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BackgroundCurrently, intensive lipid lowering is recommended in patients with atherosclerotic ischemic stroke or transient ischemic attack. However, the role of statin in cardioembolic stroke is unclear. We investigated the association of statin with pretreatment collateral status in cardioembolic stroke.MethodsA collaborative study from two stroke centers in distinct geographic regions included consecutive patients with acute middle cerebral artery (MCA) infarction due to atrial fibrillation (AF) who underwent cerebral angiography. The relationship between pretreatment collateral grade and the use/dose of statin at stroke onset was assessed. The angiographic collateral grade was evaluated according to the ASITN/SIR Collateral Flow Grading System.ResultsNinety-eight patients (76 statin-naïve, 22 statin users) were included. Compared with statin-naïve patients, statin users were older and more frequently had hypertension, hyperlipidemia and coronary heart disease. Excellent collaterals (grade 3-4) were more frequently observed in statin users (11 patients, 50%) than in statin-naïve patients (21 patients, 27.6%; p = 0.049). The use of atorvastatin 10 mg equivalent or higher doses of statin was associated with excellent collaterals (p for trend = 0.025). In multiple regression analysis, prestroke statin use was independently associated with excellent collaterals (odds ratio, 7.841; 95% confidence interval, CI, 1.96-31.363; p = 0.004).ConclusionsPremorbid use of statin in AF patients is associated with excellent collateral flow. Although most statin trials excluded patients with cardioembolic stroke, our data suggests the possibility that statin may be beneficial in AF-related stroke

In the HVAC system energy simulation, indoor thermal comfort condition is typically calculated based on the assumption that the clothing insulation is equal to a constant value of 0.5 clo during the cooling season and 1.0 clo during heating season. In reality, occupants frequently adjust their clothing depending on the thermal conditions, as opposed to the assumption of constant clothing insulation, indicating that the clothing variation should be captured during the building simulation to realistically model HVAC systems. In this study, the impact of the two newly developed predictive clothing insulation models on the HVAC system operation and energy consumption is quantitatively assessed using the detailed whole-building energy simulation program, EnergyPlus. The first model varies the clothing insulation as a function of outdoor air temperature measured at 6 am and the second model takes into account both 6 am outdoor air temperature and indoor operative temperature when adjusting the clothing insulation. The results of the typical assumption of the constant clothing insulation values were compared to those of the two predictive clothing models. It turned out that more accurate prediction of variations in clothing lead to an increase in the heating energy consumption. This is due to the fact that occupants took less clothing compared to the typical assumption of constant clothing value of 1.0 during the heating season.

In building energy simulation, indoor thermal comfort condition, energy use and equipment size are typically calculated based on the assumption that the clothing insulation is equal to a constant value of 0.5 clo during the cooling season and 1.0 clo during heating season. The assumption is not reflected in practice and thus it may lead to errors. In reality, occupants frequently adjust their clothing depending on the thermal conditions, as opposed to the assumption of constant clothing values above, indicating that the clothing insulation variation should be captured in building simulation software to obtain more reliable and accurate results. In this study, the impact of three newly developed dynamic clothing insulation models on the building simulation is quantitatively assessed using the detailed whole-building energy simulation program, EnergyPlus version 6.0. The results showed that when the HVAC is controlled based on indoor temperature the dynamic clothing models do not affect indoor operative temperatures, energy consumption and equipment sizing. When the HVAC is controlled based on the PMV model the use of a fixed clothing insulation during the cooling (0.5 clo) and heating (1.0 clo) season leads to the incorrect estimation of the indoor operative temperatures, energy consumption and equipment sizing. The dynamic clothing models significantly (p

Clothing affects people’s perception of the thermal environment. In this research two predictive models of clothing insulation have been developed based on 6,333 selected observations taken from ASHRAE RP-884 and RP-921 databases. The database has been used to statistically analyze the influence of 20 variables on clothing insulation. The results show that the median clothing insulation is 0.59 clo (0.50 clo (n=2,760) in summer and 0.66 clo (n=3,580) in winter). Clothing insulation is correlated with outdoor air temperature (r=0.45), operative temperature (r=0.3), relative humidity (r=0.26), air velocity (r=0.14) and metabolic activity (r=0.12). Two mixed regression models were developed. In the first one clothing insulation is a function of outdoor air temperature measured at 6 o’clock in the morning and in the second one the influence of indoor operative temperature is also taken into account. The models were able to predict only 19 and 22% of the total variance, respectively. These low predicting powers are better than the assumption of constant clothing insulation for the heating (1 clo) and cooling (0.5 clo) seasons.

This report documents the UFAD module specifications for EnergyPlus v3.1 and higher. We have conducted extensive validation of the interior zone model for Price swirl and York MIT1 variable area (VA) diffusers. These correlations should not be considered to be applicable to other diffuser types. (See below for user procedures to support other diffuser brands and types.)

Clothing affects people’s perception of the thermal environment. Two dynamic predictive models of clothing insulation were developed based on 6,333 selected observations of the 23,475 available in ASHRAE RP-884 and RP-921 databases. The observations were used to statistically analyze the influence of 20 variables on clothing insulation. The results show that the median clothing insulation is 0.59 clo (0.50 clo (n=3,384) in summer and 0.69 clo (n=2,949) in winter). The median winter clothing insulation value is significantly smaller than the value suggested in the international standards (1.0 clo). The California data (n= 2,950) shows that occupants dress equally in naturally and mechanically conditioned buildings and all the data has female and male dressing with quite similar clothing insulation levels. Clothing insulation is correlated with outdoor air (r = 0.45) and indoor operative (r=0.3) temperatures, and relative humidity (r=0.26) An index to predict the presence of a dress code is developed. Two multivariable linear mixed models were developed. In the first one clothing is a function of outdoor air temperature measured at 6 o’clock, and the second one adds the influence of indoor operative temperature. The models were able to predict 19 and 22% of the total variance, respectively. Climate variables explain only a small part of human clothing behavior; nonetheless, the predictive models allow more precise thermal comfort calculation, energy simulation, HVAC sizing and building operation than previous practice of keeping the clothing insulation values equal to 0.5 in the cooling season and 1 in the heating season.

Underfloor air distribution (UFAD) is a mechanical ventilation strategy in which the conditioned air is primarily delivered to the zone from a pressurized plenum through floor mounted diffusers. Compared to conventional overhead (OH) mixing systems, UFAD has several potential advantages, such as improved thermal comfort and indoor air quality (IAQ), layout flexibility, reduced life cycle costs and improved energy efficiency in suitable climates. In ducted OH systems designers have reasonably accurate control of the diffuser supply temperature, while in UFAD this temperature is difficult to predict due to the heat gain of the conditioned air in the supply plenum. The increase in temperature between the air entering the plenum and air leaving through a diffuser is known as thermal decay. In this study, the detailed whole-building energy simulation program, EnergyPlus, was used to explain the fundamentals of thermal decay, to investigate its influence on energy consumption and to study the parameters that affect thermal decay. It turns out that the temperature rise is considerable (annual median=3.7 K, with 50% of the values between 2.4 and 4.7 K based on annual simulations). Compared to an idealized simulated UFAD case with no thermal decay, elevated diffuser air temperatures can lead to higher supply airflow rate and increased fan and chiller energy consumption. The thermal decay in summer is higher than in winter and it also depends on the climate. The ground floor with a slab on grade has less temperature rise compared to middle and top floors. An increase of the supply air temperature causes a decrease in thermal decay. The temperature rise is not significantly affected by the perimeter zone orientation, the internal heat gain and the window-to-wall ratio.

In this paper, an EnergyPlus simulation model was used to simulate the operation of a novel integrated HVAC system. This system combines an underfloor air distribution system with a cooled radiant ceiling slab. A cooling tower supplies water to pre-cool the structural slabs during the night and early morning period. The paper compares the performance of this system to both an overhead system and an underfloor air distribution system in the cooling season for the Sacramento, California climate. The UFAD/Radiant hybrid system shows an energy reduction of between 21-25% during the peak cooling months, an electricity demand reduction of 27% during the peak hour, and improved occupant thermal comfort.

Underfloor air distribution system (UFAD) is a mechanical air distribution strategy in which the conditioned air is primarily delivered to the zone from a pressurized plenum through floor-mounted diffusers. It has several potential advantages compared to conventional overhead (OH) mixing systems. However, most of the energy simulation programs widely used by the industry are not able to represent two distinct features of UFAD systems: room air stratification and the underfloor supply plenum. The situation has been improved with the development of a UFAD module in EnergyPlus. The Center for the Built Environment developed the modeling methods, tested them extensively, and conducted numerous studies of UFAD energy performance. This paper summarizes lessons learned related to UFAD specific issues such as thermal decay, sizing, terminal units, room air stratification and thermal comfort.

The overall goal of this project is to develop ways that UFAD systems can be successfully simulated in California climates with DOE-2 programs that have no explicit UFAD models. These new methods should improve upon the current “work around” solutions offered in Title-24 alternative calculation methods (ACM) manuals in 2005 and 2008 standards [ACM 2005, 2008][CEC 2008] and other ad hoc methods used by designers.

BackgroundIt has recently been suggested that diffusion and perfusion MRI can identify subgroups likely to benefit or potentially be harmed by reperfusion therapies.Case reportWe investigated serial MRI data of two patients with occlusion of the proximal middle cerebral artery (MCA). In both cases, acute multiple cortical infarcts evident on diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) showed extensive areas of severe perfusion delays, indicating a malignant MRI profile. However, despite the malignant MRI profiles in these cases, no new ischemic lesions or hemorrhage evolved even in the presence of persistent arterial occlusion, and the patients recovered without sequelae.ConclusionsThese two cases suggest that time-domain PWI findings should be interpreted with caution in certain scenarios of acute ischemic stroke.

Complex buildings such as laboratories, data centers and cleanrooms present particular challenges for energy benchmarking because it is difficult to normalize special requirements such as health and safety in laboratories and reliability (i.e. system redundancy to maintain uptime) in data centers which significantly impact energy use. For example, air change requirements vary widely based on the type of work being performed in each laboratory space.We present methods and tools for energy benchmarking in laboratories, as an exemplar of a complex building type. First, we address whole building energy metrics and normalization parameters. We present empirical methods based on simple data filtering as well as multivariate regression analysis on the Labs21 database. The regression analysis showed lab type, lab-area ratio and occupancy hours to be significant variables. Yet the dataset did not allow analysis of factors such as plug loads and air change rates, both of which are critical to lab energy use. The simulation-based method uses an EnergyPlus model to generate a benchmark energy intensity normalized for a wider range of parameters. We suggest that both these methods have complementary strengths and limitations.Second, we present “action-oriented” benchmarking, which extends whole-building benchmarking by utilizing system-level features and metrics such as airflow W/cfm to quickly identify a list of potential efficiency actions which can then be used as the basis for a more detailed audit. While action-oriented benchmarking is not an “audit in a box” and is not intended to provide the same degree of accuracy afforded by an energy audit, we demonstrate how it can be used to focus and prioritize audit activity and track performance at the system level. We conclude with key principles that are more broadly applicable to other complex building types.

This paper summarizes the assumptions and equations behind a new spreadsheet-based cooling load design tool for underfloor air distribution (UFAD) systems developed by the Center for the Built Environment at University of California, Berkeley. After briefly reviewing previous UFAD design tools, we describe in detail how the design tool: a) transforms the zone design cooling load calculated for a standard overhead (OH) mixing system into the design cooling load for a stratified UFAD system, accounting for differences in design day cooling load profiles for OH and UFAD systems; b) splits the total UFAD cooling load into three fractions, supply plenum (SPF), zone, or room, (ZF), and return plenum (RPF); c) manages the thermal comfort in a vertically stratified environment; d) predicts the air temperature profiles and the setpoint temperature at the thermostat; eScholarship provides open access, scholarly publishing services to the University of California and delivers a dynamic research platform to scholars worldwide. e) models the air diffusers; f) predicts the design airflow rate; and g) models commonly used plenum configurations.

The installation of a raised floor system can change the thermal behaviour of the building by reducing the interaction between the heat gains and the thermally massive concrete slab. In this study, the influence of the raised floor on the summer design day zone cooling load profile is evaluated for an office building located in San Francisco by using the whole-building energy simulation program, EnergyPlus. The zone cooling load profiles and the thermal performance with and without the raised floor are compared and analyzed. The effects of structure type, windowto- wall ratio and the presence of carpet on the thermal behaviour of the raised floor are also investigated. The results show that the mere presence of the raised floor largely affects the zone cooling load profile and the peak cooling load over the range of -7% to + 40%. The most significant parameters are the zone orientation, i.e. the exposure to direct solar radiation, and the presence of floor carpeting. If carpeting is present, commonly used in U.S. office buildings, the overall impact on zone peak cooling load is reduced, ranging from 0 to 5% greater for the raised floor than without it. Without carpet the peak cooling load is 4% greater with raised floor than without it in the north zone, 22% in the east and west zones, and 12% in the south zone.

This paper presents a new spreadsheet-based cooling load design tool for underfloor air distribution (UFAD) systems developed by the Center for the Built Environment at University of California, Berkeley. After briefly reviewing previous UFAD design tools, the main characteristics of the tool are described: transformation of the zone design cooling load calculated for a standard overhead (OH) mixing system into the design cooling load for a stratified UFAD system, splits of the total UFAD cooling load into three fractions, supply plenum (SPF), zone, or room, (ZF), and return plenum (RPF); prediction of the thermal comfort in a vertically stratified environment, air temperature profiles and setpoint temperature at the thermostat; modeling of air diffusers; prediction of the design airflow rate; and modelling of commonly used plenum configurations. A practical example is reported at the end of the paper. The design tool and detailed user notes are available at: .

This paper describes the development of a simplified calculation method for design cooling loads in underfloor air distribution (UFAD) systems. The simplified design tool is able to account for key differences between UFAD and traditional mixing overhead (OH) systems. These include: (1) difference between design day cooling load profiles, (2) impact of a thermally stratified environment for UFAD vs. well-mixed for OH, and (3) impact of heat transfer (temperature gain) in underfloor air supply plenums. The new design tool allows the use of a familiar load calculation procedure for OH mixing systems as input to the UFAD design tool. Based on 87 EnergyPlus simulations, four regression models have been developed to transform the OH cooling load into the UFAD cooling load, and then to split this total load between the supply plenum, zone (room), and return plenum. The regression models mainly depend on floor level, and position (interior or perimeter) and orientation of the zone under analysis. Although considered in the analysis, supply air temperature, window-to-wall ratio, internal heat load, plenum configuration, climate, presence of the carpet and structure type do not strongly influence the developed models. The results show that, generally, UFAD has a peak cooling load 19% higher than an overhead cooling load and 22% and 37% of the total zone UFAD cooling load goes to the supply plenum in the perimeter and interior, respectively.