Kendallhale6574

Health risks were measured via validated self-report instruments. Treatment initiation and utilization were measured via self-report and chart review.

SHE did not impact women's number of health risks (all p's > .05). However, women randomized to SHE showed significantly greater increases in treatment use compared to women in the control group, as measured by chart review (χ

(1, n = 153) = 4.38, p = .036, r

= .16), and self-report (χ

(1, n = 130) = 5.89, p = .015, r

= .21). SHE was found to be an acceptable intervention.

SHE was effective in improving mental health treatment initiation and utilization compared to a control group. Computer-based interventions to address sexual trauma and its consequences are acceptable, are highly scalable, and can add value to primary care with little cost or increase in provider time.

Clinicaltrials.gov identifier NCT02957747.

Clinicaltrials.gov identifier NCT02957747.

To analyse and compare the propensity to form glistenings in 4 different types of hydrophobic acrylic intraocular lenses (IOLs) Alcon AcrySof ® MA60AC, HOYA iSert® PC-60AD, Bausch&Lomb enVista, and Kowa Avansee™ PU6A.

We used an accelerated laboratory method to create glistenings. IOLs were first immersed in saline at 45°C for 24h and then at 37°C for 2.5h. Microvacuole (MV) density and size were documented and calculated using an image analysis program.

Median density of glistenings [MV/mm

] for Alcon AcrySof ® MA60AC was 623 (range 507-804), for HOYA iSert® PC-60AD 1358 (range 684-2699), for Bausch&Lomb enVista 2 (range 1-2), and for Kowa Avansee™ PU6A 1 (range 1-4). The prevailing MV size was 0-5µm for Hoya IOLs, 5-10µm for Alcon IOLs, 20-50µm for Bausch&Lomb IOLs, and 5-50µm for Kowa IOLs.

Glistenings could be induced in all studied IOLs using the accelerated laboratory method. The Alcon AcrySof ® MA60AC and HOYA iSert® PC-60AD IOLs showed MV of high density, while the glistenings in the Hoya IOLs were smaller in size compared to the Alcon IOLs. The MV density was minimal in the Bausch&Lomb enVista and Kowa Avansee™ PU6A IOLs. The propensity of the Alcon AcrySof ® MA60AC IOLs to form glistenings in vitro correlated with the findings of clinical results that are already published.

Glistenings could be induced in all studied IOLs using the accelerated laboratory method. The Alcon AcrySof ® MA60AC and HOYA iSert® PC-60AD IOLs showed MV of high density, while the glistenings in the Hoya IOLs were smaller in size compared to the Alcon IOLs. The MV density was minimal in the Bausch&Lomb enVista and Kowa Avansee™ PU6A IOLs. The propensity of the Alcon AcrySof ® MA60AC IOLs to form glistenings in vitro correlated with the findings of clinical results that are already published.The reconstruction of dynamic of traffic injuries remains a challenge in forensic pathology and is often based on circumstantial data. Dash Cams are digital video recorders which can be located inside a vehicle and continuously record the view through the windscreen, thus providing objective evidence. Here we present the case of a traffic crash in which a pedestrian was hit by an articulated lorry. The analysis of a video recorded from a Dash Cam retrieved inside the vehicle during the death scene investigation (DSI) was crucial in the reconstruction of the manner of death. Indeed, the death, which was initially assumed to be accidental, was finally deemed as a suicide on the basis of the video recording, which showed an intentional and sudden rush of the victim to the middle of the roadway. Advantages and disadvantages of the use of Dash Cams will be discussed, focusing on the profound differences in the related national and international regulations. Based on the present case, in traffic crashes, the search for Dash Cams during the DSI may be recommended and the video recordings should be analyzed in the setting of a multidisciplinary and multimodal evaluation of the case, for a proper reconstruction of the facts.Australia does not have a formal drug early warning system. A coordinated program of fixed or event-based drug-checking is expensive and provides harm reduction information to atargeted user group. The South Australian Drug Early Warning System (SADEWS) is an informal inter-agency collaboration which rapidly and confidentially exchanges contemporary,evidence-based information about drug seizures, usage trends and clinical outcomes associated with drug use in South Australia. Information is sourced from policing, forensic analysis,waste-water analysis, medical research, clinical data and directly from people using drugs. SADEWS exchanges information relating to new drug emergences and clusters of adverseoutcomes following drug use, amongst members via secure digital platforms. The diverse but complimentary expertise of members allows a comprehensive assessment of changes tothe baseline risk associated with drug use and, where a potential community harm is identified, enables the timely delivery of warnings through formal mechanisms existing withinmember agencies. It is expected that these warnings contribute to significantly reduced medical consequences associated with community drug use through decreased drug overdosefatalities and hospital presentations rates, contributing to reduced healthcare costs. Importantly, this drug early warning system is politically risk-free, is achieved simply and without external funding or significant administrative overheads.

Automatic segmentation and classification of surgical activity is crucial for providing advanced support in computer-assisted interventions and autonomous functionalities in robot-assisted surgeries. Prior works have focused on recognizing either coarse activities, such as phases, or fine-grained activities, such as gestures. Iodoacetamide This work aims at jointly recognizing two complementary levels of granularity directly from videos, namely phases and steps.

We introduce two correlated surgical activities, phases and steps, for the laparoscopic gastric bypass procedure. We propose a multi-task multi-stage temporal convolutional network (MTMS-TCN) along with a multi-task convolutional neural network (CNN) training setup to jointly predict the phases and steps and benefit from their complementarity to better evaluate the execution of the procedure. We evaluate the proposed method on a large video dataset consisting of 40 surgical procedures (Bypass40).

We present experimental results from several baseline models for both phase and step recognition on the Bypass40.