SAMPLING BIAS IN EVALUATING THE PROBABILITY OF SEISMICALLY INDUCED SOIL LIQUEFACTION WITH SPT & CPT CASE HISTORIES

Several deterministic and probabilistic methods are used to evaluate the probability of seismically induced liquefaction of a soil. The probabilistic models usually possess some uncertainty in that model and uncertainties in the parameters used to develop that model. These model uncertainties vary from one statistical model to another. Most of the model uncertainties are epistemic, and can be addressed through appropriate knowledge of the statistical model. One such epistemic model uncertainty in evaluating liquefaction potential using a probabilistic model such as logistic regression is sampling bias. Sampling bias is the difference between the class distribution in the sample used for developing the statistical model and the true population distribution of liquefaction and non-liquefaction instances. Recent studies have shown that sampling bias can significantly affect the predicted probability using a statistical model. To address this epistemic uncertainty, a new approach was developed for evaluating the probability of seismically-induced soil liquefaction, in which a logistic regression model in combination with Hosmer-Lemeshow statistic was used. This approach was used to estimate the population (true) distribution of liquefaction to non-liquefaction instances of standard penetration test (SPT) and cone penetration test (CPT) based most updated case histories. Apart from this, other model uncertainties such as distribution of explanatory variables and significance of explanatory variables were also addressed using KS test and Wald statistic respectively. Moreover, based on estimated population distribution, logistic regression equations were proposed to calculate the probability of liquefaction for both SPT and CPT based case history. Additionally, the proposed probability curves were compared with existing probability curves based on SPT and CPT case histories.

Adaptive Sampling with Mobile Sensor Networks

Mobile sensor networks have unique advantages compared with wireless sensor networks. The mobility enables mobile sensors to flexibly reconfigure themselves to meet sensing requirements. In this dissertation, an adaptive sampling method for mobile sensor networks is presented. Based on the consideration of sensing resource constraints, computing abilities, and onboard energy limitations, the adaptive sampling method follows a down sampling scheme, which could reduce the total number of measurements, and lower sampling cost. Compressive sensing is a recently developed down sampling method, using a small number of randomly distributed measurements for signal reconstruction. However, original signals cannot be reconstructed using condensed measurements, as addressed by Shannon Sampling Theory. Measurements have to be processed under a sparse domain, and convex optimization methods should be applied to reconstruct original signals. Restricted isometry property would guarantee signals can be recovered with little information loss. While compressive sensing could effectively lower sampling cost, signal reconstruction is still a great research challenge. Compressive sensing always collects random measurements, whose information amount cannot be determined in prior. If each measurement is optimized as the most informative measurement, the reconstruction performance can perform much better. Based on the above consideration, this dissertation is focusing on an adaptive sampling approach, which could find the most informative measurements in unknown environments and reconstruct original signals. With mobile sensors, measurements are collect sequentially, giving the chance to uniquely optimize each of them. When mobile sensors are about to collect a new measurement from the surrounding environments, existing information is shared among networked sensors so that each sensor would have a global view of the entire environment. Shared information is analyzed under Haar Wavelet domain, under which most nature signals appear sparse, to infer a model of the environments. The most informative measurements can be determined by optimizing model parameters. As a result, all the measurements collected by the mobile sensor network are the most informative measurements given existing information, and a perfect reconstruction would be expected. To present the adaptive sampling method, a series of research issues will be addressed, including measurement evaluation and collection, mobile network establishment, data fusion, sensor motion, signal reconstruction, etc. Two dimensional scalar field will be reconstructed using the method proposed. Both single mobile sensors and mobile sensor networks will be deployed in the environment, and reconstruction performance of both will be compared.In addition, a particular mobile sensor, a quadrotor UAV is developed, so that the adaptive sampling method can be used in three dimensional scenarios.

Improved Dynamic Headspace Sampling and Detection using Capillary Microextraction of Volatiles Coupled to Gas Chromatography Mass Spectrometry

Sampling and preconcentration techniques play a critical role in headspace analysis in analytical chemistry. My dissertation presents a novel sampling design, capillary microextraction of volatiles (CMV), that improves the preconcentration of volatiles and semivolatiles in a headspace with high throughput, near quantitative analysis, high recovery and unambiguous identification of compounds when coupled to mass spectrometry. The CMV devices use sol-gel polydimethylsiloxane (PDMS) coated microglass fibers as the sampling/preconcentration sorbent when these fibers are stacked into open-ended capillary tubes. The design allows for dynamic headspace sampling by connecting the device to a hand-held vacuum pump. The inexpensive device can be fitted into a thermal desorption probe for thermal desorption of the extracted volatile compounds into a gas chromatography-mass spectrometer (GC-MS). The performance of the CMV devices was compared with two other existing preconcentration techniques, solid phase microextraction (SPME) and planar solid phase microextraction (PSPME). Compared to SPME fibers, the CMV devices have an improved surface area and phase volume of 5000 times and 80 times, respectively. One (1) minute dynamic CMV air sampling resulted in similar performance as a 30 min static extraction using a SPME fiber. The PSPME devices have been fashioned to easily interface with ion mobility spectrometers (IMS) for explosives or drugs detection. The CMV devices are shown to offer dynamic sampling and can now be coupled to COTS GC-MS instruments. Several compound classes representing explosives have been analyzed with minimum breakthrough even after a 60 min. sampling time. The extracted volatile compounds were retained in the CMV devices when preserved in aluminum foils after sampling. Finally, the CMV sampling device were used for several different headspace profiling applications which involved sampling a shipping facility, six illicit drugs, seven military explosives and eighteen different bacteria strains. Successful detection of the target analytes at ng levels of the target signature volatile compounds in these applications suggests that the CMV devices can provide high throughput qualitative and quantitative analysis with high recovery and unambiguous identification of analytes.

Caracterización y prevalencia del compromiso ocular en pacientes con enfermedad autoinmune y autoinflamatoria en un centro de referencia reumatológica en Colombia entre los años 2000 a 2015

RESUMEN Objetivo: Estimar la prevalencia de las diferentes enfermedades oftalmológicas que aparecen en el contexto de una enfermedad autoinmune (EAI) en pacientes de un centro de referencia reumatológica en Colombia, según características clínicas y sociodemográficas durante un período de 15 años, comprendido entre los años 2000 a 2015. Métodos: Se realizó un estudio descriptivo, observacional de prevalencia. El tipo de muestreo fue aleatorio estratificado con asignación proporcional en el programa Epidat 3.4. Los datos se analizaron en el programa SPSS v22.0 y se realizó análisis univariado de las variables categóricas, para las variables cuantitativas se realizaron medidas de tendencia central. Resultados: De 1640 historias clínicas revisadas, se encontraron 634 pacientes (38,65%) con compromiso ocular. Si excluimos los pacientes con SS, que por definición presentan ojo seco, 222 pacientes (13,53%) presentaron compromiso oftalmológico. Del total de pacientes, el 83,3% fueron mujeres. La AR fue la enfermedad autoinmune con mayor compromiso oftalmológico con 138 pacientes (62,2%), y en último lugar la sarcoidosis con 1 solo paciente afectado. La QCS fue la manifestación más común en todos los grupos diagnósticos de EAI, con 146 pacientes (63,5%). De 414 pacientes con Síndrome de Sjögren (SS) y QCS 8 presentaron compromiso ocular adicional, siendo la uveítis la segunda patología ocular asociada en pacientes con SS y la primera causa en las espondiloartropatias (71,4 %). Los pacientes con catarata (4,1%) presentaron la mayor prevalencia de uso de corticoide (88.8%). De 222 pacientes, 28 (12,6%) presentaron uveítis. Del total de pacientes, 16 (7,2%) presentaron maculopatía por antimalaráricos y 6 (18,75%) de los pacientes con LES. Los ANAS se presentaron en el 100% los pacientes con trastorno vascular de la retina. Los pacientes con epiescleritis presentaron la mayor proporción de positivización de anticuerpos anti-DNA. La EAI que más presentó epiescleritis fue LES con 4 pacientes (12,5%) El 22% de paciente con anticuerpos anti-RNP presentaron escleritis y 32,1% de los pacientes con uveítis presentaron HLA-B27 positivo. Las manifestaciones oftalmológicas precedieron a las sistémicas entre un 11,1% y un 33,3% de los pacientes. Conclusión: Las enfermedades oculares se presentan con frecuencia en los pacientes colombianos con EAI (38.65%), siendo la AR la enfermedad con mayor compromiso ocular (62,2%) y la QCS la enfermedad ocular con mayor prevalencia en todas las EAI (63,5%). La uveítis se presentó en 28 pacientes (12,6%). Las manifestaciones oftalmológicas pueden preceder a las sistémicas. El examen oftalmológico debe ser incluido en los pacientes con EAI, por ser la enfermedad ocular una comorbilidad frecuente. Adicionalmente, los efectos oftalmológicos de las medicaciones sistémicas utilizadas en EAI deben ser estrechamente monitorizados, durante el curso del tratamiento.

Positive regional species-people correlations: A sampling artefact or a key issue for sustainable development?

Many studies are documenting positive large-scale species– people correlations (Luck, 2007; Schuldt & Assmann, 2010). The issue is scale dependent: the local association of species richness and people is in many cases a negative one (Pautasso, 2007; Pecher et al., 2010). This biogeographical pattern is thus important for conservation. If species-rich regions are also densely populated, preserving biodiversity becomes more difficult, ceteris paribus, than if species-rich regions were sparsely populated. At the same time, positive, regional species–people correlations are an opportunity for the biodiversity education of the majority of the human population and underline the importance of conservation in human-modified landscapes (e.g. Sheil & Meijaard, 2010; Ward, 2010).

Geographical patterns of the species richness of helminth parasites of moles (Talpa spp.) in Spain: Separating the effects of sampling effort from those of other conditioning factors

We analysed the viscera of 534 moles (Ta l p a spp.) from 30 of the 47 provinces of peninsular Spain, including 255 individuals of T. europaea from eight provinces, 154 individuals of T. occidentalis from 20 provinces, and 125 unidentified Ta l p a individuals from two provinces. We identified their helminth parasites and determined parasite species richness. We related parasite species richness with sampling effort using both a linear and a logarithmic function. We then performed stepwise linear regressions to predict mole parasite species richness from a small set of selected predictor variables that included sampling effort. We applied the resulting models to forecast T. euro p a e a, T. occidentalis, and Ta l p a spp. parasite species richness in all provinces with recorded host presence, assuming different levels of sampling eff o r t . F i n a l l y, we used partial regression analysis to partition the variation explained by each of the selected variables in the models. We found that mole parasite species richness is strongly conditioned by sampling effort, but that other factors such as cropland area and environmental disturbance have significant independent effects.

Spatial scale effects of sampling on the interpolation of species distribution models in the southwestern Amazon.

Knowledge of the geographical distribution of timber tree species in the Amazon is still scarce. This is especially true at the local level, thereby limiting natural resource management actions. Forest inventories are key sources of information on the occurrence of such species. However, areas with approved forest management plans are mostly located near access roads and the main industrial centers. The present study aimed to assess the spatial scale effects of forest inventories used as sources of occurrence data in the interpolation of potential species distribution models. The occurrence data of a group of six forest tree species were divided into four geographical areas during the modeling process. Several sampling schemes were then tested applying the maximum entropy algorithm, using the following predictor variables: elevation, slope, exposure, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). The results revealed that using occurrence data from only one geographical area with unique environmental characteristics increased both model overfitting to input data and omission error rates. The use of a diagonal systematic sampling scheme and lower threshold values led to improved model performance. Forest inventories may be used to predict areas with a high probability of species occurrence, provided they are located in forest management plan regions representative of the environmental range of the model projection area.

Smart sampling approaches for Decision-Focused Learning

Many real-word decision- making problems are defined based on forecast parameters: for example, one may plan an urban route by relying on traffic predictions. In these cases, the conventional approach consists in training a predictor and then solving an optimization problem. This may be problematic since mistakes made by the predictor may trick the optimizer into taking dramatically wrong decisions. Recently, the field of Decision-Focused Learning overcomes this limitation by merging the two stages at training time, so that predictions are rewarded and penalized based on their outcome in the optimization problem. There are however still significant challenges toward a widespread adoption of the method, mostly related to the limitation in terms of generality and scalability. One possible solution for dealing with the second problem is introducing a caching-based approach, to speed up the training process. This project aims to investigate these techniques, in order to reduce even more, the solver calls. For each considered method, we designed a particular smart sampling approach, based on their characteristics. In the case of the SPO method, we ended up discovering that it is only necessary to initialize the cache with only several solutions; those needed to filter the elements that we still need to properly learn. For the Blackbox method, we designed a smart sampling approach, based on inferred solutions.

Impact Of Pharmacist Interventions On Drug-related Problems And Laboratory Markers In Outpatients With Human Immunodeficiency Virus Infection.

Substantial complexity has been introduced into treatment regimens for patients with human immunodeficiency virus (HIV) infection. Many drug-related problems (DRPs) are detected in these patients, such as low adherence, therapeutic inefficacy, and safety issues. We evaluated the impact of pharmacist interventions on CD4+ T-lymphocyte count, HIV viral load, and DRPs in patients with HIV infection. In this 18-month prospective controlled study, 90 outpatients were selected by convenience sampling from the Hospital Dia-University of Campinas Teaching Hospital (Brazil). Forty-five patients comprised the pharmacist intervention group and 45 the control group; all patients had HIV infection with or without acquired immunodeficiency syndrome. Pharmaceutical appointments were conducted based on the Pharmacotherapy Workup method, although DRPs and pharmacist intervention classifications were modified for applicability to institutional service limitations and research requirements. Pharmacist interventions were performed immediately after detection of DRPs. The main outcome measures were DRPs, CD4+ T-lymphocyte count, and HIV viral load. After pharmacist intervention, DRPs decreased from 5.2 (95% confidence interval [CI] =4.1-6.2) to 4.2 (95% CI =3.3-5.1) per patient (P=0.043). A total of 122 pharmacist interventions were proposed, with an average of 2.7 interventions per patient. All the pharmacist interventions were accepted by physicians, and among patients, the interventions were well accepted during the appointments, but compliance with the interventions was not measured. A statistically significant increase in CD4+ T-lymphocyte count in the intervention group was found (260.7 cells/mm(3) [95% CI =175.8-345.6] to 312.0 cells/mm(3) [95% CI =23.5-40.6], P=0.015), which was not observed in the control group. There was no statistical difference between the groups regarding HIV viral load. This study suggests that pharmacist interventions in patients with HIV infection can cause an increase in CD4+ T-lymphocyte counts and a decrease in DRPs, demonstrating the importance of an optimal pharmaceutical care plan.

An Integrated Framework To Improve The Concept Of Resource Specialisation.

Resource specialisation, although a fundamental component of ecological theory, is employed in disparate ways. Most definitions derive from simple counts of resource species. We build on recent advances in ecophylogenetics and null model analysis to propose a concept of specialisation that comprises affinities among resources as well as their co-occurrence with consumers. In the distance-based specialisation index (DSI), specialisation is measured as relatedness (phylogenetic or otherwise) of resources, scaled by the null expectation of random use of locally available resources. Thus, specialists use significantly clustered sets of resources, whereas generalists use over-dispersed resources. Intermediate species are classed as indiscriminate consumers. The effectiveness of this approach was assessed with differentially restricted null models, applied to a data set of 168 herbivorous insect species and their hosts. Incorporation of plant relatedness and relative abundance greatly improved specialisation measures compared to taxon counts or simpler null models, which overestimate the fraction of specialists, a problem compounded by insufficient sampling effort. This framework disambiguates the concept of specialisation with an explicit measure applicable to any mode of affinity among resource classes, and is also linked to ecological and evolutionary processes. This will enable a more rigorous deployment of ecological specialisation in empirical and theoretical studies.

Falls Among The Elderly: Risk Factors In A Population-based Study.

The aim of the present study was to identify factors associated with the occurrence of falls among elderly adults in a population-based study (ISACamp 2008). A population-based cross-sectional study was carried out with two-stage cluster sampling. The sample was composed of 1,520 elderly adults living in the urban area of the city of Campinas, São Paulo, Brazil. The occurrence of falls was analyzed based on reports of the main accident occurred in the previous 12 months. Data on socioeconomic/demographic factors and adverse health conditions were tested for possible associations with the outcome. Prevalence ratios (PR) were estimated and adjusted for gender and age using the Poisson multiple regression analysis. Falls were more frequent, after adjustment for gender and age, among female elderly participants (PR = 2.39; 95% confidence interval (95% CI) 1.47 - 3.87), elderly adults (80 years old and older) (PR = 2.50; 95% CI 1.61 - 3.88), widowed (PR = 1.74; 95% CI 1.04 - 2.89) and among elderly adults who had rheumatism/arthritis/arthrosis (PR = 1.58; 95% CI 1.00 - 2.48), osteoporosis (PR = 1.71; 95% CI 1.18 - 2.49), asthma/bronchitis/emphysema (PR = 1,73; 95% CI 1.09 - 2.74), headache (PR = 1.59; 95% CI 1.07 - 2.38), mental common disorder (PR = 1.72; 95% CI 1.12 - 2.64), dizziness (PR = 2.82; 95% CI 1.98 - 4.02), insomnia (PR = 1.75; 95% CI 1.16 - 2.65), use of multiple medications (five or more) (PR = 2.50; 95% CI 1.12 - 5.56) and use of cane/walker (PR = 2.16; 95% CI 1.19 - 3,93). The present study shows segments of the elderly population who are more prone to falls through the identification of factors associated with this outcome. The findings can contribute to the planning of public health policies and programs addressed to the prevention of falls.

Factors Associated With The Onset Of Hypertension In Women Of 50 Years Of Age Or More In A City In Southeastern Brazil.

To evaluate factors associated with hypertension in Brazilian women of 50 years of age or more. A cross-sectional population based study using self-reports. A total of 622 women were included. The association between sociodemographic, clinical and behavioral factors and the woman's age at the onset of hypertension was evaluated. Data were analyzed according to cumulative continuation rates without hypertension, using the life-table method and considering annual intervals. Next, a Cox multiple regression analysis model was adjusted to analyze the occurrence rates of hypertension according to various predictor variables. Significance level was pre-established at 5% (95% confidence level) and the sampling plan (primary sampling unit) was taken into consideration. Median age at onset of hypertension was 64.3 years. Cumulative continuation rate without hypertension at 90 years was 20%. Higher body mass index (BMI) at 20-30 years of age was associated with a higher cumulative occurrence rate of hypertension over time (coefficient=0.078; p<0.001). Being white was associated with a lower cumulative occurrence rate of hypertension over time (coefficient= -0.439; p=0.003), while smoking >15 cigarettes/day was associated with a higher rate over time (coefficient=0.485; p=0.004). The results of the present study highlight the importance of weight control in young adulthood and of avoiding smoking in preventing hypertension in women aged ≥50 years.

The Use Of Medication And Associated Factors Among Adults Living In Campinas, São Paulo, Brazil: Differences Between Men And Women.

The objective of this study was to verify factors associated with the use of medication by adults, with emphasis on the differences between men and women. It was a population-based, cross-sectional study with cluster sampling conducted in two stages in Campinas in the state of São Paulo in 2008. Among the 2,413 individuals aged 20 or older, the prevalence of use of at least one drug in the three days before the research was 45.4% (95% CI: 41.3 - 49.4) in men and 64.6% (95% CI: 59.8 - 69.2) in women. For adult men over 40 years old who were not working, former smokers, with one or more chronic diseases, with two or more health problems and who sought health care or a health professional in the two weeks preceding the research showed higher prevalence of medication use. Among women, a higher prevalence of use was observed in females over 40, obese, former smokers, who reported a short sleep pattern, with one or more chronic diseases and two or more health problems, and who reported seeking a health care service or professional in the past 15 days. The findings showed some differences in the determinants of drug use in relation to gender, revealing the greater importance of health-related behavior among women.

[meanings Of The Sickening Process For Patients With Systemic Lupus Erythematosus: A Review Of The Literature.]

Systemic lupus erythematosus is an autoimmune disease that causes many psychological repercussions that have been studied through qualitative research. These are considered relevant, since they reveal the amplitude experienced by patients. Given this importance, this study aims to map the qualitative production in this theme, derived from studies of experiences of adult patients of both genders and that had used as a tool a semi-structured interview and/or field observations, and had made use of a sampling by a saturation criterion to determine the number of participants in each study. The survey was conducted in Pubmed, Lilacs, Psycinfo e Cochrane databases, searching productions in English and Portuguese idioms published between January 2005 and June 2012. The 19 revised papers that have dealt with patients in the acute phase of the disease showed themes that were categorized into eight topics that contemplated the experienced process at various stages, from the onset of the disease, extending through the knowledge of the diagnosis and the understanding of the manifestations of the disease, drug treatment and general care, evolution and prognosis. The collected papers also point to the difficulty of understanding, of the patients, on what consists the remission phase, revealing also that this is a clinical stage underexplored by psychological studies.