The Colombian conflict: a description of a mental health program in the Department of Tolima.

Colombia has been seriously affected by an internal armed conflict for more than 40 years affecting mainly the civilian population, who is forced to displace, suffers kidnapping, extortion, threats and assassinations. Between 2005 and 2008, Médecins Sans Frontières-France provided psychological care and treatment in the region of Tolima, a strategic place in the armed conflict. The mental health program was based on a short-term multi-faceted treatment developed according to the psychological and psychosomatic needs of the population. Here we describe the population attending during 2005-2008, in both urban and rural settings, as well as the psychological treatment provided during this period and its outcomes.We observed differences between the urban and rural settings in the traumatic events reported, the clinical expression of the disorders, the disorders diagnosed, and their severity. Although the duration of the treatment was limited due to security reasons and access difficulties, patient condition at last visit improved in most of the patients. These descriptive results suggest that further studies should be conducted to examine the role of short-term psychotherapy, adapted specifically to the context, can be a useful tool to provide psychological care to population affected by an armed conflict

Scaling laws and universality in the choice of election candidates

Nowadays there is an increasing interest of physicists in finding regularities related to social phenomena. This interest is clearly motivated by applications that a statistical mechanical description of the human behavior may have in our society. By using this framework, we address this work to cover an open question related to elections: the choice of elections candidates (candidature process). Our analysis reveals that, apart from the social motivations, this system displays features of traditional out-of-equilibrium physical phenomena such as scale-free statistics and universality. Basically, we found a non-linear (power law) mean correspondence between the number of candidates and the size of the electorate (number of voters), and also that this choice has a multiplicative underlying process (lognormal behavior). The universality of our findings is supported by data from 16 elections from 5 countries. In addition, we show that aspects of network scale-free can be connected to this universal behavior.Comment: Accepted for publication in EP

Transcriptome of the deep-sea black scabbardfish, Aphanopus carbo (Perciformes: Trichiuridae) : tissue-specific expression patterns and candidate genes associated to depth adaptation

Deep-sea fishes provide a unique opportunity to study the physiology and evolutionary adaptation to extreme environments. We carried out a high throughput sequencing analysis on a 454 GS-FLX titanium plate using unnormalized cDNA libraries from six tissues of A. carbo. Assemblage and annotations were performed by Newbler and InterPro/Pfam analyses, respectively. The assembly of 544,491 high quality reads provided 8,319 contigs, 55.6% of which retrieved blast hits against the NCBI nonredundant database or were annotated with ESTscan. Comparison of functional genes at both the protein sequences and protein stability levels, associated with adaptations to depth, revealed similarities between A. carbo and other bathypelagic fishes. A selection of putative genes was standardized to evaluate the correlation between number of contigs and their normalized expression, as determined by qPCR amplification. The screening of the libraries contributed to the identification of new EST simple-sequence repeats (SSRs) and to the design of primer pairs suitable for population genetic studies as well as for tagging and mapping of genes. The characterization of the deep-sea fish A. carbo first transcriptome is expected to provide abundant resources for genetic, evolutionary, and ecological studies of this species and the basis for further investigation of depth-related adaptation processes in fishes.Publisher PDFPeer reviewe

Anticipating the duration of public administration employees' future absences

Absenteeism aff ects state-owned companies who are obliged to undertake strategies to prevent it, be efficient and conduct eff ective human resource (HR) management. This paper aims to understand the reasons for Public Administration Employees’ (PAE) absenteeism and predict future employee absences. Data from 17,600 PAE from seven public databases regarding their 2016 absences was collected, and the Recency, Frequency and Monetary (RFM) and Support Vector Machine (SVM) algorithm was used for modeling the absence duration, backed up with a 10-fold cross-validation scheme. Results revealed that the worker profi le is less relevant than the absence characteristics. The most concerning employee profi le was uncovered, and a set of scenarios is provided regarding the expected days of absence in the future for each scenario. The veracity of the absence motives could not be proven and thus are totally reliable. In addition, the number of records of one absence day was disproportionate to the other records. The findings are of value to the Human Capital Management department in order to support their decisions regarding the allocation of workers and productivity management and use these valuable insights in the recruitment process. Until now, little has been known concerning the characteristics that aff ect PAE absenteeism, therefore enriching the necessity for further understanding of this matter in this particular.info:eu-repo/semantics/publishedVersio

Is this the beginning of the end for retail websites? A professional perspective

This paper expects to understand professionals opinion concerning the impact of the increasing use of Social Media (SM) and commercial Mobile Applications (MA) instead of retail websites in their online strategy. Unstructured interviews with Internet professionals were applied on the LinkedIn professional SM platform, and one hundred and twenty-seven professionals provided their perspective. Data were analyzed using a Text Mining approach, and the outcome revealed professionals resistance to set SM in the center of the online strategy and highlighted the preference of users to use search engines that, in turn, will lead them to a retail website.info:eu-repo/semantics/acceptedVersio

Unveiling research trends for organizational reputation in the nonprofit sector

Public scrutiny and the need for funds in a more competitive environment are pressuring nonprofits to be more consciously aware of their reputation. This study used automated analysis with text mining and topic modeling of 177 articles directly linked to nonprofits’ reputation and published up to 2016. After identifying the most salient topics and conducting an in-depth, critical review of the most significant articles within each topic, four theoretical and managerial implications were identified. First, managers need to develop skills to deal with risk, the Internet, and social networks. Second, risk management is an emergent, still tentative, but important topic waiting for more contributions. Third, researchers can apply lexicons developed and validated by experts to uncover knowledge relevant to the entire nonprofit sector’s organizations. Last, the trends and topics highlighted can help scholars and practitioners make better decisions in research or responses to management challenges.info:eu-repo/semantics/acceptedVersio

A data-driven approach to improve customer churn prediction based on telecom customer segmentation

Numerous valuable clients can be lost to competitors in the telecommunication industry, leading to profit loss. Thus, understanding the reasons for client churn is vital for telecommunication companies. This study aimed to develop a churn prediction model to predict telecom client churn through customer segmentation. Data were collected from three major Chinese telecom companies, and Fisher discriminant equations and logistic regression analysis were used to build a telecom customer churn prediction model. According to the results, it can be concluded that the telecom customer churn model constructed by regression analysis had higher prediction accuracy (93.94%) and better results. This study will help telecom companies efficiently predict the possibility of and take targeted measures to avoid customer churn, thereby increasing their profits.Numerous valuable clients can be lost to competitors in the telecommunication industry, leading to profit loss. Thus, understanding the reasons for client churn is vital for telecommunication companies. This study aimed to develop a churn prediction model to predict telecom client churn through customer segmentation. Data were collected from three major Chinese telecom companies, and Fisher discriminant equations and logistic regression analysis were used to build a telecom customer churn prediction model. According to the results, it can be concluded that the telecom customer churn model constructed by regression analysis had higher prediction accuracy (93.94%) and better results. This study will help telecom companies efficiently predict the possibility of and take targeted measures to avoid customer churn, thereby increasing their profits.info:eu-repo/semantics/publishedVersio

Understanding the importance of sport stadium visits to teams and cities through the eyes of online reviewers

This study explores the relationships among sport stadium visitors’ experiences, satisfaction, team brand image, and destination image. A text mining approach was first used to analyse 26,538 individual reviews from 17 European sport stadiums on TripAdvisor. The online reviews were then used as input to create a word frequency of each individual review and construct a structural equation model. Results indicate that the visitor experience had a strong impact on team brand image and a moderate effect on destination image. Satisfaction mediated the influence of the visitor experience on team brand image, but not on destination image. Team brand image exerted a significant but small impact on destination image. These findings show that stadium visits impact the marketing of both host teams and cities. City, leisure and stadium managers should therefore coordinate their efforts to highlight teams as part of a city’s cultural brand to generate image-based benefits for both.info:eu-repo/semantics/publishedVersio

Unfolding the characteristics of incentivized online reviews

The rapid growth of social media in the last decades led e-commerce into a new era of value co-creation between the seller and the consumer. Since there is no contact with the product, people have to rely on the description of the seller, knowing that sometimes it may be biased and not entirely true. Therefore, review systems emerged to provide more trustworthy sources of information, since customer opinions may be less biased. However, the need to control the consumers’ opinion increased once sellers realized the importance of reviews and their direct impact on sales. One of the methods often used was to offer customers a specific product in exchange for an honest review. Yet, these incentivized reviews bias results and skew the overall rating of the products. The current study uses a data mining approach to predict whether or not a new review published was incentivized based on several review features such as the overall rating, the helpfulness rate, and the review length, among others. Additionally, the model was enriched with sentiment score features of the reviews computed through the VADER algorithm. The results provide an in-depth understanding of the phenomenon by identifying the most relevant features which enable to differentiate an incentivized from a non-incentivized review, thus providing users and companies with a simple set of rules to identify reviews that are biased without any disclaimer. Such rules include the length of a review, its helpfulness rate, and the overall sentiment polarity score.info:eu-repo/semantics/acceptedVersio