bluuebunny/crossref_metadata_2025_split huggingface dataset:
An HFM‐CREAM model for the assessment of human reliability and quantification
Authors: Lin Chuan , Xu Qi feng , Huang Yi fan 
Published: February 2022

AbstractHuman reliability analysis (HRA) is a proactive approach to model and evaluate systematic human errors and has been extensively implemented in various complicated systems. The assessment of human errors relies heavily on the knowledge and experience of experts in real‐world cases. Moreover, there are usually specific sorts of uncertainty while experts use linguistic labels to evaluate human failure events. In this context, this paper seeks to establish a new model based on the hesitant fuzzy matrix (HFM) and the cognitive reliability and error analysis method (CREAM) to conduct a quantitative analysis of human errors. This model handles the multiple crisp scores of the common performance conditions (CPCs) given by experts according to the context description in terms of CPCs, determines the weights of CPCs by the HFM, and elicits the human error probability (HEP) point estimation formula considering consequences based on the CREAM. Finally, the effectiveness and practicality of the presented HFM‐CREAM model are demonstrated through the emergency response analysis of the steam generator tube rupture (SGTR) in nuclear power plant.
Embodied cognition through participatory simulation and mathematical description: Supporting mechanistic reasoning and explanation
Authors: Weinberg Paul J. , Sorensen‐Weinberg Erika K. 
Published: February 2022

AbstractEmbodied cognition has been a useful means to support learning in science education. In this article, we describe a model of embodied cognition through analogical mapping that is supported through the participatory simulation and mathematical description of a link and pivot system. We look at the propensity for this model of embodied cognition to support student mechanistic reasoning. While these link and pivot systems provide students with immediate perceptual accessibility to their components, they do not provide perceptual accessibility to the way that forces are transmitted through them. In an afterschool STEM program, students engaged in a participatory simulation (the Rope Walk) of the link and pivot system that allowed them to simulate the parts and forces present. Then, students progressively re‐described these physical experiences as a mathematical system; they then described the simulation and mathematical system as the physical link and pivot system. In this study, this model of embodied cognition was validated through a microgenetic analysis of student talk and gesture during the first two instructional sessions as well as during pre‐ and post‐assessments. These data show that students were supported to construct analogical mappings between three analog conceptual domains: the participatory simulation (the Rope Walk), the physical system (link and pivot system), and the mathematical system (the mathematics of circles). In addition, students made gains on measures of mechanistic reasoning and explanation.
Metal‐Free Sequential Amidation and Intramolecular Csp2−H Direct Amination of Coumarin‐3‐carboxylic Acids under Ambient Conditions: Scope and Mechanistic Insights
Authors: Mandal Mullicka , Karmakar Indrajit , Chakrabarty Kuheli , Das Gourab Kanti , Brahmachari Goutam 
Published: February 2022

AbstractA metal‐free sequential amidation and intramolecular direct Csp2−H amination of coumarin‐3‐carboxylic acids has been achieved under ambient conditions, resulting in a new series of biologically interesting chromenopyridopyrimidine‐derived polyfunctional heterocycles. The DFT study offers mechanistic insights into this transformation. The salient features of this efficient and practical method are operational simplicity, metal‐free synthesis, one‐pot sequential amidation and amination, mild reaction conditions, good to excellent yields, and gram‐scale synthetic applicability.
Virtual Screening of Antitumor Inhibitors Targeting BRD4 Based on Machine Learning Methods
Authors: Wu Keliang , Zhang Chenghua , He Bing , Li Huanxin , Tang Shan , Han Tao , Li Bingke 
Published: February 2022

AbstractBRD4 is a hot antitumor target. In this study, three kinds of machine learning methods were used to establish classification models of BRD4 inhibitors, achieving satisfactory prediction performance. Through comparison, random forest model worked best, the parameters of which were also optimized. Then, the best random forest model was applied to perform virtual screening against ZINC database and a total of 89 potential compounds with BRD4 inhibitory activity were eventually identified. Further, seven molecules were chosen from the hits, and a docking calculation was carried out for each molecule, showing a strong interaction between ligand and BRD4. Subsequently, these molecules were evaluated by molecular dynamics simulations, all having certain binding stability. The results have proved the effectiveness of the developed models based on machine learning methods and the molecules filtered by virtual screening. These models not only can guide the practice for the molecular design and synthesis, but also can provide great possibility for the discoveries and final approvals of anti‐cancer drugs targeting BRD4.
Modulating the Local Coordination Environment of Single‐Atom Catalysts for Enhanced Catalytic Performance in Hydrogen/Oxygen Evolution Reaction
Authors: Tomboc Gracita M. , Kim Taekyung , Jung Sangmin , Yoon Hyo Jae , Lee Kwangyeol 
Published: February 2022

AbstractSingle‐atom catalysts (SACs) hold the promise of utilizing 100% of the participating atoms in a reaction as active catalytic sites, achieving a remarkable boost in catalytic efficiency. Thus, they present great potential for noble metal‐based electrochemical application systems, such as water electrolyzers and fuel cells. However, their practical applications are severely hindered by intrinsic complications, namely atom agglomeration and relocation, originating from the uncontrollably high surface energy of isolated single‐atoms (SAs) during postsynthetic treatment processes or catalytic reactions. Extensive efforts have been made to develop new methodologies for strengthening the interactions between SAs and supports, which could ensure the desired stability of the active catalytic sites and their full utilization by SACs. This review covers the recent progress in SACs development while emphasizing the association between the regulation of coordination environments (e.g., coordination atoms, numbers, sites, structures) and the electrocatalytic performance of the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). The crucial role of coordination chemistry in modifying the intrinsic properties of SACs and manipulating their metal‐loading, stability, and catalytic properties is elucidated. Finally, the future challenges of SACS development and the industrial outlook of this field are discussed.
Emerging 2D Materials for Electrocatalytic Applications: Synthesis, Multifaceted Nanostructures, and Catalytic Center Design
Authors: Wu Xizheng , Xiao Sutong , Long Yanping , Ma Tian , Shao Wenjie , Cao Sujiao , Xiang Xi , Ma Lang , Qiu Li , Cheng Chong , Zhao Changsheng 
Published: February 2022

AbstractCurrently, the development of advanced 2D nanomaterials has become an interdisciplinary subject with extensive studies due to their extraordinary physicochemical performances. Beyond graphene, the emerging 2D‐material‐derived electrocatalysts (2D‐ECs) have aroused great attention as one of the best candidates for heterogeneous electrocatalysis. The tunable physicochemical compositions and characteristics of 2D‐ECs enable rational structural engineering at the molecular/atomic levels to meet the requirements of different catalytic applications. Due to the lack of instructive and comprehensive reviews, here, the most recent advances in the nanostructure and catalytic center design and the corresponding structure–function relationships of emerging 2D‐ECs are systematically summarized. First, the synthetic pathways and state‐of‐the‐art strategies in the multifaceted structural engineering and catalytic center design of 2D‐ECs to promote their electrocatalytic activities, such as size and thickness, phase and strain engineering, heterojunctions, heteroatom doping, and defect engineering, are emphasized. Then, the representative applications of 2D‐ECs in electrocatalytic fields are depicted and summarized in detail. Finally, the current breakthroughs and primary challenges are highlighted and future directions to guide the perspectives for developing 2D‐ECs as highly efficient electrocatalytic nanoplatforms are clarified. This review provides a comprehensive understanding to engineer 2D‐ECs and may inspire many novel attempts and new catalytic applications across broad fields.
Preparation and Characterization of Bio‐based Nanocomposites Packaging Films Reinforced with Cellulose Nanofibers from Unripe Banana Peels
Authors: Ahmad Kashan , Din Zia‐ud , Ullah Hidayat , Ouyang Qin , Rani Sumayya , Jan Ibadullah , Alam Mukhtar , Rahman Ziaur , Kamal Tariq , Ali Saqib , Khan Sheraz Ahmad , Shahwar Durri , Gul Farhana , Ibrahim Muhammad , Nawaz Taufiq 
Published: February 2022

Abstract
An easy and simple approach is developed to fabricate nano‐composite packaging films from starch molecules reinforced with cellulose nanofibers derived from unripe from banana peel. Addition of 10g (w/w, dry starch basis) of cellulose nanofibers into the starch matrix results in improved mechanical and thermal stability of the nano‐composite films. The results show that addition of cellulose nanofibers into the starch matrix result in significant reduction in water solubility and water vapour permeability of the packaging films. The mechanical properties (elongation at break and tensile strength) of the films are improved significantly with incorporation of nano‐particles. Fourier transform infrared spectroscopy displays similar spectra for all tested samples due to the similar chemical nature of starch and cellulose. Similarly, differential scanning calorimetry analysis shows improved thermal stability of packaging films with the addition of nanofibers derived from banana peel cellulose. Moreover, scanning electron microscopy results show smooth surfaces and even distribution of particles and spaces in the matrix films as compared to the control. These results indicate the possible use of these packaging films in the food packaging industry thanks to their biocompatible, biodegradable, and non‐toxic characteristics and features.
Earthquake‐resistant subsystem stiffness demand estimate of frame–core tube structures with mass and stiffness nonuniformities
Authors: Lai Xiao , He Shuaishuai , He Zheng 
Published: February 2022

SummaryTo develop reasonable structural schemes of frame–core tube structures in the preliminary seismic design, a stiffness estimation of the main subsystems, that is, core tube, frame, and outrigger, is provided through the rocking model (RM) and flexural–shear coupled model (FSM). A nonuniform RM (RM‐MS) is proposed with the dual nonuniform distributions of mass and subsystem stiffness corresponding to those of the nonuniform FSM (FSM‐MS). The dynamic properties of the RM‐MS are semianalytically solved with the general solution for the free vibration of the nonuniform flexural beam and the rotational stiffness matrix of outriggers. The relation between the FSM‐MS and RM‐MS is established based on the first two vibration periods and nonlinear fitting and extended to present a subsystem stiffness estimation strategy with target maximum interstory drift ratios (IDRmax) and overturning moment distribution ratios (RM,B). The feasibility and effectiveness of the strategy are fully demonstrated by three cases with different targetRM,B. RM‐MS effectively controls structural lateral stiffness of FSM‐MS in advance. With the targetRM,Bbeyond the feasible range, it is necessary to adjust the first two vibration periods estimated by FSM‐MS. Compared with the axial rigidity of frame columns, the flexural rigidity of outriggers shows higher priority to increaseRM,B.
Chromosome‐specific KASP markers for detecting Amblyopyrum muticum segments in wheat introgression lines
Authors: Grewal Surbhi , Coombes Benedict , Joynson Ryan , Hall Anthony , Fellers John , Yang Cai‐yun , Scholefield Duncan , Ashling Stephen , Isaac Peter , King Ian P. , King Julie 
Published: February 2022

AbstractMany wild‐relative species are being used in prebreeding programs to increase the genetic diversity of wheat (Triticum aestivum L.). Genotyping tools such as single nucleotide polymorphism (SNP)‐based arrays and molecular markers have been widely used to characterize wheat–wild relative introgression lines. However, due to the polyploid nature of the recipient wheat genome, it is difficult to develop SNP‐based Kompetitive allele‐specific polymerase chain reaction (KASP) markers that are codominant to track the introgressions from the wild species. Previous attempts to develop KASP markers have involved both exome‐ and polymerase chain reaction (PCR)‐amplicon‐based sequencing of the wild species. But chromosome‐specific KASP assays have been hindered by homoeologous SNPs within the wheat genome. This study involved whole genome sequencing of the diploid wheat wild relative Amblyopyrum muticum (Boiss.) Eig and development of a de novo SNP discovery pipeline that generated ∼38,000 SNPs in unique wheat genome sequences. New assays were designed to increase the density of Am. muticum polymorphic KASP markers. With a goal of one marker per 60 Mbp, 335 new KASP assays were validated as diagnostic for Am. muticum in a wheat background. Together with assays validated in previous studies, 498 well distributed chromosome‐specific markers were used to recharacterize previously genotyped wheat–Am. muticum doubled haploid (DH) introgression lines. The chromosome‐specific nature of the KASP markers allowed clarification of which wheat chromosomes were involved with recombination events or substituted with Am. muticum chromosomes and the higher density of markers allowed detection of new small introgressions in these DH lines.
Relationship of fasting glucose and longitudinal Alzheimer's disease imaging markers
Authors: Honea Robyn A. , John Casey S. , Green Zachary D. , Kueck Paul J. , Taylor Matthew K. , Lepping Rebecca J. , Townley Ryan , Vidoni Eric D. , Burns Jeffery M. , Morris Jill K. 
Published: February 2022

AbstractIntroductionFasting glucose increases with age and is linked to modifiable Alzheimer's disease risk factors such as cardiovascular disease and Type 2 diabetes (T2D).MethodsWe leveraged available biospecimens and neuroimaging measures collected during the Alzheimer's Prevention Through Exercise (APEx) trial (n = 105) to examine the longitudinal relationship between change in blood glucose metabolism and change in regional cerebral amyloid deposition and gray and white matter (WM) neurodegeneration in older adults over 1 year of follow‐up.ResultsIndividuals with improving fasting glucose (n = 61) exhibited less atrophy and regional amyloid accumulation compared to those whose fasting glucose worsened over 1 year (n = 44). Specifically, while individuals with increasing fasting glucose did not yet show cognitive decline, they did have regional atrophy in the hippocampus and inferior parietal cortex, and increased amyloid accumulation in the precuneus cortex. Signs of early dementia pathology occurred in the absence of significant group differences in insulin or body composition, and was not modified by apolipoprotein E ε4 carrier status.DiscussionDysregulation of glucose in late life may signal preclinical brain change prior to clinically relevant cognitive decline. Additional work is needed to determine whether treatments specifically targeting fasting glucose levels may impact change in brain structure or cerebral amyloid in older adults.
Diagnostic value of liver function tests and ultrasonography in dogs with suspected congenital portosystemic shunts
Authors: Devriendt Nausikaa , Serrano Gonçalo , Stock Emmelie , Paepe Dominique , de Rooster Hilde 
Published: February 2022

AbstractBackgroundDiagnosing a congenital portosystemic shunt (cPSS) in dogs can be challenging. The current study aims to report diagnostic performance of fasting ammonia (FA), preprandial, postprandial and paired serum bile acids (SBA) and abdominal ultrasound (aUS) in dogs suspected of having a cPSS.MethodsMedical records of dogs suspected of having a cPSS at initial presentation were retrospectively reviewed.ResultsIn total, 192 dogs suspected of cPSS were included: a cPSS was confirmed in 147 dogs and excluded in 45 dogs. FA had the best combined sensitivity and specificity (77.4 and 93.3%, respectively) to diagnose cPSS. The sensitivity and negative predictive value were 100.0% for paired SBA, making paired SBA the best test to exclude cPSS in this population. Sensitivity and specificity of aUS were 80.8 and 90.0%, respectively.ConclusionsIn dogs with clinical signs compatible with cPSS, elevated FA is suggestive of cPSS, whereas normal paired SBA makes the presence of a cPSS unlikely. Although aUS is a useful tool to diagnose cPSS, additional imaging is required to visualize cPSS in almost 20% of cases. Furthermore, the localisation of cPSS can be misdiagnosed, especially in case of extrahepatic cPSS that do not insert into the prehepatic vena cava.
Revisiting rescattering contributions to $$ \overline{B} $$(s) → $$ {D}_{(s)}^{\left(\ast \right)}M $$ decays
Authors: Endo Motoi , Iguro Syuhei , Mishima Satoshi 
Published: February 2022

Abstract
Motivated by the reported discrepancies between experimental data and Standard Model predictions for the branching ratios of the color-allowed decays $$ \overline{B} $$

B
¯

0 → D(*)+K− and $$ {\overline{B}}_s^0 $$

B
¯

s
0

→ $$ {D}_s^{\left(\ast \right)+}{\pi}^{-} $$

D
s

∗

+

π
−

, we study final-state rescattering effects on $$ \overline{B} $$

B
¯

(s) → $$ {D}_{(s)}^{\left(\ast \right)}P $$

D

s

∗

P
and $$ \overline{B} $$

B
¯

(s) → D(s)V, where P(V) is a light pseudoscalar (vector) meson. We consider quasi-elastic rescatterings in the framework of SU(3) and U(3) flavor symmetries, and find that the effects cannot explain the measured branching ratios of the color-allowed and color-suppressed decays simultaneously. We also perform global fits to the $$ \overline{B} $$

B
¯

(s) → $$ {D}_{(s)}^{\left(\ast \right)}P $$

D

s

∗

P
and $$ \overline{B} $$

B
¯

(s) → D(s)V data, allowing for new physics contributions to the Wilson coefficient a1 associated with the color-allowed tree amplitudes. It is shown that the fits prefer a downward shift of $$ \mathcal{O} $$
O
(10%) in a1 even in the presence of the quasi-elastic rescattering contributions.
Exact order of extreme $$L_p$$ discrepancy of infinite sequences in arbitrary dimension
Authors: Kritzinger Ralph , Pillichshammer Friedrich 
Published: February 2022

AbstractWe study the extreme $$L_p$$

L
p

discrepancy of infinite sequences in the d-dimensional unit cube, which uses arbitrary sub-intervals of the unit cube as test sets. This is in contrast to the classical star $$L_p$$

L
p

discrepancy, which uses exclusively intervals that are anchored in the origin as test sets. We show that for any dimension d and any $$p>1$$

p
>
1

, the extreme $$L_p$$

L
p

discrepancy of every infinite sequence in $$[0,1)^d$$

[
0
,
1
)

d

is at least of order of magnitude $$(\log N)^{d/2}$$

(
log
N
)

d
/
2

, where N is the number of considered initial terms of the sequence. For $$p \in (1,\infty )$$

p
∈
(
1
,
∞
)

, this order of magnitude is best possible.
A novel approach to calculating the kinetically derived maximum dose
Authors: Burgoon Lyle D. , Fuentes Claudio , Borgert Christopher J. 
Published: February 2022

AbstractThe kinetically derived maximal dose (KMD) provides a toxicologically relevant upper range for the determination of chemical safety. Here, we describe a new way of calculating the KMD that is based on sound Bayesian, theoretical, biochemical, and toxicokinetic principles, that avoids the problems of relying upon the area under the curve (AUC) approach that has often been used. Our new, mathematically rigorous approach is based on converting toxicokinetic data to the overall, or system-wide, Michaelis–Menten curve (which is the slope function for the toxicokinetic data) using Bayesian methods and using the “kneedle” algorithm to find the “knee” or “elbow”—the point at which there is diminishing returns in the velocity of the Michaelis–Menten curve (or acceleration of the toxicokinetic curve). Our work fundamentally reshapes the KMD methodology, placing it within the well-established Michaelis–Menten theoretical framework by defining the KMD as the point where the kinetic rate approximates the Michaelis–Menten asymptote at higher concentrations. By putting the KMD within the Michaelis–Menten framework, we leverage existing biochemical and pharmacological concepts such as “saturation” to establish the region where the KMD is likely to exist. The advantage of defining KMD as a region, rather than as an inflection point along the curve, is that a region reflects uncertainty and clarifies that there is no single point where the curve is expected to “break;” rather, there is a region where the curve begins to taper off as it approaches the asymptote (Vmax in the Michaelis–Menten equation).
Potentio-tunable FET sensor having a redox-polarizable single electrode for the implementation of a wearable, continuous multi-analyte monitoring device
Authors: Lefler Sharon , Ben-Shachar Berta , Masasa Hila , Schreiber David , Tamir Idan 
Published: February 2022

AbstractThe emerging field of wearable devices for monitoring bioanalytes calls for the miniaturization of biochemical sensors. The only commercially available electrochemical wearable monitoring medical devices for bioanalytes are the amperometric continuous glucose monitoring (CGM) systems. The use of such amperometric methods to monitor glucose levels requires a relatively large electrode surface area for sufficient redox species collection, allowing accurate measurements to be made. Consequently, miniaturization of such sensors bearing large electrodes is challenging. Furthermore, it is difficult to introduce and deploy more than one electrode–based sensor per device, thereby limiting the number of analytes that can be monitored in parallel. To address these limitations, we have employed a non-referenced, single polarizable electrode coupled to a fin-shaped field-effect transistor (Fin-FET). We have discovered that by passivating the FET area by a relatively thick oxide and/or polytetrafluoroethylene (PTFE) polymer, leaving only the polarizable working electrode (WE) exposed, we can monitor redox analytes at the micromolar to millimolar concentration range. We attribute this effect to the WE polarization by the solution redox species. We have exploited the superior sensitivity of the adjacent silicon-based Fin-FET to detect changes in sensor electrode potentials induced by the redox species. Furthermore, we demonstrated the correlation between a specific analyte and the biasing WE potential on the accumulation/depletion of the coupled Fin-FET channel as manifested by the transistor source-drain current. Moreover, we utilized the analyte-electrode potential interaction, which is analyte-specific, to tune the specificity of the sensor towards an analyte of choice. In addition, we demonstrated the use of a single-electrode potentiometric sweep to assist in identifying the accumulation/depletion as a result of analyte-WE state. Collectively, the tiny potentio-tunable electrochemical sensor (PTEchem sensor) area is ~50 × 50 µm, and dedicated wireless transducer facilitates the use of this sensor for wearable continuous, multi-metabolite monitoring.
Graphical abstract