Verifiable Random Functions (VRFs)

A Verifiable Random Function (VRF) is the public-key version of a keyed cryptographic hash. Only the holder of the private key can compute the hash, but anyone with public key can verify the correctness of the hash. VRFs are useful for preventing enumeration of hash-based data structures. This document specifies several VRF constructions that are secure in the cryptographic random oracle model. One VRF uses RSA and the other VRF uses Eliptic Curves (EC).https://datatracker.ietf.org/doc/draft-irtf-cfrg-vrf/First author draf

NSEC5, DNSSEC authenticated denial of existence

The Domain Name System Security Extensions (DNSSEC) introduced two resource records (RR) for authenticated denial of existence: the NSEC RR and the NSEC3 RR. This document introduces NSEC5 as an alternative mechanism for DNSSEC authenticated denial of existence. NSEC5 uses verifiable random functions (VRFs) to prevent offline enumeration of zone contents. NSEC5 also protects the integrity of the zone contents even if an adversary compromises one of the authoritative servers for the zone. Integrity is preserved because NSEC5 does not require private zone-signing keys to be present on all authoritative servers for the zone, in contrast to DNSSEC online signing schemes like NSEC3 White Lies.https://datatracker.ietf.org/doc/draft-vcelak-nsec5/First author draf

Extended Transfer Bound Error Analysis for Parametric Channel withContinuous Valued Correlated Random Nuisance Parameter

In this paper, we address the extended use of transfer bound analysis of bit error rate (BER) properties. In conjunction with proper parameter modeling, we offer a method to resolve the problem of transfer bound applicability on a system with random and possibly correlated continuous value nuisance parameters. We introduce a new additional parameter space into the original error space and join them in a product matrix for an extended transfer function evaluation. Example applications with simple trellis code for Rayleigh fading channel and phase synchronization error are investigated to demonstrate the functionality of the proved principle. Computer simulation results are presented for two different codes and various fading scenarios, and comparisons are made among analytical and measured system error performances

Impact of FTO genotypes on BMI and weight in polycystic ovary syndrome : a systematic review and meta-analysis

Aims/hypothesis FTO gene single nucleotide polymorphisms (SNPs) have been shown to be associated with obesity-related traits and type 2 diabetes. Several small studies have suggested a greater than expected effect of the FTO rs9939609 SNP on weight in polycystic ovary syndrome (PCOS). We therefore aimed to examine the impact of FTO genotype on BMI and weight in PCOS. Methods A systematic search of medical databases (PubMed, EMBASE and Cochrane CENTRAL) was conducted up to the end of April 2011. Seven studies describing eight distinct PCOS cohorts were retrieved; seven were genotyped for SNP rs9939609 and one for SNP rs1421085. The per allele effect on BMI and body weight increase was calculated and subjected to meta-analysis. Results A total of 2,548 women with PCOS were included in the study; 762 were TT homozygotes, 1,253 had an AT/CT genotype, and 533 were AA/CC homozygotes. Each additional copy of the effect allele (A/C) increased the BMI by a mean of 0.19 z score units (95% CI 0.13, 0.24; p = 2.26 × 10−11) and body weight by a mean of 0.20 z score units (95% CI 0.14, 0.26; p = 1.02 × 10−10). This translated into an approximately 3.3 kg/m2 increase in BMI and an approximately 9.6 kg gain in body weight between TT and AA/CC homozygotes. The association between FTO genotypes and BMI was stronger in the cohorts with PCOS than in the general female populations from large genome-wide association studies. Deviation from an additive genetic model was observed in heavier populations. Conclusions/interpretation The effect of FTO SNPs on obesity-related traits in PCOS seems to be more than two times greater than the effect found in large population-based studies. This suggests an interaction between FTO and the metabolic context or polygenic background of PCOS

Extending BIM for air quality monitoring

As we spend more than 90% of our time inside buildings, indoor environmental quality is a major concern for healthy living. Recent studies show that almost 80% of people in European countries and the United States suffer from SBS (Sick Building Syndrome), which affects physical health, productivity and psychological well-being. In this context, environmental quality monitoring provides stakeholders with crucial information about indoor living conditions, thus facilitating building management along its lifecycle, from design, construction and commissioning to usage, maintenance and end-of-life. However, currently available modelling tools for building management remain limited to static models and lack integration capacities to efficiently exploit environmental quality monitoring data. In order to overcome these limitations, we designed and implemented a generic software architecture that relies on accessible Building Information Model (BIM) attributes to add a dynamic layer that integrates environmental quality data coming from deployed sensors. Merging sensor data with BIM allows creation of a digital twin for the monitored building where live information about environmental quality enables evaluation through numerical simulation. Our solution allows accessing and displaying live sensor data, thus providing advanced functionality to the end-user and other systems in the building. In order to preserve genericity and separation of concerns, our solution stores sensor data in a separate database available through an application programming interface (API), which decouples BIM models from sensor data. Our proof-of-concept experiments were conducted with a cultural heritage building located in Bled, Slovenia. We demonstrated that it is possible to display live information regarding environmental quality (temperature, relative humidity, CO2, particle matter, light) using Revit as an example, thus enabling end-users to follow the conditions of their living environment and take appropriate measures to improve its quality.Pages 244-250

MTNR1B Genetic Variability Is Associated with Gestational Diabetes in Czech Women

The gene MTNR1B encodes a receptor for melatonin. Melatonin receptors are expressed in human -cells, which implies that genetic variants might affect glucose tolerance. Meta-analysis confirmed that the rs10830963 shows the most robust association. The aim of the study was to assess the rs10830963 in Czech GDM patients and controls and to study relations between the SNP and biochemical as well as anthropometric characteristics. Our cohort consisted of 880 women; 458 were diagnosed with GDM, and 422 were normoglycemic controls without history of GDM. Despite similar BMI, the GDM group showed higher WHR, waist circumference, abdominal circumference, and total body fat content. The risk allele G was more frequent in the GDM group (38.3 versus 29.4% in controls, OR 1.49 CI95% [1.22; 1.82]; OR = 0.0001). In spite of higher frequency, the G allele in the GDM group was not associated with any markers of glucose metabolism. In contrast, controls showed significant association of the allele G with FPG and with postchallenge glycemia during the oGTT. Frequency analysis indicates that rs10830963 is involved in gestational diabetes in Czech women. However, the association of the SNP with glucose metabolism, which is obvious in controls, is covert in women who have experienced GDM

Insulin sensitivity and secretion in obese Type 2 diabetic women after various bariatric operations

Objective: To compare the effects of biliopancreatic diversion (BPD) and laparoscopic gastric banding (LAGB) on insulin sensitivity and secretion with the effects of laparoscopic gastric plication (P). Methods: A total of 52 obese women (age 30-66 years) suffering from type 2 diabetes mellitus (T2DM) were prospectively recruited into three study groups: 16 BPD; 16 LAGB, and 20 P. Euglycemic clamps and mixed meal tolerance tests were performed before, at 1 month and at 6 months after bariatric surgery. Beta cell function derived from the meal test parameters was evaluated using mathematical modeling. Results: Glucose disposal per kilogram of fat free mass (a marker of peripheral insulin sensitivity) increased significantly in all groups, especially after 1 month. Basal insulin secretion decreased significantly after all three types of operations, with the most marked decrease after BPD compared with P and LAGB. Total insulin secretion decreased significantly only following the BPD. Beta cell glucose sensitivity did not change significantly post-surgery in any of the study groups. Conclusion: We documented similar improvement in insulin sensitivity in obese T2DM women after all three study operations during the 6-month postoperative follow-up. Notably, only BPD led to decreased demand on beta cells (decreased integrated insulin secretion), but without increasing the beta cell glucose sensitivity

Wearable wireless inertial measurement for sports applications

The advent of MEMS inertial sensors has reduced the size, cost and power requirements of 6 Degrees-of-Freedom inertial measurement systems to a level where their use can be considered for wearable wireless monitoring devices. Many applications for such Wearable Wireless Inertial Measurement Units exist in the area of sports and sports science. Such a system would be critical in providing data for the analysis of the kinematic motion data of an athlete - to characterise a player’s technique or track progress and provide accurate, quantitative feedback to player and coach in near real time. A small, lightweight and low power device with the ability to sense the full range of human motion at a high sampling rate is required for such applications. It must also be robust, well sealed and comfortable to wear. Further development and miniaturisation of such devices coupled with progress in energy scavenging may lead to their use in other areas and their near ubiquity, with the potential to be embedded within clothes, buildings, materials, objects and people for health monitoring, location tracking and other purpose