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We consider a semiparametric panel stochastic frontier model where one-sided firm effects representing inefficiencies are correlated with the regressors. A form of the Chamberlain-Mundlak device is used to relate the logarithm of the effects to the regressors resulting in a lognormal distribution for the effects. The function describing the technology is modeled nonparametrically using penalized splines. Both Bayesian and non-Bayesian approaches to estimation are considered, with an emphasis on Bayesian estimation. A Monte Carlo experiment is used to investigate the consequences of ignoring correlation between the effects and the regressors, and choosing the wrong functional form for the technology.

Organizational cultures that facilitate collaboration are valuable, but little is known about how to create them. The authors investigate the microfoundations of this problem using computational models of dyadic coupled learning. The authors find that merely altering initial beliefs about the consequence of actions (without altering the consequences themselves) can under some conditions create cultures that promote collaboration. The results of this study show why the right initial “framing” of a situation – established for instance through persuasive rhetoric, an inspiring vision, or careful recruitment choices – may under the right conditions be self-reinforcing, instead of becoming empty symbolism.

This paper aims to develop an efficient algorithm combining straightforward response surface functions with Monte Carlo simulation to conduct seismic reliability analysis in a systematical way.

The representative slip surfaces are identified and based on to calibrate multiple response surface functions with acceptable accuracy. The calibrated response surfaces are used to determine the yield acceleration in Newmark sliding displacement analysis. Then, the displacement-based limit state function is adopted to conduct seismic reliability analysis.

The calibrated response surface functions have fairly good accuracy in predicting the yield acceleration in Newmark sliding displacement analysis. The seismic reliability is influenced by such factors as PGA, spatial variability and threshold value. The proposed methodology serves as an effective tool for geotechnical practitioners.

The multiple sources of a seismic slope response can be effectively determined using the multiple response surface functions, which are easily implemented within geotechnical engineering.

The purpose of this paper is to scope the field of child-related online harms and to produce a resource pack to communicate all the different dimensions of this domain to teachers and carers.

With children increasingly operating as independent agents online, their teachers and carers need to understand the risks of their new playground and the range of risk management strategies they can deploy. Carers and teachers play a prominent role in applying the three M’s: mentoring the child, mitigating harms using a variety of technologies (where possible) and monitoring the child’s online activities to ensure their cybersecurity and cybersafety. In this space, the core concepts of “cybersafety” and “cybersecurity” are substantively different and this should be acknowledged for the full range of counter-measures to be appreciated. Evidence of core concept conflation emerged, confirming the need for a resource pack to improve comprehension. A carefully crafted resource pack was developed to convey knowledge of risky behaviors for three age groups and mapped to the appropriate “three M’s” to be used as counter-measures.

The investigation revealed key concept conflation, and then identified a wide range of harms and countermeasures. The resource pack brings clarity to this domain for all stakeholders.

The number of people who were involved in the empirical investigation was limited to those living in Scotland and Nigeria, but it is unlikely that the situation is different elsewhere because the internet is global and children’s risky behaviors are likely to be similar across the globe.

Others have investigated this domain, but no one, to the authors’ knowledge, has come up with the “Three M’s” formulation and a visualization-based resource pack that can inform educators and carers in terms of actions they can take to address the harms.

The purpose of this paper is to present a novel manufacturing process that aims to pattern metal tracks onto polyimide at atmospheric pressure and ambient environment. The process can be scaled up for industrial applications.

From a thorough literature survey, different approaches were carried out for processing polyimide. Following a design of experiments for the processing and various characterisation techniques, a micro‐coil was manufactured as a test demonstrator.

The characteristics of some main formaldehyde‐based electroless copper baths were compared. The quality of the sidewalls was characterised and the performance of the process was assessed.

This paper demonstrates a high‐value manufacturing technique that is mass manufacturable, low cost and suitable for use on 3D surfaces. Criteria required for the development of a direct‐writing process have been described. The issues surrounding electroless plating on polyimide have been explained.

This paper aims to present the estimation of the output voltage of metal oxide semiconductor field effect transistor (MOSFET) using the extended Kalman filter (EKF) method.

The method uses EKF for MOSFET output voltage estimation. To implement the EKF method, the state space model has been obtained using Kirchhoff’s current law and Enz-Krummenacher-Vittoz model of the MOSFET circuit.

The proposed method can be used for any mode of MOSFET operation besides near the quiescent point region. The nonlinearity that occurs in the saturation region of MOSFET can also be considered in the proposed method. The proposed method can also be used for a large input signal. Though Kalman filter can be used for the small amplitude input signal, it results in inaccurate estimation due to the linearization of the nonlinear system.

The method is able to track the parameters when they are slowly changing with time.

The proposed method presents maximal precision of simulation as the maximal precision of simulation requires modeling of the circuit in terms of device parameters and circuit elements.

The authors aim to develop a conceptual framework for longitudinal estimation of stress-related states in the wild (IW), based on the machine learning (ML) algorithms that use physiological and non-physiological bio-sensor data.

The authors propose a conceptual framework for longitudinal estimation of stress-related states consisting of four blocks: (1) identification; (2) validation; (3) measurement and (4) visualization. The authors implement each step of the proposed conceptual framework, using the example of Gaussian mixture model (GMM) and K-means algorithm. These ML algorithms are trained on the data of 18 workers from the public administration sector who wore biometric devices for about two months.

The authors confirm the convergent validity of a proposed conceptual framework IW. Empirical data analysis suggests that two-cluster models achieve five-fold cross-validation accuracy exceeding 70% in identifying stress. Coefficient of accuracy decreases for three-cluster models achieving around 45%. The authors conclude that identification models may serve to derive longitudinal stress-related measures.

Proposed conceptual framework may guide researchers in creating validated stress-related indicators. At the same time, physiological sensing of stress through identification models is limited because of subject-specific reactions to stressors.

Longitudinal indicators on stress allow estimation of long-term impact coming from external environment on stress-related states. Such stress-related indicators can become an integral part of mobile/web/computer applications supporting stress management programs.

Timely identification of excessive stress may improve individual well-being and prevent development stress-related diseases.

The study develops a novel conceptual framework for longitudinal estimation of stress-related states using physiological and non-physiological bio-sensor data, given that scientific knowledge on validated longitudinal indicators of stress is in emergent state.

The purpose of this paper is to solve the problem of tuning of EKF parameters (process and measurement noise co-variance matrices) designed for attitude estimation using Global Positioning System (GPS) aided inertial sensors by employing a Human Opinion Dynamics (HOD)-based optimization technique and modifying the technique using maximum likelihood estimators and study its performance as compared to Particle Swarm Optimization (PSO) and manual tuning.

A model for the determination of attitude of flight vehicles using inertial sensors and GPS measurement is designed and experiments are carried out to collect raw sensor and reference data. An HOD-based model is utilized to estimate the optimized process and measurement noise co-variance matrix. Added to it, few modifications are proposed in the HOD model by utilizing maximum likelihood estimator and finally the results obtained by the proposed schemes analysed.

Analysis of the results shows that utilization of evolutionary algorithms for tuning is a significant improvement over manual tuning and both HOD and PSO-based methods are able to achieve the same level of accuracy. However, the HOD methods show better convergence and is easier to implement in terms of tuning parameters. Also, utilization of maximum likelihood estimator shows better search during initial iterations which increases the robustness of the algorithm.

The paper is unique in its sense that it utilizes a HOD-based model to solve tuning problem of EKF for attitude estimation.

Integrated care is widely supported as a means of improving treatment outcomes for people with co-occurring mental health and substance use disorders. Over the past two decades, Australian state and federal governments have identified integrated care as a policy priority and invested in a number of research and capacity building initiatives. This study aims to examine Australian research evaluating the effectiveness of integrated treatment approaches to provide insight into implications for future research and practice in integrated treatment.

This narrative review examines Australian research evaluating empirical evidence of the effectiveness of integrated treatment approaches within specific populations and evidence from initiatives aimed at integrating care at the service or system level.

Research conducted within the Australian context provides considerable evidence to support the effectiveness of integrated approaches to treatment, particularly for people with high prevalence co-occurring disorders or symptoms of these (i.e. anxiety and depression). These have been delivered through various modalities (including online and telephone-based services) to improve health outcomes in a range of populations. However, there is less evidence regarding the effectiveness of specific models or systems of integrated care, including for more severe mental disorders. Despite ongoing efforts on behalf of the Australian government, attempts to sustain system-level initiatives have remained hampered by structural barriers.

Effective integrated interventions can be delivered by trained clinicians without requiring integration at an organisational or structural level. While there is still considerable work to be done in terms of building sustainable models at a system level, this evidence provides a potential foundation for the development of integrated care models that can be delivered as part of routine practice.

The purpose of this paper is to propose a novel on‐line print‐defect detecting approach.

The proposed method uses incremental principal component analysis (IPCA) to model a variety pattern with respect to the detected image itself.

The algorithm is constructed and deployed to a real‐time detecting print‐defect system, and the test results show that the system reduces false alarms dramatically.

The paper describes groundbreaking work which, for the first time in the printing industry, uses IPCA in relation to print‐defect detecting.