There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

With digital equipment becoming increasingly networked, either on wired or wireless networks, for personal and professional use alike, distributed software systems have become a crucial element in information and communications technologies. The study of these systems forms the core of the ARLES' work, which is specifically concerned with defining new system software architectures, based on the use of emerging networking technologies. In this context, we concentrate on the study of distributed systems which bring to life the vision of ubiquitous computing systems, also known as ambient intelligence.

반도체 공정 overview

Background: About a third of home-dwelling older people fall each year, and institutionalized older people even report a two- or threefold higher rate for falling

Sensitivity and false alarm rate of a fall sensor in long-term fall detection in the elderly

Mobile devices are becoming increasingly sophisticated and the latest generation of smart cell phones now incorporates many diverse and powerful sensors These sensors include GPS sensors, vision sensors (ie, cameras), audio sensors (ie, microphones), light sensors, temperature sensors, direction sensors (ie, magnetic compasses), and acceleration sensors (ie, accelerometers) The availability of these sensors in mass-marketed communication devices creates exciting new opportunities for data mining and data mining applications In this paper we describe and evaluate a system that uses phone-based accelerometers to perform activity recognition, a task which involves identifying the physical activity a user is performing To implement our system we collected labeled accelerometer data from twenty-nine users as they performed daily activities such as walking, jogging, climbing stairs, sitting, and standing, and then aggregated this time series data into examples that summarize the user activity over 10- second intervals We then used the resulting training data to induce a predictive model for activity recognition This work is significant because the activity recognition model permits us to gain useful knowledge about the habits of millions of users passively---just by having them carry cell phones in their pockets Our work has a wide range of applications, including automatic customization of the mobile device's behavior based upon a user's activity (eg, sending calls directly to voicemail if a user is jogging) and generating a daily/weekly activity profile to determine if a user (perhaps an obese child) is performing a healthy amount of exercise

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Activity recognition using cell phone accelerometers

The conducting polymer poly(ethylene dioxythiopene) (PEDOT) has been investigated as a coating for visual prosthesis electrode arrays. The prototype electrode array was coated with PEDOT doped with two conventional anions: paratoluene sulfonate (pTS) and lithium perchlorate (LiClO4). PEDOT variants were analyzed for charge injection limit, electrochemical stability following continuous biphasic stimulation, accelerated ageing and steam sterilization conditions. It was found that PEDOT/LiClO4 was the most stable conducting polymer under chronic stimulation and high temperature circumstances. However, PEDOT/pTS exhibited acceptable stability in comparison to conventional platinum.

Electrochemical stability of poly(ethylene dioxythiophene) electrodes

For pt.I see ibid., p.Z004024-7. For pt.II see ibid., p.Z004558-61. This paper examines the rendering of luminous spots ("phosphenes") in the visual field, and their stochastic positioning as a means of anti-aliasing the resulting spotty image ("phosphene image"). We derive an equation concerning the correlations of pairs of phosphenes comprising the phosphene image, and show the relationship to the statistics governing the stochastic positioning. We present some examples where stochastic rendering assists the veridical perception of textures, and argue for its superiority as cf. ordered rendering. Our preliminary results suggest that it may be perceptually effective to manufacture disordered arrays of stimulating electrodes for intraocular implantation.

Psychophysics of prosthetic vision: III. stochastic rendering, the phosphene image, and perception.

A finite element model of epiretinal stimulation is presented, consisting of a continuum description of active retinal tissue in contact with bulk vitreous fluid. Simulations were undertaken to investigate the effect of mesh element size in the finite element model on threshold current. The threshold current varied by approximately 0.6% when the maximum mesh element size was changed from 125 to 225 mum. Threshold currents for activation of retinal ganglion cells were determined for electrodes placed at different heights above the retinal surface. These results compared favorably with published experimental data on transretinal electrical stimulation of mammalian retina in an isolated preparation. Model threshold values were some 2-5 times higher than that of the experimental values.

Finite Element Bidomain Model of Epiretinal Stimulation

Discovering information encoded in non-invasively recorded biosignals which belies an individual's well-being can help facilitate the development of low-cost unobtrusive medical device technologies, or enable the unsupervised performance of physiological assessments without excessive oversight from trained clinical personnel. Although the unobtrusive or unsupervised nature of such technologies often results in less accurate measures than their invasive or supervised counterparts, this disadvantage is typically outweighed by the ability to monitor larger populations than ever before. The expected consequential benefit will be an improvement in healthcare provision and health outcomes for all. The process of discovering indicators of health in unsupervised or unobtrusive biosignal recordings, or automatically ensuring the validity and quality of such signals, is best realized when following a proven systematic methodology. This paper provides a brief tutorial review of supervised learning, which is a sub-discipline of machine learning, and discusses its application in the development of algorithms to interpret biosignals acquired in unsupervised or semi-supervised environments, with the aim of estimating well-being. Some specific examples in the disparate application areas of telehealth electrocardiogram recording and calculating post-operative systemic vascular resistance are discussed in the context of this systematic approach for information discovery.

Applications of supervised learning to biological signals: ECG signal quality and systemic vascular resistance

Stimulation of the diseased retina via an intraoc- ular electrode array is a proposed means of restoring some vision to the profoundly blind. A prosthetic device to this end would involve post-implantation calibration (analogous to cochlear implant fitting), wherein the subject indicates those discrete positions in the visual field where luminous percepts are elicited. This procedure would be a source of noise, because the indicated positions would only approximate the actual positions in the visual field. Put differently, the procedure introduces sampling jitter, and would therefore affect clinical outcomes such as mobility and reading speeds. The nature of this noise is the concern of the present paper; we derive an expression for the noise power spectrum as it relates to the statistical nature of the sampling jitter. We show that, generally, jitter has greater effect on higher spatial-frequencies, that is, those areas of the implantee's visual perception that represent fine detail are more prone to noise. More specifically, the noise spectrum depends on the characteristic function of the random variable describing the sampling jitter. Our results signal the need for experimental work that characterizes sampling jitter in implantees, plus the need for simulations that allow a better understanding of perception and the noisy phosphene image.

/pdf/psychophysics-of-prosthetic-vision-ii-stochastic-sampling-35fi7tl2u0.pdf

Nigel H. Lovell

Papers

Electrochemical stability of poly(ethylene dioxythiophene) electrodes

Psychophysics of prosthetic vision: III. stochastic rendering, the phosphene image, and perception.

Finite Element Bidomain Model of Epiretinal Stimulation

Applications of supervised learning to biological signals: ECG signal quality and systemic vascular resistance

Psychophysics of prosthetic vision: II. stochastic sampling, the phosphene image, and noise.