Miracle-dz/UniFAR-FTUs huggingface dataset:
Comment on"Atomic structure and electron impact excitation of Al-like ions (Ga--Br)"by HB Wang and G Jiang in At. Data Nucl. Data Tables 148 (2022) 101532

In a recent paper, Wang and Jiang (At. Data Nucl. Data Tables 148 (2022) 101532) have reported data for energy levels, radiative rates (A-values), and effective collision strengths ($\Upsilon$) for some transitions of five Al-like ions, namely Ga~XIX, Ge~XX, As~XXI, Se~XXII, and Br~XXIII. On a closer examination we find that their reported data for energy levels and A-values are generally correct, but not for $\Upsilon$. Their $\Upsilon$ values, for all transitions (allowed or forbidden) and for all ions, invariably decrease at higher temperatures. This is mainly because they have adopted a limited range of electron energies for the calculations of collision strengths. We demonstrate this with our calculations with the Flexible Atomic Code (FAC), and conclude that their $\Upsilon$ values are inaccurate, unreliable, and should not be adopted in any applications or modelling analysis.
At-Admission Prediction of Mortality and Pulmonary Embolism in COVID-19 Patients Using Statistical and Machine Learning Methods: An International Cohort Study

By September, 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients.
Do Models Really Learn to Follow Instructions? An Empirical Study of Instruction Tuning

Recent works on instruction tuning (IT) have achieved great performance with zero-shot generalizability to unseen tasks. With additional context (e.g., task definition, examples) provided to models for fine-tuning, they achieved much higher performance than untuned models. Despite impressive performance gains, what models learn from IT remains understudied. In this work, we analyze how models utilize instructions during IT by comparing model training with altered vs. original instructions. Specifically, we create simplified task definitions by removing all semantic components and only leaving the output space information, and delusive examples that contain incorrect input-output mapping. Our experiments show that models trained on simplified task definition or delusive examples can achieve comparable performance to the ones trained on the original instructions and examples. Furthermore, we introduce a random baseline to perform zeroshot classification tasks, and find it achieves similar performance (42.6% exact-match) as IT does (43% exact-match) in low resource setting, while both methods outperform naive T5 significantly (30% per exact-match). Our analysis provides evidence that the impressive performance gain of current IT models can come from picking up superficial patterns, such as learning the output format and guessing. Our study highlights the urgent need for more reliable IT methods and evaluation.
Compass-like manipulation of electronic nematicity in Sr3Ru2O7

Significance Nematicity, breaking of rotational symmetry without a reduction in translational symmetry, is found in many strongly correlated electron materials, including high temperature superconductors such as the cuprates and iron pnictides. Sr3Ru2O7 is a particularly striking example of a nematic state, where electronic transport shows an anisotropy that depends on the direction of an applied magnetic field, however the microscopic mechanism has remained an open question. Here, using scanning tunneling microscopy, we image how the electronic states in Sr3Ru2O7 evolve as a function of field direction. Our results demonstrate a compass-like control of the electronic structure. They can be modeled and fully understood based on the interaction of magnetism and spin–orbit coupling and their collective influence on the electronic structure.
Word Measures On Wreath Products I

Every word $w$ in the free group $F_r$ of rank $r$ induces a probability measure (the $w$-measure) on every compact group $G$, by substitution of Haar-random $G$-elements in the letters. This measure is determined by its Fourier coefficients: the $w$-expectations $\mathbb{E}_w[\chi]$ of the irreducible characters of $G$. For every compact group $G$, the wreath product with the symmetric group $G\wr S_n$ has some natural irreducible characters $\chi$, and we approximate $\mathbb{E}_w[\chi]$ for every word $w\in F_r$, revealing new automorphism-invariant quantities of words that generalize the primitivity rank $\pi(w)$. This generalizes previous works by Parzanchevsky-Puder and Magee-Puder. We demonstrate applications to automorphism groups of trees, investigate properties of the new invariants, and show polynomial decay of $\mathbb{E}_w[\chi]$ also for wreath products with more general actions.
SurgMAE: Masked Autoencoders for Long Surgical Video Analysis

There has been a growing interest in using deep learning models for processing long surgical videos, in order to automatically detect clinical/operational activities and extract metrics that can enable workflow efficiency tools and applications. However, training such models require vast amounts of labeled data which is costly and not scalable. Recently, self-supervised learning has been explored in computer vision community to reduce the burden of the annotation cost. Masked autoencoders (MAE) got the attention in self-supervised paradigm for Vision Transformers (ViTs) by predicting the randomly masked regions given the visible patches of an image or a video clip, and have shown superior performance on benchmark datasets. However, the application of MAE in surgical data remains unexplored. In this paper, we first investigate whether MAE can learn transferrable representations in surgical video domain. We propose SurgMAE, which is a novel architecture with a masking strategy based on sampling high spatio-temporal tokens for MAE. We provide an empirical study of SurgMAE on two large scale long surgical video datasets, and find that our method outperforms several baselines in low data regime. We conduct extensive ablation studies to show the efficacy of our approach and also demonstrate it's superior performance on UCF-101 to prove it's generalizability in non-surgical datasets as well.
Group fairness without demographics using social networks

Group fairness is a popular approach to prevent unfavorable treatment of individuals based on sensitive attributes such as race, gender, and disability. However, the reliance of group fairness on access to discrete group information raises several limitations and concerns, especially with regard to privacy, intersectionality, and unforeseen biases. In this work, we propose a “group-free" measure of fairness that does not rely on sensitive attributes and, instead, is based on homophily in social networks, i.e., the common property that individuals sharing similar attributes are more likely to be connected. Our measure is group-free as it avoids recovering any form of group memberships and uses only pairwise similarities between individuals to define inequality in outcomes relative to the homophily structure in the network. We theoretically justify our measure by showing it is commensurate with the notion of additive decomposability in the economic inequality literature and also bound the impact of non-sensitive confounding attributes. Furthermore, we apply our measure to develop fair algorithms for classification, maximizing information access, and recommender systems. Our experimental results show that the proposed approach can reduce inequality among protected classes without knowledge of sensitive attribute labels. We conclude with a discussion of the limitations of our approach when applied in real-world settings.
On Statistical Properties of Sharpness-Aware Minimization: Provable Guarantees

Sharpness-Aware Minimization (SAM) is a recent optimization framework aiming to improve the deep neural network generalization, through obtaining flatter (i.e. less sharp) solutions. As SAM has been numerically successful, recent papers have studied the theoretical aspects of the framework and have shown SAM solutions are indeed flat. However, there has been limited theoretical exploration regarding statistical properties of SAM. In this work, we directly study the statistical performance of SAM, and present a new theoretical explanation of why SAM generalizes well. To this end, we study two statistical problems, neural networks with a hidden layer and kernel regression, and prove under certain conditions, SAM has smaller prediction error over Gradient Descent (GD). Our results concern both convex and non-convex settings, and show that SAM is particularly well-suited for non-convex problems. Additionally, we prove that in our setup, SAM solutions are less sharp as well, showing our results are in agreement with the previous work. Our theoretical findings are validated using numerical experiments on numerous scenarios, including deep neural networks.
Density functional description of long-range electron Coulomb interactions in bulk SnS

A high-throughput benchmarking technique for testing the performance of different exchange-correlation functionals and pseudopotentials is proposed and applied to bulk SnS. It is shown that, contrary to the popular view that the local density approximation can best describe layered materials, a semilocal pseudopotential with a functional having a gradient dependence better described lattice vectors and `tetragonicity' of the lattice. We classify the pseudopotentials based on this value and show that the participation ratio of maximally localized Wannier functions follows the theory which states that more distorted structures have higher anti-bonding hybridization as stabilizing factor. In order to classify pseudopotentials, the local and nonlocal potential contributions to the dynamical Born effective charges are taken for each pseudopotential. Finally, a strategy is proposed for learning exchange-correlation functionals based on the distinction between short and long range parts of the Kohn-Sham potential.
Macrophages influence Schwann cell myelin autophagy after nerve injury and in a model of Charcot‐Marie‐Tooth disease

The complex cellular and molecular interactions between Schwann cells (SCs) and macrophages during Wallerian degeneration are a prerequisite to allow rapid uptake and degradation of myelin debris and axonal regeneration after peripheral nerve injury. In contrast, in non‐injured nerves of Charcot‐Marie‐Tooth 1 neuropathies, aberrant macrophage activation by SCs carrying myelin gene defects is a disease amplifier that drives nerve damage and subsequent functional decline. Consequently, targeting nerve macrophages might be a translatable treatment strategy to mitigate disease outcome in CMT1 patients. Indeed, in previous approaches, macrophage targeting alleviated the axonopathy and promoted sprouting of damaged fibers. Surprisingly, this was still accompanied by robust myelinopathy in a model for CMT1X, suggesting additional cellular mechanisms of myelin degradation in mutant peripheral nerves. We here investigated the possibility of an increased SC‐related myelin autophagy upon macrophage targeting in Cx32def mice.
The selective regulation of immune responses by matrix metalloproteinase MMP14 in Ostrinia furnacalis

Matrix metalloproteinases (MMPs) are crucial for tissue remodeling and immune responses in insects, yet it remains unclear how MMPs affect the various immune processes against pathogenic infections and whether the responses vary among insects. In this study, we used the lepidopteran pest Ostrinia furnacalis larvae to address these questions by examining the changes of immune‐related gene expression and antimicrobial activity after the knockdown of MMP14 and bacterial infections. We identified MMP14 in O. furnacalis using the rapid amplification of complementary DNA ends (RACE), and found that it was conserved and belonged to the MMP1 subfamily. Our functional investigations revealed that MMP14 is an infection‐responsive gene, and its knockdown reduces phenoloxidase (PO) activity and Cecropin expression, while the expressions of Lysozyme, Attacin, Gloverin, and Moricin are enhanced after MMP14 knockdown. Further PO and lysozyme activity determinations showed consistent results with gene expression of these immune‐related genes. Finally, the knockdown of MMP14 decreased larvae survival to bacterial infections. Taken together, our data indicate that MMP14 selectively regulates the immune responses, and is required to defend against bacterial infections in O. furnacalis larvae. Conserved MMPs may serve as a potential target for pest control using a combination of double‐stranded RNA and bacterial infection.
The Effect of Amniotic Membrane Extracted Eye Drop on Repairing The Corneal Epithelial in Patients after Trans-Epithelial Photorefractive Keratectomy: A Randomized Controlled Trial

Objective: Recent studies imply extensive applications for the human amniotic membrane (hAM) and its extract in medicine and ophthalmology. The content of hAM meets many requirements in eye surgeries, such as refractive surgery as the most important and commonly used method for treating the dramatically increasing refractive errors. However, they are associated with complications such as corneal haziness and corneal ulcer. This study was designed to evaluate the impact of amniotic membrane extracted eye drop (AMEED) on Trans-PRK surgery complications. Materials and Methods: This randomized controlled trial was performed during two years (July 1, 2019-September 1, 2020). Thirty-two patients (64 eyes), including 17 females and 15 males, aged 20 to 50 years (mean age of 29.59 ± 6.51) with spherical equivalent between -5 to -1.5 underwent Trans Epithelial Photorefractive Keratectomy (Trans-PRK) surgery. One eye was selected per case (case group) and the other eye was considered as control. Randomization was done using the random allocation rule. The case group was treated with AMEED, and the artificial tear drop every 4 hours. The control eyes received artificial tear drops instilled every 4 hours. The evaluation continued for three days after the Trans-PRK surgery. Results: A significant decrease in CED size was found in the AMEED group on the second day after surgery (P=0.046). Also, this group had a substantial reduction in pain, hyperemia, and haziness. Conclusion: This study showed that AMEED drop can increase the healing rate of corneal epithelial lesions after Trans- PRK surgery and reduce the early and late complications of Trans-PRK surgery. Researchers and Ophthalmologists should consider AMEED as a selection in patients with persistent corneal epithelial defects and patients who have difficulty in corneal epithelial healing. We understood AMEED has a different effect on the cornea after surgery; therefore, the researcher must know AMEED’s exact ingredients and help expand AMEED uses (registration number: TCTR20230306001).
A positive proportion of locally soluble Thue equations are globally insoluble

We show that a positive proportion of integral binary cubic forms that locally everywhere represent $1$ do not globally represent $1$. We order all classes of binary cubic forms by their absolute discriminants. We prove the same result for binary forms of any degree $n \geq 3$, provided that these forms are ordered by the maximum of the absolute values of their coefficients.
Partner Effects of Childhood Maltreatment: A Systematic Review and Meta-Analysis

Although several studies have shown that childhood maltreatment (CM) is associated with a host of negative consequences including romantic relationship difficulties for victims in adulthood, most overlooked the potential effects on the romantic partner. This systematic review and meta-analysis aims to comprehensively synthesize the literature on the association between a person’s CM and their partner’s individual and couple outcomes. We searched PubMed, PsycNET, Medline, CINAHL, and Eric using search strings related to CM and partner. We identified 3,238 articles after removal of duplicates; 28 studies met the inclusion criteria and relied on independent sample. The studies reported associations between a person’s CM and a wide breadth of partner’s negative couple outcomes (e.g., communication, sexuality) as well as intra-individual psychological difficulties (e.g., psychological distress, emotion, and stress reactivity). Meta-analytic results showed significant, but trivial to small associations between a person’s CM and their partner’s lower relationship satisfaction (r = −.09, 95% CI [−.14, −.04]), higher intimate partner violence (r = .08, [.05, .12]), and higher psychological distress (r = .11, [.06, .16]). These associations were similar for women and men and did not differ as a function of sample’s mean age, proportion of cultural diversity, and publication year. These findings suggest that a person’s CM is related to their partner’s outcomes including to the partner’s intra-individual outcomes. Prevention and intervention strategies should acknowledge that a person’s CM may also affect their romantic partner, considering the couple as a reciprocal system, and offer victims’ romantic partners specific services.
Conversion Rate of HTO to OBT in Plants

ABSTRACT The conversion rate of tritiated water (HTO) in plants’ leaves to organically bound tritium (OBT) in their edible parts in the open air was obtained for several vegetables (komatsuna, radish and cherry tomato) during a chronic tritiated hydrogen (HT) release experiment at Chalk River in 1994. During the experiment, HT gas was continuously released to the atmosphere at the cultivated site for 12 days, and HTO and OBT concentrations in cultivated plants were measured. For plants’ leaves, the conversion rate of HTO to OBT was about 0.2 (% hr−1), but it varied with their growth stage. A chamber experiment was also carried out in laboratory for comparison. The chamber experiment results showed that the conversion rate under artificial lights was half that in the field experiment.
3,5,3'-Triiodo-L-Thyronine Regulates Actin Cytoskeleton Dynamic in The Differentiated PC-12 Cells during Hypoxia through An αvβ3 Integrin

Objective: Thyroid hormones are involved in the pathogenesis of various neurological disorders. Ischemia/hypoxia that induces rigidity of the actin filaments, which initiates neurodegeneration and reduces synaptic plasticity. We hypothesized that thyroid hormones via alpha-v-beta-3 (αvβ3) integrin could regulate the actin filament rearrangement during hypoxia and increase neuronal cell viability. Materials and Methods: In this experimental study, we analysed the dynamics of actin cytoskeleton according to the G/F actin ratio, cofilin-1/p-cofilin-1 ratio, and p-Fyn/Fyn ratio in differentiated PC-12 cells with/without T3 hormone (3,5,3'-triiodo-L-thyronine) treatment and blocking αvβ3-integrin-antibody under hypoxic conditions using electrophoresis and western blotting methods. We assessed NADPH oxidase activity under the hypoxic condition by the luminometric method and Rac1 activity using the ELISA-based (G-LISA) activation assay kit. Results: The T3 hormone induces the αvβ3 integrin-dependent dephosphorylation of the Fyn kinase (P=0.0010), modulates the G/F actin ratio (P=0.0010) and activates the Rac1/NADPH oxidase/cofilin-1 (P=0.0069, P=0.0010, P=0.0045) pathway. T3 increases PC-12 cell viability (P=0.0050) during hypoxia via αvβ3 integrin-dependent downstream regulation systems. Conclusion: The T3 thyroid hormone may modulate the G/F actin ratio via the Rac1 GTPase/NADPH oxidase/ cofilin1signaling pathway and αvβ3-integrin-dependent suppression of Fyn kinase phosphorylation.
The revolving door phenomenon in severe psychiatric disorders: A systematic review

Background: The treatment of psychiatric patients has suffered a major change over the last decades, with long-term hospitalizations being replaced by short-term stays and appropriate aftercare in outpatient services. Some chronically ill patients exhibit a pattern of multiple hospitalizations, designated as the Revolving Door (RD) phenomenon. Aims: This review aims to analyse the existing literature regarding sociodemographic, clinical and other factors associated with multiple hospitalizations in psychiatric facilities. Method: The search performed in the PubMed database for the terms revolving[Title] AND (psyc*[Title] OR schizo*[Title] OR mental[Title]) presented 30 citations, 8 of which met the eligibility criteria. Four other studies found in references of these articles were also included in the review. Results: Albeit the use of different criteria to define the RD phenomenon, it is more likely to be associated with patients who are younger, single, with low educational level, unemployed, diagnosed with a psychotic disorder, particularly schizophrenia, and with alcohol and/or substance use. It is also associated with a younger age on disease onset, suicidality, noncompliance and voluntary type of admission. Conclusion: Recognizing patients with a RD pattern of admissions and prediction of rehospitalization can help the development of preventive intervention strategies and identify potential limitations in existing health care delivery systems.