Quantifying input uncertainty in an assemble-to-order system simulation with correlated input variables of mixed types

We consider an assemble-to-order production system where the product demands and the time since the last customer arrival are not independent. The simulation of this system requires a multivariate input model that generates random input vectors with correlated discrete and continuous components. In this paper, we capture the dependence between input variables in an undirected graphical model and decouple the statistical estimation of the univariate input distributions and the underlying dependence measure into separate problems. The estimation errors due to finiteness of the real-world data introduce the so-called input uncertainty in the simulation output. We propose a method that accounts for input uncertainty by sampling the univariate empirical distribution functions via bootstrapping and by maintaining a posterior distribution of the precision matrix that corresponds to the dependence structure of the graphical model. The method improves the coverages of the confidence intervals for the expected profit the per period. © 2014 IEEE

AUTOMATIC EXTRACTION OF SURFACE DYNAMICS USING GOOGLE EARTH ENGINE FOR UNDERSTANDING DROUGHT PHENOMENON

Atmospheric drought due to meteorological events occurring out of seasonal norms, and consequent droughts in agriculture and wetlands cause great damage to the ecological balance. The initial effects of this situation appear on a local scale, while the aftereffects, which last for years, appear on a global scale. Monitoring and detecting drought with remote sensing technologies can contribute to the management of water resources and forest areas and enable many measures to be taken to reduce the effects of drought. Within the scope of this study, a system that automatically performs the extraction of different drought parameters depending on years has been developed. Işıklı Lake was selected as the study area and the change of water areas over the years has been extracted from satellite images. With the system developed on the Google Earth Engine platform, different parameters were analyzed over a 13-year period and their consistency was tested. As a result, it is seen that the water areas in the lake decreased by 30% between 2010 and 2022. Likewise, the systematic decrease in the parameters, especially in 2015 and afterward, indicates the drought in the region. With the proposed automatic system, it is thought that early precautions can be taken for drought scenarios that may occur in larger-scale regions

Near optimality guarantees for data-driven newsvendor with temporally dependent demand: A Monte Carlo approach

We consider a newsvendor problem with stationary and temporally dependent demand in the absence of complete information about the demand process. The objective is to compute a probabilistic guarantee such that the expected cost of an inventory-target estimate is arbitrarily close to the expected cost of the optimal critical-fractile solution. We do this by sampling dependent uniform random variates matching the underlying dependence structure of the demand process - rather than sampling the actual demand which requires the specification of a marginal distribution function - and by approximating a lower bound on the probability of the so-called near optimality. Our analysis sheds light on the role of temporal dependence in the resulting probabilistic guarantee, which has been only investigated for independent and identically distributed demand in the inventory management literature. © 2013 IEEE

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

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

Diazoxide-responsive hyperinsulinemic hypoglycemia caused by HNF4A gene mutations

Objective: The phenotype associated with heterozygous HNF4A gene mutations has recently been extended to include diazoxide responsive neonatal hypoglycemia in addition to maturity-onset diabetes of the young (MODY). To date, mutation screening has been limited to patients with a family history consistent with MODY. In this study, we investigated the prevalence of HNF4A mutations in a large cohort of patients with diazoxide responsive hyperinsulinemic hypoglycemia (HH). Subjects and methods: We sequenced the ABCC8, KCNJ11, GCK, GLUD1, and/or HNF4A genes in 220 patients with HH responsive to diazoxide. The order of genetic testing was dependent upon the clinical phenotype. Results: A genetic diagnosis was possible for 59/220 (27%) patients. KATP channel mutations were most common (15%) followed by GLUD1 mutations causing hyperinsulinism with hyperammonemia (5.9%), and HNF4A mutations (5%). Seven of the 11 probands with a heterozygous HNF4A mutation did not have a parent affected with diabetes, and four de novo mutations were confirmed. These patients were diagnosed with HI within the first week of life (median age 1 day), and they had increased birth weight (median +2.4 SDS). The duration of diazoxide treatment ranged from 3 months to ongoing at 8 years. Conclusions: In this large series, HNF4A mutations are the third most common cause of diazoxide responsive HH. We recommend that HNF4A sequencing is considered in all patients with diazoxide responsive HH diagnosed in the first week of life irrespective of a family history of diabetes, once KATP channel mutations have been excluded

Moving beyond European and Latin American Typologies:The Peculiarities of AKP’s Populism in Turkey

Despite the growing literature on Turkish populism, there is yet no consensus on how best to categorise the Justice and Development Party (Adalet ve Kalkınma Partisi or AKP). This article argues that this lack of consensus is due to a selective focus on the attributes of AKP’s populism. Indeed, when the party’s features are examined holistically, it does not neatly conform to the dominant typologies of populism, which were conceived mostly for European and Latin American examples. For historical reasons, AKP’s populist discourse defines “the people” versus “the elite” in civilisational terms and combines this with strategies of neo-liberalism, strong party organisation and grassroots mobilisation. This blend of populism distinguishes the AKP case from the exclusionary/inclusionary and classical/neo-liberal/radical typologies previously identified by the literature. However, the Bharatiya Janata Party in India and the Thai Rak Thai Party in Thailand have similar attributes to the AKP, drawing attention to the need to move beyond the existing ideological and strategic approaches to populism and towards a more comprehensive socio-cultural approach. The article contributes to the literature on populism by highlighting possible avenues for further research based on such a comprehensive understanding of populism based also on cases from Asia

Spin–orbit precession for eccentric black hole binaries at first order in the mass ratio

We consider spin–orbit ('geodetic') precession for a compact binary in strong-field gravity. Specifically, we compute ψ, the ratio of the accumulated spin-precession and orbital angles over one radial period, for a spinning compact body of mass m 1 and spin s 1, with ${{s}_{1}}\ll Gm_{1}^{2}/c$ , orbiting a non-rotating black hole. We show that ψ can be computed for eccentric orbits in both the gravitational self-force and post-Newtonian frameworks, and that the results appear to be consistent. We present a post-Newtonian expansion for ψ at next-to-next-to-leading order, and a Lorenz-gauge gravitational self-force calculation for ψ at first order in the mass ratio. The latter provides new numerical data in the strong-field regime to inform the effective one-body model of the gravitational two-body problem. We conclude that ψ complements the Detweiler redshift z as a key invariant quantity characterizing eccentric orbits in the gravitational two-body problem