The multiple pheromone ant clustering algorithm and its application to real world domains

The Multiple Pheromone Ant Clustering Algorithm (MPACA) models the collective behaviour of ants to find clusters in data and to assign objects to the most appropriate class. It is an ant colony optimisation approach that uses pheromones to mark paths linking objects that are similar and potentially members of the same cluster or class. Its novelty is in the way it uses separate pheromones for each descriptive attribute of the object rather than a single pheromone representing the whole object. Ants that encounter other ants frequently enough can combine the attribute values they are detecting, which enables the MPACA to learn influential variable interactions. This paper applies the model to real-world data from two domains. One is logistics, focusing on resource allocation rather than the more traditional vehicle-routing problem. The other is mental-health risk assessment. The task for the MPACA in each domain was to predict class membership where the classes for the logistics domain were the levels of demand on haulage company resources and the mental-health classes were levels of suicide risk. Results on these noisy real-world data were promising, demonstrating the ability of the MPACA to find patterns in the data with accuracy comparable to more traditional linear regression models. © 2013 Polish Information Processing Society.

Psychological cue use and implications for a clinical decision support system

Effective clinical decision making depends upon identifying possible outcomes for a patient, selecting relevant cues, and processing the cues to arrive at accurate judgements of each outcome's probability of occurrence. These activities can be considered as classification tasks. This paper describes a new model of psychological classification that explains how people use cues to determine class or outcome likelihoods. It proposes that clinicians respond to conditional probabilities of outcomes given cues and that these probabilities compete with each other for influence on classification. The model explains why people appear to respond to base rates inappropriately, thereby overestimating the occurrence of rare categories, and a clinical example is provided for predicting suicide risk. The model makes an effective representation for expert clinical judgements and its psychological validity enables it to generate explanations in a form that is comprehensible to clinicians. It is a strong candidate for incorporation within a decision support system for mental-health risk assessment, where it can link with statistical and pattern recognition tools applied to a database of patients. The symbiotic combination of empirical evidence and clinical expertise can provide an important web-based resource for risk assessment, including multi-disciplinary education and training. © 2002 Informa UK Ltd All rights reserved.

Growing better brains? Pregnancy and neuroscience discourses in English social and welfare policies

In recent years, English welfare and health policy has started to include pregnancy within the foundation stage of child development. The foetus is also increasingly designated as ‘at risk’ from pregnant women. In this article, we draw on an analysis of a purposive sample of English social and welfare policies and closely related advocacy documents to trace the emergence of neuroscientific claims-making in relation to the family. In this article, we show that a specific deterministic understanding of the developing brain that only has a loose relationship with current scientific evidence is an important component in these changes. We examine the ways in which pregnancy is situated in these debates. In these debates, maternal stress is identified as a risk to the foetus; however, the selective concern with women living in disadvantage undermines biological claims. The policy claim of neurological ‘critical windows’ also seems to be influenced by social concerns. Hence, these emerging concerns over the foetus’ developing brain seem to be situated within the gendered history of policing women’s pregnant bodies rather than acting on new insights from scientific discoveries. By situating these developments within the broader framework of risk consciousness, we can link these changes to wider understandings of the ‘at risk’ child and intensified surveillance over family life.

Predictors of client retention in alternative -to -prison substance abuse programs

Increased treatment retention among substance abusing individuals has been associated with reduced drug use, fewer arrests, and decreased unemployment, as well as a reduction in health risk behaviors. This longitudinal study examined the predictors of client retention for alternative to prison substance abuse treatment programs through assessing the roles of motivational factors and the client-worker relationship. The sample was comprised of 141 male felony offenders who were legally mandated to community based long-term residential drug treatment programs. ^ The primary measures used in the study were the consecutive days a participant remained in treatment, Stages of Change Readiness Model and Treatment Eagerness Scale (SOCRATES), the Working Alliance Inventory (WAI), and The Readiness Ruler. Hierarchical multiple regression analysis was conducted for four hypotheses (a) participants who are more motivated to change at the time of entry will remain in treatment longer, (b) participants who have a strong therapeutic alliance will remain in treatment a greater number of consecutive days than participants who have weaker therapeutic alliance, (c) motivation to change, as measured at treatment entry, will be positively related to therapeutic alliance, (d) during the course of treatment variation in motivation to change will be predicted by the therapeutic alliance. ^ Results support the following conclusions: Among clients in alternative-to prison programs the number of days in treatment is positively related to their motivation to change. The therapeutic alliance is not a predictor of the number of days in treatment. Motivation to change, particularly recognition of a drug problem, is positively related to the therapeutic alliance. Changes in motivation to change in response to treatment are positively related to the therapeutic alliance among clients in an alternative to prison substance abuse treatment programs. These results carry forward prior research and have implications for social work practice, research, and social welfare policy. ^

Chlorine contribution to quantitative structure and activity relationship models of disinfection by -products' quantum chemical descriptors and toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

Predictors of client retention in alternative to prison substance abuse programs

Increased treatment retention among substance abusing individuals has been associated with reduced drug use, fewer arrests, and decreased unemployment, as well as a reduction in health risk behaviors. This longitudinal study examined the predictors of client retention for alternative to prison substance abuse treatment programs through assessing the roles of motivational factors and the client-worker relationship. The sample was comprised of 141 male felony offenders who were legally mandated to community based long-term residential drug treatment programs. The primary measures used in the study were the consecutive days a participant remained in treatment, Stages of Change Readiness Model and Treatment Eagerness Scale (SOCRATES), the Working Alliance Inventory (WAI), and The Readiness Ruler. Hierarchical multiple regression analysis was conducted for four hypotheses (a) participants who are more motivated to change at the time of entry will remain in treatment longer, (b) participants who have a strong therapeutic alliance will remain in treatment a greater number of consecutive days than participants who have weaker therapeutic alliance, (c) motivation to change, as measured at treatment entry, will be positively related to therapeutic alliance, (d) during the course of treatment variation in motivation to change will be predicted by the therapeutic alliance. Results support the following conclusions: Among clients in alternative-to prison programs the number of days in treatment is positively related to their motivation to change. The therapeutic alliance is not a predictor of the number of days in treatment. Motivation to change, particularly recognition of a drug problem, is positively related to the therapeutic alliance. Changes in motivation to change in response to treatment are positively related to the therapeutic alliance among clients in an alternative to prison substance abuse treatment programs. These results carry forward prior research and have implications for social work practice, research, and social welfare policy.

Process inventory and pollution prevention overview for the citrus industry

Florida citrus represents approximately 70 percent of the industry production in the United States; therefore, any associated agricultural and industrial contamination is of concern and a focus of attention. The use of synthetic organic chemicals has become a farmer's necessity in order to supply consumers with high quality products, free of pest damage. However, industrial citrus wastes and chemical residual levels worry not only government agencies but also consumers since they indicate a serious habitat risk. This study assesses citrus industrial processes and the paths that chemical substances follow from the time the citrus seed is planted until consumers get a final product as either fresh fruit or processed product. The study is built on information from United States Environmental Protection Agency (US EPA) manuals, Dade County Environmental Resources Management (DERM) inspection records, United States Food and Drug Administration (US FDA) regulations, Florida standards, journal publications, and research reports. Pollution prevention (P2 or prevention-of-pollution) alternatives are identified; alternatives are proposed, evaluated, and included. Strategies are described and pollution prevention opportunities proposed to minimize citrus wastes generation, chemical residuals in products, their environmental impact and health risk aspects while maximizing product quality.

Riscos à saúde dos trabalhadores em unidade de alimentação e nutrição de um Hospital Universitário

The Food and Nutrition Units (FNU) are designed to produce food for healthy and/or sick communities and need to be done in a way to ensure the quality of foodstuffs that were produced. In these units, in the working environment, in general, there is excessive noise, heat and physical condition with many adaptations, presence of obstacles, inadequate flows, as well as the ways of the working organization may represent risks for workers health and lead to errors during production and/or distribution of food. The main goal of this study was to analyse the working processes in the Food Production Unit of the university’s hospital and identify the workers' health risk factors, using for this the knowledge of ergonomics, specifically the method of Ergonomic Work Analysis (EWA). After this analysis it was possible to develop proposals that will bring improvements to the working conditions, minimizing health risk factors during the process of meals production. It’s crucial to reassert this method considers the work activity performed in real time and highlights the importance of listening and the engagement of the workers in the changing process. It is a descriptive research with a qualitative approach. In the field research were collected demographics data, employment characteristics of the individuals (age, education, stocking sector, the total length of service and length of service in the industry) and data related to their usual work (task analysis, activity analysis and Analysis of the working environment) in the FNU. The instruments that were used in this study were document analysis, global and systematic observations and semi structured interviews in order to identify the main complaints related to those activities developed by them. The study was based on data for the analysis of Bardin, 2011, so the documents have been selected and including those that treat issues related to risks to workers' health were selected. The result of semi-structured interviews, global and systematic observations took place a confrontation of this material to the theoretical framework, held the inference and the interpretation of results the light of the knowledge of ergonomics and legislation. Issues related to the risks and the perception of workers has crafted a table showing the frequency of responses to the physical, chemical and biological and even the risk of accidents and was made a descriptive analysis. The results of this analysis indicated that the unit in question presents several problems ambience of jobs, both in terms of physical structure, but also in the organization of work. Non-conformities that leads to a favourable environment to the development of disease and injury hazards and compromising the quality of food produced. It is necessary to comply with legislation and that short, medium and long-term measures are taken to ensure the physical integrity of workers and improve the working environment.

Indicadores e fatores preditivos de uso abusivo de álcool em adultos jovens

The abusive use of alcohol is closely related to dependence and to social and work damages. The main focus of this thesis is to create an instrument about alcohol abuse, in order to differentiate the degree of commitment of the symptomatology, considering its psychosocial factors of prediction. As specific goals: I) characterize the state of the art about assessment related to the abuse and dependence to alcohol; II) investigate and systematize aspects related to the predictive psychosocial factors for alcohol dependence; III) build an instrument for the assessment of alcohol abuse and protection and risk factors for the development of an alcohol dependence; and IV) verify validity evidence of the instrument built for the Brazilian population. In Study I, it was possible to observe the prevalence of articles related to the use of alcohol in a problematic way, without a classification dependence, it is lower than the one of articles that investigate the disease when it is already manifested, not to mention a few systematic studies about the theme of alcohol abuse in the scientific environment. In Study II, focus groups (FGs) were conducted, the analysis about the discourses of the focus groups were made through the ALCESTE software and it was possible to observe a response pattern that existed among the participants in different groups, with the generation of five classes. In Study III, we developed an instrument that contemplated aspects of the Alcohol Dependence Syndrome of the Millon Clinical Multiaxial Inventory-III, in addition to the characteristics defined in Study I and in Study II. The final version of the instrument had 59 items assessed through the likert scale of five points. In Study IV, the administration of the instrument was performed in an online format with university students ranging from 18 to 24 years old, residents in Brazilian metropolitan cities. The results evidenced that the internal consistency of the instrument is considered satisfactory (α = 0,882) and in what it refers to classes, the most significant data was the one related to financial loss and criteria for the diagnosis of alcohol abuse. It is important to consider the evaluative potential of risk and protective factors for the development of alcohol dependence of the instrument as a whole. Once the indicators of abuse and the profile of the abusers has been modified, the patient may have his/her treatment/intervention focused on the trouble and/or specific syndrome, thus having a clear and fast improvement.

Modulating membership grades to gain consensus for fuzzy set uncertainty values in a clinical decision support system

This paper deals with a very important issue in any knowledge engineering discipline: the accurate representation and modelling of real life data and its processing by human experts. The work is applied to the GRiST Mental Health Risk Screening Tool for assessing risks associated with mental-health problems. The complexity of risk data and the wide variations in clinicians' expert opinions make it difficult to elicit representations of uncertainty that are an accurate and meaningful consensus. It requires integrating each expert's estimation of a continuous distribution of uncertainty across a range of values. This paper describes an algorithm that generates a consensual distribution at the same time as measuring the consistency of inputs. Hence it provides a measure of the confidence in the particular data item's risk contribution at the input stage and can help give an indication of the quality of subsequent risk predictions. © 2010 IEEE.

Text-messaging as a Tool for Medication Adherence and Behavior Change in Disease Management among Patients with Coronary Heart Disease

Background: Evidence-based medication and lifestyle modification are important for secondary prevention of cardiovascular disease but are underutilized. Mobile health strategies could address this gap but existing evidence is mixed. Therefore, we piloted a pre-post study to assess the impact of patient-directed text messages as a means of improving medication adherence and modifying major health risk behaviors among coronary heart disease (CHD) patients in Hainan, China.

Methods: 92 CVD patients were surveyed between June and August 2015 (before the intervention) and then between October and December 2015 (after 12 week intervention) about (a) medication use (b) smoking status,(c) fruit and vegetable consumption, and (d) physical activity uptake. Acceptability of text-messaging intervention was assessed at follow-up. Descriptive statistics, along with paired comparisons between the pre and post outcomes were conducted using both parametric (t-test) and non-parametric (Wilcoxon signed rank test) methods.

Results: The number of respondents at follow-up was 82 (89% retention rate). Significant improvements were observed for medication adherence (P<0.001) and for the number of cigarettes smoked per day (P=.022). However there was no change in the number of smokers who quitted smoking at follow-up. There were insignificant changes for physical activity (P=0.91) and fruit and vegetable consumption.

Automated Assessment of Image Quality and Dose Attributes in Clinical CT Images

Computed tomography (CT) is a valuable technology to the healthcare enterprise as evidenced by the more than 70 million CT exams performed every year. As a result, CT has become the largest contributor to population doses amongst all medical imaging modalities that utilize man-made ionizing radiation. Acknowledging the fact that ionizing radiation poses a health risk, there exists the need to strike a balance between diagnostic benefit and radiation dose. Thus, to ensure that CT scanners are optimally used in the clinic, an understanding and characterization of image quality and radiation dose are essential.

The state-of-the-art in both image quality characterization and radiation dose estimation in CT are dependent on phantom based measurements reflective of systems and protocols. For image quality characterization, measurements are performed on inserts imbedded in static phantoms and the results are ascribed to clinical CT images. However, the key objective for image quality assessment should be its quantification in clinical images; that is the only characterization of image quality that clinically matters as it is most directly related to the actual quality of clinical images. Moreover, for dose estimation, phantom based dose metrics, such as CT dose index (CTDI) and size specific dose estimates (SSDE), are measured by the scanner and referenced as an indicator for radiation exposure. However, CTDI and SSDE are surrogates for dose, rather than dose per-se.

Currently there are several software packages that track the CTDI and SSDE associated with individual CT examinations. This is primarily the result of two causes. The first is due to bureaucracies and governments pressuring clinics and hospitals to monitor the radiation exposure to individuals in our society. The second is due to the personal concerns of patients who are curious about the health risks associated with the ionizing radiation exposure they receive as a result of their diagnostic procedures.

An idea that resonates with clinical imaging physicists is that patients come to the clinic to acquire quality images so they can receive a proper diagnosis, not to be exposed to ionizing radiation. Thus, while it is important to monitor the dose to patients undergoing CT examinations, it is equally, if not more important to monitor the image quality of the clinical images generated by the CT scanners throughout the hospital.

The purposes of the work presented in this thesis are threefold: (1) to develop and validate a fully automated technique to measure spatial resolution in clinical CT images, (2) to develop and validate a fully automated technique to measure image contrast in clinical CT images, and (3) to develop a fully automated technique to estimate radiation dose (not surrogates for dose) from a variety of clinical CT protocols.

Extended-release ranolazine: critical evaluation of its use in stable angina.

Coronary heart disease is the major cause of morbidity and mortality throughout the world, and is responsible for approximately one of every six deaths in the US. Angina pectoris is a clinical syndrome characterized by discomfort, typically in the chest, neck, chin, or left arm, induced by physical exertion, emotional stress, or cold, and relieved by rest or nitroglycerin. The main goals of treatment of stable angina pectoris are to improve quality of life by reducing the severity and/or frequency of symptoms, to increase functional capacity, and to improve prognosis. Ranolazine is a recently developed antianginal with unique methods of action. In this paper, we review the pharmacology of ranolazine, clinical trials supporting its approval for clinical use, and studies of its quality of life benefits. We conclude that ranolazine has been shown to be a reasonable and safe option for patients who have refractory ischemic symptoms despite the use of standard medications (for example, nitrates, beta-adrenergic receptor antagonists, and calcium channel antagonists) for treatment of anginal symptoms, and also provides a modestly improved quality of life.

Chlorine Contribution to Quantitative Structure and Activity Relationship Models of Disinfection By-Products' Quantum Chemical Descriptors and Toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: 1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (ELUMO) via QSAR modelling and analysis; 2) to validate the models by using internal and external cross-validation techniques; 3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: 1) Linear or Multi-linear Regression (MLR); 2) Partial Least Squares (PLS); and 3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: 1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; 2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; 3) ELUMO are shown to correlate highly with the NCl for several classes of DBPs; and 4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

Looking for Determinants of Ontological Security in the Spain of the Crisis

The concept of ontological security has a remarkable echo in the current sociology to describe emotional status of men of late modernity. However, the concept created by Giddens in the eighties has been little used in empirical research covering various sources of risk or uncertainty. In this paper, a scale for ontological security is proposed. To do this, we start from the results of a research focused on the relationship between risk, uncertainty and vulnerability in the context of the economic crisis in Spain. These results were produced through nine focus groups and a telephone survey with standardized questionnaire applied to a national sample of 2,408 individuals over 18 years. This work is divided into three main sections. In the fi rst, a scale has been built from the results of the application of different items present in the questionnaire used. The second part explores the relationships of the scale obtained with the variables further approximate the emotional dimensions of individuals. The third part observes the variables that contribute to changes in the scale: These variables show the structural feature of the ontological security.