On-machine surface defect detection using light scattering and deep learning

This paper presents an on-machine surface defect detection system using light scattering and deep learning. A supervised deep learning model is used to mine the information related to defects from light scattering patterns. A convolutional neural network is trained on a large dataset of scattering patterns that are predicted by a rigorous forward scattering model. The model is valid for any surface topography with homogeneous materials and has been verified by comparing with experimental data. Once the neural network is trained, it allows for fast, accurate and robust defect detection. The system capability is validated on micro-structured surfaces produced by ultra-precision diamond machining

Responsible AI Considerations in Text Summarization Research: A Review of Current Practices

AI and NLP publication venues have increasingly encouraged researchers to reflect on possible ethical considerations, adverse impacts, and other responsible AI issues their work might engender. However, for specific NLP tasks our understanding of how prevalent such issues are, or when and why these issues are likely to arise, remains limited. Focusing on text summarization -- a common NLP task largely overlooked by the responsible AI community -- we examine research and reporting practices in the current literature. We conduct a multi-round qualitative analysis of 333 summarization papers from the ACL Anthology published between 2020-2022. We focus on how, which, and when responsible AI issues are covered, which relevant stakeholders are considered, and mismatches between stated and realized research goals. We also discuss current evaluation practices and consider how authors discuss the limitations of both prior work and their own work. Overall, we find that relatively few papers engage with possible stakeholders or contexts of use, which limits their consideration of potential downstream adverse impacts or other responsible AI issues. Based on our findings, we make recommendations on concrete practices and research directions

Enchanting Program Specification Synthesis by Large Language Models using Static Analysis and Program Verification

Formal verification provides a rigorous and systematic approach to ensure the correctness and reliability of software systems. Yet, constructing specifications for the full proof relies on domain expertise and non-trivial manpower. In view of such needs, an automated approach for specification synthesis is desired. While existing automated approaches are limited in their versatility, i.e., they either focus only on synthesizing loop invariants for numerical programs, or are tailored for specific types of programs or invariants. Programs involving multiple complicated data types (e.g., arrays, pointers) and code structures (e.g., nested loops, function calls) are often beyond their capabilities. To help bridge this gap, we present AutoSpec, an automated approach to synthesize specifications for automated program verification. It overcomes the shortcomings of existing work in specification versatility, synthesizing satisfiable and adequate specifications for full proof. It is driven by static analysis and program verification, and is empowered by large language models (LLMs). AutoSpec addresses the practical challenges in three ways: (1) driving \name by static analysis and program verification, LLMs serve as generators to generate candidate specifications, (2) programs are decomposed to direct the attention of LLMs, and (3) candidate specifications are validated in each round to avoid error accumulation during the interaction with LLMs. In this way, AutoSpec can incrementally and iteratively generate satisfiable and adequate specifications. The evaluation shows its effectiveness and usefulness, as it outperforms existing works by successfully verifying 79% of programs through automatic specification synthesis, a significant improvement of 1.592x. It can also be successfully applied to verify the programs in a real-world X509-parser project

Clinical Study Underestimated Rate of Status Epilepticus according to the Traditional Definition of Status Epilepticus

properly cited. Purpose. Status epilepticus (SE) is an important neurological emergency. Early diagnosis could improve outcomes. Traditionally, SE is defined as seizures lasting at least 30 min or repeated seizures over 30 min without recovery of consciousness. Some specialists argued that the duration of seizures qualifying as SE should be shorter and the operational definition of SE was suggested. It is unclear whether physicians follow the operational definition. The objective of this study was to investigate whether the incidence of SE was underestimated and to investigate the underestimate rate. Methods. This retrospective study evaluates the difference in diagnosis of SE between operational definition and traditional definition of status epilepticus. Between July 1, 2012, and June 30, 2014, patients discharged with ICD-9 codes for epilepsy (345.X) in Chia-Yi Christian Hospital were included in the study. A seizure lasting at least 30 min or repeated seizures over 30 min without recovery of consciousness were considered SE according to the traditional definition of SE (TDSE). A seizure lasting between 5 and 30 min was considered SE according to the operational definition of SE (ODSE); it was defined as underestimated status epilepticus (UESE). Results. During a 2-year period, there were 256 episodes of seizures requiring hospital admission. Among the 256 episodes, 99 episodes lasted longer than 5 min, out of which 61 (61.6%) episodes persisted over 30 min (TDSE) and 38 (38.4%) episodes continued between 5 and 30 min (UESE). In the 38 episodes of seizure lasting 5 to 30 minutes, only one episode was previously discharged as SE (ICD-9-CM 345.3). Conclusion. We underestimated 37.4% of SE. Continuing education regarding the diagnosis and treatment of epilepsy is important for physicians

Annulated Dialkoxybenzenes as Catholyte Materials for Non‐aqueous Redox Flow Batteries: Achieving High Chemical Stability through Bicyclic Substitution

1,4‐Dimethoxybenzene derivatives are materials of choice for use as catholytes in non‐aqueous redox flow batteries, as they exhibit high open‐circuit potentials and excellent electrochemical reversibility. However, chemical stability of these materials in their oxidized form needs to be improved. Disubstitution in the arene ring is used to suppress parasitic reactions of their radical cations, but this does not fully prevent ring‐addition reactions. By incorporating bicyclic substitutions and ether chains into the dialkoxybenzenes, a novel catholyte molecule, 9,10‐bis(2‐methoxyethoxy)‐1,2,3,4,5,6,7,8‐octahydro‐1,4:5,8‐dimethanenoanthracene (BODMA), is obtained and exhibits greater solubility and superior chemical stability in the charged state. A hybrid flow cell containing BODMA is operated for 150 charge–discharge cycles with a minimal loss of capacity.A novel bicyclical substituted dialkoxy‐benzene molecule, 9,10‐bis(2‐methoxy‐ethoxy)‐1,2,3,4,5,6,7,8‐octahydro‐1,4:5,8‐dimethanenoanthracene (BODMA), is developed for use as catholyte materials in non‐aqueous redox flow batteries with greater solubility (in their neutral state) and improved chemical stability (in their charged state). A hybrid flow cell using BODMA demonstrates stable efficiencies and capacity over 150 cycles. The molecular design approach of BODMA can be inspirational for future development of redox active molecules.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139992/1/aenm201701272.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139992/2/aenm201701272-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139992/3/aenm201701272_am.pd

Strategies towards enabling lithium metal in batteries: interphases and electrodes

Despite the continuous increase in capacity, lithium-ion intercalation batteries are approaching their performance limits. As a result, research is intensifying on next-generation battery technologies. The use of a lithium metal anode promises the highest theoretical energy density and enables use of lithium-free or novel high-energy cathodes. However, the lithium metal anode suffers from poor morphological stability and Coulombic efficiency during cycling, especially in liquid electrolytes. In contrast to solid electrolytes, liquid electrolytes have the advantage of high ionic conductivity and good wetting of the anode, despite the lithium metal volume change during cycling. Rapid capacity fade due to inhomogeneous deposition and dissolution of lithium is the main hindrance to the successful utilization of the lithium metal anode in combination with liquid electrolytes. In this perspective, we discuss how experimental and theoretical insights can provide possible pathways for reversible cycling of twodimensional lithium metal. Therefore, we discuss improvements in the understanding of lithium metal nucleation, deposition, and stripping on the nanoscale. As the solid–electrolyte interphase (SEI) plays a key role in the lithium morphology, we discuss how the proper SEI design might allow stable cycling. We highlight recent advances in conventional and (localized) highly concentrated electrolytes in view of their respective SEIs. We also discuss artificial interphases and three-dimensional host frameworks, which show prospects of mitigating morphological instabilities and suppressing large shape change on the electrode level

Patrocles: a database of polymorphic miRNA-mediated gene regulation in vertebrates

The Patrocles database (http://www.patrocles.org/) compiles DNA sequence polymorphisms (DSPs) that are predicted to perturb miRNA-mediated gene regulation. Distinctive features include: (i) the coverage of seven vertebrate species in its present release, aiming for more when information becomes available, (ii) the coverage of the three compartments involved in the silencing process (i.e. targets, miRNA precursors and silencing machinery), (iii) contextual information that enables users to prioritize candidate ‘Patrocles DSPs’, including graphical information on miRNA-target coexpression and eQTL effect of genotype on target expression levels, (iv) the inclusion of Copy Number Variants and eQTL information that affect miRNA precursors as well as genes encoding components of the silencing machinery and (v) a tool (Patrocles finder) that allows the user to determine whether her favorite DSP may perturb miRNA-mediated gene regulation of custom target sequences. To support the biological relevance of Patrocles' content, we searched for signatures of selection acting on ‘Patrocles single nucleotide polymorphisms (pSNPs)’ in human and mice. As expected, we found a strong signature of purifying selection against not only SNPs that destroy conserved target sites but also against SNPs that create novel, illegitimate target sites, which is reminiscent of the Texel mutation in sheep

Association of maternal Vitamin D status with glucose tolerance and caesarean section in a multi-ethnic Asian cohort: the growing up in Singapore towards healthy outcomes study

10.1371/journal.pone.0142239PLoS ONE10111-16GUSTO (Growing up towards Healthy Outcomes