Stress-induced rise in body temperature is repeatable in free-ranging Eastern chipmunks (Tamias striatus)

In response to handling or other acute stressors, most mammals, including humans, experience a temporary rise in body temperature (T b). Although this stress-induced rise in T b has been extensively studied on model organisms under controlled environments, individual variation in this interesting phenomenon has not been examined in the field. We investigated the stress-induced rise in T b in free-ranging eastern chipmunks (Tamias striatus) to determine first if it is repeatable. We predicted that the stress-induced rise in T b should be positively correlated to factors affecting heat production and heat dissipation, including ambient temperature (T a), body mass (M b), and field metabolic rate (FMR). Over two summers, we recorded both T b within the first minute of handling time (T b1) and after 5 min of handling time (T b5) 294 times on 140 individuals. The mean ∆T b (T b5 – T b1) during this short interval was 0.30 ± 0.02°C, confirming that the stress-induced rise in T b occurs in chipmunks. Consistent differences among individuals accounted for 40% of the total variation in ∆T b (i.e. the stress-induced rise in T b is significantly repeatable). We also found that the stress-induced rise in T b was positively correlated to T a, M b, and mass-adjusted FMR. These results confirm that individuals consistently differ in their expression of the stress-induced rise in T b and that the extent of its expression is affected by factors related to heat production and dissipation. We highlight some research constraints and opportunities related to the integration of this laboratory paradigm into physiological and evolutionary ecology.

Cache and carry : hoarding behavior of arctic fox

Food-hoarding animals are expected to preferentially cache items with lower perishability and/or higher consumption time. We observed arctic foxes (Alopex lagopus) foraging in a greater snow goose (Anser caerulescens atlanticus) colony where the main prey of foxes consisted of goose eggs, goslings, and lemmings (Lemmus and Dicrostonyx spp.). We recorded the number of prey consumed and cached and the time that foxes invested in these activities. Foxes took more time to consume a goose egg than a lemming or gosling but cached a greater proportion of eggs than the other prey type. This may be caused by the eggshell, which presumably decreases the perishability and/or pilfering risk of cached eggs, but also increases egg consumption time. Arctic foxes usually recached goose eggs but rarely recached goslings or lemmings. We tested whether the rapid-sequestering hypothesis could explain this recaching behavior. According to this hypothesis, arctic foxes may adopt a two-stage strategy allowing both to maximize egg acquisition rate in an undefended nest and subsequently secure eggs in potentially safer sites. Foxes spent more time carrying an egg and traveled greater distances when establishing a secondary than a primary cache. To gain further information on the location and subsequent fate of cached eggs, we used dummy eggs containing radio transmitters. Lifespan of primary caches increased with distance from the goose nest. Secondary caches were generally located farther from the nest and had a longer lifespan than primary caches. Behavioral observations and the radio-tagged egg technique both gave results supporting the rapid-sequestering hypothesis.

Value analysis of just-in-time demolition approach

The recent deconstruction approach for demolition projects promotes reusing and recycling materials. However, the demolition project is interrupted and slowed down while the project team wait for the waste exchange process. Wasted materials generated from the demolition project have to be stored on demolition site or extra depository. Cost and time might be lost for the inventory of wasted materials and products. Just-in-Time (JIT) is a matured method widely used in manufacture industry as well as construction industry. It is utilised to reduce the inventory of both raw materials and final products. It is also used to shorten production cycle and improve the quality of the products. The JIT philosophy can be applied into demolition project so that the inventory of wasted materials can be eliminated and the project time can be shortened. To implement JIT demolition, the waste exchange process can be performed before the wasted materials are generated from the project. Material owners and demanders can virtually plan for waste handling before the demolition project is physically implemented. As a result, waste materials can be sent to demanders through transportation right after they are produced from the project. Applying JIT philosophy in demolition projects can effectively reduce the inventory of wasted materials and the amount of demolition waste to be sent to landfills. Therefore the cost and time of the project are reduced, and the quality of final delivered materials is improved.

Web enabled just-in-time salvaged material management for demolition projects

The demolition activities of buildings produce numerous environmental pressures as a large proportion of demolition waste materials are sent to landfill directly in many projects. Web-based waste exchange systems could provide right solutions for releasing these pressures. Because the approaches adopted in current waste exchange systems are inefficient, these systems cannot generate waste exchange, not achieving their final goal, environmental protection. The Just-in-time (JIT) philosophy has been applied in the manufacture industry for decades and it is proven to be effective to eliminate or minimise inventory during production. This research aims to adopt the JIT philosophy into a demolition project management informapon system so that the system is more efficient in handling waste exchange. The system structure, key components and Just-in-time adoption are proposed and identified. Finally, a proto typed system is demonstrated.

Application of co-operative agents in handling fluctuations in a pull production system

This paper presents the general details of the structure and strategy of a multi-agent system that is being developed to improve the performance of pull (kanban) production control to handle large fluctuations in product demand. Employing a set of generic, heterarchial agents each controlling a single product and co-operating together to ensure that all components, regardless of demand fluctuation, are manufactured on time as per basic kanban principles. Preliminary results indicate that the basic kanban model does not cater for large demand fluctuations and the application of this multi-agent strategy may be beneficial to improving the overall system performance and increase the likelihood that all products will be manufactured on time.

Simulation-based input loading condition optimisation of airport baggage handling systems

Scheduling check-in station operations are a challenging problem within airport systems. Prior to determining check-in resource schedules, an important step is to estimate the Baggage Handling System (BHS) operating capacity under non-stationary conditions. This ensures that check-in stations are not overloaded with bags, which would adversely affect the system and cause cascade stops and blockages. Cascading blockages can potentially lead to a poor level of service and in worst scenario a customer may depart without their bags. This paper presents an empirical study of a multiobjective problem within a BHS system. The goal is to estimate near optimal input operating conditions, such that no blockages occurs at check-in stations, while minimising the baggage travel time and maximising the throughput performance measures. We provide a practical hybrid simulation and binary search technique to determine a near optimal input throughput operating condition. The algorithm generates capacity constraint information that may be used by a scheduler to plan check-in operations based on flight arrival schedules.

Kernel performance in meeting hard real-time system characteristics (the ARTOS real-time kernel)

Describes the design and implementation of an operating system kernel specifically designed to support real-time applications. It emphasises portability and aims to support state-of-the-art concepts in real-time programming. Discusses architectural aspects of the ARTOS kernel, and introduces new concepts on the areas of interrupt processing, scheduling, mutual exclusion and inter-task communication. Also explains the programming environment of ARTOS kernal and its task model, defines the real-time task states and system data structures and discusses exception handling mechanisms which are used to detect missed deadlines and take corrective action.

Estimating performance indexes of a baggage handling system using metamodels

In this study, we develop some deterministic metamodels to quickly and precisely predict the future of a technically complex system. The underlying system is essentially a stochastic, discrete event simulation model of a big baggage handling system. The highly detailed simulation model of this is used for conducting some experiments and logging data which are then used for training artificial neural network metamodels. Demonstrated results show that the developed metamodels are well able to predict different performance measures related to the travel time of bags within this system. In contrast to the simulation models which are computationally expensive and expertise extensive to be developed, run, and maintained, the artificial neural network metamodels could serve as real time decision aiding tools which are considerably fast, precise, simple to use, and reliable.

A generalised data analysis approach for baggage handling systems simulation

Airport baggage handling systems are a critical infrastructure component within major airports, and essential to ensure smooth luggage transfer while preventing dangerous material being loaded onto aircraft. This paper proposes a standard set of measures to assess the expected performance of a baggage handling system through discrete event simulation. These evaluation methods also have application in the study of general network systems. Results from the application of these methods reveal operational characteristics of the studied BHS, in terms of metrics such as peak throughput, in-system time and system recovery time.

An effective heuristic for stockyard planning and machinery scheduling at a coal handling facility

Coal handling is a complex process involving different correlated and highly dependent operations such as selecting appropriate product types, planning stockpiles, scheduling stacking and reclaiming activities and managing train loads. Planning these operations manually is time consuming and can result in non-optimized schedules as future impact of decisions may not be appropriately considered. This paper addresses the operational scheduling of the continuous coal handling problem with multiple conflicting objectives. As the problem is NP-hard in nature, an effective heuristic is presented for planning stockpiles and scheduling resources to minimize delays in production and the coal age in the stockyard. A model of stockyard operations within a coal mine is described and the problem is formulated as a Bi- Objective Optimization Problem (BOOP). The algorithm efficacy is demonstrated on different real-life data scenarios. Computational results show that the solution algorithm is effective and the coal throughput is substantially impacted by the conflicting objectives. Together, the model and the proposed heuristic, can act as a decision support system for the stockyard planner to explore the effects of alternative decisions, such as balancing age and volume of stockpiles, and minimizing conflicts due to stacker and reclaimer movements.

A dynamic time warped clustering technique for discrete event simulation-based system analysis

Abstract This paper introduces a novel approach for discrete event simulation output analysis. The approach combines dynamic time warping and clustering to enable the identification of system behaviours contributing to overall system performance, by linking the clustering cases to specific causal events within the system. Simulation model event logs have been analysed to group entity flows based on the path taken and travel time through the system. The proposed approach is investigated for a discrete event simulation of an international airport baggage handling system. Results show that the method is able to automatically identify key factors that influence the overall dwell time of system entities, such as bags that fail primary screening. The novel analysis methodology provides insight into system performance, beyond that achievable through traditional analysis techniques. This technique also has potential application to agent-based modelling paradigms and also business event logs traditionally studied using process mining techniques.

Maximizing real-time streaming services based on a multi-servers networking framework

In recent years, we have witnessed substantial exploitation of real-time streaming applications, such as video surveillance system on road crosses of a city. So far, real world applications mainly rely on the traditional well-known client-server and peer-to-peer schemes as the fundamental mechanism for communication. However, due to the limited resources on each terminal device in the applications, these two schemes cannot well leverage the processing capability between the source and destination of the video traffic, which leads to limited streaming services. For this reason, many QoS sensitive application cannot be supported in the real world. In this paper, we are motivated to address this problem by proposing a novel multi-server based framework. In this framework, multiple servers collaborate with each other to form a virtual server (also called cloud-server), and provide high-quality services such as real-time streams delivery and storage. Based on this framework, we further introduce a (1-?) approximation algorithm to solve the NP-complete "maximum services"(MS) problem with the intention of handling large number of streaming flows originated by networks and maximizing the total number of services. Moreover, in order to backup the streaming data for later retrieval, based on the framework, an algorithm is proposed to implement backups and maximize streaming flows simultaneously. We conduct a series of experiments based on simulations to evaluate the performance of the newly proposed framework. We also compare our scheme to several traditional solutions. The results suggest that our proposed scheme significantly outperforms the traditional solutions.