Endoscopic resection of a large colonic leiomyosarcoma

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On the Learnability of Software Router Performance via CPU Measurements

In the last decade the ICT community observed a growing popularity of software networking paradigms. This trend consists in moving network applications from static, expensive, hardware equipment (e.g. router, switches, firewalls) towards flexible, cheap pieces of software that are executed on a commodity server. In this context, a server owner may provide the server resources (CPUs, NICs, RAM) for customers, following a Service-Level Agreement (SLA) about clients' requirements. The problem of resource allocation is typically solved by overprovisioning, as the clients' application is opaque to the server owner, and the resource required by clients' applications are often unclear or very difficult to quantify. This paper shows a novel approach that exploits machine learning techniques in order to infer the input traffic load (i.e., the expected network traffic condition) by solely looking at the runtime CPU footprint

Climate and environmental data contribute to the prediction of grain commodity prices using deep learning

Background: Grain commodities are important to people's daily lives and their fluctuations can cause instability for households. Accurate prediction of grain prices can improve food and social security. Methods & Materials: This study proposes a hybrid Long Short-Term Memory (LSTM)-Convolutional Neural Network (CNN) model to forecast weekly oat, corn, soybean and wheat prices in the United States market. The LSTM-CNN is a multivariate model that uses weather data, macroeconomic data, commodities grain prices and snow factors, including Snow Water Equivalent (SWE), snowfall and snow depth, to make multistep ahead forecasts. Results: Of all the features, the snow factor is used for the first time for commodity price forecasting. We used the LSTM-CNN model to evaluate the 5, 10, 15 and 20 weeks ahead forecasting and this hybrid model had the lowest Mean Squared Error (MSE) at 5, 10 and 15 weeks ahead of prediction. In addition, Shapley values were calculated to analyse the feature contribution of the LSTM-CNN model when forecasting the testing set. Based on the feature contribution, SWE ranked third, fifth and seventh in feature importance in the 5-week ahead forecast for corn, oats and wheat, respectively, and 7–8 places higher than total precipitation, indicating the potential use of SWE in grain price forecasting. Conclusion: The hybrid multivariate LSTM-CNN model outperformed other models and the newly involved climate data, SWE, showed the research potential of using snow as an input variable to predict grain prices over a multistep ahead time horizon

Rapid malignant progression of an intraparenchymal choroid plexus papillomas

Background: Choroid plexus tumors (CPTs) are rare neoplasms accounting for only 0.3-0.6% of all brain tumors in adults and 2-5% in children. The World Health Organization (WHO) classification describes three histological grades: grade I is choroid plexus papilloma (CPP), grade II is atypical papilloma, and grade III is the malignant form of carcinoma. In adults, CPTs rarely have a supratentorial localization. Case Description: Here we report a very rare case of an intraparenchymal parietal CPP with a rapid histological transition from grade I to grade III WHO in a 67-year-old man, in <7 months. Conclusion: Because of the rarity of these oncotypes, descriptions of each new case are useful, mostly to consider this diagnostic entity in extraventricular brain tumors of adults, despite an unusual location

Peripheral facial palsy following ventriculoperitoneal shunt. The lesson we have learned

The most frequent complications after shunt surgery are infective and obstructive. Other types are less common, and eventually occur due to technical errors during brain ventricular puncture, opening the intraperitoneal cavity or the tunnelling of the catheter between the two points. Although rare, there are well-reported complications related to the poor positioning of the distal catheter, with perforation of organs and tissues. We report a very rare case of a male patient with normal pressure hydrocephalus submitted to ventriculoperitoneal shunt. During tunnelling of the shunt stylet, a peripheral facial palsy due to injury to the extra cranial segment of the facial nerve occurred. To the best of our knowledge this is the second case described in Literature. The patient and the surgeon should be aware of this very rare but possible complication in shunt surgery being careful to the course of the facial nerve in the mastoid region

Pane di festa. Le cuddure a Roccafiorita e Limina

Il capitolo analizza gli usi rituali delle cuddure, dolce tipico della Valle d'Agrò, e ne indaga le valenze simboliche legate al ciclo di morte-rinascita proprio delle festività pasquali

Quantifying the Bias of Transformer-Based Language Models for African American English in Masked Language Modeling

In recent years, groundbreaking transformer-based language models (LMs) have made tremendous advances in natural language processing (NLP) tasks. However, the measurement of their fairness with respect to different social groups still remains unsolved. In this paper, we propose and thoroughly validate an evaluation technique to assess the quality and bias of language model predictions on transcripts of both spoken African American English (AAE) and Spoken American English (SAE). Our analysis reveals the presence of a bias towards SAE encoded by state-of-the-art LMs such as BERT and DistilBERT and a lower bias in distilled LMs. We also observe a bias towards AAE in RoBERTa and BART. Additionally, we show evidence that this disparity is present across all the LMs when we only consider the grammar and the syntax specific to AAE

Malattie Infettive

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