Ethnicity and incidence of Hodgkin lymphoma in Canadian population

<p>Abstract</p> <p>Background</p> <p>Research has shown that ethnicity is a significant predictor of Hodgkin lymphoma (HL). Variations in cancer incidence among ethnic groups in the same country can lead to important information in the search for etiological factors. Other risk factors important in the etiology of HL are medical history and exposure to pesticides. In this report we investigated the association between ethnicity and HL in the presence of medical history, and exposure to pesticides.</p> <p>Methods</p> <p>The data resulting from a matched population-based case-control study conducted in six provinces of Canada (Ontario, Quebec, Manitoba, Saskatchewan, Alberta, and British Columbia) was analyzed to determine whether or not there was any association between ethnicity and incidence of HL when adjusted for personal medical history and pesticide exposure. Information on ethnicity, personal medical history, and pesticide exposure was collected by questionnaires via mail on 316 men diagnosed with HL; and on 1506 controls. A conditional logistic regression was utilized and results were presented as odds ratios and 95% confidence intervals.</p> <p>Results</p> <p>In our study population, the distribution of ethnic groups was: 38.5% North American, 15% British, 8.4% Western European, 8.2% Eastern European, 1.7% Asian, 1.4% Scandinavian and 27% of other ethnic origin. Compared to North Americans (i) the risk of HL was greater among the Eastern European descendents (Odds Ratio (OR_adj): 1.82; 95% confidence interval (CI): 1.02, 3.25) and Western European (OR_adj: 1.62; 95% CI: 0.95–2.76) descent population (borderline significance at 5% level); and (ii) the risk of HL was lower in Asian descents. Diagnosis with measles (OR_adj: 0.72, 95% C.I.: 0.53–0.98) and/or positive history of allergy desensitization shots (OR_adj: 0.55, 95% C.I.: 0.30–0.99) were negatively associated with the incidence of HL, while diagnosis with acne (OR_adj: 2.12, 95% C.I.: 1.19–3.78), shingles (OR_adj: 2.41, 95% C.I.: 1.38–4.22) and positive family history of cancer (OR_adj: 1.93, 95% C.I.: 1.40–2.65) increased the risk of HL. Exposure to individual herbicide dichlorprop showed an increased risk of HL (OR_adj: 6.35, 95% C.I.: 1.56–25.92).</p> <p>Conclusion</p> <p>In Canada, compared to North Americans descendents, the risk of HL was significantly greater among the Eastern European and Western European descent population. Our results related to association between ethnicity and HL support the findings reported by other researchers. Our data showed that subjects who were diagnosed with measles or had allergy desensitization shots negatively associated with the incidence of HL; and other medical conditions, ever diagnosed with acne, and positive family history of cancer were positively associated with the incidence of HL.</p

An Evaluation of Human Conversational Preferences in Social Human-Robot Interaction

To generate context-aware behaviors in robots, robots are required to have a careful evaluation of its encounters with humans. Unwrapping emotional hints in observable cues in an encounter will improve a robot’s etiquettes in a social encounter. This article presents an extended human study conducted to examine how several factors in an encounter influence a person’s preferences upon an interaction at a particular moment. We analyzed the nature of conversation preferred by a user considering the type of conversation a robot could have with its user, having the interaction initiated by the robot itself. We took an effort to explore how such preferences differ as the factors present in the surrounding alter. A social robot equipped with the capability to initiate a conversation is deployed to conduct the study by means of a wizard-of-oz (WoZ) experiment. During this study, conversational preferences of users could vary from “no interaction at all” to a “long conversation.” We changed three factors in an encounter which can be different from each other in each circumstance: the audience or outsiders in the environment, user’s task, and the domestic area in which the interaction takes place. Conversational preferences of users within the abovementioned conditions were analyzed in a later stage, and critical observations are highlighted. Finally, implications that could be helpful in shaping future social human-robot encounters were derived from the analysis of the results

Smart Metering Design and Applications

XII, 141 p. 67 illus., 40 illus. in color.online

Hybrid Navigation Decision Control Mechanism for Intelligent Wheel-Chair

The continuous rising of the elderly/disabled population has created a requirement for assistive robotics devices to counter the lack of trustworthy servants. Intelligent Wheelchairs are developed for that particular purpose. Intelligent Wheelchairs differ depending on the interactive modality and most commonly found modalities are speech-controlled. Since these are assistive devices that need to act as human companions, it is necessary to have a dialogue between the device and the user. Even though the wheelchair is fully automated, the user should have control over it at some point. However, this exchange of control should be intelligent and transitions need to be executed in order to safeguard the user. Therefore the purpose of this paper is to propose an intelligent system that would navigate an intelligent voice-controlled wheelchair facilitating the intelligent exchange of control between the user and the wheelchair. This control is not simultaneous and one can override the other only when navigation could lead to collisions. In the proposed method, users can control the wheelchair using fixed vocal commands, and execution of those commands will be performed using the spatial and control parameters. Control of the wheelchair will be exchanged between the user and the wheelchair itself considering specific parameters such as obstacle distance, collision time, the velocity of the wheelchair among others. User control mode has 5 definite vocal commands with classifiers to identify any navigation command into the command model and considers uncertain terms such as &#x2018;little&#x2019; and &#x2018;hard&#x2019; for &#x2018;Turn&#x2019; commands. Command classification had produced a Cohen&#x2019;s Kappa value of 0.9462 and the classifier for the uncertain terms had produced a Cohen&#x2019;s Kappa value of 0.7325. Both were acceptable values for those particular classifications. As per the experiment results, the proposed system reduced the vocal command frequency and risk of collisions through proper control of the velocity levels and intelligent exchange of control at given locations

Understanding uncertain information in vocal description for creating virtual spatial maps

Assistive robots are developed for supporting daily activities of elderly people to uplift the living standards. The assistive robots should be friendly, reliable, active, and comprehensible in order to satisfy the needs of elderly population. Human activities are frequently related to navigational tasks and human tend to use descriptions which include natural language phrases and uncertain terms such as “near”, “little”, “far”, “small”, “large”, “close”to describe about spatial information. Therefore assistive robots should be capable of analysing and understanding descriptions which contain natural language phrases with uncertain terms and creating a conceptual map for effective navigation. This paper proposes a method to understand spatial information in a description with uncertain terms and creates a conceptual map in a robot memory which can be linked with spatial map for purposeful, effective and human friendly navigation task. Human studies have been carried out to study different types of descriptions related to navigation tasks. The Virtual Spatial Data Identifier (VSDI) and Uncertain Term Identifier (UTI) modules have been introduced in order to evaluate the spatial information in description to create a virtual map. Results of the system have been compared with the results of a human study in order to evaluate performance of the proposed system

An Intelligent Gesture Classification Model for Domestic Wheelchair Navigation with Gesture Variance Compensation

Elderly and disabled population is rapidly increasing. It is important to uplift their living standards by improving the confidence towards daily activities. Navigation is an important task, most elderly and disabled people need assistance with. Replacing human assistance with an intelligent system which is capable of assisting human navigation via wheelchair systems is an effective solution. Hand gestures are often used in navigation systems. However, those systems do not possess the capability to accurately identify gesture variances. Therefore, this paper proposes a method to create an intelligent gesture classification system with a gesture model which was built based on human studies for every essential motion in domestic navigation with hand gesture variance compensation capability. Experiments have been carried out to evaluate user remembering and recalling capability and adaptability towards the gesture model. Dynamic Gesture Identification Module (DGIM), Static Gesture Identification Module (SGIM), and Gesture Clarifier (GC) have been introduced in order to identify gesture commands. The proposed system was analyzed for system accuracy and precision using results of the experiments conducted with human users. Accuracy of the intelligent system was determined with the use of confusion matrix. Further, those results were analyzed using Cohen’s kappa analysis in which overall accuracy, misclassification rate, precision, and Cohen’s kappa values were calculated

Multilocus sequence typing reveals diverse known and novel genotypes of Leptospira spp. circulating in Sri Lanka.

BackgroundLeptospirosis has gained much attention in Sri Lanka since its large outbreak in 2008. However, most of the cases were clinically diagnosed and information on Leptospira genotypes and serotypes currently prevailing in the country is lacking.Methodology/principal findingsWe retrospectively analyzed 24 Leptospira strains from human patients as well as isolated and characterized three Leptospira strains from black rats using the microscopic agglutination test with antisera for 19 serovars and multilocus sequence typing. The isolates were identified as Leptospira borgpetersenii sequence types (STs) 143 and 144; L. interrogans STs 30, 34, 43, 44, 74, 75, 80, 308, 313, 314, 316, and 317; and L. kirschneri ST318. Six of the 15 STs were identified for the first time in this study. Five serogroups such as Autumnalis, Grippotyphosa, Hebdomadis, Javanica, and Pyrogenes were detected among the isolates. Contrary to previous studies, various genotypes including novel STs were isolated during an outbreak in Southern Province. L. borgpetersenii serogroup Javanica ST143 was isolated both from a human and black rat.Conclusions/significanceThis study revealed that genetically diverse Leptospira strains currently circulate in Sri Lanka: some genotypes have been circulating and others have emerged recently, which may explain the recent surge of leptospirosis patients with varying clinical manifestations and frequent outbreaks of leptospirosis. Black rats were identified as the source of infection for humans, but reservoir animals for other genotypes remain unknown