bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnostic Potential of Exosomal microRNAs in Colorectal Cancer
Authors: Dohmen Jonas , Semaan Alexander , Kobilay Makbule , Zaleski Martin , Branchi Vittorio , Schlierf Anja , Hettwer Karina , Uhlig Steffen , Hartmann Gunther , Kalff Jörg C. , Matthaei Hanno , Lingohr Philipp , Holdenrieder Stefan
Published: June 2022

Background: Despite the significance of colonoscopy for early diagnosis of colorectal adenocarcinoma (CRC), population-wide screening remains challenging, mainly because of low acceptance rates. Herein, exosomal (exo-miR) and free circulating microRNA (c-miR) may be used as liquid biopsies in CRC to identify individuals at risk. Direct comparison of both compartments has shown inconclusive results, which is why we directly compared a panel of 10 microRNAs in this entity. Methods: Exo-miR and c-miR levels were measured using real-time quantitative PCR after isolation from serum specimens in a cohort of 69 patients. Furthermore, results were compared to established tumor markers CEA and CA 19-9. Results: Direct comparison of exo- and c-miR biopsy results showed significantly higher microRNA levels in the exosomal compartment (p < 0.001). Exo-Let7, exo-miR-16 and exo-miR-23 significantly differed between CRC and healthy controls (all p < 0.05), while no c-miR showed this potential. Sensitivity and specificity can be further enhanced using combinations of multiple exosomal miRNAs. Conclusions: Exosomal microRNA should be considered as a promising biomarker in CRC for future studies. Nonetheless, results may show interference with common comorbidities, which must be taken into account in future studies.
Quantitation of a Urinary Profile of Biomarkers in Gaucher Disease Type 1 Patients Using Tandem Mass Spectrometry
Authors: Menkovic Iskren , Boutin Michel , Alayoubi Abdulfatah , Curado Filipa , Bauer Peter , Mercier François E. , Auray-Blais Christiane
Published: June 2022

Gaucher disease is a rare inherited disorder caused by a deficiency of the lysosomal acid beta-glucocerebrosidase enzyme. Metabolomic studies by our group targeted several new potential urinary biomarkers. Apart from lyso-Gb1, these studies highlighted lyso-Gb1 analogs −28, −26, −12 (A/B), +2, +14, +16 (A/B), +30, and +32 Da, and polycyclic lyso-Gb1 analogs 362, 366, 390, and 394 Da. The main objective of the current study was to develop and validate a robust UPLC-MS/MS method to study the urine distribution of these biomarkers in patients. Method: Urine samples were purified using solid-phase extraction. A 12 min UPLC-MS/MS method was developed. Results: Validation assays revealed high precision and accuracy for creatinine and lyso-Gb1. Most lyso-Gb1 analogs had good recovery rates and high intra- and interday precision assays. Biomarker-estimated LOD and LOQ levels ranged from 56–109 pM to 186–354 pM, respectively. Comparison between GD patients and healthy controls showed significant differences in most biomarker levels. Typically, treated GD patients presented lower biomarker levels compared to untreated patients. Conclusions: These data suggest that the metabolites investigated might be interesting GD biomarkers. More studies with a larger cohort of patients will be needed to better understand the clinical significance of these GD biomarkers.
Advances in OCT Imaging in Myopia and Pathologic Myopia
Authors: Li Yong , Zheng Feihui , Foo Li Lian , Wong Qiu Ying , Ting Daniel , Hoang Quan V. , Chong Rachel , Ang Marcus , Wong Chee Wai
Published: June 2022

Advances in imaging with optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) technology, including the development of swept source OCT/OCTA, widefield or ultra-widefield systems, have greatly improved the understanding, diagnosis, and treatment of myopia and myopia-related complications. Anterior segment OCT is useful for imaging the anterior segment of myopes, providing the basis for implantable collamer lens optimization, or detecting intraocular lens decentration in high myopic patients. OCT has enhanced imaging of vitreous properties, and measurement of choroidal thickness in myopic eyes. Widefield OCT systems have greatly improved the visualization of peripheral retinal lesions and have enabled the evaluation of wide staphyloma and ocular curvature. Based on OCT imaging, a new classification system and guidelines for the management of myopic traction maculopathy have been proposed; different dome-shaped macula morphologies have been described; and myopia-related abnormalities in the optic nerve and peripapillary region have been demonstrated. OCTA can quantitatively evaluate the retinal microvasculature and choriocapillaris, which is useful for the early detection of myopic choroidal neovascularization and the evaluation of anti-vascular endothelial growth factor therapy in these patients. In addition, the application of artificial intelligence in OCT/OCTA imaging in myopia has achieved promising results.
Sarcoidosis Mimicking Primary Lung Cancer on 99mTc-3PRGD2 Scintigraphy in a PTC Patient
Authors: Yang Ye , Jia Xi , Wang Yuanbo , Liu Yan , Liu Yu , Gao Rui
Published: June 2022

Sarcoidosis is a multi-system disease of unknown etiology that typically occurs in middle-aged adults, often presenting as the formation of granulomas in various organs, including the lungs. Non-typical pulmonary sarcoidosis is rare, and it isnecessary to distinguish its imaging features from lung cancer and tuberculosis. They may appear as an irregular mass with multiple nodules on thoracic computed tomography (CT). In this case, primary lung cancer was suspected in a 57-year-old papillary thyroid carcinoma patient, as the pulmonary lesions were non-radioiodine avid and progressed shortly afterward. The asymmetrical focal uptake that was demonstrated in integrin receptor imaging (99mTc-PEG4-E[PEG4-c(RGDfK)]2 (99mTc-3PRGD2)) warranted flexible-bronchoscope biopsy. Meanwhile, no evidence of malignancy was found, and pathological manifestations led to the subsequent six months of anti-tuberculosis treatment. Combined with the fact that standard anti-tuberculosis showed no improvement, and the patient’s condition was stabilized by corticosteroid treatment alone, a final diagnosis of sarcoidosis was made by an MDT (multidisciplinary consultation). Reported herein is the first case of a hyper vascularization condition within the non-typical asymmetrical sarcoidosis lesions, which should help to establish that the uptake of 3PRDG2 in sarcoidosis can avoid imaging pitfalls.
Evaluating the Impact of High Intensity Interval Training on Axial Psoriatic Arthritis Based on MR Images
Authors: Chronaiou Ioanna , Giskeødegård Guro Fanneløb , Neubert Ales , Hoffmann-Skjøstad Tamara Viola , Thomsen Ruth Stoklund , Hoff Mari , Bathen Tone Frost , Sitter Beathe
Published: June 2022

High intensity interval training (HIIT) has been shown to benefit patients with psoriatic arthritis (PsA). However, magnetic resonance (MR) imaging has uncovered bone marrow edema (BME) in healthy volunteers after vigorous exercise. The purpose of this study was to investigate MR images of the spine of PsA patients for changes in BME after HIIT. PsA patients went through 11 weeks of HIIT (N = 19, 4 men, median age 52 years) or no change in physical exercise habits (N = 20, 8 men, median age 45 years). We acquired scores for joint affection and pain and short tau inversion recovery (STIR) and T1-weighted MR images of the spine at baseline and after 11 weeks. MR images were evaluated for BME by a trained radiologist, by SpondyloArthritis Research Consortium of Canada (SPARCC) scoring, and by extraction of textural features. No significant changes of BME were detected in MR images of the spine after HIIT. This was consistent for MR image evaluation by a radiologist, by SPARCC, and by texture analysis. Values of textural features were significantly different in BME compared to healthy bone marrow. In conclusion, BME in spine was not changed after HIIT, supporting that HIIT is safe for PsA patients.
Diagnosis of Tooth Prognosis Using Artificial Intelligence
Authors: Lee Sang J. , Chung Dahee , Asano Akiko , Sasaki Daisuke , Maeno Masahiko , Ishida Yoshiki , Kobayashi Takuya , Kuwajima Yukinori , Da Silva John D. , Nagai Shigemi
Published: June 2022

The accurate diagnosis of individual tooth prognosis has to be determined comprehensively in consideration of the broader treatment plan. The objective of this study was to establish an effective artificial intelligence (AI)-based module for an accurate tooth prognosis decision based on the Harvard School of Dental Medicine (HSDM) comprehensive treatment planning curriculum (CTPC). The tooth prognosis of 2359 teeth from 94 cases was evaluated with 1 to 5 levels (1—Hopeless, 5—Good condition for long term) by two groups (Model-A with 16, and Model-B with 13 examiners) based on 17 clinical determining factors selected from the HSDM-CTPC. Three AI machine-learning methods including gradient boosting classifier, decision tree classifier, and random forest classifier were used to create an algorithm. These three methods were evaluated against the gold standard data determined by consensus of three experienced prosthodontists, and their accuracy was analyzed. The decision tree classifier indicated the highest accuracy at 0.8413 (Model-A) and 0.7523 (Model-B). Accuracy with the gradient boosting classifier and the random forest classifier was 0.6896, 0.6687, and 0.8413, 0.7523, respectively. Overall, the decision tree classifier had the best accuracy among the three methods. The study contributes to the implementation of AI in the decision-making process of tooth prognosis in consideration of the treatment plan.
Transcatheter Arterial Embolization (TAE) Using N-Butyl-2-cyanoacrylate (NBCA) as the First Choice for Postpartum Vulvovaginal Hematoma; Case Series and Reviews of the Literature
Authors: Misugi Takuya , Hamuro Akihiro , Kitada Kohei , Kurihara Yasushi , Tahara Mie , Terayama Eisaku , Kageyama Ken , Yamamoto Akira , Tachibana Daisuke
Published: June 2022

Transcatheter arterial embolization (TAE) has long been reported to be safe, effective, and to have a high clinical and technical success rate for vulvovaginal hematoma. We used a permanent embolic material, diluted N-butyl-2-cyanoacrylate (NBCA), for the first choice intervention for six cases of vulvovaginal hematoma, in order to confirm the effectiveness of NBCA. Regarding post-embolization adverse events, we did not observe any fever nor necrosis or pain in the vaginal wall or vulva, in all cases. The use of NBCA as a first-line treatment for TAE of vulvovaginal hematoma is considered to be effective, in the following two ways: First, hemostasis can be achieved by adjusting the mixing ratio of NBCA and lipiodol, according to the distance between the tip of the catheter and the site of injury. Second, NBCA does not cause complications such as pain, necrosis, or infection, and it can be used safely. There are no reports clearly recommending NBCA as the first choice in the treatment of TAE for vulvovaginal hematoma. This is the first report to examine the efficacy and safety of NBCA as the first-line intervention for such cases.
The Effect of Face Masks during COVID-19 Pandemic on Ocular Surface Temperature—A Clinical Thermographic Analysis
Authors: Kapelushnik Noa , Benyosef Shahar , Skaat Alon , Abdelkader Amir , Landau Prat Daphna , Blum-Meirovitch Sharon , Leshno Ari
Published: June 2022

Due to the COVID-19 pandemic, the center for disease control and prevention (CDC) recommends face-mask wearing for all people above the age of two years. The wearing of face masks creates a unique airflow towards the ocular surface which may influence the normal physiological conditions of the ocular and periocular surface. Healthy subjects with no ocular history were enrolled in this cross-sectional study. The Therm-App thermal imaging camera was used for ocular surface temperature (OST) measurements during inspirium and expirium. Five regions of interest (ROIs) were used to measure OST: medial conjunctive, cornea, lateral conjunctive, upper eyelid and entire orbital area. Additional measurements in the same locations were made with the upper margin of the mask taped with micropore surgical tape. Thirty-one patients were included in this study. OST during expirium was significantly higher compared to the temperature during inspirium in all locations measured (p < 0.001, paired samples t-test). The temperature of the upper eyelid was higher by more than 0.5 °C during expirium. Taping the mask’s upper edges to the skin resulted in non-significant temperature changes in inspirium vs. expirium. In conclusion, wearing a face mask creates air flow towards the periocular and ocular surface, which changes the OST mostly on the eyelids.
Criteria for the Classification of the Interradicular Septum Shape in Maxillary Molars with Clinical Importance for Prosthetic-Driven Immediate Implant Placement
Authors: Milenkovic Jovana , Vasiljevic Milica , Jovicic Nemanja , Milovanovic Dragan , Selakovic Dragica , Rosic Gvozden
Published: June 2022

The aim of this study was to use cone-beam computed tomography (CBCT) to evaluate the morphometric properties of the interradicular septum (IRS) in the maxillary molar region that may be indicative for prosthetic-driven implant placement. Following the repetitive algorithm based on the visual identification of IRS shapes, we described the following IRS shapes: arrow, boat, drop, and palatal and buccal convergence. The incidence of IRS shapes showed significant differences for the first and second maxillary molars (the highest frequency for the arrow shape, and the lowest for the drop shape) with no significant difference between the molars. The most prominent width indicative for implant placement was observed in the palatal convergence shape, whereas the height criteria were the most satisfying in the buccal convergence-shaped IRS for both molars. Apart from the parameters in the coronal view, the image analysis in the axial view revealed that IRS surface area, required for the implant placement, was the most prominent in the palatal convergence shape for the first, and boat shape for the second molars. Our results showed the benefits of CBCT diagnostics in posterior maxilla morphometric analysis. IRS shape classification may be helpful in achieving more rapid and accurate planning for interventions in this region.
Diagnostics of COVID-19 Based on CRISPR–Cas Coupled to Isothermal Amplification: A Comparative Analysis and Update
Authors: Hernandez-Garcia Armando , Morales-Moreno Melissa D. , Valdés-Galindo Erick G. , Jimenez-Nieto Eric P. , Quezada Andrea
Published: June 2022

The emergence of the COVID-19 pandemic prompted fast development of novel diagnostic methods of the etiologic virus SARS-CoV-2. Methods based on CRISPR–Cas systems have been particularly promising because they can achieve a similar sensitivity and specificity to the benchmark RT-qPCR, especially when coupled to an isothermal pre-amplification step. Furthermore, they have also solved inherent limitations of RT-qPCR that impede its decentralized use and deployment in the field, such as the need for expensive equipment, high cost per reaction, and delivery of results in hours, among others. In this review, we evaluate publicly available methods to detect SARS-CoV-2 that are based on CRISPR–Cas and isothermal amplification. We critically analyze the steps required to obtain a successful result from clinical samples and pinpoint key experimental conditions and parameters that could be optimized or modified to improve clinical and analytical outputs. The COVID outbreak has propelled intensive research in a short time, which is paving the way to develop effective and very promising CRISPR–Cas systems for the precise detection of SARS-CoV-2. This review could also serve as an introductory guide to new labs delving into this technology.
Efficiency and Safety of Dental Implantation in the Area of Hyperdense Jaw Lesions: A Narrative Review
Authors: Taghsimi Kimya , Vasilyev Andrey Vyacheslavovich , Kuznetsova Valeriya Sergeevna , Galtsova Angelina Vladimirovna , Badalyan Varditer Agabekovna , Babichenko Igor Ivanovich
Published: June 2022

Background. Mineralized lesions of the jaws are often found incidentally on radiographs and computed tomography. Most of them are benign, and only a few rare cases are associated with malignant transformation. However, there is little clinical data on successful rehabilitation with implants in patients with mineralized lesions. This narrative review aimed to study the efficiency and safety of dental implantation in the area of hyperdense lesions. Materials and Methods. A PubMed, Google Scholar, and Science Direct database search was carried out with keywords and manually. Results. The literature exploration identified 323 articles; only 19 of them matched the search criteria and reported cases about dental implantation in the lesion area. It has been shown that in 84.2% of described cases, dental implantation was successful: in the osteoid osteoma, odontoma, cementoblastoma, idiopathic osteosclerosis, and condensing osteitis areas dental implantation was performed without any complications. The possibility of lesion recurrence and implant failure limited the use of dental implants in the area of osteoblastoma and cemento-osseous dysplasia. Although most cases of dental implantation in hyperdense jaw lesions were successful and were not accompanied by complications, further research is needed.
Casorati Inequalities for Statistical Submanifolds in Kenmotsu Statistical Manifolds of Constant ϕ-Sectional Curvature with Semi-Symmetric Metric Connection
Authors: Decu Simona , Vîlcu Gabriel-Eduard
Published: June 2022

In this paper, we prove some inequalities between intrinsic and extrinsic curvature invariants, namely the normalized δ-Casorati curvatures and the scalar curvature of statistical submanifolds in Kenmotsu statistical manifolds of constant ϕ-sectional curvature that are endowed with semi-symmetric metric connection. Furthermore, we investigate the equality cases of these inequalities. We also describe an illustrative example.
Retrieval and Ranking of Combining Ontology and Content Attributes for Scientific Document
Authors: Jiang Xinyu , Tian Bingjie , Tian Xuedong
Published: June 2022

Traditional mathematical search models retrieve scientific documents only by mathematical expressions and their contexts and do not consider the ontological attributes of scientific documents, which result in gaps between the queries and the retrieval results. To solve this problem, a retrieval and ranking model is constructed that synthesizes the information of mathematical expressions with related texts, and the ontology attributes of scientific documents are extracted to further sort the retrieval results. First, the hesitant fuzzy set of mathematical expressions is constructed by using the characteristics of the hesitant fuzzy set to address the multi-attribute problem of mathematical expression matching; then, the similarity of the mathematical expression context sentence is calculated by using the BiLSTM two-way coding feature, and the retrieval result is obtained by synthesizing the similarity between the mathematical expression and the sentence; finally, considering the ontological attributes of scientific documents, the retrieval results are ranked to obtain the final search results. The MAP_10 value of the mathematical expression retrieval results on the Ntcir-Mathir-Wikipedia-Corpus dataset is 0.815, and the average value of the NDCG@10 of the scientific document ranking results is 0.9; these results prove the effectiveness of the scientific document retrieval and ranking method.
Blockchain-Based Traceability System to Support the Indonesian Halal Supply Chain Ecosystem
Authors: Alamsyah Andry , Hakim Naufal , Hendayani Ratih
Published: June 2022

The halal industry is constantly developing into a broader concept of the Islamic economy, an economic activity that follows the Islamic-based principle. As a populous Muslim country, Indonesia follows the growth trend by aiming to dominate the global halal market. The strategy is to improve the current halal assurance process. Presently, the technology and procedure do not provide enough process transparency, traceability, and granularity of information. To achieve the strategic goal, a technological change is needed. A new emerging technology, blockchain, may potentially answer the challenge. This study’s first objective is to discuss improving the current assurance practice in the Indonesian halal supply chain ecosystem, particularly in the meat industry. The second objective is to construct a traceability system model for the supply chain. Our goal is to propose a blockchain-based halal traceability system model. The model can be enhanced to be a national standard tool to develop the economy towards a sustainable supply chain.
Mathematics Anxiety and Self-Efficacy of Mexican Engineering Students: Is There Gender Gap?
Authors: Morán-Soto Gustavo , González-Peña Omar Israel
Published: June 2022

Studies have reported that there is a gender disparity wherein women do not study equally to men in bachelor’s degrees in science, technology, engineering, and math (STEM) areas, although they lead the race of having a better terminal efficiency rate in higher education. This research explores engineering students’ math anxiety and math self-efficacy levels, aiming to determine if there is a gender gap for this specific population. Data were collected from 498 students using adapted items from existing surveys. These items were translated to Spanish, and validity tests were used to establish content validity and reliability. A multivariate analysis of variance (MANOVA) was used to determine possible differences between male and female math anxiety and math self-efficacy levels. Male engineering students reported higher self-efficacy and lower math anxiety levels, and this difference was shown to be significant according to the MANOVA results. Findings of this research could help engineering educators to better understand how their students feel when they are practicing and performing math-related activities and what type of strategies could be designed when aiming to ameliorate female students’ math anxiety feelings.
Teaching 21st Century Skills in Saudi Arabia with Attention to Elementary Science Reading Habits
Authors: Alotaibi Wadha H. , Alghamdi Amani Khalaf H.
Published: June 2022

Saudi Arabia’s Vision 2030 urges the teaching of 21st century skills. This study involved female elementary science teachers (n = 55) and students (n = 232) (intentionally taught using science reading and not intentionally taught this way) in two offices of a Saudi Eastern Province school board. Descriptive statistical analyses of teachers’ beliefs and students’ thoughts on science reading revealed key results. Most teachers believed that students had a high degree of eagerness and passion to learn science, were always passionate and eager to read scientific texts, had a high desire to participate in class discussions of scientific readings, and had a moderate understanding of what they had read. However, the students were more ambivalent. Students who were intentionally taught using science reading scored higher on reading tendencies than those not intentionally taught this way. These statistically insignificant results were interpreted to further garner insights into the Saudi context that is fully grounded in Islam, which deeply values reading.
A Structural Model to Explain Influences of Organisational Communication on the Organisational Commitment of Primary School Staff
Authors: De Nobile John , Bilgin Ayse Aysin
Published: June 2022

Organisational commitment is a job attitude frequently linked to employee morale, motivation and behaviour. High organisational commitment has been associated with increased effort and productivity, while low commitment has been associated with low productivity, absenteeism and turnover. There is evidence to suggest aspects of organisational communication are important in this regard. This article reports the results of a study that investigated the relationships between a comprehensive set of aspects of organisational communication and general organisational commitment, while also identifying those that had the most important effects on organisational commitment. Participants were 1575 staff members from government and non-government primary schools across all states and territories of Australia. Data were gathered using a survey comprising the Organisational Communication in Primary Schools Questionnaire and a five-item general organisational commitment scale. Exploratory and confirmatory factor analyses were used to identify and validate constructs for measurement. Structural equation modelling was used to identify important relationships. Of the ten aspects of organisational communication identified, five had significant effects on general organisational commitment. The most important of these concerned openness between principals and staff, supportive communication among colleagues (positive effects) and communication overload (negative effects). Implications for school leadership and school culture are discussed along with directions for further research.
Will–Skill–Tool Components as Key Factors for Digital Media Implementation in Education: Austrian Teachers’ Experiences with Digital Forms of Instruction during the COVID-19 Pandemic
Authors: Woltran Flora , Lindner Katharina-Theresa , Dzojic Tanja , Schwab Susanne
Published: June 2022

Although comprehensive digitalization (e.g., the provision of skills and resources) had already been placed on Austria’s education policy agenda prior to the emergence of COVID-19, there is evidence that educators had some difficulty ensuring digital learning opportunities for their students when schools closed in early 2020. Against this backdrop, the present study, which drew on qualitative data from the large-scale INCL-LEA (Inclusive Home Learning) study, aimed to determine whether secondary school teachers (n = 17) from Viennese schools met the prerequisites for successfully implementing digital instruction, formulated in the Will–Skill–Tool model developed by Christensen and Kzenek (2008). Findings reveal that teachers primarily associated their sufficient digital skills with three factors: (1) basic interest and competence, (2) recently attended training, and/or (3) a positive attitude toward changing teaching practices. Interestingly, some educators recognized that digitization offers great potential for implementing individualized teaching approaches. However, the findings point to the didactic necessity of digital socialization in terms of social communication and inclusion when establishing emergency digital education.
High-Accuracy 3D Contour Measurement by Using the Quaternion Wavelet Transform Image Denoising Technique
Authors: Fan Lei , Wang Yongjun , Zhang Hongxin , Li Chao , Xin Xiangjun
Published: June 2022

In this paper, we propose an image denoising algorithm based on the quaternion wavelet transform (QWT) to address sinusoidal fringe images under strong noise in structured light 3D profilometry. The analysis of a quaternion wavelet shows that the amplitude image of the quaternion wavelet is easily affected by noise. However, the three phase images, which mainly reflect edge and texture information, are randomly and disorderly distributed with respect to noise. The QWT denoising algorithm is suitable for processing sinusoidal fringe images of complex structures in a high-accuracy 3D measurement system. Sinusoidal fringe images are collected and denoised by using the QWT algorithm and classical Gaussian smoothing (GS) denoising algorithm, and GS is used as a reference for the QWT algorithm. The results indicate that the standard deviation is reduced from 0.1448 for raw sinusoidal fringe images to 0.0192, and the signal-to-noise ratio is improved from 4.6213 dB to 13.3463 dB by using the QWT algorithm. The two algorithms have the same denoising effect for a surface with less information. For a surface with rich information, the details of the 3D contour are lost because of the image “blurring” caused by using the GS algorithm, while all edge details of the 3D contour are reconstructed by using the QWT denoising algorithm because of its characteristic of information and noise being separated from the source. For the measured face mask, the error is less than ±0.02 mm. In addition, it takes less than 20 s to run the QWT algorithm to process eight sinusoidal fringe images, which meets the requirements of high-precision measurements.
A Novel Cascade Model for End-to-End Aspect-Based Social Comment Sentiment Analysis
Authors: Ding Hengbing , Huang Shan , Jin Weiqiang , Shan Yuan , Yu Hang
Published: June 2022

The end-to-end aspect-based social comment sentiment analysis (E2E-ABSA) task aims to discover human’s fine-grained sentimental polarity, which can be refined to determine the attitude in response to an object revealed in a social user’s textual description. The E2E-ABSA problem includes two sub-tasks, i.e., opinion target extraction and target sentiment identification. However, most previous methods always tend to model these two tasks independently, which inevitably hinders the overall practical performance. This paper investigates the critical collaborative signals between these two sub-tasks and thus proposes a novel cascade social comment sentiment analysis model for jointly tackling the E2E-ABSA problem, namely CasNSA. Instead of treating the opinion target extraction and target sentiment identification as discrete procedures in previous works, our new framework takes the contextualized target semantic encoding into consideration to yield better sentimental polarity judgment. Additionally, extensive empirical results show that the proposed approach effectively achieves a 68.13% F1-score on SemEval-2014, 62.34% F1-Score on SemEval-2015, 56.40% F1-Score on SemEval-2016, and 50.05% F1-score on a Twitter dataset, which is higher than the existing approaches. Ablated experiments demonstrate that the CasNSA model substantially outperforms state-of-the-art methods, even when using fixed words embedding rather than pre-trained BERT fine tuning. Moreover, in-depth performance analysis on the social comment datasets further validates that our work gains superior performance and reliability effectively and efficiently in realistic scenarios.
A Novel and Compact Slotted-Decahedral Antenna for 5G Devices
Authors: Olan Nuñez Karen Nallely , Murphy Arteaga Roberto S.
Published: June 2022

In this paper, a compact SISO (Single-Input Single-Output) antenna with a novel slotted-decahedral geometry is presented. The design was performed using a full-wave simulator (FWS). A decahedral patch with an eight-pointed star-shaped slot and two rectangular grooves is the main characteristic of the proposed novel radiator. The decagon shape, eight-pointed star-shaped slot, rectangular grooves, and separate section give rise to radiation. The SISO antenna operates from 23.1 to 29.94 GHz covering the proposed frequency bands for 5G wireless communication systems. The radiation pattern stability, moderate to high gain values (6.5 dBi, average), good radiation efficiency (higher than 89.4%), wide impedance bandwidth (6.84 GHz), compactness (13 × 13 × 0.787 mm3) and ease of manufacture are the principles advantages of this novel geometry. The experimental validation of the SISO antenna was performed, and good agreement was obtained with simulation results, and an equivalent circuit model was proposed. The proposed SISO antenna can be easily integrated into wireless sensors, drones, backhaul, and 5G devices which support IoT, working in the n257, n258 and n261 frequency bands.
Defending Adversarial Attacks against DNN Image Classification Models by a Noise-Fusion Method
Authors: Shi Lin , Liao Teyi , He Jianfeng
Published: June 2022

Adversarial attacks deceive deep neural network models by adding imperceptibly small but well-designed attack data to the model input. Those attacks cause serious problems. Various defense methods have been provided to defend against those attacks by: (1) providing adversarial training according to specific attacks; (2) denoising the input data; (3) preprocessing the input data; and (4) adding noise to various layers of models. Here we provide a simple but effective Noise-Fusion Method (NFM) to defend adversarial attacks against DNN image classification models. Without knowing any details about attacks or models, NFM not only adds noise to the model input at run time, but also to the training data at training time. Two l∞-attacks, the Fast Gradient Signed Method (FGSM) and the Projected Gradient Descent (PGD), and one l1-attack, the Sparse L1 Descent (SLD), are applied to evaluate defense effects of the NFM on various deep neural network models which used MNIST and CIFAR-10 datasets. Various amplitude noises with different statistical distribution are applied to show the defense effects of the NFM in different noise. The NFM also compares with an adversarial training method on MNIST and CIFAR-10 datasets. Results show that adding noise to the input images and the training images not only defends against all three adversarial attacks but also improves robustness of corresponding models. The results indicate possibly generalized defense effects of the NFM which can extend to other adversarial attacks. It also shows potential application of the NFM to models not only with image input but also with voice or audio input.
New Heuristic Algorithm for Low Energy Mapping for 2.5-D Integration
Authors: Sun Haiyan , Peng Xinwei , Cang Dongqing , Zhao Jicong , Liu Yanhua
Published: June 2022

A chiplet placement algorithm for 2.5-D IC integration on an interposer is discussed in this paper. Inspired by the NoC (network-on-chip) mapping problem, we propose a novel chiplet placement algorithm called the CCEOA (chiplet communication energy optimization algorithm), which takes into account the actual size of the chiplet. The CCEOA can map chiplets to mesh topology, resulting in a layout with a low CEC (communication energy consumption). The algorithm considers the spacing of the chiplets while selecting the initial nodes and the nodes to map the next chiplet. Furthermore, because there exist nodes resulting in the same CEC increment during the mapping process, the algorithm adopts a secondary local exploration strategy to further select nodes. Meanwhile, the lateral and vertical placements of chiplets are also considered. The algorithm is implemented and evaluated with a 2.5-D IC integration with 22 chiplets to demonstrate its efficiency and the accuracy.
Optimal Slip Ratio Tracking Integral Sliding Mode Control for an EMB System Based on Convolutional Neural Network Online Road Surface Identification
Authors: Shen Yanan , Mao Jingfeng , Wu Aihua , Liu Runda , Zhang Kaijian
Published: June 2022

As the main branch of the brake-by-wire system, the electro-mechanical brake (EMB) system is the future direction of vehicle brake systems. In order to enhance the vehicle braking effect and improve driver safety, a convolutional neural network (CNN) online road surface identification algorithm and an optimal slip ratio tracking integral sliding mode controller (ISMC) combined EMB braking control strategy is proposed in this paper. Firstly, according to the quarter-vehicle model and Burckhardt tire model, the vehicle braking control theory based on the optimal slip ratio is analyzed. Secondly, using the VGG-16 CNN method, an online road surface identification algorithm is proposed. Through a comparative study under the same dataset conditions, it is verified that the VGG-16 method has a higher identification accuracy rate than the SVM method. In order to further improve the generalization ability of VGG-16 CNN image identification, data enhancement is performed on the road surface image data training set, including image flipping, clipping, and adjusting sensitivity. Then, combined with the EMB system model, an exponential approach law method-based ISMC is designed to achieve the optimal slip ratio tracking control of the vehicle braking process. Finally, MATLAB/Simulink software is used to verify the correctness and effectiveness of the proposed strategy and shows that the strategy of real-time identifying road surface conditions through vision can make the optimal slip ratio of vehicle braking control reasonably adjusted, so as to ensure that the adhesion coefficient of wheel braking always reaches the peak value, and finally achieves the effect of rapid braking.
A Low Phase Noise Dual-Loop Dual-Output Frequency Synthesizer in SiGe BiCMOS
Authors: Chen Zhe , Hou Debin , Chen Jixin , Yan Pinpin
Published: June 2022

In this article, a dual-loop dual-output frequency synthesizer designed for IEEE802.11aj (45 GHz) standard is presented. In order to support the super-heterodyne transceiver, the Loop1 output frequency is fixed for easy design of high-performance IF transceiver and filter, and the Loop2 output frequency varies for the channel selection according to the IEEE802.11aj (45 GHz) standard. The power hungry high-speed prescaler (or multi-modulus-divider) is replaced with a mixer in Loop2, thus the in-band phase noise and DC power consumption can be improved. The dual-loop dual-output synthesizer is fabricated in 0.13 µm SiGe BiCMOS technology, occupies an area of 2.7 mm × 2.4 mm, and consumes 610 mW DC power. Measured results show the phase noise of the frequency synthesizer are −79.3 dBc/Hz@10 kHz and −129.1 dBc/Hz@10 MHz at 12.96 GHz for Output1 and −76.6 dBc/Hz@10 kHz and −117.2 dBc/Hz@10 MHz at 32.535 GHz for Output2. The low-reference spur of −69.2 dBc and low-power level spurious tones at the outputs are observed during the measurement. To the best of our knowledge, this work is the first reported dual-loop dual-output synthesizer designed for IEEE802.11aj (45 GHz) standard.
Computational Electromagnetics for Industrial Applications
Authors: Antonini Giulio , Romano Daniele , Lombardi Luigi
Published: June 2022

Nowadays, computational electromagnetics (CEMs) methods play an important role in the rapid modeling and design of electromagnetic (EM) systems and their industrial applications [...]
High−Performance 4H−SiC UV p−i−n Photodiode: Numerical Simulations and Experimental Results
Authors: Rao Sandro , Mallemace Elisa D. , Della Corte Francesco G.
Published: June 2022

In this work, the optical response of a high−performance 4H−SiC−based p−i−n ultraviolet (UV) photodiode was studied by means of an ad hoc numerical model. The spectral responsivity and the corresponding external photodiode quantum efficiency were calculated under different reverse biases, up to 60 V, and in the wavelength range from λ = 190 to 400 nm. The responsivity peak is R = 0.168 A/W at λ = 292 nm at 0 V and improves as bias increases, reaching R = 0.212 A/W at 60 V and λ = 298 nm. The external quantum efficiency is about 71% and 88%. The good quality of the simulation setup was confirmed by comparison with experimental measurements performed on a p−i−n device fabricated starting from a commercial 4H−SiC wafer. The developed numerical model, together with the material electrical and optical parameters used in our simulations, can be therefore explored for the design of more complex 4H−SiC−based solid−state electronic and optoelectronic devices.
A 12-Bit 50 MS/s Split-CDAC-Based SAR ADC Integrating Input Programmable Gain Amplifier and Reference Voltage Buffer
Authors: Xu Zhuofan , Hu Biao , Wu Tianxiang , Yao Yuting , Chen Yong , Ren Junyan , Ma Shunli
Published: June 2022

This article describes an asynchronous split-CDAC-based SAR ADC with integrated input PGA and an RV-Buffer. The split CDAC structure not only reduces the area of the ADC, but also relieves the driving pressure of the input PGA and RV-Buffer. Using the input PGA instead of the traditional input buffer as the driving circuit of the ADC increases the dynamic input range of the ADC. The proposed on-chip RV-Buffer can provide 1.1 V positive and 0.1 V negative voltage, avoiding the disturbance caused by off-chip reference. This prototype is implemented in a 65 nm CMOS process and occupies an active area of 0.088 mm2. The input PGA can provide 0–18 dB programmable gain with a step of 3 dB. Measurement results show that as the provided gain changes, the ADC’s SNR is best, reaching 50.9 dB, and the SFDR is beat, reaching 62.35 dB at 50 MS/s.
A Generative Model for Traffic Demand with Heterogeneous and Spatiotemporal Characteristics in Massive Wi-Fi Systems
Authors: Lee Jae-Min , Kim Jong-Deok
Published: June 2022

A substantial amount of money and time is required to optimize resources in a massive Wi-Fi network in a real-world environment. Therefore, to reduce cost, proposed algorithms are first verified through simulations before implementing them in a real-world environment. A traffic model is essential to describe user traffic for simulations. Existing traffic models are statistical models based on a discrete-time random process and combine a spatiotemporal characteristic model with the varying parameters, such as average and variance, of a statistical model. The spatiotemporal characteristic model has a mathematically strict assumption that the access points (APs) have approximately similar traffic patterns that increase during day times and decrease at night. The mathematical assumption ensures a homogeneous representation of the network traffic. It does not include heterogeneous characteristics, such as the fact that lecture buildings on campus have a high traffic during lectures, while restaurants have a high traffic only during mealtimes. Therefore, it is difficult to represent heterogeneous traffic using this mathematical model. Deep learning can be used to represent heterogeneous patterns. This study proposes a generative model for Wi-Fi traffic that considers spatiotemporal characteristics using deep learning. The proposed model learns the heterogeneous traffic patterns from the AP-level measurement data without any assumptions and generates similar traffic patterns based on the data. The result shows that the difference between the sample generated by the proposed model and the collected data is up to 72.1% less than that reported in previous studies.
Deep Reinforcement Learning-Based Real-Time Joint Optimal Power Split for Battery–Ultracapacitor–Fuel Cell Hybrid Electric Vehicles
Authors: Kim Daniel , Hong Seokjoon , Cui Shengmin , Joe Inwhee
Published: June 2022

Hybrid energy storage systems for hybrid electric vehicles (HEVs) consisting of multiple complementary energy sources are becoming increasingly popular as they reduce the risk of running out of electricity and increase the overall lifetime of the battery. However, designing an efficient power split optimization algorithm for HEVs is a challenging task due to their complex structure. Thus, in this paper, we propose a model that jointly learns the optimal power split for a battery/ultracapacitor/fuel cell HEV. Concerning the mechanical system of the HEV, two propulsion machines with complementary operation characteristics are employed to achieve higher efficiency. Additionally, to train and evaluate the model, standard driving cycles and real driving cycles are employed as input to the mechanical system. Then, given the inputs, a temporal attention long short-term memory model predicts the next time step velocity, and through that velocity, the predicted load power and its corresponding optimal power split is computed by a soft actor–critic deep reinforcement learning model whose training phase is aided by shaped reward functions. In contrast to global optimization techniques, the local velocity and load power prediction without future knowledge of the driving cycle is a step toward real-time optimal energy management. The experimental results show that the proposed method is robust to different initial states of charge values, better allocates the power to the energy sources and thus better manages the state of charge of the battery and the ultracapacitor. Additionally, the use of two motors significantly increases the efficiency of the system, and the prediction step is shown to be a reliable way to plan the HESS power split in advance.
Control Design for Electric Vehicles
Authors: Gáspár Péter
Published: June 2022

The recent research in the field of electrical and autonomous vehicles is developing in exciting directions [...]
Changes in the Parasitism Rate and Parasitoid Community Structure of the Horse Chestnut Leafminer, Cameraria ohridella (Lepidoptera: Gracillariidae), in the Czech Republic
Authors: Volter Lubomír , Prenerová Eva , Weyda František , Zemek Rostislav
Published: June 2022

The horse chestnut leafminer, Cameraria ohridella, Deschka and Dimić, is a moth that has invaded most of Europe since it was first recorded in Macedonia near Lake Ohrid in 1985. It attacks horse chestnut trees and causes aesthetic and vitality problems. The parasitism rate, other mortality rates, and parasitoid structure were studied during a five-year survey at six sites in the Czech Republic. The results showed that the total parasitism rates varied from 1.9% to 20.5%, with an average of 7.2%, similar to other those published studies. The parasitism rate was significantly related to year, the developmental stage of C. ohridella, latitude, and greenery maintenance but not to C. ohridella population density, altitude, or area size. In contrast, the total other mortality rates varied from 13.7% to 59.5%, with an average of 31%, but overall temporal changes in the values indicated a declining trend. The parasitoid complex was predominantly polyphagous parasitoids of the family Eulophidae, similar to that found previously in south-eastern Europe. The results further revealed that the most abundant parasitoid species, Minotetrastichus frontalis (Nees), was gradually replaced by Pediobius saulius (Walker). The increasing abundance of P. saulius is thus an interesting adaptation of an autochthonous parasitoid to a new host.
Microsite Drivers of Natural Seed Regeneration of Eucalyptus globulus Labill. in Burnt Plantations
Authors: Águas Ana , Matias Hugo , Rodrigues Abel , Bailey Tanya , Silva Joaquim , Rego Francisco
Published: June 2022

Fire regimes are changing in several regions of the world. In those regions, some exotic species may be better adapted to new regimes than the native species. This study focused on identifying the microsite characteristics associated with the occurrence of post-fire Eucalyptus globulus regeneration from seeds, outside the species native-range. This information is important in helping to assess the naturalization status of the species, to understand its invasion risk, and to manage wildlings in plantations. To characterize the establishment niche, pairs of microsites (sapling presence/absence) were sampled in four salvage-logged plantations of E. globulus two years after fire (20 pairs/plantation). Microsites of wildlings from three size classes and control microsites were established in one of these plantations (20 quartets) in order to characterize the recruitment niche and to assess ontogenic niche shifts. Two post-fire wildling cohorts were identified. The first emerged just after fire and was abundant. The second emerged after logging and was scarce, probably due to seed limitation. First-cohort wildlings were observed in microsites characterized by a high incidence of fire-related variables (charcoal, ash, increased soil pH and K). The aggregated distribution of these wildlings and their association with other species may indicate the existence of facilitative relationships and/or the exploitation of resource-rich patches. All these factors were relevant for first-cohort persistence and likely also for its establishment and recruitment. Second-cohort wildlings occurred in microsites where salvage-logging disturbance was evident, showing the importance of this disturbance for its emergence. Wildling size diversity was explained by the two recruitment events and by the asymmetrical competition between wildlings and adults. No niche shifts were detected. The high densities of E. globulus wildlings found established in burnt plantations indicated naturalization was in progress. The timing of major recruitment events and the phenology of the species should be considered for monitoring this regeneration and scheduling control interventions, if required.