Parameterized cellular material for the elastic mimetization of cancellous bone

Bone tissue mechanical properties and trabecular microarchitecture are the main factors that determine the biomechanical properties of cancellous bone. Artificial cancellous microstructures, typically described by a reduced number of geometrical parameters, can be designed to obtain a mechanical behavior mimicking that of natural bone. In this work, we assess the ability of the parameterized microstructure introduced by Kowalczyk (P. Kowalczyk, Comput Meth Biomech Biomed Eng, 9:135–147, 2006) to mimic the elastic response of cancellous bone. An optimization approach is devised to find the geometrical parameters of the artificial microstructure that better mimics the elastic response of target natural bone specimen. This is done via a Pattern Search algorithm that minimizes the difference between the symmetry class decompositions of the elastic tensors. The performance of the method is demonstrated via analyses for 146 bone samples.Publicado en: Mecánica Computacional vol. XXXV, no. 8.Facultad de Ingenierí

Parameterized cellular material for the elastic mimetization of cancellous bone

Bone tissue mechanical properties and trabecular microarchitecture are the main factors that determine the biomechanical properties of cancellous bone. Artificial cancellous microstructures, typically described by a reduced number of geometrical parameters, can be designed to obtain a mechanical behavior mimicking that of natural bone. In this work, we assess the ability of the parameterized microstructure introduced by Kowalczyk (P. Kowalczyk, Comput Meth Biomech Biomed Eng, 9:135–147, 2006) to mimic the elastic response of cancellous bone. An optimization approach is devised to find the geometrical parameters of the artificial microstructure that better mimics the elastic response of target natural bone specimen. This is done via a Pattern Search algorithm that minimizes the difference between the symmetry class decompositions of the elastic tensors. The performance of the method is demonstrated via analyses for 146 bone samples.Publicado en: Mecánica Computacional vol. XXXV, no. 8.Facultad de Ingenierí

Parameterized cellular material for the elastic mimetization of cancellous bone

Bone tissue mechanical properties and trabecular microarchitecture are the main factors that determine the biomechanical properties of cancellous bone. Artificial cancellous microstructures, typically described by a reduced number of geometrical parameters, can be designed to obtain a mechanical behavior mimicking that of natural bone. In this work, we assess the ability of the parameterized microstructure introduced by Kowalczyk (P. Kowalczyk, Comput Meth Biomech Biomed Eng, 9:135–147, 2006) to mimic the elastic response of cancellous bone. An optimization approach is devised to find the geometrical parameters of the artificial microstructure that better mimics the elastic response of target natural bone specimen. This is done via a Pattern Search algorithm that minimizes the difference between the symmetry class decompositions of the elastic tensors. The performance of the method is demonstrated via analyses for 146 bone samples.Publicado en: Mecánica Computacional vol. XXXV, no. 8.Facultad de Ingenierí

Compact Adaptively Secure ABE for NC1 from k-Lin

We present compact attribute-based encryption (ABE) schemes for NC1 that are adaptively secure under the k-Lin assumption with polynomial security loss. Our KP-ABE scheme achieves ciphertext size that is linear in the atttribute length and independent of the policy size even in the many-use setting, and we achieve an analogous efficiency guarantee for CP-ABE. This resolves the central open problem posed by Lewko and Waters (CRYPTO 2011). Previous adaptively secure constructions either impose an attribute ``one-use restriction\u27\u27 (or the ciphertext size grows with the policy size), or require q-type assumptions

Function-Hiding Inner Product Encryption

We extend the reach of functional encryption schemes that are provably secure under simple assumptions against unbounded collusion to include function-hiding inner product schemes. Our scheme is a private key functional encryption scheme, where ciphertexts and secret keys correspond to vectors and a decryptor learns the value of the inner product of ciphertext and secret key vectors. Our scheme employs asymmetric bilinear maps and relies only on the SXDH assumption to satisfy a natural indistinguishability-based security notion where arbitrarily many key and ciphertext vectors can be simultaneously changed as long as the key-ciphertext dot product relationships are all preserved

Mitigating the One-Use Restriction in Attribute-Based Encryption

We present a key-policy attribute-based encryption scheme that is adaptively secure under a static assumption and is not directly affected by an attribute one-use restriction. Our construction improves upon the only other such scheme (Takashima \u2717) by mitigating its downside of a ciphertext size that is dependent on the maximum size of any supported attribute set

Strong Hardness of Privacy from Weak Traitor Tracing

A central problem in differential privacy is to accurately answer a large family $Q$ of statistical queries over a data universe $X$. A statistical query on a dataset $D \in X^n$ asks ``what fraction of the elements of $D$ satisfy a given predicate $p$ on $X$?\u27\u27 Ignoring computational constraints, it is possible to accurately answer exponentially many queries on an exponential size universe while satisfying differential privacy (Blum et al., STOC\u2708). Dwork et al. (STOC\u2709) and Boneh and Zhandry (CRYPTO\u2714) showed that if both $Q$ and $X$ are of polynomial size, then there is an efficient differentially private algorithm that accurately answers all the queries. They also proved that if $Q$ and $X$ are both exponentially large, then under a plausible assumption, no efficient algorithm exists. We show that, under the same assumption, if either the number of queries or the data universe is of exponential size, then there is no differentially private algorithm that answers all the queries. Specifically, we prove that if one-way functions and indistinguishability obfuscation exist, then: 1) For every $n$, there is a family $Q$ of $\tilde{O}(n^7)$ queries on a data universe $X$ of size $2^d$ such that no $poly(n,d)$ time differentially private algorithm takes a dataset $D \in X^n$ and outputs accurate answers to every query in $Q$. 2) For every $n$, there is a family $Q$ of $2^d$ queries on a data universe $X$ of size $\tilde{O}(n^7)$ such that no $poly(n,d)$ time differentially private algorithm takes a dataset $D \in X^n$ and outputs accurate answers to every query in $Q$. In both cases, the result is nearly quantitatively tight, since there is an efficient differentially private algorithm that answers $\tilde{\Omega}(n^2)$ queries on an exponential size data universe, and one that answers exponentially many queries on a data universe of size $\tilde{\Omega}(n^2)$. Our proofs build on the connection between hardness results in differential privacy and traitor-tracing schemes (Dwork et al., STOC\u2709; Ullman, STOC\u2713). We prove our hardness result for a polynomial size query set (resp., data universe) by showing that they follow from the existence of a special type of traitor-tracing scheme with very short ciphertexts (resp., secret keys), but very weak security guarantees, and then constructing such a scheme

In Pursuit of Clarity In Obfuscation

An account of meandering research efforts in the area of cryptographic obfuscation over several years

Three dimensions of central bank credibility and inferential expectations: The Euro zone

We use the behavior of inflation among Eurozone countries to provide information about the degree of credibility of the European Central Bank (ECB) since 2008. We define credibility along three dimensions–official target credibility, cohesion credibility and anchoring credibility–and show in a new econometric framework that the latter has deteriorated in recent history; that is, price setters are less likely to rely on the ECB target when forming inflation expectations

Strategies to Target Tumor Immunosuppression

The tumor microenvironment is currently in the spotlight of cancer immunology research as a key factor impacting tumor development and progression. While antigen-specific immune responses play a crucial role in tumor rejection, the tumor hampers these immune responses by creating an immunosuppressive microenvironment. Recently, major progress has been achieved in the field of cancer immunotherapy, and several groundbreaking clinical trials demonstrated the potency of such therapeutic interventions in patients. Yet, the responses greatly vary among individuals. This calls for the rational design of more efficacious cancer immunotherapeutic interventions that take into consideration the “immune signature” of the tumor. Multimodality treatment regimens that aim to enhance intratumoral homing and activation of antigen-specific immune effector cells, while simultaneously targeting tumor immunosuppression, are pivotal for potent antitumor immunity