Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness and safety of a cream product containing zinc oxide for alleviating mosquito bite symptoms

Abstract BACKGROUND: People frequently experience discomfort with immediate wheal, delayed papules, and pruritus from mosquito bites. A topical cream product containing zinc oxide is commercially available for the management of insect bites, but there has been no published evidence for its effectiveness and safety. AIMS: To evaluate the effectiveness and safety of this product in symptoms caused by mosquito bites. METHODS: An open-label, controlled study was performed on 41 healthy participants. All subjects received Aedes aegypti mosquito bites on the forearm. Then test product was randomly applied to the bitten areas of the left or right arm. The other arm was left untreated (control). The onset of pruritus relief was noted. The severity of pruritus was assessed using a visual analogue scale (VAS), ranging from 0 mm (no pruritus) to 100 mm (severe pruritus), and a 4-point pruritus score (0 = none; 1 = mild, not affecting normal activities; 2 = moderate, affecting normal activities to some extent; 3 = severe, significantly affecting activities) at four time points: 15 minutes after the mosquito bite (baseline), as well as 1 hour, 24 hours, and 48 hours after initiating treatment. The size of the bite reaction lesion was also measured at all time points. Any local cutaneous adverse reactions observed during the study were documented. RESULTS: The onset of pruritus relief in the treated group (25 ± 21.7 minutes) was significantly faster compared to the untreated group (118.7 ± 304.8 minutes). The reduction in VAS score at 1 hour was significantly greater in the product group (30.5 ± 16.22) compared to the control group (14.9 ± 9.9). Moreover, there was a significant difference in the reduction of pruritus score at 1 hour, with the product group (1.1 ± 0.5) showing a higher reduction compared to the control group (0.3 ± 0.4). However, there was no significant difference in the reduction of bite lesion size between the two groups. Throughout the study, no adverse events were reported. CONCLUSION: Our preliminary findings indicate that the product effectively reduces pruritus caused by mosquito bites but does not have a significant impact on the size of the bite lesions. The product was found to be safe and may be an option for managing mosquito bites pruritus.
The potential impact of GLP‐1 agonists on obstructive sleep apnoea

What are the potential downsides? Although these medications are generally well tolerated, a small proportion will experience limiting side-effects, particularly gastrointestinal. There are also contraindications, most notably those with a history (or family history) of medullary carcinoma of the thyroid, pancreatitis or during pregnancy. Further, their benefits in the elderly are less clear. More importantly, when patients stop these medications, most will have rebound weight gain. On average patients regain two-thirds of the weight initially lost over a 12-month period. 10 This means that if these medications are commenced as a treatment for OSA with obesity, we are con-signing them to long-term (potentially indefinite) therapy if they want to maintain the benefits. This plays into the final concern, which is how as a society do we afford these medications? Even if we only consider OSA, rather than obesity itself, it is estimated that just under 1 billion people around the world have OSA, 11 the majority of whom will be overweight or obese. The high cost of the medications combined with the high prevalence of OSA means that there is no way that universal healthcare funding schemes can afford these medications, unless strict criteria are in place to prioritize those who can gain subsidized access and/or a duration of use limit is in place. 12 This will no doubt exacerbate inequities in healthcare access and outcome between those from lower versus higher socioeconomic populations, as the attributable benefit from GLP-1 agonists is likely to be dependent on a patient ’ s ability to afford them.
RETINITIS PIGMENTOSA ASSOCIATED WITH THE EYS C2139Y VARIANT

Supplemental Digital Content is Available in the Text. The EYS C2139Y variant is a prevalent cause of blinding retinitis pigmentosa in East Asian populations. C2139Y was causative for retinitis pigmentosa in 11.3% of unrelated individuals with retinitis pigmentosa in Singapore. Approximately 0.66% of Singaporean Chinese and 0.34% of East Asians carry this variant, making it very attractive for targeted therapy. Purpose: The study aimed to describe the phenotypic features of retinitis pigmentosa (RP) associated with the previously described EYS C2139Y variant in Singaporeans and establish the importance of this variant as a prevalent cause of RP among East Asians. Methods: A clinical phenotyping and exome-sequencing study was conducted on consecutive patients with nonsyndromic RP. Epidemiological analysis was performed using Singaporean and global population-based genetic data. Results: A study of 150 consecutive unrelated individuals with nonsyndromic RP found that 87 (58%) of cases had plausible genotypes. A previously described missense variant in the EYS gene, 6416G>A (C2139Y), occurred heterozygously or homozygously in 17 of 150 families (11.3%), all with autosomal recessive RP. Symptom onset in EYS C2139Y-related RP ranged from 6 to 45 years, with visual acuity ranging from 20/20 at 21 years to no light perception by 48 years. C2139Y-related RP had typical findings, including sectoral RP in cases with EYS E2703X in trans. The median age at presentation was 45 years and visual fields declined to less than 20° (Goldmann V4e isopter) by age 65 years. Intereye correlation for visual acuity, fields, and ellipsoid band width was high (r2 = 0.77–0.95). Carrier prevalence was 0.66% (allele frequency of 0.33%) in Singaporean Chinese and 0.34% in East Asians, suggesting a global disease burden exceeding 10,000 individuals. Conclusion: The EYS C2139Y variant is common in Singaporean RP patients and other ethnic Chinese populations. Targeted molecular therapy for this single variant could potentially treat a significant proportion of RP cases worldwide.
Influence of the Antarctic Oscillation on the South Atlantic Convergence Zone

The South Atlantic convergence zone (SACZ) is the main summer-typical atmospheric phenomenon occurring in South America, and it is of great interest because it regulates the rainy season in the most populated regions of Brazil. Frequency variability, persistence, and geographical position of the SACZ and its relationship with intraseasonal variability is well described in the literature. However, the influence of extratropical forcing on the SACZ is not well understood. Consequently, the aim of this study is to evaluate the role of the Antarctic Oscillation (AAO) in SACZ events. The persistence and frequencies of SACZ events, mean, standard deviation of total precipitation per event, lag composite of daily precipitation and geopotential height anomalies were obtained for each phase of the AAO. Therefore, frequency, persistence and total precipitation of SACZ events were higher in positive AAO (AAO+) than negative AAO (AAO−). A teleconnection mechanism between the extratropics and the SACZ region is evident in AAO+, through intensification of the polar and subtropical jets, in the days preceding SACZ. The same was not observed in the AAO−, where the anomalies were confined in the subtropical region and displaced to the South Atlantic Ocean.
INTEGRATING MACULAR OPTICAL COHERENCE TOMOGRAPHY WITH ULTRAWIDE-FIELD IMAGING IN A DIABETIC RETINOPATHY TELEMEDICINE PROGRAM USING A SINGLE DEVICE

Integration of optical coherence tomography with ultrawide-field imaging markedly increased the detection and reduced false-positive assessments of diabetic macular edema and epiretinal membrane. This approach could substantially improve disease identification and assessment accuracy in a space and time-efficient manner for large-scale, diabetic retinopathy, telemedicine screening programs. Purpose: To determine the effect of combined macular spectral-domain optical coherence tomography (SD-OCT) and ultrawide field retinal imaging (UWFI) within a telemedicine program. Methods: Comparative cohort study of consecutive patients with both UWFI and SD-OCT. Ultrawide field retinal imaging and SD-OOCT were independently evaluated for diabetic macular edema (DME) and nondiabetic macular abnormality. Sensitivity and specificity were calculated with SD-OCT as the gold standard. Results: Four hundred twenty-two eyes from 211 diabetic patients were evaluated. Diabetic macular edema severity by UWFI was as follows: no DME 93.4%, noncenter involved DME (nonciDME) 5.1%, ciDME 0.7%, ungradable DME 0.7%. SD-OCT was ungradable in 0.5%. Macular abnormality was identified in 34 (8.1%) eyes by UWFI and in 44 (10.4%) eyes by SD-OCT. Diabetic macular edema represented only 38.6% of referable macular abnormality identified by SD-OCT imaging. Sensitivity/specificity of UWFI compared with SD-OCT was 59%/96% for DME and 33%/99% for ciDME. Sensitivity/specificity of UWFI compared with SDOCT was 3%/98% for epiretinal membrane. Conclusion: Addition of SD-OCT increased the identification of macular abnormality by 29.4%. More than 58.3% of the eyes believed to have any DME on UWF imaging alone were false-positives by SD-OCT. The integration of SD-OCT with UWFI markedly increased detection and reduced false-positive assessments of DME and macular abnormality in a teleophthalmology program.
Recent Advances in the Measurement Error Literature

This article reviews recent significant progress made in developing estimation and inference methods for nonlinear models in the presence of mismeasured data that may or may not conform to the classical assumption of independent zero-mean errors. The aim is to cover a broad range of methods having differing levels of complexity and strength of the required assumptions. Simple approaches that form the elementary building blocks of more advanced approaches are discussed first. Then, special attention is devoted to methods that rely on readily available auxiliary variables (e.g., repeated measurements, indicators, or instrumental variables). Results relaxing most of the commonly invoked simplifying assumptions are presented (linear measurement structure, independent errors, zero-mean errors, availability of auxiliary information). This article also provides an overview of important connections with related fields, such as latent variable models, nonlinear panel data, factor models, and set identification, and applications of the methods to other fields traditionally unrelated to measurement error models.
Champs de vecteurs, théorème d'approximation de Meyers-Serrin et phénomène de Lavrentev pour des fonctionnelles dégénérées

Nous prouvons la densite des fonctions regulieres dans les espaces de Sobolev et de type BV associes a une famille de champs de vecteurs lipschitziens. Ces resultats sont appliques a l'etude des proprietes de minimum de certaines fonctionnelles non coercives
Hyperspectral instrumentation to image and characterize the fluorescence of materials

Optical instruments for space applications with improved performances (smaller pixels and spectral range extension) are becoming more and more sensitive to chemical contamination and particle sedimentation. Outgassing under vacuum conditions causes dramatic flux losses, especially in the UV bandwidth. Furthermore, it is difficult to perform physicochemical analyses of contaminated surfaces on flight models, in a clean room. Conventional analytical techniques such as FTIR (Fourier Transform Infrared interferometer) need the tool to be in contact with the studied area, which is forbidden when working on satellites. In addition, it does not give any information about the distribution of the contaminants in the field of view. The probed area is large, mono-pixel, and the sensitivity of the instrument is too low for hundred nanometer thin film deposits. A first study has shown that we could benefit from using the UV/visible fluorescence spectra to partially identify contaminants and polymer materials. The shape of the fluorescence spectra of adhesives, paints and varnishes have specific signatures that could be recorded into a designated reference database. The location of the presence of these contaminants on such sensitive optics is also relevant. To acquire both these parameters, we designed a specific compact hyperspectral instrument to remotely acquire cube images (500x500 pixels) in a 5 degree field of view, and on a wide range of continuous wavelengths from UV at 320 nm up to the near infrared at 1000 nm. This paper will present the chosen trade-off between different critical optics for a new portable version of this instrument. It is dedicated to space and cultural heritage applications and the first results on an engineering prototype will be shown.
Smartphone Stories: Experiences of Blind and Low Vision Older Adults in Acquiring a Smartphone

Older adults experience challenges with adopting novel technology due to intrinsic and social factors. However, the mobile phone adoption experiences of blind and low vision (BLV) older adults have largely been unexplored. We shed light on the socio-technical aspects of mobile phone adoption based on deep qualitative interviews with five BLV adults aged 60 and above. We found that narratives of smartphone accessibility can be misleading, expert knowledge is needed although scarce, and although smartphones increase access to society, using a smartphone with accessibility features for BLV people can be isolating. We present design implications for smartphones in order to improve shared access to the phone environment and to support inclusion and independent learning following smartphone adoption.
Evaluating Zero-Shot Event Structures: Recommendations for Automatic Content Extraction (ACE) Annotations

Zero-shot event extraction (EE) methods infer richly structured event records from text, based only on a minimal user specification and no training examples, which enables flexibility in exploring and developing applications. Most event extraction research uses the Automatic Content Extraction (ACE) annotated dataset to evaluate supervised EE methods, but can it be used to evaluate zero-shot and other low-supervision EE? We describe ACE’s event structures and identify significant ambiguities and issues in current evaluation practice, including (1) coreferent argument mentions, (2) conflicting argument head conventions, and (3) ignorance of modality and event class details. By sometimes mishandling these subtleties, current work may dramatically understate the actual performance of zero-shot and other low-supervision EE, considering up to 32% of correctly identified arguments and 25% of correctly ignored event mentions as false negatives. For each issue, we propose recommendations for future evaluations so the research community can better utilize ACE as an event evaluation resource.
Unsupervised Graph-Text Mutual Conversion with a Unified Pretrained Language Model

Graph-to-text (G2T) generation and text-to-graph (T2G) triple extraction are two essential tasks for knowledge graphs. Existing unsupervised approaches become suitable candidates for jointly learning the two tasks due to their avoidance of using graph-text parallel data. However, they adopt multiple complex modules and still require entity information or relation type for training. To this end, we propose INFINITY, a simple yet effective unsupervised method with a unified pretrained language model that does not introduce external annotation tools or additional parallel information. It achieves fully unsupervised graph-text mutual conversion for the first time. Specifically, INFINITY treats both G2T and T2G as a bidirectional sequence generation task by fine-tuning only one pretrained seq2seq model. A novel back-translation-based framework is then designed to generate synthetic parallel data automatically. Besides, we investigate the impact of graph linearization and introduce the structure-aware fine-tuning strategy to alleviate possible performance deterioration via retaining structural information in graph sequences. As a fully unsupervised framework, INFINITY is empirically verified to outperform state-of-the-art baselines for G2T and T2G tasks. Additionally, we also devise a new training setting called cross learning for low-resource unsupervised information extraction.
XDailyDialog: A Multilingual Parallel Dialogue Corpus

High-quality datasets are significant to the development of dialogue models.However, most existing datasets for open-domain dialogue modeling are limited to a single language.The absence of multilingual open-domain dialog datasets not only limits the research on multilingual or cross-lingual transfer learning, but also hinders the development of robust open-domain dialog systems that can be deployed in other parts of the world.In this paper, we provide a multilingual parallel open-domain dialog dataset, XDailyDialog, to enable researchers to explore the challenging task of multilingual and cross-lingual open-domain dialog. XDailyDialog includes 13K dialogues aligned across 4 languages (52K dialogues and 410K utterances in total). We then propose a dialog generation model, kNN-Chat, which has a novel kNN-search mechanism to support unified response retrieval for monolingual, multilingual, and cross-lingual dialogue. Experiment results show the effectiveness of this framework. We will make XDailyDialog and kNN-Chat publicly available soon.
Bi-Phone: Modeling Inter Language Phonetic Influences in Text

A large number of people are forced to use the Web in a language they have low literacy in due to technology asymmetries. Written text in the second language (L2) from such users often contains a large number of errors that are influenced by their native language (L1). We propose a method to mine phoneme confusions (sounds in L2 that an L1 speaker is likely to conflate) for pairs of L1 and L2.These confusions are then plugged into a generative model (Bi-Phone) for synthetically producing corrupted L2 text.Through human evaluations, we show that Bi-Phone generates plausible corruptions that differ across L1s and also have widespread coverage on the Web.We also corrupt the popular language understanding benchmark SuperGLUE with our technique (FunGLUE for Phonetically Noised GLUE) and show that SoTA language understating models perform poorly.We also introduce a new phoneme prediction pre-training task which helps byte models to recover performance close to SuperGLUE. Finally, we also release the SuperGLUE benchmark to promote further research in phonetically robust language models. To the best of our knowledge, FunGLUE is the first benchmark to introduce L1-L2 interactions in text.
Constrained Tuple Extraction with Interaction-Aware Network

Tuples extraction is a fundamental task for information extraction and knowledge graph construction. The extracted tuples are usually represented as knowledge triples consisting of subject, relation, and object. In practice, however, the validity of knowledge triples is associated with and changes with the spatial, temporal, or other kinds of constraints. Motivated by this observation, this paper proposes a constrained tuple extraction (CTE) task to guarantee the validity of knowledge tuples. Formally, the CTE task is to extract constrained tuples from unstructured text, which adds constraints to conventional triples. To this end, we propose an interaction-aware network. Combinatorial interactions among context-specific external features and distinct-granularity internal features are exploited to effectively mine the potential constraints. Moreover, we have built a new dataset containing totally 1,748,826 constrained tuples for training and 3656 ones for evaluation. Experiments on our dataset and the public CaRB dataset demonstrate the superiority of the proposed model. The constructed dataset and the codes are publicly available.
A Cross-Modality Context Fusion and Semantic Refinement Network for Emotion Recognition in Conversation

Emotion recognition in conversation (ERC) has attracted enormous attention for its applications in empathetic dialogue systems. However, most previous researches simply concatenate multimodal representations, leading to an accumulation of redundant information and a limited context interaction between modalities. Furthermore, they only consider simple contextual features ignoring semantic clues, resulting in an insufficient capture of the semantic coherence and consistency in conversations. To address these limitations, we propose a cross-modality context fusion and semantic refinement network (CMCF-SRNet). Specifically, we first design a cross-modal locality-constrained transformer to explore the multimodal interaction. Second, we investigate a graph-based semantic refinement transformer, which solves the limitation of insufficient semantic relationship information between utterances. Extensive experiments on two public benchmark datasets show the effectiveness of our proposed method compared with other state-of-the-art methods, indicating its potential application in emotion recognition. Our model will be available at https://github.com/zxiaohen/CMCF-SRNet.
Hunt for Buried Treasures: Extracting Unclaimed Embodiments from Patent Specifications

Patent applicants write patent specificationsthat describe embodiments of inventions.Some embodiments are claimed for a patent,while others may be unclaimeddue to strategic considerations.Unclaimed embodiments may be extracted byapplicants later and claimed incontinuing applications togain advantages over competitors.Despite being essential for corporate intellectual property (IP) strategies,unclaimed embodiment extraction is conducted manually,and little research has been conducted on its automation.This paper presents a novel task ofunclaimed embodiment extraction (UEE)and a novel dataset for the task.Our experiments with Transformer-based modelsdemonstratedthat the task was challenging as it requiredconducting natural language inference onpatent specifications, which consisted oftechnical, long, syntactically and semanticallyinvolved sentences.We release the dataset and code to foster this new area of research.
Controle Preditivo de Torque em Cascata do Motor Indução com Observador de Torque de Carga de Segunda Ordem

— This work investigates the combination of ﬁnite control set predictive torque control and dead-beat speed control techniques for application in induction motor speed drives. As a result, no proportional-integral controllers were necessary, avoiding cumbersome parameters design. The proposed control structure uses the dead-beat principle along with a second order load torque estimator. Simulated results showed the proposed controller allowed the induction motor drive to perform the fastest dynamic possible independently from design parameters, and the load torque estimator avoided the use of a torque sensor. sobressinal in- dependente de sintonia de ganhos, sem necessidade de ajuste de um controlador. Com o uso do estimador de torque de carga, evitou-se a necessidade de medi¸c˜ao do torque no eixo. Palavras-chave— Controle dead-beat , Controle preditivo de torque, Estima¸c˜ao de torque, Motor de indu¸c˜ao.