Direct support and general support maintenance repair parts and special tools lists (including depot maintenance repair parts and special tools lists) : crusher, roll, diesel and electric driven, wheel mounted, pneumatic tires, 75 ton per hour, NSN 3820-00-788-5999, Eagle crusher model 5230B, NSN 3820-00-876-7876, Eagle crusher model 5230C and model 5230D, component ...

Includes index.

Unit, direct support, and general support maintenance repair parts and special tools lists : crusher, roll, diesel and electric driven, wheel mounted, pneumatic tires, 75 ton per hour, NSN 3820-00-788-5999, Eagle crusher model 5230B, NSN 3820-00-876-7876, Eagle crusher model 5230D and model 5230D, component of crushing and screening plant ....

"September 1991."

Unit, direct support, and general support maintenance repair parts and special tools lists : crusher, jaw, diesel and electric driven, wheel mounted, pneumatic tires, 75 ton per hour, NSN 3820-00-783-7311, Eagle crusher models, model 5157 ... component of crushing and screening plant ....

"September 1991."

Organization, direct support, and general support maintenance repair parts and special tools list : feeder, fines, bituminous mix, Army model 811A, NSN 3895-00-025-9932, barber-greene model 811A, component of mixing plant asphalt, 100-150 ton per hour.

Includes change no. 1 inserted at front.

Organizational maintenance repair parts and special tools lists : feeder, aggregate, chain driven, NSN 3895-00-515-4651, Barber-Greene model 815, component of mixing plant, asphalt 100-150 ton per hour, model KA-60, NSN 3895-00-936-8613.

Includes index.

Direct support and general support maintenance repair parts and special tools lists : feeder, aggregate, chain driven NSN 3895-00-515-4651, Barber-Greene model 815, component of mixing plant, asphalt 100-150 ton per hour, model KA-60 NSN 3895-00-936-8613.

Includes index.

Direct support and general support maintenance repair parts and special tools lists : dryer, aggregate, diesel engine driven, 4 wheel mtd., NSN 3895-00-236-8123, Barber-Greene MDL DA-60 : component of mixing plant asphalt, 100-150 ton per hour, NSN 3895-00-936-8613, Barber-Greene MDL KA-60.

Includes indexes.

Organizational maintenance repair parts and special tools lists : mixer, bituminous material, non-self loading, DED, NSN 3895-00-933-0577, Barber-Greene model KA60, component of mixing plant, asphalt, 100-150 ton per hour, NSN 3895-00-936-8613.

Includes index.

Direct support and general support maintenance repair parts and special tools lists (including depot maintenance repair parts and special tools lists) : mixer, bituminous material, non-self loading, DED, NSN 3895-00-933-0577, Barber-Greene model KA60, component of mixing plant, asphalt 100-150 ton per hour, NSN 3895-00-936-8613.

Includes index.

Unit, direct and general support maintenance repair parts and special tools lists : feeder, aggregate, chain driven, NSN 3895-00-515-4651, Barber-Greene model 815, component of mixing plant, asphalt, 100-150 ton per hour, model KA-60, NSN 3895-00-936-8613.

Includes indexes.

Organizational, direct and general support, and depot maintenance repair parts and special tools lists : motor generator, power supply generator, 60 kw, 120/208, 240/416 volt, 3-phase, 4 wire service, 400 hertz, DC component output, 28 volt, 10 amp, motor input AC, 416 volt, 3-phase, 60 hertz, portable skid mounted (General Dynamics Corp. model 14105008), FSN 6125-917-2244.

"November 1970."

Intuition and its component parts in the heuristic processing of deception detection: Hunch, *evidence, and reliance on intuitive efficacy

Rated trust in intuitive efficacy (measured as trust, belief, use, accuracy and weighting of intuition) was investigated as a predictor of self-designated use of intuitive (hunch and hunch plus evidential belief) vs. deliberative (evidential belief and evidential belief plus hunch) deception detection judgments and actual accuracy. Twenty-nine student participants were filmed as they made true and deceptive statements about their everyday activities on a given evening (last Friday night), and college students (N=238) judged 20 (10=true, 10=deceptive) of these filmed statements as truthful or deceptive. Participants provided ratings of reliance on hunches vs. evidential belief, confidence in film judgments, intuitive efficacy, accuracy in deception detection, reliance on cues to deception, and experiences with intuition. Generalized estimated equation modeling using binary logistics demonstrated accuracy in identifying true vs. deceptive statements was predicted by film number, hunch-evidence ratings, weighting of intuition, and total cues cited. Weighting of intuition was predictive of accuracy across participants, with higher weighting predictive of higher accuracy in general. Participants who cited evidential belief plus hunch and moderate to high weighting incorrectly reversed their true vs. deceptive judgments. Accuracy for true statements was higher for hunches and hunch plus evidential belief, whereas accuracy for deceptive statements was higher for evidential belief Accuracy for participants who relied on evidential belief plus hunch was at chance. Subjective experiences underlying judgments differed by participant and type of film viewed (true vs. deceptive) and were predicted by hunch-evidence ratings, trust, use, intuitive accuracy, and total cues cited. Trust predicted increases in judging films to be true, whereas use and accuracy predicted increases in judging films as deceptive; none were predictive of accuracy. Increased number of cues cited predicted judgments of deception, whereas decreased number of cues cited predicted truth. The study concluded that participants have the capacity to self-define their judgments as subjectively vs. deliberately based, provide subjective assessments of the influence of intuitive vs. objective information on their judgments, and can apply this self-knowledge, through effective weighting of intuition vs. other types of information, in making accurate judgments of true and deceptive everyday statements.

Multiple socioeconomic circumstances and health : associations and explanations among Finnish and British public sector employees

Socioeconomic health inequalities have been widely documented, with a lower social position being associated with poorer physical and general health and higher mortality. For mental health the results have been more varied. However, the mechanisms by which the various dimensions of socioeconomic circumstances are associated with different domains of health are not yet fully understood. This is related to a lack of studies tackling the interrelations and pathways between multiple dimensions of socioeconomic circumstances and domains of health. In particular, evidence from comparative studies of populations from different national contexts that consider the complexity of the causes of socioeconomic health inequalities is needed. The aim of this study was to examine the associations of multiple socioeconomic circumstances with physical and mental health, more specifically physical functioning and common mental disorders. This was done in a comparative setting of two cohorts of white-collar public sector employees, one from Finland and one from Britain. The study also sought to find explanations for the observed associations between economic difficulties and health by analysing the contribution of health behaviours, living arrangements and work-family conflicts. The survey data were derived from the Finnish Helsinki Health Study baseline surveys in 2000-2002 among the City of Helsinki employees aged 40-60 years, and from the fifth phase of the London-based Whitehall II study (1997-9) which is a prospective study of civil servants aged 35-55 years at the time of recruitment. The data collection in the two countries was harmonised to safeguard maximal comparability. Physical functioning was measured with the Short Form (SF-36) physical component summary and common mental disorders with the General Health Questionnaire (GHQ-12). Socioeconomic circumstances were parental education, childhood economic difficulties, own education, occupational class, household income, housing tenure, and current economic difficulties. Further explanatory factors were health behaviours, living arrangements and work-family conflicts. The main statistical method used was logistic regression analysis. Analyses were conducted separately for the two sexes and two cohorts. Childhood and current economic difficulties were associated with poorer physical functioning and common mental disorders generally in both cohorts and sexes. Conventional dimensions of socioeconomic circumstances i.e. education, occupational class and income were associated with physical functioning and mediated each other’s effects, but in different ways in the two cohorts: education was more important in Helsinki and occupational class in London. The associations of economic difficulties with health were partly explained by work-family conflicts and other socioeconomic circumstances in both cohorts and sexes. In conclusion, this study on two country-specific cohorts confirms that different dimensions of socioeconomic circumstances are related but not interchangeable. They are also somewhat differently associated with physical and mental domains of health. In addition to conventionally measured dimensions of past and present socioeconomic circumstances, economic difficulties should be taken into account in studies and attempts to reduce health inequalities. Further explanatory factors, particularly conflicts between work and family, should also be considered when aiming to reduce inequalities and maintain the health of employees.

Analysis of functional networks involved in motor execution and motor imagery using combined hierarchical clustering analysis and independent component analysis

Cognitive experiments involving motor execution (ME) and motor imagery (MI) have been intensively studied using functional magnetic resonance imaging (fMRI). However, the functional networks of a multitask paradigm which include ME and MI were not widely explored. In this article, we aimed to investigate the functional networks involved in MI and ME using a method combining the hierarchical clustering analysis (HCA) and the independent component analysis (ICA). Ten right-handed subjects were recruited to participate a multitask experiment with conditions such as visual cue, MI, ME and rest. The results showed that four activation clusters were found including parts of the visual network, ME network, the MI network and parts of the resting state network. Furthermore, the integration among these functional networks was also revealed. The findings further demonstrated that the combined HCA with ICA approach was an effective method to analyze the fMRI data of multitasks.

Knowledge spillover in Indian automobile industry : the process and the coverage

In India, as the production of passenger cars increased, many local small and medium enterprises (SMEs) entered the parts and components manufacturing sector. The sources of knowledge for large enterprises and SMEs are different. Naturally, spillover effects among large enterprises and between large enterprises and SMEs are different. This paper focuses on knowledge spillover among large enterprises and from large enterprises to SMEs. Subcontractor can absorb relation-specific skills through repeated interaction with parent company. The results of field survey emphasizes that relation-specific skills are a determinant factor of spillover effects from assemblers and large auto component manufacturers to SMEs. Econometric analysis shows that spillover effects among medium and large automobile units and from medium and large automobile units to small units went beyond boundary of cluster.