Real-time traffic event detection using Twitter data

Incident detection is an important component of intelligent transport systems and plays a key role in urban traffic management and provision of traveller information services. Due to its importance, a wide number of researchers have developed different algorithms for real-time incident detection. However, the main limitation of existing techniques is that they do not work well in conditions where random factors could influence traffic flows. Twitter is a valuable source of information as its users post events as they happen or shortly after. Therefore, Twitter data have been used to predict a wide variety of real-time outcomes. This paper aims to present a methodology for a real-time traffic event detection using Twitter. Tweets are obtained through the Twitter streaming application programming interface in real time with a geolocation filter. Then, the author used natural language processing techniques to process the tweets before they are fed into a text classification algorithm that identifies if it is traffic related or not. The authors implemented their methodology in the West Midlands region in the UK and obtained an overall accuracy of 92·86%

Versailles project on advanced materials and standards (VAMAS) interlaboratory study on measuring the number concentration of colloidal gold nanoparticles

We describe the outcome of a large international interlaboratory study of the measurement of particle number concentration of colloidal nanoparticles, project 10 of the technical working area 34, "Nanoparticle Populations" of the Versailles Project on Advanced Materials and Standards (VAMAS). A total of 50 laboratories delivered results for the number concentration of 30 nm gold colloidal nanoparticles measured using particle tracking analysis (PTA), single particle inductively coupled plasma mass spectrometry (spICP-MS), ultraviolet-visible (UV-Vis) light spectroscopy, centrifugal liquid sedimentation (CLS) and small angle X-ray scattering (SAXS). The study provides quantitative data to evaluate the repeatability of these methods and their reproducibility in the measurement of number concentration of model nanoparticle systems following a common measurement protocol. We find that the population-averaging methods of SAXS, CLS and UV-Vis have high measurement repeatability and reproducibility, with between-labs variability of 2.6%, 11% and 1.4% respectively. However, results may be significantly biased for reasons including inaccurate material properties whose values are used to compute the number concentration. Particle-counting method results are less reproducibile than population-averaging methods, with measured between-labs variability of 68% and 46% for PTA and spICP-MS respectively. This study provides the stakeholder community with important comparative data to underpin measurement reproducibility and method validation for number concentration of nanoparticles

Versailles project on advanced materials and standards (VAMAS) interlaboratory study on measuring the number concentration of colloidal gold nanoparticles

We describe the outcome of a large international interlaboratory study of the measurement of particle number concentration of colloidal nanoparticles, project 10 of the technical working area 34, "Nanoparticle Populations" of the Versailles Project on Advanced Materials and Standards (VAMAS). A total of 50 laboratories delivered results for the number concentration of 30 nm gold colloidal nanoparticles measured using particle tracking analysis (PTA), single particle inductively coupled plasma mass spectrometry (spICP-MS), ultraviolet-visible (UV-Vis) light spectroscopy, centrifugal liquid sedimentation (CLS) and small angle X-ray scattering (SAXS). The study provides quantitative data to evaluate the repeatability of these methods and their reproducibility in the measurement of number concentration of model nanoparticle systems following a common measurement protocol. We find that the population-averaging methods of SAXS, CLS and UV-Vis have high measurement repeatability and reproducibility, with between-labs variability of 2.6%, 11% and 1.4% respectively. However, results may be significantly biased for reasons including inaccurate material properties whose values are used to compute the number concentration. Particle-counting method results are less reproducibile than population-averaging methods, with measured between-labs variability of 68% and 46% for PTA and spICP-MS respectively. This study provides the stakeholder community with important comparative data to underpin measurement reproducibility and method validation for number concentration of nanoparticles

Versailles project on advanced materials and standards (VAMAS) interlaboratory study on measuring the number concentration of colloidal gold nanoparticles

We describe the outcome of a large international interlaboratory study of the measurement of particle number concentration of colloidal nanoparticles, project 10 of the technical working area 34, "Nanoparticle Populations" of the Versailles Project on Advanced Materials and Standards (VAMAS). A total of 50 laboratories delivered results for the number concentration of 30 nm gold colloidal nanoparticles measured using particle tracking analysis (PTA), single particle inductively coupled plasma mass spectrometry (spICP-MS), ultraviolet-visible (UV-Vis) light spectroscopy, centrifugal liquid sedimentation (CLS) and small angle X-ray scattering (SAXS). The study provides quantitative data to evaluate the repeatability of these methods and their reproducibility in the measurement of number concentration of model nanoparticle systems following a common measurement protocol. We find that the population-averaging methods of SAXS, CLS and UV-Vis have high measurement repeatability and reproducibility, with between-labs variability of 2.6%, 11% and 1.4% respectively. However, results may be significantly biased for reasons including inaccurate material properties whose values are used to compute the number concentration. Particle-counting method results are less reproducibile than population-averaging methods, with measured between-labs variability of 68% and 46% for PTA and spICP-MS respectively. This study provides the stakeholder community with important comparative data to underpin measurement reproducibility and method validation for number concentration of nanoparticles

Measuring particle size distribution of nanoparticle enabled medicinal products, the joint view of EUNCL and NCI-NCL. A step by step approach combining orthogonal measurements with increasing complexity

The particle size distribution (PSD) and the stability of nanoparticles enabled medicinal products (NEP) in complex biological environments are key attributes to assess their quality, safety and efficacy. Despite its low resolution, dynamic light scattering (DLS) is the most common sizing technique since the onset of NEP in pharmaceutical technologies. Considering the limitations of the existing sizing measurements and the challenges posed by complex NEPs both scientists and regulators encourage the combination of multiple orthogonal high-resolution approaches to shed light in the NEP sizing space (e.g. dynamic light scattering, electron microscopy, field flow fractionation coupled to online sizing detectors, centrifugal techniques, particle tracking analysis and tunable resistive pulse sensing). The pharmaceutical and biotechnology developers are now challenged to find their own pragmatic characterisation approaches, which should be fit for purpose and minimize costs at the same time, in a complicated landscape where only a few standards exist. In order to support the community, the European Nanomedicine Characterisation Laboratory (EUNCL) and the US National Cancer Institute Nanotechnology Characterization Laboratory (NCI-NCL) have jointly developed multiple standard operating procedures (SOPs) for NEP assessment, including the measurements of particle size distribution, and are offering wide access to their ‘state of the art’ characterisation platforms, in addition to making SOPs publicly available. This joint perspective article would like to present the NCI-NCL and EUNCL multi-step approach of incremental complexity to measure particle size distribution and size stability of NEPs, consisting of a quick preliminary step to assess sample integrity and stability by low resolution techniques (pre-screening), followed by the combination of complementary high resolution sizing measurements performed both in simple buffers and in complex biological media. Test cases are presented to demonstrate: i) the need for employing at least one high-resolution sizing technique, ii) the importance of selecting the correct sizing techniques for the purpose, and iii) the robustness of utilizing orthogonal sizing techniques to study the physical properties of complex NEP samples.JRC.F.2-Consumer Products Safet

Automated retrieval of information on threatened species from online sources using machine learning

1. As resources for conservation are limited, gathering and analysing information from digital platforms can help investigate the global biodiversity crisis in a cost-efficient manner. Development and application of methods for automated content analysis of digital data sources are especially important in the context of investigating human-nature interactions. 2. In this study, we introduce novel application methods to automatically collect and analyse textual data on species of conservation concern from digital platforms. An end-to-end pipeline is constructed that begins from searching and downloading news articles about species listed in Appendix I of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) along with news articles from specific Twitter handles and proceeds with implementing natural language processing and machine learning methods to filter and retain only relevant articles. A crucial aspect here is the automatic annotation of training data, which can be challenging in many machine learning applications. A Named Entity Recognition model is then used to extract additional relevant information for each article. 3. The data collected over a 1-month period included 15,088 articles focusing on 585 species listed in Appendix I of CITES. The accuracy of the neural network to detect relevant articles was 95.91% while the Named Entity recognition model helped extract information on prices, location and quantities of traded animals and plants. A regularly updated database, which can be queried and analysed for various research purposes and to inform conservation decision making, is generated by the system. 4. The results demonstrate that natural language processing can be used successfully to extract information from digital text content. The proposed methods can be applied to multiple digital data platforms at the same time and used to investigate human-nature interactions in conservation science and practice.Peer reviewe

In vitro-ex vivo model systems for nanosafety assessment

Engineered nanomaterials have unique and novel properties enabling wide-ranging new applications in nearly all fields of research. As these new properties have raised concerns about potential adverse effects for the environment and human health, extensive efforts are underway to define reliable, cost- and time-effective, as well as mechanistic-based testing strategies to replace the current method of animal testing, which is still the most prevalent model used for the risk assessment of chemicals. Current approaches for nanomaterials follow this line. The aim of this review is to explore and qualify the relevance of new in vitro and ex vivo models in (nano)material safety assessment, a crucial prerequisite for translation into applications

Thionamides inhibit the transcription factor nuclear factor-kappaB by suppression of Rac1 and inhibitor of kappaB kinase alpha

Thionamides, inhibitors of the thyroid peroxidase-mediated iodination, are clinically used in the treatment of hyperthyroidism. However, the use of antithyroid drugs is associated with immunomodulatory effects, and recent studies with thionamide-related heterocyclic thioderivates demonstrated direct anti-inflammatory and immunosuppressive properties. Using primary human T-lymphocytes, we show that the heterocyclic thionamides carbimazole and propylthiouracil inhibit synthesis of the proinflammatory cytokines tumor necrosis factor (TNF)alpha and interferon (IFN)gamma. In addition, DNA binding of nuclear factor (NF)-kappaB, a proinflammatory transcription factor that regulates both TNFalpha and IFNgamma synthesis, and NF-kappaB-dependent reporter gene expression were reduced. Abrogation of NF-kappaB activity was accompanied by reduced phosphorylation and proteolytic degradation of inhibitor of kappaB (IkappaB)alpha, the inhibitory subunit of the NF-kappaB complex. Carbimazole inhibited NF-kappaB via the small GTPase Rac-1, whereas propylthiouracil inhibited the phosphorylation of IkappaBalpha by its kinase inhibitor of kappaB kinase alpha. Methimazole had no effect on NF-kappaB induction, demonstrating that drug potency correlated with the chemical reactivity of the thionamide-associated sulfur group. Taken together, our data demonstrate that thioureylenes with a common, heterocyclic structure inhibit inflammation and immune function via the NF-kappaB pathway. Our results may explain the observed remission of proinflammatory diseases upon antithyroid therapy in hyperthyroid patients. The use of related thioureylenes may provide a new therapeutic basis for the development and application of anti-inflammatory compounds

Carbon monoxide inhalation reduces pulmonary inflammatory response during cardiopulmonary bypass in pigs

BACKGROUND: Cardiopulmonary bypass (CPB) is associated with pulmonary inflammation and dysfunction. This may lead to acute lung injury and acute respiratory distress syndrome with increased morbidity and mortality. The authors hypothesized that inhaled carbon monoxide before initiation of CPB would reduce inflammatory response in the lungs. METHODS: In a porcine model, a beating-heart CPB was used. The animals were either randomized to a control group, to standard CPB, or to CPB plus carbon monoxide. In the latter group, lungs were ventilated with 250 ppm inhaled carbon monoxide in addition to standard ventilation before CPB. Lung tissue samples were obtained at various time points, and pulmonary cytokine levels were determined. RESULTS: Hemodynamic parameters were largely unaffected by CPB or carbon monoxide inhalation. There were no significant differences in cytokine expression in mononuclear cells between the groups throughout the experimental time course. Compared with standard CPB animals, carbon monoxide significantly suppresses tumor necrosis factor-alpha and interleukin-1beta levels (P < 0.05) and induced the antiinflammatory cytokine interleukin 10 (P < 0.001). Carbon monoxide inhalation modulates effector caspase activity in lung tissue during CPB. CONCLUSIONS: The results demonstrate that inhaled carbon monoxide significantly reduces CPB-induced inflammation via suppression of tumor necrosis factor alpha, and interleukin-1beta expression and elevation of interleukin 10. Apoptosis induced by CPB was associated with caspase-3 activation and was significantly attenuated by carbon monoxide treatment. Based on the observations of this study, inhaled carbon monoxide could represent a potential new therapeutic modality for counteracting CPB-induced lung injury