Characteristics of low-level smokers.

Average daily cigarette consumption has decreased, and some evidence suggests that the rate of "some day" smoking has increased; however, relatively little is known about low-level smokers. The present analysis describes and compares low-level versus heavier smokers, using cross-sectional and longitudinal data. Data from the Community Intervention Trial for Smoking Cessation (COMMIT) were used in this analysis. Population-based cross-sectional tobacco use telephone surveys were performed in 22 North American communities in 1988 and 1993, and the prevalence and characteristics of low-level smoking and reasons for quitting are reported from the 1993 prevalence survey. In addition, a cohort of 6,603 smokers was identified in 1988 and interviewed again in 1993 and 2001 to assess patterns of low-level smoking over time and its association with smoking cessation. In 1988, 7.6% were low-level smokers; in 1993, 10.7% were low-level smokers. Compared with heavier smokers, low-level smokers were more likely to be female, older, not married, Black or Hispanic; to have a 4-year college degree; to have no other adult smokers in the household; and to wait longer in the day to have their first cigarette. Low-level smokers also were less likely to report trying to quit because of the expense of smoking or physician advice to quit. They were more likely to try to quit because of trying to set a good example; concern for second-hand smoke; and factors such as bad breath, smell, or the taste of smoking. Those who smoked full-priced premium brands and who worked in a completely smoke-free worksite were more likely to be low-level smokers. Compared with heavier smokers, low-level smokers had similar rates of making a future quit attempt, lower use rates of nicotine replacement therapy, and higher cessation rates. Low-level smokers may be a growing segment of the smoker population and have different characteristics, health risks, and intervention needs compared with their heavier smoking counterparts.     

Weld defect formation in FSWed coppers

This work was undertaken to explore the formation of weld defects in FSWed copper metals via both numerical and experimental approaches. The 4 mm-thick copper sheets were friction stir welded at a tool rotational speed of 710 rpm and tool translational speed of 40 mm/min. Microstructural evaluations were performed on the welded specimens. Also a 3D arbitrary Lagrangian Eulerian numerical model was developed to obtain temperature and material velocity profiles. To this aim, DEFORM-3D was implemented for developing the numerical simulation. Numerical results for temperature values showed good agreement with the recorded experimental data. They also suggest that on the advancing side (AS) of the trailing side, the pin velocity has the minimum amount (zero), and this is the main reason for the formation of tunneling cavity. Experimental results show that a force is created between the reminder of material at the joint and the rim of AS. This force causes a prong of surface material from the AS rim to penetrate into lower parts of weld. It seems that the inadequate pressure (low values of the plunge depth), inadequate surface materials, and the trapped air are the main causes for the formation of the weld defects.     

Performance of advanced color difference and CAM02‐based formulas in prediction of the Crispening effect for reflective samples

The Crispening effect is defined as an increase in the perceived color difference of the two stimuli, when their color (chromaticity or luminance) is close to the background on which the two stimuli are compared. In this study, the amount of the Crispening effect for three achromatic backgrounds and also the performance of six different color difference formulas (CDFs) for prediction of this effect have been investigated, by preparing 85 sample pairs in 9 CIE's recommended color centers. Regarding the results, the maximum (50%) and the minimum (4%) amount of the Crispening effect belong to the gray and the purple centers, respectively. According to the results of a comparative test, the Crispening intensifies when two stimuli have just lightness difference instead of just chromaticity difference. The highest variation was for the gray samples, in which the amount of the Crispening effect increased from 35% to 65%. By using PF/3 and STRESS index, it is also concluded that CMC and CIEDE2000 perform better than CAM02‐SCD and CAM02‐UCS in prediction of the Crispening effect on the dark gray and gray backgrounds. According to the results, the significant differences between the performances of the CDFs disappear when the luminance of the background increases. Huang's power functions also do not improve these results significantly. Furthermore, the results indicate that the traditional L* equation used in CIELAB performs similar to the Whittle's formula in prediction of the Crispening effect for reflective samples, and no significant difference was obtained.     

Multiscale modeling of elastic properties of cortical bone

We model cortical bone as a composite material with hierarchical structure. At a nanostructural level, bone is composed of cross-linked collagen molecules, containing water and non-collagenous proteins in their gaps, reinforced with hydroxyapatite-like nanocrystals. Such a nanocomposite structure represents a mineralized collagen fibril, which serves as a primary building block of bone. At a sub-microstructural level (few microns), the mineralized collagen fibrils are embedded in an extrafibrillar hydroxyapatite matrix to form a single lamella, which also contains the lacunar cavities. At a microstructural level (hundreds of microns) one can distinguish two lamellar structures in the mature cortical bone: osteons, made of concentric layers of lamellae surrounding long hollow Haversian canals, and interstitial lamellae made of remnants of old osteons. At a mesostructural level (several millimeters), the cortical bone is represented by a random collection of osteons and resorption cavities in the interstitial lamellae. A macrostructural level is the whole bone level containing both the cortical (compact) and trabecular (spongy) bone types. In this paper, we predict analytically the effective elastic constants of cortical bone by modeling its elastic response at these different scales, spanning from the nanostructural to mesostructural levels, using micromechanics methods and composite materials laminate theories. The results obtained at a lower scale serve as inputs for the modeling at a higher scale. The predictions are in good agreement with the experimental data reported in literature.     

Designing and planning a multi-echelon multi-period multi-product closed-loop supply chain utilizing genetic algorithm

Designing and planning a closed-loop supply chain in a comprehensive structure is vital for its applicability. To cope with the design and planning issue of a comprehensive closed-loop supply chain network, this paper develops an extended model, which is multi-echelon, multi-product, and multi-period in a mixed integer linear programming framework. The word “comprehensive,” in our mathematical approach, in designing and planning a closed-loop supply chain problem, can be analyzed from two complementary angles: including all possible entities (facilities) of a real condition and considering minimum limitations on possible flows between entities. In our proposed model, customers can be supplied via manufacturers, warehouses, and distributors, as an example. The proposed model is solved by CPLEX optimization software and by a developed genetic algorithm. During this computational analysis, we compare results of proposed pretuned genetic algorithm with a global optimum of CPLEX solver. Then, a sufficient number of large-size instances are generated and solved by the proposed genetic algorithm. To the best of our knowledge, there has been no similar multi-period multi-product closed-loop supply chain design and planning problem utilizing any kind of meta-heuristics let alone genetic algorithms. Therefore, in this issue, it is an original research, and results prove the acceptable performances of the developed genetic algorithm.     

Hybrid cascode compensation with feedforward stage for high-speed area-efficient three-stage CMOS amplifiers

Hybrid cascode feedforward compensation (HCFC) is proposed for low-power area-efficient three stage amplifiers driving large capacitive loads. With no overhead in power or area, the total compensation capacitor is divided and shared between two internal high-speed loops instead of solely one loop as is common in prior art. Detailed analysis of HCFC shows significant improvement in terms of stability and bandwidth. This is verified for a 1.2-V amplifier driving a 500-pF capacitive load in 90-nm CMOS technology, where HCFC reduces the total capacitor size and improves the gain-bandwidth by at least 30 and 40 %, respectively, compared to the prevailing schemes.     

Design of a neuro-fuzzy–regression expert system to estimate cost in a flexible jobshop automated manufacturing system

We propose a cost estimation model based on a fuzzy rule backpropagation network, configuring the rules to estimate the cost under uncertainty. A multiple linear regression analysis is applied to analyze the rules and identify the effective rules for cost estimation. Then, using a dynamic programming approach, we determine the optimal path of the manufacturing network. Finally, an application of this model is illustrated through a numerical example showing the effectiveness of the proposed model for solving the cost estimation problem under uncertainty.     

Mathematical programming approach to optimize material flow in an AGV-based flexible jobshop manufacturing system with performance analysis

An automated manufacturing system (AMS) is a complex network of processing, inspecting, and buffering nodes connected by system of transportation mechanisms. For an AMS, it is desirable to be capable to increase or decrease the output with the rise and fall of demand. Such specifications show the complexity of decision making in the field of AMSs and the need for concise and accurate modeling methods. Therefore, in this paper, a flexible jobshop automated manufacturing system is proposed to optimize the material flow. The flexibility is on the multi-shops of the same type and also multiple products that can be produced. An automated guided vehicle is applied for material handling. The objective is to optimize the material flow regarding the demand fluctuations and machine specifications. An illustrative example is presented to test the validity of the proposed mathematical model.     

Recent Approaches in the Development of Encapsulated Delivery Systems for Probiotics

The concept of probiotics has been well-known for more than a century. The availability and survival of the consumed probiotics in the colon has not been proved convincingly and needs further studies and clarification. It was not known whether the fastidious probiotics could reach the targeted site of action due to gastrointestinal stress. However, probiotics must sustain themselves in high number, survive during passage through the stomach to the intestine, and react symbiotically with the host when they reach the colon. This review consolidates some of the recent findings and new strategies on the development of a delivery system for targeted colonic delivery of probiotics.