A simulation-based support tool for data-driven decision making: Operational testing for dependence modeling

Dependencies occur naturally between input processes of many manufacturing and service applications. When the dependence parameters are known with certainty, the failure to factor the dependencies into decisions is well known to waste significant resources in system management. Our focus is on the case of unknown dependence parameters that must be estimated from finite amounts of historical input data. In this case, the estimates of the unknown dependence parameters are random variables and simulations are designed to account for the dependence parameter uncertainty to better support the data-driven decision making. The premise of our paper is that there are certain cases in which the assumption of an independent input process to minimize the expected cost of input parameter uncertainty becomes preferable to accounting for the dependence parameter uncertainty in the simulation. Therefore, a fundamental question to answer before capturing the dependence parameter uncertainty in a stochastic system simulation is whether there is sufficient statistical evidence to represent the dependence, despite the uncertainty around its estimate, in the presence of limited data. We seek an answer for this question within a data-driven inventory-management context by considering an intermittent demand process with correlated demand size and number of interdemand periods. We propose two new finite-sample hypothesis tests to serve as the decision support tools determining when to ignore the correlation and when to account for the correlation together with the uncertainty around its estimate. We show that a statistical test accounting for the expected cost of correlation parameter uncertainty tends to reject the independence assumption less frequently than a statistical test which only considers the sampling distribution of the correlation-parameter estimator. The use of these tests is illustrated with examples and insights are provided into operational testing for dependence modeling. © 2014 IEEE

The Factors that influence AI-based chatbots' impact on customer experience in a B2B context

This study focuses on the implementation of AI (artificial intelligence) based chatbots by SMEs to improve customer experience in a B2B (business-to-business) setting. The findings uncover the factors that influence customer experience of SME (small and medium-sized enterprise) clients when they interact with an AI-based chatbot. In today’s rapidly evolving business landscape, SMEs are looking for new ways to provide a better customer experience for their clients. Adopting AI-based technologies is an increasingly popular way to improve customer interactions and achieve a competitive advantage. B2B companies adopt AI-based chatbots to facilitate human-like service interactions with their customers at various touchpoints (Kushwaha et al., 2021). Not only large companies but also SMEs started to apply AI-based chatbots after the increase of more accessible technologies. However, there are a limited number of studies that explored the impact of AI-based chatbot implementation by SMEs on customer experience. While AI-based chatbots provide cost- and time-saving opportunities for companies, they still don’t meet customer expectations at a desired level (Adam et al., 2021). By understanding the factors that influence customer experience during the interaction with an AI-based chatbot, SMEs can provide efficient customer service and achieve improved customer satisfaction. This study builds on the frameworks developed by Hoyer et al. (2020), Kushwaha et al. (2021), Adam et al. (2021) to understand the factors that influence customer experience when SME clients interact with an AI-based chatbot. The underpinning theories and models of the study are social response theory, technology acceptance model, diffusion of innovation theory, and information systems success model. The findings of the study show that the perceived expertise of an AI-based chatbot plays a more important role in improving customer experience than other factors such as visual cues or speed when clients interact with the chatbot. Moreover, the user’s own expertise is an important factor in setting the customer’s expectations for the chatbot. The conceptual framework in the study should be tested in a further study to understand the significance of the proposed relationships

Use of biochemical and protein profiles of seminal plasma to prediction of semen quality and fertility in stallions

The identification of various substances in seminal plasma has opened the way to study their functionality. It was aimed to identify the electrophoretic protein profile (EPP) and biochemical parameters (BP) of seminal plasma (SP) as predictors of semen quality and fertility in stallion. Forty-six ejaculates from 7 fertile stallions, aged between 6-26 years, were collected from May to July and 117 mares were used to obtain fertility data. For each ejaculate, volume, sperm motility, concentration were determined and seminal plasma samples were collected to perform one-dimensional electrophoresis and biochemical profiling. Following the estrus detection, mares were inseminated with fresh sperm. Pregnancy rates and foal rates were recorded. The concentration of 15-18 kDa molecular weight (MW) proteins has shown a positive correlation with sperm concentration and foal rate. Besides, a strong positive correlation was found between sperm concentration and 23-28 kDa MW proteins (r=0.77). The volume of 19-22 kDa MW proteins was negatively correlated with pregnancy and foal rate. Similarly, the volume of high MW proteins (173-385 kDa) correlated negatively with sperm motility and foal rate. Apart from the protein profile, while Magnesium and Glucose levels were negatively correlated with sperm quality and foal rate, Cholesterol level was a positive indicator of the quality of semen as well as the foaling rate. Moreover, the total protein level was correlated negatively with the sperm concentration whereas triglyceride was correlated positively. In conclusion, EPP and BP of seminal plasma are valuable clinical tools as predictors of fertility and semen quality in the stallion.Fil: Stelletta, C.. Università di Padova; ItaliaFil: Alberti, S.. Università di Padova; ItaliaFil: Cil, B.. Ankara University; TurquíaFil: Tekin, K.. Ankara University; TurquíaFil: Tirpan, M. B.. Ankara University; TurquíaFil: Argañaraz, Martin Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; ArgentinaFil: Akcay, E.. Ankara University; TurquíaFil: Daskin, A.. Ankara University; Turquí

Area Invariance of Apparent Horizons under Arbitrary Boosts

It is a well known analytic result in general relativity that the 2-dimensional area of the apparent horizon of a black hole remains invariant regardless of the motion of the observer, and in fact is independent of the $t=constant$ slice, which can be quite arbitrary in general relativity. Nonetheless the explicit computation of horizon area is often substantially more difficult in some frames (complicated by the coordinate form of the metric), than in other frames. Here we give an explicit demonstration for very restricted metric forms of (Schwarzschild and Kerr) vacuum black holes. In the Kerr-Schild coordinate expression for these spacetimes they have an explicit Lorentz-invariant form. We consider {\it boosted} versions with the black hole moving through the coordinate system. Since these are stationary black hole spacetimes, the apparent horizons are two dimensional cross sections of their event horizons, so we compute the areas of apparent horizons in the boosted space with (boosted) $t = constant$, and obtain the same result as in the unboosted case. Note that while the invariance of area is generic, we deal only with black holes in the Kerr-Schild form, and consider only one particularly simple change of slicing which amounts to a boost. Even with these restrictions we find that the results illuminate the physics of the horizon as a null surface and provide a useful pedagogical tool. As far as we can determine, this is the first explicit calculation of this type demonstrating the area invariance of horizons. Further, these calculations are directly relevant to transformations that arise in computational representation of moving black holes. We present an application of this result to initial data for boosted black holes.Comment: 19 pages, 3 figures. Added a new section and 2 plots along with a coautho

A rotating three component perfect fluid source and its junction with empty space-time

The Kerr solution for empty space-time is presented in an ellipsoidally symmetric coordinate system and it is used to produce generalised ellipsoidal metrics appropriate for the generation of rotating interior solutions of Einstein's equations. It is shown that these solutions are the familiar static perfect fluid cases commonly derived in curvature coordinates but now endowed with rotation. The resulting solutions are also discussed in the context of T-solutions of Einstein's equations and the vacuum T-solution outside a rotating source is presented. The interior source for these solutions is shown not to be a perfect fluid but rather an anisotropic three component perfect fluid for which the energy momentum tensor is derived. The Schwarzschild interior solution is given as an example of the approach.Comment: 14 page

Next-generation sequencing reveals deep intronic cryptic ABCC8 and HADH splicing founder mutations causing hyperinsulinism by pseudoexon activation

Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc.Next-generation sequencing (NGS) enables analysis of the human genome on a scale previously unachievable by Sanger sequencing. Exome sequencing of the coding regions and conserved splice sites has been very successful in the identification of disease-causing mutations, and targeting of these regions has extended clinical diagnostic testing from analysis of fewer than ten genes per phenotype to more than 100. Noncoding mutations have been less extensively studied despite evidence from mRNA analysis for the existence of deep intronic mutations in >20 genes. We investigated individuals with hyperinsulinaemic hypoglycaemia and biochemical or genetic evidence to suggest noncoding mutations by using NGS to analyze the entire genomic regions of ABCC8 (117 kb) and HADH (94 kb) from overlapping ~10 kb PCR amplicons. Two deep intronic mutations, c.1333-1013A>G in ABCC8 and c.636+471G>T HADH, were identified. Both are predicted to create a cryptic splice donor site and an out-of-frame pseudoexon. Sequence analysis of mRNA from affected individuals' fibroblasts or lymphoblastoid cells confirmed mutant transcripts with pseudoexon inclusion and premature termination codons. Testing of additional individuals showed that these are founder mutations in the Irish and Turkish populations, accounting for 14% of focal hyperinsulinism cases and 32% of subjects with HADH mutations in our cohort. The identification of deep intronic mutations has previously focused on the detection of aberrant mRNA transcripts in a subset of disorders for which RNA is readily obtained from the target tissue or ectopically expressed at sufficient levels. Our approach of using NGS to analyze the entire genomic DNA sequence is applicable to any disease

GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo during the Second Part of the Third Observing Run

The third Gravitational-Wave Transient Catalog (GWTC-3) describes signals detected with Advanced LIGO and Advanced Virgo up to the end of their third observing run. Updating the previous GWTC-2.1, we present candidate gravitational waves from compact binary coalescences during the second half of the third observing run (O3b) between 1 November 2019, 15∶00 Coordinated Universal Time (UTC) and 27 March 2020, 17∶00 UTC. There are 35 compact binary coalescence candidates identified by at least one of our search algorithms with a probability of astrophysical origin pastro>0.5. Of these, 18 were previously reported as low-latency public alerts, and 17 are reported here for the first time. Based upon estimates for the component masses, our O3b candidates with pastro>0.5 are consistent with gravitational-wave signals from binary black holes or neutron-star–black-hole binaries, and we identify none from binary neutron stars. However, from the gravitational-wave data alone, we are not able to measure matter effects that distinguish whether the binary components are neutron stars or black holes. The range of inferred component masses is similar to that found with previous catalogs, but the O3b candidates include the first confident observations of neutron-star–black-hole binaries. Including the 35 candidates from O3b in addition to those from GWTC-2.1, GWTC-3 contains 90 candidates found by our analysis with pastro>0.5 across the first three observing runs. These observations of compact binary coalescences present an unprecedented view of the properties of black holes and neutron stars

GW190521: A Binary Black Hole Merger with a Total Mass of 150 M

© 2020 authors. Published by the American Physical Society. On May 21, 2019 at 03:02:29 UTC Advanced LIGO and Advanced Virgo observed a short duration gravitational-wave signal, GW190521, with a three-detector network signal-to-noise ratio of 14.7, and an estimated false-alarm rate of 1 in 4900 yr using a search sensitive to generic transients. If GW190521 is from a quasicircular binary inspiral, then the detected signal is consistent with the merger of two black holes with masses of 85-14+21 Mm and 66-18+17 Mm (90% credible intervals). We infer that the primary black hole mass lies within the gap produced by (pulsational) pair-instability supernova processes, with only a 0.32% probability of being below 65 Mm. We calculate the mass of the remnant to be 142-16+28 Mm, which can be considered an intermediate mass black hole (IMBH). The luminosity distance of the source is 5.3-2.6+2.4 Gpc, corresponding to a redshift of 0.82-0.34+0.28. The inferred rate of mergers similar to GW190521 is 0.13-0.11+0.30 Gpc-3 yr-1