testing some extensions in a small real world testbed. As a proof of concept, we illustrate the OpenFlow capability of isolation between research and production traffics in a wireless backhaul.
Fractured Neck of Femur in the Mobile Independent Elderly Patient: Should We Treat with Total Hip Replacement?

Purpose. To report the outcome of displaced subcapital neck of femur fractures in the independent elderly (>70 years) managed with total hip arthroplasty through a modified Hardinge approach. Methods. Between 1998 and 2000, a surgeon performed a cemented hip replacement using a modified lateral approach in 35 consecutive patients in the Hawke's Bay Regional Hospital, Hastings. Medical charts and out-patient follow-up clinic records were reviewed with respect to outcomes, with particular reference to complications. Independent review of functional outcome was completed at one year postsurgery using a questionnaire. Results. At an average follow-up of 1.8 years (range, 1–3 years), no patient needed further surgery. One patient had died, giving a mortality rate at one year of 2.9%. All other medical complications were successfully treated. The overall prevalence of early medical complications was 43%. There were no dislocations, and 80% of patients had a good clinical outcome at their latest follow-up. Conclusion. The modified lateral approach of Hardinge minimises the incidence of postoperative dislocation. However, there was a high incidence of medical complications and aggressive treatment of such complications was necessary, both preoperatively and postoperatively. The number of pre-existing medical conditions was a significant factor influencing patient morbidity.
Short-pulse intracavity Raman laser.

We propose a new method for producing intense short laser pulses by using an intracavity Raman laser in an interlocking ring configuration with copropagating unidirectional pump and Stokes pulses. The temporal duration of the Raman output pulses is given by the difference between the round-trip times of the two cavities and therefore can be easily controlled and varied continuously. A theoretical model is described, and an analytic solution is presented.
Scaffold number in yeast signaling system sets tradeoff between system output and dynamic range

Although the proteins comprising many signaling systems are known, less is known about their numbers per cell. Existing measurements often vary by more than 10-fold. Here, we devised improved quantification methods to measure protein abundances in the Saccharomyces cerevisiae pheromone response pathway, an archetypical signaling system. These methods limited variation between independent measurements of protein abundance to a factor of two. We used these measurements together with quantitative models to identify and investigate behaviors of the pheromone response system sensitive to precise abundances. The difference between the maximum and basal signaling output (dynamic range) of the pheromone response MAPK cascade was strongly sensitive to the abundance of Ste5, the MAPK scaffold protein, and absolute system output depended on the amount of Fus3, the MAPK. Additional analysis and experiment suggest that scaffold abundance sets a tradeoff between maximum system output and system dynamic range, a prediction supported by recent experiments.
Accuracy of Premium Calculation Models for CAT Bonds - An Empirical Analysis

CAT bonds are of significant importance in the field of alternative risk transfer. Since the market of CAT bonds is not complete, the application of an appropriate pricing model is of high relevance. We apply different premium calculation models in order to compare them with regard to their predictive power. Without taking the financial crisis into account, a version of the Wang transformation model and the linear model are the most accurate ones. In contrast, under consideration of the financial crisis, all analyzed models are approximately equivalent. Furthermore, we find that CAT bond specific information does not improve out-of-sample results.
From proteome lists to biological impact– tools and strategies for the analysis of large MS data sets

MS has become a method‐of‐choice for proteome analysis, generating large data sets, which reflect proteome‐scale protein–protein interaction and PTM networks. However, while a rapid growth in large‐scale proteomics data can be observed, the sound biological interpretation of these results clearly lags behind. Therefore, combined efforts of bioinformaticians and biologists have been made to develop strategies and applications to help experimentalists perform this crucial task. This review presents an overview of currently available analytical strategies and tools to extract biologically relevant information from large protein lists. Moreover, we also present current research publications making use of these tools as examples of how the presented strategies may be incorporated into proteomic workflows. Emphasis is placed on the analysis of Gene Ontology terms, interaction networks, biological pathways and PTMs. In addition, topics including domain analysis and text mining are reviewed in the context of computational analysis of proteomic results. We expect that these types of analyses will significantly contribute to a deeper understanding of the role of individual proteins, protein networks and pathways in complex systems.
Case Studies of Knowledge Modeling for Knowledge Preservation and Sharing in the US Nuclear Power Industry

As populations age and large numbers of skilled workers progress toward retirement, the importance of preserving and sharing expert knowledge is becoming an increasing concern for organisations worldwide. This article contains descriptions of two case studies involving initiatives to elicit, preserve, and share expert knowledge in the nuclear power industry using a knowledge modeling toolkit named CmapTools and knowledge elicitation techniques that were originated at the Institute for Human and Machine Cognition, Pensacola, FL. , USA. Along with an account of preparations for the work including the selection of the experts, the course of the sessions, results and impacts of the studies, missed opportunities, and lessons learned are described. Some similarities and some interesting differences between the case studies are discussed.
Implementation of an Algorithm for Prosthetic Joint Infection : Deviations and Problems

Background: The outcome of revision surgery in arthroplasty is based on a precise diagnosis. In addition, the treatment varies based on whether the prosthetic failure is caused by aseptic or septic loosening. Algorithms can help to identify periprosthetic joint infections (PJI) and standardize diagnostic steps, however, algorithms tend to oversimplify the treatment of complex cases. We conducted a process analysis during the implementation of a PJI algorithm to determine problems and deviations associated with the implementation of this algorithm. Patients and Methods: Fifty patients who were treated after implementing a standardized algorithm were monitored retrospectively. Their treatment plans and diagnostic cascades were analyzed for deviations from the implemented algorithm. Each diagnostic procedure was recorded, compared with the algorithm, and evaluated statistically. Results: We detected 52 deviations while treating 50 patients. In 25 cases, no discrepancy was observed. Synovial fluid aspiration was not performed in 31.8% of patients (95% confidence interval [CI], 18.1%–45.6%), while white blood cell counts (WBCs) and neutrophil differentiation were assessed in 54.5% of patients (95% CI, 39.8%–69.3%). We also observed that the prolonged incubation of cultures was not requested in 13.6% of patients (95% CI, 3.5%–23.8%). In seven of 13 cases (63.6%; 95% CI, 35.2%–92.1%), arthroscopic biopsy was performed; 6 arthroscopies were performed in discordance with the algorithm (12%; 95% CI, 3%–21%). Conclusion: Self-critical analysis of diagnostic processes and monitoring of deviations using algorithms are important and could increase the quality of treatment by revealing recurring faults.
Meteorin Regulates Mesendoderm Development by Enhancing Nodal Expression

During gastrulation, distinct lineage specification into three germ layers, the mesoderm, endoderm and ectoderm, occurs through an elaborate harmony between signaling molecules along the embryonic proximo-distal and anterior-posterior axes, and Nodal signaling plays a key role in the early embryonic development governing embryonic axis formation, mesoderm and endoderm specification, and left-right asymmetry determination. However, the mechanism by which Nodal expression is regulated is largely unknown. Here, we show that Meteorin regulates Nodal expression and is required for mesendoderm development. It is highly expressed in the inner cell mass of blastocysts and further in the epiblast and extra-embryonic ectoderm during gastrulation. Genetic ablation of the Meteorin gene resulted in early embryonic lethality, presumably due to impaired lineage allocation and subsequent cell accumulation. Embryoid body culture using Meteorin-null embryonic stem (ES) cells showed reduced Nodal expression and concomitant impairment of mesendoderm specification. Meteorin-null embryos displayed reduced levels of Nodal transcripts before the gastrulation stage, and impaired expression of Goosecoid, a definitive endoderm marker, during gastrulation, while the proximo-distal and anterior-posterior axes and primitive streak formation were preserved. Our results show that Meteorin is a novel regulator of Nodal transcription and is required to maintain sufficient Nodal levels for endoderm formation, thereby providing new insights in the regulation of mesendoderm allocation.