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This work presents a method for early detection of epileptic seizures from EEG data, taking into account information about both the temporal and the spatial evolution of the seizures. The system was designed using over 8 hours of EEG, including 10 seizures in 5 patients. Seizure detection was accomplished in three main stages: multiresolution overcomplete decomposition by the à-trous algorithm, feature extraction by computing power spectral density and sample entropy values of subbands and detection by using z-test and support vector machines (SVM). Results highlight large differences between the sub-band sample entropy values during ictal and normal EEG epochs, respectively, reveling a substantial increase of such parameter during the crisis. This enables high detection accuracy and specificity especially in beta and gamma bands (16-125 Hz). The detection performance of the proposed method was evaluated based on the ground truth provided by the expert neurophysiologist, and the results show that our technique is capable to obtain a high accuracy (above the 95% on average), with a high temporal resolution. This enables reaching very low detection latency and early detection of the seizures onset. Furthermore, spatial information, within the limits of the acquisition, on the evolution of the crisis is maintained since all the channels are separately processed.

We review the etiology and age incidence of precocious puberty in 438 girls examined between 1988-1998; 428 (97.7%) had central precocious puberty (CPP), the remaining 10 (2.3%) gonadotropin-independent precocious puberty (GIPP) of ovarian origin. The majority of CPP girls (59.6%) were aged between 7-7.9 yr, 22.4% were 6 year olds, and only 18% were under 6 years old. Cranial CT and/or MRI performed in 304/428 girls, showed neurogenic abnormalities in 56/304 (18.4%) CPP girls; 30 (9.9%) were due to previously diagnosed intracranial abnormalities and the remaining 26 (8.5%) were detected at the diagnosis of CPP. The frequency of neurogenic CPP tended to be higher in girls under 4 years of age while the frequency of idiopathic CPP tended to be higher in girls aged between 7-7.9 years, but no statistically significant differences were found. Interestingly, some CNS anomalies either of tumoral or congenital origin were detected at presentation in 7% of the girls aged over 7 years. Other related or coincidental clinical anomalies, mainly due to genetic diseases, were observed in 22/304 (7.2%) patients. History of precocious maternal menarche was found in 12/304 (4%) girls. In conclusion, idiopathic CPP was observed in 74% of the girls in this study. Neurogenic anomalies or other coincidental or related clinical findings were observed in the remaining 26%. The increased frequency of idiopathic CPP in girls aged over 7 years may suggest an early, but otherwise normal onset of puberty in many of these girls as a consequence of the trend towards earlier maturation. Nonetheless, the finding of CNS anomalies also in the older patients, raises the question of whether these patients should undergo a complete diagnostic work-up.

Purpose Establishing thought leadership by disseminating relevant digital content through social media has become one of the main priorities for marketers in business-to-business (B2B) settings. However, academic research has only recently started to address this phenomenon. In particular, researchers have not yet examined whether and how thought leadership positively influences a firm’s relationship with its customers. This paper aims to propose and test a model to explain how a firm’s thought leadership improves its customer relationship performance. Design/methodology/approach A cross-sectional research design was applied using covariance-based structural equation modeling to estimate the suggested model. Data were collected from a sample of 160 firms in different industries that create and share content on social media. Findings Thought leadership on social media positively influences brand performance and, in turn, customer relationship performance in B2B settings. Moreover, establishing thought leadership on social media results from specific thought leadership capabilities and is supported by social media capabilities. Research limitations/implications This study advances knowledge on social media thought leadership in B2B settings by proposing and testing a model that combines available insights from three distinct but interrelated B2B streams of studies: branding, social media marketing and thought leadership. Moreover, this study conceptualizes the effects of thought leadership, which is consistent with the relational nature of B2B settings. In fact, it explores thought leadership as a means to maintain and strengthen business relationships. However, further studies are needed to explore detailed strategies that affect the effectiveness of thought leadership. Practical implications The results provide managers with evidence on the effectiveness of a thought leadership strategy. Establishing thought leadership on social media can help to nurture customer relationships over time. By sharing valuable content, suppliers can continuously demonstrate their cutting-edge competences and expertise, thus keeping their brand relevant to customers. Originality/value This is the first study to provide evidence of the benefits of social media thought leadership on customer relationships in B2B settings.

Standardization of cardiac troponin I (cTnI) immunoassays remains an unmet target and comparability of current commercial methods is modest. We hence planned a study to investigate whether realignment of cTnI data by means of reference samples may improve comparability among different cTnI methods. Seventy six routine serum samples were collected in one center, centrifuged, aliquoted and shipped to participant centers, along with four additional reference serum samples with defined cTnI concentrations. The centers performed blind measurement of thawed aliquots and reference samples using four widespread contemporary-sensitive immunoassays (Ortho-Clinical Diagnostics Vitros cTnI ES, Beckman Coulter DXI 800 AccuTnI, Siemens Healthcare Diagnostics Dimension Vista cTnI and Abbott Diagnostics Architect STAT cTnI). Test results were analyzed as provided by the centers, and also after data alignment by means of polynomial regression parameters obtained on reference sera. In five out of six circumstances the Deming fit improved after harmonization. The median inter-assay variability increased from 22% to 53% after alignment with polynomial regression parameters. A reduction of bias was observed in half of the circumstances, whereas in the remaining the bias increased. After harmonization, the agreement at diagnostic thresholds decreased in 4 out of 6 circumstances. These results show that calibration may only be a minor contributor of inter-assay variability of commercial cTnI immunoassays. Harmonization by means of reference sera was also counterproductive for improving methods agreement around a diagnostic threshold.