Homogeneous Segments Research Articles

Method for creating location-specific audio textures

An approach is proposed for creating location-specific audio textures for virtual location-exploration services. The presented approach creates audio textures by processing a small amount of audio recorded at a given location, providing a cost-effective way to produce a versatile audio signal that characterizes the location. The resulting texture is non-repetitive and conserves the location-specific characteristics of the audio scene, without the need of collecting large amount of audio from each location. The method consists of two stages: analysis and synthesis. In the analysis stage, the source audio recording is segmented into homogeneous segments. In the synthesis stage, the audio texture is created by randomly drawing segments from the source audio so that the consecutive segments will have timbral similarity near the segment boundaries. Results obtained in listening experiments show that there is no statistically significant difference in the audio quality or location-specificity of audio when the created audio textures are compared to excerpts of the original recordings. Therefore, the proposed audio textures could be utilized in virtual location-exploration services. Examples of source signals and audio textures created from them are available at http://www.cs.tut.fi/~heittolt/audiotexture .

Innovation Diffusion Model for a Product Incorporating Segment-specific Strategy and the Spectrum Effect of Promotion

Promotion is an important component of a firm's marketing mix. It assists in dispersing the product information into minds of the customers and takes them to the final stage of purchase. Various promotional strategies are used by firms to capture maximum potential adopters in the market. Firms adopt segment driven marketing to best utilize its finite marketing resources. Mass market promotion and differentiated market promotion are amongst the two widely used techniques of promotion used in a heterogeneous market, segmented into homogeneous segments. Through mass market promotion, a product is promoted in the entire market, using a common promotional strategy, thereby creating a spectrum effect in all the segments of the market. Whereas, differentiated market promotion targets each segment of the market with distinct promotional strategies. In a segmented market, both types of promotional strategies play different and important roles for product adoption in the market. Innovation diffusion models are used to describe the adoption growth of durable technology products over their product life cycle. There is vast literature of innovation diffusion modeling. The existing literature mostly assumes a homogeneous market while formulating the model and effect of mass and differentiated promotion techniques on adoption growth in a segmented market is not yet analyzed. In this paper, we develop an innovation diffusion model for a durable technology consumer product considering the combined effect of mass and differentiated promotion along with the internal influence factors on adoption growth in segmented market. Model validity is tested on a real time data in four segments. Fairly good results have been obtained.

Resolving the Structural Basis of Factor VIII Activation

Activated Factor VIII (FVIIIa) is the essential co-factor for the serine protease Factor IXa (FIXa) in the membrane-bound Tenase complex. In the blood coagulation process, the interaction between FVIIIa and FIXa in presence of Ca2+ and phospholipids amplifies the proteolytic activity of Factor IXa more than 100.000 times. The Tenase complex catalyzes the activation of Factor X and initiates a cascade of multi-protein complex formation which amplifies the Thrombin production and secures the formation of a blood clot.Here we report for the first time the 3D-structure of the membrane-bound FVIIIa form, which is the most physiologically relevant in relation to the delicate equilibrium of hemostasis and thrombosis.The structure of the membrane bound light chain (domains A3-C1-C2) of human FVIII helically organized onto lipid bilayer nanotubes (LNT) clarified that the domains adopt a different organization than in the crystal structure which represents the molecule in solution. These differences of the membrane-bound FVIII structure have to be confirmed for the full length FVIII protein and the active form. To achieve this, high resolution Cryo-EM data of porcine FVIII and FVIIIa helically organized on LNT at closest to physiological conditions were collected. A newly developed process of iterated rounds of 2D refinement was applied to select only highly organized homogenous helical segments for an effective iterative helical real-space reconstruction (IHRSR). The calculated porcine FVIII and FVIIIa membrane-bound structures at subnanometer resolution were combined with flexible docking to define the changes in the FVIIIa interfaces important for its function.Understanding the structural differences and similarities between the membrane-bound activated FVIII and the non-activated FVIII will make an indispensable contribution to the field of coagulation in determining unique targets for the design of specific therapeutic drugs against Hemophilia A and thrombosis.

BiomvRhsmm: genomic segmentation with hidden semi-Markov model.

High-throughput technologies like tiling array and next-generation sequencing (NGS) generate continuous homogeneous segments or signal peaks in the genome that represent transcripts and transcript variants (transcript mapping and quantification), regions of deletion and amplification (copy number variation), or regions characterized by particular common features like chromatin state or DNA methylation ratio (epigenetic modifications). However, the volume and output of data produced by these technologies present challenges in analysis. Here, a hidden semi-Markov model (HSMM) is implemented and tailored to handle multiple genomic profile, to better facilitate genome annotation by assisting in the detection of transcripts, regulatory regions, and copy number variation by holistic microarray or NGS. With support for various data distributions, instead of limiting itself to one specific application, the proposed hidden semi-Markov model is designed to allow modeling options to accommodate different types of genomic data and to serve as a general segmentation engine. By incorporating genomic positions into the sojourn distribution of HSMM, with optional prior learning using annotation or previous studies, the modeling output is more biologically sensible. The proposed model has been compared with several other state-of-the-art segmentation models through simulation benchmarking, which shows that our efficient implementation achieves comparable or better sensitivity and specificity in genomic segmentation.

Exploring heterogeneity in travel time expenditure of aging populations in the Netherlands: results of a CHAID analysis

The aim of this paper is to contribute to the increasing literature on travel behavior and time use of the elderly. The Dutch National Travel Survey, administered in 2009, was used as a data source. First, various facets of activity-travel patterns of the elderly were compared against overall sample averages. Results indicate that the new generation of elderly people do not differ that much from other age groups in terms of their activity-travel behavior. Differences in behavior can be largely understood in terms of constraints acting on agendas. Moreover, travel patterns of elderly are affected by socio-demographic variables. Second, to further qualify the average findings, the Chi-square automatic interaction detection (CHAID) method was applied to explore heterogeneity among the elderly in terms of travel time expenditure. It is analyzed how differences in travel time co-vary with socio-demographics, in addition to activity type, activity duration and travel aspects. The results suggest that the aging population can be systematically broken down into several homogeneous cohort segments. Travel time of elderly groups depends significantly on transport modes, travel motivation, and seven socio-demographic variables (gender, age, living environment, personal net-income, household size and season). Moreover, there is less heterogeneity in travel time of elderly who are older than 75years old. However, for younger elderly people, especially the group aged from 65 to 74years old, heterogeneity affects their travel.

Risk-type density diagrams by crash type on two-lane rural roads

The research presented here aims to plot density diagrams per road crash risk type to identify all possible scenarios where driving is less than safe. The starting point was the prediction of injury crash rate on horizontal homogeneous segments of two-lane rural roads for three main injurious crash types (head-on/side collisions, rear-end crashes, and single-vehicle run-off-road crashes) as observed on the network. A careful analysis of the database shows that a wide variety of factors appear to be influenced or associated with the crash dynamic, as follows: the road scenario (combination of infrastructure and environmental conditions found at the site at the time of the crash), mean lane width, the horizontal curvature indicator (measurement of the curvature change rate), and mean speed. Crashes recorded from 2003 to 2010, of which 1597 were injurious, and 645 resulted only in damage to property, were analyzed on more than 3700 km of road network in Southern Italy. Generalized estimating equations with a negative binomial distribution were implemented. Risk-type density charts were plotted to thoroughly identify all possible combinations of existing explicative variables producing hazardous conditions on the road. The different shades in the diagrams represent different ranges of injurious crash rates: the white band shows low levels, while a black band shows high values. It is not possible to consider working on an explanatory variable to reduce hazardous conditions on the road network without also considering how this variation might affect the influence of the remaining explanatory variables on crash phenomena and, consequently, on the predictive model. The risk maps make it possible to keep under control in a simple and immediate approach the way each variable as a result of variations of a part or of all.

Traffic state estimation and uncertainty quantification based on heterogeneous data sources: A three detector approach

This study focuses on how to use multiple data sources, including loop detector counts, AVI Bluetooth travel time readings and GPS location samples, to estimate macroscopic traffic states on a homogeneous freeway segment. With a generalized least square estimation framework, this research constructs a number of linear equations that map the traffic measurements as functions of cumulative vehicle counts on both ends of a traffic segment. We extend Newell’s method to solve a stochastic three-detector problem, where the mean and variance estimates of cell-based density and flow can be analytically derived through a multinomial probit model and an innovative use of Clark’s approximation method. An information measure is further introduced to quantify the value of heterogeneous traffic measurements for improving traffic state estimation on a freeway segment.

Model based clustering of customer choice data

In several empirical applications analyzing customer-by-product choice data, it may be relevant to partition individuals having similar purchase behavior in homogeneous segments. Moreover, should individual- and/or product-specific covariates be available, their potential effects on the probability to choose certain products may be also investigated. A model for joint clustering of statistical units (customers) and variables (products) is proposed in a mixture modeling framework, and an appropriate EM-type algorithm for ML parameter estimation is presented. The model can be easily linked with similar proposals appeared in various contexts, such as co-clustering of gene expression data, clustering of words and documents in web-mining data analysis.

Sensitivity of Compressed Spectral Arrays for Detecting Seizures in Acutely Ill Adults

Continuous EEG recordings (cEEGs) are increasingly used in evaluation of acutely ill adults. Pre-screening using compressed data formats, such as compressed spectral array (CSA), may accelerate EEG review. We tested whether screening with CSA can enable detection of seizures and other relevant patterns. Two individuals reviewed the CSA displays of 113 cEEGs. While blinded to the raw EEG data, they marked each visually homogeneous CSA segment. An independent experienced electroencephalographer reviewed the raw EEG within 60 s on either side of each mark and recorded any seizures (and isolated epileptiform discharges, periodic epileptiform discharges (PEDs), rhythmic delta activity (RDA), and focal or generalized slowing). Seizures were considered to have been detected if the CSA mark was within 60 s of the seizure. The electroencephalographer then determined the total number of seizures (and other critical findings) for each record by exhaustive, page-by-page review of the entire raw EEG. Within each of the 39 cEEG recordings containing seizures, one CSA reviewer identified at least one seizure, while the second CSA reviewer identified 38/39 patients with seizures. The overall detection rate was 89.0 % of 1,190 total seizures. When present, an average of 87.9 % of seizures were detected per individual patient. Detection rates for other critical findings were as follows: epileptiform discharges, 94.0 %; PEDs, 100 %; RDA, 97.9 %; focal slowing, 100 %; and generalized slowing, 100 %. CSA-guided review can support sensitive screening of critical pathological information in cEEG recordings. However, some patients with seizures may not be identified.

A CAN Topology Optimization of Pure Electric Vechicle

In the design of CAN network system, as CAN bus topology will affect network performance and cost, it is important to optimize the network topology. This paper analyzes the CAN busload based on CAN protocol, calculates the upper limit of transmission message frames in a single CAN bus. As the amount of information on the bus is increasing, a single CAN bus cannot meet the communication requirements, we put forward dividing the network into multiple homogeneous segments via multi-objective optimization method, developing a genetic algorithm strategy and solving the problem in a MATLAB platform. Finally utilize the method to design a pure electric vehicle network topology.

SEGMENTATION OF HERITAGE BUILDING BY MEANS OF GEOMETRIC AND RADIOMETRIC COMPONENTS FROM TERRESTRIAL LASER SCANNING

Abstract. Nowadays, the terrestrial laser scanning represents an integral source of data for cultural heritage 3D storage and access through digital communication tools. The achievement of 3D models requires the implementation of several tasks such as segmentation. Segmentation is the key step during the point cloud processing where all homogeneous areas are identified, which describe a building facade. Usually, a large part of the segmentation approach focuses on the geometric information contained in the point cloud data by exploiting mathematical representation of a parametric surface. However, due to the complexity of the architecture, such segmentation does not suffice. Henceforth, other approaches turn to the use of color and laser intensity components. Although a variety of algorithms have been developed in this sense, problems of over-segmentation or under-segmentation are observed. In this context, we propose a new approach for point cloud segmentation aiming at a more accurate result. This approach relies on all the components of a colored point – both geometric and radiometric – combining the RGB values, laser intensity and geometric data. Our process begins with the extraction of homogeneous planar segments using the RANSAC algorithm. Next, the result is subjected to a radiometric-based segmentation, first through color similarity as one of the homogeneity criteria of a region growing algorithm, then through the use of intensity similarity for segment fusion. Experiments are performed on a facade presenting an example of Moroccan classical architecture located in Casablanca's Medina. Results show the importance of integrating all point cloud components, both geometric and radiometric.

Information extraction from sensor networks using the Watershed transform algorithm

Wireless sensor networks are an effective tool to provide fine resolution monitoring of the physical environment. Sensors generate continuous streams of data, which leads to several computational challenges. As sensor nodes become increasingly active devices, with more processing and communication resources, various methods of distributed data processing and sharing become feasible. The challenge is to extract information from the gathered sensory data with a specified level of accuracy in a timely and power-efficient approach. This paper presents a new solution to distributed information extraction that makes use of the morphological Watershed algorithm. The Watershed algorithm dynamically groups sensor nodes into homogeneous network segments with respect to their topological relationships and their sensing-states. This setting allows network programmers to manipulate groups of spatially distributed data streams instead of individual nodes. This is achieved by using network segments as programming abstractions on which various query processes can be executed. Aiming at this purpose, we present a reformulation of the global Watershed algorithm. The modified Watershed algorithm is fully asynchronous, where sensor nodes can autonomously process their local data in parallel and in collaboration with neighbouring nodes. Experimental evaluation shows that the presented solution is able to considerably reduce query resolution cost without scarifying the quality of the returned results. When compared to similar purpose schemes, such as “Logical Neighborhood”, the proposed approach reduces the total query resolution overhead by up to 57.5%, reduces the number of nodes involved in query resolution by up to 59%, and reduces the setup convergence time by up to 65.1%.

Accuracy assessment and classification efficiency of object-based image analysis of aerial imagery

Following text is focused on finding a proper balance between classification accuracy and classification efficiency of object based image analysis of aerial imagery. For image classification were used tools of Feature Analyst, an ArcGIS extension, which are based on image filtering and searching for homogeneous segments corresponding to the threshold values defined by the training areas and corrected with tools of object recognition. The classification accuracy was assessed using the error matrices and calculating user’s and producer’s accuracy. To evaluate the time and work consumption, index of classification efficiency was introduced, which is a weighted value of accuracy and number of objects. To evaluate the tools of object recognition, the principle of fuzzy logic was used, which calculates accuracy with inclusion of alternative category. For the study was used a cut of aerial imagery of protected area of Křivoklatsko as a typical example of the character of available image data in the territory of Czech Republic – large area of fields, forests and meadows with a very heterogeneous character, water body with sun reflection, net of narrow roads and small villages. From the final values of accuracy is obvious, that Feature analyst provides comparable results with other authors. From the point of view of classification efficiency, application of tools of object recognition and its effect on the time and work consumption, it is a question of the extent of study area and the heterogeneity of the features of the physical world on the image data. <b>Přesnost a efektivita objektové klasifikace leteckých snímků</b> Článek se zabývá objektovou klasifikací výřezu leteckých snímků z území CHKO Křivoklátsko v okolí obce Kalinova Ves. Sledována je především přesnost objektové klasifikace v porovnání s její efektivitou, pracností a časovou náročností zpracování. Pro zpracování leteckých snímků byly použity nástroje extenze Feature Analyst pro ArcGIS, pracující na základě vyhledávání homogenních ploch v rámci obrazu, které odpovídají kriteriím nastaveným pomocí trénovacích ploch a pomocí tzv. rozpoznávání objektů. Přesnost klasifikace byla stanovena pro jednotlivé sledované kategorie krajinného krytu pomocí kontingenčních tabulek a chybových matic na základě referenčního souboru objektů, který z hlediska počtu a velikosti objektů odpovídal rozložení objektů v jednotlivých kategoriích. Byla sledována přesnost jak z hlediska uživatele (zda všechny vektorové objekty, které reprezentují objekty reálného světa v rámci jedné kategorie, byly klasifikovány správně), tak z hlediska zpracovatele (zda objekty v rámci jedné kategorie byly klasifikovány správně). Zároveň byl definován index efektivity, který přesnost klasifikace váží počtem objektů v rámci kategorie, čímž je do výpočtu zahrnuta i pracnost a časová náročnost zpracování. Přesnost klasifikace byla rozšířena i o tzv. alternativní kategorii využívanou v rámci fuzzy principu, tedy druhou možnou kategorii, do které mohl být objekt zařazen s ohledem na radiometrické hodnoty definované pomocí trénovacích ploch. Porovnáním výsledků přesnosti klasifikace se započtením alternativní kategorie a bez jejího započtení je možné posoudit úspěšnost rozpoznávání objektů v jednotlivých kategoriích. Z hlediska zpracování je možné rozdělit výsledné kategorie krajinného krytu na kategorie, které jsou tvořeny několika velkými plochami s heterogenním charakterem na obrazových datech (pole, les, louky), kategorie, které jsou tvořeny velkým počtem plošně malých objektů s radiometricky homogenním obrazem (komunikace, zastavěná plocha), a kategorie, které mají podobnou radiometrickou definici jako jiné kategorie a je možné je identifikovat pouze pomocí funkce rozpoznávání objektů (zahrada vs. louka, telené pásy podél toků vs. les). Obrazově heterogenní kategorie byly klasifikovány v první fázi a pro následné zpracování byly z klasifikační masky odstraněny. Z porovnání přesnosti se započítáním alternativní kategorie, přesnosti bez jejího započítání a s efektivitou klasifikace vychází, že z hlediska pracnosti a časové náročnosti (s ohledem na rozsah zpracovávaných dat) je vhodnější vytvořit vektorový obraz těchto kategorií pomocí manuální vektorizace. Oproti tomu plošně malé a radiometricky homogenní objekty jsou poté v obrazových datech identifikovány bez pracného několikanásobného definování trénovacích ploch, časově náročné vícenásobné iterace a rozpoznávání objektů. Z hlediska přesnosti zpracování jsou výsledky dosažené pomocí extenze Feature Analyst porovnatelné s výsledky, které byly dosaženy v pracích jiných autorů.

A new approach of speaker clustering based on the stereophonic differential energy

In this paper, we present a new approach of speech clustering with regards of the speaker identity. It consists in grouping the homogeneous speech segments that are obtained at the end of the segmentation process, by using the spatial information provided by the stereophonic speech signals. The proposed method uses the differential energy of the two stereophonic signals collected by two cardioid microphones, in order to cluster all the speech segments that belong to the same speaker. The total number of clusters obtained at the end should be equal to the real number of speakers present in the meeting room and each cluster should contain the global intervention of only one speaker. The proposed system is suitable for debates or multi-conferences for which the speakers are located at fixed positions. Basically, our approach tries to make a speaker localization with regards to the position of the microphones, taken as a spatial reference. Based on this localization, the new proposed method can recognize the speaker identity of any speech segment during the meeting. So, the intervention of each speaker is automatically detected and assigned to him by estimating his relative position. In a purpose of comparison, two types of clustering methods have been implemented and experimented: the new approach, which we called Energy Differential based Spatial Clustering (EDSC) and a classical statistical approach called "Mono-Gaussian based Sequential Clustering" (MGSC). Experiments of speaker clustering are done on a stereophonic speech corpus called DB15, composed of 15 stereophonic scenarios of about 3.5 minutes each. Every scenario corresponds to a free discussion between two or three speakers seated at fixed positions in the meeting room. Results show the outstanding performances of the new approach in terms of precision and speed, especially for short speech segments, where most of clustering techniques present a strong failure.

Preferences for lamb meat: A choice experiment for Spanish consumers

This paper analyzes consumers' preferences for different lamb meat attributes using a choice experiment. In particular, preferences for the type of commercial lamb meat (“Ternasco” and “Suckling”) and the origin of production (locally produced “Ojinegra from Teruel”) were evaluated. Moreover, we endogenously identify consumers' segments based on consumers' preferences for the analyzed attributes. Data come from a survey administrated in Spain during 2009. A latent class model was used to estimate the effect of the attributes on consumer utility, derive the willingness to pay and determine consumers' segments. Results suggest that consumers' preferences for both attributes are heterogeneous and two homogenous consumers' segments were detected. The largest segment (79%) did not value any of the analyzed attributes while the smaller one (21%) valued both of them positively. In particular, consumers in this second segment are willing to pay an extra premium for the “Ternasco” lamb meat, around double the premium they are willing to pay for the locally produced lamb meat “Ojinegra from Teruel”.

Multi-scale factors controlling the pattern of floodplain width at a network scale: The case of the Rhône basin, France

In this study the floodplain width (FW) was assessed for the entire Rhône catchment river network (32,160km long) to highlight controlling factors. The FW data, which is measured every kilometre on a digital elevation model (DTM), is aggregated into spatial homogenous segments using a Pettitt break detection test, resulting in aggregated geographical objects (AGO). Based on these AGOs, an analysis of the variability of the floodplain width was performed. The general pattern for the Rhône network shows a downstream increase in FW related to the concept of river continuum. This general pattern explains ca. 30% of the variation in FW. Deviations from this general trend are, however, large. Values for floodplain widths are normalized for catchment scale to study deviations that do not depend on scale effects. Based on a conceptual model, the main environmental parameters influencing FW were identified. These parameters include lithology and different parameters that influence the river profile, such as base level changes and tectonics, sediment load and discharge. An analysis of catchment-wide patterns shows that the main variations on the scaling effect are caused by lithology. Superposed on this general scaling pattern, disturbed by lithological variations, are the variations in floodplain width caused by disturbances in the geomorphic system, which influence floodplain slope, sediment, and water discharge and which include inherited landscapes. Although large data sets become increasingly available and the applied methodology reduces data noise, data availability and quality still hampers studies at a larger scale. Nevertheless, such information sources are becoming crucial because they are more and more accessible and diverse, and the analysis is now easier with the increasing capacities of GIS technologies. As a result, they are becoming very complementary to field studies to understand geomorphic processes at wider spatial and longer temporal scales. In a sense, the tradition of geomorphology may evolve in the next years, with image data providing additional evidence of Earth evolution.

Mechanisms of Protein Binding to DNA: Statistical Interactions are Important

Protein molecules binding to DNA initiate sequences of biochemical transitions that control and regulate all major processes in living cells (1). It has long been understood that the efficient transfer of genetic information is possible when genome-regulating protein molecules are found to be strongly bound to special sequences on DNA, known as specific binding sites. It was later realized that finding these target sequences might be complicated by the existence of a large number (≃106–109 per DNA) of other nonspecific binding sites and because of low concentrations of relevant protein molecules (2–4). Although significant experimental and theoretical efforts to investigate mechanisms of protein binding to DNA have been made, the role and functioning of nonspecific interactions has not been fully understood.

A unified framework for domain independent online speaker indexing in eigen-voice space using an index tree of reference models

Speaker indexing referred in literature as speaker diarization is an important task in audio indexing and retrieval. Speaker indexing includes two important and usually separate stages, namely speaker segmentation and speaker clustering. Speaker indexing can be divided into online and offline categories. This paper mainly focuses on domain independent online speaker indexing. For this purpose, the proposed framework should be parameter free and no application specific parameters such as utterance duration or threshold settings are required. To reduce dependency on parameters, the traditional speaker segmentation is reformed to a voting based homogeneous speech segmentation, in which several approaches are applied in parallel to decide on the existence of a change point. In online indexing, data insufficiency is encountered at each time slice. In the proposed framework, a set of reference speaker models are used as side information to facilitate online tracking. To improve the indexing accuracy, adaptation approaches in eigen-voice decomposition space are proposed in this paper. To enhance the tracking performance from the computational cost point of view, an index structure of the reference models is proposed to speed up the search in the model space. The proposed framework is evaluated on the 2002 Rich Transcription Broadcast News and Conversational Telephone Speech Corpus (in Garofolo, NIST Rich Transcription, 2002) as well as a synthetic dataset. The indexing error of the proposed framework on telephone conversations, broadcast news and synthetic dataset are 7.51 %, 6.36 % and 9.34 %, respectively. Also, using the index tree structure approach, the tracking run time of the proposed framework is improved by 32 %.

Linking sediment trapping efficiency with morphological traits of Salix tiller barriers on marly gully floors under ecological rehabilitation

Soil erosion is considered to be a major threat for soil quality worldwide. Overgrazing and deforestation are the main causes of a recent increase in soil erosion. When devoid of vegetation, marly terrains are particularly prone to severe hydric erosion with gully formation. It is commonly acknowledged that the presence of vegetation interacts with the sediment yield, especially in the gully floor. In the southern Alps, there is a promising ecological engineering approach used to decrease the sediment yield at marly gullies, consisting in implanting bioengineering works to trap sediment in gully floors. Here, vegetation barriers are made of a line of Salix purpurea cuttings (non-native species but widely used in bioengineering), arranged perpendicularly to the flow, on a dead-wood sill, resprouting and forming tillers. Our objective was to better understand how morphological traits of Salix tiller barriers can explain their sediment trapping efficiency. The history of sediment trapping has been recorded on a sample of 77 Salix barriers since their implantation, from 2002 to 2008. Then, focusing on still visible and homogeneous segments of tiller barriers only (49 segments), the basal diameter, basal stem density and basal shoot branching of the tillers, as well as the sediment deposit heights were measured in spring 2010. The results showed that Salix tillers barriers are able to trap sediment in marly gully floors under ecological rehabilitation. The sediment trapping records showed that there is a structural efficient threshold beyond which Salix barriers can trap sediment. We suggest that this threshold is explained by the fact that the basal stem diameter also reaches a threshold value of about 6mm, usually during the 3rd year after Salix cuttings are implanted. Beyond this threshold, the results suggest that the main tiller morphological trait which explains the efficiency of sediment-trapping barriers is the basal shoot branching. The present study is innovative in the sense that the sediment flow conditions in gully beds are much stronger than those found in previous studies. The results found here provide practitioners with useful data for designing gullies restoration with Salix cuttings.

Desafios para a discussão de missão institucional complexa: o caso de um Instituto de Pesquisa em Saúde

This study is based on an adaptation of the Strategic Démarche Approach applied to the Evandro Chagas Institute of Clinical Research (IPEC) in Brazil, from April to July 2009. The results are related to the experience of the Leishmaniasis Laboratory. A strategic analysis of four homogeneous segments was performed, considering the administration of care and specific teaching and research indicators. In both portfolios, all segments showed competitiveness and an appropriate response to mission goals. However, the second portfolio (teaching/research) showed a greater concentration of production in one segment. A highlight was the presence in the work team of cultural traits consistent with the objectives of cultural change. This experience, by operating indirectly in furtherance of the features of the new culture that emerges, revealed the potential of the method in question, to effect policies, processes and resources in a democratic and communicative way, which contributes to the operationalization of the guidelines of the Brazilian Unified Health System.