Ego depletion and persistent performance in a cycling task

We tested the assumption that persistent performance in an exhausting indoor cycling task would depend on momentarily available self-control strength (N = 20 active participants). In a within-subjects design (two points of measurement, exactly seven days apart), participants’ self-control strength was experimentally manipulated (depletion: yes vs. no; order counterbalanced) via the Stroop test before the participants performed a cycling task. In line with our hypothesis, hierarchical linear modelling (HLM) revealed that participants consistently performed worse over a period of 18 minutes when they were ego depleted. In addition, HLM analysis revealed that depleted participants invested less effort in the cycling task, as indicated by their lower heart rate. This effect escalated over time, as indicated by a time × condition interaction. These results indicate that self-control strength is necessary to obtain an optimal level of performance in endurance tasks requiring high levels of persistence. Practical implications are discussed.

A Passive WiFi Source Localization System based on Fine-grained Power-based Trilateration

Indoor localization systems become more interesting for researchers because of the attractiveness of business cases in various application fields. A WiFi-based passive localization system can provide user location information to third-party providers of positioning services. However, indoor localization techniques are prone to multipath and Non-Line Of Sight (NLOS) propagation, which lead to significant performance degradation. To overcome these problems, we provide a passive localization system for WiFi targets with several improved algorithms for localization. Through Software Defined Radio (SDR) techniques, we extract Channel Impulse Response (CIR) information at the physical layer. CIR is later adopted to mitigate the multipath fading problem. We propose to use a Nonlinear Regression (NLR) method to relate the filtered power information to propagation distances, which significantly improves the ranging accuracy compared to the commonly used log-distance path loss model. To mitigate the influence of ranging errors, a new trilateration algorithm is designed as well by combining Weighted Centroid and Constrained Weighted Least Square (WC-CWLS) algorithms. Experiment results show that our algorithm is robust against ranging errors and outperforms the linear least square algorithm and weighted centroid algorithm.

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system.

Real-time localization using software defined radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system.

SCAD: Sensor Context-aware Adaptive Duty-cycled Beaconless Opportunistic Routing for WSNs

Low quality of wireless links leads to perpetual transmission failures in lossy wireless environments. To mitigate this problem, opportunistic routing (OR) has been proposed to improve the throughput of wireless multihop ad-hoc networks by taking advantage of the broadcast nature of wireless channels. However, OR can not be directly applied to wireless sensor networks (WSNs) due to some intrinsic design features of WSNs. In this paper, we present a new OR solution for WSNs with suitable adaptations to their characteristics. Our protocol, called SCAD-Sensor Context-aware Adaptive Duty-cycled beaconless opportunistic routing protocol is a cross-layer routing approach and it selects packet forwarders based on multiple sensor context information. To reach a balance between performance and energy-efficiency, SCAD adapts the duty-cycles of sensors according to real-time traffic loads and energy drain rates. We compare SCAD against other protocols through extensive simulations. Evaluation results show that SCAD outperforms other protocols in highly dynamic scenarios.

Passively Track WiFi Users with an Enhanced Particle Filter using Power-based Ranging

Passive positioning systems produce user location information for third-party providers of positioning services. Since the tracked wireless devices do not participate in the positioning process, passive positioning can only rely on simple, measurable radio signal parameters, such as timing or power information. In this work, we provide a passive tracking system for WiFi signals with an enhanced particle filter using fine-grained power-based ranging. Our proposed particle filter provides an improved likelihood function on observation parameters and is equipped with a modified coordinated turn model to address the challenges in a passive positioning system. The anchor nodes for WiFi signal sniffing and target positioning use software defined radio techniques to extract channel state information to mitigate multipath effects. By combining the enhanced particle filter and a set of enhanced ranging methods, our system can track mobile targets with an accuracy of 1.5m for 50% and 2.3m for 90% in a complex indoor environment. Our proposed particle filter significantly outperforms the typical bootstrap particle filter, extended Kalman filter and trilateration algorithms.

Contextualizing local-scale point sample data using global-scale spatial datasets: Lessons learnt from the analysis of large-scale land acquisitions

This paper examines how the geospatial accuracy of samples and sample size influence conclusions from geospatial analyses. It does so using the example of a study investigating the global phenomenon of large-scale land acquisitions and the socio-ecological characteristics of the areas they target. First, we analysed land deal datasets of varying geospatial accuracy and varying sizes and compared the results in terms of land cover, population density, and two indicators for agricultural potential: yield gap and availability of uncultivated land that is suitable for rainfed agriculture. We found that an increase in geospatial accuracy led to a substantial and greater change in conclusions about the land cover types targeted than an increase in sample size, suggesting that using a sample of higher geospatial accuracy does more to improve results than using a larger sample. The same finding emerged for population density, yield gap, and the availability of uncultivated land suitable for rainfed agriculture. Furthermore, the statistical median proved to be more consistent than the mean when comparing the descriptive statistics for datasets of different geospatial accuracy. Second, we analysed effects of geospatial accuracy on estimations regarding the potential for advancing agricultural development in target contexts. Our results show that the target contexts of the majority of land deals in our sample whose geolocation is known with a high level of accuracy contain smaller amounts of suitable, but uncultivated land than regional- and national-scale averages suggest. Consequently, the more target contexts vary within a country, the more detailed the spatial scale of analysis has to be in order to draw meaningful conclusions about the phenomena under investigation. We therefore advise against using national-scale statistics to approximate or characterize phenomena that have a local-scale impact, particularly if key indicators vary widely within a country.

Tuberculosis Mortality and Living Conditions in Bern, Switzerland, 1856-1950.

BACKGROUND Tuberculosis (TB) is a poverty-related disease that is associated with poor living conditions. We studied TB mortality and living conditions in Bern between 1856 and 1950. METHODS We analysed cause-specific mortality based on mortality registers certified by autopsies, and public health reports 1856 to 1950 from the city council of Bern. RESULTS TB mortality was higher in the Black Quarter (550 per 100,000) and in the city centre (327 per 100,000), compared to the outskirts (209 per 100,000 in 1911-1915). TB mortality correlated positively with the number of persons per room (r = 0.69, p = 0.026), the percentage of rooms without sunlight (r = 0.72, p = 0.020), and negatively with the number of windows per apartment (r = -0.79, p = 0.007). TB mortality decreased 10-fold from 330 per 100,000 in 1856 to 33 per 100,000 in 1950, as housing conditions improved, indoor crowding decreased, and open-air schools, sanatoria, systematic tuberculin skin testing of school children and chest radiography screening were introduced. CONCLUSIONS Improved living conditions and public health measures may have contributed to the massive decline of the TB epidemic in the city of Bern even before effective antibiotic treatment became finally available in the 1950s.

A Study of Radon in Air and Water in Maine Schools

The transfer coefficient of radon from water to air was investigated in schools. Kitchens, bathrooms and locker rooms were studied for seven schools in Maine. Simulations were done in water-use rooms where radon in air detectors were in place. Quantities measured were radon in water (270-24500 F) and air (0-80 q), volume of water used, emissivities (0.01-0.99) and ventilation rates (0.012-0.066A). Variation throughout the room of the radon concentration was found. Values calculated for the transfer coefficient for kitchens and baths were ranged from 9.6 x to 2.0 x The transfer coefficient was calculated using these parameters and was also measured using concentrations of radon in water and air. This provides a means by which radon in air can be estimated using the transfer coefficient and the concentration in the water in other schools and it can be used to estimate the dose caused by radon released from water use. This project was partially funded by the United States Environmental Protection Agency (grant #X828l2 101-0) and by the State of Maine (grant #10A500178). These are the first measurements of this type to be done in schools in the United States.

THE NATURAL BACKGROUND GAMMA RADIATION EXPOSURE IN THE METROPOLITAN AREA OF THE VALLEY OF MEXICO

Measurements of the natural background radiation have been made at numerous places throughout the world. Very little work in this field has been done in developing countries. In Mexico the natural radiation to which the population is exposed has not been assessed. This dissertation represents a pioneer study in this environmental area. The radiation exposure which occupants within buildings receive as a result of naturally occurring radionuclides present in construction materials is the principal focus.^ Data were collected between August 1979 and November 1980. Continuous monitoring was done with TLDs placed on site for periods of 3 to 6 months. The instrumentation used for "real-time" measurements was a portable NaI (Tl) scintillation detector. In addition, radiometric measurements were performed on construction materials commonly used in Mexican homes.^ Based on TLD readings taken within 75 dwellings, the typical indoor exposure for a resident of the study area is 9.2 (mu)Rh('-1). The average reading of the 152 indoor scintillometer surveys was 9.5 (mu)Rh('-1), the outdoor reading 7.5 (mu)Rh('-1). Results of one-way and multi-way analyses of the exposure data to determine the effect due to building materials type, geologic subsoil, age of dwelling, and elevation are also presented. The results of 152 indoor scintillometer surveys are described. ^

SAMPLING METHODOLOGY FOR AIRBORNE SEMIVOLATILE ORGANIC POLLUTANTS USING POLYURETHANE FOAMS (COLLECTION, PESTICIDES, VOLATILE)

Indoor and ambient air organic pollutants have been gaining attention because they have been measured at levels with possible health effects. Studies have shown that most airborne polychlorinated biphenyls (PCBs), pesticides and many polycyclic aromatic hydrocarbons (PAHs) are present in the free vapor state. The purpose of this research was to extend recent investigative work with polyurethane foam (PUF) as a collection medium for semivolatile compounds. Open-porous flexible PUFs with different chemical makeup and physical properties were evaluated as to their collection affinities/efficiencies for various classes of compounds and the degree of sample recovery. Filtered air samples were pulled through plugs of PUF spiked with various semivolatiles under different simulated environmental conditions (temperature and humidity), and sampling parameters (flow rate and sample volume) in order to measure their effects on sample breakthrough volume (V(,B)). PUF was also evaluated in the passive mode using organo-phosphorus pesticides. Another major goal was to improve the overall analytical methodology; PUF is inexpensive, easy to handle in the field and has excellent airflow characteristics (low pressure drop). It was confirmed that the PUF collection apparatus behaves as if it were a gas-solid chromatographic system, in that, (V(,B)) was related to temperature and sample volume. Breakthrough volumes were essentially the same using both polyether and polyester type PUF. Also, little change was observed in the V(,B)s after coating PUF with common chromatographic liquid phases. Open cell (reticulated) foams gave better recoveries than closed cell foams. There was a slight increase in (V(,B)) with an increase in the number of cells/pores per inch. The high-density polyester PUF was found to be an excellent passive and active collection adsorbent. Good recoveries could be obtained using just solvent elution. A gas chromatograph equipped with a photoionization detector gave excellent sensitivities and selectivities for the various classes of compounds investigated. ^

Environmental and behavioral risk factors for moderate or severe rotavirus diarrhea in children less than 24 months

On a global basis rotaviruses are the most important agents involved in childhood diarrhea. In developing countries they account for 6% of all diarrheas and 20% of all diarrhea related deaths of children under 5 years of age, with over 1 billion episodes and over 4 million deaths annually. Given the disease burden, there is a need for better understanding the risk factors involved in rotavirus disease, to identify areas of intervention. In order to provide this information, two areas were developed: a review of the literature, examining the causal evidence for rotavirus diarrhea and a case comparison study. The case comparison study analyzed two areas: identifying climate factors and, identifying environmental and behavioral risk factors. The literature review showed that few analytical studies have identified specific risk factors such as home environment, and a winter seasonal trend for temperate areas, but in key areas evidence is contradictory. The case comparison study for climate factors demonstrated that seasonality occurs in a tropical country like Venezuela and that a complex interplay between weather conditions contribute to the seasonal pattern. A positive association between rain fall (OR 4.1); dew point (OR 2.3) and temperature differential during the day (OR 1.4) and, an inverse association with temperature (OR 0.5) and relative humidity (OR 0.8) was found. This information is useful in understanding the seasonal pattern of rotavirus and for planning health care needs. The second analysis demonstrated that environmental variables such as crowding (OR 14.3), contact with someone with an infectious disease (OR 4.9) and animal ownership (OR 2.3) were important. Restricting the analysis to animal owners demonstrated that living In a rural settling (OR 13.8), defecating in inappropriate places (OR 7.2), crowding(4.2) and indoor animals (4.0) are of importance. Behavioral variables identified were: lack of breast feeding (OR 4.0) and visiting when someone was sick (OR 3.4). Biological and demographic variables of importance were: age, with a dose response relationship; undernurishment (OR 11.3) and household per capita monthly income less than US $ 16.30 (OR 8.5). Using a diarrhea compeer group we found that, although some of the previous variables were of importance, no major differences were found. These findings are important in identifying paths for prevention and further research. ^

Optimization of a DNSH passive sampling method to measure airborne carbonyls

Various airborne aldehydes and ketones (i.e., airborne carbonyls) present in outdoor, indoor, and personal air pose a risk to human health at present environmental concentrations. To date, there is no adequate, simple-to-use sampler for monitoring carbonyls at parts per billion concentrations in personal air. The Passive Aldehydes and Ketones Sampler (PAKS) originally developed for this purpose has been found to be unreliable in a number of relatively recent field studies. The PAKS method uses dansylhydrazine, DNSH, as the derivatization agent to produce aldehyde derivatives that are analyzed by HPLC with fluorescence detection. The reasons for the poor performance of the PAKS are not known but it is hypothesized that the chemical derivatization conditions and reaction kinetics combined with a relatively low sampling rate may play a role. This study evaluated the effect of absorption and emission wavelengths, pH of the DNSH coating solution, extraction solvent, and time post-extraction for the yield and stability of formaldehyde, acetaldehyde, and acrolein DNSH derivatives. The results suggest that the optimum conditions for the analysis of DNSHydrazones are the following. The excitation and emission wavelengths for HPLC analysis should be at 250nm and 500nm, respectively. The optimal pH of the coating solution appears to be pH 2 because it improves the formation of di-derivatized acrolein DNSHydrazones without affecting the response of the derivatives of the formaldehyde and acetaldehyde derivatives. Acetonitrile is the preferable extraction solvent while the optimal time to analyze the aldehyde derivatives is 72 hours post-extraction. ^

Evaluation of residential bioaerosol concentrations and their related health effects

Limited research has been conducted on the collection of bioaerosols and their health effects on individuals in the El Paso area. A year long study was conducted in the region to evaluate indoor bioaerosol concentrations (Mota et al., unpublished data). As part of the study, air samples were collected during each season for a year from 38 homes from the El Paso area. The main objective of the study was to assess seasonality differences in bioaerosol concentrations. The air samples were then cultured and analyzed for bacterial and fungal concentrations. As a supplement to that study, a health questionnaire was given during each seasonal air sampling to the participating resident to complete regarding their health status. The aim of this study was to evaluate the health questionnaire and assess any associations between the collected bioaerosol concentrations and the self-reported respiratory symptoms of the participating home residents. Symptom frequencies were tabulated and basic descriptive statistics, along with logistic regressions, were conducted on the relationship between “High” reporters of symptoms and bioaerosol concentrations and environmental factors. The most commonly reported symptoms by homeowners were nasal symptoms and allergies. In addition, there was evidence to support an association between indoor respirable bacteria concentrations and homeowners that report greater than or equal to 8 respiratory symptoms (OR=1.10, p=0.045). Smoking status, indoor humidity and season also displayed associations with homeowners that report greater than or equal to 8 respiratory symptoms (OR=3.3, p=0.045; OR=71.0, p=0.030; OR=7.2, 3.2, p=0.001, 0.008). With such a strong association, future assessment of symptoms, bioaerosol concentrations and environmental factors is needed to further establish their relationship. ^