Leveraging the Crowd for Dependency Management: An Empirical Study on the Dependabot Compatibility Score

Dependabot, a popular dependency management tool, includes a compatibility score feature that helps client packages assess the risk of accepting a dependency update by leveraging knowledge from "the crowd". For each dependency update, Dependabot calculates this compatibility score as the proportion of successful updates performed by other client packages that use the same provider package as a dependency. In this paper, we study the efficacy of the compatibility score to help client packages assess the risks involved with accepting a dependency update. We analyze 579,206 pull requests opened by Dependabot to update a dependency, along with 618,045 compatibility score records calculated by Dependabot. We find that a compatibility score cannot be calculated for 83% of the dependency updates due to the lack of data from the crowd. Yet, the vast majority of the scores that can be calculated have a small confidence interval and are based on low-quality data, suggesting that client packages should have additional angles to evaluate the risk of an update and the trustworthiness of the compatibility score. To overcome these limitations, we propose metrics that amplify the input from the crowd and demonstrate the ability of those metrics to predict the acceptance of a successful update by client packages. We also demonstrate that historical update metrics from client packages can be used to provide a more personalized compatibility score. Based on our findings, we argue that, when leveraging the crowd, dependency management bots should include a confidence interval to help calibrate the trust clients can place in the compatibility score, and consider the quality of tests that exercise candidate updates

Exploring the Impact of the Output Format on the Evaluation of Large Language Models for Code Translation

Code translation between programming languages is a long-existing and critical task in software engineering, facilitating the modernization of legacy systems, ensuring cross-platform compatibility, and enhancing software performance. With the recent advances in large language models (LLMs) and their applications to code translation, there is an increasing need for comprehensive evaluation of these models. In this study, we empirically analyze the generated outputs of eleven popular instruct-tuned LLMs with parameters ranging from 1B up to 46.7B on 3,820 translation pairs across five languages, including C, C++, Go, Java, and Python. Our analysis found that between 26.4% and 73.7% of code translations produced by our evaluated LLMs necessitate post-processing, as these translations often include a mix of code, quotes, and text rather than being purely source code. Overlooking the output format of these models can inadvertently lead to underestimation of their actual performance. This is particularly evident when evaluating them with execution-based metrics such as Computational Accuracy (CA). Our results demonstrate that a strategic combination of prompt engineering and regular expression can effectively extract the source code from the model generation output. In particular, our method can help eleven selected models achieve an average Code Extraction Success Rate (CSR) of 92.73%. Our findings shed light on and motivate future research to conduct more reliable benchmarks of LLMs for code translation.Comment: Accepted into 2024 IEEE/ACM First International Conference on AI Foundation Models and Software Engineering (Forge

Disaturated-phosphatidylcholine and Surfactant protein-B turnover in human acute lung injury and in control patients

<p>Abstract</p> <p>Background</p> <p>Patients with Adult Respiratory Distress Syndrome (ARDS) and Acute Lung Injury (ALI) have low concentrations of disaturated-phosphatidylcholine and surfactant protein-B in bronchoalveolar lavage fluid. No information is available on their turnover.</p> <p>Objectives</p> <p>To analyze disaturated-phosphatidylcholine and surfactant protein-B turnover in patients with ARDS/ALI and in human adults with normal lungs (controls).</p> <p>Methods</p> <p>²H₂O as precursor of disaturated-phosphatidylcholine-palmitate and 1¹³C-Leucine as precursor of surfactant protein-B were administered intravenously to 12 patients with ARDS/ALI and to 8 controls. Disaturated-phosphatidylcholine and surfactant protein-B were isolated from serial tracheal aspirates, and their fractional synthetic rate was derived from the ²H and ¹³C enrichment curves, obtained by gas chromatography mass spectrometry. Disaturated-phosphatidylcholine, surfactant protein-B, and protein concentrations in tracheal aspirates were also measured.</p> <p>Results</p> <p>1) Surfactant protein-B turned over at faster rate than disaturated-phosphatidylcholine both in ARDS/ALI patients and in controls. 2) In patients with ARDS/ALI the fractional synthesis rate of disaturated-phosphatidylcholine was 3.1 times higher than in controls (p < 0.01), while the fractional synthesis rate of surfactant protein-B was not different. 3) In ARDS/ALI patients the concentrations of disaturated-phosphatidylcholine and surfactant protein-B in tracheal aspirates were markedly and significantly reduced (17% and 40% of the control values respectively).</p> <p>Conclusions</p> <p>1) Disaturated-phosphatidylcholine and surfactant protein-B have a different turnover both in healthy and diseased lungs. 2) In ARDS/ALI the synthesis of these two surfactant components may be differently regulated.</p

Respiratory Effects of Exposure to Traffic-Related Air Pollutants During Exercise

Traffic-related air pollution (TRAP) is increasing worldwide. Habitual physical activity is known to prevent cardiorespiratory diseases and mortality, but whether exposure to TRAP during exercise affects respiratory health is still uncertain. Exercise causes inflammatory changes in the airways, and its interaction with the effects of TRAP or ozone might be detrimental, for both athletes exercising outdoor and urban active commuters. In this Mini-Review, we summarize the literature on the effects of exposure to TRAP and/or ozone during exercise on lung function, respiratory symptoms, performance, and biomarkers. Ozone negatively affected pulmonary function after exercise, especially after combined exposure to ozone and diesel exhaust (DE). Spirometric changes after exercise during exposure to particulate matter and ultrafine particles suggest a decrease in lung function, especially in patients with chronic obstructive pulmonary disease. Ozone frequently caused respiratory symptoms during exercise. Women showed decreased exercise performance and higher symptom prevalence than men during TRAP exposure. However, performance was analyzed in few studies. To date, research has not identified reliable biomarkers of TRAP-related lung damage useful for monitoring athletes' health, except in scarce studies on airway cells obtained by induced sputum or bronchoalveolar lavage. In conclusion, despite partly counteracted by the positive effects of habitual exercise, the negative effects of TRAP exposure to pollutants during exercise are hard to assess: outdoor exercise is a complex model, for multiple and variable exposures to air pollutants and pollutant concentrations. Further studies are needed to identify pollutant and/or time thresholds for performing safe outdoor exercise in cities

Pediatric emergency department mental health assessments in the 2 years following the COVID-19 outbreak reveal higher vulnerability for eating disorder and suicide risk

Background: In the post-COVID era an increase in Emergency Department (ED) mental health assessments has been consistently reported among youth populations. Methods: Pediatric ED mental health assessments in the 2 years following the COVID-19 pandemic (March 2020-February 2022) were compared to those in the immediately preceding same period (March 2018-February 2020), in terms of rates and risk profiles. Results: During the pre-pandemic and post-pandemic periods, 158 and 268 ED accesses were counted respectively, and an overall 1.64 (95 % CI: 1.34–1.99) monthly IRR was estimated. During the post-pandemic period, youth accessing ED were less likely to have a personal history of psychiatric disorders (OR: 0.49; 95 % CI: 0.28–0.86) and to receive an extemporaneous administration of psychopharmacological therapy in ED (OR: 0.28; 95 % CI: 0.14–0.57), despite being more frequently discharged from ED with a background psychopharmacological therapy in place (OR: 2.02; 95 % CI: 1.02–4.01). Finally, during the post-pandemic period, an increase in ED accesses for eating disorder (OR: 2.77; 95 % CI: 1.49–5.13) and suicidal thoughts-self-harm (OR: 2.00; 95 % CI: 1.07–3.74) was observed, when compared to ED access for anxiety-agitation. Conclusions: This report suggests higher rates of post-COVID pediatric ED mental health assessments, especially for eating disorder and suicide risk, with a preponderance of youth whose ED access may be their first mental health specialist contact

The latent structure and reliability of the emotional trait section of the Affective and Emotional Composite Temperament Scale (AFECTS)

Background: The Emotional and Affective Composite Temperament (AFECT) model describes originally six traits of volition, anger, inhibition (fear and caution subordinate factors), control, sensitivity, and coping. However, fear and caution have shown opposite relatioships with criteria-variables, indicating factor independence. Objective: The current investigation aimed to advance in the evaluation of the psychometric properties of the emotional trait section of the Emotional and Affective Composite Temperament Scale (AFECTS) by examining the suitability of a 7-factor structure and the reliability of each scale using data from a population-based sample. Methods: AFECTS was administered via face-to-face assessments in a single-session, population-based cross-sectional survey. Samples was composed of teenagers and adults (14 to 35 years). The latent structure and reliability were analyzed via structural equation modeling: confirmatory factor analysis was used to test the a priori correlated 7-factor model (with fear and caution designed as single-factors) and trait-scores reliability was assessed by the estimation of information curves. Results: Findings attested the suitability of the 7-factor model presumed to underline the item set of the traits section of AFECTS and information curve interpretation showed adequate levels of reliability for all trait-scores. Discussion: The 7-factor model showed robust indicators of construct validity for the AFECTS

Variabilidade espacial de atributos físicos do solo em diferentes sistemas de manejo.

A variabilidade espacial de atributos físicos do solo (areia total, silte, argila, densidades do solo e de partículas, porosidade total e umidade gravimétrica) foi avaliada em Passo Fundo (RS), em três sistemas de manejo: preparo convencional, semeadura direta (ambos em LATOSSOLO VERMELHO Distroférrico) e pastagem (LATOSSOLO VERMELHO Distrófico), na malha de amostragem de 10 x 10 m e profundidades de 0-0,10, 0,10-0,20 e 0,20-0,30 m. Nos sistemas com cultivo foi também avaliada a variabilidade da produção de trigo, colhendo-se áreas de 1 m², na mesma malha de amostragem. As propriedades do solo avaliadas seguiram a distribuição normal, na maioria dos sistemas de manejo e profundidades. As menores variabilidades foram observadas para argila e densidade de partículas (CVs<10%) e as maiores para areia total e silte (10%<CVs<20%). A área sob pastagem foi a que apresentou a menor variabilidade, com os demais sistemas bem aproximados entre si. Dependência espacial com grau variando de forte a moderado foi observada para todos os atributos físicos e para a produção de trigo nos sistemas de manejo avaliados. Ocorreu correlação espacial cruzada da produção de trigo com granulometria, no sistema de semeadura direta, sendo positiva para areia total e silte e negativa para argila

Influencia da cobertura vegetal morta na reducao da velocidade da enxurrada e na distribuicao de tamanho dos sedimentos transportados.

O efeito da porcentagem de cobertura do solo com residuos culturais na reducao da velocidade do escoamennto superficial da agua e distribuicao de tamanho dos sedimentos erodidos, foi avaliado em condicoes de chuva simulada, na Estacao Experimental Agronomica da UFRGS, em Guaiba (RS). A area utilizada para o estudo encontra-se em solo franco-arenoso (Podzolico Vermelho-Amarelo distrofico abrupto petroferrico), com 7,5% de declividade. Os tratamentos principais consistiram em residuos culturais de milho, trigo e soja, espalhados uniformemente sobre superficie de solo preparada convencionalmente, em percentagens de cobertura do solo de 0 a 100% Independente do tipo de residuo cultural utilizado, o aumento na percentagem de cobertura do solo diminuiu acentuadamente a velocidade do escoamento superficial da agua, com a resteva de trigo mostrando-se mais eficaz. A percentagem de sedimentos de maior tamanho transportados na enxurrada e os valores do indice D50 diminuiram com o aumento da percentagem de cobertura do solo em todos os tipos de residuos culturais estudados, e cresceram com o aumento da velocidade do escoamento superficial da agua