Advantage of single-trial models for response to selection in wheat breeding multi-environment trials

An investigation was conducted to evaluate the impact of experimental designs and spatial analyses (single-trial models) of the response to selection for grain yield in the northern grains region of Australia (Queensland and northern New South Wales). Two sets of multi-environment experiments were considered. One set, based on 33 trials conducted from 1994 to 1996, was used to represent the testing system of the wheat breeding program and is referred to as the multi-environment trial (MET). The second set, based on 47 trials conducted from 1986 to 1993, sampled a more diverse set of years and management regimes and was used to represent the target population of environments (TPE). There were 18 genotypes in common between the MET and TPE sets of trials. From indirect selection theory, the phenotypic correlation coefficient between the MET and TPE single-trial adjusted genotype means [r(p(MT))] was used to determine the effect of the single-trial model on the expected indirect response to selection for grain yield in the TPE based on selection in the MET. Five single-trial models were considered: randomised complete block (RCB), incomplete block (IB), spatial analysis (SS), spatial analysis with a measurement error (SSM) and a combination of spatial analysis and experimental design information to identify the preferred (PF) model. Bootstrap-resampling methodology was used to construct multiple MET data sets, ranging in size from 2 to 20 environments per MET sample. The size and environmental composition of the MET and the single-trial model influenced the r(p(MT)). On average, the PF model resulted in a higher r(p(MT)) than the IB, SS and SSM models, which were in turn superior to the RCB model for MET sizes based on fewer than ten environments. For METs based on ten or more environments, the r(p(MT)) was similar for all single-trial models.

Polyethism and comparability of termite choice assays in a model system using Microcerotermes turneri (Termitidae : Termitinae): Implications for standardised testing techniques

Traditional measures of termite food preference assess consequences of foraging behavior such as wood consumption, aggregation and/or termite survivorship. Although studies have been done to investigate the specifics of foraging behavior this is not generally integrated into choice assay experiments. Here choice assays were conducted with small isolated (orphaned) groups of workers and compared with choice assays involving foragers from whole nests (non-orphaned) in the laboratory. Aggregation to two different wood types was used as a measure of preference. Specific worker caste and instars participating in initial exploration were compared between assay methods, with samples of termites taken from nest carton material and sites where termites were feeding. Aggregation results differ between choice assay techniques. Castes and instars responsible for initial exploration, as determined in whole nest trials, were not commonly found exploring in isolated group trials, nor were they numerous in termites taken from active feeding sites. Consequently the use of small groups of M. turneri worker termites extracted from active feeding sites may not be appropriate for use in choice assays.

Aberrant protective force generation during neural provocation testing and the effect of treatment in patients with neurogenic cervicobrachial pain

Background: Observation of the occurrence of protective muscle activity is advocated in assessment of the peripheral nervous system by means of neural provocation tests. However, no studies have yet demonstrated abnormal force generation in a patient population. Objectives: To analyze whether aberrations in shoulder girdle-elevation force during neural tissue provocation testing for the median nerve (NTPTI) can be demonstrated, and whether possible aberrations can be normalized following cervical mobilization. Study Design: A single-blind randomized comparative controlled study. Setting: Laboratory setting annex in a manual therapy teaching practice. Participants: Twenty patients with unilateral or bilateral neurogenic cervicobrachial pain. Methods: During the NTPTI, we used a load cell and electrogoniometer to record continuously the shoulder-girdle elevation force in relation to the available range of elbow extension. Following randomization, we analyzed the immediate treatment effects of a cervical contralateral lateral glide mobilization technique (experimental group) and therapeutic ultrasound (control group). Results: On the involved side, the shoulder-girdle elevation force occur-red earlier, and the amount of force at the end of the test was substantially, though not significantly, greater than that on the uninvolved side at the corresponding range of motion. Together with a significant reduction in pain perception after cervical mobilization, a clear tendency toward normalization of the force curve could be observed, namely, a significant decrease in force generation and a delayed onset. The control group demonstrated no differences. Conclusions: Aberrations in force generation during neural, provocation testing are present in patients with neurogenic pain and can be normalized with appropriate treatment modalities.

A framework and tool support for the systematic testing of model-based specifications

Formal specifications can precisely and unambiguously define the required behavior of a software system or component. However, formal specifications are complex artifacts that need to be verified to ensure that they are consistent, complete, and validated against the requirements. Specification testing or animation tools exist to assist with this by allowing the specifier to interpret or execute the specification. However, currently little is known about how to do this effectively. This article presents a framework and tool support for the systematic testing of formal, model-based specifications. Several important generic properties that should be satisfied by model-based specifications are first identified. Following the idea of mutation analysis, we then use variants or mutants of the specification to check that these properties are satisfied. The framework also allows the specifier to test application-specific properties. All properties are tested for a range of states that are defined by the tester in the form of a testgraph, which is a directed graph that partially models the states and transitions of the specification being tested. Tool support is provided for the generation of the mutants, for automatically traversing the testgraph and executing the test cases, and for reporting any errors. The framework is demonstrated on a small specification and its application to three larger specifications is discussed. Experience indicates that the framework can be used effectively to test small to medium-sized specifications and that it can reveal a significant number of problems in these specifications.

Testing integrability with a single bit of quantum information

We show that deterministic quantum computing with a single bit can determine whether the classical limit of a quantum system is chaotic or integrable using O(N) physical resources, where N is the dimension of the Hilbert space of the system under study. This is a square-root improvement over all known classical procedures. Our study relies strictly on the random matrix conjecture. We also present numerical results for the nonlinear kicked top.

The impact of neurodynamic testing on the perception of experimentally induced muscle pain

Neurodynamic tests such as the straight leg raising (SLR) and slump test are frequently used for assessment of mechanosensitivity of neural tissues. However, there is ongoing debate in the literature regarding the contributions of neural and non-neural tissues to the elicited symptoms because many structures are affected by these tests. Sensitizing manoeuvres are limb or spinal movements added to neurodynamic tests, which aim to identify the origin of the symptoms by preferentially loading or unloading neural structures. A prerequisite for the use of sensitizing manoeuvres to identify neural involvement is that the addition of sensitizing manoeuvres has no impact on pain perception when the origin of the pain is non-neural. In this study, experimental muscle pain was induced by injection of hypertonic saline in tibialis anterior or soleus in 25 asymptomatic, naive volunteers. A first experiment investigated the impact of hip adduction, abduction, medial and lateral rotation in the SLR position. In a second experiment, the different stages of the slump test were examined. The intensity and area of experimentally induced muscle pain did not increase when sensitizing manoeuvres were added to the SLR or throughout the successive stages of the slump test. The findings of this study lend support to the validity of the use of sensitizing manoeuvres during neurodynamic testing. (C) 2004 Elsevier Ltd. All rights reserved.

Zero-non-zero patterned vector error correction modeling for I(2) cointegrated time series with applications in testing PPP and stock market relationships

Vector error-correction models (VECMs) have become increasingly important in their application to financial markets. Standard full-order VECM models assume non-zero entries in all their coefficient matrices. However, applications of VECM models to financial market data have revealed that zero entries are often a necessary part of efficient modelling. In such cases, the use of full-order VECM models may lead to incorrect inferences. Specifically, if indirect causality or Granger non-causality exists among the variables, the use of over-parameterised full-order VECM models may weaken the power of statistical inference. In this paper, it is argued that the zero–non-zero (ZNZ) patterned VECM is a more straightforward and effective means of testing for both indirect causality and Granger non-causality. For a ZNZ patterned VECM framework for time series of integrated order two, we provide a new algorithm to select cointegrating and loading vectors that can contain zero entries. Two case studies are used to demonstrate the usefulness of the algorithm in tests of purchasing power parity and a three-variable system involving the stock market.

MULTIPRED: A computational system for prediction of promiscuous HLA binding peptides

MULTIPRED is a web-based computational system for the prediction of peptide binding to multiple molecules ( proteins) belonging to human leukocyte antigens (HLA) class I A2, A3 and class II DR supertypes. It uses hidden Markov models and artificial neural network methods as predictive engines. A novel data representation method enables MULTIPRED to predict peptides that promiscuously bind multiple HLA alleles within one HLA supertype. Extensive testing was performed for validation of the prediction models. Testing results show that MULTIPRED is both sensitive and specific and it has good predictive ability ( area under the receiver operating characteristic curve A(ROC) > 0.80). MULTIPRED can be used for the mapping of promiscuous T-cell epitopes as well as the regions of high concentration of these targets termed T-cell epitope hotspots. MULTIPRED is available at http:// antigen.i2r.a-star.edu.sg/ multipred/.

Morphology of breast cancer as a means of triage of patients for BRCA1 genetic testing

Background: Women who have germline mutations in the BRCA1 gene are at substantially increased lifetime risk of developing breast and ovarian cancer but are otherwise normal. Currently. early age of onset of cancer and a strong family history are relied upon as the chief clues as to who should be offered genetic testing. Certain morphologic and immunohistochemical features are overrepresented in BRCA1-associated breast cancers but these differences have not been incorporated into the current selection criteria for genetic testing. Design: Each of the 4 pathologists studied 30 known cases of BRCA1- and BRCA2-associated breast cancer from kConFab families. After reviewing the literature, we agreed on a semiquantitative scoring system for estimating the chances of presence of an underlying BRCA1 mutation, based on the number of the reported prototypic features present. After a time lag of 12 months, we each examined a series of 62 deidentified cases of breast cancer, inclusive of cases of BRCA1-associated breast cancer and controls. The controls included cases of BRCA2-associated breast cancer and sporadic cases. Results: Our predictions had a sensitivity of 92%, specificity of 86%, positive predictive value of 61%, and negative predictive value of 98%. For comparison the sensitivity of currently used selection criteria are in the range of 25% to 30%. Conclusion: The inclusion of morphologic and immunohistochemical features of breast cancers in algorithms to predict the likelihood of presence of germline mutations in the BRCA1 gene improves the accuracy of the selection process.

The role of BNP testing in heart failure

Brain natriuretic peptide (BNP) levels are simple and objective measures of cardiac function. These measurements can be used to diagnose heart failure, including diastolic dysfunction, and using them has been shown to save money in the emergency department setting. The high negative predictive value of BNP tests is particularly helpful for ruling out heart failure. Treatment with angiotensin-converting enzyme inhibitors, angiotensin-II receptor blockers, spironolactone, and diuretics reduces BNP levels, suggesting that BNP testing may have a role in monitoring patients with heart failure. However, patients with treated chronic stable heart failure may have levels in the normal range (i.e., BNP less than 100 pg per mL and N-terminal proBNP less than 125 pg per mL in patients younger than 75 years). Increases in BNP levels may be caused by intrinsic cardiac dysfunction or may be secondary to other causes such as pulmonary or renal diseases (e.g., chronic hypoxia). BNP tests are correlated with other measures of cardiac status such as New York Heart Association classification. BNP level is a strong predictor of risk of death and cardiovascular events in patients previously diagnosed with heart failure or cardiac dysfunction.

A case study in specification and implementation testing

Achieving consistency between a specification and its implementation is an important part of software development In previous work, we have presented a method and tool support for testing a formal specification using animation and then verifying an implementation of that specification. The method is based on a testgraph, which provides a partial model of the application under test. The testgraph is used in combination with an animator to generate test sequences for testing the formal specification. The same testgraph is used during testing to execute those same sequences on the implementation and to ensure that the implementation conforms to the specification. So far, the method and its tool support have been applied to software components that can be accessed through an application programmer interface (API). In this paper, we use an industrially-based case study to discuss the problems associated with applying the method to a software system with a graphical user interface (GUI). In particular, the lack of a standardised interface, as well as controllability and observability problems, make it difficult to automate the testing of the implementation. The method can still be applied, but the amount of testing that can be carried on the implementation is limited by the manual effort involved.