1,952 research outputs found
Canada Update - Highlights of Major Legal News and Significant Court Cases from May 2008 to July 2008
Cluster Headache: What's New?
BACKGROUND: Cluster headache is a highly disabling primary headache disorder which is widely described as the most painful condition a human can experience.
AIM: To provide an overview of the clinical characteristics, epidemiology, risk factors, differential diagnosis, pathophysiology and treatment options of cluster headache, with a focus on recent developments in the field.
METHODS: Structured review of the literature on cluster headache.
RESULTS: Cluster headache affects approximately one in 1000 of the population. It is characterised by attacks of severe unilateral head pain associated with ipsilateral cranial autonomic symptoms, and the tendency for attacks to occur with circadian and circannual periodicity. The pathophysiology of cluster headache and other primary headache disorders has recently become better understood and is thought to involve the hypothalamus and trigeminovascular system. There is good quality evidence for acute treatment of attacks with parenteral triptans and high flow oxygen; preventive treatment with verapamil; and transitional treatment with oral corticosteroids or greater occipital nerve injection. New pharmacological and neuromodulation therapies have recently been developed.
CONCLUSION: Cluster headache causes distinctive symptoms, which once they are recognised can usually be managed with a variety of established treatments. Recent pathophysiological understanding has led to the development of newer pharmacological and neuromodulation therapies, which may soon become established in clinical practice
Titanium Dioxide Modifications for Energy Conversion: Learnings from Dye-Sensitized Solar Cells
During the last two and half decade modifying anatase TiO2 has appreciably enhanced our understanding and application of this semiconducting, non-toxic material. In the domain of DSCs, the main focus has been to achieve band adjustment to facilitate electron injection from anchored dyes, and high electronic mobility for photo-generated electron collection. In retrospection, there is a dire need to assimilate and summarize the findings of these studies to further catalyze the research, better understanding and comparison of the structure–property relationships in modifying TiO2 efficiently for crucial photocatalytic, electrochemical and nanostructured applications. This chapter aims at categorizing the typical approaches used to modify TiO2 in the domain of DSCs such as through TiO2 paste additives, TiO2 doping, metal oxides inclusion, dye solution co-adsorbing additives, post staining surface treatment additives and electrolyte additives. A summary of the consequences of these modifications on electron injection, charge extraction, electronic mobility, conduction band shift and surface states has been presented. This chapter is expected to hugely benefit the researchers employing TiO2 in energy, catalysis and battery applications
Unveiling Global Narratives: A Multilingual Twitter Dataset of News Media on the Russo-Ukrainian Conflict
The ongoing Russo-Ukrainian conflict has been a subject of intense media
coverage worldwide. Understanding the global narrative surrounding this topic
is crucial for researchers that aim to gain insights into its multifaceted
dimensions. In this paper, we present a novel dataset that focuses on this
topic by collecting and processing tweets posted by news or media companies on
social media across the globe. We collected tweets from February 2022 to May
2023 to acquire approximately 1.5 million tweets in 60 different languages.
Each tweet in the dataset is accompanied by processed tags, allowing for the
identification of entities, stances, concepts, and sentiments expressed. The
availability of the dataset serves as a valuable resource for researchers
aiming to investigate the global narrative surrounding the ongoing conflict
from various aspects such as who are the prominent entities involved, what
stances are taken, where do these stances originate, and how are the different
concepts related to the event portrayed.Comment: Dataset can be found at https://zenodo.org/record/804345
Comparative effectiveness of pharmacologic and nonpharmacologic interventions for orthodontic pain relief at peak pain intensity:A Bayesian network meta-analysis
Analysis of temperature variations in fixed-bed columns using non-isothermal and non-equilibrium transport model
A non-isothermal and non-equilibrium two-component lumped kinetic model of fixed-bed column liquid chromatography is formulated with the linearized isotherm and solved analytically to study the influence of temperature variations on the process. The model equations constitute a system of convection-diffusion PDE for mass and energy balances in the bulk phase coupled with differential equations for mass and energy balances in the stationary phase. The analytical solutions are derived for Dirichlet boundary conditions by implementing the Laplace transformation, Tschirnhaus-Vieta approach, the linear decomposition technique and an elementary solution technique of ODE. An efficient and accurate numerical Laplace inversion technique is applied to bring back the solution in the actual time domain. In order to validate the derived analytical solutions for concentration and temperature fronts, the high resolution upwind finite volume scheme is applied to approximate the model equations numerically. Various case studies are carried out assuming realistic model parameters. The results obtained will be beneficial for interpreting mass and energy profiles in non-equilibrium and non-isothermal liquid chromatographic columns and provide deeper insight into the sensitivity of the separation process without performing costly and time-consuming laboratory experiments
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TIB's visual analytics group at MediaEval '20: Detecting fake news on corona virus and 5G conspiracy
Fake news on social media has become a hot topic of research as it negatively impacts the discourse of real news in the public. Specifi-cally, the ongoing COVID-19 pandemic has seen a rise of inaccurate and misleading information due to the surrounding controversies and unknown details at the beginning of the pandemic. The Fak-eNews task at MediaEval 2020 tackles this problem by creating a challenge to automatically detect tweets containing misinformation based on text and structure from Twitter follower network. In this paper, we present a simple approach that uses BERT embeddings and a shallow neural network for classifying tweets using only text, and discuss our findings and limitations of the approach in text-based misinformation detection
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Check square at CheckThat! 2020: Claim Detection in Social Media via Fusion of Transformer and Syntactic Features
In this digital age of news consumption, a news reader has the ability to react, express and share opinions with others in a highly interactive and fast manner. As a consequence, fake news has made its way into our daily life because of very limited capacity to verify news on the Internet by large companies as well as individuals. In this paper, we focus on solving two problems which are part of the fact-checking ecosystem that can help to automate fact-checking of claims in an ever increasing stream of content on social media. For the first prob-lem, claim check-worthiness prediction, we explore the fusion of syntac-tic features and deep transformer Bidirectional Encoder Representations from Transformers (BERT) embeddings, to classify check-worthiness of a tweet, i.e. whether it includes a claim or not. We conduct a detailed feature analysis and present our best performing models for English and Arabic tweets. For the second problem, claim retrieval, we explore the pre-trained embeddings from a Siamese network transformer model (sentence-transformers) specifically trained for semantic textual similar-ity, and perform KD-search to retrieve verified claims with respect to a query tweet
TIB's Visual Analytics Group at MediaEval '20: Detecting Fake News on Corona Virus and 5G Conspiracy
Fake news on social media has become a hot topic of research as it negatively
impacts the discourse of real news in the public. Specifically, the ongoing
COVID-19 pandemic has seen a rise of inaccurate and misleading information due
to the surrounding controversies and unknown details at the beginning of the
pandemic. The FakeNews task at MediaEval 2020 tackles this problem by creating
a challenge to automatically detect tweets containing misinformation based on
text and structure from Twitter follower network. In this paper, we present a
simple approach that uses BERT embeddings and a shallow neural network for
classifying tweets using only text, and discuss our findings and limitations of
the approach in text-based misinformation detection.Comment: MediaEval 2020 Fake News Tas
G × E Interaction and Heterosis in Elite Tomato Hybrids for Growth, Earliness and Fruit Parameters in Diverse Agro-Climatic Zones of Punjab
Six promising tomato hybrids selected from a pool of 60 F1 hybrids were evaluated for seven traits, along with the check hybrid (TH-1) at two locations falling under different agro-climatic zones of Punjab, India. G × E interaction was significant for early yield, fruit weight and total fruit yield, whereas, it was non-significant for fruit number, locule number, pericarp thickness and vine length. Overall higher mean-early-yield, fruit number, fruit weight and total yield at Ludhiana, rather than at Bathinda, may be due to higher organic carbon, available phosphorus and available potash and low electrical conductivity of the experimental soil at Ludhiana. Pooled analysis showed that hybrid TH-21 had the maximum early-yield (3.73 tha-1), fruit weight (72.7 g) and locule number (2.65), whereas, TH-23 had the highest fruit number per vine (53.7) and total fruit yield (51.2 tha-1). The magnitude of pooled standard heterosis was maximum for vine length (140.7%), followed by early yield (114.8%), total yield (88.3%), fruit number (49.7%), fruit weight (27.6%), pericarp thickness (16.4%) and locule number (-21.6%). On the basis of stability and superiority for fruit weight, fruit number, early and total yield, TH-21 was found to be the most promising hybrid, followed by TH-23
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