87 resultados para Pedestrian Behavior.
Resumo:
The objective of this article is to study the problem of pedestrian classification across different light spectrum domains (visible and far-infrared (FIR)) and modalities (intensity, depth and motion). In recent years, there has been a number of approaches for classifying and detecting pedestrians in both FIR and visible images, but the methods are difficult to compare, because either the datasets are not publicly available or they do not offer a comparison between the two domains. Our two primary contributions are the following: (1) we propose a public dataset, named RIFIR , containing both FIR and visible images collected in an urban environment from a moving vehicle during daytime; and (2) we compare the state-of-the-art features in a multi-modality setup: intensity, depth and flow, in far-infrared over visible domains. The experiments show that features families, intensity self-similarity (ISS), local binary patterns (LBP), local gradient patterns (LGP) and histogram of oriented gradients (HOG), computed from FIR and visible domains are highly complementary, but their relative performance varies across different modalities. In our experiments, the FIR domain has proven superior to the visible one for the task of pedestrian classification, but the overall best results are obtained by a multi-domain multi-modality multi-feature fusion.
Resumo:
Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns.
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This research investigates the link between rivalry and unethical behavior. We propose that people will engage in greater unethical behavior when competing against their rivals than when competing against non-rival competitors. Across a series of experiments and an archival study, we find that rivalry is associated with increased use of deception, unsportsmanlike behavior, willingness to employ unethical negotiation tactics, and misreporting of performance. We also explore the psychological underpinnings of rivalry, which help to illuminate how it differs from general competition, and why it increases unethical behavior. Rivalry as compared to non-rival competition was associated with increased status concerns, contingency of self-worth, and performance goals; mediation analyses revealed that performance goals played the biggest role in explaining why rivalry promoted greater unethicality. Lastly, we find that merely thinking about a rival can be enough to promote greater unethical behavior, even in domains unrelated to the rivalry. These findings highlight the importance of rivalry as a widespread, powerful, yet largely unstudied phenomenon with significant organizational implications. Further, the results help to inform when and why unethical behavior occurs within organizations, and demonstrate that the effects of competition are dependent upon relationships and prior interactions.
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Different treatments that could be implemented in the home environ-ment are evaluated with the objective of reaching a more rational and efficient use of energy. We consider that a detailed knowledge of energy-consuming behaviour is paramount for the development and implementation of new technologies, services and even policies that could result in more rational energy use. The proposed evaluation methodology is based on the development of economic experiments implemented in an experimental economics laboratory, where the behaviour of individuals when making decisions related to energy use in the domestic environment can be tested.
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Evidence shows that nutritional and environmental stress stimuli during postnatal period influence brain development and interactions between gut and brain. In this study we show that in rats, prevention of weaning from maternal milk results in depressive-like behavior, which is accompanied by changes in the gut bacteria and host metabolism. Depressive-like behavior was studied using the forced-swim test on postnatal day (PND) 25 in rats either weaned on PND 21, or left with their mother until PND 25 (non-weaned). Non-weaned rats showed an increased immobility time consistent with a depressive phenotype. Fluorescence in situ hybridization showed non-weaned rats to harbor significantly lowered Clostridium histolyticum bacterial groups but exhibit marked stress-induced increases. Metabonomic analysis of urine from these animals revealed significant differences in the metabolic profiles, with biochemical phenotypes indicative of depression in the non-weaned animals. In addition, non-weaned rats showed resistance to stress-induced modulation of oxytocin receptors in amygdala nuclei, which is indicative of passive stress-coping mechanism. We conclude that delaying weaning results in alterations to the gut microbiota and global metabolic profiles which may contribute to a depressive phenotype and raise the issue that mood disorders at early developmental ages may reflect interplay between mammalian host and resident bacteria.
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This paper examines the extent to which engineers can influence the competitive behavior of bidders in Best Value or multi-attribute construction auctions, where both the (dollar) bid and technical non-price criteria are scored according to a scoring rule. From a sample of Spanish construction auctions with a variety of bid scoring rules, it is found that bidders are influenced by the auction rules in significant and predictable ways. The bid score weighting, bid scoring formula and abnormally low bid criterion are variables likely to influence the competitiveness of bidders in terms of both their aggressive/conservative bidding and concentration/dispersion of bids. Revealing the influence of the bid scoring rules and their magnitude on bidders’ competitive behavior opens the door for the engineer to condition bidder competitive behavior in such a way as to provide the balance needed to achieve the owner’s desired strategic outcomes.
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Mechanisms and consequences of the effects of estrogen on the brain have been studied both at the fundamental level and with therapeutic applications in mind. Estrogenic hormones binding in particular neurons in a limbic-hypothalamic system and their effects on the electrophysiology and molecular biology of medial hypothalamic neurons were central in establishing the first circuit for a mammalian behavior, the female-typical mating behavior, lordosis. Notably, the ability of estradiol to facilitate transcription from six genes whose products are important for lordosis behavior proved that hormones can turn on genes in specific neurons at specific times, with sensible behavioral consequences. The use of a gene knockout for estrogen receptor alpha (ERalpha) revealed that homozygous mutant females simply would not do lordosis behavior and instead were extremely aggressive, thus identifying a specific gene as essential for a mammalian social behavior. In dramatic contrast, ERbeta knockout females can exhibit normal lordosis behavior. With the understanding, in considerable mechanistic detail, of how the behavior is produced, now we are also studying brain mechanisms for the biologically adaptive influences which constrain reproductive behavior. With respect to cold temperatures and other environmental or metabolic circumstances which are not consistent with successful reproduction, we are interested in thyroid hormone effects in the brain. Competitive relations between two types of transcription factors - thyroid hormone receptors and estrogen receptors have the potential of subserving the blocking effects of inappropriate environmental circumstances on female reproductive behaviors. TRs can compete with ERalpha both for DNA binding to consensus and physiological EREs and for nuclear coactivators. In the presence of both TRs and ERs, in transfection studies, thyroid hormone coadministration can reduce estrogen-stimulated transcription. These competitive relations apparently have behavioral consequences, as thyroid hormones will reduce lordosis, and a TRbeta gene knockout will increase it. In sum, we not only know several genes that participate in the selective control of this sex behavior, but also, for two genes, we know the causal routes. Estrogenic hormones are also the foci of widespread attention for their potential therapeutic effects improving, for example, certain aspects of mood and cognition. The former has an efficient animal analog, demonstrated by the positive effects of estrogen in the Porsolt forced swim test. The latter almost certainly depends upon trophic actions of estrogen on several fundamental features of nerve cell survival and growth. The hypothesis is raised that the synaptic effects of estrogens are secondary to the trophic actions of this type of hormone in the nucleus and nerve cell body.
Resumo:
The estrogen receptor and glucocorticoid receptor are members of the nuclear receptor superfamily that can signal using both non-genomic and genomic transcriptional modes. Though genomic modes of signaling have been well characterized and several behaviors attributed to this signaling mechanism, the physiological significance of non-genomic modes of signaling has not been well understood. This has partly been due to the controversy regarding the identity of the membrane ER (mER) or membrane GR (mGR) that may mediate rapid, non-genomic signaling and the downstream signaling cascades that may result as a consequence of steroid ligands binding the mER or the mGR. Both estrogens and glucocorticoids exert a number of actions on the hypothalamus, including feedback. This review focuses on the various candidates for the mER or mGR in the hypothalamus and the contribution of non-genomic signaling to classical hypothalamically driven behaviors and changes in neuronal morphology. It also attempts to categorize some of the possible functions of non-genomic signaling at both the cellular level and at the organismal level that are relevant for behavior, including some behaviors that are regulated by both estrogens and glucocorticoids in a potentially synergistic manner. Lastly, it attempts to show that steroid signaling via non-genomic modes may provide the organism with rapid behavioral responses to stimuli.
Resumo:
Melts of ABA triblock copolymer molecules with identical end blocks are examined using self-consistent field theory (SCFT). Phase diagrams are calculated and compared with those of homologous AB diblock copolymers formed by snipping the triblocks in half. This creates additional end segments which decreases the degree of segregation. Consequently, triblock melts remain ordered to higher temperatures than their diblock counterparts. We also find that middle-block domains are easier to stretch than end-block domains. As a result, domain spacings are slightly larger, the complex phase regions are shifted towards smaller A-segment compositions, and the perforated-lamellar phase becomes more metastable in triblock melts as compared to diblock melts. Although triblock and diblock melts exhibit very similar phase behavior, their mechanical properties can differ substantially due to triblock copolymers that bridge between otherwise disconnected A domains. We evaluate the bridging fraction for lamellar, cylindrical, and spherical morphologies to be about 40%–45%, 60%–65%, and 75%–80%, respectively. These fractions only depend weakly on the degree of segregation and the copolymer composition.