214 resultados para temporal sampling


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Crop simulation models have the potential to assess the risk associated with the selection of a specific N fertilizer rate, by integrating the effects of soil-crop interactions on crop growth under different pedo-climatic and management conditions. The objective of this study was to simulate the environmental and economic impact (nitrate leaching and N2O emissions) of a spatially variable N fertilizer application in an irrigated maize field in Italy. The validated SALUS model was run with 5 nitrogen rates scenarios, 50, 100, 150, 200, and 250 kg N ha−1, with the latter being the N fertilization adopted by the farmer. The long-term (25 years) simulations were performed on two previously identified spatially and temporally stable zones, a high yielding and low yielding zone. The simulation results showed that N fertilizer rate can be reduced without affecting yield and net return. The marginal net return was on average higher for the high yield zone, with values ranging from 1550 to 2650 € ha−1 for the 200 N and 1485 to 2875 € ha−1 for the 250 N. N leaching varied between 16.4 and 19.3 kg N ha−1 for the 200 N and the 250 N in the high yield zone. In the low yield zone, the 250 N had a significantly higher N leaching. N2O emissions varied between 0.28 kg N2O ha−1 for the 50 kg N ha−1 rate to a maximum of 1.41 kg N2O ha−1 for the 250 kg N ha−1 rate.

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Recently, a stream of project management research has recognized the critical role of boundary objects in the organization of projects. In this paper, we investigate how one advanced scheduling tool, the Integrated Master Schedule (IMS), is used as a temporal boundary object at various stages of complex projects. The IMS is critical to megaprojects which typically span long periods of time and face a high degree of complexity and uncertainty. In this paper, we conceptualize projects of this type as complex adaptive systems (CAS). We report the findings of four case projects on how the IMS mapped interactions, interdependencies, constraints, and fractal patterns of these emerging projects, and how the process of IMS visualization enabled communication and negotiation of project realities. This paper highlights that this advanced timeline tool acts as a boundary object and elicits shared understanding of complex projects from their stakeholders.

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Background The onsite treatment of sewage and effluent disposal within the premises is widely prevalent in rural and urban fringe areas due to the general unavailability of reticulated wastewater collection systems. Despite the seemingly low technology of the systems, failure is common and in many cases leading to adverse public health and environmental consequences. Therefore it is important that careful consideration is given to the design and location of onsite sewage treatment systems. It requires an understanding of the factors that influence treatment performance. The use of subsurface effluent absorption systems is the most common form of effluent disposal for onsite sewage treatment and particularly for septic tanks. Additionally in the case of septic tanks, a subsurface disposal system is generally an integral component of the sewage treatment process. Therefore location specific factors will play a key role in this context. The project The primary aims of the research project are: • to relate treatment performance of onsite sewage treatment systems to soil conditions at site; • to identify important areas where there is currently a lack of relevant research knowledge and is in need of further investigation. These tasks were undertaken with the objective of facilitating the development of performance based planning and management strategies for onsite sewage treatment. The primary focus of the research project has been on septic tanks. Therefore by implication the investigation has been confined to subsurface soil absorption systems. The design and treatment processes taking place within the septic tank chamber itself did not form a part of the investigation. In the evaluation to be undertaken, the treatment performance of soil absorption systems will be related to the physico-chemical characteristics of the soil. Five broad categories of soil types have been considered for this purpose. The number of systems investigated was based on the proportionate area of urban development within the Brisbane region located on each soil types. In the initial phase of the investigation, though the majority of the systems evaluated were septic tanks, a small number of aerobic wastewater treatment systems (AWTS) were also included. This was primarily to compare the effluent quality of systems employing different generic treatment processes. It is important to note that the number of different types of systems investigated was relatively small. As such this does not permit a statistical analysis to be undertaken of the results obtained. This is an important issue considering the large number of parameters that can influence treatment performance and their wide variability. The report This report is the second in a series of three reports focussing on the performance evaluation of onsite treatment of sewage. The research project was initiated at the request of the Brisbane City Council. The work undertaken included site investigation and testing of sewage effluent and soil samples taken at distances of 1 and 3 m from the effluent disposal area. The project component discussed in the current report formed the basis for the more detailed investigation undertaken subsequently. The outcomes from the initial studies have been discussed, which enabled the identification of factors to be investigated further. Primarily, this report contains the results of the field monitoring program, the initial analysis undertaken and preliminary conclusions. Field study and outcomes Initially commencing with a list of 252 locations in 17 different suburbs, a total of 22 sites in 21 different locations were monitored. These sites were selected based on predetermined criteria. To obtain house owner agreement to participate in the monitoring study was not an easy task. Six of these sites had to be abandoned subsequently due to various reasons. The remaining sites included eight septic systems with subsurface effluent disposal and treating blackwater or combined black and greywater, two sites treating greywater only and six sites with AWTS. In addition to collecting effluent and soil samples from each site, a detailed field investigation including a series of house owner interviews were also undertaken. Significant observations were made during the field investigations. In addition to site specific observations, the general observations include the following: • Most house owners are unaware of the need for regular maintenance. Sludge removal has not been undertaken in any of the septic tanks monitored. Even in the case of aerated wastewater treatment systems, the regular inspections by the supplier is confined only to the treatment system and does not include the effluent disposal system. This is not a satisfactory situation as the investigations revealed. • In the case of separate greywater systems, only one site had a suitably functioning disposal arrangement. The general practice is to employ a garden hose to siphon the greywater for use in surface irrigation of the garden. • In most sites, the soil profile showed significant lateral percolation of effluent. As such, the flow of effluent to surface water bodies is a distinct possibility. • The need to investigate the subsurface condition to a depth greater than what is required for the standard percolation test was clearly evident. On occasion, seemingly permeable soil was found to have an underlying impermeable soil layer or vice versa. The important outcomes from the testing program include the following: • Though effluent treatment is influenced by the physico-chemical characteristics of the soil, it was not possible to distinguish between the treatment performance of different soil types. This leads to the hypothesis that effluent renovation is significantly influenced by the combination of various physico-chemical parameters rather than single parameters. This would make the processes involved strongly site specific. • Generally the improvement in effluent quality appears to take place only within the initial 1 m of travel and without any appreciable improvement thereafter. This relates only to the degree of improvement obtained and does not imply that this quality is satisfactory. This calls into question the value of adopting setback distances from sensitive water bodies. • Use of AWTS for sewage treatment may provide effluent of higher quality suitable for surface disposal. However on the whole, after a 1-3 m of travel through the subsurface, it was not possible to distinguish any significant differences in quality between those originating from septic tanks and AWTS. • In comparison with effluent quality from a conventional wastewater treatment plant, most systems were found to perform satisfactorily with regards to Total Nitrogen. The success rate was much lower in the case of faecal coliforms. However it is important to note that five of the systems exhibited problems with regards to effluent disposal, resulting in surface flow. This could lead to possible contamination of surface water courses. • The ratio of TDS to EC is about 0.42 whilst the optimum recommended value for use of treated effluent for irrigation should be about 0.64. This would mean a higher salt content in the effluent than what is advisable for use in irrigation. A consequence of this would be the accumulation of salts to a concentration harmful to crops or the landscape unless adequate leaching is present. These relatively high EC values are present even in the case of AWTS where surface irrigation of effluent is being undertaken. However it is important to note that this is not an artefact of the treatment process but rather an indication of the quality of the wastewater generated in the household. This clearly indicates the need for further research to evaluate the suitability of various soil types for the surface irrigation of effluent where the TDS/EC ratio is less than 0.64. • Effluent percolating through the subsurface absorption field may travel in the form of dilute pulses. As such the effluent will move through the soil profile forming fronts of elevated parameter levels. • The downward flow of effluent and leaching of the soil profile is evident in the case of podsolic, lithosol and kransozem soils. Lateral flow of effluent is evident in the case of prairie soils. Gleyed podsolic soils indicate poor drainage and ponding of effluent. In the current phase of the research project, a number of chemical indicators such as EC, pH and chloride concentration were employed as indicators to investigate the extent of effluent flow and to understand how soil renovates effluent. The soil profile, especially texture, structure and moisture regime was examined more in an engineering sense to determine the effect of movement of water into and through the soil. However it is not only the physical characteristics, but the chemical characteristics of the soil also play a key role in the effluent renovation process. Therefore in order to understand the complex processes taking place in a subsurface effluent disposal area, it is important that the identified influential parameters are evaluated using soil chemical concepts. Consequently the primary focus of the next phase of the research project will be to identify linkages between various important parameters. The research thus envisaged will help to develop robust criteria for evaluating the performance of subsurface disposal systems.

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Background: Falciparum malaria is the most deadly among the four main types of human malaria. Although great success has been achieved since the launch of the National Malaria Control Programme in 1955, malaria remains a serious public health problem in China. This paper aimed to analyse the geographic distribution, demographic patterns and time trends of falciparum malaria in China. Methods: The annual numbers of falciparum malaria cases during 1992–2003 and the individual case reports of each clinical falciparum malaria during 2004–2005 were extracted from communicable disease information systems in China Center for Diseases Control and Prevention. The annual number of cases and the annual incidence were mapped by matching them to corresponding province- and county-level administrative units in a geographic information system. The distribution of falciparum malaria by age, gender and origin of infection was analysed. Time-series analysis was conducted to investigate the relationship between the falciparum malaria in the endemic provinces and the imported falciparum malaria in non-endemic provinces. Results: Falciparum malaria was endemic in two provinces of China during 2004–05. Imported malaria was reported in 26 non-endemic provinces. Annual incidence of falciparum malaria was mapped at county level in the two endemic provinces of China: Yunnan and Hainan. The sex ratio (male vs. female) for the number of cases in Yunnan was 1.6 in the children of 0–15 years and it reached 5.7 in the adults over 15 years of age. The number of malaria cases in Yunnan was positively correlated with the imported malaria of concurrent months in the non-endemic provinces. Conclusion: The endemic area of falciparum malaria in China has remained restricted to two provinces, Yunnan and Hainan. Stable transmission occurs in the bordering region of Yunnan and the hilly-forested south of Hainan. The age and gender distribution in the endemic area is characterized by the predominance of adult men cases. Imported falciparum malaria in the non-endemic area of China, affected mainly by the malaria transmission in Yunnan, has increased both spatially and temporally. Specific intervention measures targeted at the mobile population groups are warranted.

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Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

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Time series regression models were used to examine the influence of environmental factors (soil water content and soil temperature) on the emissions of nitrous oxide (N2O) from subtropical soils, by taking into account temporal lagged environmental factors, autoregressive processes, and seasonality for three horticultural crops in a subtropical region of Australia. Fluxes of N2O, soil water content, and soil temperature were determined simultaneously on a weekly basis over a 12-month period in South East Queensland. Annual N2O emissions for soils under mango, pineapple, and custard apple were 1590, 1156, and 2038 g N2O-N/ha, respectively, with most emissions attributed to nitrification. The N2O-N emitted from the pineapple and custard apple crops was equivalent to 0.26 and 2.22%, respectively, of the applied mineral N. The change in soil water content was the key variable for describing N2O emissions at the weekly time-scale, with soil temperature at a lag of 1 month having a significant influence on average N2O emissions (averaged) at the monthly time-scale across the three crops. After accounting for soil temperature and soil water content, both the weekly and monthly time series regression models exhibited significant autocorrelation at lags of 1–2 weeks and 1–2 months, and significant seasonality for weekly N2O emissions for mango crop and for monthly N2O emissions for mango and custard apple crops in this location over this time-frame. Time series regression models can explain a higher percentage of the temporal variation of N2O emission compared with simple regression models using soil temperature and soil water content as drivers. Taking into account seasonal variability and temporal persistence in N2O emissions associated with soil water content and soil temperature may lead to a reduction in the uncertainty surrounding estimates of N2O emissions based on limited sampling effort.

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Automated airborne collision-detection systems are a key enabling technology for facilitat- ing the integration of unmanned aerial vehicles (UAVs) into the national airspace. These safety-critical systems must be sensitive enough to provide timely warnings of genuine air- borne collision threats, but not so sensitive as to cause excessive false-alarms. Hence, an accurate characterisation of detection and false alarm sensitivity is essential for understand- ing performance trade-offs, and system designers can exploit this characterisation to help achieve a desired balance in system performance. In this paper we experimentally evaluate a sky-region, image based, aircraft collision detection system that is based on morphologi- cal and temporal processing techniques. (Note that the examined detection approaches are not suitable for the detection of potential collision threats against a ground clutter back- ground). A novel collection methodology for collecting realistic airborne collision-course target footage in both head-on and tail-chase engagement geometries is described. Under (hazy) blue sky conditions, our proposed system achieved detection ranges greater than 1540m in 3 flight test cases with no false alarm events in 14.14 hours of non-target data (under cloudy conditions, the system achieved detection ranges greater than 1170m in 4 flight test cases with no false alarm events in 6.63 hours of non-target data). Importantly, this paper is the first documented presentation of detection range versus false alarm curves generated from airborne target and non-target image data.

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The use of Bayesian methodologies for solving optimal experimental design problems has increased. Many of these methods have been found to be computationally intensive for design problems that require a large number of design points. A simulation-based approach that can be used to solve optimal design problems in which one is interested in finding a large number of (near) optimal design points for a small number of design variables is presented. The approach involves the use of lower dimensional parameterisations that consist of a few design variables, which generate multiple design points. Using this approach, one simply has to search over a few design variables, rather than searching over a large number of optimal design points, thus providing substantial computational savings. The methodologies are demonstrated on four applications, including the selection of sampling times for pharmacokinetic and heat transfer studies, and involve nonlinear models. Several Bayesian design criteria are also compared and contrasted, as well as several different lower dimensional parameterisation schemes for generating the many design points.

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Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it difficult to compare the various approaches. As a result of this, we seek to comprehensively evaluate state of the art spatio- temporal features under a common evaluation framework with popular benchmark datasets (KTH, Weizmann) and more challenging datasets such as Hollywood2. The purpose of this work is to provide guidance for researchers, when selecting features for different applications with different environmental conditions. In this work we evaluate four popular descriptors (HOG, HOF, HOG/HOF, HOG3D) using a popular bag of visual features representation, and Support Vector Machines (SVM)for classification. Moreover, we provide an in-depth analysis of local feature descriptors and optimize the codebook sizes for different datasets with different descriptors. In this paper, we demonstrate that motion based features offer better performance than those that rely solely on spatial information, while features that combine both types of data are more consistent across a variety of conditions, but typically require a larger codebook for optimal performance.

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Ocean gliders constitute an important advance in the highly demanding ocean monitoring scenario. Their effciency, endurance and increasing robustness make these vehicles an ideal observing platform for many long term oceanographic applications. However, they have proved to be also useful in the opportunis-tic short term characterization of dynamic structures. Among these, mesoscale eddies are of particular interest due to the relevance they have in many oceano-graphic processes.

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Persistent, lipophilic organochlorine pesticides (OCPs) such as dichlorodiphenyltrichloroethane (DDT), hexachlorocyclohexanes (HCHs), dieldrin, chlordanes, hexachlorobenzene (HCB) and mirex are known to accumulate in human samples [1, 2]. Persistent OCPs are among the chemicals that are covered under the Stockholm Convention on persistent organic pollutants [3]. Exceptions to this include relatively less lipophillic compounds like HCH (KOW<10^5). In Australia, OCPs such as DDT and HCHs were introduced in the 1940s. This followed a period of widespread use until the 1970s when recognition of risks related to OCPs resulted in reduced use and their ultimate ban in the 1980s. Mirex, however, remained in very restricted use in Northern Australia for treatment of one species of termites (the Giant Termite (Mastotermes darwinensis)) but this use was phased out in 2007.

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Purpose: Photoreceptor interactions reduce the temporal bandwidth of the visual system under mesopic illumination. The dynamics of these interactions are not clear. This study investigated cone-cone and rod-cone interactions when the rod (R) and three cone (L, M, S) photoreceptor classes contribute to vision via shared post-receptoral pathways. Methods: A four-primary photostimulator independently controlled photoreceptor activity in human observers. To determine the temporal dynamics of receptoral (L, S, R) and post-receptoral (LMS, LMSR, +L-M) pathways (5 Td, 7° eccentricity) in Experiment 1, ON-pathway sensitivity was assayed with an incremental probe (25ms) presented relative to onset of an incremental sawtooth conditioning pulse (1000ms). To define the post-receptoral pathways mediating the rod stimulus, Experiment 2 matched the color appearance of increased rod activation (30% contrast, 25-1000ms; constant cone excitation) with cone stimuli (variable L+M, L/L+M, S/L+M; constant rod excitation). Results: Cone-cone interactions with luminance stimuli (LMS, LMSR, L-cone) reduced Weber contrast sensitivity by 13% and the time course of adaptation was 23.7±1ms (μ±SE). With chromatic stimuli (+L-M, S), cone pathway sensitivity was also reduced and recovery was slower (+L-M 8%, 2.9±0.1ms; S 38%, 1.5±0.3ms). Threshold patterns at ON-conditioning pulse onset were monophasic for luminance and biphasic for chromatic stimuli. Rod-rod interactions increased sensitivity(19%) with a recovery time of 0.7±0.2ms. Compared to cone-cone interactions, rod-cone interactions with luminance stimuli reduced sensitivity to a lesser degree (5%) with faster recovery (42.9±0.7ms). Rod-cone interactions were absent with chromatic stimuli. Experiment 2 showed that rod activation generated luminance (L+M) signals at all durations, and chromatic signals (L/L+M, S/L+M) for durations >75ms. Conclusions: Temporal dynamics of cone-cone interactions are consistent with contrast sensitivity loss in the MC pathway for luminance stimuli and chromatically opponent responses in the PC and KC pathway with chromatic stimuli. Rod-cone interactions limit contrast sensitivity loss during dynamic illumination changes and increase the speed of mesopic light adaptation. The change in relative weighting of the temporal rod signal within the major post-receptoral pathways modifies the sensitivity and dynamics of photoreceptor interactions.

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Purpose: IpRGCs mediate non-image forming functions including photoentrainment and the pupil light reflex (PLR). Temporal summation increases visual sensitivity and decreases temporal resolution for image forming vision, but the summation properties of nonimage forming vision are unknown. We investigated the temporal summation of inner (ipRGC) and outer (rod/cone) retinal inputs to the PLR. Method: The consensual PLR of the left eye was measured in six participants with normal vision using a Maxwellian view infrared pupillometer. Temporal summation was investigated using a double-pulse protocol (100 ms stimulus pairs; 0–1024 ms inter-stimulus interval, ISI) presented to the dilated fellow right eye (Tropicamide 1%). Stimulus lights (blue λmax = 460 nm; red λmax = 638 nm) biased activity to inneror outer retinal inputs to non-image forming vision. Temporal summation was measured suprathreshold (15.2 log photons.cm−2.s−1 at the cornea) and subthreshold (11.4 log photons.cm−2.s−1 at the cornea). Results: RM-ANOVAs showed the suprathreshold and subthreshold 6 second post illumination pupil response (PIPR: expressed as percentage baseline diameter) did not significantly vary for red or blue stimuli (p > .05). The PIPR for a subthreshold red 16 ms double-pulse control condition did not significantly differ with ISI (p > .05). The maximum constriction amplitude for red and blue 100 ms double- pulse stimuli did not significantly vary with ISI (p > .05). Conclusion: The non-significant changes in suprathreshold PIPR and subthreshold maximum pupil constriction indicate that inner retinal ipRGC inputs and outer retinal photoreceptor inputs to the PLR do not show temporal summation. The results suggest a fundamental difference between the temporal summation characteristics of image forming and non-image forming vision.

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This work investigates the accuracy and efficiency tradeoffs between centralized and collective (distributed) algorithms for (i) sampling, and (ii) n-way data analysis techniques in multidimensional stream data, such as Internet chatroom communications. Its contributions are threefold. First, we use the Kolmogorov-Smirnov goodness-of-fit test to show that statistical differences between real data obtained by collective sampling in time dimension from multiple servers and that of obtained from a single server are insignificant. Second, we show using the real data that collective data analysis of 3-way data arrays (users x keywords x time) known as high order tensors is more efficient than centralized algorithms with respect to both space and computational cost. Furthermore, we show that this gain is obtained without loss of accuracy. Third, we examine the sensitivity of collective constructions and analysis of high order data tensors to the choice of server selection and sampling window size. We construct 4-way tensors (users x keywords x time x servers) and analyze them to show the impact of server and window size selections on the results.