Functional data analysis is typically conducted within the L²-Hilbert space framework. There is by now a fully developed statistical toolbox allowing for the principled application of the functional ...data machinery to real-world problems, often based on dimension reduction techniques such as functional principal component analysis. At the same time, there have recently been a number of publications that sidestep dimension reduction steps and focus on a fully functional L²-methodology. This paper goes one step further and develops data analysis methodology for functional time series in the space of all continuous functions. The work is motivated by the fact that objects with rather different shapes may still have a small L²-distance and are therefore identified as similar when using a L²-metric. However, in applications it is often desirable to use metrics reflecting the visualization of the curves in the statistical analysis. The methodological contributions are focused on developing two-sample and change-point tests as well as confidence bands, as these procedures appear to be conducive to the proposed setting. Particular interest is put on relevant differences; that is, on not trying to test for exact equality, but rather for prespecified deviations under the null hypothesis.
The procedures are justified through large-sample theory. To ensure practicability, nonstandard bootstrap procedures are developed and investigated addressing particular features that arise in the problem of testing relevant hypotheses. The finite sample properties are explored through a simulation study and an application to annual temperature profiles
...even if significant findings or clinical anecdotes support the use of racially tailored practices, they should be rigorously critiqued and mediating variables, such as structural conditions, ...should be analysed accordingly. ...it should be taught that racial health disparities are a consequence of structural racism. ...resolutions denouncing race-based medicine across clinical leadership should be adopted. ...clinical research should be used to examine structural barriers, rather than using race as a proxy for biology.
The concept of 'idiopathic' Parkinson's disease (PD) as a single entity has been challenged with the identification of several clinical subtypes, pathogenic genes and putative causative environmental ...agents. In addition to classic motor symptoms, non-motor manifestations (such as rapid eye movement sleep disorder, anosmia, constipation and depression) appear at prodromic/premotor stage and evolve, along with cognitive impairment and dysautonomia, as the disease progresses, often dominating the advanced stages of the disease. The key molecular pathogenic mechanisms include α-synuclein misfolding and aggregation, mitochondrial dysfunction, impairment of protein clearance (associated with deficient ubiquitin-proteasome and autophagy-lysosomal systems), neuroinflammation and oxidative stress. The involvement of dopaminergic as well as noradrenergic, glutamatergic, serotonergic and adenosine pathways provide insights into the rich and variable clinical phenomenology associated with PD and the possibility of alternative therapeutic approaches beyond traditional dopamine replacement therapies.One of the biggest challenges in the development of potential neuroprotective therapies has been the lack of reliable and sensitive biomarkers of progression. Immunotherapies such as the use of vaccination or monoclonal antibodies directed against aggregated, toxic α-synuclein.as well as anti-aggregation or protein clearance strategies are currently investigated in clinical trials. The application of glucagon-like peptide one receptor agonists, specific PD gene target agents (such as GBA or LRRK2 modifiers) and other potential disease modifying drugs provide cautious optimism that more effective therapies are on the horizon. Emerging therapies, such as new symptomatic drugs, innovative drug delivery systems and novel surgical interventions give hope to patients with PD about their future outcomes and prognosis.
The technology that develops has an impact on education causes changes in learning styles; learning can be done anywhere at anytime. This fact is one of the reasons that a learning model to integrate ...conventional learning and online learning is needed. This research aims to determine the effect of the application of the hybrid learning model on student learning outcomes in thermochemistry in the Basic Chemistry subject of the 2018/2019 academic year. The approach used in this study is a quantitative method using the quasi-experiment research type. The technique of data collection used was in the form of tests and the observation forms. Hypothesis test was using the t-test. Hypothesis results that Ha is accepted because the value of tcount > ttable is 2,130 > 2,036. Based on the results, it can be concluded that there is an influence of the hybrid learning model to the student outcomes in learning thermochemistry.
As anticipated in the title, this contribution is basically divided into two, strictly connected, parts. The first is a personal overview of the ruthenium drug candidate NAMI‐A, almost 30 years after ...its synthesis and the discovery of its unprecedented antimetastatic properties in animal models at nontoxic dosages. The sections relating to the chemical and biological behavior of the complex, and the hypotheses on its mechanism(s) of action, are kept to a minimum, whereas more space is devoted to discussion of the results of the clinical investigations. The second part deals in detail with a number of undemonstrated misconceptions (or myths) that, over the years, have thrived around NAMI‐A and other ruthenium drug candidates, thus negatively affecting the whole field of Ru anticancer drugs.
Almost 30 years after the discovery of NAMI‐A, and after two clinical phase studies have been accomplished, the time seems to be appropriate for drawing up a balance sheet. The undemonstrated misconceptions (or myths) that, over the years, have thrived around NAMI‐A and other ruthenium drug candidates are also critically addressed in detail.
The Novel Weapons Hypothesis postulates that the release of allelochemicals by alien plants can inhibit the growth of evolutionary naïve native plants. On the other hand, when species share a recent ...evolutionary history, recognition of phytochemicals from neighboring plants can have adaptive value by providing cues to signal suitable conditions conducive to establishment. This has been termed the Biochemical Recognition Hypothesis. We explored these two hypotheses by conducting germination experiments in South Africa and Spain and a growth experiment in South Africa, using invasive Australian acacias and native species from each region. The experiments exposed seeds of the selected recipient species to leachates collected under acacias, nearby uninvaded vegetation, or distilled water. We then measured total germination, and above and below ground biomass in the growth experiment. Our results did not support the Novel Weapons Hypothesis, but instead we found some leachates collected under acacias and uninvaded areas to stimulate the germination and early growth of some of our selected acacias and native species. Such effects occurred both at the intra- and interspecific level. In general, interspecific stimulatory effects between invasive acacias occurred irrespective of whether they had overlapping native ranges in Australia. We also found leachates from uninvaded areas in South Africa to have stimulatory effects on one invasive acacia and one native species. Hence, our results support the Biochemical Recognition Hypothesis, suggesting that chemically-induced signals may facilitate acacia establishment in sites that have already been transformed by acacias.
Do Better ImageNet Models Transfer Better? Kornblith, Simon; Shlens, Jonathon; Le, Quoc V.
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),
2019-June
Conference Proceeding
Open access
Transfer learning is a cornerstone of computer vision, yet little work has been done to evaluate the relationship between architecture and transfer. An implicit hypothesis in modern computer vision ...research is that models that perform better on ImageNet necessarily perform better on other vision tasks. However, this hypothesis has never been systematically tested. Here, we compare the performance of 16 classification networks on 12 image classification datasets. We find that, when networks are used as fixed feature extractors or fine-tuned, there is a strong correlation between ImageNet accuracy and transfer accuracy (r = 0.99 and 0.96, respectively). In the former setting, we find that this relationship is very sensitive to the way in which networks are trained on ImageNet; many common forms of regularization slightly improve ImageNet accuracy but yield features that are much worse for transfer learning. Additionally, we find that, on two small fine-grained image classification datasets, pretraining on ImageNet provides minimal benefits, indicating the learned features from ImageNet do not transfer well to fine-grained tasks. Together, our results show that ImageNet architectures generalize well across datasets, but ImageNet features are less general than previously suggested.
Abstract
Diabetic retinopathy (DR) is a well-recognized microvascular complication of diabetes. Growing evidence suggests that, in addition to retinal vascular damage, there is significant damage to ...retinal neural tissue in DR. Studies reveal neuronal damage before clinically evident vascular lesions and DR is now classified as a neurovascular complication. Hyperglycemia causes retinal damage through complex metabolic pathways leading to oxidative stress, inflammation, vascular damage, capillary ischemia, and retinal tissue hypoxia. Retinal hypoxia is further worsened by high oxygen consumption in the rods. Persistent hypoxia results in increases in vascular endothelial growth factor (VEGF) and other pro-angiogenic factors leading to proliferative DR/macular edema and progressive visual impairment. Optimal glucose control has favorable effects in DR. Other treatments for DR include laser photocoagulation, which improves retinal oxygenation by destroying the high oxygen consuming rods and their replacement by low oxygen consuming glial tissue. Hypoxia is a potent stimulator of VEGF, and intravitreal anti-VEGF antibodies are effective in regressing macular edema and in some studies, retinal neovascularization. In this review, we highlight the complex pathophysiology of DR with a focus on retinal oxygen/fuel consumption and hypoxic damage to retinal neurons. We discuss potential mechanisms through which sodium-glucose cotransporter 2 (SGLT2) inhibitors improve retinal hypoxia—through ketone bodies, which are energetically as efficient as glucose and yield more ATP per molecule of oxygen consumed than fat, with less oxidative stress. Retinal benefits would occur through improved fuel energetics, less hypoxia and through the anti-inflammatory/oxidative stress effects of ketone bodies. Well-designed studies are needed to explore this hypothesis.
Alzheimer’s disease (AD) is a neurodegenerative disease with high morbidity and mortality, for which there is no available cure. Currently, it is generally believed that AD is a disease caused by ...multiple factors, such as amyloid-beta accumulation, tau protein hyperphosphorylation, oxidative stress, and inflammation. Multitarget prevention and treatment strategies for AD are recommended. Interestingly, naturally occurring dietary flavonoids, a class of polyphenols, have been reported to have multiple biological activities and anti-AD effects in several AD models owing to their antioxidative, anti-inflammatory, and anti-amyloidogenic properties. In this review, we summarize and discuss the existing multiple pathogenic factors of AD. Moreover, we further elaborate on the biological activities of natural flavonoids and their potential mode of action and targets in managing AD by presenting a wide range of experimental evidence. The gathered data indicate that flavonoids can be regarded as prophylactics to slow the advancement of AD or avert its onset. Different flavonoids have different activities and varying levels of activity. Further, this review summarizes the structure–activity relationship of flavonoids based on the existing literature and can provide guidance on the design and selection of flavonoids as anti-AD drugs.
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