bluuebunny/crossref_metadata_2025_split huggingface dataset:
Maroons: Blackgirlhood in Plain Sight
Authors: Dill LeConté J. 
Published: May 2022

AbstractHistorically and globally, Black people have engaged in practices of maroonage to resist bondage and re‐make free homes and communities. In this article, I offer maroons as a keyword and assert that Blackgirls are present‐day maroons in plain sight who resist structural bondage and re‐make practices of survivance in the pursuit of freedoms on an everyday basis. Through the article, I share and analyze ethnographic data as well as poetry and lyrics written by Blackgirls and womxn who enact their/our resistance and maroonage in plain sight.
Yogurt fortification by microencapsulation of beetroot extract (Beta vulgaris L.) using maltodextrin, gum arabic, and whey protein isolate
Authors: Yousefi Shima , Kavyanirad Mohammad , Aminifar Mehrnaz , Weisany Weria , Mousavi Khaneghah Amin 
Published: May 2022

AbstractThe effect of three different coating materials, including maltodextrin (MD, 9.95–20.05%), gum arabic (GA, 4.98–10.02%), and whey protein isolate (WPI, 4.95–15.05%), was optimized in order to produce high‐quality beetroot extract powder (BEP) using response surface modeling (RSM). Beetroot extract (BE) was encapsulated using MD, GA, and WPI by implementing a spray‐drying method. The highest total phenolic content (TPC) was obtained at 15% MD, 7.5% GA, and 10% WPI. The same results were achieved for antioxidant activity. Increasing the MD and GA contents resulted in reducing the moisture adsorption of microencapsulated BEP.
Physical, Psychological and Social Secondary Consequences of the COVID‐19 Pandemic in Turkish University Students
Authors: Örgev Cemil , Kınalı Gülşah 
Published: May 2022

AbstractThis study aims to investigate the effect of the COVID‐19 pandemic on university students and their families. A total of 274 students participated in this study. A questionnaire is developed regarding the physical, psychological, and social effects of the COVID‐19 pandemic, and sent to the students via e‐mail. According to the results of the study, students who contracted COVID‐19 experienced significantly higher musculoskeletal pain (MSP) (p = 0.01). Students with increased propensity for harmful habits experienced significantly more MSP (p = 0.01). Anxiety levels of students who experienced MSP were significantly higher (p = 0.01). Students living in an inadequate home environment were significantly more prone to harmful habits (p = 0.01). The anxiety level of the students who experienced domestic unrest was high (p = 0.02). The home environment of students with economic difficulties was significantly inadequate (p = 0.01). The anxiety levels of the students whose participation in sports and art activities decreased, were high (p = 0.04). The home environment of the students who reported that they were positively affected by distance education was significantly inadequate (p = 0.03). The authors suggest that physiotherapy, nutrition and psychological assistance services should be provided to students, scholarship opportunities and extracurricular activities (art and sports activities) should be increased.
Amplifying Lateral Flow Assay Signals for Rapid Detection of COVID‐19 Specific Antibodies
Authors: Alhabbab Rowa Y. , Alfaleh Mohamed A. , Alsulaiman Reem M. , Alamri Sawsan S. , Eyouni Mais S. , ElAssouli M‐Zaki , Abuzenadah Adel M. , Hashem Anwar M. 
Published: May 2022

AbstractRapid lateral flow immune‐assays are point‐of‐care diagnostic tools that are easy to use, cheap, and do not need centralized infrastructure. Therefore, these devices are appealing for rapid detection of the humoral immune responses to infections, particularly severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). The novel technique introduced here uses a complex of anti‐SARS‐CoV‐2 N‐protein antibodies conjugated to gold nanoparticles that are bound to five SARS‐CoV‐2 N protein conjugated to gold nanoparticles to amplify the signals obtained from the conjugated SARS‐CoV‐2 N protein and to enhance the assay detection limit. To validate the performance of the adopted lateral flow, serum from SARS‐CoV‐2 seropositive individuals and prepandamic negative samples are tested and compared to a validated enzyme‐linked immunosorbent assay (ELISA) for the detection of SARS‐CoV‐2 N protein specific IgG and IgM antibodies. The data shows that the designed lateral flow assay has an excellent sensitivity and specificity upon detecting IgM and IgG antibodies by applying only 2 µL from the serum sample to the adopted strips. Taken together, the developed lateral flow immunoassay assay provides a rapid, specific, and highly sensitive means to detect the immune responses against SARS‐CoV‐2 with only 2 µL from the serum sample.
Uncovering shape signatures of resting‐state functional connectivity by geometric deep learning on Riemannian manifold
Authors: Dan Tingting , Huang Zhuobin , Cai Hongmin , Lyday Robert G. , Laurienti Paul J. , Wu Guorong 
Published: May 2022

AbstractFunctional neural activities manifest geometric patterns, as evidenced by the evolving network topology of functional connectivities (FC) even in the resting state. In this work, we propose a novel manifold‐based geometric neural network for functional brain networks (called “Geo‐Net4Net” for short) to learn the intrinsic low‐dimensional feature representations of resting‐state brain networks on the Riemannian manifold. This tool allows us to answer the scientific question of how the spontaneous fluctuation of FC supports behavior and cognition. We deploy a set of positive maps and rectified linear unit (ReLU) layers to uncover the intrinsic low‐dimensional feature representations of functional brain networks on the Riemannian manifold taking advantage of the symmetric positive‐definite (SPD) form of the correlation matrices. Due to the lack of well‐defined ground truth in the resting state, existing learning‐based methods are limited to unsupervised methodologies. To go beyond this boundary, we propose to self‐supervise the feature representation learning of resting‐state functional networks by leveraging the task‐based counterparts occurring before and after the underlying resting state. With this extra heuristic, our Geo‐Net4Net allows us to establish a more reasonable understanding of resting‐state FCs by capturing the geometric patterns (aka. spectral/shape signature) associated with resting states on the Riemannian manifold. We have conducted extensive experiments on both simulated data and task‐based functional resonance magnetic imaging (fMRI) data from the Human Connectome Project (HCP) database, where our Geo‐Net4Net not only achieves more accurate change detection results than other state‐of‐the‐art counterpart methods but also yields ubiquitous geometric patterns that manifest putative insights into brain function.
Numerical investigation of MHD flow of Williamson nanofluid with variable viscosity pasting a wedge within porous media: A non‐Darcy model approach
Authors: Mishra Pankaj , Kumar Dhirendra , Dharmendar Reddy Y. , Shankar Goud B. 
Published: May 2022

AbstractThe present analysis is done for the investigation of the effect of various physical parameters on magnetohydrodynamic Williamson nanofluid boundary layer flow past a wedge through porous media taking a non‐Darcy–Falkner–Skan model with consideration of varying wall temperature, variable viscosity, the effect of Brownian motion, and thermophoresis in the presence of heat source. The corresponding governing equations under the appropriate boundary conditions are first converted into ordinary differential equations (ODEs) in view of similarity transformations. Application of shooting method has been made to deal with these ODEs, and the effects of various parameters on nondimensional velocity, temperature, and concentration are investigated through graphs. Also, the effects of various parameters on surface skin friction, heat, and mass transfer rates are analyzed and are shown in Table 3. It has been noticed that heat and mass transfer rates are enhanced with variable viscosity coefficient and reduced with Brownian motion and thermophoresis parameters. As a significant outcome, the skin friction is found to be increased with increasing values of the Williamson parameter while it is found to be decreased with increasing value of variable viscosity coefficient. At last, validation of the current findings is attended to after comparing with similar results obtained earlier.
Representation of hydrological processes in a rural lowland catchment in Northern Germany usingSWATandSWAT+
Authors: Wagner Paul D. , Bieger Katrin , Arnold Jeffrey G. , Fohrer Nicola 
Published: May 2022

AbstractThe latest version of the Soil and Water Assessment Tool (SWAT+) features several improvements compared with previous versions of the model, for example, the definition of landscape units that allow for a better representation of spatio‐temporal dynamics. To evaluate the new model capabilities in lowland catchments characterized by near‐surface groundwater tables and extensive tile drainage, we assess the performance of two SWAT+ model setups in comparison to a setup based on a previous SWAT model version (SWAT3Swith a modified three groundwater storage model) in the Kielstau catchment in Northern Germany. The Kielstau catchment has an area of about 50 km2, is dominated by agricultural land use, and has been thoroughly monitored since 2005. In both SWAT+ setups, the catchment is divided into upland areas and floodplains, but in the first SWAT+ model setup, runoff from the hydrologic response units is summed up at landscape unit level and added directly to the stream. In the second SWAT+ model setup, runoff is routed across the landscape before it reaches the streams. Model results are compared with regard to (i) model performance for stream flow at the outlet of the catchment and (ii) aggregated as well as temporally and spatially distributed water balance components. All three model setups show a very good performance at the catchment outlet. In comparison to a previous version of the SWAT model that produced more groundwater flow, the SWAT+ model produced more tile drainage flow and surface runoff. Results from the new SWAT+ model confirm that the representation of routing processes from uplands to floodplains in the model further improved the representation of hydrological processes. Particularly, the stronger spatial heterogeneity that can be related to characteristics of the landscape, is very promising for a better understanding and model representation of hydrological fluxes in lowland areas. The outcomes of this study are expected to further prove the applicability of SWAT+ and provide useful information for future model development.
Precision health diagnostic and surveillance network uses S gene target failure (SGTF) combined with sequencing technologies to track emerging SARS‐CoV‐2 variants
Authors: Guerrero‐Preston Rafael , Rivera‐Amill Vanessa , Caraballo Karem , Rodríguez‐Torres Sebastian , Purcell‐Wiltz Ana , García Andrea A. , Torres Raphael S. , Zamuner Fernando T. , Zanettini Claudio , MacKay Matthew J. , Baits Rachel , Salgado Daisy , Khullar Gaurav , Metti Jessica , Baker Timothy , Dudley Joel , Vale Keilyn , Pérez Gabriela , De Jesús Lorena , Miranda Yaima , Ortiz Denise , García‐Negrón Amanda , Viera Liliana , Ortiz Alberto , Canabal Jorge A. , Romaguera Josefina , Jiménez‐Velázquez Ivonne , Marchionni Luigi , Rodríguez‐Orengo José F. , Baez Adriana , Mason Christopher E. , Sidransky David 
Published: May 2022

AbstractIntroductionThe severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) pandemic revealed a worldwide lack of effective molecular surveillance networks at local, state, and national levels, which are essential to identify, monitor, and limit viral community spread. SARS‐CoV‐2 variants of concern (VOCs) such as Alpha and Omicron, which show increased transmissibility and immune evasion, rapidly became dominant VOCs worldwide. Our objective was to develop an evidenced‐based genomic surveillance algorithm, combining reverse transcription polymerase chain reaction (RT‐PCR) and sequencing technologies to quickly identify highly contagious VOCs, before cases accumulate exponentially.MethodsDeidentified data were obtained from 508,969 patients tested for coronavirus disease 2019 (COVID‐19) with the TaqPath COVID‐19 RT‐PCR Combo Kit (ThermoFisher) in four CLIA‐certified clinical laboratories in Puerto Rico (n = 86,639) and in three CLIA‐certified clinical laboratories in the United States (n = 422,330).ResultsTaqPath data revealed a frequency of S Gene Target Failure (SGTF) > 47% for the last week of March 2021 in both, Puerto Rico and US laboratories. The monthly frequency of SGTF in Puerto Rico steadily increased exponentially from 4% in November 2020 to 47% in March 2021. The weekly SGTF rate in US samples was high (>8%) from late December to early January and then also increased exponentially through April (48%). The exponential increase in SGFT prevalence in Puerto Rico was concurrent with a sharp increase in VOCs among all SARS‐CoV‐2 sequences from Puerto Rico uploaded to Global Influenza Surveillance and Response System (GISAID) (n = 461). Alpha variant frequency increased from <1% in the last week of January 2021 to 51.5% of viral sequences from Puerto Rico collected in the last week of March 2021.ConclusionsAccording to the proposed evidence‐based algorithm, approximately 50% of all SGTF patients should be managed with VOCs self‐quarantine and contact tracing protocols, while WGS confirms their lineage in genomic surveillance laboratories. Our results suggest this workflow is useful for tracking VOCs with SGTF.
Reactive oxygen species generated by infrared laser light in optical tweezers inhibits the germination of bacterial spores
Authors: Malyshev Dmitry , Robinson Nicholas Finlay , Öberg Rasmus , Dahlberg Tobias , Andersson Magnus 
Published: May 2022

AbstractBacterial spores are highly resistant to heat, radiation and various disinfection chemicals. The impact of these on the biophysical and physicochemical properties of spores can be studied on the single‐cell level using optical tweezers. However, the effect of the trapping laser on spores' germination rate is not fully understood. In this work, we assess the impact of 1064 nm laser light on the germination of Bacillus thuringiensis spores. The results show that the germination rate of spores after laser exposure follows a sigmoid dose‐response relationship, with only 15% of spores germinating after 20 J of laser light. Under anaerobic growth conditions, the percentage of germinating spores at 20 J increased to 65%. The results thereby indicate that molecular oxygen is a major contributor to the germination‐inhibiting effect observed. Thus, our study highlights the risk for optical trapping of spores and ways to mitigate it.
Drug‐Drug Interactions of Artemisinin‐Based Combination Therapies in Malaria Treatment: A Narrative Review of the Literature
Authors: Hernandez Maldonado Joyce , Grundmann Oliver 
Published: May 2022

AbstractArtemisinin is an antimalarial compound derived from the plant Artemisia annua L., also known as sweet wormwood. According to the World Health Organization, artemisinin‐based combination therapy (ACT) is an essential treatment for malaria, specifically Plasmodium falciparum, which accounts for most malaria‐related mortality. ACTs used to treat uncomplicated malaria include artemether‐lumefantrine, artesunate‐amodiaquine, artesunate‐mefloquine, artesunate‐sulphadoxine‐pyrimethamine, and dihydroartemisinin‐piperaquine. Although the mechanism of action and clinical capabilities of artemisinin in malaria treatment are widely known, more information on the potential for drug interactions needs to be further investigated. Some studies show pharmacokinetic and pharmacodynamic drug interactions with HIV antiviral treatment but few studies have been conducted on most other drug classes. Based on known genotypes of cytochrome P450 (CYP) enzymes, CYP2B6 and CYP3A are primarily involved in the metabolism of artemisinin and its derivatives. Reduced functions in these enzymes can lead to subtherapeutic concentrations of the active metabolite, dihydroartemisinin, that may cause treatment failure, which has been shown in some studies with cardiovascular, antibiotic, and antiparasitic drugs. Although the clinical importance remains unclear to date, clinicians should be aware of potential drug‐drug interactions and monitor patients on ACT closely.
Synthesis of methyl glycolate via low‐temperature hydrogenation of dimethyl oxalate over an efficient and stable Ru/activated carbon catalyst
Authors: Zheng Hongyan , Xue Yanfeng , Niu Yulan , Gao Xiaoqing , Wang Yueqing , Ding Guoqiang , Zhu Yulei 
Published: May 2022

AbstractBACKGROUNDSyngas to dimethyl oxalate (DMO) followed by hydrogenation to methyl glycolate (MG) is considered to be an environmentally friendly and economical route. However, the catalyst with super performance and low cost for this route is still challenging. In this work, a simple and low‐lost fabrication method was developed to prepare a Ru/activated carbon (AC) catalyst and was used for DMO hydrogenation to MG under mild reaction conditions.RESULTSThe Ru/AC catalyst showed the best performance in the low‐temperature hydrogenation of DMO to MG compared to Ru/SiO2 and Ru/Al2O3. A series of characterization results showed that the super catalytic properties of Ru/AC catalyst might be attributed to the higher dispersion of Ru on support and its smallest nanoparticles size, weak surface acidity and electron‐deficient state of Ru species. The key parameters such as Ru loading, temperature, weight hourly space velocity, and pressure, were comprehensively investigated. MG selectivity of 94.6% with DMO conversion of 97.2% were obtained over the 4.0 Ru/AC catalyst at 90 °C. The 4.0Ru/AC catalyst showed excellent stability and there was no obvious deactivation after 1032 h test.CONCLUSIONSThe Ru/AC catalyst is effective for the DMO hydrogenation to MG under mild conditions and has great promise for industrial applications because of its low cost, simple preparation, high efficiency, and long life. © 2022 Society of Chemical Industry (SCI).
The ratio of creatinine and cystatin C estimated glomerular filtration rates as a surrogate marker in patients with hepatocellular carcinoma undergoing hepatic resection
Authors: Harimoto Norifumi , Araki Kenichiro , Yamanaka Takahiro , Hagiwara Kei , Ishii Norihiro , Tsukagoshi Mariko , Watanabe Akira , Takizawa Makiko , Yokobori Takehiko , Shirabe Ken 
Published: May 2022

AbstractBackgroundThe ratio of creatinine and cystatin C estimated glomerular filtration rates (eGFRcre/eGFRcys) is significantly positively correlated with sarcopenia. However, there are no published reports on the relationship between eGFRcre/eGFRcys and long‐term prognosis in patients after hepatic resection for hepatocellular carcinoma (HCC).MethodsA total of 157 patients who had undergone curative hepatic resection for HCC were retrospectively reviewed. Cystatin C levels were measured in serum samples that had been frozen after collection at surgery. We aimed to investigate the significance of cystatin C in prognostic value following hepatic resection for HCC.ResultsThe best cut‐off eGFRcre/eGFRcys value for overall survival after hepatic resection for HCC was 1.0025. High eGFRcre/eGFRcys was significantly associated with poor liver function, low skeletal muscle mass, large tumor size, large ascitic volume, worse overall and recurrence‐free survival. The eGFRcre/eGFRcys was significantly related to severe recurrence patterns (multiple liver recurrences, distant metastasis).ConclusionsPreoperative eGFRcre/eGFRcys can predict overall and recurrence‐free survival in HCC patients undergoing hepatic resection. The eGFRcre/eGFRcys is a simple and reliable surrogate marker that indicates eligibility for hepatic resection for HCC.
Gait biomechanics phenotypes among total knee arthroplasty candidates by machine learning cluster analysis
Authors: Young‐Shand Kathryn L. , Roy Patrice C. , Dunbar Michael J. , Abidi Syed S. R. , Astephen Wilson Janie L. 
Published: May 2022

AbstractKnee osteoarthritis patient phenotyping is relevant to developing targeted treatments and assessing the treatment efficacy of total knee arthroplasty (TKA). This study aimed to identify clusters among TKA candidates based on demographic and knee mechanic features during gait, and compare gait changes between clusters postoperatively. TKA patients underwent 3D gait analysis 1‐week pre (n = 134) and 1‐year post‐TKA (n = 105). Principal component analysis was applied to frontal and sagittal knee angle and moment waveforms, extracting major patterns of variability. Age, sex, body mass index, gait speed, and frontal and sagittal pre‐TKA angle and moment PC scores previously identified as relevant to TKA outcomes were standardized (mean = 0, SD = 1, [134 × 15]). Multidimensional scaling and machine learning‐based hierarchical clustering were applied. Final clusters were validated by examining intercluster differences pre‐TKA and gait feature changes (PostPCscore – PrePCscore) by k‐way Χ2 and ANOVA tests. Four TKA candidate phenotypes yielded optimum clustering metrics, interpreted as higher and lower functioning clusters that were predominantly male and female. Higher functioning clusters pre‐TKA (clusters 1 and 4) had more dynamic sagittal flexion moment (p < 0.001) and frontal plane adduction moment (p < 0.001) loading/un‐loading patterns during stance. Post‐TKA, higher functioning clusters demonstrated less knee mechanic improvements during gait (flexion angle p < 0.001; flexion moment p < 0.001). TKA candidates can be characterized by four clusters, predominately separated by sex and knee joint biomechanics. Post‐TKA knee kinematics and kinetics improvements were cluster‐specific; lower functioning clusters experienced more improvement. Cluster‐based patient profiling may aid in triaging and developing OA management and surgical strategies meeting group‐level function needs.
Generative adversarial network‐based single‐pixel imaging
Authors: Zhao Ming , Li Fengqiang , Huo Fengyue , Tian Zhiming 
Published: May 2022

AbstractSingle‐pixel imaging can reconstruct two‐dimensional images of a scene with only a single‐pixel detector. It has been widely used for imaging in nonvisible bandwidth (e.g., near‐infrared and X‐ray) where focal‐plane array sensors are challenging to be manufactured. In this paper, we propose a generative adversarial network‐based reconstruction algorithm for single‐pixel imaging, which demonstrates efficient reconstruction in high speed and higher reconstruction quality compared with other state‐of‐the‐art deep learning‐based reconstruction methods. We also co‐optimize sampling masks and reconstruction pipeline to enhance the performance. We verify the proposed method with both synthetic and real‐world experiments and demonstrate a good quality of reconstruction of a real‐world plaster using a 5% sampling rate.