A survey on deep learning in image polarity detection: Balancing generalization performances and computational costs

Deep convolutional neural networks (CNNs) provide an effective tool to extract complex information from images. In the area of image polarity detection, CNNs are customarily utilized in combination with transfer learning techniques to tackle a major problem: the unavailability of large sets of labeled data. Thus, polarity predictors in general exploit a pre-trained CNN as the feature extractor that in turn feeds a classification unit. While the latter unit is trained from scratch, the pre-trained CNN is subject to fine-tuning. As a result, the specific CNN architecture employed as the feature extractor strongly affects the overall performance of the model. This paper analyses state-of-the-art literature on image polarity detection and identifies the most reliable CNN architectures. Moreover, the paper provides an experimental protocol that should allow assessing the role played by the baseline architecture in the polarity detection task. Performance is evaluated in terms of both generalization abilities and computational complexity. The latter attribute becomes critical as polarity predictors, in the era of social networks, might need to be updated within hours or even minutes. In this regard, the paper gives practical hints on the advantages and disadvantages of the examined architectures both in terms of generalization and computational cost

Historical suitability and sustainability of sicani mountains landscape (western Sicily): An integrated approach of phytosociology and archaeobotany

Since 2015, the ongoing project "Harvesting Memories" has been focused on long-term landscape dynamics in Sicani Mountains (Western Sicily). Archaeological excavations in the case study site of Contrada Castro (Corleone) have investigated a settlement which was mainly occupied during the Early Middle Ages (late 8th-11th century AD). This paper aims to understand the historical suitability and sustainability of this area analysing the correlation between the current dynamics of plant communities and the historical use of woods detected by the archaeobotanical record. An integrated approach between phytosociology and archaeobotany has been applied. The vegetation series of the study area has been used as a model to understand the ecological meaning and spatial distribution of archaeobotanical data on charcoals from the Medieval layers of the Contrada Castro site. The intersection between the frequency data of the archaeobotanical record and the phytosociological analysis have confirmed the maintenance of the same plant communities during the last millennium due to the sustainable exploitation of wood resources. An integrated comparison between the structure and composition of current phytocoenoses with archaeobotanical data allowed us to confirm that this landscape is High Nature Value (HNV) farmland and to interpret the historical vegetation dynamics linked to the activities and economy of a rural community

Floristic and vegetation changes on a small mediterranean island over the last century

A synthetic and updated overview about the vascular flora and vegetation of the Island of Capo Passero (SE‐Sicily) is provided. These data issue from two series of field surveys—the first carried out between 1997 and 2000, and the second between 2005 and 2019 and mostly focused on refining and implementing vegetation data. The current islet’s flora consists of 269 taxa, of which 149 (58%) are annual plants. The Mediterranean species are largely prevailing, 108 (40%) of which have a strictly Mediterranean biogeographical status. The comparison with a species list published in 1919 and updated in 1957 suggest that, despite the overall prevalence of anemochorous taxa, the vertebrate fauna represents an important vector for the plant colonization of the island, while the immigration of myrmechocorous taxa does not compensate the extinction rate. As many as 202 phy-tosociological relevés, 191 of which issue from original recent field surveys, enabled identifying 12 different plant communities. The comparison with a vegetation map published in 1965 suggests a strong reduction in dune habitats (2120 and 2210 according to EU ‘Habitats’ Directive 92/43), as well as a deep disruption in the succession typical of the local psammophilous vegetation series. In order to preserve rare, endangered and protected plant species (such as Aeluropus lagopoides, Cichorium spinosum, Limonium hyblaeum, L. syracusanum, Poterium spinosum, Senecio pygmaeus and Spergularia heldreichii) and to stop the ongoing habitat degradation, urgent and effective conservation measures should be adopted for this tiny, yet precious islet

A study on text-score disagreement in online reviews

In this paper, we focus on online reviews and employ artificial intelligence tools, taken from the cognitive computing field, to help understanding the relationships between the textual part of the review and the assigned numerical score. We move from the intuitions that 1) a set of textual reviews expressing different sentiments may feature the same score (and vice-versa); and 2) detecting and analyzing the mismatches between the review content and the actual score may benefit both service providers and consumers, by highlighting specific factors of satisfaction (and dissatisfaction) in texts. To prove the intuitions, we adopt sentiment analysis techniques and we concentrate on hotel reviews, to find polarity mismatches therein. In particular, we first train a text classifier with a set of annotated hotel reviews, taken from the Booking website. Then, we analyze a large dataset, with around 160k hotel reviews collected from Tripadvisor, with the aim of detecting a polarity mismatch, indicating if the textual content of the review is in line, or not, with the associated score. Using well established artificial intelligence techniques and analyzing in depth the reviews featuring a mismatch between the text polarity and the score, we find that -on a scale of five stars- those reviews ranked with middle scores include a mixture of positive and negative aspects. The approach proposed here, beside acting as a polarity detector, provides an effective selection of reviews -on an initial very large dataset- that may allow both consumers and providers to focus directly on the review subset featuring a text/score disagreement, which conveniently convey to the user a summary of positive and negative features of the review target.Comment: This is the accepted version of the paper. The final version will be published in the Journal of Cognitive Computation, available at Springer via http://dx.doi.org/10.1007/s12559-017-9496-

SentiBench - a benchmark comparison of state-of-the-practice sentiment analysis methods

In the last few years thousands of scientific papers have investigated sentiment analysis, several startups that measure opinions on real data have emerged and a number of innovative products related to this theme have been developed. There are multiple methods for measuring sentiments, including lexical-based and supervised machine learning methods. Despite the vast interest on the theme and wide popularity of some methods, it is unclear which one is better for identifying the polarity (i.e., positive or negative) of a message. Accordingly, there is a strong need to conduct a thorough apple-to-apple comparison of sentiment analysis methods, \textit{as they are used in practice}, across multiple datasets originated from different data sources. Such a comparison is key for understanding the potential limitations, advantages, and disadvantages of popular methods. This article aims at filling this gap by presenting a benchmark comparison of twenty-four popular sentiment analysis methods (which we call the state-of-the-practice methods). Our evaluation is based on a benchmark of eighteen labeled datasets, covering messages posted on social networks, movie and product reviews, as well as opinions and comments in news articles. Our results highlight the extent to which the prediction performance of these methods varies considerably across datasets. Aiming at boosting the development of this research area, we open the methods' codes and datasets used in this article, deploying them in a benchmark system, which provides an open API for accessing and comparing sentence-level sentiment analysis methods

Sentiment analysis tools should take account of the number of exclamation marks!!!

There are various factors that affect the sentiment level expressed in textual comments. Capitalization of letters tends to mark something for attention and repeating of letters tends to strengthen the emotion. Emoticons are used to help visualize facial expressions which can affect understanding of text. In this paper, we show the effect of the number of exclamation marks used, via testing with twelve online sentiment tools. We present opinions gathered from 500 respondents towards “like” and “dislike” values, with a varying number of exclamation marks. Results show that only 20% of the online sentiment tools tested considered the number of exclamation marks in their returned scores. However, results from our human raters show that the more exclamation marks used for positive comments, the more they have higher “like” values than the same comments with fewer exclamations marks. Similarly, adding more exclamation marks for negative comments, results in a higher “dislike”

Clinical failures of endovascular abdominal aortic aneurysm repair: Incidence, causes, and management

AbstractObjective: Despite well-documented good early results and benefits of endoluminal stent graft repair of abdominal aortic aneurysm (J Vasc Surg 2002;35:1137-44.)(AAA), the long-term outcome of this method of treatment remains uncertain. In particular, concern exists that late effectiveness and durability are inferior to that of open repair. To determine the incidence and causes of clinical failures of endovascular AAA repair, a 7-year experience with 362 primary AAA endografts was reviewed. Methods: Clinical failures were defined as deaths within 30 days of the procedure, conversions (early and late) to open AAA repair, AAA rupture after endoluminal treatment, or AAA sac growth of more than 5 mm in maximal diameter despite endograft repair. Endoleak status per se was not considered unless it resulted in an adverse event. If clinical problems arose but could be corrected with catheter-based therapies or limited surgical procedures, thereby maintaining the integrity of successful stent graft treatment of the AAA, such cases were considered as primary assisted success and not classified as clinical failures. Results: The average follow-up period was 1.5 years. Six deaths (1.6%) occurred after the procedure, all in elderly patients or patients at high risk. Five patients (1.4%) needed early conversion (immediate, 2 days) to open repair for access problems or technical difficulties with deployment, resulting in an implantation success rate of 98.6%. Eight patients (2.2%) underwent late conversion for a variety of problems, including AAA expansion (n = 4), endograft thrombosis (n = 1), secondary graft infection (n = 2), and rupture at 3 years (n = 1). Rupture occurred in an additional two patients for a total incidence rate of 0.8%. AAA sac growth of greater than 5 mm was observed in 20 patients (5.6%), four of whom have undergone successful catheter-based treatments to date. Overall, 39 patients (10.7%) needed catheter-based (n = 45) or limited surgical (n = 4) reinterventions for a variety of late problems that were successful in 92%. Conclusion: In our 7-year experience, one or more clinical failures of endovascular AAA repair were observed in 31 patients (8.3%). Reinterventions were necessitated in a total of 10.7% of patients but were usually successful in maintaining AAA exclusion and limiting AAA growth. These results emphasize that endovascular repair provides good results and many benefits for most properly selected patients but is not as durable as standard open repair. (J Vasc Surg 2002;35:1137-44.

Redox regulation of cellular stress response in multiple sclerosis

Multiple sclerosis (MS) is an autoimmune-mediated neurodegenerative disease with characteristic foci of inflammatory demyelination in the brain, spinal cord, and optic nerves. Recent studies have demonstrated not only that axonal damage and neuronal loss are significant pathologic components of MS, but that this neuronal damage is thought to cause the permanent neurologic disability often seen in MS patients. Emerging finding suggests that altered redox homeostasis and increased oxidative stress, primarily implicated in the pathogenesis of MS, are a trigger for activation of a brain stress response. Relevant to maintenance of redox homeostasis, integrated mechanisms controlled by vitagenes operate in brain in preserving neuronal survival during stressful conditions. Vitagenes encode for heat shock proteins (Hsp) Hsp32, Hsp70, the thioredoxin and the sirtuin protein systems. In the present study we assess stress response mechanisms in the CSF, plasma and lymphocytes of control patients compared to MS patients. We found that the levels of vitagenes Hsp72, Hsc70, HO-1, as well as oxidative stress markers carbonyls and hydroxynonenals were significantly higher in the blood and CSF of MS patients than in control patients. In addition, an increased expression of Trx and sirtuin 1, together with a decrease in the expression of TrxR were observed. Our data strongly support a pivotal role for redox homeostasis disruption in the pathogenesis of MS and, consistently with the notion that new therapies that prevent neurodegeneration through nonimmunomodulatory mechanisms can have a tremendous potential to work synergistically with current MS therapies, unravel important targets for new cytoprotective strategies

High-dose-rate Brachytherapy as Adjuvant Local rEirradiation for Salvage Treatment of Recurrent breAst cancer (BALESTRA): a retrospective mono-institutional study

Purpose: To evaluate clinical results of catheter-based interstitial high-dose-rate (HDR) brachytherapy (BT) as adjuvant treatment in previously irradiated recurrent breast cancer. Material and methods: Between January 2011 and September 2015, 31 consecutive patients with histologically confirmed recurrent breast cancer after conservative surgery and conventional whole breast radiotherapy, were retreated with a second conservative surgical resection and reirradiated with adjuvant interstitial HDR-BT. None of the brachytherapy implant was performed during the quadrantectomy procedure. A dose of 34 Gy in 10 fractions, 2 fractions per day, with a minimal interval of 6 hours was delivered. Results: At the time of the implant, the median age of patients was 59.7 years (range, 39.3-74.9 years). The median time from first treatment until BT for local recurrence was 11.9 years (range, 2.5-27.8 years). The median interval between salvage surgery and BT was 3.6 months (range, 1-8.2 months). No acute epidermitis or soft tissue side effects higher than grade 2 were recorded, with good cosmetic results in all patients. Most of the patients presented grade 1-2 late side effects. Only one patient developed grade 3 liponecrosis. After a median follow-up of 73.7 months (range, 28.8-102.4 months), the overall survival and cancer specific survival were 87.1% and 90.3%, respectively; 5-year local control and 5-year progression-free survival rate were 90.3% and 83.9%, respectively. Conclusions: Our preliminary analysis showed that HDR-BT is a feasible treatment for partial breast reirradiation offering very low complications rate and fast procedure. Higher patients' cohort is warranted in order to define the role of this treatment modality in the breast conservative management of local recurrence