Monetary Perspective On Underground Economic Activity In The United States

There are widespread reports of a growing underground, or unobserved, economy in the United States and in other countries. The unobserved economy seems to develop principally from efforts to evade taxes and government regulation. Although no single definition of such activity has been universally accepted, the term generally refers to activity – whether legal or illegal – generating income that either is underreported or not reported at all (see Chapter 1 in this volume). Some authors narrow the definition to cover income produced in legal activity that is not set down in the recorded national income statistics. Recent discussion of underground economic activity was stimulated by publication of two estimates, one by Gutmann (1977) and the other by Feige (1979), of the size of the underground economy in the United States; these estimates were derived from aggregate monetary statistics. In the ensuing years, numerous other estimates have been made of the underground economy in the United States and in other countries. The magnitude of some of these estimates has prompted congressional hearings and various government studies. In 1979, the Internal Revenue Service (IRS, 1979) estimated that, for 1976, individuals failed to report between $75 billion and$100 billion in income from legal sources and another $25 billion to$35 billion from three types of illegal activity – drugs, gambling, and prostitution. In a more recent study, the IRS estimated that unreported income from legal sources rose from $93.9 billion in 1973 to$249.7 billion in 1981 whereas unreported income from these same three illegal activities rose from $9.3 billion to$34 billion (IRS, 1983)

Extended analytical study of the free-wing/free-trimmer concept

The free wing/free trimmer concept was analytically studied in order to: (1) compare the fore and aft trimmer configurations on the basis of equal lift capability, rather than equal area; (2) assess the influence of tip mounted aft trimmers, both free and fixed, on the lateral directional modes and turbulence responses; (3) examine the feasibility of using differential tip mounted trimmer deflection for lateral control; (4) determine the effects of independent fuselage attitude on the lateral directional behavior; and (5) estimate the influence of wing sweep on dynamic behavior and structural weight. Results indicate that the forward trimmer concept is feasible with the reduced size examined, but it remains inferior to the aft trimmer in every respect except structural weight. Differential motion of the aft trimmer is found to provide powerful lateral control; while the effect of fuselage deck angle is a reduction of the dutch roll damping ratio for nose-down attitudes

Multiple object tracking with non-unique data-to-object association via generalized hypothesis testing

A generalized hypothesis testing approach is applied to the problem of tracking several objects where several different associations of data with objects are possible. Such problems occur, for instance, when attempting to distinctly track several aircraft maneuvering near each other or when tracking ships at sea. Conceptually, the problem is solved by first, associating data with objects in a statistically reasonable fashion and then, tracking with a bank of Kalman filters. The objects are assumed to have motion characterized by a fixed but unknown deterministic portion plus a random process portion modeled by a shaping filter. For example, the object might be assumed to have a mean straight line path about which it maneuvers in a random manner. Several hypothesized associations of data with objects are possible because of ambiguity as to which object the data comes from, false alarm/detection errors, and possible uncertainty in the number of objects being tracked. The statistical likelihood function is computed for each possible hypothesized association of data with objects. Then the generalized likelihood is computed by maximizing the likelihood over parameters that define the deterministic motion of the object

Gravity-assisted trajectories for unmanned space exploration

Gravity assistance to modify heliocentric trajectories of manned space probe

Long-term material compatibility testing system

System includes procedure for hermetically sealing solid materials and fluids in glass ampoule and use of temperature-controlled facility containing sample holder, which permits sample containers to be retrieved safely and conveniently. Solid material and fluid are sealed within chemically-clean glass ampoule according to highly detailed procedure

Infection studies with watermelon wilt caused by Fusarium niveum EFS.

Watermelon wilt, caused by Fusarium niveum, is a serious disease in Iowa and in many other sections of the United States. The present Iowa acreage is less than 10 percent of the acreage before wilt became a factor. Three heretofore undescribed seedling symptoms are described. These are: seedling rot, damping off and stunting. The organism may cause lesions on any of the roots. These are at first water-logged and become discolored in advanced stages. The lesions vary in length from a trace to 28 centimeters. Infection may be induced thru the use of infested soil, by means of spore suspensions of the organism injected with a hypodermic needle into the hypocotyl and by the insertion of the mycelium into wounds. It is probable that the organism enters the host thru root hairs, root injuries and thru the epidermis of the hypocotyl. Fusarium niveum has been recovered from primary, secondary and tertiary roots, from stems, petioles, leaves, peduncles, melon flesh and seeds of infected plants. The organism has also been recovered from and observed in the vascular tissues of what appeared to be normal, healthy plants. The organism flourishes at high temperatures. Its optimum on potato dextrose falls between 24 and 32°C., the minimum below 12°C. and the maximum above 35 °C. The organism flourishes on acid media, the optimum falls between pH 4.6 and 6.0 and the minimum below 3.0. With proper technique, seedling susceptibility in the greenhouse gives a good index of the susceptibility to be expected in the field