BIOMECHANICAL CHANGES IN A PROFESSIONAL BASEBALL PITCHER: EARLY VS. LATE INNINGS

The purpose of the study was to investigate the effects of extended play on the kinematic and kinetic parameters of the baseball pitch in order to gain a better understanding of injury mechanisms and preventive strategies. Four professional pitchers were videotaped with high-speed (120 Hz) cameras during the second, fourth and sixth innings of the same game. Video data were digitised for one fastball for each inning, and kinematic and kinetic parameters were calculated from the 3D coordinate data. Comparisons between the pitches were based on standard deviations found for the same parameters in a similar study of 40 professional pitchers. Shoulder and elbow ranges of motion, peak varus torque, shoulder and elbow distraction and the rates of angular velocities were among the variables to show significant change

Creating a Safety Assurance Case for an ML Satellite-Based Wildfire Detection and Alert System

Wildfires are a common problem in many areas of the world with often catastrophic consequences. A number of systems have been created to provide early warnings of wildfires, including those that use satellite data to detect fires. The increased availability of small satellites, such as CubeSats, allows the wildfire detection response time to be reduced by deploying constellations of multiple satellites over regions of interest. By using machine learned components on-board the satellites, constraints which limit the amount of data that can be processed and sent back to ground stations can be overcome. There are hazards associated with wildfire alert systems, such as failing to detect the presence of a wildfire, or detecting a wildfire in the incorrect location. It is therefore necessary to be able to create a safety assurance case for the wildfire alert ML component that demonstrates it is sufficiently safe for use. This paper describes in detail how a safety assurance case for an ML wildfire alert system is created. This represents the first fully developed safety case for an ML component containing explicit argument and evidence as to the safety of the machine learning

Payments for Ecosystem Services: Legal and Institutional Frameworks

Analysis and engagement with partners working on ecosystem services transactions, policies and laws over the past 10 years have demonstrated a clear need to better understand the legal and institutional frameworks that have the potential to promote or hinder the development of payments for ecosystem services (PES) schemes, as well as the complex legal considerations that affect ecosystem services projects. In response, the IUCN Environmental Law Centre and The Katoomba Group have worked on a joint initiative to analyze the legal and institutional frameworks of water-related PES schemes and projects in four Andean countries: South America (Northeastern)-Brazil; Bolivia, Colombia and Peru. It has resulted in this report. Country-based analysts with experience in ecosystem services transactions have developed country and project assessments to define existing and recommend future regulatory and institutional frameworks that enable equitable and long-lasting ecosystem services transactions. Partners from North America (Central America)-Costa Rica; North America-Mexico; Ecuador and the North America-United States provided feedback on the assessments. The country assessments yielded lessons which were used to develop a set of recommendations on legal frameworks, property rights, enabling institutions, PES contracts, and governance issues supporting the future development of PES schemes

Adapting an in‐person patient–caregiver communication intervention to a tailored web‐based format

Background : Interventions that target cancer patients and their caregivers have been shown to improve patient‐caregiver communication, support, and emotional well‐being. Objective : To adapt an in‐person communication intervention for cancer patients and caregivers to a web‐based format, and to examine the usability and acceptability of the web‐based program among representative users. Methods : A tailored, interactive web‐based communication program for cancer patients and their family caregivers was developed based on an existing in‐person, nurse‐delivered intervention. The development process involved: (1) building a multidisciplinary team of content and web design experts, (2) combining key components of the in‐person intervention with the unique tailoring and interactive features of a web‐based platform, and (3) conducting focus groups and usability testing to obtain feedback from representative program users at multiple time points. Results : Four focus groups with 2–3 patient–caregiver pairs per group ( n = 22 total participants) and two iterations of usability testing with four patient–caregiver pairs per session ( n = 16 total participants) were conducted. Response to the program's structure, design, and content was favorable, even among users who were older or had limited computer and Internet experience. The program received high ratings for ease of use and overall usability (mean System Usability Score of 89.5 out of 100). Conclusions : Many elements of a nurse‐delivered patient–caregiver intervention can be successfully adapted to a web‐based format. A multidisciplinary design team and an iterative evaluation process with representative users were instrumental in the development of a usable and well‐received web‐based program. Copyright © 2011 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90066/1/pon1900.pd

Dynamic Control Flow in Large-Scale Machine Learning

Many recent machine learning models rely on fine-grained dynamic control flow for training and inference. In particular, models based on recurrent neural networks and on reinforcement learning depend on recurrence relations, data-dependent conditional execution, and other features that call for dynamic control flow. These applications benefit from the ability to make rapid control-flow decisions across a set of computing devices in a distributed system. For performance, scalability, and expressiveness, a machine learning system must support dynamic control flow in distributed and heterogeneous environments. This paper presents a programming model for distributed machine learning that supports dynamic control flow. We describe the design of the programming model, and its implementation in TensorFlow, a distributed machine learning system. Our approach extends the use of dataflow graphs to represent machine learning models, offering several distinctive features. First, the branches of conditionals and bodies of loops can be partitioned across many machines to run on a set of heterogeneous devices, including CPUs, GPUs, and custom ASICs. Second, programs written in our model support automatic differentiation and distributed gradient computations, which are necessary for training machine learning models that use control flow. Third, our choice of non-strict semantics enables multiple loop iterations to execute in parallel across machines, and to overlap compute and I/O operations. We have done our work in the context of TensorFlow, and it has been used extensively in research and production. We evaluate it using several real-world applications, and demonstrate its performance and scalability.Comment: Appeared in EuroSys 2018. 14 pages, 16 figure

The North Wyke Farm Platform: Methodologies Used in the Remote Sensing of the Quantity and Quality of Drainage Water

The North Wyke Farm Platform(NWFP) for agri-environmental research in temperate grassland was established in the UK in 2010 (Orr et al. 2011). Here we describe the instrumentation and methodologies used to monitor the quantity and quality of drainage water at a total of 15 H-flumes draining 5 sub-catchments within three farmlets. Each of 15 flume laboratories is supplied with 3 kW of mains power and connected to both fibre optic and UHF (Ultra High Frequency) radio networks for data exchange. The radio data network also provides telemetry for rain gauges and soil temperature/moisture probes located away from the flumes and within the catchment blocks. Water flow is measured using bubbler flow meters and when flow is above a defined threshold level, water is pumped into bespoke 13-litre stainless steel bypass cells on a 15-minute cycle using bi-directional peristaltic pumps. A range of sensors located within the bypass cells measure the following water quality parameters: nitrate, ammonium, dissolved organic carbon, temperature, conductivity, turbidity, pH and dissolved oxygen. Total phosphorus and ortho phosphorus are measured at one flume in each farmlet. Networked auto-samplers are also provided at each flume site for the measurement of other wa-ter quality parameters as required. All data are logged and sent to a dedicated server at a 15 min resolution while a web front end allows advanced visualization capabilities and remote control of the entire system. The system is configured to allow for flexibility and future expansion to a wider range of parameters

Superior outcomes of nodal metastases compared to visceral sites in oligometastatic colorectal cancer treated with stereotactic ablative radiotherapy

BACKGROUND: Stereotactic ablative radiotherapy (SBRT) is a radical option for oligometastatic colorectal cancer (CRC) patients, but most data relate to visceral metastases. METHODS: A prospective, multi-centre database of CRC patients treated with SBRT was interrogated. Inclusion criteria were ECOG PS 0-2, ≤ 3 sites of disease, a disease free interval of > 6 months unless synchronous liver metastases. Primary endpoints were local control (LC), progression free survival (PFS) and overall survival (OS). RESULTS: 163 patients (172 metastases) were analysed. The median FU was 16 months (IQR 12.2 - 22.85). The LC at 1 year was 83.8% (CI 76.4% - 91.9%) with a PFS of 55% (CI 47% - 64.7%) respectively. LC at 1 year was 90% (CI 83% - 99%) for nodal metastases (NM), 75% (63% - 90%) for visceral metastases (VM). NM had improved median PFS (9 vs 19 months) [HR 0.6, CI 0.38 - 0.94, p = 0.032] and median OS (32 months vs not reached) [HR 0.28, CI 0.18 - 0.7, p = 0.0062] than VM, regardless of whether the NM were located inside or outside the pelvis. On multivariate analysis, NM and ECOG PS 0 were significant good prognostic factors. An exploratory analysis suggests KRAS WT is also a good prognostic factor. CONCLUSION: Nodal site is an important prognostic determinant of SBRT that should incorporated into patient selection. We hypothesise this may have an immunoediting basis

The North Wyke Farm Platform: A New UK National Capability for Research into Sustainability of Agricultural Temperate Grassland Management

The North Wyke Farm Platform is a new UK National Capability that will enable studies that can be closely monitored and controlled under different land-use options at the farm-scale. As a Biotechnology and Biological Sciences Research Council-funded National Capability, the Farm Platform provides centralised scientific facilities including core data (field and water chemistry, water flow rates, greenhouse gas emissions from soils, livestock and agronomic data, and farm management records). Access to the Farm Platform for experimental work or to data will be available to other research users and collaborators. This shared approach will enhance the depth and breadth of information gained for the benefit of the wider community

Galaxy Zoo: Exploring the Motivations of Citizen Science Volunteers

The Galaxy Zoo citizen science website invites anyone with an Internet connection to participate in research by classifying galaxies from the Sloan Digital Sky Survey. As of April 2009, more than 200,000 volunteers had made more than 100 million galaxy classifications. In this paper, we present results of a pilot study into the motivations and demographics of Galaxy Zoo volunteers, and define a technique to determine motivations from free responses that can be used in larger multiple-choice surveys with similar populations. Our categories form the basis for a future survey, with the goal of determining the prevalence of each motivation.Comment: 15 pages, 3 figure