Study of fuel insolubles: Formation conditions and characterization of copper compounds

The solids formed in the systems containing copper in different oxidation states, in the presence and absence of hexanoic acid and dodecanethiol, together and separately, at room temperature, were studied. The experiments were performed in a mineral oil matrix, free of sulfur compounds and metals; a diesel oil matrix; and the reagents alone, without any matrix. The deposits formed were analyzed by elemental analysis (EA), infrared spectroscopy (IR), thermogravimetric analysis (TGA) and total copper by inductively coupled plasma-optical emission spectrometry (ICP-OES), for their identification and determination of the probable structures. In samples containing both hexanoic acid and dodecanethiol, when there is copper(I), anhydrous copper(II) hexanoate is preferentially formed, but in samples of copper(II), copper(II) mercaptate is formed first. In samples of metallic copper in mineral oil matrix, no deposit formations occur. In all cases in which deposits were formed, they were the same as in diesel oil matrix.     

Photocatalytic degradation of 2,2‐bis(4‐hydroxy‐3‐methylphenyl) propane (BPP) based on molecular recognition interaction

BACKGROUND: Endocrine disruptors in the aquatic environment and their potential adverse effects are currently issues of concern. One of these endocrine disruptors is 2,2‐bis(4‐hydroxy‐3‐methylphenyl)propane (BPP). In this work the molecular recognition interaction of BPP with β‐cyclodextrin (β‐CD) was studied using IR spectroscopy and steady state fluorescence spectroscopy, and the photocatalytic degradation behaviour of BPP based on molecular recognition interaction was investigated in a TiO₂/UV–visible (λ_max = 365 nm) system. This might provide a new method for the treatment of some organic pollutants in wastewater. RESULTS: β‐CD reacts with BPP to form a 1:1 inclusion complex, the formation constant of which is 4.94 × 10³ L mol^?1. The photodegradation rate constant of BPP after molecular recognition by β‐CD showed a 1.42‐fold increase in the TiO₂/UV–visible (λ_max = 365 nm) system. The photodegradation of BPP depended on the concentration of β‐CD, the pH value, the gaseous medium and the initial concentration of BPP. The photodegradation efficiency of BPP with molecular recognition was higher than that without molecular recognition. After 100 min of irradiation the mineralisation efficiency of BPP after molecular recognition by β‐CD reached 94.8%, whereas the mineralisation efficiency of BPP before molecular recognition by β‐CD was only 40.6%. CONCLUSION: The photocatalytic degradation of BPP after molecular recognition by β‐CD can be enhanced in the TiO₂/UV‐visible (λ_max = 365 nm) system. This enhancement is dependent on the enhancement of the adsorption of BPP, the moderate inclusion depth of BPP in the β‐CD cavity and the increase in the frontier electron density of BPP after molecular recognition. Copyright © 2008 Society of Chemical Industry     

Machine-learning paradigms for selecting ecologically significant input variables

Harmful algal blooms, which are considered a serious environmental problem nowadays, occur in coastal waters in many parts of the world. They cause acute ecological damage and ensuing economic losses, due to fish kills and shellfish poisoning as well as public health threats posed by toxic blooms. Recently, data-driven models including machine-learning (ML) techniques have been employed to mimic dynamics of algal blooms. One of the most important steps in the application of a ML technique is the selection of significant model input variables. In the present paper, we use two extensively used ML techniques, artificial neural networks (ANN) and genetic programming (GP) for selecting the significant input variables. The efficacy of these techniques is first demonstrated on a test problem with known dependence and then they are applied to a real-world case study of water quality data from Tolo Harbour, Hong Kong. These ML techniques overcome some of the limitations of the currently used techniques for input variable selection, a review of which is also presented. The interpretation of the weights of the trained ANN and the GP evolved equations demonstrate their ability to identify the ecologically significant variables precisely. The significant variables suggested by the ML techniques also indicate chlorophyll-a (Chl-a) itself to be the most significant input in predicting the algal blooms, suggesting an auto-regressive nature or persistence in the algal bloom dynamics, which may be related to the long flushing time in the semi-enclosed coastal waters. The study also confirms the previous understanding that the algal blooms in coastal waters of Hong Kong often occur with a life cycle of the order of 1–2 weeks.     

Benchmark test of the effectiveness of a nitrogen cooled beryllium reflector-filter

We present a comparison between the calculated and the measured effectiveness of a nitrogen cooled beryllium reflector-filter in increasing the cold flux of a polyethylene moderator at the same temperature. We also discuss the impact of the quality of beryllium on the results.     

Fiber–fiber interactions in carbon mat thermoplastics

Carbon mat thermoplastics (CMT) consisting of 12.7 mm long, chopped carbon fibers in a polypropylene matrix were manufactured using the wetlay technique at fiber volume fractions (FVF) from 10% to 25%, and tests simulating the compression molding process were conducted. The packing stress of the CMT followed a power law relation with FVF. A single fiber pull-out fixture was used to measure the frictional and hydrodynamic lubrication coefficients at fiber–fiber touch points, and results were fit with an existing relation for glass mat thermoplastics. In isothermal squeeze flow the load–displacement behavior for the 10% FVF CMT was similar in shape to that for a fluid with a yield stress. However, for FVFs of 15–25%, the load–displacement curves showed a load spike at the beginning of the flow, then followed the curve for a fluid with a yield stress. The spike was attributed to fiber breakage that increased with increasing FVF of the sample.     

Comparison of three internationally certified firefighter protective ensembles: Physiological responses,mobility, and comfort

BackgroundFire protective ensembles (FPEs) are essential to safely perform firefighting job tasks; however, they are often burdensome to the workers. The aim of this study was to compare three internationally certified fire protective ensembles from the European Union (EU), South Korea (SK), and United States (US) on physiological responses, mobility, and comfort.MethodsTen male professional firefighters performed a battery of exercises in the laboratory following the ASTM F3031-17 standard to evaluate mobility, occupation-specific performance, and physiological responses (body weight, heart rate (HR), core temperature (T_c), breathing rate (BR), and rating of perceived exertion (RPE)) to 20 min of treadmill walking (3.2 mph, 5% incline). All participants carried out the evaluation wearing each FPE in a random order. Mixed effects models examined time (pre-vs. post-) by ensemble (EU, SK, US) interactions for all physiological variables and compared comfort, performance, and subjective variables across ensembles.ResultsNo interaction effects were observed for body weight, HR, T_c, BR, or RPE (p = 0.890, p = 0.994, p = 0.897, p = 0.435, and p = 0.221; respectively). SK had greater trunk flexion than EU (78.4° vs. 74.6°, p = 0.026) and US had lower standing reach than EU (105.5 cm vs. 115.4 cm, p = 0.004). Agility circuit time was lower in US (9.3 s) compared to EU (9.8 s) or SK (9.9 s) (p = 0.051 and p = 0.019, respectively).ConclusionsThe findings suggest that physiological burden remained largely unchanged across the international FPEs. However, mobility, performance, and comfort may be significantly influenced across types. International stakeholders and end users should consider design implications when choosing fire protective ensembles.     

Generating phenotypical erroneous human behavior to evaluate human–automation interaction using model checking

Breakdowns in complex systems often occur as a result of system elements interacting in unanticipated ways. In systems with human operators, human–automation interaction associated with both normative and erroneous human behavior can contribute to such failures. Model-driven design and analysis techniques provide engineers with formal methods tools and techniques capable of evaluating how human behavior can contribute to system failures. This paper presents a novel method for automatically generating task analytic models encompassing both normative and erroneous human behavior from normative task models. The generated erroneous behavior is capable of replicating Hollnagel's zero-order phenotypes of erroneous action for omissions, jumps, repetitions, and intrusions. Multiple phenotypical acts can occur in sequence, thus allowing for the generation of higher order phenotypes. The task behavior model pattern capable of generating erroneous behavior can be integrated into a formal system model so that system safety properties can be formally verified with a model checker. This allows analysts to prove that a human–automation interactive system (as represented by the model) will or will not satisfy safety properties with both normative and generated erroneous human behavior. We present benchmarks related to the size of the statespace and verification time of models to show how the erroneous human behavior generation process scales. We demonstrate the method with a case study: the operation of a radiation therapy machine. A potential problem resulting from a generated erroneous human action is discovered. A design intervention is presented which prevents this problem from occurring. We discuss how our method could be used to evaluate larger applications and recommend future paths of development.     

Public key distribution scheme for delay tolerant networks based on two-channel cryptography

A delay tolerant network (DTN) is a store carry and forward network characterized by highly mobile nodes, intermittent connectivity with frequent disruptions, limited radio range and physical obstructions. Emerging applications of DTN include rural DTN, vehicular DTN and pocket DTN. The development of DTN raises a number of security-related challenges due to inconsistent network access and unreliable end-to-end network path. One of the challenges is initial secure context establishment as it is unrealistic to assume that public key infrastructure (PKI) is always globally present and available, hence, the public key management becomes an open problem for DTN. In this paper, for the first time, we propose a dynamic virtual digraph (DVD) model for public key distribution study by extending graph theory and then present a public key distribution scheme for pocket DTN based on two-channel cryptography. By distinguishing between owners and carriers, public key exchange and authentication issues in the decentralized pocket DTN environment can be solved by a two-channel cryptography process and our simulation results have proven it.     

A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres

In recent years unmanned vehicles have grown in popularity, with an ever increasing number of applications in industry, the military and research within air, ground and marine domains. In particular, the challenges posed by unmanned marine vehicles in order to increase the level of autonomy include automatic obstacle avoidance and conformance with the Rules of the Road when navigating in the presence of other maritime traffic. The USV Master Plan which has been established for the US Navy outlines a list of objectives for improving autonomy in order to increase mission diversity and reduce the amount of supervisory intervention. This paper addresses the specific development needs based on notable research carried out to date, primarily with regard to navigation, guidance, control and motion planning. The integration of the International Regulations for Avoiding Collisions at Sea within the obstacle avoidance protocols seeks to prevent maritime accidents attributed to human error. The addition of these critical safety measures may be key to a future growth in demand for USVs, as they serve to pave the way for establishing legal policies for unmanned vessels.