Micrurus ruatanus

Number of Pages: 2Integrative BiologyGeological Science

MPS - Decision Support System for Multiobjective Project Scheduling

The report presents a decision support system (DSS) for multiobjective project scheduling under multiple-category resource constraints. It handles quite a general class of nonpreemptive scheduling problems with renewable, nonrenewable and doubly-constrained resources, multiple performing modes of activities, precedence constraints in the form of an activity network and multiple project performance criteria of time and cost type. The DSS has been implemented on a microcomputer compatible with IBM PC, and called MPS. It is based on three kinds of heuristics: parallel priority rules, simulated annealing and branch-and-bound. The last algorithm can even yield exact solutions when sufficient processing time is available. Some parts of the MPS are interactive, in particular, the search for a best compromise schedule. Graphical facilities enable a thorough evaluation of feasible schedules. The report starts with a methodological guide presenting the problem formulation and the three heuristics. Then, the general scheme of the MPS is given together with an executive guide. An expanding menu and all its options are described and illustrated with a simple example. The last part presents a real problem solving consisting in scheduling 40 farm activities

Rough set and rule-based multicriteria decision aiding

The aim of multicriteria decision aiding is to give the decision maker a recommendation concerning a set of objects evaluated from multiple points of view called criteria. Since a rational decision maker acts with respect to his/her value system, in order to recommend the most-preferred decision, one must identify decision maker's preferences. In this paper, we focus on preference discovery from data concerning some past decisions of the decision maker. We consider the preference model in the form of a set of "if..., then..." decision rules discovered from the data by inductive learning. To structure the data prior to induction of rules, we use the Dominance-based Rough Set Approach (DRSA). DRSA is a methodology for reasoning about data, which handles ordinal evaluations of objects on considered criteria and monotonic relationships between these evaluations and the decision. We review applications of DRSA to a large variety of multicriteria decision problems

Robust spike timing in an excitable cell with delayed feedback

This is the author accepted manuscript. The final version is available from the Royal Society via the DOI in this recordData and materials availability: Data and computer code related to the mathematical model and dynamic clamp experiments can be downloaded from the GitHub repository https://github.com/SlowinskiPiotr/MorrisLecarDDEThe initiation and regeneration of pulsatile activity is a ubiquitous feature observed in excitable systems with delayed feedback. Here, we demonstrate this phenomenon in a real biological cell. We establish a critical role of the delay resulting from the finite propagation speed of electrical impulses on the emergence of persistent multiple-spike patterns. We predict the co-existence of a number of such patterns in a mathematical model and use a biological cell subject to dynamic clamp to confirm our predictions in a living mammalian system. Given the general nature of our mathematical model and experimental system, we believe that our results capture key hallmarks of physiological excitability that are fundamental to information processing.Medical Research Council (MRC)Wellcome TrustEngineering and Physical Sciences Research Council (EPSRC)Technical University of Munich – Institute for Advanced StudyRoyal Societ

A feasibility study using movement and perspective-taking as a diagnostic aid for psychosis

This is the final version.STUDY SUMMARY Study Title: A feasibility study using movement and perspective-taking as a diagnostic aid for psychosis. Internal ref. no. (or short title): Movement and perspective-taking as a diagnostic aid for psychosis. Study Design: Feasibility study. Study Participants: People accepted for an assessment for psychosis or risk of developing psychosis and people with first episode psychosis or being at risk of developing psychosis. Planned Size of Sample (if applicable): 100 service users and 50 controls. Follow up duration (if applicable): N/A. Planned Study Period: 1/3/18 - 31/8/18. Research Question/Aim(s): 1/ We want to investigate accuracy of classifiers based on movement and coordination during an interaction with a computer avatar in people who are considered at risk of psychosis or who have a newly diagnosed psychotic disorder, compared to healthy controls and those who do not have psychosis or a future risk of psychosis. 2/ We want to investigate feasibility of this diagnostic procedure in a clinical setting and gather opinions about the task and the interface from the service users and clinicians

Evidence for Quantum Interference in SAMs of Arylethynylene Thiolates in Tunneling Junctions with Eutectic Ga-In (EGaIn) Top-Contacts

This paper compares the current density (J) versus applied bias (V) of self-assembled monolayers (SAMs) of three different ethynylthiophenol-functionalized anthracene derivatives of approximately the same thickness with linear-conjugation (AC), cross-conjugation (AQ), and broken-conjugation (AH) using liquid eutectic Ga-In (EGaIn) supporting a native skin (~1 nm thick) of Ga2O3 as a nondamaging, conformal top-contact. This skin imparts non-Newtonian rheological properties that distinguish EGaIn from other top-contacts; however, it may also have limited the maximum values of J observed for AC. The measured values of J for AH and AQ are not significantly different (J ≈ 10-1 A/cm2 at V = 0.4 V). For AC, however, J is 1 (using log averages) or 2 (using Gaussian fits) orders of magnitude higher than for AH and AQ. These values are in good qualitative agreement with gDFTB calculations on single AC, AQ, and AH molecules chemisorbed between Au contacts that predict currents, I, that are 2 orders of magnitude higher for AC than for AH at 0 < |V| < 0.4 V. The calculations predict a higher value of I for AQ than for AH; however, the magnitude is highly dependent on the position of the Fermi energy, which cannot be calculated precisely. In this sense, the theoretical predictions and experimental conclusions agree that linearly conjugated AC is significantly more conductive than either cross-conjugated AQ or broken conjugate AH and that AQ and AH cannot necessarily be easily differentiated from each other. These observations are ascribed to quantum interference effects. The agreement between the theoretical predictions on single molecules and the measurements on SAMs suggest that molecule-molecule interactions do not play a significant role in the transport properties of AC, AQ, and AH.

Artificial Intelligence and Intellectual Property Law - Position Statement of the Max Planck Institute for Innovation and Competition of 9 April 2021 on the Current Debate

This Position Statement presents a broad overview of issues arising at the intersection of AI and IP law based on the work of the Max Planck Institute for Innovation and Competition research group on Regulation of the Digital Economy. While the analysis is approached mainly from a perspective de lege lata, it also identifies questions which require further reflection de lege ferenda supported by in-depth interdisciplinary research. The scope is confined to substantive European IP law, in particular, as regards copyright, patents, designs, databases and trade secrets. Specific AI-related issues are mapped out around the core questions of IP law, namely, the eligibility for protection under the respective IP regimes, allocation of rights and the scope of protection. The structure of the analysis reflects three key components of AI: inputs required for the development of AI systems, AI as a process and the output of AI applications. Overall, it is emphasised that, while recent legal and policy discussions have mostly focused on AI-aided and AI-generated output, a more holistic view that accounts for the role of IP law across the AI innovation cycle is indispensable