Do personal conditions and circumstances surrounding partner loss explain loneliness in newly bereaved older adults?

This longitudinal study aims to explain loneliness in newly bereaved older adults, taking into account personal and circumstantial conditions surrounding the partner's death. A distinction is made between emotional and social loneliness. Data were gathered both before and after partner loss. Results were interpreted within the framework of the Theory of Mental Incongruity. The findings reveal that being unable to anticipate the partner's death is related to higher levels of emotional loneliness. Standards of instrumental support, measured indirectly by poor physical condition, lead to stronger emotional as well as social loneliness. Standards measured directly by importance attached to support or contacts result in higher emotional loneliness but, unexpectedly, in lower social loneliness. Furthermore, difficulties with establishing personal contacts, caused, for instance, by social anxiety, add to loneliness. It is concluded that circumstances related to the partner's illness may contribute to emotional loneliness after bereavement. Moreover, the results highlight the importance of taking coping attitudes into consideration for a better understanding of how newly bereaved older adults adapt to the loss of a partner

Imaginary Quadratic Class Groups and a Survey of Time-Lock Cryptographic Applications

Imaginary quadratic class groups have been proposed as one of the main hidden-order group candidates for time-lock cryptographic applications such as verifiable delay functions (VDFs). They have the advantage over RSA groups that they do \emph{not} need a trusted setup. However, they have historically been significantly less studied by the cryptographic research community. This survey provides an introduction to the theory of imaginary quadratic class groups and discusses several considerations that need to be taken into account for practical applications. In particular, we describe the relevant computational problems and the main classical and quantum algorithms that can be used to solve them. From this discussion, it follows that choosing a discriminant $\Delta=-p$ with $p\equiv 3\mod{4}$ prime is one of the most promising ways to pick a class group \CL(\Delta) without the need for a trusted setup, while simultaneously making sure that there are no easy to find elements of low order in \CL(\Delta). We provide experimental data on class groups belonging to discriminants of this form, and compare them to the Cohen-Lenstra heuristics which predict the average behaviour of \CL(\Delta) belonging to a random \emph{fundamental} discriminant. Afterwards, we describe the most prominent constructions of VDFs based on hidden-order groups, and discuss their soundness and sequentiality when implemented in imaginary quadratic class groups. Finally, we briefly touch upon the post-quantum security of VDFs in imaginary quadratic class groups, where the time on can use a fixed group is upper bounded by the runtime of quantum polynomial time order computation algorithms

Fuzzy Private Set Intersection with Large Hyperballs

Traditional private set intersection (PSI) involves a receiver and a sender holding sets $X$ and $Y$, respectively, with the receiver learning only the intersection $X\cap Y$. We turn our attention to its fuzzy variant, where the receiver holds $|X|$ hyperballs of radius $\delta$ in a metric space and the sender has $|Y|$ points. Representing the hyperballs by their center, the receiver learns the points $x\in X$ for which there exists $y\in Y$ such that $\mathsf{dist}(x,y)\leq \delta$ with respect to some distance metric. Previous approaches either require general-purpose multi-party computation (MPC) techniques like garbled circuits or fully homomorphic encryption (FHE), leak details about the sender’s precise inputs, support limited distance metrics, or scale poorly with the hyperballs\u27 volume. This work presents the first black-box construction for fuzzy PSI (including other variants such as PSI cardinality, labeled PSI, and circuit PSI), which can handle polynomially large radius and dimension (i.e., a potentially exponentially large volume) in two interaction messages, supporting general $L_{p\in[1,\infty]}$ distance, without relying on garbled circuits or FHE. The protocol excels in both asymptotic and concrete efficiency compared to existing works. For security, we solely rely on the assumption that the Decisional Diffie-Hellman (DDH) holds in the random oracle model

Transcription profiling of rheumatic diseases

Rheumatic diseases are a diverse group of disorders. Most of these diseases are heterogeneous in nature and show varying responsiveness to treatment. Because our understanding of the molecular complexity of rheumatic diseases is incomplete and criteria for categorization are limited, we mainly refer to them in terms of group averages. The advent of DNA microarray technology has provided a powerful tool to gain insight into the molecular complexity of these diseases; this technology facilitates open-ended survey to identify comprehensively the genes and biological pathways that are associated with clinically defined conditions. During the past decade, encouraging results have been generated in the molecular description of complex rheumatic diseases, such as rheumatoid arthritis, systemic lupus erythematosus, Sjögren syndrome and systemic sclerosis. Here, we describe developments in genomics research during the past decade that have contributed to our knowledge of pathogenesis, and to the identification of biomarkers for diagnosis, patient stratification and prognostication

On time-lock cryptographic assumptions in abelian hidden-order groups

In this paper we study cryptographic finite abelian groups of unknown order and hardness assumptions in these groups. Abelian groups necessitate multiple group generators, which may be chosen at random. We formalize this setting and hardness assumptions therein. Furthermore, we generalize the algebraic group model and strong algebraic group model from cyclic groups to arbitrary finite abelian groups of unknown order. Building on these formalizations, we present techniques to deal with this new setting, and prove new reductions. These results are relevant for class groups of imaginary quadratic number fields and time-lock cryptography build upon them

The Implementation of Brazil Sustainable Urban Mobility Policy

Institute of Transport and Logistics Studies. Faculty of Economics and Business. The University of Sydne

The Gene Expression Profile in the Synovium as a Predictor of the Clinical Response to Infliximab Treatment in Rheumatoid Arthritis

Background: Although the use of TNF inhibitors has fundamentally changed the way rheumatoid arthritis (RA) is treated, not all patients respond well. It is desirable to facilitate the identification of responding and non-responding patients prior to treatment, not only to avoid unnecessary treatment but also for financial reasons. In this work we have investigated the transcriptional profile of synovial tissue sampled from RA patients before anti-TNF treatment with the aim to identify biomarkers predictive of response. Methodology/Principal Findings: Synovial tissue samples were obtained by arthroscopy from 62 RA patients before the initiation of infliximab treatment. RNA was extracted and gene expression profiling was performed using an in-house spotted long oligonucleotide array covering 17972 unique genes. Tissue sections were also analyzed by immunohistochemistry to evaluate cell infiltrates. Response to infliximab treatment was assessed according to the EULAR response criteria. The presence of lymphocyte aggregates dominated the expression profiles and a significant overrepresentation of lymphocyte aggregates in good responding patients confounded the analyses. A statistical model was set up to control for the effect of aggregates, but no differences could be identified between responders and non-responders. Subsequently, the patients were split into lymphocyte aggregate positive-and negative patients. No statistically significant differences could be identified except for 38 transcripts associated with differences between good- and non-responders in aggregate positive patients. A profile was identified in these genes that indicated a higher level of metabolism in good responding patients, which indirectly can be connected to increased inflammation. Conclusions/Significance: It is pivotal to account for the presence of lymphoid aggregates when studying gene expression patterns in rheumatoid synovial tissue. In spite of our original hypothesis, the data do not support the notion that microarray analysis of whole synovial biopsy specimens can be used in the context of personalized medicine to identify non-responders to anti-TNF therapy before the initiation of treatmen