A multi-criteria decision support system for a routing problem in waste collection

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Continuous monitoring of concrete mechanical properties since an early age to support construction phasing

The assessment of concrete mechanical properties during construction of concrete structures is of paramount importance for many intrinsic operations. However many of the available non-destructive methods for mechanical properties have limitations for use in construction sites. One of such methodologies is EMM-ARM, which is a variant of classic resonant frequency methods. This paper aims to demonstrate the efforts towards in-situ applicability of EMMARM, as to provide real-time information about concrete mechanical properties such as E-modulus and compressive strength. To achieve the aforementioned objective, a set of adaptations to the method have been successfully implemented and tested: (i) the reduction of the beam span; (ii) the use of a different mould material and (iii) a new support system for the beams. Based on these adaptations, a reusable mould was designed to enable easier systematic use of EMMARM. A pilot test was successfully performed under in-situ conditions during a bridge construction.

A decision support system for a waste collection vehicle routing problem

The selective collection of municipal solid waste for recycling is a very complex and expensive process, where a major issue is to perform cost-efficient waste collection routes. Despite the abundance of commercially available software for fleet management, they often lack the capability to deal properly with sequencing problems and dynamic revision of plans and schedules during process execution. Our approach to achieve better solutions for the waste collection process is to model it as a vehicle routing problem, more specifically as a team orienteering problem where capacity constraints on the vehicles are considered, as well as time windows for the waste collection points and for the vehicles. The final model is called capacitated team orienteering problem with double time windows (CTOPdTW).We developed a genetic algorithm to solve routing problems in waste collection modelled as a CTOPdTW. The results achieved suggest possible reductions of logistic costs in selective waste collection.

The effect of secular trends in the classroom furniture mismatch: support for continuous update of school furniture standards

In order to create safer schools, the Chilean authorities published a Standard regarding school furniture dimensions. The aims of this study are twofold: to verify the existence of positive secular trend within the Chilean student population and to evaluate the potential mismatch between the anthropometric characteristics and the school furniture dimensions defined by the mentioned standard. The sample consists of 3078 subjects. Eight anthropometric measures were gathered, together with six furniture dimensions from the mentioned standard. There is an average increase for some dimensions within the Chilean student population over the past two decades. Accordingly, almost 18% of the students will find the seat height to be too high. Seat depth will be considered as being too shallow for 42.8% of the students. It can be concluded that the Chilean student population has increased in stature, which supports the need to revise and update the data from the mentioned Standard. Practitioner Summary: Positive secular trend resulted in high levels of mismatch if furniture is selected according to the current Chilean Standard which uses data collected more than 20 years ago. This study shows that school furniture standards need to be updated over time.

A proactive intelligent decision support system for predicting the popularity of online news

"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

Process simulation support in BPM tools: The case of BPMN

Due to the increasing acceptance of BPM, nowadays BPM tools are extensively used in organizations. Core to BPM are the process modeling languages, of which BPMN is the one that has been receiving most attention these days. Once a business process is described using BPMN, one can use a process simulation approach in order to find its optimized form. In this context, the simulation of business processes, such as those defined in BPMN, appears as an obvious way of improving processes. This paper analyzes the business process modeling and simulation areas, identifying the elements that must be present in the BPMN language in order to allow processes described in BPMN to be simulated. During this analysis a set of existing BPM tools, which support BPMN, are compared regarding their limitations in terms of simulation support.

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Methodology for real-time adaptation of tunnels support using the observational method

The observational method in tunnel engineering allows the evaluation in real time of the actual conditions of the ground and to take measures if its behavior deviates considerably from predictions. However, it lacks a consistent and structured methodology to use the monitoring data to adapt the support system in real time. The definition of limit criteria above which adaptation is required are not defined and complex inverse analysis procedures (Rechea et al. 2008, Levasseur et al. 2010, Zentar et al. 2001, Lecampion et al. 2002, Finno and Calvello 2005, Goh 1999, Cui and Pan 2012, Deng et al. 2010, Mathew and Lehane 2013, Sharifzadeh et al. 2012, 2013) may be needed to consistently analyze the problem. In this paper a methodology for the real time adaptation of the support systems during tunneling is presented. In a first step limit criteria for displacements and stresses are proposed. The methodology uses graphics that are constructed during the project stage based on parametric calculations to assist in the process and when these graphics are not available, since it is not possible to predict every possible scenario, inverse analysis calculations are carried out. The methodology is applied to the “Bois de Peu” tunnel which is composed by two tubes with over 500 m long. High uncertainty levels existed concerning the heterogeneity of the soil and consequently in the geomechanical design parameters. The methodology was applied in four sections and the results focus on two of them. It is shown that the methodology has potential to be applied in real cases contributing for a consistent approach of a real time adaptation of the support system and highlight the importance of the existence of good quality and specific monitoring data to improve the inverse analysis procedure.

Spousal support and satisfaction with healthcare services as moderators between psychological morbidity and adherence to diet in Type 2 Diabetes patients

Objectives: This study analyzed the moderating role of partners’ support and satisfaction with healthcare services in the relationship between psychological morbidity and adherence to diet in patients with type 2 diabetes (T2DM). Methods: Participants were 387 recently diagnosed T2DM patients that answered the following instruments: Revised Summary of Diabetes Self- Care Activities Measure, Hospital Anxiety and Depression Scales, Multidimensional Diabetes Questionnaire and Patient Satisfaction Questionnaire. Results: Partners’ positive and negative support moderated the relationship between psychological morbidity and adherence to diet. Satisfaction with healthcare services also moderated the relationship between psychological morbidity and adherence to diet. Conclusions: Intervention programs to promote adherence to diet in patients with type 2 diabetes should focus on partners’ support and patient satisfaction with healthcare services.

Repository power: how repositories can support Open Access mandates

Many funding agencies have Open Access mandates in place, but how often are scientific publications as outputs linked to funding details? The benefits of linking funding information to publications as part of the deposit workflow can assist in adhering to Open Access mandates. This paper examines how OpenAIRE – Open Access Infrastructure for Research in Europe – can ease monitoring Open Access and reporting processes for funders, and presents some results and opportunities. It also outlines how it relies on cleaned and curated repository content, a vital cog in the ever turning wheel of the global scholarly landscape, and the benefits it brings.

Breastfeeding and depression: a systematic review of the literature

Background: Research has separately indicated associations between pregnancy depression and breastfeeding, breastfeeding and postpartum depression, and pregnancy and postpartum depression. This paper aimed to provide a systematic literature review on breastfeeding and depression, considering both pregnancy and postpartum depression. Methods: An electronic search in three databases was performed using the keywords: “breast feeding”, “bottle feeding”, “depression”, “pregnancy”, and “postpartum”. Two investigators independently evaluated the titles and abstracts in a first stage and the full-text in a second stage review. Papers not addressing the association among breastfeeding and pregnancy or postpartum depression, non-original research and research focused on the effect of antidepressants were excluded. 48 studies were selected and included. Data were independently extracted. Results: Pregnancy depression predicts a shorter breastfeeding duration, but not breastfeeding intention or initiation. Breastfeeding duration is associated with postpartum depression in almost all studies. Postpartum depression predicts and is predicted by breastfeeding cessation in several studies. Pregnancy and postpartum depression are associated with shorter breastfeeding duration. Breastfeeding may mediate the association between pregnancy and postpartum depression. Pregnancy depression predicts shorter breastfeeding duration and that may increase depressive symptoms during postpartum. Limitations: The selected keywords may have led to the exclusion of relevant references. Conclusions: Although strong empirical evidence regarding the associations among breastfeeding and pregnancy or postpartum depression was separately provided, further research, such as prospective studies, is needed to clarify the association among these three variables. Help for depressed pregnant women should be delivered to enhance both breastfeeding and postpartum psychological adjustment.

Breastfeeding is negatively affected by prenatal depression and reduces postpartum depression

Background. This prospective cohort study explored the effects of prenatal and postpartum depression on breastfeeding and the effect of breastfeeding on postpartum depression. Method. The Edinburgh Postpartum Depression Scale (EPDS) was administered to 145 women at the first, second and third trimester, and at the neonatal period and 3 months postpartum. Self-report exclusive breastfeeding since birth was collected at birth and at 3, 6 and 12 months postpartum. Data analyses were performed using repeated-measures ANOVAs and logistic and multiple linear regressions. Results. Depression scores at the third trimester, but not at 3 months postpartum, were the best predictors of exclusive breastfeeding duration (β =−0.30, t=−2.08, p<0.05). A significant decrease in depression scores was seen from childbirth to 3 months postpartum in women who maintained exclusive breastfeeding for53 months (F1,65 =3.73, p<0.10, ηp 2 =0.05). Conclusions. These findings suggest that screening for depression symptoms during pregnancy can help to identify women at risk for early cessation of exclusive breastfeeding, and that exclusive breastfeeding may help to reduce symptoms of depression from childbirth to 3 months postpartum.

Breastfeeding and postpartum depression: state of the art review

Objective: To review the literature on the association between breastfeeding and postpartum depression. Sources: A review of literature found on MEDLINE/ PubMed database. Summary of findings: The literature consistently shows that breastfeeding provides a wide range of benefits for both the child and the mother. The psychological benefits for the mother are still in need of further research. Some studies point out that pregnancy depression is one of the factors that may contribute to breastfeeding failure. Others studies also suggest an association between breastfeeding and postpartum depression; the direction of this association is still unclear. Breastfeeding can promote hormonal processes that protect mothers against postpartum depression by attenuating cortisol response to stress. It can also reduce the risk of postpartum depression, by helping the regulation of sleep and wake patterns for mother and child, improving mother’s self efficacy and her emotional involvement with the child, reducing the child’s temperamental difficulties, and promoting a better interaction between mother and child. Conclusions: Studies demonstrate that breastfeeding can protect mothers from postpartum depression, and are starting to clarify which biological and psychological processes may explain this protection. However, there are still equivocal results in the literature that may be explained by the methodological limitations presented by some studies.

Depressed mothers and infants are more relaxed during breastfeeding versus bottlefeeding interactions: brief report

Depressed and non-depressed mothers and their 3-month-old infants were videotaped during breastfeeding and bottlefeeding interactions. The videotapes were subsequently coded for a number of feeding interaction behaviors as well as being rated on the Interaction Rating Scales. No differences were noted between the depressed and non-depressed mothers. Several breastfeeding versus bottlefeeding group effects were observed. The breastfeeding mothers showed less burping and less intrusive behavior during the nipple-in periods as well as during the nipple-out periods. In addition, the breastfeeding mothers and their infants received better ratings on the Interaction Rating Scales. These data suggest that the depressed mothers and their infants not unlike the non-depressed mothers and their infants were benefited by breastfeeding.

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.