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

The Physical Properties and Effective Temperature Scale of O-type Stars as a Function of Metallicity. III. More Results from the Magellanic Clouds

In order to better determine the physical properties of hot, massive stars as a function of metallicity, we obtained very high SNR optical spectra of 26 O and early B stars in the Magellanic Clouds. These allow accurate modeling even in cases where the He I 4471 line has an equivalent width of only a few tens of mA. The spectra were modeled with FASTWIND, with good fits obtained for 18 stars; the remainder show signatures of being binaries. We include stars in common to recent studies to investigate possible systematic differences. The "automatic" FASTWIND modeling method of Mokiem and collaborators produced temperatures 1100 K hotter on the average, presumably due to the different emphasis given to various temperature-sensitive lines. More significant, however, is that the automatic method always produced some "best" answer, even for stars we identify as composite (binaries). The temperatures found by the TLUSTY/CMFGEN modeling of Bouret, Heap, and collaborators yielded temperatures 1000 K cooler than ours, on average. Significant outliers were due either to real differences in the data (some of the Bouret/Heap data were contaminated by moonlight continua) or the fact we could detect the HeI line needed to better constrain the temperature. Our new data agrees well with the effective temperature scale we presented previously. We confirm that the "Of" emission-lines do not track luminosity classes in the exact same manner as in Milky Way stars. We revisit the the issue of the "mass discrepancy", finding that some of the stars in our sample do have spectroscopic masses that are significantly smaller than those derived from stellar evolutionary models. We do not find that the size of the mass discrepancy is simply related to either effective temperature or surface gravity.Comment: ApJ, in pres

Theodora Patrona, Return Narratives. Ethnic Space in Late-Twentieth-Century Greek American and Italian American Literature

Theodora Patrona, Return Narratives. Ethnic Space in Late-Twentieth-Century Greek American and Italian American Literature Fairleigh Dickinson University Press, 2017. Pp. 209. ISBN: 9781611479959 Sostene M. Zangari In his poem “Heritage,” Countee Cullen articulates the cultural void affecting African-American intellectuals who, denied direct access to their ancestral home, were not able to turn its culture and traditions into that ‘usable past’ that could provide the foundations for construct..

A Phase 1 Study of Intravenous Busulfan as a Conditioning Regimen for Multiple Myeloma

The efficacy of melphalan (MEL) 140 mg/m 2 pre-transplant conditioning versus MEL 200 mg/m 2 for the elderly is still debated. We hypothesized that single-agent intravenous busulfan (BU) would show significant anti-myeloma efficacy and be better tolerated by elderly patients. A prospective 3+3 dose escalation study enrolled symptomatic multiple myeloma (MM) patients 65 years or older with SWOG performance 0–2 for treatment with intravenous BU pre-transplant at different administration levels. The primary objective was to determine the maximum tolerated dose (MTD) of BU that could be safely given over the least number of days. All patients, except one, received maintenance treatment post-transplant, mostly for 2 years. We enrolled 13 patients, mean age of 73 years (range 68–80). Pharmacokinetic analysis showed no greater than 2% accumulation in the 13 patients, confirming a lack of accumulation in the multi-dose regimen. No deaths occurred in the peri-transplant period. Grade 3/4 adverse effects were hematological, no dose-limiting toxicity was observed and MTD was not reached. Three patients developed grade 3 mucositis but none developed veno-occlusive disease. Ten (77%) patients achieved a complete remission (CR) post-transplant with a remarkably long average time to best response of 6.7 months (range: 6–14 m), and two attained a partial response. Median overall survival was 84 months (95% CI, 21–104) and the median progression-free survival was 60 months (95% CI, 9–93). Our results suggest that IV BU could be an alternative conditioning regimen to MEL 140 in elderly patients with MM, and supports future randomized trials

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