bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impedance drop determines ablation lesion volume at the same level of ablation index
Authors: Oh Seil , Choe Won-Seok , Lee So-Ryoung , Choi Eue-Keun 
Published: April 2023

AbstractNew parameters such as ablation index (AI) have been developed to create reliable ablation lesions. This study was performed to evaluate whether RF energy delivery with the same ablation index creates the similar ablation lesion volume. Ablation lesions were created in 5 pig hearts at ex-vivo state. Ablation was performed using an external-irrigation contact-force sensing catheter on the epicardial side of the left ventricle with 90-degree of angle. RF ablation time was adjusted for targeting AI 600 at 8 different conditions. Lesion volume created with 0–5 g of contact force at 20 W was significantly lower than that of 11–20 g at 40W despite of the same AI (125 ± 76.2 vs. 272 ± 49.5 mm3, P < 0.05). Quality of ablation lesion was variable in the condition of poor contact at low power for the ablation of ex-vivo swine left ventricle, and high-quality lesions could be expected when the impedance drop is satisfactory even though the same level of AI is applied during ablation.
Characterization of features and outcomes of young patients (< 45 years) presenting with ST-segment elevation myocardial infarction
Authors: Samir Ahmad , Almahjori Mohammed , Zarif Basem , Elshinawi Mai , Yehia Hesham , Elhafy Mohamed , Shehata Ahmed , Farrag Azza 
Published: April 2023

Abstract
Background
Coronary artery disease (CAD) is the commonest cause of death worldwide. ST-segment elevation myocardial infarction (STEMI) and its consequences can be devastating particularly at younger age for a bigger impact on the patient’s psychology and ability to work. Little is known about the differential features and outcomes of young STEMI patients in Egypt. This study characterized young STEMI patients (≤ 45 years) compared to patients > 45 years and evaluated 1-year outcomes.

Results
A total of 492 eligible STEMI patients who presented to the National Heart Institute and Cairo University Hospitals were recruited. Young STEMI patients (< 45 years old) represented 20% of all STEMI comers. Male gender was predominant in both groups, yet with a significantly higher proportion in the younger compared to older patients (87% vs. 73%, p = 0.004). Compared to older patients, young STEMI patients had characteristically higher rates of smoking (72.4% vs. 49.7%, p < 0.001) and family history (13.3% vs. 4.8%, p = 0.002), while significantly lower rate of other conventional CAD risk factors as diabetes, hypertension, and dyslipidemia (20.4% vs. 44.7%, 20.4% vs. 44.9% and 12.7% vs. 21.8%, respectively, p < 0.05 for all). Follow-up was continued for at least 12 months after the index event. Younger STEMI patients had fewer major adverse cardiovascular events and fewer heart failure hospitalizations compared to the older controls (10.2 vs. 23.9% and 18.4% vs. 34.8%, respectively, p < 0.005 for both), however, 1-year mortality was similar (3.1% vs. 4.1%, p = 0.64).

Conclusions
Younger STEMI patients (≤ 45 years) show peculiar characteristics, with significantly higher rates of smoking and family history of premature CAD, while less prevalence of other conventional CAD risk factors. Overall MACE occurred less in younger STEMI patients; however, the mortality rate was similar to the older controls.
Problems associated with implementation of bioengineering in hill road construction in Nepal
Authors: Shah Prashant , Dahal Khetraj 
Published: April 2023

Abstract
The landslide disaster, feeble geology, rapid deforestation, poor drainage system, and increase in mechanical strain have weakened the Krishna Bhir slope, Prithvi Highway, Dhading, Nepal. The objective of this article was to study about the problems associated with bioengineering implementation in hill road construction with the future recommendations. For primary research, map study, field observation, in-depth interview, focus-group discussion, and questionnaire survey were used as an instrument for the field study. Published reports, papers, thesis, database and manuals, and field observation were also reviewed. Landslide caused the loss of property, ill effects on lifestyle, disturbance in movement of goods and services, loss of availability of water due to damage in water supply system, damage in sewage disposal system, etc. During the construction period using bioengineering technique, major problem occurred during installation of the bioengineered system (RII = 0.791), lack of training during construction (RII = 0.839), unavailability of space (RII = 0.817), inadequate supply of appropriate instruments (RII = 0.821), and improper selection of vegetation types (RII = 0.839). The major problems were also seen during site monitoring and evaluation (RII = 0.853). Proper selection of plant species (RII = 0.936) before implementation of bioengineering technique is needed at hill road, but the high installation costs (RII = 0.841) could be the major limitation. Bioengineering application has a bright future if proper actions are taken in time. Solutions need to be formulated and implemented by understanding the major limitations of bioengineering technique.
Roles of host proteases in the entry of SARS-CoV-2
Authors: Zabiegala Alexandria , Kim Yunjeong , Chang Kyeong-Ok 
Published: April 2023

AbstractThe spike protein (S) of SARS-CoV-2 is responsible for viral attachment and entry, thus a major factor for host susceptibility, tissue tropism, virulence and pathogenicity. The S is divided with S1 and S2 region, and the S1 contains the receptor-binding domain (RBD), while the S2 contains the hydrophobic fusion domain for the entry into the host cell. Numerous host proteases have been implicated in the activation of SARS-CoV-2 S through various cleavage sites. In this article, we review host proteases including furin, trypsin, transmembrane protease serine 2 (TMPRSS2) and cathepsins in the activation of SARS-CoV-2 S. Many betacoronaviruses including SARS-CoV-2 have polybasic residues at the S1/S2 site which is subjected to the cleavage by furin. The S1/S2 cleavage facilitates more assessable RBD to the receptor ACE2, and the binding triggers further conformational changes and exposure of the S2’ site to proteases such as type II transmembrane serine proteases (TTPRs) including TMPRSS2. In the presence of TMPRSS2 on the target cells, SARS-CoV-2 can utilize a direct entry route by fusion of the viral envelope to the cellular membrane. In the absence of TMPRSS2, SARS-CoV-2 enter target cells via endosomes where multiple cathepsins cleave the S for the successful entry. Additional host proteases involved in the cleavage of the S were discussed. This article also includes roles of 3C-like protease inhibitors which have inhibitory activity against cathepsin L in the entry of SARS-CoV-2, and discussed the dual roles of such inhibitors in virus replication.
The New Emperor's Clothes
Authors: Ngan Quincy 
Published: April 2023

Abstract
This article contextualizes the visual intrigue that was created by the fifteenth-century Chinese poet and painter Sun Ai (ca. 1452–1536) when he broke from convention by using indigo blue to color the leaves of a cotton plant and a mulberry branch in a pair of paintings now in the Palace Museum, Beijing. The key to the meaning of this unique coloration lies in the poems inscribed by Shen Zhou (1427–1509) and Qian Renfu (1446–1526), as well as the socioeconomic connotations of silk, cotton, and indigo in those scholars' regions. It is argued that these paintings were made shortly after the Hongzhi emperor (r. 1487–1505) banned the submission of multicolored cotton and silk textiles. Considered in that context, the monochromatic use of indigo not only alluded to what cotton fibers and silkworms would ultimately produce—cloth and silk to be dyed indigo—but also stood in stark contrast to the kaleidoscopic appearance of the clothing banned by Hongzhi. The collaboration between Shen Zhou and Qian Renfu makes the paintings prominent examples of the layered nuance achieved in traditional Chinese painting through the interplay of color and poetry.
The stock market reaction to COVID-19 vaccination in ASEAN
Authors: Herlina Marizsa , Mafruhat Ade Yunita , Kurniati Eti , Wildan Wildan , Salsabila Hilwa Gifty 
Published: April 2023

Previous studies have shown that the confirmed cases drive investor sentiment, reflecting the stock's return. Based on this, the vaccination growth is also expected to drive the investor’s sentiment, which can be reflected in the return of the stock market in ASEAN. Therefore, this study explores the vaccination impact on stock returns in ASEAN countries. This study contributes to the gap of taking the COVID-19 vaccination impact to the stock return into account by using the panel regression model with HC and Driscoll and Kraay robust covariance matrix estimator, which addresses the cross-dependency and heterogeneity problems. This study is one of the early studies of the topic, especially in ASEAN. The panel regression model with HC and Driscoll and Kraay robust covariance matrix estimator uses three variables: the daily stocks return, vaccine growth, and cases growth. It is a balanced panel data that includes six countries and 117 daily series data, making 702 observations used in the study. The results show conflicting results where daily vaccination growth negatively affects the stock return. This problem can arise for several reasons, such as the uncertainty in the financial market and cross-dependency and heterogeneity detected in the model. We can see that the investors still have a negative sentiment because COVID-19 has resulted in uncertainty on the financial market in ASEAN. This gives us practical implications that the ASEAN country members’ government needs to push vaccination policy more aggressively.
Lateral flow immunoassay-based laboratory algorithm for rapid diagnosis of diphtheria
Authors: Melnikov Vyacheslav G. , Berger Anja , Dangel Alexandra , Sing Andreas 
Published: April 2023

Background: In industrialised countries diphtheria is a rare but still life-threatening disease with a recent increase in cases due to migration and zoonotic aspects. Due to the rarity of the disease, laboratory diagnosis of diphtheria is often carried out in central reference laboratories and involves the use of sophisticated equipment and specially trained personnel. The result of the diphtheria agent detection can usually be obtained after 5-6 days or more. Authors suggest a Lateral Flow Immunoassay (LFIA)-based laboratory algorithm for the diagnosis of diphtheria, which may render less time in issuing a result and could promote the testing be performed in laboratories closer to the patient. Methods: LFIA for diphtheria toxin (DT) detection was designed using a pair of monoclonal antibodies to receptor-binding subunit B of the DT, and validated with 322 corynebacterial cultures as well as 360 simulated diphtheria specimens. Simulated diphtheria specimens were obtained by spiking of human pharyngeal samples with test strains of corynebacteria. The simulated specimens were plated on selective tellurite agar and after 18-24 hours of incubation, grey/black colonies characteristic of the diphtheria corynebacteria were examined for the DT using LFIA. Results: The diagnostic sensitivity of the LFIA for DT detection on bacterial cultures was 99.35%, and the specificity was 100%. Also, the LFIA was positive for all pharyngeal samples with toxigenic strains and negative for all samples with non-toxigenic strains. For setting LFIA, a 6-hour culture on Elek broth was used; thus, under routine conditions, the causative agent of diphtheria could be detected within two working days after plating of the clinical specimen on the tellurite medium of primary inoculation. Conclusions: The availability of such a simple and reliable methodology will speed up and increase the accuracy of diphtheria diagnosis globally
The Electric Dial-a-Ride Problem on a Fixed Circuit
Authors: Molenbruch Yves , Braekers Kris , Eisenhandler Ohad , Kaspi Mor 
Published: April 2023

Shared mobility services involving electric autonomous shuttles have increasingly been implemented in recent years. Because of various restrictions, these services are currently offered on fixed circuits and operated with fixed schedules. This study introduces a service variant with flexible stopping patterns and schedules. Specifically, in the electric dial-a-ride problem on a fixed circuit (eDARP-FC), a fleet of capacitated electric shuttles operates on a given circuit consisting of a recharging depot and a sequence of stations where passengers can be picked up and dropped off. The shuttles may perform multiple laps, between which they may need to recharge. The goal of the problem is to determine the vehicles’ stopping sequences and schedules, including recharging plans, so as to minimize a weighted sum of the total passenger excess time and the total number of laps. The eDARP-FC is formulated as a nonstandard lap-based mixed integer linear programming and is shown to be NP-Hard. Efficient polynomial time algorithms are devised for two special scheduling subproblems. These algorithms and several heuristics are then applied as subroutines within a large neighborhood search metaheuristic. Experiments on instances derived from a real-life system demonstrate that the flexible service results in a 32%–75% decrease in the excess time at the same operational costs. Funding: This work was supported by the Fonds Wetenschappelijk Onderzoek [Project Data-Driven Logistics: Grant S007318N; Project Optimizing the Design of a Hybrid Urban Mobility System: Grant G020222N; and Grant OR4Logistics]. Y. Molenbruch is partially funded by the Fonds Wetenschappelijk Onderzoek [Grant 1202719N]. The computational resources and services used in this work were provided by the Flemish Supercomputer Center funded by the Fonds Wetenschappelijk Onderzoek and the Flemish Government. Supplemental Material: The electronic companion is available at https://doi.org/10.1287/trsc.2023.1208 .
Relation Extraction for Knowledge Graph Generation in the Agriculture Domain: A Case Study on Soybean Pests and Disease
Authors: Wang Pengxiang , Zhang Cong , Wang Dingqian , Zhang Shaohua , Wang Jun , Wang Xianzhi , Huang Lan 
Published: April 2023

HighlightsWith the aim to reduce the burden of acquiring expert knowledge and strengthen the connection between written knowledge and the fields, this article investigated the problem of automatically extracting and organizing soybean pests and disease knowledge from text.Entities and relations were extracted using multiple models with deep neural network structures. Performance of these models were compared and evaluated in detail.A knowledge graph was automatically constructed using the extracted information, and made publicly available.ABSTRACT. Precision agriculture is an emerging type of agriculture that intensively uses information technology to automate agricultural production. Soybean (Glycine max (L.) Merri.), is an important crop in China, with an annual demand of approximately 110 million tons. However, in China, soybean production is threatened by more than 30 kinds of disease and 100 kinds of pests. With the rapidly increasing specialized information in the literature, it is difficult for farmers to keep up. Relation extraction automatically identifies and extracts structured knowledge from natural language text and thus can help to alleviate the problem. In this study, we propose to employ relation extraction to systematically extract information from expert-written text, and generate a knowledge graph from the extracted information. This case study was planned in China, therefore we mainly used Chinese texts. Firstly, we carefully chose expert-written text on soybean pests and disease, labeled the entities, and classified their thematic relations into five categories. Then, we built and trained three relation extraction models using state-of-the-art deep learning architectures and evaluated their performance on our task. Finally, we constructed an example knowledge graph from the extracted information and demonstrated their potential usage for automatic reasoning and solution recommendation for pests and disease prevention. In total, this study sampled 1038 entities and 1569 relation instances. Experimental results showed that our best model achieved an F1 score of 98.49% on identifying relations from text. Experimental results also showed the effectiveness of the example knowledge graph. Keywords: Bidirectional encoder representation from transformers, Knowledge graph, Relation extraction, Soybean pests and disease.
High-efficiency Ge-based waveguide photodetector integrated with a grating coupler on silicon-on-insulator
Authors: Zhang Junming , Jing Wenlong , Yuan Xixi , Miao Tian , Zhang Ningning , Wang Liming , Hu Huiyong 
Published: April 2023

We propose the design of a composite device structure with germanium-based (Ge-based) waveguide photodetectors integrated with grating couplers on a silicon-on-insulator platform. The finite-difference time-domain method is used to establish simulation models and optimize the design of the waveguide detector and grating coupler. For the grating coupler, by adjusting the size parameters to the optimal value and combining the advantages of the nonuniform grating and the Bragg reflector structure, the peak coupling efficiency reaches 85% at 1550 nm and 75.5% at 2000 nm, which is, respectively, 31.3% and 14.6% higher than that of uniform grating. For the waveguide detector, a germanium–tin (GeSn) alloy was introduced to replace Ge as the active absorption layer at 1550 and 2000 nm, which not only broadened the detection range and significantly improved the light absorption of the detector but also realized the near-complete light absorption of the GeSn alloy when the device length was 10 µm. These results make it possible to miniaturize the device structure of Ge-based waveguide photodetectors.
Does cognitive function impairment affect the duration of hospitalization and in-hospital mortality in geriatric patients hospitalized for COVID-19?
Authors: Janc Jarosław , Woźniak Anna , Leśnik Patrycja , Łysenko Lidia 
Published: April 2023

Aims
To assess the effect of cognitive function, performance of activities of daily living (ADLs), degree of depression, and fear of infection among geriatric patients hospitalized in internal medicine wards for COVID-19 on the duration of hospitalization and in-hospital mortality.

Methods
This observational survey study was conducted during the second, third, and fourth waves of the COVID-19 pandemic. The study included elderly patients of both sexes, aged ≥ 65 years, hospitalized for COVID-19 in internal medicine wards. The following survey tools were used: AMTS, FCV-19S, Lawton IADL, Katz ADL, and GDS15. The duration of hospitalization and in-hospital mortality were also assessed.

Results
A total of 219 patients were included in the study. The results showed that impaired cognitive function in geriatric patients (AMTS) was associated with higher in-hospital mortality among COVID-19 patients. There was no statistical significance between fear of infection (FCV-19S) and risk of death. The impaired ability to perform complex ADLs (Lawton IADL) before the onset of the disease was not associated with higher in-hospital mortality among COVID-19 patients. The diminished ability to perform basic ADLs (Katz ADL) before the onset of the disease was not associated with higher in-hospital mortality in COVID-19. The degree of depression (GDS15) was not associated with higher in-hospital mortality in COVID-19 patients. Statistically, significantly better survival was observed for patients with normal cognitive function (p = 0.005). No statistically significant differences in survival were observed in relation to the degree of depression or independence in performing ADLs. Cox proportional hazards regression analysis showed a statistically significant effect of age on mortality (p = 0.004, HR 1.07).

Conclusion
In this study, we observe that cognitive function impairments and the older age of patients treated for COVID-19 in the medical ward increase the in-hospital risk of death.
Efficient novel penultimate joint detector for shrimps selection employing convolutional pose machine
Authors: Zhang Haodong , Ren Tao , Dong Puqing , Dimirovski Georgi Marko 
Published: April 2023

Abstract
Manual labor involved in shrimp extraction selection accounts for an extremely high proportion of processing time and also entails reduced accuracy and efficiency moreover even it could induce potential safety hazards. The key to substitute the manual process with automation lies in the identification and pinpointing of the penultimate joint in shrimps. Therefore, a cascaded neural network is proposed in this study to implement the detection of key points in a multi-shrimp scenario processing. More specifically, our model includes two stages: a shrimp detector based on YOLOv3 and followed by a pose estimator based on Convolutional Pose Machine (CPM). With the combination of attention mechanism and improved NMS strategy, our detector is equipped to resist noise interference in dense case, ubiquitous on the production line. Experimental results indicate that both the detection rate and the speed information extraction have achieved the standard of industry applications.
Fetal brain activity and the free energy principle
Authors: Miyagi Yasunari , Hata Toshiyuki , Miyake Takahito 
Published: April 2023

Abstract

Objectives
To study whether the free energy principle can explain fetal brain activity and the existence of fetal consciousness via a chaotic dimension derived using artificial intelligence.

Methods
In this observational study, we used a four-dimensional ultrasound technique obtained to collect images of fetal faces from pregnancies at 27–37 weeks of gestation, between February and December 2021. We developed an artificial intelligence classifier that recognizes fetal facial expressions, which are thought to relate to fetal brain activity. We then applied the classifier to video files of facial images to generate each expression category’s probabilities. We calculated the chaotic dimensions from the probability lists, and we created and investigated the free energy principle’s mathematical model that was assumed to be linked to the chaotic dimension. We used a Mann–Whitney test, linear regression test, and one-way analysis of variance for statistical analysis.

Results
The chaotic dimension revealed that the fetus had dense and sparse states of brain activity, which fluctuated at a statistically significant level. The chaotic dimension and free energy were larger in the sparse state than in the dense state.

Conclusions
The fluctuating free energy suggests consciousness seemed to exist in the fetus after 27 weeks.