Optimal designs for minimising covariances among parameter estimators in a linear model

We construct approximate optimal designs for minimising absolute covariances between least-squares estimators of the parameters (or linear functions of the parameters) of a linear model, thereby rendering relevant parameter estimators approximately uncorrelated with each other. In particular, we consider first the case of the covariance between two linear combinations. We also consider the case of two such covariances. For this we first set up a compound optimisation problem which we transform to one of maximising two functions of the design weights simultaneously. The approaches are formulated for a general regression model and are explored through some examples including one practical problem arising in chemistry

Edge-functionalized and substitutional doped graphene nanoribbons: electronic and spin properties

Graphene nanoribbons are the counterpart of carbon nanotubes in graphene-based nanoelectronics. We investigate the electronic properties of chemically modified ribbons by means of density functional theory. We observe that chemical modifications of zigzag ribbons can break the spin degeneracy. This promotes the onset of a semiconducting-metal transition, or of an half-semiconducting state, with the two spin channels having a different bandgap, or of a spin-polarized half-semiconducting state -where the spins in the valence and conduction bands are oppositely polarized. Edge functionalization of armchair ribbons gives electronic states a few eV away from the Fermi level, and does not significantly affect their bandgap. N and B produce different effects, depending on the position of the substitutional site. In particular, edge substitutions at low density do not significantly alter the bandgap, while bulk substitution promotes the onset of semiconducting-metal transitions. Pyridine-like defects induce a semiconducting-metal transition.Comment: 12 pages, 5 figure

The Standard Capacity Model:Towards a polyhedron representation of container vessel capacity

Container liner shipping is about matching spare capacity to cargo in need of transport. This can be realized using cargo flow networks, where edges are associated with vessel capacity. It is hard, though, to calculate free capacity of container vessels unless full-blown non-linear stowage optimization models are applied. This may cause such flow network optimization to be intractable. To address this challenge, we introduce the Standard Capacity Model (SCM). SCMs are succinct linear capacity models derived from vessel data that can be integrated in higher order optimization models as mentioned above. In this paper, we introduce the hydrostatic core of the SCM. Our results show that it can predict key parameters like draft, trim, and stress forces accurately and thus can model capacity reductions due to these factors

IS THERE AN OPTIMAL COGNITIVE APPLICATION TO BE USED FOR COGNITIVE REMEDIATION IN CLINICAL PSYCHIATRIC PRACTICE?

Cognitive dysfunction is a common characteristic across a number of psychiatric conditions. With growing technological advances, application based cognitive remediation (cognitive apps) is becoming steadily popular due to its accessibility, ease of use and minimal interference with the activities of daily life. However, despite a number of benefits that application based cognitive training possesses, it is not clear, whether the utilisation of these apps is a reliable approach that can be recommended in clinical psychiatric practice in order to restore cognition. In the present review, we have analysed eleven applications which trained the cognitive domains of memory, attention, language, processing speed, executive function and perception with respect to the structure and function of the applications, duration of use and measuring and monitoring of user progress and assessed them, based on the published data, for efficacy in the general population and clinical subgroups of the population. We conclude that, given that there are differences between the apps, given that there is a difference between the general population using these apps and groups suffering pathological conditions using them, given that cognitive deficits are caused by different pathological processes in different illnesses and that different illnesses present with different ranges of deficits, it is not possible to make blanket recommendations for the use of the apps. Nor is there sufficient published evidence for any of the apps to be specifically recommended for cognitive remediation. More evidence, such as trials of specific apps in different conditions, trials of specific apps against therapist guided techniques and blind trials of different apps against each other are necessary before recommendations of particular apps for particular remedial treatments can be made. Nor can ‘brain training’ in normal populations be seen as preventing cognitive decline or be seen as proof that cognitive remediation can improve cognition in pathological groups. Our paper serves as a useful reference to what apps are available, how they compare, and what the published evidence is, with a view to planning further research

Optimal static pricing for a tree network

We study the static pricing problem for a network service provider in a loss system with a tree structure. In the network, multiple classes share a common inbound link and then have dedicated outbound links. The motivation is from a company that sells phone cards and needs to price calls to different destinations. We characterize the optimal static prices in order to maximize the steady-state revenue. We report new structural findings as well as alternative proofs for some known results. We compare the optimal static prices versus prices that are asymptotically optimal, and through a set of illustrative numerical examples we show that in certain cases the loss in revenue can be significant. Finally, we show that static prices obtained using the reduced load approximation of the blocking probabilities can be easily obtained and have near-optimal performance, which makes them more attractive for applications.Massachusetts Institute of Technology. Center for Digital BusinessUnited States. Office of Naval Research (Contract N00014-95-1-0232)United States. Office of Naval Research (Contract N00014-01-1-0146)National Science Foundation (U.S.) (Contract DMI-9732795)National Science Foundation (U.S.) (Contract DMI-0085683)National Science Foundation (U.S.) (Contract DMI-0245352

Supervised Learning Approaches to Classify Stratospheric Warming Events

Sudden stratospheric warmings are prominent examples of dynamical wave–mean flow interactions in the Arctic stratosphere during Northern Hemisphere winter. They are characterized by a strong temperature increase on time scales of a few days and a strongly disturbed stratospheric vortex. This work investigates a wide class of supervised learning methods with respect to their ability to classify stratospheric warmings, using temperature anomalies from the Arctic stratosphere and atmospheric forcings such as ENSO, the quasi-biennial oscillation (QBO), and the solar cycle. It is demonstrated that one representative of the supervised learning methods family, namely nonlinear neural networks, is able to reliably classify stratospheric warmings. Within this framework, one can estimate temporal onset, duration, and intensity of stratospheric warming events independently of a particular pressure level. In contrast to classification methods based on the zonal-mean zonal wind, the approach herein distinguishes major, minor, and final warmings. Instead of a binary measure, it provides continuous conditional probabilities for each warming event representing the amount of deviation from an undisturbed polar vortex. Additionally, the statistical importance of the atmospheric factors is estimated. It is shown how marginalized probability distributions can give insights into the interrelationships between external factors. This approach is applied to 40-yr and interim ECMWF (ERA-40/ERA-Interim) and NCEP–NCAR reanalysis data for the period from 1958 through 2010

Solving the generalized multi-port container stowage planning problem by a matheuristic algorithm

We focus on a simplified container stowage planning problem where containers of different size and weight must be loaded and unloaded at multiple ports while maintaining the stability of the ship. We initially investigate how the difficulty in solving the problem changes with and without the consideration of container sizes and weight constraints. For this purpose, we provide integer programming formulations for the general problem as well as some special cases with identical container size and/or identical weights and evaluate their performance in randomly generated small- and medium-scale instances. We develop a matheuristic procedure, namely, an insert-and-fix heuristic, exploiting the special structure of the proposed formulations. The Insert-and-Fix method, in combination with a constructive algorithm that gives the solver an initial solution in each iteration, provides solutions with a low number of rehandles for instances with up to 5000 TEUs.Spanish Ministry of Science, Innovation, and Universities, FPU Grant A-2015-12849 and under the project “OPTEP-Port Terminal Operations Optimization” (No. RTI2018-094940-B-I00) financed with FEDER, Spain funds. The second author acknowledges the partial support by Data-driven logistics, Spain (FWO-S007318N) and Internal Funds KU Leuven, Spain

Organizational Citizenship Behavior pada Karyawan: Peranan Quality of Work Life dan Komitmen Organisasi

This study aims to examine the influence of Quality of Work Life (QWL) and Organizational Commitment on Organizational Citizenship Behavior (OCB) among employees. OCB is an extra-role behavior that supports organizational effectiveness and enhances business sustainability by encouraging employees to contribute beyond their formal duties. This study employs a quantitative approach with a correlational design and involves 104 employees of PT. Kerta Rajasa Raya (51 males, 53 females, average age = 34 years). Data were collected through questionnaires measuring QWL (α = 0.949), Organizational Commitment (α = 0.900), and OCB (α = 0.887). Multiple linear regression analysis indicates that QWL and Organizational Commitment collectively contribute 50.3% to OCB (R² = 0.503, p 0.01). Partially, QWL (t = 3.901, p 0.01) and Organizational Commitment (t = 3.253, p = 0.002) significantly influence OCB. The findings suggest that higher QWL and Organizational Commitment increase employees’ tendency to engage in OCB. Therefore, organizations should enhance QWL through employee welfare programs, a supportive work environment, and work-life balance. Additionally, fostering commitment through supportive leadership, effective communication, and fair reward systems can strengthen employee engagement, boost work motivation, and optimize organizational productivity in a sustainable manner. Penelitian ini bertujuan untuk menguji pengaruh Quality of Work Life (QWL) dan Komitmen Organisasi terhadap Organizational Citizenship Behavior (OCB) pada karyawan. OCB merupakan perilaku ekstra peran yang mendukung efektivitas organisasi dan meningkatkan keberlanjutan perusahaan dengan mendorong karyawan untuk berkontribusi di luar tugas formal mereka. Penelitian ini menggunakan pendekatan kuantitatif dengan desain korelasional dan melibatkan 104 karyawan PT. Kerta Rajasa Raya (51 laki-laki, 53 perempuan, rerata usia = 36 tahun). Data dikumpulkan melalui kuesioner yang mengukur QWL (α = 0.949), Komitmen Organisasi (α = 0.900), dan OCB (α = 0.887). Analisis regresi linear berganda menunjukkan bahwa QWL dan Komitmen Organisasi secara simultan berkontribusi sebesar 50.3% terhadap OCB (R² = 0.503, p 0.01). Secara parsial, QWL (t = 3.901, p 0.01) dan Komitmen Organisasi (t = 3.253, p = 0.002) memiliki pengaruh signifikan terhadap OCB. Hasil ini menunjukkan bahwa semakin baik QWL dan semakin tinggi Komitmen Organisasi, semakin besar kecenderungan karyawan untuk menunjukkan OCB. Oleh karena itu, organisasi perlu meningkatkan QWL melalui kesejahteraan, lingkungan kerja yang mendukung, serta keseimbangan kerja-hidup. Selain itu, membangun komitmen melalui kepemimpinan yang suportif, komunikasi efektif, serta sistem penghargaan yang adil dapat memperkuat keterikatan karyawan, meningkatkan motivasi kerja, dan mengoptimalkan produktivitas organisasi secara berkelanjutan