Power of Criminal Attractors: Modeling the Pull of Activity Nodes

The spatial distribution of crime has been a long-standing interest in the field of criminology. Research in this area has shown that activity nodes and travel paths are key components that help to define patterns of offending. Little research, however, has considered the influence of activity nodes on the spatial distribution of crimes in crime neutral areas - those where crimes are more haphazardly dispersed. Further, a review of the literature has revealed a lack of research in determining the relative strength of attraction that different types of activity nodes possess based on characteristics of criminal events in their immediate surrounds. In this paper we use offenders' home locations and the locations of their crimes to define directional and distance parameters. Using these parameters we apply mathematical structures to define rules by which different models may behave to investigate the influence of activity nodes on the spatial distribution of crimes in crime neutral areas. The findings suggest an increasing likelihood of crime as a function of geometric angle and distance from an offender's home location to the site of the criminal event. Implications of the results are discussed.Crime Attractor, Directionality of Crime, Mathematical Modeling, Computational Criminology

A sequence of factorizable subgroups

Let G be a non-abelian non-simple group. In this article the group G such that G=MCG(M) will be studied, where M is a proper maximal subgroup of G and CG(M) is the centralizer of M in G

Social Interactions of Eating Behaviour among High School Students: A Cellular Automata Approach

BACKGROUND:Overweight and obesity in children and adolescents is a global epidemic posing problems for both developed and developing nations. The prevalence is particularly alarming in developed nations, such as the United States, where approximately one in three school-aged adolescents (ages 12-19) are overweight or obese. Evidence suggests that weight gain in school-aged adolescents is related to energy imbalance exacerbated by the negative aspects of the school food environment, such as presence of unhealthy food choices. While a well-established connection exists between the food environment, presently there is a lack of studies investigating the impact of the social environment and associated interactions of school-age adolescents. This paper uses a mathematical modelling approach to explore how social interactions among high school adolescents can affect their eating behaviour and food choice.METHODS:In this paper we use a Cellular Automata (CA) modelling approach to explore how social interactions among school-age adolescents can affect eating behaviour, and food choice. Our CA model integrates social influences and transition rules to simulate the way individuals would interact in a social community (e.g., school cafeteria). To replicate these social interactions, we chose the Moore neighbourhood which allows all neighbours (eights cells in a two-dimensional square lattice) to influence the central cell. Our assumption is that individuals belong to any of four states; Bring Healthy, Bring Unhealthy, Purchase Healthy, and Purchase Unhealthy, and will influence each other according to parameter settings and transition rules. Simulations were run to explore how the different states interact under varying parameter settings.RESULTS:This study, through simulations, illustrates that students will change their eating behaviour from unhealthy to healthy as a result of positive social and environmental influences. In general, there is one common characteristic of changes across time; students with similar eating behaviours tend to form groups, represented by distinct clusters. Transition of healthy and unhealthy eating behaviour is non-linear and a sharp change is observed around a critical point where positive and negative influences are equal.CONCLUSIONS:Conceptualizing the social environment of individuals is a crucial step to increasing our understanding of obesogenic environments of high-school students, and moreover, the general population. Incorporating both contextual, and individual determinants found in real datasets, in our model will greatly enhance calibration of future models. Complex mathematical modelling has a potential to contribute to the way public health data is collected and analyzed

Analyzing The Impact Of Social Factors On Homelessness: A Fuzzy Cognitive Map Approach

Background The forces which affect homelessness are complex and often interactive in nature. Social forces such as addictions, family breakdown, and mental illness are compounded by structural forces such as lack of available low-cost housing, poor economic conditions, and insufficient mental health services. Together these factors impact levels of homelessness through their dynamic relations. Historic models, which are static in nature, have only been marginally successful in capturing these relationships. Methods Fuzzy Logic (FL) and fuzzy cognitive maps (FCMs) are particularly suited to the modeling of complex social problems, such as homelessness, due to their inherent ability to model intricate, interactive systems often described in vague conceptual terms and then organize them into a specific, concrete form (i.e., the FCM) which can be readily understood by social scientists and others. Using FL we converted information, taken from recently published, peer reviewed articles, for a select group of factors related to homelessness and then calculated the strength of influence (weights) for pairs of factors. We then used these weighted relationships in a FCM to test the effects of increasing or decreasing individual or groups of factors. Results of these trials were explainable according to current empirical knowledge related to homelessness. Results Prior graphic maps of homelessness have been of limited use due to the dynamic nature of the concepts related to homelessness. The FCM technique captures greater degrees of dynamism and complexity than static models, allowing relevant concepts to be manipulated and interacted. This, in turn, allows for a much more realistic picture of homelessness. Through network analysis of the FCM we determined that Education exerts the greatest force in the model and hence impacts the dynamism and complexity of a social problem such as homelessness. Conclusions The FCM built to model the complex social system of homelessness reasonably represented reality for the sample scenarios created. This confirmed that the model worked and that a search of peer reviewed, academic literature is a reasonable foundation upon which to build the model. Further, it was determined that the direction and strengths of relationships between concepts included in this map are a reasonable approximation of their action in reality. However, dynamic models are not without their limitations and must be acknowledged as inherently exploratory

Erythroderma: A clinical study of 97 cases

BACKGROUND: Erythroderma is a rare skin disorder that may be caused by a variety of underlying dermatoses, infections, systemic diseases and drugs. METHODS: We reviewed the clinical, laboratory and biopsy material of 97 patients diagnosed with erythroderma who were treated in our department over a 6-year period (1996 through 2002). RESULTS: The male-female ratio was 1.85:1. The mean age at diagnosis was 46.2 years. The most common causative factors were dermatoses (59.7%), followed by drug reactions (21.6%), malignancies (11.3%) and idiopathic causes (7.2%). Carbamazepine was the most common drug (57.1%). The best clinicopathologic correlation was found in cutaneous T-cell lymphoma and pityriasis rubra pilaris related erythroderma. Apart from scaling and erythema that were present in all patients, pruritus was the most common finding (97.5%), followed by fever (33.6%), lymphadenopathy (21.3%), edema (14.4%) and hyperkeratosis (7.2%). CONCLUSION: This study outlines that underlying etiologic factors of erythroderma may show geographic variations. Our series had a high percentage of erythroderma secondary to preexisting dermatoses and a low percentage of idiopathic cases. There was no HIV-infected patient among our series based on multiple serum antibody tests. The clinical features of erythroderma were identical, irrespective of the etiology. The onset of the disease was usually insidious except in drug-induced erythroderma, where it was acute. The group associated with the best prognosis was that related to drugs

Integrated Circuits and Systems for a Fully-Flexible Wireless Ambulatory EEG Monitoring and Diagnostics Headband

This thesis presents the design, development, and experimental characterization of wireless integrated circuits and systems built for ambulatory electroencephalography (EEG) monitoring and diagnostics. Two prototypes are presented. The first one is a 3x4 mm2 integrated circuit (IC), designed and fabricated in a 130nm CMOS technology, and integrates eight recording channels. A novel analog circuit is employed in each channel that detects and removes motion artifacts during amplification, resulting in a clean EEG prior to digitization. The idea prevents the amplifier saturation and removes the need for post processing of the digitized signals using artifact pattern recognition algorithms. The second prototype is an integrated system in the form of a fully-flexible wearable wireless medical device. It integrates eight motion-resilient, active-electrode recording channels, with inter-digitated non-contact electrodes embedded into each of them, all implemented on a 4-layer polyimide flexible substrate, yielding the smallest form factor reported for a wearable EEG device. The flexible main board is connected to a 13x17 mm2 rigid printed circuit board that hosts a low-power FPGA and a BLE 5.0 transceiver, which add diagnostic capability and wireless operation features to the device, respectively. The entire wearable solution with the battery weighs 9.2 grams