UNIMIB@NEEL-IT: Named Entity Recognition and Linking of Italian Tweets

Questo articolo descrive il sistema proposto dal gruppo UNIMIB per il task di Named Entity Recognition and Linking applicato a tweet in lingua italiana (NEEL-IT). Il sistema, che rappresenta un approccio iniziale al problema, \ue8 costituito da tre passaggi fondamentali: (1) Named Entity Recognition tramite l\u2019utilizzo di Conditional Random Fields, (2) Named Entity Linking considerando sia approcci supervisionati sia modelli di linguaggio basati su reti neurali, e (3) NIL clustering tramite un approccio basato su grafi.This paper describes the framework proposed by the UNIMIB Team for the task of Named Entity Recognition and Linking of Italian Tweets (NEEL-IT). The proposed pipeline, which represents an entry level system, is composed of three main steps: (1) Named Entity Recognition using Conditional Random Fields, (2) Named Entity Linking by considering both Supervised and Neural-Network Language models, and (3) NIL clustering byusing a graph-based approach

Calving difficulty influences rumination time and inflammatory profile in Holstein dairy cows

Difficult calving may adversely affect dairy cow health and performance. Maternal:fetal disproportion is a major cause of dystocia. Therefore, the main objective of this study was to assess the effects of dam:calf body weight ratio (D:C) on calving difficulty, rumination time, lying time, and inflammatory profile in 25 Holstein dairy cows. Using automatic monitoring systems, we monitored behavior and production in 9 primiparous and 16 pluriparous cows between dry-off and 30 d in milk. During the same period, we collected blood samples to monitor metabolism and inflammatory profile of these cows. Calvings were video recorded to assess calving difficulty and observe the duration of the expulsive stage. After parturition, the cows were separated into 3 classes according to their D:C: easy (E; D:C >17), medium (M; 14 < D:C <17), and difficult (D; D:C <14). The cows in class D showed relatively longer labor durations (108 min vs. 54 and 51 min for classes D, M, and E, respectively) and higher calving assistance rates (50% vs. 0 and 11% of calvings for classes D, M, and E, respectively) than those in the other 2 classes. Compared with the cows in classes M and E, those in class D exhibited shorter rumination times on the day of calving (176 min/d vs. 288 and 354 min/d for classes D, M, and E, respectively) and during the first week of lactation (312 min/d vs. 339 and 434 min/d for classes D, M, and E, respectively) and maintained lower rumination values until 30 DIM (399 min/d vs. 451 and 499 min/d for classes D, M, and E, respectively). Primiparous class D cows had shorter resting times during the first week after calving compared with those in class M (8 vs. 11 h/d for classes D and M, respectively). Interclass differences were found in terms of the levels of inflammation markers such as acute-phase proteins (ceruloplasmin, albumin, retinol, and paraoxonase). Moreover, cows in class D had lower plasma levels of fructosamine and creatinine after calving. Low D:C reduced postcalving rumination time and increased inflammation grade, suggesting a lower welfare of these animals at the onset of lactation. The D:C might serve as a useful index for the identification of cows at relatively higher risk of metabolic and inflammatory disease, thus helping farmers and veterinarians improve the welfare and health of these cows

The accuracy of NIRS in predicting chemical composition and fibre digestibility of hay-based total mixed rations

The aim of this study was to develop near-infrared spectroscopy (NIRS) prediction models for the estimation of chemical components and the fibre undegradable fractions (uNDF) of hay-based total mixed rations (TMR). A total of 205 TMR samples were used for the study. All the chemical components were measured using standard AOAC reference methods and expressed as percentages of dry matter (DM). Prediction models were developed using both cross- and independent validation and different mathematical treatments applied on spectral data. The best spectral treatment was chosen based on the method which simultaneously achieved the lowest root mean square error and the highest explained variance in cross-validation. The coefficient of determination in external validation (R2P) was the greatest for starch prediction model (R2P = 0.84), followed by acid detergent fibre (ADF; R2P = 0.79), and amylase-treated ash-corrected NDF with addition of sodium sulphite (aNDFom) and crude protein prediction models (CP; R2P = 0.73). The concordance correlation coefficient (CCC) in validation ranged from 0.66 (ash prediction model) to 0.92 (starch prediction model), indicating substantial to accurate models’ predictive ability. This study indicated that NIRS can be a screening method for the prediction of CP, Starch, aNDFom, ADF, acid detergent lignin (ADL), uNDF and Ash. The use of TMR utilised in various herds provided high variability for the NIRS calibration dataset, implying that the developed NIRS pre-diction models could be applicable to TMR collected from herds located in the Parmigiano Reggiano cheese production area.Highlights NIRS can be successfully employed to determine quickly and at cost-effective different compositional and digestibility traits in hay-based TMR. TMR analysis predicted by NIRS can support nutritionists in the formulation of diets containing a proper nutrient profile to sustain physiological, metabolic, and immunological processes. The use of NIR technology for TMR analysis can allow frequent monitoring of rations and increasingly timely corrections, maximising cows’ diet utilisation and conversion of the ingested feed

The use of monensin for ketosis prevention in dairy cows during the transition period: A systematic review

Since the approval by the European Medicines Agency in 2013 of a monensin controlled-release capsule (CRC) for the prevention of ketosis in dairy cows, there has been widespread use across Europe. In recent decades, several papers have investigated the effects of monensin used as a CRC or as a feed additive to improve cattle energy metabolism and improve feed efficiency. Since the CRC is the only form of monensin permitted in Europe in dairy cows, the objective of this review was to report and summarize observations from the literature on the effects of this treatment in transition cows. The peer-reviewed literature published from 1997 was scanned, and papers written in English were evaluated for eligibility. Only papers evaluating the use of monensin in dairy cows for the prevention of ketosis during the transition period were reviewed. In total, 42 papers met the required criteria and were included in this review. The major findings focused on cow metabolism and health, rumen fermentation and milk production and quality. Overall, the review of the existing literature confirmed that monensin delivered as a CRC during the transition period has effects of different magnitude compared to other forms, doses or durations of administration. Studies agree on the antiketotic effects of this treatment, showing evidence of an increased propionate production in the rumen, reduced blood β-hydroxybutyrate, and improved liver function in treated cows, mainly resulting in reduced incidence of peripartum disease. On the contrary, the effects of CRC on ammonia production and rumen microflora are less robust than those reported for other forms. Of importance for the European market is the well-documented absence of any negative impact on milk and cheese production and composition using the CRC treatment

In vitro evaluation of sugar digestibility in molasses

Beet and cane molasses mainly contain mono- di-, and tri-saccharides, composed by hexoses, as well as pentoses in traces. However, rationing software consider sugars as only one entity, with a rate of digestion similar to 20% h(-1). The aim of this initial study was to investigate and evaluate the in vitro digestion dynamics and rates of the sugar fraction in molasses. Three beet and three cane molasses were randomly selected from a variety of samples collected world-wide and digested via in vitro rumen fermentation, at 1, 2, 3, 4, 6, 8, and 24 h. Samples were then analysed with a specific enzymatic kit to quantify residual sucrose, glucose, fructose, raffinose, galactose, and arabinose. Complete disappearance of sucrose happened within 3 hours of incubation. Glucose and fructose were completely digested within 4-6 h, showing variability among samples. Even if not so representative, galactose showed a similar trend of digestion (97% digestion within 3-4 h). Raffinose was quite slower in cane molasses, while it was completely digested within 1 h in beet molasses. Arabinose, a pentose, never reached a complete digestion, and its fermentation dynamic was different compared to other sugars. Calculated rates of digestion for sucrose, glucose and fructose, most representative sugars in molasses, were higher than 50% h(-1) in both cane and beet. Obtained results showed that sugar fraction in molasses may vary, and different sugars are rapidly fermented by rumen microbes. Modern rationing models should consider a modification of sugar rates of digestion, since the actual one appears too slow than those observed in vitro

In vitro evaluation of sugar digestibility in molasses

Beet and cane molasses mainly contain mono- di-, and tri-saccharides, composed by hexoses, as well as pentoses in traces. However, rationing software consider sugars as only one entity, with a rate of digestion ∼20% h−1. The aim of this initial study was to investigate and evaluate the in vitro digestion dynamics and rates of the sugar fraction in molasses. Three beet and three cane molasses were randomly selected from a variety of samples collected world-wide and digested via in vitro rumen fermentation, at 1, 2, 3, 4, 6, 8, and 24 h. Samples were then analysed with a specific enzymatic kit to quantify residual sucrose, glucose, fructose, raffinose, galactose, and arabinose. Complete disappearance of sucrose happened within 3 hours of incubation. Glucose and fructose were completely digested within 4-6 h, showing variability among samples. Even if not so representative, galactose showed a similar trend of digestion (97% digestion within 3-4 h). Raffinose was quite slower in cane molasses, while it was completely digested within 1 h in beet molasses. Arabinose, a pentose, never reached a complete digestion, and its fermentation dynamic was different compared to other sugars. Calculated rates of digestion for sucrose, glucose and fructose, most representative sugars in molasses, were higher than 50% h−1 in both cane and beet. Obtained results showed that sugar fraction in molasses may vary, and different sugars are rapidly fermented by rumen microbes. Modern rationing models should consider a modification of sugar rates of digestion, since the actual one appears too slow than those observed in vitro.Highlights Molasses are unique blends of several sugars Major sugars are digested in few hours Rationing software should consider a faster rate of digestion for different sugars

effects of three different diets on the fatty acid profile and sensory properties of fresh pecorino cheese primo sale

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A simulation tool for MRPC telescopes of the EEE project

The Extreme Energy Events (EEE) Project is mainly devoted to the study of the secondary cosmic ray radiation by using muon tracker telescopes made of three Multigap Resistive Plate Chambers (MRPC) each. The experiment consists of a telescope network mainly distributed across Italy, hosted in different building structures pertaining to high schools, universities and research centers. Therefore, the possibility to take into account the effects of these structures on collected data is important for the large physics programme of the project. A simulation tool, based on GEANT4 and using GEMC framework, has been implemented to take into account the muon interaction with EEE telescopes and to estimate the effects on data of the structures surrounding the experimental apparata.A dedicated event generator producing realistic muon distributions, detailed geometry and microscopic behavior of MRPCs have been included to produce experimental-like data. The comparison between simulated and experimental data, and the estimation of detector resolutions is here presented and discussed

New Eco-gas mixtures for the Extreme Energy Events MRPCs: results and plans

The Extreme Energy Events observatory is an extended muon telescope array, covering more than 10 degrees both in latitude and longitude. Its 59 muon telescopes are equipped with tracking detectors based on Multigap Resistive Plate Chamber technology with time resolution of the order of a few hundred picoseconds. The recent restrictions on greenhouse gases demand studies for new gas mixtures in compliance with the relative requirements. Tetrafluoropropene is one of the candidates for tetrafluoroethane substitution, since it is characterized by a Global Warming Power around 300 times lower than the gas mixtures used up to now. Several mixtures have been tested, measuring efficiency curves, charge distributions, streamer fractions and time resolutions. Results are presented for the whole set of mixtures and operating conditions, %. A set of tests on a real EEE telescope, with cosmic muons, are being performed at the CERN-01 EEE telescope. The tests are focusing on identifying a mixture with good performance at the low rates typical of an EEE telescope.Comment: 8 pages, 6 figures, proceedings for the "XIV Workshop on Resistive Plate Chambers and Related Detectors" (19-23 February 2018), Puerto Vallarta, Jalisco State, Mexic