bluuebunny/crossref_metadata_2025_split huggingface dataset:
Photoplethysmography temporal marker-based machine learning classifier for anesthesia drug detection
Authors: Khalid Syed Ghufran , Ali Syed Mehmood , Liu Haipeng , Qurashi Aisha Ghazal , Ali Uzma 
Published: September 2022

AbstractAnesthesia drug overdose hazards and lack of gold standards in anesthesia monitoring lead to an urgent need for accurate anesthesia drug detection. To investigate the PPG waveform features affected by anesthesia drugs and develop a machine-learning classifier with high anesthesia drug sensitivity. This study used 64 anesthesia and non-anesthesia patient data (32 cases each), extracted from Queensland and MIMIC-II databases, respectively. The key waveform features (total area, rising time, width 75%, 50%, and 25%) were extracted from 16,310 signal recordings (5-s duration). Discriminant analysis, support vector machine (SVM), and K-nearest neighbor (KNN) were evaluated by splitting the dataset into halve training (11 patients, 8570 segments) and halve testing dataset (11 patients, 7740 segments). Significant differences exist between PPG waveform features of anesthesia and non-anesthesia groups (p < 0.05) except total area feature (p > 0.05). The KNN classifier achieved 91.7% (AUC = 0.95) anesthesia detection accuracy with the highest sensitivity (0.88) and specificity (0.90) as compared to other classifiers. Kohen’s kappa also shows almost perfect agreement (0.79) with the KNN classifier. The KNN classifier trained with significant PPG features has the potential to be used as a reliable, non-invasive, and low-cost method for the detection of anesthesia drugs for depth analysis during surgical operations and postoperative monitoring.
Graphical abstract
Estimating the market risk premium for valuations: arithmetic or geometric mean or something in between?
Authors: Kaserer Christoph 
Published: September 2022

AbstractIt is well-known that using arithmetic averages of yearly return observations leads to downward biased discount rates estimations. Well-known corrections, however, lead to upward biased results under the presence of negative serial correlation. Using a simulation analysis, we first show that a specific variant of the Cooper estimator, labelled as C4 in this paper, leads to robust estimations even under the presence of both serial correlation and heteroscedasticity. We also show that among the simple estimators, i.e. the arithmetic (AM) or geometric mean (GM) or the mean of both (MoM), the first one tends to perform best unless there is a high degree of negative serial correlation. In that case using the so-called mean of means rule would be better. Secondly, using data from Jordà et al. (Q J Econ 134(3):1225–1298, 2019) we find negative serial correlation and heteroscedasticity in market risk premia to be a widely spread phenomenon. Finally, we use this data to derive presumably least biased market risk premia estimations based on the C4 estimator. For the majority of the countries we find that these estimations are somewhere between the arithmetic and geometric average. When comparing these simple estimators among each other based on the empirical data, we find the arithmetic mean and mean of means to perform almost equally well, while the geometric mean clearly underperforms. Moreover, we found some evidence that the MoM is slightly outperforming the AM under a local CAPM perspective, while the opposite tends to be true under a global CAPM perspective. This leads us the cautious conclusion that the mean of means rule used by practitioners has some empirical rationale when there is evidence for substantial negative serial correlation.
Theoretical description of PIV measurement errors
Authors: Cameron Stuart Murray 
Published: September 2022

AbstractExpressions for particle image velocimetry (PIV) mean error and error variance are derived for iterative deformation method algorithms. The analytical expressions explicitly account for the role of in- and out-of-plane displacements, displacement gradients, particle image diameter, fill factor of the imaging sensor, image noise, light sheet intensity distribution, seeding particle concentration, the interpolation function used to deform PIV images, and the interrogation window size and weighting window. The newly derived analytical expressions show good agreement with errors estimated using synthetic image sets.
How to analyze postoperative radiographs after total hip replacement
Authors: Budzińska Martyna Barbara , Maciąg Bartosz Michał , Żarnovsky Krystian , Kordyaczny Tomasz , Kowalczyk Inga Magdalena , Adamska Olga , Stolarczyk Artur 
Published: September 2022

AbstractTotal hip replacement is one of the most widely performed surgeries. It is stated as the most efficient method of treating end-stage osteoarthritis of the hip joint. What is more, it significantly improves the quality of patients’ lives, relieves them from pain and restores decreased range of motion, provided that is conducted properly. Aim of this article is to indicate which constituents of prosthetic placement can be easily measured on postoperative radiographs and point out how to interpret obtained results. Multiple mechanical factors, such as center of rotation, femoral offset, acetabular offset, acetabular inclination, acetabular anteversion and leg length discrepancy can be measured on postoperative radiographs. To provide a successful surgery and to acquire both radiological and clinical satisfying results, proper prosthetic placement is crucial. Malpositioning of each element, in varying degrees may lead to dislocation or reoperation.
Transit Ridership Modeling at the Bus Stop Level: Comparison of Approaches Focusing on Count and Spatially Dependent Data
Authors: Marques Samuel de França , Pitombo Cira Souza 
Published: September 2022

AbstractBoarding and alighting modeling at the bus stop level is an important tool for operational planning of public transport systems, in addition to contributing to transit-oriented development. The interest variables, in this case, present two particularities that strongly influence the performance of proposed estimates: they demonstrate spatial dependence and are count data. Moreover, in most cases, these data are not easy to collect. Thus, the present study proposes a comparison of approaches for transit ridership modeling at the bus stop level, applying linear, Poisson, Geographically Weighted and Geographically Weighted Poisson (GWPR) regressions, as well as Universal Kriging (UK), to the boarding and alighting data along a bus line in the city of São Paulo, Brazil. The results from goodness-of-fit measures confirmed the assumption that adding asymmetry and spatial autocorrelation, isolated and together, to the transportation demand modeling, contributes to a gradual improvement in the estimates, highlighting the GWPR and UK spatial estimation techniques. Moreover, the spatially varying relationships between the variables of interest (boardings and alightings) and their predictors (land use and transport system features around the bus stops), shown in the present study, may support land use policies toward transit-oriented development. In addition, by using an approach with little information, the good results achieved proved that satisfactory boarding and alighting modeling can be done in regions where there is a lack of travel demand data, as in the case of emerging countries.
Chemical shift assignments of the C-terminal domain of CaBP1 bound to the IQ-motif of voltage-gated Ca2+ channel (CaV1.2)
Authors: Salveson Ian , Ames James B. 
Published: September 2022

AbstractThe neuronal L-type voltage-gated Ca2+ channel (CaV1.2) interacts with Ca2+ binding protein 1 (CaBP1), that promotes Ca2+-induced channel activity. The binding of CaBP1 to the IQ-motif in CaV1.2 (residues 1644–1665) blocks the binding of calmodulin and prevents Ca2+-dependent inactivation of CaV1.2. This Ca2+-induced binding of CaBP1 to CaV1.2 is important for modulating neuronal synaptic plasticity, which may serve a role in learning and memory. Here we report NMR assignments of the C-terminal domain of CaBP1 (residues 99–167, called CaBP1C) that contains two Ca2+ bound at the third and fourth EF-hands (EF3 and EF4) and is bound to the CaV1.2 IQ-motif from CaV1.2 (BMRB accession no. 51518).
A conceptual model of mindful organizing for effective safety and crisis management. The role of organizational culture
Authors: Petitta Laura , Martínez-Córcoles Mario 
Published: September 2022

AbstractThe Covid-19 pandemic has involved nations world-wide in the necessity to manage and control the spread of infection, and challenged organizations to effectively counteract an unchartered medical crisis while preserving the safety of workers. While the pandemic and geopolitical turmoil caused by the war in Ukraine are recent examples of complex environments that require effective safety and crisis management, organizations may generally need to find ways to deal with the unexpected and reliably perform in the face of fluctuations. Mindful organizing (MO) is defined as the collective capability to detect discriminatory details about emerging issues and act swiftly in response to these details, thus allowing members to anticipate, and recover from, any errors or unexpected events that arise. Organizational culture refers to the mindset shared among members which orients their actions and thus qualifies as a relevant contextual factor that determines whether the specific forms of perceiving and acting entailed by MO may emerge in an organization. The present paper aimed to propose a conceptual model linking organizational culture, MO and organizational outcomes (i.e., safety, reliability, crisis management), and delineate arguments to address the match/mismatch between MO and culture types. Specifically, it is proposed that organizational culture determines the way an organization develops MO and the subsequent ability to handle unexpected events which might jeopardize organizational effectiveness and safety. Our contribution bridges the still disparate fields of MO and organizational culture, and provides scholars and practitioners with a complexity- and uncertainty-sensitive integrative framework in order to intervene on organizational outcomes.
Enzyme immunoassays for the detection of mycotoxins in plant-based milk alternatives: pitfalls and limitations
Authors: Rehagel Christina , Maul Ronald , Gützkow Kim Lara , Akineden Ömer 
Published: September 2022

AbstractPlant-based milk alternatives (PBMAs) are a potential source of mycotoxin uptake. To ensure food safety, simple and rapid testing methods of PBMAs for mycotoxins are therefore required. This study investigated the applicability of enzyme immunoassay (EIA) methods for direct testing of PBMAs without sample extraction. Mycotoxin analyses included aflatoxin B1 (AFB1), sterigmatocystin (STC), ochratoxin A (OTA), deoxynivalenol (DON), and T-2/HT-2-toxin (T-2/HT-2). It was found that the PBMA matrix negatively affected the EIA to varying degrees, thus affecting the reliability of the results. A dilution of PBMAs of at least 1:8 was necessary to overcome matrix interference. This resulted in calculated detection limits of 0.4 µg/L (AFB1), 2 µg/L (STC), 0.08 µg/L (OTA), 16 µg/L (DON), and 0.4 µg/L (T-2/HT-2). After analysis of 54 PBMA products from German retail stores, positive results in at least one test system were obtained for 23 samples. However, most positive results were near the calculated detection limit. Control analyses of selected samples by LC–MS/MS for AFB1, STC, and OTA qualitatively confirmed the presence of trace amounts of STC in some samples, but quantitative agreement was poor. It was concluded that the high diversity of ingredients used in PBMAs led to a highly variable degree of sample matrix interference even in a 1:8 dilution. Since the use of higher dilutions conflicts with the need to achieve low detection limits, the application of EIA for routine mycotoxin analysis in PBMA for mycotoxins requires further study on the development of a feasible sample preparation method.
Construction of 2D and 3D rock physics templates for quantitative prediction of physical properties of a carbonate reservoir in SW of Iran
Authors: Rahmani Forouzan , Emami Niri Mohammad , Jozanikohan Golnaz 
Published: September 2022

AbstractThe characterization of carbonate rocks is not straightforward, as they often experience complex diagenetic processes causing them to expose wide variations in pore types. This research aims to characterize the properties of a carbonate reservoir with a complicated porous structure through rock physics principles and tools. Two representative wells from an oil field located in SW of Iran were selected, and two-dimensional (2D) and three-dimensional (3D) rock physics templates (RPTs) were constructed by employing the appropriate rock physics models. The porosity, water saturation, and pore type are considered reservoir parameters affecting carbonate rock's elastic properties and indicating the reservoir quality. The 2D RPTs described variations in two reservoir parameters in terms of elastic properties. However, they were not able to simultaneously characterize all three reservoir parameters. The proposed 3D RPTs revealed the underlying relationship of elastic properties with pore aspect ratio, water saturation, and porosity. To validate the constructed RPTs, well logging data, scanning electron microscope images, and thin section images were utilized. The RPTs were also employed to predict the reservoir properties quantitatively, and these predictions were compared with the petrophysical data. The average errors of the predicted porosity and water saturation by 3D RPT were, respectively, 1.22% and 6.66% for well A, and 2.65% and 8.18% for well B. The 2D RPTs provided three sets of predictions for porosity and water saturation (considering three specific pore aspect ratios of 0.03, 0.1, and 0.5), all with higher average errors compared to the predictions by 3D RPT for both wells. The obtained results proved that 3D RPT could predict reservoir properties more accurately. Finally, based on the estimated values of pore aspect ratio, water saturation, and porosity using 3D RPTs, the reservoir under study was divided into distinct depth intervals, and a quality level was assigned to each interval. The introduced rock physics-based procedure for a carbonate reservoir characterization could increase the reliability in predicting the reservoir properties, enhance the ability to detect the reservoir fluid, and thereby reduce the interpretation risk.
The value of CT-based radiomics nomogram in differential diagnosis of different histological types of gastric cancer
Authors: Huang Hao , Xu Fangyi , Chen Qingqing , Hu Hongjie , Qi Fangyu , Zhao Jiaojiao 
Published: September 2022

AbstractTo establish and verify a nomogram based on computed tomography (CT) radiomics analysis to predict the histological types of gastric cancer preoperatively for patients with surgical indications. A sum of 171 patients with gastric cancer were included into this retrospective study. The least absolute shrinkage and selection operator (LASSO) was used for feature selection while the multivariate Logistic regression method was used for radiomics model and nomogram building. The area under curve (AUC) was used for performance evaluation in this study. The radiomics model got AUCs of 0.755 (95% CI 0.650–0.859), 0.71 (95% CI 0.543–0.875) and 0.712 (95% CI 0.500–0.923) for histological prediction in the training, the internal and external verification cohorts. The radiomics nomogram based on radiomics features and Carbohydrate antigen 125 (CA125) showed good discriminant performance in the training cohort (AUC: 0.777; 95% CI 0.679–0.875), the internal (AUC: 0.726; 95% CI 0.5591–0.8933) and external verification cohort (AUC: 0.720; 95% CI 0.5036–0.9358). The calibration curve of the radiomics nomogram also showed good results. The decision curve analysis (DCA) shows that the radiomics nomogram is clinically practical. The radiomics nomogram established and verified in this study showed good performance for the preoperative histological prediction of gastric cancer, which might contribute to the formulation of a better clinical treatment plan.
Characterization and Optimization of Chitosan Production by Aspergillus terreus
Authors: Abo Elsoud Mostafa M. , Mohamed Sahar S. , Selim Manal S. , Sidkey Nagwa M. 
Published: September 2022

AbstractThe production of the amino polysaccharide (chitosan) from crustacean sources has faced many hindrances due to environmental, seasonal and noneconomic issues. On the other hand, mycogenic chitosan has many advantages that make it suitable for many medical and nutritional applications over the non-mycological counterparts. A number of fungal isolates have been screened for chitosan production, where the most potent fungal isolate has been genetically identified using 18S rDNA and selected to be the focus of the current study. The factors affecting chitosan production by the selected fungal isolate have been studied and numerically optimized and validated using Box–Behnken design. The produced chitosan has been collected, purified and characterized for the degree of deacetylation (DDA), molecular weight (MW), water-binding (WBC) and fat-binding capacities (FBC). Results showed that Aspergillus terreus (F3) was the most potent chitosan-producing fungal isolate with maximum validated productivity (2.92 g/l) at the following conditions: glucose, 35.6 g/l; (NH4)2SO4, 4.6 g/l; CaCl2, 0.29 g/l; and pH 7.9 at 23.2 °C for 10 days. The purified chitosan has the following characteristics: 71.9%, DDA; 54.1165 KD, MW; 58.6%, WBC; and 47.6%, FBC. The features and applications of fungal chitosan are not fully uncovered which necessitates further studies.
State-of-the-art literature review methodology: A&nbsp;six-step approach for knowledge synthesis
Authors: Barry Erin S. , Merkebu Jerusalem , Varpio Lara 
Published: September 2022

Introduction Researchers and practitioners rely on literature reviews to synthesize large bodies of knowledge. Many types of literature reviews have been developed, each targeting a specific purpose. However, these syntheses are hampered if the review type’s paradigmatic roots, methods, and markers of rigor are only vaguely understood. One literature review type whose methodology has yet to be elucidated is the state-of-the-art (SotA) review. If medical educators are to harness SotA reviews to generate knowledge syntheses, we must understand and articulate the paradigmatic roots of, and methods for, conducting SotA reviews.
Methods We reviewed 940 articles published between 2014–2021 labeled as SotA reviews. We (a) identified all SotA methods-related resources, (b) examined the foundational principles and techniques underpinning the reviews, and (c) combined our findings to inductively analyze and articulate the philosophical foundations, process steps, and markers of rigor.
Results In the 940 articles reviewed, nearly all manuscripts (98%) lacked citations for how to conduct a SotA review. The term “state of the art” was used in 4 different ways. Analysis revealed that SotA articles are grounded in relativism and subjectivism.
Discussion This article provides a 6-step approach for conducting SotA reviews. SotA reviews offer an interpretive synthesis that describes: This is where we are now. This is how we got here. This is where we could be going. This chronologically rooted narrative synthesis provides a methodology for reviewing large bodies of literature to explore why and how our current knowledge has developed and to offer new research directions.
A posteriori error estimators for discontinuous Galerkin method for diffusion problems, based on the hypercircle method
Authors: Alsheikh Dina N. , Katsaounis Theodoros 
Published: September 2022

AbstractIn this work, we apply the hypercircle method to Discontinuous Galerkin (DG) approximations of second order diffusion problems featuring inhomogeneous Dirichlet and Neumann boundary conditions. We focus on the interior penalty discontinuous Galerkin (IPDG) approximations of diffusion problems in primal variational formulation and produce a Prager–Synge theorem for such DG methods. Using the hypercircle method, we derive an a posteriori error estimator in terms of an equilibrated flux. The estimator is proven to be reliable and efficient. Numerical results are presented which illustrate the estimator’s performance.
Role of frailty on cardiac rehabilitation in hospitalized older patients
Authors: Bencivenga Leonardo , Femminella Grazia Daniela , Ambrosino Pasquale , Bosco Quirino , De Lucia Claudio , Perrotta Giovanni , Formisano Roberto , Komici Klara , Vitale Dino Franco , Ferrara Nicola , Maniscalco Mauro , Cacciatore Francesco , Papa Antimo , Rengo Giuseppe 
Published: September 2022

Abstract
Background
Cardiovascular diseases are the leading cause of mortality, morbidity, and disability in the world, especially in the older adults. A relevant proportion of patients admitted to Cardiac Rehabilitation (CR) may suffer from frailty, a complex geriatric syndrome with multifactorial aetiology.

Aims
The hypothesis underlying the study is that frailty complicates the management of older patients undergoing CR. The main objective is, therefore, to determine the relationship between frailty and CR outcomes in hospitalized older adults.

Methods
The participants have been recruited among patients aged ≥ 65 years admitted at the hospital for CR. A Comprehensive Geriatric Assessment (CGA)-based Frailty Index (FI) was created following a standard procedure. The outcome was measured as the ratio between 6-min walk test (6MWT) distance at the end of CR and normal predicted values for a healthy adult of same age and gender, according to reference equations.

Results
The study population consisted of 559 elderly patients, 387 males (69.2%), with age of 72 (69–76) years. The most frequent diagnosis at admission was ischaemic heart disease (231, 41.5%) and overall 6MWT ratio was 0.62 ± 0.21. At the multivariable regression analysis, gender, diagnosis and FI were significantly and independently associated with 6MWT ratio (p ≤ 0.0001, p ≤ 0.001 and p ≤ 0.0001, respectively), while no significant association emerged for age.

Conclusion
FI resulted independently correlated to 6MWT ratio in a population of older patients undergoing in-hospital CR programs. Frailty is a multifactorial geriatric syndrome whose assessment is essential for prognostic evaluation of older patients, also in CR clinical setting.