bluuebunny/crossref_metadata_2025_split huggingface dataset:
Process optimization and simulation of biodiesel synthesis from waste cooking oil through supercritical transesterification reaction without catalyst
Authors: Ahmed Anas , Ali Abulhassan , Mubashir Muhammad , Lim Hooi Ren , Khoo Kuan Shiong , Show Pau Loke 
Published: January 2023

Abstract
This study reports optimization and simulation of biodiesel synthesis from waste cooking oil through supercritical transesterification reaction without the use of any catalyst. Although the catalyst enhances the reaction rate but due to the presence of water contents in waste cooking oil, the use of catalyst could cause a negative impact on the biodiesel yield. The transesterification reaction without catalyst also offers the advantage of the reduction of pretreatment cost. This study comprises of two steps; first step involves the development and validation of process simulation scheme. The second step involves the optimization using Response Surface Methodology. Face-centered central composite design of experiments is used for experimental matrix development and subsequent statistical analysis of the results. Analysis of variance (ANOVA) is employed for optimization purpose. In addition, a sensitivity study of the process parameters including pressure, temperature, and molar ration of oil-to-methanol was conducted. The statistical analysis reveals that temperature is the most influential process parameter as compared to pressure and oil-to-methanol molar ratio. The optimization study results in the maximum biodiesel yield (94.16%) at an optimum temperature of 274.8°C, 7.02 bar pressure, and an oil-to-methanol molar ratio of 12.43.
Performance and application of Si/Ti3C2T
x
(MXene) composites in lithium ion battery
Authors: Jiang Tingting , Xiong Qilun , Yang Hao , Chen George Z 
Published: January 2023

Abstract
The excellent theoretical specific charge (lithium) storage capacity and rich abundance of silicon (Si), and the good mechanical and electrical properties of titanium based MXene (Ti3C2T
x
) nanosheets promise high performance composites (Si/Ti3C2T
x
) for negative electrodes (negatrodes) in future lithium ion battery (LIB) applications. In particular, the Si/Ti3C2T
x
composites have been preliminarily shown to offer large and stable cyclic capacity, good rate capability and a highly profitable market prospect. To better understand and help further improve the electrochemical performance of these composites, this review focuses on the electrochemical processes occurring in Si/MXene composites from a material perspective. Different cells used for electrochemical measurements, the related materials properties and the reaction processes and kinetics of Si/MXene composites as negatrode in LIB are reviewed. The perspective is also discussed for practical applications in flexible electronic devices and automobiles.
Autonomous victim detection system based on deep learning and multispectral imagery
Authors: Cruz Ulloa Christyan , Garrido Luis , del Cerro Jaime , Barrientos Antonio 
Published: January 2023

Abstract
Post-disaster environments resulting from catastrophic events, leave sequels such as victims trapped in debris, which are difficult to detect by rescuers in a first inspection. Technological advances in electronics and perception have allowed the development of versatile and powerful optical sensors capable of capturing light in spectrums that humans cannot. new deep learning techniques, such as convolutional neural networks (CNNs), has allowed the generation of network models capable of autonomously detecting specific image patterns according to previous training. This work introduces an autonomous victim detection system to be deployed by using search and rescue robots. The proposed system defines new indexes based on combining the multispectral bands (Blue, Green, Red, Nir, Red Edge) to obtain new multispectral images where relevant characteristics of victims and the environment are highlighted. CNNs have been used as a second phase for automatically detecting victims in these new multispectral images. A qualitative and quantitative analysis of new indexes proposed by the authors has been carried out to evaluate their efficiency in contrast to the state-of-the-art ones. A data set has been generated to train different CNN models based on the best obtained index to analyze their effectiveness in detecting victims. The results show an efficiency of 92% in automatically detecting victims when applying the best multispectral index to new data. This method has also been contrasted with others based on thermal and RGB imagery to detect victims, where it has been proven that it generates better results in situations of outdoor environments and different weather conditions.
Environmental Virtue Aesthetics
Authors: Hall Nicole , Brady Emily 
Published: January 2023

AbstractHow should we characterize the interaction between moral and aesthetic values in the context of environmental aesthetics? This question is important given the urgency of many environmental problems and the particular role played by aesthetic value in our experience of environment. To address this question, we develop a model of Environmental Virtue Aesthetics (EVA) that, we argue, offers a promising alternative to current theories in environmental aesthetics with respect to the relationship between aesthetics and ethics. EVA counters environmental aesthetic theories that focus more narrowly on scientific knowledge and ground aesthetic value in ways that obfuscate pluralistic modes of appreciation of and relationships with natural and semi-natural environments. To develop EVA, we work with a revised notion of respect and engage with ideas concerning the development of aesthetic sensibilities, care, and virtuous aesthetic appreciation. EVA has the potential to support forms of human-nature co-flourishing, as well as constituting an aesthetic grounding for ecological citizenship.
Comparison of falls and cost-effectiveness of the group versus individually delivered Lifestyle-integrated Functional Exercise (LiFE) program: final results from the LiFE-is-LiFE non-inferiority trial
Authors: Jansen Carl-Philipp , Gottschalk Sophie , Nerz Corinna , Labudek Sarah , Kramer-Gmeiner Franziska , Klenk Jochen , Clemson Lindy , Todd Chris , Dams Judith , König Hans-Helmut , Becker Clemens , Schwenk Michael 
Published: January 2023

Abstract

Background
the individually delivered Lifestyle-integrated Functional Exercise (LiFE) was shown to improve physical activity (PA) and reduce fall incidence, however being rather resource-consuming due to one-to-one delivery. A potentially less resource-intensive group format (gLiFE) was developed and compared against the original program, considering higher risk of falling due to possible PA enhancement.

Objective
to investigate non-inferiority in terms of PA-adjusted fall risk and cost-effectiveness of gLiFE at 12-month follow-up.

Design
single-blinded, randomised, multi-centre non-inferiority trial.

Setting
community.

Subjects
in total, 309 adults aged 70+ years at risk of or with history of falling; n = 153 in gLiFE, n = 156 in LiFE.

Methods
LiFE was delivered one-to-one at the participants’ homes, gLiFE in a group. PA-adjusted fall risk was analysed using negative binomial regression to compare incidence rate ratios (IRR). Cost-effectiveness was presented by incremental cost-effectiveness ratios and cost-effectiveness acceptability curves, considering quality-adjusted life years, PA and falls as effect measures. Secondary analyses included PA (steps/day) and fall outcomes.

Results
non-inferiority was inconclusive (IRR 0.96; 95% confidence interval, CI 0.67; 1.37); intervention costs were lower for gLiFE, but cost-effectiveness was uncertain. gLiFE participants significantly increased PA (+1,090 steps/day; 95% CI 345 and 1.835) versus insignificant increase in LiFE (+569, 95% CI −31; 1,168). Number of falls and fallers were reduced in both formats.

Conclusion
non-inferiority of gLiFE compared with LiFE was inconclusive after 12 months. Increases in PA were clinically relevant in both groups, although nearly twice as high in gLiFE. Despite lower intervention costs of gLiFE, it was not clearly superior in terms of cost-effectiveness.
Examining the effect of interventions in emergency care for older people using a system dynamics decision support tool
Authors: England Tracey , Brailsford Sally , Evenden Dave , Street Andrew , Maynou Laia , Mason Suzanne M , Preston Louise , Burton Christopher , Van Oppen James , Conroy Simon 
Published: January 2023

Abstract

Background
Rising demand for Emergency and Urgent Care is a major international issue and outcomes for older people remain sub-optimal. Embarking upon large-scale service development is costly in terms of time, energy and resources with no guarantee of improved outcomes; computer simulation modelling offers an alternative, low risk and lower cost approach to explore possible interventions.

Method
A system dynamics computer simulation model was developed as a decision support tool for service planners. The model represents patient flow through the emergency care process from the point of calling for help through ED attendance, possible admission, and discharge or death. The model was validated against five different evidence-based interventions (geriatric emergency medicine, front door frailty, hospital at home, proactive care and acute frailty units) on patient outcomes such as hospital-related mortality, readmission and length of stay.

Results
The model output estimations are consistent with empirical evidence. Each intervention has different levels of effect on patient outcomes. Most of the interventions show potential reductions in hospital admissions, readmissions and hospital-related deaths.

Conclusions
System dynamics modelling can be used to support decisions on which emergency care interventions to implement to improve outcomes for older people.
multiMiAT: an optimal microbiome-based association test for multicategory phenotypes
Authors: Sun Han , Wang Yue , Xiao Zhen , Huang Xiaoyun , Wang Haodong , He Tingting , Jiang Xingpeng 
Published: January 2023

AbstractMicrobes can affect the metabolism and immunity of human body incessantly, and the dysbiosis of human microbiome drives not only the occurrence but also the progression of disease (i.e. multiple statuses of disease). Recently, microbiome-based association tests have been widely developed to detect the association between the microbiome and host phenotype. However, the existing methods have not achieved satisfactory performance in testing the association between the microbiome and ordinal/nominal multicategory phenotypes (e.g. disease severity and tumor subtype). In this paper, we propose an optimal microbiome-based association test for multicategory phenotypes, namely, multiMiAT. Specifically, under the multinomial logit model framework, we first introduce a microbiome regression-based kernel association test for multicategory phenotypes (multiMiRKAT). As a data-driven optimal test, multiMiAT then integrates multiMiRKAT, score test and MiRKAT-MC to maintain excellent performance in diverse association patterns. Massive simulation experiments prove the success of our method. Furthermore, multiMiAT is also applied to real microbiome data experiments to detect the association between the gut microbiome and clinical statuses of colorectal cancer as well as for diverse statuses of Clostridium difficile infections.
SPNE: sample-perturbed network entropy for revealing critical states of complex biological systems
Authors: Zhong Jiayuan , Ding Dandan , Liu Juntan , Liu Rui , Chen Pei 
Published: January 2023

AbstractComplex biological systems do not always develop smoothly but occasionally undergo a sharp transition; i.e. there exists a critical transition or tipping point at which a drastic qualitative shift occurs. Hunting for such a critical transition is important to prevent or delay the occurrence of catastrophic consequences, such as disease deterioration. However, the identification of the critical state for complex biological systems is still a challenging problem when using high-dimensional small sample data, especially where only a certain sample is available, which often leads to the failure of most traditional statistical approaches. In this study, a novel quantitative method, sample-perturbed network entropy (SPNE), is developed based on the sample-perturbed directed network to reveal the critical state of complex biological systems at the single-sample level. Specifically, the SPNE approach effectively quantifies the perturbation effect caused by a specific sample on the directed network in terms of network entropy and thus captures the criticality of biological systems. This model-free method was applied to both bulk and single-cell expression data. Our approach was validated by successfully detecting the early warning signals of the critical states for six real datasets, including four tumor datasets from The Cancer Genome Atlas (TCGA) and two single-cell datasets of cell differentiation. In addition, the functional analyses of signaling biomarkers demonstrated the effectiveness of the analytical and computational results.
Residential turnover and crime—Evidence from administrative data for England and Wales
Authors: Braakmann Nils 
Published: January 2023

Abstract
This article combines administrative data on housing transactions with monthly crime data for the years 2014–18 to investigate the link between residential turnover and crime. Using a panel of 34,753 small neighbourhoods in England and Wales as well as street-level data for London, estimates from models with multiple fixed effects suggest that higher turnover is associated with higher overall crime rates. These effects are small and driven by increases in property and violent crime. Using information on price growth, I document differential effects for high-turnover, high price growth (‘attractive’) and high turnover, low price growth (‘declining’) areas.
Long-term clinical trials of biologics in plaque psoriasis demonstrate heterogeneous study designs
Authors: Grolleau Chloé , Le Cleach Laurence , Shourick Jason , Sbidian Emilie , Afach Sivem 
Published: January 2023

Numerous network meta-analyses have provided comparative efficacy and safety data for treatments in psoriaasis over a short period (8-24 weeks). So, we conducted a systematic review to map the design and synthesize all 1-year efficacy and safety data of biologic treatments for moderate-to-severe psoriasis from the randomized controlled trials (RCTs) included in the Cochrane review (Sbidian et al., 2022).
Among the 81 RCTs included, many different designs are presented after the induction phase. Within a single trial, each arm (placebo, intervention, active comparator) could have a different design: single randomization; crossover; re-randomization. In addition, there was selection of patients into each arm based on the level of PASI response achieved or PGA achieved.
A milestone reached in the standardization of lichen sclerosus trial outcomes
Authors: Thorlacius Linnea , Alam Murad 
Published: January 2023

CORALS (Core Outcomes for Research in Lichen Sclerosus) reached an important milestone with their final consensus on three quite broad core domains: clinical signs, symptoms and LS specific quality of life.
This commentary illuminates why there is need for more methodological guidance in core outcome set development processes regarding: (1) the appropriate level of granularity during the domain definition process; and (2) the preferred number of final core domains.
Direct brain recordings suggest a causal subsequent-memory effect
Authors: Rubinstein Daniel Y , Weidemann Christoph T , Sperling Michael R , Kahana Michael J 
Published: January 2023

AbstractEndogenous variation in brain state and stimulus-specific evoked activity can both contribute to successful encoding. Previous studies, however, have not clearly distinguished among these components. We address this question by analysing intracranial EEG recorded from epilepsy patients as they studied and subsequently recalled lists of words. We first trained classifiers to predict recall of either single items or entire lists and found that both classifiers exhibited similar performance. We found that list-level classifier output—a biomarker of successful encoding—tracked item presentation and recall events, despite having no information about the trial structure. Across widespread brain regions, decreased low- and increased high-frequency activity (HFA) marked successful encoding of both items and lists. We found regional differences in the hippocampus and prefrontal cortex, where in the hippocampus HFA correlated more strongly with item recall, whereas, in the prefrontal cortex, HFA correlated more strongly with list performance. Despite subtle differences in item- and list-level features, the similarity in overall classification performance, spectral signatures of successful recall and fluctuations of spectral activity across the encoding period argue for a shared endogenous process that causally impacts the brain’s ability to learn new information.
Consensus recommendations for COVID-19-related myocarditis in athletes: proof of concept—case report
Authors: Abdelfattah Omar M , Mathur Tarun , Martinez Matthew W 
Published: January 2023

AbstractBackgroundPost-viral myocarditis has been associated with sudden cardiac death in athletes. Since the beginning of the COVID-19 pandemic, the concern of post-viral myocarditis impacting the professional athletic community has been present.Case summaryAn elite-level basketball player presented after a positive COVID-19 test with findings consistent with ventricular tachycardia related to myocardial fibrosis/scar from a COVID-19-related myocarditis. Although rare, COVID-19 myocarditis can occur. This case illustrates how the consensus guidelines for return-to-play correctly identified the player as high risk with appropriate downstream evaluation by cardiac magnetic resonance (CMR) imaging. The stepwise approach is illustrated in this case and highlights the utility and success of the algorithm when approaching athletes with COVID-19-related myocarditis risk and determining a return to exercise.DiscussionDiligence is required to identify competitive athletes with features suggestive of myocarditis at the initial presentation and with the return to exercise. Cardiopulmonary symptoms in the setting of recent COVID-19 infection should prompt additional testing in a stepwise fashion and often benefit from CMR in addition to the triad testing with electrocardiography, echocardiography, and cardiac troponin measurement to further investigate clinical presentations of COVID-19-related myocarditis.
Benedicamus Domino: delight in singing praise to God at Las Huelgas of Burgos
Authors: Catalunya David 
Published: January 2023

Abstract
The Las Huelgas Codex (Hu) features one of the most varied collections of medieval polyphony in Europe. It contains the repertory of Mass Ordinary settings, sequences, organa, conductus and motets that was in use at the royal nunnery of Las Huelgas in Burgos during the 13th and 14th centuries. While most of this repertory is known from other earlier sources, several of the numerous settings of the Benedicamus Domino in Hu are unique pieces that reflect an apparently local practice. Closer inspection reveals, however, that nearly all of these ‘unique’ Benedicamus settings were created by borrowing and reworking musical material from other sections of the manuscript. This article considers the Benedicamus Domino settings as a musically cohesive sub-repertory in Hu, showcasing a rich array of reworking techniques. The article also considers the ritual function of the Benedicamus Domino within the liturgy of the royal convent, as well as the performance context and the distribution of singing duties between the nuns and the clerics of the monastery.
Results from rapid-cycle recurrent genomic selection in spring bread wheat
Authors: Dreisigacker Susanne , Pérez-Rodríguez Paulino , Crespo-Herrera Leonardo , Bentley Alison R , Crossa José 
Published: January 2023

Abstract
Genomic selection (GS) in wheat breeding programs is of great interest for predicting the genotypic values of individuals, where both additive and nonadditive effects determine the final breeding value of lines. While several simulation studies have shown the efficiency of rapid-cycling GS strategies for parental selection or population improvement, their practical implementations are still lacking in wheat and other crops. In this study, we demonstrate the potential of rapid-cycle recurrent GS (RCRGS) to increase genetic gain for grain yield (GY) in wheat. Our results showed a consistent realized genetic gain for GY after 3 cycles of recombination (C1, C2, and C3) of bi-parental F1s, when summarized across 2 years of phenotyping. For both evaluation years combined, genetic gain through RCRGS reached 12.3% from cycle C0 to C3 and realized gain was 0.28 ton ha−1 per cycle with a GY from C0 (6.88 ton ha−1) to C3 (7.73 ton ha−1). RCRGS was also associated with some changes in important agronomic traits that were measured (days to heading, days to maturity, and plant height) but not selected for. To account for these changes, we recommend implementing GS together with multi-trait prediction models.