Martian atmospheric hydrogen and deuterium: Seasonal changes and paradigm for escape to space.

Mars' water history is fundamental to understanding Earth-like planet evolution. Water escapes to space as atoms, and hydrogen atoms escape faster than deuterium giving an increase in the residual D/H ratio. The present ratio reflects the total water Mars has lost.

The trilemma of innovation, logistics performance, and environmental quality in 25 topmost logistics countries: A quantile regression evidence.

While the deployment of technological innovation was able to avert a devastating global supply chain fallout arising from the impact of ravaging COronaVIrus Disease 19 (COVID-19) pandemic, little is known about potential environmental cost of such achievement. The aim of this paper is to identify the determinants of logistics performance and investigate its empirical linkages with economic and environmental indicators. We built a macro-level dataset for the top 25 ranked logistics countries from 2007 to 2018, conducting a set of panel data tests on cross-sectional dependence, stationarity and cointegration, to provide preliminary insights.

Convergence behaviours of energy series and GDP nexus hypothesis: A non-parametric Bayesian application.

With the EU Green Deal initiatives, European members seek to launch the first climate neutral continent by 2050. This paper assesses the stochastic convergence of per capita energy consumption series for an illustrative sample of 15 EU countries with memberships prior to the 2004 enlargement, using data spanning the 1970-2018 period. Results from the confidence interval subsampling (asymmetric and equal-tailed) highlight that 11 out of the 15 EU series exhibit a long-run memory behaviour, while a diverging pattern was observed for the UK, Germany, Portugal, and Italy.

What does the EKC theory leave behind? A state-of-the-art review and assessment of export diversification-augmented models.

Over the past three decades, researchers have extensively examined the environmental Kuznets curve (EKC) hypothesis. Despite their early focus on the ecological impacts of anthropogenic development, associated conclusions differ and often conflict. In this study, we conducted a state-of-the-art review of this topic and shed light on the methodological challenges that the literature attempted to overcome so far.

Assessing a fossil fuels externality with a new neural networks and image optimisation algorithm: the case of atmospheric pollutants as confounders to COVID-19 lethality.

This paper demonstrates how the combustion of fossil fuels for transport purpose might cause health implications. Based on an original case study [i.e.

Life cycle assessment of greywater treatment systems for water-reuse management in rural areas.

Water scarcity is a major concern worldwide. Population growth, as well as the intensive use of water resources for industrial and agricultural activities, among others, have caused water stress in various regions of the world. Rural areas are usually more affected due to water scarcity and a lack of sanitary infrastructure.

Machine Learning Classification of Inflammatory Bowel Disease in Children Based on a Large Real-World Pediatric Cohort CEDATA-GPGE® Registry.

The rising incidence of pediatric inflammatory bowel diseases (PIBD) facilitates the need for new methods of improving diagnosis latency, quality of care and documentation. Machine learning models have shown to be applicable to classifying PIBD when using histological data or extensive serology. This study aims to evaluate the performance of algorithms based on promptly available data more suited to clinical applications.

Revisiting the dynamic interactions between economic growth and environmental pollution in Italy: evidence from a gradient descent algorithm.

Although the literature on the relationship between economic growth and CO emissions is extensive, the use of machine learning (ML) tools remains seminal. In this paper, we assess this nexus for Italy using innovative algorithms, with yearly data for the 1960-2017 period. We develop three distinct models: the batch gradient descent (BGD), the stochastic gradient descent (SGD), and the multilayer perceptron (MLP).

Can biomass energy curtail environmental pollution? A quantum model approach to Germany.

This paper aims to investigate the causal relationship among renewable energy technologies, biomass energy consumption, per capita GDP, and CO emissions for Germany. We constructed an innovative algorithm, the Quantum model, and applied it with Machine Learning experiments - through a software capable of emulating a quantum system - to data over the period of 1990-2018. This process is possible after eliminating the "irreversibility" of classical computations (unitary transformations) by making the process "reversible".

NO levels as a contributing factor to COVID-19 deaths: The first empirical estimate of threshold values.

This study represents the first empirical estimation of threshold values between nitrogen dioxide (NO) concentrations and COVID-19-related deaths in France. The concentration of NO linked to COVID-19-related deaths in three major French cities were determined using Artificial Neural Networks experiments and a Causal Direction from Dependency (D2C) algorithm. The aim of the study was to evaluate the potential effects of NO in spreading the epidemic.

Waste generation, wealth and GHG emissions from the waste sector: Is Denmark on the path towards circular economy?

Municipal solid waste (MSW) is one of the most urgent issues associated with economic growth and urban population. When untreated, it generates harmful and toxic substances spreading out into the soils. When treated, they produce an important amount of Greenhouse Gas (GHG) emissions directly contributing to global warming.

The relationship between air pollution and COVID-19-related deaths: An application to three French cities.

Being heavily dependent to oil products (mainly gasoline and diesel), the French transport sector is the main emitter of Particulate Matter (PMs) whose critical levels induce harmful health effects for urban inhabitants. We selected three major French cities (Paris, Lyon, and Marseille) to investigate the relationship between the Coronavirus Disease 19 (COVID-19) outbreak and air pollution. Using Artificial Neural Networks (ANNs) experiments, we have determined the concentration of PM and PM linked to COVID-19-related deaths.

The relationship between municipal solid waste and greenhouse gas emissions: Evidence from Switzerland.

Municipal solid waste generation is becoming a prominent issue in the environmental arena. The aim of this paper is to investigate the relationship among municipal waste generation, greenhouse gas emissions, and GDP in Switzerland over the period 1990-2017. We apply both time series procedures (stationarity and causality tests) and a Machine Learning approach.

A novel conditional NPM-ALK-driven model of CD30+ T-cell lymphoma mediated by a translational stop cassette.

Targeted expression of transgenes is essential for the accurate representation of human disease in in vivo models. Current approaches to generate conditional transgenic mouse models are cumbersome and not amenable to high-throughput analysis since they require de novo generation and characterization of genetically modified mice. Here we describe a new system for lineage-restricted expression of transgenes based on a retroviral vector incorporating a translational stop cassette flanked by loxP recombination sites.

[Polycystic ovary syndrome and congenital adrenal hyperplasia: a different entity for comparable phenotypes?].

The phenotypes of the polycystic ovarian syndrome (PCOS) and congenital adrenal hyperplasia syndrome (CAHS) present a number of similarities. The main symptoms of PCOS are obesity, menstrual disorders, hirsutism, and low fertility in which the pituitary and adrenal glands are spared. The CAHS is a group of various entities all characterised by different degrees of malfunction of the 21-hydroxylase (CYP21) enzyme.

[Mastectomy and reconstruction: what kind of safety, which attitude?].

Breast reconstruction should be regarded as a significant part of breast cancer treatment. Immediate reconstruction has the advantages of a better cosmetic result, a better illness approach and of avoiding the need of a second major operative procedure. Immediate and early delayed reconstruction does not significantly increase the risk of local or systemic disease recurrence and the type of surgery performed should depend on the further therapy chosen.

Cystadenocarcinoma of the abdominal wall following caesarean section: case report and review of the literature.

Objectives: Endometriosis affecting surgical scars is a well-described entity that can complicate surgery involving hysterotomies. Malignant transformation is a rare event that has been reported complicating ovarian endometriosis mainly.

Case: A 60-year-old woman having in the past two uneventful caesarean deliveries presented with a solid lower abdominal mass.