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Agent-based models are useful to study emergent behaviour in social systems. In general, existing agent models tend to be quite simple, but there are social problems that require the consideration of some aspects with uncertainty as human thinking does. Those characteristics can be addressed by using fuzzy sets theory in the specification of the attributes that describe agents representing individuals, and in the functions that model the evolution of individual change of mind, the relationships among individuals in a social network, the inheritance, and the similarity between individuals. This paper discusses the fuzzification of agent-based models and analyses experimentation results for a specific case of the study of the evolution of human values in a society.

This paper describes a new approach for estimating term weights in a document, and shows how the new weighting scheme can be used to improve the accuracy of a text classifier. The method uses term co-occurrence as a measure of dependency between word features. A random walk model is applied on a graph encoding words and co-occurrence dependencies, resulting in scores that represent a quantification of how a particular word feature contributes to a given context. Experiments performed on three standard classification datasets show that the new random walk based approach outperforms the traditional term frequency approach of feature weighting.

In the last decade, the desire for safer oral anticoagulants (OACs) led to the emergence of newer drugs. Available clinical trials demonstrated a lower risk of OACs-associated life-threatening bleeding events, including intracranial hemorrhage, compared to warfarin. Nontraumatic spinal hematoma is an uncommon yet life-threatening neurosurgical emergency that can be associated with the use of these agents. Rivaroxaban, one of the newly approved OACs, is a direct factor Xa inhibitor. To the best of our knowledge, to date, only two published cases report the incidence of rivaroxaban-induced nontraumatic spinal subdural hematoma (SSDH). Our case is the third one described and the first one to involve the cervicothoracic spine.

Cancer associated inflammation is one of the key determinants of outcome in patients with cancer. An elevated neutrophil: lymphocyte ratio (NLR) has been identified as a predictor of worse survival in patients with various solid tumors compared to hematologic malignancies but no reports yet examined its impact on multiple myeloma. The aim of this study was to examine the prognostic value of an elevated NLR in multiple myeloma.

Cancer associated inflammation is one of the key determinants of outcome in patients with cancer. An elevated neutrophil: lymphocyte ratio (NLR) has been identified as a predictor of worse survival in patients with various solid tumors compared to hematologic malignancies but no reports yet examined its impact on multiple myeloma. The aim of this study was to examine the prognostic value of an elevated NLR in multiple myeloma.We had approval by our institutional review board to collect the data on patients diagnosed with multiple myeloma at Staten Island University Hospital between year 2000 and 2012 identified from our local cancer database. Data on demographics, conventional prognostic markers, laboratory analyzes including blood count results, and histopathology were collected and analyzed. A cox proportional survival analysis was carried out to assess the relationship between NLR and mortality. NLR was assessed as a continuous variable as well as categorical variable (quartile 0.5-1.5, 1.6-2.2, 2.3-3.8, and 3.9-22.3).A total of 96 patients were identified with a median age at diagnosis of 70 (IQR of 61 to 79) years. The median neutrophil count was 3.5 (2.5—5.1) x 10-9/liters, median lymphocyte count 1.5 (1.05-2.4) × 10-9/liters, while the NLR was 2.28 (1.53-3.88). The median overall survival was 147.5 weeks, IQR (88.5-320). NLR did not prove to be a significant predictor of death as a continuous variable (0.95 (0.85-1.06), p =0.35). Furthermore, there was no significant difference in survival with any of the quartiles of NLR. Compare to lowest quartile of NLR, Hazards ratio for the consecutive quartiles were 1.25 (0.56-2.79, p 0.55), 1.36 (0.61-3.04, p=0.45) and 0.89 (0.36-2.22, p=0.80).NLR does not appear to offer useful predictive ability for outcome and survival in multiple myeloma patients. Our study is limited with small sample size, further studies are needed to validate our results.No relevant conflicts of interest to declare.