bluuebunny/crossref_metadata_2025 huggingface dataset:
From the Triage to the Intermediate Area: A Simple and Fast Model for COVID-19 in the Emergency Department
Authors: Poggiali Erika , Fabrizi Enrico , Bastoni Davide , Iannicelli Teresa , Galluzzo Claudia , Canini Chiara , Cillis Maria Grazia , Ponzi Davide Giulio , Magnacavallo Andrea , Vercelli Andrea
Published: July 2022

Introduction: The early identification of patients with SARS-CoV-2 infection is still a real challenge for emergency departments (ED). First, we aimed to develop a score, based on the use of the lung ultrasonography (LUS), in addition to the pre-triage interview, to correctly address patients; second, we aimed to prove the usefulness of a three-path organization (COVID-19, not-COVID-19 and intermediate) compared to a two-path organization (COVID-19, non-COVID-19). Methods: We retrospectively analysed 292 patients admitted to our ED from 10 April to 15 April 2020, with a definite diagnosis of positivity (93 COVID-19 patients) or negativity (179 not-COVID-19 patients) for SARS-COV-2 infection. Using a logistic regression, we found a set of predictors for infection selected from the pre-triage interview items and the LUS findings, which contribute with a different weight to the final score. Then, we compared the organization of two different pathways. Results: The most informative factors for classifying the patient are known nasopharyngeal swab positivity, close contact with a COVID-19 patient, fever associated with respiratory symptoms, respiratory failure, anosmia or dysgeusia, and the ultrasound criteria of diffuse alveolar interstitial syndrome, absence of B-lines and presence of pleural effusion. Their sensitivity, specificity, accuracy, and AUC-ROC are, respectively, 0.83, 0.81, 0.82 and 0.81. The most significant difference between the two pathways is the percentage of not-COVID-19 patients assigned to the COVID-19 area, that is, 10.6% (19/179) in the three-path organization, and 18.9% (34/179) in the two-path organization (p = 0.037). Conclusions: Our study suggests the possibility to use a score based on the pre-triage interview and the LUS findings to correctly manage the patients admitted to the ED, and the importance of an intermediate area to limit the spread of SARS-CoV-2 in the ED and, as a consequence, in the hospital.
Dehydrocorydaline Accelerates Cell Proliferation and Extracellular Matrix Synthesis of TNFα-Treated Human Chondrocytes by Targeting Cox2 through JAK1-STAT3 Signaling Pathway
Authors: Sha Yongqiang , Zhang Beibei , Chen Liping , Wang Chunli , Sun Tao
Published: July 2022

Osteoarthritis (OA) causes severe degeneration of the meniscus and cartilage layer in the knee and endangers joint integrity and function. In this study, we utilized tumor necrosis factor α (TNFα) to establish in vitro OA models and analyzed the effects of dehydrocorydaline (DHC) on cell proliferation and extracellular matrix (ECM) synthesis in human chondrocytes with TNFα treatment. We found that TNFα treatment significantly reduced cell proliferation and mRNA and protein expression levels of aggrecan and type II collagen, but caused an increase in mRNA and protein expression levels of type I collagen, matrix metalloproteinase 1/13 (MMP1/13), and prostaglandin-endoperoxide synthase 2 (PTGS2, also known as Cox2) in human chondrocytes. DHC significantly promoted the cell activity of normal human chondrocytes without showing cytotoxity. Moreover, 10 and 20 μM DHC clearly restored cell proliferation, inhibited mRNA and protein expression levels of type I collagen, MMP 1/13, and Cox2, and further increased those of aggrecan and type II collagen in the TNFα-treated human chondrocytes. RNA transcriptome sequencing indicated that DHC could improve TNFα-induced metabolic abnormalities and inflammation reactions and inhibit the expression of TNFα-induced inflammatory factors. Furthermore, we found that the JAK1-STAT3 signaling pathway was confirmed to be involved in the regulatory effects of DHC on cell proliferation and ECM metabolism of the TNFα-treated human chondrocytes. Lastly, to explore the effects of DHC in vivo, we established an anterior cruciate ligament transection (ACLT)-stimulated rat OA model and found that DHC administration significantly attenuated OA development, inhibited the enzymatic hydrolysis of ECM, and reduced phosphorylated JAK1 and STAT3 protein expression in vivo after ACLT for 6 weeks. These results suggest that DHC can effectively relieve OA progression, and it has a potential to be utilized for the clinical prevention and therapy of OA as a natural small molecular drug.
Peptidomic Approaches and Observations in Neurodegenerative Diseases
Authors: Muqaku Besnik , Oeckl Patrick
Published: July 2022

Mass spectrometry (MS), with its immense technological developments over the last two decades, has emerged as an unavoidable technique in analyzing biomolecules such as proteins and peptides. Its multiplexing capability and explorative approach make it a valuable tool for analyzing complex clinical samples concerning biomarker research and investigating pathophysiological mechanisms. Peptides regulate various biological processes, and several of them play a critical role in many disease-related pathological conditions. One important example in neurodegenerative diseases is the accumulation of amyloid-beta peptides (Aβ) in the brain of Alzheimer’s disease (AD) patients. When investigating brain function and brain-related pathologies, such as neurodegenerative diseases, cerebrospinal fluid (CSF) represents the most suitable sample because of its direct contact with the brain. In this review, we evaluate publications applying peptidomics analysis to CSF samples, focusing on neurodegenerative diseases. We describe the methodology of peptidomics analysis and give an overview of the achievements of CSF peptidomics over the years. Finally, publications reporting peptides regulated in AD are discussed.
Optimization of Turbine Blade Aerodynamic Designs Using CFD and Neural Network Models
Authors: Zhang Chao , Janeway Matthew
Published: July 2022

Optimization methods have been widely applied to the aerodynamic design of gas turbine blades. While applying optimization to high-fidelity computational fluid dynamics (CFD) simulations has proven capable of improving engineering design performance, a challenge has been overcoming the prolonged run-time due to the computationally expensive CFD runs. Reduced-order models and, more recently, machine learning methods have been increasingly used in gas turbine studies to predict performance metrics and operational characteristics, model turbulence, and optimize designs. The application of machine learning methods allows for utilizing existing knowledge and datasets from different sources, such as previous experiments, CFD, low-fidelity simulations, 1D or system-level studies. The present study investigates inserting a machine learning model that utilizes such data into a high-fidelity CFD driven optimization process, and hence effectively reduces the number of required evaluations of the CFD model. Artificial Neural Network (ANN) models were trained on data from over three thousand two-dimensional (2D) CFD analyses of turbine blade cross-sections. The trained ANN models were then used as surrogates in a nested optimization process alongside a full three-dimensional Navier–Stokes CFD simulation. The much lower evaluation cost of the ANN model allows for tens of thousands of design evaluations to guide the search of the best blade profiles to be used in the more expensive, high-fidelity CFD runs, improving the progress of the optimization while reducing the required computation time. It is estimated that the current workflow achieves a five-fold reduction in computational time in comparison to an optimization process that is based on three-dimensional (3D) CFD simulations alone. The methodology is demonstrated on the NASA/General Electric Energy Efficient Engine (E3) high pressure turbine blade and found Pareto front designs with improved blade efficiency and power over the baseline. Quantitative analysis of the optimization data reveals that some design parameters in the present study are more influential than others, such as the lean angle and tip scaling factor. Examining the optimized designs also provides insight into the physics, showing that the optimized designs have a lower amount of pressure drop near the trailing edge, but have an earlier onset of pressure drop on the suction side surface when compared to the baseline design, contributing to the observed improvements in efficiency and power.
A Scoring System for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Quantitative Functional MRI
Authors: Liao Chien-Chang , Cheng Yu-Fan , Yu Chun-Yen , Tsang Leung-Chit Leo , Chen Chao-Long , Hsu Hsien-Wen , Chang Wan-Ching , Lim Wei-Xiong , Chuang Yi-Hsuan , Huang Po-Hsun , Ou Hsin-You
Published: July 2022

Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is a histopathological marker and risk factor for HCC recurrence. We integrated diffusion-weighted imaging (DWI) and magnetic resonance (MR) image findings of tumors into a scoring system for predicting MVI. In total, 228 HCC patients with pathologically confirmed MVI who underwent surgical resection or liver transplant between November 2012 and March 2021 were enrolled retrospectively. Patients were divided into a right liver lobe group (n = 173, 75.9%) as the model dataset and a left liver lobe group (n = 55, 24.1%) as the model validation dataset. Multivariate logistic regression identified two-segment involved tumor (Score: 1; OR: 3.14; 95% CI: 1.22 to 8.06; p = 0.017); ADCmin ≤ 0.95 × 10−3 mm2/s (Score: 2; OR: 10.88; 95% CI: 4.61 to 25.68; p = 0.000); and largest single tumor diameter ≥ 3 cm (Score: 1; OR: 5.05; 95% CI: 2.25 to 11.30; p = 0.000), as predictive factors for the scoring model. Among all patients, sensitivity was 89.66%, specificity 58.04%, positive predictive value 68.87%, and negative predictive value 84.41%. For validation of left lobe group, sensitivity was 80.64%, specificity 70.83%, positive predictive value 78.12%, and negative predictive value 73.91%. The scoring model using ADCmin, largest tumor diameter, and two-segment involved tumor provides high sensitivity and negative predictive value in MVI prediction for use in routine functional MR.
The Increasing Incidence of Neuroendocrine Neoplasms Worldwide: Current Knowledge and Open Issues
Authors: Rossi Roberta Elisa , Massironi Sara
Published: July 2022

Neuroendocrine neoplasms (NENs) include a heterogeneous group of tumors derived from neuroendocrine cells, most commonly arising from the gastro-entero-pancreatic (GEP) and bronchopulmonary tracts [...]
Effect of Pneumococcal Vaccine on Mortality and Cardiovascular Outcomes: A Systematic Review and Meta-Analysis
Authors: Jaiswal Vikash , Ang Song Peng , Lnu Kriti , Ishak Angela , Pokhrel Nishan Babu , Chia Jia Ee , Hajra Adrija , Biswas Monodeep , Matetic Andrija , Dhatt Ravinder , Mamas Mamas A.
Published: July 2022

Various studies have suggested the possible cardiovascular (CV) protective effects of the pneumococcal vaccine (PV). Therefore, we conducted a meta-analysis to assess the association between recipients of PV with mortality and CV outcomes among patients with and without established cardiovascular disease. We performed a systematic literature search in PubMed, Embase, and Scopus for studies evaluating the effect of PV on mortality and CV outcomes. A total of 15 studies with 347,444 patients were included in the meta-analysis: 111,784 patients received PV (32%) and 235,660 patients were in the unvaccinated group (68%). Recipients of PV were associated with decreased all-cause mortality (HR, 0.76 (95% CI: 0.66 to 0.87), p < 0.001). PV was associated with a decrease in the incidence of myocardial infarction (MI) (HR, 0.73 (95% CI: 0.56–0.96), p = 0.02), without significant reduction in CV mortality (HR, 0.87 (95% CI: 0.72–1.07), p = 0.18) and stroke (HR, 1.01 (95% CI: 0.93–1.10), p = 0.82). Our study found PV was associated with decreased risk of all-cause mortality and MI. Future RCTs will be necessary to confirm benefits associated with receipt of PV.
A Survey of Radiomics in Precision Diagnosis and Treatment of Adult Gliomas
Authors: Du Peng , Chen Hongyi , Lv Kun , Geng Daoying
Published: July 2022

Glioma is the most common primary malignant tumor of the adult central nervous system (CNS), which mostly shows invasive growth. In most cases, surgery is often difficult to completely remove, and the recurrence rate and mortality of patients are high. With the continuous development of molecular genetics and the great progress of molecular biology technology, more and more molecular biomarkers have been proved to have important guiding significance in the individualized diagnosis, treatment, and prognosis evaluation of glioma. With the updates of the World Health Organization (WHO) classification of tumors of the CNS in 2021, the diagnosis and treatment of glioma has entered the era of precision medicine in the true sense. Due to its ability to non-invasively achieve accurate identification of glioma from other intracranial tumors, and to predict the grade, genotyping, treatment response, and prognosis of glioma, which provides a scientific basis for the clinical application of individualized diagnosis and treatment model of glioma, radiomics has become a research hotspot in the field of precision medicine. This paper reviewed the research related to radiomics of adult gliomas published in recent years and summarized the research proceedings of radiomics in differential diagnosis, preoperative grading and genotyping, treatment and efficacy evaluation, and survival prediction of adult gliomas.
Treatment and Outcomes of Clostridioides difficile Infection in Switzerland: A Two-Center Retrospective Cohort Study
Authors: Filippidis Paraskevas , Kampouri Eleftheria , Woelfle Maximilian , Badinski Tina , Croxatto Antony , Galperine Tatiana , Papadimitriou-Olivgeris Matthaios , Grandbastien Bruno , Achermann Yvonne , Guery Benoit
Published: July 2022

Objectives: Clostridioides difficile infection (CDI) is the leading cause of healthcare-associated diarrhea, often complicated by severe infection and recurrence with increased morbidity and mortality. Data from large cohorts in Switzerland are scarce. We aimed to describe diagnostic assays, treatment, outcomes, and risk factors for CDI in a large cohort of patients in Switzerland. Methods: We conducted a retrospective cohort study of CDI episodes diagnosed in patients from two tertiary care hospitals in Switzerland. During a 3-month follow-up, we used a composite outcome combining clinical cure at day 10, recurrence at week 8, or death, to evaluate a patient’s response. Unfavorable outcomes consisted in the occurrence of any of these events. Results: From January 2014 to December 2018, we included 826 hospitalized patients with documented CDI. Overall, 299 patients (36.2%) had a severe infection. Metronidazole was used in 566 patients (83.7%), compared to 82 patients (12.1%) treated with vancomycin and 28 patients (4.1%) treated with fidaxomicin. Overall mortality at week 8 was at 15.3% (112/733). Eighty-six patients (12.7%) presented with clinical failure at day 10, and 78 (14.9%) presented with recurrence within 8 weeks; 269 (39.8%) met the composite outcome of death, clinical failure, or recurrence. The Charlson Comorbidity Index score (p < 0.001), leukocytes > 15 G/L (p = 0.008), and the use of metronidazole (p = 0.012) or vancomycin (p = 0.049) were factors associated with the composite outcome. Conclusions: Our study provides valuable insights on CDI treatment and outcomes in Switzerland, highlights the heterogeneity in practices among centers, and underlines the need for the active monitoring of clinical practices and their impact on clinical outcomes through large multicentric cohorts.
Vertical Structure and Seasonal Variability of Shear on the Southwestern Continental Slope of the East China Sea
Authors: Ouyang Zhiling , Liu Ze , Hou Yijun
Published: July 2022

The vertical structure and seasonal variability of shear were examined using nearly three years of mooring ADCP (acoustic Doppler current profiler) data on the southwestern continental slope of the East China Sea (ECS). Shear spectra suggest that the sub-inertial currents (SICs); near-inertial waves (NIWs); and diurnal (D1), semidiurnal (D2), and tridiurnal (D3) internal tides (ITs) dominate the local shear field. The shear exhibits a remarkable surface-intensified pattern with high values occurring mostly in the upper 200 m. Significant seasonal variations can be found in the shear, but with differences between the upper (50–200 m averaged) and lower layers (210–570 m averaged). Satellite altimeter data indicate that the meander of the Kuroshio mainstream and the Kuroshio intrusion affect the seasonal variation of total shear by mainly influencing the shear caused by SICs. In addition, the shear efficiency (SE) of D2 ITs is obviously less than that of NIWs and that of D1 and D3 ITs via analyzing the kinetic energy (KE) densities and shear caused by these motions, since the predominant mode of the former is the first baroclinic mode, while the latter is dominated by higher baroclinic modes with large vertical wavenumbers. Moreover, the SE of incoherent ITs is relatively stronger than that of coherent ITs as a result of a larger proportion of high baroclinic modes in the incoherent component compared to the coherent component, based on modal decomposition.
Deep Reinforcement Learning Based Time-Domain Interference Alignment Scheduling for Underwater Acoustic Networks
Authors: Zhao Nan , Yao Nianmin , Gao Zhenguo , Lu Zhimao
Published: July 2022

Message conflicts caused by large propagation delays severely affect the performance of Underwater Acoustic Networks (UWANs). It is necessary to design an efficient transmission scheduling algorithm to improve the network performance. Therefore, we propose a Deep Reinforcement Learning (DRL) based Time-Domain Interference Alignment (TDIA) scheduling algorithm (called DRLSA-IA). The main objective of DRLSA-IA is to increase network throughput and reduce collisions. In DRLSA-IA, underwater nodes are regarded as agents of DRL. Nodes intelligently learn the scheduling by continuously interacting with the environment. Therefore, DRLSA-IA is suitable for the highly dynamic underwater environment. Moreover, we design a TDIA-based reward mechanism to improve the network throughput. With the TDIA-based reward mechanism, DRLSA-IA can achieve parallel transmissions and effectively reduce conflicts. Unlike other TDIA-based algorithms that require enumeration of the state space, nodes merely feed the current state to obtain the transmission decision. DRLSA-IA solves the problem of computational expense. Simulation results show that DRLSA-IA can greatly improve the network performance, especially in terms of throughput, packet delivery ratio and fairness under different network settings. Overall, DRLSA-IA can effectively improve network performance and is suitable for ever-changing underwater environments.
Institutional Ownership and Investment Efficiency: Evidence from Iran
Authors: Moradi Mohammad , Yazdifar Hassan , Eskandar Hoda , Namazi Navid Reza
Published: July 2022

Investment efficiency shows how well a company invests its assets. Although institutional shareholders play undeniable roles in companies, it is not clear whether they are able to monitor managers and make investment decisions or not. This study gives answers to stakeholders, addresses concerns about the effect of the owners on investment efficiency, and aims to add to the literature on emerging markets by investigating the relationship in Iran, a different environment from developed ones. Based on monitoring power, the shareholders are divided into two types: active and passive ones. Investment problems are classified into two types: over- and under-investment problems. The sample consists of 101 firms listed on the Tehran Stock Exchange between 2010 and 2016. Some regression models are used. The results illustrated that institutional owners have a positive effect on investment efficiency and decrease both over- and under-investment problems and so, the efficient monitoring school is approved. Additionally, active ones are positively correlated with investment efficiency and decrease both investment inefficiency problems. Institutional ownership is the cause of investment efficiency, not the reverse. Based on findings, in emerging markets like Iran’s market, investors are recommended to give notice to the level of active ownership in firms; ownership structure is a good sign of efficiency.
Parsimonious AHP-DEA Integrated Approach for Efficiency Evaluation of Production Processes
Authors: Ammirato Salvatore , Fattoruso Gerarda , Violi Antonio
Published: July 2022

This document proposes an innovative composite indicator to measure and control the performance of production processes. The aim is to provide a tool for controlling the efficiency of the processes, assessed in relation to the number and the impact of occurring “errors”, which can take into account the opinion of experts in the specific domain. This allows for the definition of a more realistic and effective decision support system. Our composite indicator is based on an integrated approach based on Data Envelopment Analysis (DEA), and a new multi-criteria method such as Parsimonious Analytical Hierarchy Process (PAHP). The results obtained on a real test case, based on the automotive production domain, show that the composite indicator built with PAHP-DEA allows us to have clear evidence of the efficiency level of each process and the overall impact of errors on all the processes under evaluation. From a methodological point of view, we have for the first time combined the new thrifty AHP with the DEA. From an application point of view, this work introduces a new tool capable of evaluating the efficiency of production processes in an extremely competitive sector, exploiting the knowledge of the experts in the domain of errors, internal processes and the dynamics that occur.
Survey of the Intermolecular Disulfide Bonds Observed in Protein Crystal Structures Deposited in the Protein Data Bank
Authors: Carugo Oliviero
Published: July 2022

About 5% of the disulfide bonds (DBs) observed in the Protein Data Bank bridge two protein chains. Several of their features were comprehensively analyzed, resulting in a structural atlas of the intermolecular DBs. The analysis was performed on a very large set of data extracted from the Protein Data Bank, according to the RaSPDB procedure. It was observed that the two chains tend to have different sequences and belong to the same structural class. Intermolecular DBs tend to be more solvent accessible and less distorted from the most stable conformation than intermolecular DBs while showing similar B-factors. They tend to occur in beta strands and in mainly-beta structures. These and other data should prove useful in protein modelling and design.
Emerging SARS-CoV-2 Mutational Variants of Concern Should Not Vary in Susceptibility to Microbicidal Actives
Authors: Ijaz M. Khalid , Nims Raymond W. , McKinney Julie
Published: July 2022

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is evolving, with emergence of mutational variants due to the error-prone replication process of RNA viruses, in general. More recently, the Delta and Omicron variants (including sub-variants BA.1–5) predominate globally, and a Delta–Omicron recombinant termed Deltacron has emerged. The emergence of variants of concern (VOC) demonstrating immune evasion and potentially greater transmissibility and virulence naturally raises concern in both the infection control communities and the public at large, as to the continued suitability of interventions intended to mitigate the risk of viral dissemination and acquisition of the associated disease COVID-19. We evaluated the virucidal efficacy of targeted surface hygiene products (an ethanol/quaternary ammonium compound (QAC)-containing disinfectant spray, a QAC disinfectant wipe, a lactic acid disinfectant wipe, and a citric acid disinfectant wipe) through both theoretical arguments and empirical testing using international standard methodologies (ASTM E1053-20 hard surface test and EN14476:2013+A2:2019 suspension test) in the presence of soil loads simulating patients’ bodily secretions/excretions containing shed virus. The results demonstrate, as expected, complete infectious viral inactivation (≥3.0 to ≥4.7 log10 reduction in infectious virus titer after as little as 15 s contact time at room temperature) by these surface hygiene agents of the original SARS-CoV-2 isolate and its Beta and Delta VOC. Through appropriate practices of targeted surface hygiene, it is expected that irrespective of the SARS-CoV-2 VOC encountered as the current pandemic unfolds (and, for that matter, any emerging and/or re-emerging enveloped virus), the chain of infection from virus-contaminated fomites to the hand and mucous membranes of a susceptible person may be disrupted.
4-(Benzo[d]thiazol-2-yl)-1-(2-nitrophenyl)-1H-1,2,3-triazol-5-amine
Authors: Pokhodylo Nazariy T. , Obushak Mykola D.
Published: July 2022

The protocol for the reaction of 2-nitrophenyl azide with 2-(benzo[d]thiazol-2-yl)acetonitrile has been selected. It was found that an optimal condition under which the target 4-(benzo[d]thiazol-2-yl)-1-(2-nitrophenyl)-1H-1,2,3-triazol-5-amine could be formed in good yield is the triethylamine system as a base in the DMF solution. The synthesized triazole is promising both for the evaluation of its antiproliferative properties and for the study of the path to new ring annulation by transforming nitro and amino groups.
Particle Characterization of Manufactured Sand and Its Influence on Concrete Properties
Authors: Wu Jiale , Shen Weiguo , Zhao Deqiang , Wu Miaomiao , Yu Zhen , Zhao Zhicheng , Li Zhitang , Wu Dinglve , Sun Jiangtao
Published: July 2022

With the rapid development of infrastructure construction, it is an inevitable trend to replace natural sand in short supply with manufactured sand to meet sustainable development. In this paper, the relationship between the particle shape characteristics of manufactured sand and concrete performance is discussed using a morphological analysis and concrete experiments. The particle shape parameters of five types of manufactured sand were obtained by using the aggregate image measurement system (AIMS) and digital image processing (DIP) techniques, and the correlations between different parameters were analyzed. Moreover, the properties of concrete with the five kinds of manufactured sand were tested. The results show that particle size and type have a significant impact on particle shape parameters. Particle shape parameters, especially angularity, correlate well with the workability and compressive strength of concrete while having little effect on the durability of concrete. An accurate understanding of the morphological characteristics of manufactured sand is conducive to the optimization of concrete mix designs. Therefore, it is suggested that a manufactured-sand shape test be included in aggregate specification.
Gel Evolution of Copper Tailing-Based Green Geopolymers in Marine Related Environments
Authors: Li Jing , Yang Lang , Rao Feng , Tian Xiang
Published: July 2022

Geopolymers have attracted extensive attention in the marine environment because of its special reticulate nanostructure. Gel evolutions of copper tailing-based green geopolymers were studied under air, deionized water, seawater, freeze–thaw cycle and carbonization environments. Their mechanical properties and microstructures were characterized by compressive strength measurement, X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR) and scanning electron microscopy (SEM). It was found that the deionized water and natural marine water exposure promoted the evolution degree of geopolymers and improved their compressive strength, while exposure to the carbonization environment weakened the gel evolution and decreased the cross-linking degree of the Sodium aluminosilicate hydrate (N-A-S-H)gel structure, resulting in a decline of compressive strength. The geopolymer exposed in the freeze–thaw cycle exhibited the worst deterioration due to the expansion caused by the crystallization in the geopolymer. These results are essential and beneficial to further understanding the gel formation process in various marine environments and could promote the investigation of green concrete.
Scalable, Robust and Highly Productive Novel Convecdiff Membrane Platform for mAb Capture
Authors: Grünberg Mario , Kuchemüller Kim B. , Töppner Katrin , Busse Ricarda A.
Published: July 2022

The recombinant monoclonal antibody capture step represents the current bottleneck in downstream processing. Protein A resins are diffusion-limited chromatography materials which require low flow rates to achieve a binding capacity above 30 g L−1 with the result of low productivity. Here, we present a novel chromatography membrane combining superior binding capacities with high flow rates for high productivity while achieving comparable product quality as state-of-the-art protein A resins. Further, we demonstrate full scalability of this convecdiff technology with experimental data demonstrating suitability for bioprocessing at different scales. This technology results in more than 10-fold higher productivity compared to Protein A resins, which is maintained during scale up. We demonstrate the influence of residence times, feed titers and the cleaning regime on productivity and indicate optimal utilization of the convecdiff membrane based on feed titer availability. The underlying high productivity and short cycle times of this material enable the purification of monoclonal antibodies with 10-times less chromatography material used per batch and utilization of the membrane within one batch. Provided in disposable consumables, this novel technology will remove column handling in bioprocesses and resin re-use over multiple batches.
Effect of Mn Element on the Structures and Properties of A2B7-Type La–Y–Ni-Based Hydrogen Storage Alloys
Authors: Deng Anqiang , Luo Yongchun , Zhou Jianfei , Xie Yunding , Yuan Yuan , Kang Xiaoyan , Shen Bingjin , Zhang Haimin
Published: July 2022

The structures, hydrogen storage behaviors and electrochemical properties of Y0.75La0.25Ni3.5−xMnx (x = 0–0.3) alloys were analyzed by X-ray diffraction, Neutron powder diffraction, pressure–composition isotherms and electrochemical tests. All alloys have a multiphase structure. With the increase in Mn content, the Gd2Co7-type phase of the alloys gradually transforms into the Ce2Ni7-type phase; the Mn atom mainly occupies the Ni sites in the [AB5] subunit and the interface between the [AB5] and [A2B4] subunits; the V[A2B4]/V[AB5] continuously decreases from 1.045 (x = 0) to 1.019 (x = 0.3), which reduces the volume mismatch between [A2B4] and [AB5] subunits. The maximum hydrogen absorption of the series alloys increases first and then decreases, and the addition of Mn effectively promotes the hydrogen absorption/desorption performance of the alloys. The maximum discharge capacity of the alloy electrodes is closely related to their hydrogen storage capacity at 0.1 MPa and hydrogen absorption/desorption plateau pressure. The cyclic stability of all the Mn-containing alloy electrodes is improved clearly compared to that of Mn-free alloy electrodes, because the volume mismatch between the [AB5] and [A2B4] subunits of the alloys becomes smaller after the addition of Mn, which can improve the structural stability and reduce the corrosion of alloys during hydrogen absorption/desorption cycles. When the Mn content is between 0.1 and 0.15, the Ce2Ni7-type phase of the alloys has high abundance and the alloy electrodes exhibit excellent overall performance.
Micromechanics-Based Low Cycle Fatigue Life Prediction Model of ECAPed Aluminum Alloy
Authors: Sun Teng , Xie Yiji , Pan Yuchen , Zheng Zhanguang , Xie Changji , Huang Zeng
Published: July 2022

Ultrafine-grained aluminum alloys (UFG AA) show great potential in the design of fatigue-resistant lightweight alloys, and the methodology to assess low-cycle fatigue (LCF) life remains to be studied. In this work, a micromechanics-based LCF life prediction model is presented by conducting crystal plasticity finite element simulation (CPFEM). The fatigue indicator parameter (FIP) of maximum accumulated equivalent plastic strain energy, modulated by triaxiality, is developed to assess the material damage in the microstructure. Particularly, a new multiaxial strain parameter is proposed by considering the combined influence of the mean strain and non-proportional cyclic additional hardening effect, and then directly embedding into the cyclic J-integral. Finally, the reformulated Manson-Coffin relationship is theoretically constructed by correlating the crack tip opening displacement to the crack propagation equation. The results show the scatter fatigue life of UFG AA6061 is not only related to the inhomogeneous evolution of plastic deformation but also to the local stress state. Since the proposed approach considers both the deformation mechanisms at the micro-scale and the corresponding macroscopic responses, it can predict the LCF life of UFG AA with reasonable accuracy.
The Microstructural Evolution of Nickel Single Crystal under Cyclic Deformation and Hyper-Gravity Conditions: A Molecular Dynamics Study
Authors: Deng Xiaojuan , Xiao Yudi , Ma Yiwu , Huang Bowen , Hu Wangyu
Published: July 2022

Turbine blades are subjected to cyclic deformation and intensive hyper-gravity force during high-speed rotation. Therefore, understanding the dynamic mechanical behavior is important to improve the performance of the blade. In this work, [001](010), [110](−110), and [11−2](111) pre-existing crack models of nickel single crystals under increasing cyclic tensile deformations were studied by using molecular dynamics simulations. In addition, a novel hyper-gravity loading method is proposed to simulate the rotation of the blade. Four hyper-gravity intensities, i.e., 1 × 1012 g, 3 × 1012 g, 6 × 1012 g, and 8 × 1012 g, and different temperatures were applied during the cyclic deformation. The fatigue life decreased rapidly with the elevated hyper-gravity strength, although the plastic mechanism is consistent with the zero-gravity condition. The stress intensity factor for the first dislocation nucleation indicates that the critical stress strongly depends on the temperatures and hyper-gravity intensities. Moreover, the crack length in relation to hyper-gravity intensity is discussed and shows anisotropy along the direction of hyper-gravity. A temperature-induced brittle-to-ductile transition is observed in the [001](010) crack model. The present work enhances our understanding of the fatigue mechanism under hyper-gravity conditions from an atomistic viewpoint.
Real-Time Monitoring of the Temperature, Flow, and Pressure Inside High-Temperature Proton Exchange Membrane Fuel Cells
Authors: Lee Chi-Yuan , Weng Fang-Bor , Chiu Chun-Wei , Nawale Shubham-Manoj , Lai Bo-Jui
Published: July 2022

The proton exchange membrane fuel cell (PEMFC) system is a highly efficient and environmentally friendly energy conversion technology. However, the local temperature, flow, and pressure inhomogeneity within the fuel cell during the electrochemical reaction process may lead to depletion of PEMFC material and uneven fuel distribution, thus affecting the performance and service life of high-temperature PEMFCs. In this study, micromachining technology is used to develop a three-in-one flexible micro-sensor that is resistant to a high-temperature electrochemical environment (120~200 °C). Appropriate materials and process parameters are used to protect the micro-sensor from failure or damage under long-term testing, and to conduct a real-time micro-monitor of the local temperature, flow, and pressure distribution inside high-temperature PEMFCs.
Investigations of Micro-Deformation in Monocrystalline Copper at Low Temperatures via Indentation
Authors: Wang Shunbo , Zhao Dan , Niu Yihan , Wang Zhaoxin , Yang Hongxiu , Zhao Hongwei
Published: July 2022

Indentation experiments on differently oriented faces of monocrystalline copper were conducted to investigate the micro-deformation process at temperatures ranging from room temperature to 150 K. The morphologies and textures of the residual imprints were observed using electron microscopy. Distinct slip bands were observed inside the imprints at 150 K compared to smooth surfaces at room temperature. Molecular dynamics simulations were performed to identify the deformation process beneath the indentation region. The results showed that plastic deformation was inhibited with decreasing temperature, but elastic recovery during the unloading process was enhanced, resulting in inner slip bands (ISBs) being observable in the residual imprints. The performances of these ISBs were strongly associated with the angles between the indentation direction and major slip surfaces and could be considered microscopic forms on the surfaces of aggregated geometrically necessary dislocations (GNDs). This work helped reveal the micro-deformation mechanism of indentations inside imprints.
Performance Improvement of Single-Frequency CW Laser Using a Temperature Controller Based on Machine Learning
Authors: Qiao Haoming , Peng Weina , Jin Pixian , Su Jing , Lu Huadong
Published: July 2022

The performance improvement of an all-solid-state single-frequency continuous-wave (CW) laser with high output power is presented in this paper, which is implemented by employing a temperature control system based on machine learning to control the temperature of laser elements including gain crystal, laser diode and so on. Because the developed temperature controller based on machine learning combines the back propagation (BP) neural network algorithm with the proportion-integration-differentiation (PID) control algorithm, the parameters of the PID are adaptive with the variation of the environment. As a result, the control speeds and control abilities of the temperatures of the elements are dramatically enhanced. In this case, the output characteristic and the adaptability to the environment as well as the stability of the single-frequency CW laser are also improved greatly.
Temperature Compensation Method Based on an Improved Firefly Algorithm Optimized Backpropagation Neural Network for Micromachined Silicon Resonant Accelerometers
Authors: Huang Libin , Jiang Lin , Zhao Liye , Ding Xukai
Published: July 2022

The output of the micromachined silicon resonant accelerometer (MSRA) is prone to drift in a temperature-changing environment. Therefore, it is crucial to adopt an appropriate suppression method for temperature error to improve the performance of the accelerometer. In this study, an improved firefly algorithm-backpropagation (IFA-BP) neural network is proposed in order to realize temperature compensation. IFA can improve a BP neural network’s convergence accuracy and robustness in the training process by optimizing the initial weights and thresholds of the BP neural network. Additionally, zero-bias experiments at room temperature and full-temperature experiments were conducted on the MSRA, and the reproducible experimental data were used to train and evaluate the temperature compensation model. Compared with the firefly algorithm-backpropagation (FA-BP) neural network, it was proven that the IFA-BP neural network model has a better temperature compensation performance. The experimental results of the zero-bias experiment at room temperature indicated that the stability of the zero-bias was improved by more than an order of magnitude after compensation by the IFA-BP neural network temperature compensation model. The results of the full-temperature experiment indicated that in the temperature range of −40 °C~60 °C, the variation of the scale factor at full temperature improved by more than 70 times, and the variation of the bias at full temperature improved by around three orders of magnitude.
An Efficient YOLO Algorithm with an Attention Mechanism for Vision-Based Defect Inspection Deployed on FPGA
Authors: Yu Longzhen , Zhu Jianhua , Zhao Qian , Wang Zhixian
Published: July 2022

Industry 4.0 features intelligent manufacturing. Among them, the vision-based defect inspection algorithm is remarkable for quality control in parts manufacturing. With the help of AI and machine learning, auto-adaptive instead of manual operation is achievable in this field, and much progress has been made in recent years. In this study, considering the demand of inspection features in industrialization, we made further improvement in smart defect inspection. An efficient algorithm using Field Programmable Gate Array (FPGA)-accelerated You Only Look Once (YOLO) v3 based on an attention mechanism is proposed. First, because of the relatively fixed camera angle and defect features, an attention mechanism based on the concept of directing the focus of defect inspection is proposed. The attention mechanism consists of three improvements: (a) image preprocessing, which is to tailor images for selectively concentrating on the defect relevant things. Image preprocessing mainly includes cutting, zooming and splicing, named CZS operations. (b) Tailoring the YOLOv3 backbone network, which is to ignore invalid inspection regions in deep neural networks and optimize the network structure. (c) Data augmentation. First, two improvements can be made to efficiently reduce deep learning operations and accelerate the inspection speed, but the preprocessed images are similar and the lack of diversity will reduce network accuracy. So, (c) is added to mitigate the lack of considerable amounts of training data. Second, the algorithm is deployed on a PYNQ-Z2 FPGA board to meet the industrialization production requirements for accuracy, efficiency and extensibility. FPGA can provide a low-latency, low-cost, high-power-efficiency and flexible architecture that enables deep learning acceleration for industrial scenarios. A Xilinx Deep Neural Network Development Kit (DNNDK) converted the improved YOLOv3 to Programmable Logic (PL), which can be deployed on FPGA. The conversion process mainly consists of pruning, quantization and compilation. Experimental results showed that the algorithm had high efficiency, inspection accuracy reached 99.2%, processing speed reached 1.54 Frames per Second (FPS), and power consumption was only 10 W.
Experimental Investigation on the Effect of Surface Shape and Orientation in Magnetic Field Assisted Mass Polishing
Authors: Loh Yee-Man , Cheung Chi-Fai , Wang Chunjin , Ho Lai-Ting
Published: July 2022

Magnetic field assisted finishing (MFAF) technology has been widely used in industries such as aerospace, biomedical, and the optical field for both external and internal surface finishing due to its high conformability to complex surfaces and nanometric surface finishing. However, most of the MFAF methods only allow polishing piece-by-piece, leading to high post-processing costs and long processing times with the increasing demand for high precision products. Hence, a magnetic field-assisted mass polishing (MAMP) method was recently proposed, and an experimental investigation on the effect of surface posture is presented in this paper. Two groups of experiments were conducted with different workpiece shapes, including the square bar and roller bar, to examine the effect of surface orientation and polishing performance on different regions. A simulation of magnetic field distribution and computational fluid dynamics was also performed to support the results. Experimental results show that areas near the chamber wall experience better polishing performance, and the surface parallel or inclined to polishing direction generally allows better shearing and thus higher polishing efficiency. Both types of workpieces show notable polishing performance where an 80% surface roughness improvement was achieved after 20-min of rough polishing and 20-min of fine polishing reaching approximately 20 nm.
Evaluation of Virucidal Quantitative Carrier Test towards Bovine Viruses for Surface Disinfectants While Simulating Practical Usage on Livestock Farms
Authors: Hasan Md. Amirul , Miyaoka Yu , Kabir Md. Humayun , Kadota Chisaki , Hakim Hakimullah , Shoham Dany , Murakami Harumi , Takehara Kazuaki
Published: July 2022

Livestock farming is affected by the occurrence of infectious diseases, but outbreaks can be prevented by effective cleaning and disinfection along with proper farm management. In the present study, bovine coronavirus (BCoV) and bovine rotavirus A (RVA) were inactivated using food additive-grade calcium hydroxide (FdCa(OH)2) solution, quaternary ammonium compound (QAC) and their mixture through suspension tests as the primary screening, and afterward via carrier tests using dropping or dipping techniques as the secondary screenings. Viruses in the aqueous phase can be easily inactivated in the suspension tests, but once attached to the materials, they can become resistant to disinfectants, and require longer times to be inactivated. This highlights the importance of thorough cleaning with detergent before disinfection, and keeping elevated contact durations of proper disinfectants to reduce viral contamination and decrease infectious diseases incidence in farms. It was also reaffirmed that the suspension and carrier tests are necessary to evaluate disinfectants and thus determine their actual use. Particularly, the mixture of QAC and FdCa(OH)2 was found to exhibit synergistic and broad-spectrum effects compared to their use alone, and is now recommended for use on livestock farms.
Phage Products for Fighting Antimicrobial Resistance
Authors: Huang Yuanling , Wang Wenhui , Zhang Zhihao , Gu Yufeng , Huang Anxiong , Wang Junhao , Hao Haihong
Published: July 2022

Antimicrobial resistance (AMR) has become a global public health issue and antibiotic agents have lagged behind the rise in bacterial resistance. We are searching for a new method to combat AMR and phages are viruses that can effectively fight bacterial infections, which have renewed interest as antibiotic alternatives with their specificity. Large phage products have been produced in recent years to fight AMR. Using the “one health” approach, this review summarizes the phage products used in plant, food, animal, and human health. In addition, the advantages and disadvantages and future perspectives for the development of phage therapy as an antibiotic alternative to combat AMR are also discussed in this review.
Historical Review of Studies on Cyrtophorian Ciliates (Ciliophora, Cyrtophoria) from China
Authors: Qu Zhishuai , Pan Hongbo , Gong Jun , Wang Congcong , Filker Sabine , Hu Xiaozhong
Published: July 2022

The subclass Cyrtophoria are a group of morphologically specialized ciliates which mainly inhabit soil, freshwater, brackish water, and marine environments. In this study, we revise more than 50 publications on the taxonomy, phylogeny, and ecology of cyrtophorian ciliates in China since the first publication in 1925, most of which were carried out in coastal areas. The research history can be divided into three periods: the early stage, the Tibet stage, and the molecular stage. To date, 103 morpho-species (147 isolates) have been formally recorded in China, with ciliature patterns described for 82 of them. A species checklist and an illustrated identification key to the genera are provided. A total of 100 small subunit rDNA sequences have been obtained for 74 taxonomic hits (lowest taxonomic rank to species or genus). These sequences are used for the study of molecular phylogeny. Based on these morphological data and molecular phylogeny analyses, we synthesize the understanding of the phylogeny of cyrtophorian ciliates. We hypothesize that the key evolutionary event of cyrtophorian ciliates lies in the separation of the stomatogenesis zone (postoral kineties) from the left kineties, namely, the formation of an independent “sexual organelle”. We, furthermore, briefly summarize the ecological features of cyrtophorian ciliates and provide a comprehensive bibliography of related research from China. Finally, we give an outlook on the future research directions of these taxa.