bluuebunny/crossref_metadata_2025_split huggingface dataset:
A generalized analysis of high‐order N‐path filters
Authors: Moradino Vahid , Najafiaghdam Esmaeil 
Published: September 2022

AbstractIn N‐path filter analysis, assumptions are used to simplify their analysis to avoid the complexity of the calculations. These assumptions limit the number of examinable circuits. This paper analyzes a general system including an arbitrary number of N‐path filters to generalize the analysis. In the proposed method, due to the calculation of harmonic transfer functions for each independent capacitor in each time interval, it is possible to examine N‐path filters in the presence of common capacitors between multiple branches, leakage resistors, and branches with asymmetric switching. The absence of discontinuous jumps during the switching moments and switching operation in a non‐overlapping fashion with a specified periodicity are the only assumptions of the proposed method. As a result, more LPTV (linear periodically time‐varying) systems can be analyzed using the calculations provided. After presenting the method, we show the proposed method's ability by analyzing a recently published impedance‐transforming N‐path filter and examining its details.
Magnesium Promoted Active and Isoselective ROP of rac‐Lactide and ϵ‐Caprolactone Under Mild Conditions
Authors: Sagar Shweta , Bano Kulsum , Sarkar Alok , Pal Kuntal , Panda Tarun K. 
Published: September 2022

AbstractA novel amidophosphine sulfur‐supported magnesium complex, [Ph2P(S)NCH2CH2N−(CH2CH2)O]Mg(C4H9)(THF)] (2) enabling efficient ring‐opening polymerization of rac‐lactide (LA) and ϵ‐caprolactone (CL) is disclosed. Achieved incredible selectivity for ROP of rac‐lactide for the first time using a magnesium catalyst affording isoselective PLA with a Pi value of 0.77. The polymerization of rac‐LA as well as ϵ‐CL proceeded under mild reaction conditions in absence of any external initiator, to yield corresponding polyesters with a great control over the molecular weight. The kinetic studies reveal that both sulfur and magnesium centers simultaneously work together to drive high yield and selectivity.
Near‐Infrared Squaraine Dyes as Bright Fluorescent Probes: A Structure–Activity Photophysical Investigation in Liposomes
Authors: Renno Giacomo , Cardano Francesca , Ilieva Viktoria , Viscardi Guido , Fin Andrea 
Published: September 2022

AbstractThe efficient investigation of biological membranes is a constant demand in chemical biology. Several families of Near Infra‐Red (NIR) dyes have been already studied for the selective staining of a plethora of biological structures, macro and supramolecular assemblies. In this context, a small library of symmetrical and unsymmetrical NIR squaraine dyes have been synthetized and investigated as fluorescent probes to stain the lipid bilayer membrane in large unilamellar vesicles (LUVs) as cell membrane model. The hydrophobic‐hydrophilic character of the NIR dyes has been modulated by introducing carboxylic moieties on the aromatic core, as well as by varying the length of the alkyl chains used in the quaternarization of the indolenine nitrogen. The photophysical properties and the kinetic of the insertion into different LUVs models have been analysed with respect to the probe structures. The discussed results represent versatile key data to support the design of new NIR sensors for bioimaging.
Interplay between cellular changes in the knee joint, circulating lipids and pain behaviours in a slowly progressing murine model of osteoarthritis
Authors: Gowler Peter R. W. , Turnbull James , Shahtaheri Mohsen , Walsh David A. , Barrett David A. , Chapman Victoria 
Published: September 2022

AbstractBackgroundSynovial inflammation has known contributions to chronic osteoarthritis (OA) pain, but the potential role in transitions from early to late stages of OA pain is unclear.MethodsThe slowly progressing surgical destabilization of the medial meniscus (DMM) murine OA model and sham control, was used in male C57BL/6J mice to investigate the interplay between knee inflammation, plasma pro‐ and anti‐inflammatory oxylipins and pain responses during OA progression. Changes in joint histology, macrophage infiltration, chemokine receptor CX3CR1 expression, weight bearing asymmetry, and paw withdrawal thresholds were quantified 4, 8 and 16 weeks after surgery. Plasma levels of multiple bioactive lipid mediators were quantified using liquid chromatography with tandem mass‐spectrometry (LC–MS/MS).ResultsStructural joint damage was evident at 8 weeks post‐DMM surgery onwards. At 16 weeks post‐DMM surgery, synovial scores, numbers of CD68 and CD206 positive macrophages and pain responses were significantly increased. Plasma levels of oxylipins were negatively correlated with joint damage and synovitis scores at 4 and 8 weeks post‐DMM surgery. Higher circulating levels of the pro‐resolving oxylipin pre‐cursor 17‐HDHA were associated with lower weight bearing asymmetry at week 16.ConclusionsThe transition to chronic OA pathology and pain is likely influenced by both joint inflammation and plasma oxylipin mediators of inflammation and levels of pro‐resolution molecules.SignificanceUsing a slow progressing surgical model of osteoarthritis we show how the changing balance between local and systemic inflammation may be of importance in the progression of pain behaviours during the transition to chronic osteoarthritis pain.
Production prediction and main controlling factors in a highly heterogeneous sandstone reservoir: Analysis on the basis of machine learning
Authors: Wang Zhao , Tang Hongming , Cai Hui , Hou Yawei , Shi Hongfu , Li Jingling , Yang Tao , Feng Yutian 
Published: September 2022

AbstractOwing to a lengthy oil‐bearing interval, strong anisotropism, and significant difference in the fluid properties of the sandstone oil reservoir in P Oilfield, it is quite challenging to accurately the productivity of the oil well at the initial stage. In this study, a deep neural network model is established, based on a gradient boosting algorithm, XGBoost, to forecast the initial productivity of oil wells, followed by an evaluation of the main controlling factors of productivity. One hundred oil wells in the study area were divided into training and verification groups. With a specific productivity index of an oil well with a stable period of approximately 6 months at the initial production stage as the target data, and geological, engineering, and oil reservoir parameters as input data, hyper‐parameters for adjustment and optimization were selected, and a deep‐learning‐based unconsolidated sandstone productivity forecast model was established to forecast the initial productivity of oil wells in the target area. The mean square root error of the forecast result was <0.15, which is highly consistent with actual productivity. Finally, by adopting the XGBoost algorithm, the weight ranking of the controlling factors of productivity was clarified as follows: microscopic pore structure parameter > crude oil viscosity > median grain size > lithology index > well completion method > flow zone indicator. Machine learning has the advantages of effective forecasting of oil well productivity and the main controlling factors using multiple dimensions and big data.
Solar‐light‐driven ZnO/biochar treatment of pesticides contaminated wastewater: A practical and computational study
Authors: Samy Mahmoud , Gar Alalm Mohamed , Ezeldean Eman , El‐Dissouky A. , Badr Nadia B. E. , Al‐Muhtaseb Ala'a , Alhajeri Nawaf S. , Osman Ahmed I. , Tawfik Ahmed 
Published: September 2022

AbstractBiochar (BC) was prepared by carbonizing sludge from agricultural lignocellulosic waste fermentation and then used to adsorb lambda‐cyhalothrin (LM), malathion (MA), and oxamyl (OX) as potential pesticides in agrochemical industrial wastewater. Additionally, the photodegradation performance of ZnO and ZnO/Fe was evaluated using various catalyst doses in a constructed parabolic solar collector reactor. The optimal ZnO catalyst dose and reaction time was 1.0 g/L and 135 min. OX, MA, and LM removal increased from 38%, 30%, and 24% in pristine ZnO to 55%, 70%, and 46.9% in the case of the addition of BC with ZnO (ZnO/BC), respectively. The doping of ZnO with iron did not improve the photodegradation efficiency due to the reduction of crystallinity and catalyst affinity towards the pollutants after introducing those ions. The mechanism of degradation was proposed, and the by‐products generated were identified. The total cost was estimated for pure ZnO, the addition of BC with ZnO (ZnO/BC), and the addition of BC with iron‐doped ZnO (ZnO/Fe/BC). The highest binding energy of −44.74 was recorded for BC–OX complex, followed by BC–LM at −42.97. The adsorption of LM, MA, and OX by ZnO/BC is primarily due to the hydrophobic interaction, hydrogen bonding, and π–π interaction. After three cycles of recycling ZnO/BC, the degradation efficiency remained 55–52.5% for OX, 70–65% for MA, and 46.9–42.8% for LM, indicating excellent reusability and stability of the composite catalyst. The low cost of the solar‐light‐driven ZnO/BC process may improve the technique's feasibility for large‐scale implementation.
Phenolic compounds of sugar beet (Beta vulgaris L.): Separation method, chemical characterization, and biological properties
Authors: Arjeh Edris , Khodaei Seyedeh Mahsa , Barzegar Mohsen , Pirsa Sajad , Karimi Sani Iraj , Rahati Shiva , Mohammadi Farzad 
Published: September 2022

AbstractSugar beet (Beta vulgaris L.) is a good source of bioactive compounds. However, information on the biological properties of sugar beet root is limited and its beneficial effects have not been completely understood. In this work, 10 phenolic compounds have been separated and identified in various parts of sugar beet for the first time, including the most abundant epicatechin (31.16 ± 1.89 mg/100 g), gallic acid (30.57 ± 2.69 mg/100 g), and quercetin‐3‐O‐rutinoside (30.14 ± 3.63 mg/100 g). The biological activity tests indicated that sugar beet peel potently scavenged the nitric oxide and DPPH (2,2‐diphenyl‐1‐picrylhydrazyl) free radicals with IC50 values of 88.17 ± 05.14 and 28.77 ± 0.62 μg/ml, respectively. In addition, sugar beet peel exhibited the highest reducing power, IC50 values of 11.98 ± 1.20 μg/ml, and the highest ion‐chelating activity, IC50 values of 48.52% and 55.21% for cupric and ferrous ions at 250 μg/ml, respectively. Compared to synthetic antioxidants, sugar beet showed promising biological activities, which could be considered further in future studies.
Primary health care in China: A decade of development after the 2009 health care reform
Authors: Wu You , Zhang Zeyu , Zhao Ning , Yan Yue , Zhao Lina , Song Qi , Ma Rong , Li Changfeng , Li Jinyi , Liu Suibin , Bi Xinran , Zhang Zongjiu 
Published: September 2022

AbstractOver 40 years ago, primary health care (PHC) was defined in the Alma‐Ata Declaration as a critical component of the health care system to address the basic health demand of the people. In China, the Government attaches great importance to health care at the primary level. After the launch of the historical Reform of the Medical and Health Care System in 2009, the PHC system in China has witnessed major progress and breakthroughs, especially in its steadily increased capacity, continuously improved accessibility, and betterment in equality. In this review, we summarized published literatures and official policies, synthesized data from the electronic registration information system of the National Health Commission, national statistical reports, and yearbooks in health care. The review is intended to describe the systematic development of PHC in China in the last decade. The main results include: the solid national policy foundation, increasing number of PHC institutions and workforce, better training of PHC professionals, major achievements in primary health indicators, government financial support to PHC institutions, improved PHC budgeting and insurance coverage, and the advancement of supporting technologies. Challenges and prospects are also discussed.
Multistep screening and selection of COVID‐19 convalescent plasma donors at the early stage of the SARS‐CoV‐2 pandemic: A retrospective analysis
Authors: Brosig Andreas M. , Ossner Thomas , Pamler Irene , Friedinger Susanne , Bica Adelina‐Florina , Mohrez Morad , Tlili Ikram , Mueller Viktoria , Becke Christine , Haehnel Viola , Baeuerlein Veronika , Stemmer Barbara , Burkhardt Ralph , Offner Robert 
Published: September 2022

AbstractBackground and AimsThe COVID‐19 pandemic reached Bavaria in February 2020. Almost simultaneously, Chinese physicians published reports on the first successful treatments with plasma from COVID‐19 convalescent donors. With these silver linings on the horizon, we decided to establish the manufacturing of anti‐severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) antibody‐containing plasma from COVID‐19 convalescent donors at our site. Here we describe our donor selection process, built from the ground up, which enabled us to cope with the immense resonance after our social media call for donors.MethodsAs a first step, we created a specific questionnaire for telephone interviews applied by trained students to filter the wave of callers interested in plasma donation. Afterward, the medical staff evaluated the hotline questionnaires and chose eligible donors to be invited for on‐site donor evaluation. Data documentation was performed with MS Excel, and statistical analyses were calculated with GraphPad Prism 8. A quantitative in‐house ELISA was used to detect anti‐SARS‐CoV‐2 antibodies and determine specific titers.ResultsOut of 1465 calls from potential plasma donors, we could register 420 persons with a completed questionnaire. Evaluation of questionnaires identified 222 of 420 persons as eligible for donation, and 55 were directly asked for on‐site donor qualification. Subsequently, as anti‐SARS‐CoV‐2 antibody titers ≥1:800 were required, we invited 89 of 222 potential donors for an antibody screening. This procedure resulted in another 28 potential donors for an on‐site evaluation. Finally, 12 donors qualified with a titer of 1:400 and 24 with ≥1:800.ConclusionIdentifying suitable COVID‐19 convalescent plasma donors was expected to be highly time‐consuming. Implementing a screening procedure with our hotline questionnaire helped us streamline the donor selection process and reduce the workload for the staff. We propose combining the described selection process with the later introduced on‐site antibody screening as an effective strategy.
Thermal Transients in Three‐Core Power Cable Systems: First Principle Modelling and Verification
Authors: Brynem Frode , Kokkula Satyanarayana 
Published: September 2022

AbstractThis paper presents research related to developing a thermal model for three‐core power cable systems used in offshore wind farms. Three‐core power cable systems are a significantly more complicated thermo‐electrical system than single‐core power cables, primarily due to the geometric asymmetry and the number of heat sources. There are tools available that can model thermal transients in three‐core cable systems, but these tools demand a nontrivial level of prerequisite knowledge and training on the part of the user. Therefore, this research aimed at developing and testing a first principle model specifically tuned for thermal transients in three‐core cables. The model has been tested by comparing its predictions with empirical temperature data collected from heat cycle testing on three‐core cables at Nexans' facilities. To increase the quality of the predictions, part of the research was also to measure the thermal properties of swellable tape and filling compound (used in three‐core cables). The first principle model's predictions correspond well with the empirical data, the research results are promising. The model must be tested more thoroughly with different use cases before it can complement or replace current working methods.
Complexity identification in major infrastructure project information systems using graph theory
Authors: Murphy Joseph , Dickerson Charles , Thorpe Tony , Goodier Chris , Zahiroddiny Sonia , Pestana Andrew 
Published: September 2022

AbstractInformation management for major infrastructure projects is a critical task requiring ever increasing time and resources. Whilst the digitisation of construction industry information has progressed over multiple dimensions, there are still gaps in machine readable information for adequate suitability assessment of projects against their requirements. With digital twins at the heart of the digitisation agenda, it is vital that the industry expand the information available to validate and verify asset and network outcomes throughout their lifecycle. Within the construction industry, systems engineering is being deployed for asset and information requirements and model‐based systems engineering can support digital techniques in managing construction information requirements. However, as an intensive task it must be selectively deployed to obtain value within a complex operating system. An opportunity exists to use data and relationships held in electronic document management systems that currently store project requirements. To achieve this, graph/network theory can be used to visualise and analyse the connectivity of document datapoints. This study deploys a python modelling environment to create digraphs that are used to visualise and identify key data from a document management system, identifying the highest degree and betweenness for documents from a sample size of 20 queries producing 327 vertices. It demonstrates a useful means of interrogating the data rapidly that is quick to scale and expand. There are opportunities to deploy this across multiple digital systems to further map complexity and interactions between them. Identification is the critical first step for data driven point of application ‘surgical’ model‐based systems engineering.
Serious Games with SysML: Gamifying Threat Modelling in a Small Business Setting
Authors: Georgsen R.E. , Køien G. Myrdahl 
Published: September 2022

AbstractThis paper describes using casual games to capture and disseminate expert security knowledge with a digital model at a small company. Most companies in the global supply chain are Very Small Entities (VSE), meaning they employ five (5) to twenty‐five (25) people. These companies represent a risk because they have little to no security proficiency and limited resources and incentive to prioritize system security. Moreover, this is a hidden risk because the companies higher up in the supply chain rely on contractual mechanisms to enforce compliance with security requirements. Small companies rely on informal methods in their daily work and are resistant to change. Threat modelling in the context of Agile Model‐Based Systems Engineering (AMBSE) can provide VSEs with a structure that allows them to retain their informal operational agility. When modelling using games, the security expert plays the dual role of modeler and educator, and the engineering team is gaining security proficiency, improving the quality of both their current and future work. Players reported improved understanding of other stakeholders' perspectives. Agility, proficiency, and stakeholder alignment are among the critical foundation concepts identified by the INCOSE led Future of Systems Engineering Initiative (FuSE) to improve system security.
Situational awareness and human factors when designing complex systems
Authors: Helle Dag Eirik , Frølich Marcus , Langen Tommy , Muller Gerrit 
Published: September 2022

AbstractThe background for this paper is to prepare for the execution of a research project in systems engineering about situational awareness and human factors. The authors use a major defense company as the case for this research. The company is developing a new weapon system that allows one operator to operate multiple remote weapon systems. The systems will produce a large amount of data that the operators must use in their decision‐making process. To make the right decisions, the operators need good situational awareness.The authors have examined publications about situational awareness and human factors and elaborated on the research design for the upcoming research project. Findings in the literature suggest that situational awareness consists of three levels. In all three levels, several factors affect an operator's ability to build and maintain situational awareness. The hypothesis for the upcoming research project is that the company lacks in‐depth knowledge about situational awareness.
Revisiting the synthesis of bis(2‐hydroxy‐3,5‐di‐t‐butylphenyl)methanone
Authors: Lin Xin‐Jie , Huang Shih‐Peng , Huang Min‐Jie , Wang Chien‐Lung , Peng Chi‐How , Liu Hsueh‐Ju , Wu Yen‐Ku 
Published: September 2022

AbstractDescribed is our effort toward establishing a practical and sustainable synthesis of bis(2‐hydroxy‐3,5‐di‐t‐butylphenyl)methanone. In it, we found the phenol‐aldehyde condensation could be efficiently catalyzed by sulfonic acid‐functionalized microporous carbon spheres (MCS‐SO3H). Additionally, we developed practical and sustainable procedures for the synthesis of the title ligand by applying readily available reagents in lieu of toxic chromium trioxide and fuming boron tribromide.
Validation of high concentrated thrombin time assay for unfractionated heparin monitoring
Authors: Apipongrat Dollapak , Police Pornnapa , Lamool Rattapan , Butthep Punnee , Chantkran Wittawat 
Published: September 2022

AbstractBackgroundThe high concentrated thrombin time (hcTT), a thrombin time modified by increasing the thrombin concentration, is a possible alternative assay to activated partial thromboplastin time (aPTT) in unfractionated heparin (UFH) monitoring. This study aimed to determine the optimal thrombin concentration used in the hcTT assay for UFH monitoring.MethodsA total of 30 blood samples obtained from healthy volunteers were included in this study. Thrombin concentrations of 10.0, 15.0, 20.0, and 25.0 IU/ml were used in the hcTT assay. The consistency between the hcTT and anti‐FXa assays was evaluated. To validate the hcTT assay, linearity, repeatability, reproducibility, and diagnostic performance of the assay were assessed.ResultsThe hcTT assay using thrombin concentration of 15.0 IU/ml showed a strong correlation to the anti‐FXa assay with R2 of 0.72 and the Spearman's correlation coefficient (rs) of 0.97 (95% CI, 0.96–0.98). Within‐run and day‐to‐day run variabilities of the assay were satisfactory (all coefficients of variation <10%). We found an excellent correlation between the results which were measured using different reagents with intra‐ or inter‐laboratory instruments. Notably, as compared to the aPTT assay, the hcTT assay showed a significantly better performance in identifying the samples which contain UFH at the supratherapeutic level, with an AUC of 0.97 vs. 0.91, p = 0.049.ConclusionThe hcTT assay can be used as an alternative assay for UFH therapy monitoring. A further study using clinical samples is recommended to confirm the appropriateness of the hcTT assay for clinical application.