Interactive synthesis of code-level security rules

Motivation: Certain studies use short-TE MRS to estimate metabolites such as gamma-aminobutyric acid. The findings of such studies hinge on the correlation of this technique to the gold-standard edited MRS technique. Goal(s): We investigate how the false negative rate and false positive rate of studies vary as a function of correlation between short-TE and MEGA-edited metabolite estimates. Approach: Simulated data was used to numerically estimate the false positive and false negative rates, using parameters obtained from the literature. Results: We show that these studies can have largely inflated false positive and false negative rates as compared to their nominally designed values. Impact: The false negative and false positive rate can be markedly inflated when using short-TE MRS to estimate metabolites such as gamma-aminobutyric acid. This calls for increased caution in interpreting results, and the accommodation of these effects when designing statistical analyses.

Ranaviruses have been identified as the etiologic agent in many amphibian die-offs across the globe. Polymerase chain reaction (PCR) is commonly used to detect ranavirus infection in amphibian hosts, but the test results may vary between tissue samples obtained by lethal and non-lethal procedures. Testing liver samples for infection is a common lethal sampling technique to estimate ranavirus prevalence because the pathogen often targets this organ and the liver is easy to identify and collect. However, tail clips or swabs may be more practicable for ranavirus surveillance programs compared with collecting and euthanizing animals, especially for uncommon species. Using PCR results from liver samples for comparison, we defined false-positive test results as occurrences when a non-lethal technique indicated positive but the liver sample was negative. Similarly, we defined false-negative test results as occurrences when a non-lethal technique was negative but the liver sample was positive. Using these decision rules, we estimated false-negative and false-positive rates for tail clips and swabs. Our study was conducted in a controlled facility using American bullfrog Lithobates catesbeianus tadpoles; false-positive and false-negative rates were estimated after different periods of time following exposure to ranavirus. False-negative and false-positive rates were 20 and 6%, respectively, for tail samples, and 22 and 12%, respectively, for swabs. False-negative rates were constant over time, but false-positive rates decreased with post-exposure duration. Our results suggest that non-lethal sampling techniques can be useful for ranavirus surveillance, although the prevalence of infection may be underestimated when compared to results obtained with liver samples.

The Effect of Testing Reliability on Visual Field Sensitivity in Normal Eyes: The Singapore Chinese Eye Study

A bug detection tool is an important tool in software engineering development. Many research papers have proposed techniques for detecting software bug, but there are certain semantic bugs that are not easy to detect. In our views, a bug can occur from incorrect logics that when a program is executed with a particular input, the program will behave in unexpected ways. In this paper, we propose a method and tool for software bugs detection by finding such input that causes an unexpected output guided by the fitness function. The method uses a Hierarchical Similarity Measurement Model (HSM) to help create the fitness function to examine a program behavior. Its tool uses Particle Swarm Optimization (PSO) with Search Space Reduction (SSR) to manipulate input by contracting and eliminating unfavorable areas of input search space. The programs under experiment were selected from four different domains such as financial, decision support system, algorithms and machine learning. The experimental result shows a significant percentage of success rate up to 93% in bug detection, compared to an estimated success rate of 28% without SSR.

To evaluate the false-negative and false-positive error rates both in a screening and a non-screening population. A total of 4192 prostatic biopsies were reported in a 6-year period by 15 consultant histopathologists, two of whom had an interest in uropathology and were deemed to be specialists (J.O. and C.S.). All biopsies were reviewed prior to the multidisciplinary team (MDT) meeting. The overall false-negative rate was 1.7% (screening 2.1%, non-screening 1.5%). The overall false-positive rate was 0.5% (screening 0.9%, non-screening 0.4%). These error rates varied among pathologists, with the false-negative rate ranging from 0% to 9.3%, and the false-positive rate ranging from 0% to 3.8%. The false-negative rate was three times greater than the false-positive rate, showing that detection of significant pathology is far greater in the negative biopsies. More errors occurred in the screening population than in the non-screening population. The consultants making the most errors were non-specialists, but the specialists also made false-negative errors, suggesting that just using specialist reporting alone would not have eradicated errors.

An Evaluation of Conventional Culture, invA PCR, and the Real-Time PCR iQ-Check Kit as Detection Tools for Salmonella in Naturally Contaminated Premarket and Retail Turkey

The influence of fatigue and related factors on automated perimetric testing was evaluated in both eyes of sixteen normal observers and sixteen patients with early-to-moderate visual field loss using a Digilab 750 automated perimeter and a customized test procedure. False positive rate, false negative rate, and detection sensitivity at 5,10,15, and 20 degrees eccentricity were measured in 1.5-rain intervals throughout a 21-min visual field examination. Half of the normal observers and patients with visual field loss were given a briefrest(1.5-min) midway through each visual field exam to determine whether this would reduce fatigue effects. Our findings revealed that patients displayed considerably higher average false positive and false negative rates than normal observers. However, neither the patients nor normal observers demonstrated any consistent changes in false positive rate or false negative rate as a function of testing duration. In contrast, both normal observers and patients showed an average decrease in sensitivity as a function of increasing test duration with the magnitude of the time-dependent sensitivity loss becoming greater with increasing stimulus eccentricity. Patients demonstrated a larger time-dependent sensitivity loss than normal observers, averaging ~4dB at 20 degrees eccentricity. The introduction of a brief pause midway through the test procedure appeared to reduce the time-dependent sensitivity loss for the second half of the test procedure, especially for greater eccentricities.

Several different types of detectors, software, and hardware designs are employed in instruments used to monitor radioactive content of freight shipments in order to detect illicit trafficking of nuclear materials. The instruments can be container monitors, hand-held radiation detectors, mobile analysis systems, or fixed radiation portal monitors. However, within the various groupings (e.g., portal monitors), all instruments are expected to solve the same problem, that is, to detect and identify any radioactive material present according to the prescribed investigative procedure or CONOPS. The best way to compare the performance of different instruments is with a numerical score or Figure of Merit (FOM). The FOM must quantify the performance of the instrument with respect to true positives (TP), false positives (FP), and false negatives (FN). The minimization of FN for certain radionuclides (e.g., uranium and plutonium or other Special Nuclear Material (SNM)) is more important than the minimization of FN for non-threat nuclides (e.g., low level NORM). In a similar way, the minimization of FP for SNM is more important than falsely reporting the common NORM nuclides which represent no threat. System performance depends on the measurement detail (e.g., transit speed through a portal, measurement time in general, amount and distribution of NORM), therefore the test conditions should also be included in the statement of the FOM. The FOM is expected to vary significantly with the above measurement details. A FOM has been developed based on the number of true positives (TP), the number of false important positives (FIP), the number of FP, the number of true positives for SNM (TPSNM), and the number of false positives for SNM (FPSNM). This formula rates the overall performance with extra weight given to FP and FN for SNM. Examples will be shown for testing of portal monitors.

Relationships between age and visual field (VF) reliability indices were investigated using a large real-world dataset (42,421 VF data points from 11,525 eyes of 5930 subjects). All VFs tested and stored at Shimane University Hospital between 1988 and 2019 were exported. Correlations between age, mean deviation (MD), pattern standard deviation (PSD), and reliability indices including fixation losses (FLs), false negatives (FNs), and false positives (FPs) were analyzed. The mean ± standard deviation age was 65.0 ± 15.1 years; MD—−6.9 ± 8.1 decibels (dB); PSD—6.3 ± 4.6 dB; FL—8.6 ± 11.7%; FN—5.3 ± 8.3%; and FP—2.6 ± 5.0%. Univariate analyses showed strong associations between age and FNs (correlation coefficient, ρ = 0.20, p < 0.0001) and MD (ρ = −0.21, p < 0.0001). All FLs, FNs, and FPs were lowest during the third decade (20–29 years) of life. FLs were elevated consistently after that decade, and FNs were elevated sharply after the seventh decade. FPs were relatively stable after the fourth decade (30–39 years). Mixed-effect regression analyses in subjects 40 years and older showed that older age was associated with worse FLs (p < 0.0001) and FNs (p < 0.0001) but not FPs (p = 0.4126). Aging affects FLs and FNs with different modes but had minimal effects on FPs. Decreased VF sensitivity, deteriorated macular function, and technical difficulties with testing may be mechanisms of age-related changes in FLs and FNs.

How do we make the best choice in assays used to monitor HLA antibodies in renal recipients awaiting transplant? A comparison of flowpra beads with luminex single-antigen beads

MP32-18 EVALUATING THE DIAGNOSTIC ACCURACY OF BIPARAMETRIC MAGNETIC RESONANCE IMAGING IN MUSCLE-INVASIVE BLADDER CANCER

This study aimed to compare the results of the IMO vifa 24plus(1-2) and HFA 24-2 visual field tests. We included 52 patients (104 eyes) with glaucoma who visited Chukyo Eye Clinic between June 2023 and March 2024. On the same day, the HFA 24-2 test using the Swedish Interactive Threshold Algorithm Standard and the IMO vifa 24plus(1-2) test using the Ambient Interactive Zippy Estimated strategy were performed. A Wilcoxon signed-rank test was used to compare fixation, false positives, false negatives, and total test time for both eyes between the HFA and IMO vifa tests. Only eyes with reliable test results were selected, and the visual field index (VFI), mean deviation (MD), and pattern standard deviation (PSD) were examined using Spearman's rank correlation coefficient and the Wilcoxon signed-rank test. The test times for the HFA 24-2 and IMO vifa 24plus(1-2) were 716.83±118.80 and 628.75±142.70 s, respectively, with the IMO vifa being significantly shorter (P<0.001). For fixation, the results were 15.85±16.57% and 11.09±15.20%, with significantly better fixation in the IMO vifa (P<0.0001). False positives and negatives were 4.52±5.19 / 4.14±6.85% and 4.97±7.99 / 5.47±7.86%, respectively, with no significant differences, though the IMO vifa showed a slightly higher trend (P=0.980, 0.056). In eyes with reliable results, the HFA 24-2 and IMO vifa 24plus(1-2) outcomes were as follows: MD (-6.45±7.23, -6.85±7.35, P=0.724), PSD (7.13±4.75, 7.49±4.87, P=0.061), VFI (80.86±21.61, 80.86±21.74, P=0.644). The Spearman rank correlation coefficients between the HFA 24-2 and IMO vifa 24plus(1-2) were MD: 0.938, PSD: 0.949, VFI: 0.932 (all P<0.001). The IMO vifa demonstrates a very high correlation with HFA and allows for a shorter examination time. Fixation errors are significantly improved compared to HFA, while there is no significant difference in false positives or false negatives.

This paper proposes a pointer alias analysis for automatic error detection. State-of-the-art pointer alias analyses are either too slow or too imprecise for finding errors in real-life programs. We propose a hybrid pointer analysis that tracks actively manipulated pointers held in local variables and parameters accurately with path and context sensitivity and handles pointers stored in recursive data structures less precisely but efficiently. We make the unsound assumption that pointers passed into a procedure, in parameters, global variables, and locations reached by applying simple access paths to parameters and global variables, are all distinct from each other and from any other locations. This assumption matches the semantics of many functions, reduces spurious aliases and speeds up the analysis.We present a program representation, called IPSSA, which captures intraprocedural and interprocedural definition-use relationships of directly and indirectly accessed memory locations. This representation makes it easy to create demand-driven path-sensitive and context-sensitive analyses.We demonstrate how a program checker based on IPSSA can be used to find security violations. Our checker, when applied to 10 programs, found 6 new violations and 8 previously reported ones. The checker generated only one false warning, suggesting that our approach is effective in creating practical and easy-to-use bug detection tools.

Recent advances in microarray technology have opened new ways for functional annotation of previously uncharacterised genes on a genomic scale. This has been demonstrated by unsupervised clustering of co-expressed genes and, more importantly, by supervised learning algorithms. Using prior knowledge, these algorithms can assign functional annotations based on more complex expression signatures found in existing functional classes. Previously, support vector machines (SVMs) and other machine-learning methods have been applied to a limited number of functional classes for this purpose. Here we present, for the first time, the comprehensive application of supervised neural networks (SNNs) for functional annotation. Our study is novel in that we report systematic results for ~100 classes in the Munich Information Center for Protein Sequences (MIPS) functional catalog. We found that only ~10% of these are learnable (based on the rate of false negatives). A closer analysis reveals that false positives (and negatives) in a machine-learning context are not necessarily "false" in a biological sense. We show that the high degree of interconnections among functional classes confounds the signatures that ought to be learned for a unique class. We term this the "Borges effect" and introduce two new numerical indices for its quantification. Our analysis indicates that classification systems with a lower Borges effect are better suitable for machine learning. Furthermore, we introduce a learning procedure for combining false positives with the original class. We show that in a few iterations this process converges to a gene set that is learnable with considerably low rates of false positives and negatives and contains genes that are biologically related to the original class, allowing for a coarse reconstruction of the interactions between associated biological pathways. We exemplify this methodology using the well-studied tricarboxylic acid cycle.

Detecting concurrency bugs is becoming increasingly important. Many pattern-based concurrency bug detectors focus on the specific types of interleavings that are correlated to concurrency bugs. To detect multiple types of concurrency bugs, general detectors focus on multiple types of interleaving patterns, including data race pattern, atomicity violation pattern, and atomic-set violation pattern. Unfortunately, they suffer from redundant analysis due to repeated interleavings, which may affect the efficiency of concurrency bug detection. Hence, we propose an approach to identify the repeated interleavings. To the best of our knowledge, this is the first approach that can prune repeated interleavings to improve the efficiency of concurrency bug detection. We apply our approach to existing general detectors (PECAN and Maple) to avoid analyzing repeated interleavings. We evaluated the general detectors with and without our approach, respectively. The experimental results show that the bug detection results are not affected. With our approach, the bug detection time of PECAN and Maple are reduced by 40.0 % and 44.4 %, respectively. Additionally, our approach does not affect the overhead of bug detection, and consumes only a little memory.