Spouses' use of pressure and persuasion to promote osteoarthritis patients' medical adherence after orthopedic surgery.

Objective: The authors investigated health-related effects of social control (influence) that spouses exert in relation to osteoarthritis patients' medical adherence after total knee replacement surgery. Patients' behavioral and emotional responses to control were examined as mediators of associations between spouses' use of two control strategies (pressure, persuasion) and patients' physical and psychological recovery. Design: The authors used a three-wave panel design with assessments at one month before surgery, 1 month and 3 months after surgery. Data were collected during in-person interviews with 70 married, older adult patients. Main Outcome Measures: Recovery outcomes were assessed as improvement in knee limitations and depressive symptoms at the 3 month follow-up. Results: Spousal pressure and persuasion at one month postsurgery were indirectly associated with patients' recovery outcomes through patients' positive emotional responses to control. Conclusion: Although there are often immediate behavioral benefits in response to partners' use of both pressure and persuasion, the long-term health effects of these strategies seem to be accounted for by their opposing links to positive emotions. Findings further refine theory on health-related social control in marriage. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The impact of ferrous ion reduction of chlorite ion on drinking water process performance

The use of chlorine dioxide (ClO₂) as a primary disinfectant and pre-oxidant in drinking water treatment is being explored as an alternative to chlorine for reducing disinfection by-product formation and to assure compliance with United States Environmental Protection Agency's Stage 1 Disinfection/Disinfection By-Products Rule. However, the ClO₂ by-product chlorite ion (ClO₂⁻) is also regulated by the same regulation. Ferrous iron (Fe(II)) has been shown to effectively reduce chlorite ion to chloride ion (Cl⁻) and this study was conducted to evaluate the impact on overall treatment process performance due to the ferric hydroxide solids that form from the reaction. Ferrous iron application was explored at three different points in a pilot-scale water treatment system: pre-rapid mix, pre-settling and pre-filter. Chlorite ion concentrations were effectively reduced from 2 mg/L to less than 0.3 mg/L using an Fe(II) dose of approximately 6 mg/L for all trials. Fe(II) addition at the rapid mix caused no adverse effects and, in fact, allowed for reduction of the alum dose due to the newly formed ferric hydroxide acting as a supplemental coagulant. An increase of 241 and 247% of total suspended solids influent to the filter process was observed when Fe(II) was applied at the pre-settling and pre-filter locations. Pilot-scale filter runs during these trials were less than 2 h and never obtained true steady state conditions. Jar testing was performed to better understand the nature of the ferric hydroxide solids that are formed when Fe(II) was oxidized to Fe(III) and to explore the effectiveness of Fe(II) addition at intermediate stages in the flocculation process.     

High-performance flat-panel solar thermoelectric generators with high thermal concentration

The conversion of sunlight into electricity has been dominated by photovoltaic and solar thermal power generation. Photovoltaic cells are deployed widely, mostly as flat panels, whereas solar thermal electricity generation relying on optical concentrators and mechanical heat engines is only seen in large-scale power plants. Here we demonstrate a promising flat-panel solar thermal to electric power conversion technology based on the Seebeck effect and high thermal concentration, thus enabling wider applications. The developed solar thermoelectric generators (STEGs) achieved a peak efficiency of 4.6% under AM1.5G (1 kW m(-2)) conditions. The efficiency is 7-8 times higher than the previously reported best value for a flat-panel STEG, and is enabled by the use of high-performance nanostructured thermoelectric materials and spectrally-selective solar absorbers in an innovative design that exploits high thermal concentration in an evacuated environment. Our work opens up a promising new approach which has the potential to achieve cost-effective conversion of solar energy into electricity.     

CAE FOR THE MANUFACTURING ENGINEER: THE ROLE OF PROCESS SIMULATION IN CONCURRENT ENGINEERING

As America refocuses its attention on the factory, design and manufacturing engineers must work together closely to design the appropriate products, and matching production process in a team effort. By building off the designer's CAE tools that predict product performance, the manufacturing engineer is today able to simulate the proposed production process. Process simulations for the following manufacturing processes are available or being developed:

▪Forging, ▪Machining, ▪Injection Molding, ▪Die Casting, ▪Investment Casting, ▪Metal Forming, ▪Heat Treating, ▪Assembly Tolerancing

By utilizing the same 3-D solid model and finite element modeling tools used by the designer, coupled to powerful analysis simulation tools to predict the transient nonlinear heat transfer and plastic material flow found in many manufacturing processes, the manufacturing engineer is able to explore alternative processing plans, evaluate trade-offs and even influence the design to produce superior products.

Process simulation brings a science to support the manufacturing engineers experience for reduced lead time, lower cost, increase product quality and better understanding of the process. The next step will be to directly link the process simulation to an expert system.

This paper describes the current state of technology in the area of manufacturing process computer simulation for a number of manufacturing operations and suggests how these tools can be used “up-front” and lead to concurrent engineering.     

环保型纤维纺织品的生态性及染整加工(下)

上期提要:综述了罗布麻纤维、天然彩色棉花、甲壳素纤维、Lyocell纤维、聚乳酸纤维、大豆蛋白纤维等环保纤维纺织品的生态性和染整加工要点.     

Evaluation of the thiamine dose-response relationship for lake trout (Salvelinus namaycush) fry using an individual based model

Substantial natural reproduction of lake trout (Salvelinus namaycush) has not been achieved in the Great Lakes, except for Lake Superior and a few areas in Lake Huron, despite continued stocking efforts. Low thiamine levels in lake trout eggs, which can result in lethal and sublethal impacts (thiamine deficiency complex, TDC) on fry, may contribute to widespread recruitment failure in lake trout populations. We hypothesized that incorporation of sublethal impacts into dose-response curves would result in estimates of EC50s (median lethal concentrations) for fry greater than the estimates that rely only on acute mortality and that predation would exacerbate thiamine effects. To investigate the sublethal effects of TDC (prey capture success and predation mortality) on cohort growth and survival, we developed an individual-based model for lake trout fry. The model tracks daily activities, including consumption, respiration, growth, and mortality, of lake trout from hatch until fry reach a length of 33?mm when we assume fry feed naturally and thiamine effects are minimized. Model output with sublethal impacts resulted in an EC50 (7.3?nmol/g) that was greater than published studies that are limited to acute mortality (1.5?nmol/g). Furthermore, when we included interstitial and pelagic predation, the impact of sublethal effects shifted the EC50 values even higher (7.4–10?nmol/g). Simulation results indicate that low thiamine levels, in combination with moderate to high predation, can eliminate lake trout cohorts. Our simulations suggest that the sublethal effects of low thiamine can contribute to poor lake trout recruitment more than previously suspected.     

Balance between model detail and experimental information in steam methane reforming over a Ni/MgO-SiO2 catalyst

The optimization and full understanding of chemical reactions is aided by the construction of an adequate kinetic model. The development of such a kinetic model remains a challenging task. To tackle this challenge in the most efficient way, an iterative, systematic methodology, originally demonstrated for n-hexane hydroisomerization, is now extended aiming at finding the balance between the envisaged model detail and available information, often originating from time-consuming and expensive experiments. Steam methane reforming on the Ni/MgO-SiO₂ case study is used for this purpose, that is, the construction of a kinetic model that embeds a maximum amount of information contained in the dataset. The kinetic model is expanded stepwise from a power law model over a model with reactant adsorption toward a Langmuir–Hinshelwood–Hougen–Watson model. The performance of the initially underparameterized model improved significantly by adding reactant adsorption, yet including product adsorption led to overparameterization rather than enhanced model performance. © 2019 American Institute of Chemical Engineers AIChE J, 65: 1222–1233, 2019     

On Data Integration Problems With Manifolds

This article focuses on data integration problems where the predictor variables for some response variable partition into known subsets. This type of data is often referred to as multi-view data, and each subset of the predictors is called a data view. Accounting for data views can add practical value in terms of both interpretation and predictive performance. Many existing approaches for multi-view data rely on view-agreement principles, strong smoothness assumptions, or regularization penalties. The former approaches can be sensitive to modest noise in the response or predictor variables, while the latter approach is linear and can usually be out-performed. We develop semiparametric data integration methods to span key tradeoffs including the bias-variance tradeoff on prediction error, the possibility that the data may be fully viewed with no appreciable view relationships, and the use of sparse anchor point methods to detect and use manifolds (i.e., possibly nonelliptical structures) within views if they enhance performance. Theoretical results help justify the new technique, and its effectiveness and computational feasibility are demonstrated empirically. This new semiparametric methodology is available for public use through the supplemental R package mvltools. Additional supplementary material for this article is also available online.     

First-principles modeling for optimal design,operation, and integration of energy conversion and storage systems

Energy and electricity consumption is expected to increase in the foreseeable future. Concurrently, sustainability concerns of fossil-based energy resources have motivated the use of renewable and reusable energy resources, and the use of more efficient energy-converting and energy-consuming systems. Consequently, for the past decade, there have been major theoretical and experimental advances in (1) energy generation from renewable and reusable resources and (2) energy-consuming and energy-converting devices. This review article focuses on the recent theoretical advances in renewable energy conversion devices such as photovoltaic and fuel cells, and in energy storage devices such as rechargeable batteries, flow batteries, and supercapacitors. Due to similar chemistry, electrochemistry, and physics of these systems, modeling similarities between different energy systems are highlighted. This review puts into perspective how first-principles mathematical modeling has contributed to systematic advances in the optimal design, operation, and integration of these systems. © 2018 American Institute of Chemical Engineers AIChE J, 65: e16482 2019