Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Context-Aware Code Comment Generation

Code comments are vital for software maintenance and comprehension, but many software projects suffer from the lack of meaningful and up-to-date comments in practice. This paper presents a novel approach to automatically generate code comments at a function level by targeting object-oriented programming languages. Unlike prior work that only uses information locally available within the target function, our approach leverages broader contextual information by considering all other functions of the same class. To propagate and integrate information beyond the scope of the target function, we design a novel learning framework based on the bidirectional gated recurrent unit and a graph attention network with a pointer mechanism. We apply our approach to produce code comments for Java methods and compare it against four strong baseline methods. Experimental results show that our approach outperforms most methods by a large margin and achieves a comparable result with the state-of-the-art method.
Adversarial Text Generation via Sequence Contrast Discrimination

In this paper, we propose a sequence contrast loss driven text generation framework, which learns the difference between real texts and generated texts and uses that difference. Specifically, our discriminator contains a discriminative sequence generator instead of a binary classifier, and measures the ‘relative realism’ of generated texts against real texts by making use of them simultaneously. Moreover, our generator uses discriminative sequences to directly improve itself, which not only replaces the gradient propagation process from the discriminator to the generator, but also avoids the time-consuming sampling process of estimating rewards in some previous methods. We conduct extensive experiments with various metrics, substantiating that our framework brings improvements in terms of training stability and the quality of generated texts.
Syntactic and Semantic-driven Learning for Open Information Extraction

One of the biggest bottlenecks in building accurate, high coverage neural open IE systems is the need for large labelled corpora. The diversity of open domain corpora and the variety of natural language expressions further exacerbate this problem. In this paper, we propose a syntactic and semantic-driven learning approach, which can learn neural open IE models without any human-labelled data by leveraging syntactic and semantic knowledge as noisier, higher-level supervision. Specifically, we first employ syntactic patterns as data labelling functions and pretrain a base model using the generated labels. Then we propose a syntactic and semantic-driven reinforcement learning algorithm, which can effectively generalize the base model to open situations with high accuracy. Experimental results show that our approach significantly outperforms the supervised counterparts, and can even achieve competitive performance to supervised state-of-the-art (SoA) model.
ISWARA at WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets using BERT and FastText Embeddings

This paper presents Iswara’s participation in the WNUT-2020 Task 2 “Identification of Informative COVID-19 English Tweets using BERT and FastText Embeddings”,which tries to classify whether a certain tweet is considered informative or not. We proposed a method that utilizes word embeddings and using word occurrence related to the topic for this task. We compare several models to get the best performance. Results show that pairing BERT with word occurrences outperforms fastText with F1-Score, precision, recall, and accuracy on test data of 76%, 81%, 72%, and 79%, respectively
BERT-based Spatial Information Extraction

Spatial information extraction is essential to understand geographical information in text. This task is largely divided to two subtasks: spatial element extraction and spatial relation extraction. In this paper, we utilize BERT (Devlin et al., 2018), which is very effective for many natural language processing applications. We propose a BERT-based spatial information extraction model, which uses BERT for spatial element extraction and R-BERT (Wu and He, 2019) for spatial relation extraction. The model was evaluated with the SemEval 2015 dataset. The result showed a 15.4% point increase in spatial element extraction and an 8.2% point increase in spatial relation extraction in comparison to the baseline model (Nichols and Botros, 2015).
The effects of coding intensity in Medicare Advantage on plan benefits and finances.

OBJECTIVE To assess how beneficiary premiums, expected out-of-pocket costs, and plan finances in the Medicare Advantage (MA) market are related to coding intensity. DATA SOURCES/STUDY SETTING MA plan characteristics and administrative records from the Centers for Medicare and Medicaid Services (CMS) for the sample of beneficiaries enrolled in both MA and Part D between 2008 and 2015. Medicare claims and drug utilization data for Traditional Medicare (TM) beneficiaries were used to calibrate an independent measure of health risk. STUDY DESIGN Coding intensity was measured by comparing the CMS risk score for each MA contract with a contract level risk score developed using prescription drug data. We conducted regressions of plan outcomes, estimating the relationship between outcomes and coding intensity. To develop prescription drug scores, we assigned therapeutic classes to beneficiaries based on their prescription drug utilization. We then regressed nondrug spending for TM beneficiaries in 2015 on demographic and therapeutic class identifiers for 2014 and used the coefficients to predict relative risk. PRINCIPAL FINDINGS We found that, for each $1 increase in potential revenue resulting from coding intensity, MA plan bid submissions declined by $0.10 to $0.19, and another $0.21 to $0.45 went toward reducing plans' medical loss ratios, an indication of higher profitability. We found only a small impact on beneficiary's projected out-of-pocket costs in a plan, which serves as a measure of the generosity of plan benefits, and a $0.11 to $0.16 reduction in premiums. As expected, coding intensity's effect on bids was substantially larger in counties with higher levels of MA competition than in less competitive counties. CONCLUSIONS While coding intensity increases taxpayers' costs of the MA program, enrollees and plans both benefit but with larger gains for plans. The adoption of policies to more completely adjust for coding intensity would likely affect both beneficiaries and plan profits.
Network principal component analysis: a versatile tool for the investigation of multigroup and multiblock datasets

MOTIVATION Complex data structures composed of different groups of observations and blocks of variables are increasingly collected in many domains, including metabolomics. Analysing these high-dimensional data constitutes a challenge, and the objective of this article is to present an original multivariate method capable of explicitly taking into account links between data tables when they involve the same observations and/or variables. For that purpose, an extension of standard principal component analysis called NetPCA was developed. RESULTS The proposed algorithm was illustrated as an efficient solution for addressing complex multigroup and multiblock datasets. A case study involving the analysis of metabolomic data with different annotation levels and originating from a chronic kidney disease (CKD) study was used to highlight the different aspects and the additional outputs of the method compared to standard PCA. On the one hand, the model parameters allowed an efficient evaluation of each group's influence to be performed. On the other hand, the relative relevance of each block of variables to the model provided decisive information for an objective interpretation of the different metabolic annotation levels. AVAILABILITY NetPCA is available as a Python package with NumPy dependencies. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Clinical Magnetoencephalography Practice in the United States Ten Years Later: A Survey-Based Reappraisal.

PURPOSE Broader utilization of magnetoencephalography (MEG) and optimization of clinical practice remain strategic goals of the American Clinical Magnetoencephalography Society. Despite the implementation of the first MEG Clinical Practice Guidelines, clinical adoption has been less than expected, prompting a reassessment. METHODS Twenty-five clinical MEG centers were invited to participate anonymously in a survey of clinical practice. RESULTS Centers (N = 18) mostly operated within an academic medical center (10/18), were owned by the "hospital" (10/18), associated with a level 4 National Association of Epilepsy center (15/18), and directed by neurologists (10/18). A total of 873 (median 59) epilepsy studies, 1,179 evoked fields (of all types), and 1,607 (median 30) research MEG studies were reported. Fourteen of 17 centers serve children (median 35%), but only 5 of 14 sedate children for MEG. All (N = 14) centers record EEG simultaneous with MEG, and 57% used dipole source localization. The median reporting time for epilepsy studies was 12 and 10 days for presurgical mapping studies. Most (12/14) were favorable toward the Clinical Practice Guidelines and "formalized certification" but were against mandating the latter. CONCLUSIONS A plateau in MEG volumes suggests that MEG has not become a part of the standard of care, and correspondingly, the Clinical Practice Guidelines appeared to have had little impact on clinical practice. The American Clinical Magnetoencephalography Society must continue to engage magnetoencephalographers, potential referrers, and vendors.
Cannula With Long and Narrow Tubing vs Short Binasal Prongs for Noninvasive Ventilation in Preterm Infants: Noninferiority Randomized Clinical Trial.

Importance Use of cannulas with long and narrow tubing (CLNT) has gained increasing popularity for applying noninvasive respiratory support for newborn infants thanks to ease of use, perceived patient comfort, and reduced nasal trauma. However, there is concern that this interface delivers reduced and suboptimal support. Objective To determine whether CLNT is noninferior to short binasal prongs and masks (SPM) when providing nasal intermittent positive pressure ventilation (NIPPV) in preterm infants. Design, Setting, and Participants This randomized controlled, unblinded, prospective noninferiority trial was conducted between December 2017 and December 2019 at 2 tertiary neonatal intensive care units. Preterm infants born between 24 weeks' and 33 weeks and 6 days' gestation were eligible if presented with respiratory distress syndrome with the need for noninvasive ventilatory support either as initial treatment after birth or after first extubation. Analysis was performed by intention to treat. Interventions Randomization to NIPPV with either CLNT or SPM interface. Main Outcomes and Measures The primary outcome was the need for intubation within 72 hours after NIPPV treatment began. Noninferiority margin was defined as 15% or less absolute difference. Results Overall, 166 infants were included in this analysis, and infant characteristics and clinical condition (including fraction of inspired oxygen, Pco2, and pH level) were comparable at recruitment in the CLNT group (n = 83) and SPM group (n = 83). The mean (SD) gestational age was 29.3 (2.2) weeks vs 29.2 (2.5) weeks, and the mean (SD) birth weight was 1237 (414) g vs 1254 (448) g in the CLNT and SPM groups, respectively. Intubation within 72 hours occurred in 12 of 83 infants (14%) in the CLNT group and in 15 of 83 infants (18%) in the SPM group (risk difference, -3.6%; 95% CI, -14.8 to 7.6 [within the noninferiority margin], χ2﻿ P = .53). Moderate to severe nasal trauma was significantly less common in the CLNT group compared with the SPM group (4 [5%] vs 14 [17%]; P = .01). There were no differences in other adverse events or in the course during hospitalization. Conclusions and Relevance In this study, CLNT was noninferior to SPM in providing NIPPV for preterm infants, while causing significantly less nasal trauma. Trial Registration ClinicalTrials.gov Identifier: NCT03081611.
Bostwick Autoderm and Implant Technique - Improved Outcomes for Obese Patients in Immediate Breast Reconstruction.

BACKGROUND The Bostwick autoderm technique utilizes the patient's own de-epithelialized mastectomy flap for lower pole coverage of an implant, similar to the use of acellular dermal matrix (ADM). The skin is closed over the autoderm flap in a Wise pattern. Unlike ADM, autoderm is perfused tissue that offers immediate protection for the implant. Because of this extra protective vascularized layer, implants can often be salvaged in cases of wound breakdown. METHODS A retrospective review of 370 patients and 592 immediate implant reconstructed breasts was performed. RESULTS 422 (71%) were reconstructed with autoderm, 93 (16%) with TMC (total muscle coverage) and 77 (13%) with ADM. Higher BMI patients were overrepresented in the autoderm group. 91 (21.3%) of the reconstructions in the autoderm group were performed on patients with a BMI > 35 compared to 4 (4.3%) in the TMC group and 2 (2.6%) in the ADM group. In spite of this higher number of obese patients, the complication rate in the ADM group was similar to the ADM group. The implant loss rate for all reconstructions was 3.4%. There were 17 (4%) losses in the autoderm group, 0 in the TMC group, and 20 (3.4%) in the ADM group. There were 15 patients and 28 breasts that had pre-pectoral reconstruction. CONCLUSION The autoderm flap is a safe, reliable, and resource-conscientious technique for immediate, implant-based breast reconstruction.
Anti-programmed cell death-1 therapy in octogenarian and nonagenarian advanced/metastatic melanoma patients.

Immunotherapy with anti-programmed cell death-1 (PD-1) agents is an effective treatment for metastatic melanoma. Octogenarians and nonagenarians represent a significant cohort of melanoma patients. This multicenter retrospective analysis enrolled 499 patients treated with nivolumab or pembrolizumab. Seventy-three patients were aged 80-100, 218 patients were aged 65-79, and 208 patients were <65 years old. Baseline parameters were comparable. The median overall survival (OS) was 14.7, 18.7, 25.9, and the median progression-free survival (PFS) was 8.7, 7.7, and 6.2 months in the age groups of 80-100, 65-79, and <65 years, respectively. The median melanoma-specific survival (MSS) was 22.5, 27.8, and 31.6 months in the age groups of 80-100, 65-79, and <65 years, respectively. There was no statistically significant difference in OS (P = 0.2897), PFS (P = 0.7155), and MSS (P = 0.9235) between the group of 80-100 years old vs. 65-79 and vs. <65 years old patients. Overall response rate and disease control rate was similar in all groups (P = 0.06974 and P = 0.89435, respectively). Overall, the immune-related adverse event (irAE) rate was comparable in the three age groups (41, 34, and 37.5% in the groups of patients aged 80-100, 65-79, and <65 years, respectively). Also, the rates of G3 and G4 irAEs were comparable (4, 6, and 7% in the groups of patients, respectively). The efficacy and toxicity of anti-PD-1 therapy in octogenarians and nonagenarians with metastatic melanoma are similar as in patients aged <65 years and 65-79 years. The patients' age should not be considered as an exclusion criterion for anti-PD-1 treatment.
Monitoring the psychological, social, and economic impact of the COVID‐19 pandemic in the population: Context, design and conduct of the longitudinal COVID‐19 psychological research consortium (C19PRC) study

The C19PRC study aims to assess the impact of the COVID‐19 pandemic in the adult population of the UK, Republic of Ireland, and Spain. This paper describes the conduct of the first two waves of the UK survey (the “parent” strand of the Consortium) during March–April 2020.
The duration effect of pictorial health warnings on tobacco consumption in Mexico

ABSTRACT Pictorial health warnings (PHW) were introduced in Mexico by the end of 2010. Different studies have assessed how PHW influence attitude or desire to renounce smoking, but they have not studied the actual effect on the demand of tobacco products. Our objective in this paper is to analyze the effect of duration of pictorial health warnings on consumption of tobacco in Mexico. We assess the influence of different consecutive rounds of pictorial warnings, taking into account their length and the use of repeated images. We use a Dynamic Least Squares model (DOLS) with quarterly data (1994-2015), to estimate the long run demand of cigarettes in Mexico, as a function of per-capita income, the relative price of tobacco, different regulatory measures and the different rounds of pictograms, its duration, and the use of repeated images. We find evidence indicating that the pictorial health warnings have reduced consumption of cigarettes, that the effect has decreased in the last rounds, and that the most effective duration of the rounds is six months. PHW regulation deters consumption; however, its effectiveness decreases over time, suggesting that consumers tend to adapt to images.
Using Integrative Modeling Platform to compute, validate, and archive a model of a protein complex structure

Biology is advanced by producing structural models of biological systems, such as protein complexes. Some systems are recalcitrant to traditional structure determination methods. In such cases, it may still be possible to produce useful models by integrative structure determination that depends on simultaneous use of multiple types of data. An ensemble of models that are sufficiently consistent with the data is produced by a structural sampling method guided by a data‐dependent scoring function. The variation in the ensemble of models quantified the uncertainty of the structure, generally resulting from the uncertainty in the input information and actual structural heterogeneity in the samples used to produce the data. Here, we describe how to generate, assess, and interpret ensembles of integrative structural models using our open source Integrative Modeling Platform program (https://integrativemodeling.org).
Measurement of autophagic flux in humans: an optimized method for blood samples

ABSTRACT Autophagic flux is a critical cellular process that is vastly under-appreciated in terms of its importance to human health. Preclinical studies have demonstrated that reductions in autophagic flux cause cancer and exacerbate chronic diseases, including heart disease and the pathological hallmarks of dementia. Autophagic flux can be increased by targeting nutrition-related biochemical signaling. To date, translation of this knowledge has been hampered because there has been no way to directly measure autophagic flux in humans. In this study we detail a method whereby human macroautophagic/autophagic flux can be directly measured from human blood samples. We show that whole blood samples can be treated with the lysosomal inhibitor chloroquine, and peripheral blood mononuclear cells isolated from these samples could be used to measure autophagic machinery protein LC3B-II. Blocking of autophagic flux in cells while still in whole blood represents an important advance because it preserves genetic, nutritional, and signaling parameters inherent to the individual. We show this method was reproducible and defined LC3B-II as the best protein to measure autophagic flux in these cells. Finally, we show that this method is relevant to assess intra-individual variation induced by an intervention by manipulating nutrition signaling with an ex vivo treatment of whole blood that comprised leucine and insulin. Significantly, this method will enable the identification of factors that alter autophagic flux in humans, and better aid their translation in the clinic. With further research, it could also be used as a novel biomarker for risk of age-related chronic disease. Abbreviations: AMPK: AMP-activated protein kinase; ACTB: actin beta; ATG5: autophagy related 5; BAF: bafilomycin A1; CQ: chloroquine; DMSO: dimethyl sulfoxide; DPBS: Dulbecco’s phosphate-buffered saline; EDTA: ethylenediaminetetraacetic acid; KO: knockout; MAP1LC3A/LC3A: microtubule associated protein 1 light chain 3 alpha; MAP1LC3B/LC3B: microtubule associated protein 1 light chain 3 beta; MAP1LC3C/LC3C: microtubule associated protein 1 light chain 3 gamma; MTOR: mechanistic target of rapamycin kinase; NBR1: NBR1 autophagy cargo receptor; PBMCs: peripheral blood mononuclear cells; PMNs: polymorphonuclear cells; RPMI: Roswell Park Memorial Institute; SQSTM1: sequestosome 1; TBST: Tris-buffered saline containing 0.1% (v:v) Tween 20; TEM: transmission electron microscopy.
The role of chlorine atom on the binding between acrylonitrile derivatives and fat mass and obesity‐associated protein

In this work, seven acrylonitrile derivatives were selected as potential inhibitors of fat and obesity‐related proteins (FTO) by the aid of fluorescence spectroscopy, ultraviolet visible spectroscopy, molecular docking, and cytotoxicity methods. Results show that the interaction between 3‐amino‐2‐(4‐chlorophenyl)‐3‐phenylacrylonitrile (1a) and FTO was the strongest among these derivatives. Thermodynamic analysis and molecular modeling show that the main force between 1a and FTO is hydrophobic interaction. The cytotoxicity test showed that the IC50 value of 1a was 46.64 μmol/L, which indicated 1a had the smallest IC50 value and had the best inhibitory effect on the proliferation of leukemia K562 cells among the seven derivatives. Both our previous results and this work show that chlorine atoms play important role in the binding of small molecules and FTO. This work brings new information for the study of FTO inhibitors.
Is Timing to Surgery an Independent Risk Factor for Complications Following Operative Treatment of Periprosthetic Lower Extremity Fractures?

Supplemental Digital Content is Available in the Text. Objective: To identify whether timing to surgery was related to major 30-day morbidity and mortality rates in periprosthetic hip and knee fractures [OTA/AO 3 (IV.3, V.3), OTA/AO 4 (V4)]. Design: Retrospective database review. Setting: Hospitals participating in the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database. Patients: Patients in the NSQIP database with periprosthetic hip or knee fractures between 2007 and 2015. Intervention: Surgical management of periprosthetic hip and knee fractures including revision or open reduction internal fixation. Main Outcome Measurements: Major 30-day morbidity and mortality after operative treatment of periprosthetic hip or knee fractures. Results: A total of 1265 patients, mean age 72, including 883 periprosthetic hip and 382 periprosthetic fractures about the knee were reviewed. Delay in surgery greater than 72 hours is a risk factor for increased 30-day morbidity in periprosthetic hip and knee fractures [relative risk = 2.90 (95% confidence interval: 1.74–4.71); P-value ≤ 0.001] and risk factor for increased 30-day mortality [relative risk = 8.98 (95% confidence interval: 2.14–37.74); P-value = 0.003]. Conclusions: Using NSQIP database to analyze periprosthetic hip and knee fractures, delay to surgery is an independent risk factor for increased 30-day major morbidity and mortality when controlling for patient functional status and comorbidities. Although patient optimization and surgical planning are paramount, minimizing extended delays to surgery is a potentially modifiable risk factor in the geriatric periprosthetic lower extremity fracture patient. Level of Evidence: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.