Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic finite-element model of axon extracellular stimulation

We study the electrical influence of an electrode over an axon of nonzero thickness in time using a two-dimensional finite element formulation. Although our inspiration comes from the practice of peripheral nerve stimulation, other types of neural tissue excitation can benefit from the model. Our formulation combines a Hodgkin-Huxley model to account for nerve dynamics with electrostatic intra- and extracellular potentials. Thus, the influence of external electrode geometry and parameters can be addressed instead of simplifying them to point current sources. We show first numerical results for different extracellular stimuli and explore future enhancement directions.
Electrodiagnostic consultation and identification of neuromuscular conditions in persons with diabetes

Introduction: Although the American Association of Neuromuscular and Electrodiagnostic Medicine recommends that electrodiagnostic procedures should be performed by physicians with specialty training, these procedures are increasingly being performed by non‐specialists. Methods: We used a nationally representative sample of Medicare beneficiaries with diabetes who used electrodiagnostic services in 2006 to examine whether specialists and non‐specialists were different in the rates of identifying common neuromuscular conditions. Results: Specialists (neurologists and physiatrists) performed 62% of electrodiagnostic consultations; non‐specialist physicians and non‐physicians performed 31% and 5%, respectively. After adjusting for age, race/ethnicity, diabetes severity, and comorbidities, specialists were 1.26–9 times more likely than non‐physicians to diagnose polyneuropathy, lumbosacral radiculopathy, cervical radiculopathy, carpal tunnel syndrome, and ulnar neuropathy. Almost 80% of electrodiagnostic studies performed by specialists included electromyography testing; fewer than 13% by non‐specialists did. Conclusions: Inadequate use of electromyography and fewer specific diagnoses suggest that many non‐specialists perform insufficiently comprehensive electrodiagnostic studies. Muscle Nerve, 2011
Delayed annihilation of antiprotons in helium gas.

The delayed annihilation of antiprotons, which was recently discovered in liquid $^{4}\mathrm{He}$ at KEK, has been studied at CERN in gas-phase $^{4}\mathrm{He}$ and $^{3}\mathrm{He}$. The annihilation time spectra in gaseous $^{4}\mathrm{He}$ at various pressures were found to be similar to that for liquid $^{4}\mathrm{He}$. The observed average lifetime in the region tg1 \ensuremath{\mu}sec for 3 atm $^{4}\mathrm{He}$ was about 3.2 \ensuremath{\mu}sec, while for 3 atm $^{3}\mathrm{He}$ gas it was 2.8 \ensuremath{\mu}sec, i.e., shorter by 15%. The time spectra show a growth-decay-type function, which is indicative of the presence of a series of metastable states. For $^{4}\mathrm{He}$ and $^{3}\mathrm{He}$ they have nearly identical shapes, differing only in the time scale by (14 \ifmmode\pm\else\textpm\fi{}3)%. These observations are qualitatively consistent with the atomic model of p\ifmmode\bar\else\textasciimacron\fi{}${\mathit{e}}^{\mathrm{\ensuremath{-}}}$${\mathrm{He}}^{2+}$ proposed by Condo [Phys. Lett. 9, 65 (1964)]. The time spectra were found to be sensitive to the presence of small amounts (as small as 20 ppm) of ${\mathrm{H}}_{2}$. No evidence was seen for delayed annihilation in gaseous Ne.
The Potential for CYP2D6 Inhibition Screening Using a Novel Scintillation Proximity Assay-Based Approach

High throughput inhibition screens for human cytochrome P450s (CYPs) are being used in preclinical drug metabolism to support drug discovery programs. The versatility of scintillation proximity assay (SPA) technology has enabled the development of a homogeneous high throughput assay for cytochrome P450 2D6 (CYP2D6) inhibition screen using [O-methyl-'4C]dextromethorphan as substrate. The basis of the assay was the trapping of the 0- demethylation product, [14C]HCHO, on SPA beads. Enzyme kinetics parameters Vm,,. and apparent Ki,, determined using pooled human liver microsomes and microsomes from baculovirus cells coexpressing human CYP2D6 and NADPH-cytochrome P450 reductase, were 245 pmol [14C]HCHO/min/mg protein and 11,tM, and 27 pmol ['4C]HCHO/min/pmol and 1.6,uM, respectively. In incubations containing either pooled microsomes or recombinant CYP2D6, [14C]dextromethorphan 0-demethylase activity was inhibited in the presence of quinidine (IC50 = 1.0,uM and 20 nM, respectively). By comparison, inhibitors selective for other CYP isoforms were relatively weak (IC50 > 25 tM). In agreement, a selective CYP2D6 inhibitory monoclonal antibody caused greater than 90% inhibition of [14C]dextromethorphan O-demethylase activity in human liver microsomes, whereas CYP2C9/19- and CYP3A4/5-selective antibodies elicited a minimal inhibitory effect. SPA-based [14C]dextromethorphan 0-demethylase activity was also shown to correlate (r2 = 0.6) with dextromethorphan O-demethylase measured by high-performance liquid chromatography in a bank of human liver microsomes (N = 15 different organ donors). In a series of known CYP2D6 inhibitors/substrates, the SPA-based assay resolved potent inhibitors (IC50 <2 μM) from weak inhibitors (IC50 ≥ 20 μM). It is concluded that the SPA-based assay described herein is suitable for CYP2D6 inhibition screening using either native human liver microsomes or cDNA-expressed CYP2D6.
Bis[μ-N-(3-methoxy-2-oxidobenzylidene-1:2κ2 O 2:O 2)-l-isoleucinato-2κ2 N,O]bis(1,10-phenanthroline-1κ2 N,N′)dinickel(II) methanol tetrasolvate trihydrate

In the title complex, [Ni2(C14H17NO4)2(C12H8N2)2]·4CH3OH·3H2O, the two NiII ions are bridged by two Schiff base anions, leading to a dinuclear complex. One NiII ion is six-coordinated by four O atoms and two N atoms of two tridentate Schiff base ligands derived from the condensation of l-isoleucine and o-vanillin. The other NiII ion is six-coordinated by four N atoms of two 1,10-phenanthroline ligands and two O atoms of the Schiff base ligands. In the crystal, intermolecular O—H⋯O and C—H⋯O hydrogen bonds lead to a three-dimensional structure. Intramolecular C—H⋯O hydrogen bonds are also present. One of the methyl groups of the l-isoleucinate moieties is disordered over two sets of sites with an occupancy ratio of 0.687 (19):0.313 (19) and two methanol molecules are half-occupied.
Web-Queryable Large-Scale Data Sets for Hypothesis Generation in Plant Biology

The approaching end of the 21st century's first decade marks an exciting time for plant biology. Several National Science Foundation Arabidopsis 2010 Projects will conclude, and whether or not the stated goal of the National Science Foundation 2010 Program—to determine the function of 25,000 Arabidopsis genes by 2010—is reached, these projects and others in a similar vein, such as those performed by the AtGenExpress Consortium and various plant genome sequencing initiatives, have generated important and unprecedented large-scale data sets. While providing significant biological insights for the individual laboratories that generated them, these data sets, in conjunction with the appropriate tools, are also permitting plant biologists worldwide to gain new insights into their own biological systems of interest, often at a mouse click through a Web browser. This review provides an overview of several such genomic, epigenomic, transcriptomic, proteomic, and metabolomic data sets and describes Web-based tools for querying them in the context of hypothesis generation for plant biology. We provide five biological examples of how such tools and data sets have been used to provide biological insight.
Target tracking in wireless sensor networks using compressed Kalman filter

Sensor nodes in Wireless Sensor Network (WSN) need to communicate with other sensor nodes and/or a fusion centre in order to accomplish target tracking task. The limited onboard energy and wireless bandwidth are critical issues in many WSNs. In this paper, we propose a Compressed Kalman Filtering (CKF) algorithm to reduce the totality of transmitted data, hence the total energy consumption as well as the wireless bandwidth. Based on the well-known Kalman Filtering (KF) algorithm, the proposed method introduces an additional operation which replaces the state error covariance matrix in the KF algorithm by a diagonal matrix. This diagonal matrix is chosen to be an upper bound of the original covariance matrix to prevent the divergence of the proposed algorithm. A suboptimal solution is derived for general case, i.e. for a system with arbitrary dimension. The derived suboptimal solution does not require much more computation than the standard KF and can be easily implemented in cheap simple sensor nodes. Better solutions are derived for the cases where target is travelling in either 1D space or 2D space. Simulation results show that our proposed algorithm can improve energy efficiency significantly with comparable tracking performance, as compared to the original KF algorithm.
Peritonitis-free survival in peritoneal dialysis : an update taking competing risks into account

Background. Peritonitis-free survival is commonly reported in the peritoneal dialysis (PD) literature. The Kaplan–Meier method appears to be the only technique used to date, although it has known limitations for cohorts with multiple outcomes, as in PD. In the presence of these ‘competing risks’ outcomes, the Kaplan–Meier estimate is interpretable only under restrictive assumptions. In contrast, methods which take competing risks into account provide unbiased estimates of probabilities of outcomes as actually experienced by patients. Methods. We analysed peritonitis-free survival in a cohort of 8711 incident patients from the ‘Registre de Dialyse Péritonéale deLangueFrançaise’between1 January2000and31 December 2007 by calculating the cumulative incidence (CI) of the first episode of peritonitis using the Kaplan–Meier method and a method accounting for competing risks. We compared the CI in different patient groups by the log-rank test and a test developed for competing risk data, Gray’s test. Results. After 5 years of PD, the CI of at least one peritonitis episodewas0.4, and theprobabilityof anyoutcomewas0.96. The Kaplan–Meier method overestimated the CI by a large amount. Compared with the log-rank test, Gray’s test led to different conclusions in three out of seven comparisons. Conclusions. The competing risk approach shows that the CI of at least one peritonitis episode was lower than reported by the Kaplan–Meier method but that survival peritonitis-free and still on PD was overall low. The competing risk approach provides estimates which have a clearer interpretation than Kaplan–Meier methods and could be more widely used in PD research.
The structure of the harmonin/sans complex reveals an unexpected interaction mode of the two Usher syndrome proteins

The hereditary hearing-vision loss disease, Usher syndrome I (USH1), is caused by defects in several proteins that can interact with each other in vitro. Defects in USH1 proteins are thought to be responsible for the developmental and functional impairments of sensory cells in the retina and inner ear. Harmonin/USH1C and Sans/USH1G are two of the USH1 proteins that interact with each other. Harmonin also binds to other USH1 proteins such as cadherin 23 (CDH23) and protocadherin 15 (PCDH15). However, the molecular basis governing the harmonin and Sans interaction is largely unknown. Here, we report an unexpected assembly mode between harmonin and Sans. We demonstrate that the N-terminal domain and the first PDZ domain of harmonin are tethered by a small-domain C-terminal to PDZ1 to form a structural and functional supramodule responsible for binding to Sans. We discover that the SAM domain of Sans, specifically, binds to the PDZ domain of harmonin, revealing previously unknown interaction modes for both PDZ and SAM domains. We further show that the synergistic PDZ1/SAM and PDZ1/carboxyl PDZ binding-motif interactions, between harmonin and Sans, lock the two scaffold proteins into a highly stable complex. Mutations in harmonin and Sans found in USH1 patients are shown to destabilize the complex formation of the two proteins.
Clinical evaluation of the Shin‐Nippon SRW‐5000 autorefractor in adults: an update

The Shin‐Nippon SRW‐5000 is an open view autorefractor that superseded the Canon R‐1 autorefractor in the mid‐1990s and has been used widely in optometry and vision science laboratories. It has been used to measure refractive error, accommodation responses both statically and dynamically, off‐axis refractive error, and adapted to measure pupil size. This paper presents an overview of the original 2001 clinical evaluation of the SRW‐5000 in adults (Mallen et al., Ophthal Physiol Opt 2001; 21: 101) and provides an update on the use and modification of the instrument since the original publication.
Dynamic Graph Algorithms Using Dynamic Forest Techniques

A dynamic graph problem is a problem of maintaining a graph subject to edge insertions and/or deletions, and queries about some property of the graph. An incremental dynamic graph algorithm supports just edge insertions, a decremental dynamic graph algorithm supports just edge deletions, and a fully dynamic graph algorithm supports both edge insertions and deletions. In this paper, we survey some of the currently best results in dynamic graph algorithms, first describing the dynamic forest data structures used, then describing the high-level techniques used and presenting an amortized analysis. Then, we discuss some open conjectures about whether the results described in this paper could be generalized.
Clinical outcome and tolerability of duloxetine in the treatment of major depressive disorder: a 12-week study with plasma levels

Duloxetine (DLX) is a dual serotonin and norepinephrine reuptake inhibitor that has been recently approved for the treatment of major depressive disorder (MDD). However, little is known about the relationship between DLX plasma levels and clinical response. The aims of this open-label study were 1) to assess clinical outcome and tolerability of DLX by means of clinician and patient assessments and 2) to evaluate the value of plasma DLX levels as predictors of clinical response and tolerability. This was a naturalistic, open-label study of 45 outpatients affected with MDD (16 men and 29 women), who received DLX at doses of 30—120 mg/day and were evaluated at baseline (T0) and after 2, 4 and 12 weeks (T1—3). The assessments included the Hamilton Rating Scales for Depression (HRSD) and Anxiety (HRSA), Clinical Global Impression-Severity (CGI-S), Beck’s Depression Inventory (BDI) and a mood visual analogue scale (VAS). Compared with T0, there were significant improvements in HRSD at T1, T2 and T3 (P < 0.001), in HRSA, CGI-S and the self-administered BDI at T2 and T3 (P < 0.001), and in the VAS scores shown at T3 (P = 0.01). DLX treatment was safe and well tolerated. Plasma DLX levels at T2 ranged from 5 to 135 ng/mL (mean ± SD = 53.56 ± 39.45) and correlated almost significantly with the DLX dose (r = 0.35; P = 0.069). There was a significant curvilinear quadratic relationship between the improvement of HRSA scores and plasma DLX levels (R2 = 0.27; P = 0.02). The incidence of anxiety or irritability was associated with the highest plasma levels. Our findings suggest that monitoring plasma DLX levels may be helpful in predicting better treatment responses and tolerability. The present data seem to suggest an optimal anxiolytic efficacy of DLX at intermediate plasma levels.
Random Walks on Stochastic and Deterministic Small-World Networks

SUMMARY Many deterministic small-world network models have been proposed so far, and they have been proven useful in describing some real-life networks which have ﬁxed interconnections. Search e ﬃ ciency is an important property to characterize small-world networks. This paper tries to clarify how the search procedure behaves when random walks are performed on small-world networks, including the classic WS small-world network and three deterministic small-world network models: the deterministic small-world network created by edge iterations, the tree-structured deterministic small-world network, and the small-world network derived from the deterministic uniform recursive tree. Detailed experiments are carried out to test the search e ﬃ ciency of various small-world networks with regard to three di ﬀ erent types of random walks. From the results, we conclude that the stochastic model outperforms the deterministic ones in terms of average search steps.
Distinct functions of calmodulin are required for the uptake step of receptor‐mediated endocytosis in yeast: the type I myosin Myo5p is one of the calmodulin targets

The uptake step of receptor‐mediated endocytosis in yeast is dependent on the calcium binding protein calmodulin (Cmd1p). In order to understand the role that Cmd1p plays, a search was carried out for possible targets among the genes required for the internalization process. Co‐immunoprecipitation, two‐hybrid and overlay assays demonstrated that Cmd1p interacts with Myo5p, a type I unconventional myosin. Analysis of the endocytic phenotype and the Cmd1p–Myo5p interaction in thermosensitive cmd1 mutants indicated that the Cmd1p–Myo5p interaction is required for endocytosis in vivo. However, the Cmd1p–Myo5p interaction requirement was partially overcome by deleting the calmodulin binding sites (IQ motifs) from Myo5p, suggesting that these motifs inhibit Myo5p function. Additionally, genetic and biochemical evidence obtained with a collection of cmd1 mutant alleles strongly suggests that Cmd1p plays an additional role in the internalization step of receptor‐mediated endocytosis in yeast.
Efficient Low Dissipative High Order Schemes for Multiscale MHD Flows , I : Basic Theory

The objective of this paper is to extend our recently developed highly parallelizable nonlinear stable high order schemes for complex multiscale hydrodynamic applications to the viscous MHD equations. These schemes employed multiresolution wavelets as adaptive numerical dissipation controls t o limit the amount of and to aid the selection and/or blending of the appropriate types of dissipation to be used. The new scheme is formulated for both the conservative and non-conservative form of the MHD equations in curvilinear grids. The four advantages of the present approach over existing MHD schemes reported in the open literature are as follows. First, the scheme is constructed for long-time integrations of shock/turbulence/combustion MHD flows. Available schemes are too diffusive for long-time integrations and/or turbulence/combustion problems. Second, unlike existing schemes for the conservative MHD equations which suffer from ill-conditioned eigendecompositions, the present scheme makes use of a well-conditioned eigen-decomposition obtained from a minor modification of the eigenvectors of the non-conservative MHD equations t o solve the conservative form of the MHD equations. Third, this approach of using the non-conservative eigensystem when solving the conservative equations also works well in the context of standard shock-capturing schemes for the MHD equations. Fourth, a new approach to minimize the numerical error of the divergence-free magnetic condition for high order schemes is introduced. Numerical experiments with typical MHD model problems revealed the applicability of the newly developed schemes for the MHD equations.
CHEER: Rich Model Helps Poor Model via Knowledge Infusion

There is a growing interest in applying deep learning (DL) to healthcare, driven by the availability of data with multiple feature channels in <italic>rich-data</italic> environments (e.g., intensive care units). However, in many other practical situations, we can only access data with much fewer feature channels in a <italic>poor-data</italic> environments (e.g., at home), which often results in predictive models with poor performance. How can we boost the performance of models learned from such <italic>poor-data</italic> environment by leveraging knowledge extracted from existing models trained using <italic>rich data</italic> in a related environment? To address this question, we develop a knowledge infusion framework named <monospace>CHEER</monospace> that can succinctly summarize such <italic>rich model</italic> into transferable representations, which can be incorporated into the <italic>poor model</italic> to improve its performance. The infused model is analyzed theoretically and evaluated empirically on several datasets. Our empirical results showed that <monospace>CHEER</monospace> outperformed baselines by 5.60 to 46.80 percent in terms of the macro-F1 score on multiple physiological datasets.
An Unfitted Formulation for the Interaction of an Incompressible Fluid with a Thick Structure via an XFEM/DG Approach

A numerical procedure that combines an extended finite element formulation and a discontinuous Galerkin technique is presented, with the final aim of providing an effective tool for the simulation of three-dimensional (3D) fluid-structure interaction problems. In this work we consider a thick structure immersed in a fluid. We describe the numerical models and discuss the specific implementation issues arising in three dimensions. Finally, 3D numerical results are provided to show the effectiveness of the approach.
Feedback Mechanisms for FDD Massive MIMO With D2D-Based Limited CSI Sharing

Channel state information (CSI) feedback is a challenging issue in frequency division duplexing (FDD) massive MIMO systems. This paper studies a cooperative feedback scheme, where the users first exchange their CSI with each other through device-to-device (D2D) communications, then compute the precoder by themselves, and feedback the precoder to the base station (BS). Analytical results are derived to show that the cooperative precoder feedback is more efficient than the CSI feedback in terms of interference mitigation. To reduce the delays for CSI exchange, we develop an adaptive CSI exchange strategy based on signal subspace projection and optimal bit partition. Numerical results demonstrate that the proposed cooperative precoder feedback scheme with adaptive CSI exchange significantly outperforms the CSI feedback scheme, even under moderate delays for CSI exchange via D2D.
Natural selection? The evolution of diagnostic criteria for gestational diabetes

Gestational diabetes is a common pregnancy disorder which is generally managed with diet, exercise, metformin or insulin treatment and which usually resolves after delivery of the infant. Identifying and treating gestational diabetes improves maternal and fetal outcomes and allows for health promotion to reduce the mother’s risk of type 2 diabetes in later life. However, there remains considerable controversy about the optimal method of identification and diagnosis of women with gestational diabetes. The NICE-2015 diagnostic criteria (75 g oral glucose tolerance test (OGTT) 0 h ≥5.6 mmol/L; 2 h ≥7.8 mmol/L) are based upon cost-effectiveness estimates using observational data, while the WHO-2013 criteria (75 g OGTT 0 h ≥5.1 mmol/L; 1 h ≥10.0 mmol/L; 2 h ≥8.5 mmol/L) identify women and infants at risk of adverse outcomes according to prospective data. There is also considerable controversy about testing for gestational diabetes using universal or risk factor-based screening, and when and how testing should be performed. The aim of this review is to provide a summary of the clinical biochemistry aspects to these debates and to highlight the importance of appropriate identification of gestational diabetes and subsequent type 2 diabetes in this population.