bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of the retraining strategies for multi-label text message classification in call/contact center systems
Authors: Poczeta Katarzyna , Płaza Mirosław , Zawadzki Michał , Michno Tomasz , Krechowicz Maria 
Published: May 2024

AbstractToday, in many areas of technology, we can come across applications of various artificial intelligence methods. They usually involve models trained on some specific pool of learning data. Sometimes, however, the data analyzed by these solutions can change its nature over time. This usually results in a decrease in classification efficiency. In such a case, the use of techniques to retrain the originally trained reference models should be considered. One of the industries where the nature of data changes quite dynamically over time is the broadly defined call/contact center systems. An example of a module that is often found in this type of system and that, due to frequently changing marketing campaigns, requires the use of learning techniques is the automatic classification of text data. The paper describes the process of retraining the original reference models used in a multi-label text message classification method dedicated directly to call/contact center systems applications. In order to carry out the retraining process, Polish-language data from the actual archives of a large commercial contact center system and English-language data extracted from a publicly available database were used. The study was conducted for models based on artificial neural networks and bidirectional encoder representations from transformer type models. In addition, two different retraining strategies were studied, the results of which were compared with data obtained from the operation of reference models. As a result of the research work, an improvement of up to 5% in classification efficiency, as described by the metric Emotica was obtained, which means that proper integration of the retraining process brings tangible benefits to the solution tested in the article. Thus, it can also benefit the solutions used in business.
Comparing the quantum witness, the entropic Leggett–Garg inequality and the NCGD
Authors: Tan Xiangguan , Zhang Yuxia , Qiu Tianhui 
Published: May 2024

AbstractIn this paper, we investigate the violation of the quantum witness, the entropic Leggett–Garg inequality (LGI) and the no-coherence-generating-and-detecting (NCGD) dynamics, under projective and coarsening measurements. We consider a qubit in the three scenarios: coherent dynamics, in the presence of dissipation, and in the presence of dephasing. For the pure qubit, we find that in the case of the projective measurement, the non-violation conditions of the quantum witness and the NCGD are the same; while the non-violation conditions of the entropic LGI and the quantum witness do not contain each other, i.e., a suitable conjunction of the quantum witness and the entropic LGI may be better for testing macrorealism. Also, for the pure qubit with coarsening measurement similar results can be obtained. For the dissipative qubit with projective measurement, the quantum witness and the NCGD can be both violated for a wider parameter regime than the entropic LGI. For the dissipative qubit with coarsening measurement, the violation of the NCGD is the most robust compared to the quantum witness and the entropic LGI. For the dephasing qubit with projective and coarsening measurements, the relationship among the quantum witness, the entropic LGI and the NCGD is similar to that of the pure qubit. In addition, we find that for pure, dissipative and dephasing qubits, the robustness of the coarsening measurement in final resolution is more vulnerable than that of the coarsening measurement in reference for the entropic LGI.
A study of extractive summarization of long documents incorporating local topic and hierarchical information
Authors: Wang Ting , Yang Chuan , Zou Maoyang , Liang Jiaying , Xiang Dong , Yang Wenjie , Wang Hongyang , Li Jia 
Published: May 2024

AbstractIn recent years, the transformer-based language models have achieved remarkable success in the field of extractive text summarization. However, there are still some limitations in this kind of research. First, the transformer language model usually regards the text as a linear sequence, ignoring the inherent hierarchical structure information of the text. Second, for long text data, traditional extractive models often focus on global topic information, which poses challenges in how they capturing and integrating local contextual information within topic segments. To address these issues, we propose a long text extractive summarization model that employs a local topic information extraction module and a text hierarchical extraction module to capture the local topic information and document's hierarchical structure information of the original text. Our approach enhances the ability to determine whether a sentence belongs to the summary. In this experiment, ROUGE score is used as the experimental evaluation index, and evaluates the model on three large public datasets. Through experimental validation, the model demonstrates superior performance in terms of ROUGE-1, ROUGE-2, and ROUGE-L scores compared to current mainstream summarization models, affirming the effectiveness of incorporating local topic information and document hierarchical structure into the model.
Artificial intelligence for volumetric measurement of cerebral white matter hyperintensities on thick-slice fluid-attenuated inversion recovery (FLAIR) magnetic resonance images from multiple centers
Authors: Kuwabara Masashi , Ikawa Fusao , Nakazawa Shinji , Koshino Saori , Ishii Daizo , Kondo Hiroshi , Hara Takeshi , Maeda Yuyo , Sato Ryo , Kaneko Taiki , Maeyama Shiyuki , Shimahara Yuki , Horie Nobutaka 
Published: May 2024

AbstractWe aimed to develop a new artificial intelligence software that can automatically extract and measure the volume of white matter hyperintensities (WMHs) in head magnetic resonance imaging (MRI) using only thick-slice fluid-attenuated inversion recovery (FLAIR) sequences from multiple centers. We enrolled 1092 participants in Japan, comprising the thick-slice Private Dataset. Based on 207 randomly selected participants, neuroradiologists annotated WMHs using predefined guidelines. The annotated images of participants were divided into training (n = 138) and test (n = 69) datasets. The WMH segmentation model comprised a U-Net ensemble and was trained using the Private Dataset. Two other models were trained for validation using either both thin- and thick-slice MRI datasets or the thin-slice dataset alone. The voxel-wise Dice similarity coefficient (DSC) was used as the evaluation metric. The model trained using only thick-slice MRI showed a DSC of 0.820 for the test dataset, which is comparable to the accuracy of human readers. The model trained with the additional thin-slice dataset showed only a slightly improved DSC of 0.822. This automatic WMH segmentation model comprising a U-Net ensemble trained on a thick-slice FLAIR MRI dataset is a promising new method. Despite some limitations, this model may be applicable in clinical practice.
Addressing practical challenges of LiB cells in their pack applications
Authors: Tan Cher Ming , Yang Yan , Kumar K. Jithendra Mani , Mishra Debesh Devadutta , Liu Tsung-Yu 
Published: May 2024

AbstractIn a battery pack, several lithium-ion batteries (LiBs) are connected in series and parallel so that sufficient voltage, current and power can be provided for applications. To ensure safe operation, when one of the LiB cells in a pack has its SoH below 80%, the entire pack will have to be discarded. Thus, ensuring all the LiB cells degrade similarly in a pack is crucial to maximize the potential of all the cells in a pack. There are several methods to perform screening on the LiB cells for such purpose, but there exist many practical challenges for estimating and predicting the degradation rate of the cells before they are chosen to be put in a pack which will be described in this work. This work provides solutions to some of these challenges and shows through experiments that one can screen the weak cells from production batch with just the first discharge cycle, and one can also predict the statistical distribution of the degradation rates of LiB cells in a production batch. On-line in-situ determination of the SoH of each cell connected in a pack is also made possible with a solution presented in this work, and this method is verified over many different types of LiB from various manufacturers.
Exploration of neuroanatomical characteristics to differentiate prodromal Alzheimer’s disease from cognitively unimpaired amyloid-positive individuals
Authors: Kim Hak Hyeon , Kwon Min Jeong , Jo Sungman , Park Ji Eun , Kim Ji Won , Kim Jae Hyoung , Kim Sang Eun , Kim Ki Woong , Han Ji Won 
Published: May 2024

AbstractDifferentiating clinical stages based solely on positive findings from amyloid PET is challenging. We aimed to investigate the neuroanatomical characteristics at the whole-brain level that differentiate prodromal Alzheimer’s disease (AD) from cognitively unimpaired amyloid-positive individuals (CU A+) in relation to amyloid deposition and regional atrophy. We included 45 CU A+ participants and 135 participants with amyloid-positive prodromal AD matched 1:3 by age, sex, and education. All participants underwent 18F-florbetaben positron emission tomography and 3D structural T1-weighted magnetic resonance imaging. We compared the standardized uptake value ratios (SUVRs) and volumes in 80 regions of interest (ROIs) between CU A+ and prodromal AD groups using independent t-tests, and employed the least absolute selection and shrinkage operator (LASSO) logistic regression model to identify ROIs associated with prodromal AD in relation to amyloid deposition, regional atrophy, and their interaction. After applying False Discovery Rate correction at < 0.1, there were no differences in global and regional SUVR between CU A+ and prodromal AD groups. Regional volume differences between the two groups were observed in the amygdala, hippocampus, entorhinal cortex, insula, parahippocampal gyrus, and inferior temporal and parietal cortices. LASSO logistic regression model showed significant associations between prodromal AD and atrophy in the entorhinal cortex, inferior parietal cortex, both amygdalae, and left hippocampus. The mean SUVR in the right superior parietal cortex (beta coefficient = 0.0172) and its interaction with the regional volume (0.0672) were also selected in the LASSO model. The mean SUVR in the right superior parietal cortex was associated with an increased likelihood of prodromal AD (Odds ratio [OR] 1.602, p = 0.014), particularly in participants with lower regional volume (OR 3.389, p < 0.001). Only regional volume differences, not amyloid deposition, were observed between CU A+ and prodromal AD. The reduced volume in the superior parietal cortex may play a significant role in the progression to prodromal AD through its interaction with amyloid deposition in that region.
Research on roller monitoring technology based on distributed fiber optic sensing system
Authors: Xie Miao , Li Bo , Ma Suning , Lu Jinnan , Hu Guilin , Meng Qingshuang , Luo Jiaxing 
Published: May 2024

AbstractAs one of the key components of the belt conveyor, the roller bears the task of supporting and rolling the conveyor belt, and monitoring its condition is very important. The traditional monitoring of the conveyor roller group adopts worker inspection, which has strong subjectivity. Monitoring using sensors necessitates the use of numerous sensors, which can pose wiring challenges. The use of inspection robots for monitoring results can be discontinuous, and their performance may be limited. This study proposes a fault diagnosis method for rollers based on a distributed fiber optic sensing system. By improving the traditional Isolation Forest (IForest), a framework called Incremental Majority Voting Isolation Forest (IMV-IForest) is proposed. By analyzing the optical signal, we extracted the variation patterns of roller faults over time and space, and analyzed the abnormal score distribution between fault data and normal data. Using the dataset collected on-site, we compared and analyzed IMV-IForest with the traditional IForest and the Extended Isolation Forest (E-iForest). The results indicate that the variation of the fault of the faulty roller with time and space can be used for early prediction of roller faults; determine an anomaly score threshold of 0.6; improved IForest have faster computation time and higher accuracy. Finally, to verify the effectiveness of the proposed scheme, a 3-month experiment was conducted on a 600 m long belt conveyor in a certain mine, and on-site monitoring results were obtained. By comparing with manual detection results, it was shown that the proposed method has high recognition rate for faulty idlers, with an accuracy rate of 97.92%, and can effectively diagnose faulty idlers.
Stress analysis under centrifugal load of the multiple corrugated diaphragm coupling based on rotating shell thin film model
Authors: Cao Angang , Sun Shiru 
Published: May 2024

AbstractCentrifugal force is one of the factors that cannot be ignored in high-speed shaft systems. The multiple corrugated diaphragm (MCD) Coupling is suitable for high-power and high-speed situations; hence, it is crucial to investigate the stress and deformation of the wave disc under centrifugal load. This paper first uses the rotating shell thin film model to derive the circumferential stress and deformation displacement of the MCD under centrifugal load. Then, the finite element method is used to verify the results obtained from the analytical solution. The results show the feasibility of using the rotating shell thin film model for centrifugal load analysis of the MCD, providing a new approach for the theoretical analysis of the MCD.
Exosomal miR-493 suppresses MAD2L1 and induces chemoresistance to intraperitoneal paclitaxel therapy in gastric cancer patients with peritoneal metastasis
Authors: Makinoya Masahiro , Miyatani Kozo , Matsumi Yoshiaki , Sakano Yu , Shimizu Shota , Shishido Yuji , Hanaki Takehiko , Kihara Kyoichi , Matsunaga Tomoyuki , Yamamoto Manabu , Tokuyasu Naruo , Takano Shuichi , Sakamoto Teruhisa , Hasegawa Toshimichi , Saito Hiroaki , Nakayama Yuji , Osaki Mitsuhiko , Okada Futoshi , Fujiwara Yoshiyuki 
Published: May 2024

AbstractIntraperitoneal (IP) chemotherapy with paclitaxel (PTX) for gastric cancer (GC) with peritoneal metastasis (PM) is considered a promising treatment approach, however, there are no useful biomarkers to predict the efficacy of IP therapy. We examined the association between intra-peritoneal exosomes, particularly exosomal micro-RNAs (exo-miRNAs), and IP-chemo sensitivity. MKN45 cells that were cultured with intra-peritoneal exosomes from patients who did not respond to IP therapy with PTX (IPnon-respond group) exhibited resistance to PTX compared with exosomes from responding patients (IPrespond group) (p = 0.002). A comprehensive search for exo-miRNAs indicated that miR-493 was significantly up-regulated in exosomes from the IPnon-respond group compared with those collected from the IPrespond group. The expression of miR-493 in PTX-resistant MKN45 cells (MKN45PTX-res) was higher compared with that in MKN45. In addition, MKN45PTX-res cells exhibited lower MAD2L1 gene and protein expression compared with MKN45. Finally, miR-493 enhancement by transfection of miR-493 mimics significantly down-regulated MAD2L1 expression in MKN45 cells and reduced PTX sensitivity. Our results suggest that intra-peritoneal exo-miR-493 is involved in chemoresistance to PTX by downregulating MAD2L1 in GC with PM. Exo-miR-493 may be a biomarker for chemoresistance and prognosis of GC patients with PM and may also be a promising therapeutic target.
Safe and effective hybrid endoscopic submucosal dissection with ALL IN ONE snare in porcine gastric model (with video)
Authors: Yang Lang , Ma Xian-zong , Su Hui , Zhang Jie , Sheng Jian-qiu , Jin Peng 
Published: May 2024

AbstractThis study aimed to evaluate the safety and efficiency of hybrid endoscopic submucosal dissection (H-ESD) using a newly developed ALL IN ONE (AIO) snare. This was a matched control study in a porcine model. Five paired simulated stomach lesions 2–2.5 cm in size were removed by H-ESD using an AIO snare or conventional ESD (C-ESD) using an endoscopic knife. The outcomes of the two procedures were compared, including en-bloc resection rates, procedure times, intraprocedural bleeding volumes, muscular injuries, perforations, thicknesses of the submucosal layer in resected specimens, and stomach defects. All simulated lesions were resected en-bloc. Specimens resected by H-ESD and C-ESD were similar in size (7.68 ± 2.92 vs. 8.42 ± 2.42 cm2; P = 0.676). H-ESD required a significantly shorter procedure time (13.39 ± 3.78 vs. 25.99 ± 4.52 min; P = 0.031) and submucosal dissection time (3.99 ± 1.73 vs. 13.1 ± 4.58 min; P = 0.003) versus C-ESD; H-ESD also yielded a faster dissection speed (241.37 ± 156.84 vs. 68.56 ± 28.53 mm2/min; P = 0.042) and caused fewer intraprocedural bleeding events (0.40 ± 0.55 vs. 3.40 ± 1.95 times/per lesion; P = 0.016) than C-ESD. The thicknesses of the submucosal layer of the resected specimen (1190.98 ± 134.07 vs. 1055.90 ± 151.76 μm; P = 0.174) and the residual submucosal layer of the stomach defect (1607.94 ± 1026.74 vs. 985.98 ± 445.58 μm; P = 0.249) were similar with both procedures. The AIO snare is a safe and effective device for H-ESD and improves the treatment outcomes of gastric lesions by shortening the procedure time.
Robust language-based mental health assessments in time and space through social media
Authors: Mangalik Siddharth , Eichstaedt Johannes C. , Giorgi Salvatore , Mun Jihu , Ahmed Farhan , Gill Gilvir , V. Ganesan Adithya , Subrahmanya Shashanka , Soni Nikita , Clouston Sean A. P. , Schwartz H. Andrew 
Published: May 2024

AbstractIn the most comprehensive population surveys, mental health is only broadly captured through questionnaires asking about “mentally unhealthy days” or feelings of “sadness.” Further, population mental health estimates are predominantly consolidated to yearly estimates at the state level, which is considerably coarser than the best estimates of physical health. Through the large-scale analysis of social media, robust estimation of population mental health is feasible at finer resolutions. In this study, we created a pipeline that used ~1 billion Tweets from 2 million geo-located users to estimate mental health levels and changes for depression and anxiety, the two leading mental health conditions. Language-based mental health assessments (LBMHAs) had substantially higher levels of reliability across space and time than available survey measures. This work presents reliable assessments of depression and anxiety down to the county-weeks level. Where surveys were available, we found moderate to strong associations between the LBMHAs and survey scores for multiple levels of granularity, from the national level down to weekly county measurements (fixed effects β = 0.34 to 1.82; p < 0.001). LBMHAs demonstrated temporal validity, showing clear absolute increases after a list of major societal events (+23% absolute change for depression assessments). LBMHAs showed improved external validity, evidenced by stronger correlations with measures of health and socioeconomic status than population surveys. This study shows that the careful aggregation of social media data yields spatiotemporal estimates of population mental health that exceed the granularity achievable by existing population surveys, and does so with generally greater reliability and validity.
Experimental investigation of geometric quantum speed limits in an open quantum system
Authors: Pires Diego Paiva , deAzevedo Eduardo R. , Soares-Pinto Diogo O. , Brito Frederico , Filgueiras Jefferson G. 
Published: May 2024

AbstractThe quantum speed limit (QSL) is a fundamental lower bound on the evolution time for quantum systems, and its tightness has been observed to be dependent on the properties of the physical process. However, experimental studies exploring the QSL in open quantum systems are still missing. Here, we studied geometric quantum speed limits of a qubit subject to decoherence in an ensemble of chloroform molecules in a Nuclear Magnetic Resonance experiment. We controlled the system-reservoir interaction and the spin relaxation rates by adding a paramagnetic salt, allowing the observation of both Markovian and non-Markovian open system dynamics for the qubit. We used two distinguishability measures of quantum states to assess the speed of the qubit evolution: the quantum Fisher information (QFI) and Wigner-Yanase skew information (WY). For non-Markovianity and low salt concentrations, we found crossovers between QSLs related to those metrics. The WY metric sets the tighter QSL for high concentrations and Markovian dynamics. We also show that QSLs are sensitive even to small fluctuations in spin magnetization.
Pre-failure operational anomalies of the Kakhovka Dam revealed by satellite data
Authors: Yang Qing , Shen Xinyi , He Kang , Zhang Qingyuan , Helfrich Sean , Straka William , Kellndorfer Josef M. , Anagnostou Emmanouil N. 
Published: May 2024

AbstractOn June 6, 2023, the Kakhovka Dam in Ukraine experienced a catastrophic breach that led to the loss of life and substantial economic values. Prior to the breach, the supporting structures downstream of the spillway had shown signs of being compromised. Here, we use multi-source satellite data, meteorological reanalysis, and dam design criteria to document the dam’s pre-failure condition. We find that anomalous operation of the Kakhovka Dam began in November 2022, following the destruction of a bridge segment, which led to persistent overtopping from late April 2023 up to the breach, contributing to the erosion of the spillway foundation. Moreover, our findings also highlight safety and risk-reduction measures pivotal in avoiding such scenarios. To help prevent future disasters, we advocate for greater transparency in the design parameters of key water structures to enable risk management, and conclude that remote sensing technology can help ensuring water infrastructure safety.