26,641 research outputs found
Rank-based linkage I: triplet comparisons and oriented simplicial complexes
Rank-based linkage is a new tool for summarizing a collection 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 . Rank-based linkage is applied
to the -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
-nearest neighbor graph on . In steps it builds an
edge-weighted linkage graph where
is called the in-sway between objects and . Take to be
the links whose in-sway is at least , and partition into components of
the graph , for varying . 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
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
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
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
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
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 . 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
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
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
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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