Book Review

We often are startled when someone presents us with a new awareness of the significance of issues or phenomena at which we have been looking for years but have never really seen. Freda Adler will startle a number of people who read her book Sisters in Crime. She will also anger them. The only thing her book will not do is leave people unmoved. Sisters in Crime provides punch, provocation, revelation, promise, and explanation, as the author uses the central theme of the change in the rate and nature of crimes committed by women to explore women\u27s roles and fortunes in our society

Tearing Out the Income Tax by the (Grass)Roots

Landscapes are increasingly fragmented, and conservation programs have started to look at network approaches for maintaining populations at a larger scale. We present an agent-based model of predator–prey dynamics where the agents (i.e. the individuals of either the predator or prey population) are able to move between different patches in a landscaped network. We then analyze population level and coexistence probability given node-centrality measures that characterize specific patches. We show that both predator and prey species benefit from living in globally well-connected patches (i.e. with high closeness centrality). However, the maximum number of prey species is reached, on average, at lower closeness centrality levels than for predator species. Hence, prey species benefit from constraints imposed on species movement in fragmented landscapes since they can reproduce with a lesser risk of predation, and their need for using anti-predatory strategies decreases.authorCount :

Siamese Network for Fake Item Detection

Currently, most multimedia users choose to purchase items through e-commerce. Nevertheless, one of the main concerns of online shopping is the possibility of obtaining counterfeit products. Therefore, it is crucial to monitor the authenticity of the product, thus adopting an automatic mechanism to validate the similarity between the purchased item and the delivered one. To overcome this issue, we propose a Siamese Network model for detecting forged items. Preliminary experimentation on a publicly available dataset proves the effectiveness of our solution

Fighting Misinformation, Radicalization and Bias in Social Media

Social media have become the ideal place for black hats and malicious individuals to target susceptible users through different attack vectors and then manipulate their opinions and interests. Fake news, radicalization, and pushing bias into the data represent some popular ways noxious users adopt to perpetrate their criminal intents. In this evolving scenario, Artificial Intelligence techniques represent a valuable tool to early detect and mitigate the risk due to the spreading of these emerging attacks. In this work, we describe the Machine Learning based solutions developed to address the problems mentioned above and our current research

GenRec: A Flexible Data Generator for Recommendations

The scarcity of realistic datasets poses a significant challenge in benchmarking recommender systems and social network analysis methods and techniques. A common and effective solution is to generate synthetic data that simulates realistic interactions. However, although various methods have been proposed, the existing literature still lacks generators that are fully adaptable and allow easy manipulation of the underlying data distributions and structural properties. To address this issue, the present work introduces GenRec, a novel framework for generating synthetic user-item interactions that exhibit realistic and well-known properties observed in recommendation scenarios. The framework is based on a stochastic generative process based on latent factor modeling. Here, the latent factors can be exploited to yield long-tailed preference distributions, and at the same time they characterize subpopulations of users and topic-based item clusters. Notably, the proposed framework is highly flexible and offers a wide range of hyper-parameters for customizing the generation of user-item interactions. The code used to perform the experiments is publicly available at https://anonymous.4open.science/r/GenRec-DED3

LLASP: Fine-tuning Large Language Models for Answer Set Programming

Recently, Large Language Models (LLMs) have showcased their potential in various natural language processing tasks, including code generation. However, while significant progress has been made in adapting LLMs to generate code for several imperative programming languages and tasks, there remains a notable gap in their application to declarative formalisms, such as Answer Set Programming (ASP). In this paper, we move a step towards exploring the capabilities of LLMs for ASP code generation. First, we perform a systematic evaluation of several state-of-the-art LLMs. Despite their power in terms of number of parameters, training data and computational resources, empirical results demonstrate inadequate performances in generating correct ASP programs. Therefore, we propose LLASP, a fine-tuned lightweight model specifically trained to encode fundamental ASP program patterns. To this aim, we create an ad-hoc dataset covering a wide variety of fundamental problem specifications that can be encoded in ASP. Our experiments demonstrate that the quality of ASP programs generated by LLASP is remarkable. This holds true not only when compared to the non-fine-tuned counterpart but also when compared to the majority of eager LLM candidates, particularly from a semantic perspective. All the code and data used to perform the experiments are publicly available at https://anonymous.4open.science/r/LLASP-D86C/

Reflexiones sobre el diagnóstico de déficit de atención

One hundred and thirty two medical histories of cases with attention deficit hyperactivity disorder (ADHD) admitted during 3 years in the Argentine Foundation for Mental Health [Fundación Argentina para la Salud Mental (FASAM)] are examined. These medical histories are reassessed from the clinical-psychiatric and psycodiagnostic points of view. Findings indicate that near 10% of the researched population was admitted in FASAM with a ADHD diagnosis, of which 84.6% had been erroneously diagnosed in compliance with the criteria stated in the Diagnosis and Statistical Manual of Mental Disorders (DSM IV); 90.9% were administered stimulants as the only treatment. Conclusion: The symptoms shown by these patients were construed as caused exclusively by the attention deficit. A reductionist approach of patients ruling out the possibility of other disorders with similar symptomatology was the main reason leading to the misconceived diagnosis.Se consideran 132 historias clínicas recibidas en la Fundación Argentina para la Salud Mental (FASAM), durante 3 años. A estos historiales se los reevalúa de modo clínico psiquiátrico y psicodiagnóstico. Los hallazgos indican que cerca del 10% de la población estudiada llegó a la FASAM con diagnóstico de TDAH, de estos el 84,6% había sido erróneamente diagnosticado, según criterios del Manual Diagnóstico y Estadístico de los Trastornos Mentales (DSM IV); el 90,9% recibía estimulantes como único tratamiento. Como conclusión: Los síntomas presentados por estos pacientes se interpretaron como causados exclusivamente por el déficit de atención, la causa principal de error diagnóstico fue un enfoque reduccionista de los pacientes, que descartaba la posibilidad de otros trastornos de sintomatología similar

Vaginal Inflammatory Status in Pregnant Women with Normal and Pathogenic Microbiota in Lower Genital Tract

Objective. To assess the vaginal inflammatory status (VIS) in pregnant women, whether symptomatic or asymptomatic, by leukocyte quantification in relation to the microbiota during each pregnancy trimester (T). Materials and Methods. A thousand two hundred and forty eight vaginal exudates from pregnant women were prospectively examined. All the patients underwent a clinical and colposcopic examination and a microbiological study of vaginal exudates. Leukocyte quantification was determined by May-Grunwald Giemsa staining as LNR per field (400X). Results. Statistically significant differences (SSD) in LNR were observed in the VIS of asymptomatic patients (AP) compared with that of symptomatic ones (SP) with normal microbiota: 10–15 for the 1st T, <10, 20 to 25 and >25 for the 2nd T and >25 for the 3rd; with candidiasis: <10 for the 1st T, <10, 15 to 20 and >25 for the 2nd T and <10 and >25 for the 3rd T. In women with trichomoniasis, SSD in the LNR were observed between SP with LNR ≥ 10 and AP with NLR < 10 in the three trimesters altogether. In women with BV, no SSD were observed in the LNR of any AP with respect to SP for the three T. Conclusion. The VIS is influenced by vaginal microbiota and depends on the state of pregnancy and also, on gestational age. The pronounced leukocyte increase in asymptomatic patients in the absence of lower genital tract infection during the third trimester of pregnancy should be highlighted

An Encryption and Error-Control Coding scheme based on Non binary LDPC codes

In this paper we present a combined error-control coding and encryption scheme that provides to a given system with both high levels of reliability of the transmission and security. These two aims are usually present in wireless data transmission systems. The scheme is based on efficient Non Binary Low Density Parity Check codes which were selected for this design because they outer perform their binary counterparts. By means of a set of operations over the parity check matrix of the code, encryption capabilities are added to the scheme, without producing any degradation in the corresponding Bit Error Rate performance, as usually happens when encryption and error control coding are applied separately.Sociedad Argentina de Informática e Investigación Operativ

Leverage points for addressing marine and coastal pollution: a review

Despite an increasing understanding of the issue of marine pollution, humanity continues on a largely unsustainable trajectory. This study aimed to identify and classify the range of scientific studies and interventions to address coastal and marine pollution. We reviewed 2417 scientific papers published between 2000 and 2018, 741 of which we analysed in depth. To classify pollution interventions, we applied the systems-oriented concept of leverage points, which focuses on places to intervene in complex systems to bring about systemic change. We found that pollution is largely studied as a technical problem and fewer studies engage with pollution as a systemic social-ecological issue. While recognising the importance of technical solutions, we highlight the need to focus on under-researched areas pertaining to the deeper drivers of pollution (e.g. institutions, values) which are needed to fundamentally alter system trajectories.info:eu-repo/semantics/publishedVersio