Generative Models For Deep Learning with Very Scarce Data

The goal of this paper is to deal with a data scarcity scenario where deep learning techniques use to fail. We compare the use of two well established techniques, Restricted Boltzmann Machines and Variational Auto-encoders, as generative models in order to increase the training set in a classification framework. Essentially, we rely on Markov Chain Monte Carlo (MCMC) algorithms for generating new samples. We show that generalization can be improved comparing this methodology to other state-of-the-art techniques, e.g. semi-supervised learning with ladder networks. Furthermore, we show that RBM is better than VAE generating new samples for training a classifier with good generalization capabilities

VConv-DAE: Deep Volumetric Shape Learning Without Object Labels

With the advent of affordable depth sensors, 3D capture becomes more and more ubiquitous and already has made its way into commercial products. Yet, capturing the geometry or complete shapes of everyday objects using scanning devices (e.g. Kinect) still comes with several challenges that result in noise or even incomplete shapes. Recent success in deep learning has shown how to learn complex shape distributions in a data-driven way from large scale 3D CAD Model collections and to utilize them for 3D processing on volumetric representations and thereby circumventing problems of topology and tessellation. Prior work has shown encouraging results on problems ranging from shape completion to recognition. We provide an analysis of such approaches and discover that training as well as the resulting representation are strongly and unnecessarily tied to the notion of object labels. Thus, we propose a full convolutional volumetric auto encoder that learns volumetric representation from noisy data by estimating the voxel occupancy grids. The proposed method outperforms prior work on challenging tasks like denoising and shape completion. We also show that the obtained deep embedding gives competitive performance when used for classification and promising results for shape interpolation

Protocol for a mixed-methods exploratory investigation of care following intensive care discharge: the REFLECT study

© Author(s) 2019. Re-use permitted under CC BY. Published by BMJ.INTRODUCTION: A substantial number of patients discharged from intensive care units (ICUs) subsequently die without leaving hospital. It is unclear how many of these deaths are preventable. Ward-based management following discharge from ICU is an area that patients and healthcare staff are concerned about. The primary aim of REFLECT (Recovery Following Intensive Care Treatment) is to develop an intervention plan to reduce in-hospital mortality rates in patients who have been discharged from ICU. METHODS AND ANALYSIS: REFLECT is a multicentre mixed-methods exploratory study examining ward care delivery to adult patients discharged from ICU. The study will be made up of four substudies. Medical notes of patients who were discharged from ICU and subsequently died will be examined using a retrospective case records review (RCRR) technique. Patients and their relatives will be interviewed about their post-ICU care, including relatives of patients who died in hospital following ICU discharge. Staff involved in the care of patients post-ICU discharge will be interviewed about the care of this patient group. The medical records of patients who survived their post-ICU stay will also be reviewed using the RCRR technique. The analyses of the substudies will be both descriptive and use a modified grounded theory approach to identify emerging themes. The evidence generated in these four substudies will form the basis of the intervention development, which will take place through stakeholder and clinical expert meetings. ETHICS AND DISSEMINATION: Ethical approval has been obtained through the Wales Research and Ethics Committee 4 (17/WA/0107). We aim to disseminate the findings through international conferences, international peer-reviewed journals and social media. TRIAL REGISTRATION NUMBER: ISRCTN14658054.Peer reviewedFinal Published versio

Response of finite-time particle detectors in non-inertial frames and curved spacetime

The response of the Unruh-DeWitt type monopole detectors which were coupled to the quantum field only for a finite proper time interval is studied for inertial and accelerated trajectories, in the Minkowski vacuum in (3+1) dimensions. Such a detector will respond even while on an inertial trajctory due to the transient effects. Further the response will also depend on the manner in which the detector is switched on and off. We consider the response in the case of smooth as well as abrupt switching of the detector. The former case is achieved with the aid of smooth window functions whose width, $T$, determines the effective time scale for which the detector is coupled to the field. We obtain a general formula for the response of the detector when a window function is specified, and work out the response in detail for the case of gaussian and exponential window functions. A detailed discussion of both $T \rightarrow 0$ and $T \rightarrow \infty$ limits are given and several subtlities in the limiting procedure are clarified. The analysis is extended for detector responses in Schwarzschild and de-Sitter spacetimes in (1+1) dimensions.Comment: 29 pages, normal TeX, figures appended as postscript file, IUCAA Preprint # 23/9

Pose-Normalized Image Generation for Person Re-identification

Person Re-identification (re-id) faces two major challenges: the lack of cross-view paired training data and learning discriminative identity-sensitive and view-invariant features in the presence of large pose variations. In this work, we address both problems by proposing a novel deep person image generation model for synthesizing realistic person images conditional on the pose. The model is based on a generative adversarial network (GAN) designed specifically for pose normalization in re-id, thus termed pose-normalization GAN (PN-GAN). With the synthesized images, we can learn a new type of deep re-id feature free of the influence of pose variations. We show that this feature is strong on its own and complementary to features learned with the original images. Importantly, under the transfer learning setting, we show that our model generalizes well to any new re-id dataset without the need for collecting any training data for model fine-tuning. The model thus has the potential to make re-id model truly scalable.Comment: 10 pages, 5 figure

Acculturation and the Prevalence of Depression in Older Mexican Americans: Baseline Results of the Sacramento Area Latino Study on Aging

HTo determine the association between acculturation, immigration, and prevalence of depression in older Mexican Americans. DESIGN: Cross-sectional analysis from a cohort study. SETTING: Urban and rural counties of the Central Valley of Northern California. PARTICIPANTS: One thousand seven hundred and eighty-nine Latinos recruited from a population-based sample (85% Mexican Americans) with a mean age of 70.6 (range 60–100; standard deviation (SD) = 7.13); 58.2% were women. MEASUREMENTS: Depressive symptoms were assessed with the Center for Epidemiologic Studies—Depression scale (CES-D). Acculturation was measured with the Acculturation Rating Scale for Mexican Americans—II. Psychosocial, behavioral, and medical histories were also obtained. RESULTS: The prevalence of depression (CES-D ≥ 16) was 25.4%. Women were at greater risk (32.0%) than men (16.3%; male/female odds ratio (OR) = 2.43, 95% confidence interval (CI) = 1.90–3.09). The prevalence of depression was higher among immigrants (30.4%, OR = 1.70, 95% CI = 1.36–2.13), bicultural participants (24.2%, OR = 1.66, 95% CI = 1.24–2.24), and less-acculturated participants (36.1%, OR = 2.95, 95% CI = 2.22–3.93) compared with U.S.-born (20.5%) and more-acculturated groups (16.1%). When adjustments for education, income, psychosocial, behavioral, and health-problem factors were made, the least-acculturated participants were at significantly higher risk of depression than highly acculturated Mexican Americans (OR = 1.56, 95% CI = 1.06–2.31). CONCLUSIONS: These findings are consistent with previously reported estimates of a higher prevalence of depression for older Mexican Americans than non-Hispanic Caucasians and African Americans and are the first to report the prevalence and risk of depression for older U.S.-born and immigrant Mexican Americans. The high prevalence of depression of the least acculturated group may be related to cultural barriers encountered by immigrants and less-acculturated older Mexican Americans and to poorer health status.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65541/1/j.1532-5415.2001.49186.x.pd

Synthesis and characterization of biodegradable lignin nanoparticles with tunable surface properties

Lignin nanoparticles can serve as biodegradable carriers of biocidal actives with minimal environmental footprint. Here we describe the colloidal synthesis and interfacial design of nanoparticles with tunable surface properties using two different lignin precursors, Kraft (Indulin AT) lignin and Organosolv (high-purity lignin). The green synthesis process is based on flash precipitation of dissolved lignin polymer, which enabled the formation of nanoparticles in the size range of 45–250 nm. The size evolution of the two types of lignin particles is fitted on the basis of modified diffusive growth kinetics and mass balance dependencies. The surface properties of the nanoparticles are fine-tuned by coating them with a cationic polyelectrolyte, poly(diallyldimethylammonium chloride). We analyze how the colloidal stability and dispersion properties of these two types of nanoparticles vary as a function of pH and salinities. The data show that the properties of the nanoparticles are governed by the type of lignin used and the presence of polyelectrolyte surface coating. The coating allows the control of the nanoparticles’ surface charge and the extension of their stability into strongly basic regimes, facilitating their potential application at extreme pH conditions

Interpolating between the Bose-Einstein and the Fermi-Dirac distributions in odd dimensions

We consider the response of a uniformly accelerated monopole detector that is coupled to a superposition of an odd and an even power of a quantized, massless scalar field in flat spacetime in arbitrary dimensions. We show that, when the field is assumed to be in the Minkowski vacuum, the response of the detector is characterized by a Bose-Einstein factor in even spacetime dimensions, whereas a Bose-Einstein as well as a Fermi-Dirac factor appear in the detector response when the dimension of spacetime is odd. Moreover, we find that, it is possible to interpolate between the Bose-Einstein and the Fermi-Dirac distributions in odd spacetime dimensions by suitably adjusting the relative strengths of the detector's coupling to the odd and the even powers of the scalar field. We point out that the response of the detector is always thermal and we, finally, close by stressing the apparent nature of the appearance of the Fermi-Dirac factor in the detector response.Comment: RevTeX, 7 page

Evidence for shape coexistence in 98^{98}Mo

A $\gamma\gamma$ angular correlation experiment has been performed to investigate the low-energy states of the nucleus $^{98}$Mo. The new data, including spin assignments, multipole mixing ratios and lifetimes reveal evidence for shape coexistence and mixing in $^{98}$Mo, arising from a proton intruder configuration. This result is reproduced by a theoretical calculation within the proton-neutron interacting boson model with configuration mixing, based on microscopic energy density functional theory. The microscopic calculation indicates the importance of the proton particle-hole excitation across the Z=40 sub-shell closure and the subsequent mixing between spherical vibrational and the $\gamma$-soft equilibrium shapes in $^{98}$Mo.Comment: 6 pages, 5 figures, 3 tables; published in Phys. Rev.

Bilingual Teacher Educators at an HSI: A Border Pedagogy for Latinx Teacher Development

As a borderlands’ institution, we are developing a mission and vision for our HSI identity in the college of education, as well as in our university. We envision pedagogical practices embedded in our teacher preparation that are context specific to our bilingual, biliterate, and bicultural community; one that not only prepares PTs to effectively teach all students, but also promotes strong values for equity and social justice. For our Latinx PTs, this aim has two purposes: 1) to tailor our educational practices capitalizing on their unique strengths and addressing possible challenges in their professional development, and 2) preparing them to successfully promote their students’ academic achievement through rigorous, culturally appropriate and sustainable practices (Paris, 2012). We draw on a growing body of seminal work in Latinx teacher preparation to theorize a set of border pedagogies for our context. These represent specific pedagogies that foster the development of Latinx teachers who are knowledgeable of the appropriate teaching practices for all types of students. Furthermore, we pursue practices that can help our students develop into advocates for social justice, aware of the many social and political forces impacting the schools where they will serve. These specific practices should take into consideration the specific cultural and professional identities of our preservice teachers. As a special interest research group within our college, aiming to develop an HSI identity that is context-based, we engaged in a meta-synthesis of professional literature that includes empirical research and theoretical work about the preparation of Latinx PTs in our border region. We foresee the application of these pedagogies for other regions where Latinx PTs can benefit; and envision furthering our research in the future, to explore metaphorical borders, including Latinx PTs’ hybrid transcultural identities outside our geographical border