Validation of a context analysis method for microRNA data

We have previously presented a data-oriented approach to the study of microRNA-gene interactions, a hot topic of research in molecular biology, building heavily on methods from the document analysis field. This paper evaluates the performances of the method by means of a cross-validation approach. Latent information can be effectively exploited to suggest directions for laboratory experiments, an important topic in microRNA research, since these experiments are costly in both resources and time

Layered ensemble model for short-term traffic flow forecasting with outlier detection

YesReal time traffic flow forecasting is a necessary requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. This paper focuses on short-term traffic flow forecasting by taking into consideration both spatial (road links) and temporal (lag or past traffic flow values) information. We propose a Layered Ensemble Model (LEM) which combines Artificial Neural Networks and Graded Possibilistic Clustering obtaining an accurate forecast of the traffic flow rates with outlier detection. Experimentation has been carried out on two different data sets. The former was obtained from real UK motorway and the later was obtained from simulated traffic flow on a street network in Genoa (Italy). The proposed LEM model for short-term traffic forecasting provides promising results and given the ability for outlier detection, accuracy, robustness of the proposed approach, it can be fruitful integrated in traffic flow management systems

Tracking time evolving data streams for short-term traffic forecasting

YesData streams have arisen as a relevant topic during the last few years as an efficient method for extracting knowledge from big data. In the robust layered ensemble model (RLEM) proposed in this paper for short-term traffic flow forecasting, incoming traffic flow data of all connected road links are organized in chunks corresponding to an optimal time lag. The RLEM model is composed of two layers. In the first layer, we cluster the chunks by using the Graded Possibilistic c-Means method. The second layer is made up by an ensemble of forecasters, each of them trained for short-term traffic flow forecasting on the chunks belonging to a specific cluster. In the operational phase, as a new chunk of traffic flow data presented as input to the RLEM, its memberships to all clusters are evaluated, and if it is not recognized as an outlier, the outputs of all forecasters are combined in an ensemble, obtaining in this a way a forecasting of traffic flow for a short-term time horizon. The proposed RLEM model is evaluated on a synthetic data set, on a traffic flow data simulator and on two real-world traffic flow data sets. The model gives an accurate forecasting of the traffic flow rates with outlier detection and shows a good adaptation to non-stationary traffic regimes. Given its characteristics of outlier detection, accuracy, and robustness, RLEM can be fruitfully integrated in traffic flow management systems

Graded possibilistic clustering of non-stationary data streams

YesMultidimensional data streams are a major paradigm in data science. This work focuses on possibilistic clustering algorithms as means to perform clustering of multidimensional streaming data. The proposed approach exploits fuzzy outlier analysis to provide good learning and tracking abilities in both concept shift and concept drift

Dynamic Collection Scheduling Using Remote Asset Monitoring: Case Study in the UK Charity Sector

Remote sensing technology is now coming onto the market in the waste collection sector. This technology allows waste and recycling receptacles to report their fill levels at regular intervals. This reporting enables collection schedules to be optimized dynamically to meet true servicing needs in a better way and so reduce transport costs and ensure that visits to clients are made in a timely fashion. This paper describes a real-life logistics problem faced by a leading UK charity that services its textile and book donation banks and its high street stores by using a common fleet of vehicles with various carrying capacities. Use of a common fleet gives rise to a vehicle routing problem in which visits to stores are on fixed days of the week with time window constraints and visits to banks (fitted with remote fill-monitoring technology) are made in a timely fashion so that the banks do not become full before collection. A tabu search algorithm was developed to provide vehicle routes for the next day of operation on the basis of the maximization of profit. A longer look-ahead period was not considered because donation rates to banks are highly variable. The algorithm included parameters that specified the minimum fill level (e.g., 50%) required to allow a visit to a bank and a penalty function used to encourage visits to banks that are becoming full. The results showed that the algorithm significantly reduced visits to banks and increased profit by up to 2.4%, with the best performance obtained when the donation rates were more variable

Extremely Low-Frequency Electromagnetic Fields Affect Myogenic Processes in C2C12 Myoblasts: Role of Gap-Junction-Mediated Intercellular Communication

Extremely low-frequency electromagnetic fields (ELF-EMFs) can interact with biological systems. Although they are successfully used as therapeutic agents in physiatrics and rehabilitative practice, they might represent environmental pollutants and pose a risk to human health. Due to the lack of evidence of their mechanism of action, the effects of ELF-EMFs on differentiation processes in skeletal muscle were investigated. C2C12 myoblasts were exposed to ELF-EMFs generated by a solenoid. The effects of ELF-EMFs on cell viability and on growth and differentiation rates were studied using colorimetric and vital dye assays, cytomorphology, and molecular analysis of MyoD and myogenin expression, respectively. The establishment of functional gap junctions was investigated analyzing connexin 43 expression levels and measuring cell permeability, using microinjection/dye-transfer assays. The ELF-EMFs did not affect C2C12 myoblast viability or proliferation rate. Conversely, at ELF-EMF intensity in the mT range, the myogenic process was accelerated, through increased expression of MyoD, myogenin, and connexin 43. The increase in gap-junction function suggests promoting cell fusion and myotube differentiation. These data provide the first evidence of the mechanism through which ELF-EMFs may provide therapeutic benefits and can resolve, at least in part, some conditions of muscle dysfunction

From IR to X-rays: approaches to go through the coating system of historical bowed string musical instruments

Some historical bowed string musical instruments produced in Italy from the 16th to 18th Centuries are considered until now peak-quality masterpieces of the violin-making art. Technical skills were mostly lost after the disappearance of the prominent workshops, and nowadays ancient methods and materials are charming secrets to be revealed by scientific techniques. This work discusses the results obtained by investigating the complex coating systems on bowed string instruments produced by four violin-makers, namely: Jacobus Stainer, Gasparo da Salò, Giovanni Paolo Maggini and Lorenzo Guadagnini. They were selected in order to represent convincingly - albeit not exhaustively - the variety of situations that can be encountered when multi-layered coatings on historical bowed string instruments are considered. The coating systems have been investigated though micro-invasive and non-invasive procedures [1], employing UV-imaging, portable X-ray fluorescence, optical microscopy, scanning electron microscopy coupled with energy dispersive X-ray spectrometry and Fourier transform infrared microscopy. In addition, two tomographic techniques (synchrotron radiation micro-computed tomography and optical coherence tomography) have been used to image the finishing layers spread on the wood substrate [2,3]. Chemical investigations and images on cross-sections have been compared with the morphological view obtained by tomography, with particular attention to the ability of the tomographic insight to distinguish and measure the various overlying layers, and to highlight the presence of dispersed particles

Consumo e absorcao aparente total de macroelementos minerais (Ca, P, Mg, Na e K), de dietas com diferentes niveis de volumoso.

Avaliaram-se os efeitos dos niveis de volumoso nas dietas sobre os consumos e as absorcoes aparentes (AP) do calcio (Ca), fosforo (P), magnesio (Mg), sodio (Na) e potassio (K). Utilizaram-se 40 bezerros, com peso vivo medio inicial de 60 kg, distribuidos em delineamento inteiramente casualizado e alimentados a vontade com racoes constituidas de niveis crescentes de volumoso na base de MS: T1= 10%; T2 = 25%; T3= 40%, T4= 55% e T5= 90%. Como volumoso utilizou-se o feno de capim Coast-cross (Cynodon dactylon) picado. Os consumos quando expressos em g/dia, estimaram-se os respectivos consumos maximos de Ca, P, Mg, Na e K para o nivel de 47,0; 30,0; 45,3; 41,0 e 51,8% de volumoso na dieta. As absorcoes aparentes do Ca, P, e K, foram afetadas pelos niveis de volumoso nas dietas, estimando-se maximas absorcoes de 58,7; 56,1 e 78,3% para os niveis de 20,3; 23,1 e 45,2% de volumoso nas dietas, respectivamente