bluuebunny/crossref_metadata_2025_split huggingface dataset:
Character gated recurrent neural networks for Arabic sentiment analysis
Authors: Omara Eslam , Mousa Mervat , Ismail Nabil 
Published: June 2022

AbstractSentiment analysis is a Natural Language Processing (NLP) task concerned with opinions, attitudes, emotions, and feelings. It applies NLP techniques for identifying and detecting personal information from opinionated text. Sentiment analysis deduces the author's perspective regarding a topic and classifies the attitude polarity as positive, negative, or neutral. In the meantime, deep architectures applied to NLP reported a noticeable breakthrough in performance compared to traditional approaches. The outstanding performance of deep architectures is related to their capability to disclose, differentiate and discriminate features captured from large datasets. Recurrent neural networks (RNNs) and their variants Long-Short Term Memory (LSTM), Gated Recurrent Unit (GRU), Bi-directional Long-Short Term Memory (Bi-LSTM), and Bi-directional Gated Recurrent Unit (Bi-GRU) architectures are robust at processing sequential data. They are commonly used for NLP applications as they—unlike RNNs—can combat vanishing and exploding gradients. Also, Convolution Neural Networks (CNNs) were efficiently applied for implicitly detecting features in NLP tasks. In the proposed work, different deep learning architectures composed of LSTM, GRU, Bi-LSTM, and Bi-GRU are used and compared for Arabic sentiment analysis performance improvement. The models are implemented and tested based on the character representation of opinion entries. Moreover, deep hybrid models that combine multiple layers of CNN with LSTM, GRU, Bi-LSTM, and Bi-GRU are also tested. Two datasets are used for the models implementation; the first is a hybrid combined dataset, and the second is the Book Review Arabic Dataset (BRAD). The proposed application proves that character representation can capture morphological and semantic features, and hence it can be employed for text representation in different Arabic language understanding and processing tasks.
Association of weight change patterns across adulthood with incident asthma: a retrospective cohort study
Authors: Zhang Wei , Du Jie , Wang Shaochun , Ma Huihui 
Published: June 2022

AbstractThis study aimed to investigate the relationship between weight change patterns across adulthood and the risk of incident asthma later in life using data from the National Health and Nutrition Examination Survey (NHANES) 2001–2018. In this retrospective cohort study, asthma was defined by self-report questionnaires, and age at diagnosis was used to estimate the time of asthma onset. Based on BMI at 25 years old (young adulthood) and BMI at 10 years before the survey (middle adulthood), patterns of weight change were divided into five categories including stable normal, non-obese to obese, obese to non-obese, maximum overweight and stable obese. A total of 27,359 participants (female 13,582, 49.6%) were enrolled in this study and during a mean follow-up of 9.8 years, 1035 subjects occurred asthma. After adjusting for age, gender, race, education, family income and smoking status, participants changing from non-obese to obese, stable obese had significantly higher risks of incident asthma than those with normal weight during adulthood (HR1.70, 95% CI 1.35–2.15, P < 0.0001; HR 1.66, 95% CI 1.21–2.19 P = 0.0019, respectively). The findings suggested that maintaining normal weight during adulthood may be important for preventing incident asthma in later life.
Pricing risk-based catastrophe bonds for earthquakes at an urban scale
Authors: Mistry Harsh K. , Lombardi Domenico 
Published: June 2022

AbstractCatastrophe risk-based bonds are used by governments, financial institutions and (re)insurers to transfer the financial risk associated to the occurrence of catastrophic events, such as earthquakes, to the capital market. In this study, we show how municipalities prone to earthquakes can use this type of insurance-linked security to protect their building stock and communities from economic losses, and ultimately increase their earthquake resilience. We consider Benevento, a middle-sized historical town in southern Italy, as a case study, although the same approach is applicable to other urban areas in seismically active regions. One of the crucial steps in pricing catastrophe bonds is the computation of aggregate losses. We compute direct economic losses for each exposed asset based on high spatial resolution hazard and exposure models. Finally, we use the simulated loss data to price two types of catastrophe bonds (zero-coupon and coupon bonds) for different thresholds and maturity times. Although the present application focuses on earthquakes, the framework can potentially be applied to other natural disasters, such as hurricanes, floods, and other extreme weather events.
Immunotherapeutic effects of recombinant colorectal cancer antigen produced in tomato fruits
Authors: Park Se Hee , Ji Kon-Young , Park Seo Young , Kim Hyun Min , Ma Sang Hoon , Do Ju Hui , Kang Hyuno , Kang Hyung Sik , Oh Doo-Byoung , Shim Jae Sung , Joung Young Hee 
Published: June 2022

AbstractThe production of pharmacological vaccines in plants has been an important goal in the field of plant biotechnology. GA733-2, the protein that is also known as colorectal carcinoma (CRC)-associated antigen, is a strong candidate to produce a colorectal cancer vaccine. Tomato is the one of the major targets for production of an edible vaccine, as tomato is a fruit consumed in fresh form. It also contains high content of vitamins that aid activation of immune response. In order to develop an edible colorectal cancer vaccine, the transgene rGA733-Fc that encodes a fusion protein of GA733-2, the fragment crystallizable (Fc) domain, and the ER retention motif (rGA733-Fc) was introduced into tomato plants (Solanumlycopersicum cv. Micro-Tom). The transgenic plants producing rGA733-Fc (rGA733-FcOX) protein were screened based on stable integration of transgene expression cassette and expression level of rGA733-Fc protein. Further glycosylation pattern analysis revealed that plant derived rGA733-Fc protein contains an oligomannose glycan structure, which is a typical glycosylation pattern found on ER-processing proteins. The red fruits of rGA733-FcOX transgenic tomato plants containing approximately 270 ng/g FW of rGA733-Fc protein were orally administered to C57BL/6 mice. Oral administration of tomato fruits of the rGA733-Fc expressing transgenic plants delayed colorectal cancer growth and stimulated immune responses compared to oral administration of tomato fruits of the h-Fc expressing transgenic plants in the C57BL/6J mice. This is the first study showing the possibility of producing an edible colorectal cancer vaccine using tomato plants. This research would be helpful for development of plant-derived cancer edible vaccines.
Ultra-sensitive gas sensor based fano resonance modes in periodic and fibonacci quasi-periodic Pt/PtS2 structures
Authors: Zaki Shrouk E. , Basyooni Mohamed A. 
Published: June 2022

AbstractUltra-sensitive greenhouse gas sensors for CO2, N2O, and CH4 gases based on Fano resonance modes have been observed through periodic and quasi-periodic phononic crystal structures. We introduced a novel composite based on metal/2D transition metal dichalcogenides (TMDs), namely; platinum/platinum disulfide (Pt/PtS2) composite materials. Our gas sensors were built based on the periodic and quasi-periodic phononic crystal structures of simple Fibonacci (F(5)) and generalized Fibonacci (FC(7, 1)) quasi-periodic phononic crystal structures. The FC(7, 1) structure represented the highest sensitivity for CO2, N2O, and CH4 gases compared to periodic and F(5) phononic crystal structures. Moreover, very sharp Fano resonance modes were observed for the first time in the investigated gas sensor structures, resulting in high Fano resonance frequency, novel sensitivity, quality factor, and figure of merit values for all gases. The FC(7, 1) quasi-periodic structure introduced the best layer sequences for ultra-sensitive phononic crystal greenhouse gas sensors. The highest sensitivity was introduced by FC(7, 1) quasiperiodic structure for the CH4 with a value of 2.059 (GHz/m.s−1). Further, the temperature effect on the position of Fano resonance modes introduced by FC(7, 1) quasi-periodic PhC gas sensor towards CH4 gas has been introduced in detail. The results show the highest sensitivity at 70 °C with a value of 13.3 (GHz/°C). Moreover, the highest Q and FOM recorded towards CH4 have values of 7809 and 78.1 (m.s−1)−1 respectively at 100 °C.
Simulating the effect of different lighting conditions on left-turn driving behavior using a scenario-based anger method
Authors: He Wu , Xiong Jing Jing , Wang Xuan , Mao Yan 
Published: June 2022

AbstractAnger is a key factor affecting drivers' subjective judgment and driving skills. The influence of anger on driving behavior has been widely studied, but there is a lack of comparative research under different lighting conditions. Through a driving simulation experiment, this paper studies the influence of anger on left-turn driving behavior under two light conditions day and night. In the experiment, 32 licensed participants were divided into two groups, one in emotional neutrality and the other in anger. Among them, the emotional state of anger is induced by a traffic-related video. The results showed that compared with daytime participants, participants at night had higher anger intensity, shorter gap acceptance, and post encroachment time (PET) when left-turn driving. In addition, compared with neutral emotion participants, angry participants tended to accept shorter gap acceptance and PET when turning left. This indicates that participants failed to respond correctly to left-turn driving behavior in a state of anger. However, the response of gender differences to situational driving anger was not affected by light conditions. The anger intensity of male participants during the day and night was higher than that of female participants, and the gap between acceptance and PETs during left-turn was shorter than that of female participants. This shows that male participants are more likely to produce high-intensity anger and are more likely to make dangerous driving decisions in a state of anger. This paper puts forward some suggestions on identifying anger and preventing angry driving.
Piezo1 is the cardiac mechanosensor that initiates the cardiomyocyte hypertrophic response to pressure overload in adult mice
Authors: Yu Ze-Yan , Gong Hutao , Kesteven Scott , Guo Yang , Wu Jianxin , Li Jinyuan Vero , Cheng Delfine , Zhou Zijing , Iismaa Siiri E. , Kaidonis Xenia , Graham Robert M. , Cox Charles D. , Feneley Michael P. , Martinac Boris 
Published: June 2022

AbstractPressure overload-induced cardiac hypertrophy is a maladaptive response with poor outcomes and limited treatment options. The transient receptor potential melastatin 4 (TRPM4) ion channel is key to activation of a Ca2+/calmodulin-dependent kinase II (CaMKII)-reliant hypertrophic signaling pathway after pressure overload, but TRPM4 is neither stretch-activated nor Ca2+-permeable. Here we show that Piezo1, which is both stretch-activated and Ca2+-permeable, is the mechanosensor that transduces increased myocardial forces into the chemical signal that initiates hypertrophic signaling via a close physical interaction with TRPM4. Cardiomyocyte-specific deletion of Piezo1 in adult mice prevented activation of CaMKII and inhibited the hypertrophic response: residual hypertrophy was associated with calcineurin activation in the absence of its usual inhibition by activated CaMKII. Piezo1 deletion prevented upregulation of the sodium–calcium exchanger and changes in other Ca2+ handling proteins after pressure overload. These findings establish Piezo1 as the cardiomyocyte mechanosensor that instigates the maladaptive hypertrophic response to pressure overload, and as a potential therapeutic target.
Tunable fluorescent amino-functionalized Ti3C2Tx MXene quantum dots for ultrasensitive Fe3+ ion sensing
Authors: Wang Zhiwei , Zhu Yuanhang , Wu Yuchen , Ding Weiyuan , Li Xiuting 
Published: June 2022

The amino-rich Ti3C2Tx QDs exhibit superior fluorescent probe behavior for Fe3+ ion detection for environmental analysis.
A novel nano‐scale architecture of Vedic multiplier using majority logic in quantum‐dot cellular automata technology
Authors: Huang Junjun , Lale S. 
Published: June 2022

AbstractQuantum‐dot cellular automata (QCA) is a useful nano‐scale technology that uses less space and energy than complementary metal oxide semiconductor (CMOS) for circuits designing. Innovative digital automation continually strives for increased density while consuming very little power. QCA, which is based on Coulomb repulsion, is one of the most recent nanotechnologies. On the other hand, derived computing could serve as a useful prototype for energy‐efficient nano‐scale layouts. A multiplier is an important component of various digital circuits. On the basis of QCA, promising nanotechnology, a high‐speed and simple multiplier is constructed in this study. This research focuses on multiplier designs based on two‐bit Vedic multiplier mathematics. The authors use the QCADesigner‐E modelling environment to develop an ultra‐efficient and less complicated two‐bit Vedic multiplier with the assistance of the majority gate for low‐energy and high‐speed nanotechnology applications. Compared with other current structures, the suggested architecture has a reduced cell count and area. Furthermore, simulation findings showed that the suggested design is long‐term viable and may be utilized to implement complicated circuit designs for nano‐communication networks.
Battery voltage fault diagnosis for electric vehicles considering driving condition variation
Authors: Zhang Hui , Li Shaopeng , Chen Feng , Pan Xiaofeng , Feng Hongxia , Sun Yifan 
Published: June 2022

AbstractTo ensure the real‐time operation safety of electric vehicles (EVs), it is essential to diagnose the fault in a battery pack timely and accurately. In this paper, with considering driving condition, a battery voltage fault diagnosis method is proposed based on the real‐world operation data of EVs with a high sampling frequency. Firstly, based on driving behaviour, the driving condition of EVs is classified into four categories, and accordingly, the operation process is divided into four segments. The influencing mechanism of driving condition on battery voltage is revealed by detailed analysis on extracted operation segments. Secondly, four BP neural network (BPNN)‐based voltage prediction models are developed, respectively, for the four kinds of driving conditions. Based on the statistical analysis of prediction error and the comparison with other voltage prediction models, the superiority and stability of the four well‐trained BPNN models are verified. Thirdly, the voltage abnormity levels and thresholds for fault diagnosis are set considering driving condition differences. The effectiveness of the proposed method is verified using the actual operational data. The verification results show that the proposed method can achieve good voltage prediction and fault diagnosis for EVs under various driving conditions during the entire operation process.
A deep learning network based on multi-scale and attention for the diagnosis of chronic atrophic gastritis
Authors: Chong Yanwen , Xie Ningdi , Liu Xin , Zhang Meng , Huang Fengxing , Fang Jun , Wang Fan , Pan Shaoming , Nie Haihang , Zhao Qiu 
Published: June 2022

Abstract
Background and study aim Chronic atrophic gastritis plays an important role in the process of gastric cancer. Deep learning is gradually introduced in the medical field, and how to better apply a convolutional neural network (CNN) to the diagnosis of chronic atrophic gastritis remains a research hotspot. This study was designed to improve the performance of CNN on diagnosing chronic atrophic gastritis by constructing and evaluating a network structure based on the characteristics of gastroscopic images.
Methods Three endoscopists reviewed the endoscopic images of the gastric antrum from the Gastroscopy Image Database of Zhongnan Hospital and labelled available images according to pathological results. Two novel modules proposed recently were introduced to construct the Multi-scale with Attention net (MWA-net) considering the characters of similar medical images. After training the network using images of training sets, the diagnostic ability of the MWA-net was evaluated by comparing it with those of other deep learning models and endoscopists with varying degrees of expertise.
Results As a result, 5,159 images of the gastric antrum from 2,240 patients were used to train and test the MWA-net. Compared with the direct application of famous networks, the MWA-net achieved the best performance (accuracy, 92.13%) with an increase of 1.80% compared to that of ResNet. The suspicious lesions indicated by the network are consistent with the conclusion of experts. The sensitivity and specificity of the convolutional network for gastric atrophy diagnosis are 90.19% and 94.51%, respectively, which are higher than those of experts.
Conclusions Highly similar images of chronic atrophic gastritis can be identified by the proposed MWA-net, which has a better performance than other well-known networks. This work can further reduce the workload of gastroscopists, simplify the diagnostic process and provide medical assistance to more residents.
Aryl Ketone Mediated Light-Driven Naphthylation of C(sp3)–H Bonds Attached to either Oxygen or Nitrogen Substituents
Authors: Kamijo Shin , Azami Masaya , Murafuji Toshihiro 
Published: June 2022

AbstractA light-driven naphthylation was achieved at C(sp3)–H bonds attached to either oxygen or nitrogen substituents using sulfonylnaphthalenes as a naphthalene precursor in the presence of 4-benzoylpyridine at ambient temperature. The present transformation is proposed to proceed through the generation of a carbon radical species via chemoselective cleavage of the heteroatom-substituted C(sp3)–H bond by photoexcited 4-benzoylpyridine, the addition of the derived carbon radical to the electron-deficient sulfonylnaphthalene, and then rearomatization by releasing sulfinyl radical.
Mild Synthesis of Symmetric 3,5-Disubstituted Nitrobenzenes
Authors: Silva Artur M. S. , Albuquerque Hélio M. T. , Francisco Telmo N. , Sousa Joana L. C. , Guieu Samuel 
Published: June 2022

AbstractA mild synthesis of 3,5-disubstituted nitrobenzenes from readily available 3-formylchromones is reported. The developed methodology follows a cascade process, promoted by 1,8-diazabicyclo[5.4.0]undec-7-ene. The proposed mechanism involves an initial Michael addition of nitromethane at C-2 of a 3-formylchromone. The resultant intermediate undergoes another Michael reaction with a second 3-formylchromone molecule. After ring closure through intramolecular cyclization, the aromatization is completed by deformylation, affording the 3,5-disubstituted nitrobenzenes in 52–86% yield. The reported method produces three new C–C bonds in a simple and straightforward manner, and it is consistent with gram-scale synthesis.
Rivaroxaban Underdose for Atrial Fibrillation with Stable Coronary Disease: The AFIRE Trial Findings
Authors: Arashi Hiroyuki , Yamaguchi Junichi , Hagiwara Nobuhisa , Yasuda Satoshi , Kaikita Koichi , Akao Masaharu , Ako Junya , Matoba Tetsuya , Nakamura Masato , Miyauchi Katsumi , Kimura Kazuo , Hirayama Atsushi , Matsui Kunihiko , Ogawa Hisao ,   on behalf of the AFIRE investigators
Published: June 2022

Abstract
Background Rivaroxaban monotherapy was noninferior to combination therapy (rivaroxaban plus antiplatelet therapy) in efficacy but superior in safety in the Atrial Fibrillation and Ischemic Events with Rivaroxaban in Patients with Stable Coronary Artery Disease (AFIRE) trial. Among 2,215 patients with atrial fibrillation (AF) and stable coronary artery disease (CAD), 1,378 had baseline creatinine clearance (CrCl) ≥50 mL/min and received 10 (underdose) or 15 mg/d (standard-dose) rivaroxaban. We aimed to assess the effects of rivaroxaban underdose on clinical outcomes.
Methods We assessed efficacy endpoint (a composite of stroke, systemic embolism, myocardial infarction, unstable angina requiring revascularization, and death from any cause) and major bleeding in the subgroup of patients with preserved renal function in the AFIRE trial.
Results Age ≥75 years, female sex, lower CrCl, heart failure, and percutaneous coronary intervention history were associated with the underdose prescription. The underdose group had a similar incidence of the efficacy endpoint (3.62 vs. 3.51% per patient-year; p = 0.871) and significantly lower incidence of major bleeding (0.82 vs. 2.17% per patient-year; p = 0.022) than the standard-dose group. In patients receiving monotherapy, the incidences of efficacy endpoint and major bleeding were similar between the groups, whereas in those receiving combination therapy, the incidence of major bleeding was significantly lower in the underdose group than that in the standard-dose group.
Conclusion In patients with AF, stable CAD, and preserved renal function, rivaroxaban underdose was associated with similar rates of thrombotic events but a lower incidence of hemorrhagic events than the standard dose.
Clinical Trial Registration AFIRE UMIN Clinical Trials Registry (https://www.umin.ac.jp/ctr/), number UMIN000016612, and ClinicalTrials.gov, number NCT02642419.
Evaluation of Patients Presenting to the Pediatric Emergency Department with Seizures during the COVID-19 Pandemic
Authors: Tekin Emine , Diler Durgut Betül , Akoğlu Handan Ayhan 
Published: June 2022

AbstractThe coronavirus disease 2019 pandemic has led to significant changes in hospital visits worldwide. The admission rates have remarkably decreased. This study investigates the characteristics of 104 patients (54 girls, 50 boys) who presented to our pediatric emergency department (ED) with seizures during the pandemic between May 2020 and May 2021. Regarding seizure type, 84 generalized and 20 focal seizures had occurred. Tonic, tonic–clonic, clonic, and hypomotor seizures were seen in descending order. Thirty-seven patients were diagnosed with epilepsy, and 32 patients with first afebrile, 25 first febrile, and 10 recurrent febrile seizures. No patients had acute symptomatic seizures. In 85 patients, the seizures had stopped before the ED visit; only one lasted >60 minutes. Benzodiazepines were administered as a first-line drug. Demographical features, electroencephalogram (EEG), and cranial imaging findings, laboratory test results, and distribution by month and by the hour of ED visit were analyzed. Study data was in accordance with the literature by seizure types, seizure management, and cranial imaging rates but differed by distribution in terms of month and the hour of ED visit. The EEG abnormality rate was higher among the first afebrile seizure cases. The number of patients with seizures was 69, that is, 0.3% of emergency admissions, for the 4 months of 2019 before the pandemic, and 104, that is, 0.4% of emergency admissions for the whole initial year of the pandemic thereafter. So, the number of patients with seizures had decreased, but their rate had increased, which could be attributed to a decrease in the number of nonurgent presentations to the ED during the pandemic.