A rapid method for investigating the absorption of formaldehyde from air by wool

Formaldehyde emitted from household products, such as furniture produced with medium density fibreboards, has been reported as causing health concerns in both domestic and business environments, these concerns being generally known as ‘sick building syndrome’. A number of differing approaches to removing formaldehyde from the atmosphere have been investigated. It is known that formaldehyde binds to wool fibres when the formaldehyde is in the liquid phase. However, few investigations into the sorption potential of wool for vapour phase formaldehyde have been made. This article details a rapid, novel method to directly measure the uptake of formaldehyde by wool and by inference, other materials. The data detailed in this article also demonstrates the significant ability of wool to sorb formaldehyde in the vapour state.     

Cargo scheduling decision support for offshore oil and gas production: a case study

Woodside Energy Ltd (Woodside), Australia’s largest independent oil and gas company, operates multiple oil and gas facilities off the coast of Western Australia. These facilities require regular cargo shipments from supply vessels based in Karratha, Western Australia. In this paper, we describe a decision support model for scheduling the cargo shipments to minimize travel cost and trip duration, subject to various operational restrictions including vessel capacities, cargo demands at the facilities, time windows at the facilities, and base opening times. The model is a type of non-standard vehicle routing problem involving multiple supply vessels—a primary supply vessel that visits every facility during a round trip taking at most 1 week, and other supply vessels that are used on an ad hoc basis when the primary vessel cannot meet all cargo demands. We validate the model via test simulations using real data provided by Woodside.     

Minimizing control variation in nonlinear optimal control

In any real system, changing the control signal from one value to another will usually cause wear and tear on the system’s actuators. Thus, when designing a control law, it is important to consider not just predicted system performance, but also the cost associated with changing the control action. This latter cost is almost always ignored in the optimal control literature. In this paper, we consider a class of optimal control problems in which the variation of the control signal is explicitly penalized in the cost function. We develop an effective computational method, based on the control parameterization approach and a novel transformation procedure, for solving this class of optimal control problems. We then apply our method to three example problems in fisheries, train control, and chemical engineering.     

Effect of biotin supplementation on meat quality of F1 Wagyu/Black Angus feedlot steers of known genotype

Biotin (D-biotin) was supplemented to F1 Wagyu/Black Angus steers fed a wheat-based ration to evaluate the effect on meat quality. One hundred and eight steers of known Wagyu sire lines were assigned to three biotin treatments (0, 10 and 20mg/head/day) with each treatment replicated four times using an unfasted liveweight of 410.5kg (±24.42 SD). Biotin supplementation had no effect (P>0.05) on beef marbling standard at either the 5/6th or 10/11th rib quartering site, 10/11th rib intra-muscular fat percentage, intra-muscular fat fatty acid composition or adipose melting points. Wagyu genotype had an effect (P<0.05) on beef marbling standard and intra-muscular fat percentage at the 10/11th rib, inter-muscular and intra-muscular melting point and fatty acid composition of intra-muscular fat. A significant (P<0.001) but poor correlation existed between beef marbling standard and intra-muscular fat percentage (R(2)=0.198). Total conjugated linoleic acid had a highly significantly (P<0.0001) positive correlation to intra-muscular fat percentage (R(2)=0.446).     

Computational Method for a Class of Switched System Optimal Control Problems

We consider an optimal control problem with dynamics that switch between several subsystems of nonlinear differential equations. Each subsystem is assumed to satisfy a linear growth condition. Furthermore, each subsystem switch is accompanied by an instantaneous change in the state. These instantaneous changes-called ldquostate jumpsrdquo-are influenced by a set of control parameters that, together with the subsystem switching times, are decision variables to be selected optimally. We show that an approximate solution for this optimal control problem can be computed by solving a sequence of conventional dynamic optimization problems. Existing optimization techniques can be used to solve each problem in this sequence. A convergence result is also given to justify this approach.     

Exploring the social dimensions and complexity of cumulative impacts: a case study of forest policy changes in Western Australia

Social impacts resulting from policy changes and other interventions interact and aggregate, and are influenced by additional interventions and exogenous factors, leading to cumulative social impacts. We explored these complex impacts through a case study of forest policy changes introduced in the state of Western Australia between 1999 and 2004. In this process, we both drew on and modified the recently-proposed Cumulative Effects Assessment and Management (CEAM) framework, to improve its utility as an analytical tool for exploring cumulative social impacts that arise from policy changes in natural resource sectors. Our findings highlight the complexity of the pathways that lead to social impacts and the significant influence of individuals' responses. The findings also demonstrate the importance of considering cumulative impacts - negative and positive, and intended and unintended – when designing and implementing mitigation strategies, emphasizing the value of adaptive management approaches. Our results suggest that the CEAM framework, appropriately contextualized and adapted, is relevant to the assessment of social impacts associated with interventions in complex natural resource management cases, and probably more widely.     

Optimal switching instants for a switched-capacitor DC/DC power converter

We consider a switched-capacitor DC/DC power converter with variable switching instants. The determination of optimal switching instants giving low output ripple and strong load regulation is posed as a non-smooth dynamic optimization problem. By introducing a set of auxiliary differential equations and applying a time-scaling transformation, we formulate an equivalent optimization problem with semi-infinite constraints. Existing algorithms can be applied to solve this smooth semi-infinite optimization problem. The existence of an optimal solution is also established. For illustration, the optimal switching instants for a practical switched-capacitor DC/DC power converter are determined using this approach.     

Optimal control problems with a continuous inequality constraint on the state and the control

We consider an optimal control problem with a nonlinear continuous inequality constraint. Both the state and the control are allowed to appear explicitly in this constraint. By discretizing the control space and applying a novel transformation, a corresponding class of semi-infinite programming problems is derived. A solution of each problem in this class furnishes a suboptimal control for the original problem. Furthermore, we show that such a solution can be computed efficiently using a penalty function method. On the basis of these two ideas, an algorithm that computes a sequence of suboptimal controls for the original problem is proposed. Our main result shows that the cost of these suboptimal controls converges to the minimum cost. For illustration, an example problem is solved.     

Immunometabolism of Myeloid-Derived Suppressor Cells: Implications for Mycobacterium tuberculosis Infection and Insights from Tumor Biology

The field of immunometabolism seeks to decipher the complex interplay between the immune system and the associated metabolic pathways. The role of small molecules that can target specific metabolic pathways and subsequently alter the immune landscape provides a desirable platform for new therapeutic interventions. Immunotherapeutic targeting of suppressive cell populations, such as myeloid-derived suppressor cells (MDSC), by small molecules has shown promise in pathologies such as cancer and support testing of similar host-directed therapeutic approaches in MDSC-inducing conditions such as tuberculosis (TB). MDSC exhibit a remarkable ability to suppress T-cell responses in those with TB disease. In tumors, MDSC exhibit considerable plasticity and can undergo metabolic reprogramming from glycolysis to fatty acid oxidation (FAO) and oxidative phosphorylation (OXPHOS) to facilitate their immunosuppressive functions. In this review we look at the role of MDSC during M. tb infection and how their metabolic reprogramming aids in the exacerbation of active disease and highlight the possible MDSC-targeted metabolic pathways utilized during M. tb infection, suggesting ways to manipulate these cells in search of novel insights for anti-TB therapies.     

Optimal control computation for nonlinear systems with state-dependent stopping criteria

In this paper, we consider a challenging optimal control problem in which the terminal time is determined by a stopping criterion. This stopping criterion is defined by a smooth surface in the state space; when the state trajectory hits this surface, the governing dynamic system stops. By restricting the controls to piecewise constant functions, we derive a finite-dimensional approximation of the optimal control problem. We then develop an efficient computational method, based on nonlinear programming, for solving the approximate problem. We conclude the paper with four numerical examples.