Improved Failure Mode Identification and Reliability Estimates for Electricity Transmission Towers

Studies on the theory of structural system reliability includes identification of main the failure modes and calculation of inclusive failure probabilities for the structural system. The efficient and accurate identification of failure modes in structural systems is difficult and represents a key focus for research in system reliability. The fundamental theory of the branch and bound algorithm for stage critical strength is reviewed in this paper. Some deficiencies in this method are highlighted. Corresponding approaches to overcome these deficiencies are proposed. Calculated system reliability solutions to the classical model, a truss with 10 elements, indicate that the improvement measures proposed in this paper increase the efficiency of recognising the main failure modes of the structural system, and are readily validated. The outcomes of this type of benchmark analysis suggest that the proposed methodology may be capable of representing a suitable basis for the structural system reliability analysis of complex truss-like structures, including transmission towers. Using the proposed approach, the principal failure modes and system reliability of a transmission tower are calculated. Based on practical engineering considerations, effective methods to improve this structural system reliability are proposed

ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and application

Abstract Background The increasing global cancer incidence corresponds to serious health impact in countries worldwide. Knowledge-powered health system in different languages would enhance clinicians’ healthcare practice, patients’ health management and public health literacy. High-quality corpus containing cancer information is the necessary foundation of cancer education. Massive non-structural information resources exist in clinical narratives, electronic health records (EHR) etc. They can only be used for training AI models after being transformed into structured corpus. However, the scarcity of multilingual cancer corpus limits the intelligent processing, such as machine translation in medical scenarios. Thus, we created the cancer specific cross-lingual corpus and open it to the public for academic use. Methods Aiming to build an English-Chinese cancer parallel corpus, we developed a workflow of seven steps including data retrieval, data parsing, data processing, corpus implementation, assessment verification, corpus release, and application. We applied the workflow to a cross-lingual, comprehensive and authoritative cancer information resource, PDQ (Physician Data Query). We constructed, validated and released the parallel corpus named as ECCParaCorp, made it openly accessible online. Results The proposed English-Chinese Cancer Parallel Corpus (ECCParaCorp) consists of 6685 aligned text pairs in Xml, Excel, Csv format, containing 5190 sentence pairs, 1083 phrase pairs and 412 word pairs, which involved information of 6 cancers including breast cancer, liver cancer, lung cancer, esophageal cancer, colorectal cancer, and stomach cancer, and 3 cancer themes containing cancer prevention, screening, and treatment. All data in the parallel corpus are online, available for users to browse and download (http://www.phoc.org.cn/ECCParaCorp/). Conclusions ECCParaCorp is a parallel corpus focused on cancer in a cross-lingual form, which is openly accessible. It would make up the imbalance of scarce multilingual corpus resources, bridge the gap between human readable information and machine understanding data resources, and would contribute to intelligent technology application as a preparatory data foundation e.g. cancer-related machine translation, cancer system development towards medical education, and disease-oriented knowledge extraction. </jats:sec

Comparison of the onset of uterine contractions determined from tocodynamometry and maternal perception

The aim of this study was to investigate the time difference (TD) between the onset of uterine contraction (UC) determined from tocodynamometry (TOCO) and identified by maternal perception. The online available Icelandic database was used to calculate TD, which was defined as the difference between when it was felt by a pregnant woman and the starting point on the UC signal recorded by a TOCO. A total of 295 TDs from 78 recordings (from a total of 33 participants; among them, 13 participants included at least 3 recordings from different gestational weeks) were analyzed with the overall mean±SD of TD calculated. For each individual participant with at least 3 recordings, regression analysis was then performed to investigate the relationship between the mean TD from each recording with gestational week, with their overall slope calculated. The results showed that 85.4% of TDs was within [−40, 40] s, with an overall mean TD of 3.04 s (p>0.05), indicating that there was no significant difference between the UC onset determined from TOCO and maternal perception. It was also noticed that 61.5% recordings (48 out of 78 recordings) had all positive or negative TD for all the UCs analyzed within a recording. Furthermore, the regression analysis showed that the regression line slope was negative for 10 out of the 13 participants with at least 3 recordings from different gestational weeks, resulting in that the overall slope (−2.85±5.58) was significantly negative (p<0.05), and indicating that UC onset TD decreased with gestational weeks. In summary, this study quantitatively investigated the TD between the onset of UCs determined from TOCO and maternal perception, providing scientific evidence for future studies to understand the underlying mechanism of the time sequence of UC activity determined from different techniques

Harnessing conversion bridge strategy by organic semiconductor in polymer matrix memristors for high‐performance multi‐modal neuromorphic signal processing

Abstract Organic memristors, integrating chemically designed resistive switching and mechanical flexibility, present promising hardware opportunities for neuromorphic computing, particularly in the development of next‐generation wearable artificial intelligence devices. However, challenges persist in achieving high yield, controllable switching, and multi‐modal information processing. In this study, we introduce an efficient distribution of conversion bridges (EDCB) strategy by dispersing organic semiconductor (poly[2,5‐bis(3‐tetradecylthiophen‐2‐yl)thieno[3,2‐b]thiophene], PBTTT) in elastomer (polystyrene‐block‐poly(ethylene‐ran‐butylene)‐block‐polystyrene, SEBS). This innovative approach results in memristors with exceptional yield, high stretchability, and reliable switching performance. By fine‐tuning the semiconductor content, we shift the primary charge carriers from ions to electrons, realizing modulable non‐volatile, and volatile duo‐mode memristors. This advancement enables multi‐modal signal processing at distinct operational mechanisms—non‐volatile mode for image recognition in convolutional neural networks (CNNs) and volatile mode for dynamic classification and prediction in reservoir computing (RC). A fully analog RC hardware system is further demonstrated by integrating the distinct volatile and non‐volatile modes of the EDCB‐based memristor into the dynamic neuron network and the linear regression layer of the RC respectively, achieving high accuracy in online arrhythmia detection tasks. Our work paves the way for high‐yield organic memristors with mechanical flexibility, advancing efficient multi‐mode neuromorphic computing within a unified memristor system integrating volatile and non‐volatile functionalities

Identification, Characterization, and Receptor Binding Mechanism of New Umami Peptides from Traditional Fermented Soybean Paste (Dajiang)

Dajiang, a traditional Chinese condiment, is made from fermented soybeans. It is highly popular among consumers as a result of its delicious umami flavor, which mainly originates from umami peptides. To examine the mechanism of umami taste in Dajiang, we selected Dajiang samples with strong umami taste and subjected them to purification and identification analysis using ethanol precipitation, gel chromatography, reversed-phase high-performance liquid chromatography, and ultraperformance liquid chromatography–tandem mass spectrometry. Subsequently, on the basis of toxicity and umami prediction analysis, we screened, synthesized, and characterized three novel bean umami peptides in Dajiang: TLGGPTTL, 758.4174 Da; GALEQILQ, 870.4811 Da; and HSISDLQ, 911.4713 Da. Their sensory threshold values were 0.25, 0.40, and 0.17 mmol/L, respectively. Furthermore, molecular docking results showed that hydrogen-bonding and hydrophobic interactions are important interaction forces in the binding of umami peptide to taste receptors. Ser147 and Glu148 of the T1R3 taste receptor are important amino acid residues for binding of the three umami peptides. This study uncovers the mechanism of umami-peptide-driven flavor in fermented soybean products

Comparison of electrohysterogram signal measured by surface electrodes with different designs: A computational study with dipole band and abdomen models

Non-invasive measurement of uterine activity using electrohysterogram (EHG) surface electrodes has been attempted to monitor uterine contraction. This study aimed to computationally compare the performance of acquiring EHG signals using monopolar electrode and three types of Laplacian concentric ring electrodes (bipolar, quasi-bipolar and tri-polar). With the implementation of dipole band model and abdomen model, the performances of four electrodes in terms of the local sensitivity were quantifed by potential attenuation. Furthermore, the efects of fat and muscle thickness on potential attenuation were evaluated using the bipolar and tri-polar electrodes with diferent radius. The results showed that all the four types of electrodes detected the simulated EHG signals with consistency. That the bipolar and tri-polar electrodes had greater attenuations than the others, and the shorter distance between the origin and location of dipole band at 20dB attenuation, indicating that they had relatively better local sensitivity. In addition, ANOVA analysis showed that, for all the electrodes with diferent outer ring radius, the efects of fat and muscle on potential attenuation were signifcant (all p<0.01). It is therefore concluded that the bipolar and tri-polar electrodes had higher local sensitivity than the others, indicating that they can be applied to detect EHG efectively