Identifying the health care-initiated and self-initiated interventions used by women for the management of rectal emptying difficulty secondary to obstructive defecation: a scoping review protocol.

OBJECTIVE: This scoping review aims to identify interventions used by women for the management of rectal emptying difficulty secondary to obstructive defecation. INTRODUCTION: Rectal emptying difficulty is typically a symptom of obstructive defecation syndrome. Even though a range of interventions are already available for this condition, this review is necessary to increase understanding of what interventions women find useful and are acceptable for them. This depth of understanding will facilitate the development of a specific care pathway to support women living with rectal emptying difficulty secondary to obstructive defecation syndrome. INCLUSION CRITERIA: This review will consider studies that include adult women (over 18 years of age) living in the community who have experienced difficulty with rectal emptying secondary to obstructive defecation and who have not had surgical intervention. Exclusion criteria include prolapse surgery and surgical techniques, oral laxatives, vaginal pessaries, cognitive impairment, pregnancy, and those residing in care homes. METHODS: The databases to be searched include MEDLINE, Embase, CINAHL, PsycINFO, Emcare, AMED, Web of Science, Scopus, PROSPERO, Open Grey, ClinicalTrials.gov, International Clinical Trials Registry Platform Search Portal, UK Clinical Trials Gateway, International Standard Randomised Controlled Trial Number Registry, JBI Evidence Synthesis, Epistemonikos, Cochrane Library, and gray literature. Studies conducted in English from any time period will be considered for inclusion. The titles and abstracts will then be screened by two independent reviewers for assessment against the inclusion criteria for the review

Exactly Sparse Extended Information Filters for Feature-Based SLAM

Recent research concerning the Gaussian canonical form for Simultaneous Localization and Mapping (SLAM) has given rise to a handful of algorithms that attempt to solve the SLAM scalability problem for arbitrarily large environments. One such estimator that has received due attention is the Sparse Extended Information Filter (SEIF) proposed by Thrun et al., which is reported to be nearly constant time, irrespective of the size of the map. The key to the SEIF's scalability is to prune weak links in what is a dense information (inverse covariance) matrix to achieve a sparse approximation that allows for efficient, scalable SLAM. We demonstrate that the SEIF sparsification strategy yields error estimates that are overconfident when expressed in the global reference frame, while empirical results show that relative map consistency is maintained. In this paper, we propose an alternative scalable estimator based on an information form that maintains sparsity while preserving consistency. The paper describes a method for controlling the population of the information matrix, whereby we track a modified version of the SLAM posterior, essentially by ignoring a small fraction of temporal measurements. In this manner, the Exactly Sparse Extended Information Filter (ESEIF) performs inference over a model that is conservative relative to the standard Gaussian distribution. We compare our algorithm to the SEIF and standard EKF both in simulation as well as on two nonlinear datasets. The results convincingly show that our method yields conservative estimates for the robot pose and map that are nearly identical to those of the EKF.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86031/1/mwalter-22.pd

Sparse Extended Information Filters: Insights into Sparsification

Recently, there have been a number of variant Simultaneous Localization and Mapping (SLAM) algorithms that have made substantial progress towards large-area scalability by parameterizing the SLAM posterior within the information (canonical/inverse covariance) form. Of these, probably the most well-known and popular approach is the Sparse Extended Information Filter (SEIF) by Thrun et al. While SEIFs have been successfully implemented with a variety of challenging real-world datasets and have led to new insights into scalable SLAM, open research questions remain regarding the approximate sparsification procedure and its effect on map error consistency. In this paper, we examine the constant-time SEIF sparsification procedure in depth and offer new insight into issues of consistency. In particular, we show that exaggerated map inconsistency occurs within the global reference frame where estimation is performed, but that empirical testing shows that relative local map relationships are preserved. We then present a slightly modified version of their sparsification procedure, which is shown to preserve sparsity while also generating both local and global map estimates comparable to those obtained by the non-sparsified SLAM filter. While this modified approximation is no longer constant-time, it does serve as a theoretical benchmark against which to compare SEIFs constant-time results. We demonstrate our findings by benchmark comparison of the modified and original SEIF sparsification rule using simulation in the linear Gaussian SLAM case and real-world experiments for a nonlinear dataset.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86045/1/reustice-31.pd

Sensor Fusion of Structure-from-Motion, Bathymetric 3D, and Beacon-Based Navigation Modalities

This paper describes an approach for the fusion of 30 data underwater obtained from multiple sensing modalities. In particular, we examine the combination of imagebased Structure-From-Motion (SFM) data with bathymetric data obtained using pencil-beam underwater sonar, in order to recover the shape of the seabed terrain. We also combine image-based egomotion estimation with acousticbased and inertial navigation data on board the underwater vehicle. We examine multiple types of fusion. When fusion is pe?$ormed at the data level, each modality is used to extract 30 information independently. The 30 representations are then aligned and compared. In this case, we use the bathymetric data as ground truth to measure the accuracy and drijl of the SFM approach. Similarly we use the navigation data as ground truth against which we measure the accuracy of the image-based ego-motion estimation. To our knowledge, this is the frst quantitative evaluation of image-based SFM and egomotion accuracy in a large-scale outdoor environment. Fusion at the signal level uses the raw signals from multiple sensors to produce a single coherent 30 representation which takes optimal advantage of the sensors' complementary strengths. In this papel; we examine how lowresolution bathymetric data can be used to seed the higherresolution SFM algorithm, improving convergence rates, and reducing drift error. Similarly, acoustic-based and inertial navigation data improves the convergence and driji properties of egomotion estimation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86044/1/hsingh-35.pd

Towards High-resolution Imaging from Underwater Vehicles

Large area mapping at high resolution underwater continues to be constrained by sensor-level environmental constraints and the mismatch between available navigation and sensor accuracy. In this paper, advances are presented that exploit aspects of the sensing modality, and consistency and redundancy within local sensor measurements to build high-resolution optical and acoustic maps that are a consistent representation of the environment. This work is presented in the context of real-world data acquired using autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs) working in diverse applications including shallow water coral reef surveys with the Seabed AUV, a forensic survey of the RMS Titanic in the North Atlantic at a depth of 4100 m using the Hercules ROV, and a survey of the TAG hydrothermal vent area in the mid-Atlantic at a depth of 3600 m using the Jason II ROV. Specifically, the focus is on the related problems of structure from motion from underwater optical imagery assuming pose instrumented calibrated cameras. General wide baseline solutions are presented for these problems based on the extension of techniques from the simultaneous localization and mapping (SLAM), photogrammetric and the computer vision communities. It is also examined how such techniques can be extended for the very different sensing modality and scale associated with multi-beam bathymetric mapping. For both the optical and acoustic mapping cases it is also shown how the consistency in mapping can be used not only for better global mapping, but also to refine navigation estimates.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86051/1/hsingh-21.pd

Toward mutual information based place recognition

Abstract — This paper reports on a novel mutual information (MI) based algorithm for robust place recognition. The pro-posed method provides a principled framework for fusing the complementary information obtained from 3D lidar and camera imagery for recognizing places within an a priori map of a dynamic environment. The visual appearance of the locations in the map can be significantly different due to changing weather, lighting conditions and dynamical objects present in the environment. Various 3D/2D features are extracted from the textured point clouds (scans) and each scan is represented as a collection of these features. For two scans acquired from the same location, the high value of MI between the features present in the scans indicates that the scans are captured from the same location. We use a non-parametric entropy estimator to estimate the true MI from the sparse marginal and joint histograms of the features extracted from the scans. Experimental results using seasonal datasets collected over several years are used to validate the robustness of the proposed algorithm. I

Women's experiences of managing digitation: do we ask enough in primary care?

The aim of this paper was to consider the available evidence for the current management of pelvic organ prolapse, which is a common presentation in primary care. However, not all women will present, only presenting when symptoms become bothersome. Particular attention was paid to understanding the problem of rectocele and its influence on obstructive defaecation symptoms. The burden of rectocele and its consequences are not truly known. Furthermore, healthcare professionals may not always enquire about bowel symptoms and patients may not disclose them. Complex emotions around coping and managing stress add to the challenges with seeking healthcare. Therefore, the impact on the lived experience of women who have difficulty with rectal emptying can be significant. The review identified a dearth of knowledge about women living with the problem of obstructive defaecation resulting in the use of digitation. Improving the management of digitation, an under-reported problem, is necessary to improve the quality of life for women. Primary care needs to increase access to conservative measures for women struggling with bothersome symptoms, such as constipation, the need to digitate or anxiety

Case Series of Synthetic Cannabinoid Intoxication from One Toxicology Center.

Synthetic cannabinoid use has risen at alarming rates. This case series describes 11 patients exposed to the synthetic cannabinoid, MAB-CHMINACA who presented to an emergency department with life-threatening toxicity including obtundation, severe agitation, seizures and death. All patients required sedatives for agitation, nine required endotracheal intubation, three experienced seizures, and one developed hyperthermia. One developed anoxic brain injury, rhabdomyolysis and died. A significant number were pediatric patients. The mainstay of treatment was aggressive sedation and respiratory support. Synthetic cannabinoids pose a major public health risk. Emergency physicians must be aware of their clinical presentation, diagnosis and treatment

Additive manufacturing of glass with laser powder bed fusion

Its transparency, esthetic appeal, chemical inertness, and electrical resistivity make glass an excellent candidate for small‐ and large‐scale applications in the chemical, electronics, automotive, aerospace, and architectural industries. Additive manufacturing of glass has the potential to open new possibilities in design and reduce costs associated with manufacturing complex customized glass structures that are difficult to shape with traditional casting or subtractive methods. However, despite the significant progress in the additive manufacturing of metals, polymers, and ceramics, limited research has been undertaken on additive manufacturing of glass. In this study, a laser powder bed fusion method was developed for soda lime silica glass powder feedstock. Optimization of laser processing parameters was undertaken to define the processing window for creating three‐dimensional multilayer structures. These findings enable the formation of complex glass structures with micro‐ or macroscale resolution. Our study supports laser powder bed fusion as a promising method for the additive manufacturing of glass and may guide the formation of a new generation of glass structures for a wide range of applications

A perspective on emerging automotive safety applications, derived from lessons learned through participation in the DARPA Grand Challenges

This paper reports on various aspects of the Intelligent Vehicle Systems (IVS) team's involvement in the recent 2007 DARPA Urban Challenge, wherein our platform, the autonomous “XAV-250,'' competed as one of the 11 finalists qualifying for the event. We provide a candid discussion of the hardware and software design process that led to our team's entry, along with lessons learned at this event and derived from participation in the two previous Grand Challenges. In addition, we give an overview of our vision-, radar-, and LIDAR-based perceptual sensing suite, its fusion with a military-grade inertial navigation package, and the map-based control and planning architectures used leading up to and during the event. The underlying theme of this article is to elucidate how the development of future automotive safety systems can potentially be accelerated by tackling the technological challenges of autonomous ground vehicle robotics. Of interest, we will discuss how a production manufacturing mindset imposes a unique set of constraints upon approaching the problem and how this worked for and against us, given the very compressed timeline of the contests. © 2008 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/61244/1/20264_ftp.pd