Post-deposition treatment effects on hydroxyapatite vacuum plasma spray coatings

The purpose of this work is to evaluate the effects of post-deposition heat treatments on high and low crystallinity hydroxyapatite coatings on Ti6Al4V alloy. HA layers were produced by the vacuum plasma spray (VPS) technique, and the desired degrees of crystallinity were obtained by changing the deposition parameters. An analysis of the mechanical properties of the coatings and their adhesion to the substrate has been done by shear strength test. X-ray diffraction analysis was used to detect the structure and the chemical components in which HA dissociates during the deposition process and heat treatments. The data obtained indicates that heat treatments can increase the crystallinity of HA, but they also introduce a mechanical degradation of the coatings. After heat treatments, it was also observed that a large amount of tetracalcium phosphate was formed.     

The role of squamous cell carcinoma antigen in the management of laryngeal and hypopharyngeal cancer

BACKGROUND: The efficacy of squamous cell carcinoma antigen (SCC-Ag) in laryngeal cancer to predict those patients who will relapse after primary treatment (surgery or radiotherapy) and its utility to detect relapses early and thereby increase salvage rates and cure were assessed. METHODS: Sixty healthy donors and 168 patients with laryngeal cancer were included in this prospective trial. Squamous cell carcinoma antigen was measured at diagnosis in all patients, 24 hours and 1 week after surgery in 113 patients and every 10 Gy of administered dose and 2 weeks after treatment in 49 patients primarily referred to radiotherapy. The marker was determined every 3-6 months during follow-up. All patients who relapsed had SCC-Ag studies before and after salvage treatment. RESULTS: The selected cut-off value was 1.5 ngr/ml (mean value in control group, 0.65 + 2 standard deviation [0.38]). Seventy-eight percent of patients with cancer had elevated SCC-Ag values at diagnosis. Squamous cell carcinoma antigen was statistically related to TNM categories (T, P < 0.04; N, P < 0.05; Stage, P < 0.01). Seventy-five percent of those patients with previously elevated pretreatment values normalized after treatment. Incomplete surgical resection (P < 0.0001) or persistence of the disease after radiotherapy (P < 0.01) were related to high posttreatment values. Squamous cell carcinoma antigen was elevated in 88% of the patients who relapsed. In 55% of the recurrences, SCC-Ag was elevated 3 months before pathologic confirmation of relapse. Salvage by surgery or radiotherapy was effective in 70% of the patients. Squamous cell carcinoma antigen posttreatment values were the most important factor in predicting disease free survival (DFS) (P < 0.0001) and overall survival (P < 0.03). CONCLUSIONS: Squamous cell carcinoma antigen is an excellent marker of residual disease after primary treatment that can lead to the addition of other therapeutic procedures (surgery and postoperative radiotherapy). The absence of posttreatment SCC-Ag is the best predictor of DFS, its presence detects recurrence in early stages, permitting salvage of an increased proportion of patients primarily referred for palliative treatment.     

Domain-specific discrete event modelling and simulation using graph transformation

Graph transformation is being increasingly used to express the semantics of domain-specific visual languages since its graphical nature makes rules intuitive. However, many application domains require an explicit handling of time to accurately represent the behaviour of a real system and to obtain useful simulation metrics to measure throughputs, utilization times and average delays. Inspired by the vast knowledge and experience accumulated by the discrete event simulation community, we propose a novel way of adding explicit time to graph transformation rules. In particular, we take the event scheduling discrete simulation world view and provide rules with the ability to schedule the occurrence of other rules in the future. Hence, our work combines standard, efficient techniques for discrete event simulation (based on the handling of a future event set) and the intuitive, visual nature of graph transformation. Moreover, we show how our formalism can be used to give semantics to other timed approaches and provide an implementation on top of the rewriting logic system Maude.     

Smooth Loops from Unconstrained Video

Converting unconstrained video sequences into videos that loop seamlessly is an extremely challenging problem. In this work, we take the first steps towards automating this process by focusing on an important subclass of videos containing a single dominant foreground object. Our technique makes two novel contributions over previous work: first, we propose a correspondence‐based similarity metric to automatically identify a good transition point in the video where the appearance and dynamics of the foreground are most consistent. Second, we develop a technique that aligns both the foreground and background about this transition point using a combination of global camera path planning and patch‐based video morphing. We demonstrate that this allows us to create natural, compelling, loopy videos from a wide range of videos collected from the internet.     

Two-space variability compensation technique for speaker verification in short length and reverberant environments

The performance of state-of-the-art speaker verification in uncontrolled environment is affected by different variabilities. Short duration variability is very common in these scenarios and causes the speaker verification performance to decrease quickly while the duration of verification utterances decreases. Linear discriminant analysis (LDA) is the most common session variability compensation algorithm, nevertheless it presents some shortcomings when trained with insufficient data. In this paper we introduce two methods for session variability compensation to deal with short-length utterances on i-vector space. The first method proposes to incorporate the short duration variability information in the within-class variance estimation process. The second proposes to compensate the session and short duration variabilities in two different spaces with LDA algorithms (2S-LDA). First, we analyzed the behavior of the within and between class scatters in the first proposed method. Then, both proposed methods are evaluated on telephone session from NIST SRE-08 for different duration of the evaluation utterances: full (average 2.5 min), 20, 15, 10 and 5 s. The 2S-LDA method obtains good results on different short-length utterances conditions in the evaluations, with a EER relative average improvement of 1.58%, compared to the best baseline (WCCN[LDA]). Finally, we applied the 2S-LDA method in speaker verification under reverberant environment, using different reverberant conditions from Reverb challenge 2013, obtaining an improvement of 8.96 and 23% under matched and mismatched reverberant conditions, respectively.     

Estimation of predictive accuracy in survival analysis using R and S-PLUS

When the purpose of a survival regression model is to predict future outcomes, the predictive accuracy of the model needs to be evaluated before practical application. Various measures of predictive accuracy have been proposed for survival data, none of which has been adopted as a standard, and their inclusion in statistical software is disregarded. We developed the surev library for R and S-PLUS, which includes functions for evaluating the predictive accuracy measures proposed by Schemper and Henderson. The library evaluates the predictive accuracy of parametric regression models and of Cox models. The predictive accuracy of the Cox model can be obtained also when time-dependent covariates are included because of non-proportional hazards or when using Bayesian model averaging. The use of the library is illustrated with examples based on a real data set.     

Meta-modelling and graph grammars for multi-paradigm modelling in AToM<Superscript>3</Superscript>

This paper presents the combined use of meta-modelling and graph grammars for the generation of visual modelling tools for simulation formalisms. In meta-modelling, formalisms are described at a meta-level. This information is used by a meta-model processor to generate modelling tools for the described formalisms. We combine meta-modelling with graph grammars to extend the model manipulation capabilities of the generated modelling tools: edit, simulate, transform into another formalism, optimize and generate code. We store all (meta-)models as graphs, and thus, express model manipulations as graph grammars.We present the design and implementation of these concepts in AToM³ (A_To_ol for M_ulti-formalism, M_eta-M_odelling). AToM³ supports modelling of complex systems using different formalisms, all meta-modelled in their own right. Models in different formalisms may be transformed into a single common formalism for further processing. These transformations are specified by graph grammars. Mosterman and Vangheluwe [18] introduced the term multi-paradigm modelling to denote the combination of multiple formalisms, multiple abstraction levels, and meta-modelling. As an example of multi-paradigm modelling we present a meta-model for the Object-Oriented Continuous Simulation Language OOCSMP, in which we combine ideas from UML class diagrams (to express the OOCSMP model structure), Causal Block Diagrams (CBDs), and Statecharts (to specify the methods of the OOCSMP classes). A graph grammar is able to generate OOCSMP code, and then a compiler for this language (C-OOL) generates Java applets for the simulation execution.     

Inhibitors of Mitochondrial Human Carbonic Anhydrases VA and VB as a Therapeutic Strategy against Paclitaxel-Induced Neuropathic Pain in Mice

Neuropathy development is a major dose-limiting side effect of anticancer treatments that significantly reduces patient’s quality of life. The inadequate pharmacological approaches for neuropathic pain management warrant the identification of novel therapeutic targets. Mitochondrial dysfunctions that lead to reactive oxygen species (ROS) increase, cytosolic Ca²⁺ imbalance, and lactate acidosis are implicated in neuropathic pain pathogenesis. It has been observed that in these deregulations, a pivotal role is played by the mitochondrial carbonic anhydrases (CA) VA and VB isoforms. Hence, preclinical studies should be conducted to assess the efficacy of two novel selenides bearing benzenesulfonamide moieties, named 5b and 5d, and able to inhibit CA VA and VB against paclitaxel-induced neurotoxicity in mice. Acute treatment with 5b and 5d (30–100 mg/kg, per os – p.o.) determined a dose-dependent and long-lasting anti-hyperalgesic effect in the Cold plate test. Further, repeated daily treatment for 15 days with 100 mg/kg of both compounds (starting the first day of paclitaxel injection) significantly prevented neuropathic pain development without the onset of tolerance to the anti-hyperalgesic effect. In both experiments, acetazolamide (AAZ, 100 mg/kg, p.o.) used as the reference drug was partially active. Moreover, ex vivo analysis demonstrated the efficacy of 5b and 5d repeated treatments in reducing the maladaptive plasticity that occurs to glia cells in the lumbar portion of the spinal cord and in improving mitochondrial functions in the brain and spinal cord that were strongly impaired by paclitaxel-repeated treatment. In this regard, 5b and 5d ameliorated the metabolic activity, as observed by the increase in citrate synthase activity, and preserved an optimal mitochondrial membrane potential (ΔΨ) value, which appeared depolarized in brains from paclitaxel-treated animals. In conclusion, 5b and 5d have therapeutic and protective effects against paclitaxel-induced neuropathy without tolerance development. Moreover, 5b and 5d reduced glial cell activation and mitochondrial dysfunction in the central nervous system, being a promising candidate for the management of neuropathic pain and neurotoxicity evoked by chemotherapeutic drugs.