Miracle-dz/UniFAR-FTUs huggingface dataset:
Aggregating Risks with Partial Dependence Information

We consider the problem of aggregating dependent risks in the presence of partial dependence information. More concretely, we assume that the risks involved belong to independent subgroups and the dependence structure within each group is unknown. A sharp convex upper bound exists in this setting, and this constrained upper bound improves the existing, unconstrained, comonotonic upper bound in convex order. Moreover, we prove the uniqueness of this constrained upper bound and provide a characterization in terms of the distribution of its sum. Numerical illustrations are provided to show the improvement of the new upper bound.
Composite quantile regression for massive datasets

ABSTRACT Analysis of massive datasets is challenging owing to limitations of computer primary memory. Composite quantile regression (CQR) is a robust and efficient estimation method. In this paper, we extend CQR to massive datasets and propose a divide-and-conquer CQR method. The basic idea is to split the entire dataset into several blocks, applying the CQR method for data in each block, and finally combining these regression results via weighted average. The proposed approach significantly reduces the required amount of primary memory, and the resulting estimate will be as efficient as if the entire data set is analysed simultaneously. Moreover, to improve the efficiency of CQR, we propose a weighted CQR estimation approach. To achieve sparsity with high-dimensional covariates, we develop a variable selection procedure to select significant parametric components and prove the method possessing the oracle property. Both simulations and data analysis are conducted to illustrate the finite sample performance of the proposed methods.
Evaluation of a Regional Reanalysis and ERA-Interim over East Asia Using In Situ Observations during 2013–14

AbstractIn this study, the East Asia Regional Reanalysis (EARR) is developed for the period 2013–14 and characteristics of the EARR are examined in comparison with ERA-Interim (ERA-I) reanalysis. The EARR is based on the Unified Model with 12-km horizontal resolution, which has been an operational numerical weather prediction model at the Korea Meteorological Administration since being adopted from the Met Office in 2011. Relative to the ERA-I, in terms of skill scores, the EARR performance for wind, temperature, relative humidity, and geopotential height improves except for mean sea level pressure, the lower-troposphere geopotential height, and the upper-air relative humidity. In a similar way, RMSEs of the EARR are smaller than those of ERA-I for wind, temperature, and relative humidity, except for the upper-air meridional wind and the upper-air relative humidity in January. With respect to the near-surface variables, the triple collocation analysis and the correlation coefficients confirm that EARR pro.
Kesetaraan Gender dalam Perspektif Al-Qurâ€™an dan Implikasinya terhadap Hukum Islam

In this paper, the writer emphasises justice and equality in the perspective of the Qur'an and the Hadith. Islam as a religion holds the values of justice and equality contains the principles of equality. Both men and women are equally as worshippers of Allah; men and women alike as the leaders on this earth; they alike receive primordial covenant. It is believed that Adam and Eve were both active in the cosmic drama, men and women have the potential to achieve optimal performance. The implementation of the gender equality based on the perspective of the Qur'an in Islamic law leads to the transformation of Islamic law relating to the issues of the relation of equality between men and women. It is also within professional fields such as the female judge whose produce the legal products based on gender equality .
Different sources of nitric oxide mediate neurovascular coupling in the lateral geniculate nucleus of the cat

NO mediated vasodilatation after NMDA postsynaptic activity (Iadecola et al., 1993), NO mediated vasodilation linked to the tissue plasminogen activator (Park et al., 2008), adenosine and epoxyeicosatrienoic acids mediated (Peng et al., 2002; Shi et al., 2008) and related to astrocyte activity (Zonta et al., 2003; Iadecola and Nedergaard, 2007). In order to shed further light on the mechanisms involved in coupling and on the capacity of metabolic signals to predict neuronal activity (and vice versa) we have used extracellular recordings of spike activity in vivo combined with spectrophotometry to measure oxyhaemoglobin (OxyHb), as an indicator of blood fl ow (Devor et al., 2003). In addition, we were simultaneously able to measure methemoglobin (MetHb), which refl ects the local level of nitric oxide (Kelm et al., 1997; González-Mora et al., 2002) and experimentally alter the NO environment by pharmacological manipulation. Given the current relevance of imaging techniques, both in clinical and experimental studies, any further insight into this fi eld could have signifi cant implications in, for example, interpretation of fMRI data, and could open new lines of research in fi elds ranging from neurochemistry to imaging, as well as contributing to our basic understanding of CNS function, with particular reference to the visual system. Extracellular single unit recordings were simultaneously recorded with spectroscopic optical measures of OxyHb and MetHb in the LGN (Horsley–Clarke coordinates A5.5/L8.5-9) of nine adult cats of either sex. Animals were anaesthetised with isofl urane in nitrous oxide (70%) and oxygen (30%) (isofl urane – 5% for induction, 2–3% for surgery and 0.5–1% for maintenance) and paralysed with gallamine triethiodide (loading dose of 40 mg, maintenance 10 mg kg/h IV, see de Labra et al., 2007). All procedures conformed to the guidelines
Can Ensembling Pre-processing Algorithms Lead to Better Machine Learning Fairness?

As machine learning (ML) systems get adopted in more critical areas, it has become increasingly crucial to address the bias that could occur in these systems. Several fairness pre-processing algorithms are available to alleviate implicit biases during model training. These algorithms employ different concepts of fairness, often leading to conflicting strategies with consequential trade-offs between fairness and accuracy. In this work, we evaluate three popular fairness pre-processing algorithms and investigate the potential for combining all algorithms into a more robust pre-processing ensemble. We report on lessons learned that can help practitioners better select fairness algorithms for their models.
Asymptotic scale-dependent stability of surface quasi-geostrophic vortices: semi-analytic results

ABSTRACT The scale-dependent stability of surface quasi-geostrophic (SQG) vortices is studied both analytically and numerically. In particular, we study the sensitivity of the stability of SQG vortices on a nondimensional number , namely the square root of the Burger number, which sets the transition scale between different dynamical regimes corresponding to local and nonlocal dynamics. We analyse the stability of two different examples. The first example is given by a Rankine vortex, characterised by constant buoyancy. For this case, asymptotic analysis suggests that the frequencies of the perturbations at scales smaller than the transition scale show a dependence. At scales larger than the transition scale, the frequencies scale instead like . The second example consists of a Rankine vortex shielded by a filament characterised by a different value of constant buoyancy. For this example we study the dispersion relation for the perturbations for the cases in which the inner vortex and the outer filament have different asymptotic properties behaviour.
Effects of fiber Bragg grating design on dual-grating demodulation performance

Dual-grating demodulation has been both effective and simple in most fiber Bragg grating (FBG) sensors because it involves self-demodulation, and in theory, temperature effects are eliminated. Here, by applying the coupled-mode theory, influences of FBG design parameters such as grating length, refractive index modulation depth, and apodization type on the dual-grating demodulation performance are investigated. It is found that particular performance concerns and priorities can be appropriately addressed by proper selection of FBG design parameters. As an example, experiments using FBGs with properly selected parameters based on our analysis are carried out and compared with the previous experiments using available FBGs. The results show that proper FBG parameter selection can be effective for particular performance requirement.
Abstract Background: We investigated the circadian changes and effects on mood and cognitive performance after working consecutive night shifts in a rapidly rotating shift system. Cognitive function, sleep propensity and sleep-related hormones (growth hormone, cortisol, prolactin, thyrotropin) in th

case control study Authors: Yu-San Chang, M.D., M.S., Hsiang-Lan Chen, M.T. , M.S., Yu-Hsuan Wu, M.D., Chung-Yao Hsu, M.D., Ph.D., Ching-Kuan Liu, M.D., Ph.D., Chin Hsu, Ph.D. a Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan b Faculty of Nursing Department, Meiho University, Pingtung, Taiwan c Kaohsiung Municipal Kai-Syuan Psychiatric Hospital, Kaohsiung, Taiwan d Department of Neurology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan e Kaohsiung Medical University, Kaohsiung, Taiwan f Department of Physiology, Kaohsiung Medical University, Kaohsiung, Taiwan *Address correspondence to: Ching-Kuan Liu, M.D., Ph.D., Kaohsiung Medical University, No. 100, Tzyou 1st Road, Kaohsiung 807, Taiwan E-mail: yusanc@kcg.gov. tw Tel: 886-7-7513171 ext. 2373 Fax: 886-7-7161843
Learning with Similarities on Subsets

Many machine learning models are based on similarities between new examples and previously observed examples. Such models are extremely flexible and can adapt to a wide range of tasks. However, if examples are composed of many variables, then even if we collect a large number of examples, it is possible that no two examples will be significantly similar. This, in turn, means that a learning algorithm may require an unreasonably large number of examples to learn such models. In this thesis, however, we show that a small modification of such models, using similarities on subsets of the variables, rather than similarities on all variables, can allow us to learn using fewer examples and without a large increase in the required computational complexity, if two conditions hold. The first condition is that similarities on certain subsets are indicative of the targets. The second condition is that the variables can be partitioned into a small number of groups such that the variables within each group are highly dependent. For instance, suppose we want to learn a classifier which takes images of handwritten digits and outputs the digit drawn in the image. We would like to learn such a classifier based on example images. If we measure similarity to a new example image, depicting a 4, it is quite possible that many of the most similar previous images we have depict a 9. However, if we measure similarity on certain subsets of the pixels, for example, on the region corresponding to the top third of the image, then on this subset of the pixels, it is unlikely that an image depicting a 4 will be similar to an image depicting a 9. For such a task, a learning algorithm based on measuring similarities to previous examples would be able to learn a more accurate classifier, from fewer examples, by using similarities on subsets. But how can the learning algorithm efficiently find suitable subsets of variables on which to measure similarity? This seems like a daunting task, as the number of possible subsets grows exponentially in the number of variables. In this thesis, we suggest that if similarities on certain subsets are indicative of the targets, and if the variables can be partitioned into a small number of groups, such that the variables within each group are highly dependent, then one can find appropriate subsets on which to measure similarity, by considering combinations of groups of highly dependent variables. The small number of groups leads to a small number of subsets we need to consider and hence to a manageable computational effort. The high dependence of the variables within each group allows us to achieve much of the reduction in the number of examples that can be achieved by measuring similarities on subsets, even though we are only considering a small portion of all possible subsets.
Helioseismology

Oscillations detected on the solar surface provide a unique possibility for investigations of the interior properties of a star. Through major observational efforts, including extensive observations from space, as well as development of sophisticated tools for the analysis and interpretation of the data, we have been able to infer the large-scale structure and rotation of the solar interior with substantial accuracy, and we are beginning to get information about the complex subsurface structure and dynamics of sunspot regions, which dominate the magnetic activity in the solar atmosphere and beyond. The results provide a detailed test of the modeling of stellar structure and evolution, and hence of the physical properties of matter assumed in the models. In this way the basis for using stellar modeling in other branches of science is very substantially strengthened; an important example is the use of observations of solar neutrinos to constrain the properties of the neutrino.
Clinical validation of the new T‐ and Y‐Shape models for the quantitative analysis of coronary bifurcations: An interobserver variability study

Objectives This article presents the results of an interobserver validation study of our new T- and Y-shape bifurcation models including their edge segment analyses. Background Over the last years, the coronary artery intervention procedures have been developed more and more toward bifurcation stenting. Because traditional straight vessel quantitative coronary arteriography (QCA) is not sufficient for these measurements, the need has grown for new bifurcation analysis methods. Methods In this article, our two new bifurcation analysis models are presented, the Y-shape and T-shape model. These models were designed for the accurate measurement of the clinically relevant parameters of a coronary bifurcation, for different morphologies and intervention strategies and include an edge segment analysis, to accurately measure (drug-eluting) stent, stent edge, and ostial segment parameters. Results The results of an interobserver validation study of our T-shape and Y-shape analyses are presented, both containing the pre- and post-intervention analyses of each 10 cases. These results are associated with only small systematic and random errors, in the majority of the cases compliant with the QCA guidelines for straight analyses. The results for the edge segment analyses are also very good, with almost all the values within the margins that have been set by our brachytherapy directive. Conclusions Our new bifurcation approaches including their edge segment analyses are very robust and reproducible, and therefore a great extension to the field of quantitative coronary angiography. © 2012 Wiley Periodicals, Inc.
Constructivist Teaching/Learning Theory and Participatory Teaching Methods.

Evidence for the teaching involves transmission of knowledge, superiority of guided transmission is explained in the context of our knowledge, but it is also much more that. In this study we have examined General Sir John Kotelawala Defence University’s cadet and civilian students’ response to constructivist learning theory and participatory teaching methods, especially concepts and knowledge on the learning platform in the Defence University. Target population of this study represents 41 students. All students were given a questionnaire related to constructivist learning theory and participatory teaching methods. The claims of constructivist teaching/learning theory that this paper has singled out are the following: 1) learning is an active experience; 2) the ideas students hold about the subject and topic being taught will form a part of their learning experience; and 3) learning is socially and culturally rooted. Recent developments in Constructivist Teaching/Learning Theory was explained and briefly described in this paper.
Emergence and magnetic-field variation of chiral-soliton lattice and skyrmion lattice in the strained helimagnet Cu 2 OSeO 3

We demonstrate emergence of both the chiral soliton lattice and skyrmion lattice and investigate their magnetic-field variation in the strained ${\mathrm{Cu}}_{2}{\mathrm{OSeO}}_{3}$ thin plate by means of small-angle resonant soft x-ray scattering. The tensile strain stabilizes a helical spin structure with the modulation vector along the strain direction. Consequently, when increasing the field perpendicular to the modulation vector, it undergoes large shrinkage and higher-order diffraction peaks are also observed, which is in accord with a typical feature of the chiral soliton lattice. The skyrmion lattice also appears in the presence of tensile strain but is elongated along the strain direction in reciprocal space. The magnetic-field dependence of the modulation vector along the strain direction agrees with the theoretical model quantitatively, while that along other directions does not. The agreement, however, becomes worse at lower temperatures, which may be attributed to the large potential barrier for skyrmion annihilation.
Protein Interactions

High throughput methods for detecting protein interactions require assessment of their accuracy. We present two forms of computational assessment. The first method is the expression profile reliability (EPR) index. The EPR index estimates the biologically relevant fraction of protein interactions detected in a high throughput screen. It does so by comparing the RNA expression profiles for the proteins whose interactions are found in the screen with expression profiles for known interacting and non-interacting pairs of proteins. The second form of assessment is the paralogous verification method (PVM). This method judges an interaction likely if the putatively interacting pair has paralogs that also interact. In contrast to the EPR index, which evaluates datasets of interactions, PVM scores individual interactions. On a test set, PVM identifies correctly 40% of true interactions with a false positive rate of ∼1%. EPR and PVM were applied to the Database of Interacting Proteins (DIP), a large and diverse collection of protein-protein interactions that contains over 8000 Saccharomyces cerevisiae pairwise protein interactions. Using these two methods, we estimate that ∼50% of them are reliable, and with the aid of PVM we identify confidently 3003 of them. Web servers for both the PVM and EPR methods are available on the DIP website (dip.doe-mbi.ucla.edu/Services.cgi).
Dual-energy X-ray micro-CT imaging of hybrid Ni/Al open-cell foam

In this paper, we employ dual-energy X-ray microfocus tomography (DECT) measurement to develop high-resolution finite element (FE) models that can be used for the numerical assessment of the deformation behaviour of hybrid Ni/Al foam subjected to both quasi-static and dynamic compressive loading. Cubic samples of hybrid Ni/Al open-cell foam with an edge length of [15]mm were investigated by the DECT measurement. The material was prepared using AlSi7Mg0.3 aluminium foam with a mean pore size of [0.85]mm, coated with nanocrystalline nickel (crystallite size of approx. [50]nm) to form a surface layer with a theoretical thickness of [0.075]mm. CT imaging was carried out using state-of-the-art DSCT/DECT X-ray scanner developed at Centre of Excellence Telč. The device consists of a modular orthogonal assembly of two tube-detector imaging pairs, with an independent geometry setting and shared rotational stage mounted on a complex 16-axis CNC positioning system to enable unprecedented measurement variability for highly-detailed tomographical measurements. A sample of the metal foam was simultaneously irradiated using an XWT-240-SE reflection type X-ray tube and an XWT-160-TCHR transmission type X-ray tube. An enhanced dual-source sampling strategy was used for data acquisition. X-ray images were taken using XRD1622 large area GOS scintillator flat panel detectors with an active area of [410 × 410]mm and resolution [2048 × 2048]pixels. Tomographic scanning was performed in 1,200 projections with a 0.3 degree angular step to improve the accuracy of the generated models due to the very complex microstructure and high attenuation of the investigated material. Reconstructed data was processed using a dual-energy algorithm, and was used for the development of a 3D model and voxel model of the foam. The selected parameters of the models were compared with nominal parameters of the actual foam and showed good correlation.
Assessment of the relationship between public service motivation and job performance of Imam Khomeini Relief Foundation (IKRF) staff considering mediating role of person-organization Fit (a case study of Hormozgan, Kerman and Bushehr provinces)

One of the concepts that has attracted an increasing attention in the last two to three decades in the literature of management and organization; is public service motivation. This theory is based on the assumption that the managers and employees of the public sector are interested to work in the public sector,basically, with incentives such as tasks and obligations of citizenship, sacrifice and devotion, compassion,and with these features, mainly, they are encouraged to collaborate and attract in government agencies and other institutions. Given the importance of this model in achieving organizational goals, subject of this study is allocated to assessment of the relationship between public service motivation and job performance Imam Khomeini Relief Committee (IKRF) staff (a case study of Hormozgan, Kerman and Bushehr provinces) considering mediating role of person-organization Fit. Population of the current study are Managers and experts working in the offices of the Imam Khomeini Relief Committee (IKRF)in of Hormozgan , Kerman and Bushehr provinces.in this study , the stratified random sampling proportional to size has been used. By this method, totally, 149 people are selected as samples. Among data collection tools, in this study, Paterson's job performance questionnaire and also, "Kim" and "Vandnaybyl" Inventory of public service motivation questionnaire are used. To analyze, after making use of AMOS structural equation modeling software, the model fit index and path coefficient test are used in order to prove the hypotheses. The results of the analysis of information indicate that there is a significant relation between all the study hypotheses at 95 percent.
Cost‐Loss Analysis of Ensemble Solar Wind Forecasting: Space Weather Use of Terrestrial Weather Tools

This commentary concerns recent work on solar wind forecasting by Owens and Riley (2017, https://doi.org/10.1002/2017SW001679). The approach taken makes effective use of tools commonly used in terrestrial weather—notably, via use of a simple model—generation of an “ensemble” forecast, and application of a “cost‐loss” analysis to the resulting probabilistic information, to explore the benefit of this forecast to users with different risk appetites. This commentary aims to highlight these useful techniques to the wider space weather audience and to briefly discuss the general context of application of terrestrial weather approaches to space weather.
Caractéristique d'Euler-Poincaré

RÉSUMÉ. — Soit G un groupe fini opérant sur un espace topologique localement compact X satisfaisant à certaines hypothèses de finitude cohomologique. On note X, l'ensemble des points de X, dont le stabilisateur appartient à une classe de conjugaison s