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The GLT project is deploying a new submillimeter (submm) VLBI station in Greenland. Our primary scientific goal is to image a shadow of the supermassive black hole (SMBH) of six billion solar masses in M87 at the center of the Virgo cluster of galaxies. The expected SMBH shadow size of 40-50 μas requires superbly high angular resolution, suggesting that the submm VLBI would be the only way to obtain the shadow image. The Summit station in Greenland enables us to establish baselines longer than 9,000 km with ALMA in Chile and SMA in Hawaii as well as providing a unique u–v coverage for imaging M87. Our VLBI network will achieve a superior angular resolution of about 20 μas at 350 GHz, corresponding to ∼ 2.5 times of the Schwarzschild radius of the supermassive black hole in M87. We have been monitoring the atmospheric opacity at 230 GHz since August. 2011; we have confirmed the value on site during the winter season is comparable to the ALMA site thanks to high altitude of 3,200 m and low temperature of −50°C. We will report current status and future plan of the GLT project towards our expected first light on 2015–2016.

The morphology-performance-fitness paradigm has long been a guiding principle inspiring a great deal of laboratory and field studies fundamental to understanding functional-morphology relationships across the tree of life. Despite the power of experimental approaches, they also come with inherent limitations associated with equipment and animal costs, as well as ethical considerations for the types of manipulations that can be implemented. Modeling can provide an opportunity to surmount some of these challenges by offering greater flexibility in manipulating variables and exploring a wider parameter space than is tractable during animal experimentation. However, effective implementation of these tools requires careful consideration of the limitations and benefits they convey, requiring both greater interdisciplinary training from early stages of educational development and increased collaboration and synergies among scientists from traditionally separate disciplines. With institutions increasingly recognizing the need for and investing in providing universal access to computational and rapid prototyping resources, we believe that it is an opportune moment to prioritize greater synergy to accelerate discovery and innovation across fields. [ABSTRACT FROM AUTHOR]

The ability to upright quickly and efficiently when overturned on the ground (terrestrial self-righting) is crucial for living organisms and robots. Previous studies have mapped the diverse behaviors used by various animals to self-right on different substrates, and proposed physical models to explain how body morphology can favor specific self-righting methods. However, to our knowledge, no studies have quantified and modeled all of an animal's limb motions during these complicated behaviors. Here, we studied terrestrial self-righting by immature invasive spotted lanternflies (Lycorma delicatula), an insect species that must frequently recover from being overturned after jumping and falling in its native habitat. These nymphs self-righted successfully in 92–100% of trials on three substrates with different friction and roughness, with no significant difference in the time or number of attempts required. They accomplished this using three stereotypic sequences of movements. To understand these motions, we combined 3D poses tracked on multi-view high-speed video with articulated 3D models created using photogrammetry and Blender rendering software. The results were used to calculate the mechanical properties (e.g. potential and kinetic energy, angular speed, stability margin, torque, force, etc.) of these insects during righting trials. We used an inverted physical pendulum model (a "template") to estimate the kinetic energy available in comparison to the increase in potential energy required to flip over. While these insects began righting using primarily quasistatic motions, they also used dynamic leg motions to achieve final tip-over. However, this template did not describe important features of the insect's center of mass trajectory and rotational dynamics, necessitating the use of an "anchor" model comprising the 3D rendered body model and six articulated two-segment legs to model the body's internal degrees of freedom and capture the role of the legs' contribution to inertial reorientation. This anchor elucidated the sequence of highly coordinated leg movements these insects used for propulsion, adhesion, and inertial reorientation during righting, and how they frequently pivot about a body contact point on the ground to flip upright. In the most frequently used method, diagonal rotation, these motions allowed nymphs to spin their bodies to upright with lower force with a greater stability margin compared to the other less frequently used methods. We provide a concise overview of necessary background on 3D orientation and rotational dynamics, and the resources required to apply these low-cost modeling methods to other problems in biomechanics. [ABSTRACT FROM AUTHOR]

Nondisplaced femoral neck fractures are sometimes misdiagnosed by radiographs, which may deteriorate into displaced fractures. However, few efficient artificial intelligent methods have been reported. We developed an automatic detection method using deep learning networks to pinpoint femoral neck fractures on radiographs to assist physicians in making an accurate diagnosis in the first place. Our proposed accurate automatic detection method, called the direction-aware fracture-detection network (DAFDNet), consists of two steps, namely region-of-interest (ROI) segmentation and fracture detection. The first step removes the noise region and pinpoints the femoral neck region. The fracture-detection step uses a direction-aware deep learning algorithm to mark the exact femoral neck fracture location in the region detected in the first step. A total of 3840 femoral neck parts in anterior–posterior (AP) pelvis radiographs collected from the China Medical University Hospital database were used to test our method. The simulation results showed that DAFDNet outperformed the U-Net and DenseNet methods in terms of the IOU value, Dice value, and Jaccard value. Our proposed DAFDNet demonstrated over 94.8% accuracy in differentiating non-displaced Garden type I and type II femoral neck fracture cases. Our DAFDNet method outperformed the diagnostic accuracy of general practitioners and orthopedic surgeons in accurately locating Garden type I and type II fracture locations. This study can determine the feasibility of applying artificial intelligence in a clinical setting and how the use of deep learning networks assists physicians in improving correct diagnoses compared to the current traditional orthopedic manual assessments. [ABSTRACT FROM AUTHOR]

In this study, we develop an innovative method that assists computer-aided diagnosis in the determination process of the exact location of the femoral neck junction in plain radiographs. Our algorithm consists of two phases, i.e., coarse prediction and fine matching, which are implemented by supervised deep learning method and unsupervised clustering, respectively. In coarse prediction, standard masks are first produced by a specialist and trained in our proposed feature propagation network (FPU-Net) with supervised learning on the femoral neck dataset. In fine matching, the standard masks are first classified into different categories using our proposed three parameters with unsupervised learning. The predicted mask from FPU-Net is matched with each category of standard masks by calculating the values of intersection of union (IOU), and finally the predicted mask is substituted by the standard mask with the largest IOU value. A total of 4320 femoral neck parts in anterior–posterior (AP) pelvis radiographs collected from China Medical University Hospital database were used to test our method. Simulation results show that, on the one hand, compared with other segmentation methods, the method proposed in this paper has a larger IOU value and better suppression of noise outside the region of interest; on the other hand, the introduction of unsupervised learning for fine matching can help in the accurate localization segmentation of femoral neck images. Accurate femoral neck segmentation can assist surgeons to diagnose and reduce the misdiagnosis rate and burden. [ABSTRACT FROM AUTHOR]

Chern-Horng Lee,1 Cheng-Li Lin,2 Tzung-Hai Yen,3 Sen-Yung Hsieh4,5 1Department of Geriatric Medicine and General Internal Medicine, Chang Gung Memorial Hospital, Linkou Branch, Taoyuan, Taiwan; 2Management Office for Health Data, China Medical University Hospital, Taichung, Taiwan; 3Department of Nephrology, Chang Gung Memorial Hospital, Linkou Branch, Taoyuan, Taiwan; 4Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Linkou Branch, Taoyuan, Taiwan; 5College of Medicine, Chang Gung University, Taoyuan, TaiwanCorrespondence: Sen-Yung Hsieh, Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Linkou, Taoyuan, 333, Taiwan, Tel +886-975368031, Fax +886-33272324, Email siming.shia@msa.hinet.net; siming@cgmh.org.twPurpose: Aspirin, known to reduce the risk of liver cancer, has been proposed as a preventive measure for patients with chronic hepatitis and cirrhosis. However, concerns regarding aspirin’s potential to cause gastrointestinal (GI) mucosal injury and bleeding have emerged. Several antiplatelets other than aspirin (APOA) that pose a smaller risk of GI bleeding than aspirin have been proposed as potential aspirin substitutes. This study investigated whether APOAs were effective at reducing the risk of hepatocellular carcinoma (HCC). Additionally, we evaluated the safety of APOAs, specifically regarding their potential to increase the risk of GI bleeding, in a nationwide cirrhosis cohort.Patients and Methods: For the period January 1, 2000, to December 31, 2017, we identified 686 993 patients with cirrhosis from a national database. A control group was established using 1:2 propensity score matching on the basis of sex, age, comorbidities, and medication use.Results: Daily use of APOAs was significantly associated with lower incidences of HCC (aHR 0.67; 95% CI, 0.60– 0.73; P < 0.001) and showed no significant increase in GI bleeding risk (aHR 1.04; 95% CI, 0.93– 1.15; P = 0.533) compared to nonuse of APOAs. However, the risks of intracranial hemorrhage (aHR, 1.41; 95% CI, 1.18 to 1.69; P < 0.001) and overall mortality (aHR, 2.03; 95% CI, 1.95 to 2.10; P < 0.001) were higher in the APOA user group.Conclusion: Our results suggest that although daily use of APOAs other than aspirin may decrease the HCC risk of patients with cirrhosis, it may also increase their risks of intracranial hemorrhage and overall mortality. Therefore, the use of APOAs as an alternative to aspirin for HCC prevention in patients with cirrhosis requires careful consideration.Keywords: cirrhosis, antiplatelet agents, hepatocellular carcinoma, intracranial hemorrhage, mortality

A major ongoing research effort seeks to understand the behavior, ecology and control of the spotted lanternfly (SLF) (Lycorma delicatula), a highly invasive pest in the U.S. and South Korea. These insects undergo four nymphal stages (instars) before reaching adulthood, and appear to shift host plant preferences, feeding, dispersal and survival patterns, anti-predator behaviors, and response to traps and chemical controls with each stage. However, categorizing SLF life stage is challenging for the first three instars, which have the same coloration and shape. Here we present a dataset of body mass and length for SLF nymphs throughout two growing seasons and compare our results with previously-published ranges of instar body lengths. An analysis using two clustering methods revealed that 1st-3rd instar body mass and length fell into distinct clusters consistently between years, supporting using these metrics to stage nymphs during a single growing season. The length ranges for 2nd-4th instars agreed between years in our study, but differed from those reported by earlier studies for diverse locations, indicating that it is important to obtain these metrics relevant to a study's region for most accurate staging. We also used these data to explore the scaling of SLF instar bodies during growth. SLF nymph body mass scaled with body length varied between isometry (constant shape) and growing somewhat faster than predicted by isometry in the two years studied. Using previously published data, we also found that SLF nymph adhesive footpad area varies in direct proportion to weight, suggesting that footpad adhesion is independent of nymphal stage, while their tarsal claws display positive allometry and hence disproportionately increasing grasp (mechanical adhesion). By contrast, mouthpart dimensions are weakly correlated with body length, consistent with predictions that these features should reflect preferred host plant characteristics rather than body size. We recommend future studies use the body mass vs length growth curve as a fitness benchmark to study how SLF instar development depends on factors such as hatch date, host plant, temperature, and geographic location, to further understanding of life history patterns that help prevent further spread of this invasive insect. [ABSTRACT FROM AUTHOR]

Objectives: To measure the impact of full versus partial ABCDE bundle implementation on specific cost centers and related resource utilization. Design: Retrospective cohort study. Setting: Two medical ICUs within Montefiore Health System (Bronx, NY). Patients: Four hundred and seventy-two mechanically ventilated patients admitted to the medical ICUs during a hospitalization which began and ended between January 1, 2013 and December 31, 2013. Interventions: The full (A)wakening, (B)reathing, (C)oordination, (D)elirium Monitoring/Management and (E)arly Mobilization bundle was implemented in the intervention ICU while a portion of the bundle (A, B, and D components) was implemented in the comparison ICU. Measurements and Main Results: Relative to the comparison ICU, implementation of the entire bundle in the intervention ICU was associated with a 27.3% (95% CI: 9.9%, 41.3%; P = 0.004) decrease in total hospital laboratory costs and a 2,888.6% (95% CI: 77.9%, 50,113.2%; P = 0.018) increase in total hospital physical therapy costs. Cost of total hospital medications, diagnostic radiology and respiratory therapy were unchanged. Relative to the comparison ICU, total hospital resource use decreased in the intervention ICU (incidence rate ratio [95% CI], laboratory: 0.68 [0.54, 0.87], P = 0.002; diagnostic radiology: 0.75 [0.59, 0.96], P = 0.020). Conclusions: Full ABCDE bundle implementation resulted in a decrease in total hospital laboratory costs and total hospital laboratory and diagnostic resource utilization while leading to an increase in physical therapy costs. [ABSTRACT FROM AUTHOR]