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The article sheds light on Chinese as a Second Language Learner Corpus Research, emphasising advances and lacks in this field. First, the paper describes the potential of learner corpora in the investigation of learner language. Second, it provides an overview of Chinese learner corpus-based research and reviews existing L2 Chinese learner corpora. The paper highlights the lack of L2 Chinese learner corpora collecting data from Italian learners. Therefore, it emphasises the importance of compiling corpora to conduct studies on the acquisition of L2 Chinese by learners whose L1s are other than English or Asian languages.

Small-Cell Lung Cancer (SCLC) accounts for 15 % of all lung cancer cases. Due to comorbidities and its aggressive behaviour, patients are highly symptomatic even at a non-metastatic stage. Standardizing the care pathway and introducing a simultaneous care approach could address the unmet needs of this disease. However, there is no uniformity in the involvement of palliative care physicians and in the simultaneous use of palliative care and cancer therapies. In this context, 13 experts from Lazio region undertook a process to deepen their understanding of the regional provision of simultaneous care to patients with SCLC by structuring and carrying out a survey. The survey covered 35–52 % of SCLC cases in the region, confirming heterogeneous results in both management and therapeutic approach, particularly in the area of simultaneous care. The working group met to define practical recommendations with the aim of standardizing the management of this disease.

This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.

This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.

Genetic improvement through breeding is one of the key approaches to increasing biomass supply. This paper documents the breeding progress to date for four perennial biomass crops (PBCs) that have high output-input energy ratios: namely Panicum virgatum (switchgrass), species of the genera Miscanthus (miscanthus), Salix (willow) and Populus (poplar). For each crop, we report on the size of germplasm collections, the efforts to date to phenotype and genotype, the diversity available for breeding and on the scale of breeding work as indicated by number of attempted crosses. We also report on the development of faster and more precise breeding using molecular breeding techniques. Poplar is the model tree for genetic studies and is furthest ahead in terms of biological knowledge and genetic resources. Linkage maps, transgenesis and genome editing methods are now being used in commercially focused poplar breeding. These are in development in switchgrass, miscanthus and willow generating large genetic and phenotypic data sets requiring concomitant efforts in informatics to create summaries that can be accessed and used by practical breeders. Cultivars of switchgrass and miscanthus can be seed-based synthetic populations, semihybrids or clones. Willow and poplar cultivars are commercially deployed as clones. At local and regional level, the most advanced cultivars in each crop are at technology readiness levels which could be scaled to planting rates of thousands of hectares per year in about 5 years with existing commercial developers. Investment in further development of better cultivars is subject to current market failure and the long breeding cycles. We conclude that sustained public investment in breeding plays a key role in delivering future mass-scale deployment of PBCs.

Genetic improvement through breeding is one of the key approaches to increasing biomass supply. This paper documents the breeding progress to date for four perennial biomass crops (PBCs) that have high output-input energy ratios: namely Panicum virgatum (switchgrass), species of the genera Miscanthus (miscanthus), Salix (willow) and Populus (poplar). For each crop, we report on the size of germplasm collections, the efforts to date to phenotype and genotype, the diversity available for breeding and on the scale of breeding work as indicated by number of attempted crosses. We also report on the development of faster and more precise breeding using molecular breeding techniques. Poplar is the model tree for genetic studies and is furthest ahead in terms of biological knowledge and genetic resources. Linkage maps, transgenesis and genome editing methods are now being used in commercially focused poplar breeding. These are in development in switchgrass, miscanthus and willow generating large genetic and phenotypic data sets requiring concomitant efforts in informatics to create summaries that can be accessed and used by practical breeders. Cultivars of switchgrass and miscanthus can be seed-based synthetic populations, semihybrids or clones. Willow and poplar cultivars are commercially deployed as clones. At local and regional level, the most advanced cultivars in each crop are at technology readiness levels which could be scaled to planting rates of thousands of hectares per year in about 5 years with existing commercial developers. Investment in further development of better cultivars is subject to current market failure and the long breeding cycles. We conclude that sustained public investment in breeding plays a key role in delivering future mass-scale deployment of PBCs.

This article investigates the current state of Chinese Learner Corpus Research (CLCR) and outlines its main features and critical issues. Thirty years have passed since the compilation of the first Chinese learner corpus. Since then, the number of Chinese learner corpus projects has considerably increased in China and outside China, leading to a parallel growth in L2 Chinese studies as well. Despite the increasingly wide-ranging accessibility of L2 Chinese learner corpora and achievements in CLCR, there are no research which analyze the current state of this expanding field, defining its key features and gaps. This study therefore aims to fill this lack in the literature and sheds light on the learner-corpus based research in the Chinese context. The study also aims to provide an updated and useful reference of current trends and limitations in CLCR to help scholars better guide future research in order to address current gaps in the field. First, the paper introduces origins, development, and current trends in CLCR; main features and limits of learner corpus design, analysis, and annotation in CLCR are also analyzed. Second, the paper provides an overview of existing L2 Chinese learner corpora, by grouping them according to mode (written, spoken and multimodal) and size (large-scale and small-scale). Finally, the article directs attention toward challenges in this field, concluding with future directions for CLCR and its intersections with Second Language Acquisition (SLA) to support L2 Chinese teaching and learning.

BackgroundGestational age is often used as a proxy for developmental maturity by clinicians and researchers alike. DNA methylation has previously been shown to be associated with age and has been used to accurately estimate chronological age in children and adults. In the current study, we examine whether DNA methylation in cord blood can be used to estimate gestational age at birth.ResultsWe find that gestational age can be accurately estimated from DNA methylation of neonatal cord blood and blood spot samples. We calculate a DNA methylation gestational age using 148 CpG sites selected through elastic net regression in six training datasets. We evaluate predictive accuracy in nine testing datasets and find that the accuracy of the DNA methylation gestational age is consistent with that of gestational age estimates based on established methods, such as ultrasound. We also find that an increased DNA methylation gestational age relative to clinical gestational age is associated with birthweight independent of gestational age, sex, and ancestry.ConclusionsDNA methylation can be used to accurately estimate gestational age at or near birth and may provide additional information relevant to developmental stage. Further studies of this predictor are warranted to determine its utility in clinical settings and for research purposes. When clinical estimates are available this measure may increase accuracy in the testing of hypotheses related to developmental age and other early life circumstances.

Citizen science has emerged as a potent approach for environmental monitoring, leveraging the collective efforts of volunteers to gather data at unprecedented scales. Within the framework of the I-CHANGE project, MeteoTracker, a citizen science initiative, was employed to collect meteorological measurements. Through MeteoTracker, volunteers contributed to a comprehensive dataset, enabling insights into local weather patterns and trends. This paper presents the analysis and the results of the validation of such observations against the official Italian civil protection in situ weather network, demonstrating the effectiveness of citizen science in generating valuable environmental data. The work discusses the methodology employed, including data collection and statistical analysis techniques, i.e., time-series analysis, spatial and temporal interpolation, and correlation analysis. The overall analysis highlights the high quality and reliability of citizen-generated data as well as the strengths of the MeteoTracker platform. Furthermore, our findings underscore the potential of citizen science to augment traditional monitoring efforts, inform decision-making processes in environmental research and management, and improve the social awareness about environmental and climate issues. [ABSTRACT FROM AUTHOR]

Frits ME Franssen1,2, Peter Alter,3 Nadav Bar,4 Birke J Benedikter5,6, Stella Iurato,7 Dieter Maier,8 Michael Maxheim,3 Fabienne K Roessler,4 Martijn A Spruit,1–2,9 Claus F Vogelmeier,3 Emiel FM Wouters1,2, Bernd Schmeck3,5 On behalf of the SysMed-COPD consortium 1Department of Research and Education, CIRO, Horn, The Netherlands; 2Department of Respiratory Medicine, Maastricht University Medical Centre, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht, The Netherlands; 3Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps University of Marburg (UMR), Member of the German Center for Lung Research (DZL), Marburg, Germany; 4Department of Chemical Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; 5Institute for Lung Research, Universities of Giessen and Marburg Lung Centre, Philipps-University Marburg, Member of the German Center for Lung Research (DZL), Marburg, Germany; 6Department of Medical Microbiology, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands; 7Viscovery Software GmbH, Vienna, Austria; 8Biomax Informatics AG, Planegg, Germany; 9REVAL - Rehabilitation Research Center, BIOMED - Biomedical Research Institute, Faculty of Rehabilitation Sciences, Hasselt University, Diepenbeek, BelgiumAbstract: Chronic airflow limitation is the common denominator of patients with chronic obstructive pulmonary disease (COPD). However, it is not possible to predict morbidity and mortality of individual patients based on the degree of lung function impairment, nor does the degree of airflow limitation allow guidance regarding therapies. Over the last decades, understanding of the factors contributing to the heterogeneity of disease trajectories, clinical presentation, and response to existing therapies has greatly advanced. Indeed, diagnostic assessment and treatment algorithms for COPD have become more personalized. In addition to the pulmonary abnormalities and inhaler therapies, extra-pulmonary features and comorbidities have been studied and are considered essential components of comprehensive disease management, including lifestyle interventions. Despite these advances, predicting and/or modifying the course of the disease remains currently impossible, and selection of patients with a beneficial response to specific interventions is unsatisfactory. Consequently, non-response to pharmacologic and non-pharmacologic treatments is common, and many patients have refractory symptoms. Thus, there is an ongoing urgency for a more targeted and holistic management of the disease, incorporating the basic principles of P4 medicine (predictive, preventive, personalized, and participatory). This review describes the current status and unmet needs regarding personalized medicine for patients with COPD. Also, it proposes a systems medicine approach, integrating genetic, environmental, (micro)biological, and clinical factors in experimental and computational models in order to decipher the multilevel complexity of COPD. Ultimately, the acquired insights will enable the development of clinical decision support systems and advance personalized medicine for patients with COPD.Keywords: chronic obstructive pulmonary disease, personalized medicine, systems medicine, review

Following detailed presentation of the Core Conflictual Relationship Theme (CCRT), there is the objective of relevant methods for what has been described as verbalization and visualization of data. Such is also termed data mining and text mining, and knowledge discovery in data. The Correspondence Analysis methodology, also termed Geometric Data Analysis, is shown in a case study to be comprehensive and revealing. Quite innovative here is how the analysis process is structured. For both illustrative and revealing aspects of the case study here, relatively extensive dream reports are used. The dream reports are from an open source repository of dream reports, and the current study proposes a possible framework for the analysis of dream report narratives, and further, how such an analysis could be relevant within the psychotherapeutic context. This Geometric Data Analysis here confirms the validity of CCRT method.

We start with a description of Lacan’s work that we then take into our analytics methodology. In a first investigation, a Lacan-motivated template of the Poe story is fitted to the data. A segmentation of the storyline is used in order to map out the diachrony. Based on this, it will be shown how synchronous aspects, potentially related to Lacanian registers, can be sought. This demonstrates the effectiveness of an approach based on a model template of the storyline narrative. In a second and more comprehensive investigation, we develop an approach for revealing, that is, uncovering, Lacanian register relationships. Objectives of this work include the wide and general application of our methodology. This methodology is strongly based on the “letting the data speak” Correspondence Analysis analytics platform of Jean-Paul Benzécri, that is also the geometric data analysis, both qualitative and quantitative analytics, developed by Pierre Bourdieu.

The book springs out from the will, expressed by some American psychoanalysts in 2010, to have a collection of some of the most representative Italian contributions to psychoanalysis, in that Italian psychoanalysis had undertaken an original and interesting theoretical and technical configuration yet not fully known abroad. So, history and epistemology of psychoanalysis needed of such a source.

Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses. A specific class of deep learning-based methods allows for the prediction of regulatory effects per variant on several cell type-specific chromatin features. We here describe "DeepWAS", a new approach that integrates these regulatory effect predictions of single variants into a multivariate GWAS setting. Thereby, single variants associated with a trait or disease are directly coupled to their impact on a chromatin feature in a cell type. Up to 61 regulatory SNPs, called dSNPs, were associated with multiple sclerosis (MS, 4,888 cases and 10,395 controls), major depressive disorder (MDD, 1,475 cases and 2,144 controls), and height (5,974 individuals). These variants were mainly non-coding and reached at least nominal significance in classical GWAS. The prediction accuracy was higher for DeepWAS than for classical GWAS models for 91% of the genome-wide significant, MS-specific dSNPs. DSNPs were enriched in public or cohort-matched expression and methylation quantitative trait loci and we demonstrated the potential of DeepWAS to generate testable functional hypotheses based on genotype data alone. DeepWAS is available at https://github.com/cellmapslab/DeepWAS.

Stressful life events are major environmental risk factors for anxiety disorders, although not all individuals exposed to stress develop clinical anxiety. The molecular mechanisms underlying the influence of environmental effects on anxiety are largely unknown. To identify biological pathways mediating stress-related anxiety and resilience to it, we used the chronic social defeat stress (CSDS) paradigm in male mice of two inbred strains, C57BL/6NCrl (B6) and DBA/2NCrl (D2), that differ in their susceptibility to stress. Using a multi-omics approach, we identified differential mRNA, miRNA and protein expression changes in the bed nucleus of the stria terminalis (BNST) and blood cells after chronic stress. Integrative gene set enrichment analysis revealed enrichment of mitochondrial-related genes in the BNST and blood of stressed mice. To translate these results to human anxiety, we investigated blood gene expression changes associated with exposure-induced panic attacks. Remarkably, we found reduced expression of mitochondrial-related genes in D2 stress-susceptible mice and in exposure-induced panic attacks in humans, but increased expression of these genes in B6 stress-susceptible mice. Moreover, stress-susceptible vs. stress-resilient B6 mice displayed more mitochondrial cross-sections in the post-synaptic compartment after CSDS. Our findings demonstrate mitochondrial-related alterations in gene expression as an evolutionarily conserved response in stress-related behaviors and validate the use of cross-species approaches in investigating the biological mechanisms underlying anxiety disorders.

In continuation of what has been said in the first part of this two-part paper, herein we present further considerations on symbolism, reconsider some related psychodynamic case reports with some possible variants about their interpretations, and will apply what is said to some further speculations on mathematical symbolism and thought. In this second part, we continue with the numeration of the first part Σύμβολου, 1.

Stroke is a leading cause of death and disability and is the third highest cause of death in the western world. Medical illness after ischemic stroke contribute substantially to poor stroke outcomes. The early in-hospital complications of stroke patients are mainly: pneumonia (hospital acquired pulmonary infection), increased intracranial pressure (neuroimaging evidence of cerebral edema or brain shift syndrome with clinical deterioration), urinary tract infection, intracerebral bleeding, recurrent stroke, epileptic seizures, thrombosis or pulmonary embolism. All these complications influence the patient’s outcomes and require diagnostic and therapeutic measures. Pulmonary embolism is a major contributor to in-hospital death after stroke. Although the rate of clinically overt pulmonary embolism after stroke has been estimated to be less than 1%, pulmonary emboli account for up to 50% of early deaths after stroke. In daily practice, the clinical burden of pulmonary embolism in patient with stroke is, however, underestimated since the clinical symptoms of stroke may obscure the recognition of this complication. The aim of this article is to describe the clinical and therapeutic aspects of pulmonary embolism as complication after stroke.