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O estado de pandemia que teve início em 2019, com o primeiro caso e estende-se até́ a atualidade, tem como agente causal o SARS-COV-2, reconhecido pela OMS (Organização Mundial de Saúde) como uma doença respiratória que é denominada como COVID-19 . O vírus apresentou uma alta taxa de transmissibilidade e também apresentou alto índice de mortalidade na população mundial, com mais de três milhões de pessoas mortas no mundo, sendo dessas no Brasil mais de quinhentos mil.² No caso das gestantes, em função de sua condição de imunossupressão, quando apresentam a forma sintomática da COVID 19 podem desenvolver maiores complicações respiratórias e evoluir para óbito, sendo assim mais suscetíveis a permanência em unidade de terapia intensiva.4,5O presente estudo tem por objetivo geral entender o perfil clínico e epidemiológico das gestantes e puérperas que evoluíram para óbito e fizeram uso de unidade de terapia intensiva, com diagnóstico confirmado de COVID 19, no ano de 2020, no Estado de Pernambuco. Trata-se de um estudo com abordagem quantitativa de caráter transversal e retrospectivo. A coleta de dados foi realizada através de pesquisa no Sistema de Informação da Vigilância Epidemiológica da Gripe (SIVE Gripe), foram coletadas informações acerca dos dados sociodemográficos das mulheres, seus antecedentes pessoais, dados obstétricos, internação em UTI, suporte ventilatório, uso de retrovirais e desfecho duro. Como resultados, das 210 mulheres estudadas, 82% eram pardas, cerca de 80% das mulheres estavam no terceiro trimestre (59,5%) ou puérperas (25,2%). Das que estiveram na UTI, 75% utilizaram suporte ventilatório, 17% usaram retrovirais, 14% da amostra evoluiu para óbito

Nowadays, society has challenged the scienti c community to nd solutions able to use technology to solve the gentri cation3 of city centers. Within this context, smart cities have had an important role because they view each citizen as a data source. In the same way, the Internet of Things network increases the number of physical devices generating peta-bytes of information into a Smart city architecture. Thus an appropriate Machine Learning approach is required to process and analyze collected data. In this paper, we apply three di erent Machine Learning techniques such as Convolutional Neural Network (CNN), Long-Short Term Memory (LSTM), and a combined architecture, which we call CNN-LSTM, to the data generated by LinkNYC Kiosks devices | based on the city of New York |, and come to the conclusion the combined model gets better results in predicting human mobility.

Explainable artificial intelligence has been used in several scientific fields to understand how and why a machine learning model makes its predictions. Its characteristics have allowed for greater transparency and outcomes in AI-powered decision-making. This building trust and confidence can be useful in human mobility research. This work provides a comparative study in terms of the explainability of artificial intelligence on smart human mobility in the context of a regression problem. Decision Tree, LIME, SHAP, and Seldon Alibi are explainable approaches to describe human mobility using a dataset generated from New York Services. Based on our results, all of these approaches present relevant indicators for our problem., This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. It has also been supported by national funds through FCT – Fundação para a Ciência e Tecnologia through project UIDB/04728/2020.

Artificial Intelligence is a hot topic and Machine Learning is one of the most fluent approaches and practices. The problem with many AI models is that they can be useful for predicting but they are bad at explaining why they behave a certain way. In some contexts, the explanation may even be more important than the prediction itself, mainly in systems in which decisions are made based on their predictions. Therefore, it is increasingly necessary to provide a forecast accompanied by an explanation, when decisions are made automatically. This paper aims to contribute to the solution of problem based on human mobility research, or at least, to be a starting point for its solution, This work has been supported by FCT - Fundacao para a Ciencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. It has also been supported by na tional funds through FCT – Fundac¸ao para a Ciência e Tecnologia through project UIDB/04728/2020.

Developing secure and fast asymmetric cryptographic primitives is a priority in cryptography. This fact steams from high demand for fast communication involving an increasing amount of private and sensible information. To this end, we propose an efficient McEliece-based cryptosystem to handle large messages that can be easily implemented in hardware. The main idea is to incorporate Low-Density Parity-Check (LDPC) codes after several parallel runs of the original McEliece cryptosystem. In this way, we achieve a low circuit-depth complexity while profiting from the capability of LDPC codes to deal with high-dimensional data. The proposed cryptosystem is at least as hard as the original McEliece cryptosystem, and therefore, it is believed to be robust to quantum attacks. Moreover, known attacks to McEliece cryptosystems based on LDPC codes are ineffective against our proposal. The key size of the cryptosystem is roughly ten times smaller than the original McEliece for similar levels of security. Finally, we present a variant of the proposed cryptosystem that is resistant to adaptive indistinguishability chosen-chiphertext attacks (IND-CCA2), which is a desirable property that the original McEliece cryptosystem does not fulfill.

Reproducibility and comparability of empirical results are at the core tenet of the scientific method in any scientific field. To ease reproducibility of empirical studies, several benchmarks in software engineering research, such as Defects4J, have been developed and widely used. For quantum software engineering research, however, no benchmark has been established yet. In this position paper, we propose a new benchmark -- named QBugs -- which will provide experimental subjects and an experimental infrastructure to ease the evaluation of new research and the reproducibility of previously published results on quantum software engineering.

About 160 years ago, the concept of entropy was introduced in thermodynamics by Rudolf Clausius. Since then, it has been continually extended, interpreted, and applied by researchers in many scientific fields, such as general physics, information theory, chaos theory, data mining, and mathematical linguistics. This paper presents The Entropy Universe, which aims to review the many variants of entropies applied to time-series. The purpose is to answer research questions such as: How did each entropy emerge? What is the mathematical definition of each variant of entropy? How are entropies related to each other? What are the most applied scientific fields for each entropy? We describe in-depth the relationship between the most applied entropies in time-series for different scientific fields, establishing bases for researchers to properly choose the variant of entropy most suitable for their data. The number of citations over the past sixteen years of each paper proposing a new entropy was also accessed. The Shannon/differential, the Tsallis, the sample, the permutation, and the approximate entropies were the most cited ones. Based on the ten research areas with the most significant number of records obtained in the Web of Science and Scopus, the areas in which the entropies are more applied are computer science, physics, mathematics, and engineering. The universe of entropies is growing each day, either due to the introducing new variants either due to novel applications. Knowing each entropy’s strengths and of limitations is essential to ensure the proper improvement of this research field.

There are increasingly more discussions on and guidelines about different levels of indicators surrounding smart cities (e.g., comfort, well-being and weather conditions). They are an important opportunity to illustrate how smart urban development strategies and digital tools can be stretched or reinvented to address localised social issues. Thus, multi-source heterogeneous data provides a new driving force for exploring urban human mobility patterns. In this work, we forecast human mobility data using LinkNYC kiosks and Metropolitan Transportation Authority (MTA) Wi-Fi in New York City to study how comfort and well-being indicators influence people's movements. By comparing the forecasting performance of statistical and deep learning methods on the aggregated mobile data we show that each class of methods has its advantages and disadvantages depending on the forecasting scenario. However, for our time-series forecasting problem, deep learning methods are preferable when it comes to simplicity and immediacy of use, since they do not require a time-consuming model selection for each different cell. Deep learning approaches are also appropriate when aiming to reduce the maximum forecasting error. Statistical methods instead have shown their superiority in providing more precise forecasting results, but they require data domain knowledge and computationally expensive techniques in order to select the best parameters., This work has been supported by FCT -Fundacao para a Ciencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. It has also been supported by national funds through FCT -Fundacao para a Ciencia e Tecnologia through project UIDB/04728/2020.

Human mobility is important in understanding urban spaces. Citizens interact with urban spaces using the available infrastructures, not just in the mobility sector but in public services, and in Information and Communications Technology (ICT) services, that simultaneously record their footprints. Besides, the number of mobile users is increasing very rapidly in the Internet of Things (IoT) era. These additional devices will produce a great amount of data and create new big challenges for network infrastructure. Because of this new connectivity platform, and the fast growth of wireless communication, it’s important to discuss the arrival of 5G systems. They will have a large impact on coverage, spectral efficiency, data rate of global mobile traffic, and IoT devices, and in turn it will be possible to analyze the lifestyle and understand the mobility of people, such as the most frequently visited urban spaces. Therefore, this paper is relevant in the context of smart cities and will allow for an easy connection between citizens and technology innovation hub, acquiring detailed data on human movements. Based on the analysis of generated data we try to widen this view and present an integrated approach to the analysis of human mobility using LinkNYC kiosks and 311 Service Requests in New York city.

We propose an entanglement-based quantum bit string commitment protocol whose composability is proven in the random oracle model. This protocol has the additional property of preserving the privacy of the committed message. Even though this property is not resilient against man-in-the-middle attacks, this threat can be circumvented by considering that the parties communicate through an authenticated channel. The protocol remains secure (but not private) if we realize the random oracles as physical unclonable functions in the so-called bad PUF model with access before the opening phase., Comment: 8 pages, 4 figures

A design for a novel mobile sensing system, called Temperature Measurement System Architecture (TMSA), that uses people as mobile sensing nodes in a network to capture spatiotemporal properties of pedestrians in urban environments is presented in this paper. In this dynamic, microservices approach, real-time data and an open-source IoT platform are combined to provide weather conditions based on information generated by a fleet of mobile sensing platforms. TMSA also offers several advantages over traditional methods using participatory sensing or more recently crowd-sourced data from mobile devices, as it provides a framework in which citizens can bring to light data relevant to urban planning services or learn human behaviour patterns, aiming to change users’ attitudes or behaviors through social influence. In this paper, we motivate the need for and demonstrate the potential of such a sensing paradigm, which supports a host of new research and application developments, and illustrate this with a practical urban sensing example., This work has been supported by FCT - Fundacao para a Ciencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. It has also been supported by na tional funds through FCT – Fundação para a Ciência e Tecnologia through project ˆ UIDB/04728/2020.

The significant improvement in the field of Internet of Things (IoT) has made human life more sophisticated. In fact, the IoT is covering devices and appliances that support one or more common ecosystems, and can be controlled via devices associated with that ecosystem. This control is only possible by building an architecture. Whether in indoor or outdoor environments, IoT services are only available to individuals or pedestrians because a IoT architecture enables that the quality of its components (i.e. Cloud/Fog servers, protocol communication and IoT devices) and the way they interact are directly correlated in terms of effectiveness and applicability. This paper aims to provide a comprehensive overview of an architecture in pedestrian-oriented applications in an IoT environment. Moreover, our survey has taken into account the main challenges and limitations of each component of IoT technology.

The logical depth with significance b of a string x is the shortest running time of a program for x that can be compressed by at most b bits. Another definition is based on algorithmic probability. We give a simple new proof for the known relation between the two definitions. We also prove the following: Given a string we can consider the maximal decrease in logical depth when the significance parameter increases by 1. There exists a sequence of strings of lengths n = 1, 2, ..., such that this maximal decrease as a function of n rises faster than any computable function but not as fast as the Busy Beaver function. This holds also for the computation times of the shortest programs of these strings.

The oblivious transfer primitive is sufficient to implement secure multiparty computation. However, secure multiparty computation based only on classical cryptography is severely limited by the security and efficiency of the oblivious transfer implementation. We present a method to efficiently and securely generate and distribute oblivious keys by exchanging qubits and by performing commitments using classical hash functions. With the presented hybrid approach, quantum and classical, we obtain a practical and high-speed oblivious transfer protocol, secure even against quantum computer attacks. The oblivious distributed keys allow implementing a fast and secure oblivious transfer protocol, which can pave the way for the widespread of applications based on secure multiparty computation., 11 pages, 5 figures

It is well known, due to the no-go theorems, that perfectly secure bit commitment is impossible. For that reason, there exist many proposals for bit commitment protocols that are secure under certain assumptions (such as the existence of a trusted party, computational hardness, or noisy memories). In this paper, we investigate the minimal assumptions required to obtain a secure bit commitment protocol. We show that it is possible to construct a bit commitment scheme with two parties Alice and Bob as long as there is a third party that is willing to broadcast either entangled qubits for the parties or to produce classical strings that are xor-correlated. We also show that the bit commitment scheme proposed is universally composable.

Quantum key distribution, which allows two distant parties to share an unconditionally secure cryptographic key, promises to play an important role in the future of communication. For this reason such technique has attracted many theoretical and experimental efforts, thus becoming one of the most prominent quantum technologies of the last decades. The security of the key relies on quantum mechanics and therefore requires the users to be capable of performing quantum operations, such as state preparation or measurements in multiple bases. A natural question is whether and to what extent these requirements can be relaxed and the quantum capabilities of the users reduced. Here we demonstrate a novel quantum key distribution scheme, where users are fully classical. In our protocol, the quantum operations are performed by an untrusted third party acting as a server, which gives the users access to a superimposed single photon, and the key exchange is achieved via interaction-free measurements on the shared state. We also provide a full security proof of the protocol by computing the secret key rate in the realistic scenario of finite-resources, as well as practical experimental conditions of imperfect photon source and detectors. Our approach deepens the understanding of the fundamental principles underlying quantum key distribution and, at the same time, opens up new interesting possibilities for quantum cryptography networks, Comment: Version accepted by Quantum - 9 pages, 4 figures + Appendix (16 pages, 4 figures)

Changes can be seen as normal situations within the management process of an organization. Two elements are strong contributors as systematic support: management of change (MOC) and the critical success factors (CSF) for change, which also should desirable to be sustainable. The general goal of this work consists in identifying which CSF are determinant in the organizational change process, in specific in the approach of a Brazilian chemical and petrochemical company’s organizational MOC process in addition to the inclusion of proactive corporate sustainability management through a present scenario diagnosis. The aim of this paper is to identify which are the decisive CSF in the organizational change process, associated to the proactive management of corporate sustainability, through sustainability criteria. The methodology for the research was the case study. Main results identified forty-five CSF related to the organization’s MOC process and the Global Report Initiative (GRI) model as being the most adopted in the world business. Contributions from the literature were identified in CSF in the MOC process within the organization, such as constant and efficient communication process and resources, aiming to incorporate practices to the current organizational change model. Leadership and resources were the most relevant dimensions of CSF identified in the case study. Regarding the understanding of sustainability concepts, it was found among the answerers a vision that emphasizes the environmental dimension, despite social and economic dimensions, as well as gaps in their understanding of sustainability concepts and the connection of this subject with CSF in the MOC

Quantum key distribution is one of the most fundamental cryptographic protocols. Quantum walks are important primitives for computing. In this paper we take advantage of the properties of quantum walks to design new secure quantum key distribution schemes. In particular, we introduce a secure quantum key-distribution protocol equipped with verification procedures against full man-in-the-middle attacks. Furthermore, we present a one-way protocol and prove its security. Finally, we propose a semi-quantum variation and prove its robustness against eavesdropping., published version; 40 pages; 8 figures

Security of data is crucial in nowadays societies. One of the most basic security protocols are the zero-knowledge protocols where a prover convinces a verifier of the knowledge of a secret information without revealing that piece of information. The tradicional approach to prove the security of these protocols is based on the (im)possibility of simulation of the interactions. A more fundamental way to prove the security is based solely on the information conveyed about proof. In order to establish that connection and quantifying the number of possible transformations that one can use in these protocols, we use Kolmogorov complexity and in particular we focus on the incompressibility theorem. In this paper we study the counterpart of this theorem by, instead of providing the number of x such that for a fixed y, Kt(x|y) ≈ Kt(x), we study for a fixed y the number of x such that Kt(x|y) ≈ Kt(x). As a second contribution of this paper we present an extension of the results regarding Kolmogorov one-way functions started in [3]. This cryptographic primitives have the property to be easy to compute but hard to invert and are a basilar ingredient for digital security.

In a witness hiding protocol the prover tries to convince the verifier that he knows a witness to an instance of an \(\mathbf{NP}\) problem without revealing the witness. We propose a new look at witness hiding based on the information conveyed in each particular instance of the protocol.

A simple notion of quantum Turing machine with deterministic, classical control is proposed and shown to be powerful enough to compute any unitary transformation which is computable by a finitely generated quantum circuit. An efficient universal machine with the s-m-n property is presented. The BQP class is recovered. A robust notion of plain Kolmogorov complexity of quantum states is proposed and compared with those previously reported in the literature.

"SPIE Proceedings Vol. 10453", We theoretically predict several plasmonic effects that arise when a monolayer of small polarisable particles is deposited on graphene, related to surface plasmon-polaritons (SPPs) supported by the latter in the terahertz (THz) spectral range. The electromagnetic coupling between graphene SPPs and dipole moments of the nanoparticles (NPs) gives rise to optical properties that are not present in the individual components of this system. The polarisation characteristics of the particles are modified, namely: (i) individual NP’s polarisability is renormalized and (ii) their dipole-dipole interaction includes, beyond the usual ∝ ρ−3 term (ρ is the particleparticle distance), an indirect particle-particle coupling arises via polarisation charges induced on the graphenecovered interface by each particle – this indirect coupling oscillates with the interparticle distance. We derived coupled-dipole equations taking into account all these effects, allowing us to calculate an effective optical conductivity of the particles’ monolayer and study the optical properties of the composite (G+NPs) system. One of the G+NPs system’s unique features is a collective resonant mode, causing a considerable enhancement of the THz radiation absorption in graphene, while the reflection drops to nearly zero for a broad range of angles of incidence. The frequency of this resonant mode can be adjusted by changing the Fermi energy in graphene via electrostatic gating and therefore it can be used for electrically controlled reflection and transmission of THz radiation. Another remarkable finding is that the composite layer supports s-polarised surface polaritons linked to Drude plasmons in graphene., We are grateful to the European Commission for funding through the Graphene Flagship Core 1 Project (No 696656). Financial support from the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Financing UID/FIS/04650/2013 and PEst-OE/MAT/UI0013/2014 is also acknowledged., info:eu-repo/semantics/publishedVersion

We present a quantum scheme for signing contracts between two clients (Alice and Bob) using entangled states and the services of a third trusted party (Trent). The trusted party is only contacted for the initialization of the protocol, and possibly at the end, to verify clients&rsquo, honesty and deliver signed certificates. The protocol is fair, i.e., the probability that a client, say Bob, can obtain a signed copy of the contract, while Alice cannot, can be made arbitrarily small, and scales as N &minus, 1 / 2 , where 4 N is the total number of rounds (communications between the two clients) of the protocol. Thus, the protocol is optimistic, as cheating is not successful, and the clients rarely have to contact Trent to confirm their honesty by delivering the actual signed certificates of the contract. Unlike the previous protocol (Paunković et al., Phys. Rev. A 84, 062331 (2011)), in the present proposal, a single client can obtain the signed contract alone, without the need for the other client&rsquo, s presence. When first contacting Trent, the clients do not have to agree upon a definitive contract. Moreover, even upon terminating the protocol, the clients do not reveal the actual contract to Trent. Finally, the protocol is based on the laws of physics, rather than on mathematical conjectures and the exchange of a large number of signed authenticated messages during the actual contract signing process. Therefore, it is abuse-free, as Alice and Bob cannot prove they are involved in the contract signing process.

Given today’s growing number of devices around users, and, at the same time, their faster and frequent interactions with these devices, new security mechanisms have emerged aiming at reducing the time spent by users with authentication as well as raising the security level related to identity verification. In this sense, there are several proposals in the literature with transparent and continuous authentication mechanisms that combine biometric data retrieved from actions that users already do while using mobile devices (e.g. location, screen touch, keystroke, gait, voice, among others). In the literature review performed in this work were found nine proposals that use outdoor location and merge other kinds of biometric features as input to their proposed authentication mechanism. These proposals have in common not only the use of outdoor location but they also fail to evaluate properly each biometric features set individually. Therefore, this work provides a new process for evaluation of biometric features by adapting guidelines of machine learning to perform experiments based on a statistical methodology. This is important to know how the mechanism works, which allows the identification and reuse of features extraction techniques that provide the best performance. Moreover, this process is also used in this work to evaluate and compare the outdoor location features identified in literature. For this evaluation, experiments were conducted with three classification algorithms (C4.5, SVM, and Naive Bayes) available in the WEKA machine learning environment and four datasets, two of which are public (Geolife and MIT Reality). Besides that, twelve measures were collected, being nine efficacy and three efficiency measures. In the analysis of the experimental results, significant variations were found in accuracy, CPU time, and memory regarding all evaluated scenarios. With these results, this work provides evidence of the viability of the proposed process and guides the choice of outdoor location features and learning algorithms that provide better performance for constructing transparent and continuous authentication mechanisms. Com um número cada vez maior de dispositivos ao redor dos usuários e, ao mesmo tempo, aplicações que demandam interações mais rápidas e frequentes com esses equipamentos, novos mecanismos buscam reduzir o tempo gasto pelos usuários com autenticação e aumentar o nível de segurança relacionado com a verificação de identidade. Nesse sentido, existem várias propostas na literatura com mecanismos de autenticação transparente e contínua que combinam dados biométricos obtidos a partir de ações que os usuários já realizam enquanto usam os dispositivos móveis (e.g. localização, toque na tela, digitação, marcha, voz, entre outras). Na revisão da literatura realizada neste trabalho, foram encontradas nove propostas que usam a localização outdoor do usuário combinada com outros tipos de features biométricas como entrada para o mecanismo de autenticação proposto. Essas propostas têm em comum não só o uso da localização outdoor, mas também o fato de não conseguirem avaliar de maneira adequada cada conjunto de features individualmente. Sendo assim, este trabalho tem como objetivo propor um processo de avaliação de features biométricas, adaptando diretrizes de aprendizado de máquina, para realização de experimentos com base em uma metodologia estatística. Esse processo de avaliação é importante para a completa compreensão do funcionamento do mecanismo proposto, o que permite a identificação e o reuso das técnicas de extração de features que oferecem melhor desempenho. Além disso, um estudo de caso usando o processo é realizado para a avaliação e a comparação das features de localização outdoor identificadas na literatura. Nessa avaliação foram realizados experimentos com três algoritmos de classificação (C4.5, SVM e Naive Bayes) disponíveis no ambiente de aprendizado de máquina WEKA e quatro conjuntos de dados, sendo dois deles públicos (Geolife e MIT Reality). Foram também coletadas doze medidas, sendo nove delas de eficácia e três de eficiência. A análise dos resultados dos experimentos mostrou variações significativas na acurácia, uso de CPU e memória, considerando todos os cenários avaliados. Com esses resultados, este trabalho fornece evidências sobre a viabilidade do processo proposto, produzindo resultados para guiar a escolha de features de localização outdoor e algoritmos de aprendizado que oferecem melhor desempenho para a construção de mecanismos de autenticação transparente e contínua.

Quantum Cryptography is a rapidly developing field of research that benefits from the properties of Quantum Mechanics in performing cryptographic tasks. Quantum walks are a powerful model for quantum computation and very promising for quantum information processing. In this paper, we present a quantum public-key cryptographic system based on quantum walks. In particular, in the proposed protocol the public-key is given by a quantum state generated by performing a quantum walk. We show that the protocol is secure and analyze the complexity of public key generation and encryption/decryption procedures.

We introduced a new method for distinguishing two probability ensembles called one from each method, in which the distinguisher receives as input two samples, one from each ensemble. We compare this new method with multi-sample from the same method already exiting in the literature and prove that there are ensembles distinguishable by the new method, but indistinguishable by the multi-sample from the same method. To evaluate the power of the proposed method we also show that if non-uniform distinguishers (probabilistic circuits) are used, the one from each method is not more powerful than the classical one, in the sense that does not distinguish more probability ensembles. Moreover we obtain that there are classes of ensembles, such that - any two members of the class are easily distinguishable (a definition introduced in this paper) using one sample from each ensemble;- there are pairs of ensembles in the same class that are indistinguishable by multi-sample from the same method.

We prove several results relating injective one-way functions, time-bounded conditional Kolmogorov complexity, and time-bounded conditional entropy. First we establish a connection between injective, strong and weak one-way functions and the expected value of the polynomial time-bounded Kolmogorov complexity, denoted here by E(K t (x|f(x))). These results are in both directions. More precisely, conditions on E(K t (x|f(x))) that imply that f is a weak one-way function, and properties of E(K t (x|f(x))) that are implied by the fact that f is a strong one-way function. In particular, we prove a separation result: based on the concept of time-bounded Kolmogorov complexity, we find an interval in which every function f is a necessarily weak but not a strong one-way function. Then we propose an individual approach to injective one-way functions based on Kolmogorov complexity, defining Kolmogorov one-way functions and prove some relationships between the new proposal and the classical definition of one-way functions, showing that a Kolmogorov one-way function is also a deterministic one-way function. A relationship between Kolmogorov one-way functions and the conjecture of polynomial time symmetry of information is also proved. Finally, we relate E(K t (x|f(x))) and two forms of time-bounded entropy, the unpredictable entropy H unp, in which "one-wayness" of a function can be easily expressed, and the Yao+ entropy, a measure based on compression/decompression schema in which only the decompressor is restricted to be time-bounded.

Purpose Disagreement on the interpretation of diagnostic tests and clinical decisions remains an important problem in medicine. As no strategy to assess agreement seems to be fail-safe to compare the degree of agreement, or disagreement, we propose a new information-based approach to assess disagreement. Methods The sum over all logarithms of possible outcomes of a variable is a valid measure of the amount of information contained in the variable. The proposed measure is based on the amount of information contained in the differences between two observations. This measure is normalized and satisfies the flowing properties: it is a metric, scaled invariant and it has differential weighting. Results Two real examples and a simulation were used to illustrate the usefulness of the proposed measure to compare the degree of disagreement. Conclusions Used as complement to the existing methods, we believe our approach can be useful to compare the degree of disagreement among different populations.

We study characterizations of one-way functions in terms of time-bounded Kolmogorov complexity. As the main contribution, we propose definitions for strong and weak Kolmogorov one-way functions and show that these are equivalent to classical strong and weak one-way functions, respectively. The new definitions were motivated by the fact that the expected value approach is not able to characterize strong one-way functions as we prove in the paper.