I looked into the MIND diet after seeing it referenced in a PBS fund-raising infomercial. Basically it makes some modifications to the DASH and Mediterranean diets. I think it may have possibilities, but the critique is that the study used a relatively small, very racially homogeneous sample from retirement homes in Chicago, that they relied on self-reported food diaries, and that dropout over the course of the study was not evenly distributed between the test and control groups. Having said that, some subsequent studies have come to similar conclusions.
Dementia is now the 6th leading cause of death in the U.S.1 and the prevention of cognitive decline, the hallmark feature of dementia, is a public health priority. It is estimated that delaying disease onset by just 5 years will reduce the cost and prevalence by half.2 Diet interventions have the potential to be effective preventive strategies. Two randomized trials of the cultural-based Mediterranean diet3 and of the blood pressure lowering DASH diet (Dietary Approach to Systolic Hypertension)4 observed protective effects on cognitive decline.5;6 We devised a new diet that is tailored to protection of the brain, called MIND (Mediterranean-DASH Diet Intervention for Neurodegenerative Delay). The diet is styled after the Mediterranean and DASH diets but with modifications based on the most compelling findings in the diet-dementia field. For example, a number of prospective studies7–10 observed slower decline in cognitive abilities with high consumption of vegetables, and in the two U.S. studies, the greatest protection was from green leafy vegetables.7;8 Further, all of these studies found no association of overall fruit consumption with cognitive decline. However, animal models11 and one large prospective cohort study12 indicate that at least one particular type of fruit – berries - may protect the brain against cognitive loss. Thus, among the unique components of the MIND diet score are that it specifies consumption of green leafy vegetables and berries but does not score other types of fruit. In this study, we related the MIND diet score to cognitive decline in the Memory and Aging Project (MAP) and compared the estimated effects to those of the Mediterranean and DASH diets, dietary patterns that we previously reported were protective against cognitive decline among the MAP study participants.13
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METHODS
Study Population
The analytic sample is drawn from the Rush Memory and Aging Project (MAP), a study of residents of more than 40 retirement communities and senior public housing units in the Chicago area. Details of the MAP study were published previously.14 Briefly, the ongoing open cohort study began in 1997 and includes annual clinical neurological examinations. At enrollment, participants are free of known dementia15;16 and agree to annual clinical evaluation and organ donation after death. We excluded persons with dementia based on accepted clinical criteria as previously described.15,16 Participants meeting criteria for mild cognitive impairment17 (n=220) were not excluded except in secondary analyses. From February 2004- 2013, the MAP study participants were invited to complete food frequency questionnaires at the time of their annual clinical evaluations. During that period, a total of 1,545 older persons had enrolled in the MAP study, 90 died and 149 withdrew before the diet study began, leaving 1306 participants eligible for these analyses. Of these, 1068 completed the dietary questionnaires of which 960 survived and had at least two cognitive assessments for the analyses of change. The analytic sample was 95% white and 98.5% non-Hispanic. The Institutional Review Board of Rush University Medical Center approved the study, and all participants gave written informed consent.
Cognitive Assessments
Each participant underwent annual structured clinical evaluations including cognitive testing. Technicians, trained and certified according to standardized neuropsychological testing methods, administered 21 tests, 19 of which summarized cognition in five cognitive domains (episodic memory, working memory, semantic memory, visuospatial ability, and perceptual speed) as described previously.18 Composite scores were computed for each cognitive domain and for a global measure of all 19 tests. Raw scores for each test were standardized using the mean and standard deviation from the baseline population scores, and the standardized scores averaged. The number of annual cognitive assessments analyzed for participants ranged from 2 to 10 with 52% of sample participants having 5 or more cognitive assessments.
Diet Assessment
FFQs were collected at each annual clinical evaluation. For these prospective analyses of the estimated dietary effects on cognitive change, we used the first obtained FFQ to relate dietary scores to cognitive change from that point forward. Longitudinal analyses of change in MIND diet score using all available FFQs in a linear mixed model indicated a very small but statistically significant decrease in MIND score of −0.026 (p=0.02) compared to the intercept MIND diet score of 7.37.
Diet scores were computed from responses to a modified Harvard semi-quantitative food frequency questionnaire (FFQ) that was validated for use in older Chicago community residents.19 The FFQ ascertains usual frequency of intake over the previous 12 months of 144 food items. For some food items, natural portion sizes (e.g. 1 banana) were used to determine serving sizes and calorie and nutrient levels. Serving sizes for other food items were based on sex-specific mean portion sizes reported by the oldest men and women of national surveys.
Can you provide some image difference results between the reference images and the resulting super-resolution output? That would help to visualize what sort of structure, if any, is introduced by the super-resolution process.
The "leopard spots" example is particularly interesting in how the super-resolution just hallucinates seemingly similar textures which can be completely different from the actual texture in the reference patch. (Such artifacts have been specifically pointed out in the context of analogous deep learning approaches applied to medical images).
It is not structure per se (although in the case of the leopard there is structure). It is an illicit inference.
Given a diffusion process (as blur) there are an infinite number of initial states which converge to a specific final state. This is the nature of diffusion (think of it as: as long as the total initial energy is the same, the final state of a diffusion process is “homogeneous density of energy”). So inferring an “initial state” is totally invalid.
Edit: look at the 64 to 256 to 1024 example in the “Unconditional…” section and take a look at the artifact on the bottom left (to the viewer) teeth and lip. If that is not an artifact… Same on the top-right teeth.
Also: how does the algorithm know it is facial hair and not just makeup? It might be both but it generates facial hair.
I'm curious to know if the various blemishes (acne scars, moles, etc...) are there in the true images. Also, the braids in one of the pictures don't look as simple/contiguous as I think real braids would be.
Still, it's very cool how it fills in realistic looking details.
Thanks, what I am asking for is a visualization on the pixel level which shows the difference between the reference image, and the associated super-resolution image, as is often used to highlight the minimal differences in adversarial examples that confuse image classifiers. For example, see:
The company Aclima (https://www.aclima.io/) has a commercial business in which they pay drivers to drive around and collect air quality data, including methane concentration. Originally they co-located the sensors on the Google StreetMap vehicles, but now they run their own fleet. I don't think they've made it out to rural Alabama quite yet, though. . .
However, early prototype IVAS systems were simply not rugged enough for operational use, with one iteration notably unable to work in the rain. The Army has conducted more rigorous testing of the latest version, with what it had indicated were positive results. Soldiers have also experimented with using IVAS headsets within vehicles and during airmobile operations.
Questions have also been raised about the conformal batteries that soldiers need to carry in their gear to power the IVAS headsets, both in regard to how long they can keep the systems running and safety concerns about what might happen if they get shot or otherwise damaged in combat. The Army has said in the past that it has made progress on improving the capabilities of the batteries and their resistance to incoming fire.
Russia and China have already moved to prohibit access to these LEO internet services, or try to compel the providers to bring down all data that originates in their country to in-country servers for review and control. They are also developing their own constellations in order to provide a service which they can control.
