An automated patient monitoring using discrete‐time wireless sensor networks

In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature.     

Wind flow patterns about buildings

A knowledge of building wake characteristics is useful in a variety of applications including dispersion of pollutants downwind of conventional or nuclear power plants, airport runway interference effect, take-off/landing limitations at heliports, pedestrian wind comfort, and wind loads on structures. Recent investigations have advanced both understanding of physical flow processes occurring in the near and far wake regions and theoretical predictive capability for flow and diffusion in the far wake region. These studies have shown, for example, that separation cavities immediately downwind are not enclosed by free streamlines as in two-dimensional separation/reattachment, that organized vortices can play an important role in wake development, and that theoretical solutions for some wake regions are possible.     

Patients' awareness of stroke signs, symptoms, and risk factors

BACKGROUND AND PURPOSE: We sought to determine knowledge at the time of symptom onset regarding the signs, symptoms, and risk factors of stroke in patients presenting to the emergency department with potential stroke. METHODS: Patients admitted from the emergency department with possible stroke were identified prospectively. A standardized, structured interview with open-ended questions was performed within 48 hours of symptom onset to assess patients' knowledge base concerning stroke signs, symptoms, and risk factors. RESULTS: Of the 174 eligible patients, 163 patients were able to respond to the interview questions. Of these 163 patients, 39% (63) did not know a single sign or symptom of stroke. Unilateral weakness (26%) and numbness (22%) were the most frequently noted symptoms. Patients aged > or = 65 years were less likely to know a sign or symptom of stroke than those aged < 65 years (percentage not knowing a single sign or symptom, 47% versus 28%, P = .016). Similarly, 43% of patients did not know a single risk factor for stroke. The elderly were less likely to know a risk factor than their younger counterparts. CONCLUSIONS: Almost 40% of patients admitted with a possible stroke did not know the signs, symptoms, or risk factor of a stroke. Further public education is needed to increase awareness of the warning signs and risk factors of stroke.     

Polymer-Based Ion Trap Chemical Sensor

Ion traps are widely used in chemical analysis, and they are especially important in current attempts to miniaturize mass spectrometers to create portable instruments. The ultimate aim is to build a handheld device that would require a smaller mass analyzer. To accomplish this task, a robust precision fabrication procedure is desired. In this paper, the authors report a new approach to fabricating ion traps using stereolithography apparatus (SLA), which provides precision monolithic fabrication. An SLA-fabricated rectilinear ion trap, which employs a very simple electrode geometry, is shown to provide detection capabilities within a useful mass range encompassing that of interest in the detection of numerous volatile organic compounds, including those relevant to homeland security applications. Single small ion traps and integrated trap arrays can be made through this approach, which allows higher operating pressures and reduced power requirements     

Space and time efficient parallel algorithms and software for EST clustering

Expressed sequence tags, abbreviated as ESTs, are DNA molecules experimentally derived from expressed portions of genes. Clustering of ESTs is essential for gene recognition and for understanding important genetic variations such as those resulting in diseases. We present the algorithmic foundations and implementation of PaCE, a parallel software system we developed for large-scale EST clustering. The novel features of our approach include 1) design of space-efficient algorithms to limit the space required to linear in the size of the input data set, 2) a combination of algorithmic techniques to reduce the total work without sacrificing the quality of EST clustering, and 3) use of parallel processing to reduce runtime and facilitate clustering of large data sets. Using a combination of these techniques, we report the clustering of 327,632 rat ESTs in 47 minutes, and 420,694 Triticum aestivum ESTs in 3 hours and 15 minutes, using a 60-processor IBM xSeries cluster. These problems are well beyond the capabilities of state-of-the-art sequential software. We also present thorough experimental evaluation of our software including quality assessment using benchmark Arabidopsis EST data.     

沉默的文化——妇女的住房和土地权利

我们即将对第四届妇女大会（北京）召开十年以来的妇女发展状况进行回顾，并且要对千年发展目标的执行情况进行中期评估。因此，我们有必要对那些影响妇女日常生活的关键问题进行审视并采取相应的行动，这些问题一直被各国政府和国际社会所忽视。     

Autocalibration of multiprojector CAVE-like immersive environments

In this paper, we present the first method for the geometric autocalibration of multiple projectors on a set of CAVE-like immersive display surfaces including truncated domes and 4 or 5-wall CAVEs (three side walls, floor, and/or ceiling). All such surfaces can be categorized as swept surfaces and multiple projectors can be registered on them using a single uncalibrated camera without using any physical markers on the surface. Our method can also handle nonlinear distortion in the projectors, common in compact setups where a short throw lens is mounted on each projector. Further, when the whole swept surface is not visible from a single camera view, we can register the projectors using multiple pan and tilted views of the same camera. Thus, our method scales well with different size and resolution of the display. Since we recover the 3D shape of the display, we can achieve registration that is correct from any arbitrary viewpoint appropriate for head-tracked single-user virtual reality systems. We can also achieve wallpapered registration, more appropriate for multiuser collaborative explorations. Though much more immersive than common surfaces like planes and cylinders, general swept surfaces are used today only for niche display environments. Even the more popular 4 or 5-wall CAVE is treated as a piecewise planar surface for calibration purposes and hence projectors are not allowed to be overlapped across the corners. Our method opens up the possibility of using such swept surfaces to create more immersive VR systems without compromising the simplicity of having a completely automatic calibration technique. Such calibration allows completely arbitrary positioning of the projectors in a 5-wall CAVE, without respecting the corners.     

Entanglement mean field theory: Lipkin–Meshkov–Glick Model

Entanglement mean field theory is an approximate method for dealing with many-body systems, especially for the prediction of the onset of phase transitions. While previous studies have concentrated mainly on applications of the theory on short-range interaction models, we show here that it can be efficiently applied also to systems with long-range interaction Hamiltonians. We consider the (quantum) Lipkin–Meshkov–Glick spin model, and derive the entanglement mean field theory reduced Hamiltonian. A similar recipe can be applied to obtain entanglement mean field theory reduced Hamiltonians corresponding to other long-range interaction systems. We show, in particular, that the zero temperature quantum phase transition present in the Lipkin–Meshkov–Glick model can be accurately predicted by the theory.