Miracle-dz/UniFAR-FTUs huggingface dataset:
COVID-19 Classification on Chest X-ray Images Using Deep Learning Methods

Since December 2019, the coronavirus disease has significantly affected millions of people. Given the effect this disease has on the pulmonary systems of humans, there is a need for chest radiographic imaging (CXR) for monitoring the disease and preventing further deaths. Several studies have been shown that Deep Learning models can achieve promising results for COVID-19 diagnosis towards the CXR perspective. In this study, five deep learning models were analyzed and evaluated with the aim of identifying COVID-19 from chest X-ray images. The scope of this study is to highlight the significance and potential of individual deep learning models in COVID-19 CXR images. More specifically, we utilized the ResNet50, ResNet101, DenseNet121, DenseNet169 and InceptionV3 using Transfer Learning. All models were trained and validated on the largest publicly available repository for COVID-19 CXR images. Furthermore, they were evaluated on unknown data that was not used for training or validation, authenticating their performance and clarifying their usage in a medical scenario. All models achieved satisfactory performance where ResNet101 was the superior model achieving 96% in Precision, Recall and Accuracy, respectively. Our outcomes show the potential of deep learning models on COVID-19 medical offering a promising way for the deeper understanding of COVID-19.
The Renal Manifestations of SARS-CoV-2: A Guide for Family Physicians

COVID-19 is a devastating systemic disease characterized by multisystem involvement driven by exuberant hyperinflammatory and dysregulations in coagulation. In COVID-19 patients, renal failure contributes to morbidity and mortality, and its early detection and timely management are critical to minimize such untoward and irreversible complications. In the healthcare system, family physicians constitute the first node in the management of patients, yet there is a dearth of reports and guidelines focusing on them for specific organ affection. This review provides an overview of recent studies examining the renal manifestations following SARS-CoV-2 infection. We focus on the tell-tale signs and laboratory findings of renal affection in the pediatric and adult populations with COVID-19, specifically for family practitioners to assist in their appropriate triage. Among different manifestations, urinary abnormalities and a modest increase in creatinine are the early indicators of renal affection in COVID-19 patients. Although renal transplant patients are conventionally managed by specialized teams, they may present to family physicians during a pandemic. This review provides a framework for family physicians to promptly detect early indicators of renal involvement in patients infected with SARS-CoV-2, including providing triage guidance for kidney transplant recipients.
A Designed Host Defense Peptide for the Topical Treatment of MRSA-Infected Diabetic Wounds

Diabetes mellitus is a chronic disease characterized by metabolic dysregulation which is frequently associated with diabetic foot ulcers that result from a severely compromised innate immune system. The high levels of blood glucose characteristic of diabetes cause an increase in circulating inflammatory mediators, which accelerate cellular senescence and dampen antimicrobial activity within dermal tissue. In diabetic wounds, bacteria and fungi proliferate in a protective biofilm forming a structure that a compromised host defense system cannot easily penetrate, often resulting in chronic infections that require antimicrobial intervention to promote the healing process. The designed host defense peptide (dHDP) RP557 is a synthesized peptide whose sequence has been derived from naturally occurring antimicrobial peptides (AMPs) that provide the first line of defense against invading pathogens. AMPs possess an amphipathic α-helix or β-sheet structure and a net positive charge that enables them to incorporate into pathogen membranes and perturb the barrier function of Gram-positive and Gram-negative bacteria along with fungi. The capacity of skin to resist infections is largely dependent upon the activity of endogenous AMPs that provided the basis for the design and testing of RP557 for the resolution of wound infections. In the current study, the topical application of RP557 stopped bacterial growth in the biofilm of methicillin-resistant Staphylococcus aureus (MRSA) USA300 infected wounds on the flanks of clinically relevant diabetic TALLYHO mice. Topical application of RP557 reduced bacterial load and accelerated wound closure, while wound size in control diabetic mice continued to expand. These studies demonstrate that RP557 reduces or eliminates an infection in its biofilm and restores wound-healing capacity.
EnKF and Hybrid Gain Ensemble Data Assimilation. Part I: EnKF Implementation

AbstractThe desire to do detailed comparisons between variational and more scalable ensemble-based data assimilation systems in a semioperational environment has led to the development of a state-of-the-art EnKF system at ECMWF. A broad description of the ECMWF EnKF is given in this paper, focusing on highlighting differences compared to standard EnKF practice. In particular, a discussion of the novel algorithm used to control imbalances between the mass and wind fields in the EnKF analysis is given. The scalability and computational properties of the EnKF are reviewed and the implementation choices adopted at ECMWF described. The sensitivity of the ECMWF EnKF to ensemble size, horizontal resolution, and representation of model errors is also discussed. A comparison with 4DVar will be found in Part II of this two-part study.
Impact of the interannual variability of the South China Sea monsoon trough on tropical cyclone activity over the western North Pacific

The present study reveals the impact of the interannual variability of the South China Sea monsoon trough (SCSMT) on tropical cyclone (TC) activity over the South China Sea (SCS) and the western North Pacific (WNP) from June to August during the period of 1958–2019. The SCSMT can influence TC genesis and occurrence through affecting the large‐scale environmental conditions and barotropic energy conversion. The intensification of the SCSMT can lead to enhanced low‐level vorticity and upper‐level divergence, decreased vertical wind shear, and increased midlevel humidity over the northern SCS and subtropical WNP. The strengthening of the SCSMT is accompanied by an intensification and eastward extension of the WNP monsoon trough and eastward retreat of the WNP subtropical high. All these changes associated with the SCSMT are favourable for TC genesis and occurrence over the north SCS and WNP. More TCs form over the WNP around 20° N, while higher TC occurrence frequency appears over the north SCS and WNP north of 20° N. Diagnostic results of eddy kinetic energy distribution and barotropic energy conversion provide a possible explanation for the impact of the SCSMT on TC activity. The synoptic‐scale disturbances are more active in the WNP region north of 20° N which might lead to an increase in TC occurrence frequency. While the barotropic energy conversion is intensified in the northern SCS and east of Philippines, more eddy energy converted from the mean flow is favourable for TC genesis. The meridional shear of mean zonal wind and the meridional convergence of mean meridional wind, which are related with the interannual variability of the SCSMT, primarily contribute to the barotropic energy conversion.
EGFR Pathway Expression Persists in Recurrent Glioblastoma Independent of Amplification Status

Simple Summary We compared gene expression in matched primary and recurrent glioblastoma samples, with a focus on those harbouring extra copies of the gene called EGFR (amplified samples). Our results show that in the setting of newly diagnosed glioblastoma, EGFR-amplified compared to EGFR non-amplified tumours display altered gene expression in the EGFR pathway, but this distinction is lost in the setting of recurrent disease. We validated this finding in an independent dataset. EGFR pathway overexpression may be a common mechanism underlying glioblastoma recurrence. Abstract Background: Glioblastoma mortality is driven by tumour progression or recurrence despite administering a therapeutic arsenal consisting of surgical resection, radiation, and alkylating chemotherapy. The genetic changes underlying tumour progression and chemotherapy resistance are poorly understood. Methods: In this study, we sought to define the relationship between EGFR amplification status, EGFR mRNA expression, and EGFR pathway activity. We compared RNA-sequencing data from matched primary and recurrent tumour samples (n = 40 patients, 20 with EGFR amplification). Results: In the setting of glioblastoma recurrence, the EGFR pathway was overexpressed regardless of EGFR-amplification status, suggesting a common genomic endpoint in recurrent glioblastoma, although EGFR amplification did associate with higher EGFR mRNA expression. Three of forty patients in the study cohort had EGFR-amplified tumours and received targeted EGFR therapy. Their molecular subtypes and clinical outcomes did not significantly differ from patients who received conventional chemotherapy. Conclusion: Our findings suggest that while the EGFR amplification may confer a unique molecular profile in primary glioblastoma, pathway analysis reveals upregulation of the EGFR pathway in recurrence, regardless of amplification status. As such, the EGFR pathway may be a key mediator of glioblastoma progression.
Urinary 15-F2t-Isoprostane Concentrations in Dogs with Liver Disease

Simple Summary Similar to humans, dogs are affected by a variety of liver diseases with various causes and presentations. Recently, growing interest has focused on measuring markers of oxidative stress in patients with liver disease; however, no study to date has compared markers of oxidative stress between dogs with different liver diseases. This study aimed to evaluate markers of oxidative stress in dogs with different types of liver disease by measuring a compound known as 15-F2t-isoprostane in their urine. Among dogs with one of three different types of liver diseases, only those with a congenital portosystemic shunt (CPSS) had a significant increase in this oxidative stress marker when compared with a group of healthy control dogs. Abstract Isoprostanes are stable end products of lipid peroxidation that can be used as markers of oxidative stress. It was previously reported that a cohort of dogs with various liver diseases had increased urinary isoprostane concentrations compared to healthy control (HC) dogs. The aim of this study was to measure and report urinary isoprostane concentrations in dogs with different types of liver diseases. Urine was collected from 21 HC dogs and from 40 dogs with liver disease, including 25 with chronic hepatitis (CH), 7 with steroid hepatopathy (SH), and 8 with a congenital portosystemic shunt (CPSS). In this prospective, observational study, urinary 15-F2t-isoprostane (F2-IsoP) concentrations were measured by liquid chromatography/mass spectrometry and normalized to urinary creatinine concentrations. Concentrations were compared between groups using a Kruskal–Wallis test followed by Dunn’s multiple comparisons tests. Significance was set at p < 0.05. The median (range) urinary F2-IsoP to creatinine ratios (ng/mg UCr) were 3.6 (2.2–12.4) for HC dogs, 5.7 (2.4–11.3) for dogs with CH, 4.8 (2.4–8.6) for dogs with SH, and 12.5 (2.9–22.9) for dogs with CPSS. CPSS dogs had significantly higher urinary F2-IsoP concentrations than HC dogs (p = 0.004), suggesting increased oxidative stress among this cohort.
Researchers’ subjectivities in a study of infants & toddlers

ABSTRACT Our purpose in this article is to examine the subjective processes of researchers while becoming conscious during the investigation of infants and toddlers (I/Ts) in educational settings. Based on the intertwining between Cultural-historical Psychology and Ethnography in Education, we followed a group of I/Ts at a Brazilian Early Childhood Education Center between 2017 and 2019. This extended length of time in the field allowed us to build a logic of inquiry with consciousness as its foundation. We focus on an analysis of four events which occurred at different times within this two-year period that make visible the researcher’s processes of becoming conscious at the center of the research process itself. Becoming conscious enabled repositioning ourselves as researchers, transforming the research process, and reorganizing the latter as a whole. In this study, we demonstrate that ‘becoming conscious’ involves considering whether the research extends beyond being an object of knowledge, and includes a meta-analysis of the research path actually taken through approximations and distancing with data, as well as the creation of new interpretations, solutions and combinations of these, as the study progressed. We argue that becoming conscious, as a relational and situated process, is an essential dimension of educational research.
Three-dimensional particle image velocimetry: error analysis of stereoscopic techniques

A geometric error model for analysis and design of stereoscopic PIV systems is presented. The model allows displacement errors in either translational or angular systems to be analysed for any given angle or camera separation and for any off-axis position. A parameter for the analysis of the system performance is also introduced based on the ratio of out-of-plane to in-plane errors. This is subsequently used to investigate the relative performance of translational and angular PIV systems for camera angles up to and camera separations of half the object distance. Results from this analysis show similar trends in centreline characteristics for both types of stereo systems but different trends in off-axis error ratios due to imaging geometry. The results have also suggested that a CCD-based angular PIV stereo system offers up to 40% greater out-of-plane accuracy for a given field of view and laser power than previous translational systems.
Effectiveness of a Primary Care Multidisciplinary Treatment for Patients with Chronic Pain Compared with Treatment as Usual

To manage chronic pain, multidisciplinary interventions have been increasingly deployed, mostly in secondary or tertiary care settings. Evidence on the effectiveness of multidisciplinary intervention within primary care is scarce. This study examined the effectiveness of a primary care multidisciplinary treatment for chronic pain compared with treatment as usual (TAU). The intervention consisted of pain neuroscience education and treatment by a GP, psychologist, and physiotherapist. Both groups filled out patient-reported outcome measures at baseline, 6 months, and 12 months. The results indicated there were no statistically significant differences for the primary outcomes of pain intensity, number of pain sites, and health-related quality of life (HR-QoL). There was a statistically significant difference in the secondary outcome perceived health change in favor of the intervention group. None of the other differences were statistically significant. A post-hoc analysis showed that there were statistically significant effects on patients’ illness perceptions in favor of the intervention group. Based on the results, the findings do not support effectiveness of a low intensity outpatient multidisciplinary primary care treatment to treat chronic pain compared with TAU. However, as a result of several study limitations, it is considered unwarranted to conclude that multidisciplinary treatment in primary care is not valuable at all.
Plant community responses to alterations in soil abiotic and biotic conditions are decoupled for above‐ and below‐ground traits

Plant functional traits are increasingly recognised as being impacted by soil abiotic and biotic factors. Yet, the question to what extent the coupling between community‐level above‐ and below‐ground traits is affected by soil conditions remains open. In a field experiment in dune grassland, we quantified the responses of both community‐level leaf and root traits to changes in soil abiotic and biotic conditions using soil inoculation by living and sterile soil inocula originated from different dune ecosystems. Altered soil conditions resulted in a strong decoupling in responses of community‐level leaf and root traits. Changes in soil abiotic conditions imposed by soil inoculation were more important in determining the decoupling of the leaf vs root relationships than additions of soil biota. Altered soil abiotic factors influenced both leaf and root traits at the community level and caused the entire community‐level trait spectrum to shift, while experimental additions of living soil inocula only significantly influenced root traits towards longer and thinner roots. Synthesis. Our results bring direct evidence that, at a plant community level, the dynamics of plant above‐ground traits are not informative of below‐ground traits. Particularly, below‐ground abiotic processes are a major driver of commonly observed trait spectra. We suggest that future study is required to test the general pattern of leaf and root correlations across different ecosystems under field conditions.
Online Compression and Reconstruction for Communication of Force-Tactile Signals

We focus on force-tactile signals that are generated by sliding fingertips on physical surfaces. In tactile-communication applications, these signals are sent to surface-haptics devices for tactile-texture display. To ensure the high reliability and low latency for such communication, we present a method that compresses the signals into compact representations before transmission, and approximately reconstructs them with reasonably small errors before display. Specifically, the method is based on stacked auto-encoder (SAE) and gated recurrent unit (GRU). The former achieves compression and reconstruction without considering channel noise; the latter suppresses the channel noise for the received compact representations before reconstruction. The proposed method is numerically evaluated, using HapTex and TUM184 datasets. Results show that the method (i) achieves a high compression ratio with a reasonably small reconstruction error, (ii) can be efficiently implemented for online deployment, and (iii) requires no statistical assumption of force-tactile signals and channel noise.
Weakly guiding analysis of elliptical core step index waveguides based on the characteristic numbers of Mathieu's equation

A new weak guidance analysis for step index elliptical core optical fibers is developed. The method shows that weakly guiding, or linearly polarized (LP), modes are determined by and correspond uniquely to the characteristic numbers of Mathieu's equation. This is the first analysis of elliptical core weakly guiding modes which determines propagation constants and indexes modes by directly solving the underlying Mathieu's equation through the sole use of characteristic numbers. The resulting new analysis resolves an ambiguity in the standard literature concerning the classification of weakly guiding modes.
Fully-Decoupled Radio Access Networks: A Resilient Uplink Base Stations Cooperative Reception Framework

To cope with the even more urgent spectrum and energy efficiency challenge for trillion-level terminal access and data uploading in the next generation mobile communication network (6G), in this paper, we investigate the uplink transmission in an original fully-decoupled radio access networks (FD-RAN) architecture. Specifically, we propose a resilient uplink base station cooperative reception framework in FD-RAN, which is a large-scale fading based two-tier signal combination approach for the uplink transmission, including the localized signal combination at the base station and centralized signal combination at the edge cloud, respectively. Then, we formulate a weighted sum-rate maximization problem for the uplink transmission optimization, and decompose it into two subproblems. A spectrum-efficiency maximized virtual service cluster selection (SEMVS) algorithm is designed by leveraging the channel statistical information for solving subproblem one, and a fractional programming based power control (FPPC) algorithm is introduced for the power optimization of subproblem two. Compared to the typical RAN architectures with corresponding access and power control methods, simulation results demonstrate the significant performance improvements of uplink FD-RAN with the proposed solution.
How I Met Your V2X Sensor Data: Analysis of Projection-Based Light Field Visualization for Vehicle-to-Everything Communication Protocols and Use Cases

The practical usage of V2X communication protocols started emerging in recent years. Data built on sensor information are displayed via onboard units and smart devices. However, perceptually obtaining such data may be counterproductive in terms of visual attention, particularly in the case of safety-related applications. Using the windshield as a display may solve this issue, but switching between 2D information and the 3D reality of traffic may introduce issues of its own. To overcome such difficulties, automotive light field visualization is introduced. In this paper, we investigate the visualization of V2X communication protocols and use cases via projection-based light field technology. Our work is motivated by the abundance of V2X sensor data, the low latency of V2X data transfer, the availability of automotive light field prototypes, the prevalent dominance of non-autonomous and non-remote driving, and the lack of V2X-based light field solutions. As our primary contributions, we provide a comprehensive technological review of light field and V2X communication, a set of recommendations for design and implementation, an extensive discussion and implication analysis, the exploration of utilization based on standardized protocols, and use-case-specific considerations.
Data assimilation and parametrisation of lakes in HIRLAM

ABSTRACT When the resolution of numerical weather prediction (NWP) and climate models increases, it becomes more and more important to correctly account for the lake–atmosphere interactions. One possible way to handle lake effects is to use a lake model, which treats the lake surface temperature and ice conditions as prognostic variables. Such a parametrisation eliminates the traditional for NWP need to prescribe lake characteristics based on long-term climate averages. At the same time, new in situ and satellite measurements are becoming available for an operational practice. This offers the possibility to assimilate lake observations into the NWP models. We study the applicability of the prognostic and observation-based approaches and compare both. As a first step towards integrated lake data assimilation and forecasting in NWP, we suggest using the results of the prognostic lake parametrisation as the background for objective analysis (spatialisation) of the lake water surface temperature observations. We run NWP experiments in the Nordic conditions, where the freezing and melting of lakes can significantly influence local weather. Our results indicate that a lake model, usually used in climate studies, works well also in the NWP model even without assimilation of observations. However, it is possible to improve the description of the changing lake surface state by using good observation data. In this case, the lake model provides a better background for the data assimilation than a lake surface temperature climatology.