ALIS: A novel metric in lineage-independent evaluation of scholars

Evaluative bibliometrics often attempts to explore various methods to measure individual scholarly influence. Scholarly independence (SI) is a unique indicator that can be used to understand and assess the research performances of individual scholars. The SI is a rare quality that most funding agencies and universities seek during funding decisions or hiring processes. We propose author lineage independent score (ALIS), a unique model to measure SI of a scholar by using his or her academic genealogy tree as the underlying graph structure. The analysis is performed on real data of 100 authors, collected from the Web of Science (WoS) and the Mathematics Genealogy Project. The analysis is further validated on a larger scale, on a simulated sample of 10,000 authors. The simulation exercise is the proof-of-concept for scalability of the metric and the proposed optimisation model. ALIS exploits genealogical relationships between scholars and their mentors and collaborating communities and constructs an influence scoring model based on the Genealogy tree structure of the respective scholars. The implications from the theoretical model are found to be profound in tracing known and recursive citation patterns among peers. The genealogy tree is used to investigate the advisor–advisee relationship and lays the foundation for defining metrics used to calculate the various indicators such as non-genealogy citations (NGCs), non-community citations (NCCs) and other citation quotient (OCQ). As these indicators/parameters are novel and thus not readily accessible, algorithms are written to compute these indicator values for the scholars under study.

The Formation of Isolated Ultra-Diffuse Galaxies in Romulus25

We use the Romulus25 cosmological simulation volume to identify the largest-ever simulated sample of field ultra-diffuse galaxies (UDGs). At z = 0, we find that isolated UDGs have average star formation rates, colors, and virial masses for their stellar masses and environment. UDGs have moderately elevated HI masses, being 70% (300%) more HI-rich than typical isolated dwarf galaxies at luminosities brighter (fainter) than MB=-14. However, UDGs are consistent with the general isolated dwarf galaxy population and make up ∼20% of all field galaxies with 107<M⋆/M⊙<109. The HI masses, effective radii, and overall appearances of our UDGs are consistent with existing observations of field UDGs, but we predict that many isolated UDGs have been missed by current surveys. Despite their isolation at z = 0, the UDGs in our sample are the products of major mergers. Mergers are no more common in UDG than non-UDG progenitors, but mergers that create UDGs tend to happen earlier – almost never occurring after z = 1, produce a temporary boost in spin, and cause star formation to be redistributed to the outskirts of galaxies, resulting in lower central star formation rates. The centers of the galaxies fade as their central stellar populations age, but their global star formation rates are maintained through bursts of star formation at larger radii, producing steeper negative g-r color gradients. This formation channel is unique relative to other proposals for UDG formation in isolated galaxies, demonstrating that UDGs can potentially be formed through multiple mechanisms.

Simulation and Construction of Fast Neutron Multi-Counter Based on Liquid Flash

As an important attribute authentication technology, the Fast Neutron Multiplicity Counting analysis method has the potential to solve the shortcomings of existing measurement methods. In this paper, the Geant4 10.4 program based on Monte Carlo method is used to simulate the geometric model, physical process and primary behavior, and simulate the detection system composed of six liquid flash probes in three different layouts to achieve the measurement of sample properties. Pu samples were measured by using different layout detection systems. By comparing the detection efficiency and the multiplicity count rate, it was determined that the No. 2 layout was used as the final detection system, and the detection efficiency was about 3.9%. The variation of the detection efficiency of the simulated sample in the radial direction is obtained. The uniform detection efficiency zone of the system is ±3 cm from the center of the cavity. The detection efficiency deviation is less than 0.12%, the mass deviation is less than 5%, and the deviation variance is less than 10%, and the detection system meets the requirements for sample measurement. Studies have shown that the built detection system has the ability to measure sample properties and can be used in the next step of the study.

On Computations in Renewal Risk Models—Analytical and Statistical Aspects

We discuss aspects of numerical methods for the computation of Gerber-Shiu or discounted penalty-functions in renewal risk models. We take an analytical point of view and link this function to a partial-integro-differential equation and propose a numerical method for its solution. We show weak convergence of an approximating sequence of piecewise-deterministic Markov processes (PDMPs) for deriving the convergence of the procedures. We will use estimated PDMP characteristics in a subsequent step from simulated sample data and study its effect on the numerically computed Gerber-Shiu functions. It can be seen that the main source of instability stems from the hazard rate estimator. Interestingly, results obtained using MC methods are hardly affected by estimation.

Methodologies for Establishing the Probability of Pipeline Failure at Slope Crossings

Pipelines in transmission pipeline networks often traverse land slopes along the right-of-way; especially near water crossings. While the vast majority of these slopes are stable, some might have a potential for instability related movements. Accordingly, pipelines subjected to these movements are susceptible to strain overload which may cause loss of containment in terms of buckling and/or tensile elongation failure modes. In order to analyze the risk of failure of pipelines due to slope movement it is beneficial to establish probabilistic approaches that can predict the likelihood of failure at each site given both aleatory and epistemic uncertainties. Estimation of such likelihood would support prioritization of integrity mitigation actions and confirm pipelines’ safety. There is a gap in pipeline literature in terms of available probabilistic approaches to analyze, assess, and manage such an integrity threat. Two probabilistic approaches are presented herein; a qualitative ranking analysis of slope hazards (QuRASH) and a semi-quantitative analysis of slope hazards (SQuASH). QuRASH is a qualitative approach that adopts site scores based on available slope characteristics, historical movements, expert opinion, and mitigation strategies. SQuASH is a reliability-based explicit limit state approach. Both approaches were applied to a large simulated sample of slope crossings that exhibit characteristics representative of North America transmission pipeline slope crossings. The resulting probabilities of failures were directly compared to those predicted based on expert judgement. The high ranked sites compared favorably with those evaluated by experts to exhibit elevated threats. This successful comparison provides a certain level of confidence in the proposed approaches.

Adaptive Testing With a Hierarchical Item Response Theory Model

The hierarchical item response theory (H-IRT) model is very flexible and allows a general factor and subfactors within an overall structure of two or more levels. When an H-IRT model with a large number of dimensions is used for an adaptive test, the computational burden associated with interim scoring and selection of subsequent items is heavy. An alternative approach for any high-dimension adaptive test is to reduce dimensionality for interim scoring and item selection and then revert to full dimensionality for final score reporting, thereby significantly reducing the computational burden. This study compared the accuracy and efficiency of final scoring for multidimensional, local multidimensional, and unidimensional item selection and interim scoring methods, using both simulated and real item pools. The simulation study was conducted under 10 conditions (i.e., five test lengths and two H-IRT models) with a simulated sample of 10,000 students. The study with the real item pool was conducted using item parameters from an actual 45-item adaptive test with a simulated sample of 10,000 students. Results indicate that the theta estimations provided by the local multidimensional and unidimensional item selection and interim scoring methods were relatively as accurate as the theta estimation provided by the multidimensional item selection and interim scoring method, especially during the real item pool study. In addition, the multidimensional method required the longest computation time and the unidimensional method required the shortest computation time.

GEE Estimators in Mixture Model with Varying Concentrations

We discuss semiparametric mixture model where some components are parametrized with common Euclidean parameter and others are fully unknown. We introduce GEE approach and adaptive GEE-based approach for parameter estimation. Proposed estimators are tested on simulated sample.