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

Neurodevelopmental and neurodegenerative disorders (NNDs) are a group of conditions with a broad range of core and co-morbidities, associated with dysfunction of the central nervous system. Improvements in high throughput sequencing have led to the detection of putative risk genetic loci for NNDs, however, quantitative neurogenetic approaches need to be further developed in order to establish causality and underlying molecular genetic mechanisms of pathogenesis. Here, we discuss an approach for prioritizing the contribution of genetic risk loci to complex-NND pathogenesis by estimating the possible impacts of these loci on gene regulation. Furthermore, we highlight the use of a tissue-specificity gene expression index and the application of artificial intelligence (AI) to improve the interpretation of the role of genetic risk elements in NND pathogenesis. Given that NND symptoms are associated with brain dysfunction, risk loci with direct, causative actions would comprise genes with essential functions in neural cells that are highly expressed in the brain. Indeed, NND risk genes implicated in brain dysfunction are disproportionately enriched in the brain compared with other tissues, which we refer to as brain-specific expressed genes. In addition, the tissue-specificity gene expression index can be used as a handle to identify non-brain contexts that are involved in NND pathogenesis. Lastly, we discuss how using an AI approach provides the opportunity to integrate the biological impacts of risk loci to identify those putative combinations of causative relationships through which genetic factors contribute to NND pathogenesis.

Quantitative neurogenetics: applications in understanding disease.

A circuit capable of delivering stimuli to the surface of the retina by means of radio frequency (RF) data and power delivery thereby eliminating the need for wires or other invasive methods of transmission is described. The implanted circuit decodes transmitted data and sends a specific, charge balanced, biphasic, constant current stimulus to any one of 100 stimulating electrode sites placed upon the surface of the retina. Following the delivery of a given stimulus sequence, data which facilitates the determination of the retinal tissue impedance is transmitted to the external electronics via a telemetry facility.

A 100 channel neural stimulator for excitation of retinal ganglion cells

With an ever increasing number of biological models available on the internet, a standardized modeling framework is required to allow information to be accessed or visualized. Based on the Physiome Modeling Framework, the Field Markup Language (FML) is being developed to describe and exchange field information for biological models. In this paper, we describe the basic features of FML, its supporting application framework and its ability to incorporate CellML models to construct tissue-scale biological models. As a typical application example, we present a spatially-heterogeneous cardiac pacemaker model which utilizes both FML and CellML to describe and solve the underlying equations of electrical activation and propagation.

Field Markup Language: Biological Field Representation in XML

A prototype of an epi-retinal vision prosthesis based upon an efficient electrode addressing schema has been developed. This system has the ability to stimulate multiple electrode regions simultaneously, hence greatly improving the maximum rate of stimulation compared to many currently available neural stimulation devices based on serial stimulation protocols. To minimize the problem of cross talk between stimulating electrodes, a hexagon layout of electrodes was implemented. Basic tests were completed using a field programmable gate array logic system driving analogue circuitry to inject current into physiological saline via electrodes in hexagon arrangements and in a simple paired arrangement. The hexagon layout of electrodes was shown to clearly reduce the interaction between multiple current sources and hence cross talk

An FPGA-Based Vision Prosthesis Prototype: Implementing an Efficient Multiplexing Method for Addressing Electrodes

An implantable vision prosthesis has been developed to deliver externally controlled, charge balanced, constant current, biphasic electrical stimuli to the inner retina. The device is intended as a treatment to blindness. Specifically, degenerative disorders of the retina such as retinitis pigmentosa, macular degeneration, choroideremia, etc. would be treated with such a device. Many profoundly blind patients suffering from the aforementioned conditions are plagued with sleeping disorders associated with the loss of photic input. Restoration of light and dark perception may serve to restore circadian rhythm and thus this has been set as the initial goal for the device. In an effort to confirm the device's ability to provide light and dark perception an implantable electrode with a 3.9 mm/sup 2/ contact area was inserted into the posterior eye chamber of the Ovis aries (common name: sheep). Using this electrode, stimuli from the implant were applied to the inner retina and an ensemble averaged evoked potential was successfully recorded from the visual cortex using sub-dural electrodes. This resulted in an electrically induced visual evoked potential with peak amplitude of 140 /spl plusmn/ 20 /spl mu/V (N = 3) that was qualitatively similar to a visual evoked potential evinced using stroboscopic light stimuli.

http://www.researchgate.net/profile/Nigel_Lovell/publication/3958132_Physiological_response_in_Ovis_aries_resulting_from_electrical_stimuli_delivered_by_an_implantable_vision_prosthesis/links/54683fe30cf2f5eb18037413.pdf

Nigel H. Lovell

Papers

Quantitative neurogenetics: applications in understanding disease.

A 100 channel neural stimulator for excitation of retinal ganglion cells

Field Markup Language: Biological Field Representation in XML

An FPGA-Based Vision Prosthesis Prototype: Implementing an Efficient Multiplexing Method for Addressing Electrodes

Physiological response in Ovis aries resulting from electrical stimuli delivered by an implantable vision prosthesis