Query: FFT-based Terrain Segmentation for Underwater Mapping

Relevant passages:
On the segmentation of 3D LIDAR point clouds <=SEP=> This paper presents a set of segmentation methods for various types of 3D point clouds. Segmentation of dense 3D data (e.g. Riegl scans) is optimised via a simple yet efficient voxelisation of the space. Prior ground extraction is empirically shown to significantly improve segmentation performance. Segmentation of sparse 3D data (e.g. Velodyne scans) is addressed using ground models of non-constant resolution either providing a continuous probabilistic surface or a terrain mesh built from the structure of a range image, both representations providing close to real-time performance. All the algorithms are tested on several hand labeled data sets using two novel metrics for segmentation evaluation.

Efficient Graph-Based Image Segmentation <=SEP=> This paper addresses the problem of segmenting an image into regions. We define a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image. We then develop an efficient segmentation algorithm based on this predicate, and show that although this algorithm makes greedy decisions it produces segmentations that satisfy global properties. We apply the algorithm to image segmentation using two different kinds of local neighborhoods in constructing the graph, and illustrate the results with both real and synthetic images. The algorithm runs in time nearly linear in the number of graph edges and is also fast in practice. An important characteristic of the method is its ability to preserve detail in low-variability image regions while ignoring detail in high-variability regions.

Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes <=SEP=> We present a 3-D shape-based object recognition system for simultaneous recognition of multiple objects in scenes containing clutter and occlusion. Recognition is based on matching surfaces by matching points using the spin-image representation. The spin-image is a data level shape descriptor that is used to match surfaces represented as surface meshes. We present a compression scheme for spin-images that results in efficient multiple object recognition which we verify with results showing the simultaneous recognition of multiple objects from a library of 20 models. Furthermore, we demonstrate the robust performance of recognition in the presence of clutter and occlusion through analysis of recognition trials on 100 scenes. This research was performed at Carnegie Mellon University and was supported by the US Department of Energy under contract DE-AC21-92MC29104. 1

A Method for Registration of 3-D Shapes <=SEP=> Tianhe Yang Summary of " A Method for Registration of 3-D Shapes "

Underwater Vehicle Obstacle Avoidance and Path Planning Using a MultiBeam Forward Looking Sonar <=SEP=> This paper describes a new framework for segmentation of sonar images, tracking of underwater objects and motion estimation. This framework is applied to the design of an obstacle avoidance and path planning system for underwater vehicles based on a multi-beam forward looking sonar sensor. The real-time data flow (acoustic images) at the input of the system is first segmented and relevant features are extracted. We also take advantage of the real-time data stream to track the obstacles in following frames to obtain their dynamic characteristics. This allows us to optimize the preprocessing phases in segmenting only the relevant part of the images. Once the static (size and shape) as well as dynamic characteristics (velocity, acceleration, ...) of the obstacles have been computed, we create a representation of the vehicle’s workspace based on these features. This representation uses constructive solid geometry(CSG) to create a convex set of obstacles defining the workspace. The tracking takes also into account obstacles which are no longer in the field of view of the sonar in the path planning phase. A well-proven nonlinear search (sequential quadratic programming) is then employed, where obstacles are expressed as constraints in the search space. This approach is less affected by local minima than classical methods using potential fields. The proposed system is not only capable of obstacle avoidance but also of path planning in complex environments which include fast moving obstacles. Results obtained on real sonar data are shown and discussed. Possible applications to sonar servoing and real-time motion estimation are also discussed.

Finding the shortest paths by node combination <=SEP=> By repeatedly combining the source node's nearest neighbor, we propose a node combination (NC) method to implement the Dijkstra's algorithm. The NC algorithm finds the shortest paths with three simple iterative steps: find the nearest neighbor of the source node, combine that node with the source node, and modify the weights on edges that connect to the nearest neighbor. The NC algorithm is more comprehensible and convenient for programming as there is no need to maintain a set with the nodes' distances. Experimental evaluations on various networks reveal that the NC algorithm is as efficient as Dijkstra's algorithm. As the whole process of the NC algorithm can be implemented with vectors, we also show how to find the shortest paths on a weight matrix. } is the set of nodes, E = {e ij j if there is a link from v i to v j } is the set of edges and W = {w ij j 1 6 i, j 6 N} is the weight matrix for E. Given two nodes v s , v t of G, the shortest path problem can be defined as how to find a path with the minimum sum of the weights on the edges in a v s , v t-path. Generally, v s and v t are called source node and sink node, respectively. The shortest path problem is one of the most fundamental network optimization problems with widespread applications [1–4]. Among the various shortest path algorithms developed [5–12], Dijkstra's algorithm is probably the most well-known. It maintains a set S of solved nodes, comprising those nodes whose final shortest path distance from the source v s has determined, and labels d(i), storing the upper bound of the shortest path distance from v s to v i. The algorithm repeatedly selects the node v k 2 VnS with the minimum d(i), adds v k to S, and updates d(i) for nodes that are incident to v k Step 1. Select a node v k from Q such that dðv k Þ ¼ min v j 2Q dðv j Þ, if d(v k) = 1, stop, otherwise go to Step 2. Step 3. for every v j 2 Q, update d(v j) = min{d(v j), d(v k) + w kj }. Go to Step 1. In practice, Dijkstra's algorithm relies heavily on the strategies used to select the next minimum labeled …

User friendly SLAM initialization <=SEP=> The development of new Simultaneous Localization and Mapping (SLAM) techniques is quickly advancing in research communities and rapidly transitioning into commercial products. Creating accurate and high-quality SLAM maps relies on a robust initialization process. However, the robustness and usability of SLAM initialization for end-users has often been disregarded. This paper presents and evaluates a novel tracking system for 6DOF pose tracking between a single keyframe and the current camera frame, without any prior scene knowledge. Our system is particularly suitable for SLAM initialization, since it allows 6DOF pose tracking in the intermediate frames before a wide-enough baseline between two keyframes has formed. We investigate how our tracking system can be used to interactively guide users in performing an optimal motion for SLAM initialization. However, our findings from a pilot study indicate that the need for such motion can be completely hidden from the user and outsourced to our tracking system. Results from a second user study show that letting our tracking system create a SLAM map as soon as possible is a viable and usable solution. Our work provides important insight for SLAM systems, showing how our novel tracking system can be integrated with a user interface to support fast, robust and user-friendly SLAM initialization.

Online Dictionary Learning on Symmetric Positive Definite Manifolds with Vision Applications <=SEP=> Symmetric Positive Definite (SPD) matrices in the form of region covariances are considered rich descriptors for images and videos. Recent studies suggest that exploiting the Riemannian geometry of the SPD manifolds could lead to improved performances for vision applications. For tasks involving processing large-scale and dynamic data in computer vision, the underlying model is required to progressively and efficiently adapt itself to the new and unseen observations. Motivated by these requirements, this paper studies the problem of online dictionary learning on the SPD manifolds. We make use of the Stein divergence to recast the problem of online dictionary learning on the manifolds to a problem in Reproducing Kernel Hilbert Spaces, for which, we develop efficient algorithms by taking into account the geometric structure of the SPD manifolds. To our best knowledge, our work is the first study that provides a solution for online dictionary learning on the SPD manifolds. Empirical results on both large-scale image classification task and dynamic video processing tasks validate the superior performance of our approach as compared to several state-of-the-art algorithms.

Web Content Analysis: Expanding the Paradigm <=SEP=> Are established methods of content analysis (CA) adequate to analyze web content, or should new methods be devised to address new technological developments? This chapter addresses this question by contrasting narrow and broad interpretations of the concept of web content analysis. The utility of a broad interpretation that subsumes the narrow one is then illustrated with reference to research on weblogs (blogs), a popular web format in which features of HTML documents and interactive computer-mediated communication converge. The chapter concludes by proposing an expanded Web Content Analysis (WebCA) paradigm in which insights from paradigms such as discourse analysis and social network analysis are operationalized and implemented within a general content analytic framework.

ZoomNet: Deep Aggregation Learning for High-Performance Small Pedestrian Detection <=SEP=> It remains very challenging for a single deep model to detect pedestrians of different sizes appears in an image. One typical remedy for the small pedestrian detection is to upsample the input and pass it to the network multiple times. Unfortunately this strategy not only exponentially increases the computational cost but also probably impairs the model effectiveness. In this work, we present a deep architecture, refereed to as ZoomNet, which performs small pedestrian detection by deep aggregation learning without up-sampling the input. ZoomNet learns and aggregates deep feature representations at multiple levels and retains the spatial information of the pedestrian from different scales. ZoomNet also learns to cultivate the feature representations from the classification task to the detection task and obtains further performance improvements. Extensive experimental results demonstrate the state-of-the-art performance of ZoomNet. The source code of this work will be made public available to facilitate further studies on this problem.

On Oblique Random Forests <=SEP=> Abstract. In his original paper on random forests, Breiman proposed two different decision tree ensembles: one generated from “orthogonal” trees with thresholds on individual features in every split, and one from “oblique” trees separating the feature space by randomly oriented hyperplanes. In spite of a rising interest in the random forest framework, however, ensembles built from orthogonal trees (RF) have gained most, if not all, attention so far. In the present work we propose to employ “oblique” random forests (oRF) built from multivariate trees which explicitly learn optimal split directions at internal nodes using linear discriminative models, rather than using random coefficients as the original oRF. This oRF outperforms RF, as well as other classifiers, on nearly all data sets but those with discrete factorial features. Learned node models perform distinctively better than random splits. An oRF feature importance score shows to be preferable over standard RF feature importance scores such as Gini or permutation importance. The topology of the oRF decision space appears to be smoother and better adapted to the data, resulting in improved generalization performance. Overall, the oRF propose here may be preferred over standard RF on most learning tasks involving numerical and spectral data.

The ATILF-LLF System for Parseme Shared Task: a Transition-based Verbal Multiword Expression Tagger <=SEP=> We describe the ATILF-LLF system built for the MWE 2017 Shared Task on automatic identification of verbal multiword expressions. We participated in the closed track only, for all the 18 available languages. Our system is a robust greedy transition-based system, in which MWE are identified through a MERGE transition. The system was meant to accommodate the variety of linguistic resources provided for each language, in terms of accompanying morphological and syntactic information. Using per-MWE Fscore, the system was ranked first1 for all but two languages (Hungarian and Romanian).

Indistinguishability of Random Systems <=SEP=> An (X ,Y)-random system takes inputs X1, X2, . . . ∈ X and generates, for each new input Xi, an output Yi ∈ Y, depending probabilistically on X1, . . . , Xi and Y1, . . . , Yi−1. Many cryptographic systems like block ciphers, MAC-schemes, pseudo-random functions, etc., can be modeled as random systems, where in fact Yi often depends only on Xi, i.e., the system is stateless. The security proof of such a system (e.g. a block cipher) amounts to showing that it is indistinguishable from a certain perfect system (e.g. a random permutation). We propose a general framework for proving the indistinguishability of two random systems, based on the concept of the equivalence of two systems, conditioned on certain events. This abstraction demonstrates the common denominator among many security proofs in the literature, allows to unify, simplify, generalize, and in some cases strengthen them, and opens the door to proving new indistinguishability results. We also propose the previously implicit concept of quasi-randomness and give an efficient construction of a quasi-random function which can be used as a building block in cryptographic systems based on pseudorandom functions.

CEC : Research in visualization techniques for field construction <=SEP=> Field construction can be planned, monitored, and controlled at two distinct levels: 1) the activity or schedule level; and 2) the operation or process level. Graphical 3D visualization can serve as an effective communication method at both levels. Several research efforts in visualizing construction are rooted in scheduling. They typically involve linking activity-based construction schedules and 3D CAD models of facilities to describe discretely-evolving construction “product” visualizations (often referred to as 4D CAD). The focus is on communicating what component(s) are built where and when, with the intention of studying the optimal activity sequence, spatial, and temporal interferences, etc. The construction processes or operations actually involved in building the components are usually implied. A second approach in visualizing construction is rooted in discrete-event simulation that, in addition to visualizing evolving construction products, also concerns the visualization of the operations and processes that are performed in building them. In addition to what is built where and when, the approach communicates who builds it and how by depicting the interaction between involved machines, resources, and materials. This paper introduces the two approaches, and describes the differences in concept, form, and content between activity level and operations level construction visualization. An example of a structural steel framing operation is presented to elucidate the comparison. This work was originally published in the proceedings of the 2002 IEEE Winter Simulation Conference (Kamat and Martinez 2002). This paper expands on the original work, by describing recent advances in both activity and operations level construction visualization.

Brain—Computer Interface <=SEP=> Human-computer interfaces (HCIs) have become ubiquitous. Interfaces such as keyboards and mouses are used daily while interacting with computing devices (Ebrahimi et al., 2003). There is a developing need, however, for HCIs that can be used in situations where these typical interfaces are not viable. Direct brain-computer interfaces (BCI) is a developing field that has been adding this new dimension of functionality to HCI. BCI has created a novel communication channel, especially for those users who are unable to generate necessary muscular movements to use typical HCI devices.

Human Performance Issues and User Interface Design for Teleoperated Robots <=SEP=> In the future, it will become more common for humans to team up with robotic systems to perform tasks that humans cannot realistically accomplish alone. Even for autonomous and semiautonomous systems, teleoperation will be an important default mode. However, teleoperation can be a challenging task because the operator is remotely located. As a result, the operator's situation awareness of the remote environment can be compromised and the mission effectiveness can suffer. This paper presents a detailed examination of more than 150 papers covering human performance issues and suggested mitigation solutions. The paper summarizes the performance decrements caused by video images bandwidth, time lags, frame rates, lack of proprioception, frame of reference, two-dimensional views, attention switches, and motion effects. Suggested solutions and their limitations include stereoscopic displays, synthetic overlay, multimodal interfaces, and various predicative and decision support systems.

Study on advantages and disadvantages of Cloud Computing – the advantages of Telemetry Applications in the Cloud <=SEP=> As companies of all shapes and sizes begin to adapt to cloud computing, this new technology is evolving like never before. Industry experts believe that this trend will only continue to grow and develop even further in the coming few years. While Cloud computing is undoubtedly beneficial for mid-size to large companies, it is not without its downsides, especially for smaller businesses. In this paper we are presenting a list of advantages and disadvantages of Cloud computing technology, with a view to helping enterprises fully understand and adopt the concept of Cloud computing. Also, in the last chapter we are presenting a cloud application for telemetry with a focus on monitoring hydro-energy, in order to demonstrate the advantages that cloud technology can have for this domain. We consider that the way to make cloud vastly benefit all types of businesses is to know very well it's ups and downs and adapt to them accordingly. Key-Words: Cloud Computing, Grid Computing, telemetry, architecture, advantages, disadvantages.

Finding a Needle in Haystack: Facebook's Photo Storage <=SEP=> Facebook needed an architecture to address the need of storing metadata to find photos on storage machines efficiently in memory. They realized that storing a single photo in a single file would prevent them from achieving this goal; thus, they chose to store multiple photos in a single file, reducing the metadata overhead and making it more possible to store the metadata in memory. They ultimately came up with an architecture that consists of a Haystack Store (the persistent storage), Haystack Directory (used to locate photos and manage storage), and Haystack Cache (used to provide quick access to photos not found in the CDN but generating a large number of requests from users). Their architecture allowed them to choose whether to use a CDN or not, but in either case, the Cache was used to address the issue of the “long tail” problem, where less popular photos still generate requests, and does so by having any request from the user directly be stored in the Cache or by having photos fetched from a write-enabled machine to be stored in the Cache. Haystack addressed the potential of failures wiping inmemory data structures by storing these structures in index files. These index files are updated asynchronously of writes preventing performance decrease. To efficiently handle modifications, Haystack chose to append modified files to the end of the file as well as record file to delete the old version of the file. The old version of the file, along with any files marked deleted through delete requests are deleted through an operation called compaction, which takes files not marked deleted or only new versions of modified file and stores it in a new file on disk. This way, deletes and modifications are handled asynchronously of writes and thus is efficient.

Similarity Preserving Snippet-Based Visualization of Web Search Results <=SEP=> Internet users are very familiar with the results of a search query displayed as a ranked list of snippets. Each textual snippet shows a content summary of the referred document (or webpage) and a link to it. This display has many advantages, for example, it affords easy navigation and is straightforward to interpret. Nonetheless, any user of search engines could possibly report some experience of disappointment with this metaphor. Indeed, it has limitations in particular situations, as it fails to provide an overview of the document collection retrieved. Moreover, depending on the nature of the query for example, it may be too general, or ambiguous, or ill expressed the desired information may be poorly ranked, or results may contemplate varied topics. Several search tasks would be easier if users were shown an overview of the returned documents, organized so as to reflect how related they are, content wise. We propose a visualization technique to display the results of web queries aimed at overcoming such limitations. It combines the neighborhood preservation capability of multidimensional projections with the familiar snippet-based representation by employing a multidimensional projection to derive two-dimensional layouts of the query search results that preserve text similarity relations, or neighborhoods. Similarity is computed by applying the cosine similarity over a "bag-of-wordsâ' vector representation of collection built from the snippets. If the snippets are displayed directly according to the derived layout, they will overlap considerably, producing a poor visualization. We overcome this problem by defining an energy functional that considers both the overlapping among snippets and the preservation of the neighborhood structure as given in the projected layout. Minimizing this energy functional provides a neighborhood preserving two-dimensional arrangement of the textual snippets with minimum overlap. The resulting visualization conveys both a global view of the query results and visual groupings that reflect related results, as illustrated in several examples shown.

The Tale of e-Government: A Review of the Stories that Have Been Told So Far and What is Yet to Come <=SEP=> Since its first appearance, the concept of eGovernment has evolved into a recognized means that has helped the public sector to increase its efficiency and effectiveness. A lot of research has therefore been done in this area to elaborate on the different aspects encompassing this concept. However, when looking at the existing e-Government literature, research mostly focuses on one specific aspect of e-Government and there are few generic publications that provide an overview of the diversity of this interdisciplinary research field over a longer term period. This study analyzes the abstracts of eight e-Government journals from 2000 to 2016 by means of a quantitative text mining analysis, backed by a qualitative Delphi approach. The article concludes with a discussion on the findings and implications as well as directions for future research.

Public health implications of altered puberty timing. <=SEP=> Changes in puberty timing have implications for the treatment of individual children, for the risk of later adult disease, and for chemical testing and risk assessment for the population. Children with early puberty are at a risk for accelerated skeletal maturation and short adult height, early sexual debut, potential sexual abuse, and psychosocial difficulties. Altered puberty timing is also of concern for the development of reproductive tract cancers later in life. For example, an early age of menarche is a risk factor for breast cancer. A low age at male puberty is associated with an increased risk for testicular cancer according to several, but not all, epidemiologic studies. Girls and, possibly, boys who exhibit premature adrenarche are at a higher risk for developing features of metabolic syndrome, including obesity, type 2 diabetes, and cardiovascular disease later in adulthood. Altered timing of puberty also has implications for behavioral disorders. For example, an early maturation is associated with a greater incidence of conduct and behavior disorders during adolescence. Finally, altered puberty timing is considered an adverse effect in reproductive toxicity risk assessment for chemicals. Recent US legislation has mandated improved chemical testing approaches for protecting children's health and screening for endocrine-disrupting agents, which has led to changes in the US Environmental Protection Agency's risk assessment and toxicity testing guidelines to include puberty-related assessments and to the validation of pubertal male and female rat assays for endocrine screening.

Effect of written emotional expression on immune function in patients with human immunodeficiency virus infection: a randomized trial. <=SEP=> OBJECTIVES
To determine whether writing about emotional topics compared with writing about neutral topics could affect CD4+ lymphocyte count and human immunodeficiency virus (HIV) viral load among HIV-infected patients.


METHODS
Thirty-seven HIV-infected patients were randomly allocated to 2 writing conditions focusing on emotional or control topics. Participants wrote for 4 days, 30 minutes per day. The CD4+ lymphocyte count and HIV viral load were measured at baseline and at 2 weeks, 3 months, and 6 months after writing.


RESULTS
The emotional writing participants rated their essays as more personal, valuable, and emotional than those in the control condition. Relative to the drop in HIV viral load, CD4+ lymphocyte counts increased after the intervention for participants in the emotional writing condition compared with control writing participants.


CONCLUSIONS
The results are consistent with those of previous studies using emotional writing in other patient groups. Based on the self-reports of the value of writing and the preliminary laboratory findings, the results suggest that emotional writing may provide benefit for patients with HIV infection.

A Quantitative Comparison of Semantic Web Page Segmentation Approaches <=SEP=> This paper explores the effectiveness of different semantic web page segmentation algorithms on modern websites. We compare three known algorithms each serving as an example of a particular approach to the problem, and one self-developed algorithm, WebTerrain, that combines two of the approaches. With our testing framework we have compared the performance of four algorithms for a large benchmark we have constructed. We have examined each algorithm for a total of eight different configurations (varying datasets, evaluation metric and the type of the input HTML documents). We found that all algorithms performed better on random pages on average than on popular pages, and results are better when running the algorithms on the HTML obtained from the DOM rather than on the plain HTML. Overall there is much room for improvement as we find the best average F-score to be 0.49, indicating that for modern websites currently available algorithms are not yet of practical use.

Smith-Petersen osteotomy in thoracolumbar deformity surgery. <=SEP=> OBJECTIVE
To describe the technique and indications of a Smith-Petersen osteotomy in spinal deformity surgery.


METHODS
Pertinent literature was reviewed to describe the indications and reported complications of this corrective technique.


RESULTS
The operative nuances of the technique are described.


CONCLUSION
A Smith-Petersen osteotomy is a safe and effective surgical technique to obtain correction of spinal deformity in both the sagittal and coronal planes.

Ensembles for unsupervised outlier detection: challenges and research questions a position paper <=SEP=> Ensembles for unsupervised outlier detection is an emerging topic that has been neglected for a surprisingly long time (although there are reasons why this is more difficult than supervised ensembles or even clustering ensembles). Aggarwal recently discussed algorithmic patterns of outlier detection ensembles, identified traces of the idea in the literature, and remarked on potential as well as unlikely avenues for future transfer of concepts from supervised ensembles. Complementary to his points, here we focus on the core ingredients for building an outlier ensemble, discuss the first steps taken in the literature, and identify challenges for future research.

Efficient SIMD code generation for runtime alignment and length conversion <=SEP=> When generating codes for today's multimedia extensions, one of the major challenges is to deal with memory alignment issues. While hand programming still yields best performing SIMD codes, it is both time consuming and error prone. Compiler technology has greatly improved, including techniques that simdize loops with misaligned accesses by automatically rearranging mis-aligned memory streams in registers. Current techniques are applicable to runtime alignments, but they aggressively reduce the alignment overhead only when all alignments are known at compile time. This paper presents two major enhancements to the state of the art, improving both performance and coverage. First, we propose a novel technique to simdize loops with runtime alignment nearly as efficiently as those with compile-time misalignment. Runtime alignment is pervasive in real applications because it is either part of the algorithms, or it is an artifact of the compiler's inability to extract accurate alignment information from complex applications. Second, we incorporate length conversion operations, e.g., conversions between data of different sizes, into the alignment handling framework. Length conversions are pervasive in multimedia applications where mixed integer types are often used. Supporting length conversion can greatly improve the coverage of simdizable loops. Experimental results indicate that our runtime alignment technique achieves a 19% to 32% speedup increase over prior art for a benchmark stressing the impact of misaligned data. We also demonstrate speedup factors of up to 8.11 for real benchmarks over sequential execution.

Turning the Waiting Room into a Classroom: Weekly Classes Using a Vegan or a Portion-Controlled Eating Plan Improve Diabetes Control in a Randomized Translational Study. <=SEP=> BACKGROUND
In research settings, plant-based (vegan) eating plans improve diabetes management, typically reducing weight, glycemia, and low-density lipoprotein (LDL) cholesterol concentrations to a greater extent than has been shown with portion-controlled eating plans.


OBJECTIVE
The study aimed to test whether similar benefits could be found using weekly nutrition classes in a typical endocrinology practice, hypothesizing that a vegan eating plan would improve glycemic control, weight, lipid concentrations, blood pressure, and renal function and would do so more effectively than a portion-controlled eating plan.


DESIGN
In a 20-week trial, participants were randomly assigned to a low-fat vegan or portion-controlled eating plan.


PARTICIPANTS/SETTING
Individuals with type 2 diabetes treated in a single endocrinology practice in Washington, DC, participated (45 starters, 40 completers).


INTERVENTION
Participants attended weekly after-hours classes in the office waiting room. The vegan plan excluded animal products and added oils and favored low-glycemic index foods. The portion-controlled plan included energy intake limits for weight loss (typically a deficit of 500 calories/day) and provided guidance on portion sizes.


MAIN OUTCOME MEASURES
Body weight, hemoglobin A1c (HbA1c), plasma lipids, urinary albumin, and blood pressure were measured.


STATISTICAL ANALYSES PERFORMED
For normally distributed data, t tests were used; for skewed outcomes, rank-based approaches were implemented (Wilcoxon signed-rank test for within-group changes, Wilcoxon two-sample test for between-group comparisons, and exact Hodges-Lehmann estimation to estimate effect sizes).


RESULTS
Although participants were in generally good metabolic control at baseline, body weight, HbA1c, and LDL cholesterol improved significantly within each group, with no significant differences between the two eating plans (weight: -6.3 kg vegan, -4.4 kg portion-controlled, between-group P=0.10; HbA1c, -0.40 percentage point in both groups, P=0.68; LDL cholesterol -11.9 mg/dL vegan, -12.7 mg/dL portion-controlled, P=0.89). Mean urinary albumin was normal at baseline and did not meaningfully change. Blood pressure changes were not significant.


CONCLUSIONS
Weekly classes, integrated into a clinical practice and using either a low-fat vegan or portion-controlled eating plan, led to clinical improvements in individuals with type 2 diabetes.

On Two Metaphors for Learning and the Dangers of Choosing Just One <=SEP=> The upshots of the former section can be put as follows: All our concepts and beliefs have their roots in a limited number of fundamental ideas that cross disciplinary boundaries and are carried from one domain to another by the language we use. One glance at the current discourse on learning should be enough to realize that nowadays educational research is caught between two metaphors that, in this article, will be called the acquisition metaphor and the participation metaphor. Both of these metaphors are simultaneously present in most recent texts, but while the acquisition metaphor is likely to be more prominent in older writings, more recent studies are often dominated by the participation metaphor.

Visual feature integration and the temporal correlation hypothesis. <=SEP=> The mammalian visual system is endowed with a nearly infinite capacity for the recognition of patterns and objects. To have acquired this capability the visual system must have solved what is a fundamentally combinatorial problem. Any given image consists of a collection of features, consisting of local contrast borders of luminance and wavelength, distributed across the visual field. For one to detect and recognize an object within a scene, the features comprising the object must be identified and segregated from those comprising other objects. This problem is inherently difficult to solve because of the combinatorial nature of visual images. To appreciate this point, consider a simple local feature such as a small vertically oriented line segment placed within a fixed location of the visual field. When combined with other line segments, this feature can form a nearly infinite number of geometrical objects. Any one of these objects may coexist with an equally large number of other

Virgin soil in irony research : Personality , humor , and the “ sense of irony ” <=SEP=> he aim of the paper is fourfold: (a) show why humor scholars should study irony, (b) explore the need for considering interindividual differences in healthy adults’ irony performance, (c) stress the necessity for developing tools assessing habitual differences in irony performance, and (d) indicate future directions for joint irony and humor research and outline possible applications. Verbal irony is often employed with a benevolent humorous intent by speakers, but can also serve as a means of disparagement humor. In both cases, encoding and decoding activities entailing irony need to be considered in the context of the psychology of humor. We argue that verbal irony performance can be considered a phenomenon native to the realm of humor and individual differences. We point out that research has widely neglected the meaningfulness of variance in irony performance within experimental groups when looking at determinants of irony detection and production. Based on theoretical considerations and previous empirical findings we show that this variance can be easily related to individual-differences variables such as the sense of humor, dispositions toward laughter and ridicule (e.g., gelotophobia), and general mental ability. Furthermore, we hypothesize that there is an enduring trait determining irony performance we will label the sense of irony. The sense of irony possibly goes along with inclinations toward specific affective and cognitive processing patterns when dealing with verbal irony. As an application, novel irony performance tests can help to study psychological and neurophysiological correlates of irony performance more feasibly, that is, in nonclinical groups. DOI: https://doi.org/10.1037/tps0000054 Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-124094 Accepted Version Originally published at: Bruntsch, Richard; Hofmann, Jennifer; Ruch, Willibald (2016). Virgin soil in irony research: Personality, humor, and the “sense of irony”. Translational Issues in Psychological Science, 2(1):25-34. DOI: https://doi.org/10.1037/tps0000054 VIRGIN SOIL IN IRONY RESEARCH 1 Running head: VIRGIN SOIL IN IRONY RESEARCH Virgin soil in irony research: Personality, humor, and the “sense of irony”