Miracle-dz/UniFAR-FTUs huggingface dataset:
Sleep cognitions associated with anxiety and depression in the elderly

Purpose The objective of this study was to identify the maladaptive sleep-related cognitions most often maintained by the elderly, according to the presence or absence of anxiety and mood disorders. The presence of dysfunctional sleep-related beliefs and attitudes at bedtime in asymptomatic, depressive, and anxious seniors was thus compared. The second objective was to verify the relationships between various dysfunctional cognitions and mental disorders. Method The sample in this study consisted of 2,759 participants aged 65 years and over, with a mean age of 73.8 years. They were recruited through a method of random generation of telephone numbers according to a sampling strategy based on geographic location. After the goal of the study was explained to them, the participants agreed to have health professionals visit their home and to answer questions in a 1.5-hour-long structured interview (after signing a consent form). Results Depressive and anxious seniors adopt dysfunctional sleep-related cognitions in higher proportions than asymptomatic older persons. Once we had controlled for the other factors, we were able to specifically link two sleep-related beliefs and all the sleep-related attitudes studied to the probability of being anxious or depressive. Conclusion The clarifications obtained will make it possible to improve detection, assessment, and intervention processes regarding anxiety or mood disorders, by pinpointing the most direct link between each of the dysfunctional cognitions and the two types of mental disorders, and not just the link to sleep problems.
Top scoring pair classifiers : asymptotics and applications

The original top scoring pair (TSP) classifier was proposed by Geman et al. (2004) for binary classification of diseases based on genetic profiles. We show the consistency of two versions of the TSP classifier and their two cross-validated counterparts relative to two different risks: the classical misclassification risk and an asymmetric version of this risk which gives more weight to the rarer class. A numerical study illustrates our results and sheds further light on the different TSP classification procedures.
The initial level of MLL-partial tandem duplication affects the clinical outcomes in patients with acute myeloid leukemia

Abstract This study aimed to analyze the effects of the initial MLL-partial tandem duplication (PTD) expression levels on clinical outcomes in 36 MLL-PTD-positive acute myeloid leukemia (AML) patients between 2014 and 2016. ROC curves showed 1.0% MLL-PTD as the optimal diagnostic cutoff for complete remission (CR). Nineteen and 17 cases had MLL-PTD <1.0% (low-level group) and ≥1.0% (high-level group), respectively. The FAB type distribution (M2 incidence, 100% vs. 53%, p = .003) and double-CEBPA-mutation incidence (37% vs. 0%, p = .008) significantly differed between the groups, as did the CR rates after the first (78.9% vs. 35.3%, p = .008) and second chemotherapies (84.2% vs. 47.1%, p = .001). High MLL-PTD level was the only independent factor affecting the CR rate (odds ratio = 0.16, p = .024). The 24-month overall survival was significantly lower in the high-level group (52.6% vs. 29.4%, p = .043). In conclusion, AML patients with high initial MLL-PTD levels have lower induction CR and survival rates.
Encoderless flux vector oriented control of brushless doubly-fed reluctance generators

An angular position and velocity observer-based sensorless flux vector-oriented control scheme for a prominent doubly-fed reluctance generator has been presented and experimentally validated. This technology allows the use of the same partially rated power converter as the traditional slipring doubly-excited induction generator, while offering competitive performance with added cost benefits of high reliability and maintenance-free operation afforded by its brushless construction. The controller viability has been demonstrated on a laboratory machine prototype for emulated variable speed and loading conditions similar to those encountered in wind turbines.
Gonadotrophin‐Inhibitory Hormone in the Cichlid Fish Cichlasoma dimerus: Structure, Brain Distribution and Differential Effects on the Secretion of Gonadotrophins and Growth Hormone

The role of gonadotrophin‐inhibitory hormone (GnIH) in the inhibition of the reproductive axis has been well‐established in birds and mammals. However, its role in other vertebrates, such as the teleost fish, remains controversial. In this context, the present study aimed to evaluate whether GnIH modulates the release of gonadotrophins and growth hormone (GH) in the cichlid fish Cichlasoma dimerus. First, we partially sequenced the precursor polypeptide for GnIH and identified three putative GnIH peptides. Next, we analysed the expression of this precursor polypeptide via a polymerase chain reaction in the reproductive axis of both sexes. We found a high expression of the polypeptide in the hypothalamus and gonads of males. Immunocytochemistry allowed the observation of GnIH‐immunoreactive somata in the nucleus posterioris periventricularis and the nucleus olfacto‐retinalis, with no differences between the sexes. GnIH‐immunoreactive fibres were present in all brain regions, with a high density in the nucleus lateralis tuberis and at both sides of the third ventricle. Finally, we performed in vitro studies on intact pituitary cultures to evaluate the effect of two doses (10−6 m and 10−8 m) of synthetic C. dimerus (cd‐) LPQRFa‐1 and LPQRFa‐2 on the release of gonadotrophins and GH. We observed that cd‐LPQRFa‐1 decreased β‐luteinising hormone (LH) and β‐follicle‐stimulating hormone (FSH) and also increased GH release to the culture medium. The release of β‐FSH was increased only when it was stimulated with the higher cd‐LPQRFa‐2 dose. The results of the present study indicate that cd‐LPQRFa‐1, the cichlid fish GnIH, inhibits β‐LH and β‐FSH release and stimulates GH release in intact pituitary cultures of C. dimerus. The results also show that cd‐LPQRF‐2 could act as an β‐FSH‐releasing factor in this fish species.
Repetitively Mode-Locked Cavity-Enhanced Absorption Spectroscopy (RML-CEAS) for Near-Infrared Gas Sensing

A Pound-Drever-Hall (PDH)-based mode-locked cavity-enhanced sensor system was developed using a distributed feedback diode laser centered at 1.53 µm as the laser source. Laser temperature scanning, bias control of the piezoelectric ceramic transducer (PZT) and proportional-integral-derivative (PID) feedback control of diode laser current were used to repetitively lock the laser modes to the cavity modes. A gas absorption spectrum was obtained by using a series of absorption data from the discrete mode-locked points. The 15 cm-long Fabry-Perot cavity was sealed using an enclosure with an inlet and outlet for gas pumping and a PZT for cavity length tuning. The performance of the sensor system was evaluated by conducting water vapor measurements. A linear relationship was observed between the measured absorption signal amplitude and the H2O concentration. A minimum detectable absorption coefficient of 1.5 × 10–8 cm–1 was achieved with an averaging time of 700 s. This technique can also be used for the detection of other trace gas species by targeting the corresponding gas absorption line.
Vg1-Nodal heterodimers are the endogenous inducers of mesendoderm

Nodal is considered the key inducer of mesendoderm in vertebrate embryos and embryonic stem cells. Other TGF-beta-related signals, such as Vg1/Dvr1/Gdf3, have also been implicated in this process but their roles have been unclear or controversial. Here we report that zebrafish embryos without maternally provided vg1 fail to form endoderm and head and trunk mesoderm, and closely resemble nodal loss-of-function mutants. Although Nodal is processed and secreted without Vg1, it requires Vg1 for its endogenous activity. Conversely, Vg1 is unprocessed and resides in the endoplasmic reticulum without Nodal, and is only secreted, processed and active in the presence of Nodal. Co-expression of Nodal and Vg1 results in heterodimer formation and mesendoderm induction. Thus, mesendoderm induction relies on the combination of two TGF-beta-related signals: maternal and ubiquitous Vg1, and zygotic and localized Nodal. Modeling reveals that the pool of maternal Vg1 enables rapid signaling at low concentrations of zygotic Nodal.
Structural and Genetic Analyses of the Mycobacterium tuberculosis Protein Kinase B Sensor Domain Identify a Potential Ligand-binding Site*

Monitoring the environment with serine/threonine protein kinases is critical for growth and survival of Mycobacterium tuberculosis, a devastating human pathogen. Protein kinase B (PknB) is a transmembrane serine/threonine protein kinase that acts as an essential regulator of mycobacterial growth and division. The PknB extracellular domain (ECD) consists of four repeats homologous to penicillin-binding protein and serine/threonine kinase associated (PASTA) domains, and binds fragments of peptidoglycan. These properties suggest that PknB activity is modulated by ECD binding to peptidoglycan substructures, however, the molecular mechanisms underpinning PknB regulation remain unclear. In this study, we report structural and genetic characterization of the PknB ECD. We determined the crystal structures of overlapping ECD fragments at near atomic resolution, built a model of the full ECD, and discovered a region on the C-terminal PASTA domain that has the properties of a ligand-binding site. Hydrophobic interaction between this surface and a bound molecule of citrate was observed in a crystal structure. Our genetic analyses in M. tuberculosis showed that nonfunctional alleles were produced either by deletion of any of single PASTA domain or by mutation of individual conserved residues lining the putative ligand-binding surface of the C-terminal PASTA repeat. These results define two distinct structural features necessary for PknB signal transduction, a fully extended ECD and a conserved, membrane-distal putative ligand-binding site.
Structure of supporting elements in the dorsal fin of percid fishes

The dorsal fin is one of the most varied swimming structures in Acanthomorpha, the spiny‐finned fishes. This fin can be present as a single contiguous structure supported by bony spines and soft lepidotrichia, or it may be divided into an anterior, spiny dorsal fin and a posterior, soft dorsal fin. The freshwater fish family Percidae exhibits especially great variation in dorsal fin spacing, including fishes with separated fins of varying gap length and fishes with contiguous fins. We hypothesized that fishes with separated dorsal fins, especially those with large gaps between fins, would have stiffened fin elements at the leading edge of the soft dorsal fin to resist hydrodynamic loading during locomotion. For 10 percid species, we measured the spacing between dorsal fins and calculated the second moment of area of selected spines and lepidotrichia from museum specimens. There was no significant relationship between the spacing between dorsal fins and the second moment of area of the leading edge of the soft dorsal fin.
Elastic Switch Migration for Control Plane Load Balancing in SDN

Software-defined network (SDN) provides a solution for the scalable network framework with decoupled control and data plane. Migrating switches can balance the resource utilization of controllers and improve network performance. Switch migration problem has to date been formulated as a resource utilization maximization problem to address the scalability of the control plane. However, this problem is NP-hard with high-computational complexities and without addressing the security challenges of the control plane. In this paper, we propose a switch migration method, which interprets switch migration as a signature matching problem and is formulated as a 3-D earth mover’s distance model to protect strategically important controllers in the network. Considering the scalability, we further propose a heuristic method which is time-efficient and suitable to large-scale networks. Simulation results show that our proposed methods can disguise strategically important controllers by diminishing the difference of traffic load between controllers. Moreover, our proposed methods can significantly relieve the traffic pressure of controllers and prevent saturation attacks.
Synthetic MRI for Clinical Neuroimaging: Results of the Magnetic Resonance Image Compilation (MAGiC) Prospective, Multicenter, Multireader Trial

The authors performed a prospective multireader, multicasenoninferiority trial of 1526 images read by 7 blinded neuroradiologists with prospectively acquired synthetic and conventional brain MR imaging case-control pairs from 109 subjects with neuroimaging indications. Each case included conventional T1- and T2-weighted, T1 and T2 FLAIR, and STIR and/or proton density and synthetic reconstructions from multiple-dynamic multiple-echo imaging. Images were randomized and independently assessed. Overall synthetic MR imaging quality was similar to that of conventional proton-density, STIR, and T1- and T2-weighted contrast views across neurologic conditions. Artifacts were more common in synthetic T2 FLAIR, but were readily recognizable and did not mimic pathology. BACKGROUND AND PURPOSE: Synthetic MR imaging enables reconstruction of various image contrasts from 1 scan, reducing scan times and potentially providing novel information. This study is the first large, prospective comparison of synthetic-versus-conventional MR imaging for routine neuroimaging. MATERIALS AND METHODS: A prospective multireader, multicase noninferiority trial of 1526 images read by 7 blinded neuroradiologists was performed with prospectively acquired synthetic and conventional brain MR imaging case-control pairs from 109 subjects (mean, 53.0 ± 18.5 years of age; range, 19–89 years of age) with neuroimaging indications. Each case included conventional T1- and T2-weighted, T1 and T2 FLAIR, and STIR and/or proton density and synthetic reconstructions from multiple-dynamic multiple-echo imaging. Images were randomized and independently assessed for diagnostic quality, morphologic legibility, radiologic findings indicative of diagnosis, and artifacts. RESULTS: Clinical MR imaging studies revealed 46 healthy and 63 pathologic cases. Overall diagnostic quality of synthetic MR images was noninferior to conventional imaging on a 5-level Likert scale (P < .001; mean synthetic-conventional, −0.335 ± 0.352; Δ = 0.5; lower limit of the 95% CI, −0.402). Legibility of synthetic and conventional morphology agreed in >95%, except in the posterior limb of the internal capsule for T1, T1 FLAIR, and proton-density views (all, >80%). Synthetic T2 FLAIR had more pronounced artifacts, including +24.1% of cases with flow artifacts and +17.6% cases with white noise artifacts. CONCLUSIONS: Overall synthetic MR imaging quality was similar to that of conventional proton-density, STIR, and T1- and T2-weighted contrast views across neurologic conditions. While artifacts were more common in synthetic T2 FLAIR, these were readily recognizable and did not mimic pathology but could necessitate additional conventional T2 FLAIR to confirm the diagnosis.
Exponentially Consistent Kernel Two-Sample Tests

Given two sets of independent samples from unknown distributions $P$ and $Q$, a two-sample test decides whether to reject the null hypothesis that $P=Q$. Recent attention has focused on kernel two-sample tests as the test statistics are easy to compute, converge fast, and have low bias with their finite sample estimates. However, there still lacks an exact characterization on the asymptotic performance of such tests, and in particular, the rate at which the type-II error probability decays to zero in the large sample limit. In this work, we show that a class of kernel two-sample tests are exponentially consistent on Polish, locally compact Hausdorff space, e.g., $\mathbb R^d$. The obtained exponential decay rate is further shown to be optimal among all two-sample tests meeting the given level constraint, and is independent of particular kernels provided that they are bounded continuous and characteristic. Key to our approach are an extended version of Sanov's theorem and a recent result that identifies the Maximum Mean Discrepancy as a metric of weak convergence of probability measures.
Agent‐based models in translational systems biology

Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent‐based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent‐based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. Copyright © 2009 John Wiley & Sons, Inc.
Identifying prognostic biomarkers based on aberrant DNA methylation in kidney renal clear cell carcinoma

The outcome of kidney renal clear cell carcinoma (KIRC) differs even among individuals with similar clinical characteristics. DNA methylation is regarded as a regulator of gene expression in cancers, which may be a molecular marker of prognosis. In this study, we aimed to mine novel methylation markers of the prognosis of KIRC. We revealed a total of 2793 genes differentially methylated in their promoter regions (DMGs) and 2979 differentially expressed genes (DEGs) in KIRC tissues compared with normal tissues using The Cancer Genome Atlas datasets. Then, we detected 57 and 34 subpathways enriched among the DMGs and DEGs, respectively, using the R package iSubpathwayMiner. We retained 56 subpathways related to both aberrant methylation and expression based on a hypergeometric test for further analysis. An integrated gene regulatory network was constructed using the regulatory relationships between genes in the subpathways. Using the top 15% of the nodes from the network ranked by degree, survival analysis was performed. We validated four DNA methylation signatures (RAC2, PLCB2, VAV1, and PARVG) as being highly correlated with prognosis in KIRC. These findings suggest that DNA methylation might become a prognostic predictor in KIRC and could supplement histological prognostic prediction.
Superstructures on Spherical Gold Crystals

Abstract Spherically shaped crystals of gold were grown by solidification of a drop of melt in UHV. Their surfaces were investigated in situ by RHEED. The superstructures (001) (5 × 20) and (110) (1 × 2) were observed again. Further superstructures were found: on (001) vicinal planes, (227) (1 × 1), (111) (23 × 1) and (551)c(1 × 1). Several of the new structures are related to structures already known.
How to Assess Quality of Research in Iran, From Input to Impact? Introduction of Peer-Based Research Evaluation Model in Iran.

BACKGROUND Research evaluation is a systematic and objective process to measure relevance, efficiency and effectiveness of research activities, and peer review is one of the most important tools for assessing quality of research. The aim of this study was introducing research evaluation indicators based on peer reviewing. METHODS This study was implemented in 4 stages. A list of objective-oriented evaluation indicators were designed in 4 axes, including; governance and leadership, structure, knowledge production and research impact. RESULTS The top 10% medical sciences research centers (RCs) were evaluated based on peer review. Adequate equipment and laboratory instruments, high quality research publication and national or international cooperation were the main strengths in medical sciences RCs and the most important weaknesses included failure to adhere to strategic plans, parallel actions in similar fields, problems in manpower recruitment, knowledge translation & exchange (KTE) in service providers and policy makers' levels. CONCLUSION Peer review evaluation can improve the quality of research.
Different Types of Chaos in Two Simple Differential Equations

Abstract Different types of chaotic flow are possible in the 3-dimensional state spaces of two simple non-linear differential equations. The first equation consists of a 2-variable, double-focus subsystem complemented by a linearly coupled third variable. It produces at least three types of chaos: Lorenzian chaos, "sandwich" chaos, and "horseshoe" chaos. Two figure 8-shaped chaotic regimes of the latter type are possible simultaneously, running through each other like 2 links of a chain. In the second equation, a transition between two different types of horseshoe chaos (spiral chaos and screw chaos) is possible. While sandwich chaos allows for a genuine strange attractor, the same has not yet been demonstrated for horseshoe chaos. Unlike the situation in the analogous 1-dimensional case, an emergent period-3 solution is not necessarily stable in the horseshoe. Since chaos is a "super-oscillation" (emergent with the third dimension), the existence of "super-chaos" is postulated for the nect level. A six-minute, super-8 sound film, demonstrating the different behavioral modes and their bifurcations in the 2 equations, has been prepared. Chaos sounds as musical as a snore.
Model sensitivity assessment for sensorless PM and reluctance motor drives

Sensorless drives for permanent magnet and reluctance synchronous motors are an interesting option in modern drives. Modified observers, such as the ones based on extended electromotive force or active flux, are used to get a unified model of the motor. The fundamental frequency based observer is of easy implementation, although the reliability of the model is undermined by parameter variations and corrupted measurements, especially when anisotropic motors are adopted. This study aims at analysing the influence of all motor model uncertainties, by means of an analytical sensitivity analysis. The resulting functions and graphic plots are useful to draw interesting considerations about the sensorless drive, in terms of motor selection and control design.
Vertical Optical Scanning with Panoramic Vision for Tree Trunk Reconstruction

This paper presents a practical application of a technique that uses a vertical optical flow with a fisheye camera to generate dense point clouds from a single planimetric station. Accurate data can be extracted to enable the measurement of tree trunks or branches. The images that are collected with this technique can be oriented in photogrammetric software (using fisheye models) and used to generate dense point clouds, provided that some constraints on the camera positions are adopted. A set of images was captured in a forest plot in the experiments. Weighted geometric constraints were imposed in the photogrammetric software to calculate the image orientation, perform dense image matching, and accurately generate a 3D point cloud. The tree trunks in the scenes were reconstructed and mapped in a local reference system. The accuracy assessment was based on differences between measured and estimated trunk diameters at different heights. Trunk sections from an image-based point cloud were also compared to the corresponding sections that were extracted from a dense terrestrial laser scanning (TLS) point cloud. Cylindrical fitting of the trunk sections allowed the assessment of the accuracies of the trunk geometric shapes in both clouds. The average difference between the cylinders that were fitted to the photogrammetric cloud and those to the TLS cloud was less than 1 cm, which indicates the potential of the proposed technique. The point densities that were obtained with vertical optical scanning were 1/3 less than those that were obtained with TLS. However, the point density can be improved by using higher resolution cameras.