850 resultados para Analyzing human behavior


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Human saliva mirrors body’s health and well-being and many of the biomolecules present in blood or urine can also be found in salivary secretions. However, biomolecular concentrations in saliva are usually one tenth to one thousandth of the levels in blood (Pfaffe et al., 2011). Sensitive detection technology platforms are therefore required to detect biomolecules in saliva. Another road block to the advancement of salivary diagnostics is the lack of information related to healthy state saliva vs. a diseased saliva, baseline levels and reference ranges and diurnal variations. Saliva has numerous advantages over blood or urine as a diagnostic fluid: (a) the non-invasive nature of sample collection and the simple, safe, painless and cost-effective methods to collect it; (b) unskilled personnel can collect saliva samples at multiple time points; and (c) the total protein concentration is approximately a quarter of that is present in plasma, which makes it easier to investigate low abundance proteins (Pfaffe et al., 2011). Currently, saliva assays are routinely used to determine, diseases such as HIV, drugs and substances of abuse to provide information on exposure and give qualitative information on the type of illicit drug used (Kintz et al., 2009), cortisol levels for diagnosing Cushing’s syndrome (Doi et al., 2008), and use for biomonitoring of exposure to chemicals (Caporossi et al., 2010) to measure hormones (Gröschl, 2009)....

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Purpose: To determine the relative contributions of rods, cones and melanopsin to pupil responses in humans using temporal sinusoidal stimulation for light levels spanning the low mesopic to photopic range. Methods: A four-primary Ganzfeld photostimulator controlled flicker stimulations at seven light levels (-2.7 to 2 log cd/m2) and five frequencies (0.5 to 8Hz). Pupil diameter was measured using a high-resolution eyetracker. Three kinds of sinusoidal photoreceptor modulations were generated using silent substitution: 1) rod modulation, 2) cone modulation, and 3) combined rod and cone modulation in phase (Experiment 1) or phase shifted (Experiment 2) from a fixed rod phase. The melanopsin excitation was computed for each condition. A vector sum model was used to estimate the relative contribution of rods, cones and melanopsin to the pupil response. Results: From Experiment 1, the pupil frequency response peaked at 1Hz at two mesopic light levels for the three modulation conditions. Analyzing the rod-cone phase difference for the combined modulations (Experiment 2) identified a V-shaped response amplitude with a minimum between 135° and 180°. The pupil response phases increased as cone modulation phase increased. The pupil amplitude increased with increasing light level for cone and combined in-phase rod and cone modulation, but not for the rod modulation. Conclusions: These results demonstrate that cone- and rod-pathway contributions are more predominant than melanopsin contribution to the phasic pupil response. The combined rod, cone and melanopsin inputs to the phasic state of the pupil light reflex follow linear summation.

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Over the last few years, investigations of human epigenetic profiles have identified key elements of change to be Histone Modifications, stable and heritable DNA methylation and Chromatin remodeling. These factors determine gene expression levels and characterise conditions leading to disease. In order to extract information embedded in long DNA sequences, data mining and pattern recognition tools are widely used, but efforts have been limited to date with respect to analyzing epigenetic changes, and their role as catalysts in disease onset. Useful insight, however, can be gained by investigation of associated dinucleotide distributions. The focus of this paper is to explore specific dinucleotides frequencies across defined regions within the human genome, and to identify new patterns between epigenetic mechanisms and DNA content. Signal processing methods, including Fourier and Wavelet Transformations, are employed and principal results are reported.

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Human factors such as distraction, fatigue, alcohol and drug use are generally ignored in car-following (CF) models. Such ignorance overestimates driver capability and leads to most CF models’ inability in realistically explaining human driving behaviors. This paper proposes a novel car-following modeling framework by introducing the difficulty of driving task measured as the dynamic interaction between driving task demand and driver capability. Task difficulty is formulated based on the famous Task Capability Interface (TCI) model, which explains the motivations behind driver’s decision making. The proposed method is applied to enhance two popular CF models: Gipps’ model and IDM, and named as TDGipps and TDIDM respectively. The behavioral soundness of TDGipps and TDIDM are discussed and their stabilities are analyzed. Moreover, the enhanced models are calibrated with the vehicle trajectory data, and validated to explain both regular and human factor influenced CF behavior (which is distraction caused by hand-held mobile phone conversation in this paper). Both the models show better performance than their predecessors, especially in presence of human factors.

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Due to anatomical and biomechanical similarities to human shoulder, kangaroo was chosen as a model to study shoulder cartilage. Comprehensive enzymatic degradation and indentation tests were applied on kangaroo shoulder cartilage to study mechanisms underlying its strain-rate-dependent mechanical behavior. We report that superficial collagen plays a more significant role than proteoglycans in facilitating strain-rate-dependent behavior of kangaroo shoulder cartilage. By comparing the mechanical properties of degraded and normal cartilages it was noted that proteoglycan and collagen degradation significantly compromised strain-rate-dependent mechanical behavior of the cartilage. Superficial collagen contributed equally to the tissue behavior at all strain-rates. This is different to studies reported on knee cartilage and confirms the importance of superficial collagen on shoulder cartilage mechanical behavior. A porohyperelastic numerical model also indicated that collagen disruption would lead to faster damage of the shoulder cartilage than when proteoglycans are depleted.

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Solid–interstitial fluid interaction, which depends on tissue permeability, is significant to the strain-rate-dependent mechanical behavior of humeral head (shoulder) cartilage. Due to anatomical and biomechanical similarities to that of the human shoulder, kangaroos present a suitable animal model. Therefore, indentation experiments were conducted on kangaroo shoulder cartilage tissues from low (10−4/s) to moderately high (10−2/s) strain-rates. A porohyperelastic model was developed based on the experimental characterization; and a permeability function that takes into account the effect of strain-rate on permeability (strain-rate-dependent permeability) was introduced into the model to investigate the effect of rate-dependent fluid flow on tissue response. The prediction of the model with the strain-rate-dependent permeability was compared with those of the models using constant permeability and strain-dependent permeability. Compared to the model with constant permeability, the models with strain-dependent and strain-rate-dependent permeability were able to better capture the experimental variation at all strain-rates (p<0.05). Significant differences were not identified between models with strain-dependent and strain-rate-dependent permeability at strain-rate of 5×10−3/s (p=0.179). However, at strain-rate of 10−2/s, the model with strain-rate-dependent permeability was significantly better at capturing the experimental results (p<0.005). The findings thus revealed the significance of rate-dependent fluid flow on tissue behavior at large strain-rates, which provides insights into the mechanical deformation mechanisms of cartilage tissues.

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Introduction Decreased water displacement following increased neural activity has been observed using diffusion-weighted functional MRI (DfMRI) at high b-values. The physiological mechanisms underlying the diffusion signal change may be unique from the standard blood oxygenation level-dependent (BOLD) contrast and closer to the source of neural activity. Whether DfMRI reflects neural activity more directly than BOLD outside the primary cerebral regions remains unclear. Methods Colored and achromatic Mondrian visual stimuli were statistically contrasted to functionally localize the human color center Area V4 in neurologically intact adults. Spatial and temporal properties of DfMRI and BOLD activation were examined across regions of the visual cortex. Results At the individual level, DfMRI activation patterns showed greater spatial specificity to V4 than BOLD. The BOLD activation patterns were more prominent in the primary visual cortex than DfMRI, where activation was localized to the ventral temporal lobe. Temporally, the diffusion signal change in V4 and V1 both preceded the corresponding hemodynamic response, however the early diffusion signal change was more evident in V1. Conclusions DfMRI may be of use in imaging applications implementing cognitive subtraction paradigms, and where highly precise individual functional localization is required.

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- Objective Driver sleepiness is a major crash risk factor, but may be under-recognized as a risky driving behavior. Sleepy driving is usually rated as less of a road safety issue than more well-known risky driving behaviors, such as drink driving and speeding. The objective of this study was to compare perception of crash risk of sleepy driving, drink driving, and speeding. - Methods In total, 300 Australian drivers completed a questionnaire that assessed crash risk perceptions for sleepy driving, drink driving, and speeding. Additionally, the participants perception of crash risk was assessed for five different contextual scenarios that included different levels of sleepiness (low, high), driving duration (short, long), and time of day/circadian influences (afternoon, night-time) of driving. - Results The analysis confirmed that sleepy driving was considered a risky driving behavior, but not as risky as high levels of speeding (p < .05). Yet, the risk of crashing at 4 am was considered as equally risky as low levels of speeding (10 km over the limit). The comparisons of the contextual scenarios revealed driving scenarios that would arguably be perceived as quite risky due to time of day/circadian influences were not reported as high risk. - Conclusions The results suggest a lack of awareness or appreciation of circadian rhythm functioning, particularly the descending phase of circadian rhythm that promotes increased sleepiness in the afternoon and during the early hours of the morning. Yet, the results suggested an appreciation of the danger associated with long distance driving and driver sleepiness. Further efforts are required to improve the community’s awareness of the impairing effects from sleepiness and in particular, knowledge regarding the human circadian rhythm and the increased sleep propensity during the circadian nadir.

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Humans are a social species with the internal capability to process social information from other humans. To understand others behavior and to react accordingly, it is necessary to infer their internal states, emotions and aims, which are conveyed by subtle nonverbal bodily cues such as postures, gestures, and facial expressions. This thesis investigates the brain functions underlying the processing of such social information. Studies I and II of this thesis explore the neural basis of perceiving pain from another person s facial expressions by means of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG). In Study I, observing another s facial expression of pain activated the affective pain system (previously associated with self-experienced pain) in accordance with the intensity of the observed expression. The strength of the response in anterior insula was also linked to the observer s empathic abilities. The cortical processing of facial pain expressions advanced from the visual to temporal-lobe areas at similar latencies (around 300 500 ms) to those previously shown for emotional expressions such as fear or disgust. Study III shows that perceiving a yawning face is associated with middle and posterior STS activity, and the contagiousness of a yawn correlates negatively with amygdalar activity. Study IV explored the brain correlates of interpreting social interaction between two members of the same species, in this case human and canine. Observing interaction engaged brain activity in very similar manner for both species. Moreover, the body and object sensitive brain areas of dog experts differentiated interaction from noninteraction in both humans and dogs whereas in the control subjects, similar differentiation occurred only for humans. Finally, Study V shows the engagement of the brain area associated with biological motion when exposed to the sounds produced by a single human being walking. However, more complex pattern of activation, with the walking sounds of several persons, suggests that as the social situation becomes more complex so does the brain response. Taken together, these studies demonstrate the roles of distinct cortical and subcortical brain regions in the perception and sharing of others internal states via facial and bodily gestures, and the connection of brain responses to behavioral attributes.

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Human growth and attained height are determined by a combination of genetic and environmental effects and in modern Western societies > 80% of the observed variation in height is determined by genetic factors. Height is a fundamental human trait that is associated with many socioeconomic and psychosocial factors and health measures, however little is known of the identity of the specific genes that influence height variation in the general population. This thesis work aimed to identify the genetic variants that influence height in the general population by genome-wide linkage analysis utilizing large family samples. The study focused on analysis of three separate sets of families consisting of: 1) 1,417 individuals from 277 Finnish families (FinnHeight), 2) 8,450 individuals from 3,817 families from Australia and Europe (EUHeight) and 3) 9,306 individuals from 3,302 families from the United States (USHeight). The most significant finding in this study was found in the Finnish family sample where we a locus in the chromosomal region 1p21 was linked to adult height. Several regions showed evidence for linkage in the Australian, European and US families with 8q21 and 15q25 being the most significant. The region on 1p21 was followed up with further studies and we were able to show that the collagen 11-alpha-1 gene (COL11A1) residing at this location was associated with adult height. This association was also confirmed in an independent Finnish population cohort (Health 2000) consisting of 6,542 individuals. From this population sample, we estimated that homozygous males and females for this gene variant were 1.1 and 0.6 cm taller than the respective controls. In this thesis work we identified a gene variant in the COL11A1 gene that influences human height, although this variant alone explains only 0.1% of height variation in the Finnish population. We also demonstrated in this study that special stratification strategies such as performing sex-limited analyses, focusing on dizygous twin pairs, analyzing ethnic groups within a population separately and utilizing homogenous populations such as the Finns can improve the statistical power of finding QTL significantly. Also, we concluded from the results of this study that even though genetic effects explain a great proportion of height variance, it is likely that there are tens or even hundreds of genes with small individual effects underlying the genetic architecture of height.

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This thesis presents methods for locating and analyzing cis-regulatory DNA elements involved with the regulation of gene expression in multicellular organisms. The regulation of gene expression is carried out by the combined effort of several transcription factor proteins collectively binding the DNA on the cis-regulatory elements. Only sparse knowledge of the 'genetic code' of these elements exists today. An automatic tool for discovery of putative cis-regulatory elements could help their experimental analysis, which would result in a more detailed view of the cis-regulatory element structure and function. We have developed a computational model for the evolutionary conservation of cis-regulatory elements. The elements are modeled as evolutionarily conserved clusters of sequence-specific transcription factor binding sites. We give an efficient dynamic programming algorithm that locates the putative cis-regulatory elements and scores them according to the conservation model. A notable proportion of the high-scoring DNA sequences show transcriptional enhancer activity in transgenic mouse embryos. The conservation model includes four parameters whose optimal values are estimated with simulated annealing. With good parameter values the model discriminates well between the DNA sequences with evolutionarily conserved cis-regulatory elements and the DNA sequences that have evolved neutrally. In further inquiry, the set of highest scoring putative cis-regulatory elements were found to be sensitive to small variations in the parameter values. The statistical significance of the putative cis-regulatory elements is estimated with the Two Component Extreme Value Distribution. The p-values grade the conservation of the cis-regulatory elements above the neutral expectation. The parameter values for the distribution are estimated by simulating the neutral DNA evolution. The conservation of the transcription factor binding sites can be used in the upstream analysis of regulatory interactions. This approach may provide mechanistic insight to the transcription level data from, e.g., microarray experiments. Here we give a method to predict shared transcriptional regulators for a set of co-expressed genes. The EEL (Enhancer Element Locator) software implements the method for locating putative cis-regulatory elements. The software facilitates both interactive use and distributed batch processing. We have used it to analyze the non-coding regions around all human genes with respect to the orthologous regions in various other species including mouse. The data from these genome-wide analyzes is stored in a relational database which is used in the publicly available web services for upstream analysis and visualization of the putative cis-regulatory elements in the human genome.

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Chlamydia trachomatis is the most common bacterial sexually transmitted pathogen worldwide. Infection can result in serious reproductive pathologies, including pelvic inflammatory disease, ectopic pregnancy, and infertility, in women. However, the processes that result in these reproductive pathologies have not been well defined. Here we review the evidence for the human disease burden of these chlamydial reproductive pathologies. We then review human-based evidence that links Chlamydia with reproductive pathologies in women. We present data supporting the idea that host, immunological, epidemiological, and pathogen factors may all contribute to the development of infertility. Specifically, we review the existing evidence that host and pathogen genotypes, host hormone status, age of sexual debut, sexual behavior, coinfections, and repeat infections are all likely to be contributory factors in development of infertility. Pathogen factors such as infectious burden, treatment failure, and tissue tropisms or ascension capacity are also potential contributory factors. We present four possible processes of pathology development and how these processes are supported by the published data. We highlight the limitations of the evidence and propose future studies that could improve our understanding of how chlamydial infertility in women occurs and possible future interventions to reduce this disease burden.

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The First International Workshop on Behavior Change Support Systems attracted a great research interest. The selected papers focused on abstraction, implementation and evaluation of Behavior Change Support Systems. The workshop is an evidence of how researchers from around the globe have their own perspective of behavior change interventions. In this abstract, we have attempted to outline core issues that can enhance persuasiveness of such support systems. Finally, we highlight important research questions relating to the development of effective Behavior Change Support Systems.

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Human age is surrounded by assumed set of rules and behaviors imposed by local culture and the society they live in. This paper introduces software that counts the presence of a person on the Internet and examines the activities he/she conducts online. The paper answers questions such as how "old" are you on the Internet? How soon will a newbie be exposed to adult websites? How long will it take for a new Internet user to know about social networking sites? And how many years a user has to surf online to celebrate his/her first "birthday" of Internet presence? Paper findings from a database of 105 school and university students containing their every click of first 24 hours of Internet usage are presented. The findings provide valuable insights for Internet Marketing, ethics, Internet business and the mapping of Internet life with real life. Privacy and ethical issues related to the study have been discussed at the end. © Springer Science+Business Media B.V. 2010.

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Cancer is a leading cause of death worldwide and the total number of cancer cases continues to increase. Many cancers, for example sinonasal cancer and lung cancer, have clear external risk factors and so are potentially preventable. The occurrence of sinonasal cancer is strongly associated with wood dust exposure and the main risk factor for lung cancer is tobacco smoking. Although the molecular mechanisms involved in lung carcinogenesis have been widely studied, very little is known about the molecular changes leading to sinonasal cancer. In this work, mutations in the tumour suppressor TP53 gene in cases of sinonasal cancer and lung cancer and the associations of these mutations with exposure factors were studied. In addition, another important mechanism in many cancers, inflammation, was explored by analyzing the expression of the inflammation related enzyme, COX-2, in sinonasal cancer. The results demonstrate that TP53 mutations are frequent in sinonasal cancer and lung cancer and in both cancers they are associated with exposure. In sinonasal cancer, the occurrence of TP53 mutation significantly increased in relation to long duration and high level of exposure to wood dust. Smoking was not associated with the overall occurrence of the TP53 mutation in sinonasal cancer, but was associated with multiple TP53 mutations. Furthermore, inflammation appears to play a part in sinonasal carcinogenesis as indicated by our results showing that the expression of COX-2 was associated with adenocarcinoma type of tumours, wood dust exposure and non-smoking. In lung cancer, we detected statistically significant associations between TP53 mutations and duration of smoking, gender and histology. We also found that patients with a tumour carrying a G to T transversion, a mutation commonly found in association with tobacco smoking, had a high level of smoking-related bulky DNA adducts in their non-tumorous lung tissue. Altogether, the information on molecular changes in exposure induced cancers adds to the observations from epidemiological studies and helps to understand the role and impact of different etiological factors, which in turn can be beneficial for risk assessment and prevention.