On the shortness of vectors to be found by the Ideal-SVP quantum algorithm

The hardness of finding short vectors in ideals of cyclotomic number fields (hereafter, Ideal-SVP) can serve as a worst-case assumption for numerous efficient cryptosystems, via the average-case problems Ring-SIS and Ring-LWE. For a while, it could be assumed the Ideal-SVP problem was as hard a

Cohort profile: the Utrecht Cardiovascular Cohort-Second Manifestations of Arterial Disease (UCC-SMART) Study-an ongoing prospective cohort study of patients at high cardiovascular risk in the Netherlands

PURPOSE: The Utrecht Cardiovascular Cohort-Second Manifestations of Arterial Disease (UCC-SMART) Study is an ongoing prospective single-centre cohort study with the aim to assess important determinants and the prognosis of cardiovascular disease progression. This article provides an update of the rationale, design, included patients, measurements and findings from the start in 1996 to date. PARTICIPANTS: The UCC-SMART Study includes patients aged 18-90 years referred to the University Medical Center Utrecht, the Netherlands, for management of cardiovascular disease (CVD) or severe cardiovascular risk factors. Since September 1996, a total of 14 830 patients have been included. Upon inclusion, patients undergo a standardised screening programme, including questionnaires, vital signs, laboratory measurements, an ECG, vascular ultrasound of carotid arteries and aorta, ankle-brachial index and ultrasound measurements of adipose tissue, kidney size and intima-media thickness. Outcomes of interest are collected through annual questionnaires and adjudicated by an endpoint committee. FINDINGS TO DATE: By May 2022, the included patients contributed to a total follow-up time of over 134 000 person-years. During follow-up, 2259 patients suffered a vascular endpoint (including non-fatal myocardial infarction, non-fatal stroke and vascular death) and 2794 all-cause deaths, 943 incident cases of diabetes and 2139 incident cases of cancer were observed up until January 2020. The UCC-SMART cohort contributed to over 350 articles published in peer-reviewed journals, including prediction models recommended by the 2021 European Society of Cardiology CVD prevention guidelines. FUTURE PLANS: The UCC-SMART Study guarantees an infrastructure for research in patients at high cardiovascular risk. The cohort will continue to include about 600 patients yearly and follow-up will be ongoing to ensure an up-to-date cohort in accordance with current healthcare and scientific knowledge. In the near future, UCC-SMART will be enriched by echocardiography, and a food frequency questionnaire at baseline enabling the assessment of associations between nutrition and CVD and diabetes

The deuteron: structure and form factors

A brief review of the history of the discovery of the deuteron in provided. The current status of both experiment and theory for the elastic electron scattering is then presented.Comment: 80 pages, 33 figures, submited to Advances in Nuclear Physic

MArBled Circuits: Mixing Arithmetic and Boolean Circuits with Active Security

Most modern actively-secure multiparty computation (MPC) protocols involve generating random data that is secret-shared and authenticated, and using it to evaluate arithmetic or Boolean circuits in different ways. In this work we present a generic method for converting authenticated secret-shared data between different fields, and show how to use it to evaluate so-called ``mixed\u27\u27 circuits with active security and in the full-threshold setting. A mixed circuit is one in which parties switch between different subprotocols dynamically as computation proceeds, the idea being that some protocols are more efficient for evaluating arithmetic circuits, and others for Boolean circuits. One use case of our switching mechanism is for converting between secret-sharing-based MPC and garbled circuits (GCs). The former is more suited to the evaluation of arithmetic circuits and can easily be used to emulate arithmetic over the integers, whereas the latter is better for Boolean circuits and has constant round complexity. Much work already exists in the two-party semi-honest setting, but the $n$-party dishonest majority case was hitherto neglected. We call the actively-secure mixed arithmetic/Boolean circuit a marbled circuit. Our implementation showed that mixing protocols in this way allows us to evaluate a linear Support Vector Machine with $400$ times fewer AND gates than a solution using GC alone albeit with twice the preprocessing required using only SPDZ (Damgård et al., CRYPTO \u2712), and thus our solution offers a tradeoff between online and preprocessing complexity. When evaluating over a WAN network, our online phase is $10$ times faster than the plain SPDZ protocol

Ovarian cancer histology-specific incidence trends in Canada 1969–1993: age-period-cohort analyses

This study examined histology-specific incidence trends of ovarian cancer in Canada, 1969–1993. The impact of age, period and cohort effects on these trends were studied by means of age-period-cohort analysis. Age-standardized incidence rates of serous, endometrioid, clear cell and germ cell tumours increased significantly and the rates of sex cord-stromal and other classified epithelial ovarian tumours decreased considerably. The rates of mucinous and NOS/unclassified tumours remained unchanged. Cohort effect has a major impact on incidence trends of serous, endometrioid, germ cell, sex cord-stromal and other classified epithelial ovarian tumours but no meaningful impact on trends of mucinous, clear cell, or NOS/unclassified ovarian tumours. Various cohort patterns by histology subtypes were observed: the risk of developing serious tumours increased markedly among birth cohorts of 1895–1930, stabilized thereafter and decreased among young cohorts of 1950–1960; the risk of germ cell tumours increased significantly among young cohorts of 1965–1980; and the risk of sex cord-stromal tumours dropped constantly among cohorts 1910–1950. Various period patterns by histology subtypes observed in this study suggested changes in histology classification criteria over the period. Further studies need to consider the various etiologies and the classification criteria changes according to histology subtypes. © 1999 Cancer Research Campaig

Efficient Protocols for Oblivious Linear Function Evaluation from Ring-LWE

An oblivious linear function evaluation protocol, or OLE, is a two-party protocol for the function $f(x) = ax + b$, where a sender inputs the field elements $a,b$, and a receiver inputs $x$ and learns $f(x)$. OLE can be used to build secret-shared multiplication, and is an essential component of many secure computation applications including general-purpose multi-party computation, private set intersection and more. In this work, we present several efficient OLE protocols from the ring learning with errors (RLWE) assumption. Technically, we build two new passively secure protocols, which build upon recent advances in homomorphic secret sharing from (R)LWE (Boyle et al., Eurocrypt 2019), with optimizations tailored to the setting of OLE. We upgrade these to active security using efficient amortized zero-knowledge techniques for lattice relations (Baum et al., Crypto 2018), and design new variants of zero-knowledge arguments that are necessary for some of our constructions. Our protocols offer several advantages over existing constructions. Firstly, they have the lowest communication complexity amongst previous, practical protocols from RLWE and other assumptions; secondly, they are conceptually very simple, and have just one round of interaction for the case of OLE where $b$ is randomly chosen. We demonstrate this with an implementation of one of our passively secure protocols, which can perform more than 1 million OLEs per second over the ring $\mathbb{Z}_m$, for a 120-bit modulus $m$, on standard hardware

Let’s not forget tautomers

A compound exhibits tautomerism if it can be represented by two structures that are related by an intramolecular movement of hydrogen from one atom to another. The different tautomers of a molecule usually have different molecular fingerprints, hydrophobicities and pKa’s as well as different 3D shape and electrostatic properties; additionally, proteins frequently preferentially bind a tautomer that is present in low abundance in water. As a result, the proper treatment of molecules that can tautomerize, ~25% of a database, is a challenge for every aspect of computer-aided molecular design. Library design that focuses on molecular similarity or diversity might inadvertently include similar molecules that happen to be encoded as different tautomers. Physical property measurements might not establish the properties of individual tautomers with the result that algorithms based on these measurements may be less accurate for molecules that can tautomerize—this problem influences the accuracy of filtering for library design and also traditional QSAR. Any 2D or 3D QSAR analysis must involve the decision of if or how to adjust the observed Ki or IC50 for the tautomerization equilibria. QSARs and recursive partitioning methods also involve the decision as to which tautomer(s) to use to calculate the molecular descriptors. Docking virtual screening must involve the decision as to which tautomers to include in the docking and how to account for tautomerization in the scoring. All of these decisions are more difficult because there is no extensive database of measured tautomeric ratios in both water and non-aqueous solvents and there is no consensus as to the best computational method to calculate tautomeric ratios in different environments

Dual targeting of p53 and c-MYC selectively eliminates leukaemic stem cells

e Glasgow and Manchester Experimental Cancer Medicine Centres (ECMC), which are funded by CR-UK and the Chief Scientist’s Office (Scotland). We acknowledge the funders who have contributed to this work: MRC stratified medicine infrastructure award (A.D.W.), CR-UK C11074/A11008 (F.P., L.E.M.H., T.L.H., A.D.W.); LLR08071 (S.A.A., E.C.); LLR11017 (M.C.); SCD/04 (M.C.); LLR13035 (S.A.A., K.D., A.D.W., and A.P.); LLR14005 (M.T.S., D.V.); KKL690 (L.E.P.); KKL698 (P.B.); LLR08004 (A.D.W., A.P. and A.J.W.); MRC CiC (M.E.D.); The Howat Foundation (FACS support); Friends of Paul O’Gorman (K.D. and FACS support); ELF 67954 (S.A.A.); BSH start up fund (S.A.A.); MR/K014854/1 (K.D.)

A Macroecological Analysis of SERA Derived Forest Heights and Implications for Forest Volume Remote Sensing

Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H100, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H100 and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 102–106 plants/hectare and heights 6–49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H100