The potential for energy efficiency in electric end usetechnologies

The authors summarize a recent study conducted by the Electric Power research Institute (EPRI) that contains estimates of potential energy savings that will result if the most efficient electricity technologies readily available immediately attain complete market saturation in the year 2000. They first define and contrast various efficiency scenarios and then summarize the energy savings forecast associated with demand-side management measured by sector. These estimates have been developed through discussions with a wide range of experts both inside and outside the utility industry, review of the trade and technical literature, and simulations and forecasts using several end-use models. The main results for efficient technologies that reduce electric usage are presented     

How to Better Use Expert Advice

This work is concerned with online learning from expert advice. Extensive work on this problem generated numerous expert advice algorithms whose total loss is provably bounded above in terms of the loss incurred by the best expert in hindsight. Such algorithms were devised for various problem variants corresponding to various loss functions. For some loss functions, such as the square, Hellinger and entropy losses, optimal algorithms are known. However, for two of the most widely used loss functions, namely the 0/1 and absolute loss, there are still gaps between the known lower and upper bounds.In this paper we present two new expert advice algorithms and prove for them the best known 0/1 and absolute loss bounds. Given an expert advice algorithm ALG, the goal is to form an upper bound on the regret L _ALG – L* of ALG, where L _ALG is the loss of ALG and L* is the loss of the best expert in hindsight. Typically, regret bounds of a canonical form C · are sought where N is the number of experts and C is a constant. So far, the best known constant for the absolute loss function is C = 2.83, which is achieved by the recent IAWM algorithm of Auer et al. (2002). For the 0/1 loss function no bounds of this canonical form are known and the best known regret bound is , where C ₁ = e – 2 and C ₂ = 2 . This bound is achieved by a P-norm algorithm of Gentile and Littlestone (1999). Our first algorithm is a randomized extension of the guess and double algorithm of Cesa-Bianchi et al. (1997). While the guess and double algorithm achieves a canonical regret bound with C = 3.32, the expected regret of our randomized algorithm is canonically bounded with C = 2.49 for the absolute loss function. The algorithm utilizes one random choice at the start of the game. Like the deterministic guess and double algorithm, a deficiency of our algorithm is that it occasionally restarts itself and therefore forgets what it learned. Our second algorithm does not forget and enjoys the best known asymptotic performance guarantees for both the absolute and 0/1 loss functions. Specifically, in the case of the absolute loss, our algorithm is canonically bounded with C approaching and in the case of the 0/1 loss, with C approaching 3/ . In the 0/1 loss case the algorithm is randomized and the bound is on the expected regret.     

New Bounds for Multidimensional Packing

Abstract. New upper and lower bounds are presented for a multidimensional generalization of bin packing called box packing. Several variants of this problem, including bounded space box packing, square packing, variable-sized box packing and resource augmented box packing are also studied. The main results, stated for d=2 , are as follows: a new upper bound of 2.66013 for online box packing, a new 14/9 + ɛ polynomial time offline approximation algorithm for square packing, a new upper bound of 2.43828 for online square packing, a new lower bound of 1.62176 for online square packing, a new lower bound of 2.28229 for bounded space online square packing and a new upper bound of 2.32571 for online two-sized box packing.     

Holtzman and Harlan Sprague-Dawley rats: differences in DRL 72-sec performance and 8-hydroxy-di-propylamino tetralin-induced hypothermia

Several compounds were tested on the differential-reinforcement-of-low-rate 72-sec (DRL 72-sec) schedule, a behavioral screen to determine putative antidepressants; these compounds were evaluated in two outbred stocks of rats, Harlan and Holtzman Sprague-Dawley rats. A dose-response determination for the tricyclic antidepressants, imipramine and desipramine, the selective serotonin (5-hydroxytryptamine; 5-HT) reuptake inhibitor, fluoxetine, the 5-HT2 receptor antagonist, ketanserin, the 5-HT1A receptor agonist, (+/-)8-hydroxy-di-propylamino tetralin (8-OH-DPAT) and the dopamine releasing compound, amphetamine, were assessed in both rat stocks. The two stocks of rats differed in their baseline performance on the DRL 72-sec schedule. The Harlan rats had a higher reinforcement rate and a lower response rate than the Holtzman rats. In Holtzman, but not in Harlan rats, imipramine, ketanserin, fluoxetine and 8-OH-DPAT increased reinforcement rate and decreased response rate on the DRL 72-sec schedule, confirming previous studies. However, desipramine was the only drug to increase reinforcement rate and decrease response rate in both Holtzman and Harlan rats; in Harlan rats, drugs that primarily act upon the 5-HT system, imipramine, ketanserin, fluoxetine and 8-OH-DPAT, disrupted the DRL 72-sec performance and did not increase the number of reinforcements over baseline as was seen in Holtzman rats. Amphetamine disrupted DRL 72-sec performance in both Holtzman and Harlan rats in a similar manner. The hypothermic response to 8-OH-DPAT was also assessed in the two stocks of rats; Holtzman rats had a smaller decrease in core body temperature than Harlan rats. The observed behavioral and pharmacological differences between Holtzman and Harlan rat stocks may be genetically and/or environmentally mediated.     

Brain serotonin neurotoxicity and primary pulmonary hypertension from fenfluramine and dexfenfluramine. A systematic review of the evidence

OBJECTIVES: Obesity is an important clinical problem, and the use of dexfenfluramine hydrochloride for weight reduction has been widely publicized since its approval by the Food and Drug Administration. However, animal and human studies have demonstrated toxic effects of fenfluramines that clinicians should be aware of when considering prescribing the drugs. Our purpose was to systematically review data on brain serotonin neurotoxicity in animals treated with fenfluramines and the evidence linking fenfluramines to primary pulmonary hypertension (PPH). DATA SOURCES: Archival articles and reviews identified through a computerized search of MEDLINE from 1966 to April 1997 using "fenfluramine(s)," "serotonin," "neurotoxicity," "behavior," "anorexigens," "weight loss," and "primary pulmonary hypertension" as index terms. STUDY SELECTION: Reports dealing with long-term effects of fenfluramines on brain serotonin neurons, body weight, and pulmonary function in animals and humans. DATA EXTRACTION: Reports were reviewed by individuals with expertise in serotonin neurobiology, neurotoxicity, neuropsychiatry, and pulmonary medicine and evaluated for appropriateness for inclusion in this review. DATA SYNTHESIS: Fenfluramines cause dose-related, long-lasting reductions in serotonin axonal markers in all the animal species tested and with all the routes of drug administration used. Doses of fenfluramines that produce signs of brain serotonin neurotoxicity in animals are on the same order as those used to treat humans for weight loss when one takes into account known relations between body mass and drug clearance. However, no human studies have been conducted, and the pathological and clinical potential for neurotoxicity in humans is unknown. Appetite suppressants-most commonly fenfluramines-increase the risk of developing PPH (odds ratio, 6.3), particularly when used for more than 3 months (odds ratio, >20). CONCLUSIONS: Fenfluramine and dexfenfluramine have been demonstrated to damage brain serotonin neurons in animal studies. It is not known if such damage occurs in humans or if there are clinical consequences. Use of fenfluramines is associated with an increased risk of PPH. Future studies should address the long-term consequences of prolonged use of fenfluramines.     

Characteristics of the ATLAS and CMS detectors

The goal for the detection of new physics processes in particle collisions at Large Hadron Collider energies, combined with the broad spectrum of possibilities for how the physics might be manifest, leads to detectors of unprecedented scope and size for particle physics experiments at colliders. The resulting two detectors, ATLAS (A Toroidal LHC ApparatuS) and CMS (compact muon spectrometer), must search for the new physics processes within very complex events arising from the very high-energy collisions. The two experiments share many basic design features-in particular, the need for very selective triggering to weed out the bulk of the uninteresting events; the order in which detector types are arrayed in order to provide maximum information about each event; and the very large angular coverage required to constrain the energy carried by any non-interacting particles. However, within these basic constraints, the detectors are quite different given the different emphases placed on issues such as resolution and background rejection. Both common features and the distinct differences will be presented.     

A solution to the rheumatoid factor paradox: pathologic rheumatoid factors can be tolerized by competition with natural rheumatoid factors

Rheumatoid factors (RF) associated with arthritic joint erosion are only seen transiently, if at all, in nondiseased individuals. Therefore, a tolerance mechanism must exist that prevents pathologic RF B cells from expressing Abs. Surprisingly, it has been shown that pathologic RF B cells are not tolerized by any previously established tolerance mechanism such as deletion, receptor editing, anergy, or prevention of memory establishment. How are pathologic RF cells tolerized? By simulating the RF response with a cellular automaton model immune system, we demonstrate that pathologic RFs can be tolerized by the novel mechanism of "competitive tolerance" with natural, nonpathologic RFs. We then demonstrate that competitive tolerance can be broken when a sequestered pool of expanding B cells are inappropriately subjected to chronic stimulation (as appears to occur in MRL/lpr mice and in patients with rheumatoid arthritis).