Miracle-dz/UniFAR-FTUs huggingface dataset:
Barriers to Optimal Health for Under 5s Experiencing Homelessness and Living In Temporary Accommodation in High-Income Countries: A Scoping Review

Background: The first 5 years of life are crucial for optimising growth, health, and cognitive development. However, many children do not reach their full cognitive and developmental potential because of multilevel barriers, including those resulting from poverty and homelessness. This review summarises the evidence characterising the barriers to achieving optimal health and cognitive outcomes, and to accessing health services for homeless children younger than 5 years of age (U5s)-one of the most vulnerable populations in High Income Countries (HICs). Methods: For this scoping review, we followed the PRISMA-ScR checklist and CATS framework. We searched Medline, PubMed, Embase, CINAHL, Web of Science, OVID Maternity and Infant Care, and The Cochrane Library (publications dates from Jan 1, 1980, to Jun 23, 2020) using the key words “homelessness”, “housing”, “paediatrics”, “interpersonal relations”, “social exclusion”, “toddler”, “children under 5”, “engagement”, and “communication and insecurity”. The search strategy yielded 3253 articles. Retrieved articles were organised by study design. Because of the considerable heterogeneity of methods and outcomes, we used a narrative synthesis analytic approach. Our outcome of interest was barriers to optimal health and accessing health services, focusing on U5s living in HICs. Findings: Twenty-nine full texts were selected in the final synthesis, including primary research studies and systematic or narrative reviews of primary research studies from HICs. There was limited evidence describing links among housing insecurity, health, and cognitive outcomes in U5s. This age group was rarely studied as a discrete group and often combined with older ages (eg, ≤25 years). The quality of articles varied greatly because of the heterogeneity in study design. Nevertheless, important themes were identified: barriers were described at the individual and family level (eg, ethnicity, immigration status, and fear), system level (eg, policies, poor access to medication, absence of care plan, and no insurance) and community level (eg, transportation limitations and poor housing conditions). Interpretation: Although evidence is sparse, further methodologically rigorous research is needed to identify what barriers exist for U5s and their parents in accessing health services, and how this affects the child’s health. The multi-level nature of these barriers implies a system’s approach may be required. However, more evidence is needed including cross-sector studies and tailored interventions to address these barriers by working directly with experts with experience of social exclusion and their children. *Corresponding author Diana Margot Rosenthal, UCL Great Ormond Street Institute of Child Health, Faculty of Population Health Sciences,30 Guilford Street, London WC1N 1EH, UK, Email: diana.rosenthal@ucl.ac. uk Submitted: 14 January 2021 Accepted: 12 February 2021 Published: 17 February 2021
Gloss measurement of papers - the effect of luminance factor

For a range of papers of luminance factor varying from 20% upwards and of gloss varying from almost complete matt to gloss high enough to give fair mirror images the equation G = S(a + 10/L) is proposed, where G is a measure of visual gloss, S is the relative intensity of reflected light under 45° - 45° conditions of illuminating and viewing, L is the luminance factor expressed as a percentage and a is a constant which, under the conditions used by the authors, is approximately 0.20. The visual gradings of eight papers out of ten are not markedly affected by the conditions of observation, but for the remaining two there is a highly significant shift in grading according to whether these conditions permit formation of mirror images or not. Gloss is considered to be a gestalt, corresponding to no single physical property of a surface, being judged by appraisal of a physical situation taken as a whole. The validity of the method used in establishing the psychological gloss scale is checked by experiments in weight grading.
Influence of organobentonite structure on toluene adsorption from water solution

Due to increase water pollution by organic compound derived from hydrocarbons such as toluene, several alternative technologies for remediation of polluted water have been originated. In this work natural bentonites were modified with cetyltrimethylammonium (CTMA+) for obtaining organophilic bentonites. The obtained CTMA-bentonites would be suitable for use as adsorbents of toluene present in water. The influence of structural characteristics of CTMA-bentonites on their adsorption capacity was studied. It was shown that adsorption of toluene depended on homogeneous interlayer space associated with arrangements of CTMA+ paraffin-monolayer and bilayer models, accompanied by a high degree ordering of the carbon chain of organic cation in both arrangements. However, packing density would not have an evident influence on the retention capacity of these materials. The solids obtained were characterized by chemical analysis, X-ray diffractions and infrared spectroscopy. Toluene adsorption was measured by UV-visible spectrophotometer. Adsorption capacity was studied by determining adsorption isotherms and adsorption coefficient calculation. The adsorption isotherms were straight-line indicating a partition phenomenon of toluene between the aqueous and organic phase present in organophilic bentonites.
Deep Learning on medical images: ill-deﬁned labels can be a good thing

It is usual to come across public available datasets that often provide label distributions that do not match the real world distributions (RWD) where the data came from when working on deep learning (DL) algorithms for medical images. On top of that, it is possible to observe that data curation strategies developed for dataset creation could be partially responsible for the distancing of distributions present on said medical image datasets. By data curation we mean all processes of cleaning and transformation of the acquired data following certain semantic conditions and domain-speciﬁc knowledge. Although it is expected that the curation stage modify the distribution of the data, we signal that one must tap gently into the cleaning and transformation steps of data curation in order to avoid rendering a dataset worthless from the perspective of supervised learning DL algorithms. In this study, we will explore the experiences we had on the creation of two chest x-ray (CXR) datasets and one DL model for pulmonary tuberculosis (TB) classiﬁcation. By promoting the discussion of data curation not only as process to ﬁlter noises and artifacts related to the data itself, but as a multidisciplinary approach needed to reduce unwanted bias in the process of dataset creation while demanding ﬁdelity to RWD, we hope more attention will be bestowed upon the current limitations of DL models trained with medical image datasets that fall short of maintaining real world applicability.
Determination of the Onset of Shear Thinning of Polydimethylsiloxane

The shear stress and the first normal stress difference were simultaneously measured in shear flow start-up experiments and a subsequent stress relaxation. The measured polydimethylsiloxane show shear thinning flow behavior with a first Newtonian region up to the shear rate at the onset of shear thinning. We found that the shear stress and the first normal stress difference have an equal shear rate at the onset of shear thinning. The shear stress at the onset of shear thinning does not depend on the molecular weight of the polymer and on temperature. Similar to the viscosity master curve, it is possible to create a normal stress master curve, outgoing from the first normal stress coefficient. The shear rate at the onset of shear thinning is estimated from the viscosity master curve and the shear rate at the onset of normal stress thinning from the normal stress master curve. The shear stress and the first normal stress difference have similar transient behavior with start-up stress curves without maximum in stress growth experiments with shear rates from the first Newtonian region. The shear flow start-up experiment with the shear rate at the onset of shear thinning leads to the first indication of an overshoot of the start-up curve. The shear flow start-up experiments with shear rates from the shear thinning region show start-up curves with a maximum for the shear stress and for the first normal stress difference. It was found that the shear rate at the onset of shear thinning and the shear rate at the onset of normal stress thinning, determined by the shear flow start-up measurements, are equal to the values obtained from the master curves. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci 2008
ADVENT OF DEEP ARGO DATA & AN ATTEMPT AT ANALYZING THE DEEPER SOUND SPEED PROFILES FOR EXTRAPOLATION CORREC- TIONS

Both R. Davis & D. Webb were able to develop Argo float technology during early 1990s. A profiling array comprising of 3300 such floats was proposed to cover the oceans globally in 1998 by the Argo’s Science Team. The first Argo profiling float came into existence in the year 1999. By the year 2007, Argo had achieved its target of 3000 active floats covering the desired global ocean. The conventional depth for obtaining Argo data has been 0 2000 meters. As a giant leap forward, by the middle of 2014, a workshop named, “Deep Argo Implementation Workshop”, was held in Hobart. In this conference, Johnson et al. proposed an array of 1228 floats providing coverage of 5° × 5° × 15-day cycles. Deployment of pilot arrays for covering particular regions has already been executed. Deep Ninja and Deep Arvor from Japan and France simultaneously cover depths of 0 4000, while Apex & Solo of Unites States are developed to cover 0 6000 meters. This study is focused on obtaining insitu data from a couple of deep Argo buoys and then, compares their salinity, temperature, and sound speed's in-situ values with the extrapolated ones. Prior to availability of deep Argo, the data in depth was usually extrapolated for various parameter calculations. The literature presents numerous methods and examples for extrapolation of vertical profiles for salinity, temperature, and sound speed profiles. The measured temperature and salinity parameters with the pressure were converted to sound speed profile. The extrapolation was carried out using MATLAB’s polyfit and polyval functions. The comparative analysis among in-situ data and the extrapolated one illustrates deviation in deeper vertical profiles especially after 2500 meters. The analysis results are presented in the form of graphs and marked accordingly for both in-situ and extrapolated curves. In addition, the study focuses on varying factors responsible for the typical anomalies especially in deeper oceans. The anomalies suggest that for deeper depth calculations, the real measured values present more accurate results instead of mere extrapolations.
On the Consistency of Kernel Classification Rule for Functional Random Field

Abstract: We consider the classical moving window rule of classification for functional spatially dependent data. We investigate asymptotic properties of this nonparametric classification rule based on training data drawn from α or β mixing random field taking values in infinite-dimensional space. We extend the results of Younso (2017a) concerning both the consistency and the strong consistency of the moving window classifier to the spatially dependent case under mild assumptions. We propose a method for bandwidth selection and we conduct some simulation studies.
Establishing a reference collection and DNA barcoding the coastal fishes of the United Arab Emirates

Journal of the Ocean Science Foundation, 35, 54–64 (2020) Establishing a reference collection and DNA barcoding the coastal fishes of the United Arab Emirates WILLIAM B. LUDT 1, 2 RIMA W. JABADO 3 SHAMSA M. AL HAMELI 4 LAYNE FREEMAN 5 GENTA TERUYAMA 5 PROSANTA CHAKRABARTY 5 SHAIKHA S. AL DHAHERI 4 1Department of Ichthyology, Natural History Museum of Los Angeles County, 900 Exposition Blvd, Los Angeles, CA 90007, USA corresponding author: wludt@nhm.org 2National Museum of Natural History, Smithsonian Institution, PO Box 37012, Washington, DC 20013-7012, USA 3Elasmo Project, PO Box 29588, Dubai, United Arab Emirates 4Environment Agency Abu Dhabi, PO Box 45553, Abu Dhabi, United Arab Emirates 5Ichthyology Section, 119 Foster Hall, Museum of Natural Science, Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
Employee-Management Relationships in the Wake of Corporate Downsizing*

This study explored the change of employee-management relationships in the wake of corporate downsizing. The purpose of this study was to 1) gain qualitative insights into relationships between management and employees in downsized organizations, and 2) provide a workable application on how to maintain good employee relationships during and after downsizing. Qualitative data collected from interviews revealed that the relationship with management was generally negatively viewed by employees, while management generally viewed this relationship with employees as positive. According to this study, management should enhance trust, commitment, and a communal relationship with its employees.
Impact of Bacterial Extracellular Polymers on Lindane Transport

The ECPs (at a concentration of 30 mg/L) extracted from Pseudomonas aeruginosa, Escherichia coli JM109, and Bacillus subtilis cultures in their stationary phase enhanced the transport of a model pesticide (lindane) in a sand column by 46.1, 31.8, and 19.3% (decrease in retardation factor), respectively. This was because lindane had a larger partition coefficient value between the aqueous phase and the extracellular polymers (ECPs) (Kdom) than between the aqueous phase and the medium matrix (Kds), and the ECPs had a smaller partition coefficient value between the aqueous phase and the medium matrix (Kdoms) than lindane (Kds). Among the ECPs examined, the ECPs extracted from P. aeruginosa had the greatest efficiency in facilitating lindane transport, followed by E. coli JM109 and B. subtilis. It was concluded that when Kdom reached a certain value (greater than 10 mL/g), Kdoms would be the determining factor in facilitating lindane transport. Increase of the ECP concentration increased the efficiency in fac.
A NOVEL TRANSFER LEARNING BASED ON ALBERT FOR MALICIOUS NETWORK TRAFFIC CLASSIFICATION

In network security research, malicious traﬃc classiﬁcation is a very important detection method. Deep learning methods receive more and more attention in malicious traﬃc classiﬁcation research because they are highly accurate and do not require researchers to manually extract features. However, deep learning methods depend strongly on computing power and training data, and malicious traﬃc lacks suﬃcient effective training data. The extremely unbalanced distribution of the data sets will seriously aﬀect the performance of the model. In this work, we focus on network traﬃc embedding, and we want to transfer the natural language representation model to network traﬃc. We propose two methods: 1) Pre-train the model with unlabeled traﬃc and then ﬁne-tune the model with labeled traﬃc data; 2) Transfer the pre-trained language model with language data to the network traﬃc classiﬁcation problem, and ﬁne-tune the model with the labeled network traﬃc. Comparing these two methods reveals that the ALBERT network traﬃc model pre-trained with network traﬃc data has faster convergence speeds, higher accuracy rates, and fewer false alarms. We mainly use cross-layer parameter sharing and reduce the vocab size to reduce the model’s parameters and reduce the model’s computing power requirements. The experiments based on the ISCX-2012 data and ISCX-2017 data sets prove that our ALBERT network traﬃc model performs well in accuracy and true positive rates (TPR). As for the indicator of detection time, our ALBERT network model only took 20ms to complete the classiﬁcation of the network ﬂow, while the original BERT model took 42ms. More importantly, we greatly reduced the model’s dependence on the amount of labeled training data. This will greatly promote the progress of the application of the model.
ROBUST OFF-AXIS DIGITAL HOLOGRAPHIC IMAGING SYSTEM IN COMPRESSIVE SENSING FRAMEWORK

Digital holographic imaging technique based on digital sensor arrays such as CCD/CMOS requires a larger number of pixels to capture the interference pattern into holograms with high resolution. These holographic images hence require large memory for data storage and transmission of 3D information. This paper demonstrates a compressive sensing (CS) method merged with off-axis digital Fresnel holography to reconstruct object wavefront from incomplete hologram pixels detection. Two different sampling masks, i.e. random sampling mask and uniform subsampling mask are considered to reduce the digital hologram samples to reconstruct the object wavefront from fewer hologram measurements. The robustness of the proposed method is validated by reconstructing intensity and phase images of good quality using Haar wavelet sparsified CS approach. The quantitative analysis shows that the proposed compressive off-axis digital holographic system is capable of reconstructing superior quality intensity and phase images of the object wavefront with only 25% hologram pixels. The quantitative comparisons of the results are presented from a numerical experiment to show the proof of the concept.
Effortless Machine Learning on TPUs with Julia

Google’s Cloud TPUs are a promising new hardware architecture for machine learning workloads. They have powered many of Google’s milestone machine learning achievements in recent years. Google has now made TPUs available for general use on their cloud platform and as of very recently has opened them up further to allow use by non-TensorFlow frontends. We describe a method and implementation for ofﬂoading suitable sections of Julia programs to TPUs via this new API and the Google XLA compiler. Our method is able to completely fuse the forward pass of a VGG19 model expressed as a Julia program and into a single TPU exectuable to be ofﬂoaded to the device. Our method composes well with existing compiler-based automatic differentiation techniques on Julia code, and we are thus able to also automatically obtain the VGG19 backwards pass and similarly ofﬂoad it to the TPU. Targeting TPUs using our compiler, we are able to evaluate the VGG19 forward pass on a batch of 100 images in 0.23s which compares favorably to the 52.4s required for the original model on the CPU. Our implementation is less than 1000 lines of Julia, with no TPU specﬁc changes made to the core Julia compiler or any other Julia packages.
A procedure for calculating thermodynamic functions of cavity formation from the pure solvent simulation data

It is shown that the thermodynamic quantities for the process of inserting a cavity into a liquid are given by the ensemble average of the function ζ and the correlation in the fluctuation of this function with the thermodynamic quantity of interest. The function ζ is defined for each configuration of the system as the fraction of volume, at each point of which a cavity of given size can be placed. The algorithm for computing this volume is already known. As a by‐product of this derivation, it is pointed out that the entropy change upon cavity insertion is made of two parts—that associated with simple restriction of the solvent configurations due to the presence of the cavity and another that results from the reorganization of the solvent around the cavity. The latter part precisely cancels the change in enthalpy, so that the free energy of cavity formation is entirely given by the entropy change associated with the simple restriction in the configuration of the solvent. A potentially useful approximati.
Optimization of Microprojectile Bombardment Parameters for Pollen-Mediated Transformation in Gossypium hirsutum L

Mature pollen-mediated transformation in cotton (Gossypium hirsutum L.) by microprojectile bombardment was established under gaseous medium in our laboratories. Bombardment parameters influencing the vitality, in vitro germinability and GUS transient expression of bombarded pollen were studied and optimized by the Gray System Analysis method. Optimum conditions for cotton are summarized as follows: the microprojectiles were 0.8-1.1 m diameter metal (tungsten or gold) granules; target distance between the stopping screen and the tissue was 5 cm for a JQ-700 gene delivery device, or 8 cm for a PDS-1000/He apparatus; and mature pollen was bombarded one time at a velocity of 450 m/s for the JQ-700 gene delivery device, or under 1100 psi shot pressure for the PDS-1000/He apparatus. Seeds were set after pollinating with the bombarded pollen.
LESSON 6: TRIDIAGONAL MATRICES

1. General properties (transfer matrix for eigenvectors and spectral duality, characteristic polynomials, Christoffel-Darboux sums, eigenvectors) 2. Real symmetric tridiagonal matrices (simplicity of eigenvalues, eigenvectors, Vandermonde determinant of eigenvalues, map to eigenvalues and a unit vector, periodic matrices, bands, lemniscates) 3.Tridiagonal models (free particle, particle in electric field, Harper model, 1D Anderson model, Thouless formula, Hatano-Nelson model, Lloyd model) 4. Measures of localization of eigenvectors (probability width, participation ratio, entropy). 5. Methods of tridiagonalization (Lanczos and Householder), Beta ensembles 6. Dynamical localization in quantum chaos (the kicked rotator, the Maryland construction)
Proposing a framework for evaluating haptic feedback as a modality for velocity guidance

—Current approaches to motion guidance with haptic feedback largely focus on correcting errors in position. Yet, for applications such as rehabilitation, there are advantages to adding velocity guidance. In this paper, we present an experimental platform designed to evaluate haptic feedback as a feasible modality for velocity guidance. This wearable platform consists of two vibration motors actuated via a microcontroller in response to changes in angular velocity of a user’s upper limb. The system produces vibrotactile stimuli with intensities dependent on the difference between the participant’s velocity and a prescribed velocity proﬁle. The observations made through this analysis will enable future studies into the role of haptic feedback in velocity modulation. Coupled with existing work in trajectory guidance, this system holds the potential to enable more robust motion guidance.
Online Appendix to Accompany Household Search and the Aggregate Labor Market

This online appendix includes four sections. In Section 1, we show detailed results for some models presented in the main text. We also show additional output and robustness exercises based on different parameterizations of the model. Finally, we derive the program of the bachelor household. In Section 2, we describe in detail the CPS data and provide further evidence on the AWE. In Section 3, we present the numerical algorithm we used to solve the incomplete market models and discuss the properties of the solution. Finally, in Section 4 we present the derivation of the solution of the complete market model and describe in detail the numerical procedure we propose to solve this model. A separate document which is posted online contains the appendix for the unemployment insurance extension considered in Section 8 of the paper.
The Metric Backbone in the Human Connectome and across Lifespan

1 Center for Social and Biomedical Complexity, School of Informatics, Computing, & Engineering, Indiana University, Bloomington IN, USA 2 Indiana University Network Science Institute, Indiana University, Bloomington IN, USA 3 INESC-ID, Lisboa, Portugal 4 Department of Psychological and Brain Sciences, Indiana University, Bloomington IN, USA 5 Program in Neuroscience, Indiana University, Bloomington IN, USA 6 Instituto Gulbenkian de Ciência, Oeiras, Portugal anmont@iu.edu