bluuebunny/crossref_metadata_2025 huggingface dataset:
Serum Levels of HCY, MIF, and hs-CRP Correlate with Glycolipid Metabolism in Adults with Never-Medicated First-Episode Schizophrenia
Authors: Zhong Xiao , Ao Qin , Xing Fei
Published: November 2021

Objective. It has been reported that the prevalence of metabolic syndrome (MS) in multiepisode patients with schizophrenia is 35.3%, which is 2- to 4-fold higher than in the general population. The study is designed to compare the glycolipid metabolism in patients with first-episode schizophrenia (FES) with sex- and age-matched healthy controls to investigate changes in serum levels of homocysteine (Hcy), macrophage migration inhibitory factor (MIF), and high-sensitive C-reactive protein (hs-CRP) and their relationships with the glycolipid metabolism in patients with FES. Methods. His case-control study included 88 patients diagnosed with FES and 88 sex- and age-matched healthy controls. Patient psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS), Young Mania Rating Scale (YMRS), and 17-item Hamilton Rating Scale for Depression (HAMD-17). Patients with FES were classified into MS and non-MS groups. Results. There were significant differences in the education level, body mass index (BMI), and waist circumference between the patients with FES and healthy controls (all

p
>
0.05

). The patients with FES had higher levels of FPG and blood glucose at the oral glucose tolerance test (OGTT) (2 h glucose) concomitant with higher proportion of impaired glucose tolerance (IGT) and homeostasis model assessment of insulin resistance (HOMA2-IR) than healthy controls (all

p
<
0.001

). It was revealed that the patients with FES showed higher serum levels of Hcy, MIF, and hs-CRP than healthy controls (all

p
<
0.001

). The serum level of Hcy shared positive correlations with the score of PANSS totals (r = 0.551) and the negative syndrome of the PANSS scale (r = 0.494). The serum levels of MIF and hs-CRP was only positively correlated with the negative syndrome of the PANSS scale (r = 0.320 and r = 0.446). The level of Hcy shared positive correlations with the levels of FPG, 2 h glucose, and HOMA2-IR; the level of MIF was only positively correlated with the level of HOMA2-IR; the level of hs-CRP had a positive correlation with both levels of FPG and 2 h glucose (all

p
<
0.001

). The levels of Hcy, MIF, and hs-CRP all shared positive correlations with the TG level and negative correlations with the HDL-C level (all

p
<
0.001

). There were remarkable differences between the MS and non-MS groups with regard to BMI, waist circumference, negative subscale of the PANSS scale, FPG, TG, and HDL-C (all

p
<
0.05

). Elevated levels of Hcy, MIF, and hs-CRP were detected in the MS group compared to the non-MS group (all

p
<
0.05

). Conclusion. These findings suggest that increased concentrations of HCY, MIF, and hs-CRP may contribute to the abnormal glycolipid metabolism in the context of schizophrenia.
Intelligent Diagnosis of Cervical Cancer Based on Data Mining Algorithm
Authors: Zhang Lei , Zhu Yuanyuan , Song Yuchen , Han Yaqing , Sun Danli , Qin Shanshan , Gao Yingchun
Published: November 2021

The intelligent diagnosis of cervical cancer by using a class of data mining algorithms has important practical significance. In particular, the useful information included in a significant quantity of medical data may not only discreetly boost the development of medical technology but also detect cervical cancer in the future. This paper improves the data mining algorithm and combines image recognition technology and data mining technology to extract and analyze image features. Moreover, this paper makes full use of the information contained in the image to realize the segmentation of the cervical cancer cell image, select the feature vector according to the characteristics of the cervical cancer cell, and use the statistical classification method to design the classifier. The test results show that the automatic recognition effect of this system is good, and it has a good auxiliary diagnosis effect. Therefore, it can be verified in clinical practice in the follow-up.
Three-Dimensional Structure Analysis of Urban Landscape Based on Big Data Technology and Digital Technology
Authors: Yang Xiaozhou , Bai Fan
Published: November 2021

In order to improve the effect of urban landscape design, this paper combines big data technology with digital technology. For scenes and solutions containing SDS paths, a processing method similar to photon graphs is used and added to the calculation of two-way optical path tracking. In the processing scene, this paper uses the two-way optical path tracking method to perform specular reflection or refraction from the subpath starting from the light source and then store information such as the light energy of the points on the diffuse reflection surface or the directional reflection surface. Moreover, this paper combines the actual needs of urban landscape design to construct an urban landscape design system based on big data technology and digital technology. Finally, this paper designs experiments to carry out urban landscape simulation and design effect evaluation. From the test results, it can be seen that the system designed in this paper basically meets the needs of urban landscape planning and design.
Metagenomic Sequencing Analysis for Acne Using Machine Learning Methods Adapted to Single or Multiple Data
Authors: Wang Yu , Sun Mengru , Duan Yifan
Published: November 2021

The human health status can be assessed by the means of research and analysis of the human microbiome. Acne is a common skin disease whose morbidity increases year by year. The lipids which influence acne to a large extent are studied by metagenomic methods in recent years. In this paper, machine learning methods are used to analyze metagenomic sequencing data of acne, i.e., all kinds of lipids in the face skin. Firstly, lipids data of the diseased skin (DS) samples and the healthy skin (HS) samples of acne patients and the normal control (NC) samples of healthy person are, respectively, analyzed by using principal component analysis (PCA) and kernel principal component analysis (KPCA). Then, the lipids which have main influence on each kind of sample are obtained. In addition, a multiset canonical correlation analysis (MCCA) is utilized to get lipids which can differentiate the face skins of the above three samples. The experimental results show the machine learning methods can effectively analyze metagenomic sequencing data of acne. According to the results, lipids which only influence one of the three samples or the lipids which simultaneously have different degree of influence on these three samples can be used as indicators to judge skin statuses.
Modeling of Tunnel Concrete Lining under Fire and Explosion Damage
Authors: Yang Zhaopeng , Wang Linbing , Gao Zhifei
Published: November 2021

This paper presents studies that focus on fire and explosion‐induced damage of tunnel structures by employing the Discrete Element Method (DEM). By assuming a two‐dimensional aggregate distribution and reconstructing the digital representation of the experimental concrete blocks, a numerical model of the tunnel lining concrete was established in the PFC2D program. The temperature distribution and the shock wave pressure at the surface of the tunnel lining were obtained by using Fluent and LS‐Dyna separately; the final damage simulation of concrete section under different conditions was carried out in PFC2D. The results showed that PFC2D cooperatively provided more accurate and effective modeling and visualization of impact damage of concrete blocks. The visualizations of damage indicated the degree of damage more clearly and more intuitively. These findings also provide a potential method for further study of the damage assessment for entire tunnel lining structures.
Improved Quantitative Susceptibility Mapping under Laplace Algorithm in Diagnosis of Parkinson’s Disease
Authors: Chen Guangxi , Zeng Liang , Yang Liu , Yu Yixian , Sun Panli , Yao Tao
Published: November 2021

To explore the application value of quantitative susceptibility mapping (QSM) based on Laplace algorithm in the diagnosis of Parkinson’s disease, 48 Parkinson’s disease patients admitted to our hospital were included as the research objects. They were randomly divided into control group (24 cases) and experimental group (24 cases). All patients underwent quantitative magnetic susceptibility imaging scan. In the experimental group, the improved Laplace algorithm was used for QSM diagnosis, while in the control group, conventional QSM diagnosis was used. Through calculations of precision, recall, dice similarity coefficient, intersection-over-union (IoU), and area under the curve (AUC), the quality improvement effect of the improved Laplace algorithm for QSM image was assessed. Then, the diagnostic accuracy of the algorithm was verified by comparing with the results of QSM image diagnosis in Parkinson’s patients without algorithm processing. The results showed that compared with the traditional Laplace algorithm, the improved Laplace algorithm can considerably reduce the image noise level (

P
<
0.05

). The dice, IoU, precision, and recall rate of image quality evaluation indicator were considerably improved (

P
<
0.05

), and the AUC reached 0.896. There were no significant differences in fraction anisotropy (FA) and mean diffusivity (MD) between the two groups (

P
>
0.05

) and no significant differences in magnetic susceptibility of brain nuclei between the two groups (

P
>
0.05

). However, they all showed high magnetic susceptibility in the substantia nigra region of the brain. Compared with the control group, the diagnostic accuracy of the experimental group was 97.5 ± 1.23%, which was considerably higher than that of the control group (86.5 ± 3.56%) (

P
<
0.05

). In short, the image quality of QSM based on Laplace improved algorithm was greatly improved, and the diagnostic accuracy of PD was also greatly improved, which was worthy of promotion in the field of clinical QSM imaging diagnosis of PD.
Analysis of Multiterm Initial Value Problems with Caputo–Fabrizio Derivative
Authors: Al-Refai Mohammed , Syam Muhammed
Published: November 2021

In this paper, we discuss the solvability of a class of multiterm initial value problems involving the Caputo–Fabrizio fractional derivative via the Laplace transform. We derive necessary and sufficient conditions to guarantee the existence of solutions to the problem. We also obtain the solutions in closed forms. We present two examples to illustrate the validity of the obtained results.
Electrospinning and Catalytic Properties of Cyclodextrin Functionalized Polyoxymethylene (POM) Nanofibers Supported by Silver Nanoparticles
Authors: Zhang C. Q. , Wang Y. M. , Li S. Z. , Feng X. D. , Liu L. H. , Wang Y. , Zhao L. P.
Published: November 2021

A series of novel composite microfibers composed of β-cyclodextrin (β-CDs) functionalized POM (polyoxymethylene) were prepared using electrospining technology with a mixture of hexafluoroisopropanol (HFIP) and N,N-dimethylformamide (DMF) as solvent. The concentration of β-CDs with respect to the POM was varied from 0 to 50 wt.%. The effect of β-CDs content on the morphology of POM/β-CD composite microfiber was investigated. The results showed that the introduction of β-CDs reduced the surface roughness and porosity of the microfibers, and the morphology of the fibers was changed. The increase of β-CDs content from 10% to 50% has led to increased average diameter of POM/β-CD composite fiber from 2.1 μm to 6.4 μm. The mechanical properties of the blend fiber mats were further investigated. In addition, silver nanoparticles were introduced to the POM/β-CD composite microfiber matrices during electrospinning. The POM/β-CD composite fiber allows CDs to form host–guest complexes with various small molecules and macromolecules. The TEM, SEM, XRD, and XPS were utilized to characterize the prepared samples. The data suggest that Ag nanoparticles were homogeneously distributed within the POM/β-CD fibers, and no aggregation was observed. The catalytic activity of Ag nanoparticles was tracked by ultraviolet-visible (UV-vis) spectroscopy which showed excellent catalytic degradation performance of organic dyes in the presence of NaBH4. The Ag/POM/β-CD mats are promising for use in waste treatment, molecular recognition, catalysis, and so on.
Echocardiographic Features of Patients with Coronary Heart Disease and Angina Pectoris under Deep Learning Algorithms
Authors: Han Xianjing , Liang Guoxin
Published: November 2021

Based on the VGG19-fully convolutional network (FCN) (VGG19-FCN) and U-Net model in the deep learning algorithms, the left ventricle in the ultrasonic cardiogram was segmented automatically. In addition, this study evaluated the value of ultrasonic cardiogram features after segmentation by the optimized algorithm in diagnosing patients with coronary heart disease (CHD) and angina pectorisody; patients with arrhythmia; and pa. In this study, 30 patients with confirmed CHD and 30 normal people without CHD from the same hospital in a certain area were selected as the research objects. Firstly, the VGG19-FCN and U-Net model algorithms were selected to automatically segment the left ventricular part of the apical four-chamber static image, which was realized through the weights of the fine-tune basic model algorithm. Subsequently, the experimental subjects were divided into a normal group and a CHD group, and the data were obtained through the ultrasonic cardiogram feature analysis of automatic segmentation by the algorithm. The differences in the ejection fraction (EF), left ventricular fractional shortening (FS), and E/A values (in early and late of the diastolic phase) of the left ventricle for patients in the two groups were compared. In addition, the ultrasonic cardiogram left ventricular segmentation results of normal people and patients with CHD were compared. A comprehensive analysis suggested that the U-Net model was more suitable for the practical application of automatic ultrasonic cardiogram segmentation. According to the analyzed data results, the global systolic function parameters (EF, FS, and E/A values) of the left ventricle for patients showed statistically obvious differences (

P
<
0.05

). In summary, deep learning algorithms can effectively improve the efficiency of ultrasonic cardiogram left ventricular segmentation, show a great role in the diagnosis of CHD patients, and provide a reliable theoretical basis and foundation research on the subsequent CHD imaging diagnosis. The comprehensive analysis showed that the U-Net model was more suitable for the practical application of echocardiographic automatic segmentation, and this study can effectively improve the efficiency of echocardiographic left ventricular segmentation, which played an important role in the diagnosis of coronary heart disease, providing a reliable theoretical basis and foundation for subsequent CHD imaging research.
Development and Validation of a Stability-Indicating HPLC Method for the Simultaneous Determination of trans-Resveratrol and cis-Resveratrol in an Injectable Solution
Authors: Mota-Lugo Esmeralda , Dolores-Hernández Mariana , Morales-Hipólito Elvia A. , Blanco-Alcántara Iris A. , Cuatecontzi-Flores Hugo , López-Arellano Raquel
Published: November 2021

trans-Resveratrol, a phytochemical compound with antioxidant power and various therapeutic effects, such as cardioprotective, chemopreventive, and neuroprotective, among others, has disadvantages of poor solubility and limited stability, creating difficulties for the development of new strategies for its quantification. This study developed and validated an analytical stability method for trans-resveratrol by high-pressure liquid chromatography with photodiode-array detection (HPLC-PDA), which allowed its quantification in the presence of its degradation products. The quantification of trans-resveratrol occurred at a retention time of 2.6 min, with ammonium formate (10 mM, pH = 4)/acetonitrile, 70/30 v/v, as mobile phase. The validation met the ICH Q2 criteria of specificity, method linearity (2.8–4.2 μg/ml), precision and accuracy, robustness, quantification limit (0.176 μg/ml), and detection (0.058 μg/ml). As degradation products, cis-resveratrol was observed at 3.9 min, which could be resveratrone in 3.2 min and five unidentified products in 0.7, 1.0, 1.4, 1.8, and 5 min. Some solutions subjected to temperature stress of 40 and 60°C, UV light, and acidic and basic hydrolysis exhibited colour changes. An analytical method was obtained by HPLC-PDA, which allowed quantifying the stability of trans-resveratrol in a fast and specific manner in the presence of its degradation products.
Intelligent Recognition Method of Athlete Wrong Movement Based on Image Vision
Authors: Lu Wang , Hou JiangYuan
Published: November 2021

Current methods of human body movement recognition neglect the depth denoising and edge restoration of movement image, which leads to great error in athletes’ wrong movement recognition and poor application intelligence. Therefore, an intelligent recognition method based on image vision for sports athletes’ wrong actions is proposed. The basic principle, structure, and 3D application of computer image vision technology are defined. Capturing the human body image and point cloud data, the three-dimensional dynamic model of sports athletes action is constructed. The color camera including CCD sensor and CMOS sensor is selected to collect the wrong movement image of athlete and provide image data for the recognition of wrong movement. Wavelet transform coefficient and quantization matrix threshold are introduced to denoise the wrong motion images of athletes. Based on this, the feature of sports athlete’s motion contour image is extracted in spatial frequency domain, and the edge of the image is further recovered by Canny operator. Experimental results show that the proposed method can accurately identify the wrong movements of athletes, and there is no redundancy in the recognition results. Image denoising effect is good and less time-consuming and can provide a reliable basis for related fields.
Diverse Dynamic Behaviors and Firing Activities of the Modified Fractional‐Order Hindmarsh–Rose Neuronal Model Induced by Fractional‐Order
Authors: Yang Xin , Zhang GuangJun , Li XueRen , Wang Dong
Published: November 2021

It is important to investigate the firing activities of neurons, and previous experimental works have shown that fractional‐order neuronal models depict the firing rate of neurons more verifiably. In this study, a modified fractional‐order Hindmarsh–Rose neuronal model is proposed, and the dynamics and firing activities are investigated. Some novel phenomenon can be found. First, by analyzing numerically and theoretically, the Hopf bifurcation is found to occur when the external direct current stimulus is chosen appropriately. The effects of fractional‐order on the bifurcation are also studied. Second, when injecting a direct current stimulus, compared with the integer‐order model, the system has more varying dynamic behaviors and firing pattern transitions. Under different external current stimulus, periodic firing patterns and chaotic firing patterns occur when fractional‐order changes, but the regions of chaotic firing patterns are different. In other words, the transition mode of periodic firing and chaotic firing induced by fractional‐order is different under different external current stimulus. The two‐dimensional colored diagram of firing patterns is also investigated. Finally, when injecting periodic current stimulus, regular/irregular bursting, multiple spiking, regular\irregular square wave bursting, and mixed firing mods are found by setting the appropriate fractional‐order, amplitude, and frequency of the external current stimulus. Some firing patterns cannot be found in integer‐order models. When the amplitude is chosen at appropriate values, the region of frequency when the system displays the mixed firing modes decreases with increasing fractional‐order.
Modelling the COVID‐19 Mortality Rate with a New Versatile Modification of the Log‐Logistic Distribution
Authors: Muse Abdisalam Hassan , Tolba Ahlam H. , Fayad Eman , Abu Ali Ola A. , Nagy M. , Yusuf M.
Published: November 2021

The goal of this paper is to develop an optimal statistical model to analyze COVID‐19 data in order to model and analyze the COVID‐19 mortality rates in Somalia. Combining the log‐logistic distribution and the tangent function yields the flexible extension log‐logistic tangent (LLT) distribution, a new two‐parameter distribution. This new distribution has a number of excellent statistical and mathematical properties, including a simple failure rate function, reliability function, and cumulative distribution function. Maximum likelihood estimation (MLE) is used to estimate the unknown parameters of the proposed distribution. A numerical and visual result of the Monte Carlo simulation is obtained to evaluate the use of the MLE method. In addition, the LLT model is compared to the well‐known two‐parameter, three‐parameter, and four‐parameter competitors. Gompertz, log‐logistic, kappa, exponentiated log‐logistic, Marshall–Olkin log‐logistic, Kumaraswamy log‐logistic, and beta log‐logistic are among the competing models. Different goodness‐of‐fit measures are used to determine whether the LLT distribution is more useful than the competing models in COVID‐19 data of mortality rate analysis.
Application Effect of Computer-Assisted Local Anesthesia in Patient Operation
Authors: Hao Yuchen , Zhang Zheqi , Meng Yan
Published: November 2021

In order to avoid the psychological harm caused by pain to patients, in this study, the application effect of computer-assisted local anesthesia in patient surgery was studied. In this method, 72 patients with hypertension, 35 males and 37 females, aged 53–83 years, with an average age of 70.8 ± 1.3 years, were selected for appointment tooth extraction in the department of stomatology from January to December 2014. All patients were booked for tooth extraction by ECG monitoring. Patients who were contraindicated for tooth extraction, had a history of mental illness, and had used antianxiety drugs and sedatives within 1 week before surgery were excluded. Patients were randomly divided into two groups according to their ID numbers: observation group, 36 cases, and control group. Painless oral local anesthesia injection instrument was used for local anesthesia injection. In the control group, 36 patients were injected with local anesthesia by traditional manual injection. The results showed that 86.11% of patients in the observation group had decreased anxiety scores after anesthesia, while only 13.88% of patients in the control group had decreased anxiety scores. Among patients with decreased anxiety scores, 80.65% in the observation group became nondental anxiety compared with 28.57% in the control group. Computer-assisted oral local anesthesia can effectively control dental anxiety and relieve the pain and discomfort of local anesthesia injection, and improve patient satisfaction, conducive to the smooth nursing work.
Biocompatible and Biomaterials Application in Drug Delivery System in Oral Cavity
Authors: Hakim Lotfollah Kamali , Yazdanian Mohsen , Alam Mostafa , Abbasi Kamyar , Tebyaniyan Hamid , Tahmasebi Elahe , Khayatan Danial , Seifalian Alexander , Ranjbar Reza , Yazdanian Alireza
Published: November 2021

Biomaterials applications have rapidly expanded into different fields of sciences. One of the important fields of using biomaterials is dentistry, which can facilitate implantation, surgery, and treatment of oral diseases such as peri-implantitis, periodontitis, and other dental problems. Drug delivery systems based on biocompatible materials play a vital role in the release of drugs into aim tissues of the oral cavity with minimum side effects. Therefore, scientists have studied various delivery systems to improve the efficacy and acceptability of therapeutic approaches in dental problems and oral diseases. Also, biomaterials could be utilized as carriers in biocompatible drug delivery systems. For instance, natural polymeric substances, such as gelatin, chitosan, calcium phosphate, alginate, and xanthan gum are used to prepare different forms of delivery systems. In addition, some alloys are conducted in drug complexes for the better in transportation. Delivery systems based on biomaterials are provided with different strategies, although individual biomaterial has advantages and disadvantages which have a significant influence on transportation of complex such as solubility in physiological environments or distribution in tissues. Biomaterials have antibacterial and anti-inflammatory effects and prolonged time contact and even enhance antibiotic activities in oral infections. Moreover, these biomaterials are commonly prepared in some forms such as particulate complex, fibers, microspheres, gels, hydrogels, and injectable systems. In this review, we examined the application of biocompatible materials in drug delivery systems of oral and dental diseases or problems.
FDA-MIMO Beampattern Synthesis with an Analytical Method
Authors: Zhou Changlin , Wang Chunyang , Gong Jian , Tan Ming , Zhao Yingjian , Liu Mingjie
Published: November 2021

Since the beampattern has the characteristics of range-angle dependence, frequency diverse array multiple-input multiple-output (FDA-MIMO) radar has a good application prospect. There have been many studies to improve the performance of the beampattern by optimizing the frequency offset. However, on the basis of fully understanding the time parameters, the relationship between the array element frequency offset and the beampattern performance still needs to be clarified. Based on a new FDA-MIMO radar framework, this paper presents an analytical solution of the beampattern, which removes the influence of the time parameter. Taking the minimum main lobe as the objective function, an analytical method for solving a better frequency offset is given. Then, a method of using the window function was proposed to reduce the high side lobes of the range dimension. Comparing with the existing FDA radar beampattern design methods, it can achieve a more focusing beampattern. The simulation results verify the correctness of the theory.
Incentive and Coordination in the Two-Sided Market: Evidence from the P2P Lending Market
Authors: Zhao Yingxiu , Shi Baojuan
Published: November 2021

Two-sided markets serve as information intermediaries by connecting participants on both sides. In this study, we focus on the coordination of participants in the P2P lending market using a coupon strategy as an incentive to attract investment. Using a two-sided market model, we find that when a platform adopts the coupon strategy, (i) the platform utility and participants’ utility are both greater and (ii) the number of participants is greater. In addition, as most research on two-sided markets and coupon strategy focuses on theoretical models, our study provides empirical support using data from Renrendai.com over 2018 to 2019.
Major Outer Membrane Protein from Legionella pneumophila Inhibits Phagocytosis but Enhances Chemotaxis of RAW 264.7 Macrophages by Regulating the FOXO1/Coronin-1 Axis
Authors: Yang Zehui , Chen Yingying , Zhang Qiang , Chen Xiaodong , Deng Ze
Published: November 2021

Legionella pneumophila is an intracellular pathogen that can cause Legionnaire’s disease by invading alveolar epithelial cells and macrophages. The major outer membrane protein (MOMP) plays an important role in the interaction between bacteria and host cells. However, the role of MOMP in the process of L. pneumophila invasion of macrophages and its working mechanism remain unknown. We aimed to explore the effects of MOMP on phagocytosis and chemotaxis of RAW 264.7 macrophages. The chemotactic activity, toxicity, and phagocytosis of RAW 264.7 cocultured with different concentrations of MOMP were determined by Transwell, CCK-8, and neutral red uptake assays, respectively. Target genes were detected by double-luciferase and pull down assays. qRT-PCR and Western blot were performed to analyze the expression of several important proteins involved in the immune response pathway, including coronin-1, interleukins (IL-10), forkhead transcription factor 1 (FOXO1), nucleotide-binding oligomerization domain protein (NOD) 1, NOD2, and receptor-interacting protein (RIP) 2. After coculturing with MOMP, cytological observation indicated a decrease of phagocytosis and a marked increase of chemotaxis in RAW 264.7 macrophages. The phagocytosis degree of RAW 264.7 macrophage varied with the concentration gradient of MOMP in a time-dependent manner. MOMP could increase the expression levels of MCP-1, IL-10, NOD2, and RIP2 and decrease the expression levels of FOXO1 and coronin-1 in cell culture supernatants. In addition, we found that FOXO1 could promote its transcription by binding to the promoter of coronin-1. The results of the present study suggested that MOMP could inhibit phagocytosis and facilitate chemotaxis of RAW 264.7 macrophage, which might be associated with the FOXO1/coronin-1 axis.
Internet of Things-Based Ultrasound-Guided Erector Spinae Plane Block Combined with Edaravone Anesthesia in Thoracoscopic Lobectomy
Authors: Wang Xiuyan , Zhou Xuan , Li Lin , Liu Cuijie
Published: November 2021

This paper aimed to study the application value of Internet of Things (IoT) edge computing algorithm-based ultrasound-guided erector spinae plane block combined with edaravone anesthesia in thoracoscopic lobectomy. A total of 110 patients undergoing thoracoscopic resection were selected as subjects. The patients were anesthetized with erector spinae plane block combined with edaravone before surgery and underwent chest ultrasound scan. IoT edge computing algorithm was constructed and applied to ultrasound images of patients to enhance and denoise the images. It was found that, in different mixed noise mixtures (Gaussian noise 10% + speckle noise 90%; Gaussian noise 30% + speckle noise 70%), the edge computing algorithm can still maintain the edge information of the output image, showing better performance on edge information detection and denoising compared with the Prewitt and Canny operator. In addition, visual analog scale (VAS) scores decreased with postoperative time after edaravone anesthesia induction and erector spinae plane block lobectomy and reached the lowest level after five days. In short, erector spinae plane block combined with edaravone showed good sedative and analgesic effects on patients undergoing thoracoscopic lobectomy. Ultrasound images processed by IoT edge computing algorithm showed high accuracy in the identification of lung lesions, which was worth applying to clinical diagnosis.
Maternal and Fetal Outcomes in Women with Diabetes in Pregnancy Treated before and after the Introduction of a Standardized Multidisciplinary Management Protocol
Authors: Morlando Maddalena , Savoia Fabiana , Conte Anna , Schiattarella Antonio , La Verde Marco , Petrizzo Michela , Carpentieri Mauro , Capristo Carlo , Esposito Katherine , Colacurci Nicola
Published: November 2021

Background. Diabetes in pregnancy is associated with an increased risk to the woman and to the developing fetus. Currently, there is no consensus on the optimal management strategies for the follow-up and the timing of delivery of pregnancies affected by gestational and pregestational diabetes, with different international guidelines suggesting different management options. Materials and Methods. We conducted a retrospective cohort study from January 2017 to January 2021, to compare maternal and neonatal outcomes of pregnancies complicated by gestational and pregestational diabetes, followed-up and delivered in a third level referral center before and after the introduction of a standardized multidisciplinary management protocol including diagnostic, screening, and management criteria. Results. Of the 131 women included, 55 were managed before the introduction of the multidisciplinary management protocol and included in group 1 (preprotocol), while 76 were managed according to the newly introduced multidisciplinary protocol and included in group 2 (after protocol). We observed an increase in the rates of vaginal delivery, rising from 32.7% to 64.5% (<0.001), and the rate of successful induction of labor improved from 28.6% to 86.2% (

P
<
0.001

). No differences were found in neonatal outcomes, and the only significant difference was demonstrated for the rates of fetal macrosomia (20% versus 5.3%,

P

: 0.012). Therefore, the improvements observed in the maternal outcomes did not impact negatively on fetal and neonatal outcomes. Conclusion. The introduction of a standardized multidisciplinary management protocol led to an improvement in the rates of vaginal delivery and in the rate of successful induction of labor in our center. A strong cooperation between obstetricians, diabetologists, and neonatologists is crucial to obtain a successful outcome in women with diabetes in pregnancy.
The Effect of Joint Damage on a Coal Wall and the Influence of Joints on the Abutment Pressure on a Fully Mechanised Working Face with Large Mining Height
Authors: Guo Weibin , Zhang Shengwei , Li Yuhui
Published: November 2021

Coal wall spalling is regarded as a key technical problem influencing safe and efficient mining of large‐mining‐height working faces while the distribution of abutment pressure within the limit equilibrium zone (LEZ) influences coal wall spalling within a large‐mining‐height working face. This research attempted to explore the distribution characteristics of abutment pressure within the LEZ in a large‐mining‐height working face. For this purpose, the influences of the orientation of joints on mechanical characteristics of coal with joints and on the distribution of abutment pressure within the LEZ in the large‐mining‐height working face were analysed by theoretical analysis and numerical simulation. Research results show that the damage variable of coal with joints first rises, then decreases, and finally increases with increasing dip angle of the joints; as the azimuth of the joints increases, the damage variable first declines, then increases; the damage variable gradually declines with increasing joint spacing; an increase in the dip angle of joints corresponds to first reduction, then growth, and a final decrease of the abutment pressure at the same position in front of the coal walls; on certain conditions, the abutment pressure at the same position within the LEZ first rises, then declines as the azimuth of joints increases; with the growth of the joint spacing, the abutment pressure at the same position within the LEZ rises. The dip angle and azimuth of joints marginally affect the abutment pressure within the LEZ.
Exploring the Built Environment Factors in the Metro That Influence the Ridership and the Market Share of the Elderly and Students
Authors: Ning Jiang , Lyu Tao , Wang Yuanqing
Published: November 2021

The metro has developed rapidly in the past two decades and has become one of the crucial patterns of transportation for urban residents in China. Many studies have explored the factors affecting metro ridership, but few have focused on the metro usage of specific groups, such as the elderly and students. This paper uses the negative binomial regression model to explore the relationship between the built environment and the metro ridership of three types of people (adults, the elderly, and students) by using the metro smart card data of Qingdao. We also used the fractional response model to discuss the factors that influence the ridership share for the elderly and students. The results show that most variables promote the metro usage of the three groups of people but have a significantly different effect on the market share of those groups. Specifically, the number of schools, hospitals, supermarkets, squares, parks, and scenic spots near metro stations significantly increases the proportion of the elderly metro usage. The number of bus stops and schools substantially increases the share of metro ridership by students. The research results can provide valuable insights for promoting the metro’s overall ridership and minimizing the gap in allocating public transport resources among different groups.
Finerenone Reduces Risk of Incident Heart Failure in Patients With Chronic Kidney Disease and Type 2 Diabetes: Analyses From the FIGARO-DKD Trial
Authors: Filippatos Gerasimos , Anker Stefan D. , Agarwal Rajiv , Ruilope Luis M. , Rossing Peter , Bakris George L. , Tasto Christoph , Joseph Amer , Kolkhof Peter , Lage Andrea , Pitt Bertram ,   on behalf of the FIGARO-DKD Investigators
Published: November 2021

Background:

Chronic kidney disease and type 2 diabetes are independently associated with heart failure (HF), a leading cause of morbidity and mortality. In the FIDELIO-DKD (Finerenone in Reducing Kidney Failure and Disease Progression in Diabetic Kidney Disease) and FIGARO-DKD (Finerenone in Reducing Cardiovascular Mortality and Morbidity in Diabetic Kidney Disease) trials, finerenone (a selective, nonsteroidal mineralocorticoid receptor antagonist) improved cardiovascular outcomes in patients with albuminuric chronic kidney disease and type 2 diabetes. These prespecified analyses from FIGARO-DKD assessed the effect of finerenone on clinically important HF outcomes.

Methods:

Patients with type 2 diabetes and albuminuric chronic kidney disease (urine albumin-to-creatinine ratio ≥30 to <300 mg/g and estimated glomerular filtration rate ≥25 to ≤90 mL per min per 1.73 m
2
, or urine albumin-to-creatinine ratio ≥300 to ≤5000 mg/g and estimated glomerular filtration rate ≥60 mL per min per 1.73 m
2
), without symptomatic HF with reduced ejection fraction, were randomized to finerenone or placebo. Time-to-first-event outcomes included new-onset HF (first hospitalization for HF [HHF] in patients without a history of HF at baseline); cardiovascular death or first HHF; HF-related death or first HHF; first HHF; cardiovascular death or total (first or recurrent) HHF; HF-related death or total HHF; and total HHF. Outcomes were evaluated in the overall population and in prespecified subgroups categorized by baseline HF history (as reported by the investigators).

Results:

Overall, 7352 patients were included in these analyses; 571 (7.8%) had a history of HF at baseline. New-onset HF was significantly reduced with finerenone versus placebo (1.9% versus 2.8%; hazard ratio [HR], 0.68 [95% CI, 0.50–0.93];
P
=0.0162). In the overall population, the incidences of all HF outcomes analyzed were significantly lower with finerenone than placebo, including an 18% lower risk of cardiovascular death or first HHF (HR, 0.82 [95% CI, 0.70–0.95];
P
=0.011), a 29% lower risk of first HHF (HR, 0.71 [95% CI, 0.56–0.90];
P
=0.0043) and a 30% lower rate of total HHF (rate ratio, 0.70 [95% CI, 0.52–0.94]). The effects of finerenone on improving HF outcomes were not modified by a history of HF. The incidence of treatment-emergent adverse events was balanced between treatment groups.

Conclusions:

The results from these FIGARO-DKD analyses demonstrate that finerenone reduces new-onset HF and improves other HF outcomes in patients with chronic kidney disease and type 2 diabetes, irrespective of a history of HF.

Registration:

URL:
https://www.clinicaltrials.gov
; Unique identifier: NCT02545049.
The Tale of Two Lexicons: Decomposing Complexity across a Distributed Lexicon
Authors: Lohndal Terje , Putnam Michael T.
Published: November 2021

The notion of complexity is evasive and often left to intuition, yet it is often invoked when studying heritage language grammars. In this article, we propose a first pass at decomposing the notion of complexity into smaller components in a formal grammatical model. In particular, we argue that a distributed model of the lexicon (i.e., one that assumes that principles that generate both words and phrases are one and the same) allows us to identify three components: syntactic features, the hierarchical organization of features, and the mapping between syntactic features and their exponents. Based on grammatical gender in different language pairs, in particular the heritage language American Norwegian (AmNo), we illustrate how this distributed model can account for developments in heritage language grammars whereby the grammatical gender system is considered to have become less complex. More generally, the article demonstrates that a distributed architecture is better suited empirically and theoretically as a heuristic to understand complexity effects in heritage grammars and beyond.
Heritage Language Variation and Change – How Complex Is It?
Authors: Nagy Naomi , Gadanidis Timothy
Published: November 2021

We focus on complexity from the comparative variationist perspective, a sociolinguistic approach that examines variable aspects of language (that is, different ways of saying the same thing). Arguably, variable elements are harder to acquire than categorical ones, as a Variability Matrix must be acquired along with every element. This matrix contains probabilistic information about when each form is (more) appropriate, according to an array of factors. These include inter-speaker (social) and intra-speaker (linguistic context) predictors. We ask how the Variability Matrix for predictors of a variable compares between heritage speakers (people living in a context where their language is a minority language) and homeland speakers (people living in a context where their language is a majority language), and how these can fairly be compared.

In the variationist approach, multivariate regression analyses reveal the predictors (and levels within each predictor) of a response or dependent variable and their corresponding Variability Matrices. However, the variationist field lacks an established comparative methodology to determine how/if varieties differ. One shortcoming is that different-sized samples are often compared, implicating different levels of statistical significance even when the populations’ patterns are identical.

Comparison of variable patterns in Heritage and Homeland Cantonese illustrates one solution. We revise analyses conducted previously of two morphosyntactic variables: prodrop and classifiers (Nagy, 2015; Nagy & Lo, 2019) in Cantonese, applying a bootstrap procedure to mitigate issues associated with unequal-sized datasets frequent in studies of minority and endangered varieties.

From these analyses, we learn that heritage and homeland grammars’ degrees of complexity are similar: the matrices of (significant) frequencies are the same size. This approach allows us to consider not just which surface forms constitute the heritage vs. homeland varieties, but also the complexity of the decision-making process the speakers apply in selecting among the forms. As one might expect, heritage and homeland speakers are capable of equally complex processes.
Phonological Complexity: Bernese Swiss German in Ohio and Misiones
Authors: Klosinski Robert , Hoffman Andrew D.
Published: November 2021

This article investigates the notion of complexity as it applies to two phonological characteristics of Heritage Bernese Swiss German, namely /l/-vocalization and /nd/-velarization. We survey literature on the role of complexity in language change generally, as well as how it applies to heritage languages specifically. We then present findings from our study of two groups of Heritage Bernese speakers, one in the United States and one in Argentina, with additional reference to the local contact languages. Our findings suggest that the loss of /nd/-velarization in Misiones, Argentina is most likely the result of an internally-driven reduction of complexity. For both the Ohio and Misiones communities, however, /l/-vocalization has been maintained. We conclude by discussing the importance of research into language dyads beyond those in the United States as well as pursuing research on lesser-studied heritage languages.
The Problematic Sales of the Spanish Ortelius Atlas after 1612
Authors: Imhof Dirk
Published: November 2021

In 1612, Balthasar I and Jan Moretus II, managers of the Antwerp Plantin Press, were able to buy the copperplates and the stock of Ortelius’s atlas in various languages at the auction of Jan Baptist Vrients’s possessions. The two brothers endeavored to sell what they purchased through various means and sold the copies as if they were new editions.

In this article I trace the sale of Ortelius’s Spanish atlas in detail from 1612 to 1641. After an examination of the initial period of occasional sales between 1612 and 1630, I will turn to the unexpected confiscation of some copies of the atlas in Spain in 1630. I will conclude by demystifying the so-called 1641 edition. In this way, the distribution of Ortelius’s Spanish atlas in the first half of the seventeenth century will offer a remarkable overview of the afterlife of this once influential work.
Variarum Scripturarum Exempla, Willem Silvius’ Writing-Book Discovered
Authors: Vandommele Jeroen J. M.
Published: November 2021

This article attributes a manuscript in the collection of the KB, the National Library of the Netherlands, to Willem Silvius (c. 1520–1580), an Antwerp printer and a former writing master. The manuscript carries the title Variarum Scripturarum Exempla and contains 44 writing samples in eight different languages. It probably served as Silvius’ personal writing-book, which he used to attract customers when he was working as a writing master in Louvain. In 1562 he intended to publish the manuscript as the first printed exemplar-book in the Low Countries which contained writing models for different languages and settings. Although this publication never materialised, Silvius’ writing-book is a testimonial for the life and the achievements of one of most significant printers of sixteenth century Antwerp.
Return Sponsorships in the EU’s New Pact on Migration and Asylum: High Stakes, Low Gains
Authors: Sundberg Diez Olivia , Trauner Florian , De Somer Marie
Published: November 2021

The concept of ‘return sponsorships’ is central to the European Commission’s New Pact on Migration and Asylum, and its ambition to deliver a “fresh start on migration”. Enabling a system of mandatory yet flexible solidarity, the concept is designed to overcome the opposing viewpoints that have long marked political discussions over responsibility-sharing within Europe. This article critically considers whether return sponsorships can work in practice. It identifies three challenges. First, the proposal’s envisioned solidarity measures lack predictability and tangibility. Second, return sponsorships will create new vulnerabilities for those issued return orders. Third, the mechanism is informed by the improbable assumption that more conditionalities vis-à-vis third countries will substantially increase the EU’s return rate. Overall, the Commission is taking a considerable risk. The return sponsorship concept will likely prolong the polarised discussions among Member States and provide only modest support to countries at the EU’s external border.
Border Walls, Pushbacks, and the Prohibition of Collective Expulsions: The Case of N.D. and N.T. v. Spain
Authors: Sardo Alessio
Published: November 2021

This essay explores the impact of N.D. and N.T. v. Spain on the ECHR system. The case deals with the immediate return of aliens at Melilla’s border fence. Based on conceptual analysis, the author submits to critical scrutiny the arguments developed by the ECtHR. The Court’s reasoning is framed within the riveting interdisciplinary debate on external border control. The Grand Chamber’s final decision reduces the scope of the protection offered by Article 4 Protocol 4, for it introduces a highly indeterminate exception to the prohibition of summary returns at the border. The author suggests that this solution might favor non-entrée strategies and promote the current trend of externalizing the asylum procedures. Introducing broad exceptions to the prohibition of collective expulsion, especially if coupled with strong presumptions in favor of States, increases the effectiveness of border walls qua accountability waivers.