Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence of the Impact of Stapler Choice on Clinical and Economic Outcomes in Video-Assisted Thoracoscopic Surgeries (VATS): A Perspective from Thoracic Surgeons in China

Background: VATS lobectomies have been shown to offer benefits over open thoracotomies in terms of clinical and economic outcomes for patients and hospitals. New innovation in stapling technology is expected to deliver improved clinical and economic outcomes in VATS procedures. This study documents comparative evidence between major brands of staplers, and an aggregate qualitative reaction from practicing thoracic surgeons in China in terms of utility of such evidence in informing surgical choice in China. Methods: Brief summaries of published pre-clinical and real-world database studies were presented to a group of thoracic surgeons on-site in Shanghai. The evidence focused on comparing two major stapler brands on device stability, bleeding complications, air leaks, and procedure economics. Surgeons’ anonymized reactions to the presented evidence were captured through instant polls conducted using an on-line polling software. Following a simplified Delphi Consensus development methodology, absolute proportions of surgeon responses were calculated, with an a priori threshold of 80% used as a general consensus position. Results: Based on their review of the evidence, surgeons most agreed that a stapler does have a role to play in the outcomes of VATS lobectomies. Based on multiple corroborating studies, surgeons agreed that stapler choice does influence bleeding and air leak outcomes in lung surgery. Cost of staplers was mentioned as a barrier for adoption owing to lack of understanding of downstream value of higher priced technology and further building the economic value proposition was suggested. Conclusion: The presented evidence was found to be informative for clinical decision making. Additional guidance was sought regarding cartridge/ reload selection, which would positively affect the quality and cost of minimally invasive thoracic surgery. Observation of similar benefits associated with latest powered and tissue-specific staplers across patients and geographies helps build further confidence in their utility in China.
Development and Validation of a HPLC Method for 5-Fu Quantification Following In Vitro Skin Permeation Assay

Introduction: The drug 5-Fluorouracil (5-FU) is used in various therapies as anti metabolic including several cancers and many skin diseases. In this work, we develop a bioanalytical method to quantify the 5-FU into the porcine ear skin samples after in vitro skin permeation studies by HPLC-UV. However, skin matrices samples represent the major bioanalytical challenge due to the complexity of this matrix. This method was developed in a High-Performance Liquid Chromatography (Shimadzu LC 10AD), a C8 Phenomenex (100mm x 4,6mm, 5μm, 110A) chromatography column and detector UV-visible operated at 265nm. The mobile phase was composed by Methanol: Water (10:90) v/v, acidified with 0.05% (v/v) orthophosphoric acid (pH 4.5), injection volume was 30 μL and the mobile phase flow was optimized to 0.8mL per minute. The skin samples from in vitro permeation studies were subjected to tape stripping, to remove the stratum corneum, then dose the drug retained on this layer separately. Afterward, the remaining epidermis and dermis samples were submitted by a liquid-liquid extraction process was successfully employed, more than 80% of 5-FU was recovered from the skin, for the purpose of dosing the retained drug from the viable epidermis and dermis and 5-FU assessed by HPLC. The obtained results by HPLC agreed to the qualitative confocal laser microscopy. The proposed bioanalytical method was simple, selective, sensible, presented limits of detection and quantification were 0.07 and 0.1 μg/mL respectively. The method was also precise, accurate, robust and efficient in eliminating the interferences of the skin maintaining the bioanalytical method confidence.
Preliminary Data on Post Market Safety Profiles of COVID 19 Vaccines in Rheumatic Diseases: Assessments on Various Vaccines in Use, Different Rheumatic Disease Subtypes, and Immunosuppressive Therapies: A Two-Centers Study

An increased risk of developing severe infections has been evidenced in rheumatic disease (RD) patients, and anti-COVID-19 vaccination is strictly recommended for RD patients. However, up to now, no data are available on safety, immunogenicity and efficacy of COVID-19 vaccinations in RD patients. The possible development of adverse events (AEs), including the flare-up of underlying RD, represents a matter of growing importance. The aim of our study is to assess, in RD patients, the safety profile of different types of approved vaccines and the possible influence of immunosuppressive therapies and clinical or demographic characteristics of RD patients on development of AEs. Participants (n = 185; 30.7%) received anti-COVID-19 vaccinations, 137 with autoimmune/chronic inflammatory RD (Au/cIn-RD) and 48 with nonautoimmune/chronic inflammatory RD (no-Au/cIn-RD). AEs were recorded in 42% of patients after the first dose of vaccine, and in 26% of patients after the second dose. The most common reported AEs after anti-COVID 19 vaccines were site injection pain (17%), headache (12%), fever (12%), myalgia (10%) and fatigue (10%). Relapses of the underlying Au/c-In-RD were recorded in 2.2% of patients after the first dose of vaccine. In Au/c-In-RD the risk of developing AEs after the first dose of vaccine was lower in older patients (OR = 0.95; p = 0.001), and in the group of patients with complete control of RD (OR: 0.2; p = 0.010). A lower percentage of AEs was observed in patients with complete control of their Au/cIn-RD (29%) compared to those with low (57%) or moderate-high disease activity (63%) (p = 0.002 and p = 0.006 respectively). In this study all types of COVID-19 vaccines in use in Italy seemed safe in RD patients. The results of this study might provide reassuring information for Au/cIn RD patients and clinicians and could strengthen the data on vaccine safety to guide the use of COVID-19 vaccines in Au/cIn-RD on immunosuppressive agents.
Understanding the Effect of Traffic Congestion on Accidents Using Big Data

Understanding the temporal and spatial dynamics of traffic accidents are a key determinant in their mitigation. This article leverages big data and a Poisson model with fixed effects to understand the causality of traffic congestion on road accidents in ten cities in Latin America: Bogota, Buenos Aires, Lima, Mexico City, Montevideo, Rio de Janeiro, San Salvador, Santiago, Santo Domingo, and Sao Paulo. Analyzing over 10 billion observations in 2019, results show a positive non-linear causality of congestion on the number of accidents. Overall, the results suggest that a 10% reduction in traffic delay would reduce accidents by 3.4%, equivalent to over 72 thousand traffic accidents. Sao Paulo and Mexico City would be particularly benefited, with reductions of 5.4% and 4.7%, respectively. The results of this paper aim to support policymakers in emerging economies in implementing measures to reduce congestion and, with it, the related direct and indirect costs borne by societies.
Robust Image Denoising using Kernel Predicting Networks

We present a new method for designing high quality denoisers that are robust to varying noise characteristics of input images. Instead of taking a conventional blind denoising approach or relying on explicit noise parameter estimation networks as well as invertible camera imaging pipeline models, we propose a two-stage model that ﬁrst processes an input image with a small set of specialized denoisers, and then passes the resulting intermediate denoised images to a kernel predicting network that estimates per-pixel denoising kernels. We demonstrate that our approach achieves robustness to noise parameters at a level that exceeds comparable blind denoisers, while also coming close to state-of-the-art denoising quality for camera sensor noise
Impact of dynamic snow density on GlobSnow snow water equivalent retrieval accuracy

Snow water equivalent (SWE) is an important variable in describing global seasonal snow cover. Traditionally, SWE has been measured manually at snow transects or using observations from weather stations. However, these measurements have a poor spatial coverage, and a good alternative to in situ measurements is to use spaceborne passive microwave observations, which can provide global coverage at daily timescales. The reliability and accuracy of SWE estimates made using spaceborne microwave radiometer data can be improved by assimilating radiometer observations with weather station snow depth observations as done in the GlobSnow SWE retrieval methodology. However, one possible source of uncertainty in the GlobSnow SWE retrieval approach is the constant snow density used in modelling emission of snow. In this paper, three versions of spatially and temporally varying snow density fields were implemented using snow transect data from Eurasia and Canada and automated snow observations from the United States. Snow density fields were used to post-process the baseline GlobSnow v.3. 0 SWE product. Decadal snow density information, i.e. fields where snow density for each day of the year was taken as the mean calculated for the corresponding day over 10 years, was found to produce the best results. Overall, post-processing GlobSnow SWE retrieval with dynamic snow density information improved overestimation of small SWE values and underestimation of large SWE values, though underestimation of SWE values larger than 175 mm was still significant.
Large-Margin Contrastive Learning with Distance Polarization Regularizer

Contrastive learning (CL) pretrains models in a pairwise manner, where given a data point, other data points are all regarded as dissimilar, including some that are semantically similar. The issue has been addressed by properly weighting similar and dissimilar pairs as in positive-unlabeled learning , so that the objective of CL is unbiased and CL is consistent . However, in this paper, we argue that this great solution is still not enough: its weighted objective hides the issue where the semantically similar pairs are still pushed away; as CL is pretraining, this phenomenon is not our desideratum and might affect downstream tasks. To this end, we propose large-margin contrastive learning (LMCL) with distance polarization reg-ularizer , motivated by the distribution characteristic of pairwise distances in metric learning . In LMCL, we can distinguish between intra-cluster and inter-cluster pairs, and then only push away inter-cluster pairs, which solves the above issue explicitly. Theoretically, we prove a tighter error bound for LMCL; empirically, the superiority of LMCL is demonstrated across multiple domains, i.e. , image classiﬁcation, sentence representation, and reinforcement learning.
More Unequal Income but Less Progressive Taxation: Economics or Politics?∗

Since the 1970s, income inequality in the U.S. has increased sharply. During the same time span, the U.S. federal income tax has become less progressive. Why? I examine this question in a Ramsey optimal tax policy framework. Within this framework, the tax policy is determined by: (1) a set of Pareto weights representing the government’s preference over different households; and (2) household lifetime utilities summarizing the effects of economic fundamentals. I first study the changes in economic fundamentals using an overlapping generations incomplete-markets life-cycle model with heterogeneous households. The model features both endogenous human capital accumulation and household labor supply and is calibrated to the U.S. economy in the 1970s and 2010s. Then I use this economic model to determine whether the change in income tax is the result of an optimal policy response to changing economic fundamentals or the consequence of a change in Pareto weights. I interpret the latter as changes in the political influences of various income groups. I find that: (1) changes in economic fundamentals alone induce a less progressive optimal income tax and can account for 40% of the reduction in progressivity we observe; and (2) the change in Pareto weights required to explain the remaining part of tax policy change favors high-income households and also implies less valued government services. Finally, using a stylized political economy model, I discuss potential explanations for this change in Pareto weights such as the lower cost of conveying information to swing voters and the rising inequality of voter turnout among different socioeconomic groups. ∗Email: chunzan@sas.upenn. edu. I thank Dirk Krueger, Harold Cole, and Guido Menzio for invaluable advice, guidance, and encouragement through this project. I also thank Urban Jermann, Iourii Manovskii, Enrique Mendoza, Guillermo Ordonez, Andrew Postlewaite, José-Vı́ctor Rı́os-Rull, and the participants of the Penn Money Macro Workshop and the Penn Macro Club for their helpful discussions.
When is Sentinel Lymph Node Biopsy Useful in Ductal Carcinoma In Situ? The Experience at a Latin American Cancer Center

Introduction Ductal carcinoma in situ (DCIS) accounts for 15% of breast cancers. Surgery is the main treatment, and the use of sentinel node biopsy (SLNB) is restricted to patients at risk of infiltration, which is estimated to be around 26%. Materials and methods Aimed at evaluating the benefit of SLNB in patients with DCIS at the Breast and Soft Tissue Functional Unit of the National Cancer Institute (INC for its initials in Spanish), a descriptive observational study of a retrospective cases series was conducted between August 1, 2013, and September 30, 2018. Results A total of 40 patients with a median age of 57 years were included in the study; 62.5% of them underwent mastectomy with SLNB, and the remaining 37.5% underwent conservative surgery with SLNB. 100% of sentinel nodes were identified, by using lymphoscintigraphy in 95%. Sentinel node was positive in four patients (10%), three of whom had infiltration in the surgical specimen reported. With a follow-up of 49 months, only one patient had a local relapse. None of the patients had axillary or distant recurrence. Conclusions SLNB in DCIS should be limited to patients with risk factors for infiltration (tumor size greater than 3 cm, comedo-type histology, and high-grade DCIS), and patients with an indication for mastectomy. Its percentage of complications is low, and a high identification percentage in surgical groups with adequate training.
Monetary Policy Shocks and Inflation Inequality

We evaluate household-level inflation rates since 1980, for which we compute various dispersion measures, and we assess their reaction to monetary policy shocks. We find that (i) contractionary monetary policy significantly and persistently decreases inflation dispersion in the economy, and that (ii) different demographic groups are heterogeneously affected by monetary policy. Due to different consumption bundles, lower-income households experience higher average inflation, which at the same time is decreasing more after a contractionary monetary policy shock, leading to an overall convergence of inflation rates between income groups. Finally, these results imply that (iii) consumption and income inequality are significantly different when controlling for different inflation rates.
CRAMÉR-TYPE MODERATE DEVIATION THEOREMS FOR NONNORMAL

1Department of Statistics and Data Science, Southern University of Science and Technology 2Department of Statistics, Chinese University of Hong Kong, qmshao@sta.cuhk. edu.hk 3Department of Mathematics, Hong Kong University of Science and Technology, mzhangag@connect.ust. hk 4Department of Statistics, Chinese University of Hong Kong 5Department of Statistics and Applied Probability, National University of Singapore, zszhang.stat@gmail.com
Mindfulness: A Current Review

The concept of mindfulness, defined by Kabat-Zinn, refers to a mechanism where the experiences are always at the center of attention. This concept, which dates back almost 2500 years, attracted the attention of several researchers in recent years. It was suggested that mindfulness could contribute to the treatment of psychopathologies and various intervention methods were developed. On the other hand, there are also studies on the action mechanisms of these intervention methods in the literature. The present literature review aimed to describe the concept of mindfulness, to investigate the correlations between mindfulness and psychopathologies and transdiagnostic variables, and to provide a general framework on awareness skills and techniques designed to develop these skills.
A Search for Rapid Mid-infrared Variability in Gamma-Ray-emitting Narrow-line Seyfert 1 Galaxies

Fermi-LAT’s detection of γ-rays from narrow-line Seyfert 1 galaxies (NLS1s) has received increasing attention. Understanding these γ-NLS1s is of interest because they have some properties similar to blazars, which are known to show rapid and large-amplitude variability. Based on the largest sample of γ-NLS1s (25 sources), we carried out a systematic search for rapid mid-infrared (MIR, 3.4 and 4.6 μm) variability using the multiepoch data of the Wide-field Infrared Survey Explorer (WISE). We also compared a few variability properties between γ-NLS1s and γ-ray blazars. Our main results are as follows. (1) Thirteen γ-NLS1s showed significant (>3σ) rapid variability in at least one of the two MIR bands. The MIR emission of these sources is dominated by the synchrotron emission of relativistic electrons in the jet. (2) The γ-NLS1s with flat radio spectra are more variable than those not detected in γ-rays. (3) The γ-NLS1s tend to show smaller amplitude of variability as well as lower duty cycle relative to γ-ray blazars. (4) The γ-NLS1s tend to show a trend of bluer-when-brighter on both intraday and long timescales, similar to γ-ray blazars. (5) The γ-NLS1s that are more variable on long timescales have larger amplitudes of variability and higher duty cycles on intraday timescales. (6) In the majority of cases, the γ-NLS1s fall in the WISE Gamma-ray Blazar Strip (WGS). However, we noted migrations outside of the WGS due to significant variability.
Temporal and spatial differentiation of Pleistocene and recent Saiga deduced from morphometric analyses of cranial remains

Acknowledgements This work was supported by the National Science Centre Poland (Narodowe Centrum Nauki, Polska) under Grant no. 2020/37/B/NZ8/02595 as well as the Faculty of Biological Sciences, University of Wrocław (the internal grant for the young scientists, grant number 0420/2315/2017). We are very grateful to anonymous reviewers for their insightful comments and remarks, which significantly improved the manuscript. Abstract
Determinants of Mutual Fund Selection by Individual investors in Coimbatore city

Mutual Fund Investments in India are contributing a lot to the growth of capital Market. This study explores the Fund Selection criteria adopted by Mutual Fund Investors of Coimbatore city by eliciting informating from 526 Mutual Fund investors. Data collected were analysed and the results are in tandem with the past studies on the criteria considered the most important for Mutual Fund selection as Past performance of the fund. Factor Analysis was performed and six factors such as Intrinsic Fund Quality, Fund Sponsor Facility, Investor Service & Transparency, Reputation, Credibility of Fund and Tangible Benefits were extracted. The study also revealed that Print media was the most influencing source of information. The association between influence of information source and importance given to fund selection criteria of mutual fund investments was studied and found that there is relationship between the two.
Systematic revision of the trans-Bassian moriomorphine genus Theprisa Moore (Coleoptera, Carabidae)

Abstract The Australian genus Theprisa Moore, 1963, is taxonomically revised to comprise five species, two newly described: Theprisadarlingtoni Liebherr & Porch, sp. nov. of Tasmania, and Theprisaotway Liebherr, Porch & Maddison, sp. nov. from the Otway Ranges, Victoria. Two previously described species, T.australis (Castelnau) and T.montana (Castelnau), are distributed in the mountains of Victoria. The third previously described species, T.convexa (Sloane) is found in Tasmania. A lectotype is designated for T.convexa because the various syntypes are ambiguously labelled. Cladistic analysis based on morphological characters establishes monophyly of Theprisa relative to the Australian genera Sitaphe Moore and Spherita Liebherr. This and a second clade of Australian genera (Pterogmus Sloane, Thayerella Baehr, and Neonomius Moore) do not form a natural group, but are cladistically interdigitated among two monophyletic New Zealand lineages (Tarastethus Sharp, and Trichopsida Larochelle and Larivière) suggesting substantial trans-Tasman diversification among these groups. Hypothesized relationships within Theprisa are consistent with two bouts of speciation involving the Bass Strait; an initial event establishing T.convexa as adelphotaxon to the other four species, and a more recent event establishing the sister species T.darlingtoni and T.montana. Geographic restriction of T.otway to the Otway Ranges is paralleled by Otway endemics in several other carabid beetle genera, as well as by endemics in numerous other terrestrial arthropod taxa. Whereas these numerous Otway endemics support the distinctive nature of the Otway Range fauna, their biogeographic relationships are extremely varied, illustrating that the Otways have accrued their distinctive biodiversity via various means.
Combined Effects of Unhealthy Lifestyle Behaviors on Metabolic Syndrome among Postmenopausal Women

This study aimed to identify the combined effects of unhealthy lifestyle behaviors, including diet, sedentary behavior, and physical activity on metabolic syndrome (MS) and components of MS among postmenopausal women. Secondary data analysis was conducted using the Korean National Health and Nutrition Examination Survey (2014–2018) with a cross-sectional study design. Logistic regression analysis was conducted with data from 6114 Korean postmenopausal women. While no significant effects of unhealthy lifestyle behaviors, either individually or as a combination, were found for MS, prolonged sedentary behavior without poor dietary behavior and insufficient physical activity was associated with increased likelihood of abdominal obesity (adjusted odds ratio [AOR]: 1.59, 95% confidence interval [CI]: 1.10–2.29) and impaired fasting glucose (AOR: 1.54, 95% CI: 1.13–2.10). The combination of poor dietary behavior and prolonged sedentary behaviors was also associated with increased likelihood of abdominal obesity (AOR: 1.48, 95% CI: 1.10–2.00) and impaired fasting glucose (AOR: 1.49, 95% CI: 1.14–1.96). In addition, prolonged sedentary behavior and insufficient physical activity together were associated with increased likelihood of abdominal obesity (AOR: 2.81, 95% CI: 1.90–4.20) and impaired fasting glucose (AOR: 1.59, 95% CI: 1.13–2.24). Finally, combining poor dietary behavior, prolonged sedentary behavior, and insufficient physical activity was also associated with increased likelihood of abdominal obesity (AOR: 2.05, 95% CI: 1.50–2.80) and impaired fasting glucose (AOR: 1.71, 95% CI: 1.32–2.23). Strategies for replacing sedentary behavior of postmenopausal women with activities are warranted for prevention of abdominal obesity and impaired fasting glucose.