Fast and robust curve skeletonization for real-world elongated objects

We consider the problem of extracting curve skeletons of three-dimensional, elongated objects given a noisy surface, which has applications in agricultural contexts such as extracting the branching structure of plants. We describe an efficient and robust method based on breadth-first search that can determine curve skeletons in these contexts. Our approach is capable of automatically detecting junction points as well as spurious segments and loops. All of that is accomplished with only one user-adjustable parameter. The run time of our method ranges from hundreds of milliseconds to less than four seconds on large, challenging datasets, which makes it appropriate for situations where real-time decision making is needed. Experiments on synthetic models as well as on data from real world objects, some of which were collected in challenging field conditions, show that our approach compares favorably to classical thinning algorithms as well as to recent contributions to the field.Comment: 47 pages; IEEE WACV 2018, main paper and supplementary materia

Suffering in ancient worldview: a comparative study of Acts, Fourth Maccabees, and Seneca

This thesis analyzes how suffering functions in the worldviews of the Roman Stoic Seneca, the Jewish author of 4 Maccabees, and the Christian historian Luke. Acts 17:17–18 invites such a comparison by presenting Paul’s Christian missionary activity in direct engagement with Hellenistic Judaism and popular Greco-Roman philosophy, including Stoicism. Chapters 1, 3, and 5 offer close readings of representative texts from Acts, 4 Maccabees, and Seneca’s essays and letters with a view to highlighting the authors’ treatments of suffering. Chapters 2, 4, and 6 utilize heuristic worldview questions to clarify and synthesize how each writer accounts for suffering, vis-à-vis their perspectives on God, humanity, the world’s problem and its solution, and the future. Chapter 7 presents an ancient conversation between these three authors modeled after Cicero’s De Natura Deorum. This thesis makes at least three significant contributions to scholarship. First, this is the only extended comparison of Seneca, Luke, and 4 Maccabees. The value and importance of studying early Christianity alongside Stoicism and Hellenistic Judaism is well known, but previous studies have focused on Paul, not Luke, who is typically compared with Josephus, not 4 Maccabees. Second, building on N. T. Wright’s work, this study demonstrates that worldview questions offer a fruitful method for comparing different authors and groups. This study does not attempt to prove literary or intellectual dependence but to compare these authors at the worldview level. Third, this thesis contributes to the important and often neglected theme of suffering in Luke-Acts, 4 Maccabees, and Seneca’s writings. This is the first systematic treatment of suffering in Seneca’s thought and in 4 Maccabees. This study builds on Cunningham’s and Mittelstadt’s recent monographs on suffering in Luke- Acts and advances the discussion by offering clear definitions of suffering and persecution, illustrated by first-century examples, and by an extended worldview comparison of Luke with other authors. In Luke-Acts, God is not “outside suffering” as Seneca argues but acts through the suffering of Jesus and his followers to set the world of sin and suffering right again, in fulfillment of his ancient promises

Multispecies Fruit Flower Detection Using a Refined Semantic Segmentation Network

In fruit production, critical crop management decisions are guided by bloom intensity, i.e., the number of flowers present in an orchard. Despite its importance, bloom intensity is still typically estimated by means of human visual inspection. Existing automated computer vision systems for flower identification are based on hand-engineered techniques that work only under specific conditions and with limited performance. This letter proposes an automated technique for flower identification that is robust to uncontrolled environments and applicable to different flower species. Our method relies on an end-to-end residual convolutional neural network (CNN) that represents the state-of-the-art in semantic segmentation. To enhance its sensitivity to flowers, we fine-tune this network using a single dataset of apple flower images. Since CNNs tend to produce coarse segmentations, we employ a refinement method to better distinguish between individual flower instances. Without any preprocessing or dataset-specific training, experimental results on images of apple, peach, and pear flowers, acquired under different conditions demonstrate the robustness and broad applicability of our method

The analysis of animate object motion using neural networks and snakes

This paper presents a mechanism for analysing the deformable shape of an object as it moves across the visual field. An object’s outline is detected using active contour models, and is then re-represented as shape, location and rotation invariant axis crossover vectors. These vectors are used as input for a feedforward backpropagation neural network, which provides a confidence value determining how ‘human’ the network considers the given shape to be. The network was trained using simulated human shapes as well as simulated non-human shapes, including dogs, horses and inanimate objects. The network was then tested on unseen objects of these classes, as well as on an unseen object class. Analysis of the network’s confidence values for a given animated object identifies small, individual variations between different objects of the same class, and large variations between object classes. Confidence values for a given object are periodic and parallel the paces being taken by the object

Segmenting root systems in X-ray computed tomography images using level sets

The segmentation of plant roots from soil and other growing media in X-ray computed tomography images is needed to effectively study the root system architecture without excavation. However, segmentation is a challenging problem in this context because the root and non-root regions share similar features. In this paper, we describe a method based on level sets and specifically adapted for this segmentation problem. In particular, we deal with the issues of using a level sets approach on large image volumes for root segmentation, and track active regions of the front using an occupancy grid. This method allows for straightforward modifications to a narrow-band algorithm such that excessive forward and backward movements of the front can be avoided, distance map computations in a narrow band context can be done in linear time through modification of Meijster et al.'s distance transform algorithm, and regions of the image volume are iteratively used to estimate distributions for root versus non-root classes. Results are shown of three plant species of different maturity levels, grown in three different media. Our method compares favorably to a state-of-the-art method for root segmentation in X-ray CT image volumes.Comment: 11 page

CHARACTERIZATION OF TWO TYPE IV COLLAGENS INVOLVED IN AUTOSOMAL RECESSIVE HEREDITARY NEPHROPATHY

The glomerular basement membrane (GBM) of the kidney is highly specialized and required for filtration of waste products from the bloodstream. One of the major structural and functional units of the GBM is a network composed of type IV collagen heterotrimers, or protomers. Early in development of the human and dog, an isoform switch occurs, and the α1α1α2 (IV) network found in the nascent GBM is replaced with α3α4α5 (IV) protomers. Mutations in any of the genes encoding proteins found in the mature GBM network may prevent protomer formation and cause a progressive disorder leading to end stage renal failure (ESRD). In the human, the disease is known as Alport syndrome (AS) and is characterized by proteinuria, hematuria, and in half of affected patients, deficits in hearing. The GBM undergoes characteristic ultrastructural changes, and immunostaining of renal samples reveals a loss of α3 (IV) and α5 (IV) proteins with a corresponding increase in α1 (IV) chains. Hereditary nephropathy (HN) is the canine counterpart of AS and has been reported in different breeds. Affected dogs display clinicopathological signs identical to those described in AS patients, with the exception of hearing loss. There were two major objectives for this project. The first objective was to amplify and sequence a region previously lacking coverage on CFA25 between the genes encoding the α3 (IV) and α4 (IV) chains. This was necessary in order to span gap regions in the canine reference genome. The second objective was to identify the mutation causative for HN in a breed not previously reported to present with the disease

Centrifugalno i centripetalno razmišljanje o biopsihosocijalnom modelu u psihijatriji

The biopsychosocial model, which was deeply influential on psychiatry following its introduction by George L. Engel in 1977, has recently made a comeback. Derek Bolton and Grant Gillett have argued that Engel’s original formulation offered a promising general framework for thinking about health and disease, but that this promise requires new empirical and philosophical tools in order to be realized. In particular, Bolton and Gillett offer an original analysis of the ontological relations between Engel’s biological, social, and psychological levels of analysis. I argue that Bolton and Gillett’s updated model, while providing an intriguing new metaphysical framework for medicine, cannot resolve some of the most vexing problems facing psychiatry, which have to do with how to prioritize different sorts of research. These problems are fundamentally ethical, rather than ontological. Without the right prudential motivation, in other words, the unification of psychiatry under a single conceptual framework seems doubtful, no matter how compelling the model. An updated biopsychosocial model should include explicit normative commitments about the aims of medicine that can give guidance about the sorts of causal connections to be prioritized as research and clinical targets.Biopsihosocijalni model, koji je imao dubok utjecaj na psihijatriju nakon što ga je uveo George L. Engel 1977., nedavno se vratio. Derek Bolton i Grant Gillett tvrde da je Engelova izvorna formulacija ponudila obećavajući opći okvir za razmišljanje o zdravlju i bolesti, ali da to obećanje zahtijeva nove empirijske i filozofske alate kako bi se ostvarilo. Bolton i Gillett nude originalnu analizu ontoloških odnosa između Engelove biološke, društvene i psihološke razine analize. Argumentiram da Boltonov i Gillettov ažurirani model, iako pruža intrigantan novi metafizički okvir za medicinu, ne može riješiti neke od najzahtjevnijih problema s kojima se psihijatrija suočava, a koji se odnose na to kako dati prioritet različitim vrstama istraživanja. Ti su problemi u osnovi etički, a ne ontološki. Bez prave prudencijalne motivacije, drugim riječima, objedinjavanje psihijatrije pod jednim pojmovnim okvirom čini se upitnim, ma koliko uvjerljiv model. Ažurirani biopsihosocijalni model trebao bi uključivati ​​eksplicitne normativne obveze o ciljevima medicine koji mogu dati smjernice o vrstama uzročno-posljedičnih veza kojima se treba dati prioritet kao istraživačkim i kliničkim ciljevima