Analyzing How BERT Performs Entity Matching

State-of-the-art Entity Matching (EM) approaches rely on transformer architectures, such as BERT, for generating highly contextualized embeddings of terms. The embeddings are then used to predict whether pairs of entity descriptions refer to the same real-world entity. BERT-based EM models demonstrated to be effective, but act as black-boxes for the users, who have limited insight into the motivations behind their decisions. In this paper, we perform a multi-facet analysis of the components of pre-trained and fine-tuned BERT architectures applied to an EM task. The main findings resulting from our extensive experimental evaluation are (1) the fine-tuning process applied to the EM task mainly modifies the last layers of the BERT components, but in a different way on tokens belonging to descriptions of matching / non-matching entities; (2) the special structure of the EM datasets, where records are pairs of entity descriptions is recognized by BERT; (3) the pair-wise semantic similarity of tokens is not a key knowledge exploited by BERT-based EM models

Management of the greater trochanteric pain syndrome: a systematic review

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Random forests highlight the combined effect of environmental heavy metals exposure and genetic damages for cardiovascular diseases

Heavy metals are a dangerous source of pollution due to their toxicity, permanence in the environment and chemical nature. It is well known that long-term exposure to heavy metals is related to several chronic degenerative diseases (cardiovascular diseases, neoplasms, neurodegenerative syndromes, etc.). In this work, we propose a machine learning framework to evaluate the severity of cardiovascular diseases (CVD) from Human scalp hair analysis (HSHA) tests and genetic analysis and identify a small group of these clinical features mostly associated with the CVD risk. Using a private dataset provided by the DD Clinic foundation in Caserta, Italy, we cross-validated the classification performance of a Random Forests model with 90 subjects affected by CVD. The proposed model reached an AUC of 0.78 ± 0.01 on a three class classification problem. The robustness of the predictions was assessed by comparison with different cross-validation schemes and two state-ofthe-art classifiers, such as Artificial Neural Network and General Linear Model. Thus, is the first work that studies, through a machine learning approach, the tight link between CVD severity, heavy metal concentrations and SNPs. Then, the selected features appear highly correlated with the CVD phenotype, and they could represent targets for future CVD therapies

Hormonal therapy with megestrol in inoperable hepatocellular carcinoma characterized by variant oestrogen receptors

Variant liver oestrogen receptor transcripts in hepatocellular carcinoma are associated with aggressive clinical course and unresponsiveness to tamoxifen. To evaluate the impact on survival and on tumour growth of megestrol (progestin drug acting at post-receptorial level) we enrolled 45 patients with HCC characterized by variant liver oestrogen receptors in a prospective, randomized study with megestrol vs. placebo. Presence of variant oestrogen receptors was determined by RT/PCR. 24 patients were randomized to no treatment and 21 to therapy with megestrol 160 mg day−1. Results were analysed by Kaplan-Meier and Cox methods. Survival of hepatocellular carcinoma characterized by variant oestrogen receptors was extremely poor (median survival 7 months); megestrol significantly improved survival (18 months) (P = 0.0090). Tumour growth at one year was significantly slowed down in megestrol-treated patients (P = 0.0212). Bilirubin levels, presence of portal thrombosis, HBV aetiology and treatment were identified at univariate analysis as factors significantly associated with survival; at multivariate analysis, only megestrol therapy (P = 0.0003), presence of HBV infection (P = 0.0009) and presence of portal vein thrombosis (P = 0.0051) were factors independently related with survival. (1) Megestrol slows down the aggressive tumour growth of patients with hepatocellular carcinoma characterized by variant estrogen receptors and (2) is also able to favourably influence the course of disease, more than doubling median survival. © 2001 Cancer Research Campaignhttp://www.bjcancer.co

Evaluation of microbial contamination of air in two haematology departments equipped with ventilation systems with different filtration devices

Background. Nosocomial infections (NI) are above all due to health-care workers practices, but also the contamination of the environment could lead to their rise in health-care facilities. Introduction. In the last years, the incidence of NI has increased due to a substantial rise in the number of immuno-compromised patients. These patients are often gathered in hospital areas declared at ?high risk? of infection such as Hematology and Bone Marrow Transplant ward. In this study, we evaluated microbial contamination of the air in two divisions with high risk patients, focusing on the validity of the air system with correla- tion to the presence or not of the HEPA absolute filters. Methods. An environmental surveillance study has been carried out in two Divisions of Haematology, in two different Hospitals. Investigations have been performed by sampling air and by analyzing bacterial and fungal growth on microbiology plates after an incubation period. Results. Unit A, without HEPA filters in the ventilation systems, showed a gradual increase in the bacterial load 20 and 60 days after cleaning of the ventilation system. Mycetes and Aspergilli were not present in basal conditions, at 20 or 60 days after decontamination. Unit B, equipped with HEPA filters placed at the inlet vents, showed extremely low values of the bacterial load either in basal conditions or upon inspection 60 days after cleaning. No mycetes were present. Discussion. From the results obtained, it was evident that fol- lowing the cleaning operation, the quality of the air is excellent in both types of equipment, since no mycetes were present and the bacterial load was inf. 20 CFU/mc in all the sites tested. However, although in subsequent controls mycetes were absent in both types of equipment, a great difference in the suspended bacterial load was found: Unit B was close to sterility whereas in Unit A a progressive increase was observed

Clinical evidence in the treatment of rotator cuff tears with hyaluronic acid

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Efficacy and Safety of Neem Oil for the Topical Treatment of Bloodsucking Lice Linognathus stenopsis in Goats under Field Conditions

The aim of the present study was to evaluate the efficacy and safety of neem oil on caprine pediculosis and on kids’ growth performances. The neem (Azadirachta indica) belongs to the Meliaceae family, and in Eastern countries it is mainly considered for the insecticidal activities of the kernel oil. The neem seeds contain bioactive principles, such as azadirachtin A, salannin, nimbin, and nimbolide. The trial was carried out on 24 kids, 120 days old, maintained in open yards. Animals were divided in 4 homogeneous groups (n = 6 animals/group) based on age, louse count, body condition score (BCS) and live body weight: Control Group (C, saline NaCl, 0.9%), Neem Group 1 (NO-100, 100 mL of neem oil per 10 kg), Neem Group 2 (NO-200, 200 mL/10 kg), Neem Group 3 (NO-300, 300 mL/10 kg). The treatments were performed by spraying the insecticide on the goat’s body. The study lasted 56 days, and weekly, the kids underwent louse count, BCS and body weight determination, and FAMACHA score. Data were analyzed by ANOVA for repeated measures. The species of lice identified was Linognathus stenopsis. Kids belonging to NO-200 and NO-300 showed a stronger reduction of louse count throughout the study (>95%). The daily weight gain recorded was significantly higher (p < 0.05) in NO-300 than C. No differences were found for BCS and FAMACHA scores. The results of this trial showed that the administration of neem oil to control caprine pediculosis caused by sucking lice represents an alternative to synthetic compounds

Sparse Exploratory Factor Analysis

Sparse principal component analysis is a very active research area in the last decade. It produces component loadings with many zero entries which facilitates their interpretation and helps avoid redundant variables. The classic factor analysis is another popular dimension reduction technique which shares similar interpretation problems and could greatly benefit from sparse solutions. Unfortunately, there are very few works considering sparse versions of the classic factor analysis. Our goal is to contribute further in this direction. We revisit the most popular procedures for exploratory factor analysis, maximum likelihood and least squares. Sparse factor loadings are obtained for them by, first, adopting a special reparameterization and, second, by introducing additional [Formula: see text]-norm penalties into the standard factor analysis problems. As a result, we propose sparse versions of the major factor analysis procedures. We illustrate the developed algorithms on well-known psychometric problems. Our sparse solutions are critically compared to ones obtained by other existing methods

Piecewise smooth systems near a co-dimension 2 discontinuity manifold: can one say what should happen?

We consider a piecewise smooth system in the neighborhood of a co-dimension 2 discontinuity manifold $\Sigma$. Within the class of Filippov solutions, if $\Sigma$ is attractive, one should expect solution trajectories to slide on $\Sigma$. It is well known, however, that the classical Filippov convexification methodology is ambiguous on $\Sigma$. The situation is further complicated by the possibility that, regardless of how sliding on $\Sigma$ is taking place, during sliding motion a trajectory encounters so-called generic first order exit points, where $\Sigma$ ceases to be attractive. In this work, we attempt to understand what behavior one should expect of a solution trajectory near $\Sigma$ when $\Sigma$ is attractive, what to expect when $\Sigma$ ceases to be attractive (at least, at generic exit points), and finally we also contrast and compare the behavior of some regularizations proposed in the literature. Through analysis and experiments we will confirm some known facts, and provide some important insight: (i) when $\Sigma$ is attractive, a solution trajectory indeed does remain near $\Sigma$, viz. sliding on $\Sigma$ is an appropriate idealization (of course, in general, one cannot predict which sliding vector field should be selected); (ii) when $\Sigma$ loses attractivity (at first order exit conditions), a typical solution trajectory leaves a neighborhood of $\Sigma$; (iii) there is no obvious way to regularize the system so that the regularized trajectory will remain near $\Sigma$ as long as $\Sigma$ is attractive, and so that it will be leaving (a neighborhood of) $\Sigma$ when $\Sigma$ looses attractivity. We reach the above conclusions by considering exclusively the given piecewise smooth system, without superimposing any assumption on what kind of dynamics near $\Sigma$ (or sliding motion on $\Sigma$) should have been taking place.Comment: 19 figure