Low Rank Research Articles

MIMt: a curated 16S rRNA reference database with less redundancy and higher accuracy at species-level identification

MotivationAccurate determination and quantification of the taxonomic composition of microbial communities, especially at the species level, is one of the major issues in metagenomics. This is primarily due to the limitations of commonly used 16S rRNA reference databases, which either contain a lot of redundancy or a high percentage of sequences with missing taxonomic information. This may lead to erroneous identifications and, thus, to inaccurate conclusions regarding the ecological role and importance of those microorganisms in the ecosystem.ResultsThe current study presents MIMt, a new 16S rRNA database for archaea and bacteria’s identification, encompassing 47 001 sequences, all precisely identified at species level. In addition, a MIMt2.0 version was created with only curated sequences from RefSeq Targeted loci with 32 086 sequences. MIMt aims to be updated twice a year to include all newly sequenced species. We evaluated MIMt against Greengenes, RDP, GTDB and SILVA in terms of sequence distribution and taxonomic assignments accuracy. Our results showed that MIMt contains less redundancy, and despite being 20 to 500 times smaller than existing databases, outperforms them in completeness and taxonomic accuracy, enabling more precise assignments at lower taxonomic ranks and thus, significantly improving species-level identification.

Systematic Review of Dimensions and Indicators in Sustainable and Smart Cities: Trends, Interdependencies, and Continental Variations

Accelerated urbanization challenges cities globally. Ensuring good quality of life and environmental protection requires innovative, data-driven solutions. Sustainable and smart cities (SSCs) offer a promising response, but effective implementation depends on selecting and using appropriate dimensions and indicators. The main objective of this article is to present a systematic review within the framework of SSCs to study trends in the use of dimensions and indicators. A citation frequency index (Q) considering quartiles is used to determine the importance of the variables considered in this study. A spatiotemporal analysis of the dimensions and indicators detected is also performed. The results suggest that the multifaceted nature of SSCs necessitates a holistic approach, with environmental (Q3 = 0.536) and social (Q2 = 0.403) dimensions being principal. Despite the lower ranking (Q1 = 0.080) of the information and communication technology (ICT) dimension, its pervasive influence highlights its evolving importance. Effective ICT implementation relies on robust social and environmental foundations, illustrating their interdependence. The governance (Q1 = 0.169) dimension is also essential for the creation of transparent and equitable urban policies. Key indicators related to energy systems (Q2 = 0.379), data analysis (Q2 = 0.327), and resource management (Q2 = 0.291) are crucial for operational efficiency and sustainability. Continental differences in prioritizing SSC dimensions highlight the importance of context-specific strategies, reflecting unique challenges and opportunities faced by different continental areas. By understanding and addressing these continental differences, policymakers and urban planners can more effectively promote sustainable and resilient urban development worldwide.

From Neopatrimonial Science to Consumption of Academic Degrees: The Case of Political Science in Ukraine

Abstract This paper is devoted to the transformation of the practices of obtaining academic degrees in Ukraine by applicants from outside the Academy. My hypothesis is that neopatrimonial science, political regime, and credentialism have led to consumption of academic degrees in Ukraine. It is a socially and politically selective process, where the initial pattern is established by the reference groups of top officials. This pattern is subsequently copied and reproduced by lower ranks. It is related to (economically) favorable conditions contributing to the transfer of academic regalia from the category of luxury goods to objects of mass consumption. This process has its own specific features for different groups of applicants from outside the Academy, where the significant factors are the applicant’s position and its rank, regional structure of the political regime, and gender. The empirical basis of the work was: (a) career patterns of 642 former and current governors and/or heads of Regional Councils during 1992–2024; (b) 1,735 candidate (PhD) theses in political science defended during 1999–2024.

Non-supersymmetric heterotic strings and chiral CFTs

Non-supersymmetric heterotic strings share various properties with their supersymmetric counterparts. Torus compactifications of the latter live in a component of the moduli space of string vacua with 16 supercharges, and various asymmetric orbifolds thereof realize vacua in other components, exhibiting qualitative differences such as rank reduction. We set out to study the analogous problem for non-supersymmetric heterotic strings, framing it in relation to chiral fermionic CFTs with central charge 24, which were classified recently. We find that for the case analogous to the so-called CHL string, which has gauge group rank reduced by 8, there are in total four non-supersymmetric versions. These include the well known E8 string and three other constructions a la CHL, which can be distinguished qualitatively by how tachyons appear in their classical moduli spaces. We also discuss the classification problem for lower rank theories and the relationship between MSDS models and Scherk-Schwarz reductions.

The gendered effects of parenthood on career outcomes: Do family gaps explain gender differences along the science pipeline?

This study, based on data from 2225 faculty members at a Portuguese research-intensive university, investigates the combined impact of gender and parental status on academic rank and salary. Parenthood significantly influences women's concentration at lower tenure-track ranks, leading to wage gaps that disadvantage mothers. However, the impact of family status on women's career progression shows that while having young children initially hinders their transition to the tenure track, it does not significantly reduce their chances of earning tenure or reaching higher academic ranks. Lower wages for mothers result from slower academic grade advancement, not within-rank disparities, which poses barriers to progression. The study illuminates the interplay of gender and parenthood, shifting the focus from individual factors to gendered institutional processes shaping career trajectories, providing valuable insights into the mechanisms underlying the persistent gender gap in academia.

Exploring online health information quality criteria on social media: a mixed method approach

PurposeThis article outlines a research study that ranked health information quality criteria on social media from experts’ perspectives.MethodologyA mixed-method approach (qualitative-quantitative) used in current research. In the qualitative phase a literature review explored existing dimensions for evaluating social media content quality, focusing on identifying common dimensions and attributes. Furthermore, a quantitative method involving experts was utilized to rank the health information quality criteria for social media.ResultsThe findings indicated various dimensions of health information quality in the literature. Out of 17 criteria, accuracy, credibility, and reliability had the highest ranks, while originality, value-added, and amount of data had the lowest ranks, respectively, according to experts.ConclusionThe endeavor to bolster the dissemination of reliable health information on social media demands a sustained commitment to enhancing accountability, transparency, and accuracy, ensuring that users have access to information that is not only informative but also trustworthy.

Hybrid plug-and-play CT image restoration using nonconvex low-rank group sparsity and deep denoiser priors

Abstract Objective. Low-dose computed tomography (LDCT) is an imaging technique that can effectively help patients reduce radiation dose, which has attracted increasing interest from researchers in the field of medical imaging. Nevertheless, LDCT imaging is often affected by a large amount of noise, making it difficult to clearly display subtle abnormalities or lesions.
Therefore, this paper proposes a multiple complementary priors CT image reconstruction method by simultaneously considering both the internal prior and external image information of CT images, thereby enhancing the reconstruction quality of CT images.
Approach. Specifically, we propose a CT image reconstruction method based on weighted nonconvex low-rank regularized group sparse and deep image priors under hybrid plug-and-play framework by utilizing the weighted nonconvex low rankness and group sparsity of dictionary domain coefficients of each group of similar patches, and a convolutional neural network (CNN) denoiser.
To make the proposed reconstruction problem easier to tackle, we utilize the Alternate Direction Method of Multipliers (ADMM) for optimization.Main results. To verify the performance of the proposed method, we conduct detailed simulation experiments on the images of the abdominal, pelvic, and thoracic at projection views of 45, 65, and 85, and at noise levels of 1×10^5 and 1×10^6, respectively. A large number of qualitative and quantitative experimental results indicate that the proposed method has achieved better results in texture preservation and noise suppression compared to several existing iterative reconstruction methods.
Significance. The proposed method fully considers the internal nonlocal low rankness and sparsity, as well as the external local information of CT images, providing a more effective solution for CT image reconstruction. Consequently, this method enables doctors to diagnose and treat diseases more accurately by reconstructing high-quality CT images.

Comparative efficacy of colchicine and intensive LDL-C lowering in patients with ASCVD receiving statins: a network meta-analysis of randomised controlled trials

Abstract Background Adding intensive low-density lipoprotein cholesterol (LDL-C) lowering treatments or colchicine to statins resulted in additional cardiovascular benefits. However, the relative efficacy and priority of these agents are unclear. Purpose We aimed to compare the effects of these supplementary agents on cardiovascular outcomes in patients with atherosclerotic cardiovascular diseases (ASCVD) receiving statins. Methods We performed a systematic review and frequentist network meta-analysis on randomized controlled trials. The primary efficacy endpoint was the main adverse cardiovascular event (MACE), and the secondary efficacy endpoints were myocardial infarct, stroke, coronary revascularization, cardiovascular death and all-cause mortality. The safety endpoints were treatment discontinuation and non-cardiovascular death. Colchicine was used as reference treatment. Random-effects model was used in case of high heterogeneity, the fixed-effects model was preferred otherwise. We ranked the comparative effects of all drugs with surface under the cumulative ranking (SUCRA) probabilities. Results 17 trials totaling 85823 participants treated with colchicine, proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor, Niemann-Pick C1-like 1 protein (NPC1L1) inhibitor and ATP citrate lyase (ACL) inhibitor were included. Compared with colchicine, NPC1L1 inhibitor was associated with increased risk of MACE (risk ratio [RR]: 1.39, 1.21-1.59), stroke (RR: 1.81, 1.09-3.00) and coronary revascularization (RR: 1.36, 1.11-1.68), and PCSK9 inhibitor was associated with increased risk of MACE (RR: 1.27, 1.10-1.46). However, NPC1L1 inhibitor (RR: 0.68, 0.48-0.96) and PCSK9 inhibitor (RR: 0.64, 0.44-0.93) were associated with reduced risk of non-cardiovascular death in comparison to colchicine. PCSK9 inhibitors had a lower risk of MACE (RR: 0.91, 95% CI: 0.85-0.98) and coronary revascularization (RR: 0.89, 95% CI: 0.81-0.97) compared with NPC1L1 inhibitor. Although no regimen prolonged survival, colchicine had the lowest rank at non-cardiovascular death and the worse performance on all-cause mortality. Conclusions In patients with ASCVD receiving statins, inflammation-inhibiting with colchicine seems to be superior to intensive LDL-C lowering therapy with PCSK9 inhibitor or NPC1L1 inhibitor in cardiovascular prevention. However, using colchicine as an alternative to intensive lipid-lowering therapy may need to be weighed against the greater cardiovascular benefits and the potential harms of higher non-cardiovascular death. Given the worse performance of colchicine on survival based on current evidence, colchicine may be more appropriate for patients who have been treated with intensive LDL-C-lowering agents but still have recurrent cardiovascular events.Forest plots of included agentsRadar plot of treatments based on SUCRA

Integrating E-Scooters into Urban Transportation: Issues, Policies, and Opportunity for System Change

Consider a kick scooter with a broad and low floor, broad wheels, and cancellation if ride reassurance and satisfaction are your top priorities. Choose a kick scooter with big casters, a low deck, a low overall weight, exceptional bearings, preferable without being suspended, if efficiency and speed are priorities. No need to be a licenced driver. Use with little exertion. Electric scooters are friendly to the economy. zero noise disturbance. Brushless DC Motors, often known as BLDC, are a more recent invention with superior capability to DC brushed motors. In general, brushless motors are more powerful, run longer, are more energy-efficient, don't overheat as quickly, and are cleaner. An extremely common e-scooter choice is a brushed motor. The bare maximum motor power for an adult electronic scooter is 250 watts. This power allows a scooter to travel over flat terrain and slight inclines without discomfort. Motors of 400 to 500 watts should be taken into consideration by those who intend to push their scooters up severe inclines. Alternative: Battery Capacity (kWh), Range (km), Top Speed (kmph), and Price (in thousand rupees), Charging Time (hours). Evaluation Preference: Ola S1, TVS iQube Electric, Ather 450X, Hero Electric Photon, Bajaj Chetak, Okinawa Ridge Plus, Simple One, Bounce Infinity E1, Hero Electric Optima CX, Ampere V48. “From the result it is seen that Simple One and is got the first rank whereas is the Ather 450X got is having the lowest rank”4. “The value of the dataset for Drilling engineers in MOORA (Multi-objective Optimization on the basis of Ratio Analysis) shows that it results in Insect layer and top ranking”.

On Hidden Rank Deficiency in MCR Problems

ABSTRACTPure component decomposition problems in chemometrics can be classified into rank‐regular and rank‐deficient problems. Rank‐deficient problems are characterized by a spectral data matrix that has a lower rank than the number of chemical species. However, it is possible that there exists rank‐regular factorization of the spectral data matrix, but none of these solutions can be interpreted chemically, and only a solution of the MCR problem with rank deficiency is chemically meaningful. Then we say that the underlying problem suffers from a hidden rank deficiency. In this paper, MCR problems with hidden rank deficiency are introduced and analyzed with several examples for problems of rank 2 and rank 3. The area of feasible solutions is determined with the help of additional constraints on the solution.

Native Faculty in Library and Information Science, 1990–2022

We assessed the representation of Native faculty in LIS programs from 1990 to 2022. We comparative representation in LIS against trends in postsecondary education in the U.S. We utilized ALISE and federal data sources. We found that in both fields, Native faculty held lower ranking positions, predominantly as assistant professors. We also revealed that the quantity of Native LIS faculty was extremely low throughout the period assessed, with the possibility of a very few outlier LIS programs driving national statistics. Our study suggests that factors affecting representation of Native faculty in LIS might be similar to those in postsecondary education.

Tatars in the regular army during the Patriotic War of 1812 and the foreign campaigns of 1813–1814

One of the topical issues of historical science in the Russian Federation is the analysis and popularization of historical information about the participation of the peoples of the country in military campaigns to protect the Fatherland from foreign intervention. The purpose of the study is to tell about the service of Tatars, both officers and lower ranks, in the regular army during the Patriotic War of 1812 and the foreign campaigns of 1813–1814. Actualization of interest to the military history of the Tatar people during the period of the Russian Empire as a whole, with the search and bringing into the public space the names of heroes and participants of military campaigns, is also one of the tasks of this study. The leading method in studying this problem was an integrated approach based on the study of different types of sources. Research materials: the work involves special historical research (monographs and scientific articles), published and unpublished historical sources of the first quarter of the 19th century, reference publications. Results and scientific novelty of the work: the facts of the service of the Tatar people in the regular army during the Patriotic War of 1812 and the foreign campaigns of 1813–1814 have been established, the personalities of Tatar officers, both from among the nobility and from the lower ranks, as well as soldiers and sailors from the Tatars who served in the regular army have been identified. Biographies of veterans of the Patriotic War of 1812 and the foreign campaigns of 1813–1814 from the Tatars are given. For citation: Abdullin Kh.M. Tatars in the regular army during the Patriotic War of 1812 and the foreign campaigns of 1813–1814. From History and Culture of Peoples of the Middle Volga Region. 2024, vol.14, no.3, pp.96–107. https://doi.org/10.22378/2410-0765.2024-14-3.96-107

ANALISIS PENGARUH SIKAP PETERNAK TERHADAP KEMAMPUAN BERWIRAUSAHA PENGGEMUKAN DAN PEMBIBITAN SAPI DI KECAMATAN PADEMAWU KABUPATEN PAMEKASAN

Pamekasan Regency has the lowest cattle population in Madura, 194,283 heads. The attitude of farmers who have an important role in the cattle business. This study aims to determine 1) the entrepreneurial characteristics of farmers, 2) the attributes of the dominant attitudes of farmers, and 3) the relationship between the attitudes of farmers and their entrepreneurial abilities in Pademawu District, Pamekasan Regency. The method used is descriptive quantitative, using secondary and primary data from 35 cattle breeders. This study uses a descriptive analysis and multi-attribute Fishbein. The results of this study indicate that 1) the entrepreneurial characteristics of breeders are still common, and their entrepreneurial skills are still low; 2) the dominant attitude of farmers in entrepreneurship is the selling price of farmers, while the attitude that has the lowest rank is maintenance; 3) the relationship between attitudes and abilities in entrepreneurship of breeders is said to be quite close, entrepreneurial attitudes of breeders such as motivation, yield orientation, risk-taking, opportunity utilization and perceptions of livestock business are not dominant attributes, but have a large enough effect. Cattle breeders in Pademawu District need counseling about maintenance risks, financial management, opportunity utilization, yield orientation, and increased motivation.

Toward Centrality Evaluation of Yearning Symptoms for Prolonged Grief Disorder: A Cross-Cultural Approach

Background: The new ICD-11 diagnosis of prolonged grief disorder (PGD) is characterized by the prominent role of yearning as hallmark symptom. A secondary analysis of eight international datasets on PGD was conducted to evaluate this assumption. Additionally, cross-cultural comparison explored whether the centrality of yearning differs across world regions. Methods: Primary studies originated from German-speaking countries (n = 4 samples), other European countries and Israel (n = 3 samples), as well as China (n = 1 samples). Different PGD measures were used, including yearning and longing as symptoms. For the centrality assessment of yearning, PGD symptoms were ranked by their factor loadings from confirmatory factor analyses, followed by statistical testing to determine significant differences between yearning and other symptoms of PGD in their factor loading estimates. Subsequently, ranking positions of yearning in three world regions (German-speaking, other Europe-Israel, and China) were compared. Finally, proxy thresholds for individuals at high-risk states for PGD were defined for the different datasets, and sensitivity-specificity analyses of yearning were performed. Results: Yearning was ranked high in five out of 12 models tested. In the German-speaking region, it was predominantly ranked among the most central symptoms; in the other Europe-Israel region as well as China, it tended to fall into the middle or lower rankings of symptom centrality. Sensitivity values were consistently high, while specificity values indicated moderate levels. Discussion: In line with previous research on the general outcomes of grief, the present study showed that yearning may be subject to a culture-specific distribution. Other central symptoms such as feeling as if a part of oneself died have also been shown to potentially play a central role in PGD across world regions. On the other hand, the sensitivity-specificity analyses revealed that yearning can be considered a significant (diagnostically highly sensitive) symptom for individuals in high-risk states for PGD, although it has only moderate specificity (i.e., its absence does not necessarily indicate individuals experiencing normative grief). Nonetheless, a culture-sensitive approach to psychopathology should consider the cultural differences in the centrality of this symptom group. More research is needed to better understand the role of yearning and its determinants across world regions.

Investigating deep learning strategies for fast denoising of 5D cardiac photon-counting micro-CT images


Photon-counting detectors (PCDs) for CT imaging use energy thresholds to simultaneously acquire projections at multiple energies, making them suitable for spectral imaging and material decomposition. Unfortunately, setting multiple energy thresholds results in noisy analytical reconstructions due to low photon counts in high-energy bins. Iterative reconstruction provides high quality photon-counting CT (PCCT) images but requires enormous computation time for 5D (3D + energy + time) in vivo cardiac imaging. 

Approach. 
We recently introduced UnetU, a deep learning (DL) approach that accurately denoises axial slices from 4D (3D + energy) PCCT reconstructions at various acquisition settings. In this study, we explore UnetU configurations for 5D cardiac PCCT denoising, focusing on singular value decomposition (SVD) modifications along the energy and time dimensions and alternate network architectures such as 3D U-net, FastDVDNet, and Swin Transformer UNet. We compare our networks to multi-energy non-local means (ME NLM), an established PCCT denoising algorithm. 

Main results. 
Our evaluation, using real mouse data and the digital MOBY phantom, revealed that all DL methods were more than 16 times faster than iterative reconstruction. DL denoising with SVD along the energy dimension was most effective, consistently providing low root mean square error and spatio-temporal reduced reference entropic difference, alongside strong qualitative agreement with iterative reconstruction. This superiority was attributed to lower effective rank along the energy dimension than the time dimension in 5D cardiac PCCT reconstructions. ME NLM sometimes outperformed DL with time SVD or time and energy SVD, but lagged behind iterative reconstruction and DL with energy SVD. Among alternate DL architectures with energy SVD, none consistently outperformed UnetU Energy (2D). 

Significance. 
Our study establishes UnetU Energy as an accurate and efficient method for 5D cardiac PCCT denoising, offering a 32-fold speed increase from iterative reconstruction. This advancement sets a new benchmark for DL applications in cardiovascular imaging.

Tensor Completion Using Bilayer Multimode Low-Rank Prior and Total Variation.

In this article, we propose a novel bilayer low-rankness measure and two models based on it to recover a low-rank (LR) tensor. The global low rankness of underlying tensor is first encoded by LR matrix factorizations (MFs) to the all-mode matricizations, which can exploit multiorientational spectral low rankness. Presumably, the factor matrices of all-mode decomposition are LR, since local low-rankness property exists in within-mode correlation. In the decomposed subspace, to describe the refined local LR structures of factor/subspace, a new low-rankness insight of subspace: a double nuclear norm scheme is designed to explore the so-called second-layer low rankness. By simultaneously representing the bilayer low rankness of the all modes of the underlying tensor, the proposed methods aim to model multiorientational correlations for arbitrary N -way ( N ≥ 3 ) tensors. A block successive upper-bound minimization (BSUM) algorithm is designed to solve the optimization problem. Subsequence convergence of our algorithms can be established, and the iterates generated by our algorithms converge to the coordinatewise minimizers in some mild conditions. Experiments on several types of public datasets show that our algorithm can recover a variety of LR tensors from significantly fewer samples than its counterparts.

Robust Low-Tubal-Rank Tensor Completion Based on Tensor Factorization and Maximum Correntopy Criterion.

The goal of tensor completion is to recover a tensor from a subset of its entries, often by exploiting its low-rank property. Among several useful definitions of tensor rank, the low tubal rank was shown to give a valuable characterization of the inherent low-rank structure of a tensor. While some low-tubal-rank tensor completion algorithms with favorable performance have been recently proposed, these algorithms utilize second-order statistics to measure the error residual, which may not work well when the observed entries contain large outliers. In this article, we propose a new objective function for low-tubal-rank tensor completion, which uses correntropy as the error measure to mitigate the effect of the outliers. To efficiently optimize the proposed objective, we leverage a half-quadratic minimization technique whereby the optimization is transformed to a weighted low-tubal-rank tensor factorization problem. Subsequently, we propose two simple and efficient algorithms to obtain the solution and provide their convergence and complexity analysis. Numerical results using both synthetic and real data demonstrate the robust and superior performance of the proposed algorithms.

FuBay: An Integrated Fusion Framework for Hyperspectral Super-Resolution Based on Bayesian Tensor Ring.

Fusion with corresponding finer-resolution images has been a promising way to enhance hyperspectral images (HSIs) spatially. Recently, low-rank tensor-based methods have shown advantages compared with other kind of ones. However, these current methods either relent to blind manual selection of latent tensor rank, whereas the prior knowledge about tensor rank is surprisingly limited, or resort to regularization to make the role of low rankness without exploration on the underlying low-dimensional factors, both of which are leaving the computational burden of parameter tuning. To address that, a novel Bayesian sparse learning-based tensor ring (TR) fusion model is proposed, named as FuBay. Through specifying hierarchical sprasity-inducing prior distribution, the proposed method becomes the first fully Bayesian probabilistic tensor framework for hyperspectral fusion. With the relationship between component sparseness and the corresponding hyperprior parameter being well studied, a component pruning part is established to asymptotically approaching true latent rank. Furthermore, a variational inference (VI)-based algorithm is derived to learn the posterior of TR factors, circumventing nonconvex optimization that bothers the most tensor decomposition-based fusion methods. As a Bayesian learning methods, our model is characterized to be parameter tuning-free. Finally, extensive experiments demonstrate its superior performance when compared with state-of-the-art methods.

Clinicopathological Insights to the Nerve Growth Factor NGF Associated Stress Response in Pregnancy and Therapeutic Potential in Fetal Neurodevelopment

The nerve growth factor has a significant role in fetal neurogenesis and sustaining pregnancy. Objectives: To investigate the effects of nerve growth factor in stress response during pregnancy on developing fetus to bring clinicopathological correlation on the role of nerve growth factor in maternal stress markers (cortisol levels, glucocorticoids, depression, anxiety, and brain-derived neurotrophic factor levels) and fetal brain development. Methods: Following PRISMA guidelines, this study was extracted from PubMed, ScienceDirect, Nature, and Google Scholar articles from January 2014 to April 2024. The examination of pregnant women in published research gave a possibility to understand the application of nerve growth factor as a suitable biomarker for brain stress and fetal neuronal development. To exclude studies with lower ranks, each of the selected studies was assessed for adherence to evidence-based research methodology. The studies were taken from China, Europe, America and South Asia (including Pakistan). Results: Increased nerve growth factor levels were associated with maternal stress reactions which caused changes in cortisol levels and the amygdaloidal complex area. However, the increased nerve growth factor level was linked to changes in the fetal brain such as the weight of the fetal brain and stress biomarkers in the amniotic fluid sample inferring a critical role in the modulation of maternal stress on the fetal neurodevelopmental spheres. Conclusions: It was concluded that it is important to note how stress and nerve growth factors interact during pregnancy to create effective interventions to reduce stress dependence for the better health of both the mother and child.

Fast Candidate Screening for Post-diagnosis Refinement

Oftentimes fault candidates produced by logic diagnosis are too many to effectively guide the follow-on failure analysis. In this work, we propose a novel two-stage fast screening method to sift through large amount of candidates in the fault callout outputted by the commercial diagnosis tool. Candidates that are unlikely to be true ones are re-assigned lower ranks or discarded as diagnosis noise. Experimental results based on benchmark designs from various sources show that within the new categorical ranking list, the number of remaining candidates is only 53.78% of the original ones produced by the diagnosis tool, while ensuring an average accuracy of 91.65%, leading to a 1.98 × increase in diagnostic resolution. Our fast screening method only takes seconds of model training and computation, while using no other additional resource besides necessary inputs for generic logic diagnosis.