Nonlinear saturation of ion-acoustic instability

It is proposed that the wave mediated indirect wave-particle interaction may be responsible for nonlinear saturation of current driven low frequency ion-acoustic turbulence. This process decreases the growth rate and increases the damping rate of the wave. Comparison has been made with some experiments.

Effect of ionic temperature on propagation of ion-acoustic solitary waves in a collisionless plasma of warm-ion fluid and non-isothermal electrons

Using a perturbation technique, we derive Modified Korteweg—de Vries (MKdV) equations for a mixture of warm-ion fluid (γ i = 3) and hot and non-isothermal electrons (γ e> 1), (i) when deviations from isothermality are finite, and (ii) when deviations from isothermality are small. We obtain stationary solutions for these equations, and compare them with the corresponding solutions for a mixture of warm-ion fluid (γ i = 3) and hot, isothermal electrons (γ i = 1).

Prevention of foot ulcers in the at-risk patient with diabetes: A systematic review

Background Prevention of foot ulcers in patients with diabetes is extremely important to help reduce the enormous burden of foot ulceration on both patient and health resources. A comprehensive analysis of reported interventions is not currently available, but is needed to better inform caregivers about effective prevention. The aim of this systematic review is to investigate the effectiveness of interventions to prevent first and recurrent foot ulcers in persons with diabetes who are at risk for ulceration. Methods The available medical scientific literature in PubMed, EMBASE, CINAHL and the Cochrane database was searched for original research studies on preventative interventions. Both controlled and non-controlled studies were selected. Data from controlled studies were assessed for methodological quality by two independent reviewers. Results From the identified records, a total of 30 controlled studies (of which 19 RCTs) and another 44 non-controlled studies were assessed and described. Few controlled studies, of generally low to moderate quality, were identified on the prevention of a first foot ulcer. For the prevention of recurrent plantar foot ulcers, multiple RCTs with low risk of bias show the benefit for the use of daily foot skin temperature measurements and consequent preventative actions, as well as for therapeutic footwear that demonstrates to relieve plantar pressure and that is worn by the patient. To prevent recurrence, some evidence exists for integrated foot care when it includes a combination of professional foot treatment, therapeutic footwear and patient education; for just a single session of patient education, no evidence exists. Surgical interventions can be effective in selected patients, but the evidence base is small. Conclusion The evidence base to support the use of specific self-management and footwear interventions for the prevention of recurrent plantar foot ulcers is quite strong, but is small for the use of other, sometimes widely applied, interventions and is practically nonexistent for the prevention of a first foot ulcer and non-plantar foot ulcer.

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Symposium: Food pricing and affordability of ‘healthy’ versus ‘less healthy’ diets: An international approach to monitoring and surveillance

Symposium co-ordinated by The International Network for Food and Obesity/NCDs Research, Monitoring and Action Support (INFORMAS) Purpose Global monitoring of the price and affordability of foods, meals and diets is urgently needed. There are major methodological challenges in developing robust, cost-effective, standardized, and policy relevant tools, pertinent to nutrition, obesity, and diet-related non-communicable diseases and their inequalities. There is increasing pressure to take into account environmental sustainability. Changes in price differentials and affordability need to be comparable between and within countries and over time. Robust tools could provide baseline data for monitoring and evaluating structural, economic and social policies at the country/regional and household levels. INFORMAS offers one framework for consideration.

Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.