Miracle-dz/UniFAR-FTUs huggingface dataset:
Prenatal and Neonatal Pulmonary Thrombosis as a Potential Complication of SARS-CoV-2 Infection in Late Pregnancy

Neonatal venous thrombosis is a rare condition that can be iatrogenic or occur due to viral infections or genetic mutations. Thromboembolic complications are also commonly observed as a result of SARS-CoV-2 infections. They can affect pediatric patients, especially the ones suffering from multisystem inflammatory syndrome in children (MIS-C) or multisystem inflammatory syndrome in neonates (MIS-N). The question remains whether the maternal SARS-CoV-2 infection during pregnancy can lead to thromboembolic complications in fetuses and neonates. We report on a patient born with an embolism in the arterial duct, left pulmonary artery, and pulmonary trunk, who presented several characteristic features of MIS-N, suspecting that the cause might have been the maternal SARS-CoV2 infection in late pregnancy. Multiple genetic and laboratory tests were performed. The neonate presented only with a positive result of IgG antibodies against SARS-CoV-2. He was treated with low molecular weight heparin. Subsequent echocardiographic tests showed that the embolism dissolved. More research is necessary to evaluate the possible neonatal complications of maternal SARS-CoV-2 infection.
Clinico-Pathological and Radiological Spectrum of Mediastinal Masses in a Tertiary Care Center: A Cross-Sectional Study

Introduction The phrase “mediastinal mass” refers to a mass within the mediastinum. About 50% of all mediastinal masses, including teratoma, thymoma, lymphoma, and thyroid illness, are anterior mediastinal tumors. Data on the mediastinal mass in India are relatively sparse, especially in this region, compared to those from other countries. Mediastinal masses are very infrequent lesions that might occasionally present a diagnostic and therapeutic challenge to the doctor. The current study describes the socio-demographic characteristics, symptoms, diagnosis, and location of mediastinal mass among the study participants. Methodology We carried out a retrospective, cross-sectional study in a tertiary care center in Chennai for three years. We included patients with an age above 16 years who visited the tertiary care center in Chennai during the study period. We included all patients with a mediastinal mass diagnosed by CT scan, with or without signs and symptoms of mediastinal compression. Patients under the age of 16 and those with insufficient data were both excluded from the study. As per the universal sampling technique, we included all the patients who met the eligibility criteria during the study period (three years) as study subjects. By using the hospital records, we collected all data about the patients like socio-demographic data, presenting complaints, past history, x-ray findings, and co-morbidities. Similarly, we recorded blood parameters, pleural fluid parameters, and histopathological reports from the laboratory register. Results The mean age of the study participants was 41.11 years, with a high proportion of patients belonging to the age group of 21 to 30 years. Over 70% of the study participants were male. Only about 54.5% of the study participants had symptoms because of a mediastinal mass. The most common local symptom felt by the patients was dyspnea, followed by a dry cough. Weight loss was the most common symptom for the patients. Most study participants (47.7%) had seen a doctor within one month of the onset of symptoms. About 4.5% of the patients had pleural effusion, as diagnosed by x-ray. Most of the study participants had a mass in the anterior mediastinum, followed by the posterior mediastinum. Most of the participants (15.9%) had non-caseating granulomatous inflammation suggestive of sarcoidosis. Conclusion The most common tumor found in our study was lymphoma, which was followed by non-caseating granulomatous disease and thymoma. Anterior compartments are most commonly involved. We observed the most common presentation in the third decade of life with a male to female ratio of 2:1, with dyspnea being the most common symptom, followed by a dry cough. Our study found 4.5% of the patients had pleural effusion as a complication.
Partial regularity of minimizers of p(x)‐growth functionals with 1 < p(x) < 2

We prove partial regularity of minimizers u for p(x) ‐energy functionals of the following type: E(u)=∫Ω(Aijαβ(x,u)DαuiDβuj)p(x)/2dx, assuming that Aijαβ(x,u) and p(x) are sufficiently smooth and that p(x) is subquadratic.
KaRIn Noise Reduction Using a Convolutional Neural Network for the SWOT Ocean Products

The SWOT (Surface Water Ocean Topography) mission will provide high-resolution and two-dimensional measurements of sea surface height (SSH). However, despite its unprecedented precision, SWOT’s Ka-band Radar Interferometer (KaRIn) still exhibits a substantial amount of random noise. In turn, the random noise limits the ability of SWOT to capture the smallest scales of the ocean’s topography and its derivatives. In that context, this paper explores the feasibility, strengths and limits of a noise-reduction algorithm based on a convolutional neural network. The model is based on a U-Net architecture and is trained and tested with simulated data from the North Atlantic. Our results are compared to classical smoothing methods: a median filter, a Lanczos kernel smoother and the SWOT de-noising algorithm developed by Gomez-Navarro et al. Our U-Net model yields better results for all the evaluation metrics: 2 mm root mean square error, sub-millimetric bias, variance reduction by factor of 44 (16 dB) and an accurate power spectral density down to 10–20 km wavelengths. We also tested various scenarios to infer the robustness and the stability of the U-Net. The U-Net always exhibits good performance and can be further improved with retraining if necessary. This robustness in simulation is very encouraging: our findings show that the U-Net architecture is likely one of the best candidates to reduce the noise of flight data from KaRIn.
Social Spending, Poverty, and Immigration: A Systematic Analysis of Welfare State Effectiveness and Nativity in 24 Upper- and Middle-Income Democracies

Previous research has highlighted the disadvantaged position immigrants often face in the economy, particularly when it comes to labor market outcomes such as employment or earnings. Extending this literature, the present study evaluates the economic exclusion of immigrants, conceptualized not as labor market outcomes but as relative poverty. This study examines the relationship between welfare generosity and immigrant poverty across rich western democracies and compares this relationship with that of native poverty. One publicly held belief is that immigrants disproportionately benefit from welfare generosity, while the literature on welfare chauvinism suggests greater social spending may not necessarily benefit immigrants. Furthermore, the effects may vary by spending and immigrant type. This study uses the Luxembourg Income Study to consider differences in the effects of welfare generosity on the odds an immigrant or native household is poor, how this effect varies by the type of spending, and how the effect changes depending on factors such as region of origin or citizenship status. Using four waves of data circa 2004 to 2014 across 24 upper- and middle-income democracies, the results show some support for welfare chauvinism and advantages to being an intra-EU immigrant and citizen immigrant.
Testing of the Facial Expression Coding System (FACES) for middle school–aged special education students and development of a training protocol

Emotion regulation is a key developmental skillset, but many existing measures rely on self-report or laboratory-based measurement approaches. This study aimed to develop a training and implementation protocol for the widely used Facial Expression Coding System (FACES) to be used in real-world settings with pre-recorded video data. A revised coding system with supplemental guidelines and training procedures was developed to use FACES with video data recorded in special education classrooms. This system resulted in adequate interrater reliability as well as reduced training time for coders. Specific training methods included close study of code definitions, coding of practice video, quantitative analysis of observation data to generate interrater agreement and kappa statistics, review of comparison charts to identify discrepancies between coder and training observations using the Noldus Observer XT software, and post-observation discussions. The revised FACES protocol and new training method presented here offer a more robust, efficient, and versatile tool that can be applied to systematic behavior observations conducted of students in real-world classroom settings.
Pulmonary embolism at CT pulmonary angiography in patients with COVID-19 at a tertiary care center in Nepal: a cross-sectional study

Introduction: Coronavirus disease 2019 (COVID-19) began to spread in December 2019 and was declared a pandemic by WHO on 11 March 2020. Pulmonary embolism (PE) is a known sequel to COVID-19 infection. Many patients showed worsened symptoms of thrombotic events of pulmonary arteries during the second week of the disease for which computed tomography pulmonary angiography (CTPA) is recommended. The most frequent complications in critically ill patients are prothrombotic coagulation abnormalities and thromboembolism. So, this study aimed to assess the prevalence of PE in patients with COVID-19 infection and to evaluate the relation to disease severity on CTPA findings. Methods: This cross-sectional study was performed to evaluate the patients who tested positive for COVID-19 and underwent CTPA. COVID-19 infection in participants was confirmed by a PCR of nasopharyngeal or oropharyngeal swab samples. Frequencies of computed tomography severity scores and CTPA were calculated and compared with clinical and laboratory findings. Results: The study included 92 patients with COVID-19 infection. Positive PE was found in 18.5% of the patients. The mean age of the patients was 59.83±13.58 years with an age range of 30–86 years. Among the total participants, 27.2% underwent ventilation, 19.6% died during treatment, and 80.4% of them got discharged. PE was developed in patients who did not receive prophylactic anticoagulation, which is statistically significant (P≤0.001). There was also a significant relationship between mechanical ventilation and CTPA findings. Conclusions: The authors conclude from their study that PE is one of the complications of COVID-19 infection. Rising D-dimer during the second week of disease alerts clinicians to do CTPA to exclude or confirm PE. This will help in the early diagnosis and treatment of PE.
New Indole-3-Propionic Acid and 5-Methoxy-Indole Carboxylic Acid Derived Hydrazone Hybrids as Multifunctional Neuroprotectors

In light of the known neuroprotective properties of indole compounds and the promising potential of hydrazone derivatives, two series of aldehyde-heterocyclic hybrids combining those pharmacophores were synthesized as new multifunctional neuroprotectors. The obtained derivatives of indole-3-propionic acid (IPA) and 5-methoxy-indole carboxylic acid (5MICA) had good safety profiles: Hemolytic effects < 5% (200 μM) and IC50 > 150 µM were found in the majority of the SH-SY5Y and bEnd3 cell lines. The 2,3-dihydroxy, 2-hydroxy-4-methoxy, and syringaldehyde derivatives of 5MICA exhibited the strongest neuroprotection against H2O2-induced oxidative stress in SH-SY5Y cells and 6-OHDA-induced neurotoxicity in rat-brain synaptosomes. All the compounds suppressed the iron-induced lipid peroxidation. The hydroxyl derivatives were also the most active in terms of deoxyribose-degradation inhibition, whereas the 3,4-dihydroxy derivatives were able to decrease the superoxide-anion generation. Both series of compounds showed an increased inhibition of hMAO-B, with greater expression detected in the 5MICA hybrids. The in vitro BBB model with the bEnd3 cell line showed that some compounds increased the permeability of the endothelial monolayer while maintaining the tight junctions. The combined results demonstrated that the derivatives of IPA and 5MICA showed strong neuroprotective, antioxidant, MAO-B inhibitory activity and could be considered as prospective multifunctional compounds for the treatment of neurodegenerative disorders.
Outdoor River Activities: Relations with Geological Background and Extreme Events in the Perspective of Geoeducation

As for sport climbing, also for outdoor activities such as rafting and canyoning, a strong connection with geofeatures on a long and short time scale exists. For investigating this, three river segments were selected in the Sesia hydrographic basin (Sesia Val Grande UNESCO Global Geopark, Northwest Italy). Here, commercial rafting and canyoning activities are popular, and important geological features are present (Sesia Supervolcano, Insubric Line). The segments were investigated using partly IDRAIM (system for stream hydromorphological assessment, analysis, and monitoring). Bedrock features, confinement, sinuosity, bankfull bottom, morphological units, and steepness were characterized. The segments were hence divided in several reaches. Correlations on the long time scale were found mainly between the geology and bankfull bottom configuration, while sinuosity allowed us to highlight the possible structural control on the genesis of gorges. Moreover, the analysis of changes in a short time scale along the river segments after the extreme meteorological event occurred on 2–3 October 2020, highlighted a rapids difficulty variation, channels diversion, and woody–rocky debris accumulation in the bankfull, deeply influencing river activities. Through the proposed approach, new frontiers in the outreach of geosciences could be opened, especially in virtue of the several Sustainable Development Goals that could be achieved through river outdoor activities, among the others new employment opportunities for local operators.
Phosphorylation Promotes the Accumulation of PERIOD Protein Foci

Circadian clock drives the 24-h rhythm in our behavior and physiology. The molecular clock consists of a series of transcriptional/translational feedback loops operated by a number of clock genes. A very recent study reported that the clock protein PERIOD (PER) is organized into discrete foci at the nuclear envelope in fly circadian neurons, which is believed to be important for controlling the subcellular localization of clock genes. Loss of inner nuclear membrane protein lamin B receptor (LBR) leads to disruption of these foci, but how they are regulated is yet unknown. Here, we found that PER foci are likely phase-separated condensates, the formation of which is mediated by intrinsically disordered region in PER. Phosphorylation promotes the accumulation of these foci. Protein phosphatase 2A, which is known to dephosphorylate PER, hampers the accumulation of the foci. On the other hand, the circadian kinase DOUBLETIME (DBT) which phosphorylates PER enhances the accumulation of the foci. LBR likely facilitates PER foci accumulation by destabilizing the catalytic subunit of protein phosphatase 2A, MICROTUBULE STAR (MTS). In conclusion, here, we demonstrate a key role for phosphorylation in promoting the accumulation of PER foci, while LBR modulates this process by impinging on the circadian phosphatase MTS.
Lower bound limit analysis with adaptive remeshing

The objective of this work is to present an adaptive remeshing procedure for lower bound limit analysis with application to soil mechanics. Unlike conventional finite element meshes, a lower bound grid incorporates statically admissible stress discontinuities between adjacent elements. These discontinuities permit large stress jumps over an infinitesimal distance and reduce the number of elements needed to predict the collapse load accurately. In general, the role of the discontinuities is crucial as their arrangement and distribution has a dramatic influence on the accuracy of the lower bound solution (Limit Analysis and Soil Plasticity, 1975). To ensure that the discontinuities are positioned in an optimal manner requires an error estimator and mesh adaptation strategy which accounts for the presence of stress singularities in the computed stress field.
Hypoxia-induced Wnt/β-catenin signaling activation in subchondral bone osteoblasts leads to an osteoarthritis-like phenotype of chondrocytes in articular cartilage

Background: Osteoarthritis (OA) is a whole-joint disease and characterized by alterations in the articular cartilage, subchondral bone, ligaments, and synovial membrane. The crosstalk between cartilage and subchondral bone plays a crucial role in the pathogenesis and progression of OA. Hypoxia has been reported to play an important role in cartilage degradation and subchondral bone remodeling in OA. In this study, we aimed to identify the involvement of hypoxia in modifying the osteoblast phenotypes and determine whether these alterations could influence the metabolism of chondrocytes. Methods: First, the levels of Hif-1α in subchondral bone of different compartments in patients with OA were assessed using immunohistochemistry (IHC). In in vitro, human primary osteoblasts were cultured under hypoxic and normoxic conditions, and the hypoxic or normoxic conditioned media (HCM and NCM) were used to culture human primary chondrocytes. Then, phenotypic changes in osteoblasts were assessed using reverse transcription-polymerase chain reaction (RT-PCR), Western blotting, and enzyme-linked immunosorbent assay (ELISA). Furthermore, the expression of type II collagen (COL2A1), aggrecan (ACAN), SRY-related high-mobility group-box gene 9 (SOX9), matrix metalloproteinase 13 (MMP13), and matrix metalloproteinase 3 (MMP3) in chondrocytes was measured using RT-PCR. Finally, the serum levels of Wnt-related proteins were determined using ELISA. Results: Hif-1α was significantly increased in severely sclerotic subchondral bone compared to less damaged subchondral bone. β-Catenin and SOST were identified as upregulated and downregulated in hypoxic osteoblasts, respectively. The hypoxia-induced results were confirmed by ELISA. Stimulating human primary chondrocytes with HCM significantly induced MMP13 and MMP3 and inhibited COL2A1, ACAN, and SOX9 mRNA expression. The serum levels of DKK-1 were significantly increased in human OA. Conclusion: Together, these findings revealed that hypoxia in subchondral bone is a key factor in the crosstalk between chondrocytes and osteoblasts and facilitates the shift of chondrocytes toward an OA-like phenotype probably by activating the Wnt/β-catenin signaling pathway in osteoblasts.
An Incremental Inverse Reinforcement Learning Approach for Motion Planning with Separated Path and Velocity Preferences

Humans often demonstrate diverse behaviors due to their personal preferences, for instance, related to their individual execution style or personal margin for safety. In this paper, we consider the problem of integrating both path and velocity preferences into trajectory planning for robotic manipulators. We first learn reward functions that represent the user path and velocity preferences from kinesthetic demonstration. We then optimize the trajectory in two steps, first the path and then the velocity, to produce trajectories that adhere to both task requirements and user preferences. We design a set of parameterized features that capture the fundamental preferences in a pick-and-place type of object transportation task, both in the shape and timing of the motion. We demonstrate that our method is capable of generalizing such preferences to new scenarios. We implement our algorithm on a Franka Emika 7-DoF robot arm and validate the functionality and flexibility of our approach in a user study. The results show that non-expert users are able to teach the robot their preferences with just a few iterations of feedback.
Pre-trained Perceptual Features Improve Differentially Private Image Generation

Training even moderately-sized generative models with differentially-private stochastic gradient descent (DP-SGD) is difficult: the required level of noise for reasonable levels of privacy is simply too large. We advocate instead building off a good, relevant representation on an informative public dataset, then learning to model the private data with that representation. In particular, we minimize the maximum mean discrepancy (MMD) between private target data and a generator's distribution, using a kernel based on perceptual features learned from a public dataset. With the MMD, we can simply privatize the data-dependent term once and for all, rather than introducing noise at each step of optimization as in DP-SGD. Our algorithm allows us to generate CIFAR10-level images with $\epsilon \approx 2$ which capture distinctive features in the distribution, far surpassing the current state of the art, which mostly focuses on datasets such as MNIST and FashionMNIST at a large $\epsilon \approx 10$. Our work introduces simple yet powerful foundations for reducing the gap between private and non-private deep generative models. Our code is available at \url{https://github.com/ParkLabML/DP-MEPF}.
Multi-domain learning CNN model for microscopy image classification

For any type of microscopy image, getting a deep learning model to work well requires considerable effort to select a suitable architecture and time to train it. As there is a wide range of microscopes and experimental setups, designing a single model that can apply to multiple imaging domains, instead of having multiple per-domain models, becomes more essential. This task is challenging and somehow overlooked in the literature. In this paper, we present a multi-domain learning architecture for the classification of microscopy images that differ significantly in types and contents. Unlike previous methods that are computationally intensive, we have developed a compact model, called Mobincep, by combining the simple but effective techniques of depth-wise separable convolution and the inception module. We also introduce a new optimization technique to regulate the latent feature space during training to improve the network's performance. We evaluated our model on three different public datasets and compared its performance in single-domain and multiple-domain learning modes. The proposed classifier surpasses state-of-the-art results and is robust for limited labeled data. Moreover, it helps to eliminate the burden of designing a new network when switching to new experiments.
Local dimer dynamics in higher dimensions

We consider local dynamics of the dimer model (perfect matchings) on hypercubic boxes $[n]^d$. These consist of successively switching the dimers along alternating cycles of prescribed (small) lengths. We study the connectivity properties of the dimer configuration space equipped with these transitions. Answering a question of Freire, Klivans, Milet and Saldanha, we show that in three dimensions any configuration admits an alternating cycle of length at most 6. We further establish that any configuration on $[n]^d$ features order $n^{d-2}$ alternating cycles of length at most $4d-2$. We also prove that the dynamics of dimer configurations on the unit hypercube of dimension $d$ is ergodic when switching alternating cycles of length at most $4d-4$. Finally, in the planar but non-bipartite case, we show that parallelogram-shaped boxes in the triangular lattice are ergodic for switching alternating cycles of lengths 4 and 6 only, thus improving a result of Kenyon and R\'emila, which also uses 8-cycles. None of our proofs make reference to height functions.