bluuebunny/crossref_metadata_2025 huggingface dataset:
SARS-CoV-2 Infection of Rhesus Macaques Treated Early with Human COVID-19 Convalescent Plasma
Authors: Deere Jesse D. , Carroll Timothy D. , Dutra Joseph , Fritts Linda , Sammak Rebecca Lee , Yee JoAnn L. , Olstad Katherine J. , Reader J. Rachel , Kistler Amy , Kamm Jack , Di Germanio Clara , Shaan Lakshmanappa Yashavanth , Elizaldi Sonny R. , Roh Jamin W. , Simmons Graham , Watanabe Jennifer , Pollard Rachel E. , Usachenko Jodie , Immareddy Ramya , Schmidt Brian A. , O’Connor Shelby L. , DeRisi Joseph , Busch Michael P. , Iyer Smita S. , Van Rompay Koen K. A. , Hartigan-O’Connor Dennis J. , Miller Christopher J.
Published: November 2021

Antiviral treatment options for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain very limited. One treatment that was explored beginning early in the pandemic (and that is likely to be tested early in future pandemics) is plasma collected from people who have recovered from coronavirus disease 2019 (COVID-19), known as convalescent plasma (CP).
A Nanobody-Mediated Virus-Targeting Drug Delivery Platform for the Central Nervous System Viral Disease Therapy
Authors: Zhu Song , Luo Fei , Zhu Bin , Ling Fei , Wang Er-Long , Liu Tian-Qiang , Wang Gao-Xue
Published: November 2021

CNS viral diseases have resulted in many deadly epidemics throughout history and continue to pose one of the greatest threats to public health. Drug therapy remains challenging due to the complex structure and relative impermeability of the biological tissues and barriers.
Oleate Hydratase (OhyA) Is a Virulence Determinant in Staphylococcus aureus
Authors: Radka Christopher D. , Batte Justin L. , Frank Matthew W. , Rosch Jason W. , Rock Charles O.
Published: November 2021

The oleate hydratase protein family was discovered in commensal bacteria that utilize host unsaturated fatty acids as the substrates to produce a spectrum of hydroxylated products. These hydroxy fatty acids are thought to act as signaling molecules that suppress the inflammatory response to create a more tolerant environment for the microbiome.
S. aureus
is a significant human pathogen, and defining the mechanisms used to evade the immune response is critical to understanding pathogenesis.
S. aureus
expresses an OhyA that produces at least three 10-hydroxy fatty acids from host unsaturated fatty acids at the infection site, and an
S. aureus
strain lacking the
ohyA
gene has compromised virulence in an immunocompetent infection model.
Effect of PEP flute self-care versus usual care in early covid-19: non-drug, open label, randomised controlled trial in a Danish community setting
Authors: Mollerup Annette , Henriksen Marius , Larsen Sofus Christian , Bennetzen Anita Selmer , Simonsen Mette Kildevæld , Kofod Linette Marie , Knudsen Jenny Dahl , Nielsen Xiaohui Chen , Weis Nina , Heitmann Berit Lilienthal
Published: November 2021

Objective

To determine whether positive expiratory pressure (PEP) by PEP flute self-care is effective in reducing respiratory symptoms among community dwelling adults with SARS-CoV-2 infection and early stage covid-19.

Design

Non-drug, open label, randomised controlled trial.

Setting

Capital Region and Region Zealand in Denmark from 6 October 2020 to 26 February 2021.

Participants

Community dwelling adults, able to perform self-care, with a new SARS-CoV-2 infection (verified by reverse transcription polymerase chain reaction tests) and symptoms of covid-19.

Intervention

Participants were randomised to use PEP flute self-care in addition to usual care or have usual care only. Randomisation was based on permuted random blocks in a 1:1 ratio, stratified for sex and age (<60 or ≥60 years). The PEP self-care group was instructed to use a PEP flute three times per day during the 30 day intervention.

Main outcome measures

Primary outcome was a change in symptom severity from baseline to day 30, as assessed by the self-reported COPD (chronic obstructive pulmonary disease) assessment test (CAT), which was adjusted for baseline values and stratification factors. Participants completed the CAT test questionnaire every day online. Secondary outcomes were self-reported urgent care visits due to covid-19, number of covid-19 related symptoms, and change in self-rated health, all within 30-days’ follow-up.

Results

378 participants were assigned to the PEP flute self-care intervention (n=190) or usual care only (n=188). In the PEP self-care group, the median number of days with PEP flute use was 21 days (interquartile range 13-25). For the intention-to-treat population, a group difference was observed in changes from baseline in CAT scores of −1.2 points (95% confidence interval −2.1 to −0.2; P=0.017) in favour of the PEP flute self-care group. At day 30, the PEP flute self-care group also reported less chest tightness, less dyspnoea, more vigour, and higher level of daily activities, but these differences were small, and no consistent effects were seen on the secondary outcomes. No serious adverse events were reported.

Conclusions

In community dwelling adults with early covid-19, PEP flute self-care had a significant, yet marginal and uncertain clinical effect on respiratory symptom severity, as measured by CAT scores.

Trial registration

ClinicalTrials.gov
NCT04530435
.
Study protocol: establishment of a multicentre pre-eclampsia database and biobank in Sweden: GO PROVE and UP MOST, a prospective cohort study
Authors: Thorgeirsdottir Lilja , Andersson Malin , Karlsson Ove , Thörn Sven-Egron , Oras Jonatan , Sengpiel Verena , Svanvik Teresia , Elden Helen , Linden Karolina , Junus Katja , Lager Susanne , Enskär Ida , van Veen Teelkien , Wikström Johan , Björkman-Burtscher Isabella , Stigsdotter Neely Anna , Wikström Anna-Karin , Bergman Lina
Published: November 2021

Introduction

Pre-eclampsia, a multisystem disorder in pregnancy, is one of the most common causes of maternal morbidity and mortality worldwide. However, we lack methods for objective assessment of organ function in pre-eclampsia and predictors of organ impairment during and after pre-eclampsia. The women’s and their partners’ experiences of pre-eclampsia have not been studied in detail. To phenotype different subtypes of the disorder is of importance for prediction, prevention, surveillance, treatment and follow-up of pre-eclampsia.

The aim of this study is to set up a multicentre database and biobank for pre-eclampsia in order to contribute to a safer and more individualised treatment and care.

Methods and analysis

This is a multicentre cohort study. Prospectively recruited pregnant women ≥18 years, diagnosed with pre-eclampsia presenting at Sahlgrenska University Hospital, Uppsala University Hospital and at Södra Älvsborgs Hospital, Sweden, as well as normotensive controls are eligible for participation. At inclusion and at 1-year follow-up, the participants donate biosamples that are stored in a biobank and they are also asked to participate in various organ-specific evaluations. In addition, questionnaires and interviews regarding the women’s and partner’s experiences are distributed at follow-up.

Ethics and dissemination

By creating a database and biobank, we will provide the means to explore the disorder in a broader sense and allow clinical and laboratory discoveries that can be translated to clinical trials aiming at improved care of women with pre-eclampsia. Further, to evaluate experiences and the psychological impact of being affected by pre-eclampsia can improve the care of pregnant women and their partners. In case of incidental pathological findings during examinations performed, they will be handled in accordance with clinical routine. Data are stored in a secure online database. Biobank samples are identified through the women’s personal identification number and pseudonymised after identification in the biobank before analysis.

This study was approved by the regional ethical review board in Gothenburg on 28 December 2018 (approval number 955-18) and by the Swedish Ethical Review Authority on 27 February 2019 (approval number 2019-00309).

Results from the study will be published in international peer-reviewed journals.

Trial registration number

ISRCTN13060768
Positive Health dialogue tool and value-based healthcare: a qualitative exploratory study during residents’ outpatient consultations
Authors: Bock Lotte A , Noben Cindy Y G , Yaron Gili , George Erwin L J , Masclee Adrian A M , Essers Brigitte A B , Van Mook Walther N K A
Published: November 2021

Objective

To explore how residents experienced the application of the Positive Health dialogue tool (PH-tool) during outpatient consultations and its influence on the delivery of value-based healthcare (VBHC).

Design

Qualitative study using non-participant observations of outpatient consultations during which residents used the PH-tool, followed by longitudinal individual, semistructured interviews. To analyse the data from observations and interviews, observational form notes’ summarisation and categorisation, and an iterative-inductive thematic approach was used.

Participants

Eight residents—five from the ear, nose, and throat-department and three from the gastroenterology-hepatology-department—were selected through convenience sampling, accounting for 79 observations and 79 interviews.

Results

Residents had bivalent experiences with using the PH-tool. Residents discussed three main benefits: a gained insight into the individual patient’s context and functioning, a changed dynamics in resident–patient communication, and an increased awareness regarding value in terms of patient-related outcomes and healthcare costs. Three barriers became apparent: doubts regarding the PH-tool’s relevance and scope, boundaries of superspecialised medical professionals, and a lack of demarcation in clinical practice.

Conclusion

The PH-tool use can be beneficial for residents during outpatient consultations with new patients and follow-up in cases of multidimensional problems, particularly in cases of chronic conditions and generalist care. In these situations, the tool yielded valuable patient information beyond physical health, helped foster patient engagement, and enabled tailoring the treatment plan to individual patients’ needs. On the other hand, the PH-tool was not a good fit for simple problems, clearly demarcated help requests, periodic follow-up consultations, or verbose patients. In addition, it was not suitable for superspecialised care, because it yielded an abundance of general information. For particular patients and problems, using the PH-tool seems a promising strategy to increase VBHC delivery. Nevertheless, further research and detailing is needed to better align the PH-tool’s broad intent and clinical practice.
Abstracts from international emergency medicine journals
Authors: Production EMJ
Published: November 2021

Editor’s note: EMJ has partnered with the journals of multiple international emergency medicine societies to share from each a highlighted research study, as selected by their editors. This edition will feature an abstract from each publication.
Applications of the Columbus steerable guidewire
Authors: von Hessling Alexander , Reyes del Castillo Tomás , Lehmann Lutz , Roos Justus Erasmus , Karwacki Grzegorz
Published: November 2021

The Columbus steerable guidewire (Rapid Medical, Israel) is a 0.014 inch guidewire with a remotely controlled deflectable tip intended for neuronavigational purposes. 1 The tip can be shaped by pulling or pushing the handle. Pulling the handle decreases the radius (from 4 mm to 2 mm) and curves the tip, while pushing the handle increases the curvature radius and straightens the tip until it bends in the opposite direction. The amount of deflection is at the discretion of the operator. Video 1 The response of the Columbus guidewire to rotational movements is inferior to that of standard wires, and the tip is very soft and malleable but brings great support when bent. We present two cases where the Columbus guidewire was used. In the first case, the Columbus enabled us to probe a posterior cerebral artery arising from a giant basilar tip aneurysm without wall contact. In the second case, the Columbus was used as a secondary wire to help cannulate the pericallosal artery in a patient with a recurrent anterior complex aneurysm; this subsequently permitted successful stent-assisted coiling of the aneurysm.

Video 1

­
FLOWER-MI and the root of the problem with non-culprit revascularisation
Authors: Li Kam Wa Matthew E , De Silva Kalpa , Collet Carlos , Perera Divaka
Published: November 2021

How do we reduce cardiac death and myocardial infarction by percutaneous coronary intervention (PCI) in coronary heart disease? Although the interventional community continues to grapple with this question in stable angina, the benefits of PCI for non-culprit lesions found at ST-elevation myocardial infarction are established. Is it then wishful thinking that an index developed in stable coronary disease, for identifying lesions capable of causing ischaemia will show an incremental benefit over angiographically guided non-culprit PCI? This is the question posed by the recently published FLOW Evaluation to Guide Revascularization in Multi-vessel ST-elevation Myocardial Infarction (FLOWER-MI) trial. We examine the trial design and results; ask if there is any relationship between the baseline physiological significance of a non-culprit lesion and vulnerability to future myocardial infarction; and consider if more sophisticated methods can help guide or defer non-culprit revascularisation.
Role of anthropogenic drivers in altering the forest community structure in a prime tiger habitat in central India
Authors: Dasgupta Soumya , Bhattacharya Tapajit , Bhamburkar Prafulla , Kaul Rahul
Published: November 2021

Tropical forests are complex systems with heterogeneous community assemblages often threatened under anthropogenic disturbances and grazing. We studied the change in plant community composition and structure under a disturbance gradient in the tropical dry deciduous forest of the corridor area between Nagzira Wildlife Sanctuary and Navegaon National Park of central India. We tested the hypothesis that the plant community will change along the gradient of proximity to human settlements depending on the anthropogenic stress. We sampled 183 nested quadrat plots to collect data on species abundance and various disturbance parameters. Density, diversity, and importance value index were calculated, and multivariate analysis was performed to assess the changes in species assemblage along the disturbance gradients. We found 76% overall dissimilarity between the plant communities in the three distance classes perpetrated by the difference in mean abundance of species like Tectona grandis, Terminalia sp., and Largerstroemia parviflora. The anthropogenic factors influence the density and diversity of tree species and regeneration classes. We found the abundance of regeneration class increased along the distance from the villages. The study intensifies the need for proper management and conservative approach to preserve the diversity of the forest patches for their structural and functional contiguity as a corridor in central India’s highly susceptible and intricate corridor framework.
Three avatars of mock modularity
Authors: Dabholkar Atish , Putrov Pavel
Published: November 2021

Mock theta functions were introduced by Ramanujan in 1920 but a proper understanding of mock modularity has emerged only recently with the work of Zwegers in 2002. In these lectures, we describe three manifestations of this apparently exotic mathematics in three important physical contexts of holography, topology and duality where mock modularity has come to play an important role.
Weyl anomalies on conformal manifolds and moduli spaces
Authors: Niarchos Vasilis
Published: November 2021

A Weyl (conformal) anomaly signals a subtle quantum breaking of classical conformal invariance in conformal field theory. Over the years, Weyl anomalies have been used to characterize nonperturbative properties of conformal field theory. Anomalies associated with the energy–momentum tensor, like the coefficients [Formula: see text] and [Formula: see text] in four space–time dimensions, are generic and have been studied extensively. More generally, in even dimensions, there are also conformal anomalies associated with any primary operator that has integer scaling dimension. Some of the most interesting features of Weyl anomalies have to do with their behavior under continuous deformations or in vacua with spontaneously broken conformal symmetry. In this review, we summarize the defining properties of conformal anomalies, their classification into A- and B-type, and their implications on the structure of correlation functions. We point out that type-B anomalies can exhibit complicated dynamics and review recent progress in the study of this dynamics with special focus on four-dimensional [Formula: see text] superconformal field theories. We emphasize two applications of type-B anomalies in this context: potential constraints on the holonomy of superconformal manifolds and the deconstruction of anomalies in higher dimensions from anomalies in broken phases of lower-dimensional conformal field theories.
Parallelizing of the DBSCAN algorithm in the ClusterLogs framework
Authors: Zherdev Ivan , Zhukov Konstantin , Grigorieva Maria , Korobkov Sergey
Published: November 2021

ClusterLogs is a framework for the automatic categorization of computing jobs and resources by error messages in distributed computing systems. Initially, it was developed for high-energy physics experiments, but it can be applied in other areas. The first prototype of the framework was limited to sequential execution and did not allow the processing of a large amount of data in an acceptable time. In the next prototype, the system was significantly improved by the parallelization of several data preprocessing stages. In this paper, we focus on the parallelization of the DBSCAN algorithm, the main method used for clustering of the numeric vectors representing the error messages.
Quantization of open strings in time-dependent black holes
Authors: Marchioro Dáfni F. Z. , Nedel Daniel L.
Published: November 2021

In this paper, the open string is quantized in a time-dependent black hole background. By time-dependent black hole, one means a Vaydia geometry in the adiabatic approximation, which in [Formula: see text] dimensions is a BTZ black hole with a time-dependent mass. The worldsheet two-point function is derived and it is shown to have the same type of singularity as the flat space one. However, the equal times two-point function depends on the particular Cauchy surface where the worldsheet fields are defined. Finite temperature effects are incorporated through the Liouville–von Neumann approach to nonequilibrium thermodynamics.
UV, FL and IR spectroscopic analysis of N-confused meso-tetra(methoxyphenyl)porphyrins
Authors: Peng Su-Hong , Wang Li-Li , Cai Sha-Sha , Xiao Hui-Qing , Zhao Xin-Tong , Wang Hui , Liu Hai-Yang
Published: November 2021

UV, FL and IR spectra of isomer A (in DCM) and isomer B (in DMAc) of N-confused 5,10,15,20-tetra([Formula: see text]-methoxyphenyl)porphyrin ([Formula: see text]-isomer, 1), N-confused 5,10,15,20-tetra([Formula: see text]-methoxyphenyl)porphyrin ([Formula: see text]-isomer, 2) and N-confused 5,10,15,20-tetra([Formula: see text]-methoxyphenyl)porphyrin ([Formula: see text]-isomer, 3) were investigated. Significant red shifts are observed from [Formula: see text]-isomer (1) to [Formula: see text]-isomer (3) in UV-vis absorption and fluorescence spectra. The fluorescence lifetime ([Formula: see text] of isomer A and isomer B of the samples (1, 2 and 3) are ca. 1.39[Formula: see text]1.79 ns and 1.68[Formula: see text]2.09 ns, respectively. In addition, the order of fluorescence quantum yield for isomer A is 1 >2 > 3, but for isomer B it is 1 < 3 <2. The isomer B of 2shows the strongest emission in accord with the strongest absorption. The isomer A of 1shows the strongest emission with the fluorescence quantum yield of 0.045, which is nearly double that of 3. The introduction of the methoxy group at the orthoposition increases steric hindrance, the molecular rigidity and the flow of [Formula: see text]-electron, thereby favourable to the fluorescence enhancement. The IR absorption peaks of 1, 2 and 3 were investigated and empirically assigned. The effects of the position of the substituents on the absorption frequency were also discussed. The absorption frequency of the C=C phenyl stretching in plane changed obviously by conjugative effect and steric effect when the methoxy group was at the orthoormetaposition in comparison with paraposition.
Coefficient inequalities for new subclasses of bi-univalent functions defined by using the function fδ
Authors: Sağsöz Fatma , Orhan Halit
Published: November 2021

In this investigation, we introduce and study two new subclasses of bi-univalent functions defined by using the function [Formula: see text] and Salagean differential operator. Furthermore, we find estimates on the coefficients [Formula: see text] and [Formula: see text] for these function classes.
Development of algorithm simulating spatial fold change of cell signaling for pattern formation in zebrafish
Authors: Gonen Bilal , Bheemanathini Sai Nikhil
Published: November 2021

Embryos develop robust spatiotemporal patterns by encoding and interpreting biological signals in real time. Developmental patterns often scale with body or tissue size even when total cell number, cell size or growth rate are changed. A striking example of patterning is the segmentation of somites — the precursors of vertebral column. Despite decade-long efforts, how positional information for segmentation is encoded by cell signaling remained elusive. To address this fundamental question, we studied a novel zebrafish tail explant model that recapitulated the scaling of somite sizes with the length of unsegmented tissue in growing intact embryos. This paper provides an algorithm written in MATLAB as well as Python and finally finding a way to write an efficient algorithm to be able to answer the question described above. Information encoding by spatial fold-change of cell signaling is a remarkable strategy that could be utilized for engineering precisely patterned tissues or organs. We also discuss the limitations of simulations performed using MATLAB with performance decreasing with the large data sets. So, we tried to analyze the factors that impacted the performance of the algorithm. Finally, we tried to answer questions regarding the language selection in which a simulation method can be written efficiently.
GEOPOLITICAL RISKS AND THE HIGH-FREQUENCY MOVEMENTS OF THE US TERM STRUCTURE OF INTEREST RATES
Authors: GUPTA RANGAN , MAJUMDAR ANANDAMAYEE , NEL JACOBUS , SUBRAMANIAM SOWMYA
Published: November 2021

We use daily data for the period 25th November 1985 to 10th March 2020 to analyze the impact of newspapers-based measures of geopolitical risks (GPRs) on United States (US) Treasury securities by considering the level, slope and curvature factors derived from the term structure of interest rates of maturities covering 1 to 30 years. No evidence of predictability of the overall GPRs (or for threats and acts) is detected using linear causality tests. However, evidence of structural breaks and nonlinearity is provided by statistical tests performed on the linear model, which indicates that the Granger causality cannot be relied upon, as they are based on a misspecified framework. As a result, we use a data-driven approach, specifically a nonparametric causality-in-quantiles test, which is robust to misspecification due to regime changes and nonlinearity, to reconsider the predictive ability of the overall and decomposed GPRs on the three latent factors. Moreover, the zero lower bound situation, visible in our sample period, is captured by the lower quantiles, as this framework allows us to capture the entire conditional distribution of the three factors. Using this robust model, we find overwhelming evidence of causality from the GPRs, with relatively stronger effects from threats than acts, for the entire conditional distribution of the three factors, with higher impacts on medium- and long-run maturities, i.e., curvature and level factors, suggesting the predictability of the entire US term structure based on information contained in GPRs. Our results have important implications for academics, investors and policymakers.
Detecting and Analyzing Collusive Entities on YouTube
Authors: Dutta Hridoy Sankar , Jobanputra Mayank , Negi Himani , Chakraborty Tanmoy
Published: November 2021

YouTube sells advertisements on the posted videos, which in turn enables the content creators to monetize their videos. As an unintended consequence, this has proliferated various illegal activities such as artificial boosting of views, likes, comments, and subscriptions. We refer to such
videos
(gaining likes and comments artificially) and
channels
(gaining subscriptions artificially) as “collusive entities.” Detecting such collusive entities is an important yet challenging task. Existing solutions mostly deal with the problem of spotting fake views, spam comments, fake content, and so on, and oftentimes ignore how such fake activities emerge via collusion. Here, we collect a large dataset consisting of two types of collusive entities on YouTube—
videos
submitted to gain collusive likes and comment requests and
channels
submitted to gain collusive subscriptions.

We begin by providing an in-depth analysis of collusive entities on YouTube fostered by various
blackmarket services
. Following this, we propose models to detect three types of collusive YouTube entities: videos seeking collusive likes, channels seeking collusive subscriptions, and videos seeking collusive comments. The third type of entity is associated with temporal information. To detect videos and channels for collusive likes and subscriptions, respectively, we utilize one-class classifiers trained on our curated collusive entities and a set of novel features. The SVM-based model shows significant performance with a true positive rate of 0.911 and 0.910 for detecting collusive videos and collusive channels, respectively. To detect videos seeking collusive comments, we propose
CollATe
, a novel end-to-end neural architecture that leverages time-series information of posted comments along with static metadata of videos.
CollATe
is composed of three components: metadata feature extractor (which derives metadata-based features from videos), anomaly feature extractor (which utilizes the time-series data to detect sudden changes in the commenting activity), and comment feature extractor (which utilizes the text of the comments posted during collusion and computes a similarity score between the comments). Extensive experiments show the effectiveness of
CollATe
 (with a true positive rate of 0.905) over the baselines.
Casein from Bovine Milk as a Binder for Silicon Based Electrodes
Authors: Chandrasiri K. W. D. Kaveendi , Jayawardana M D. Chamithri D. , Abeywardana Maheeka Yapa , Kim Jongjung , Lucht Brett L.
Published: November 2021

Silicon is a promising anode material for lithium ion batteries due to the high theoretical capacity (∼3600mAh/g). However, silicon-based electrodes face rapid degradation due to the extensive volume variation (∼300%) during the lithiation/delithiation process. Binders used in the electrode fabrication play a crucial role for silicon electrodes since it can reduce the mechanical fracture during the cycling process. Recent investigations suggest that in addition to the importance of the mechanical properties of the binder, the chemical reactions between the binder and the surface of the silicon particles also contribute to stabilization. Further investigations suggest that functionalized small molecules can also modify the surface of silicon particles and stabilize cycling. An inexpensive, environmentally friendly alternative has been investigated as a binder for silicon electrodes. Casein is a milk protein found in bovine milk rich in amine groups and carboxylic acid groups which can form bonds with the silanol groups in silicon. A comparative study conducted between PVDF and Casein as binders have shown that when casein was used as binder, it shows better performance compared to PVDF. Surface morphology and solid electrolyte interphase (SEI) was analyzed using electron microscopy techniques and spectroscopic methods and the results will be discussed.
The Use of Stemming in the Arabic Text and Its Impact on the Accuracy of Classification
Authors: Atwan Jaffar , Wedyan Mohammad , Bsoul Qusay , Hammadeen Ahmad , Alturki Ryan
Published: November 2021

The ongoing growth in the vast amount of digital documents and other data in the Arabic language available online has increased the need for classification methods that can deal with the complex nature of such data. The classification of Arabic plays a large and important role in many modern applications and interferes with other sciences, which start from search engines and do not end with the Internet of Things. However, addressing the Arab classification errors with high performance is largely insufficient to deal with the huge quantities to reveal the classification of Arab documents; while some work was tackled out on the classification of the Arabic text, most of the research has focused on English text. The methods proposed for English are not suitable for Arabic as the morphology of the two languages differs substantially. Moreover, morphologically, the preprocessing of Arabic text is a particularly challenging task. In this study, three commonly used classification algorithms, namely, the K-nearest neighbor, Naïve Bayes, and decision tree, were implemented for Arabic text in order to assess their effectiveness with and without the use of a light stemmer in the preprocessing phase. In the experiment, a dataset from Agency France Persse (AFP) Arabic Newswire 2001 consisting of four categories and 800 files was classified using the three classifiers. The result showed that the decision tree with light stemmer had the best accuracy rate for classification algorithm with 93%.
Comorbidities and Environmental Factors Associated with Atopic Dermatitis in Children and Adults in Dermatology-Venereology in Cotonou, Benin
Authors: Dégboé Bérénice , Atadokpèdé Félix , Nguessie Christabelle , Kouassi Alida , Elégbédé Nadège , Maffo Nina , Akpadjan Fabrice , Adégbidi Hugues
Published: November 2021

Introduction. The objective of this work was to document the comorbidities and environmental factors associated with atopic dermatitis (AD) in dermatology Venereology in Cotonou. Methods. A cross-sectional, prospective, and analytical study included, from January 2016 to December 2018, in the Dermatology-Venereology Department of the National Teaching Hospital Hubert Koutoukou Maga (CNHU-HKM) of Cotonou, children and adults after free and informed consent, in whom the diagnosis of AD was retained according to the criteria of the United Kingdom Working Party. Severity was assessed using SCORAD (severity scoring of atopic dermatitis). Results. The overall prevalence of AD was 7.7%. AD was more frequent in children (56.8% and 40.6%) and adults (59.8% and 37.4%) from urban and periurban areas (0.003 < 

p
<
0.034

). It was more frequent in children who regularly dewormed and those with complete vaccination (0.001 < 

p
<
0.01

). In 54.8% of children and 58.9% of adults, flare-ups occurred during the warm season. The main associated comorbidities were rhinitis and conjunctivitis in both children (49.7% and 36.1%, respectively) and adults (32.7% and 26.2%, respectively). The main triggering factors in children were heat (43.2%), pneumallergens (28.4%), and skin irritants (22.6%). In adults, we noted skin irritants (58.9%), heat (47.7%), and psychological factors (34.6%). In adults, the use of detergent soaps was associated with lichenified and severe AD (0.003 < 

p
<
0.006

) and that of lightening soaps with acute AD (

p
=
0.042

). Conclusion. AD in the Dermatology-Venereology Department of the CNHU-HKM of Cotonou was associated with comorbidities. It was influenced by environmental factors related to the tropical climate and by skin irritants or allergens.
Green Synthesis of Gold and Iron Nanoparticles for Targeted Delivery: An In Vitro and In Vivo Study
Authors: Khanzada Beenish , Akthar Nosheen , Bhatti Muhammad Zeeshan , Ismail Hammad , Alqarni Mohammed , Mirza Bushra , Mostafa-Hedeab Gomaa , Batiha Gaber El-Saber
Published: November 2021

Nanotechnology has vast applications in almost all fields of science and technology. The use of medicinal plants for the synthesis of metallic nanoparticles has gained much attention nowadays. In the current research work, six medicinal plants were used for the synthesis of gold nanoparticles (AuNPs) and iron nanoparticles (FeNPs). The synthesized nanoparticles were characterized by different techniques including UV-visible spectrophotometry, scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR). Furthermore, the activities of green synthesized nanoparticles were screened in vitro using, for example, antibacterial, antioxidant, cytotoxic, and DNA protection assays. Both FeNPs and AuNPs had spherical shapes with an average size less than 50 nm and were found to have good antimicrobial and nontoxic effects. Furthermore, FeNPs from Ficus microcarpa demonstrated high drug loading efficiency (65%) as compared to an anti-inflammatory drug (diclofenac potassium, DFP). We also evaluated the drug delivery potential, as well as anti-inflammatory and anticoagulant properties, of nanoparticles in vivo. Interestingly, AuNPs of Syzygium cumini exhibited strong anti-inflammatory potential as compared to DFP and diclofenac-loaded FeNPs of Ficus microcarpa. The results suggest potential pharmacological applications of biogenic synthesized AuNPs and FeNPs which can be explored further. The study revealed that the green synthesized AuNPs and FeNPs provide a promising approach for the synthesis of drug-loaded nanoparticles and consequently in the field of targeted drug delivery.
Analysis of Students’ Behavior in English Online Education Based on Data Mining
Authors: Wang Chunxia
Published: November 2021

With the formation of global economic integration for better exchange and cooperation with nations around the world, mastering English is extremely essential. In the context of today’s big era with a variety of English learning methods, it is required that data mining be applied to online English education. Owing to the continuous application of data mining techniques and the improvement of the online learning system, its application in education is also more and more prevalent. In the face of a large amount of learning data and student behavior data, the traditional methods have the problems of low processing efficiency, more memory requirements, and large prediction error. Therefore, this paper proposes a student behavior analysis method of online English education based on data mining. The student behavior data is collected, and an online English education learning behavior model is established. The data mining model is built to filter the obtained behavior data through data preparation, data statistics, and analysis. Furthermore, the apriori algorithm is used to mine association rules and calculate the similarity of data followed by the application of a fuzzy neural network to mine the behavior data of English online education students. The experimental results show that this method has high data processing efficiency, takes up less space, and produces a low prediction error.
Comparison of Phase Estimation Methods for Quantitative Susceptibility Mapping Using a Rotating-Tube Phantom
Authors: Keenan Kathryn E. , Berman Ben P. , Rýger Slávka , Russek Stephen E. , Wang Wen-Tung , Butman John A. , Pham Dzung L. , Dagher Joseph
Published: November 2021

Quantitative Susceptibility Mapping (QSM) is an MRI tool with the potential to reveal pathological changes from magnetic susceptibility measurements. Before phase data can be used to recover susceptibility (

Δ
χ

), the QSM process begins with two steps: data acquisition and phase estimation. We assess the performance of these steps, when applied without user intervention, on several variations of a phantom imaging task. We used a rotating-tube phantom with five tubes ranging from

Δ
χ
=
0.05

ppm to

Δ
χ
=
0.336

 ppm. MRI data was acquired at nine angles of rotation for four different pulse sequences. The images were processed by 10 phase estimation algorithms including Laplacian, region-growing, branch-cut, temporal unwrapping, and maximum-likelihood methods, resulting in approximately 90 different combinations of data acquisition and phase estimation methods. We analyzed errors between measured and expected phases using the probability mass function and Cumulative Distribution Function. Repeatable acquisition and estimation methods were identified based on the probability of relative phase errors. For single-echo GRE and segmented EPI sequences, a region-growing method was most reliable with Pr (relative error <0.1) = 0.95 and 0.90, respectively. For multiecho sequences, a maximum-likelihood method was most reliable with Pr (relative error <0.1) = 0.97. The most repeatable multiecho methods outperformed the most repeatable single-echo methods. We found a wide range of repeatability and reproducibility for off-the-shelf MRI acquisition and phase estimation approaches, and this variability may prevent the techniques from being widely integrated in clinical workflows. The error was dominated in many cases by spatially discontinuous phase unwrapping errors. Any postprocessing applied on erroneous phase estimates, such as QSM’s background field removal and dipole inversion, would suffer from error propagation. Our paradigm identifies methods that yield consistent and accurate phase estimates that would ultimately yield consistent and accurate

Δ
χ

estimates.
A Modified Slime Mould Algorithm for Global Optimization
Authors: Tang An-Di , Tang Shang-Qin , Han Tong , Zhou Huan , Xie Lei
Published: November 2021

Slime mould algorithm (SMA) is a population‐based metaheuristic algorithm inspired by the phenomenon of slime mould oscillation. The SMA is competitive compared to other algorithms but still suffers from the disadvantages of unbalanced exploitation and exploration and is easy to fall into local optima. To address these shortcomings, an improved variant of SMA named MSMA is proposed in this paper. Firstly, a chaotic opposition‐based learning strategy is used to enhance population diversity. Secondly, two adaptive parameter control strategies are proposed to balance exploitation and exploration. Finally, a spiral search strategy is used to help SMA get rid of local optimum. The superiority of MSMA is verified in 13 multidimensional test functions and 10 fixed‐dimensional test functions. In addition, two engineering optimization problems are used to verify the potential of MSMA to solve real‐world optimization problems. The simulation results show that the proposed MSMA outperforms other comparative algorithms in terms of convergence accuracy, convergence speed, and stability.
Orthogonally Biadditive Operators
Authors: Dzhusoeva Nonna , Kulaev Ruslan , Pliev Marat
Published: November 2021

In this article, we introduce and study a new class of operators defined on a Cartesian product of ideal spaces of measurable functions. We use the general approach of the theory of vector lattices. We say that an operator

T
:
E
×
F
⟶
W

defined on a Cartesian product of vector lattices

E

and

F

and taking values in a vector lattice

W

is orthogonally biadditive if all partial operators

T

y

:
E
⟶
W

and

T

x

:
F
⟶
W

are orthogonally additive. In the first part of the article, we prove that, under some mild conditions, a vector space of all regular orthogonally biadditive operators

O
B

A

r

E
,
F
;
W

is a Dedekind complete vector lattice. We show that the set of all horizontally-to-order continuous regular orthogonally biadditive operators is a projection band in

O
B

A

r

E
,
F
;
W

. In the last section of the paper, we investigate orthogonally biadditive operators on a Cartesian product of ideal spaces of measurable functions. We show that an integral Uryson operator which depends on two functional variables is orthogonally biadditive and obtain a criterion of the regularity of an orthogonally biadditive Uryson operator.
The Immunomodulatory Effects of Phellodendri Cortex Polysaccharides on Cyclophosphamide-Induced Immunosuppression in Mice
Authors: Cheng Yi , Liu Lu , Mo Simei , Gao Jianxiong , Zhang Hongjian , Zhang Heli , Zhang Chunsheng , Song Xu , Li Lixia , Geng Zhe
Published: November 2021

Cyclophosphamide is a commonly used anticancer drug, and immunosuppression is one of the most common side effects. How to recover the immunological function is important for cyclophosphamide-treated patients. In the present study, Phellodendri Cortex polysaccharides (CPP) could enhance the proliferation of mouse spleen lymphocytes in vitro. The immunoregulatory function of CPP was then investigated in cyclophosphamide-induced immunosuppressed mice. In CPP-treated groups, mice were orally treated with CPP at doses of 1, 0.5, and 0.25 g/kg bodyweight from 1 to 11 d, respectively. The cyclophosphamide was administrated in CPP and cyclophosphamide groups from 12 to 14 d. In the cyclophosphamide and normal control groups, the mice received equal volume of saline from 1 to 14 d. The results showed that CPP (1 g/kg) could significantly increase the bodyweight of mice, even during cyclophosphamide treatment. The organ coefficients of the spleen and thymus were recovered by CPP treatment. CPP upregulated the contents of cytokines (IL-2, IL-6, IFN-γ, and TNF-α) in serum, which were downregulated by cyclophosphamide. The mRNA levels of these cytokines were also elevated by CPP treatment in the spleen. Cyclophosphamide upregulated the expressions of NF-κB p65, TLR4, and MyD88, suggesting that the NF-κB signaling pathway was activated by cyclophosphamide. After CPP treatment, it was recovered to normal level. These results indicated that CPP alleviated the cyclophosphamide-induced immunosuppression.
Racial and Socioeconomic Disparities in Out-Of-Hospital Cardiac Arrest Outcomes: Artificial Intelligence-Augmented Propensity Score and Geospatial Cohort Analysis of 3,952 Patients
Authors: Monlezun Dominique J. , Samura Alfred T. , Patel Ritesh S. , Thannoun Tariq E. , Balan Prakash
Published: November 2021

Introduction. Social disparities in out-of-hospital cardiac arrest (OHCA) outcomes are preventable, costly, and unjust. We sought to perform the first large artificial intelligence- (AI-) guided statistical and geographic information system (GIS) analysis of a multiyear and multisite cohort for OHCA outcomes (incidence and poor neurological disposition). Method. We conducted a retrospective cohort analysis of a prospectively collected multicenter dataset of adult patients who sequentially presented to Houston metro area hospitals from 01/01/07-01/01/16. Then AI-based machine learning (backward propagation neural network) augmented multivariable regression and GIS heat mapping were performed. Results. Of 3,952 OHCA patients across 38 hospitals, African Americans were the most likely to suffer OHCA despite representing a significantly lower percentage of the population (42.6 versus 22.8%;

p
<
0.001

). Compared to Caucasians, they were significantly more likely to have poor neurological disposition (OR 2.21, 95%CI 1.25–3.92;

p
=
0.006

) and be discharged to a facility instead of home (OR 1.39, 95%CI 1.05–1.85;

p
=
0.023

). Compared to the safety net hospital system primarily serving poorer African Americans, the university hospital serving primarily higher income commercially and Medicare insured patients had the lowest odds of death (OR 0.45,

p
<
0.001

). Each additional $10,000 above median household income was associated with a decrease in the total number of cardiac arrests per zip code by 2.86 (95%CI -4.26- -1.46;

p
<
0.001

); zip codes with a median income above $54,600 versus the federal poverty level had 14.62 fewer arrests (

p
<
0.001

). GIS maps showed convergence of the greater density of poor neurologic outcome cases and greater density of poorer African American residences. Conclusion. This large, longitudinal AI-guided analysis statistically and geographically identifies racial and socioeconomic disparities in OHCA outcomes in a way that may allow targeted medical and public health coordinated efforts to improve clinical, cost, and social equity outcomes.
COVID-19 and Pneumonia Diagnosis in X-Ray Images Using Convolutional Neural Networks
Authors: Abiyev Rahib H. , Ismail Abdullahi
Published: November 2021

This paper proposes a Convolutional Neural Networks (CNN) based model for the diagnosis of COVID-19 and non-COVID-19 viral pneumonia diseases. These diseases affect and damage the human lungs. Early diagnosis of patients infected by the virus can help save the patient’s life and prevent the further spread of the virus. The CNN model is used to help in the early diagnosis of the virus using chest X-ray images, as it is one of the fastest and most cost-effective ways of diagnosing the disease. We proposed two convolutional neural networks (CNN) models, which were trained using two different datasets. The first model was trained for binary classification with one of the datasets that only included pneumonia cases and normal chest X-ray images. The second model made use of the knowledge learned by the first model using transfer learning and trained for 3 class classifications on COVID-19, pneumonia, and normal cases based on the second dataset that included chest X-ray (CXR) images. The effect of transfer learning on model constriction has been demonstrated. The model gave promising results in terms of accuracy, recall, precision, and F1_score with values of 98.3%, 97.9%, 98.3%, and 98.0%, respectively, on the test data. The proposed model can diagnose the presence of COVID-19 in CXR images; hence, it will help radiologists make diagnoses easily and more accurately.
On a Diophantine Inequality with
s
Primes
Authors: Yan Xiaofei , Zhang Lu
Published: November 2021

Let

2
<
c
<
δ

. In this study, for prime numbers

p

1

,
…
,

p

s

and a sufficiently large real number

N

, we prove the Diophantine inequality

p
1
c

+
⋯
+

p
s
c

−
N

<

N

−

9
/

10
c

δ
−
c

, where

δ
=

294
−
210
s

/

123
−
97
s

and

s
≥
5

. When

s
=
5

, this result improves a previous result.