Abstract:
An intact immune system is essential to prevent the development and progression of neoplastic cells in a process termed immune surveillance. During this process the innate and the adaptive immune systems closely cooperate and especially T cells play an important role to detect and eliminate tumor cells. Due to the mechanism of central tolerance the frequency of T cells displaying appropriate arranged tumor-peptide-specific-T-cell receptors is very low and their activation by professional antigen-presenting cells, such as dendritic cells, is frequently hampered by insufficient costimulation resulting in peripheral tolerance. In addition, inhibitory immune circuits can impair an efficient antitumoral response of reactive T cells. It also has been demonstrated that large tumor burden can promote a state of immunosuppression that in turn can facilitate neoplastic progression. Moreover, tumor cells, which mostly are genetically instable, can gain rescue mechanisms which further impair immune surveillance by T cells. Herein, we summarize the data on how tumor cells evade T-cell immune surveillance with the focus on solid tumors and describe approaches to improve anticancer capacity of T cells.

Abstract:
The purpose of this little survey is to give a simple description of the main approaches to quantum error correction and quantum fault-tolerance. Our goal is to convey the necessary intuitions both for the problems and their solutions in this area. After characterising quantum errors we present several error-correction schemes and outline the elements of a full fledged fault-tolerant computation, which works error-free even though all of its components can be faulty. We also mention alternative approaches to error-correction, so called error-avoiding or decoherence-free schemes. Technical details and generalisations are kept to a minimum.

Abstract:
Entanglement between three or more parties exhibits a realm of properties unknown to two-party states. Bipartite states are easily classified using the Schmidt decomposition. The Schmidt coefficients of a bipartite pure state encompass all the non-local properties of the state and can be "seen" by looking at one party's density matrix only. Pure states of three and more parties however lack such a simple form. They have more invariants under local unitary transformations than any one party can "see" on their sub-system. These "hidden non-localities" will allow us to exhibit a class of multipartite states that cannot be distinguished from each other by any party. Generalizing a result of BPRST and using a recent result by Nielsen we will show that these states cannot be transformed into each other by local actions and classical communication. Furthermore we will use an orthogonal subset of such states to hint at applications to cryptography and illustrate an extension to quantum secret sharing (using recently suggested ((n,k))-threshold schemes).

Abstract:
This article aims to provide an introductory survey on quantum random walks. Starting from a physical effect to illustrate the main ideas we will introduce quantum random walks, review some of their properties and outline their striking differences to classical walks. We will touch upon both physical effects and computer science applications, introducing some of the main concepts and language of present day quantum information science in this context. We will mention recent developments in this new area and outline some open questions.

Abstract:
This paper describes the conversion of a Hidden Markov Model into a sequential transducer that closely approximates the behavior of the stochastic model. This transformation is especially advantageous for part-of-speech tagging because the resulting transducer can be composed with other transducers that encode correction rules for the most frequent tagging errors. The speed of tagging is also improved. The described methods have been implemented and successfully tested on six languages.

Abstract:
The described tagger is based on a hidden Markov model and uses tags composed of features such as part-of-speech, gender, etc. The contextual probability of a tag (state transition probability) is deduced from the contextual probabilities of its feature-value-pairs. This approach is advantageous when the available training corpus is small and the tag set large, which can be the case with morphologically rich languages.

Abstract:
We show that the hitting time of the discrete time quantum random walk on the n-bit hypercube from one corner to its opposite is polynomial in n. This gives the first exponential quantum-classical gap in the hitting time of discrete quantum random walks. We provide the framework for quantum hitting time and give two alternative definitions to set the ground for its study on general graphs. We then give an application to random routing.

Abstract:
We present a generalization of the Viterbi algorithm for identifying the path with minimal (resp. maximal) weight in a n-tape weighted finite-state machine (n-WFSM), that accepts a given n-tuple of input strings (s_1,... s_n). It also allows us to compile the best transduction of a given input n-tuple by a weighted (n+m)-WFSM (transducer) with n input and m output tapes. Our algorithm has a worst-case time complexity of O(|s|^n |E| log (|s|^n |Q|)), where n and |s| are the number and average length of the strings in the n-tuple, and |Q| and |E| the number of states and transitions in the n-WFSM, respectively. A straight forward alternative, consisting in intersection followed by classical shortest-distance search, operates in O(|s|^n (|E|+|Q|) log (|s|^n |Q|)) time.

Abstract:
The automatic extraction of acronyms and their meaning from corpora is an important sub-task of text mining. It can be seen as a special case of string alignment, where a text chunk is aligned with an acronym. Alternative alignments have different cost, and ideally the least costly one should give the correct meaning of the acronym. We show how this approach can be implemented by means of a 3-tape weighted finite-state machine (3-WFSM) which reads a text chunk on tape 1 and an acronym on tape 2, and generates all alternative alignments on tape 3. The 3-WFSM can be automatically generated from a simple regular expression. No additional algorithms are required at any stage. Our 3-WFSM has a size of 27 states and 64 transitions, and finds the best analysis of an acronym in a few milliseconds.