bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of Patient-Specific Covariates on Test Validity of Two Delirium Screening Instruments in Neurocritical Care Patients (DEMON-ICU)
Authors: Weiss Björn , Paul Nicolas , Spies Claudia D. , Ullrich Dennis , Ansorge Ingrid , Salih Farid , Wolf Stefan , Luetz Alawi 
Published: August 2021

Abstract
Background
Delirium screening instruments (DSIs) should be used to detect delirium, but they only show moderate sensitivity in patients with neurocritical illness. We explored whether, for these patients, DSI validity is impacted by patient-specific covariates.

Methods
Data were prospectively collected in a single-center quality improvement project. Patients were screened for delirium once daily using the Intensive Care Delirium Screening Checklist (ICDSC) and the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Reference was the daily assessment using criteria from the Diagnostic and Statistical Manual, 4th Edition, Text Revision (DSM-IV-TR). In a two-step receiver operating characteristics regression analysis adjusting for repeated measurements, the impact of acute diagnosis of stroke or transient ischemic attack (TIA), neurosurgical intervention, Richmond Agitation Sedation Scale, and ventilation status on test validity was determined.

Results
Of 181 patients screened, 101 went into final analysis. Delirium incidence according to DSM-IV-TR was 29.7%. For the first complete assessment series (CAM-ICU, ICDSC, and DSM-IV-TR), sensitivity for the CAM-ICU and the ICDSC was 73.3% and 66.7%, and specificity was 91.8% and 94.1%, respectively. Consideration of daily repeated measurements increased sensitivity for the CAM-ICU and ICDSC to 75.7% and 73.4%, and specificity to 97.3% and 98.9%, respectively. Receiver operating characteristics regression revealed that lower Richmond Agitation Sedation Scale levels significantly impaired validity of the ICDSC (p = 0.029) and the CAM-ICU in its severity scale version (p = 0.004). Neither acute diagnosis of stroke or TIA nor neurosurgical intervention or mechanical ventilation significantly influenced DSI validity.

Conclusions
The CAM-ICU and ICDSC perform well in patients requiring neurocritical care, regardless of the presence of acute stroke, TIA, or neurosurgical interventions. Yet, even very light or moderate sedation can significantly impair DSI performance.
Distress disclosure and psychological Distress among men: the role of feeling understood and loneliness
Authors: Keum Brian TaeHyuk , Oliffe John L. , Rice Simon M. , Kealy David , Seidler Zac E. , Cox Dan W. , Levant Ronald F. , Ogrodniczuk John S. 
Published: August 2021

AbstractWe examined whether men’s distress disclosure would be indirectly associated with psychological distress through feeling understood by others and loneliness as serial or parallel mediators. We conducted path analyses (N = 1827 adult men; mean 37.53 years, SD = 14.14) to test the mediators while controlling for race/ethnicity. Post-hoc multi-group analysis was conducted to examine differences across White and Asian men. The serial mediation model fit the data better than the parallel mediation model. Controlling for race/ethnicity, a significant partial indirect association was found between greater distress disclosure and lower psychological distress through greater feelings of being understood and lower feelings of loneliness. Post-hoc multi-group analysis suggested that the hypothesized paths fit equivalently across White and Asian men, and the direct effect was not significant for Asian men. Our hypothesized serial model also fit the data significantly better than alternative models with distress and the mediators predicting disclosure. Distress disclosure may be a socially conducive strategy for men to feel understood and socially connected, a process that may be associated with lower psychological distress.
Application of Artificial Intelligence in Food Industry—a Guideline
Authors: Mavani Nidhi Rajesh , Ali Jarinah Mohd , Othman Suhaili , Hussain M. A. , Hashim Haslaniza , Rahman Norliza Abd 
Published: August 2021

AbstractArtificial intelligence (AI) has embodied the recent technology in the food industry over the past few decades due to the rising of food demands in line with the increasing of the world population. The capability of the said intelligent systems in various tasks such as food quality determination, control tools, classification of food, and prediction purposes has intensified their demand in the food industry. Therefore, this paper reviews those diverse applications in comparing their advantages, limitations, and formulations as a guideline for selecting the most appropriate methods in enhancing future AI- and food industry–related developments. Furthermore, the integration of this system with other devices such as electronic nose, electronic tongue, computer vision system, and near infrared spectroscopy (NIR) is also emphasized, all of which will benefit both the industry players and consumers.
Towards individualised treatment of out-of-hospital cardiac arrest patients: an update on technical innovations in the prehospital chain of survival
Authors: Thannhauser J. , Nas J. , Waalewijn R. A. , van Royen N. , Bonnes J. L. , Brouwer M. A. , de Boer M. J. 
Published: August 2021

AbstractOut-of-hospital cardiac arrest (OHCA) is a major healthcare problem, with approximately 200 weekly cases in the Netherlands. Its critical, time-dependent nature makes it a unique medical situation, of which outcomes strongly rely on infrastructural factors and on-scene care by emergency medical services (EMS). Survival to hospital discharge is poor, although it has substantially improved, to roughly 25% over the last years. Recognised key factors, such as bystander resuscitation and automated external defibrillator use at the scene, have been markedly optimised with the introduction of technological innovations. In an era with ubiquitous smartphone use, the Dutch digital text message alert platform HartslagNu (www.hartslagnu.nl) increasingly contributes to timely care for OHCA victims. Guidelines emphasise the role of cardiac arrest recognition and early high-quality bystander resuscitation, which calls for education and improved registration at HartslagNu. As for EMS care, new technological developments with future potential are the selective use of mechanical chest compression devices and extracorporeal life support. As a future innovation, ‘smart’ defibrillators are under investigation, guiding resuscitative interventions based on ventricular fibrillation waveform characteristics. Taken together, optimisation of available prehospital technologies is crucial to further improve OHCA outcomes, with particular focus on more available trained volunteers in the first phase and additional research on advanced EMS care in the second phase.
Removal of Phenolic Compounds from Olive Mill Wastewater by Microalgae Grown Under Dark and Light Conditions
Authors: Lindner Astrid Victoria , Pleissner Daniel 
Published: August 2021

AbstractPhenolic compounds in olive mill wastewater (OMW) are considered an environmental threat due to their antimicrobial properties. Because of the metabolic versatility of microalgae, a biotic removal of these compounds seems a suitable approach. To investigate the biotic removal of phenolic compounds, the three microalgae species Chlorella vulgaris, Acutodesmus obliquus and Monoraphidium braunii were cultivated in flasks under constant light (50 µmol/m2s) and dark (1 g/L glucose) conditions in presence of different concentrations of OMW. Addition of 1% (v/v) OMW to the culture medium was shown to be non-inhibitory or even growth enhancing, and phenolic compounds were removed by 7–21% by all tested species. Cultivations with 6% (v/v) OMW resulted in a few exceptional experiments in fast growth (C. vulgaris under light, M. braunii under dark conditions) and removal of phenolic compounds (M. braunii, dark). Higher percentages (12 and 25%, v/v) of OMW were inhibitory. Under dark conditions microalgae first consumed glucose and removed phenolic compounds in a diauxic process. Removal of phenolic compounds was favoured under light conditions. Results of this study reveal the opportunities and the challenges of a microalgae-based removal of phenolic compounds and valorization of toxic OMW.
Graphic abstract
The Dangers of Mindfulness: Another Myth?
Authors: Anālayo Bhikkhu 
Published: August 2021

AbstractCriticism of potential drawbacks of mindfulness is crucial for the field to move forward and remain grounded in reality rather than become carried away by the mindfulness hype. At the same time, however, such criticism needs to be reasonable and based on actual facts rather than subjective imagination. The allegation that mindfulness is intrinsically dangerous appears to have been influenced by unreasonable claims made by Daniel Ingram, which have been taken seriously due to an apparent lack of acquaintance of some scholars with Buddhist doctrine and with genuine forms of insight meditation.
Petrophysical and petrographic characteristics of Barail Sandstone of the Surma Basin, Bangladesh
Authors: Islam Md Shofiqul , Shijan Md Hasibul Hasan , Saif Md Samin , Biswas Pradip Kumar , Faruk Muhammad Omar 
Published: August 2021

AbstractThe Barail sandstone in the Surma Basin is a medium- to coarse-grained pinkish-colored rock exposed near the northeastern margin of Bangladesh. In this study, we evaluated the reservoir quality of the Barail sandstone based on its petrophysical and petrographic characteristics. Petrophysical analyses of outcropped samples showed that sandstones are made up of 16.48% porosity and 132.48 mD permeability. Sandstone density ranges from 1.94 g/cm3 to 2.37 g/cm3, with a mean value of 2.12 g/cm3, shown as moderately compacted sandstone. Integrated data such as bulk density, porosity, permeability, Rock Quality Index (RQI), Normalized Porosity Index (NPI), Flow Zone Indicator (FZI), compressive strength, etc. with their relationships indicate that Barail sandstone owing characters to become a good petroleum reservoir. The rock samples consisted mainly of quartz with an insignificant amount of rock fragments and plagioclase feldspar and are categorized as sub-arkose to sub-litharenite. The rock samples also contains lithic (andesine, microcline, muscovite, biotite, etc.) of granitic and gneissic fabric and some volcanic product like aguite, albite, andesine, garnet, spinel and ulvo-spinel indicating the source of nearby orogeny. The euhedral to subhedral shape of the quartz grain in a porphyritic texture, moderately sorted with a smaller amount of clay minerals indicating the moderately mature rock type. The iron oxide border around the quartz grain also indicates that the Barail sandstone was deposited under dry climatic condition.
Possible ecological advantages from use of carbonless magnesia refractory bricks in secondary steelmaking: a framework LCA perspective
Authors: Boenzi F. 
Published: August 2021

AbstractIn the present paper, two types of magnesia-based refractory bricks for the wear lining of a steel ladle furnace are considered, with the aim of comparing their ecological performances. The adopted methodology is the Life Cycle Assessment (LCA) approach from cradle-to-gate of the two brick product systems, in accordance with the European and International Standard EN ISO 14044:2006, and the chosen methodology for the Life Cycle Impact Assessment (LCIA) is ReCiPe 2016, considering the midpoint impact categories and the hierarchist perspective. The conducted study is part of a European industrial research project aimed at investigating the possibility of cleanliness improvement of the steel produced in secondary steelmaking, by reducing the refractory contamination in the steel ladle furnace. The compared refractory bricks consist of a reference, currently used, MgO-C type and a more innovative "carbonless" one, containing magnesia and MA sintered spinel as principal components, on the basis of recipe data provided by the industrial partners of the project. The results attained so far in industrial practice are preliminary, because of the lack of a full-ladle lining experimentation, even though the application of the conceived innovative bricks in the upper part of the slag line of the ladle presents promising aspects. The results of the LCIA comparison between the two brick product systems highlight better performances for all the impact categories, except for "Human carcinogenic toxicity" and markedly for "Mineral resource scarcity." Besides these results, a general framework for shifting the ecological analysis to the steel production is provided. Calculations, referred to the production of one tonne of steel, are therefore performed, involving scenario assumptions not only regarding the refractory consumption but also the forecast operational features of the steel ladle with the "carbonless" lining. In this second set of results, it is clear how the principal contribution to almost all the impact categories is the electrical energy consumption of the ladle, while the contribution from the brick product systems remains important for the above-mentioned worsened impact categories, whose magnitude is strongly dependent on the refractory consumption.
Risk Factors for Death Among Hospitalized Patients Aged 21–64 Years Diagnosed with COVID-19—New York City, March 13–April 9, 2020
Authors: Bushman Dena , Davidson Alexander , Pathela Preeti , Greene Sharon K. , Weiss Don , Reddy Vasudha , Team New York City Fatal Case-Control St , Latash Julia 
Published: August 2021

Abstract
Background
COVID-19 mortality studies have primarily focused on persons aged ≥ 65 years; less is known about decedents aged <65 years.

Methods
We conducted a case-control study among NYC residents aged 21–64 years hospitalized with COVID-19 diagnosed March 13–April 9, 2020, to determine risk factors for death. Case-patients (n=343) were hospitalized decedents with COVID-19 and control-patients (n=686) were discharged from hospitalization with COVID-19 and matched 2:1 to case-patients on age and residential neighborhood. Conditional logistic regression models were adjusted for patient sex, insurance status, and marital status. Matched adjusted odds ratios (aORs) were calculated for selected underlying conditions, combinations of conditions, and race/ethnic group.

Results
Median age of both case-patients and control-patients was 56 years (range: 23–64 years). Having ≥ 1 selected underlying condition increased odds of death 4.45-fold (95% CI: 2.33–8.49). Patients with diabetes; morbid obesity; heart, kidney, or lung disease; cancer; neurologic/neurodevelopmental conditions; mental health conditions; or HIV had significantly increased odds of death. Compared with having neither condition, having both diabetes and obesity or diabetes and heart disease was associated with approximately threefold odds of death. Five select underlying conditions were more prevalent among non-Hispanic Black control-patients than among control-patients of other races/ethnicities.

Conclusions and Relevance
Selected underlying conditions were risk factors for death, and most prevalent among racial/ethnic minorities. Social services; health care resources, including vaccination; and tailored public health messaging are important for COVID-19 prevention. Strengthening these strategies for racial/ethnic minority groups could minimize COVID-19 racial/ethnic disparities.
Harmonic analysis and statistics of the first Galois cohomology group
Authors: Alberts Brandon , O’Dorney Evan 
Published: August 2021

AbstractWe utilize harmonic analytic tools to count the number of elements of the Galois cohomology group $$f\in H^1(K,T)$$

f
∈

H
1

(
K
,
T
)

with discriminant-like invariant $$\text {inv}(f)\le X$$

inv
(
f
)
≤
X

as $$X\rightarrow \infty $$

X
→
∞

. Specifically, Poisson summation produces a canonical decomposition for the corresponding generating series as a sum of Euler products for a very general counting problem. This type of decomposition is exactly what is needed to compute asymptotic growth rates using a Tauberian theorem. These new techniques allow for the removal of certain obstructions to known results and answer some outstanding questions on the generalized version of Malle’s conjecture for the first Galois cohomology group.
Neutrosophic ratio-type estimators for estimating the population mean
Authors: Tahir Zaigham , Khan Hina , Aslam Muhammad , Shabbir Javid , Mahmood Yasar , Smarandache Florentin 
Published: August 2021

AbstractAll researches, under classical statistics, are based on determinate, crisp data to estimate the mean of the population when auxiliary information is available. Such estimates often are biased. The goal is to find the best estimates for the unknown value of the population mean with minimum mean square error (MSE). The neutrosophic statistics, generalization of classical statistics tackles vague, indeterminate, uncertain information. Thus, for the first time under neutrosophic statistics, to overcome the issues of estimation of the population mean of neutrosophic data, we have developed the neutrosophic ratio-type estimators for estimating the mean of the finite population utilizing auxiliary information. The neutrosophic observation is of the form $${Z}_{N}={Z}_{L}+{Z}_{U}{I}_{N}\, {\rm where}\, {I}_{N}\in \left[{I}_{L}, {I}_{U}\right], {Z}_{N}\in [{Z}_{l}, {Z}_{u}]$$

Z
N

=

Z
L

+

Z
U

I
N

where

I
N

∈

I
L

,

I
U

,

Z
N

∈

[

Z
l

,

Z
u

]

. The proposed estimators are very helpful to compute results when dealing with ambiguous, vague, and neutrosophic-type data. The results of these estimators are not single-valued but provide an interval form in which our population parameter may have more chance to lie. It increases the efficiency of the estimators, since we have an estimated interval that contains the unknown value of the population mean provided a minimum MSE. The efficiency of the proposed neutrosophic ratio-type estimators is also discussed using neutrosophic data of temperature and also by using simulation. A comparison is also conducted to illustrate the usefulness of Neutrosophic Ratio-type estimators over the classical estimators.
Projecting the global impact of fossil fuel production from the Former Soviet Union
Authors: Mohr Steve , Wang Jianliang , Ward James , Giurco Damien 
Published: August 2021

AbstractDetailed projections of the Former Soviet Union (FSU) fossil fuel production has been created. Russian production has been modelled at the region (oblast) level where possible. The projections were made using the Geologic Resource Supply-Demand Model (GeRS-DeMo). Low, Best Guess and High scenarios were created. FSU fossil fuels are projected to peak between 2027 and 2087 with the range due to spread of Ultimately Recoverable Resources (URR) values used. The Best Guess (BG) scenario anticipates FSU will peak in 2087 with production over 170 EJ per year. The FSU projections were combined with rest of the world projections (Mohr et al. 2015b), the emissions from the High scenario for the world are similar to the IPCC A1 AIM scenario.
High-Defect-Density Graphite for Superior-Performance Aluminum-Ion Batteries with Ultra-Fast Charging and Stable Long Life
Authors: Kim Jisu , Raj Michael Ruby , Lee Gibaek 
Published: August 2021

AbstractRechargeable aluminum-ion batteries (AIBs) are a new generation of low-cost and large-scale electrical energy storage systems. However, AIBs suffer from a lack of reliable cathode materials with insufficient intercalation sites, poor ion-conducting channels, and poor diffusion dynamics of large chloroaluminate anions (AlCl4− and Al2Cl7−). To address these issues, surface-modified graphitic carbon materials [i.e., acid-treated expanded graphite (AEG) and base-etched graphite (BEG)] are developed as novel cathode materials for ultra-fast chargeable AIBs. AEG has more turbostratically ordered structure covered with abundant micro- to nano-sized pores on the surface structure and expanded interlayer distance (d002 = 0.3371 nm) realized by surface treatment of pristine graphite with acidic media, which can be accelerated the diffusion dynamics and efficient AlCl4− ions (de)-intercalation kinetics. The AIB system employing AEG exhibits a specific capacity of 88.6 mAh g−1 (4 A g−1) and ~ 80 mAh g−1 at an ultra-high current rate of 10 A g−1 (~ 99.1% over 10,000 cycles). BEG treated with KOH solution possesses the turbostratically disordered structure with high density of defective sites and largely expanded d-spacing (d002 = 0.3384 nm) for attracting and uptaking more AlCl4− ions with relatively shorter penetration depth. Impressively, the AIB system based on the BEG cathode delivers a high specific capacity of 110 mAh g−1 (4 A g−1) and ~ 91 mAh g−1 (~ 99.9% over 10,000 cycles at 10 A g−1). Moreover, the BEG cell has high energy and power densities of 247 Wh kg−1 and 44.5 kW kg−1. This performance is one of the best among the AIB graphitic carbon materials reported for chloroaluminate anions storage performance. This finding provides great significance for the further development of rechargeable AIBs with high energy, high power density, and exceptionally long life.
Comparative Study of Hybrid Artificial Intelligence Approaches for Predicting Peak Shear Strength Along Soil-Geocomposite Drainage Layer Interfaces
Authors: Chao Zhiming , Fowmes Gary , Dassanayake S. M. 
Published: August 2021

AbstractPeak shear strength of soil-Geocomposite Drain Layer (GDL) interfaces is an important parameter in the designing and operating related engineering structures. In this paper, a database compiled from 316 large direct shear tests on soil-GDL interfaces has been established. Based on this database, five different machine learning models: Back Propagation Artificial Neural Network (BPANN) and Support Vector Machine (SVM), with hyperparameters optimised by Particle Swarm Optimisation Algorithm (PSO) and Genetic Algorithm (GA), respectively, and Extreme Learning Machine (ELM) optimised by Exhaustive Method, were adopt to assess the peak shear strength of soil-GDL interfaces. Then, a comprehensive investigation and comparison of the predictive performance for the models was conducted. Also, based on the selected optimal machine learning model, sensitivity analysis was conducted, and an empirical equation developed based on it. The research indicated that GA and PSO could significantly increase forecasting precision in a small number of iterations. The BPANN model optimised by PSO has the highest forecasting precision based on the statistics criteria: Root-Mean-Square Error, Correlation Coefficient, Coefficient of Determination, Wilmot’s Index of Agreement, and Mean Absolute Percentage Error. The normal stress has the biggest impact on the peak shear strength, followed by drainage core type, moisture saturation of the soil layer, shearing surface, soil type, consolidation condition, geotextile specification, soil density and drainage core thickness, and the ranking is affected partly by the data distribution of input parameters in the database based on mechanism analysis. An empirical equation developed from the optimal model was proposed to estimate the peak shear strength, which provides convenience for geotechnical engineering personnel with limited knowledge of machine learning technique.