937 resultados para additive variance


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Additive Fertigungsverfahren eignen sich für die wirtschaftliche Herstellung von Bauteilen im Bereich kleiner bis mittlerer Stückzahlen, da keine Formen oder Spezialwerkzeuge notwendig sind. Die erzielbaren Eigenschaften sind oftmals bereits ausreichend, um einen Einsatz auch in Serienanwendungen zu ermöglichen. Verbunden mit den Vorteilen der Technologie bezüglich einer hohen Flexibilität, sowohl während der Konstruktion als auch der Fertigung, können sich durch eine konsequente Nutzung finanzielle Einsparmöglichkeiten entlang des gesamten Produktlebenszyklus ergeben. Bezüglich der Wirtschaftlichkeit der Verfahren herrscht oftmals noch Unklarheit, da geeignete Methoden fehlen, um diese zu bewerten. Bestehende Methoden und Werkzeuge zur Bewertung der Wirtschaftlichkeit konventioneller Fertigungsverfahren sind dabei für die additive Fertigung nicht direkt nutzbar. In dem Artikel wird eine Methode zur modellgestützten Abbildung einer gesamten additiven Fertigungskette vorgestellt, welche auch die Wechselwirkungen zwischen den einzelnen Prozesskettengliedern berücksichtigen soll. Eine konkrete Aussage bezüglich der Wirtschaftlichkeit der additiven Fertigung soll somit ermöglicht werden.

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Da sich Additive Manufacturing (AM) von traditionellen Produktionsverfahren unterscheidet, entstehen neue Möglichkeiten im Produktdesign und im Supply Chain Setup. Die Auswirkungen der Aufhebung traditionellen Restriktionen im Produktdesign werden unter dem Begriff „Design for Additive Manufacturing“ intensiv diskutiert. In gleicher Weise werden durch AM Restriktionen im traditionellen Supply Chain Setup aufgehoben. Insbesondere sind die folgenden Verbesserungen möglich: Reduktion von Losgrössen und Lieferzeiten, bedarfsgerechte Produktion auf Abruf, dezentrale Produktion, Customization auf Ebene Bauteil und kontinuierliche Weiterentwicklung von Bauteilen. Viele Firmen investieren nicht selbst in die AM Technologien, sondern kaufen Bauteile bei Lieferanten. Um das Potential der AM Supply Chain mit Lieferanten umzusetzen, entstehen die folgenden Anforderungen an AM Einkaufsprozesse. Erstens muss der Aufwand pro Bestellung reduziert werden. Zweitens brauchen AM Nutzer einen direkten Zugang zu den Lieferanten ohne Umweg über die Einkaufsabteilung. Drittens müssen geeignete AM Lieferanten einfach identifiziert werden können. Viertens muss der Wechsel von Lieferanten mit möglichst geringem Aufwand möglich sein. Ein mögliche Lösung sind AM spezifische E-Procurement System um diese Anforderungen zu erfüllen

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Three-hundred-forty-eight newly weaned beef calves were used in duplicate 28-day experiments to evaluate GAINPRO®, Aureomycin, or no feed additive. Diets fed were formulated to provide 14.5% crude protein (CP) and .48 megacalorie per pound net energy (Mcal/lb. NEg) . Aureomycin reduced (P < .05) average daily gain (ADG) for the first 14 days compared to GAINPRO® or no feed additive. This effect disappeared by 28 days on feed, and ADG favored (P < .05) Aureomycin-supplemented calves compared to those given no feed additives. Calves receiving GAINPRO® fell between the two treatments for 28-day ADG.

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OBJECTIVES It is well known that Sn(2+) is a notable anti-erosive agent. There are indications that biopolymers such as chitosan can enhance the effect of Sn(2+), at least in vitro. However, little information exists about their anti-erosive/anti-abrasive in situ effects. In the present in situ study, the efficacy of Sn(2+)-containing toothpastes in the presence or absence of chitosan was tested. METHODS Ten subjects participated in the randomised crossover study, wearing mandibular appliances with human enamel specimens. Specimens were extraorally demineralised (7 days, 0.5 % citric acid, pH 2.6; 6 × 2 min/day) and intraorally exposed to toothpaste suspensions (2 × 2 min/day). Within the suspension immersion time, one half of the specimens were additionally brushed intraorally with a powered toothbrush (5 s, 2.5 N). Tested preparations were a placebo toothpaste (negative control), two experimental toothpastes (F/Sn = 1,400 ppm F(-), 3,500 ppm Sn(2+); F/Sn/chitosan = 1,400 ppm F(-), 3,500 ppm Sn(2+), 0.5 % chitosan) and an SnF2-containing gel (positive control, GelKam = 3,000 ppm Sn(2+), 1,000 ppm F(-)). Substance loss was quantified profilometrically (μm). RESULTS In the placebo group, tissue loss was 11.2 ± 4.6 (immersion in suspension) and 17.7 ± 4.7 (immersion in suspension + brushing). Immersion in each Sn(2+)-containing suspension significantly reduced tissue loss (p ≤ 0.01); after immersion in suspension + brushing, only the treatments with GelKam (5.4 ± 5.5) and with F/Sn/chitosan (9.6 ± 5.6) significantly reduced loss [both p ≤ 0.05 compared to placebo; F/Sn 12.8 ± 6.4 (not significant)] CONCLUSION Chitosan enhanced the efficacy of the Sn(2+)-containing toothpaste as an anti-erosive/anti-abrasive agent. CLINICAL RELEVANCE The use of Sn(2+)- and chitosan-containing toothpaste is a good option for symptomatic therapy in patients with regular acid impacts.

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Identifying and comparing different steady states is an important task for clinical decision making. Data from unequal sources, comprising diverse patient status information, have to be interpreted. In order to compare results an expressive representation is the key. In this contribution we suggest a criterion to calculate a context-sensitive value based on variance analysis and discuss its advantages and limitations referring to a clinical data example obtained during anesthesia. Different drug plasma target levels of the anesthetic propofol were preset to reach and maintain clinically desirable steady state conditions with target controlled infusion (TCI). At the same time systolic blood pressure was monitored, depth of anesthesia was recorded using the bispectral index (BIS) and propofol plasma concentrations were determined in venous blood samples. The presented analysis of variance (ANOVA) is used to quantify how accurately steady states can be monitored and compared using the three methods of measurement.

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Coat color and pattern variations in domestic animals are frequently inherited as simple monogenic traits, but a number are known to have a complex genetic basis. While the analysis of complex trait data remains a challenge in all species, we can use the reduced haplotypic diversity in domestic animal populations to gain insight into the genomic interactions underlying complex phenotypes. White face and leg markings are examples of complex traits in horses where little is known of the underlying genetics. In this study, Franches-Montagnes (FM) horses were scored for the occurrence of white facial and leg markings using a standardized scoring system. A genome-wide association study (GWAS) was performed for several white patterning traits in 1,077 FM horses. Seven quantitative trait loci (QTL) affecting the white marking score with p-values p≤10(-4) were identified. Three loci, MC1R and the known white spotting genes, KIT and MITF, were identified as the major loci underlying the extent of white patterning in this breed. Together, the seven loci explain 54% of the genetic variance in total white marking score, while MITF and KIT alone account for 26%. Although MITF and KIT are the major loci controlling white patterning, their influence varies according to the basic coat color of the horse and the specific body location of the white patterning. Fine mapping across the MITF and KIT loci was used to characterize haplotypes present. Phylogenetic relationships among haplotypes were calculated to assess their selective and evolutionary influences on the extent of white patterning. This novel approach shows that KIT and MITF act in an additive manner and that accumulating mutations at these loci progressively increase the extent of white markings.

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Localized Magnetic Resonance Spectroscopy (MRS) is in widespread use for clinical brain research. Standard acquisition sequences to obtain one-dimensional spectra suffer from substantial overlap of spectral contributions from many metabolites. Therefore, specially tuned editing sequences or two-dimensional acquisition schemes are applied to extend the information content. Tuning specific acquisition parameters allows to make the sequences more efficient or more specific for certain target metabolites. Cramér-Rao bounds have been used in other fields for optimization of experiments and are now shown to be very useful as design criteria for localized MRS sequence optimization. The principle is illustrated for one- and two-dimensional MRS, in particular the 2D separation experiment, where the usual restriction to equidistant echo time spacings and equal acquisition times per echo time can be abolished. Particular emphasis is placed on optimizing experiments for quantification of GABA and glutamate. The basic principles are verified by Monte Carlo simulations and in vivo for repeated acquisitions of generalized two-dimensional separation brain spectra obtained from healthy subjects and expanded by bootstrapping for better definition of the quantification uncertainties.

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Previous research suggests that the personality of a relationship partner predicts not only the individual’s own satisfaction with the relationship but also the partner’s satisfaction. Based on the actor–partner interdependence model, the present research tested whether actor and partner effects of personality are biased when the same method (e.g., self-report) is used for the assessment of personality and relationship satisfaction and, consequently, shared method variance is not controlled for. Data came from 186 couples, of whom both partners provided self- and partner reports on the Big Five personality traits. Depending on the research design, actor effects were larger than partner effects (when using only self-reports), smaller than partner effects (when using only partner reports), or of about the same size as partner effects (when using self- and partner reports). The findings attest to the importance of controlling for shared method variance in dyadic data analysis.

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Distinguishing between physical and social aggression, this study examined whether the predictive effect of aggression on resource control a) is moderated by prosocial behavior and b) corresponds to a linear or a curvilinear trend. Moderating effects of children’s social preference among peers and child sex in this context were also tested. Based on a sample of 682 kindergarten children (348 girls; average age 72.7 months, 3.6 SD), multilevel regressions revealed additive linear effects of social preference and prosociality on resource control. Moderate (but not high) levels of social aggression also facilitated resource control for disliked children. There was no such threshold effect for well liked children, who increasingly controlled the resource the more socially aggressive they were. In contrast, physical aggression hampered resource control unless used very modestly. The present study has a number of positive features. First, the distinction between physical and social aggression improves our understanding of the relation between aggression and social competence and sketches a more differentiated picture of the role of different forms of aggression in resource control. Second, this study combines the concept of resource control with the concept of social preference and investigates curvilinear effects of aggression. Third, the direct observation of resource control in the Movie Viewer increases the internal validity of this study.

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Stata is a general purpose software package that has become popular among various disciplines such as epidemiology, economics, or social sciences. Users like Stata for its scientific approach, its robustness and reliability, and the ease with which its functionality can be extended by user written programs. In this talk I will first give a brief overview of the functionality of Stata and then discuss two specific features: survey estimation and predictive margins/marginal effects. Most surveys are based on complex samples that contain multiple sampling stages, are stratified or clustered, and feature unequal selection probabilities. Standard estimators can produce misleading results in such samples unless the peculiarities of the sampling plan are taken into account. Stata offers survey statistics for complex samples for a wide variety of estimators and supports several variance estimation procedures such as linearization, jackknife, and balanced repeated replication (see Kreuter and Valliant, 2007, Stata Journal 7: 1-21). In the talk I will illustrate these features using applied examples and I will also show how user written commands can be adapted to support complex samples. Complex can also be the models we fit to our data, making it difficult to interpret them, especially in case of nonlinear or non-additive models (Mood, 2010, European Sociological Review 26: 67-82). Stata provides a number of highly useful commands to make results of such models accessible by computing and displaying predictive margins and marginal effects. In my talk I will discuss these commands provide various examples demonstrating their use.

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The Health Belief Model (HBM) provided the theoretical framework for examining Universal Precautions (UP) compliance factors by Emergency Department nurses. A random sample of Emergency Nurses Association (ENA) clinical nurses (n = 900) from five states (New York, New Jersey, California, Texas, and Florida), were surveyed to explore the factors related to their decision to comply with UP. Five-hundred-ninety-eight (598) useable questionnaires were analyzed. The responders were primarily female (84.9%), hospital based (94.6%), staff nurses (66.6%) who had a mean 8.5 years of emergency nursing experience. The nurses represented all levels of hospitals from rural (4.5%) to urban trauma centers (23.7%). The mean UP training hours was 3.0 (range 0-38 hours). Linear regression was used to analyze the four hypotheses. The first hypothesis evaluating perceived susceptibility and seriousness with reported UP use was not significant (p = $>$.05). Hypothesis 2 tested perceived benefits with internal and external barriers. Both perceived benefits and internal barriers as well as the overall regression were significant (F = 26.03, p = $<$0.001). Hypothesis 3 which tested modifying factors, cues to action, select demographic variables, and the main effects of the HBM with self reported UP compliance, was also significant (F = 12.39, p = $<$0.001). The additive effects were tested by use of a stepwise regression that assessed the contribution of each of the significant variables. The regression was significant (F = 12.39, p = $<$0.001) and explained 18% of the total variance. In descending order of contribution, the significant variables related to compliance were: internal barriers (t = $-$6.267; p = $<$0.001) such as the perception that because of the nature of the emergency care environment there is sometimes inadequate time to put on UP; cues to action (t = 3.195; p = 0.001) such as posted reminder signs or verbal reminders from peers; the number of Universal Precautions training hours (t = 3.667; p = $<$0.001) meaning that as the number of training hours increase so does compliance; perceived benefits (t = 3.466; p = 0.001) such as believing that UP will provide adequate barrier protection; and perceived susceptibility (t = 2.880; p = 0.004) such as feeling that they are at risk of exposure. ^

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The recurrent interaction among orientation-selective neurons in the primary visual cortex (V1) is suited to enhance contours in a noisy visual scene. Motion is known to have a strong pop-up effect in perceiving contours, but how motion-sensitive neurons in V1 support contour detection remains vastly elusive. Here we suggest how the various types of motion-sensitive neurons observed in V1 should be wired together in a micro-circuitry to optimally extract contours in the visual scene. Motion-sensitive neurons can be selective about the direction of motion occurring at some spot or respond equally to all directions (pandirectional). We show that, in the light of figure-ground segregation, direction-selective motion neurons should additively modulate the corresponding orientation-selective neurons with preferred orientation orthogonal to the motion direction. In turn, to maximally enhance contours, pandirectional motion neurons should multiplicatively modulate all orientation-selective neurons with co-localized receptive fields. This multiplicative modulation amplifies the local V1-circuitry among co-aligned orientation-selective neurons for detecting elongated contours. We suggest that the additive modulation by direction-specific motion neurons is achieved through synaptic projections to the somatic region, and the multiplicative modulation by pandirectional motion neurons through projections to the apical region of orientation-specific pyramidal neurons. For the purpose of contour detection, the V1-intrinsic integration of motion information is advantageous over a downstream integration as it exploits the recurrent V1-circuitry designed for that task.