Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) that can deliver a high information transfer rate (ITR) usually require subject’s calibration data to learn the class- and subject-specific model parameters (e.g. the spatial filters and SSVEP templates). Normally, the amount of the calibration data for learning is proportional to the number of classes (or visual stimuli), which could be huge and consequently lead to a time-consuming calibration. This study presents a transfer learning scheme to substantially reduce the calibration effort.

Inspired by the parameter-based and instance-based transfer learning techniques, we propose a subject transfer based canonical correlation analysis (stCCA) method which utilizes the knowledge within subject and between subjects, thus requiring few calibration data from a new subject.

The evaluation study on two SSVEP datasets (from Tsinghua and UCSD) shows that the stCCA method performs well with only a small amount of calibration data, providing an ITR at 198.18±59.12 (bits/min) with 9 calibration trials in the Tsinghua dataset and 111.04±57.24 (bits/min) with 3 trials in the UCSD dataset. Such performances are comparable to those from using the multi-stimulus CCA (msCCA) and the ensemble task-related component analysis (eTRCA) methods with the minimally required calibration data (i.e., at least 40 trials in the Tsinghua dataset and at least 12 trials in the UCSD dataset), respectively.

Inter- and intra-subject transfer helps the recognition method achieve high ITR with extremely little calibration effort.

The proposed approach saves much calibration effort without sacrificing the ITR, which would be significant for practical SSVEP-based BCIs.

The proposed approach saves much calibration effort without sacrificing the ITR, which would be significant for practical SSVEP-based BCIs.We report on the solution of the heat equation, which describes the electrocaloric effect in a ferroelectric layer. The dependence of the heat flux at the layer interface and the thermodynamic efficiency on the shape and frequency of the applied pulse is investigated. BV-6 datasheet According to the calculations, the dependence of the efficiency on the frequency for a rectangular and sinusoidal pulse has a markedly different character. The maximum efficiency at 0.74 is achieved by a sinusoidal impulse at a frequency of 77.6 mHz. The new approach allows for better optimization of the cooling system. To model a heat switch, it is proposed to use a change in the Biot number over time. Theoretical calculations are compared with experimental results for a 0.5-mm-thick barium titanate plate. The maximum heat flux that can be created for a given plate under an electric field of 2 MV/m with an ideal heat switch turned out to be equal 120.72 W/m2.Unlike many other states across America that struggled to get enough diagnostic tests for coronavirus 2019 disease (COVID-19) this past spring, New Mexico was able to not only meet the demand for testing symptomatic patients, but was able to begin expanding its screening to asymptomatic individuals. How did this largely rural and relatively low-income state-among the bottom five states in population density [1] and median income per capita [2] -stay on top of testing when larger and wealthier states fell behind? The answer lies in both centralization and diversification.More than 30% of the world’s population is overweight or obese. That is double the percentage in 1980, and it is getting worse [1].That excess weight has been linked to numerous health conditions, notably type 2 (adult-onset) diabetes, the prevalence of which has also nearly doubled since 1980 [2]. Eating less and exercising more is good advice, but it doesn’t work for everyone. Other options such as gastric bypass surgeries and systemic weight-loss drugs are also not suitable for everyone, and can carry risks of their own.Wounds, especially chronic wounds, represent a significant clinical, social, and economic challenge. A recent retrospective analysis of Medicare beneficiaries in the United States identified that about 8.2 million people had at least one type of wound, with surgical wounds and diabetic ulcers among the most common and expensive to treat. The study also found that Medicare expenditures related to wound care are far greater than previously recognized; estimates for acute and chronic wound treatments ranged from US$28.1 billion to $96.8 billion [1].In March 2020, before COVID-19 laid claim to the United States, Vice President Mike Pence briefed the press about the coronavirus outbreak, which at the time was a threat to passengers aboard the Grand Princess cruise ship moored off the coast of California [1]. At the time, cases had spiked in Iran, Italy, and Spain, but the disease was still an abstraction to most Americans. When asked about a potential outbreak in Washington, D.C., Pence called on Dr. Anthony Fauci, director of the National Institute of Allergy and Infectious Disease, and a member of the U.S. Task Force, to address the question. Fauci replied that any individual who tested positive for the disease would undergo contact tracing, which he deemed “the public health weapon” for catching outbreaks before they start. Not long after, the World Health Organization declared a global pandemic, and the virus began spreading across the country.One of the most pernicious side effects of the COVID-19 pandemic is a steep rise in stress and mental health problems. According to a poll by the Kaiser Family Foundation, nearly half of American adults say that worry and stress about the pandemic is hurting their mental health [1]. There are plenty of factors feeding into this phenomenon. People are anxious about getting sick, grieving lost loved ones, and experiencing financial stress, parental stress, and loneliness. The pandemic places additional burdens on essential workers and people of color, both of whom are at greater risk of dying from the disease. COVID-19 itself has been linked to neurological problems as well as anxiety, depression, and sleep disorders [2].A motile, Gram-stain-negative, rod-shaped bacterium, designated G-4-1-14T, was obtained from forest soil sampled at Gwanggyo mountain, Gyeonggi-do, Republic of Korea. Cells were colourless, aerobic, grew optimally at 28-35 °C and hydrolysed DNA and casein. Phylogenetic analysis based on its 16S rRNA gene sequence revealed that strain G-4-1-14T formed a lineage within the genus Zoogloea. The closest members were Zoogloea resiniphila ATCC 70068T (98.6 % sequence similarity), Zoogloea caeni EMB43T (98.2 %), Zoogloea oryzae A-7T (97.7 %), Zoogloea ramigera IAM 12136T (96.9 %) and Zoogloea oleivorans BucT (96.2 %). The major respiratory quinone was ubiquinone-8 and the principal polar lipids were phosphatidylethanolamine, phosphatidyl-N-methylethanolamine, diphosphatidylglycerol and phosphatidylglycerol. The predominant cellular fatty acids were summed feature 3 (iso-C15 0 2-OH/C16   1ω7c) and C16  0. The DNA G+C content was 65.9 mol%. The average nucleotide identity and digital DNA-DNA hybridization relatedness values between strain G-4-1-14T and other type strains were ≤81.