Prognosis of intravesical bacillus Calmette-Guerin therapy for superficial bladder cancer by immunological urinary measurements: statistically weighted syndrome analysis

PURPOSE: The goal of this research was to discover new biological indicators in urine which could be used for short-term prognosis of local Bacillus Calmette-Guerin (BCG) therapy outcome in patients with superficial bladder cancer. PATIENTS AND METHODS: We measured and statistically evaluated soluble immunological molecules in urine from bladder cancer patients (n = 34) receiving BCG intravesically. Urine was collected following each of 6 weekly treatments, processed and assayed. The data base included measurements of interleukin-1 (IL-2, IL-4, IL-6, IL-10, IL-12, soluble intercellular adhesion molecule-1 (sICAM-1), tumour necrosis factor-alpha (TNF alpha), soluble CD14 (sCD14), interferon-gamma (IFN gamma), GM-CSF, volume of urine and its pH. The clinical response was evaluated by urine histology and random quadrant biopsy 3 months after the start of therapy. Patients were divided into 2 groups, with good and poor therapeutic effect. The initial complete response rate was 62% (21/34). The data base was analyzed using traditional multivariate statistical methods and a pattern recognition method which deals with combinatorial-statistical analysis (statistically weighted syndromes (SWS) method) of the gradated features. The SWS method is capable of identifying robust patterns in small "fuzzy" sets with high dimensional objects and some missing values. RESULTS: Only one parameter gave significant differences at p < 0.05, GM-CSF at instillation 6. Repeated measurement analysis of variance, backward stepwise multiple logistic regression and linear discriminant analysis failed to show any significance. However, significant differences in the structure of correlation between features in the groups with and without therapeutic effect were observed and four highly informative variables (the masses of sICAM-1, TNF alpha, sCD14 and pH) relating to 5th-6th installations were selected by SWS. These features provided accurate individual prediction of therapeutic outcome for all our patients. Cross-validation analysis and computer simulation showed the statistically significant stability of the prediction. CONCLUSION: We have selected a set of urinary variables that could be considered as a perspective combination of indicators (syndromes) of outcome of pre-operation BCG therapy of patients with superficial bladder cancer. A larger patient database will provide testing and evaluation of the biological and clinical significance of selected features. The computational syndrome-disease approach should be applicable for the solution of decision-making problems for management of cancer.     

The role of the forestomachs in the adaptation of the alimentary function in ruminants

Dietary character of ruminants in the north is principally different between "nonselective" (cattle, sheep) and "selective" (reindeer, moose) species. Due to the developed polyfunctioning, forestomach in ruminants, primarily rumen and reticulum, are involved in the homeostasis formation in enteral and interior mediums, nutrients deposition and recirculation. That provides efficiency in utilization of deficient in nutrients forage and body reserves of wild ruminants during the winter. The original functional organization of absorption processes and nutrients recirculation across the multilayer epithelium of forestomach also promotes realization of the two levels metabolism during the year and adaptation of wild ruminants to season dynamics of nutrition.     

Primary structure of gene H of cattle plague virus strain K]

The paper analyzes the standard legal and methodological assurance of the quality and safety of animal food raw materials and foodstuffs (meat, meat products, fish, shellfish, crayfish and their processing products) by the parasitic purity rates according the requirements under the Russian Federation's laws "On Sanitary and Epidemiological Well-Being of the Population", "On Protection of Consumer's Rights", "On Certification of Products and Services", those of SanPiN, such as 2.3.2.560-96 "Sanitary Requirements for the Quality and Safety of Food Raw Materials and Foodstuffs" and 3.2.569-96 "Prevention of Parasitic Diseases in the Russian Federation".     

Non-rigid metric reconstruction from perspective cameras

The metric reconstruction of a non-rigid object viewed by a generic camera poses new challenges since current approaches for Structure from Motion assume the rigidity constraint of a shape as an essential condition. In this work, we focus on the estimation of the 3-D Euclidean shape and motion of a non-rigid shape observed by a perspective camera. In such case deformation and perspective effects are difficult to decouple – the parametrization of the 3-D non-rigid body may mistakenly account for the perspective distortion. Our method relies on the fact that it is often a reasonable assumption that some of the points on the object’s surface are deforming throughout the sequence while others remain rigid. Thus, relying on the rigidity constraints of a subset of rigid points, we estimate the perspective to metric upgrade transformation. First, we use an automatic segmentation algorithm to identify the set of rigid points. These are then used to estimate the internal camera calibration parameters and the overall rigid motion. Finally, we formulate the problem of non-rigid shape and motion estimation as a non-linear optimization where the objective function to be minimized is the image reprojection error. The prior information that some of the points in the object are rigid can also be added as a constraint to the non-linear minimization scheme in order to avoid ambiguous configurations. We perform experiments on different synthetic and real data sets which show that even when using a minimal set of rigid points and when varying the intrinsic camera parameters it is possible to obtain reliable metric information.     

Bond graph based control of a three-phase inverter with LC filter – Connection to passive and active loads

This paper proposes a model of a three phase electrical inverter with a LC output filter in delta connection used in a renewable energy supply system. The concept of inverse bond graph via bicausality is used for the control law design. The control law robustness is tested by connecting passive and active (induction machine) loads.     

Conditional co-simulation of continuous and categorical variables for geostatistical applications

The modeling of uncertainty in continuous and categorical regionalized variables is a common issue in the geosciences. We present a hybrid continuous/categorical model, in which the continuous variable is represented by the transform of a Gaussian random field, while the categorical variable is obtained by truncating one or more Gaussian random fields. The dependencies between the continuous and categorical variables are reproduced by assuming that all the Gaussian random fields are spatially cross-correlated. Algorithms and computer programs are proposed to infer the model parameters and to co-simulate the variables, and illustrated through a case study on a mining data set.     

Coinductive big-step operational semantics

Using a call-by-value functional language as an example, this article illustrates the use of coinductive definitions and proofs in big-step operational semantics, enabling it to describe diverging evaluations in addition to terminating evaluations. We formalize the connections between the coinductive big-step semantics and the standard small-step semantics, proving that both semantics are equivalent. We then study the use of coinductive big-step semantics in proofs of type soundness and proofs of semantic preservation for compilers. A methodological originality of this paper is that all results have been proved using the Coq proof assistant. We explain the proof-theoretic presentation of coinductive definitions and proofs offered by Coq, and show that it facilitates the discovery and the presentation of the results.     

A revision of recent approaches for two-dimensional strip-packing problems

In this paper, we present a review of the recent approaches proposed in the literature for strip-packing problems. Many of them have been concurrently published, given some similar results for the same set of benchmarks. Due to the quantity of published papers, it is difficult to ascertain the level of current research in this area.     

Elastic Resource Allocation Algorithms for Collaboration Applications

Cloud technologies can provide elasticity to real-time audio and video (A/V) collaboration applications. However, cloud-based collaboration solutions generally operate on a best-effort basis, with neither delivery nor quality guarantees, and high-quality business focused solutions rely on dedicated infrastructure and hardware-based components. This article describes our 2-year of research in the EMD project, which targets to migrate a hardware-based and business focused A/V collaboration solution to a software-based platform hosted in the cloud, providing higher levels of elasticity and reliability. Our focus during this period was an educational collaboration scenario with teachers and students (locally present in the classroom or remotely following the classes). A model of collaboration streaming (e.g. network topology, codecs, stream, streaming workflow, software components) is defined as base for software deployment and preemptive VM allocation techniques. These heuristics are evaluated using a version of the CloudSim simulator extended to generate and simulate realistic collaboration scenarios, to manage network congestion and to monitor a.o. cost and session delay metrics. Our results show that the algorithms reduce costs when compared to previously designed approaches, having an effectiveness of 99% in meeting A/V collaboration setup deadlines, which is a stringent requirement for this collaboration application.     

Active learning paradigms for CBIR systems based on optimum-path forest classification

This paper discusses methods for content-based image retrieval (CBIR) systems based on relevance feedback according to two active learning paradigms, named greedy and planned. In greedy methods, the system aims to return the most relevant images for a query at each iteration. In planned methods, the most informative images are returned during a few iterations and the most relevant ones are only presented afterward. In the past, we proposed a greedy approach based on optimum-path forest classification (OPF) and demonstrated its gain in effectiveness with respect to a planned method based on support-vector machines and another greedy approach based on multi-point query. In this work, we introduce a planned approach based on the OPF classifier and demonstrate its gain in effectiveness over all methods above using more image databases. In our tests, the most informative images are better obtained from images that are classified as relevant, which differs from the original definition. The results also indicate that both OPF-based methods require less user involvement (efficiency) to satisfy the user's expectation (effectiveness), and provide interactive response times.