Best Management Practices: How Economical is it in Southern Agricultural Systems?

Conventional drainage systems tend to aggravate runoff and nutrient leaching problems on farms especially during the off-season. This study uses a biophysical economic model to identify, evaluate and determine multifunctional benefits of implementing and establishing nitrogen rate fertilizer application and conservation tillage practices as best management practices (BMPs) in the lower Mississippi River Basin (MRB). Simulation results showed that agricultural producers generally preferred no tillage to conventional tillage in reducing nutrient runoffs from fields because of higher net revenue per acre. Finally, given nitrogen runoff restrictions, farmers reduced crop acreage and nitrogen fertilizer application rates to help minimize losses.biopysical economic model, tillage practices, nitrogen fertilizer application rates, MRB, Agricultural and Food Policy, Crop Production/Industries, Environmental Economics and Policy, Farm Management,

A new curcuma extract (flexofytol(R)) in osteoarthritis: results from a belgian real-life experience.

This retrospective observational study summarizes the experiences of 820 patients treated with a new Curcuma extract (Flexofytol(R), 4-6 capsules per day), for more than 6 months for various forms of painful osteoarthritis. These experiences were reported by 110 Belgian general practitioners via a questionnaire that included quality-of-life parameters for assessing patient experience. Data were submitted to an independent statistician for analysis. Within the first 6 weeks, Flexofytol(R) improved patient pain, articular mobility, and quality of life. Excellent tolerance was reported, and more than half of these patients were able to discontinue analgaesic and anti-inflammatory drugs. Patient satisfaction was confirmed by their decision to maintain Flexofytol(R) therapy for more than 6 months. These data must be confirmed with randomized controlled studies. We currently conclude that Flexofytol(R) which is based on a new preparation of curcumin, is as a potential neutraceutical for the care of patients complaining of joint problems, with excellent tolerance and rapid benefits for articular mobility, pain, and quality of life.Peer reviewe

A comparative study of engagement in mobile and wearable health monitoring for bipolar disorder

ObjectivesSelf‐monitoring is recommended for individuals with bipolar disorder, with numerous technological solutions available. This study aimed to identify basic components of these solutions that increase engagement with self‐monitoring.MethodsParticipants with bipolar disorder (n = 47) monitored their symptoms with a Fitbit and a smartphone app and were randomly assigned to either review or not review recorded symptoms weekly. We tested whether individuals would better adhere to and prefer monitoring with passive monitoring with an activity tracker compared to active monitoring with a smartphone app and whether individuals would better adhere to self‐monitoring if their recorded symptoms were reviewed with an interviewer.ResultsMonitoring with a smartphone app achieved similar adherence and preference to Fitbit (P > .85). Linear mixed effects modeling found adherence decreased significantly more over the study for the Fitbit (12% more, P < .001) even though more participants reported they would use the Fitbit over a year compared to the app (72.3% vs 46.8%). Reviewing symptoms weekly did not improve adherence, but most participants reported they would prefer to review symptoms with a clinician (74.5%) and on monthly basis (57.5%) compared to alternatives. Participants endorsed sleep as the most important symptom to monitor, forgetfulness as the largest barrier to self‐monitoring, and raising self‐awareness as the best reason for self‐monitoring.ConclusionsWe recommend a combined strategy of wearable and mobile monitoring that includes reminders, targets raising self‐awareness, and tracks sleep. A clinician may want to review symptoms on a monthly basis.Trial registration: ClinicalTrials.gov NCT03358238.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154615/1/bdi12849_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154615/2/bdi12849.pd

Silicon Valley new focus on brain computer interface: hype or hope for new applications?

In the last year there has been increasing interest and investment into developing devices to interact with the central nervous system, in particular developing a robust brain-computer interface (BCI). In this article, we review the most recent research advances and the current host of engineering and neurological challenges that must be overcome for clinical application. In particular, space limitations, isolation of targeted structures, replacement of probes following failure, delivery of nanomaterials and processing and understanding recorded data. Neural engineering has developed greatly over the past half-century, which has allowed for the development of better neural recording techniques and clinical translation of neural interfaces. Implementation of general purpose BCIs face a number of constraints arising from engineering, computational, ethical and neuroscientific factors that still have to be addressed. Electronics have become orders of magnitude smaller and computationally faster than neurons, however there is much work to be done in decoding the neural circuits. New interest and funding from the non-medical community may be a welcome catalyst for focused research and development; playing an important role in future advancements in the neuroscience community

Silicon Valley new focus on brain computer interface: hype or hope for new applications? [version 1; referees: 2 approved, 1 approved with reservations]

In the last year there has been increasing interest and investment into developing devices to interact with the central nervous system, in particular developing a robust brain-computer interface (BCI). In this article, we review the most recent research advances and the current host of engineering and neurological challenges that must be overcome for clinical application. In particular, space limitations, isolation of targeted structures, replacement of probes following failure, delivery of nanomaterials and processing and understanding recorded data. Neural engineering has developed greatly over the past half-century, which has allowed for the development of better neural recording techniques and clinical translation of neural interfaces. Implementation of general purpose BCIs face a number of constraints arising from engineering, computational, ethical and neuroscientific factors that still have to be addressed. Electronics have become orders of magnitude smaller and computationally faster than neurons, however there is much work to be done in decoding the neural circuits. New interest and funding from the non-medical community may be a welcome catalyst for focused research and development; playing an important role in future advancements in the neuroscience community

Incentivizing the Use of Quantified Self Devices: The Cases of Digital Occupational Health Programs and Data-Driven Health Insurance Plans

Initially designed for a use in private settings, smartwatches, activity trackers and other quantified self devices are receiving a growing attention from the organizational environment. Firms and health insurance companies, in particular, are developing digital occupational health programs and data-driven health insurance plans centered around these systems, in the hope of exploiting their potential to improve individual health management, but also to gather large quantities of data. As individual participation in such organizational programs is voluntary, organizations often rely on motivational incentives to prompt engagement. Yet, little is known about the mechanisms employed in organizational settings to incentivize the use of quantified self devices. We therefore seek, in this exploratory paper, to offer a first structured overview of this topic and identify the main motivational incentives in two emblematical cases: digital occupational health programs and data-driven health insurance plans. By doing so, we aim to specify the nature of this new dynamic around the use of quantified self devices and define some of the key lines for further investigation