1,720,952 research outputs found
Stillbirths at Term : Case Control Study of Risk Factors, Growth Status and Placental Histology
Full text linkObjective: To investigate the proportion of stillbirths at term associated with abnormal growth using customized birth weight percentiles and to compare histological placental findings both in underweight stillborn fetuses and in live births. Methods: A retrospective case-control study of 150 singleton term stillbirths. The livebirth control groups included 586 cases of low-risk pregnancies and 153 late fetal growth restriction fetuses. Stillbirths and livebirths from low-risk pregnancies were classified using customized standards for fetal weight at birth, as adequate for gestational age (AGA; 10-90th percentile), small (SGA; 90th percentile). Placental characteristics in stillbirth were compared with those from livebirths using four categories: inflammation, disruptive, obstructive and adaptive lesions. Results: There was a higher rate of SGA (26% vs 6%, p<0.001) and LGA fetuses (10.6% vs 5.6%, p<0.05) in the stillbirth group. Among stillbirth fetuses, almost half of the SGA were very low birthweight (≤3°percentile) (12% vs 0.3%, p<0.001). The disruptive (7.3% vs 0.17%; p<0.001), obstructive (54.6% vs 7.5%;p<0.001) and adaptive (46.6% vs 35.8%;p<0.001) findings were significantly more common in than in livebirth-low risk. Placental characteristics of AGA and SGA stillbirth were compared with those of AGA and FGR livebirth. In stillbirths-SGA we found a higher number of disruptive (12.8% vs 0%; p<0.001), obstructive (58.9% vs 23.5%;p<0.001) and adaptive lesions (56.4% vs 49%; p 0.47) than in livebirth-FGR. Conclusion: The assessment of fetal weight with customized curves can identify fetuses which have not reached their genetically determined growth potential and are therefore at risk for adverse outcomes. Placental evaluation in stillbirths can reveal chronic histological signs that might be useful to clinical assessment, especially in underweight fetuses. © 2016 Mecacci et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
The First Commentary on L. S. Vygotsky’s Papers at the II All-Russian Congress of Psychoneurology in Petrograd (January 1924)
No full textAt the Second All-Russian Congress on Psychoneurology in Petrograd (January 1924), Vygotsky delivered three papers. The first paper (“Methodology of Reflexological and Psychological Research”), was printed separately, but the text of the other two reports (“How Psychology Should Be Taught Now” and “Results of a Questionnaire on the Moods of Students of the Graduating Classes of the Gomel Schools in 1923”) has not survived. A brief account of these two reports, which appeared in the magazine Krasnaya Nov’ in 1924, is reprinted here for the first time. The author was the revolutionary M.I. Ginzburg (1877-1940), a researcher at the Moscow Psychological Institute in the mid-1920s. He wrote under the pseudonym G. Dayan. Ginzburg-Dayan was severely criticised in 1935 on charges of Trotskyism.</p
A Conceptual Control System Description of Cooperative and Automated Driving in Mixed Urban Traffic With Meaningful Human Control for Design and Evaluation
No full textThe introduction of automated vehicles means that some or all operational control over these vehicles is diverted away from a human driver to a technological system. The concept of Meaningful Human Control (MHC) was derived to address control issues over automated systems, allowing a system to explicitly consider human intentions and reasons. Applying MHC to technological systems, such as automated driving is a real challenge, and the main focus of this article. An approach with mathematical elaboration has been developed that offers a first quantifiable operationalisation of MHC for the traffic domain and for use with automated vehicles. A major contribution lies in the taxonomification of control for MHC in the broader traffic environment, including consideration of the driver, the vehicle, the traffic environment, considering behaviour, moral standards and societal values, which are considered in a case study. The demonstration case shows the validity of the developed approach for an automated vehicle overtaking a cyclist on an urban street. This article is one of the first to operationalise MHC to such a level of detail and opens the door to further development of the concept for technological implementation.Transport and Plannin
A practitioner’s View of Driver Training for automated driving From Driving Examiners: A Focus group Discussion
No full textAs automated vehicles become increasingly common on the road, the call for an appropriate preparation for its drivers is becoming more urgent. Expert opinions and insights have been acquired via a focus group discussion with eleven Dutch driving examiners to assist in inventorying what types of preparations are needed. The concept of meaningful human control (MHC) as an integral part of the discussion lead to consensual findings regarding ADAS functionality and the drivers’ tasks, as well as discussion topics on driver training and levels of automation. It was concluded to have more research into human factors to safeguard proper control over automated vehicles.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and PlanningEthics & Philosophy of Technolog
Machine Learning Against Terrorism: How Big Data Collection and Analysis Influences the Privacy-Security Dilemma
No full textRapid advancements in machine learning techniques allow mass surveillance to be applied on larger scales and utilize more and more personal data. These developments demand reconsideration of the privacy-security dilemma, which describes the tradeoffs between national security interests and individual privacy concerns. By investigating mass surveillance techniques that use bulk data collection and machine learning algorithms, we show why these methods are unlikely to pinpoint terrorists in order to prevent attacks. The diverse characteristics of terrorist attacks—especially when considering lone-wolf terrorism—lead to irregular and isolated (digital) footprints. The irregularity of data affects the accuracy of machine learning algorithms and the mass surveillance that depends on them which can be explained by three kinds of known problems encountered in machine learning theory: class imbalance, the curse of dimensionality, and spurious correlations. Proponents of mass surveillance often invoke the distinction between collecting data and metadata, in which the latter is understood as a lesser breach of privacy. Their arguments commonly overlook the ambiguity in the definitions of data and metadata and ignore the ability of machine learning techniques to infer the former from the latter. Given the sparsity of datasets used for machine learning in counterterrorism and the privacy risks attendant with bulk data collection, policymakers and other relevant stakeholders should critically re-evaluate the likelihood of success of the algorithms and the collection of data on which they depend.Numerical AnalysisShip Hydromechanics and StructuresData-Intensive System
Gaps in the control of automated vehicles on roads
No full textIncreased on-road testing and market availability of partially automated vehicles (AV) offers researchers and developers the opportunity to evaluate the AV’s performance. The occurrence of new types of accidents involving AV’s has sparked questions in regard to who is actually in control over and responsible for AV control. In this contribution, we suggest a potential discrepancy in AV control with the review of recently documented accidents involving AV’s. The identification of a gap in control is performed using a recently formulated moral philosophical framework of Meaningful Human Control (MHC). This shows a discrepancy between the attribution of responsibility and the ability of a human to fulfil the role assigned to them. While a gap in control is not evident from the viewpoint of operational control, it requires the more intricate concept of MHC to expose it. Recommendations are further made that AV developers and vehicle approval authorities should consider control from a MHC perspective to avoid future gaps in control with the resulting consequences.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and PlanningEthics & Philosophy of Technolog
Full platoon control in Truck Platooning: A Meaningful Human Control perspective
No full textTruck platooning is a form of vehicle automation and cooperation that is leading the way for cooperative and automated vehicle implementation. However, much is still unknown about the effects and potential dangers of many situations in regard to cooperative control of these platoons. In this contribution, we discuss many of the challenges in regard to full platoon control, we give concepts that can answer some of the questions and make recommendations on how full platoon control should be considered by truck manufactures, ADS software developers and policy makers. A main concept that is applied is that of Meaningful Human Control (MHC). We furthermore consider driver 'reasons', both distal and proximal, to identify correct chains of MHC. We conclude that each part of a system should be responsive to the maximum amount of relevant reasons available and the availability of relevant reasons should be maximized to obtain sufficient MHC.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and PlanningEthics & Philosophy of Technolog
Four responsibility gaps with artificial intelligence: Why they matter and how to address them
Full text linkThe notion of "responsibility gap" with artificial intelligence (AI) was originally introduced in the philosophical debate to indicate the concern that "learning automata" may make more difficult or impossible to attribute moral culpability to persons for untoward events. Building on literature in moral and legal philosophy, and ethics of technology, the paper proposes a broader and more comprehensive analysis of the responsibility gap. The responsibility gap, it is argued, is not one problem but a set of at least four interconnected problems - gaps in culpability, moral and public accountability, active responsibility - caused by different sources, some technical, other organisational, legal, ethical, and societal. Responsibility gaps may also happen with non-learning systems. The paper clarifies which aspect of AI may cause which gap in which form of responsibility, and why each of these gaps matter. It proposes a critical review of partial and non-satisfactory attempts to address the responsibility gap: those which present it as a new and intractable problem ("fatalism"), those which dismiss it as a false problem ("deflationism"), and those which reduce it to only one of its dimensions or sources and/or present it as a problem that can be solved by simply introducing new technical and/or legal tools ("solutionism"). The paper also outlines a more comprehensive approach to address the responsibility gaps with AI in their entirety, based on the idea of designing socio-technical systems for "meaningful human control", that is systems aligned with the relevant human reasons and capacities
Meaningful human control as reason-responsiveness: the case of dual-mode vehicles
No full textIn this paper, in line with the general framework of value-sensitive design, we aim to operationalize the general concept of “Meaningful Human Control” (MHC) in order to pave the way for its translation into more specific design requirements. In particular, we focus on the operationalization of the first of the two conditions (Santoni de Sio and Van den Hoven 2018) investigated: the so-called ‘tracking’ condition. Our investigation is led in relation to one specific subcase of automated system: dual-mode driving systems (e.g. Tesla ‘autopilot’). First, we connect and compare meaningful human control with a concept of control very popular in engineering and traffic psychology (Michon 1985), and we explain to what extent tracking resembles and differs from it. This will help clarifying the extent to which the idea of meaningful human control is connected to, but also goes beyond, current notions of control in engineering and psychology. Second, we take the systematic analysis of practical reasoning as traditionally presented in the philosophy of human action (Anscombe, Bratman, Mele) and we adapt it to offer a general framework where different types of reasons and agents are identified according to their relation to an automated system’s behaviour. This framework is meant to help explaining what reasons and what agents (should) play a role in controlling a given system, thereby enabling policy makers to produce usable guidelines and engineers to design systems that properly respond to selected human reasons. In the final part, we discuss a practical example of how our framework could be employed in designing automated driving systems.Ethics & Philosophy of Technolog
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