Friction characteristics of 20 x 4.4, type 7, aircraft tires constructed with different tread rubber compounds

A test program was conducted at the Langley aircraft landing loads and traction facility to evaluate the friction characteristics of 20 x 4.4, type, aircraft tires constructed with experimental cut-resistant, tread rubber compounds. These compounds consisted of different blends of natural rubber (NR) and an alfin catalyzed styrene-butadiene copolymer rubber (SBR). One tire having a blend of 30 SBR and 70 NR and another having a blend of 60 SBR and 40 NR in the tread were tested together with a standard production tire with no SBR content in the tread rubber. The results of this investigation indicated that the test tires constructed with the special cut-resistant tread rubber compositions did not suffer any significant degradation in tire friction capability when compared with the standard tire. In general, tire friction capability decreased with increasing speed and surface wetness condition. As yaw angle increased, tire braking capability decreased while tire cornering capability increased. Tread-wear data based on number of brake cycles, however, suggested that the tires with alfin SBR blends experienced significantly greater wear than the standard production tire

Traction Characteristics of a 30 by 11.5-14.5, Type 8, Aircraft Tire on Dry, Wet and Flooded Surfaces

A limited test program was conducted to extend and supplement the braking and cornering data on a 30 x 11.5-14.5, type VIII, aircraft tire to refine the tire/runway friction model for use in the development of an aircraft ground performance simulation. Tire traction data were obtained on dry, wet and flooded runway surfaces at ground speeds ranging from 5 to 100 knots and at yaw angles extending up to 12 deg. These friction coefficients are presented as a function of slip characteristics, namely, the maximum and skidding drag coefficients and the maximum cornering coefficients are presented as a function of both ground speed and yaw angle to extend existing data on that tire size. Tire braking and cornering capabilities were shown to be affected by vehicle ground speed, wheel yaw attitude and the extent of surface wetness

The Precision Self-Metering Structure (PSMS)

Large, precise space systems such as space lasers, space telescopes, and space power transmitters cannot be realized until certain fundamental meteorological problems are first solved. It must be shown: (1) how a spatially distributed system of elements can be tied together in terms of a master coordinate system, (2) how master coordinates for these distributed elements can be determined with great accuracy, and (3) how mechanical integration of the elements to desired master coordinates of such accuracy can be achieved. Solutions to these problems are discussed

Arctic Centre: Rovaniemi, Finland

The Arctic Centre, developed in response to the City of Rovaniemi\u27s issuance of an ideas competition, is a complex incorporating two facilities: the Arctic Museum and the Lapland Provincial Museum

Ordered Weighted Average Based Fuzzy Rough Sets

Traditionally, membership to the fuzzy-rough lower, resp. upper approximation is determined by looking only at the worst, resp. best performing object. Consequently, when applied to data analysis problems, these approximations are sensitive to noisy and/or outlying samples. In this paper, we advocate a mitigated approach, in which membership to the lower and upper approximation is determined by means of an aggregation process using ordered weighted average operators. In comparison to the previously introduced vaguely quantified rough set model, which is based on a similar rationale, our proposal has the advantage that the approximations are monotonous w.r.t. the used fuzzy indiscernibility relation. Initial experiments involving a feature selection application confirm the potential of the OWA-based model

Body dissatisfaction, excessive exercise, and weight change strategies used by first-year undergraduate students: Comparing health and physical education and other education students

Summary Statistics for Logistic Regression Analyses Examining Dieting, Weight Change, and Disordered Eating Behaviours for Females, Controlling for Age and BMI. (DOC 95 kb

AI-Driven Analysis of Diagnostic Profiles in COVID-19 Patients: Implications for Healthcare Interventions

The COVID-19 crisis has strained global healthcare systems, highlighting the significance of investigating comorbidities and secondary diagnoses in patients. Harnessing of data-driven insights, as facilitated by artificial intelligence (AI), has shown remarkable promise in enhancing the efficacy of healthcare strategies and ameliorating patient outcomes. PURPOSE: To identify diagnostic profiles in COVID-19 patients via AI-driven analysis, focusing on comorbidities and secondary diagnoses. METHODS: The analytical groundwork was established upon the scrutiny of 42,974 patients with PCR-confirmed COVID-19 diagnosis. Each record was characterized by 850 diagnostic indicators encompassing a spectrum of ailments, such as demyelinated diseases, seizure disorders, and various additional comorbidities. The predominant racial composition of the sample was White (n = 31,329, 73%). A majority of patients were of the female gender (n = 23,534, 55%). Data were collected using Electronic Medical Records through the Cerner system from 31 hospitals in a large health system. Finite mixture modeling, a form of model-based unsupervised machine learning, was employed to ascertain the presence of latent, distinguishable patterns among secondary diagnoses. Of the approximately 850 secondary diagnoses considered, 221 exhibited prevalence in over 50 patients. A sequence of mixture models was estimated, incrementally augmenting the number of latent profiles via maximum likelihood estimation with robust standard errors. Model solutions were subjected to rigorous evaluation, culminating in the selection of three diagnostic profiles predicated on statistical model-data fit, parsimony, and interpretability. RESULTS: The selected model revealed the presence of three distinct diagnostic profiles. These profiles were characterized by patients who: (1) exhibited a notably low likelihood of presenting with secondary diagnoses, (2) demonstrated heightened probabilities of manifesting commonly observed diagnoses within the United States, such as hypertension, hyperlipidemia, and a history of tobacco use, or (3) displayed elevated probabilities of harboring multiple comorbid diagnoses, spanning domains such as lung, heart, and kidney-related conditions. The initial profile encompassed 27,002 patients (63%), followed by the second profile comprising 11,419 patients (27%), and the third profile, accounting for 4,553 patients (11%). Patients were individually assigned probabilities denoting their affiliation with each profile, with respective average classification probabilities of .98, .89, and .94, signifying a high degree of classification confidence. CONCLUSION: Our findings demonstrate the potential application of AI in informing healthcare interventions, such as tailored treatment plans, early intervention, resource allocation, patient education, research and development, and healthcare policy

Theory of Cylindrical Tubules and Helical Ribbons of Chiral Lipid Membranes

We present a general theory for the equilibrium structure of cylindrical tubules and helical ribbons of chiral lipid membranes. This theory is based on a continuum elastic free energy that permits variations in the direction of molecular tilt and in the curvature of the membrane. The theory shows that the formation of tubules and helical ribbons is driven by the chirality of the membrane. Tubules have a first-order transition from a uniform state to a helically modulated state, with periodic stripes in the tilt direction and ripples in the curvature. Helical ribbons can be stable structures, or they can be unstable intermediate states in the formation of tubules.Comment: 43 pages, including 12 postscript figures, uses REVTeX 3.0 and epsf.st

Historic Changes (1941–2008) In Side Channel And Backwater Habitats On An Unchannelized Reach Of The Missouri River

Flow regulation has had pervasive effects on aquatic ecosystems within the world’s large rivers. While channelization on the lower Missouri River has led to major changes in the river and its floodplain, including the loss of shallow water habitats, effects of upstream dams on unchannelized reaches on the Missouri have not been formally assessed. We quantified changes in the number and size of off-channel habitats, specifically backwaters and side channels, on the 95-km unchannelized reach of the Missouri below Gavins Point Dam (Yankton, South Dakota) using historical (1941, 1983–1985, 2008) aerial imagery. Total and mean areas of side channels declined by 77% and 37% and total and mean length decreased by 79% and 42% from 1941 to 2008. Total area of backwaters increased by 40% from 1941 to 2008, whereas mean area decreased by 36%. Our findings suggest that sharp declines in the area and length of side channels have occurred on this unchannelized remnant reach of the Missouri River, with likely significant impacts on aquatic ecosystem processes