Temporal Cross-Media Retrieval with Soft-Smoothing

Multimedia information have strong temporal correlations that shape the way modalities co-occur over time. In this paper we study the dynamic nature of multimedia and social-media information, where the temporal dimension emerges as a strong source of evidence for learning the temporal correlations across visual and textual modalities. So far, cross-media retrieval models, explored the correlations between different modalities (e.g. text and image) to learn a common subspace, in which semantically similar instances lie in the same neighbourhood. Building on such knowledge, we propose a novel temporal cross-media neural architecture, that departs from standard cross-media methods, by explicitly accounting for the temporal dimension through temporal subspace learning. The model is softly-constrained with temporal and inter-modality constraints that guide the new subspace learning task by favouring temporal correlations between semantically similar and temporally close instances. Experiments on three distinct datasets show that accounting for time turns out to be important for cross-media retrieval. Namely, the proposed method outperforms a set of baselines on the task of temporal cross-media retrieval, demonstrating its effectiveness for performing temporal subspace learning.Comment: To appear in ACM MM 201

Can patterns of everyday consumption indicate lifestyles? A secondary analysis of expenditures for fast moving goods and their social contexts

Ausgangspunkt der vorliegenden Studie bildet die Frage, ob sich Einkaufsformen beim täglichen Verbrauch als grundlegende Indikatoren von Lebensstilen erweisen. Datengrundlage bildet eine Sekundäranalyse von Panel-Daten zum Konsum schnelllebiger Waren, die vom weltweiten Marktforschungsunternehmen GfK im Jahr 1995 erhoben worden sind. Es wird zunächst eine Reihe von Hypothesen aufgestellt und die zugrunde gelegten Daten und die Stichprobe erläutert. Im Hauptteil der Studie werden 15 vollständige Cluster des Kaufverhaltens von Waren aus den Bereichen Nahrungsmittel, Getränke und Hygiene-Artikel untersucht und mit ausgewählten sozialen Indikatoren, wie z.B. sozialer Status, Mentalität und Umweltbewusstsein in Beziehung gesetzt. Die Ergebnisse zeigen, dass selbst der Kauf von schnelllebigen Konsumgütern in breitere Lebensstile eingebettet ist und auch im Zeitverlauf relativ konstant bleibt. (ICI

Cross-modal subspace learning with scheduled adaptive margin constraints

This work has been partially funded by the CMU Portugal research project GoLocal Ref. CMUP-ERI/TIC/0046/2014, by the H2020 ICT project COGNITUS with the grant agreement no 687605 and by the FCT project NOVA LINCS Ref. UID/CEC/04516/2019. We also gratefully acknowledge the support of NVIDIA Corporation with the donation of the GPUs used for this research.Cross-modal embeddings, between textual and visual modalities, aim to organise multimodal instances by their semantic correlations. State-of-the-art approaches use maximum-margin methods, based on the hinge-loss, to enforce a constant margin m, to separate projections of multimodal instances from different categories. In this paper, we propose a novel scheduled adaptive maximum-margin (SAM) formulation that infers triplet-specific constraints during training, therefore organising instances by adaptively enforcing inter-category and inter-modality correlations. This is supported by a scheduled adaptive margin function, that is smoothly activated, replacing a static margin by an adaptively inferred one reflecting triplet-specific semantic correlations while accounting for the incremental learning behaviour of neural networks to enforce category cluster formation and enforcement. Experiments on widely used datasets show that our model improved upon state-of-the-art approaches, by achieving a relative improvement of up to approximate to 12.5% over the second best method, thus confirming the effectiveness of our scheduled adaptive margin formulation.publishersversionpublishe

The relationship between mandibular advancement, tongue movement, and treatment outcome in obstructive sleep apnea

Study Objectives: To characterize how mandibular advancement enlarges the upper airway via posterior tongue advancement in people with obstructive sleep apnea (OSA) and whether this is associated with mandibular advancement splint (MAS) treatment outcome. Methods: One-hundred and one untreated people with OSA underwent a 3T magnetic resonance (MRI) scan. Dynamic mid-sagittal posterior tongue and mandible movements during passive jaw advancement were measured with tagged MRI. Upper airway cross-sectional areas were measured with the mandible in a neutral position and advanced to 70% of maximum advancement. Treatment outcome was determined after a minimum of 9 weeks of therapy. Results: Seventy-one participants completed the study: 33 were responders (AHI50% AHI reduction), 11 were partial responders (>50% AHI reduction but AHI>10 events/hr), and 27 nonresponders (AHI reduction 4 mm). In comparison, a model using only baseline AHI correctly classified 50.0% of patients (5-fold cross-validated 52.5%, n = 40). Conclusions: Tongue advancement and upper airway enlargement with mandibular advancement in conjunction with baseline AHI improve treatment response categorization to a satisfactory level (69.2%, 5-fold cross-validated 62.5%)

A guide for social science journal editors on easing into open science

Journal editors have a large amount of power to advance open science in their respective fields by incentivising and mandating open policies and practices at their journals. The Data PASS Journal Editors Discussion Interface (JEDI, an online community for social science journal editors: www.dpjedi.org) has collated several resources on embedding open science in journal editing (www.dpjedi.org/resources). However, it can be overwhelming as an editor new to open science practices to know where to start. For this reason, we created a guide for journal editors on how to get started with open science. The guide outlines steps that editors can take to implement open policies and practices within their journal, and goes through the what, why, how, and worries of each policy and practice. This manuscript introduces and summarizes the guide (full guide: https://doi.org/10.31219/osf.io/hstcx)

Multinational characterization of neurological phenotypes in patients hospitalized with COVID-19

Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents (January–September 2020) for a cross-sectional analysis. We assessed the frequency of International Classification of Disease code of neurological conditions by countries, healthcare systems, time before and after admission for COVID-19 and COVID-19 severity. Among 35,177 hospitalized patients with SARS-CoV-2 infection, there was an increase in the proportion with disorders of consciousness (5.8%, 95% confidence interval [CI] 3.7–7.8%, pFDR < 0.001) and unspecified disorders of the brain (8.1%, 5.7–10.5%, pFDR < 0.001) when compared to the pre-admission proportion. During hospitalization, the relative risk of disorders of consciousness (22%, 19–25%), cerebrovascular diseases (24%, 13–35%), nontraumatic intracranial hemorrhage (34%, 20–50%), encephalitis and/or myelitis (37%, 17–60%) and myopathy (72%, 67–77%) were higher for patients with severe COVID-19 when compared to those who never experienced severe COVID-19. Leveraging a multinational network to capture standardized EHR data, we highlighted the increased prevalence of central and peripheral neurological phenotypes in patients hospitalized with COVID-19, particularly among those with severe disease

Learning Multimodal Temporal Representation for Dubbing Detection in Broadcast Media

Person discovery in the absence of prior identity knowledge requires accurate association of visual and auditory cues. In broadcast data, multimodal analysis faces additional challenges due to narrated voices over muted scenes or dubbing in different languages. To address these challenges, we define and analyze the problem of dubbing detection in broadcast data, which has not been explored before. We propose a method to represent the temporal relationship between the auditory and visual streams. This method consists of canonical correlation analysis to learn a joint multimodal space, and long short term memory (LSTM) networks to model cross-modality temporal dependencies. Our contributions also include the introduction of a newly acquired dataset of face-speech segments from TV data, which we have made publicly available. The proposed method achieves promising performance on this real world dataset as compared to several baselines

International Analysis of Electronic Health Records of Children and Youth Hospitalized With COVID-19 Infection in 6 Countries

Question What are international trends in hospitalizations for children and youth with SARS-CoV-2, and what are the epidemiological and clinical features of these patients? Findings This cohort study of 671 children and youth found discrete surges in hospitalizations with variable trends and timing across countries. Common complications included cardiac arrhythmias and viral pneumonia, and laboratory findings included elevations in markers of inflammation and abnormalities of coagulation; few children and youth were treated with medications directed specifically at SARS-CoV-2. Meaning These findings suggest large-scale informatics-based approaches used to incorporate electronic health record data across health care systems can provide an efficient source of information to monitor disease activity and define epidemiological and clinical features of pediatric patients hospitalized with SARS-CoV-2 infections

Electrospun poly(d/l-lactide-co-l-lactide) hybrid matrix: a novel scaffold material for soft tissue engineering

Electrospinning is a long-known polymer processing technique that has received more interest and attention in recent years due to its versatility and potential use in the field of biomedical research. The fabrication of three-dimensional (3D) electrospun matrices for drug delivery and tissue engineering is of particular interest. In the present study, we identified optimal conditions to generate novel electrospun polymeric scaffolds composed of poly-d/l-lactide and poly-l-lactide in the ratio 50:50. Scanning electron microscopic analyses revealed that the generated poly(d/l-lactide-co-l-lactide) electrospun hybrid microfibers possessed a unique porous high surface area mimicking native extracellular matrix (ECM). To assess cytocompatibility, we isolated dermal fibroblasts from human skin biopsies. After 5 days of in vitro culture, the fibroblasts adhered, migrated and proliferated on the newly created 3D scaffolds. Our data demonstrate the applicability of electrospun poly(d/l-lactide-co-l-lactide) scaffolds to serve as substrates for regenerative medicine applications with special focus on skin tissue engineering