Empirically Analyzing the Effect of Dataset Biases on Deep Face Recognition Systems

It is unknown what kind of biases modern in the wild face datasets have because of their lack of annotation. A direct consequence of this is that total recognition rates alone only provide limited insight about the generalization ability of a Deep Convolutional Neural Networks (DCNNs). We propose to empirically study the effect of different types of dataset biases on the generalization ability of DCNNs. Using synthetically generated face images, we study the face recognition rate as a function of interpretable parameters such as face pose and light. The proposed method allows valuable details about the generalization performance of different DCNN architectures to be observed and compared. In our experiments, we find that: 1) Indeed, dataset bias has a significant influence on the generalization performance of DCNNs. 2) DCNNs can generalize surprisingly well to unseen illumination conditions and large sampling gaps in the pose variation. 3) Using the presented methodology we reveal that the VGG-16 architecture outperforms the AlexNet architecture at face recognition tasks because it can much better generalize to unseen face poses, although it has significantly more parameters. 4) We uncover a main limitation of current DCNN architectures, which is the difficulty to generalize when different identities to not share the same pose variation. 5) We demonstrate that our findings on synthetic data also apply when learning from real-world data. Our face image generator is publicly available to enable the community to benchmark other DCNN architectures.Comment: Accepted to CVPR 2018 Workshop on Analysis and Modeling of Faces and Gestures (AMFG

PP2A Antagonizes Phosphorylation of Bazooka by PAR-1 to Control Apical-Basal Polarity in Dividing Embryonic Neuroblasts

SummaryBazooka/Par-3 (Baz) is a key regulator of cell polarity in epithelial cells and neuroblasts (NBs). Phosphorylation of Baz by PAR-1 and aPKC is required for its function in epithelia, but little is known about the dephosphorylation mechanisms that antagonize the activities of these kinases or about the relevance of Baz phosphorylation for NB polarity. We found that protein phosphatase 2A (PP2A) binds to Baz via its structural A subunit. By using phospho-specific antibodies, we show that PP2A dephosphorylates Baz at the conserved serine residue 1085 and thereby antagonizes the kinase activity of PAR-1. Loss of PP2A function leads to complete reversal of polarity in NBs, giving rise to an “upside-down” polarity phenotype. Overexpression of PAR-1 or Baz, or mutation of 14-3-3 proteins that bind phosphorylated Baz, causes essentially the same phenotype, indicating that the balance of PAR-1 and PP2A effects on Baz phosphorylation determines NB polarity

Childhood leukaemia and socioeconomic status: what is the evidence?

The objectives of this systematic review are to summarise the current literature on socioeconomic status (SES) and the risk of childhood leukaemia, to highlight methodological problems and formulate recommendations for future research. Starting from the systematic review of Poole et al. (Socioeconomic status and childhood leukaemia: a review. Int. J. Epidemiol. 2006;35(2):370-384.), an electronic literature search was performed covering August 2002-April 2008. It showed that (1) the results are heterogeneous, with no clear evidence to support a relation between SES and childhood leukaemia; (2) a number of factors, most importantly selection bias, might explain inconsistencies between studies; (3) there is some support for an association between SES at birth (rather than later in childhood) and childhood leukaemia and (4) if there are any associations, these are weak, limited to the most extreme SES groups (the 10-20% most or least deprived). This makes it unlikely that they would act as strong confounders in research addressing associations between other exposures and childhood leukaemia. Future research should minimise case and control selection bias, distinguish between different SES measures and leukaemia subtypes and consider timing of exposures and cancer outcome

Analyzing and Reducing the Damage of Dataset Bias to Face Recognition With Synthetic Data

It is well known that deep learning approaches to facerecognition suffer from various biases in the available train-ing data. In this work, we demonstrate the large potentialof synthetic data for analyzing and reducing the negativeeffects of dataset bias on deep face recognition systems. Inparticular we explore two complementary application areasfor synthetic face images: 1) Using fully annotated syntheticface images we can study the face recognition rate as afunction of interpretable parameters such as face pose. Thisenables us to systematically analyze the effect of differenttypes of dataset biases on the generalization ability of neu-ral network architectures. Our analysis reveals that deeperneural network architectures can generalize better to un-seen face poses. Furthermore, our study shows that currentneural network architectures cannot disentangle face poseand facial identity, which limits their generalization ability.2) We pre-train neural networks with large-scale syntheticdata that is highly variable in face pose and the number offacial identities. After a subsequent fine-tuning with real-world data, we observe that the damage of dataset bias inthe real-world data is largely reduced. Furthermore, wedemonstrate that the size of real-world datasets can be re-duced by 75% while maintaining competitive face recogni-tion performance. The data and software used in this workare publicly available

Mitigation of skull formation in high temperature gas extraction system

The adverse impact of particle adhesions and agglomerations on gas flow performance is a prominent concern in high volume extraction systems. The formation of severe skull deposits, involving agglomeration and adhesion processes, particularly at elevated operation temperatures, necessitates labor­intensive and costly manual removal. Consequently, investigating conditions that promote increased skull generation and exploring mechanisms for spontaneous removal through crack formation and chipping are of great significance. This study comprehensively documents the operational conditions of an industrial extraction system, accom panied by elemental gas phase composition analyses. Additionally, the chemical compositions of agglomerated adhesion samples were assessed using X­ray diffraction (XRD) and inductively coupled plasma optical emission spectroscopy (ICP­OES), and their inner structure was examined through SEM. Subsequently, mechanisms leading to these build­ups were simulated on laboratory scale by covering original wall surface samples with agglomeration powder screened for a defined particle size. In experiments conducted at various high temperatures ranging from 800 °C to 1200 °C, while varying the CaCO3 content levels in the powders, a layered structure similar to the real system was successfully acquired. Moreover, under certain defined conditions and different atmospheres, crack formation, significantly impacting the chipping behavior of the skull formations from wall surfaces during application, was observed and the compressive strength was examined. Through our laboratory experiments, specific operating conditions within the calcination cycle were revealed, leading to a substantial enhancement of autonomous discharge of large particleâwall agglomerations. Based on these findings, we propose general process optimization steps to improve the overall performance of the extraction system, such as reduction of fine CaCO3 particles and reduction of the gas flow temperature

Investigating Relationships Among Self-Efficacy, Mood, and Anxiety Using Digital Technologies: Randomized Controlled Trial.

BACKGROUND Digital tools assessing momentary parameters and offering interventions in people's daily lives play an increasingly important role in mental health research and treatment. Ecological momentary assessment (EMA) makes it possible to assess transient mental health states and their parameters. Ecological momentary interventions (EMIs) offer mental health interventions that fit well into individuals' daily lives and routines. Self-efficacy is a transdiagnostic construct that is commonly associated with positive mental health outcomes. OBJECTIVE The aim of our study assessing mood, specific self-efficacy, and other parameters using EMA was 2-fold. First, we wanted to determine the effects of daily assessed moods and dissatisfaction with social contacts as well as the effects of baseline variables, such as depression, on specific self-efficacy in the training group (TG). Second, we aimed to explore which variables influenced both groups' positive and negative moods during the 7-day study period. METHODS In this randomized controlled trial, we applied digital self-efficacy training (EMI) to 93 university students with elevated self-reported stress levels and daily collected different parameters, such as mood, dissatisfaction with social contacts, and specific self-efficacy, using EMA. Participants were randomized to either the TG, where they completed the self-efficacy training combined with EMA, or the control group, where they completed EMA only. RESULTS In total, 93 university students participated in the trial. Positive momentary mood was associated with higher specific self-efficacy in the evening of the same day (b=0.15, SE 0.05, P=.005). Higher self-efficacy at baseline was associated with reduced negative mood during study participation (b=-0.61, SE 0.30, P=.04), while we could not determine an effect on positive mood. Baseline depression severity was significantly associated with lower specific self-efficacy over the week of the training (b=-0.92, SE 0.35, P=.004). Associations between higher baseline anxiety with higher mean negative mood (state anxiety: b=0.78, SE 0.38, P=.04; trait anxiety: b=0.73, SE 0.33, P=.03) and lower mean positive mood (b=-0.64, SE 0.28, P=.02) during study participation were found. Emotional flexibility was significantly enhanced in the TG. Additionally, dissatisfaction with social contacts was associated with both a decreased positive mood (b=-0.56, SE 0.15, P<.001) and an increased negative mood (b=0.45, SE 0.12, P<.001). CONCLUSIONS This study showed several significant associations between mood and self-efficacy as well as those between mood and anxiety in students with elevated stress levels, for example, suggesting that improving mood in people with low mood could enhance the effects of digital self-efficacy training. In addition, engaging in 1-week self-efficacy training was associated with increased emotional flexibility. Future work is needed to replicate and investigate the training's effects in other groups and settings. TRIAL REGISTRATION ClinicalTrials.gov NCT05617248; https://clinicaltrials.gov/study/NCT05617248

State of the Art in Dense Monocular Non-Rigid 3D Reconstruction

3D reconstruction of deformable (or non-rigid) scenes from a set of monocular 2D image observations is a long-standing and actively researched area of computer vision and graphics. It is an ill-posed inverse problem, since--without additional prior assumptions--it permits infinitely many solutions leading to accurate projection to the input 2D images. Non-rigid reconstruction is a foundational building block for downstream applications like robotics, AR/VR, or visual content creation. The key advantage of using monocular cameras is their omnipresence and availability to the end users as well as their ease of use compared to more sophisticated camera set-ups such as stereo or multi-view systems. This survey focuses on state-of-the-art methods for dense non-rigid 3D reconstruction of various deformable objects and composite scenes from monocular videos or sets of monocular views. It reviews the fundamentals of 3D reconstruction and deformation modeling from 2D image observations. We then start from general methods--that handle arbitrary scenes and make only a few prior assumptions--and proceed towards techniques making stronger assumptions about the observed objects and types of deformations (e.g. human faces, bodies, hands, and animals). A significant part of this STAR is also devoted to classification and a high-level comparison of the methods, as well as an overview of the datasets for training and evaluation of the discussed techniques. We conclude by discussing open challenges in the field and the social aspects associated with the usage of the reviewed methods.Comment: 25 page

Investigating Relationships Among Self-Efficacy, Mood, and Anxiety Using Digital Technologies: Randomized Controlled Trial

Background Digital tools assessing momentary parameters and offering interventions in people’s daily lives play an increasingly important role in mental health research and treatment. Ecological momentary assessment (EMA) makes it possible to assess transient mental health states and their parameters. Ecological momentary interventions (EMIs) offer mental health interventions that fit well into individuals’ daily lives and routines. Self-efficacy is a transdiagnostic construct that is commonly associated with positive mental health outcomes. Objective The aim of our study assessing mood, specific self-efficacy, and other parameters using EMA was 2-fold. First, we wanted to determine the effects of daily assessed moods and dissatisfaction with social contacts as well as the effects of baseline variables, such as depression, on specific self-efficacy in the training group (TG). Second, we aimed to explore which variables influenced both groups’ positive and negative moods during the 7-day study period. Methods In this randomized controlled trial, we applied digital self-efficacy training (EMI) to 93 university students with elevated self-reported stress levels and daily collected different parameters, such as mood, dissatisfaction with social contacts, and specific self-efficacy, using EMA. Participants were randomized to either the TG, where they completed the self-efficacy training combined with EMA, or the control group, where they completed EMA only. Results In total, 93 university students participated in the trial. Positive momentary mood was associated with higher specific self-efficacy in the evening of the same day (b=0.15, SE 0.05, P=.005). Higher self-efficacy at baseline was associated with reduced negative mood during study participation (b=–0.61, SE 0.30, P=.04), while we could not determine an effect on positive mood. Baseline depression severity was significantly associated with lower specific self-efficacy over the week of the training (b=–0.92, SE 0.35, P=.004). Associations between higher baseline anxiety with higher mean negative mood (state anxiety: b=0.78, SE 0.38, P=.04; trait anxiety: b=0.73, SE 0.33, P=.03) and lower mean positive mood (b=–0.64, SE 0.28, P=.02) during study participation were found. Emotional flexibility was significantly enhanced in the TG. Additionally, dissatisfaction with social contacts was associated with both a decreased positive mood (b=–0.56, SE 0.15, P<.001) and an increased negative mood (b=0.45, SE 0.12, P<.001). Conclusions This study showed several significant associations between mood and self-efficacy as well as those between mood and anxiety in students with elevated stress levels, for example, suggesting that improving mood in people with low mood could enhance the effects of digital self-efficacy training. In addition, engaging in 1-week self-efficacy training was associated with increased emotional flexibility. Future work is needed to replicate and investigate the training’s effects in other groups and settings. Trial Registration ClinicalTrials.gov NCT05617248; https://clinicaltrials.gov/study/NCT0561724

Safety of 80% vs 30–35% fraction of inspired oxygen in patients undergoing surgery: a systematic review and meta-analysis

Background: Evidence-based guidelines from the World Health Organization (WHO) have recommended a high (80%) fraction of inspired oxygen (FiO2) to reduce surgical site infection in adult surgical patients undergoing general anaesthesia with tracheal intubation. However, there is ongoing debate over the safety of high FiO2. We performed a systematic review to define the relative risk of clinically relevant adverse events (AE) associated with high FiO2. Methods: We reviewed potentially relevant articles from the WHO review supporting the recommendation, including an updated (July 2018) search of EMBASE and PubMed for randomised and non-randomised controlled studies reporting AE in surgical patients receiving 80% FiO2 compared with 30–35% FiO2. We assessed study quality and performed meta-analyses of risk ratios (RR) comparing 80% FiO2 against 30–35% for major complications, mortality, and intensive care admission. Results: We included 17 moderate–good quality trials and two non-randomised studies with serious-critical risk of bias. No evidence of harm with high FiO2 was found for major AE in the meta-analysis of randomised trials: atelectasis RR 0.91 [95% confidence interval (CI) 0.59–1.42); cardiovascular events RR 0.90 (95% CI 0.32–2.54); intensive care admission RR 0.93 (95% CI 0.7–1.12); and death during the trial RR 0.49 (95% CI 0.17–1.37). One non-randomised study reported that high FiO2 was associated with major respiratory AE [RR 1.99 (95% CI 1.72–2.31)]. Conclusions: No definite signal of harm with 80% FiO2 in adult surgical patients undergoing general anaesthesia was demonstrated and there is little evidence on safety-related issues to discourage its use in this population