Deformable M-Reps for 3D Medical Image Segmentation

M-reps (formerly called DSLs) are a multiscale medial means for modeling and rendering 3D solid geometry. They are particularly well suited to model anatomic objects and in particular to capture prior geometric information effectively in deformable models segmentation approaches. The representation is based on figural models, which define objects at coarse scale by a hierarchy of figures—each figure generally a slab representing a solid region and its boundary simultaneously. This paper focuses on the use of single figure models to segment objects of relatively simple structure.A single figure is a sheet of medial atoms, which is interpolated from the model formed by a net, i.e., a mesh or chain, of medial atoms (hence the name m-reps), each atom modeling a solid region via not only a position and a width but also a local figural frame giving figural directions and an object angle between opposing, corresponding positions on the boundary implied by the m-rep. The special capability of an m-rep is to provide spatial and orientational correspondence between an object in two different states of deformation. This ability is central to effective measurement of both geometric typicality and geometry to image match, the two terms of the objective function optimized in segmentation by deformable models. The other ability of m-reps central to effective segmentation is their ability to support segmentation at multiple levels of scale, with successively finer precision. Objects modeled by single figures are segmented first by a similarity transform augmented by object elongation, then by adjustment of each medial atom, and finally by displacing a dense sampling of the m-rep implied boundary. While these models and approaches also exist in 2D, we focus on 3D objects.The segmentation of the kidney from CT and the hippocampus from MRI serve as the major examples in this paper. The accuracy of segmentation as compared to manual, slice-by-slice segmentation is reported.     

Describing Near Surface, Transient Flow Processes in Unconfined Aquifers below Irrigated Lands: Model Application in the Western San Joaquin Valley, California

In order to rigorously examine near surface, field to field interactions between irrigation management regimes and a shallow fluctuating water table, an enhanced deforming finite element (DFE) model was recently developed. The enhanced DFE model, through a process of iteration within each time step, avoids making common assumptions regarding the changing geometry of an aquifer free surface. This paper demonstrates the usefulness and effectiveness of the model by employing it to an irrigated region in the western San Joaquin Valley, Calif., where shallow subsurface tile drains have been installed to control shallow water tables. By virtue of the problems created by the need to dispose off the drainage water, this region has been the focus of several important regional scale modeling exercises, which have evaluated the utility of management strategies, such as source control, groundwater pumping, and land retirement. By refining the focus of the analysis, the enhanced DFE model is found to be able to show that both sources control and managed pumping could be more effective drainage control strategies than predicted based on the results of regional models.     

A novel polarizer‐free dye‐doped polymer‐dispersed liquid crystal for reflective TFT displays

Abstract— A novel preparation method for dichroic dye‐doped polymer‐dispersed liquid crystals has been developed. This was achieved by creating a porous polymer matrix first by washing out the liquid crystal from a polymer‐dispersed liquid crystal (PDLC), which is then refilled with dye‐doped liquid crystal. Optimizing the liquid crystal used in the refilling results in decreased turn‐on voltage and faster response time. Poster‐standard reflectivity and newspaper‐standard contrast was demonstrated with a 3.8‐in. QVGA reflective TFT display with a drive voltage of 10 V.     

Labelled-replica techniques: post-shadow labelling of intramembrane particles in freeze-fracture replicas

Three methods are described for direct post-fracture, post-shadow labelling of individual classes of intramembrane particles (IMPs) in freeze-fracture replicas of biological membranes. The P-face IMPs corresponding to the acetylcholine receptor complexes (AChRs) of vertebrate neuroeffector junctions are identified by post-replication labelling with ferritin-antibody complexes and with neurotoxin-biotin-avidin-colloidal gold affinity ligands. (The freeze-etch nomenclature of Branton et al., 1975, is used in this report.) These post-shadow labelling techniques resemble conventional en bloc labelling techniques except that the labelling reagents must penetrate a thin but discontinuous layer of platinum superimposed on the molecules of interest. In the ‘sectioned labelled-replica technique’, the replicated and labelled tissues are stained, embedded in plastic and sectioned parallel to the replica-tissue interfaces. In the direct ‘labelled-replica techniques’, the replicated and labelled samples are freeze-dried or critical point dried, the labelled surfaces are stabilized by carbon coating, and the underlying tissues are dissolved, allowing the labelled-replicas to be examined as conventional freeze-fracture replicas. The unshadowed side of each AChR IMP is shown to retain sufficient biochemical information to permit both immunospecific and neurotoxin specific labelling despite formaldehyde fixation, freezing, fracturing, platinum shadowing, and thawing in aqueous media. A new mixed ferricyanide-osmium staining method reveals electron opaque structures spanning the membrane bilayer in the same size, number and distribution as the labelled IMPs. These experiments demonstrate the feasibility of identifying individual IMPs in freeze-fracture replicas and may allow the identification of specific membrane lesions in human disease.     

Foreword: Values in psychotherapy.

Contends that the glory of psychotherapists' "tree of psychology" is that its roots are absolutely philosophical and, therefore, limitless in scope and devoid of absolute proofs. The trunk of this tree is a solid and substantial store of scientific and empirical data. The branches bear a multitude of flowers, many of which are not quite substantial; not made to endure the critical climate of a questioning world. Ultimately, however, these flowers contain the germinating factor, that which allows human knowledge the possibility of continued growth and rejuvenation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The territory ahead for multicultural competence: The "spinning" of racism.

Multicultural competence has become a mainstay within the training of professional psychologists, yet important areas within this framework remain to be more fully addressed. In particular, the dynamics of contemporary forms of racism have largely gone unexplored, depriving psychologists of clear direction in exploring the deepest levels of racist influences in their work. This qualitative analysis sought to shed light into this area by studying White people's experiences of race and racism. Although most affirmed the existence of racism, it was "spun" by most White participants--in other words, interpreted to their own advantage-into a problem that lies outside the scope of their own lives and responsibilities. Implications and resources for the practice and training of professional psychologists are presented. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Miniaturization and geometry optimization of a polymer-based rectilinear ion trap

The fabrication, operation, and characterization of a polymer-based rectilinear ion trap mass analyzer is discussed. A novel, fast prototyping technique, stereolithography (SLA)-based fabrication, traditionally reserved for end use production parts and to fabricate master molds for rubber products, is applied here as a tool to create precise, arbitrary geometries. Taking full advantage of the SLA methodology, an open corner, polymer-based ion trap has been fabricated and tested. The use of a custom resin, Nanoform 15120 (DSM Somos, New Castle, DE), has resulted in a polymer with high heat deflection temperature and greater structural stability at higher temperatures and lower capacitance. The mass analyzer was mounted in a polymer holder and tested in a custom vacuum system using modified LCQ Duo (Thermo Fisher Corp.) electronics. The resolution, mass/charge range, and MS/MS capabilities were examined using electrospray ionization as well as atmospheric pressure chemical ionization. In the course of this study, three traps of different sizes were fabricated, beginning with a "full size" device measuring 10 x 8 x 50 mm. The next two traps were scaled down by linear factors of a half and a third. SLA is shown to allow fabrication of light, small rectilinear ion traps, which are less expensive and have the same performance as traditional machined devices of the same size. In addition, smaller traps can be built just as easily, and they show unit mass resolution to mass 300, tandem mass spectrometry capabilities, and low power consumption.     

The copula: a tool for simulating speckle dynamics

Use of a copula for generating a sequence of correlated speckle patterns is introduced. The chief characteristic of this algorithm is that it generates a continuous speckle sequence with a specified evolution of the correlation and does so with just two arrays of random numbers. Thus, physically realistic temporally varying speckle patterns with proper first- and second-order statistics are easily realized. We illustrate use of the algorithm for generating sequences with prescribed Gaussian, exponential, and equal-interval correlations and demonstrate how correlation times can be specified independently. This approach to generating sequences of random realizations with prescribed correlations should prove useful in modeling such phenomena as dynamic light scatter, flow-dependent laser speckle contrast, and propagation of spatial coherence.     

Sedentary behaviour and health at work: an investigation of industrial sector,job role,gender and geographical differences

This article presents baseline data from 1120 employees across 10 worksites enrolled in a workplace physical activity intervention. The study provides new data on physical activity, sedentary behaviour, and health and highlights gender, geographical, job type and industrial sector differences. Sitting at work accounted for more than 60% of participants’ total daily sitting time on work days. Weekly and monthly hours worked, body mass index (BMI) and waist circumference were significantly higher for workers in the private sector compared to the public sector. Employees in sales and customer services had significantly higher BMI scores and significantly lower scores for workability index (WAI), job satisfaction, organisational commitment and job motivation, compared to other groups. This study provides further evidence that work is a major contributor to sedentary behaviour and supports the pressing need for interventions particularly targeting private sector industries and sales and customer service sectors.

Practitioner Summary: Work accounts for more than 60% of the daily sitting time. Private sector employees had higher BMIs than those in the public sector and employees in sales and customer services had higher BMIs and poorer health compared to other occupations, suggesting that these groups should be targeted in workplace interventions.     

Machine learning in vehicular networking: An overview

As vehicle complexity and road congestion increase, combined with the emergence of electric vehicles, the need for intelligent transportation systems to improve on-road safety and transportation efficiency using vehicular networks has become essential. The evolution of high mobility wireless networks will provide improved support for connected vehicles through highly dynamic heterogeneous networks. Particularly, 5G deployment introduces new features and technologies that enable operators to capitalize on emerging infrastructure capabilities. Machine Learning (ML), a powerful methodology for adaptive and predictive system development, has emerged in both vehicular and conventional wireless networks. Adopting data-centric methods enables ML to address highly dynamic vehicular network issues faced by conventional solutions, such as traditional control loop design and optimization techniques. This article provides a short survey of ML applications in vehicular networks from the networking aspect. Research topics covered in this article include network control containing handover management and routing decision making, resource management, and energy efficiency in vehicular networks. The findings of this paper suggest more attention should be paid to network forming/deforming decision making. ML applications in vehicular networks should focus on researching multi-agent cooperated oriented methods and overall complexity reduction while utilizing enabling technologies, such as mobile edge computing for real-world deployment. Research datasets, simulation environment standardization, and method interpretability also require more research attention.