Miracle-dz/UniFAR-FTUs huggingface dataset:
Spanning tree enumeration via triangular rank-one perturbations of graph Laplacians

We present new short proofs of known spanning tree enumeration formulae for threshold and Ferrers graphs by showing that the Laplacian matrices of such graphs admit triangular rank-one perturbations. We then characterize the set of graphs whose Laplacian matrices admit triangular rank-one perturbations as the class of special 2-threshold graphs, introduced by Hung, Kloks, and Villaamil. Our work introduces (1) a new characterization of special 2-threshold graphs that generalizes the characterization of threshold graphs in terms of isolated and dominating vertices, and (2) a spanning tree enumeration formula for special 2-threshold graphs that reduces to the aforementioned formulae for threshold and Ferrers graphs. We consider both unweighted and weighted spanning tree enumeration.
THAT: Two Head Adversarial Training for Improving Robustness at Scale

Many variants of adversarial training have been proposed, with most research focusing on problems with relatively few classes. In this paper, we propose Two Head Adversarial Training (THAT), a two-stream adversarial learning network that is designed to handle the large-scale many-class ImageNet dataset. The proposed method trains a network with two heads and two loss functions; one to minimize feature-space domain shift between natural and adversarial images, and one to promote high classification accuracy. This combination delivers a hardened network that achieves state of the art robust accuracy while maintaining high natural accuracy on ImageNet. Through extensive experiments, we demonstrate that the proposed framework outperforms alternative methods under both standard and"free"adversarial training settings.
The Lyα forest flux correlation function: a perturbation theory perspective

The Lyα forest provides one of the best means of mapping large-scale structure at high redshift, including our tightest constraint on the distance-redshift relation before cosmic noon. We describe how the large-scale correlations in the Lyα forest can be understood as an expansion in cumulants of the optical depth field, which itself can be related to the density field by a bias expansion. This provides a direct connection between the observable and the statistics of the matter fluctuations which can be computed in a systematic manner. We discuss the way in which complex, small-scale physics enters the predictions, the origin of the much-discussed velocity bias and the `renormalization' of the large-scale bias coefficients. Our calculations are within the context of perturbation theory, but we also make contact with earlier work using the peak-background split. Using the structure of the equations of motion we demonstrate, to all orders in perturbation theory, that the large-scale flux power spectrum becomes the linear spectrum times the square of a quadratic in the cosine of the angle to the line of sight. Unlike the case of galaxies, both the isotropic and anisotropic pieces receive contributions from small-scale physics.
CNN vs ELM for Image-Based Malware Classification

Research in the field of malware classification often relies on machine learning models that are trained on high-level features, such as opcodes, function calls, and control flow graphs. Extracting such features is costly, since disassembly or code execution is generally required. In this paper, we conduct experiments to train and evaluate machine learning models for malware classification, based on features that can be obtained without disassembly or execution of code. Specifically, we visualize malware samples as images and employ image analysis techniques. In this context, we focus on two machine learning models, namely, Convolutional Neural Networks (CNN) and Extreme Learning Machines (ELM). Surprisingly, we find that ELMs can achieve accuracies on par with CNNs, yet ELM training requires less than~2\%\ of the time needed to train a comparable CNN.
SMBH seeds from dissipative dark matter

The existence of supermassive black holes (SMBHs) with masses greater than ∼ 109 M ☉ at high redshift (z ≳ 7) is difficult to accommodate in standard astrophysical scenarios. We study the possibility that (nearly) totally dissipative self-interacting dark matter (tdSIDM)–in rare, high density dark matter fluctuations in the early Universe — produces SMBH seeds through catastrophic collapse. We use a semi-analytic model, tested and calibrated by a series of N-body simulations of isolated dark matter halos, to compute the collapse criteria and timescale of tdSIDM halos, where dark matter loses nearly all of its kinetic energy in a single collision in the center-of-momentum frame. Applying this model to halo merger trees, we empirically assign SMBH seeds to halos and trace the formation and evolution history of SMBHs. We make predictions for the quasar luminosity function, the M BH-σv * relation, and cosmic SMBH mass density at high redshift and compare them to observations. We find that a dissipative dark matter interaction cross-section of σ/m ∼ 0.05 cm2/g is sufficient to produce the SMBHs observed in the early Universe while remaining consistent with ordinary SMBHs in the late Universe.
StyleKQC: A Style-Variant Paraphrase Corpus for Korean Questions and Commands

Paraphrasing is often performed with less concern for controlled style conversion. Especially for questions and commands, style-variant paraphrasing can be crucial in tone and manner, which also matters with industrial applications such as dialog systems. In this paper, we attack this issue with a corpus construction scheme that simultaneously considers the core content and style of directives, namely intent and formality, for the Korean language. Utilizing manually generated natural language queries on six daily topics, we expand the corpus to formal and informal sentences by human rewriting and transferring. We verify the validity and industrial applicability of our approach by checking the adequate classification and inference performance that fit with conventional fine-tuning approaches, at the same time proposing a supervised formality transfer task.
Spatial Decorrelation of Young Stars and Dense Gas as a Probe of the Star Formation–Feedback Cycle in Galaxies

The spatial decorrelation of dense molecular gas and young stars observed on ≲1 kpc scales in nearby galaxies indicates rapid dispersal of star-forming regions by stellar feedback. We explore the sensitivity of this decorrelation to different processes controlling the structure of the interstellar medium, the abundance of molecular gas, star formation, and feedback in a suite of simulations of an isolated dwarf galaxy with structural properties similar to NGC 300 that self-consistently model radiative transfer and molecular chemistry. Our fiducial simulation reproduces the magnitude of decorrelation and its scale dependence measured in NGC 300, and we show that this agreement is due to different aspects of feedback, including H2 dissociation, gas heating by the locally variable UV field, early mechanical feedback, and supernovae. In particular, early radiative and mechanical feedback affects the correlation on ≲100 pc scales, while supernovae play a significant role on ≳ 100 pc scales. The correlation is also sensitive to the choice of the local star formation efficiency per free fall time, ϵ ff, which provides a strong observational constraint on ϵ ff when the global star formation rate is independent of its value. Finally, we explicitly show that the degree of correlation between the peaks of molecular gas and star formation density is directly related to the distribution of the lifetimes of star-forming regions.
Immunotherapeutics for Ebola Virus Disease: Hope on the Horizon

Abstract Ebola virus disease (EVD) remains among the biggest public health threats in Africa, even though recently a vaccine was approved for human use. However, in outbreak situations treatment strategies are needed in combination with vaccination campaigns to impact and stop the spread of the disease. Here, we discuss the development of the immunotherapeutics against EDV both targeting the virus itself and bolstering the immunological environment of the host at both the pre-clinical and clinical level. The early development of antibody therapy in preclinical settings and the early pitfalls in the implementation of this therapeutic strategy are discussed. We also consider the advancement of the production, modulation, and specificity of the antibody treatment that garnered increased success in preclinical studies to the point that it was warranted to test them in a clinical setting. Initial clinical trials in an outbreak scenario proved difficult to definitively confirm the efficacy of the implemented treatment. Upon further modification and with the experiences from the challenging outbreak conditions in mind, the PALM clinical trial demonstrated efficacy of an antibody cocktail which recently received approval for human use.
Evaluating and improving simulations of diurnal variation in land surface temperature with the Community Land Model for the Tibetan Plateau

This study evaluated and improved the ability of the Community Land Model version 5.0 (CLM5.0) in simulating the diurnal land surface temperature (LST) cycle for the whole Tibetan Plateau (TP) by comparing it with Moderate Resolution Imaging Spectroradiometer satellite observations. During daytime, the model underestimated the LST on sparsely vegetated areas in summer, whereas cold biases occurred over the whole TP in winter. The lower simulated daytime LST resulted from weaker heat transfer resistances and greater soil thermal conductivity in the model, which generated a stronger heat flux transferred to the deep soil. During nighttime, CLM5.0 overestimated LST for the whole TP in both two seasons. These warm biases were mainly due to the greater soil thermal inertia, which is also related to greater soil thermal conductivity and wetter surface soil layer in the model. We employed the sensible heat roughness length scheme from Zeng, Wang & Wang (2012), the recommended soil thermal conductivity scheme from Dai et al. (2019), and the modified soil evaporation resistance parameterization, which was appropriate for the TP soil texture, to improve simulated daytime and nighttime LST, evapotranspiration, and surface (0–10 cm) soil moisture. In addition, the model produced lower daytime LST in winter because of overestimation of the snow cover fraction and an inaccurate atmospheric forcing dataset in the northwestern TP. In summary, this study reveals the reasons for biases when simulating LST variation, improves the simulations of turbulent fluxes and LST, and further shows that satellite-based observations can help enhance the land surface model parameterization and unobservable land surface processes on the TP.
Genetic and Proteomic Contributions to the Pathophysiology of Moyamoya Angiopathy and Related Vascular Diseases

Rationale This literature review describes the pathophysiological mechanisms of the current classes of proteins, cells, genes, and signaling pathways relevant to moyamoya angiopathy (MA), along with future research directions and implementation of current knowledge in clinical practice. Objective This article is intended for physicians diagnosing, treating, and researching MA. Methods and Results References were identified using a PubMed/Medline systematic computerized search of the medical literature from January 1, 1957, through August 4, 2020, conducted by the authors, using the key words and various combinations of the key words “moyamoya disease,” “moyamoya syndrome,” “biomarker,” “proteome,” “genetics,” “stroke,” “angiogenesis,” “cerebral arteriopathy,” “pathophysiology,” and “etiology. ” Relevant articles and supplemental basic science articles published in English were included. Intimal hyperplasia, medial thinning, irregular elastic lamina, and creation of moyamoya vessels are the end pathologies of many distinct molecular and genetic processes. Currently, 8 primary classes of proteins are implicated in the pathophysiology of MA: gene-mutation products, enzymes, growth factors, transcription factors, adhesion molecules, inflammatory/coagulation peptides, immune-related factors, and novel biomarker candidate proteins. We anticipate that this article will need to be updated in 5 years. Conclusion It is increasingly apparent that MA encompasses a variety of distinct pathophysiologic conditions. Continued research into biomarkers, genetics, and signaling pathways associated with MA will improve and refine our understanding of moyamoya’s complex pathophysiology. Future efforts will benefit from multicenter studies, family-based analyses, comparative trials, and close collaboration between the clinical setting and laboratory research.
Distinct kinetics of immunoglobulin isotypes reveal early diagnosis and disease severity of COVID‐19: A 6‐month follow‐up

This study provides a comprehensive dynamic analysis of different antibody isotypes against SARS-CoV-2 and their relation to disease severity or early COVID-19 diagnosis in a large patient cohort over a 6-month follow-up period, which will benefit the early diagnosis and assessment of disease severity for COVID-19. Despite ongoing studies on the kinetics of SARS-CoV-2-specific antibodies, 1–5 it is still insufficient for the comprehensive analysis of long-term kinetics and durability of viral-specific antibody isotypes and their relation to disease severity or early COVID-19 diagnosis. In this study, we eval-uated the dynamics of SARS-CoV-2-specific immunoglob-ulins (A, G, and M) and its correlation to viral clearance and disease severity in a large cohort of COVID-19 patients for 6 months. Besides, IgA and IgG in saliva and bron-choalveolar lavage fluid (BALF) were also assessed for the diagnosis of COVID-19. A patients Shenzhen
Carbon dioxide adsorption performance of N-doped zeolite Y templated carbons

N-Doped microporous carbons are prepared using zeolite NaY as a hard template with furfuryl alcohol/acetonitrile as carbon precursors. CO2 adsorption performances of these carbons are investigated intensively. Structure analysis shows that the replication of zeolite regularity, pore texture and the type of nitrogen functionalities strongly depends on the carbonization temperature. Basic nitrogen functionalities can be efficiently introduced into the carbon framework, which significantly facilitate CO2 uptake via chemical adsorption. The CO2 adsorption isotherms correlated with the Dubinin–Astakhov models, and the isosteric heats of adsorption are calculated using the Clausius–Clapeyron equation. The maximum CO2 adsorption capacity of 10.4 wt% is obtained for the YTC7 carbon due to its high surface area and abundant nitrogen functionalities. CO2 chemical adsorption on the carbons decreases with carbonization temperature due to the decomposition of basic nitrogen functionalities at higher temperature. High CO2 adsorption capacities of up to 9.3 wt% at 25 °C and 4.1 wt% at 70 °C are obtained for the YTC6 carbon. The present study suggests that low temperature vapor deposition of acetonitrile is a promising alternative method of toxic ammonia treatment for CO2 adsorption.
Self-assembly of hydroxyapatite nanostructures by microwave irradiation

Hydroxyapatite (HAp) nanorods, bowknot-like nanostructures and flower-like architectures have been directly synthesized and assembled under microwave irradiation without the help of any templates. The uniform nanorods present an average diameter of about 40 nm and a length of up to about 400 nm. The as-prepared bowknot-like nanostructures consist of sword-like HAp nanorods with a typical width of 150 nm and lengths up to 1–2 µm. The flower-like architectures are composed of leaf-like flakes with typical diameters of 150–200 nm and lengths up to 1–2 µm. The SAED and HRTEM experiments imply that the sword-like HAp nanorods and leaf-like flakes are single crystalline in nature and preferentially grow along the [001] direction. It is found that the pH value and the complex reagent EDTA play important roles in synthesis of the final HAp nanostructures. The possible mechanism is discussed for the formation of the HAp nanostructures in the presence of EDTA under microwave irradiation.
Nursing Care Coordination for Patients with Complex Needs in Primary Healthcare: A Scoping Review

Introduction: Millions of people worldwide have complex health and social care needs. Care coordination for these patients is a core dimension of integrated care and a key responsibility for primary healthcare. Registered nurses play a substantial role in care coordination. This review draws on previous theoretical work and provides a synthesis of care coordination interventions as operationalized by nurses for complex patient populations in primary healthcare. Methodology: We followed Arksey and O’Malley’s methodological framework for scoping reviews. We carried out a systematic search across CINAHL, MEDLINE, Scopus and ProQuest. Only empirical studies were included. We performed a thematic analysis using deductive (the American Nurses Association Framework) and inductive approaches. Findings were discussed with a group of experts. Results: Thirty-four articles were included in the synthesis. Overall, nursing care coordination activities were synthesized into three categories: those targeting the patient, family and caregivers; those targeting health and social care teams; and those bringing together patients and professionals. Interpersonal communication and information transfer emerged as cross-cutting activities that support every other activity. Our results also brought to light the nurses’ contribution to care coordination efforts for patients with complex needs as well as critical components that should be present in every care coordination intervention for this clientele. These include an increased intensity and frequency of activities, relational continuity of care, and home visits. Conclusion: With the growing complexity of patient’s needs, efforts must be directed towards enabling the primary healthcare level to effectively play its substantial role in care coordination. This includes finding primary care employment models that would facilitate multidisciplinary teamwork and the delivery of integrated care, and guarantee the delivery of intensive yet efficient coordinated care.
Involving metals in halogen–halogen interactions: second-sphere Lewis acid ligands for perhalometallate ions (M–X⋯X′–C)

Lewis-acidic halocarbon groups (X–C) serve as effective second-sphere ligands for perhalometallate ions and provide an alternative means to hydrogen bonds for developing the supramolecular chemistry of such ions, exemplified here by short directional M–X⋯X′–C halogen bond linkages used in conjunction with hydrogen bonds for crystal synthesis.
The Relationship Between Type D Personality and the Complexity of Coronary Artery Disease

Purpose The relationship between personality traits and cardiovascular disease has gathered sustained interest over the last years, type –D personality (TDP) being significantly associated with coronary artery disease (CAD). However, data regarding the connection between the TDP and the severity of CAD disease is scarce. The aim of our study was to assess the relationship between TDP and the complexity of CAD, and to compare it with other sociodemographic and clinical features. Patients and Methods We conducted a cross-sectional case-control clinical-based study on 221 consecutive hospitalized patients with chest pain (60 ± 10.2 years; 131 men), referred for coronary angiography. Results TDP was identified in 42 (19%) patients, using the DS 14 scale. Symptomatology profile was evaluated using the SCL-90 scale. Syntax score was greater in the subgroup of patients with TDP in comparison to non-TDP subgroup (26.21±12.03 vs 15.49±8.89, respectively, p<0.001), and most of SCL-90 symptom dimensions have significantly higher levels in the subgroup of TDP with CAD patients (all p < 0.05). Smoking (β=0.132, p=0.037), dyslipidemia (β=0.149, p=0.013), Diabetes Mellitus (β=232, p<0.001), NA dimension of TDP (β=0.255, p<0.001) and SI (β=0.279, p<0.001) dimension of TDP have a significant contribution to the complexity of CAD assessed by Syntax score. Conclusion TDP was associated with a more complex CAD assessed by Syntax score, and may represent a dynamic interface between the biological and psychological vulnerabilities and the symptoms of CAD.
A comparison of meal tolerance test and oral glucose tolerance test for predicting insulin therapy in patients with gestational diabetes

Aims To identify factors predicting a need for insulin therapy in gestational diabetes mellitus (GDM) by comparing plasma glucose (PG) levels in a 75-g oral glucose tolerance test (75-g OGTT) with those in a 500-kcal meal tolerance test (MTT) containing 75 g of carbohydrate. Subjects and methods The MTT was performed in 61 patients who diagnosed with GDM by a 75-g OGTT (age, 33.2 ± 4.5 years; prepregnancy body mass index, 22.6 ± 4.7 kg/m2; number of gestational weeks, 25.1 ± 6.4 weeks). PG and serum insulin levels were measured before the meal and up to 180 min after the meal. The insulin secretion capacity and resistance index were calculated. Results PG levels increased from 86.8 ± 8.8 mg/dL at fasting to 132.7 ± 20.1 mg/dL at 30 min, and 137.8 ± 27.7 mg/dL at 60 min after MTT in the 35 patients with needed insulin therapy; these levels were significantly higher than those in the 26 patients, who only needed diet therapy. The patients with needed insulin therapy had significantly higher fasting PG levels in the 75-g OGTT, PG levels at fasting and 30 min after the MTT, and homeostasis model assessment of insulin resistance (HOMA-IR), and a significantly lower disposition index (DI) and insulin index than patients treated by diet alone. Receiver operating characteristic curve analysis was performed for factors involved in insulin therapy, with the following cutoff values: fasting PG in the 75-g OGTT, 92 mg/dL; PG 30 min after MTT, 129 mg/dL; HOMA-IR, 1.51; DI, 3.9; HbA1c, 5.4%. Multivariate analysis revealed that the 30-min PG level after MTT and HOMA-IR predicted insulin therapy. Conclusion PG levels at 30 min after MTT may be useful for identifying patients with GDM, who need insulin therapy.