SMALL FARMS AND SUSTAINABLE DEVELOPMENT: IS SMALL MORE SUSTAINABLE?

A new, post-industrial, paradigm for agriculture is emerging under the concept of sustainable agriculture. The sustainability paradigm has emerged to solve problems created by the industrial model, primarily environmental pollution and resource base degradation. The role of farm size in this transformation to a more sustainable agriculture is the issue addressed. Using a descriptive approach, and relying on a survey of the literature including emerging paradigms and observations, we conclude that, from a sustainability perspective, the smallest effective size will be the most competitive size for farms, as for other knowledge-based enterprises of the future.Agriculture, Farm size, Paradigms, Sustainability, Environmental Economics and Policy, Farm Management,

Tolerability, safety, and efficacy of adjunctive brivaracetam for focal seizures in older patients: A pooled analysis from three phase III studies

Introduction: This analysis was conducted to assess the tolerability, safety, and efficacy of brivaracetam (BRV) for adjunctive treatment of focal (partial-onset) seizures in patients aged ≥65 years. Methods: Safety/tolerability and efficacy data for patients aged ≥65 years were pooled from three randomized, double-blind, placebo-controlled, fixed-dose Phase III studies (NCT00490035, NCT00464269, and NCT01261325). Data were pooled by treatment group: placebo or the proposed therapeutic dose range of 50–200 mg/day: BRV 50, 100, 200 mg/day. Results: Thirty-two patients aged ≥65 years were randomized to placebo or BRV 50–200 mg/day. Of these, 30 patients (93.8%) completed their respective study. In the safety population (n = 32), 87.5% placebo- vs 73.3% BRV-treated patients reported treatment-emergent adverse events (TEAEs) during the treatment period; most commonly, headache (25.0% vs 12.5%), paresthesia (0% vs 12.5%), and somnolence (50.0% vs 12.5%) for placebo- vs BRV-treated patients, respectively. During the treatment period, drug-related TEAEs were reported by 62.5% of placebo- vs 53.3% of BRV-treated patients, and serious TEAEs (SAEs) were reported by 0% of placebo- and 4.2% of BRV-treated patients; there were no drug-related SAEs and no deaths. Three SAEs (placebo 1/8; BRV 2/24) and two deaths (placebo 1/8; BRV 1/24) occurred in the post-treatment period. In the efficacy population (n = 31), median percent reduction from baseline in focal seizure frequency/28 days was 14.0% for placebo vs 25.5%, 49.6%, and 74.9% for BRV 50, 100, and 200 mg/day, respectively. The ≥50% responder rate was 14.3% for placebo vs 25.0%, 50.0%, and 66.7% for BRV 50, 100, and 200 mg/day, respectively. Conclusions: Safety/tolerability and efficacy findings in this small subgroup of older patients treated with adjunctive BRV are consistent with those observed in the much larger overall pooled population. BRV may be a suitable adjunctive treatment for older patients with uncontrolled focal seizures. Further larger studies in this population are warranted

Orion Relative Navigation Flight Software Analysis and Design

The Orion relative Navigation System has sought to take advantage of the latest developments in sensor and algorithm technology while living under the constraints of mass, power, volume, and throughput. In particular, the only sensor specifically designed for relative navigation is the Vision Navigation System (VNS), a lidar-based sensor. But it uses the Star Trackers, GPS (when available) and IMUs, which are part of the overall Orion navigation sensor suite, to produce a relative state accurate enough to dock with the ISS. The Orion Relative Navigation System has significantly matured as the program has evolved from the design phase to the flight software implementation phase. With the development of the VNS system and the STORRM flight test of the Orion Relative Navigation hardware, much of the performance of the system will be characterized before the first flight. However challenges abound, not the least of which is the elimination of the RF range and range-rate system, along with the development of the FSW in the Matlab/Simulink/Stateflow environment. This paper will address the features and the rationale for the Orion Relative Navigation design as well as the performance of the FSW in a 6-DOF environment as well as the initial results of the hardware performance from the STORRM flight

Predictors of dental visits among primary school children in the rural Australian community of Lithgow

Background: Regular dental attendance is significant in maintaining and improving children’s oral health and well-being. This study aims to determine the factors that predict and influence dental visits in primary school children residing in the rural community of Lithgow, New South Wales (NSW), Australia. Methods: All six primary schools of Lithgow were approached to participate in a cross-sectional survey prior to implementing water fluoridation in 2014. Children aged 6–13 years (n = 667) were clinically examined for their oral health status and parents were requested to complete a questionnaire on fluoride history, diet, last dental visit, and socio-demographic characteristics. Multiple logistic regression analyses were employed to examine the independent predictors of a 6-monthly and a yearly dental visit. Results: Overall, 53% of children visited a dentist within six months and 77% within twelve months. In multiple logistic regression analyses, age of the child and private health insurance coverage were significantly associated with both 6-monthly and twelve-month dental visits. In addition, each serve of chocolate consumption was significantly associated with a 27% higher odds (OR = 1.27, 95% CI: 1.05-1.54) of a 6-monthly dental visit. Conclusion: It is imperative that the socio-demographic and dietary factors that influence child oral health must be effectively addressed when developing the oral health promotion policies to ensure better oral health outcomes.James Rufus John, Haider Mannan, Subrat Nargundkar, Mario D’Souza, Loc Giang Do and Amit Aror

The Space Operations Simulation Center (SOSC) and Closed-loop Hardware Testing for Orion Rendezvous System Design

The Space Operations Simulation Center (SOSC) at the Lockheed Martin (LM) Waterton Campus in Littleton, Colorado is a dynamic test environment focused on Autonomous Rendezvous and Docking (AR&D) development testing and risk reduction activities. The SOSC supports multiple program pursuits and accommodates testing Guidance, Navigation, and Control (GN&C) algorithms for relative navigation, hardware testing and characterization, as well as software and test process development. The SOSC consists of a high bay (60 meters long by 15.2 meters wide by 15.2 meters tall) with dual six degree-of-freedom (6DOF) motion simulators and a single fixed base 6DOF robot. The large testing area (maximum sensor-to-target effective range of 60 meters) allows for large-scale, flight-like simulations of proximity maneuvers and docking events. The facility also has two apertures for access to external extended-range outdoor target test operations. In addition, the facility contains four Mission Operations Centers (MOCs) with connectivity to dual high bay control rooms and a data/video interface room. The high bay is rated at Class 300,000 (. 0.5 m maximum particles/m3) cleanliness and includes orbital lighting simulation capabilities

The Sensor Test for Orion RelNav Risk Mitigation (STORRM) Development Test Objective

The Sensor Test for Orion Relative-Navigation Risk Mitigation (STORRM) Development Test Objective (DTO) flew aboard the Space Shuttle Endeavour on STS-134 in May- June 2011, and was designed to characterize the performance of the flash LIDAR and docking camera being developed for the Orion Multi-Purpose Crew Vehicle. The flash LIDAR, called the Vision Navigation Sensor (VNS), will be the primary navigation instrument used by the Orion vehicle during rendezvous, proximity operations, and docking. The DC will be used by the Orion crew for piloting cues during docking. This paper provides an overview of the STORRM test objectives and the concept of operations. It continues with a description of STORRM's major hardware components, which include the VNS, docking camera, and supporting avionics. Next, an overview of crew and analyst training activities will describe how the STORRM team prepared for flight. Then an overview of in-flight data collection and analysis is presented. Key findings and results from this project are summarized. Finally, the paper concludes with lessons learned from the STORRM DTO

The involvement of model-based but not model-free learning signals during observational reward learning in the absence of choice

A major open question is whether computational strategies thought to be used during experiential learning, specifically model-based and model-free reinforcement learning, also support observational learning. Furthermore, the question of how observational learning occurs when observers must learn about the value of options from observing outcomes in the absence of choice has not been addressed. In the present study we used a multi-armed bandit task that encouraged human participants to employ both experiential and observational learning while they underwent functional magnetic resonance imaging (fMRI). We found evidence for the presence of model-based learning signals during both observational and experiential learning in the intraparietal sulcus. However, unlike during experiential learning, model-free learning signals in the ventral striatum were not detectable during this form of observational learning. These results provide insight into the flexibility of the model-based learning system, implicating this system in learning during observation as well as from direct experience, and further suggest that the model-free reinforcement learning system may be less flexible with regard to its involvement in observational learning