Reversal Errors Research Articles

Real-time outlier detection of satellite orbit and clock products using reverse error estimation

Real-time outlier detection of satellite orbit and clock products using reverse error estimation

Distributed Ledger Technology and Financial Reporting Integrity in Nigerian Quoted Banks: A Study on Error Reduction and Enhanced Transparency

This study investigated the effect of distributed ledger technology (DLT) factors on eliminating financial reporting errors (FREs) in quoted Nigerian banks. Using an exploratory survey design, data was collected from 300 employees of 14 quoted banks involved in financial reporting. DLT factors of public, private, hybrid, and blockchain were examined as independent variables affecting the dependent variable of FRE elimination. Descriptive analysis showed that all DLT types were perceived as highly effective for error reduction. Correlation analysis revealed strong positive relationships between DLT factors and FRE mitigation. Regression modeling found that hybrid DLT had the largest impact on error elimination, followed by private, public, and blockchain DLT. Together, the DLT factors explained 98.1% of the variance in FRE reduction. The results statistically established the significant positive effects of DLT factors on eliminating prevalent FREs like principle, omission, entry, disclosure, and reversal errors. Key contributions include providing robust empirical evidence that leveraging DLT, especially hybrid DLT, can eliminate common financial reporting errors in Nigerian banks. The pioneering study expands conceptualizations, theories, and literature regarding DLT's potential to comprehensively transform financial reporting accuracy. It offers important implications for policy, practice, and research on regulating, adopting, and studying DLT solutions to address persistent financial statement errors undermining stakeholder trust in Nigeria's banking sector. The study concludes by strongly recommending for policy and, in practice, the regulation and full adoption of DLT for the elimination of FREs in Nigeria.

HIV-1 Reverse Transcriptase Error Rates and Transcriptional Thresholds Based on Single-strand Consensus Sequencing of Target RNA Derived From In Vitro-transcription and HIV-infected Cells

Nucleotide incorporation and lacZ-based forward mutation assays have been widely used to determine the accuracy of reverse transcriptases (RTs) in RNA-dependent DNA polymerization reactions. However, they involve quite complex and laborious procedures, and cannot provide accurate error rates. Recently, NGS-based methods using barcodes opened the possibility of detecting all errors introduced by the RT, although their widespread use is limited by cost, due to the large size of libraries to be sequenced. In this study, we describe a novel and relatively simple NGS assay based on single-strand consensus sequencing that provides robust results with a relatively small number of raw sequences (around 60 Mb). The method has been validated by determining the error rate of HIV-1 (BH10 strain) RT using the HIV-1 protease-coding sequence as target. HIV-1 reverse transcription error rates in standard conditions (37 °C/3 mM Mg2+) using an in vitro-transcribed RNA were around 7.3 × 10−5. In agreement with previous reports, an 8-fold increase in RT’s accuracy was observed after reducing Mg2+ concentration to 0.5 mM. The fidelity of HIV-1 RT was also higher at 50 °C than at 37 °C (error rate 1.5 × 10−5). Interestingly, error rates obtained with HIV-1 RNA from infected cells as template of the reverse transcription at 3 mM Mg2+ (7.4 × 10−5) were similar to those determined with the in vitro-transcribed RNA, and were reduced to 1.8 × 10−5 in the presence of 0.5 mM Mg2+. Values obtained at low magnesium concentrations were modestly higher than the transcription error rates calculated for human cells, thereby suggesting a realistic transcriptional threshold for our NGS-based error rate determinations.

Measuring the Effects of Cognitive Capacity on Sentence Comprehension: Evidence From Elementary School-Age Children.

Our aim was to (a) develop a sentence comprehension measure that distinguished between cognitive capacity and syntactic knowledge in school-age children and (b) examine the relationship between comprehension performance and cognitive variables (working memory capacity and retrieval from long-term memory). We developed and administered a picture selection sentence comprehension task to 122 school-age children representing varied cognitive abilities. We evaluated comprehension accuracy and response time in two syntactically identical conditions but with different cognitive demands incorporated in picture foils-one with low demand using superfluous adjectives and another with high demand using contrastive adjectives. Children also completed tasks measuring working memory capacity and long-term memory retrieval. Comprehension accuracy was significantly lower, and response times were longer in the high-cognitive demand condition compared to the low-demand condition. Errors frequently involved incorrect attribute selection in the high-demand condition that included contrastive adjectives in picture foils, while reversal errors prevailed in the low-demand condition, which included superfluous adjectives. Accuracy correlated positively with the memory variables. Hierarchical regression analysis showed that after adjusting for comprehension in the low-cognitive demand condition (38.60% variance), memory variables accounted for 4.50% additional variance in the high-demand condition with only working memory capacity as the unique predictor. The significant role of working memory capacity in comprehending sentences with high cognitive demand indicated the recruitment of active attention and verbal rehearsal. Data support the newly developed measure's potential for assessing cognitive skills integral to sentence comprehension in school-age children. https://doi.org/10.23641/asha.26767063.

Equivalent Error Based Modelling for Prediction and Analysis of Measuring Accuracy in 3-Axis FXYZ Coordinate Measuring Machines from Position, Repeatability and Reversibility Errors

AbstractThe measuring accuracy of coordinate measuring machines (CMMs) will be affected by the different geometrical and dynamic errors, including the deviations associated to the axis displacement, the working table and the part to be measured. This work is focused on the analysis of the influence of the position errors, repeatability errors and reversibility errors in 3-axis FXYZ coordinate measuring machines, and it will be developed by a numerical model that is known as EE-based stochastic model. This model implements a new error index that is named equivalent error (EE), which will integrate the totality of machine errors of the CMMs and will allow a global description of all these error sources by means of a unique error parameter. The results obtained by this numerical model have been compared with the application of a traditional method, and it was probed that the EE-based model makes possible an increase of a 13.29% in the linear modelling of the performance of CMMs from the machine errors considered in this work, which implies a relevant improvement for the analysis and description of the effect of the distinct error sources on the achievable measuring accuracy of CMMs. For this reason, the EE-based model will be of special interest for industrial applications such as the quality control to be applied inside the production systems dedicated to manufacture mechanical components of high dimensional accuracy.

Optimum error design and 5-axis CNC machining of preloaded roller-gear-cam in roller-drive system

Roller-gear-cam (RG-cam) drive systems in machine tool rotary tables provide enhanced rotation accuracy and superior transmission efficiency due to their preloaded design. However, achieving a controllable preload engagement between the roller and RG-cam requires the use of 5-axis CNC machining using a non-formed tool, which inevitably introduces machining errors. Accordingly, this study proposes a comprehensive method for the design, analysis, and manufacture of a precision RG-cam system on a conventional 5-axis CNC machine tool. Notably, the proposed method enables the machining errors to be controlled and minimized. The feasibility of the proposed approach is demonstrated by machining a prototype roller-drive system on a 5-axis CNC machine. The accuracy of the machined RG-cam is evaluated in accordance with the ISO 230-2 standard. It is shown that the forward and reverse rotational errors of the RG-cam over a single revolution are less than 10 s.

Discrete measurements of RNA polymerase and reverse transcriptase fidelity reveal evolutionary tuning.

Direct methods for determining the fidelity of DNA polymerases are robust, with relatively little sample manipulation before sequencing. In contrast, methods for measuring RNA polymerase and reverse transcriptase fidelities are complicated by additional preparation steps that introduce ambiguity and error. Here, we describe a sequencing method, termed Roll-Seq, for simultaneously determining the individual fidelities of RNA polymerases and reverse transcriptases (RT) using Pacific Biosciences single molecule real-time sequencing. By using reverse transcriptases with high rolling-circle activity, Roll-Seq generates long concatemeric cDNA from a circular RNA template. To discern the origin of a mutation, errors are recorded and determined to occur within a single concatemer (reverse transcriptase error) or all concatemers (RNA polymerase error) over the cDNA strand. We used Roll-Seq to measure the fidelities of T7 RNA polymerases, a Group II intron-encoded RT (Induro), and two LINE RTs (Fasciolopsis buski R2-RT and human LINE-1). Substitution rates for Induro and R2-RT are the same for cDNA and second-strand synthesis while LINE-1 has 2.5-fold lower fidelity when performing second-strand synthesis. Deletion and insertion rates increase for all RTs during second-strand synthesis. In addition, we find that a structured RNA template impacts fidelity for both RNA polymerase and RT. The accuracy and precision of Roll-Seq enable this method to be applied as a complementary analysis to structural and mechanistic characterization of RNA polymerases and reverse transcriptases or as a screening method for RNAP and RT fidelity.

Mirror invariance in the subsequent acquisition of a script with separate forms for reading and writing

PurposeDoes suppression of mirror-invariance in one script generalize to a subsequently learned script? MethodWe examined mirror invariance in writing and recognition among native Latin-scriptal children and adults (n = 181) learning the Hebrew print script (for reading), and among a subset (n = 92) also learning the Hebrew cursive script (for writing). Hebrew-Latin biscriptal Israeli adults (n = 17) provided comparison. ResultsFor the most part, mirror invariance was more evident in Hebrew print than in Latin in both writing and recognition among native Latin-scriptals. The number of previously acquired scripts had no effect. Letters’ text-frequency inversely affected written mirror-error frequency. Written reversal errors were less frequent in cursive; orientation recognition was more fluent in print. ConclusionsMirror-invariance suppression in one's native script does not generalize to a subsequently acquired script. Factors affecting mirror-invariance suppression in the subsequent script include its form and function and individual letters’ text-frequency.

Comprehension of Ditransitive Constructions in Mandarin-Speaking Children with Developmental Language Disorder and Children with Autism Spectrum Disorder Plus Language Impairment.

This study examined and compared the comprehension of Mandarin ditransitive constructions in children with developmental language disorder (DLD) and children with autism spectrum disorder plus language impairment (ALI). Eighteen children with DLD, 17 children with ALI, and 27 age-matched typically developing (TDA) children, participated in a sentence-picture matching task on four patterns of Mandarin ditransitive constructions. Both children with DLD and children with ALI received significantly lower accuracy than TDA children in general and their most common errors were thematic role reversals. However, while children with ALI evinced a generalized deficit in all four patterns, only the comprehension of S1 (Subj. + Vgei + IO + DO) and S3 (Subj. + gei + IO + V + DO) was affected in children with DLD, with that of S2 (Subj. + V + DO + gei + IO) and S4 (Subj. + V + IO + DO) preserved in this population. Additionally, thematic role reversal errors were more dominant in children with DLD than in children with ALI who also committed a relatively higher proportion of Wrong Theme and No Recipient errors. It is concluded thatthe primary deficit of children with DLD lies in representing dependent relationships between the arguments and the verb as involved in thematic role assignment, but this is less critical in children with ALI, with their performance on the comprehension task possibly also related to other factors associated with the condition. To enhance the development of ditransitive constructions, intervention efforts for children with DLD and children with ALI could focus on strengthening the connection between each argument and its thematic role.

Dynamical Gaussian, lognormal, and reverse lognormal maximum‐likelihood ensemble filter

AbstractWe present a non‐Gaussian ensemble data assimilation method based on the maximum‐likelihood ensemble filter, which allows for any combination of Gaussian, lognormal, and reverse lognormal errors in both the background and the observations. The technique is fully nonlinear, does not require a tangent linear model, and uses a Hessian preconditioner to minimise the cost function efficiently in ensemble space. When the Gaussian assumption is relaxed, the results show significant improvements in the analysis skill within two atmospheric toy models, and the performance of data assimilation systems for (semi)bounded variables is expected to improve.

Frequency-dependent component of AC-DC transfer difference of a redesigned calorimetric thermal converter

This article presents an analysis of the frequency-dependent component of the AC-DC transfer difference of a calorimetric thermal voltage converter (CTVC) with substantially reduced DC reversal error. It contains an analysis of the effect of this reduction on the AC-DC transfer difference. The analysis was based on the mathematical model of a CTVC waveguide, which was extended by estimation of the residual parameters of the CTVC heater (microwave rod resistor) using the finite element method (FEM). The results of the analysis were validated by laboratory measurements. The article also contains the uncertainty budget of the AC-DC transfer difference of the new CTVC. Despite its high thermal time constant, the CTVC is currently one of the most accurate AC voltage standards in the frequency range from 1 to 100 MHz.

Tool path design for cube-machining test to minimize influence of Z-axis reversal error motion

Tool path design for cube-machining test to minimize influence of Z-axis reversal error motion

The comprehension of passives in Mandarin children with and without DLD: from the perspective of Edge Feature Underspecification Hypothesis

AbstractThis paper investigates the comprehension of long and short passives in 15 Mandarin preschool children with Developmental Language Disorder (DLD) (aged 4;2–5;11 years), 15 Typically Developing Age-matched (TDA) (aged 4;3–5;8 years) children, and 15 Typically Developing Younger (TDY) (aged 3;2–4;3 years) children by using the picture-sentence matching task. The results reveal that children with DLD encounter more difficulty comprehending long passives compared with short passive, that they perform worse on the comprehension task than TDA children and TDY children, and that this population is more likely to commit thematic role reversal errors and point to pictures with the incorrect agent (patient) than typically developing children. Given that Mandarin passives are Topic Structures, we maintain that children with DLD are insensitive to the edge feature of the moved element in long passives, leading to Relativized Minimality effect and causing the asymmetry between the comprehension of long and short passives. These results align well with the Edge Feature Underspecification Hypothesis. Errors found in the children with DLD in the comprehension task point toward impaired syntactic knowledge and the lexical semantic deficit.

Development and Human Factors Evaluation of a Portable Auditory Localization Training System.

To design and develop a Portable Auditory Localization Acclimation Training (PALAT) system capable of producing psychoacoustically accurate localization cues; evaluate the training effect against a proven full-scale, laboratory-grade system under three listening conditions; and determine if the PALAT system is sensitive to differences among electronic level-dependent hearing protection devices (HPDs). In-laboratory auditory localization training has demonstrated the ability to improve localization performance with the open (natural) ear, that is, unoccluded, and while wearing HPDs. The military requires a portable system capable of imparting similar training benefits as those demonstrated in laboratory experiments. In a full-factorial repeated measures design experiment, 12 audiometrically normal participants completed localization training and testing using an identical, optimized training protocol on two training systems under three listening conditions (open ear, TEP-100, and ComTac™ III). Statistical tests were performed on mean absolute accuracy score and front-back reversal errors. No statistical difference existed between the PALAT and laboratory-grade DRILCOM systems on two dependent localization accuracy measurements at all stages of training. In addition, the PALAT system detected the same localization performance differences among the three listening conditions. The PALAT system imparted similar training benefits as the DRILCOM system and was sensitive to HPD localization performance differences. The user-operable PALAT system and optimized training protocol can be employed by the military, law enforcement, and various industries, to improve auditory localization performance in conditions where auditory situation awareness is critical to safety.

Measuring “Where”: A Comparative Analysis of Methods Measuring Spatial Perception

The literature offers various methods for measuring sound localization. In this study, we aimed to compare these methods to determine their effectiveness in addressing different research questions by examining the effect sizes obtained from each measure. Data from 150 participants who identified the location of a sound source were analyzed to explore the effects of speaker angle, stimuli, HPD type, and condition (with/without HPD) on sound localization, using six methods for analysis: mean absolute deviation (MAD), root-mean-squared error (RMSE), very large errors (VLE), percentage of errors larger than the average error observed in a group of participants (pMean), percentage of errors larger than half the distance between two consecutive loudspeakers (pHalf), and mirror image reversal errors (MIRE). Results indicated that the MIRE measure was the most sensitive to the effects of speaker angle and HPD type, while the VLE measure was most sensitive to the effect of stimuli type. The condition variable provided the largest effect sizes, with no difference observed between measures. The data suggest that when effect sizes are substantial, all methods are adequate. However, for cases where the effect size is expected to be small, methods that yield larger effect sizes should be considered, considering their alignment with the research question.

A dynamical Gaussian, lognormal, and reverse lognormal Kalman filter

AbstractWe derive a generalization of the Kalman filter that allows for non‐Gaussian background and observation errors. The Gaussian assumption is replaced by considering that the errors come from a mixed distribution of Gaussian, lognormal, and reverse lognormal random variables. We detail the derivation for reverse lognormal errors and extend the results to mixed distributions, where the number of Gaussian, lognormal, and reverse lognormal state variables can change dynamically every analysis time. We test the dynamical mixed Kalman filter robustly on two different systems based on the Lorenz 1963 model, and demonstrate that non‐Gaussian techniques generally improve the analysis skill if the observations are sparse and uncertain, compared with the Gaussian Kalman filter.

A tRNA modification in Mycobacterium tuberculosis facilitates optimal intracellular growth.

Diverse chemical modifications fine-tune the function and metabolism of tRNA. Although tRNA modification is universal in all kingdoms of life, profiles of modifications, their functions, and physiological roles have not been elucidated in most organisms including the human pathogen, Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis. To identify physiologically important modifications, we surveyed the tRNA of Mtb, using tRNA sequencing (tRNA-seq) and genome-mining. Homology searches identified 23 candidate tRNA modifying enzymes that are predicted to create 16 tRNA modifications across all tRNA species. Reverse transcription-derived error signatures in tRNA-seq predicted the sites and presence of nine modifications. Several chemical treatments prior to tRNA-seq expanded the number of predictable modifications. Deletion of Mtb genes encoding two modifying enzymes, TruB and MnmA, eliminated their respective tRNA modifications, validating the presence of modified sites in tRNA species. Furthermore, the absence of mnmA attenuated Mtb growth in macrophages, suggesting that MnmA-dependent tRNA uridine sulfation contributes to Mtb intracellular growth. Our results lay the foundation for unveiling the roles of tRNA modifications in Mtb pathogenesis and developing new therapeutics against tuberculosis.

A tRNA modification in Mycobacterium tuberculosis facilitates optimal intracellular growth

Diverse chemical modifications fine-tune the function and metabolism of tRNA. Although tRNA modification is universal in all kingdoms of life, profiles of modifications, their functions, and physiological roles have not been elucidated in most organisms including the human pathogen, Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis. To identify physiologically important modifications, we surveyed the tRNA of Mtb, using tRNA sequencing (tRNA-seq) and genome-mining. Homology searches identified 23 candidate tRNA modifying enzymes that are predicted to create 16 tRNA modifications across all tRNA species. Reverse transcription-derived error signatures in tRNA-seq predicted the sites and presence of nine modifications. Several chemical treatments prior to tRNA-seq expanded the number of predictable modifications. Deletion of Mtb genes encoding two modifying enzymes, TruB and MnmA, eliminated their respective tRNA modifications, validating the presence of modified sites in tRNA species. Furthermore, the absence of mnmA attenuated Mtb growth in macrophages, suggesting that MnmA-dependent tRNA uridine sulfation contributes to Mtb intracellular growth. Our results lay the foundation for unveiling the roles of tRNA modifications in Mtb pathogenesis and developing new therapeutics against tuberculosis.

Chaos Detection by Fast Dynamic Indicators in Reflecting Billiards.

The propagation of electromagnetic waves in a closed domain with a reflecting boundary amounts, in the eikonal approximation, to the propagation of rays in a billiard. If the inner medium is uniform, then the symplectic reflection map provides the polygonal rays' paths. The linear response theory is used to analyze the stability of any trajectory. The Lyapunov and reversibility error invariant indicators provide an estimate of the sensitivity to a small initial random deviation and to a small random deviation at any reflection, respectively. A family of chaotic billiards is considered to test the chaos detection effectiveness of the above indicators.

Modeling of a neural network-based system for identification and control of technical object parameters

The article analyzes the effectiveness of a neural network control system for main-taining the pH level in the feedwater of a steam boiler. An intelligent control system im-plements the principle of reverse error propagation through a neural emulator. The sub-system model of steam boiler water tube blowing was used as the research object. The neural network controller and neural emulator were trained on a control system model with a PID controller using the expert correction methodology of tuning coefficients: proportionality, integration constant, and differentiation based on the analysis of tran-sient process quality indicators. The analysis of the transient processes obtained from simulation modeling allows us to state that the trained neural network control system successfully compensates for disturbances over a wide range of changes in the object's parameter values via control channels and disturbances (simulating changes in steam load).