Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Antidiabetic Regimens in Patients with Type 2 Diabetes Uncontrolled by Combination Therapy of Sulfonylurea and Metformin: Results of the MOHAS Disease Registry in Korea

Background The aim of this study was to investigate the glucose-lowering efficacy of antidiabetic treatments in patients with type 2 diabetes mellitus (T2DM) uncontrolled by sulfonylurea plus metformin. Methods This open-label, multicenter, prospective, observational study was conducted in 144 centers in Korea, from June 2008 to July 2010, and included patients with T2DM who had received sulfonylurea and metformin for at least 3 months and had levels of glycosylated hemoglobin (HbA1c) >7.0% in the last month. Data of clinical and biochemical characteristics were collected at baseline and 6 months after treatment. The treatment option was decided at the physician's discretion. Subjects were classified into the following three groups: intensifying oral hypoglycemic agents (group A), adding basal insulin (group B), or starting intensified insulin therapy (group C). Results Of 2,995 patients enrolled, 2,901 patients were evaluated, and 504 (17.4%), 2,316 (79.8%), and 81 patients (2.8%) were classified into groups A, B, and C, respectively. Subjects in group C showed relatively higher baseline levels of HbA1c and longer duration of diabetes. The mean decrease in HbA1c level was higher in the insulin treated groups (−0.9%±1.3%, −1.6%±1.3%, and −2.4%±2.3% in groups A, B, and C, respectively, P=0.042). The proportion of patients who achieved target HbA1c <7.0% was comparable among the groups; however, intensified insulin therapy seemed to be the most effective in achieving the target HbA1c of 6.5%. Conclusion These findings suggest that insulin-based therapy will be an important option in the improved management of Korean patients with T2DM whose glycemic control is not sufficient with sulfonylurea and metformin.
Selecting cases and controls for DNA sequencing studies using family histories of disease

Recent improvements in sequencing technology have enabled the investigation of so‐called missing heritability, and a large number of affected subjects have been sequenced in order to detect significant associations between human diseases and rare variants. However, the cost of genome sequencing is still high, and a statistically powerful strategy for selecting informative subjects would be useful. Therefore, in this report, we propose a new statistical method for selecting cases and controls for sequencing studies based on family history. We assume that disease status is determined by unobserved liability scores. Our method consists of two steps: first, the conditional means of liability are estimated with the liability threshold model given the individual's disease status and those of their relatives. Second, the informative subjects are selected with the estimated conditional means. Our simulation studies showed that statistical power is substantially affected by the subject selection strategy chosen, and power is maximized when affected (unaffected) subjects with high (low) risks are selected as cases (controls). The proposed method was successfully applied to genome‐wide association studies for type 2 diabetes, and our analysis results reveal the practical value of the proposed methods. Copyright © 2017 John Wiley & Sons, Ltd.
Differences in left ventricular remodelling in patients with aortic stenosis treated with transcatheter aortic valve replacement with corevalve prostheses compared to surgery with porcine or bovine biological prostheses

Aims Patients with severe aortic stenosis (AS) can be considered for treatment with either transcatheter (TAVR) or surgical aortic valve replacement (SAVR). The purpose of this study was to compare left ventricular (LV) remodeling in patients with AS after treatment with TAVR or SAVR. Methods and results This is an echocardiographic substudy of the NOTION trial, a randomized all-comers trial comparing TAVR with SAVR in patients above 70 years of age. Transthoracic echocardiograms were performed at baseline, 3 and 12 months after TAVR and SAVR. About 232 patients were included in the study, 120 were randomized to TAVR and 112 to SAVR. From baseline to 12 months post-procedure, aortic valve area (AVA) increased in both groups, but with a larger increase in the TAVR group (0.65 ± 0.04 cm2 vs. 1.02 ± 0.05 cm2 for SAVR and TAVR group, P < 0.0001). At 12 months, LV mass regression was more pronounced in the SAVR group as compared with TAVR (17.5% vs. 7.2%, P < 0.001). In the TAVR group at 12 months, end diastolic volume (EDV) increased by 10.2 ± 2.5 ml and, in the SAVR group, EDV decreased by 15.4 ± 2.6 ml with a statistically significant difference between the two groups (P < 0.0001). Paravalvular leakage (PVL) and pacemaker implantations were more common in patients treated with TAVR, which was associated with an increase in EDV (P < 0.01). Conclusion Patients undergoing SAVR had a larger LV mass regression at 1 year compared with patients undergoing TAVR, which may be due to increasing amounts of PVL and pacemakers in the TAVR group.
Simplified implementation and control of a flywheel energy system for microgrid applications

In this paper we present a simplified flywheel energy storage model using MATLAB Simulink environment for application in a microgrid. The proposed model utilizes a simplified charging and discharging model of a flywheel while preserving the kinetic characteristics using a mathematical model. Two test-cases of an islanded microgrid are presented as an application, where the flywheel system is employed to maintain the transient frequency stability and to regulate the frequency in the presence of intermittent sources as a part of the energy supply mix. The competitiveness of the emerging flywheels against batteries is also investigated based on the transient frequency stability criteria, in highlighting the viability of flywheels as a more efficient grid energy storage technology.
Location verification using secure distance bounding protocols

Authentication in conventional networks (like the Internet) is usually based upon something you know (e.g., a password), something you have (e.g., a smartcard) or something you are (biometrics). In mobile ad-hoc networks, location information can also be used to authenticate devices and users. We focus on how a provers can securely show that (s)he is within a certain distance to a verifier. Brands and Chaum proposed the distance bounding protocol as a secure solution for this problem. However, this protocol is vulnerable to a so-called "terrorist fraud attack". In this paper, we explain how to modify the distance bounding protocol to make it resistant to this kind of attacks. Recently, two other secure distance bounding protocols were published. We discuss the properties of these protocols and show how to use it as a building block in a location verification scheme
Kernel Slow Feature Analysis for Scene Change Detection

Scene change detection between multitemporal image scenes can be used to interpret the variation of regional land use, and has significant potential in the application of urban development monitoring at the semantic level. The traditional methods directly comparing the independent semantic classes neglect the temporal correlation, and thus suffer from accumulated classification errors. In this paper, we propose a novel scene change detection method via kernel slow feature analysis (KSFA) and postclassification fusion, which integrates independent scene classification with scene change detection to accurately determine scene changes and identify the “from-to” transition type. After representation with the bag-of-visual-words model, KSFA is proposed to extract the nonlinear temporally invariant features, to better measure the change probability between corresponding multitemporal image scenes. Two postclassification fusion methods, which are based on Bayesian theory and predefined rules, respectively, are then employed to identify the optimal coupled class combinations of multitemporal scene pairs. Furthermore, in addition to identifying semantic changes, the proposed method can also improve the performance of scene classification, since the unchanged scenes are more likely to belong to the same class. Two experiments with high-resolution remote sensing image scene data sets confirm that the proposed method can increase the accuracy of scene change detection, scene transition identification, and scene classification.
Toxin structures as evolutionary tools: Using conserved 3D folds to study the evolution of rapidly evolving peptides

Three‐dimensional (3D) structures have been used to explore the evolution of proteins for decades, yet they have rarely been utilized to study the molecular evolution of peptides. Here, we highlight areas in which 3D structures can be particularly useful for studying the molecular evolution of peptide toxins. Although we focus our discussion on animal toxins, including one of the most widespread disulfide‐rich peptide folds known, the inhibitor cystine knot, our conclusions should be widely applicable to studies of the evolution of disulfide‐constrained peptides. We show that conserved 3D folds can be used to identify evolutionary links and test hypotheses regarding the evolutionary origin of peptides with extremely low sequence identity; construct accurate multiple sequence alignments; and better understand the evolutionary forces that drive the molecular evolution of peptides.
The Italian National Rare Diseases Registry: a model of comparison and integration with Hospital Discharge Data

BACKGROUND Italy has been the first country at European level to implement a population-based public health registry dedicated to rare diseases. This study describes the current situation of the Italian National Rare Diseases Registry (NRDR) and compares its data with those from the National Hospital Discharge Database (HDD). METHODS Three rare diseases were analysed: Huntington disease (HD), Hereditary Haemorragic Telangiectasia (HHT) and Prader-Willi Syndrome (PWS), selected for their different characteristics. The two sources (NRDR and HDD) were linked: incidence rate ratio (IRR), sensitivity and predictive positive value (PPV) were calculated. RESULTS Incidence rates from NRDR and from HDD were compared by age groups, and IRR calculated: 1.08 for HD, 1.41 for HHT, 1.21 for PSW. For HD, sensitivity was 0.52 and PPV 0.48; for HHT sensitivity was 0.71 and PPV 0.52; for PWS the sensitivity was 0.71 and PPV 0.58. We found a strong regional variability in the results. CONCLUSIONS The integrated use of the two sources helps tracking those cases that are not captured by the Registry; further, it is a precious tool to accurately describe clinical histories of rare disease affected individuals, in terms of concomitant pathologies and medical procedures performed during hospitalization.
Signaling proteins in the spotlight

The mechanisms that regulate biomolecular function, interaction, and dynamics are an exciting area of signaling research. The molecular side of signaling still has many secrets to reveal. This Editorial Guide describes areas of particular interest with regard to understanding cellular regulation at the level of individual molecules and macromolecular complexes. Advances in technology and the accumulation of proteomic and genomic data reveal previously unknown components of signaling networks, the spatial organization of macromolecular complexes, and how information flows through the networks to produce specific cellular responses.
Identifying Forest Impacted by Development in the Commonwealth of Virginia through the Use of Landsat and Known Change Indicators

This study examines the effectiveness of using the Normalized Difference Vegetation Index (NDVI) derived from 1326 different Landsat Thematic Mapper and Enhanced Thematic Mapper images in finding low density development within the Commonwealth of Virginia’s forests. Individual NDVI images were stacked by year for the years 1995–2011 and the yearly maximum for each pixel was extracted, resulting in a 17-year image stack of all yearly maxima (a 98.7% data reduction). Using location data from housing starts and well permits, known previously forested housing starts were isolated from all other forest disturbance types. Samples from development disturbances and other forest disturbances, as well as from undisturbed forest, were used to derive vegetation index thresholds enabling separation of disturbed forest from undisturbed forest. Disturbances, once identified, could be separated into Development Disturbances and Non-Development Disturbances using a classification tree and only two variables from the Disturbance Detection and Diagnostics (D3) algorithm: the maximum NDVI in the available recovery period and the slope between the NDVI value at the time of the disturbance and the maximum NDVI in the available recovery period. Low density development disturbances of previous forest land cover had an F-measure, combining precision and recall into a single class-specific accuracy (β = 1), of 0.663. We compared our results to the NLCD 2001–2011 land cover changes from any forest (classes 41, 42, 43, and 90) to any developed (classes 21, 22, 23, and 24), resulting in an F-measure of 0.00 for the same validation points. Landsat time series stacks thus show promise for identifying even the small changes associated with low density development that have been historically overlooked/underestimated by prior mapping efforts. However, further research is needed to ensure that (1) the approach will work in other forest biomes and (2) enabling detection of these important, but spatially and spectrally subtle, disturbances still ensures accurate detection of other forest disturbances.
Historian: accurate reconstruction of ancestral sequences and evolutionary rates

Reconstruction of ancestral sequence histories, and estimation of parameters like indel rates, are improved by using explicit evolutionary models and summing over uncertain alignments. The previous best tool for this purpose (according to simulation benchmarks) was ProtPal, but this tool was too slow for practical use. Historian combines an efficient reimplementation of the ProtPal algorithm with performance-improving heuristics from other alignment tools. Simulation results on fidelity of rate estimation via ancestral reconstruction, along with evaluations on the structurally-informed alignment dataset BAliBase 3.0, recommend Historian over other alignment tools for evolutionary applications. Historian is available at https://github.com/ihh/indelhistorian under the Creative Commons Attribution 3.0 US license. Contact: Ian Holmes ihholmes+historian@gmail.com.
Neural perspectives on cognitive control development during childhood and adolescence should take into account how obesity affects brain development

Cognitive control comprises working memory, inhibition, cognitive flexibility and error monitoring and is closely tied to the development of the prefrontal cortex. The fact that the prefrontal cortex is important for cognitive control has been consistently shown among adults (1). Crone and Steinbeis explored new ways of categorising developmental progressions in cognitive control during childhood and adolescence (1). They revealed that the functional development of the dorsolateral prefrontal cortex supports the development of deliberative processes, whereas the medial prefrontal cortex supports the development of internalised decisions (1). We definitely agree with the prefrontal cortex model of cognitive control development, which takes into account the distinctions between the ventral–dorsal and the lateral–medial prefrontal cortex in children and adolescents. However, we also think that there is another very important factor that should be a fundamental part of this theoretical framework, that is the heavy burden of overweight and obesity during childhood and adolescence and its effects on cognitive control development. This paper draws attention to two important determinants related to paediatric obesity in this context: the influence of overweight and obesity on cognitive control during childhood and adolescence and how overweight and obesity might interfere with the Crone and Steinbeis model when differentiating between the ventral–dorsal and the lateral–medial prefrontal cortex. Obesity, which is defined as having excess body fat, is a major public health concern for children and adolescents. During the past 30 years, paediatric obesity has more than doubled in children and tripled in adolescents worldwide (2). Obesity in these age groups is clearly associated with a decreased ability to modulate the cognitive control network, as reflected by both electroencephalographic recordings, such as N2 and P3 components and error-related negativity, and behavioural measures (3). In addition, resting-state
PatentMiner: topic-driven patent analysis and mining

Patenting is one of the most important ways to protect company's core business concepts and proprietary technologies. Analyzing large volume of patent data can uncover the potential competitive or collaborative relations among companies in certain areas, which can provide valuable information to develop strategies for intellectual property (IP), R&D, and marketing. In this paper, we present a novel topic-driven patent analysis and mining system. Instead of merely searching over patent content, we focus on studying the heterogeneous patent network derived from the patent database, which is represented by several types of objects (companies, inventors, and technical content) jointly evolving over time. We design and implement a general topic-driven framework for analyzing and mining the heterogeneous patent network. Specifically, we propose a dynamic probabilistic model to characterize the topical evolution of these objects within the patent network. Based on this modeling framework, we derive several patent analytics tools that can be directly used for IP and R&D strategy planning, including a heterogeneous network co-ranking method, a topic-level competitor evolution analysis algorithm, and a method to summarize the search results. We evaluate the proposed methods on a real-world patent database. The experimental results show that the proposed techniques clearly outperform the corresponding baseline methods.
Rapid Microbiological Testing: Monitoring the Development of Bacterial Stress

The ability to respond to adverse environments effectively along with the ability to reproduce are sine qua non conditions for all sustainable cellular forms of life. Given the availability of an appropriate sensing modality, the ubiquity and immediacy of the stress response could form the basis for a new approach for rapid biological testing. We have found that measuring the dielectric permittivity of a cellular suspension, an easily measurable electronic property, is an effective way to monitor the response of bacterial cells to adverse conditions continuously. The dielectric permittivity of susceptible and resistant strains of Escherichia coli and Staphylococcus aureus, treated with gentamicin and vancomycin, were measured directly using differential impedance sensing methods and expressed as the Normalized Impedance Response (NIR). These same strains were also heat-shocked and chemically stressed with Triton X-100 or H2O2. The NIR profiles obtained for antibiotic-treated susceptible organisms showed a strong and continuous decrease in value. In addition, the intensity of the NIR value decrease for susceptible cells varied in proportion to the amount of antibiotic added. Qualitatively similar profiles were found for the chemically treated and heat-shocked bacteria. In contrast, antibiotic-resistant cells showed no change in the NIR values in the presence of the drug to which it is resistant. The data presented here show that changes in the dielectric permittivity of a cell suspension are directly correlated with the development of a stress response as well as bacterial recovery from stressful conditions. The availability of a practical sensing modality capable of monitoring changes in the dielectric properties of stressed cells could have wide applications in areas ranging from the detection of bacterial infections in clinical specimens to antibiotic susceptibility testing and drug discovery.
A Wideband Quad-Polarization Reconfigurable Metasurface Antenna

A low-profile wideband metasurface antenna with quad-polarization reconfiguration ability is presented in this paper. The proposed metasurface antenna is composed of a square patch, a metasurface formed by a lattice of <inline-formula> <tex-math notation="LaTeX">$4 \times 4$ </tex-math></inline-formula> periodic metal plates, and four switchable feeding probes connected with two designed single-pole double-throws switches. By properly selecting the feeding probes, the polarization of the metasurface antenna can be dynamically reconfigured among four polarization states, i.e., <inline-formula> <tex-math notation="LaTeX">$x$ </tex-math></inline-formula>-direction linear polarization, <inline-formula> <tex-math notation="LaTeX">$y$ </tex-math></inline-formula>-direction linear polarization, left-hand circular polarization, and right-hand circular polarization. To validate the proposed concept, a prototype operating at 5.6 GHz with a relatively height of <inline-formula> <tex-math notation="LaTeX">$0.067~\lambda _{0}$ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">$\lambda _{0}$ </tex-math></inline-formula> is the operating wavelength in free space) is designed, fabricated, and measured. The measured results show that both the 10-dB impedance bandwidths and the 3-dB axial ratio bandwidths are wider than 5.1–6.0 GHz for the linear and circular polarization states. The measured maximum gains are 9.39 dBic and 9.85 dBi for the circular polarization states and the linear polarization states, respectively. The simulation and experimentation verify that the proposed antenna can achieve quad-polarization reconfigurable features in a wide frequency band, which indicate the good performance of the proposed polarization reconfigurable metasurface antenna.
Calcium Fluoride Nanocrystals: Tracers for In Vivo 19 F Magnetic Resonance Imaging.

Inorganic nanocrystals (NCs) have been extensively developed for a variety of uses. The ability to obtain high-resolution NMR signals from the core nuclei of NCs in solution could offer new opportunities in materials sciences and MR imaging. Herein, we demonstrate that small, water-soluble 19 F-ionic NCs can average out homonuclear dipolar interactions, enabling one to obtain high-resolution 19 F NMR signals in solution that reflect the MR properties of F- in the crystal core. Decorating 19 F-NC surfaces with a biocompatible poly(ethylene glycol) coating maintains colloidal stability in water while preserving the NC high-resolution 19 F NMR properties, even after further functionalization. The high content and magnetic equivalence of the fluorides within the NCs enable their use as imaging tracers for in vivo 19 F MRI by facilitating a "hot-spot" display of their distribution.
A bilinear illumination model for robust face recognition

We present a technique to generate an illumination subspace for arbitrary 3D faces based on the statistics of measured illuminations under variable lighting conditions from many subjects. A bilinear model based on the higher-order singular value decomposition is used to create a compact illumination subspace given arbitrary shape parameters from a parametric 3D face model. Using a fitting procedure based on minimizing the distance of the input image to the dynamically changing illumination subspace, we reconstruct a shape-specific illumination subspace from a single photograph. We use the reconstructed illumination subspace in various face recognition experiments with variable lighting conditions and obtain accuracies which are very competitive with previous methods that require specific training sessions or multiple images of the subject