A cost-effective software testing strategy employing online feedback information

An online partitioning strategy is presented, in which test cases are selected based on feedback information collected during the testing process. The strategy differs from con- ventional approaches because the partitioning is performed online rather than off-line and because the partitioning is not based on program code or specifications. It can, therefore, be implemented in the absence of the source code or specification of the program under test. The cost-effectiveness of the proposed strategy has been empirically investigated with a set of subject programs, namely, SPACE, SED, GREP, and the Siemens Suite of Programs. The results demonstrate that the proposed strategy constantly achieves large savings in terms of the total number of test case executions needed to detect all faults

Most parsimonious haplotype allele sharing determination

<p>Abstract</p> <p>Background</p> <p>The "common disease – common variant" hypothesis and genome-wide association studies have achieved numerous successes in the last three years, particularly in genetic mapping in human diseases. Nevertheless, the power of the association study methods are still low, in particular on quantitative traits, and the description of the full allelic spectrum is deemed still far from reach. Given increasing density of single nucleotide polymorphisms available and suggested by the block-like structure of the human genome, a popular and prosperous strategy is to use haplotypes to try to capture the correlation structure of SNPs in regions of little recombination. The key to the success of this strategy is thus the ability to unambiguously determine the haplotype allele sharing status among the members. The association studies based on haplotype sharing status would have significantly reduced degrees of freedom and be able to capture the combined effects of tightly linked causal variants.</p> <p>Results</p> <p>For pedigree genotype datasets of medium density of SNPs, we present two methods for haplotype allele sharing status determination among the pedigree members. Extensive simulation study showed that both methods performed nearly perfectly on breakpoint discovery, mutation haplotype allele discovery, and shared chromosomal region discovery.</p> <p>Conclusion</p> <p>For pedigree genotype datasets, the haplotype allele sharing status among the members can be deterministically, efficiently, and accurately determined, even for very small pedigrees. Given their excellent performance, the presented haplotype allele sharing status determination programs can be useful in many downstream applications including haplotype based association studies.</p

NUMA-aware image compositing on multi-GPU platform

Sort-last parallel rendering is widely used. Recent GPU developments mean that a PC equipped with multiple GPUs is a viable alternative to a high-cost supercomputer: the Fermi architecture of a single GPU supports uniform virtual addressing, providing a foundation for non-uniform memory access (NUMA) on multi-GPU platforms. Such hardware changes require the user to reconsider the parallel rendering algorithms. In this paper, we thoroughly investigate the NUMA-aware image compositing problem, which is the key final stage in sort-last parallel rendering. Based on a proven radix-k strategy, we find one optimal compositing algorithm, which takes advantage of NUMA architecture on the multi-GPU platform. We quantitatively analyze different image compositing modes for practical image compositing, taking into account peer-to-peer communication costs between GPUs. Our experiments on various datasets show that our image compositing method is very fast, an image of a few megapixels can be composited in about 10 ms by eight GPUs

Optogenetic Control of Non-Apoptotic Cell Death

Herein, a set of optogenetic tools (designated LiPOP) that enable photoswitchable necroptosis and pyroptosis in live cells with varying kinetics, is introduced. The LiPOP tools allow reconstruction of the key molecular steps involved in these two non-apoptotic cell death pathways by harnessing the power of light. Further, the use of LiPOPs coupled with upconversion nanoparticles or bioluminescence is demonstrated to achieve wireless optogenetic or chemo-optogenetic killing of cancer cells in multiple mouse tumor models. LiPOPs can trigger necroptotic and pyroptotic cell death in cultured prokaryotic or eukaryotic cells and in living animals, and set the stage for studying the role of non-apoptotic cell death pathways during microbial infection and anti-tumor immunity

The tumor suppressive role of CAMK2N1 in castration-resistant prostate cancer.

Prostate cancer at advanced stages including metastatic and castration-resistant cancer remains incurable due to the lack of effective therapies. The CAMK2N1 gene, cloned and characterized as an inhibitor of CaMKII (calcium/calmodulin-dependent protein kinase II), has been shown to affect tumorigenesis and tumor growth. However, it is still unknown whether CAMK2N1 plays a role in prostate cancer development. We first examined the protein and mRNA levels of CAMK2N1 and observed a significant decrease in human prostate cancers comparing to normal prostate tissues. Re-expression of CAMK2N1 in prostate cancer cells reduced cellular proliferation, arrested cells in G0/G1 phases, and induced apoptotic cell death accompanied by down-regulation of IGF-1, ErbB2, and VEGF downstream kinases PI3K/AKT, as well as the MEK/ERK-mediated signaling pathways. Conversely, knockdown of CAMK2N1 had a significant opposite effects on these phenotypes. Our analyses suggest that CAMK2N1 plays a tumor suppressive role in prostate cancer cells. Reduced CAMK2N1 expression correlates to human prostate cancer progression and predicts poor clinical outcome, indicating that CAMK2N1 may serve as a biomarker. The inhibition of tumor growth by expressing CAMK2N1 established a role of CAMK2N1 as a therapeutic target

CAMK2N1 inhibits prostate cancer progression through androgen receptor-dependent signaling.

Castration resistance is a major obstacle to hormonal therapy for prostate cancer patients. Although androgen independence of prostate cancer growth is a known contributing factor to endocrine resistance, the mechanism of androgen receptor deregulation in endocrine resistance is still poorly understood. Herein, the CAMK2N1 was shown to contribute to the human prostate cancer cell growth and survival through AR-dependent signaling. Reduced expression of CAMK2N1 was correlated to recurrence-free survival of prostate cancer patients with high levels of AR expression in their tumor. CAMK2N1 and AR signaling form an auto-regulatory negative feedback loop: CAMK2N1 expression was down-regulated by AR activation; while CAMK2N1 inhibited AR expression and transactivation through CAMKII and AKT pathways. Knockdown of CAMK2N1 in prostate cancer cells alleviated Casodex inhibition of cell growth, while re-expression of CAMK2N1 in castration-resistant cells sensitized the cells to Casodex treatment. Taken together, our findings suggest that CAMK2N1 plays a tumor suppressive role and serves as a crucial determinant of the resistance of prostate cancer to endocrine therapies

Observation of the exceptional-point-enhanced Sagnac effect

Exceptional points (EPs) are special spectral degeneracies of non-Hermitian Hamiltonians that govern the dynamics of open systems. At an EP, two or more eigenvalues, and the corresponding eigenstates, coalesce. Recently, it was predicted that operation of an optical gyroscope near an EP results in improved response to rotations. However, the performance of such a system has not been examined experimentally. Here we introduce a precisely controllable physical system for the study of non-Hermitian physics and nonlinear optics in high-quality-factor microresonators. Because this system dissipatively couples counter-propagating lightwaves within the resonator, it also functions as a sensitive gyroscope for the measurement of rotations. We use our system to investigate the predicted EP-enhanced Sagnac effect and observe a four-fold increase in the Sagnac scale factor by directly measuring rotations applied to the resonator. The level of enhancement can be controlled by adjusting the system bias relative to the EP, and modelling results confirm the observed enhancement. Moreover, we characterize the sensitivity of the gyroscope near the EP. Besides verifying EP physics, this work is important for the understanding of optical gyroscopes

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

OFFLINE AND ONLINE MODELLING OF SWITCHED RELUCTANCE MOTOR BASED ON RBF NEURAL NETWORKS

Due to the highly nonlinearity of the flux-linkage characteristics of Switched Reluctance Motor drives (SRM), accurately modelling is cumbersome. In this paper, the offline-trained and the online-trained Radial Basis function (RBF) neural network model are proposed for estimating the SRM flux-linkage under running conditions. To investigate the performance of the modelling schemes, the simulation and experiments have been implemented in a 12/8 structure SRM prototype. The results show that the online-trained model exhibits much better estimation accuracy and robustness than the offline-trained model. Thus, the online-trained RBF model is more suitable for SRM performance prediction and analyzing. K e y w o r d s: offline modelling, online modelling, RBF neural network, flux-linkage, switched reluctance motor (SRM