Miracle-dz/UniFAR-FTUs huggingface dataset:
"Are you okay, honey?": Recognizing Emotions among Couples Managing Diabetes in Daily Life using Multimodal Real-World Smartwatch Data

Couples generally manage chronic diseases together and the management takes an emotional toll on both patients and their romantic partners. Consequently, recognizing the emotions of each partner in daily life could provide an insight into their emotional well-being in chronic disease management. Currently, the process of assessing each partner’s emotions is manual, time-intensive, and costly. Despite the existence of works on emotion recognition among couples, none of these works have used data collected from couples’ interactions in daily life. In this work, we collected 85 hours (1,021 5-minute samples) of real-world multimodal smartwatch sensor data (speech, heart rate, accelerometer, and gyroscope) and self-reported emotion data (n=612) from 26 partners (13 couples) managing diabetes mellitus type 2 in daily life. We extracted physiological, movement, acoustic, and linguistic features, and trained machine learning models (support vector machine and random forest) to recognize each partner’s self-reported emotions (valence and arousal). Our results from the best models were better than chance with balanced accuracies of 63.8% and 78.1% for arousal and valence respectively. This work contributes toward building automated emotion recognition systems that would eventually enable partners to monitor their emotions in daily life and enable the delivery of interventions to improve their emotional well-being.
On an Application of Generative Adversarial Networks on Remaining Lifetime Estimation

A major problem of structural health monitoring (SHM) has been the prognosis of damage and the prediction of the remaining useful life of a structure. Both tasks depend on multiple parameters, many of which are often uncertain. A wide range of models have been developed for the aforementioned tasks, but they have been either deterministic or stochastic with the ability to take into account only a restricted set of past states of the structure. In the current work, a generative model is proposed in order to make predictions about the damage evolution of structures. The model is able to perform in a population-based SHM (PBSHM) framework, to take into account many past states of the damaged structure, to incorporate uncertainties in the modelling process and to generate potential damage evolution outcomes according to data acquired from a structure. The algorithm is tested on a simulated damage evolution example and the results reveal that it is able to provide quite confident predictions about the remaining useful life of structures within a population.
REZCR: Zero-shot Character Recognition via Radical Extraction

The long-tail effect is a common issue that limits the performance of deep learning models on real-world datasets. Char-acter image datasets are also affected by such unbalanced data distribution due to differences in character usage frequency. Thus, current character recognition methods are limited when applied in the real world, especially for the categories in the tail which are lacking training samples, e.g., uncommon characters. In this paper, we propose a zero-shot character recognition framework via radical extraction (REZCR) to improve the recognition performance of few-sample character categories in the tail. Speciﬁcally, we exploit radicals, the graphical units of characters, by decomposing and reconstructing characters according to orthography. REZCR consists of an attention-based radical information extractor (RIE) and a knowledge graph-based character reasoner (KGR). The RIE aims to recognize candidate radicals and their possible structural relations from character images. The results are then fed into KGR to recognize the target character by reasoning with a pre-designed knowledge graph. We validate our method on multiple datasets, and REZCR shows promising experimental results, especially on few-sample character datasets.
Cooperate or Compete: A New Perspective on Training of Generative Networks

GANs have two competing modules: the generator module is trained to generate new examples, and the discriminator module is trained to discriminate real examples from generated examples. The training procedure of GAN is modeled as a finitely repeated simultaneous game. Each module tries to increase its performance at every repetition of the base game (at every batch of training data) in a non-cooperative manner. We observed that each module can perform better and learn faster if training is modeled as an infinitely repeated simultaneous game. At every repetition of the base game (at every batch of training data) the stronger module (whose performance is increased or remains the same compared to the previous batch of training data) cooperates with the weaker module (whose performance is decreased compared to the previous batch of training data) and only the weaker module is allowed to increase its performance.
Cybersecurity Misinformation Detection on Social Media: Case Studies on Phishing Reports and Zoom's Threat

Prior work has extensively studied misinformation related to news, politics, and health, however, misinformation can also be about technological topics. While less controversial, such misinformation can severely impact companies’ reputations and revenues, and users’ online experiences. Recently, social media has also been increasingly used as a novel source of knowledgebase for extracting timely and relevant security threats, which are fed to the threat intelligence systems for better performance. However, with possible campaigns spreading false security threats, these systems can become vulnerable to poisoning attacks. In this work, we proposed novel approaches for detecting misinformation about cybersecurity and privacy threats on social media, focusing on two topics with different types of misinformation: phishing websites and Zoom’s security & privacy threats. We developed a framework for detecting inaccurate phishing claims on Twitter. Using this framework, we could label about 9% of URLs and 22% of phishing reports as misinformation. We also proposed another framework for detecting misinformation related to Zoom’s security and privacy threats on multiple platforms. Our classifiers showed great performance with more than 98% accuracy. Employing these classifiers on the posts from Facebook, Instagram, Reddit, and Twitter, we found respectively that about 18%, 3%, 4%, and 3% of posts were misinformation. In addition, we studied the characteristics of misinformation posts, their authors, and their timelines, which helped us identify campaigns.
Numerical Estimation of the Electromagnetic Wave Scattering from Building Surfaces

The electromagnetic wave propagation in the mobile communication environments can be predicted by using ray tracing approach which incorporates reflection and diffraction. However, the diffuse scattering effects are often non-negligible in the experiments. This is because when the energy is scattered to all the directions when electromagnetic wave impinges on a rough surface e.g. building wall. In this paper we present Method Of Moments (MOM) analysis of the scattering from the 2D rough surface model of the building. This result of scattering is compared to that for Physical Optics Method (PO). Keywords—Wave Scattering, Building Surface, Method of Moment, Physical Optics
Interoceptive accuracy and bias in somatic symptom disorder, illness anxiety disorder, and functional syndromes: A systematic review and meta-analysis

Somatic symptom disorder, illness anxiety disorder, and functional syndromes are characterized by burdensome preoccupation with somatic symptoms. Etiological models propose either increased interoceptive accuracy through hypervigilance to the body, or decreased and biased interoception through top-down predictions about sensory events. This systematic review and meta-analysis summarizes findings of 68 studies examining interoceptive accuracy and 8 studies examining response biases in clinical or non-clinical groups. Analyses yielded a medium population effect size for decreased interoceptive accuracy in functional syndromes, but no observable effect in somatic symptom disorder and illness anxiety disorder. The overall effect size was highly heterogeneous. Regarding response bias, there was a small significant effect in somatic symptom disorder and illness anxiety disorder. Our findings strengthen the notion of top-down factors that result in biased rather than accurate perception of body signals in somatic symptom disorder and illness anxiety disorder.
Verbal manipulations of learning expectancy do not enhance reconsolidation

Objectives Pharmacological studies using propranolol suggest that if reactivation signals that new information will be learned (i.e., there is an expectation for learning) reconsolidation can be enhanced. We examined if the verbal instructions to expect new learning will enhance reconsolidation of fear memories using the post-retrieval extinction paradigm. Methods On day one, participants (n = 48) underwent differential fear conditioning to two images (CS+ and CS-). On day two, participants were randomly assigned to one of three groups; groups one and two had their memory for the CS+ reactivated (i.e., a single presentation of the CS+) 10 minutes prior to extinction, whereas group three did not have their memory reactivated but went right to extinction (no reactivation group). One reactivation group was told that they would learn something new about the images (expectation for learning group), and the other group was told that they would not learn anything new (no expectation for learning group). On day three, return of fear was measured following reinstatement (i.e., four shocks). Fear potentiated startle (FPS) and skin conductance response (SCR) were measured throughout. Results There was evidence of fear acquisition for participants for SCR but not FPS. With regards to reconsolidation, SCR increased for the CS+ and CS-in all groups from the end of extinction to the beginning of re-extinction (i.e., return of fear). For FPS, post-hoc tests conducted on the sub-group of participants showing fear learning showed that FPS remained stable in the two reactivation groups, but increased to the CS+, but not the CS- in the no reactivation group. Implications These findings suggest that a verbal manipulation of the expectation for learning may not be salient enough to enhance reconsolidation. Results are discussed in relation to theories on differences in between SCR, as a measure of cognitive awareness, and FPS, as a measure of fear.
Efficacy of Ubrogepant in the Acute Treatment of Migraine With Mild Pain vs Moderate or Severe Pain

Background and Objectives To examine the efficacy of ubrogepant in the treatment of migraine with mild vs moderate or severe pain. Methods This was a phase 3, open-label, dose-blinded, 52-week extension trial. Adults with migraine were randomized 1:1:1 (usual care, ubrogepant 50 mg, or ubrogepant 100 mg). Participants treated up to 8 migraine attacks of any pain intensity every 4 weeks. Efficacy outcomes (only collected for ubrogepant) included 2-hour pain freedom (2hPF), freedom from associated symptoms, and from disability. A generalized linear mixed model with binomial distribution and logit link function was used to assess the influence of baseline pain intensity on treatment outcomes in this post hoc analysis. Results Data for 19,291 attacks from 808 participants were included. 2hPF rates were higher for attacks treated when pain was mild vs moderate or severe: ubrogepant 50 mg (47.1% vs 23.6%; odds ratio [95% CI] 2.89 [2.57–3.24]) and ubrogepant 100 mg (55.2% vs 26.1%; 3.50 [3.12–3.92]; p < 0.0001 both doses). Rates of freedom from photophobia, phonophobia, and nausea 2 hours after treatment were also significantly higher following the treatment of mild vs moderate or severe pain (p < 0.001 all symptoms, both doses). At 2 hours, the proportion of attacks with normal function was more than double for both doses of ubrogepant (p < 0.001). The most common adverse event was upper respiratory tract infection (∼11% both doses). Serious adverse events were reported by 2% in ubrogepant 50 mg and 3% in ubrogepant 100 mg. Discussion Relative to treatment of attacks with moderate or severe pain, treatment with ubrogepant during mild pain resulted in significantly higher rates of freedom from pain, freedom from associated symptoms, and achieving normal function 2 hours after administration. Trial Registration Information ClinicalTrials.gov, NCT02873221. Classification of Evidence This trial provides Class III evidence that treatment of migraine with ubrogepant when pain is mild vs moderate or severe increases the likelihood of achieving pain freedom, absence of symptoms, and normal function within 2 hours postdose.
Complement C3 inhibition in severe COVID-19 using compstatin AMY-101

Complement C3 activation contributes to COVID-19 pathology, and C3 targeting has emerged as a promising therapeutic strategy. We provide interim data from ITHACA, the first randomized trial evaluating a C3 inhibitor, AMY-101, in severe COVID-19 (PaO2/FiO2 ≤ 300 mmHg). Patients received AMY-101 (n = 16) or placebo (n = 15) in addition to standard of care. AMY-101 was safe and well tolerated. Compared to placebo (8 of 15, 53.3%), a higher, albeit nonsignificant, proportion of AMY-101–treated patients (13 of 16, 81.3%) were free of supplemental oxygen at day 14. Three nonresponders and two placebo-treated patients succumbed to disease-related complications. AMY-101 significantly reduced CRP and ferritin and restrained thrombin and NET generation. Complete and sustained C3 inhibition was observed in all responders. Residual C3 activity in the three nonresponders suggested the presence of a convertase-independent C3 activation pathway overriding the drug’s inhibitory activity. These findings support the design of larger trials exploring the potential of C3-based inhibition in COVID-19 or other complement-mediated diseases.
How the Hodgkin cycle became the principle of biological relativity

The Hodgkin Cycle describes the interaction between electrical potentials and ion channel currents that enables impulses and rhythms to be generated in excitable cells. Contrary to most diagrams of that interaction, there can be no one-way flow around the cycle, which is therefore better represented as a causal ring in which the different forms of causation operate simultaneously. Such rings of interactions between different levels of biological organisation occur everywhere in living systems. This insight became generalised in the principle of biological relativity. Multi-level understanding of living organisms is not correctly represented by a gene-centric interpretation of biology. That interpretation was based on the Central Dogma of molecular biology. Yet, careful analysis of the molecular biological experiments supposed to support gene-centrism leads to its deconstruction. DNA does not replicate like a crystal. There is no replicator separate from its vehicle. Nor is the genome isolated from the rest of the body. This article is protected by copyright. All rights reserved.
Facial dermatoses induced by face masks: A systematic review and meta‐analysis of observational studies

The use of masks for infection control was common in the COVID‐19 pandemic. As numerous cross‐sectional studies have suggested a link between the use of such masks and various facial dermatoses, a systematic review and meta‐analysis of published studies was conducted to evaluate this association, as well as potential risk factors for the development of such facial dermatoses. Observational studies were searched for in MEDLINE, EMBASE and the Cochrane Central Register. Thirty‐seven observational studies with a total of 29 557 study participants were identified. This study was performed according to the Preferred Reporting Items for Systematic reviews and Meta‐Analyses (PRISMA) 2020 checklist and quality was assessed via the Newcastle‐Ottawa Quality Assessment Scale. , Overall prevalence of facial dermatoses was 55%. Individually, acne, facial dermatitis, itch and pressure injuries were consistently reported as facial dermatoses, with a pooled prevalence of 31%, 24%, 30% and 31%, respectively. Duration of mask‐wear was the most significant risk factor for the development of facial dermatoses (95% CI: 1.31–1.54, p < 0.001). Overall, facial dermatoses associated with mask wear are common, and consist of distinct entities. They are related to duration of use. Appropriate and tailored treatment is important to improve the outcomes for these affected patients.
Assessment of performance characteristics of COVID-19 ICD-10-CM diagnosis code U07.1 using SARS-CoV-2 nucleic acid amplification test results

The Food and Drug Administration’s Biologics Effectiveness and Safety Initiative conducts active surveillance to protect public health during the coronavirus disease 2019 (COVID-19) pandemic. This study evaluated performance of International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis code U07.1 in identifying COVID-19 cases in claims compared with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid amplification test results in linked electronic health records (EHRs). Care episodes in three populations were defined using COVID-19-related diagnoses (population 1), SARS-CoV-2 nucleic acid amplification test procedures (population 2), and all-cause hospitalizations (population 3) in two linked claims-EHR databases: IBM® MarketScan® Explorys® Claims-EMR Data Set (commercial) and OneFlorida Data Trust linked Medicaid-EHR. Positive and negative predictive values were calculated. Respectively, populations 1, 2, and 3 included 26,686, 26,095, and 2,564 episodes (commercial) and 29,117, 23,412, and 9,629 episodes (Florida Medicaid). The positive predictive value was >80% and the negative predictive value was >95% in each population, with the highest positive predictive value in population 3 (commercial: 91.9%; Medicaid: 93.1%). Findings did not vary substantially by patient age. Positive predictive values in populations 1 and 2 fluctuated during April–June 2020. They then stabilized in the commercial but not the Medicaid population. Negative predictive values were consistent over time in all populations and databases. Our findings indicate that U07.1 has high performance in identifying COVID-19 cases and noncases in claims databases. Performance may vary across populations and periods.
Emotional Reactivity, Emotion Regulation, and Regulatory Choice in Somatic Symptom Disorder

Persons with somatic symptom disorders (SSDs) report higher emotional reactivity and greater emotion regulation (ER) difficulties in daily life. In addition to self-reports, Schnabel et al. conducted two experimental tasks measuring emotion reactivity, ER, and choice of strategies in which individuals with SSD did not demonstrate alterations compared with healthy people. Thus, abnormalities in emotional processing associated with SSD might not be attributable to performance deficits per se. Extensive ER interventions may not necessarily be indicated for the broad mass of patients with SSD. ABSTRACT Objective Despite the transdiagnostic importance of emotional dysregulation in psychopathology, the exact nature of emotional dysregulation in somatic symptom disorders (SSDs) is still unclear. The present study compared measures of emotional reactivity, emotion regulation (ER), and regulatory choice between n = 62 individuals with SSD (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition) and n = 61 healthy participants. Methods Participants underwent two ER tasks, assessing a) efficacy of reappraisal and suppression, and 2) regulatory choice, while electrodermal activity and heart rate variability were recorded. In addition, self-reports (Emotion Reactivity Scale, Emotion Regulation Questionnaire, Difficulties in Emotion Regulation Scale) regarding habitual emotional reactions and regulation strategies were assessed. Results Individuals with SSD reported significantly higher trait emotional reactivity (Emotion Reactivity Scale; p < .001, d = 1.61), significantly more trait ER difficulties (Difficulties in Emotion Regulation Scale; p < .001, d = 1.62), and significantly lower reappraisal use in daily life (Emotion Regulation Questionnaire; p < .001, d = −0.75). On a behavioral and physiological levels, no significant group differences were found regarding emotional reactivity (subjective ratings of emotional stimuli in task 1, p values = .653–.667; electrodermal activity: p values = .224–.837), ER (task 1: p values = .077–.731; heart rate variability: p values = .522–.832), or regulatory choice (task 2: p = .380). Although individuals with SSD were equally effective in state ER (task 1), they perceived ER during the task as significantly more effortful (p = .038, d = −0.38). Conclusions Results suggest that dysregulated emotions might not result from lacking abilities in implementing ER effectively, but rather could arise from less frequent ER initiation because ER is perceived as more effortful.
Acute Care for Elders units: A model from the past or for the future?

1. A prepared environment is designed to foster independence and minimize the sterile feeling inherent in the hospital. It was designed to be more like home, with places for personal items to assist with reorientation and perhaps reduce the development of delirium 2. A patient-centered assessment was performed by the bedside nurse and shared with other members of the interdisciplinary team (IDT) to focus on activities of daily living (ADLs), nutrition, continence, and early mobility 3. A medical care review by a geriatrician and/or geriatric pharmacist to limit the number of orders that had the potential for harm including issues related to anticholinergic medications, prolonged NPO status, and unnecessary tethers such as catheters or oxygen tubes 4. Daily IDT rounds that quickly update the entire team on the “plan for the day” 5. Early planning for discharge, preferably to home, accounting for the anticipated length of stay and home needs to facilitate the transition of care
New Microsatellite Markers for Genetic Studies on Sergentomyia schwetzi (Diptera: Psychodidae): A Suspected Vector of Leishmania infantum (Trypanosomatida: Trypanosomatidae) in the Canine Leishmaniasis Focus of Mont-Rolland, Senegal

Abstract Visceral leishmaniasis is not endemic in West Africa, but prevalence of canine leishmaniasis and seroprevalence of Leishmania infantum infection in humans are high in the Mont Rolland community (Thiès region, Senegal). Previous studies in this area showed that Sergentomyia schwetzi could be the potential vector of Le. infantum. To precisely describe the biology and population structure of this potential vector, we identified eight novel microsatellite loci to characterize Se. schwetzi populations. We tested these loci in Se. schwetzi populations from five locations at Mont Rolland (Thiès, Senegal). All the loci were polymorphic, with a mean of 17.25 alleles (observed heterozygosity: 0.455). We did not detect any evidence of scoring errors due to stuttering and large allele dropout. Moreover, several of these loci were also amplified in six other sand fly species (Sergentomyia magna, Sergentomyia dubia, Sergentomyia minuta, Phlebotomus duboscqi, Phlebotomus perniciosus, and Phlebotomus ariasi). These preliminary results demonstrate the utility of these microsatellite markers for Se. schwetzi (and for the other sand fly species) population genetic studies.