Miracle-dz/UniFAR-FTUs huggingface dataset:
Intermediate shock sub-structures within a slow-mode shock occurring in partially ionised plasma

Context. Slow-mode shocks are important in understanding fast magnetic reconnection, jet formation and heating in the solar atmosphere, and other astrophysical systems. The atmospheric conditions in the solar chromosphere allow both ionised and neutral particles to exist and interact. Under such conditions, fine sub-structures exist within slow-mode shocks due to the decoupling and recoupling of the plasma and neutral species. Aims. We study numerically the fine sub-structure within slow-mode shocks in a partially ionised plasma, in particular, analysing the formation of an intermediate transition within the slow-mode shock. Methods. High-resolution 1D numerical simulations were performed using the (PIP) code using a two-fluid approach. Results. We discover that long-lived intermediate (Alfvén) shocks can form within the slow-mode shock, where there is a shock transition from above to below the Alfvén speed and a reversal of the magnetic field across the shock front. The collisional coupling provides frictional heating to the neutral fluid, resulting in a Sedov-Taylor-like expansion with overshoots in the neutral velocity and neutral density. The increase in density results in a decrease of the Alfvén speed and with this the plasma inflow is accelerated to above the Alfvén speed within the finite width of the shock leading to the intermediate transition. This process occurs for a wide range of physical parameters and an intermediate shock is present for all investigated values of plasma-β, neutral fraction, and magnetic angle. As time advances the magnitude of the magnetic field reversal decreases since the neutral pressure cannot balance the Lorentz force. The intermediate shock is long-lived enough to be considered a physical structure, independent of the initial conditions. Conclusions. Intermediate shocks are a physical feature that can exist as shock sub-structure for long periods of time in partially ionised plasma due to collisional coupling between species.
Author name disambiguation of bibliometric data: A comparison of several unsupervised approaches1

Adequately disambiguating author names in bibliometric databases is a precondition for conducting reliable analyses at the author level. In the case of bibliometric studies that include many researchers, it is not possible to disambiguate each single researcher manually. Several approaches have been proposed for author name disambiguation, but there has not yet been a comparison of them under controlled conditions. In this study, we compare a set of unsupervised disambiguation approaches. Unsupervised approaches specify a model to assess the similarity of author mentions a priori instead of training a model with labeled data. To evaluate the approaches, we applied them to a set of author mentions annotated with a ResearcherID, this being an author identifier maintained by the researchers themselves. Apart from comparing the overall performance, we take a more detailed look at the role of the parametrization of the approaches and analyze the dependence of the results on the complexity of the disambiguation task. Furthermore, we examine which effects the differences in the set of metadata considered by the different approaches have on the disambiguation results. In the context of this study, the approach proposed by Caron and van Eck (2014) produced the best results.
Algorithm Portfolios Based on Cost-Sensitive Hierarchical Clustering

Different solution approaches for combinatorial problems often exhibit incomparable performance that depends on the concrete problem instance to be solved. Algorithm portfolios aim to combine the strengths of multiple algorithmic approaches by training a classifier that selects or schedules solvers dependent on the given instance. We devise a new classifier that selects solvers based on a cost-sensitive hierarchical clustering model. Experimental results on SAT and MaxSAT show that the new method outperforms the most effective portfolio builders to date.
A framework for the online analysis of multi-electrode gastric slow wave recordings

High resolution mapping of electrical activity is becoming an important technique for analysing normal and dysrhythmic gastrointestinal (GI) slow wave activity. Several methods are used to extract meaningful information from the large quantities of data obtained, however, at present these methods can only be used offline. Thus, all analysis currently performed is retrospective and done after the recordings have finished. Limited information about the quality or characteristics of the data is therefore known while the experiments take place. Building on these offline analysis methods, an online implementation has been developed that identifies and displays slow wave activations working alongside an existing recording system. This online system was developed by adapting existing and novel signal processing techniques and linking these to a new user interface to present the extracted information. The system was tested using high resolution porcine data, and will be applied in future high resolution mapping studies allowing researchers to respond in real time to experimental observations.
Phenotypic high myopia in X-linked retinitis pigmentosa secondary to a novel mutation in the RPGR gene

ABSTRACT Background: Retinitis pigmentosa (RP) is a clinically and genetically heterogeneous disease causing progressive degeneration of retinal photoreceptor cells. The most severe form of this disease is X-linked RP (XLRP), in which photoreceptor degeneration begins in early childhood and complete blindness often occurs by the fourth decade of life. Two genes commonly associated with XLRP have been previously identified. Material and methods: One Spanish family with confirmed XLRP was studied for mutations using direct sequencing. A genotype-phenotype correlation with pathologic myopia (PM) is detailed. Results: A new pathogenic mutation in the third exon of the RP GTPase regulator (RPGR) was identified: a variant c212C>G (pSER71*). This mutation appears as a hemizygous variant in the male proband with RP, and as heterozygous variant in the females of this pedigree who invariably exhibit symmetrical PM in both eyes. Conclusion: A complete family history allowed determination of the inheritance pattern providing genetic counseling for patients and their families. The geno-phenotypic attributes of this heterozygosity suggest a correlation between RP and PM. This novel mutation would expand the mutation spectrum of RP2 and RPGR, and help to study molecular pathogenesis of RP.
Newtonian Action Advice: Integrating Human Verbal Instruction with Reinforcement Learning

A goal of Interactive Machine Learning (IML) is to enable people without specialized training to teach agents how to perform tasks. Many of the existing machine learning algorithms that learn from human instructions are evaluated using simulated feedback and focus on how quickly the agent learns. While this is valuable information, it ignores important aspects of the human-agent interaction such as frustration. In this paper, we present the Newtonian Action Advice agent, a new method of incorporating human verbal action advice with Reinforcement Learning (RL) in a way that improves the human-agent interaction. In addition to simulations, we validated the Newtonian Action Advice algorithm by conducting a human-subject experiment. The results show that Newtonian Action Advice can perform better than Policy Shaping, a state-of-the-art IML algorithm, both in terms of RL metrics like cumulative reward and human factors metrics like frustration.
Omeprazole Minimally Alters the Fecal Microbial Community in Six Cats: A Pilot Study

Although they have historically been thought of as safe medications, proton pump inhibitors such as omeprazole have been associated with an increased risk of enteric, particularly Clostridium difficile, infections in people. In cats, omeprazole is often the first choice acid suppressant prescribed for the treatment of upper gastrointestinal (GI) ulceration and bleeding. Despite this, no studies to date have explored the effect of omeprazole on the feline fecal microbiome and metabolome. Therefore, the purpose of this pilot study was to evaluate the effect of prolonged omeprazole administration on the fecal microbiome and metabolome in healthy cats to identify targets for analysis in a larger subset of cats with GI disease. A within-subjects, before and after, pilot study was performed whereby six healthy adult cats received 60 days of placebo (250 mg lactose PO q 12 h) followed by 5 mg (0.83–1.6 mg/kg PO q 12 h) omeprazole. On days 0, 30, and 60 of placebo and omeprazole therapy, the fecal microbiome and metabolome were characterized utilizing 16S ribosomal RNA sequencing by Illumina and untargeted mass spectrometry-based methods, respectively. Omeprazole administration resulted in no significant changes in the global microbiome structure or richness. However, transient changes were noted in select bacterial groups with omeprazole administration resulting in an increased sequence percentage of Streptococcus, Lactobacillus, Clostridium, and Faecalibacterium spp. and a decreased sequence percentage of Bifidobacterium spp. Significance was lost for all of these bacterial groups after adjustment for multiple comparisons. The fecal concentration of O-acetylserine and aminomalonate decreased with omeprazole therapy, but significance was lost after adjustment for multiple comparisons. The results of this pilot study conclude that omeprazole has a mild and transient impact on the fecal microbiome and metabolome when orally administered to healthy cats for 60 days. Based on the findings of this pilot study, evaluation of the effect of omeprazole specifically on Streptococcus, Lactobacillus, Clostridium, Faecalibacterium, and Bifidobacterium spp. is warranted in cats with primary GI disease.
Dissociation between Brain Amyloid Deposition and Metabolism in Early Mild Cognitive Impairment

Background The hypothetical model of dynamic biomarkers for Alzheimer’s disease (AD) describes high amyloid deposition and hypometabolism at the mild cognitive impairment (MCI) stage. However, it remains unknown whether brain amyloidosis and hypometabolism follow the same trajectories in MCI individuals. We used the concept of early MCI (EMCI) and late MCI (LMCI) as defined by the Alzheimer’s disease Neuroimaging Initiative (ADNI)-Go in order to compare the biomarker profile between EMCI and LMCI. Objectives To examine the global and voxel-based neocortical amyloid burden and metabolism among individuals who are cognitively normal (CN), as well as those with EMCI, LMCI and mild AD. Methods In the present study, 354 participants, including CN (n = 109), EMCI (n = 157), LMCI (n = 39) and AD (n = 49), were enrolled between September 2009 and November 2011 through ADNI-GO and ADNI-2. Brain amyloid load and metabolism were estimated using [18F]AV45 and [18F]fluorodeoxyglucose ([18F]FDG) PET, respectively. Uptake ratio images of [18F]AV45 and [18F]FDG were calculated by dividing the summed PET image by the median counts of the grey matter of the cerebellum and pons, respectively. Group differences of global [18F]AV45 and [18F]FDG were analyzed using ANOVA, while the voxel-based group differences were estimated using statistic parametric mapping (SPM). Results EMCI patients showed higher global [18F]AV45 retention compared to CN and lower uptake compared to LMCI. SPM detected higher [18F]AV45 uptake in EMCI compared to CN in the precuneus, posterior cingulate, medial and dorsal lateral prefrontal cortices, bilaterally. EMCI showed lower [18F]AV45 retention than LMCI in the superior temporal, inferior parietal, as well as dorsal lateral prefrontal cortices, bilaterally. Regarding to the global [18F]FDG, EMCI patients showed no significant difference from CN and a higher uptake ratio compared to LMCI. At the voxel level, EMCI showed higher metabolism in precuneus, hippocampus, entorhinal and inferior parietal cortices, as compared to LMCI. Conclusions The present results indicate that brain metabolism remains normal despite the presence of significant amyloid accumulation in EMCI. These results suggest a role for anti-amyloid interventions in EMCI aiming to delay or halt the deposition of amyloid and related metabolism impairment.
Effects of parent–child interaction training on children who are excessively exposed to digital devices: A pilot study

Objective In the last decade, the use of digital devices among children has increased. This study examines the effects of parent–child interaction training on the amount of time children use digital devices, conflict and closeness in parent–child relationships, executive functions, and the electroencephalogram absolute power in children who excessively use the digital devices. Method The sample group consisted of 12 children (24 to 47 months) who spent more than half of their waking hours using digital devices. Parents were trained to intensive interaction with the child for two months. Electroencephalogram absolute power, parent–child interaction, the amount of time children use digital devices, and children’s executive function skills were assessed. Results Parent–child intensive interaction reduces the use of digital devices; decrease the conflicts and increase the closeness in parent–child relationships; decrease executive functioning problems; and increase the absolute power of alpha and alpha 2 (F3), beta 1 (F3), and beta and beta 2 (F3, Fp2). Conclusion These findings provide evidence of the negative effects of the excessive use of digital devices in children, the importance of parent–child interaction, and its positive impacts on cognitive and brain functions in children. It might contribute to better understand the importance of parent–child interaction in the early years.
Age-Related Atrophy and Compensatory Neural Networks in Reading Comprehension

Abstract Objectives: Despite changes to brain integrity with aging, some functions like basic language processes remain remarkably preserved. One theory for the maintenance of function in light of age-related brain atrophy is the engagement of compensatory brain networks. This study examined age-related changes in the neural networks recruited for simple language comprehension. Methods: Sixty-five adults (native English-speaking, right-handed, and cognitively normal) aged 17–85 years underwent a functional magnetic resonance imaging (fMRI) reading paradigm and structural scanning. The fMRI data were analyzed using independent component analysis to derive brain networks associated with reading comprehension. Results: Two typical frontotemporal language networks were identified, and these networks remained relatively stable across the wide age range. In contrast, three attention-related networks showed increased activation with increasing age. Furthermore, the increased recruitment of a dorsal attention network was negatively correlated to gray matter thickness in temporal regions, whereas an anterior frontoparietal network was positively correlated to gray matter thickness in insular regions. Conclusions: We found evidence that older adults can exert increased effort and recruit additional attentional resources to maintain their reading abilities in light of increased cortical atrophy.
Adversarial Training for Free!

Adversarial training, in which a network is trained on adversarial examples, is one of the few defenses against adversarial attacks that withstands strong attacks. Unfortunately, the high cost of generating strong adversarial examples makes standard adversarial training impractical on large-scale problems like ImageNet. We present an algorithm that eliminates the overhead cost of generating adversarial examples by recycling the gradient information computed when updating model parameters. Our "free" adversarial training algorithm achieves comparable robustness to PGD adversarial training on the CIFAR-10 and CIFAR-100 datasets at negligible additional cost compared to natural training, and can be 7 to 30 times faster than other strong adversarial training methods. Using a single workstation with 4 P100 GPUs and 2 days of runtime, we can train a robust model for the large-scale ImageNet classification task that maintains 40% accuracy against PGD attacks. The code is available at this https URL.
The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure

There is a stark disparity between the step size schedules used in practical large scale machine learning and those that are considered optimal by the theory of stochastic approximation. In theory, most results utilize polynomially decaying learning rate schedules, while, in practice, the "Step Decay" schedule is among the most popular schedules, where the learning rate is cut every constant number of epochs (i.e. this is a geometrically decaying schedule). This work examines the step-decay schedule for the stochastic optimization problem of streaming least squares regression (both in the non-strongly convex and strongly convex case), where we show that a sharp theoretical characterization of an optimal learning rate schedule is far more nuanced than suggested by previous work. We focus specifically on the rate that is achievable when using the final iterate of stochastic gradient descent, as is commonly done in practice. Our main result provably shows that a properly tuned geometrically decaying learning rate schedule provides an exponential improvement (in terms of the condition number) over any polynomially decaying learning rate schedule. We also provide experimental support for wider applicability of these results, including for training modern deep neural networks.
A Sequence-Dependent DNA Condensation Induced by Prion Protein

Different studies indicated that the prion protein induces hybridization of complementary DNA strands. Cell culture studies showed that the scrapie isoform of prion protein remained bound with the chromosome. In present work, we used an oxazole dye, YOYO, as a reporter to quantitative characterization of the DNA condensation by prion protein. We observe that the prion protein induces greater fluorescence quenching of YOYO intercalated in DNA containing only GC bases compared to the DNA containing four bases whereas the effect of dye bound to DNA containing only AT bases is marginal. DNA-condensing biological polyamines are less effective than prion protein in quenching of DNA-bound YOYO fluorescence. The prion protein induces marginal quenching of fluorescence of the dye bound to oligonucleotides, which are resistant to condensation. The ultrastructural studies with electron microscope also validate the biophysical data. The GC bases of the target DNA are probably responsible for increased condensation in the presence of prion protein. To our knowledge, this is the first report of a human cellular protein inducing a sequence-dependent DNA condensation. The increased condensation of GC-rich DNA by prion protein may suggest a biological function of the prion protein and a role in its pathogenesis.
Differences in Posttraumatic Stress Disorder, Depression, and Attribution of Symptoms in Service Members With Combat Versus Noncombat Mild Traumatic Brain Injury

Objective: This study compares combat-related mild traumatic brain injury (mTBI) to non-combat-related mTBI in rates of posttraumatic stress disorder (PTSD) and depression after injury, severity of postconcussive symptoms (PCSs), and attribution of those symptoms to mTBI versus PTSD. Participants: A total of 371 active duty service members (SMs) with documented history of mTBI, divided into combat and non-combat-related cohorts. Design: Retrospective cohort study. Main Measures: Diagnoses of PTSD and depression based on medical record review and self-report. PCSs measured using Neurobehavioral Symptom Index. Attribution of symptoms based on a rating scale asking how much mTBI, PTSD, depression, deployment, or readjustment stress contributed to current symptoms. Results: Prevalence of PTSD was significantly higher after a combat-related mTBI, compared with a noncombat mTBI (P = .001). Prevalence of depression did not differ between the 2 groups. PCSs were high in both combat and noncombat mTBIs, with no statistical difference between groups. SMs with PTSD reported higher PCS, regardless of combat status. SMs without PTSD attributed symptoms mainly to mTBI, whereas SMs with PTSD, regardless of combat status, were much more likely to attribute symptoms to PTSD, depression, and deployment/readjustment stress. Conclusions: This research contributes to our understanding of the complex interplay between mTBI and PTSD in both combat and noncombat injuries within the military population and the importance of addressing both simultaneously.
Sickle cell disease up‐regulates vasopressin, aquaporin 2, urea transporter A1, Na‐K‐Cl cotransporter 2, and epithelial Na channels in the mouse kidney medulla despite compromising urinary concentration ability

Sickle cell disease (SCD)‐induced urinary concentration defect has been proposed as caused by impaired ability of the occluded vasa recta due to red blood cell sickling to serve as countercurrent exchangers and renal tubules to absorb water and solutes. However, the exact molecular mechanisms remain largely unknown. The present studies were undertaken to determine the effects of SCD on vasopressin, aquaporin2 (AQP2), urea transporter A1 (UTA1), Na‐K‐Cl co‐transporter 2 (NKCC2), epithelial Na channels (ENaC), aquaporin1 (AQP1), nuclear factor of activated T cells 5 (NFAT5) and Src homology region‐2 domain‐containing phosphatase‐1 (SHP‐1), an important regulator of NFAT5, in the Berkeley SCD mouse kidney medulla. Under water repletion, SCD only induced a minor urinary concentration defect associated with increased urinary vasopressin level alone with the well‐known effects of vasopressin: protein abundance of AQP2, UTA1 and ENaC‐β and apical targeting of AQP2 as compared with non‐SCD. SCD did not significantly affect AQP1 protein level. Water restriction had no further significant effect on SCD urinary vasopressin. NFAT5 is also critical to urinary concentration. Instead, water restriction‐activated NFAT5 associated with inhibition of SHP‐1 in the SCD mice. Yet, water restriction only elevated urinary osmolality by 28% in these mice as opposed to 104% in non‐SCD mice despite similar degree increases of protein abundance of AQP2, NKCC2 and AQP2‐S256‐P. Water‐restriction had no significant effect on protein abundance of ENaC or AQP1 in either strain. In conclusion, under water repletion SCD, only induces a minor defect in urinary concentration because of compensation from the up‐regulated vasopressin system. However, under water restriction, SCD mice struggle to concentrate urine despite activating NFAT5. SCD‐induced urinary concentration defect appears to be resulted from the poor blood flow in vasa recta rather than the renal tubules’ ability to absorb water and solutes.