3G networks in emergency telemedicine - An in-depth evaluation & analysis

The evolution of telecommunications technologies in connection with the robustness and the fidelity these new systems provide, have opened up many new horizons as regards the provision of healthcare and the quality of service from the side of the experts to that of the patients. The purpose of this paper is to evaluate the third generation telecommunications systems that are only recently being deployed in Europe, as well as argue on why a transition from 2G and 2.5G to 3G telecommunications systems could prove to be crucial, especially in relation to emergency telemedicine. The experimental results of the use of these systems are analyzed, the implementation of a tele-consultation unit is presented and their exploitation capabilities are explored

Ambulance 3G

Minimising the time required for a patient to receive primary care has always been the concern of the Accidents and Emergency units. Ambulances are usually the first to arrive on the scene and to administer first aid. However, as the time that it takes to transfer the patient to the hospital increases, so does the fatality rate. In this paper, a mobile teleconsultation system is presented, based primarily on third generation mobile links and on Wi-Fi hotspots around a city. This system can be installed inside an ambulance and will permit high-resolution videoconferencing between the moving vehicle and a doctor or a consultant within a base station (usually a hospital). In addition to video and voice, high quality still images and screenshots from medical equipment can also be sent. The test was carried out in Athens, Greece where a 3G system was recently deployed by Vodafone. The results show that the system can perform satisfactory in most conditions and can effectively increase the patient’s quality of service, while having a modest cost

Wiring to the Sky

Exploring the application of Image-based Lighting to inform, actuate and evaluate responsive solar control and daylighting systems

Safe density ratio modeling

An important problem in logistic regression modeling is the existence of the maximum likelihood estimators. In particular, when the sample size is small, the maximum likelihood estimator of the regression parameters does not exist if the data are completely, or quasicompletely separated. Recognizing that this phenomenon has a serious impact on the fitting of the density ratio model–which is a semiparametric model whose profile empirical log-likelihood has the logistic form because of the equivalence between prospective and retrospective sampling–we suggest a linear programming methodology for examining whether the maximum likelihood estimators of the finite dimensional parameter vector of the model exist. It is shown that the methodology can be effectively utilized in the analysis of case–control gene expression data by identifying cases where the density ratio model cannot be applied. It is demonstrated that naive application of the density ratio model yields erroneous conclusions

Pilot study to examine the effects of indoor daylight exposure on depression and other neuropsychiatric symptoms in people living with dementia in long-term care communities

Kyle Konis,1 Wendy J Mack,2 Edward L Schneider3–5 1USC School of Architecture, 2Department of Preventive Medicine, Keck School of Medicine, 3Leonard Davis School of Gerontology, 4Department of Internal Medicine, Keck School of Medicine, 5Department of Biological Sciences, Dornsife College of Letters, Arts and Sciences, Los Angeles, CA, USA Abstract: A 12-week study was conducted in eight dementia care communities involving 77 participants addressing the hypothesis that an intervention of increasing indoor exposure to daylight will reduce depression and other neuropsychiatric symptoms. At four communities, staff were enlisted to increase daylight exposure by taking participants to a perimeter room with daylight exposure for socialization in the morning (8:00–10:00 AM) each day. At the other four communities, a control group were taken to a similar sized area without daylight for socialization under typical electrical lighting conditions. Participants in the daylight intervention experienced an average decrease over the trial in the Neuropsychiatric Inventory Nursing Home Version (NPI-NH) scores (p=0.33) and the Cornell Scale for Depression in Dementia (CSDD) scores (p=0.025), while the control participants showed average but nonsignificant increases in both NPI-NH (p=0.33) and CSDD (p=0.13). Difference in outcome changes of the intervention group achieved statistical significance for CSDD (p=0.01) but not for NPI-NH (p=0.17). Our results suggest that increased exposure to daylight can reduce depression in people living with dementia. Keywords: dementia, daylight, depression, memory care communitie

Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method

In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to ‘explain’ an observed set of alleles. The other procedure is probabilistic using Bayes’ theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N

Feasibility of Achieving a Zero-Net-Energy, Zero-Net-Cost Homes

A green building competition, to be known as the Energy Free Home Challenge (EFHC), is scheduled to be opened to teams around the world in 2010. This competition will encourage both design innovation and cost reduction, by requiring design entries to meet 'zero net energy' and 'zero net cost' criteria. For the purposes of this competition, a 'zero net energy' home produces at least as much energy as it purchases over the course of a year, regardless of the time and form of the energy (e.g., electricity, heat, or fuel) consumed or produced. A 'zero net cost' home is no more expensive than a traditional home of comparable size and comfort, when evaluated over the course of a 30-year mortgage. In other words, the 'green premium' must have a payback period less than 30 years, based on the value of energy saved. The overarching goal of the competition is to develop affordable, high-performance homes that can be mass-produced at a large scale, and are able to meet occupant needs in harsh climates (as can be found where the competition will be held in Illinois). This report outlines the goals of the competition, and gauges their feasibility using both modeling results and published data. To ensure that the established rules are challenging, yet reasonable, this report seeks to refine the competition goals after exploring their feasibility through case studies, cost projections, and energy modeling. The authors of this report conducted a survey of the most progressive home energy-efficiency practices expected to appear in competition design submittals. In Appendix A, a summary can be found of recent projects throughout the United States, Canada, Germany, Switzerland, Sweden and Japan, where some of the most progressive technologies have been implemented. As with past energy efficient home projects, EFHC competitors will incorporate a multitude of energy efficiency measures into their home designs. The authors believe that the cost of electricity generated by home generation technologies will continue to exceed the price of US grid electricity in almost all locations. Strategies to minimize whole-house energy demand generally involve some combination of the following measures: optimization of surface (area) to volume ratio; optimization of solar orientation; reduction of envelope loads; systems-based engineering of high efficiency HVAC components, and on-site power generation. A 'Base Case' home energy model was constructed, to enable the team to quantitatively evaluate the merits of various home energy efficiency measures. This Base Case home was designed to have an energy use profile typical of most newly constructed homes in the Champaign-Urbana, Illinois area, where the competition is scheduled to be held. The model was created with the EnergyGauge USA software package, a front-end for the DOE-2 building energy simulation tool; the home is a 2,000 square foot, two-story building with an unconditioned basement, gas heating, a gas hot-water heater, and a family of four. The model specifies the most significant details of a home that can impact its energy use, including location, insulation values, air leakage, heating/cooling systems, lighting, major appliances, hot water use, and other plug loads. EFHC contestants and judges should pay special attention to the Base Case model's defined 'service characteristics' of home amenities such as lighting and appliances. For example, a typical home refrigerator is assumed to have a built-in freezer, automatic (not manual) defrost, and an interior volume of 26 cubic feet. The Base Case home model is described in more detail in Section IV and Appendix B