26,641 research outputs found

    Rank-based linkage I: triplet comparisons and oriented simplicial complexes

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    Rank-based linkage is a new tool for summarizing a collection SS of objects according to their relationships. These objects are not mapped to vectors, and ``similarity'' between objects need be neither numerical nor symmetrical. All an object needs to do is rank nearby objects by similarity to itself, using a Comparator which is transitive, but need not be consistent with any metric on the whole set. Call this a ranking system on SS. Rank-based linkage is applied to the KK-nearest neighbor digraph derived from a ranking system. Computations occur on a 2-dimensional abstract oriented simplicial complex whose faces are among the points, edges, and triangles of the line graph of the undirected KK-nearest neighbor graph on SS. In SK2|S| K^2 steps it builds an edge-weighted linkage graph (S,L,σ)(S, \mathcal{L}, \sigma) where σ({x,y})\sigma(\{x, y\}) is called the in-sway between objects xx and yy. Take Lt\mathcal{L}_t to be the links whose in-sway is at least tt, and partition SS into components of the graph (S,Lt)(S, \mathcal{L}_t), for varying tt. Rank-based linkage is a functor from a category of out-ordered digraphs to a category of partitioned sets, with the practical consequence that augmenting the set of objects in a rank-respectful way gives a fresh clustering which does not ``rip apart`` the previous one. The same holds for single linkage clustering in the metric space context, but not for typical optimization-based methods. Open combinatorial problems are presented in the last section.Comment: 37 pages, 12 figure

    ENABLING EFFICIENT FLEET COMPOSITION SELECTION THROUGH THE DEVELOPMENT OF A RANK HEURISTIC FOR A BRANCH AND BOUND METHOD

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    In the foreseeable future, autonomous mobile robots (AMRs) will become a key enabler for increasing productivity and flexibility in material handling in warehousing facilities, distribution centers and manufacturing systems. The objective of this research is to develop and validate parametric models of AMRs, develop ranking heuristic using a physics-based algorithm within the framework of the Branch and Bound method, integrate the ranking algorithm into a Fleet Composition Optimization (FCO) tool, and finally conduct simulations under various scenarios to verify the suitability and robustness of the developed tool in a factory equipped with AMRs. Kinematic-based equations are used for computing both energy and time consumption. Multivariate linear regression, a data-driven method, is used for designing the ranking heuristic. The results indicate that the unique physical structures and parameters of each robot are the main factors contributing to differences in energy and time consumption. improvement on reducing computation time was achieved by comparing heuristic-based search and non-heuristic-based search. This research is expected to significantly improve the current nested fleet composition optimization tool by reducing computation time without sacrificing optimality. From a practical perspective, greater efficiency in reducing energy and time costs can be achieved.Ford Motor CompanyNo embargoAcademic Major: Aerospace Engineerin

    Identifizierung prädiktiver und prognostischer Biomarker in unterschiedlichen Tumorkompartimenten des ösophagealen Adenokarzinoms

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    Das ösophageale Adenokarzinom zeigt eine global steigende Inzidenz und hat mit einer 5-Jahres-Überlebensrate von weniger als 25% eine schlechte Prognose. Personalisierte Therapieansätze sind selten und prognostische/prädiktive Biomarker des Tumormikromilieus sind unzureichend charakterisiert. Die kumulative Promotion nähert sich dieser Problematik in drei unterschiedlichen Schwerpunkten. 1. Zur Identifizierung Kompartiment-spezifischer Biomarker wurde eine Methode entwickelt, welche als kostengünstige Alternative zum sc-Seq Expressionsprofile individueller Zelltypen generiert. Dabei erfolgt die Extraktion der RNA nicht aus Einzelzellen, sondern aus flowzytometrisch-getrennten Zellkompartimenten. Die Separation der Proben in Epithelzellen, Immunzellen und Fibroblasten wurde durch verschiedene Verfahren validiert und eine suffiziente Ausbeute an RNA auch für kleine Gewebemengen gezeigt. 2. Biomarker des Immunzellkompartiments als therapeutische Angriffspunkte wurden in einem Patientenkollektiv von bis zu 551 Patienten auf ihre Bedeutung beim EAC überprüft. Es zeigte sich eine Expression der Immuncheckpoints LAG3, VISTA und IDO auf TILs durch IHC und RNA-Sonden basierte Verfahren in einem relevanten Anteil (LAG3: 11,4%, VISTA: 29%, IDO: 52,6%). Es konnte eine prognostisch günstige Bedeutung der VISTA, LAG3 und IDO Expression gezeigt werden. Durch den Vergleich von Genexpressionsprofilen aus therapienaiven und vorbehandelten Tumoren konnte zudem ein immunsuppressiver Effekt von neoadjuvanten Therapiekonzepten auf das Tumormikromilieu des EACs gezeigt werden. Dabei kam es zur verminderten Expression von Checkpoints und Anzahl TILs nach (Radio-) Chemotherapie. 3. Im Tumorzellkompartiment wurde die Rolle von Amplifikationen in ErbB-Rezeptor abhängigen Signalwegen durch FISH-Technik und Immunhistochemie evaluiert. Es fanden sich KRAS Amplifikationen in 17,1%, PIK3CA Amplifikationen in 5% sowie eine HER2/neu-Überexpression in 14,9% der untersuchten Tumore

    A Reinforcement Learning-assisted Genetic Programming Algorithm for Team Formation Problem Considering Person-Job Matching

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    An efficient team is essential for the company to successfully complete new projects. To solve the team formation problem considering person-job matching (TFP-PJM), a 0-1 integer programming model is constructed, which considers both person-job matching and team members' willingness to communicate on team efficiency, with the person-job matching score calculated using intuitionistic fuzzy numbers. Then, a reinforcement learning-assisted genetic programming algorithm (RL-GP) is proposed to enhance the quality of solutions. The RL-GP adopts the ensemble population strategies. Before the population evolution at each generation, the agent selects one from four population search modes according to the information obtained, thus realizing a sound balance of exploration and exploitation. In addition, surrogate models are used in the algorithm to evaluate the formation plans generated by individuals, which speeds up the algorithm learning process. Afterward, a series of comparison experiments are conducted to verify the overall performance of RL-GP and the effectiveness of the improved strategies within the algorithm. The hyper-heuristic rules obtained through efficient learning can be utilized as decision-making aids when forming project teams. This study reveals the advantages of reinforcement learning methods, ensemble strategies, and the surrogate model applied to the GP framework. The diversity and intelligent selection of search patterns along with fast adaptation evaluation, are distinct features that enable RL-GP to be deployed in real-world enterprise environments.Comment: 16 page

    Extended mixed integer quadratic programming for simultaneous distributed generation location and network reconfiguration

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    Introduction. To minimise power loss, maintain the voltage within the acceptable range, and improve power quality in power distribution networks, reconfiguration and optimal distributed generation placement are presented. Power flow analysis and advanced optimization techniques that can handle significant combinatorial problems must be used in distribution network reconfiguration investigations. The optimization approach to be used depends on the size of the distribution network. Our methodology simultaneously addresses two nonlinear discrete optimization problems to construct an intelligent algorithm to identify the best solution. The proposed work is novel in that it the Extended Mixed-Integer Quadratic Programming (EMIQP) technique, a deterministic approach for determining the topology that will effectively minimize power losses in the distribution system by strategically sizing and positioning Distributed Generation (DG) while taking network reconfiguration into account. Using an efficient Quadratic Mixed Integer Programming (QMIP) solver (IBM ®), the resulting optimization problem has a quadratic form. To ascertain the range and impact of various variables, our methodology outperforms cutting-edge algorithms described in the literature in terms of the obtained power loss reduction, according to extensive numerical validation carried out on typical IEEE 33- and 69-bus systems at three different load factors. Practical value. Examining the effectiveness of concurrent reconfiguration and DG allocation versus sole reconfiguration is done using test cases. According to the findings, network reconfiguration along with the installation of a distributed generator in the proper location, at the proper size, with the proper loss level, and with a higher profile, is effective.  Вступ. Для мінімізації втрат потужності, підтримки напруги в допустимому діапазоні та покращення якості електроенергії у розподільчих мережах представлена реконфігурація та оптимальне розміщення розподіленої генерації. При дослідженнях реконфігурації розподільної мережі необхідно використовувати аналіз потоку потужності та передові методи оптимізації, які можуть вирішувати серйозні комбінаторні проблеми. Підхід до оптимізації, що використовується, залежить від розміру розподільної мережі. Наша методологія одночасно вирішує дві задачі нелінійної дискретної оптимізації, щоби побудувати інтелектуальний алгоритм для визначення найкращого рішення. Пропонована робота є новою, оскільки вона використовує метод розширеного змішано-цілочисельного квадратичного програмування (EMIQP), детермінований підхід до визначення топології, що ефективно мінімізує втрати потужності в системі розподілу за рахунок стратегічного визначення розмірів та позиціонування розподіленої генерації (DG) з урахуванням реконфігурації мережі. При використанні ефективного солвера Quadratic Mixed Integer Programming (QMIP) (IBM®) результуюча задача оптимізації має квадратичну форму. Щоб з'ясувати діапазон та вплив різних змінних, наша методологія перевершує передові алгоритми, описані в літературі, з точки зору одержаного зниження втрат потужності, згідно з великою числовою перевіркою, проведеною на типових системах з шинами IEEE 33 і 69 при трьох різних коефіцієнтах навантаження. Практична цінність. Вивчення ефективності одночасної реконфігурації та розподілу DG у порівнянні з єдиною реконфігурацією проводиться з використанням тестових прикладів. Відповідно до результатів, реконфігурація мережі разом із установкою розподіленого генератора в потрібному місці, належного розміру, з належним рівнем втрат і з більш високим профілем є ефективною

    Four Lectures on the Random Field Ising Model, Parisi-Sourlas Supersymmetry, and Dimensional Reduction

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    Numerical evidence suggests that the Random Field Ising Model loses Parisi-Sourlas SUSY and the dimensional reduction property somewhere between 4 and 5 dimensions, while a related model of branched polymers retains these features in any dd. These notes give a leisurely introduction to a recent theory, developed jointly with A. Kaviraj and E. Trevisani, which aims to explain these facts. Based on the lectures given in Cortona and at the IHES in 2022.Comment: 55 pages, 11 figures; v2 - minor changes, mentioned forthcoming work by Fytas et a

    Neuroanatomical and gene expression features of the rabbit accessory olfactory system. Implications of pheromone communication in reproductive behaviour and animal physiology

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    Mainly driven by the vomeronasal system (VNS), pheromone communication is involved in many species-specific fundamental innate socio-sexual behaviors such as mating and fighting, which are essential for animal reproduction and survival. Rabbits are a unique model for studying chemocommunication due to the discovery of the rabbit mammary pheromone, but paradoxically there has been a lack of knowledge regarding its VNS pathway. In this work, we aim at filling this gap by approaching the system from an integrative point of view, providing extensive anatomical and genomic data of the rabbit VNS, as well as pheromone-mediated reproductive and behavioural studies. Our results build strong foundation for further translational studies which aim at implementing the use of pheromones to improve animal production and welfare

    Merge of two oppositely biased Wiener processes

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    We introduce a technique to merge two biased Brownian motions into a single regular process. The outcome follows a stochastic differential equation with a constant diffusion coefficient and a non-linear drift. The emerging stochastic process has outstanding properties, such as spatial and temporal translational invariance of its mean squared displacement, and can be efficiently simulated via a random walk with site-dependent one-step transition probabilities.Comment: 6 pages, no figure

    Modelling uncertainties for measurements of the H → γγ Channel with the ATLAS Detector at the LHC

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    The Higgs boson to diphoton (H → γγ) branching ratio is only 0.227 %, but this final state has yielded some of the most precise measurements of the particle. As measurements of the Higgs boson become increasingly precise, greater import is placed on the factors that constitute the uncertainty. Reducing the effects of these uncertainties requires an understanding of their causes. The research presented in this thesis aims to illuminate how uncertainties on simulation modelling are determined and proffers novel techniques in deriving them. The upgrade of the FastCaloSim tool is described, used for simulating events in the ATLAS calorimeter at a rate far exceeding the nominal detector simulation, Geant4. The integration of a method that allows the toolbox to emulate the accordion geometry of the liquid argon calorimeters is detailed. This tool allows for the production of larger samples while using significantly fewer computing resources. A measurement of the total Higgs boson production cross-section multiplied by the diphoton branching ratio (σ × Bγγ) is presented, where this value was determined to be (σ × Bγγ)obs = 127 ± 7 (stat.) ± 7 (syst.) fb, within agreement with the Standard Model prediction. The signal and background shape modelling is described, and the contribution of the background modelling uncertainty to the total uncertainty ranges from 18–2.4 %, depending on the Higgs boson production mechanism. A method for estimating the number of events in a Monte Carlo background sample required to model the shape is detailed. It was found that the size of the nominal γγ background events sample required a multiplicative increase by a factor of 3.60 to adequately model the background with a confidence level of 68 %, or a factor of 7.20 for a confidence level of 95 %. Based on this estimate, 0.5 billion additional simulated events were produced, substantially reducing the background modelling uncertainty. A technique is detailed for emulating the effects of Monte Carlo event generator differences using multivariate reweighting. The technique is used to estimate the event generator uncertainty on the signal modelling of tHqb events, improving the reliability of estimating the tHqb production cross-section. Then this multivariate reweighting technique is used to estimate the generator modelling uncertainties on background V γγ samples for the first time. The estimated uncertainties were found to be covered by the currently assumed background modelling uncertainty
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