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Alternate wetting and drying (AWD) is considered as an effective water-saving practice for rice cultivation widely applied across the world. Although AWD can reduce global warming potential compared to continuous flooding (CF), it may have negative effects on N availability for crop by promoting N losses (nitrification-denitrification, leaching) and immobilization, due to the frequent soil redox cycling. By means of a growth chamber pot experiment and a 15N stable isotope approach we investigated the interactions between water, crop residue and fertilizer N management on the contribution of different N sources (i.e. fertilizer, rice straw, soil) to rice plant N uptake. We hypothesized that with respect to CF, AWD will decrease plant uptake of fertilizer (FDN), straw (StDN), and soil (SDN) derived N due to greater losses, greater microbial N immobilization during residue turnover under oxic conditions, and less N supply from soil organic matter (OM) desorbed under reducing conditions. Moreover, we hypothesized that the underlying processes will be influence by the timing of straw addition with respect to flooding and the temporal distribution of mineral N application.Rice was grown for 60 d in a factorial setup including: (i) two water regimes: CF for 60 d vs. AWD (30 d of flooding followed by 30 d of alternating conditions involving 3 drain-flood cycles), and (ii) three straw and fertilizer managements that involved a combination of straw addition (10 Mg ha-1) 30 or 60 d before seeding (S30 and S60, respectively), and N fertilization (ammonium sulfate) split between pre-seeding and tillering in 60+60 or 80+40 kg N ha-1, such that treatments compared were S30-N60-N60, S30-N80-N40 and S60-N60‑N60. 15N-enriched fertilizer and straw were used in separate replicated setups to quantify the relative contribution of FDN, StDN and SDN to plant N uptake, as well as fertilizer use efficiency (FUE).Plant N was mainly soil and fertilizer-derived (≈ 58 and 40%, respectively), while straw only contribute a minor amount (< 3%). Although AWD reduced total N uptake by about 10-13% with respect to CF, FDN and FUE were only slightly affected by water management, suggesting that differences in N nutrition did not depend exclusively on fertilizer N losses. SDN contributed more to plant nutrition in CF than in AWD, particularly when straw was incorporated in proximity to flooding. The combination of a fresh OM supply and reducing conditions under CF favoured the reductive dissolution of Fe oxides and desorption of soil OM that increase soil N supply via mineralization. StDN contributed less to plant nutrition in AWD than in CF albeit the higher mineralization rates we expected with more frequent oxic conditions. We attributed this to a higher microbial N demand under aerobic conditions that leads to a greater immobilization SDN during decomposition. The higher SDN and StDn for N60-N60 treatment with respect to N80-N40 suggested that an equilibrated splitting of N fertilizer between pre‑seeding and tillering stages could favor microbial activity under AWD improving straw degradation and soil N release.This research was funded by the Lombardy Region through the project RISWAGEST

Public health, just as any policy-related field, faces the evergreen problem of turning knowledge into action. Among other problems, there is a clash between the inherent complexity of public health problems and the inevitable push, by decision-makers and the public, to simplify them. The Covid-19 pandemic has shown the insufficiencies of our current epistemological, methodological and normative apparatus to handle such crises in a timely manner. Despite this, several authors have been arguing for the importance of engaging global crises such as Covid-19 in ways that do not oversimplify key dimensions of the issues involved. In this paper, we contribute to this emerging scholarship. Building on existing work in the field of environmental problem-solving, we propose an integrative approach to navigating complex trade-offs in public health interventions. Briefly put, we propose that decision making should be informed by an analysis of any given problem from four distinct, but interrelated, lenses: (i) values and valuation, (ii) process and governance, (iii) power and inequalities and (iv) scientific evidence, methods and concepts. This normative framework, we argue, can help with spelling out the complexity of public health problems and with spelling out the rationale behind public health decision making to non-specialists and the general public. We illustrate our approach using the controversy over wearing face masks in the Covid-19 pandemic.

The need for fair and just AI is often related to the possibility of understanding AI itself, in other words, of turning an opaque box into a glass box, as inspectable as possible. Transparency and explainability, however, pertain to the technical domain and to philosophy of science, thus leaving the ethics and epistemology of AI largely disconnected. To remedy this, we propose an integrated approach premised on the idea that a glass-box epistemology should explicitly consider how to incorporate values and other normative considerations, such as intersectoral vulnerabilities, at critical stages of the whole process from design and implementation to use and assessment. To connect ethics and epistemology of AI, we perform a double shift of focus. First, we move from trusting the output of an AI system to trusting the process that leads to the outcome. Second, we move from expert assessment to more inclusive assessment strategies, aiming to facilitate expert and non-expert assessment. Together, these two moves yield a framework usable for experts and non-experts when they inquire into relevant epistemological and ethical aspects of AI systems. We dub our framework ‘epistemology-cum-ethics’ to signal the equal importance of both aspects. We develop it from the vantage point of the designers: how to create the conditions to internalize values into the whole process of design, implementation, use, and assessment of an AI system, in which values (epistemic and non-epistemic) are explicitly considered at each stage and inspectable by every salient actor involved at any moment.

Public health and the underlying disease processes are complex, often involving the interaction of biologic, social, psychologic, economic, and other processes that may be nonlinear and adaptive and have other features of complex systems. There is therefore a need to push the boundaries of public health beyond single-factor data analysis and expand the capacity of research methodology to tackle real-world complexities. This article sets out a way to operationalize complex systems thinking in public health, with a particular focus on how epidemiologic methods and data can contribute towards this end. Our proposed framework comprises three core dimensions—patterns, mechanisms, and dynamics—along which complex systems may be conceptualized. These dimensions cover seven key features of complex systems—emergence, interactions, nonlinearity, interference, feedback loops, adaptation, and evolution. We relate this framework to examples of methods and data traditionally used in epidemiology. We conclude that systematic production of knowledge on complex health issues may benefit from: formulation of research questions and programs in terms of the core dimensions we identify, as a comprehensive way to capture crucial features of complex systems; integration of traditional epidemiologic methods with systems methodology such as computational simulation modeling; interdisciplinary work; and continued investment in a wide range of data types. We believe that the proposed framework can support the systematic production of knowledge on complex health problems, with the use of epidemiology and other disciplines. This will help us understand emergent health phenomena, identify vulnerable population groups, and detect leverage points for promoting public health. Public health and the underlying disease processes are complex, often involving the interaction of biologic, social, psychologic, economic, and other processes that may be nonlinear and adaptive and have other features of complex systems. There is therefore a need to push the boundaries of public health beyond single-factor data analysis and expand the capacity of research methodology to tackle real-world complexities. This article sets out a way to operationalize complex systems thinking in public health, with a particular focus on how epidemiologic methods and data can contribute towards this end. Our proposed framework comprises three core dimensions-patterns, mechanisms, and dynamics-along which complex systems may be conceptualized. These dimensions cover seven key features of complex systems-emergence, interactions, nonlinearity, interference, feedback loops, adaptation, and evolution. We relate this framework to examples of methods and data traditionally used in epidemiology. We conclude that systematic production of knowledge on complex health issues may benefit from: formulation of research questions and programs in terms of the core dimensions we identify, as a comprehensive way to capture crucial features of complex systems; integration of traditional epidemiologic methods with systems methodology such as computational simulation modeling; interdisciplinary work; and continued investment in a wide range of data types. We believe that the proposed framework can support the systematic production of knowledge on complex health problems, with the use of epidemiology and other disciplines. This will help us understand emergent health phenomena, identify vulnerable population groups, and detect leverage points for promoting public health.

(1) Background: In recent years, the consumption of sprouts, thanks to their high nutritional value, and the presence of bioactive compounds with antioxidant, antiviral and antibacterial properties, is becoming an increasingly widespread habit.

The experimental revolution in the social sciences is one of the most significant methodological shifts undergone by the field since the ‘quantitative revolution’ in the nineteenth century. One of the often valued features of social science experimentation is precisely the fact that there are (alleged) clear methodological rules regarding hypothesis testing that come from the methods of the natural sciences and from the methodology of RCTs in the biomedical sciences, and that allow for the adjudication among contentious causal claims. We examine critically this claim and argue that some current understandings of the practices that surround social science experimentation overestimate the degree to which experiments can actually fulfil this role as “objective” adjudicators, by neglecting the importance of shared background knowledge or assumptions and of consensus regarding the validity of the constructs involved in an experiment. We take issue with the way the distinction between internal and external validity is often used to comment on the inferential import of experiments, used both among practitioners and among philosophers of science. We describe the ways in which the more common (dichotomous) use of the internal/external distinction differs from Cook and Campbell’s original methodological project, in which construct validity and the four-fold validity typology were all important in assessing the inferential import of experiments. We argue that the current uses of the labels internal and external, as applied to experimental validity, help to encroach a simplistic view on the inferential import of experiments that, in turn, misrepresents their capacity to provide objective knowledge about the causal relations between variables.

This paper provides surface-clearance levels for 413 radionuclides for the normal reuse of objects leaving the controlled area of a nuclear facility. Four sets of surface-specific clearance levels are derived based on choices of dose coefficients (DCs) in probabilistic dose assessments using the SUrface DOse QUantification model (SUDOQU; van Dillen and van Dijk 2018 J. Radiol. Prot. 38 1147–203). The general dose criteria for clearance, extended with a suitable dose constraint for the concept of the representative person, are applied in the derivations. These clearance levels apply to the total of fixed and removable radioactive contamination on the surface of objects. The results are discussed in the context of conservatism of the exposure scenarios (parameters, DCs), and guidance is given on the selection and application of the values.

This article addresses the contributions of the literature on the new mechanistic philosophy of science for the scientific practice of model building in ecology. This is reflected in a one-to-one interdisciplinary collaboration between an ecologist and a philosopher of science during science-in-the-making. We argue that the identification, reconstruction and understanding of mechanisms is context-sensitive, and for this case study mechanistic modeling did not present a normative role but a heuristic one. We expect our study to provides useful epistemic tools for the improvement of empirically-riven work in the debates about mechanistic explanation of ecological phenomena.

This paper proposes a novel framework for the development of interventions in vulnerable populations. The framework combines a complex systems lens with syndemic theory. Whereas funding bodies, research organizations and reporting guidelines tend to encourage intervention research that (i) focuses on singular and predefined health outcomes, (ii) searches for generalizable cause-effect relationships, and (iii) aims to identify universally effective interventions, the paper suggests that a different direction is needed for addressing health inequities: We need to (i) start with exploratory analysis of population-level data, and (ii) invest in contextualized in-depth knowledge of the complex dynamics that produce health inequities in specific populations and settings, while we (iii) work with stakeholders at multiple levels to create change within systems. This paper proposes a novel framework for the development of interventions in vulnerable populations. The framework combines a complex systems lens with syndemic theory. Whereas funding bodies, research organizations and reporting guidelines tend to encourage intervention research that (i) focuses on singular and predefined health outcomes, (ii) searches for generalizable cause-effect relationships, and (iii) aims to identify universally effective interventions, the paper suggests that a different direction is needed for addressing health inequities: We need to (i) start with exploratory analysis of population-level data, and (ii) invest in contextualized in-depth knowledge of the complex dynamics that produce health inequities in specific populations and settings, while we (iii) work with stakeholders at multiple levels to create change within systems.

Le nuove tecnologie hanno cambiato e continuano a cambiare profondamente il nostro modo di vivere. Il continuo processo di adattamento al cambiamento tecnologico condiziona e modifica costantemente le nostre interazioni in tutti gli ambiti di vita. Non ultima la salute mentale e il lavoro in psicoterapia. Il presente lavoro si pone dunque come obiettivo quello di ritrarre lo stato dell'arte di un campo in continua evoluzione ed espansione. Se da un lato questi strumenti risultano essere un'importante opportunità, dall'altro la comunità scientifica ha cominciato a porre attenzione alla problematicità dell'utilizzo degli stessi, con particolare attenzione a Internet e ai dispositivi ad esso associati. Nello specifico, l'obiettivo è di approfondire la controversia che caratterizza la letteratura sull'uso della tecnologia in termini di vantaggi e svantaggi con un focus specifico sui fattori di rischio e di protezione oltre che un'analisi dettagliata degli effetti negativi a breve e lungo termine e degli elementi comuni negli interventi evidence-based nel trattamento dell'Internet addiction nell'infanzia e nell'adolescenza.

Epistemic diversity is the ability or possibility of producing diverse and rich epistemic apparati to make sense of the world around us. In this paper we discuss whether, and to what extent, different conceptions of knowledge—notably as ‘justified true belief’ and as ‘distributed and embodied cognition’—hinder or foster epistemic diversity. We then link this discussion to the widespread move in science and philosophy towards monolingual disciplinary environments. We argue that English, despite all appearance, is no Lingua Franca, and we give reasons why epistemic diversity is also deeply hindered is monolingual contexts. Finally, we sketch a proposal for multilingual academia where epistemic diversity is thereby fostered.

Background Loss-of-function variants in MID1 are the most common cause of Opitz G/BBB syndrome (OS). The interpretation of intronic variants affecting the splicing is a rising issue in OS. Methods Exon sequencing of a 2-year-old boy with OS showed that he was a carrier of the de novo c.1286-10G>T variant in MID1. In silico predictions and minigene assays explored the effect of the variant on splicing. The minigene approach was also applied to two previously identified MID1 c.864+1G>T and c.1285+1G>T variants. Results Minigene assay demonstrated that the c.1286-10G>T variant generated the inclusion of eight nucleotides that predicted generation of a frameshift. The c.864+1G>T and c.1285+1G>T variants resulted in an in-frame deletion predicted to generate a shorter MID1 protein. In hemizygous males, this allowed reclassification of all the identified variants from "of unknown significance" to "likely pathogenic." Conclusions Minigene assay supports functional effects from MID1 intronic variants. This paves the way to the introduction of similar second-tier investigations in the molecular diagnostics workflow of OS. Impact Causative intronic variants in are rarely investigated in Opitz syndrome. is not expressed in blood and mRNA studies are hardly accessible in routine diagnostics. Minigene assay is an alternative for assessing the effect of intronic variants on splicing. This is the first study characterizing the molecular consequences of three variants for diagnostic purposes and demonstrating the efficacy of minigene assays in supporting their clinical interpretation. Review of the criteria according to the American College of Medical Genetics reassessed all variants as likely pathogenic.

In this paper, we describe a practical and convenient method to include the contribution of the ingrowth of radioactive progeny in dose assessments of the corresponding parent nuclides. This method modifies the dose coefficients (DCs) of parent nuclides by adding weighted DCs of the corresponding daughter nuclides to them. Based on the decay kinetics of serial nuclear transformations, the progeny weighting factors, with values between 0 and 1, are derived by analysis of the time-integrated activity of each nuclide in the (branched) decay chain headed by a parent nuclide. Using the electronic, nuclear-decay database of Publication 107 of the International Commission on Radiological Protection (ICRP 2008), DC weighting factors for annual dose assessments are calculated for all daughter radionuclides in the decay chains and are tabulated in this paper. Weighting factors based on integration periods other than one year, ranging from 1 h–70 years, are also provided (see the supplementary material). With a priori established weighting factors, dose assessments become significantly simplified by considering the decay kinetics of only the parent nuclides and by applying the modified DCs. This ensures that the ingrowth of progeny is taken into account realistically. In some cases, one requires a conservative estimate of the dose, for instance when dealing with issues of the clearance of materials under regulatory control. Therefore, we adapted the weighting-factor method to derive conservative DC weighting factors for dose evaluations. These values are calculated for various integration periods and compared with those from an existing method adopted by the Euratom Article 31 Group of Experts and by the International Atomic Energy Agency. Identical progeny weighting factors are obtained for long-lived parent radionuclides, whereas for short-lived parent radionuclides, the new method can yield significantly larger values. For example, the weighting factor of I-131 (daughter of parent Te-131) increases from 0.002 to 1.0 based on an integration period of 1 year. The progeny DC weighting factors, derived based on nuclear transformations in exit-only decay chains, may not always be suitable for use in radiological dose evaluations. For instance, when environmental removal pathways are dominant, the application of these weighting factors may have its limitations. This paper, therefore, provides guidance on the proper selection and application of weighting factors.

(1) Background: Classic Ehlers-Danlos syndrome (cEDS) is a heritable connective tissue disorder characterized by joint hypermobility and skin hyperextensibility with atrophic scarring. Many cEDS individuals carry variants in either the COL5A1 or COL5A2 genes. Mosaicism is relatively common in heritable connective tissue disorders but is rare in EDS. In cEDS, a single example of presumed gonosomal mosaicism for a COL5A1 variant has been published to date. (2) Methods: An 8-year-old girl with cEDS was analyzed by next-generation sequencing (NGS). Segregation was performed by Sanger sequencing in her unaffected parents. In the father, the mosaicism of the variant was further analyzed by targeted NGS and droplet digital PCR (ddPCR) in the blood and by Sanger sequencing in other tissues. (3) Results: The NGS analysis revealed the novel germline heterozygous COL5A1 c.1369G>T, p.(Glu457*) variant in the proband. Sanger chromatogram of the father’s blood specimen suggested the presence of a low-level mosaicism for the COL5A1 variant, which was confirmed by NGS and estimated to be 4.8% by ddPCR. The mosaicism was also confirmed by Sanger sequencing in the father’s saliva, hair bulbs and nails. (4) Conclusions: We described the second case of cEDS caused by paternal gonosomal mosaicism in COL5A1. Parental mosaicism could be an issue in cEDS and, therefore, considered for appropriate genetic counseling.

Le molestie olfattive indotte da impianti di trattamento di acque reflue costituiscono un vero e proprio problema ambientale. In particolare, le emissioni odorigene derivanti dall’esercizio di impianti in zone turistiche sono considerate la principale causa di disturbo notato dalla popolazione esposta. La valutazione dell’impatto indotto può essere effettuata attraverso la misurazione degli odori, utilizzando un metodo analitico, sensoriale o misto. Il sensoriale, legato al “sensore umano” è causa di notevole incertezza. L’analitico-strumentale è in grado di identificare e quantificare solo la concentrazione dei composti chimici singoli o multipli ma non l’odore complessivo di una miscela. Pertanto, integrando entrambi i metodi, nel presente articolo si vuole mostrare l’applicazione di una procedura di tipo senso-strumentale (GC/MS con porta ODP). I risultati ottenuti in uno SWWTP hanno dimostrato l’applicabilità di tale procedura nel monitoraggio delle emissioni odorigene ed hanno permesso l’identificazione di 39 sostanze diverse di cui quasi la metà responsabili di disturbi olfattivi.

(1) Background: Classic Ehlers-Danlos syndrome (cEDS) is a heritable connective tissue disorder characterized by joint hypermobility and skin hyperextensibility with atrophic scarring. Many cEDS individuals carry variants in either the COL5A1 or COL5A2 genes. Mosaicism is relatively common in heritable connective tissue disorders but is rare in EDS. In cEDS, a single example of presumed gonosomal mosaicism for a COL5A1 variant has been published to date. (2) Methods: An 8-year-old girl with cEDS was analyzed by next-generation sequencing (NGS). Segregation was performed by Sanger sequencing in her unaffected parents. In the father, the mosaicism of the variant was further analyzed by targeted NGS and droplet digital PCR (ddPCR) in the blood and by Sanger sequencing in other tissues. (3) Results: The NGS analysis revealed the novel germline heterozygous COL5A1 c.1369G>T, p.(Glu457*) variant in the proband. Sanger chromatogram of the father’s blood specimen suggested the presence of a low-level mosaicism for the COL5A1 variant, which was confirmed by NGS and estimated to be 4.8% by ddPCR. The mosaicism was also confirmed by Sanger sequencing in the father’s saliva, hair bulbs and nails. (4) Conclusions: We described the second case of cEDS caused by paternal gonosomal mosaicism in COL5A1. Parental mosaicism could be an issue in cEDS and, therefore, considered for appropriate genetic counseling.

COVID-19 has revealed that science needs to learn how to better deal with the irreducible uncertainty that comes with global systemic risks as well as with the social responsibility of science towards the public good. Further developing the epistemological principles of new theories and experimental practices, alternative investigative pathways and communication, and diverse voices can be an important contribution of history and philosophy of science and of science studies to ongoing transformations of the scientific enterprise.

There is no unified theory of causality in the sciences and in philosophy. In this paper, we focus on a particular framework, called structural causal modelling (SCM), as one possible perspective in quantitative social science research. We explain how this methodology provides a fruitful basis for causal analysis in social research, for hypothesising, modelling, and testing explanatory mechanisms. This framework is not based on a system of equations, but on an analysis of multivariate distributions. In particular, the modelling stage is essentially distribution-free. Adopting an SCM approach means endorsing a particular view on modelling in general (the hypothetico-deductive methodology), and a specific stance on exogeneity (namely as a condition of separability of inference), on the one hand, and in interpreting marginal–conditional decompositions (namely as mechanisms), on the other hand.

This article provides a systematic and pluralistic theory of causation that fits the kind of reasoning commonly found in mixed methods research. It encompasses a variety of causal concepts, notions, approaches, and methods. Each instantiation of the theory is like a mosaic, where the image appears when the tiles are appropriately displayed. This means that researchers should carefully construct a causal mosaic for each research study, articulating what is causally relevant given their particular research questions, purposes, contexts, methods, methodologies, paradigms, and resources. Our theory includes 11 propositions that can guide researchers addressing causation.

This paper deals with the fatigue failure of composite coupon characterized by circular hole and subjected to tensile cyclic loading conditions. A limited sensitivity analysis has been performed to study the onset and propagation of intralaminar damages, in terms of fibers and matrix failure. The residual strength material properties degradation model, proposed by Shokrieh and Lessard, has been implemented in the FEM code ANSYS Mechanical and employed to study the damages induced by stress concentrations and assess the effects of the stacking sequence and the geometrical parameters on the fatigue damage.

La contaminazione delle acque sotterranee, causata soprattutto da pratiche inadeguate di smaltimento rifiuti, e un problema ormai diffuso e in crescita. L’inquinamento di queste acque spesso si traduce in problemi legati all’approvvigionamento idrico e di conseguenza in rischi significativi per la salute umana. E importante, dunque, prevenire la contaminazione e li dove non e possibile attuare un’adeguata tecnica di bonifica. Il pump-and-treat (PT l'obiettivo e quello di valutarne l’efficacia attraverso un caso studio nel sud dell’Arizona, i cui risultati sono rappresentati da un set di dati storici corrispondenti a 23 anni di funzionamento di un sistema che inizialmente e solo P&T e successivamente e accompagnato da altre due tecniche di bonifica .

Ambient particulate matter is the environmental factor with the highest contribution to global disease burden and mortality. Open questions remain regarding causality at low doses and the effects of specific pollutants. Establishing causality in regards to air pollution is methodologically challenging, affecting the establishment of regulatory policies. In an effort to address this problem, we suggest combining the concept of the exposome with the Meet-in-the-Middle approach (MITM). This approach consists of measuring molecular fingerprints and relating them retrospectively to measurements of external exposure and prospectively to a health outcome. Markers robustly associated with both ends of the exposure-to-disease continuum, validate a causal hypothesis5. In the context of carcinogenesis, this approach allows establishing the relationship between the middle-to-outcome nature of the hallmarks of cancer with the bottom-to-middle approaches of the key characteristics of carcinogens. We recently demonstrated proof of principle of this approach, by investigating the temporal sequence of hallmarks of cancer from the point of view of pathological specimens of cancer (branched mutational spectra), and then by considering the key characteristics of the carcinogen, benzo(a)pyrene. The main cancer pathways affected follow a generally common sequence: resisting cell death, insensitivity to anti-growth signals, sustained proliferation (almost simultaneous), deregulated energetics, replicative immortality, and activation of invasion and metastasis. Angiogenesis and avoiding immune destruction display a varying position in the above sequence. At the same time, “key characteristics” of BaP were found associated with most hallmarks of cancer, supporting its carcinogenicity. A MITM approach, using exposomic evidence, is a promising approach that can successfully address causality concerns in regards to air-pollution toxicology and the need for regulatory policies. Key messages Investigation of tumour mutational spectra and of the mechanisms of action of a carcinogen, reveals an overlap between the hallmarks of cancer and the key characteristics of the carcinogen. This investigation provides proof of principle that the exposome/meet-in-the-middle approach can address concerns in air-pollution toxicology and provide evidence to support regulatory policies.

This article deals with the role of time in causal models in the social sciences. The aim is to underline the importance of time-sensitive causal models, in contrast to time-free models. The relation between time and causality is important, though a complex one, as the debates in the philosophy of science show. In particular, an outstanding issue is whether one can derive causal ordering from time ordering. The article examines how time is taken into account in demography and in economics as examples of social sciences in which considerations about time may diverge. We then present structural causal modeling as a modeling strategy that, while not essentially based on temporal information, can incorporate it in a more or less explicit way. In particular, we argue that temporal information is useful to the extent that it is placed in a correct causal structure, thus further corroborating the causal mechanism or generative process explaining the phenomenon under consideration. Despite the fact that the causal ordering of variables is more relevant than the temporal order for explanatory purposes, in establishing causal ordering the researcher should nevertheless take into account the time-patterns of causes and effects, as these are often episodes rather than single events. For this reason in particular, it is time to put time at the core of our causal models.

Technologies have always been bearers of profound changes in science, society, and any other aspect of life. The latest technological revolution—the digital revolution—is no exception in this respect. This paper presents the revolution brought about by digital technologies through the lenses of a specific approach: the philosophy of information. It is argued that the adoption of an informational approach helps avoiding utopian or dystopian approaches to (digital) technology, both expressions of technological determinism. Such an approach provides a conceptual framework able to address the ethical challenges that digital technologies pose, without getting stuck in the dichotomous thinking of technological determinism, and to bring together ethics, ontology, and epistemology into a coherent account.

The advantage of examining causality from the perspective of modelling is thus that it puts us naturally closer to the practice of the sciences. This means being able to set up an interdisciplinary dialogue that contrasts and compares modelling practices in different fields, say economics and biology, medicine and statistics, climate change and physics. It also means that it helps philosophers looking for questions that go beyond the narrow ‘what-is-causality’ or ‘what-are-relata’ and thus puts causality right at the centre of a complex crossroad: epistemology/methodology, metaphysics, politics/ethics. This special issue collects nine papers that touch upon various scientific fields, from system biology to medicine to quantum mechanics to economics, and different questions, from explanation and prediction to the role of both true and false assumptions in modelling.

L’impulsivita e un tratto di personalita caratterizzato da una predisposizione a emettere azioni rapide e spesso premature, senza appropriate considerazioni sulle ripercussioni future. Recenti sviluppi nell’ambito delle neuroscienze hanno evidenziato la multicomponenzialita dell’impulsivita distinguendo l’impulsivita motoria (l’inabilita a frenare una risposta motoria impellente), dall’impulsivita decisionale (preferire ricompense immedia- te e piccole a fronte di ricompense piu consistenti ma ritardate nel tempo) e dall’incapacita a mantenere il focus attentivo (attenzione sostenuta). Ciascuna di queste componenti e caratterizzata da specifici correlati neurali e risponde a trattamenti farmacologici ben precisi. Inoltre, dall’analisi fattoriale condotta sulla Barratt Impulsiveness Scale (BIS), il questionario self report piu utilizzato in clinica per misurare l’impulsivita, e emersa la pre- senza delle tre sottocomponenti. In tale articolo definiremo le tre sottocomponenti, descrivendo i diversi strumenti di laboratorio utilizzati per misurarle e, attraverso un’attenta ana- lisi della letteratura, andremo ad analizzare tali costrutti nel DDAI e nel DUS. Termineremo con una breve rassegna delle tecniche utilizzate nelle terapie cognitivo-comportamentali ad oggi disponibili che possano aiutare il terapeuta e il paziente a gestire i diversi tipi di impulsivita.