bluuebunny/crossref_metadata_2025 huggingface dataset:
HMLFC: Hierarchical Motion‐Compensated Light Field Compression for Interactive Rendering
Authors: Pratapa S. , Manocha D.
Published: November 2019

We present a new motion‐compensated hierarchical compression scheme (HMLFC) for encoding light field images (LFI) that is suitable for interactive rendering. Our method combines two different approaches, motion compensation schemes and hierarchical compression methods, to exploit redundancies in LFI. The motion compensation schemes capture the redundancies in local regions of the LFI efficiently (local coherence) and the hierarchical schemes capture the redundancies present across the entire LFI (global coherence). Our hybrid approach combines the two schemes effectively capturing both local as well as global coherence to improve the overall compression rate. We compute a tree from LFI using a hierarchical scheme and use phase shifted motion compensation techniques at each level of the hierarchy. Our representation provides random access to the pixel values of the light field, which makes it suitable for interactive rendering applications using a small run‐time memory footprint. Our approach is GPU friendly and allows parallel decoding of LF pixel values. We highlight the performance on the two‐plane parameterized light fields and obtain a compression ratio of 30–800× with a PSNR of 40–45 dB. Overall, we observe a ∼2–5× improvement in compression rates using HMLFC over prior light field compression schemes that provide random access capability. In practice, our algorithm can render new views of resolution 512 × 512 on an NVIDIA GTX‐980 at ∼200 fps.
An Efficient Solution to Structured Optimization Problems using Recursive Matrices
Authors: Rückert D. , Stamminger M.
Published: November 2019

We present a linear algebra framework for structured matrices and general optimization problems. The matrices and matrix operations are defined recursively to efficiently capture complex structures and enable advanced compiler optimization. In addition to common dense and sparse matrix types, we define mixed matrices, which allow every element to be of a different type. Using mixed matrices, the low‐ and high‐level structure of complex optimization problems can be encoded in a single type. This type is then analyzed at compile time by a recursive linear solver that picks the optimal algorithm for the given problem. For common computer vision problems, our system yields a speedup of 3–5 compared to other optimization frameworks. The BLAS performance is benchmarked against the MKL library. We achieve a significant speedup in block‐SPMV and block‐SPMM. This work is implemented and released open‐source as a header‐only extension to the C+ + math library Eigen.
Succinct Palette and Color Model Generation and Manipulation Using Hierarchical Representation
Authors: Jeong Taehong , Yang Myunghyun , Shin Hyun Joon
Published: November 2019

We propose a new method to obtain the representative colors and their distributions of an image. Our intuition is that it is possible to derive the global model from the local distributions. Beginning by sampling pure colors, we build a hierarchical representation of colors in the image via a bottom‐up approach. From the resulting hierarchy, we can obtain satisfactory palettes/color models automatically without a predefined size. Furthermore, we provide interactive operations to manipulate the results which allow the users to reflect their intention directly. In our experiment, we show that the proposed method produces more succinct results that faithfully represent all the colors in the image with an appropriate number of components. We also show that the proposed interactive approach can improve the results of applications such as recoloring and soft segmentation.
Procedural Riverscapes
Authors: Peytavie A. , Dupont T. , Guérin E. , Cortial Y. , Benes B. , Gain J. , Galin E.
Published: November 2019

This paper addresses the problem of creating animated riverscapes through a novel procedural framework that generates the inscribing geometry of a river network and then synthesizes matching real‐time water movement animation. Our approach takes bare‐earth heightfields as input, derives hydrologically‐inspired river network trajectories, carves riverbeds into the terrain, and then automatically generates a corresponding blend‐flow tree for the water surface. Characteristics, such as the riverbed width, depth and shape, as well as elevation and flow of the fluid surface, are procedurally derived from the terrain and river type. The riverbed is inscribed by combining compactly supported elevation modifiers over the river course. Subsequently, the water surface is defined as a time‐varying continuous function encoded as a blend‐flow tree with leaves that are parameterized procedural flow primitives and internal nodes that are blend operators. While river generation is fully automated, we also incorporate intuitive interactive editing of both river trajectories and individual riverbed and flow primitives. The resulting framework enables the generation of a wide range of river forms, ranging from slow meandering rivers to rapids with churning water, including surface effects, such as foam and leaves carried downstream.
Desertscape Simulation
Authors: Paris A. , Peytavie A. , Guérin E. , Argudo O. , Galin E.
Published: November 2019

We present an interactive aeolian simulation to author hot desert scenery. Wind is an important erosion agent in deserts which, despite its importance, has been neglected in computer graphics. Our framework overcomes this and allows generating a variety of sand dunes, including barchans, longitudinal and anchored dunes, and simulates abrasion which erodes bedrock and sculpts complex landforms. Given an input time varying high altitude wind field, we compute the wind field at the surface of the terrain according to the relief, and simulate the transport of sand blown by the wind. The user can interactively model complex desert landscapes, and control their evolution throughout time either by using a variety of interactive brushes or by prescribing events along a user‐defined time‐line.
Parallel Generation and Visualization of Bacterial Genome Structures
Authors: Klein T. , Mindek P. , Autin L. , Goodsell D. S. , Olson A. J. , Gröller E. M. , Viola I.
Published: November 2019

Visualization of biological mesoscale models provides a glimpse at the inner workings of living cells. One of the most complex components of these models is DNA, which is of fundamental importance for all forms of life. Modeling the 3D structure of genomes has previously only been attempted by sequential approaches. We present the first parallel approach for the instant construction of DNA structures. Traditionally, such structures are generated with algorithms like random walk, which have inherent sequential constraints. These algorithms result in the desired structure, are easy to control, and simple to formulate. Their execution, however, is very time‐consuming, as they are not designed to exploit parallelism. We propose an approach to parallelize the process, facilitating an implementation on the GPU.
Imitating Popular Photos to Select Views for an Indoor Scene
Authors: Su Rung‐De , Liao Zhe‐Yo , Chen Li‐Chi , Tung Ai‐Ling , Wang Yu‐Shuen
Published: November 2019

Selecting informative and visually appealing views for 3D indoor scenes is beneficial for the housing, decoration, and entertainment industries. A set of views that exhibit comfort, aesthetics, and functionality of a particular scene can attract customers and facilitate business transactions. However, selecting views for an indoor scene is challenging because the system has to consider not only the need to reveal as much information as possible, but also object arrangements, occlusions, and characteristics. Since there can be many principles utilized to guide the view selection, and various principles to follow under different circumstances, we achieve the goal by imitating popular photos on the Internet. Specifically, we select the view that can optimize the contour similarity of corresponding objects to the photo. Because the selected view can be inadequate if object arrangements in the 3D scene and the photo are different, our system imitates many popular photos and selects a certain number of views. After that, it clusters the selected views and determines the view/cluster centers by the weighted average to finally exhibit the scene. Experimental results demonstrate that the views selected by our method are visually appealing.
Rain Wiper: An Incremental Randomly Wired Network for Single Image Deraining
Authors: Liang X. , Qiu B. , Su Z. , Gao C. , Shi X. , Wang R.
Published: November 2019

Single image rain removal is a challenging ill‐posed problem due to various shapes and densities of rain streaks. We present a novel incremental randomly wired network (IRWN) for single image deraining. Different from previous methods, most structures of modules in IRWN are generated by a stochastic network generator based on the random graph theory, which ease the burden of manual design and further help to characterize more complex rain streaks. To decrease network parameters and extract more details efficiently, the image pyramid is fused via the multi‐scale network structure. An incremental rectified loss is proposed to better remove rain streaks in different rain conditions and recover the texture information of target objects. Extensive experiments on synthetic and real‐world datasets demonstrate that the proposed method outperforms the state‐of‐the‐art methods significantly. In addition, an ablation study is conducted to illustrate the improvements obtained by different modules and loss items in IRWN.
Field‐aligned Quadrangulation for Image Vectorization
Authors: Wei Guangshun , Zhou Yuanfeng , Gao Xifeng , Ma Qian , Xin Shiqing , He Ying
Published: November 2019

Image vectorization is an important yet challenging problem, especially when the input image has rich content. In this paper, we develop a novel method for automatically vectorizing natural images with feature‐aligned quad‐dominant meshes. Inspired by the quadrangulation methods in 3D geometry processing, we propose a new directional field optimization technique by encoding the color gradients, sidestepping the explicit computing of salient image features. We further compute the anisotropic scales of the directional field by accommodating the distance among image features. Our method is fully automatic and efficient, which takes only a few seconds for a 400×400 image on a normal laptop. We demonstrate the effectiveness of the proposed method on various image editing applications.
ManyLands: A Journey Across 4D Phase Space of Trajectories
Authors: Amirkhanov Aleksandr , Kosiuk Ilona , Szmolyan Peter , Amirkhanov Artem , Mistelbauer Gabriel , Gröller M. Eduard , Raidou Renata G.
Published: November 2019

Mathematical models of ordinary differential equations are used to describe and understand biological phenomena. These models are dynamical systems that often describe the time evolution of more than three variables, i.e., their dynamics take place in a multi‐dimensional space, called the phase space. Currently, mathematical domain scientists use plots of typical trajectories in the phase space to analyze the qualitative behavior of dynamical systems. These plots are called phase portraits and they perform well for 2D and 3D dynamical systems. However, for 4D, the visual exploration of trajectories becomes challenging, as simple subspace juxtaposition is not sufficient. We propose ManyLands to support mathematical domain scientists in analyzing 4D models of biological systems. By describing the subspaces as Lands, we accompany domain scientists along a continuous journey through 4D HyperLand, 3D SpaceLand, and 2D FlatLand, using seamless transitions. The Lands are also linked to 1D TimeLines. We offer an additional dissected view of trajectories that relies on small‐multiple compass‐alike pictograms for easy navigation across subspaces and trajectory segments of interest. We show three use cases of 4D dynamical systems from cell biology and biochemistry. An informal evaluation with mathematical experts confirmed that ManyLands helps them to visualize and analyze complex 4D dynamics, while facilitating mathematical experiments and simulations.
Inertia‐based Fast Vectorization of Line Drawings
Authors: Najgebauer Patryk , Scherer Rafał
Published: November 2019

Image vectorisation is a fundamental method in graphic design and is one of the tools allowing to transfer artist work into computer graphics. The existing methods are based mainly on segmentation, or they analyse every image pixel; thus, they are relatively slow. We introduce a novel method for fast line drawing image vectorisation, based on a multi‐scale second derivative detector accelerated by the summed‐area table and an auxiliary grid. Image is scanned initially along the grid lines, and nodes are added to improve accuracy. Applying inertia in the line tracing allows for better junction mapping in a single pass. Our method is dedicated to grey‐scale sketches and line drawings. It works efficiently regardless of the thickness of the line or its shading. Experiments show it is more than two orders of magnitude faster than the existing methods, not sacrificing accuracy.
Automatic modeling of cluttered multi‐room floor plans from panoramic images
Authors: Pintore Giovanni , Ganovelli Fabio , Villanueva Alberto Jaspe , Gobbetti Enrico
Published: November 2019

We present a novel and light‐weight approach to capture and reconstruct structured 3D models of multi‐room floor plans. Starting from a small set of registered panoramic images, we automatically generate a 3D layout of the rooms and of all the main objects inside. Such a 3D layout is directly suitable for use in a number of real‐world applications, such as guidance, location, routing, or content creation for security and energy management. Our novel pipeline introduces several contributions to indoor reconstruction from purely visual data. In particular, we automatically partition panoramic images in a connectivity graph, according to the visual layout of the rooms, and exploit this graph to support object recovery and rooms boundaries extraction. Moreover, we introduce a plane‐sweeping approach to jointly reason about the content of multiple images and solve the problem of object inference in a top‐down 2D domain. Finally, we combine these methods in a fully automated pipeline for creating a structured 3D model of a multi‐room floor plan and of the location and extent of clutter objects. These contribution make our pipeline able to handle cluttered scenes with complex geometry that are challenging to existing techniques. The effectiveness and performance of our approach is evaluated on both real‐world and synthetic models.
A Unified Neural Network for Panoptic Segmentation
Authors: Yao L. , Chyau A.
Published: November 2019

In this paper, we propose a unified neural network for panoptic segmentation, a task aiming to achieve more fine‐grained segmentation. Following existing methods combining semantic and instance segmentation, our method relies on a triple‐branch neural network for tackling the unifying work. In the first stage, we adopt a ResNet50 with a feature pyramid network (FPN) as shared backbone to extract features. Then each branch leverages the shared feature maps and serves as the stuff, things, or mask branch. Lastly, the outputs are fused following a well‐designed strategy. Extensive experimental results on MS‐COCO dataset demonstrate that our approach achieves a competitive Panoptic Quality (PQ) metric score with the state of the art.
Offline Deep Importance Sampling for Monte Carlo Path Tracing
Authors: Bako Steve , Meyer Mark , DeRose Tony , Sen Pradeep
Published: November 2019

Although modern path tracers are successfully being applied to many rendering applications, there is considerable interest to push them towards ever‐decreasing sampling rates. As the sampling rate is substantially reduced, however, even Monte Carlo (MC) denoisers–which have been very successful at removing large amounts of noise–typically do not produce acceptable final results. As an orthogonal approach to this, we believe that good importance sampling of paths is critical for producing better‐converged, path‐traced images at low sample counts that can then, for example, be more effectively denoised. However, most recent importance‐sampling techniques for guiding path tracing (an area known as “path guiding”) involve expensive online (per‐scene) training and offer benefits only at high sample counts. In this paper, we propose an offline, scene‐independent deep‐learning approach that can importance sample first‐bounce light paths for general scenes without the need of the costly online training, and can start guiding path sampling with as little as 1 sample per pixel. Instead of learning to “overfit” to the sampling distribution of a specific scene like most previous work, our data‐driven approach is trained a priori on a set of training scenes on how to use a local neighborhood of samples with additional feature information to reconstruct the full incident radiance at a point in the scene, which enables first‐bounce importance sampling for new test scenes. Our solution is easy to integrate into existing rendering pipelines without the need for retraining, as we demonstrate by incorporating it into both the Blender/Cycles and Mitsuba path tracers. Finally, we show how our offline, deep importance sampler (ODIS) increases convergence at low sample counts and improves the results of an off‐the‐shelf denoiser relative to other state‐of‐the‐art sampling techniques.
Learning to Predict Image‐based Rendering Artifacts with Respect to a Hidden Reference Image
Authors: Bemana M. , Keinert J. , Myszkowski K. , Bätz M. , Ziegler M. , Seidel H.‐P. , Ritschel T.
Published: November 2019

Image metrics predict the perceived per‐pixel difference between a reference image and its degraded (e. g., re‐rendered) version. In several important applications, the reference image is not available and image metrics cannot be applied. We devise a neural network architecture and training procedure that allows predicting the MSE, SSIM or VGG16 image difference from the distorted image alone while the reference is not observed. This is enabled by two insights: The first is to inject sufficiently many un‐distorted natural image patches, which can be found in arbitrary amounts and are known to have no perceivable difference to themselves. This avoids false positives. The second is to balance the learning, where it is carefully made sure that all image errors are equally likely, avoiding false negatives. Surprisingly, we observe that the resulting no‐reference metric, subjectively, can even perform better than the reference‐based one, as it had to become robust against mis‐alignments. We evaluate the effectiveness of our approach in an image‐based rendering context, both quantitatively and qualitatively. Finally, we demonstrate two applications which reduce light field capture time and provide guidance for interactive depth adjustment.
Mesh Defiltering via Cascaded Geometry Recovery
Authors: Wei M. , Guo X. , Huang J. , Xie H. , Zong H. , Kwan R. , Wang F. L. , Qin J.
Published: November 2019

This paper addresses the nontraditional but practically meaningful reversibility problem of mesh filtering. This reverse‐filtering approach (termed a DeFilter) seeks to recover the geometry of a set of filtered meshes to their artifact‐free status. To solve this scenario, we adapt cascaded normal regression (CNR) to understand the commonly used mesh filters and recover automatically the mesh geometry that was lost through various geometric operations. We formulate mesh defiltering by an extreme learning machine (ELM) on the mesh normals at an offline training stage and perform it automatically at a runtime defiltering stage. Specifically, (1) to measure the local geometry of a filtered mesh, we develop a generalized reverse Filtered Facet Normal Descriptor (grFND) in the consistent neighbors; (2) to map the grFNDs to the normals of the ground‐truth meshes, we learn a regression function from a set of filtered meshes and their ground‐truth counterparts; and (3) at runtime, we reversely filter the normals of a filtered mesh, using the learned regression function for recovering the lost geometry. We evaluate multiple quantitative and qualitative results on synthetic and real data to verify our DeFilter's performance thoroughly. From a practical point of view, our method can recover the lost geometry of denoised meshes without needing to know the exact filter used previously, and can act as a geometry‐recovery plugin for most of the state‐of‐the‐art methods of mesh denoising.
Single‐View Modeling of Layered Origami with Plausible Outer Shape
Authors: Kato Y. , Tanaka S. , Kanamori Y. , Mitani J.
Published: November 2019

Modeling 3D origami pieces using conventional software is laborious due to the geometric constraints imposed by the complicated layered structure. Targeting origami models used in visual content such as CG illustrations and movies, we propose an interactive system that dramatically simplifies the modeling of 3D origami pieces with plausible outer shapes, while omitting accurate inner structures. By focusing on flat origami models with a front‐and‐back symmetry commonly found in traditional artworks, our system realizes easy and quick modeling via single‐view interface; given a reference image of the target origami piece, the user draws polygons of planar faces onto the image, and assigns annotations indicating the types of folding operations. Our system automatically rectifies the manually‐specified polygons, infers the folded structures that should yield the user‐specified polygons with reference to the depth order of layered polygons, and generates a plausible 3D model while accounting for gaps between layers. Our system is versatile enough for modeling pseudo‐origami models that are not realizable by folding a single sheet of paper. Our user study demonstrates that even novice users without the specialized knowledge and experience on origami and 3D modeling can create plausible origami models quickly.
Wavelet Flow: Optical Flow Guided Wavelet Facial Image Fusion
Authors: Ding Hong , Yan Qingan , Fu Gang , Xiao Chunxia
Published: November 2019

Estimating the correspondence between the images using optical flow is the key component for image fusion, however, computing optical flow between a pair of facial images including backgrounds is challenging due to large differences in illumination, texture, color and background in the images. To improve optical flow results for image fusion, we propose a novel flow estimation method, wavelet flow, which can handle both the face and background in the input images. The key idea is that instead of computing flow directly between the input image pair, we estimate the image flow by incorporating multi‐scale image transfer and optical flow guided wavelet fusion. Multi‐scale image transfer helps to preserve the background and lighting detail of input, while optical flow guided wavelet fusion produces a series of intermediate images for further fusion quality optimizing. Our approach can significantly improve the performance of the optical flow algorithm and provide more natural fusion results for both faces and backgrounds in the images. We evaluate our method on a variety of datasets to show its high outperformance.
Global Texture Mapping for Dynamic Objects
Authors: Kim Jungeon , Kim Hyomin , Park Jaesik , Lee Seungyong
Published: November 2019

We propose a novel framework to generate a global texture atlas for a deforming geometry. Our approach distinguishes from prior arts in two aspects. First, instead of generating a texture map for each timestamp to color a dynamic scene, our framework reconstructs a global texture atlas that can be consistently mapped to a deforming object. Second, our approach is based on a single RGB‐D camera, without the need of a multiple‐camera setup surrounding a scene. In our framework, the input is a 3D template model with an RGB‐D image sequence, and geometric warping fields are found using a state‐of‐the‐art non‐rigid registration method [GXW*15] to align the template mesh to noisy and incomplete input depth images. With these warping fields, our multi‐scale approach for texture coordinate optimization generates a sharp and clear texture atlas that is consistent with multiple color observations over time. Our approach is accelerated by graphical hardware and provides a handy configuration to capture a dynamic geometry along with a clean texture atlas. We demonstrate our approach with practical scenarios, particularly human performance capture. We also show that our approach is resilient on misalignment issues caused by imperfect estimation of warping fields and inaccurate camera parameters.
Anisotropic Surface Remeshing without Obtuse Angles
Authors: Xu Qun‐Ce , Yan Dong‐Ming , Li Wenbin , Yang Yong‐Liang
Published: November 2019

We present a novel anisotropic surface remeshing method that can efficiently eliminate obtuse angles. Unlike previous work that can only suppress obtuse angles with expensive resampling and Lloyd‐type iterations, our method relies on a simple yet efficient connectivity and geometry refinement, which can not only remove all the obtuse angles, but also preserves the original mesh connectivity as much as possible. Our method can be directly used as a post‐processing step for anisotropic meshes generated from existing algorithms to improve mesh quality. We evaluate our method by testing on a variety of meshes with different geometry and topology, and comparing with representative prior work. The results demonstrate the effectiveness and efficiency of our approach.
Context‐Aware Mixed Reality: A Learning‐Based Framework for Semantic‐Level Interaction
Authors: Chen L. , Tang W. , John N. W. , Wan T. R. , Zhang J. J.
Published: November 2019

Mixed reality (MR) is a powerful interactive technology for new types of user experience. We present a semantic‐based interactive MR framework that is beyond current geometry‐based approaches, offering a step change in generating high‐level context‐aware interactions. Our key insight is that by building semantic understanding in MR, we can develop a system that not only greatly enhances user experience through object‐specific behaviours, but also it paves the way for solving complex interaction design challenges. In this paper, our proposed framework generates semantic properties of the real‐world environment through a dense scene reconstruction and deep image understanding scheme. We demonstrate our approach by developing a material‐aware prototype system for context‐aware physical interactions between the real and virtual objects. Quantitative and qualitative evaluation results show that the framework delivers accurate and consistent semantic information in an interactive MR environment, providing effective real‐time semantic‐level interactions.
A steganographic method based on optimized audio embedding technique for secure data communication in the internet of things
Authors: S Anguraj , S P Shantharajah , J Jeba Emilyn
Published: November 2019

The rapid growth of the internet and the internet of things (IoT) refers to the next phase of information revolution whose context involves billions of smart devices and sensors interconnected to facilitate speedy information and data exchange under soft real‐time constraints. Digital information revolution has caused significant changes in the data communication. This data communication may require private, secure, and sometimes malicious communication. Competent secrecy can be accomplished by applying novel and inventive audio steganography. This article focuses on the secret message followed by shuffled embedded bit substitution in original audio stream by adopting optimized audio embedding technique (OAET) from the technological observation. To hide the information in the deeper layer of the audio stream, this method uses a new elevated bit range least significant bit (LSB) audio steganography technique that decreases distortion and improves the robustness of the embedded audio stream. The proposed technique proves that the perceptual quality of audio steganography is better than the previous standard LSB technique. Experiment results proved that the cladding of the OAET provides high‐level security to the universal cyber data. The interpretation of results shows that embedding data in audio enhances the level of security when used as IoT smart speakers, where the attackers could not distinguish between the original audio and the embedded audio streams.
‘How Could the Dinosaurs Be So Close to the Future?’: How Natural History Museum Educators Tackle Deep Time
Authors: Hecht Marijke , Knutson Karen , Crowley Kevin , Lyon Mandela , McShea Patrick , Giarratani Lauren
Published: November 2019

Natural history museums play an important role in engaging the public in critical conversations about science and society. However, understanding complex concepts such as the Anthropocene requires thinking at large spatial and temporal scales. This challenge is at the forefront of a research‐practice partnership between the Carnegie Museum of Natural History (Museum) and the University of Pittsburgh Center for Learning in Out‐of‐School Environments (UPCLOSE). Together we designed a tool to help museum educators engage visitors in conceptualizing and connecting deep time with pressing environmental concerns. We observed educators using the tool in two settings: summer camp and on the Museum floor. We then interviewed educators to understand how they frame learning goals for understanding deep time and how their strategies support learner connections to the Anthropocene. While the tool was generally well received by educators, our observations and interviews also revealed two fundamental tensions. One tension was in pedagogical approaches – either inquiry or transmission – and the other was in learning goals – either wonder or relativity. Going forward, the Museum plans to use the tool both for exploration of deep time and as a professional development tool for Museum educators to better balance their use of these different approaches.
Spatio‐temporal dynamics of multi‐trophic communities reveal ecosystem‐wide functional reorganization
Authors: Pecuchet Laurene , Lindegren Martin , Kortsch Susanne , Całkiewicz Joanna , Jurgensone Iveta , Margonski Piotr , Otto Saskia A. , Putnis Ivars , Strāķe Solvita , Nordström Marie C.
Published: November 2019

Large‐scale alterations in marine ecosystems as a response to environmental and anthropogenic pressures have been documented worldwide. Yet, these are primarily investigated by assessing abundance fluctuations of a few dominant species, which inadequately reflect ecosystem‐wide changes. In addition, it is increasingly recognized that it is not species identity per se, but their traits that determine environmental responses, biological interactions and ecosystem functioning. In this study, we investigated long‐term, spatio‐temporal variability in trait composition across multiple organism groups to assess whether functional changes occur in a similar way across trophic levels and whether shifts in trait composition link to environmental change. We combined extensive trait datasets with long‐term surveys (30–40 yr) of four organism groups (phytoplankton, zooplankton, benthic invertebrates and fish) in three environmentally distinct areas of a large marine ecosystem. We found similar temporal trajectories in the community weighted mean trait time‐series of the different trophic groups, revealing ecosystem‐wide functional changes. The traits involved and their dynamics differed between areas, concurrent with climate‐driven changes in temperature and salinity, as well as more local dynamics in nutrients and oxygen. This finding highlights the importance of considering both global climate, as well as local external drivers when studying ecosystem changes. Using a multi‐trophic trait‐based approach, our study demonstrates the importance of integrating community functional dynamics across multiple trophic levels to capture ecosystem‐wide responses which could, ultimately, help moving towards a holistic understanding, assessment and management of marine ecosystems.
Millennial‐scale change in the structure of a Caribbean reef ecosystem and the role of human and natural disturbance
Authors: Cramer Katie L. , O'Dea Aaron , Leonard‐Pingel Jill S. , Norris Richard D.
Published: November 2019

Caribbean coral reefs have transformed into algal‐dominated habitats over the past half‐century, but the role of specific anthropogenic drivers is unresolved due to the lack of ecosystem‐level data predating human disturbance. To better understand the extent and causes of long‐term Caribbean reef declines, we produced a continuous 3000‐yr record of the ecosystem state of three reefs in Bocas del Toro, Caribbean Panama. From fossils and sediments obtained from reef matrix cores, we tracked changes in reef accretion rates and the taxonomic and functional group composition of fish, coral, urchin, bivalve and benthic foraminifera. This dataset provided a comprehensive picture of reef community and environmental change. At all sites, reefs shifted from systems with greater relative abundance of herbivorous fish, epifaunal suspension feeding bivalves and Diadema urchins to systems with greater relative abundance of micropredator fish, infaunal bivalves and Echinometra urchins. These transitions were initiated a millennium ago at two less‐degraded reefs fringing offshore islands and ~250 yr ago at a degraded patch reef near the continental coast. Ecosystem shifts were accompanied by a decline in reef accretion rates, and at the patch reef, a decline in water quality since the 18th century. Within all cores, synchronous increases in infaunal bivalves and declines in herbivorous fish regardless of water quality suggest a loss of hard substrate and increasingly hypoxic sediment conditions related to herbivore loss. While the early timing of ecosystem transitions at the fringing reefs implicates large‐scale hydrological change, the more recent timing of change and loss of water quality at the patch reef implicates terrigenous runoff from land‐clearing. Our whole‐ecosystem reconstruction reveals that reef ecosystem deterioration appears to follow a predictable trajectory whether driven by natural or anthropogenic disturbances and that historical local human activities have quickly unraveled reefs at a scale similar to longer‐term natural environmental change.
Occupancy in dynamic systems: accounting for multiple scales and false positives using environmental DNA to inform monitoring
Authors: Smith Matthew M. , Goldberg Caren S.
Published: November 2019

Occupancy is an important metric to understand current and future trends in populations that have declined globally. In addition, occupancy can be an efficient tool for conducting landscape‐scale and long‐term monitoring. A challenge for occupancy monitoring programs is to determine the appropriate spatial scale of analysis and to obtain precise occupancy estimates for elusive species. We used a multi‐scale occupancy model to assess occupancy of Columbia spotted frogs in the Great Basin, USA, based on environmental DNA (eDNA) detections. We collected three replicate eDNA samples at 220 sites across the Great Basin. We estimated and modeled ecological factors that described watershed and site occupancy at multiple spatial scales simultaneously while accounting for imperfect detection. Additionally, we conducted visual and dipnet surveys at all sites and used our paired detections to estimate the probability of a false positive detection for our eDNA sampling. We applied the estimated false positive rate to our multi‐scale occupancy dataset and assessed changes in model selection. We had higher naïve occupancy estimates for eDNA (0.37) than for traditional survey methods (0.20). We estimated our false positive detection rate per qPCR replicate at 0.023 (95% CI: 0.016–0.033). When the false positive rate was applied to the multi‐scale dataset, we did not observe substantial changes in model selection or parameter estimates. Conservation and resource managers have an increasing need to understand species occupancy in highly variable landscapes where the spatial distribution of habitat changes significantly over time due to climate change and human impact. A multi‐scale occupancy approach can be used to obtain regional occupancy estimates that can account for spatially dynamic differences in availability over time, especially when assessing potential declines. Additionally, this study demonstrates how eDNA can be used as an effective tool for improved occupancy estimates across broad geographic scales for long‐term monitoring.
Rethinking service design for youth with mental health needs: The development of the Youth Wellness Centre, St. Joseph's Healthcare Hamilton
Authors: Wang Alyssa , Tobon Juliana I. , Bieling Peter , Jeffs Lisa , Colvin Eamon , Zipursky Robert B.
Published: November 2019

Aim

This article describes the development and design of the Youth Wellness Centre (YWC), an innovative, youth‐friendly centre providing mental health and addiction services for emerging adults aged 17 to 25 in Hamilton, Canada. We also report on demographic and clinical characteristics of clients to evaluate how the YWC is serving populations at increased risk of developing mental disorders.

Methods

Data were extracted from clinic databases for 1520 youth at the YWC between March 2015 and 2018 to report on demographic characteristics, clinical profiles, primary presenting problems, service use and overall satisfaction with services.

Results

Marginalized groups, particularly street‐involved individuals and LGBTQ+ youth, are highly represented at the YWC, keeping with the centre's mandate of reaching at‐risk populations. Youth at the YWC carry significant mental health burdens, with 80.8% having a history of suicidal ideation and 32.8% having a history of a substance use disorder. The primary route of referral is self‐referral and the number of new clients has increased by nearly 20% in the first 3 years of operations. Overall satisfaction with the centre is on par with or slightly above provincial averages.

Conclusions

The YWC was developed to meet the mental health needs of transition‐aged youth in Hamilton by providing early intervention, system navigation and transition services. The success of the YWC in reaching high‐risk youth is demonstrated by the significant proportion of clients reporting demographic and clinical risk factors associated with increased risk for development of mental disorders. The increasing referrals to the YWC highlight the ongoing need for similar services.
Phenology responses of temperate butterflies to latitude depend on ecological traits
Authors: Faltýnek Fric Zdeněk , Rindoš Michal , Konvička Martin
Published: November 2019

Global change influences species’ seasonal occurrence, or phenology. In cold‐adapted insects, the activity is expected to start earlier with a warming climate, but contradictory evidence exists, and the reactions may be linked to species‐specific traits. Using data from the GBIF database, we selected 105 single‐brooded Holarctic butterflies inhabiting broad latitudinal ranges. We regressed patterns of an adult flight against latitudes of the records, controlling for altitude and year effects. Species with delayed flight periods towards the high latitudes, or stable flight periods across latitudes, prevailed over those that advanced their flight towards the high latitudes. The responses corresponded with the species’ seasonality (flight of early season species was delayed and flight of summer species was advanced at high latitudes) and oceanic vs. continental climatic niches (delays in oceanic, stability in continental species). Future restructuring of butterfly seasonal patterns in high latitudes will reflect climatic niches, and hence the evolutionary history of participating species.
Comparing the efficacy, exposure, and cost of clinical trial analysis methods
Authors: Oliveira Andreas , Romero Juan M. , Goldenholz Daniel M.
Published: November 2019

This study aimed to compare three commonly used analysis methods for clinical trials in epilepsy in terms of statistical efficiency, nonefficacious exposure, and cost. A realistic seizure diary simulator was employed to produce 102 000 trials, which were analyzed by the 50%‐responder rate method (RR50), median percentage change (MPC), and time to prerandomization (TTP). Half the trials compared a placebo to a drug that was 20% better, and the other half compared two placebos. The former were used to calculate statistical power; the latter were used for type 1 error rates. Based on the number of patients needed to achieve 90% power, expected number of patient‐days of nonefficacious exposures and expected cost were calculated for each method. MPC demonstrated the highest efficacy, lowest exposure, and lowest cost. RR50 demonstrated the lowest efficacy, highest exposure, and highest cost. Costs were: MPC $1 295 000, TTP $1 315 720, and RR50 $2 331 000. Selecting an optimal analysis method for a primary outcome in an epilepsy trial can have consequences in terms of nonefficacious exposure and cost. This study provides evidence supporting the use of MPC (preferred) or TTP, and evidence suggesting that RR50 would incur high costs and excess exposures.
The hidden diversity of the potato cyst nematode Globodera pallida in the south of Peru
Authors: Thevenoux Romain , Folcher Laurent , Esquibet Magali , Fouville Didier , Montarry Josselin , Grenier Eric
Published: November 2019

Our knowledge of the diversity of potato cyst nematodes in their native areas still remains patchy and should be improved. A previous study based on 42 Peruvian Globodera pallida populations revealed a clear south to north phylogeographic pattern, with five well‐supported clades and maximum diversity observed in the south of Peru. In order to investigate this phylogeographic pattern more closely, we genotyped a larger collection of Peruvian populations using both cathepsin L gene sequence data and a new set of 13 microsatellite loci. Using different genetic analyses (STRUCTURE, DAPC), we consistently obtained the same results that led to similar conclusions: the presence of a larger genetic diversity than previously known suggesting the presence of cryptic species in the south of Peru. These investigations also allowed us to clarify the geographic borders of the previously described G. pallida genetic clades and to update our knowledge of the genetic structure of this species in its native area, with the presence of additional clades. A distance‐based redundancy analysis (dbRDA) was also carried to understand whether there was a correlation between the population genetic differentiation and environmental conditions. This analysis showed that genetic distances observed between G. pallida populations are explained firstly by geographic distances, but also by climatic and soil conditions. This work could lead to a revision of the taxonomy that may have strong implications for risk assessment and management, especially on a quarantine species.
The role of windows of selection and windows of dominance in the evolution of insecticide resistance in human disease vectors
Authors: South Andy , Lees Rosemary , Garrod Gala , Carson Jessica , Malone David , Hastings Ian
Published: November 2019

Persistent insecticides sprayed onto house walls, and incorporated into insecticide‐treated bednets, provide long‐acting, cost‐effective control of vector‐borne diseases such as malaria and leishmaniasis. The high concentrations that occur immediately postdeployment may kill both resistant and susceptible insects. However, insecticide concentration, and therefore killing ability, declines in the months after deployment. As concentrations decline, resistant insects start to survive, while susceptible insects are still killed. The period of time after deployment, within which the mortality of resistant individuals is lower than that of susceptible ones, has been termed the “window of selection” in other contexts. It is recognized as driving resistance in bacteria and malaria parasites, both of which are predominantly haploid. We argue that paying more attention to these mortality differences can help understand the evolution of insecticide resistance. Because insects are diploid, resistance encoded by single genes generates heterozygotes. This gives the potential for a narrower “window of dominance,” within the window of selection, where heterozygote mortality is lower than that of susceptible homozygotes. We explore the general properties of windows of selection and dominance in driving resistance. We quantify their likely effect using data from new laboratory experiments and published data from the laboratory and field. These windows can persist months or years after insecticide deployments. Differential mortalities of resistant, susceptible and heterozygous genotypes, after public health deployments, constitute a major challenge to controlling resistance. Greater attention to mortality differences by genotype would inform strategies to reduce the evolution of resistance to existing and new insecticides.
Depositional and diagenetic history of limestones and dolostones of the Oligo‐Miocene Kujung Formation in the Northeast Java Basin, Indonesia
Authors: Syah Muhlash Hada Firman , Kano Akihiro , Iizuka Tsuyoshi , Kakizaki Yoshihiro
Published: November 2019

Lithological and geochemical features of platformal carbonates record the signatures of the global climates and the regional environmental settings and also reconstruct the diagenetic history and porosity evolution, which are essential to evaluate the potential of hydrocarbon reservoirs. This study investigates the platformal carbonates of the Oligo‐Miocene Krunji Formation of North East Java Basin, which are potentially significant hydrocarbon reservoirs. The carbonate sequence in a 283 m thick section at Kranji in East Java is subdivided into three lithological units: limestone unit 1, dolostone unit 2, and limestone unit 3, in ascending order. The strontium‐isotope ratios of well‐preserved calcite samples indicate the depositional period from Chattian (late Oligocene) to Burdigalian (early Miocene), which is consistent with ages of the foraminifer assemblages. Unit 1 consists of low‐porosity limestone, in which two horizons of subaerial exposure are recognized by the occurrence of red‐colored matrix and lower δ13C values. Unit 2 consists of dolomitic rock and exhibits coarse‐grained calcitic grains and cross‐stratified structure. Considering that this unit has been subject to dolomitization, the sediment of unit 2 was initially permeable and was likely deposited in a shoal setting. The overlying unit 3 of Aquitanian–Burdigalian age is characterized by a highly granular texture. High porosity and uniformly low δ13C and δ18O values indicate that Unit 3 was subjected to more intense meteoric diagenesis than the Chattian unit 1. This was likely a consequence of the Antarctic ice‐sheet expansion during the Oligocene/Miocene transition, which amplified sea level change. The unit 2 dolomite has high δ13C and δ18O values and a high87Sr/86Sr ratio which resulted from the reflux of seawater into permeable the sediment body in middle‐late Miocene (Burdigalian Tortonian) following the deposition of unit 3. The porosity and permeability of the Kujung Formation were initially controlled by sedimentological processes, but largely modified by later diagenetic processes.