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Extracorporeal life support systems (ECLS) are life-sustaining measures for severe cardiovascular diseases, serving as bridging treatment either until cardiovascular function is restored or alternative treatment, such as heart transplantation or the implantation of permanent ventricular assist devices is performed. Given the insufficient evidence and frequent urgency of implantation without initial patient consent, the ethical challenges and psychological burden for patients, relatives and the interprofessional intensive care team are significant. As with any treatment, an appropriate therapeutic goal for ECLS treatment based on the indications and patient informed consent is mandatory. In order to integrate the necessary ethical considerations into everyday clinical practice, a structured algorithm for handling ECLS is proposed here, which takes ethical aspects into due account. [ABSTRACT FROM AUTHOR]

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Copyright of Informationswissenschaft: Theorie, Methode & Praxis / Sciences de l’information: Théorie, Méthode & Pratique is the property of University Library of Bern and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Big data and artificial intelligence are buzzwords that everyone is talking about and yet always provide a touch of science fiction to the scenery. What is the status of these topics in anesthesia? Are the first robots already rolling through the corridors while doctors are getting bored as all the work has been done? Spoiler alert! We are still far away from achieving this. Initially, paper charts and analogue notes stand in the way of comprehensive digitization. Source systems need to be merged and data standardized, harmonized and validated. Therefore, the friendly android that is rolling towards us, waving and holding a freshly brewed cup of coffee in our thoughts will have to wait; however, a glimpse of the future is already evident in some clinics and the first promising developments are already showing what could be the standard tomorrow. Learning algorithms calculate the length of stay individually for each patient in the intensive care unit (ICU), reducing negative consequences such as readmission and mortality. The field of ultrasound technology for regional anesthesia and closed-loop anesthesia systems is also demonstrating the benefits of artificial intelligence (AI)-assisted technologies in practice. The efforts are diverse and ambitious but they repeatedly collide with privacy challenges and significant capital expenditure, which weigh heavily on an already financially strained healthcare system; however, anyone who listens carefully to the medical staff knows that robots are not what they would expect and the buzzwords big data and artificial intelligence might be less science fiction than initially assumed. [ABSTRACT FROM AUTHOR]

In this paper methods and algorithms are examined for solving one important problem of transport logistics, namely formation of roadmap. The proposed mathematical model is based on the well-known multi-depot heterogeneous vehicle routing problem with time windows algorithm. Modifications of the model provide additional conditions and restrictions. Algorithmic support of information transport system in an enterprise is connected with features of the vehicle routing problem. The suggested solution is based on modified Clarke and Wright Algorithm and Variable Neighborhood Search. The risk on the roads and the cost of toll roads are calculated, too. [ABSTRACT FROM AUTHOR]

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Artificial Intelligence (AI) has been become a household expression, especially in the past couple of years thanks to Google's AI Computer program AlphaGo defeating a couple of world-class Go masters from Korea and China. In recent years, machines have surpassed humans in the performance of certain specific tasks, such as some aspects of image recognition. Although it is unlikely that machines will exhibit broadly-applicable intelligence comparable to or exceeding that of humans in the near future, experts forecast that rapid progress in the field of specialized AI will continue, with machines reaching and exceeding human performance on an increasing number of tasks. Simultaneous interpreting, being among the most complex of human cognitive/linguistic activities, with all the associated ergonomic elements, has been discussed profusely as one of the most likely to be taken over by AI in a couple of years. Given that so much has to be there simultaneously, i. e. anticipation, restoration of the implicit-explicit balance, and communicative re-packaging ('re-ostension'1) of the discourse, simultaneous interpreting (SI) has yet to be fully explained, not the least the rich pragmatic information guiding the construction of the appropriate contexts and the speaker's underlying intentionalities, which is the centre piece of SI, given the illusive nature of meaning assembly could be quite beyond even the most intelligent robots. This paper discusses what SI is like, how AI has evolved, and concludes that AI is dramatically changing the profession, but given the rulebased nature of AI driven by data and algorithms, human intelligence as possessed by SI practitioners is still irreplaceable. SI practitioners can harness cutting-edge technologies such as AI to do a better job, which bears significance for trainers and would be SIs. [ABSTRACT FROM AUTHOR]

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Algorithms have become an indispensable part of everyday business life. They not only screen markets within a very short time, but also influence the market behavior of companies. In the age of ChatGPT and “deep learning algorithms”, many intriguing questions arise: Can algorithms be “cartel promoters”, “cartel facilitators” or even “cartel initiators”? Is the antitrust concept of “concurrence of wills” still up-to-date? When can the “conduct” of algorithms be attributed to a company? This practice-oriented article is intended to shed light on problematic constellations on the basis of a number of cases. [ABSTRACT FROM AUTHOR]

The treatment of the severely injured is, just as the injury severity and combinations, often highly complex and leaves little leeway for delay, dissent or even error. In order to reduce this to a minimum, trained emergency room teams in addition to optimal technical and structural prerequisites are necessary. This must function in an interdisciplinary fashion according to fixed consensus algorithms which are known to all team members and have been agreed by all participants. The White Paper on treatment of the severely injured of the German Society of Trauma Surgery (DGU) and the recently published S3 guidelines offer evidence-based recommendations on the structural, technical, organizational and personnel prerequisites. [ABSTRACT FROM AUTHOR]

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The symmetry of molecules can be determined, when their structure is known, using schemes of questions (algorithms), by means of which the existence of certain elements of symmetry is checked. In this paper, a new algorithm is presented, which renders feasible the prompt determination of symmetry point groups and visualizes relations between different types of symmetry. The application of the algorithm is demonstrated by means of a graphic scheme and a Pascal computer version. [ABSTRACT FROM AUTHOR]

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The rapidly growing academic and public attention to algorithmic-selection applications such as search engines and social media is indicative of their alleged great social relevance and impact on daily life in digital societies. To substantiate these claims, this paper investigates the hitherto little explored subjective relevance that Internet users assign to algorithmic-selection applications in everyday life. A representative online survey of Internet users comparatively reveals the relevance that users ascribe to algorithmic-selection applications and to their online and offline alternatives in five selected life domains: political and social orientation, entertainment, commercial transactions, socializing and health. The results show that people assign a relatively low relevance to algorithmic-selection applications compared to offline alternatives across the five life domains. The findings vary greatly by age and education. Altogether, such outcomes complement and qualify assessments of the social impact of algorithms that are primarily and often solely based on usage data and theoretical considerations.

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Background: Fluid resuscitation after severe burns remains a challenging task particularly in the preclinical and early clinical phases. To facilitate volume substitution after burn trauma several formulae have been published and evaluated, nevertheless, the optimal formula has not yet been identified. Methods: A systematic PubMed search was performed to identify published formulae for fluid resuscitation after severe burns. The search terms 'burn', 'thermal', 'treatment', 'therapy' or 'resuscitation', 'fluid', 'formula' and 'adult', 'pediatric' or 'paediatric' were used in various combinations. Analysis was limited to the period from 01.01.1950 to 30.06.2010 and database entries in PubMed (http://www.pubmed.com). Additionally, references cited in the papers were analyzed and relevant publications were also included. Publications and formulae were assessed and classified by two independent investigators. Results: Within the specified time frame eight publications (five original contributions and three book chapters) were identified of which three formulae recommended colloid solutions, four recommended electrolyte solutions and one suggested hypertonic solutions within the first 24 h for fluid resuscitation. Only one formula specifically dealt with fluid resuscitation in infants. Conclusion: The identified formulae led to sometimes strikingly diverse calculations of resuscitation fluid volumes. Therefore their use should be monitored closely and clinical values included. Urine output is a well established individual parameter. Use of colloid and hypertonic solutions leads to a reduced total fluid volume but is still controversially discussed. [ABSTRACT FROM AUTHOR]

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The article presents information related to the periodical that focuses on mathematics. Topics discussed include declaration on equal opportunities, diversity and scientific collaboration; new trends in algorithmic randomness and computable analysis; nonlocal conservation laws; mathematical models; and mathematical analysis and quantum systems.

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This paper discusses various legal challenges of the “digitisation of the single market”. The question arises to which extent the current regulatory framework appears suitable to deal with the presented challenges of digitisation and where additional regulation is required. In the field of autonomous decision-making by AI, we identified the most pressing need for new regulation. While the EU (and increasingly Austria, as well) is aware of this need, regulation to date remains scarce. Though the EU legislator has already taken specific precautions for the use of algorithms in the GDPR, such regulatory approaches are missing in most other fields of law. In contrast to this, antitrust law and product liability law already appear to be well suited to meet the challenges posed by digitisation. This is especially true for product liability law, which is in principle apt to cover the specific challenges of the convergence of software and hardware in smart products. However, uncertainty about its applicability to incorporeal goods would make clarification of current product liability legislation advisable – a view shared by the European Commission. Two more fields very recently received some legislative attention due to the changing needs of a digital society: the postal sector on the one hand, and e-government on the other hand. In both fields, new legislation – tellingly in the form of (partially) directly applicable regulations – has recently been passed by the EU – a sharp contrast to the case of self-learning AI. However, while the integration of the new regulation on cross-border parcel delivery will probably not pose major challenges for domestic markets, the implementation of the Single Digital Gateway will raise serious organisational and legal challenges for national administrations (especially when taking into account the limited success of the previous related initiative on the points of single contact under the Services Directive).

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