Recommendation Systems: An Insight Into Current Development and Future Research Challenges

Research on recommendation systems is swiftly producing an abundance of novel methods, constantly challenging the current state-of-the-art. Inspired by advancements in many related fields, like Natural Language Processing and Computer Vision, many hybrid approaches based on deep learning are being proposed, making solid improvements over traditional methods. On the downside, this flurry of research activity, often focused on improving over a small number of baselines, makes it hard to identify reference methods and standardized evaluation protocols. Furthermore, the traditional categorization of recommendation systems into content-based, collaborative filtering and hybrid systems lacks the informativeness it once had. With this work, we provide a gentle introduction to recommendation systems, describing the task they are designed to solve and the challenges faced in research. Building on previous work, an extension to the standard taxonomy is presented, to better reflect the latest research trends, including the diverse use of content and temporal information. To ease the approach toward the technical methodologies recently proposed in this field, we review several representative methods selected primarily from top conferences and systematically describe their goals and novelty. We formalize the main evaluation metrics adopted by researchers and identify the most commonly used benchmarks. Lastly, we discuss issues in current research practices by analyzing experimental results reported on three popular datasets

A Survey on Text Classification Algorithms: From Text to Predictions

In recent years, the exponential growth of digital documents has been met by rapid progress in text classification techniques. Newly proposed machine learning algorithms leverage the latest advancements in deep learning methods, allowing for the automatic extraction of expressive features. The swift development of these methods has led to a plethora of strategies to encode natural language into machine-interpretable data. The latest language modelling algorithms are used in conjunction with ad hoc preprocessing procedures, of which the description is often omitted in favour of a more detailed explanation of the classification step. This paper offers a concise review of recent text classification models, with emphasis on the flow of data, from raw text to output labels. We highlight the differences between earlier methods and more recent, deep learning-based methods in both their functioning and in how they transform input data. To give a better perspective on the text classification landscape, we provide an overview of datasets for the English language, as well as supplying instructions for the synthesis of two new multilabel datasets, which we found to be particularly scarce in this setting. Finally, we provide an outline of new experimental results and discuss the open research challenges posed by deep learning-based language models

Tribe : A Socio-Political Analysis

In 1974 we authored an essay entitled Tribe and Tribalism which recommended that the term tribe be dropped from scientific usage by anthropologists because of its pejorative connotations associated with non-European peoples and because the term is arbitrarily, rather than systematically applied. Increasing numbers of scholars are putting quotation marks around the word tribe or are using the phrase the so-called tribal societies. Still others are presenting a critical review of the term tribe before abandoning it or using it in the text in modified or altered form. The term primitive has undergone a similar evolution in recent years

Capsular closure after hip arthroscopy: our experience

BACKGROUND AND AIM OF THE WORK: In the last decade, arthroscopic treatment of hip diseases has significantly spread and evolved and currently it represents the gold standard for the treatment of femoral- acetabular impingement. In the recent years, the function of the joint capsule (and therefore the results of an arthroscopic capsulotomy) has been hugely developed, opening a heated debate. The Literature is still torn about the need for a capsular suture, but more recent studies are more oriented in its execution at the end of the surgical procedure. According to these recent studies, the joint capsule performs an essential function of primary stability, and its closure is therefore necessary to restore the native anatomy and physiology. Nevertheless, capsular management remains a controversial topic. This is a retrospective study with the aim of assessing the influence of capsular suture on the patient's functional outcome in a cohort of patients with femoral-acetabular impingement arthroscopically treated. HYPOTHESIS: Our hypothesis is that an adequate capsular suture positively influences the patient's functional outcome. METHODS AND RESULTS: 50 patients treated with hip arthroscopy for femoral-acetabular impingement have been retrospectively enrolled at the Orthopaedic Clinic of Academic Hospital of Udine during a period of two-years (2017-2018); collected data have been analysed and compared with a retrospective model. Patients have been divided into two equivalent groups, 25 treated with capsular suture, 25 without performing the suture. Patient's post-operative functional outcome has been analysed using the modified Harris Hip Score (mHHS), the Non-Arthritic Hip Score (NAHS) and the Hip Outcome Score-Sport Scale (HOS-SS). The functional outcome in patients where capsular sutures were performed was better than in non-sutured patients, in all three analysed scales. CONCLUSIONS: Capsular suture with a single side-to-side stitch at the end of the procedure can positively influence the patient's functional outcome

Asbestos Fibers Enhance the TMEM16A Channel Activity in Xenopus Oocytes

Background: The interaction of asbestos fibers with target cell membranes is still poorly investigated. Here, we detected and characterized an enhancement of chloride conductance in Xenopus oocyte cell membranes induced by exposure to crocidolite (Croc) asbestos fibers. Methods: A two-microelectrode voltage clamp technique was used to test the effect of Croc fiber suspensions on outward chloride currents evoked by step membrane depolarization. Calcium imaging experiments were also performed to investigate the variation of 'resting' oocyte [Ca2+]i following asbestos exposure. Results: The increase in chloride current after asbestos treatment, was sensitive to [Ca2+]e, and to specific blockers of TMEM16A Ca2+-activated chloride channels, MONNA and Ani9. Furthermore, asbestos treatment elevated the 'resting' [Ca2+]i likelihood by increasing the cell membrane permeability to Ca2 in favor of a tonic activation of TMEME16A channels. Western blot analysis confirmed that TMEME16A protein was endogenously present in the oocyte cell membrane and absorbed by Croc. Conclusion: the TMEM16A channels endogenously expressed by Xenopus oocytes are targets for asbestos fibers and represent a powerful tool for asbestos-membrane interaction studies. Interestingly, TMEM16A channels are highly expressed in many types of tumors, including some asbestos-related cancers, suggesting them, for the first time, as a possible early target of crocidolite-mediated tumorigenic effects on target cell membranes

Multiple myeloma presenting as CEA-producing rectal cancer

We report the case of a 57-year-old patient with multiple myeloma, characterized by extramedullary involvement of the rectum at presentation. Malignant plasma cells were found to produce carcinoembryonic antigen (CEA), a tumor antigen more commonly associated with rectal adenocarcinomas