A Scalable, Sound, Eventually-Complete Algorithm for Deadlock Immunity

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Nanotechnology enabled modulation of T cell immunity for cancer treatment

Xiaomeng Hu

Recent breakthroughs in cancer immunotherapy, exemplified by immune checkpoint blockade and CAR T cell therapy, have achieved remarkable clinical success. However, the majority of cancer patients fail to respond to immunotherapy or suffer from relapse. Nan ...

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Engineering Innate and Adaptive Immunity for Enhanced Cancer Immunotherapy

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Cancer immunotherapy has become an attractive strategy among different therapeutic modalities over the past few years and has showed great success in the clinic. However, there are many outstanding challenges hindering the current immunotherapies. In my Ph ...

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Privatized graph federated learning

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Federated learning is a semi-distributed algorithm, where a server communicates with multiple dispersed clients to learn a global model. The federated architecture is not robust and is sensitive to communication and computational overloads due to its one-m ...

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Development of stimuli-responsive chemistry for tumor-targeted immunotherapy

Céline Jasmin Prange

Cancer immunotherapy is the science of boosting the immune response of patients to fight cancer. Recent advances have brought up treatments with huge success in the clinic. Patients with ad-vanced-stage cancers were long-term cured through checkpoint inhib ...

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Hybrid Flock - Formation Control Algorithms

Alcherio Martinoli, Cyrill Silvan Baumann, Jonas Perolini, Emna Tourki

Two prominent categories for achieving coordinated multirobot displacement are flocking and navigation in formation. Both categories have their own body of literature and characteristics, including their respective advantages and disadvantages. While typic ...

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Formula Normalizations in Verification

Viktor Kuncak, Simon Guilloud, Mario Bucev, Dragana Milovancevic

We propose a new approach for normalization and simplification of logical formulas. Our approach is based on algorithms for lattice-like structures. Specifically, we present two efficient algorithms for computing a normal form and deciding the word problem ...

2023

Tight Vector Bin Packing with Few Small Items via Fast Exact Matching in Multigraphs

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We solve the Bin Packing problem in O^*(2^k) time, where k is the number of items less or equal to one third of the bin capacity. This parameter measures the distance from the polynomially solvable case of only large (i.e., greater than one third) items. O ...

Schloss Dagstuhl – Leibniz-Zentrum fur Informatik2022

Approximate CVPp in time 2(0.802n)

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We show that a constant factor approximation of the shortest and closest lattice vector problem in any l(p)-norm can be computed in time 2((0.802 + epsilon)n). This matches the currently fastest constant factor approximation algorithm for the shortest vect ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

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We present a quasilinear time algorithm to decide the word problem on a natural algebraic structures we call orthocomplemented bisemilattices, a subtheory of boolean algebra. We use as a base a variation of Hopcroft, Ullman and Aho algorithm for tree isomo ...

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An automatized method to determine latencies of motor-evoked potentials under physiological and pathophysiological conditions

Friedhelm Christoph Hummel, Takuya Morishita, Pierre Theopistos Vassiliadis, Andéol Geoffroy Cadic-Melchior, Claudia Bigoni

Background. Latencies of motor evoked potentials (MEPs) can provide insights into the motor neuronal pathways activated by transcranial magnetic stimulation. Notwithstanding its clinical relevance, accurate, unbiased methods to automatize latency detection ...

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An automatized method to determine latencies of motor-evoked potentials under physiological and pathophysiological conditions

Friedhelm Christoph Hummel, Takuya Morishita, Pierre Theopistos Vassiliadis, Andéol Geoffroy Cadic-Melchior, Claudia Bigoni

IOP Publishing Ltd2022