Making sense of consumers' tweets: sentiment outcomes for fast fashion retailers through big data analytics

Purpose- Consumers online interactions, posts, rating and ranking, reviews of products/attractions/restaurants and so on lead to a massive amount of data that marketers might access to improve the decision-making process, by impacting the competitive and marketing intelligence. The aim of this research is to help to develop understanding of consumers online generated contents in terms of positive or negative comments to increase marketing intelligence. Design/Methodology/Approach- The research focuses on the collection of 9,652 tweets referring to three fast fashion retailers of different sizes operating in the UK market, which have been shared among consumers and between consumer and firm, and subsequently evaluated through a sentiment analysis based on machine learning. Findings- Findings provide the comparison and contrast of consumers’ response towards the different retailers, while providing useful guidelines to systematically making sense of consumers’ tweets and enhancing marketing intelligence. Practical Implications- Our research provides an effective and systemic approach to (i) accessing the rich data set on consumers’ experiences based the massive number of contents that consumers generate and share online, and (ii) investigating this massive amount of data to achieve insights able to impact on retailers’ marketing intelligence. Originality/Value- To best of our knowledge, while other authors tried to identify the effect of positive or negative online comments/posts/reviews, the present study is the first one to show how to systematically detect the positive or negative sentiments of shared tweets for improving the marketing intelligence of fast fashion retailers

Sensor network optimization for damage detection on aluminium stiffened helicopter panels

Health and Usage Monitoring Systems (HUMS) has received considerable attention from the helicopter community in recent years with the declared aim to increase flight safety, increase mission reliability, extend duration of life limited components and of course reduce the maintenance costs. The latter is about 25 per cent of the direct operating cost of the helicopter, thus playing an important role especially in the case of the ageing aircrafts. In particular, with respect to helicopter fuselages, only some attempts were carried out to monitor directly on-line the damage accumulation and propagation during life. In this field, and in particular in the military applications, an integrated and reliable system for monitoring the damage in the fuselage and for evaluating the time inspections and remaining life (prognosis) is missing. However, because of the presence of many vibratory loads, the diagnosis of helicopter structures is very critical. From one hand, a very large number of sensors would be needed for a robust appreciation of the structural health, from the other hand the industrialization of the product brings the need for a low impact over the existing structures, or toward a reduction in the allowed amount of sensors. As a result, comes the importance for an optimization of the sensor network, with the aim to find out the regions inside the structure which are the most sensible to a damage and at the same time robust to noise. The aim of the present work is to define a methodology for optimising the sensors position inside an helicopter fuselage panel in order to obtain the best compromise between the simplicity and the robustness of a sensor network. In particular, a Finite Element (FE) model will be used to create a database of various damages inside the structure, thus consequently optimising the network sensitivity to any damage. The evaluation of the network performances is provided when some realistic noise [1,2] is added to the FE calculation

MicroRNA-551b expression profile in low and high-grade cervical intraepithelial neoplasia

OBJECTIVE: To evaluate the expression of microRNA (miR)-551b in patients with low and high grade cervical intraepithelial neoplasia (CIN) and to find an association with high-risk Human Papillomavirus (HR-HPV) infection-related prognostic biomarkers. PATIENTS AND METHODS: The expression level of miR-551b was determined in 50 paraffin-embedded cervical specimens (10 normal squamous epithelium, 18 condylomas, 8 CIN1, and 14 CIN2-3) using quantitative Real-time polymerase chain reaction (qRT-PCR). χ2-test compared miR-551b expression in different diagnosis groups. An Ordered Logistic Regression and a Probit correlation were made to correlate miR-551b expression levels with the cervical tissue histological findings. The immunohistochemical distribution of p16 and Ki-67 according to histopathological findings was also assessed. RESULTS: The distribution of the miR-551b expression profile was significantly lower in CIN1-3 samples compared to other histological diagnosis groups (condyloma and negative). The expression levels were inversely correlated to the cervical pathological grade, from negative to CIN2-3. A 1% increase in miR-551b expression level produced an increase of 19% to the probability of a minor histological grade diagnosis in a range from negative to CIN2-3 and an increase of 13% to the probability of a negative histological grade diagnosis. Among the cases with miR-551b expression < 0.02 (considered as cut-off value) a significant statistical correlation was found between p16 and Ki-67 expression and the diagnosis of CIN2-3. CONCLUSIONS: O ur d ata s howed a s ignificant inverse correlation between miR-551b expression and the histological grading of the lesions, suggesting a tumor suppressive function in the different stages of cervical dysplasia

Calibration of the Prompt L0 Trigger of the Silicon Pixel Detector for the ALICE Experiment

The ALICE Silicon Pixel Detector (SPD) is the innermost detector of the ALICE experiment at LHC. It includes 1200 front-end chips, with a total of ~107 pixel channels. The pixel size is 50 x 425 μm2. Each front-end chip transmits a Fast-OR signal upon registration of at least one hit in its pixel matrix. The signals are extracted every 100 ns and processed by the Pixel Trigger (PIT) system, to generate trigger primitives. Results are then sent within a latency of 800 ns to the Central Trigger Processor (CTP) to be included in the first Level 0 trigger decision. This paper describes the commissioning of the PIT, the tuning procedure of the front-end chips Fast-OR circuit, and the results of operation with cosmic muons and in tests with LHC beam

Economic evaluation of sunitinib versus pazopanib and best supportive care for the treatment of metastatic renal cell carcinoma in Chile: cost-effectiveness analysis and a mixed treatment comparison

© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group. Background: Sunitinib and Pazopanib are two metastatic renal cell carcinoma (MRCC) treatment alternatives, however the health system in Chile does not consider coverage for any. The cost-effectiveness versus relevant comparator was assessed to support evidence-based decision making. Methods: A four health states Markov model was built: first, second line treatments, BSC and death. Benefits were measured in QALYs, and efficacy estimates were obtained from an indirect treatment comparison. A 10-year time horizon and a 3% undifferentiated discount rate were considered. Deterministic and probabilistic sensitivity analyses were performed. Results: The costs of treating MRCC with Sunitinib were higher than Pazopanib and BSC. When comparing Sunitinib versus Pazopanib, the incremental benefit is small favoring Sunitinib (0.03 QALYs). The base case scenario shows an average ICER of PA versus BSC of US$62,327.11/QALY and of US$85,885/QALY for Sunitinib versus Pazopanib. The ICER was most sensitive to the OS relative to BSC, where evidence was associated to important bias. Conclusions: Sunitinib or Pazopanib can be considered cost-effective if a 3 GDP per-capita threshold is assumed. The decision between SU or PA is highly sensitive to the price of the drugs, rather than the outcomes. Therefore, the decision might be made based on cost-minimization exercise

A method for determining the distribution of carbon nanotubes in nanocomposites by electric conductivity

Carbon nanotube (CNT) polymer nanocomposites are one of the most promising materials due to their remarkable mechanical properties as well as the electrical conductivity, which offers the capability of monitoring the deformation and damage of composite structures by measuring the related conductivity variations. However, quantifying the distribution of CNTs inside the material remains a challenge with respects to both experimental and numerical works. In the current study, the electrical conductivity was used to determine the microstructure of CNT-reinforced polymer. By introducing a modified parameter related to the polar angle of CNTs, the mechanical properties as well as the electrical conductivity change with respect to deformation of nanocomposites can be replicated. After validation by experimental data from the multi-walled CNT/polymer nanocompo sites under tensile loading, the capability of the current method was then studied for composites with various weight fractions of nanotubes. (C) 2022 The Authors. Published by Elsevier B.V

Pilot study on the antibacterial activity of hydrogen peroxide and silver ions in the hospital environment

BACKGROUND: Nosocomial environmental contamination plays an important role in the transmission of several health care-associated pathogens. Control of surfaces contamination can reduce the risk of cross-infection in hospitals. The aim of our study is to evaluate the disinfectant effectiveness of hydrogen peroxide and silver ions, against nosocomial multidrug-resistant strains, when it's used directly on surfaces. METHODS: Staphylococcus aureus ATCC 6538, Pseudomonas aeruginosa ATCC 15442 and the same multidrug-resistant clinical isolates were selected to study the effectiveness of the disinfectant used in suspension or on the clean and dirty surface. RESULTS: Regarding the suspension activity test, the hydrogen peroxide and silver ions resulted effective after 5 min for ATCC strains and after 10 min for multidrug-resistant isolates; about the surface activity test, its action resulted after 10 min for ATCC strains and after 15 min for multidrug-resistant isolates. Moreover, it was more effective when used in the absence or in presence of a low concentration of biological materials. CONCLUSIONS: In a complex environment such as hospital wards, to have a disinfectant notoriously effective but more easy and quick to use would be an useful solution to treat small surfaces occasionally contaminated by biological materials

Heterodyne near-field scattering: A technique for complex fluids

The heterodyne near-field scattering (HNFS) technique for studying complex fluids such as colloidal systems was discussed. A different data reduction scheme was adopted which allowed the improvement in performance of the technique, at levels of sensitivity and accuracy much higher than those achievable with classical low-angle light scattering instrumentation. It was observed that this method also relaxes the requirements on the optical/mechanical stability of the experimental setup and allows for a real time analysis. Nonstationary samples, such as aggregating colloidal solutions, were also investigated, and their kinetics quantitatively characterized

Oral contraceptives combined with interferon β in multiple sclerosis

Objective: To test the effect of oral contraceptives (OCs) in combination with interferon b (IFN-b) on disease activity in patients with relapsing-remitting multiple sclerosis (RRMS). Methods: One hundred fifty women with RRMS were randomized in a 1:1:1 ratio to receive IFNb-1a subcutaneously (SC) only (group 1), IFN-b-1a SC plus ethinylstradiol 20 mg and desogestrel 150 mg (group 2), or IFN-b-1a SC plus ethinylestradiol 40 mg and desogestrel 125 mg (group 3). The primary endpoint was the cumulative number of combined unique active (CUA) lesions on brain MRI at week 96. Secondary endpoints included MRI and clinical and safety measures. Results: The estimated number of cumulative CUA lesions at week 96 was 0.98 (95% confidence interval [CI] 0.81–1.14) in group 1, 0.84 (95% CI 0.66–1.02) in group 2, and 0.72 (95% CI 0.53–0.91) in group 3, with a decrease of 14.1% (p 5 0.24) and 26.5% (p 5 0.04) when comparing group 1 with groups 2 and 3, respectively. The number of patients with no gadoliniumenhancing lesions was greater in group 3 than in group 1 (p 5 0.03). No significant differences were detected in other secondary endpoints. IFN-b or OC discontinuations were equally distributed across groups. Conclusions: Our results translate the observations derived from experimental models to patients, supporting the anti-inflammatory effects of OCs with high-dose estrogens, and suggest possible directions for future research