Search results

Using a sample of 214 US metropolitan areas, we examine the connection between the Great Recession and bad jobs, taking into consideration the macro-level determinants of the troubled economy. Our measure of bad jobs is derived from Kalleberg, Reskin, and Hudson’s (2000) conceptualization as those that have low pay, lack health insurance, and lack pension plans. We find that the Great Recession increased the prevalence of bad jobs, consistently for men and selectively for women. Among the macro-level processes, the decline of the manufacturing base, union membership, and public sector employment are sources of increasing bad jobs, especially for men. Those macro-level processes which are growing in influence such as casualization, globalization and financialization show no signs of reversing the negative trends in bad jobs. Human capital variables in the labor market such as educational and age variability consistently suggest more adverse effects on bad jobs for men than women. Our findings contribute to the further understanding of the nature of precarious work in a troubled economy.

To review and synthesize findings from peer-reviewed research related to students’ sources of ideas for writing, and instructional dimensions that affect students’ development of ideas for composition in grades K-8.

The ideas or content expressed in written composition are considered critical to ratings of writing quality. We utilized a Systematic Mixed Studies Review (SMSR) methodological framework (Heyvaert, Maes, & Onghena, 2011) to explore K-8 students’ ideas and writing from a range of theoretical and methodological perspectives.

Students’ ideas for writing originate from a range of sources, including teachers, peers, literature, content area curriculum, autobiographical/life experiences, popular culture/media, drawing, and play. Intertextuality, copying, social dialogue, and playful peer interactions are productive strategies K-8 writers use to generate ideas for composing, in addition to strategies introduced through planned instruction. Relevant dimensions of instruction include motivation to write, idea planning and organization, as well as specific instructional strategies, techniques, and tools to facilitate idea generation and selection within the composition process.

A permeable curriculum and effective instructional practices are crucial to support students’ access to a full range of ideas and knowledge-based resources, and help them translate these into written composition. Instructional practices for idea development and writing: (a) connect reading and writing for authentic purposes; (b) include explicit modeling of strategies for planning and “online” generation of ideas throughout the writing process across genre; (c) align instructional focus across reading, writing, and other curricular activities; (d) allow for extended time to write; and (e) incorporate varied, flexible participation structures through which students can share ideas and receive teacher/peer feedback on writing.

The complexity of atmospheric corrosion, further compounded by the effects of climate change, makes existing models inappropriate for corrosion prediction. The commonly used kinetic model and dose-response functions are restricted in their capacity to represent the non-linear behaviour of corrosion phenomena. The application of artificial intelligence (AI)-driven machine learning algorithms to corrosion data can better represent the corrosion mechanism by considering the dynamic behaviour due to changing climatic conditions. Effective use of materials, coating systems and maintenance strategies can then be made with such a corrosivity model. Accurate corrosion prediction will help to improve climate change resilience of the social, economic and energy infrastructure in line with the UN Sustainable Development Goals (SDGs) 7 (Affordable and Clean Energy), 9 (Industry, Innovation and Infrastructure) and 13 (Climate Action). This chapter discusses atmospheric corrosion prediction in relation to the SDGs and the influence of AI in overcoming the challenges.

Colonies of Actynomyces israelii bacteria have been found in removed copper intra‐uterine devices (IUD) used as a long‐term contraceptive method. The purpose of this paper is to characterize the biofilm developed under anaerobic conditions by Actynomyces israelii on IUD surface, and its influence in the copper corrosion processes.

The dissolution of copper on the intra‐uterine cavity prevents conception because of the toxic effect of the ions released. Nevertheless, microbiological growths have been detected on the IUD devices retired after long periods of insertion. In order to know about the influence of the biofilm on the corrosion of copper, electrochemical, spectroscopic and surface analysis techniques were applied to study the phenomenon.

A porous Actynomyces israelii biofilm was formed on the copper IUD surface. The bacteria colony had developed in an exopolimeric substrate, which protects it from the toxic effect of copper ions. The corrosion process was not inhibited by the biofilm, due to the pores present which permit the transport of species through them.

The results of this study show that there is no decay in the contraceptive function of the IUDs due to the presence of a bacterial biofilm on its surface.

The relationship between microbial colonization and the corrosion process of copper IUD under anaerobic conditions was characterized. These results will complement previous investigations performed on the study of corrosion of copper IUDs under different conditions.

In this work, a kind of Mannich base (C₂₁H₂₅NO) was synthesized with cinnamal aldehyde, acetophenone and diethylamine in a condensing reflux device based on the conventional method. Optimization of the inhibitor concentration was explored.

Spectral properties of this compound was investigated by FTIR, and its inhibition efficiency and mechanism on N80 steel in 20% hydrochloric acid solution were studied by weight loss measurement, electrochemical measurement (potentiodynamic polarization and electrochemical impedance spectroscopy) and surface analytical measurement (scanning electron microscope with energy dispersive spectrometer).

The results showed that the new inhibitor reduced the double-layer capacitance and increased the charge transfer resistance. The inhibition efficiency is 99.7% when the concentration of C21H25NO is 3%. The adsorption of C₂₁H₂₅NO on N80 steel surface in 20% HCl solution was found to be spontaneous and steady. Observed from the steel surface, an inhibition film was confirmed to be presented after adding inhibitor and successfully hindered the corrosive ions from reaching the bulk steel.

A new Mannich base (C₂₁H₂₅NO) was synthesized by cinnamal aldehyde, acetophenone and diethylamine for the corrosion prevention of N80 steel in 20% hydrochloric acid solution.

The ever‐increasing demand for rationalization of manufacturing activities requires closer co‐operation and integration between design and production planning. Since the impact on the overall cost of production of designing a product for ease of assembly was realized, feedback from assembly planning to the design process has become important for improving the design. Traditionally, planning for assembly takes place after the design of the product has been completed. Often it proves necessary to modify a design, because some aspect is not particularly convenient or efficient under the available assembly facilities. However, considerable time and cost savings can be made by making assembly‐planning information available to design engineers, so that they can take account of assembly factors when designing a product.

The purpose of this paper is to develop an efficient hybrid method that can collectively address assembly sequence generation (ASG) and exploded view generation (EVG) problem effectively. ASG is an act of finding feasible collision free movement of components of a mechanical product in accordance with the assembly design. Although the execution of ASG is complex and time-consuming in calculation, it is highly essential for efficient manufacturing process. Because of numerous limitations of the ASG algorithms, a definite method is still unavailable in the computer-aided design (CAD) software, and therefore the explosion of the product is not found to be in accordance with any feasible disassembly sequence (disassembly sequence is reverse progression of assembly sequence). The existing EVG algorithms in the CAD software result in visualization of the entire constituent parts of the product over single screen without taking into consideration the feasible order of assembly operations; thus, it becomes necessary to formulate an algorithm which effectively solves ASG and EVG problem in conjugation. This requirement has also been documented as standard in the “General Information Concerning Patents: 1.84 Standards for drawings” in the United States Patent and Trademark office (2005) which states that the exploded view created for any product should show the relationship or order of assembly of various parts that are permissible.

In this paper, a unique ASG method has been proposed and is further extended for EVG. The ASG follows a deterministic approach to avoid redundant data collection and calculation. The proposed method is effectively applied on products which require such feasible paths of disassembly other than canonical directions.

The method is capable of organizing the assembly operations as linear or parallel progression of assembly such that the assembly task is completed in minimum number of stages. This result is further taken for EVG and is found to be proven effective.

Assembly sequence planning (ASP) is performed most of the times considering the geometric feasibility along canonical axes without considering parallel possibility of assembly operations. In this paper, the proposed method is robust to address this issue. Exploded view generation considering feasible ASP is also one of the novel approaches illustrated in this paper.

The deep learning-based recommender framework (DLRF) is based on an improved long short-term memory (LSTM) structure with additional controllers; thus, it considers contextual information for state transition. It also handles irregularities in the data to enhance performance in generating recommendations while modelling short-term preferences. An algorithm named a multi-preference integrated algorithm (MPIA) is proposed to have dynamic integration of both kinds of user preferences aforementioned. Extensive experiments are made using Amazon benchmark datasets, and the results are compared with many existing recommender systems (RSs).

RSs produce quality information filtering to the users based on their preferences. In the contemporary era, online RSs-based collaborative filtering (CF) techniques are widely used to model long-term preferences of users. With deep learning models, such as recurrent neural networks (RNNs), it became viable to model short-term preferences of users. In the existing RSs, there is a lack of dynamic integration of both long- and short-term preferences. In this paper, the authors proposed a DLRF for improving the state of the art in modelling short-term preferences and generating recommendations as well.

The results of the empirical study revealed that the MPIA outperforms existing algorithms in terms of performance measured using metrics such as area under the curve (AUC) and F1-score. The percentage of improvement in terms AUC is observed as 1.3, 2.8, 3 and 1.9% and in terms of F-1 score 0.98, 2.91, 2 and 2.01% on the datasets.

The algorithm uses attention-based approaches to integrate the preferences by incorporating contextual information.

The purpose of this paper is to draw up an atmospheric corrosion map for an industrial zone to determine the best coating system for each location.

The outdoor atmospheric corrosion rate was measured at eight locations distributed in an oil refinery during a year. Corrosion rates were measured by weight loss of carbon steel coupons, according to ISO Standard 9223. Weathering conditions, including temperature, time of wetness, and atmospheric pollution such as chloride precipitation and sulfur content also were measured. The results were analyzed using “Surfer 8” software and the corrosion map of the refinery was derived.

An atmospheric corrosion map was derived for the oil refinery. By this approach, coating system for equipment can be selected based exactly on where the plant item is located.

Exterior coating systems for equipment now can be selected based on their application, regardless of their position in any refinery. In this article, an atmospheric corrosion map was developed for a refinery for the first time. The position of equipment on the corrosion map is a new parameter that should be considered for coating system selection.

Purpose – To synthesize the literature on coping among adolescents of color in the U.S., we examine normative and circumstantial stressors, describe coping strategies, and summarize the literature on coping for the promotion of well-being among adolescents of color, including descriptive and intervention studies.

Methods/approach – We conducted an extensive review of the literature in four scientific databases (medline, CINAHL, ERIC, and PyschInfo) between July 2010 and June 2011 (key words: (minority) adolescent(s) (of color), cope/coping, stress (ors), and adaptation/psychological). Studies included in our review were peer-reviewed articles published between 2000 and June 2011 that presented original data on the coping strategies and outcomes of adolescents of color (e.g., studies including a majority from underrepresented racial/ethnic communities) between the ages of 12 and 18.

Findings – We identified a total of 91 articles for inclusion, including 83 descriptive and 8 intervention studies. We use a matrix approach to compare descriptive studies by their purpose, study design, sample, targeted stressors, and outcomes. We then discuss the eight interventions we identified, highlighting the targeted population, intervention protocol/adaptation, feasibility/acceptability, and study outcomes.

Implications – The breadth and depth of research on coping among adolescents of color has improved significantly over the past decade, yet our review reveals several areas where further exploration is needed, including research on intra-group differences, validation of coping measures in diverse groups, measurement of the effectiveness of coping strategies over time, and most importantly, the translation of available knowledge on effective coping into culturally relevant, multifaceted interventions for adolescents and their families.