bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative diagnostic accuracy of immunoprecipitation versus immunoassay methods for detecting Aspergillus fumigatus‐specific IgG in allergic bronchopulmonary aspergillosis: A systematic review and meta‐analysis
Authors: Sehgal Inderpaul Singh , Dhooria Sahajal , Prasad Kuruswamy Thurai , Muthu Valliappan , Aggarwal Ashutosh Nath , Agarwal Ritesh
Published: June 2022

Background

The diagnostic accuracy of immunoassays versus immunoprecipitation methods for detecting A.fumigatus‐specific IgG in patients with allergic bronchopulmonary aspergillosis (ABPA) complicating asthma remains unclear.

Methods

We performed a systematic review to identify studies describing both the methods in the same ABPA subjects. We assessed study quality using the QUADAS‐2 tool. We derived the relative sensitivity and specificity using the HSROC meta‐regression model. We calculated the number‐needed‐to‐test using an immunoassay to detect one additional positive test in ABPA.

Results

Our search yielded 20 studies (796 ABPA and 929 controls). The studies had a high risk of bias. The summary estimates for sensitivity and specificity of immunoprecipitation methods were 68.6% (95% CI, 48.4–83.5) and 93.8% (95% CI, 83.6–97.8), respectively, while for immunoassays they were 85.2% (95% CI, 73.3–92.3) and 84.6% (95% CI, 76.0–90.5), respectively. The relative sensitivity and specificity of immunoassays compared to immunoprecipitation tests were 1.29 (95% CI, 1.1–1.6) and 0.91 (95% CI, 0.85–0.97), respectively. The automated immunoassays (1.77; 95% CI, 1.1–2.8) had better relative sensitivity than the manual (1.1; 95% CI, 1.02–1.18) assays compared to immunoprecipitation. The relative specificity of manual immunoassays (0.95; 95% CI, 0.91–0.99) was significantly lower, while that of automated (0.88; 95% CI, 0.77–1.0) assays was lower but not statistically different. One additional positive result was detected for every six (95% CI, 5–7) tests performed with immunoassay (versus immunoprecipitation).

Conclusion

Compared to immunoprecipiation methods, automated immunoassays have higher sensitivity and similar specificity, manual immunoassays have higher sensitivity and lower specificity, while automated immunoassays have higher sensitivity and similar specificity for detecting A.fumigatus‐IgG in patients with ABPA. [www.crd.york.ac.uk/prospero/display_record.php?RecordID=309864].
Reclaiming A. D. Gordon's deep eco‐nationalism
Authors: Shamis Asaf
Published: June 2022

This study seeks to add to the burgeoning literature on the relations between nationalism and environmentalism by examining the ideas of A. D. Gordon (1856–1922). Gordon is not well‐known outside the realm of Zionist scholarship. Nonetheless, a close re‐examination of his ideas reveals that Gordon offers a hybrid brand of deep eco‐national theory that frames traditional deep ecological themes within a general theory of nationalism. Whereas Gordon's theory introduces the ‘nation’ as a central notion to deep ecology thought, at the same time, it adds an ecological dimension rarely taken into account in theories of nationalism. This analysis further shows that although Gordon's pioneering eco‐national theory had high potential for bridging between the two disciplines, it eventually faded into obscurity like eco‐national ideas elsewhere. As Jewish national independence came into view, Gordon's distinctive eco‐nationalism was overshadowed by anthropocentric‐based Zionist politics.
Foreign firm characteristics, labour market restrictions and FDI spillovers: Evidence from Moldova
Authors: Tan Shawn W. , Tusha Dea
Published: June 2022

This paper investigates how productivity spillovers from foreign to domestic firms are affected by foreign firm characteristics and labour market conditions in Moldova. We use firm‐level administrative panel data and annual survey region‐sector indicators of labour market conditions in 2005–2014. Baseline regressions show that domestic firms benefit from backward FDI spillovers, while we find no evidence of horizontal or forward spillovers. Spillover effects are heterogeneous and depend on the ownership structure and age of foreign firms. Domestic firms in upstream sectors benefit from both wholly foreign‐owned companies (WFOC) and joint ventures (JV). However, JVs need less time in the market for positive spillovers to materialise, while WFOCs only lead to larger spillover effects when they are older. In regions and sectors where firms experience fewer labour market restrictions, backward FDI spillovers are larger. Interacting foreign firm characteristics with labour market restrictions, we find that spillovers through the labour market channel materialise only for older FDI, regardless of ownership type. The results are in line with our expectation that WFOCs need more time than JVs to develop linkages with local suppliers and lead to spillovers through this channel. Moreover, in developing countries labour market restrictions reduce labour mobility and consequently, the size of FDI spillovers across industries.
A Newly Identified Group of P-like (PL) Fimbria Genes from Extraintestinal Pathogenic Escherichia coli (ExPEC) Encode Distinct Adhesin Subunits and Mediate Adherence to Host Cells
Authors: Habouria Hajer , Bessaiah Hicham , Pokharel Pravil , Dhakal Sabin , Maris Ségolène , Buron Julie , Houle Sébastien , Dozois Charles M.
Published: June 2022

Fimbriae are important colonization factors in many bacterial species. The identification of a new type of fimbriae encoded on some IncF plasmids in
E. coli
was investigated.
T Cell-Intrinsic Interleukin 17 Receptor A Signaling Supports the Establishment of Chronic Murine Gammaherpesvirus 68 Infection
Authors: Jondle C. N. , Tarakanova V. L.
Published: June 2022

Gammaherpesviruses, such as human EBV, establish lifelong infection in >95% of adults and are associated with B cell lymphomas. Gammaherpesviruses usurp the germinal center response to establish latent infection, and the germinal center B cells are thought to be the target of viral transformation.
Microhabitat Governs the Microbiota of the Pinewood Nematode and Its Vector Beetle: Implication for the Prevalence of Pine Wilt Disease
Authors: Tian Haokai , Zhao Lilin , Koski Tuuli-Marjaana , Sun Jianghua
Published: June 2022

Our understanding of animal microbiota acquisition and dispersal-mediated variation has rapidly increased. In this study, using the model of host pine-pinewood nematode-vector beetle (
Monochamus
sp.) complex, we disentangled the routes of microbial community assembly and transmission mechanisms among these different participants responsible for highly destructive pine wilt disease.
In Vitro
Activity of Cefiderocol against Extensively Drug-Resistant Pseudomonas aeruginosa: CANWARD, 2007 to 2019
Authors: Karlowsky James A. , Walkty Andrew J. , Baxter Melanie R. , Adam Heather J. , Lagacé-Wiens Philippe R. S. , Schweizer Frank , Bay Denice , Lynch Joseph P. , Mulvey Michael R. , Zhanel George G.
Published: June 2022

After testing cefiderocol against a large collection of clinical isolates of highly antimicrobial-resistant
Pseudomonas aeruginosa
, we report that cefiderocol is active versus 97.4% of extensively drug-resistant (XDR) and 97.9% of multidrug-resistant (MDR) (
n
 = 771) isolates. These data show that cefiderocol may be a treatment option for infections caused by MDR and XDR
P. aeruginosa
.
Self-Examination Low-Cost Full-Field Optical Coherence Tomography (SELFF-OCT) for neovascular age-related macular degeneration: a cross-sectional diagnostic accuracy study
Authors: von der Burchard Claus , Sudkamp Helge , Tode Jan , Ehlken Cristoph , Purtskhvanidze Konstantine , Moltmann Moritz , Heimes Britta , Koch Peter , Münst Michael , vom Endt Malte , Kepp Timo , Theisen-Kunde Dirk , König Inke , Hüttmann Gereon , Roider Johann
Published: June 2022

Objectives

Self-Examination Low-Cost Full-Field Optical Coherence Tomography (SELFF-OCT) is a novel OCT technology that was specifically designed for home monitoring of neovascular age-related macular degeneration (AMD). First clinical findings have been reported before. This trial investigates an improved prototype for patients with AMD and focusses on device operability and diagnostic accuracy compared with established spectral-domain OCT (SD-OCT).

Design

Prospective single-arm diagnostic accuracy study.

Setting

Tertiary care centre (University Eye Clinic).

Participants

46 patients with age-related macular degeneration.

Interventions

Patients received short training in device handling and then performed multiple self-scans with the SELFF-OCT according to a predefined protocol. Additionally, all eyes were examined with standard SD-OCT, performed by medical personnel. All images were graded by at least 2 masked investigators in a reading centre.

Primary outcome measure

Rate of successful self-measurements.

Secondary outcome measures

Sensitivity and specificity of SELFF-OCT versus SD-OCT for different biomarkers and necessity for antivascular endothelial growth factor (anti-VEGF) treatment.

Results

In 86% of all examined eyes, OCT self-acquisition resulted in interpretable retinal OCT volume scans. In these patients, the sensitivity for detection of anti-VEGF treatment necessity was 0.94 (95% CI 0.79 to 0.99) and specificity 0.95 (95% CI 0.82 to 0.99).

Conclusions

SELFF-OCT was used successfully for retinal self-examination in most patients, and it could become a valuable tool for retinal home monitoring in the future. Improvements are in progress to reduce device size and to improve handling, image quality and success rates.

Trial registration number

DRKS00013755, CIV-17-12-022384.
What happens when you stop using the combined contraceptive pill? A qualitative study protocol on consequences and supply needs for women who discontinued the combined contraceptive pill in Germany
Authors: Niemann Jana , Schenk Liane , Stadler Gertraud , Richter Matthias
Published: June 2022

Introduction

For more than 60 years, contraceptive pills have been prescribed to mostly healthy biological women. An emerging body of research concerning the possible physiological and psychological side effects of hormonal contraception has been published over the past two decades. Consequently, discontinuing combined oral contraceptives (COCs) as a conscious decision for reasons other than desired pregnancy has become increasingly common for menstruating individuals. The question remains as to what physical and psychological consequences can be observed after discontinuing COCs. In addition, the consequent healthcare needs and situations of affected individuals in Germany have not been explored. This study aims to gain greater insight into the relationship between discontinuation of COCs and (1) possible health consequences, and (2) to explore the supply situation for affected women within the German healthcare system.

Methods and analysis

Qualitative episodic interviews with women who discontinue COC therapy will explore possible health consequences, and their current healthcare needs and situations in Germany. The interviews will be transcribed verbatim, coded, and in-depth thematic interpretation will be conducted. Subsequently, expert interviews with health professionals who work with women who discontinue COCs will also be conducted. The expert interviews will be analysed according to the documentary method. Overarching themes will represent the perspectives of women and health professionals on the discontinuation of COCs.

Ethics and dissemination

Ethical approval for this study has been granted by the Ethics Review Committee of Martin Luther University, Halle-Wittenberg (Germany), reference number 2021-34. The findings will be disseminated via peer-reviewed publications, posting via social media and presentations at conferences. This study is registered on the OSF platform under the following number: https://doi.org/10.17605/OSF.IO/JYWXM.
EOS: a software for flavor physics phenomenology
Authors: van Dyk D. , Beaujean F. , Blake T. , Bobeth C. , Bordone M. , Dugic K. , Eberhard E. , Gubernari N. , Graverini E. , Jung M. , Kokulu A. , Kürten S. , Leljak D. , Lüghausen P. , Meiser S. , Rahimi M. , Reboud M. , Coutinho R. Silva , Virto J. , Vos K. K. ,   The EOS Authors
Published: June 2022

is an open-source software for a variety of computational tasks in flavor physics. Its use cases include theory predictions within and beyond the Standard Model of particle physics, Bayesian inference of theory parameters from experimental and theoretical likelihoods, and simulation of pseudo events for a number of signal processes. ensures high-performance computations through a back-end and ease of usability through a front-end. To achieve this flexibility, enables the user to select from a variety of implementations of the relevant decay processes and hadronic matrix elements at run time. In this article, we describe the general structure of the software framework and provide basic examples. Further details and in-depth interactive examples are provided as part of the online documentation.
Imaging elliptically polarized infrared near-fields on nanoparticles by strong-field dissociation of functional surface groups
Authors: Rosenberger Philipp , Dagar Ritika , Zhang Wenbin , Sousa-Castillo Ana , Neuhaus Marcel , Cortes Emiliano , Maier Stefan A. , Costa-Vera Cesar , Kling Matthias F. , Bergues Boris
Published: June 2022

We investigate the strong-field ion emission from the surface of isolated silica nanoparticles aerosolized from an alcoholic solution, and demonstrate the applicability of the recently reported near-field imaging at 720 nm [Rupp et al., Nat. Comm., 10(1):4655, 2019] to longer wavelength (2 $$\mu $$
μ
m) and polarizations with arbitrary ellipticity. Based on the experimental observations, we discuss the validity of a previously introduced semi-classical model, which is based on near-field driven charge generation by a Monte-Carlo approach and classical propagation. We furthermore clarify the role of the solvent in the surface composition of the nanoparticles in the interaction region. We find that upon injection of the nanoparticles into the vacuum, the alcoholic solvent evaporates on millisecond time scales, and that the generated ions originate predominantly from covalent bonds with the silica surface rather than from physisorbed solvent molecules. These findings have important implications for the development of future theoretical models of the strong-field ion emission from silica nanoparticles, and the application of near-field imaging and reaction dynamics of functional groups on isolated nanoparticles.

Graphical abstract
PeV IceCube signals and $$H_0$$ tension in the framework of Non-Local Gravity
Authors: Capozziello Salvatore , Lambiase Gaetano
Published: June 2022

We study possible effects of non-local gravity corrections on the recent discovery by the IceCube collaboration, reporting high-energy neutrino flux detected at energies of order PeV. Considering the 4-dimensional operator $$\sim y_{\alpha \chi }\overline{{L_{{\alpha }}}}\, H\, \chi$$

∼

y

α
χ

L
α

¯

H

χ

, it is possible to explain both the IceCube neutrino rate and the abundance of Dark Matter, provided that non-local corrections are present in the cosmological background. Furthermore, the mechanism could constitute a natural way to address the $$H_0$$

H
0

tension issue.
Independent quality assessment of a commercial quantum random number generator
Authors: Petrov Mikhail , Radchenko Igor , Steiger Damian , Renner Renato , Troyer Matthias , Makarov Vadim
Published: June 2022

We reverse-engineer, test and analyse hardware and firmware of the commercial quantum-optical random number generator Quantis from ID Quantique. We show that $>99\%$
>
99
%
of its output data originates in physically random processes: random timing of photon absorption in a semiconductor material, and random growth of avalanche owing to impact ionisation. Under a strong assumption that these processes correspond to a measurement of an initially pure state of the components, our analysis implies the unpredictability of the generated randomness. We have also found minor non-random contributions from imperfections in detector electronics and an internal processing algorithm, specific to this particular device. Our work shows that the design quality of a commercial quantum-optical randomness source can be verified without cooperation of the manufacturer and without access to the engineering documentation.
iRNA5hmC-HOC: High-order correlation information for identifying RNA 5-hydroxymethylcytosine modification
Authors: Zou Hongliang
Published: June 2022

RNA 5-hydroxymethylcytosine (5 hmC) is an important RNA modification, which plays vital role in several biological processes. Currently, it is a hot topic to identify 5 hmC sites due to its benefit in understanding its biological functions. Therefore, in this study, we developed a predictor called iRNA5 hmC-HOC, which is based on a high-order correlation information method to identify 5 hmC sites. To build the model, 22 different classes of dinucleotide physicochemical (PC) properties were employed to represent RNA sequences, and the least absolute shrinkage and selection operator (LASSO) algorithm was adopted to select the most discriminative features. In the jackknife test, the proposed method achieved 89.80% classification accuracy based on support vector machine (SVM). As compared with the state-of-the-art predictors, our proposed method has significant improvement on the classification performance. It indicates that the proposed method might be a promising tool in identifying RNA 5 hmC modification sites. The dataset and source codes are available at https://figshare.com/articles/online_resource/iRNA5hmC-HOC/15177450 .
DEVELOPING VALUES-BASED INNOVATION COMPETENCES: AN ECOSYSTEMIC APPROACH
Authors: FACCIN KADÍGIA , BITTENCOURT BRUNO ANICET , MACHADO LISIANE
Published: June 2022

This paper explores how competences are developed for values-based innovation. We conduct action research to develop a values-based network–an ecosystemic project; we propose a Values-Based Innovation Competence Model (VBIC). Based on values-based innovation, innovation pedagogy and activity theory, the model presents the process of developing competences based on a system of activities with prerequisites, triggering factors and an expansive learning cycle. We discovered three additional competences that lead to the development of a values network: sensemaking, forecasting, and the meta-competence of orchestration. We also found that competences develop over time, with a hierarchical relationship between them. This model aims to help universities educate their students and organisations to facilitate values-based innovation.
A CNN Hardware Accelerator Using Triangle-based Convolution
Authors: Thomas K Amal , Poddar Soumyajit , Mondal Hemanta Kumar
Published: June 2022

Convolutional neural networks (CNNs) have gained a massive impression in the fields of computer vision and especially in the embedded applications because of their high accuracy and performance. However, high computational complexity and power consumption due to convolution operations causes a high demand for low-power accelerators. A 3D geometric optimization strategy is proposed to alleviate the area and power requirements of Multiply Accumulate operations prevalent in all spatial CNNs. The proposed technique is generic and may be easily scaled for accelerators performing spatial 2D convolution.
Nonvolatile Memristive Devices Based on In Situ Functionalized Layered rGO-MoS2 Nanocomposites
Authors: Sekhar Das Nipom , Mitra Saikat , Chowdhury Avijit , Roy Asim
Published: June 2022

Hybrid composites comprised of layered two-dimensional (2D) materials have attracted growing attention, especially in large-area electronics. Herein, we exploit the synergistic interfacial effect of molybdenum disulfide (MoS2) grafted reduced graphene oxide (rGO) and study the memristive characteristics of the layered hybrid rGO-MoS2 nanocomposites (NCs). The synthesized materials are analyzed using optical, structural, elemental, and morphological techniques. The average number of layers (∼6 to 10) is estimated from the intense X-ray diffraction peak of the polycrystalline materials. The intercalation of rGO in the rGO-MoS2 NCs results in an increased energy bandgap compared to pristine MoS2. The photoluminescence study exhibits dominant blue emission due to the restoration of the sp2-hybridized carbon domain in the reduced sheets. The surface topography of the NCs shows a 3D flower-like structure with multiple nano-petals interconnected in the form of nanosheets. The average diameter of the flower-shaped particles is calculated to be ∼258 and ∼301 nm for MoS2 and rGO-MoS2, respectively. The crossbar devices (ITO/rGO-MoS2/Cu) in a sandwich configuration (thickness ∼700 nm) are fabricated, displaying stable and repeatable bipolar resistive switching characteristics. The trapping and de-trapping of the charge carriers at the rich sulfur vacancies are responsible for bipolar memory behavior.
Student performance and perceptions of anatomy and physiology across face-to-face, hybrid, and online teaching lab styles
Authors: Pollock Nicholas B.
Published: June 2022

Demand for health professionals increased the demand for A&P courses and led to a transition to hybrid-style labs. There is a general lack of research investigating advantages/disadvantages across hybrid, online, and face-to-face styles. I found that the hybrid style had many of the advantages of online and face-to-face styles yet very few disadvantages. Hybrid lab students reported better experiences and greater satisfaction and outperformed online lab students. Face-to-face lab students, however, outperformed hybrid lab students.
Oscillators in the microvasculature: glycocalyx and beyond
Authors: Goligorsky Michael S.
Published: June 2022

The growing recognition of abundance of oscillating functions in biological systems has motivated this brief overview, which narrows down on the microvasculature. Specifically, it encompasses self-sustained oscillations of blood flow, hematocrit, and viscosity at bifurcations; blood flow effects on the oscillations of endothelial glycocalyx, mechanotransduction, and its termination to prime endothelial cells for the subsequent mechanical signaling event; oscillating affinity of hyaluronan-CD44 binding domain; spontaneous contractility of actomyosin complexes in the cortical actin web and its effects on the tension of the plasma membrane; reversible effects of sirtuin-1 on endothelial glycocalyx; and effects of plasma membrane tension on endo- and exocytosis. Some potential interactions between those oscillators, and their coupling, are discussed together with their transition into chaotic movements. Future in-depth understanding of the oscillatory activities in the microvasculature could serve as a guide to its chronotherapy under pathological conditions.
Molecular mechanisms of hepatic dysfunction in sickle cell disease: lessons from Townes mouse model
Authors: Pradhan-Sundd Tirthadipa , Kato Gregory J. , Novelli Enrico M.
Published: June 2022

Sickle cell disease (SCD) is an autosomal recessive genetic disorder that affects ∼100,000 Americans and millions of people worldwide. Erythrocyte sickling, vaso-occlusion, sterile inflammation, and hemolysis are the major pathophysiological pathways leading to liver injury in SCD. Although hepatic dysfunction affects up to 10%–40% of patients with SCD, therapeutic approaches to prevent liver injury in SCD are not known, and the molecular mechanisms promoting progressive liver injury in SCD remain poorly understood. Animal models have been beneficial in bridging the gap between preclinical and translational research in SCD. Recent advances in methodology have allowed the development of several humanized animal models to address various aspects of SCD-related liver diseases. This review provides an overview of current knowledge of the molecular mechanisms and potential therapeutic options of SCD-associated liver dysfunction using the Townes mouse model.
Excavating proteoglycan structure-function relationships: modern approaches to capture the interactions of ancient biomolecules
Authors: Critcher Meg , Huang Mia L.
Published: June 2022

Proteoglycans are now well regarded as key facilitators of cell biology. Although a majority of their interactions and functions are attributed to the decorating glycosaminoglycan chains, there is a growing appreciation for the roles of the proteoglycan core protein and for considering proteoglycans as replete protein-glycan conjugates. This appreciation, seeded by early work in proteoglycan biology, is now being advanced and exalted by modern approaches in chemical glycobiology. In this review, we discuss up-and-coming methods to unearth the fine-scale architecture of proteoglycans that modulate their functions and interactions. Crucial to these efforts is the production of chemically defined materials, including semisynthetic proteoglycans and the in situ capture of interacting proteins. Together, the integration of chemical biology approaches promises to expedite the dissection of the structural heterogeneity of proteoglycans and deliver refined insight into their functions.
Performance fatigability and recovery after dynamic multi-joint maximal exercise in elbow flexors versus knee extensors
Authors: Colosio Marta , Rasica Letizia , Baldassarre Giovanni , Temesi John , Vernillo Gianluca , Marzorati Mauro , Porcelli Simone
Published: June 2022

Elbow flexors (EFs) and knee extensors (KEs) have shown differences in performance fatigability and recovery of neuromuscular function after isometric and isotonic single-joint fatiguing contractions. However, dynamic multi-joint movements are more representative of real-world activities. The aim of the study was to assess central and peripheral mechanisms of fatigability after either arm-cranking or cycling. Ten physically active men performed maximal incremental arm-cranking and cycling until task failure. Maximal voluntary isometric contraction (MVIC) and electrically evoked forces of both EF and KE were assessed before (PRE) and 1 (POST) and 20 (POST20) min after exercise. At POST, MVIC decreased similarly to 76 ± 8% and 81 ± 7% (both P < 0.001) of PRE for EF and KE, respectively. MVIC force remained lower than PRE at POST20 for both EF and KE (85 ± 8% vs. 95 ± 3% of PRE, P ≤ 0.033), having recovered less in EF than in KE ( P = 0.003). Electrically evoked forces decreased similarly from PRE to POST in EF and KE (all P > 0.05). At POST20, the ratio of low-to-high frequency doublets was lower in EF than in KE (75 ± 13% vs. 85 ± 10% of PRE; P ≤ 0.034). Dynamic maximal incremental exercise acutely induced similar magnitudes of MVIC and evoked force loss in EF and KE. However, at POST20, impaired MVIC recovery and lower ratio of low-to-high frequency doublets in EF than in KE suggest the recovery of neuromuscular function after dynamic maximal exercises is specific to and dependent on changes within the muscles investigated.
Vanishing Poynting Observers and Electromagnetic Field Classification in Kerr and Kerr-Newman Spacetimes
Authors: Vargas–Rodríguez H. , Rosu H. C. , Medina–Guevara M. G. , Gallegos A. , Muñiz–Torres M. A.
Published: June 2022

We consider electromagnetic fields having an angular momentum density in a locally nonrotating reference frame in Schwarzschild, Kerr, and Kerr-Newman spacetimes. The nature of such fields is assessed with two families of observers, the locally nonrotating ones and those of vanishing Poynting flux. The velocity fields of the vanishing-Poynting observers in the locally nonrotating reference frames are determined using the

3
+
1

decomposition formalism. From a methodological point of view and considering a classification of the electromagnetic field based on its invariants, it is convenient to separate the consideration of the vanishing-Poynting observers into two cases corresponding to the pure and nonpure fields; additionally, if there are regions where the field rotates with the speed of light (light surfaces), it becomes necessary to split these observers into two subfamilies. We present several examples of relevance in astrophysics and general relativity, such as pure rotating dipolar-like magnetic fields and the electromagnetic field of the Kerr-Newman solution. For the latter example, we see that vanishing-Poynting observers also measure a vanishing super-Poynting vector, confirming recent results in the literature. Finally, for all nonnull electromagnetic fields, we present the 4-velocity fields of vanishing Poynting observers in an arbitrary spacetime.
Identification of the Pathogens and Laboratory Bioactivity Determination of the Rot Disease of Kiwifruit (Actinidia spp.)
Authors: Ren Yanling , Wang Tao , Tang Jian , Jiang Yingjie , Huang Yaxin , Zhang Chengping , Peng Jing , Wang Juan , Wang Shanshan , Wang Jing
Published: June 2022

Kiwifruit is an important economic crop in the world today with a high nutritional value. It can cause huge damage by causing kiwifruit rot disease; however, at present, the control methods for this disease are limited. In this study, the rotten fruits of kiwifruit (Cultivar “Jinyan”) were collected from Pujiang city (Sichuan province), Xixia city, (Henan province), Zhouzhi (Shaanxi province), Meixian city (Shaanxi province), and Bijie (Guizhou province), China, and the pathogenic fungi were identified by isolation and purification, pathogenicity test, morphological characteristics, and analysis of ribosomal DNA internal transcribed spacer (rDNA-ITS) sequences. The results showed that the pathogenic fungi of kiwifruit rot disease were Botryosphaeria dothidea and Dothiorella gregaria. Meanwhile, the in vitro antifungal activity of 11 kinds of fungicides and 5 kinds of plant essential oils against B. dothidea and D. gregaria were determined and the results showed that all the tested fungicides and plant essential oils had a certain inhibitory effect on B. dothidea and D. gregaria. Among them, propiconazole had the best inhibitory effect on B. dothidea with an EC50 value of 4.10 mg/L, and quinolinone had the best inhibitory effect on D. gregaria with the EC50 value of 10.05 mg/L. Moreover, the pesticides and essential oils have practical application values for prevention and treatment of fruit rot diseases pathogens.
An Improved Immune Genetic Algorithm for Solving the Flexible Job Shop Scheduling Problem with Batch Processing
Authors: Song Libo , Liu Chang , Shi Haibo , Zhu Jun
Published: June 2022

This paper presents a mathematical model for the flexible job shop scheduling problem (FJSP) with batch processing for manufacturing enterprises with both the flexible job shop scheduling problem and a batch process (BP) problem in actual production. An improved immune genetic algorithm (IGA) based on greedy thought combined with local scheduling rules is used to solve this scheduling problem. In the flexible job shop part, the greedy optimal solution is obtained through the greedy thought. The concept of cross-entropy is then introduced to improve the standard IGA. Calculating the cross-entropy of the individual and greedy optimal solutions for optimization considerably accelerates the optimization speed of the algorithm and enhances the ability of the algorithm to escape the local optimum. In the batching process, effective batching rules are designed to reduce blockage and improve batching efficiency; thus, the job can quickly and effectively pass the batching process and complete the entire production process. In the algorithm verification stage, standard FJSP datasets are used to simulate and verify the proposed algorithm. Considering the specific FJFP with BP problem, we perform simulation experiments with actual production data of a transformer manufacturer. The results show that the proposed method can effectively solve such problems.
A Study of Industrial Convergence in the Context of Digital Economy Based on Scientific Computing Visualization
Authors: Zhou Shiyuan , Yang Xiaoqin , Liao Zhixiong
Published: June 2022

With the rapid development of computer hardware and software and the rapid spread of network, the amount of data in scientific computing has exploded. Big data visualization has become one of the important research contents in scientific computing. Against the background of rapid development of information technology and digital technology, the scale of digital economy is increasing day by day, and China’s digital economy has ushered in unprecedented progress, and it has become an important force in leading economic development. The development of digital economy promotes industrial upgrading and transformation and facilitates industrial integration, and many traditional industries have given rise to a series of new industries. Scientific computational visualization is a new research discipline with a wide range of applications, including energy surveying, natural sciences, finance, and business. However, as a brand-new discipline, further research is needed in areas such as the application of scientific computational visualization techniques based on the digital economy environment. In this study, we propose a scientific computing visualization approach based on a big data framework for industry convergence analysis in the context of digital economy, which consists of a cloud computing platform for industry convergence in the context of digital economy by integrating neural networks in the platform, and scientific computing visualization by built-in GPU hardware. Traditional research methods for scientific computing visualization are discussed, and algorithms and techniques are classified in terms of the types of data domains studied. Finally, the further development and research directions of scientific computing visualization in the big data environment are given in conjunction with the main theoretical and application results achieved by our group in scientific computing for the field of big data visualization. Scientific computing visualization will not only promote the development and application of cutting-edge information technology, like cloud computing, big data, cyber security, artificial intelligence, computational science, system theory, and so on, but also bring a unique and disruptive development and change to the industrial integration in the context of digital economy.
Artificial Intelligence Sponge City Wisdom Management Model
Authors: Nie Dan , Fang Hualiang
Published: June 2022

Sponge city is currently a new urban rain flood management concept. It refers to the natural disaster that adapts to environmental changes and the natural disasters that is brought by rainwater. It is also known as the sponge, and the alias can also be called as “water elastic city.” The purpose of this article is, based on artificial intelligence, to study the analysis of wisdom management models in sponges. This paper first introduces the artificial intelligence algorithm and sponge city, then compares the traditional sponge city and the wisdom sponge city, then creates a LSTM neural network model, introducing artificial intelligence into sponge city intelligent dynamics in the analysis, and finally compares the rainfall data analysis to the ground. The experimental results show that, at different time points, the training results of rainfall data have shown significant regularity. The entire rainfall process exhibits a rise-decline-rise-increase trend of repetition. The maximum rainfall appeared at the 18th hour, and 7 obvious peaks occurred in 7, 11, 14, 16, 18, 21, and 23 hours.
Blockchain-Based Self-Auditing Scheme with Batch Verification for Decentralized Storage
Authors: Yuan Zhonghao , Wu Jiaojiao , Gong Jianpeng , Liu Yao , Tian Guohua , Wang Jianfeng
Published: June 2022

Data owners outsource their data to remote storage providers without keeping local replicas to save their precious storage resources. However, the ownership and management of data are separated after outsourcing. How to ensure the integrity and recoverability of outsourced data becomes a significant problem. Provable Data Possession (PDP) and Proofs of Retrievability (POR) are two cryptographic protocols that enable users to verify the integrity of outsourced data. Nevertheless, the state-of-the-art PDP and POR schemes either need users to perform the complicated audit tasks by themselves or delegate these tasks to a Third-Party Auditor (TPA). Moreover, these schemes are constructed on a centralized storage framework which vulnerably suffers single-point-of-failure. In this paper, we propose a blockchain-based decentralized self-auditing scheme with batch verification. Firstly, data owners outsource their data to decentralized storage nodes, which can achieve self-auditing based on blockchain without TPA. Secondly, our scheme uses Pedersen-based polynomial commitment to significantly reduce the number of authenticators. Furthermore, we propose a batch verification algorithm, which can verify multiple proofs from different storage nodes to improve the verification efficiency. Finally, we analyze the security of our scheme and implement a gas-efficient system prototype using the smart contracts of the Ethereum Reposten test network. The results demonstrate that the scheme is practical.
Characteristic Differences between Novices and Experts in Different Shooting Stages
Authors: Shao Shuyu , Zhang Shike , Zhang Liwei
Published: June 2022

Attention is the most important psychological factor affecting shooting performance. The wavelet packet energy analysis method was used to explore the differences in EEG characteristics and brain activity between experts and novices while aiming and shooting in real shooting environments. Results show that the frontal and occipital regions of novices were more active when they were aiming, while the frontal, central, and occipital regions of experts were more active when they were shooting. Overall, the frontal, central, and occipital regions of novices were more active (p < 0.05), whereas for experts, it was the frontal, central, parietal, and occipital regions that were more active (p < 0.05). Brain activity was mainly concentrated in the left hemisphere of the brain for experts, indicating that they began to take action when aiming and had higher neural efficiency. This study can help the selection and training of personnel for typical tasks that require attention by monitoring and analyzing the EEG signals of operators of different skill levels.
Construction of a Landscape Design and Greenery Maintenance Scheduling System Based on Multimodal Intelligent Computing and Deep Neural Networks
Authors: Ji Mingfei , Lu Jianrong , Zhang Xiaowei
Published: June 2022

Digitalization brings challenges and new opportunities to the development of landscape gardening, “smart gardening,” which is a product of landscape gardening in response to the development of the digital era. Based on the multimodal intelligent computing method and deep neural network machine learning algorithm, this paper adopts “digital landscape design logic” to analyze and research smart gardens and digital design. The digital landscape design process and methods are discussed based on design logic, design basis, environment analysis, and results presentation, and the greenery maintenance scheduling system is constructed. The paper focuses on the digital implementation of the environmental analysis of the site and uses Rhino software and Grasshopper visual programming language to build parametric logic, establish parametric analysis models, and conduct a comprehensive analysis of the current environment. The main theme of the whole paper is a logical approach to digital landscape design for smart gardens, using digital technology tools from the perspective of smart garden thinking, combining quantitative analysis and qualitative design, and intervening in digital landscape garden planning and design to explore the application of digital technology and tools.
Modified Xiaochaihu Decoction Combined with Mirtazapine in the Treatment of Persistent Depression: A Pilot Randomized Controlled Trial
Authors: Li Xin , Li Xiuyu , Gong Man , Li Chaoqun , Li Jing , Zhou Chao , He Tingting
Published: June 2022

Background. Western drugs effectively manage persistent depressive disorder (PDD) but are associated with side effects. Objective. To observe the efficacy and safety of modified Xiaochaihu Decoction combined with mirtazapine in treating PDD. Methods. Patients with PDD were enrolled at the Naval General Hospital (06/2018–02/2019) and randomized to modified Xiaochaihu Decoction and modified Xiaochaihu Decoction with mirtazapine. The self‐rating depression scale (SDS) and traditional Chinese medicine (TCM) scale were assessed at baseline and after 12 weeks. The overall clinical efficacy (primary outcome) and adverse reactions were observed. Results. Sixty‐four participants completed the trial in the combined and control groups (30 and 28), respectively. In controls, the total effective rate was 78.6%, compared with 96.7% in the combined group (P = 0.035). The scores of the SDS and TCM syndrome scale in the two groups were lower after treatment (P < 0.001) but without difference between groups (P = 0.077). The combined group showed higher improvement rates regarding insomnia (96.4% vs. 44.0%, P < 0.001), bitter taste (90.5% vs. 52.6%, P = 0.007), languid (72.0% vs. 31.8%, P = 0.006), and belching/anorexia (100% vs. 52.6%, P < 0.001). The combined group showed a higher frequency of adverse events (73.3% vs. 3.6%) (P < 0.001). Conclusion. Modified Xiaochaihu Decoction combined with mirtazapine effectively treats PDD, and its curative effect is better than that of TCM alone. Trial Registration. This trial was registered with https://www.chictr.org.cn/index.aspx/ChiCTR2100048188.
A BERT-Based Aspect-Level Sentiment Analysis Algorithm for Cross-Domain Text
Authors: Liu Ning , Zhao Jianhua
Published: June 2022

Cross-domain text sentiment analysis is a text sentiment classification task that uses the existing source domain annotation data to assist the target domain, which can not only reduce the workload of new domain data annotation, but also significantly improve the utilization of source domain annotation resources. In order to effectively achieve the performance of cross-domain text sentiment classification, this paper proposes a BERT-based aspect-level sentiment analysis algorithm for cross-domain text to achieve fine-grained sentiment analysis of cross-domain text. First, the algorithm uses the BERT structure to extract sentence-level and aspect-level representation vectors, extracts local features through an improved convolutional neural network, and combines aspect-level corpus and sentence-level corpus to form a sequence sentence pair. Then, the algorithm uses domain adversarial neural network to make the feature representation extracted from different domains as indistinguishable as possible, that is, the features extracted from the source domain and the target domain have more similarity. Finally, by training the sentiment classifier on the source domain dataset with sentiment labels, it is expected that the classifier can achieve a good sentiment classification effect in both source and target domain, and achieve sentence-level and aspect-level sentiment classification. At the same time, the error pooled values of the sentiment classifier and the domain adversary are passed backwards to realize the update and optimization of the model parameters, thereby training a model with cross-domain analysis capability. Experiments are carried out on the Amazon product review dataset, and accuracy and F1 value are used as evaluation indicators. Compared with other classical algorithms, the experimental results show that the proposed algorithm has better performance.
Boost-Phase Trajectory Planning with the Nonregular Reachable Area Constraints
Authors: Diao Yin , Mu Rongjun , Guan Yingzi , Cui Naigang
Published: June 2022

During emergency return or mission change, the boost-glide vehicle needs to meet the nonregular reachable area constraints (NRACs). Therefore, this paper introduced NRACs into boost-phase trajectory planning to extend the maneuvering range and enhance the mission adaptability of boost-glide vehicle. Firstly, the library of the reachable area boundaries was constructed with the fast computation method under the deviations of boost terminal states, and the polynomials were used to fit the boundary parameters. Secondly, the nonlinear mapping relationship between the reachable area boundary parameters and the deviations of boost terminal states was obtained by the deep neural networks (DNNs). Then, the new boundary parameters were obtained by the constraint transformation rules under NRACs and the separation window constraints and transformed into the constraints of the boost-phase terminal states by DNNs. Finally, the hp-adaptive pseudospectral method (hpPM) was adopted to complete the trajectory planning considering the path and terminal constraints. The simulation results showed that the proposed trajectory planning method considering NRACs had high trajectory planning accuracy and good deviation adaptability and exhibited excellent performance in the adjustment of reachable area. This study provides theoretical support for integrate mission decisions and trajectory planning of boost-glide vehicles.
Experimental Atherosclerosis Research on Large and Small Animal Models in Vascular Surgery
Authors: Simon Florian , Larena-Avellaneda Axel , Wipper Sabine
Published: June 2022

Animal models have significantly advanced our understanding of the mechanisms of atherosclerosis formation and the evaluation of therapeutic options. The current focus of research is on preventive strategies and includes pharmacologic and biologic interventions directed primarily against smooth-muscle cell proliferation, endovascular devices for recanalization and/or drug delivery, and an integrated approach using both devices and pharmacobiologic agents. The experience over many decades with animal models in vascular research has established that a single, ideal, naturally available model for atherosclerosis does not exist. The spectrum ranges from large animals such as pigs to small animal experiments with genetically modified rodents such as the ApoE−/− mouse with correspondingly differently pronounced changes in their lipid and lipoprotein levels. The development of transgenic variants of currently available models, e.g., an ApoE-deficient rabbit line, has widened our options. Nevertheless, an appreciation of the individual features of natural or stimulated disease in each species is of importance for the proper design and execution of relevant experiments.
Clinical Characteristics and Treatment Outcomes of Scleromyxedema: A 10-Year Retrospective Survey
Authors: Ansari Abtin , Erfani Zohre , Daneshpazhooh Maryam , Mahmoudi Leila , Saffarian Zahra , Kamyab Kambiz , Mahmoudi Hamidreza
Published: June 2022

Scleromyxedema is a rare but important mucinosis disorder of the skin that is presented with dermatological manifestations such as waxy papules, diffuse induration, and nondermatologic involvements like neurological and renal disorders. We report a case series of the data regarding the characteristics and treatment of 14 patients diagnosed with scleromyxedema and their follow-up. Patients entered the study based on scleromyxedema diagnosis criteria. Comorbidities were also recorded to evaluate their effect on the treatment process. Clinicopathological and laboratory findings and responses to their treatment were evaluated separately. There was a significant improvement after administering intravenous immunoglobulin (IVIG). Despite the lack of a definite treatment for this condition, the present study shows that the application of IVIG can improve both cutaneous and systemic symptoms. Younger patients, in particular, responded significantly to the use of IVIG. More studies are required to investigate the potential efficacy of IVIG in the treatment of scleromyxedema.