Miracle-dz/UniFAR-FTUs huggingface dataset:
Strong Premelting Effect in the Elastic Properties of hcp-Fe Under Inner-Core Conditions

On the Brink of Melting The considerable pressures and temperatures of Earth's iron-rich inner core make it a challenge to compare measurements made in experimental systems with observed seismic data. Computational simulations of core materials may reconcile any apparent differences. Martorell et al. (p. 466, published online 10 October) used ab initio simulations to predict the elastic properties of iron at core pressures. As temperatures approached the melting point of pure iron, the material was predicted to weaken to the point that seismic waves would be slowed considerably. An inner core with a small percentage of light elements like oxygen and silicon near its melting temperature would correspond well with measured seismic velocities. Elastic weakening of iron just before melting explains variations in the seismic structure of Earth’s inner core. The observed shear-wave velocity VS in Earth’s core is much lower than expected from mineralogical models derived from both calculations and experiments. A number of explanations have been proposed, but none sufficiently explain the seismological observations. Using ab initio molecular dynamics simulations, we obtained the elastic properties of hexagonal close-packed iron (hcp-Fe) at 360 gigapascals up to its melting temperature Tm. We found that Fe shows a strong nonlinear shear weakening just before melting (when T/Tm > 0.96), with a corresponding reduction in VS. Because temperatures range from T/Tm = 1 at the inner-outer core boundary to T/Tm ≈ 0.99 at the center, this strong nonlinear effect on VS should occur in the inner core, providing a compelling explanation for the low VS observed.
Smart Parking: An Application of Optical Wireless Sensor Network

Parking problems are commonplace in most major cities. The limited availability of parking results in traffic congestion, air pollution as well as driver frustration. The price for parking expansion is usually prohibitive or extremely high. Recently researchers turned to applying technologies for efficient parking management. In our previous work, we have developed an optical wireless sensor network (WSN) for traffic monitoring. We have demonstrated our system to the public in several exhibitions. It is realized that this simple invention could be applied to monitor vehicles in a parking garage. The system can then inform drivers of the number of available parking spaces and in which area should they be directed to. This kind of system should avoid driver's frustration in trying endlessly to find a parking space in a crowded parking garage. This paper describes our work to modify our original WSN and applies it to parking garages. Problems associated to applying our original WSN to parking garage are explained, and solutions are proposed
Evaluation of Basal Ganglia and Thalamic Inflammation in Children With Pediatric Autoimmune Neuropsychiatric Disorders Associated With Streptococcal Infection and Tourette Syndrome

We applied PET scanning with 11C-[R]-PK11195 (PK) to evaluate neuroinflammatory changes in basal ganglia and thalamus in children with clinically diagnosed pediatric autoimmune neuropsychiatric disorders associated with streptococcal infection (PANDAS) and Tourette syndrome. Seventeen children with PANDAS (mean age: 11.4 ± 2.6 years; 13 males), 12 with Tourette syndrome (mean age: 11.0 ± 3.0 years; 10 males), and 15 normal adults (mean age: 28.7 ± 7.9 years; 8 males) underwent dynamic PK PET imaging and binding potential, a measure of ligand-TSPO receptor (expressed by activated microglia) binding, was calculated for basal ganglia and thalamus. Binding potential values, suggesting underlying activated microglia-mediated neuroinflammation, were found to be increased in bilateral caudate and bilateral lentiform nucleus in the PANDAS group and in bilateral caudate nuclei only in the Tourette syndrome group, compared to control group. These differences in the pattern and extent of neuroinflammation also signify a possible difference in pathophysiological etiology between PANDAS and Tourette syndrome patients.
Would static analysis tools help developers with code reviews?

Code reviews have been conducted since decades in software projects, with the aim of improving code quality from many different points of view. During code reviews, developers are supported by checklists, coding standards and, possibly, by various kinds of static analysis tools. This paper investigates whether warnings highlighted by static analysis tools are taken care of during code reviews and, whether there are kinds of warnings that tend to be removed more than others. Results of a study conducted by mining the Gerrit repository of six Java open source projects indicate that the density of warnings only slightly vary after each review. The overall percentage of warnings removed during reviews is slightly higher than what previous studies found for the overall project evolution history. However, when looking (quantitatively and qualitatively) at specific categories of warnings, we found that during code reviews developers focus on certain kinds of problems. For such categories of warnings the removal percentage tend to be very high, often above 50% and sometimes up to 100%. Examples of those are warnings in the imports, regular expressions, and type resolution categories. In conclusion, while a broad warning detection might produce way too many false positives, enforcing the removal of certain warnings prior to the patch submission could reduce the amount of effort provided during the code review process.
A Study of Visual Studio Usage in Practice

Integrated Development Environments (IDEs) provide a convenient standalone solution that supports developers during various phases of software development. In order to provide better support for developers within such IDEs, we need to understand how much time developers spend using various parts of a given IDE and how often they use available assistance tools. To infer useful conclusions, such information should be gathered for different types of IDEs for different languages. In this paper, we instrument the previously unexplored Visual Studio IDE and track the interactions of developers at an industry partner's software-development department. As a result, we capture interactions for more than 6300 hours of work time, from between 27 and 84 professional C# developers. Our work reports how much time professional developers spend on activities such as code editing and execution or navigation, as well as how often they use assistance tools provided by the IDE. We compare our findings to those of prior studies involving other IDEs and discuss the implications of the commonalities and differences for research on (integrated) developer-assistance tools.
Exercise intensity and middle cerebral artery dynamics in humans

Despite its necessity for understanding healthy brain aging, the influence of exercise intensity on cerebrovascular kinetics is currently unknown. We, therefore characterized middle cerebral artery blood flow velocity (MCAv) kinetics associated with two exercise intensities: low and moderate. We hypothesized that increasing exercise intensity would increase the MCAv amplitude response (Amp) and that age and estimated fitness (V̇O2max) would be related to Amp. Baseline (BL) values were collected for 90-seconds followed by a 6-minute exercise bout. Heart rate, end-tidal CO2, mean arterial pressure and MCAv were recorded throughout. MCAv kinetics were described by Amp, time delay (TD) and time constant (τ). Sixty-four adults completed the study. Amp was greater during moderate compared to low exercise intensity (p < 0.001) while no difference was observed in either TD (p = 0.65) or τ (p = 0.47). Amp was negatively associated with age (p < 0.01) and positively correlated with estimated V̇O2max (p < 0.01). Although Amp declines with age, maintaining higher V̇O2max may benefit the cerebrovascular response to exercise.
Substitutions Near the Receptor Binding Site Determine Major Antigenic Change During Influenza Virus Evolution

Flu Drift Limited Five antigenic sites in the virus surface hemagglutinin protein, which together comprise 131 amino acid positions, are thought to determine the full scope of antigenic drift of influenza A virus. Koel et al. (p. 976) show that major antigenic change can be caused by single amino acid substitutions. These single substitutions substantially skew the way the immune system “sees” the virus. All substitutions of importance are located next to the receptor-binding site in the hemagglutinin. Because there are few positions of importance for antigenic drift, there are strict biophysical limitations to the substitutions at these positions, which restricts the number of new antigenic drift variants at any point in time. Thus, the evolution of influenza virus may be more predictable than previously thought. The major antigenic changes of the influenza virus are primarily caused by a single amino acid near the receptor binding site. The molecular basis of antigenic drift was determined for the hemagglutinin (HA) of human influenza A/H3N2 virus. From 1968 to 2003, antigenic change was caused mainly by single amino acid substitutions, which occurred at only seven positions in HA immediately adjacent to the receptor binding site. Most of these substitutions were involved in antigenic change more than once. Equivalent positions were responsible for the recent antigenic changes of influenza B and A/H1N1 viruses. Substitution of a single amino acid at one of these positions substantially changed the virus-specific antibody response in infected ferrets. These findings have potentially far-reaching consequences for understanding the evolutionary mechanisms that govern influenza viruses.
Visual Outcome and Recurrence Rate in Children With Idiopathic Intracranial Hypertension

The purpose of this retrospective study was to evaluate the visual outcome and recurrence rate of idiopathic intracranial hypertension in children. The study included 68 patients who were diagnosed with idiopathic intracranial hypertension according to the modified Dandy criteria. Permanent visual impairment was rare. Three percent remained with mild visual impairment, 4% with minimal visual field defects, and only 1 patient had severe visual impairment. However, 26% had either a prolonged course of disease or a recurring condition. Higher cerebrospinal fluid opening pressure was the only clinical predictor at presentation (P = .04). Recurrence rate was 18%, and in most cases, the second episode occurred during the first year after remission. There was no significant difference between the group of patients with only 1 episode and the group of patients with more than 1 episode. We suggest long-term follow-up after remission, for at least a year, for all children with idiopathic intracranial hypertension.
CHC and SA applied to wind energy optimization using real data

In this article we analyze different metaheuristic algorithms applied to wind farm optimization. The basic idea is to utilize CHC (a sort of GA) and Simulated Annealing to obtain an acceptable configuration of wind turbines in the wind farm. The goal is to maximize the total output energy and minimize the number of wind turbines used. The energy produced depends of the farm geometry, wind conditions, and the terrain where it is settled. After analize some case studies we face a real wind distribution taken from Comodoro Rivadavia in Argentina. We study four scenarios, three of them having a constant west wind and the last one with the mentioned real wind distribution. We conclude that our methods outperform existing ones, as well as they produce actually useful results for real wind farms.
Low-Functioning Autism and Nonsyndromic Intellectual Disability

Previous neuroradiologic studies reported a high incidence of abnormalities in low-functioning autistic children. In this population, it is difficult to know which abnormality depends on autism itself and which is related to intellectual disability associated with autism. The aim of this study was to evaluate the frequency of neuroradiologic abnormalities in low-functioning autistic children compared to Intellectual Quotient and age-matched nonsyndromic children, using the same set of magnetic resonance imaging (MRI) sequences. MRI was rated as abnormal in 44% of autistic and 54% of children with intellectual disability. The main results were mega cisterna magna in autism and hypoplastic corpus callosum in intellectual disability. These abnormalities are morphologically visible signs of altered brain development. These findings, more frequent than expected, are not specific to the 2 conditions. Although MRI cannot be considered mandatory, it allows an in-depth clinical assessment in nonsyndromic intellectual-disabled and autistic children.
User's favorite scent design using paired comparison-based Interactive Differential Evolution

This study proposes a method that creates a scent suited with a user's favor using paired comparison-based Interactive Differential Evolution. In the proposed method, the user smells two scents and selects the preferred one by simple comparison. Based on the repetitive comparisons, Differential Evolution (DE) optimizes the scent suited with the user. Each scent is composed of several source scents, and strength of each source scent is described as values in DE's vector. To investigate the efficacy of the proposed method fundamentally, smelling experiments composed of comparing experiment and evaluating experiment are performed. In the comparing experiment, the subjects compare presented pair scents and select the preferred one through ten generations, and DE evolves scent to user's favor based on the comparisons. In the evaluating experiment, the subjects evaluate four representative scents picked from 0-, 3-, 6-, 9-th generations, respectively. The results of the experiments showed a tendency of the increase of fitness value in accordance with evolution.
Ablation of NMDA receptors in dopamine neurons disrupts attribution of incentive salience to reward-paired stimuli

Midbrain dopamine (DA) neurons play a crucial role in the formation of conditioned associations between environmental cues and appetitive events. Activation of N-methyl-D-aspartate (NMDA) receptors is a key mechanism responsible for the generation of conditioned responses of DA neurons to reward cues. Here, we tested the effects of the cell type-specific inactivation of NMDA receptors in DA neurons in adult mice on stimulus-reward learning. Animals were trained in a Pavlovian learning paradigm in which they had to learn the predictive value of two conditioned stimuli, one of which (CS+) was paired with the delivery of a water reward. Over the course of conditioning, mutant mice learned that the CS+ predicted reward availability, and they approached the reward receptacle more frequently during CS+ trials than CS− trials. However, conditioned responses to the CS+ were weaker in the mutant mice, possibly indicating that they did not attribute incentive salience to the CS+. To further assess whether the attribution of incentive salience was impaired by the mutation, animals were tested in a conditioned reinforcement test. The test revealed that mutant mice made fewer instrumental responses paired with CS+ presentation, confirming that the CS+ had a weaker incentive value. Taken together, these results indicate that reward prediction learning does occur in the absence of NMDA receptors in DA neurons, but the ability of reward-paired cues to invigorate and reinforce behavior is lost.
Longitudinal trajectory of early functional recovery in patients with first episode psychosis

Background There is a large variability in the recovery trajectory and outcome of first episode of psychosis [FEP] patients. To date, individuals’ outcome trajectories at early stage of illness and potential risk factors associated with a poor outcome trajectory are largely unknown. This study aims to apply three separate predictors (positive symptoms, negative symptoms, and soft neurological signs) to identify homogeneous function outcome trajectories in patients with FEP using objective data-driven methods, and to explore the potential risk /protective factors associated with each trajectory. Methods A total of 369 first episode patients (93% antipsychotic naive) were included in the baseline assessments and followed-up at 4-8 weeks, 6 months, and 1 year. K means cluster modelling for longitudinal data (kml3d) was used to identify distinct, homogeneous clusters of functional outcome trajectories. Patients with at least 3 assessments were included in the trajectory analyses (N=129). The Scale for the Assessment of Negative Symptoms (SANS), Scale for the Assessment of Positive Symptoms (SAPS), and Neurological examination abnormalities (NEA) were used as predictors against Global Assessment of Functioning Scale (GAF). Results In each of the three predictor models, four distinct functional outcome trajectories emerged: “Poor”, “Intermediate”, “Good” and “Catch-up”. Individuals with male gender; ethnic minority status; low premorbid adjustment; low executive function/IQ, low SES, personality disorder, substance use history may be risk factors for poor recovery. Conclusions Functioning recovery in individuals with FEP is heterogeneous, although distinct recovery profiles are apparent. Data-driven trajectory analysis can facilitate better characterization of individual longitudinal patterns of functioning recovery.
A 12-Million-Year Temperature History of the Tropical Pacific Ocean

Old Gradients The surface ocean temperature gradient between the warmer Western Equatorial Pacific and the cooler Eastern Equatorial Pacific is smaller during El Niño episodes than during neutral periods or during La Niñas. Some reconstructions of Pacific Ocean sea surface temperatures (SST) covering periods before ∼3 million years ago have suggested a permanent El Niño–like state. Zhang et al. (p. 84; see the Perspective by Lea) present data from a biomarker-derived proxy for SST that indicate a sizable east-west gradient has existed for the past 12 million years, contradicting the concept of a permanent El Niño–like state existed. A strong Pacific zonal surface ocean temperature gradient has existed for the past 12 million years. [Also see Perspective by Lea] The appearance of permanent El Niño–like conditions prior to 3 million years ago is founded on sea-surface temperature (SST) reconstructions that show invariant Pacific warm pool temperatures and negligible equatorial zonal temperature gradients. However, only a few SST records are available, and these are potentially compromised by changes in seawater chemistry, diagenesis, and calibration limitations. For this study, we establish new biomarker-SST records and show that the Pacific warm pool was ~4°C warmer 12 million years ago. Both the warm pool and cold tongue slowly cooled toward modern conditions while maintaining a zonal temperature gradient of ~3°C in the late Miocene, which increased during the Plio-Pleistocene. Our results contrast with previous temperature reconstructions that support the supposition of a permanent El Niño–like state.
Symbiotic evolutionary subspace clustering

New emerging high-dimensional data sets have made traditional clustering algorithms increasingly inefficient. More sophisticated approaches are required to cope with the increasing dimensionality and cardinality of such data sets. Feature selection methods are proposed as a solution to deal with this problem, however they fail for data sets where the attribute support for different clusters is not the same. For this category of data sets subspace clustering algorithms have been introduced over the past decade. We approach this problem from the perspective of Genetic Algorithms by adopting a hierarchical data structure deployed in three stages. 1) a traditional clustering algorithm is applied independently to each attribute of the data set, thus defining a grid of potential 1-d cluster centroids. 2) representing multi-dimensional cluster centroids by indexing 1-d cluster centroids. 3) converting the problem of finding the best combination of cluster centroids into that of discrete optimization and applying a multi-objective evolutionary algorithm, which uses group fitness evaluation to give a fitness to a group of clusters, as defined by process 2. Synthetic data sets with different characteristics are generated as the ground truth to evaluate the resulting algorithm for Evolutionary Subspace Clustering (ESC) as well as benchmark against alternative subspace and full-space clustering algorithms. ESC returns competitive accuracy and while typically utilizing less attributes and scaling as attribute count increases.
Non-Invasive Assays of Cochlear Synaptopathy – Candidates and Considerations

Studies in multiple species, including in post-mortem human tissue, have shown that normal aging and/or acoustic overexposure can lead to a significant loss of afferent synapses innervating the cochlea. Hypothetically, this cochlear synaptopathy can lead to perceptual deficits in challenging environments and can contribute to central neural effects such as tinnitus. However, because cochlear synaptopathy can occur without any measurable changes in audiometric thresholds, synaptopathy can remain hidden from standard clinical diagnostics. To understand the perceptual sequelae of synaptopathy and to evaluate the efficacy of emerging therapies, sensitive and specific non-invasive measures at the individual patient level need to be established. Pioneering experiments in specific mice strains have helped identify many candidate assays. These include auditory brainstem responses, the middle-ear muscle reflex, envelope-following responses, and extended high-frequency audiograms. Unfortunately, because these non-invasive measures can be also affected by extraneous factors other than synaptopathy, their application and interpretation in humans is not straightforward. Here, we systematically examine six extraneous factors through a series of interrelated human experiments aimed at understanding their effects. Using strategies that may help mitigate the effects of such extraneous factors, we then show that these suprathreshold physiological assays exhibit across-individual correlations with each other indicative of contributions from a common physiological source consistent with cochlear synaptopathy. Finally, we discuss the application of these assays to two key outstanding questions, and discuss some barriers that still remain.
Disability, Quality of Life, and Pain Coping in Pediatric Migraine: An Observational Study

Objectives: The objective was to examine the relationship between disability, health-related quality of life (HrQoL), and pain coping in pediatric migraineurs. Method: Eighty-five patients with migraine were recruited from Pediatric Neurology clinics. Participants completed the Pediatric Migraine Disability Assessment Scale, the Pediatric Quality of Life Inventory, the Pain Coping Questionnaire, and the Pain Catastrophizing Scale. Means were compared to published norms using t-tests. Spearman correlations and logistic regression were used to explore the relationships between the variables. Results: Mean HrQoL scores were lower than norms for controls and chronically ill pediatric patients (P < .0001). Patients reported lower mean pain coping scores and higher mean pain catastrophizing scores than norms (P < .0001). After controlling for age and sex, only the relationship between disability and HrQoL remained significant (OR = 0.91, 95% CI: 0.86-0.95). Conclusion: Pediatric patients with migraine report lower HrQoL, fewer pain coping strategies and more catastrophizing than controls, while disability is inversely associated with HrQoL.