Causes Of Bloat Research Articles

Neonatal distended abdomen

The case of the neonatal distended abdomen is often referred to as “bloat”. Despite the common name, there are many different possible underlying etiologies for a distended abdomen in calves. This session discusses differential diagnoses, clinical reasoning, and diagnostic tools for investigation of common causes of bloat in calves.

Multi-objective genetic programming with partial sampling and its extension to many-objective

This paper describes a technique on an optimization of tree-structure data by of multi-objective evolutionary algorithm, or multi-objective genetic programming. GP induces bloat of the tree structure as one of the major problem. The cause of bloat is that the tree structure obtained by the crossover operator grows bigger and bigger but its evaluation does not improve. To avoid the risk of bloat, a partial sampling operator is proposed as a mating operator. The size of the tree and a structural distance are introduced into the measure of the tree-structure data as the objective functions in addition to the index of the goodness of tree structure. GP is defined as a three-objective optimization problem. SD is also applied for the ranking of parent individuals instead to the crowding distance of the conventional NSGA-II. When the index of the goodness of tree-structure data is two or more, the number of objective functions in the above problem becomes four or more. We also propose an effective many-objective EA applicable to such the many-objective GP. We focus on NSGA-II based on Pareto partial dominance (NSGA-II-PPD). NSGA-II-PPD requires beforehand a combination list of the number of objective functions to be used for Pareto partial dominance (PPD). The contents of the combination list greatly influence the optimization result. We propose to schedule a parameter r meaning the subset size of objective functions for PPD and to eliminate individuals created by the mating having the same contents as the individual of the archive set.

Neat Genetic Programming: Controlling bloat naturally

Bloat is one of the most widely studied phenomena in Genetic Programming (GP), it is normally defined as the increase in mean program size without a corresponding improvement in fitness. Several theories have been proposed in the specialized GP literature that explain why bloat occurs. In particular, the Crossover-Bias Theory states that the cause of bloat is that the distribution of program sizes during evolution is skewed in a way that encourages bloat to appear, by punishing small individuals and favoring larger ones. Therefore, several bloat control methods have been proposed that attempt to explicitly control the size distribution of programs within the evolving population. This work proposes a new bloat control method called neat-GP, that implicitly shapes the program size distribution during a GP run. neat-GP is based on two key elements: (a) the NeuroEvolution of Augmenting Topologies algorithm (NEAT), a robust heuristic that was originally developed to evolve neural networks; and (b) the Flat Operator Equalization bloat control method, that explicitly shapes the program size distributions toward a uniform or flat shape. Experimental results are encouraging in two domains, symbolic regression and classification of real-world data. neat-GP can curtail the effects of bloat without sacrificing performance, outperforming both standard GP and the Flat-OE method, without incurring in the computational overhead reported by some state-of-the-art bloat control methods.

Scalable Runtime Bloat Detection Using Abstract Dynamic Slicing

Many large-scale Java applications suffer from runtime bloat. They execute large volumes of methods and create many temporary objects, all to execute relatively simple operations. There are large opportunities for performance optimizations in these applications, but most are being missed by existing optimization and tooling technology. While JIT optimizations struggle for a few percent improvement, performance experts analyze deployed applications and regularly find gains of 2× or more. Finding such big gains is difficult, for both humans and compilers, because of the diffuse nature of runtime bloat. Time is spread thinly across calling contexts, making it difficult to judge how to improve performance. Our experience shows that, in order to identify large performance bottlenecks in a program, it is more important to understand its dynamic dataflow than traditional performance metrics, such as running time. This article presents a general framework for designing and implementing scalable analysis algorithms to find causes of bloat in Java programs. At the heart of this framework is a generalized form of runtime dependence graph computed by abstract dynamic slicing , a semantics-aware technique that achieves high scalability by performing dynamic slicing over bounded abstract domains. The framework is instantiated to create two independent dynamic analyses, copy profiling and cost-benefit analysis , that help programmers identify performance bottlenecks by identifying, respectively, high-volume copy activities and data structures that have high construction cost but low benefit for the forward execution. We have successfully applied these analyses to large-scale and long-running Java applications. We show that both analyses are effective at detecting inefficient operations that can be optimized for better performance. We also demonstrate that the general framework is flexible enough to be instantiated for dynamic analyses in a variety of application domains.

The causes of bloat, the limits of health

Applications often have large runtime memory requirements. In some cases, large memory footprint helps accomplish an important functional, performance, or engineering requirement. A large cache,for example, may ameliorate a pernicious performance problem. In general, however, finding a good balance between memory consumption and other requirements is quite challenging. To do so, the development team must distinguish effective from excessive use of memory. We introduce health signatures to enable these distinctions. Using data from dozens of applications and benchmarks, we show that they provide concise and application-neutral summaries of footprint. We show how to use them to form value judgments about whether a design or implementation choice is good or bad. We show how being independent ofany application eases comparison across disparate implementations. We demonstrate the asymptotic nature of memory health: certain designsare limited in the health they can achieve, no matter how much the data size scales up. Finally, we show how to use health signatures to automatically generate formulas that predict this asymptotic behavior, and show how they enable powerful limit studies on memory health.

A review of the development of a bloat-reduced alfalfa cultivar

The studies that led to the development of a bloat-reduced alfalfa began in 1970. Initial work focused on the causes of bloat, the characteristics of bloat-safe and bloat-causing legumes and the development of screening methodologies. The characteristics that were examined as causal factors of bloat in legume species included soluble proteins, saponins, absence of condensed tannins, and rapid breakdown of cells in the rumen. The factor or combination of factors responsible for causing bloat in animals grazing legumes have not been clearly identified; however, of the above, rapid cell breakdown was considered to be the most promising line of research to pursue in selecting a bloat-safe legume. A 4-h nylon-bag rumen digestion technique was developed, which was used to assess the initial rate of digestion (IRD) of fresh leaf material in large numbers of alfalfa genotypes. Using this technique on a population of four alfalfa cultivars, four cycles of recurrent selection for low initial rate of digestion (LIRD) were carried out over an 11-yr period. The resulting selected population, LIRD-4, had a vegetative stage initial rate of digestion that was approximately 85% of that of unselected alfalfa. To determine whether this reduction in IRD would reduce or eliminate bloat, grazing experiments comparing LIRD-4 and unselected cv. Beaver were conducted at three locations over 3 yr. Over all grazings, LIRD-4 caused significantly fewer incidences of bloat than Beaver; thus it is a bloat-reduced, rather than a bloat-safe cultivar. LIRD-4 was released in 1997 and named AC Grazeland Br. Key words: Bloat, cattle, alfalfa, low initial rate of digestion, grazing, bloat-reduced alfalfa

FRACTIONS FROM LADINO CLOVER WHICH INHIBIT BIOLOGICAL SYSTEMS

Currently, many workers believe that bloat in cattle and sheep results from any factor which interferes with eructation or which causes entrapment of gases in the rumen. Legumes which cause bloat contain substances that inhibit both muscle activity and the eructation reflex (Parsons et al., 1955; Weiss, 1953). Lindahl et al. 1954 have reported that alfalfa saponin induces bloat in sheep and cattle and that yucca saponin does not. Evans and Evans (1949) reported hydrogen cyanide from white clover as an inhibitor of smooth muscle activity and as a possible cause of bloat. Heath and Park (1953) have found, in white clover, a cholinesterase inhibitor which they suggested might be associated with bloat. Ferguson (1949 Ferguson (1950) found that tricin, a flavanoid from alfalfa, inhibited smooth muscle motility. Recently, Parsons et al. 1955 reported that legume juices and ruminal contents of bloated animals inhibit intestinal motility. Theories of the cause of bloat in ruminants have been reviewed by Cole et al. 1945, 1956, Clark and Weiss (1952) and Dougherty (1953). Thus far, techniques to measure muscle inhibition from legumes have included kymographic tracings and gross animal observations. In this study sensitive procedures were desired to test small amounts of plant constituents. Assays involving measurements of red cell cholinesterase (ChE) activity and of the oxygen consumption of rat diaphragm were adapted to supplement results obtained from kymographic tracings. By these techniques, ladino clover was tested for substances which can be inhibitory to muscle systems since such substances could be associated with bloat