bluuebunny/crossref_metadata_2025 huggingface dataset:
On Lorentz Invariant Complex Scalar Fields
Authors: Rigolin Gustavo
Published: March 2022

We obtain a Lorentz covariant wave equation whose complex wave function transforms under a Lorentz boost according to the following rule,

Ψ

x

⟶

e

i
/
ℏ

f

x

Ψ

x

. We show that the spacetime-dependent phase

f

x

is the most natural relativistic extension of the phase associated with the transformation rule for the nonrelativistic Schrödinger wave function when it is subjected to a Galilean transformation. We then generalize the previous analysis by postulating that

Ψ

x

transforms according to the above rule under proper Lorentz transformations (boosts or spatial rotations). This is the most general transformation rule compatible with a Lorentz invariant physical theory whose observables are bilinear functions of the field

Ψ

x

. We use the previous wave equations to describe several physical systems. In particular, we solve the bound state and scattering problems of two particles which interact both electromagnetically and gravitationally (static electromagnetic and gravitational fields). The former interaction is modeled via the minimal coupling prescription while the latter enters via an external potential. We also formulate logically consistent classical and quantum field theories associated with these Lorentz covariant wave equations. We show that it is possible to make those theories equivalent to the Klein-Gordon theory whenever we have self-interacting terms that do not break their Lorentz invariance or if we introduce electromagnetic interactions via the minimal coupling prescription. For interactions that break Lorentz invariance, we show that the present theories imply that particles and antiparticles behave differently at decaying processes, with the latter being more unstable. This suggests a possible connection between Lorentz invariance-breaking interactions and the matter-antimatter asymmetry problem.
A Robot Human‐Like Learning Framework Applied to Unknown Environment Interaction
Authors: Xue Xianfa , Zuo Lei , Wang Ning
Published: March 2022

Learning from demonstration (LfD) is one of the promising approaches for fast robot programming. Most learning systems learn both movements and stiffness profiles from human demonstrations. However, they rarely consider the unknown environment interaction. In this paper, a robot human‐like learning framework is proposed, where it can learn human skills through demonstration and complete the interaction task with an unknown environment. Firstly, the desired trajectory was generated by dynamic movement primitive (DMP) based on human demonstration. Then, an adaptive optimal admittance control scheme was employed to interact with environments with the reference adaptation method. Finally, the experimental study was conducted, and the effectiveness of the framework proposed in this paper was verified via a group of curved surface wiping experiments on a balloon with unknown model parameters.
Looking through the Lens: The Reality of Telesurgical Support with Interactive Technology Using Microsoft’s HoloLens 2
Authors: van der Putten Kees , Anderson Mike B. , van Geenen Rutger C.
Published: March 2022

Reality technologies in the orthopaedic arena have been increasing in use over the last decade, including virtual reality (VR), augmented reality (AR), and mixed reality (MR). MR is one of the most recent innovations and perhaps the most promising for improving the overall surgical experience. The purpose of this case report was to demonstrate a complex total knee arthroplasty case where unplanned remote assistance was used for telesurgical support using the HoloLens 2.
Renal Dynamic Imaging Information Data in the Evaluation of Renal Function in Patients with Chronic Heart Failure under the Guidance of Intelligent Region of Interest Detection Algorithm
Authors: Ma Haifang , Su Zhenjun , Yang Zhijia , Li Ya , Yang Xiaoli , Zhao Danhua , Chen Xuejiao
Published: March 2022

This work aimed to explore the application value of intelligent region of interest (ROI) detection algorithm in evaluating renal dynamic imaging information data of renal function in patients with chronic heart failure (CHF). 52 patients with CHF were selected as the research objects and grouped according to the level of renal function into an experimental group (14 cases) and an observation group (38 cases). In addition, 10 healthy people were selected as the research objects, as the control group. Different calculation methods of glomerular filtration rate (GFR) were used to evaluate the renal function of patients, and the ROI detection algorithm-assisted delineation was compared with traditional manual delineation. It was found that the GFR of the experimental group calculated by different methods was 52.58 mL/min/1.73m2 and 43.77 mL/min/1.73m2, respectively, which was significantly lower than that of the observation group (

P
<
0.05

), and that in both groups was lower than that of the control group (

P
<
0.05

). In addition, the unilateral renal function values of the two auxiliary delineations were both 13.61 mL/min/1.73 m2, while the results of the two manual delineations were significantly different (

P
<
0.05

). Therefore, renal dynamic imaging based on the ROI detection algorithm to evaluate the renal function of CHF patients showed a great improvement in effectiveness, sensitivity, stability, and efficiency compared with the traditional manual delineation, which was worthy of clinical promotion.
Optimization and Analysis of CO2 Huff-n-Puff Process in Shale Oil Reservoirs Using Response Surface Methodology (RSM)
Authors: Wang Yinqing , Hu Jinghong , Xie Weiwei , Zhang Yuan
Published: March 2022

The objective of this study is to determine the influence of operational parameters of CO2 Huff-n-Puff EOR process in the Eagle Ford shale oil reservoirs using response surface methodology (RSM). Single-factor analysis was first conducted for establishing the Box-Behnken model in RSM. We selected the primary depletion time, gas injection time, cycle number, production time per cycle, and injection rate as the primary input variables using RSM. The cumulative oil production and net present value are optimized as the output factors. After that, Design of Expert 12 software was used to design the experimental table for the above setting factors. Corresponding to the results taken from the optimization, the most significant factor is injection rate, followed by injection time, cycle number, and primary depletion time, and production time per cycle is the least significant. Additionally, the optimum responses were found as primary depletion time of 2.37 years, injection time of 3.4 months, cycle number of 3, production time per cycle of 2.2 years, and injection rate of 5000 MSCF/D. Moreover, correlation coefficient (R2) of the regression model is 0.9977, and adjusted model R2 is 0.8898, which further indicates that the model has good reliability. Results show that RSM is a useful technique for optimization, and it also provides insights into optimizing and designing the CO2 Huff-n-Puff process in the shale oil reservoirs.
Fine-Grained Urban Functional Region Identification via Mobile App Usage Data
Authors: Deng Lei , Hu Hangyu
Published: March 2022

Understanding fine-grained urban function for different regions is essential for both city managers and residents in terms of strategy design, tourism recommendation, business site selection, etc. A huge amount of data from the mobile network in the past several years provides the possibility for fine-grained urban function identification since it provides the opportunity to extract useful information about urban functions. However, challenges remain: (i) there is no prior knowledge about the existence of App usage patterns relating to urban functional regions; (ii) collected data are very noisy and data from different cellular towers have different noise levels. Therefore, it is difficult to extract unique patterns to identify urban functional regions. This article proposes a fine-grained urban functional region identification system, which utilizes mobile App usage data from cellular towers. To address challenge (i), we first extract three key variables for each cellular tower, App number, user number, and traffic. Then, we design a Davies–Bouldin index (DBI)-based filtering method to automatically select the most distinguishable features for multiclassification. To address challenge (ii), we first reduce cellular tower level noise by designing a clustering-based method to select the most representative cellular tower data. The data from these cellular towers share similar patterns for the same urban functional region and different patterns between different urban functional regions. Then, we reduce feature level noise by designing a Fourier transform-based method to reconstruct the features with several key frequency components, which preserves the most important information and removes the unnecessary noise. We evaluate our system and selected features with three representative supervised learning models, all of which achieve more than

95
%

classification accuracy.
Serum Autoantibodies against LRDD, STC1, and FOXA1 as Biomarkers in the Detection of Ovarian Cancer
Authors: Duan Yaru , Cui Chi , Qiu Cuipeng , Sun Guiying , Wang Xiao , Wang Peng , Ye Hua , Dai Liping , Shi Jianxiang
Published: March 2022

Purpose. This study is aimed at evaluating serum autoantibodies against four tumor-associated antigens, including LRDD, STC1, FOXA1, and EDNRB, as biomarkers in the immunodiagnosis of ovarian cancer (OC). Methods. The autoantibodies against LRDD, STC1, FOXA1, and EDNRB were measured using an enzyme-linked immunosorbent assay (ELISA) in 94 OC patients and 94 normal healthy controls (NHC) in the research group. In addition, the diagnostic values of different autoantibodies were validated in another independent validation group, which comprised 136 OC patients, 136 NHC, and 181 patients with benign ovarian diseases (BOD). Results. In the research group, autoantibodies against LRDD, STC1, and FOXA1 had higher serum titer in OC patients than NHC (

P
<
0.001

). The area under receiver operating characteristic curves (AUCs) of these three autoantibodies were 0.910, 0.879, and 0.817, respectively. In the validation group, they showed AUCs of 0.759, 0.762, and 0.817 and sensitivities of 49.3%, 42.7%, and 48.5%, respectively, at specificity over 90% for discriminating OC patients from NHC. For discriminating OC patients from BOD, they showed AUCs of 0.718, 0.729, and 0.814 and sensitivities of 47.1%, 39.0%, and 51.5%, respectively, at specificity over 90%. The parallel analyses demonstrated that the combination of anti-LRDD and anti-FOXA1 autoantibodies achieved the optimal diagnostic performance with the sensitivity of 58.1% at 87.5% specificity and accuracy of 72.8%. The positive rate of the optimal autoantibody panel improved from 62.4% to 87.1% when combined with CA125 in detecting OC patients. Conclusion. Serum autoantibodies against LRDD, STC1, and FOXA1 have potential diagnostic values in detecting OC.
Study on Leakage Model of Typical Penetration of Closed Structures Based on Porous Media Seepage Theory
Authors: Lin Xin , Du Zhehua
Published: March 2022

Quantitative prediction of penetration leakage rate has not been reported so far. The theoretical prediction method of leakage rate of typical penetration static seal structure of closed structure is studied. Based on porous media seepage mechanics, the relationship between leakage rate and microstructure parameters is established, and a new prediction model of the leakage rate of sealing structures is proposed. Then, the relationship between seal-specific pressure and microstructure parameters is obtained by the Hertz contact mechanics model. Finally, the leakage rate calculation, which is independent of any experimental data, is obtained innovatively. The new model is used to predict the leakage rate of penetration, and the theoretical prediction results are compared with the experimental measurement results. It is proved that the two agree well, which verifies the effectiveness of the model. The prediction model based on this method can well reflect the effects of rough surface morphology, material mechanical properties, sealing load, high temperature, and high pressure on the leakage rate. The leakage rate prediction model proposed in this paper is independent of the experimental regression coefficient and can realize the conversion relationship between different sealing media, sealing materials, and working conditions.
Design of Pedagogy Course Information Sharing System Based on Wireless Sensor Network
Authors: Jin Xianzhu
Published: March 2022

In order to improve the information sharing effect of pedagogy courses, it is necessary to improve the system information transmission network algorithm. This paper improves the wireless sensor network algorithm and analyzes and verifies the performance analysis model of the Aloha protocol in multihop underwater acoustic sensor networks (UASNs). Based on the improved performance analysis model of the Aloha protocol on the String topology network, the expected throughput of the String topology network and the average end-to-end delay can be obtained, and the transmission effect of pedagogy information in the sensor network can be improved. In addition, this paper constructs a pedagogy course information sharing system based on wireless sensor network to verify the information sharing effect of the model constructed in this paper. The experimental research results show that the system model proposed in this paper has certain effects.
Extraction and Quantification of Saponins in Quinoa (Chenopodium quinoa Willd.) Genotypes from Colombia
Authors: Mora-Ocación Mary S. , Morillo-Coronado Ana Cruz. , Manjarres-Hernández Elsa Helena.
Published: March 2022

Quinoa has a high nutraceutical potential because of the presence of secondary metabolites called saponins, which have industrial and medicinal uses and protect against attacks by pathogens. These compounds are found especially in the seed coat and give the grain a bitter taste; therefore, they must be eliminated before consumption. Despite the potential use in Colombia, there are few studies aimed at quantifying this metabolite. Therefore, the objective of this research was to evaluate two extraction methodologies (physical and chemical) and two methods for quantifying saponins in five quinoa genotypes grown in Colombia. The most efficient extraction method was the physical method. The saponin contents of the five genotypes were variable. The cluster analysis differentiated the genotypes into two groups: low saponin content (<4.49 mg/g seed) and high saponin content (>14.76 mg/g seeds). Blanca de Jericó had the lowest saponin content (<0.40%), and Amarilla de Maranganí had the highest content (>0.18%). Identifying more efficient methodologies for extracting and quantifying saponins will allow a better characterization of the germplasm and selection of genotypes with desirable characteristics for both consumption and industrial use.
How Does COVID-19 Affect Traffic on Highway Network: Evidence from Yunnan Province, China
Authors: Li Qihui , Bai Qiang , Hu Aihui , Yu Zhoulin , Yan Shixiang
Published: March 2022

The COVID-19 pandemic and antipandemic policies have significantly impacted highway transportation. Many studies have been conducted to quantify these impacts. However, quantitative analysis of the impacts on province-wide traffic in developing countries, such as China, is still inadequate. This paper tried to fill this gap by proposing equations to quantify the traffic variations of overall province-wide traffic and to analyze the intercity bus traffic variation and intercity bus usage, applying the K-means cluster method to conduct the analysis of traffic reductions in regions with different levels of economic development, and using the hypothesis testing for traffic recovery analysis. It is found that passenger vehicle traffic and truck traffic dropped by 59.67% and 68.19% during the outbreak, respectively. The intercity bus traffic on highways declined by 59.8% to 98.6%, and the intercity bus usage dropped by 55.6% on average. For traffic reductions in different regions, the higher the GDP per capita was, the more the traffic was affected by the pandemic. In regions with lower GDP per capita, traffic variations were minor. It is also found that the passenger vehicle traffic went through four stages in 99 days: the Decline Stage, Rapid Recovery Stage, Slow Recovery Stage, and Normal Stage, while truck traffic only experienced the Decline Stage, Rapid Recovery Stage, and Normal Stage and took 51 days to recover to the Normal Stage. In the Rapid Recovery Stage, the recovery rates were 15.6% and 12.9% per week for passenger vehicle traffic and truck traffic, respectively, and the recovery rate was only 2.1% for passenger vehicle traffic in the Slow Recovery Stage. Despite the recovery of traffic volumes, neither passenger-kilometers nor tonne-kilometers of freight in 2020 reached the same level as in 2019. These findings help the understanding of the pandemic’s impacts on highway traffic for researchers and can provide valuable references for decision-makers to develop antipandemic policies.
Application Practice Analysis of Ice and Snow Sports Training Assistance System Based on Internet of Things
Authors: Zhang Ping , Sun Juntao
Published: March 2022

Teachers play an essential role in physical culture, and they are not only responsible for analysis and guidance but also responsible for formulating specific training methods and training rhythms according to athletes’ personalities. Computer technology has developed rapidly into the 21st century. In sports training, some researchers have also started to analyze and generalize physical activity and movement patterns using IoT technology. Not only can it analyze the rules of specific sports science, but it can also use computers to intentionally infiltrate sports facilities to provide advanced technical support to effectively improve training and science. In this article, IoT technology is introduced to study the auxiliary system for ice and snow sports training. Before designing the system, this paper plans the system architecture in detail, including the principle of stability, the simplicity and practicality, and the principle of low price. Using this auxiliary system, the sensitivity of the lower limbs of ice and snow athletes was trained in this paper. The sensitivity scores of 5 athletes before the experiment were 50, 54, 49, 38, and 35, and the scores after the experiment were 32, 26, 31, 35, and 30, and the sensitivity was significantly improved.
MRI T2WI High Signal Is a Risk Factor for Perioperative Complications in Patients with Cervical Spondylosis with Spinal Cord Compression: A Propensity Matching Score Analysis
Authors: Huang Shengsheng , Sun Xuhua , Chen Liyi , Yi Ming , Liang Tuo , Jiang Jie , Chen Jiarui , Liu Chong , Zhan Xinli
Published: March 2022

Objective. The purpose of this study was to compare the perioperative complications and clinical efficacy of patients with cervical spondylosis with spinal cord compression (CSWSCC) with or without MRI T2WIHS (T2‐weighted image high signal) by means of propensity matching score grouping. Methods. We analyzed a single‐center data of 913 surgical patients with CSWSCC by propensity matching score in this study, of which 326 patients had preoperative cervical MRI T2WIHS. The patient’s general condition and perioperative indicators were collected. The MRI T2WIHS and normal groups were paired 1 : 1 to eliminate selection bias by propensity matching score. Finally, a total of 312 pairs were matched successfully. The results of perioperative complications and other outcome variables were compared between the two groups by Cox function analysis. Results. The postoperative blood loss, operation time, blood transfusion volume, systemic complications, local complications, volume of drainage, abnormal use of antibiotic, length of hospital stay, and JOA (Japanese Orthopaedic Association) improvement rate were analyzed. As the only complication with significant statistical difference, the incidence of IRI (ischemia‐reperfusion injury) in patients with MRI T2WIHS was significantly higher. The length of hospital stay was more significantly increased in patients with MRI T2WIHS; on the contrary, the JOA improvement rate decreased significantly. Conclusion. This study confirmed that there was no significant difference in the incidence of perioperative complications in CSWSCC patients with or without MRI T2WIHS, except for the IRI. Moreover, the JOA improvement rate of patients without MRI T2WIHS was significantly better, with the length of hospital stay reduced.
Deep Neural Networks Algorithm for Vietnamese Word Segmentation
Authors: Zheng Kexiao , Zheng Wenkui
Published: March 2022

Traditional Vietnamese word segmentation methods do not perform well in the face of Vietnamese ambiguity, in response to the enormous challenge posed by the scarcity of the Vietnamese corpus to language processing. We first investigated the most advanced deep neural network method. According to the ambiguity problem of Vietnamese word segmentation, we then proposed a Vietnamese word segmentation processing technology based on an improved long short-term memory neural network (LSTM), which is made up of an LSTM encoding and a CNN feature extraction portion. The previous important information is kept in the memory unit; the word segmentation processing task is refined into a classification problem and a sequence labeling problem, which can gain the useful features of the word segmentation character and word level automatically. The limitation of the local context window size is avoided, and the word segmentation processing task is refined into a classification problem and a sequence labeling problem. Finally, validated by a homemade Vietnamese news website crawler dataset, the experimental results show that, compared with the single LSTM, single CNN methods, and traditional methods, the performance improvement of our proposed method is more obvious. In the Vietnamese word separation task, the accuracy reaches 96.6%, the recall reaches 95.2%, and the F1 value reaches 96.3%, which is significantly better than the traditional methods CNN and LSTM.
Classification and Detection of Autism Spectrum Disorder Based on Deep Learning Algorithms
Authors: Alsaade Fawaz Waselallah , Alzahrani Mohammed Saeed
Published: March 2022

Autism spectrum disorder (ASD) is a type of mental illness that can be detected by using social media data and biomedical images. Autism spectrum disorder (ASD) is a neurological disease correlated with brain growth that later impacts the physical impression of the face. Children with ASD have dissimilar facial landmarks, which set them noticeably apart from typically developed (TD) children. Novelty of the proposed research is to design a system that is based on autism spectrum disorder detection on social media and face recognition. To identify such landmarks, deep learning techniques may be used, but they require a precise technology for extracting and producing the proper patterns of the face features. This study assists communities and psychiatrists in experimentally detecting autism based on facial features, by using an uncomplicated web application based on a deep learning system, that is, a convolutional neural network with transfer learning and the flask framework. Xception, Visual Geometry Group Network (VGG19), and NASNETMobile are the pretrained models that were used for the classification task. The dataset that was used to test these models was collected from the Kaggle platform and consisted of 2,940 face images. Standard evaluation metrics such as accuracy, specificity, and sensitivity were used to evaluate the results of the three deep learning models. The Xception model achieved the highest accuracy result of 91%, followed by VGG19 (80%) and NASNETMobile (78%).
Link Prediction Model for Weighted Networks Based on Evidence Theory and the Influence of Common Neighbours
Authors: Liu Miaomiao , Wang Yang , Chen Jing , Zhang Yongsheng
Published: March 2022

A link prediction model for weighted networks based on Dempster–Shafer (DS) evidence theory and the influence of common neighbours is proposed in this paper. First, three types of future common neighbours (FCNs) and their topological structures are proposed. Second, the concepts of endpoint weight influence, link weight influence, and high‐strength node influence are introduced. Then, the similarity based on the impacts of current common neighbours (CCNs) and FCNs is defined, respectively. Finally, the two similarity indices are fused by the DS evidence theory. This model effectively integrates multisource information and completely exploits the influence of all CCNs and FCNs on similarity. Experiments are performed on 9 real and 40 simulation‐weighted datasets, and these findings are compared with several classic algorithms. Results show that the proposed method has higher precision than other methods, which can achieve good performance in link prediction in weighted networks.
Analysis of Risk Factors of Bronchiolitis Obliterans in Children with Mycoplasma pneumoniae Bronchiolitis
Authors: Huang KunLing , Liu Jianhua , Lv Wenshan , Chu Yajuan , Li Baochi , Wu Peng , Shuai Jinfeng
Published: March 2022

Objective. To investigate the related risk factors for bronchiolitis obliterans (BO) in children with mycoplasma pneumonia (MP) bronchiolitis. Method. The clinical data of 227 children with MP bronchiolitis who were admitted to the II Department of Respiratory of Children’s Hospital of Hebei Province from January 2018 to June 2020 were retrospectively analyzed. According to the sequelae of BO, they were divided into 32 cases in the BO group and 195 cases in the non-BO group. The univariate analysis was performed on the clinical and laboratory parameters of the two groups, and the multifactor logistic regression was performed further to determine the independent risk factors for the occurrence of BO in MP bronchiolitis, and then, the cut-off value with the maximum diagnostic value of indicators was found through the ROC curve analysis. Results. The results of univariate and multivariate logistic regression analysis showed that the independent risk factors for the occurrence of BO in MP bronchioles were longer duration of moist rales (

OR
=
1.203

,

P
=
0.003

), higher levels of serum lactate dehydrogenase (LDH) (

OR
=
1.005

,

P
=
0.036

), hypoxemia (

OR
=
7.442

,

P
=
0.035

), and pleural effusion (

OR
=
4.437

,

P
=
0.004

). The area under the ROC curve was 78.2%, 72.0%, 68.2%, and 71.0%, respectively (

P
<
0.001

). The cut-off value of duration of moist rales and levels of serum LDH are 7.5 d and 330 U/L, respectively. Conclusion. Children with MP bronchiolitis with high serum LDH level (≥330 U/L), combined with hypoxemia, pleural effusion, and lung wet rale duration (≥7.5 d), may be more prone to BO, in which lung wet rale duration prediction value is the largest. Among them, duration of pulmonary moist rales has the highest predictive value.
Volcanic Ash Region Path Planning Based on Improved A-Star Algorithm
Authors: Ma Lan , Zhang Haotong , Meng Shijun , Liu Jiayue
Published: March 2022

In civil aviation flight path planning, in order to effectively reduce the safety threat caused by the volcanic ash area to the civil aviation flight, factors such as the speed and acceleration of the aircraft in the volcanic ash area must be considered. In this paper, we propose an improved A-star algorithm by adopting the concept of potential collision set and using the velocity vector idea of optimal reciprocal collision avoidance (ORCA). The improved A-star algorithm selects the optimal speed range of the aircraft from the limited elements, obtains the speed and acceleration set of the aircraft in the volcanic ash area, calculates the flight path through the displacement increment, continuously refreshes the global starting point to the target point, and finally obtains the final path planning results by calculating the total cost value. The improved A-star algorithm is used to plan two flight paths from Madrid to Cairo and Algiers to Rome in volcanic ash areas. The verification results show that the improved A-star algorithm optimizes the flight path planning in the volcanic ash area and has the advantages of less search nodes, a small search range, and short computing time.
Allium Ureteral Stent as a Treatment for Ureteral Stricture: Results and Concerns
Authors: Avitan Ofir , Bahouth Zaher , Shprits Sagi , Gorenberg Miguel , Halachmi Sarel
Published: March 2022

Introduction: Ureteral strictures could be a chronic illness that leads to severe side effects and poor quality of life. A treatment with an Allium ureteral stent (URS), a self-expanding, large-caliber URS, was implemented in our department for ureteral stricture. Our study aim was to report the long-term results, including success rate, complications, and adverse effects. Methods: We retrospectively collected data on all patients who were treated with an Allium URS in our department between January 2017 and January 2021. Demographic, clinical, radiological, and perioperative parameters were retrieved and analyzed. The primary outcome was stricture resolution rates following stent removal. Results: Our cohort included 17 patients, 9 men and 8 women. The etiology of ureteral strictures was urolithiasis in 76.5% and pelvic procedure injury in 17.6%. The overall success rate was 35.29% in an average follow-up of 10.42 ± 2.39 months after stent removal. A higher failure rate was observed in the urolithiasis etiology group (90% vs. 66.7%, p = 0.38). The mean indwelling time of the Allium stent was 14.29 ± 1.29 months. Conclusions: Although an Allium URS could be considered as a feasible and attractive treatment of ureteral strictures, due to its minimal invasiveness, the success rate of this treatment is relatively low. Therefore, this option should be carefully considered and should be discouraged in young and fit patients and reserved for older unfit patients who are unwilling to undergo surgical repair of ureteral strictures.
How to Better Distinguish between Type II and III Selective Fetal Growth Restriction in Monochorionic Twin Pregnancies?
Authors: Couck Isabel , Deprest Jan , Lewi Liesbeth
Published: March 2022

Objectives: The objective of this study is to determine additional variables, next to umbilical artery (UA) Doppler, to help differentiate between Type II and III selective fetal growth restriction (sFGR). Methods: Retrospective analysis categorizing monochorionic diamniotic twin pregnancies with sFGR and abnormal UA Doppler as either Type II or III sFGR based on the diameter of the artery-to-artery (AA) anastomosis of ≤2 or >2 mm, respectively on placental examination after birth. This exploratory study compared maternal characteristics, pregnancy outcome, placental characteristics, and ultrasound features between the two groups. Results: We included 40 sFGR placentas, 13 were classified as Type II and 27 as Type III. Maternal age was higher in Type II. Small Type II twins had lower birth weights (BWs) for gestational age and BW discordance was higher in Type II. Type III placentas were more unevenly divided, but Type III pairs differed less in BW than expected relative to their placental discordance. Type III placentas more commonly had a vein-to-vein anastomosis and larger artery-to-vein anastomoses than Type II placentas, and proximate cord insertions were only observed in Type III. On the ultrasound scan at first diagnosis, small Type II twins were more growth-restricted. An AA anastomosis was detected in half of the Type III cases and in none of the Type II group. Signs of high-output cardiac strain were observed only in large Type III twins. In contrast, placental dichotomy was detected in nearly half of the Type II cases and only one Type III case. Conclusions: The presence of an AA anastomosis, signs of cardiac strain in the large twin, and proximate cord insertions suggested Type III sFGR, whereas placental dichotomy and a severe growth restriction were typically present in Type II. Prospective studies need to validate if these markers help prenatal differentiation between Type II and III sFGR.
Efficacy and Safety of PD-1 Immune Checkpoint Inhibitors in Locally Advanced and Advanced Non-Small-Cell Lung Cancer Patients with Chronic Infection
Authors: Zhao Zhiting , Hu Ran , Chen Yan , Zhou Guoren , Yu Shaorong , Feng Jifeng
Published: March 2022

Background: Immune checkpoint inhibitors have become new research hot spots in the treatment of non-small-cell lung cancer (NSCLC), but the efficacy and safety of immunotherapy for patients with chronic infection are still unclear because existing clinical trials often exclude those patients. Materials and Methods: We identified 78 locally advanced or advanced NSCLC patients with chronic infection treated with programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors alone or combined with the chemotherapy/bevacizumab therapy, of whom 60 with hepatitis B, 2 with hepatitis C, and 16 with syphilis. Objective response rates were assessed using the RECIST v1.1. Adverse events (AEs) were graded following the National Cancer Institute Common Terminology Criteria for Adverse Events v5.0. Results: Objective responses were observed in 19 out of 78 (24.36%) patients, and the disease control rate was 69.23% (54/78). No patient achieved a complete response. The median progression-free survival (PFS) was 6.49 months (95% CI: 3.71–9.27). PFS was 1.44 months (95% CI: 0.00–4.34) for monotherapy versus 7.34 months (95% CI: 4.50–10.18) for combination therapy (p = 0.053). Patients in the first-line treatment group revealed relatively higher ORR and longer PFS (ORR: 48.00% vs. 13.20%, p = 0.001; PFS: 7.67 vs. 5.57 months, p = 0.129). Patients with combined radiotherapy showed longer PFS than those without combined radiotherapy (14.07 vs. 4.62, p = 0.027). The incidence of AEs of any grade was 73.07% (57/78), among which there were 7 cases of grade 4 AEs. The incidence of leukopenia in any grade of AEs was the highest (57.69%), followed by anemia (25.64%), elevated alanine aminotransferase or aspartate aminotransferase (24.36%), and fatigue (21.79%). Hepatic transaminase increased in 26.7% (16/60) of HBV-infected patients and remained unchanged in 65.0% (39/60) patients. Conclusions: The PD-1 inhibitor showed an acceptable toxicity profile and moderate efficacy on NSCLC patients with chronic infection, but still has the potential to increase the incidence of hepatitis.
Impact of the COVID‐19 Pandemic on Patients Without COVID‐19 With Acute Myocardial Infarction and Heart Failure
Authors: Fox Daniel K. , Waken R. J. , Johnson Daniel Y. , Hammond Gmerice , Yu Jonathan , Fanous Erika , Maddox Thomas M. , Joynt Maddox Karen E.
Published: March 2022

Background

Excess mortality from cardiovascular disease during the COVID‐19 pandemic has been reported. The mechanism is unclear but may include delay or deferral of care, or differential treatment during hospitalization because of strains on hospital capacity.

Methods and Results

We used emergency department and inpatient data from a 12‐hospital health system to examine changes in volume, patient age and comorbidities, treatment (right‐ and left‐heart catheterization), and outcomes for patients with acute myocardial infarction (AMI) and heart failure (HF) during the COVID‐19 pandemic compared with pre‐COVID‐19 (2018 and 2019), controlling for seasonal variation. We analyzed 27 427 emergency department visits or hospitalizations. Patient volume decreased during COVID‐19 for both HF and AMI, but age, race, sex, and medical comorbidities were similar before and during COVID‐19 for both groups. Acuity increased for AMI as measured by the proportion of patients with ST‐segment elevation. There were no differences in right‐heart catheterization for patients with HF or in left heart catheterization for patients with AMI. In‐hospital mortality increased for AMI during COVID‐19 (odds ratio [OR], 1.46; 95% CI, 1.21–1.76), particularly among the ST‐segment–elevation myocardial infarction subgroup (OR, 2.57; 95% CI, 2.24–2.96), but was unchanged for HF (OR, 1.02; 95% CI, 0.89–1.16).

Conclusions

Cardiovascular volume decreased during COVID‐19. Despite similar patient age and comorbidities and in‐hospital treatments during COVID‐19, mortality increased for patients with AMI but not patients with HF. Given that AMI is a time‐sensitive condition, delay or deferral of care rather than changes in hospital care delivery may have led to worse cardiovascular outcomes during COVID‐19.
Low Circulating Musclin is Associated With Adverse Prognosis in Patients Undergoing Transcatheter Aortic Valve Implantation at Low‐Intermediate Risk
Authors: Kattih Badder , Carstens Daniel C. , Boeckling Felicitas , Rasper Tina , Pergola Graziella , Dimmeler Stefanie , Vasa‐Nicotera Mariuca , Zeiher Andreas M. , Mas‐Peiro Silvia
Published: March 2022

Background

Musclin is an activity‐stimulated and cardioprotective myokine that attenuates pathological cardiac remodeling. Musclin deficiency, in turn, results in reduced physical endurance. The aim of this study was to assess the prognostic value of circulating musclin as a novel, putative biomarker to identify patients undergoing transcatheter aortic valve implantation (TAVI) who are at a higher risk of death.

Methods and Results

In this study, we measured systemic musclin levels in 368 patients undergoing TAVI who were at low to intermediate clinical risk (median EuroSCORE [European System for Cardiac Operative Risk Evaluation] II: 3.5; quartile 1–quartile, 2.2%–5.3%), whereby 209 (56.8%) patients were at low and 159 (43.2%) were at intermediate risk. Median preprocedural musclin levels were 2.7 ng/mL (quartile 1–quartile 3, 1.5–4.6 ng/mL). Musclin levels were dichotomized in low (<2.862 ng/mL, n=199 [54.1%]) or high (≥ 2.862 ng/mL, n=169 [45.9%]) groups using cutoff values determined by classification and regression tree analysis. The primary end point was 1‐year overall survival. Patients with low circulating musclin levels exhibited a significantly higher prevalence of frailty, low albumin values, hypertension, and history of stroke as well as higher N‐terminal pro‐B‐type natriuretic peptide. Low musclin levels significantly predicted risk of death in univariable (hazard ratio, 1.81; 95% CI, 1.00–3.53 [
P
=0.049]) and multivariable (adjusted hazard ratio, 2.45; 95% CI, 1.06–5.69 [
P
=0.037]) Cox regression analyses. Additionally, low musclin levels in combination with conventional EuroSCORE II suggested improved risk stratification in patients undergoing TAVI who were at low to intermediate clinical risk into subgroups with reduced 1‐year survival rates by log‐rank test (
P
for trend=0.003).

Conclusions

Circulating musclin is an independent predictor of 1‐year overall survival in patients undergoing TAVI. Combined with EuroSCORE II, circulating musclin might help to improve prediction of mortality in patients undergoing TAVI who are at low to intermediate clinical risk.
Effectiveness of Telemedicine Visits in Reducing 30‐Day Readmissions Among Patients With Heart Failure During the COVID‐19 Pandemic
Authors: Xu Hanzhang , Granger Bradi B. , Drake Connor D. , Peterson Eric D. , Dupre Matthew E.
Published: March 2022

Background

The COVID‐19 pandemic resulted in a rapid implementation of telemedicine into clinical practice. This study examined whether early outpatient follow‐up via telemedicine is as effective as in‐person visits for reducing 30‐day readmissions in patients with heart failure.

Methods and Results

Using electronic health records from a large health system, we included patients with heart failure living in North Carolina (N=6918) who were hospitalized between March 16, 2020 and March 14, 2021. All‐cause readmission within 30 days after discharge was examined using weighted logistic regression models. Overall, 7.6% (N=526) of patients received early telemedicine follow‐up, 38.8% (N=2681) received early in‐person follow‐up, and 53.6% (N=3711) did not receive follow‐up within 14 days of discharge. Compared with patients without early follow‐up, those who received early follow‐up were younger, were more likely to be Medicare beneficiaries, had more comorbidities, and were less likely to live in an disadvantaged neighborhood. Relative to in‐person visits, those with telemedicine follow‐up were of similar age, sex, and race but with generally fewer comorbidities. Overall, the 30‐day readmission rate (19.0%) varied among patients who received telemedicine visits (15.0%), in‐person visits (14.0%), or no follow‐up (23.1%). After covariate adjustment, patients who received either telemedicine (odds ratio [OR], 0.55; 95% CI, 0.44–0.72) or in‐person (OR, 0.52; 95% CI, 0.45–0.60) visits were similarly less likely to be readmitted within 30 days compared with patients with no follow‐up.

Conclusions

During the COVID‐19 pandemic, the use of telemedicine visits for early follow‐up increased rapidly. Patients with heart failure who received outpatient follow‐up either via telemedicine or in‐person had better outcomes than those who received no follow‐up.
Association Between Inappropriately Dosed Anticoagulation Therapy With Stroke Severity and Outcomes in Patients With Atrial Fibrillation
Authors: Vinding Naja E. , Butt Jawad H. , Olesen Jonas B. , Xian Ying , Kristensen Søren Lund , Rørth Rasmus , Bonde Anders Nissen , Gundlund Anna , Yafasova Adelina , Weeke Peter E. , Gislason Gunnar H. , Torp‐Pedersen Christian , Køber Lars , Fosbøl Emil L.
Published: March 2022

Background

Oral anticoagulation (OAC) is effective for stroke prevention in patients with atrial fibrillation. However, some patients experience stroke despite OAC therapy, and knowledge about the impact of prior treatment quality is lacking.

Methods and Results

Patients with atrial fibrillation on OAC therapy who had a first‐time ischemic stroke were identified in the Danish Stroke Registry (2005–2018). Patients treated with vitamin K antagonist (VKA) therapy were compared according to the international normalized ratio just before stroke (international normalized ratio <2 [subtherapeutic], international normalized ratio 2–3 [therapeutic], international normalized ratio >3 [supratherapeutic]), and patients on underdosed, appropriately dosed, and overdosed direct OAC (DOAC) therapy were compared. Stroke severity was determined using the Scandinavia Stroke Scale (0–58 points), and the risk of very severe stroke (0–14 points) was analyzed by multivariable logistic regression. One‐year mortality was determined using multivariable Cox regression. A total of 2319 patients with atrial fibrillation and stroke were included; 1196 were taking a VKA (subtherapeutic [46%], therapeutic [43%], supratherapeutic [11%]), and 1123 were taking DOAC (underdosed [23%], appropriately dosed [60%], and overdosed [17%]). Subtherapeutic and supratherapeutic VKA therapy (compared with therapeutic) and underdosed DOAC therapy (compared with appropriate and underdosed DOAC) patients were older, more often women, and more comorbid. Subtherapeutic VKA therapy was associated with very severe stroke (odds ratio [OR], 2.06 [95% CI, 1.28–3.31]), whereas supratherapeutic VKA therapy was not (OR, 1.24 [95% CI, 0.60–2.57]) compared with therapeutic VKA therapy. Patients on subtherapeutic and supratherapeutic VKA therapy had a higher 1‐year mortality (hazard ratio [HR], 1.66 [95% CI, 1.29–2.13]); HR, 1.55 [95% CI, 1.08–2.22], respectively) than those on therapeutic VKA therapy. Treatment with underdosed or overdosed DOAC therapy was not associated with very severe stroke (OR, 1.27 [95% CI, 0.76–2.15]; OR, 0.73 [95% CI, 0.37–1.43], respectively) and was not associated with 1‐year mortality (HR, 1.09 [95% CI, 0.83–1.44]; HR, 0.82 [95% CI, 0.57–1.18], respectively) than appropriate DOAC.

Conclusions

Half of the patients with atrial fibrillation with stroke were on inappropriate OAC therapy. Subtherapeutic VKA was associated with worse stroke severity and higher mortality rate than therapeutic VKA therapy. Neither underdosed nor overdosed DOAC was associated with worse outcomes in adjusted models compared with appropriately dosed DOAC. This study supports DOAC as a first‐line therapy over VKA.
Faster Zero-shot Multi-modal Entity Linking via Visual-Linguistic
Representation
Authors: Zheng Qiushuo , Wen Hao , Wang Meng , Qi Guilin , Bai Chaoyu
Published: March 2022

Multi-modal entity linking plays a crucial role in a wide range of knowledge-based modal-fusion tasks, i.e., multi-modal retrieval and multi-modal event extraction. We introduce the new ZEro-shot Multi-modal Entity Linking (ZEMEL) task, the format is similar to multi-modal entity linking, but multi-modal mentions are linked to unseen entities in the knowledge graph, and the purpose of zero-shot setting is to realize robust linking in highly specialized domains. Simultaneously, the inference efficiency of existing models is low when there are many candidate entities. On this account, we propose a novel model that leverages visuallinguistic representation through the co-attentional mechanism to deal with the ZEMEL task, considering the trade-off between performance and efficiency of the model. We also build a dataset named ZEMELD for the new task, which contains multi-modal data resources collected from Wikipedia, and we annotate the entities as ground truth. Extensive experimental results on the dataset show that our proposed model is effective as it significantly improves the precision from 68.93% to 82.62% comparing with baselines in the ZEMEL task.
The role of lemur seed dispersal in restoring degraded forest ecosystems in Madagascar
Authors: Steffens Kim J.E. , Sanamo Justin , Razafitsalama Jeremi
Published: March 2022

Anthropogenic disturbances lead to the degradation or destruction of tropical forests, with negative consequences for flora, fauna, and local people. Restoration plantings may compensate these impacts, but time and financial expenditures are high. Thus, priority is often given to plantations of a few introduced species that have little value for conservation. Animal seed dispersal may diversify and accelerate regeneration of restoration plantings, thereby lowering their costs. We studied seed dispersal quantity and quality of crowned lemurs (Eulemur coronatus) in a highly degraded forest in northern Madagascar, conducting behavioural observations and germination experiments and describing dispersed plant species’ characteristics. Crowned lemurs were highly frugivorous, dispersing a large number of seeds and plant species. While there were negative effects of gut passage on germination, the positive effects of pulp removal outweighed these, resulting in an overall positive effect on regeneration. Our study confirmed that effects of gut passage are dependent on the dispersed plant species. We found 20 plant species, including three threatened with extinction, whose only dispersers in Oronjia seem to be crowned lemurs. We conclude that lemurs play important roles in protecting plant species and maintaining healthy ecosystems through seed dispersal, and that E. coronatus is a key species in this respect. In addition, if lemurs were included in restoration, they would disperse a diversity of plant species that cannot be matched by conventional restoration plantings. Their influence would facilitate the regeneration of some, but not all plant species. Negative effects, like the spread of invasive species through seed dispersal by lemurs, must also be considered.