In this paper advanced Sentiment Analysis techniques were applied to evaluate public opinions reported by rail users with respect to four major European railway companies, i.e., Trenitalia and Italo in Italy, SNCF in France and Renfe in Spain. Two powerful language models were used, RoBERTa and BERT, to analyze big amount of text data collected from a social platform dedicated to customers reviews, i.e., TrustPilot. Data concerning the four European railway companies were first collected and classified into subcategories related to different aspects of the railway sector, such as train punctuality, quality of on-board services, safety, etc. Then, the RoBERTa and BERT models were developed to understand context and nuances of natural language. This study provides a useful support for railways companies to promote strategies for improving their service.

We report on the measurement of the response of Rhodamine 6G (R6G) dye to enhanced local surface plasmon resonance (LSPR) using a plasmonic-active nanostructured thin gold film (PANTF) sensor. This sensor features an active area of approximately ≈ 2.5 × 10¹³ nm² and is immobilized with gold nanourchins (GNU) on a thin gold film substrate (TGFS). The hexane-functionalized TGFS was immobilized with a 90 nm diameter GNU via the strong sulfhydryl group (SH) thiol bond and excited by a 637 nm Raman probe. To collect both Raman and SERS spectra, 10 μL of R6G was used at concentrations of 1 μM (6 × 10¹² molecules) and 10 mM (600 × 10¹⁴ molecules), respectively. FT-NIR showed a higher reflectivity of PANTF than TGFS. SERS was performed three times at three different laser powers for TGFS and PANTF with R6G. Two PANTF substrates were prepared at different GNU incubation times of 10 and 60 min for the purpose of comparison. The code for processing the data was written in Python. The data was filtered using the filtfilt filter from scipy.signals, and baseline corrected using the Improved Asymmetric Least Squares (ISALS) function from the pybaselines.Whittaker library. The results were then normalized using the minmax_scale function from sklearn.preprocessing. Atomic force microscopy (AFM) was used to capture the topography of the substrates. Signals exhibited a stochastic fluctuation in intensity and shape. An average corresponding enhancement factor (EF) of 0.3 × 10⁵ and 0.14 × 10⁵ was determinedforPANTFincubated at 10 and 60 min, respectively.

The development and expansion of economies depend heavily on entrepreneurship, and Malaysia is no exception. Understanding the underlying elements that impact the success or failure of user adoption behaviour of online shopping activities is significant since entrepreneurship is critical in driving economic growth and innovation. The study includes 73 articles published from 2004 to the last of 2023 from Science Direct, Scopus, Google Scholar, and Web of Science. We utilised qualitative methods and systematic review issues through the findings of “qualitative” studies as the last step inside a systematic review using Nvivo14. Our study’s result illustrated that applying the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) in Malaysian e-commerce validates the relevance of established theoretical frameworks. This study explores the relationship between 20 independent variables and five mediator factors, with dependent variables, e-commerce in Malaysia. The results highlight the intricate relationships between these variables and their importance for companies, decision-makers, and other stakeholders involved in Malaysian infrastructure financing. This review provides legislators, educators, researchers, and businesspeople with new knowledge in Malaysia so that decision-makers, investors, and aspiring entrepreneurs can make informed decisions.

Surface-enhanced Raman scattering (SERS) spectrum has the characteristics of fast-detection, high-sensitivity and low-requirements for sample pretreatment. It plays a more and more important role in the detection of organic pollutants. In this study, MIL-101 and Au nanoparticles were prepared by hydrothermal method and aqueous solution reduction method respectively, and MIL-101/Au composite nanoparticles were prepared by electrostatic interaction. The SERS properties of the composite substrate were optimized by adjusting the size of Au nanoparticles and the surface distribution density of MIL-101 nanoparticles. The detection limit of Rhodamine 6G (R6G) for the composite substrate with the optimal ratio was investigated, which was as low as 10^–11 M. It is proved that MIL-101/Au composite nanoparticles have high sensitivity to probe molecules. When they are applied to the detection of persistent organic pollutants, the detection limit for fluoranthene can reach 10^–9 M and for 3,3’,4,4’-tetrachlorobiphenyl (PCB-77) can reach 10^–5 M.

The purpose of this study is to predict the frequency of mortality from urban traffic injuries for the most vulnerable road users before, during and after the confinement caused by COVID-19 in Santiago de Cali, Colombia. Descriptive statistical methods were applied to the frequency of traffic crash frequency to identify vulnerable road users. Spatial georeferencing was carried out to analyze the distribution of road crashes in the three moments, before, during, and after confinement, subsequently, the behavior of the most vulnerable road users at those three moments was predicted within the framework of the probabilistic random walk. The statistical results showed that the most vulnerable road user was the cyclist, followed by motorcyclist, motorcycle passenger, and pedestrian. Spatial georeferencing between the years 2019 and 2020 showed a change in the behavior of the crash density, while in 2021 a trend like the distribution of 2019 was observed. The predictions of the daily crash frequencies of these road users in the three moments were very close to the reported crash frequency. The predictions were strengthened by considering a descriptive analysis of a range of values that may indicate the possibility of underreporting in cases registered in the city’s official agency. These results provide new elements for policy makers to develop and implement preventive measures, allocate emergency resources, analyze the establishment of policies, plans and strategies aimed at the prevention and control of crashes due to traffic injuries in the face of extraordinary situations such as the COVID-19 pandemic or other similar events.

Participation in the implementation of green values that are becoming a global norm often experiences challenges. In response with trends of social media use, a study of barriers to green product purchase intention among social media users is conducted. By descriptive qualitative approach, three keywords are employed, namely: (1) “barriers to green consumption”; (2) “barriers of purchase intention; and (3) “social media use and barriers to green consumption”. The findings reveal: (1) the study of barriers to green product purchase intention among social media users has been gaining importance for future research; (2) the potential future research area includes: (a) the level of belief in green products purchase intention that explains the rationalization of green consumption (green knowledge); and (b) the use of digital media through the role of social media in promoting green consumption (green promotion). The theoretical implication emphasizes contribution to the theory of sustainable marketing, namely barriers as dynamics of market interactivity that are capable of generating responsiveness leading to business competitiveness. While practical implication is shown in business efforts to transform challenges into opportunity.