Miracle-dz/UniFAR-FTUs huggingface dataset:
The Edinburgh CT and genetic diagnostic criteria for lobar intracerebral haemorrhage with cerebral amyloid angiopathy: model development and diagnostic test accuracy study

Summary Background Identification of lobar spontaneous intracerebral haemorrhage associated with cerebral amyloid angiopathy (CAA) is important because it is associated with a higher risk of recurrent intracerebral haemorrhage than arteriolosclerosis-associated intracerebral haemorrhage. We aimed to develop a prediction model for the identification of CAA-associated lobar intracerebral haemorrhage using CT features and genotype. Methods We identified adults with first-ever intracerebral haemorrhage diagnosed by CT, who died and underwent research autopsy as part of the Lothian IntraCerebral Haemorrhage, Pathology, Imaging and Neurological Outcome (LINCHPIN) study, a prospective, population-based, inception cohort. We determined APOE genotype and radiologists rated CT imaging appearances. Radiologists were not aware of clinical, genetic, and histopathological features. A neuropathologist rated brain tissue for small vessel diseases, including CAA, and was masked to clinical, radiographic, and genetic features. We used CT and APOE genotype data in a logistic regression model, which we internally validated using bootstrapping, to predict the risk of CAA-associated lobar intracerebral haemorrhage, derive diagnostic criteria, and estimate diagnostic accuracy. Findings was lobar in 62 (56%) participants, deep in 41 (37%), and infratentorial in seven (6%). Of the 62 participants with lobar intracerebral haemorrhage, 36 (58%) were associated with moderate or severe CAA compared with 26 (42%) that were associated with absent or mild CAA, and were independently associated with subarachnoid haemorrhage (32 [89%] of 36 vs 11 [42%] of 26; p=0·014), intracerebral haemorrhage with finger-like projections (14 [39%] of 36 vs 0; p=0·043), and APOE ε4 possession (18 [50%] of 36 vs 2 [8%] of 26; p=0·0020). A prediction model for CAA-associated lobar intracerebral haemorrhage using these three variables had excellent discrimination (c statistic 0·92, 95% CI 0·86–0·98), confirmed by internal validation. For the rule-out criteria, neither subarachnoid haemorrhage nor APOE ε4 possession had 100% sensitivity (95% CI 88–100). For the rule-in criteria, subarachnoid haemorrhage and either APOE ε4 possession or finger-like projections had 96% specificity (95% CI 78–100). Interpretation The CT and APOE genotype prediction model for CAA-associated lobar intracerebral haemorrhage shows excellent discrimination in this cohort, but requires external validation. The Edinburgh rule-in and rule-out diagnostic criteria might inform prognostic and therapeutic decisions that depend on identification of CAA-associated lobar intracerebral haemorrhage.
Weight management practices associated with PCOS and their relationships with diet and physical activity

STUDY QUESTION Do weight management practices differ in women with and without PCOS? SUMMARY ANSWER Women in the general population with self-reported PCOS are more likely to be using healthy weight management practices and alternative non-lifestyle measures for weight management than women without PCOS. WHAT IS KNOWN ALREADY Lifestyle management is the first-line treatment in PCOS. However, the specific weight management practices used by women with PCOS and their effect on diet and physical activity are unclear. STUDY DESIGN, SIZE, DURATION The study was a population-based observational cross-sectional study involving women in the 1973-1978 cohort (n = 7767 total; n = 556 with PCOS, n = 7211 without PCOS). PARTICIPANTS/MATERIALS, SETTING, METHODS Women with and without self-reported PCOS were included. Self-reported outcome measures included healthy lifestyle-related or alternative non-lifestyle-related (e.g. laxatives or smoking) weight management practices, dietary intake and physical activity. MAIN RESULTS AND THE ROLE OF CHANCE Women with PCOS were more likely to be following both healthy [reducing meal or snack size (odds ratio (OR) 1.50, 95% CI 1.14, 1.96, P = 0.004) and reducing fat or sugar intake (OR 1.32, 95% CI 1.03, 1.69, P = 0.027) or following a low glycaemic index diet (OR 2.88, 95% CI 2.30, 3.59, P < 0.001)] and alternative [smoking (OR 1.60, 95% CI 1.02, 2.52, P = 0.043) or use of laxative, diet pills, fasting or diuretics (OR 1.45, 95% CI 1.07, 1.97, P = 0.017)] weight management practices than women without PCOS. In PCOS, the use of a range of healthy weight management practices was associated with increases in physical activity (P < 0.001), diet quality (P < 0.001), percentage protein intake (P < 0.001) and decreases in glycaemic index (P < 0.001), and percentages of fat (P = 0.001), saturated fat (P < 0.001) or fibre (P = 0.003). Use of alternative weight management practices was associated with decreases in diet quality. LIMITATIONS, REASONS FOR CAUTION Limitations include the use of self-reported data for PCOS, height, weight, diet, physical activity and weight management behaviours. WIDER IMPLICATIONS OF THE FINDINGS In PCOS, we should focus on improving healthy weight practices across both diet quality and quantity, and on assessing alternative weight practices and their potential adverse effect on dietary intake. STUDY FUNDING/COMPETING INTEREST(S) L.M. is supported by a South Australian Cardiovascular Research Development Program Fellowship (ID AC11S374); a program collaboratively funded by the National Heart Foundation, the South Australian Department of Health and the South Australian Health and Medical Research Institute. H.T. is supported by the NHMRC. S.A.M. is supported by an NHMRC Career Development Fellowship Level 2, ID1104636 and was previously supported by an ARC Future Fellowship (2011-2015, FT100100581). The authors declare no conflict of interest. TRIAL REGISTRATION NUMBER Not applicable.
UvA-DARE ( Digital Academic Repository ) Simulating induced interdigitation in membranes

In this study we introduce a mesoscopic lipid-water-alcohol model. Dissipative particle dynamics (DPD) simulations have been used to investigate the induced interdigitation of bilayers consisting of double-tail lipids by adding alcohol molecules to the bilayer. Our simulations nicely reproduce the experimental phase diagrams. We find that alcohol can induce an interdigitated structure where the common bilayer structure changes into monolayer in which the alcohol molecules screen the hydrophobic tails from the water phase. At low concentrations of alcohol the membrane has domains of the interdigitated phase that are in coexistence with the common membrane phase. We compute the effect of the chain length of the alcohol on the phase behavior of the membrane and show that the stability of the interdigitated phase depends on the length of the alcohol. We show that we can reproduce the experimental hydrophobic thickness of the bilayer for various combinations of lipids and alcohols. We use our model to clarify some of the experimental questions related to the structure of the interdigitated phase and put forward a simple model that explains the alcohol chain length dependence of the stability of this interdigitated phase.
Varistor Behavior at Twin Boundaries in ZnO

The electrical behavior of commercial ZnO varistor devices has been examined with voltage contrast microscopy and point contact dc electrical measurements. Nonlinear voltage-dependent behavior has been observed across both of the major crystalline boundary types present in the system: Bi2O3 layer containing ZnO grain boundaries (or grain boundaries) and antimony spinel layer internal ZnO inversion twin boundaries (or twin boundaries). Twin boundaries, which bisect practically every grain in a typical commercial device, possess potential barriers with higher average breakdown voltages than do grain boundaries. Certain zinc antimonate spinel (Zn7Sb2O12) grains are electrically isolated from the matrix, whereas others are conductive within the matrix.
A framework for data prefetching using off-line training of Markovian predictors

An important technique for alleviating the memory bottleneck is data prefetching. Data prefetching solutions ranging from pure software approach by inserting prefetch instructions through program analysis to purely hardware mechanisms have been proposed. The degrees of success of those techniques are dependent on the nature of the applications. The need for innovative approach is rapidly growing with the introduction of applications such as object-oriented applications that show dynamically changing memory access behavior In this paper, we propose a novel framework for the use of data prefetchers that are trained off-line using smart learning algorithms to produce prediction models which captures hidden memory access patterns. Once built, those prediction models are loaded into a data prefetching unit in the CPU at the appropriate point during the runtime to drive the prefetching. On average by using table size of about 8KB size, we were able to achieve prediction accuracy of about 68% through our own proposed learning method and performance was boosted about 37% on average on the benchmarks we tested. Furthermore, we believe our proposed framework is amenable to other predictors and can be done as a phase of the profiling-optimizing-compiler.
ω-3 Fatty Acids and Cardiovascular Diseases: Effects, Mechanisms and Dietary Relevance

ω-3 fatty acids (n-3 FA) have, since the 1970s, been associated with beneficial health effects. They are, however, prone to lipid peroxidation due to their many double bonds. Lipid peroxidation is a process that may lead to increased oxidative stress, a condition associated with adverse health effects. Recently, conflicting evidence regarding the health benefits of intake of n-3 from seafood or n-3 supplements has emerged. The aim of this review was thus to examine recent literature regarding health aspects of n-3 FA intake from fish or n-3 supplements, and to discuss possible reasons for the conflicting findings. There is a broad consensus that fish and seafood are the optimal sources of n-3 FA and consumption of approximately 2–3 servings per week is recommended. The scientific evidence of benefits from n-3 supplementation has diminished over time, probably due to a general increase in seafood consumption and better pharmacological intervention and acute treatment of patients with cardiovascular diseases (CVD).
Spectral-spatial hybrid mechanism for feature detection using spectral correlation

This paper discusses the way in which the contiguous nature of spectral bands was exploited to generate an additional set of features to improve the overall accuracy of feature detection in hyperspectral images. The additional set of features was generated using the correlation between the spectral bands of a neighbourhood of pixels. This incorporates spatial information into the classification algorithm. This method of incorporating spatial information of a Hyperspectral image, and the method of combining it with the spectral information in the classification algorithm could be considered as two novel concepts introduced in this paper. The proposed approach follows an unsupervised procedure and produces results with an increase of more than 5% in the accuracy level, compared to the case where only the spectral data is used.
Deep Reinforcement Learning (DRL)-based Resource Management in Software-Defined and Virtualized Vehicular Ad Hoc Networks

Vehicular ad hoc networks (VANETs) have attracted great interests from both industry and academia. The developments of VANETs are heavily influenced by information and communications technologies, which have fueled a plethora of innovations in various areas, including networking, caching and computing. Nevertheless, these important enabling technologies have traditionally been studied separately in the existing works on vehicular networks. In this paper, we propose an integrated framework that can enable dynamic orchestration of networking, caching and computing resources to improve the performance of next generation vehicular networks. We formulate the resource allocation strategy in this framework as a joint optimization problem, where the gains of not only networking but also caching and computing are taken into consideration in the proposed framework. The complexity of the system is very high when we jointly consider these three technologies. Therefore, we propose a novel deep reinforcement learning approach in this paper. Simulation results with different system parameters are presented to show the effectiveness of the proposed scheme.
Evaluation of blocking constraints for survivable WDM optical networks

The advantage of a huge amount of data transmission in form of multimedia broadband services can be benefited using a technique called wavelength division multiplexing (WDM) technology. In WDM, the huge amount of bandwidth can be divided on a fiber in several non-overlapping wavelength channels simultaneously. In case of failure in optical networks, vast amount of data will be lost due to some reasons such as fiber-cut. Protection is one of the survivability methods to overcome such failures. We consider dedicated protection in this paper in which primary paths and their associated backup paths are configured at the time of connections establishment. We suppose that a failure on a primary path, the traffic is rerouted through backup path without any configuration as the backup paths are pre configured, therefore, dedicated protection provides the benefit of short recovery time. In this paper, we investigate the performance caused by various constraints in terms of blocking probability for dedicated protection in WDM networks. To evaluate the constraints for blocking probability we deploy various algorithms. In this paper, we carry out the investigation with detailed simulation experiments on different data rates in a standard NSFNET network topology. Findings of our investigation are as follows. (1) Blocking caused by the lack of backup paths is comparatively higher. (2) In certain algorithm, blocking caused by the lack of primary path is higher and considerable. (3) Two algorithms show the same pattern in all the constraints of blocking. (4) Blocking caused by the lack of primary resources and the lack of backup resources are negligible when using all the algorithms.
Robust Tolerance Design Optimization of a PM Claw Pole Motor With Soft Magnetic Composite Cores

In the past decades, various methods have been investigated for assessing performance variation and robust optimization for electromagnetic device design under uncertainties and/or tolerances. However, in actual production, the manufacturing tolerances are variable to a certain extent, which can be optimized for integrating the performance, manufacturing cost, and production quality. This paper proposes a tolerance design optimization approach by optimizing the design parameters and tolerances simultaneously based on design for six sigma technique. A permanent magnet claw pole motor with soft magnetic composite cores is optimized by using the proposed approach. For this high-dimensional optimization problem involving electromagnetic and thermal performance, Kriging model and 3-D thermal network model are employed under the multilevel framework for increasing the optimization efficiency. Finally, through the analysis, the proposed robust tolerance optimization method shows good performance with improved motor performance as well as the diversity controlling without cost increasing.
Silencing a Multifunctional microRNA Is Beneficial for Stroke Recovery

Stroke-induced endothelial cell injury leads to destruction of cerebral microvasculature and significant damage to the brain tissue. A subacute phase of cerebral ischemia is associated with regeneration involving the activation of vascular remodeling, neuroplasticity, neurogenesis, and neuroinflammation processes. Effective restoration and improvement of blood supply to the damaged brain tissue offers a potential therapy for stroke. microRNAs (miRNAs) are recently identified small RNA molecules that regulate gene expression and significantly influence the essential cellular processes associated with brain repair following stroke. A number of specific miRNAs are implicated in regulating the development and propagation of the ischemic tissue damage as well as in mediating post-stroke regeneration. In this review, I discuss the functions of the miRNA miR-155 and the effect of its in vivo inhibition on brain recovery following experimental cerebral ischemia. The article introduces new and unexplored approach to cerebral regeneration: regulation of brain tissue repair through a direct modulation of specific miRNA activity.
How does an online game based learning environment promote students' intrinsic motivation for learning natural science and how does it affect their learning outcomes?

In this study, mixed research methods were adopted to examine the online game-based learning environment for "Go Go Bugs". The purpose of this study was to determine if an online game-based learning environment can engage and motivate students to learn more natural science by using game features than the control group, which had the same learning environment, but no game features. This experiment examined the engagement by participants' frequencies of returning to the learning environment after school hours, within a time period of two weeks. The results of the comparison of pre- and post- surveys showed significant improvement in increasing participants' interest in learning natural science in a game-based learning environment over that of the non-game-based learning environment. Both quantitative and qualitative results from this study indicated that this game-based learning environment successfully motivated participants in exploring natural science and engaging in the learning activities. However, there was no significant result showing that the game-based learning environment improves students' learning achievement more than with the non-game-based learning environment.
Innovative High-Throughput SAXS Methodologies Based on Photonic Lab-on-a-Chip Sensors: Application to Macromolecular Studies

The relevance of coupling droplet-based Photonic Lab-on-a-Chip (PhLoC) platforms and Small-Angle X-Ray Scattering (SAXS) technique is here highlighted for the performance of high throughput investigations, related to the study of protein macromolecular interactions. With this configuration, minute amounts of sample are required to obtain reliable statistical data. The PhLoC platforms presented in this work are designed to allow and control an effective mixing of precise amounts of proteins, crystallization reagents and buffer in nanoliter volumes, and the subsequent generation of nanodroplets by means of a two-phase flow. Spectrophotometric sensing permits a fine control on droplet generation frequency and stability as well as on concentration conditions, and finally the droplet flow is synchronized to perform synchrotron radiation SAXS measurements in individual droplets (each one acting as an isolated microreactor) to probe protein interactions. With this configuration, droplet physic-chemical conditions can be reproducibly and finely tuned, and monitored without cross-contamination, allowing for the screening of a substantial number of saturation conditions with a small amount of biological material. The setup was tested and validated using lysozyme as a model of study. By means of SAXS experiments, the proteins gyration radius and structure envelope were calculated as a function of protein concentration. The obtained values were found to be in good agreement with previously reported data, but with a dramatic reduction of sample volume requirements compared to studies reported in the literature.
Vaccinia virus protein A46R targets multiple Toll-like–interleukin-1 receptor adaptors and contributes to virulence

Viral immune evasion strategies target key aspects of the host antiviral response. Recently, it has been recognized that Toll-like receptors (TLRs) have a role in innate defense against viruses. Here, we define the function of the vaccinia virus (VV) protein A46R and show it inhibits intracellular signalling by a range of TLRs. TLR signalling is triggered by homotypic interactions between the Toll-like–interleukin-1 resistance (TIR) domains of the receptors and adaptor molecules. A46R contains a TIR domain and is the only viral TIR domain–containing protein identified to date. We demonstrate that A46R targets the host TIR adaptors myeloid differentiation factor 88 (MyD88), MyD88 adaptor-like, TIR domain–containing adaptor inducing IFN-β (TRIF), and the TRIF-related adaptor molecule and thereby interferes with downstream activation of mitogen-activated protein kinases and nuclear factor κB. TRIF mediates activation of interferon (IFN) regulatory factor 3 (IRF3) and induction of IFN-β by TLR3 and TLR4 and suppresses VV replication in macrophages. Here, A46R disrupted TRIF-induced IRF3 activation and induction of the TRIF-dependent gene regulated on activation, normal T cell expressed and secreted. Furthermore, we show that A46R is functionally distinct from another described VV TLR inhibitor, A52R. Importantly, VV lacking the A46R gene was attenuated in a murine intranasal model, demonstrating the importance of A46R for VV virulence.
Adaptive network approach to synchronization and clustering in power grid

The dynamics of a non-linear system are governed by either change in its states or in the network topology. Though both the approaches have been independently used in literature for different applications, the dynamics when both are considered together forms the basis for explaining various phenomena across diverse fields. It has been observed that the complexity of a non-linear system is due to the interplay between the states and the underlying topology, which leads to an adaptive network. This has motivated the authors to realize the existence of similar mechanism in the context of a power grid. The major contribution of this paper is to propose an adaptive framework to comprehend synchronization and cluster formation in a power grid. The theoretical outcomes are supported through simulations carried out on the 39 node New England system.
Left atrial anatomy, atrial fibrillation burden, and P-wave duration—relationships and predictors for single-procedure success after pulmonary vein isolation

Aims Atrial fibrillation (AF) is associated with changes in left atrial (LA) volume, but the relationship between LA size, AF burden, and electrical conduction behaviour is still uncertain. The aim of this study was to quantify the association and impact of these parameters on the single-procedure outcome after circumferential antral ablation for pulmonary vein isolation. Methods and results Left atrial assessment was performed in 129 consecutive patients using pre-procedural imaging in three dimensions (sphericity, indexed volume), two dimensions (diameters), and from echocardiography in one dimension (long axis). Atrial fibrillation burden was classified based on the clinical assessment as paroxysmal and persistent and based on a validated scoring system including frequency, duration of AF episodes, and number of cardioversions into four grades (minimal, mild, moderate, and severe). P-wave duration and PR interval was measured on the 12-lead electrocardiogram at the end of the procedure. Atrial fibrillation burden score (AFB) was minimal (2%), mild (75%), moderate (9%), and severe (14%) and 65% had paroxysmal and 35% had persistent AF. The recurrence rate was significantly higher in patients with persistent AF, with higher AFB, with prolonged P-wave, and with an indexed LA volume > 55 mL/m2. In multivariable analysis, AFB (hazard ratio: 2.018(1.383-2.945), P > 0.001) and a prolonged P-wave (hazard ratio: 2.612(1.248-5.466), P = 0.011) were identified as significant predictors for AF recurrence. Conclusions In our cohort of patients with symptomatic AF, the AFB and the P-wave duration but none of the anatomical parameter revealed to be independent predictors for AF/AT recurrence after circumferential antral pulmonary vein isolation.