Miracle-dz/UniFAR-FTUs huggingface dataset:
E The 21 May 2014 M w 5 . 9 Bay of Bengal Earthquake : Macroseismic Data Suggest a High-Stress-Drop Event by

A modest but noteworthy Mw 5.9 earthquake occurred in the Bay of Bengal beneath the central Bengal fan at 21:51 Indian Standard Time (16:21 UTC) on 21 May 2014. Centered over 300 km from the eastern coastline of India (Fig. 1), it caused modest damage by virtue of its location and magnitude. However, shaking was very widely felt in parts of eastern India where earthquakes are uncommon. Media outlets reported as many as four fatalities. Although most deaths were blamed on heart attacks, the death of one woman was attributed by different sources to either a roof collapse or a stampede (see E Table S1, available in the electronic supplement to this article). Across the state of Odisha, as many as 250 people were injured (see E Table S1), most after jumping from balconies or terraces. Light damage was reported from a number of towns on coastal deltaic sediments, including collapsed walls and damage to pukka and thatched dwellings. Shaking was felt well inland into east-central India and was perceptible in multistoried buildings as far as Chennai, Delhi, and Jaipur at distances of ≈1600 km (Table 1). In the days following the earthquake, we collected accounts from conventional news outlets as well as social media. Using these accounts, we assigned intensities in keeping with practices described by Martin and Szeliga (2010). The earthquake was reported as “felt” at 310 locations in the eastern and central Indian subcontinent (Fig. 2a;E Table S1). In contrast to available data from the U.S. Geological Survey Community Internet Intensity Map (“Did You Feel It? ” [DYFI]) site (Fig. 2b), our intensity map for the 21 May 2014 earthquake (Fig. 2a) confirms initial impressions that the event was remarkably widely felt for an Mw 5.9 earthquake. The purpose of this report is to make available the newly collected intensity dataset and to present preliminary analysis of this noteworthy recent earthquake. We further show that the intensity distribution provides evidence for a high-stressdrop source. These results bear out the observation made two decades ago by Hanks and Johnston (1992, p. 20): “[Our] results suggest that it should be a fairly simple matter to infer a high-stress-drop event from intensity data alone, provided that an instrumental M0 or Mw value is known separately. ” Our study illustrates the potential value of carefully determined intensity data for investigations of earthquake source properties, especially when instrumental recordings are sparse. We suggest it may in fact be a more robust way to estimate stress drop than conventional approaches, which require correction of attenuation to estimate pulse width or corner frequency (e.g., Anderson, 1986); the estimate is then cubed to estimate stress drop (Madariaga, 1976). Lastly, we discuss potentially important implications of our results for efforts to characterize probabilistic seismic hazard in the Himalayan region.
Linking Cloud-Radiation Parameterization Performance to Large-Scale Dynamics

Parameterization of cloud-radiation interactions in an atmospheric general circulation model using a stochastic approach allows for a statistical representation of cloud field geometry. Previous work indicates that the stochastic approach to cloud-radiation parameterization performs better than typical plane-parallel algorithms in situations where the horizontal cloud fraction is between 0.2 and 0.8. However, this does not completely describe the physical situations when a stochastic approach to modeling cloud-radiation interactions is appropriate. Cluster analysis has been applied to data of the atmospheric state, cloud physical, and dynamical characteristics, and radiative transfer model results to determine the situations in which an atmospheric general circulation model would make best use of a stochastic cloud-radiation parameterization. Preliminary results from the ARM Climate Research Facility (ACRF) Tropical Western Pacific (TWP) locale indicate that situations involving deep convection may benefit the most from a stochastic approach.
A Distributed Control Strategy for Reactive Power Compensation in Smart Microgrids

We consider the problem of optimal reactive power compensation for the minimization of power distribution losses in a smart microgrid. We first propose an approximate model for the power distribution network, which allows us to cast the problem into the class of convex quadratic, linearly constrained, optimization problems. We then consider the specific problem of commanding the microgenerators connected to a microgrid, in order to achieve the optimal injection of reactive power. For this task, we design a randomized, leader-less, gossip-like optimization algorithm. We show how a distributed approach is possible, where microgenerators need to have only a partial knowledge of the problem parameters and of the state, and can perform only local measurements. For the proposed algorithm, we provide conditions for convergence together with an analytic characterization of the convergence speed. The analysis shows that, in radial networks, the best performance is achieved when we command cooperation among microgenerators that are neighbors in the electric topology. Numerical simulations are included to validate both the proposed model and the analytic results about the performance of the proposed algorithm.
CALCULATING BAR-NATAN'S CHARACTERISTIC TWO KHOVANOV HOMOLOGY

We investigate Bar-Natan's characteristic two Khovanov link homology theory studying both the filtered and bi-graded theories. The filtered theory is computed explicitly and the bi-graded theory analysed by setting up a family of spectral sequences. The E2-pages can be described in terms of groups arising from the action of a certain endomorphism on 𝔽2-Khovanov homology. Some simple consequences are discussed.
Estimating heterogeneous costs of participation in the risky asset markets

This paper develops and estimates a dynamic structural model of participation in the risky financial asset markets using household level panel data. We specify a simple economic model in order to capture the portfolio choice over the life cycle. We solve the model using numerical techniques. Then we embed the optimal solution into the statistical (auxiliary) model and estimate the structural parameters using Generalized Indirect Inference. This paper focuses on the estimation of the non proportional costs to participate in the risky asset markets. We consider heterogeneous costs among education groups. We find that participation costs in the risky asset markets are positive and significant. We also conclude that they vary a lot among education groups.
Rank based variation operators for genetic algorithms

We show how and why using genetic operators that are applied with probabilities that depend on the fitness rank of a genotype or phenotype offers a robust alternative to the Simple GA and avoids some questions of parameter tuning without having to introduce an explicit encoded self-adaptation mechanism. We motivate the algorithm by appealing to previous theoretic analysis that show how different landscapes and population states require different mutation rates to dynamically optimize the balance between exploration and exploitation. We test the algorithm on a range of model landscapes where we can see under what circumstances this Rank GA is likely to outperform the Simple GA and how it outperforms standard heuristics such as 1/N. We try to explain the reasons behind this behaviour.
The Milky Way Tomography with SDSS. II. Stellar Metallicity

Using effective temperature and metallicity derived from SDSS spectra for ~60,000 F- and G-type main-sequence stars (0.2 < g − r < 0.6), we develop polynomial models for estimating these parameters from the SDSS u − g and g − r colors. These photometric estimates have similar error properties as those determined from SDSS spectra. We apply this method to SDSS photometric data for over 2 million F/G stars and measure the unbiased metallicity distribution for a complete volume-limited sample of stars at distances between 500 pc and 8 kpc. The metallicity distribution can be exquisitely modeled using two components with a spatially varying number ratio, which correspond to disk and halo. The two components also possess the kinematics expected for disk and halo stars. The metallicity of the halo component is spatially invariant, while the median disk metallicity smoothly decreases with distance from the Galactic plane from –0.6 at 500 pc to –0.8 beyond several kiloparsecs. The absence of a correlation between metallicity and kinematics for disk stars is in a conflict with the traditional decomposition in terms of thin and thick disks. We detect coherent substructures in the kinematics-metallicity space, such as the Monoceros stream, which rotates faster than the LSR, and has a median metallicity of [Fe/H] = −0.95, with an rms scatter of only ~0.15 dex. We extrapolate our results to the performance expected from the Large Synoptic Survey Telescope (LSST) and estimate that LSST will obtain metallicity measurements accurate to 0.2 dex or better, with proper-motion measurements accurate to ~0.5 mas yr−1, for about 200 million F/G dwarf stars within a distance limit of ~100 kpc (g < 23.5).
A Novel Quantitative Simple Brain Metric Using MR Imaging for Preterm Infants

BACKGROUND AND PURPOSE: The application of volumetric techniques to preterm infants has revealed brain volume reductions. Such quantitative data are not available in routine neonatal radiologic care. The objective of this study was to develop simple brain metrics to compare brain size in preterm and term infants and to correlate these metrics with brain volumes from volumetric MR imaging techniques. MATERIALS AND METHODS: MR images from 189 preterm infants <30 weeks’ gestational age or <1250 g birthweight scanned at term-equivalent age and 36 term infants were studied. Fifteen tissue and fluid measures were systematically evaluated on 4 selected sections. The results were correlated with total brain, gray matter, white matter, and CSF volumes. RESULTS: The mean bifrontal, biparietal, and transverse cerebellar diameters were reduced (−11.6%, 95% confidence interval [CI], −13.8% to −9.3%; −12%, 95% CI, −14% to −9.8%; and −8.7%, 95% CI, −10.5% to −7% respectively) and the mean left ventricle diameter was increased (+22.3%, 95% CI, 2.9%–41.6%) in preterm infants (P < .01). Strong correlations were found between the bifrontal and biparietal measures with total brain tissue volume, whereas the size of the ventricles and the interhemispheric measure correlated with CSF volume. Intraobserver reliability was high (intraclass correlation coefficients [ICC], >0.7), where interobserver agreement was acceptable for tissue measures (ICC, >0.6) but lower for fluid measures (ICC, <0.4) CONCLUSIONS: Simple brain metrics at term-equivalent age showed smaller brain diameters and increased ventricle size in preterm infants compared with full-term infants. These measures represent a reliable and easily applicable method to quantify brain growth and assess brain atrophy in this at-risk population.
Pengaruh Brand Image Dan Brand Trust Terhadap Keputusan Pembelian Sepatu Converse

Brand image dan brand trust merupakan faktor yang dapat mempengaruhi keputusan pembelian konsumen. Brand image yang baik akan memberikan dampak positif bagi perusahaan yang akhirnya akan memberikan keuntungan bagi perusahaan melalui peningkatan pembelian konsumen karena adanya brand trust dari konsumen terhadap produk. Penelitian ini bertujuan untuk mengetahui ada atau tidaknya pengaruh brand image dan brand trust terhadap keputusan pembelian sepatu Converse. Jenis penelitian yang digunakan bersifat kausal dan metode penelitian yang digunakan adalah metode kuantitatif. Penelitian ini menggunakan sampel dari populasi sebanyak 50 responden, menggunakan metode purposive sampling . Hasil penelitian menunjukkan bahwa brand image dan brand trust berpengaruh positif dan signifikan terhadap keputusan pembelian.
Learners’ Perspective on Critical Factors to Cloud VLE Success: an Empirical Investigation

The use of Virtual Learning Environment (VLE) in academic institutions is becoming an imperative for many institutions. The growth of the advanced education system now is depending on the increased of Virtual Learning Environment (VLE) technology utilization. Education institution communities are encouraged to adopt a variety of VLE technology to support the process of teaching and learning. The objective of this research is to measure perspective of VLE acceptance among lecturers in the context of Moodle application by using data from 541 lecturers at selected Higher Education Institutions. A framework of research constructed based on a comprehensive study on the theory of service quality and the Technology Acceptance Model (TAM). Eight factors hypothesized which consist of five independent variables; organization support, knowledge support, technical assistance, system characteristics and lecturer style and innovation, two belief variables; perceived usefulness and perceived ease of use and one dependent variable; behavioral intention to use the VLE. All the factors were tested to determine whether they are important in influencing future use of the VLE and statistical analysis methods determined the key driving factors. Results of regression analysis showed that university lecturers have an above average level of VLE acceptance with the very high level of significant value.
The Effects of Chronic Ingestion of Mercuric Chloride on Fertility and Testosterone Levels in Male Sprague Dawley Rats

Although male infertility is well researched, the effects of inorganic mercury on male reproduction and fertility are less well known. Studies pertaining to mercury and male fertility identified reduced concentration of testosterone in the serum of male workers, a toxic influence on fertility of organic mercury compounds within concentrations at the workplace, and increased days to pregnancy. We evaluated the effect of chronic mercuric chloride (HgCl2) exposure in male rats on reproductive endpoints. Thirty-day old male Sprague Dawley rats (n = 31) were exposed to 0.0, 1.0, or 2.0 mg/kg/day of HgCl2 via gavage. After 60 days exposure, they were housed with nonexposed females for 21 days. A survivor analysis revealed the exposed animals took longer to impregnate the females and had a lower rate of impregnation. Further statistical analysis revealed a lower correlation between testicular testosterone levels and days to impregnate, and also lower sperm counts in the epididymis head and body of the exposed males. The results indicate that HgCl2 exposure had significant adverse effects on male rat reproduction endpoints including fertility at a dose that was not clinically toxic.
Analysis of gender, age and disability representation in music education textbooks: A research update

According to International and European Law, teachers are encouraged to analyse, challenge and to help to eliminate sexist stereotypes and distortions in curricular materials. We aimed to characterize and compare the efficacy of implementation of the gender equality-based approach in the Spanish educational system, through a content analysis of the illustrations in music education (ME) textbooks following a coding scheme constructed by the research team according to guidelines from previous studies about the depiction of women and girls in ME textbooks during two periods of Spanish democracy: before (1992–2005); and after (2006–2015). Our major findings were: (a) female characters were under-represented in both time periods studied; (b); the stereotype of women as amateur but not professional musicians is not perpetuated in the current primary ME textbooks; (c) both children and adults independently of gender were portrayed interacting with others; (d) despite the fact that women teachers are actively participating in schools, ME textbooks do not faithfully reflect that reality; and (e) the virtual absence of females and males with disabilities suggests that this aspect of inclusion is still pending. Notwithstanding, ME textbooks printed after 2006 tended to challenge some traditional stereotypes pertaining to how females and males think, play and act within the musical world.
Social justice education through trauma-informed teaching

Abstract Students in the middle grades experience tremendous development in various domains. However, childhood trauma can significantly impede this development, further exacerbating the functioning of our most vulnerable student populations. This article aims to describe the use of trauma-informed teaching as a form of middle-level, social justice education, providing a description of trauma, as well as how traditional classroom management and instruction can affect traumatized students. This article also provides narratives of current and emerging models of trauma-informed teaching, connecting them to the goals of social justice education, and providing practical strategies for implementing such practices in middle-level schools and classrooms.
Experimental Investigation of Crack Extension Patterns in Hydraulic Fracturing with Shale, Sandstone and Granite Cores

Hydraulic fracturing is an important method of reservoir stimulation in the exploitation of geothermal resources, and conventional and unconventional oil and gas resources. In this article, hydraulic fracturing experiments with shale, sandstone cores (from southern Sichuan Basin), and granite cores (from Inner Mongolia) were conducted to investigate the different hydraulic fracture extension patterns in these three reservoir rocks. The different reactions between reservoir lithology and pump pressure can be reflected by the pump pressure monitoring curves of hydraulic fracture experiments. An X-ray computer tomography (CT) scanner was employed to obtain the spatial distribution of hydraulic fractures in fractured shale, sandstone, and granite cores. From the microscopic and macroscopic observation of hydraulic fractures, different extension patterns of the hydraulic fracture can be analyzed. In fractured sandstone, symmetrical hydraulic fracture morphology could be formed, while some micro cracks were also induced near the injection hole. Although the macroscopic cracks in fractured granite cores are barely observed by naked eye, the results of X-ray CT scanning obviously show the morphology of hydraulic fractures. It is indicated that the typical bedding planes well developed in shale formation play an important role in the propagation of hydraulic fractures in shale cores. The results also demonstrated that heterogeneity influenced the pathway of the hydraulic fracture in granite cores.
Effects of Power Tracking Algorithms on Lifetime of Power Electronic Devices Used in Solar Systems

In photovoltaic solar energy systems, power management algorithms (PMAs), usually called maximum power point tracking (MPPT) algorithms, are widely used for extracting maximum available power at every point in time. However, tracking the maximum power has negative effects on the availability of solar energy systems. This is due, mainly, to the created disturbances and thermal stresses on the associated power electronic converters (PECs). This work investigates the effects of PMA on the lifetime consumption, thermal stresses and failures on DC-DC converters used in solar systems. Firstly theoretical analysis and modelling of photovoltaic solar systems including converter’s electro thermal characteristics were developed. Subsequently, experiments on photovoltaic solar systems were carried out using two different PMAs, namely, perturb and observe (P&O) and incremental conductance (IC). Real-time data was collected, under different operating conditions, including thermal behavior using thermal imaging camera and dSPACE. Converters’ thermal cycling was found to be approximately 3 °C higher with the IC algorithm. The steady state temperature was 52.7 °C, for the IC while it was 42.6 °C for P&O. Although IC algorithm offers more accurate power management tool, it causes more severe thermal stresses which, in this study, has led to approximately 1.4 times greater life consumption compared to P&O.
Rules Ventral Prefrontal Cortical Axons Use to Reach Their Targets: Implications for Diffusion Tensor Imaging Tractography and Deep Brain Stimulation for Psychiatric Illness

The ventral prefrontal cortex (vPFC) is involved in reinforcement-based learning and is associated with depression, obsessive-compulsive disorder, and addiction. Neuroimaging is increasingly used to develop models of vPFC connections, to examine white matter (WM) integrity, and to target surgical interventions, including deep brain stimulation. We used primate (Macaca nemestrina/Macaca fascicularis) tracing studies and 3D reconstructions of WM tracts to delineate the rules vPFC projections follow to reach their targets. vPFC efferent axons travel through the uncinate fasciculus, connecting different vPFC regions and linking different functional regions. The uncinate fasciculus also is a conduit for vPFC fibers to reach other cortical bundles. Fibers in the internal capsule are organized according to destination. Thalamic fibers from each vPFC region travel dorsal to their brainstem fibers. The results show regional differences in the trajectories of fibers from different vPFC areas. Overall, the medial/lateral vPFC position dictates the route that fibers take to enter major WM tracts, as well as the position within specific tracts: axons from medial vPFC regions travel ventral to those from more lateral areas. This arrangement, coupled with dorsal/ventral organization of thalamic/brainstem fibers through the internal capsule, results in a complex mingling of thalamic and brainstem axons from different vPFC areas. Together, these data provide the foundation for dividing vPFC WM bundles into functional components and for predicting what is likely to be carried at different points through each bundle. These results also help determine the specific connections that are likely to be captured at different neurosurgical targets.
Automatic Quantitative MRI Texture Analysis in Small-for-Gestational-Age Fetuses Discriminates Abnormal Neonatal Neurobehavior

Background We tested the hypothesis whether texture analysis (TA) from MR images could identify patterns associated with an abnormal neurobehavior in small for gestational age (SGA) neonates. Methods Ultrasound and MRI were performed on 91 SGA fetuses at 37 weeks of GA. Frontal lobe, basal ganglia, mesencephalon and cerebellum were delineated from fetal MRIs. SGA neonates underwent NBAS test and were classified as abnormal if ≥1 area was <5th centile and as normal if all areas were >5th centile. Textural features associated with neurodevelopment were selected and machine learning was used to model a predictive algorithm. Results Of the 91 SGA neonates, 49 were classified as normal and 42 as abnormal. The accuracies to predict an abnormal neurobehavior based on TA were 95.12% for frontal lobe, 95.56% for basal ganglia, 93.18% for mesencephalon and 83.33% for cerebellum. Conclusions Fetal brain MRI textural patterns were associated with neonatal neurodevelopment. Brain MRI TA could be a useful tool to predict abnormal neurodevelopment in SGA.