bluuebunny/crossref_metadata_2025_split huggingface dataset:
Communicating distress: suicide threats/gestures among clinical and community youth
Authors: Robinson Kealagh , Scharinger Christian , Brown Rebecca C. , Plener Paul L. 
Published: February 2022

AbstractAlthough self-injurious thoughts and behaviors are a global health concern, little is known about suicidal threat/gesture(s) where a person leads others to believe they want to end their lives when they have no intention to do so. This study assessed the lifetime prevalence of self-injurious thoughts and behaviors among both community adolescents (n = 1117) and in clinical youth (n = 191). Suicide threats/gestures were common among youth; 12.2% of community adolescents and 18.0% of clinical youth reporting having made a suicide threat/gesture, most commonly in the context of other self-injurious thoughts and behaviors. Across both samples, suicide threats/gestures were not uniquely associated with suicide attempts, and youth who reported suicide threats/gestures in the context of a history of self-harm or suicide plan(s) were no more likely to report a history of suicide attempt(s). Suicide threats/gestures were distinguished from suicide attempts in that they primarily fulfilled positive social functions, rather than autonomic functions. Findings suggest that suicidal threats/gestures are common in both community and clinical youth, and are not uniquely associated with suicide attempts, but rather function to communicate distress to others.
Development and validation of the Myasthenia Gravis TeleScore (MGTS)
Authors: Pasqualin F. , Guidoni S. V. , Albertini E. , Ermani M. , Frangiamore R. , Vanoli F. , Antozzi C. , Mantegazza R. , Bonifati D. M. 
Published: February 2022

Abstract
Objective
The aim of our study was to validate the Myasthenia Gravis TeleScore (MGTS), a scale for the evaluation of MG patients in telemedicine.

Introduction
COVID-19 pandemic has boosted telemedicine in clinical practice. It could be crucial in the care of neurological patients with chronic disease. However, there is a lack of validated disease-specific tools to evaluate MG patients in telemedicine.

Methods
The MGTS included ten items divided in four districts: ocular, generalized muscular strength, bulbar, and respiratory. Patients were assessed with two different scales: the MGTS and the INCB-MG chosen as a reference from which MGTS was partially derived. Visit in presence with INCB-MG and televisit with MGTS were performed consecutively. Televisit was conducted by another neurologist between two rooms. A blind method was adopted. The strength of correlation was determined by the correlation coefficient (r); analysis of covariance (ANOVA—Kruskal–Wallis test) was used to compare subgroups. Significance was set to p < 0.05.

Results
One hundred thirty-one patients were included in the study, 71 females and 60 males. The Spearman correlation coefficient between the INCB-MG scale and the MGTS was 0.825 (p < 0.001), indicating a very strong correlation between them. Different items showed different correlations from low to high (0.32 to 0.80). As expected, correlation was lower between items with different evaluation modality (anamnestic vs clinical).

Discussion
The MGTS demonstrated a good correlation with INCB-MG, reliability and construct validity.
Die Körordnung im deutschen und Europäischen Recht
Authors: Krimpove Dieter , Schlief Till 
Published: February 2022

ZusammenfassungPferdezucht ist nicht nur ein Wirtschaftsfaktor, sie sollte auch die Natur des Pferdes bewahren und
seine natürlichen Eigenschaften artgerecht fördern. Insofern enthält das Pferdezuchtrecht
immer auch den Aspekt des Tierschutzrechtes. Da bereits heute das Europäische Recht sowohl das Equiden-Zuchtrecht
als auch das Tierschutzrecht dominiert, stellt der Beitrag die einschlägigen Rechtsnormen und dessen
Zusammenspiel vor. Interessant erscheint hier, dass das Ineinandergreifen des Europäischen und des
deutschen Rechts zu unterschiedlichen Anreizen hinsichtlich der nationalen Bestimmung von Zuchtmerkmalen
führt.
Technology-based comparative life cycle assessment for palm oil industry: the case of Nigeria
Authors: Anyaoha Kelechi E. , Zhang Lulu 
Published: February 2022

AbstractOil palm dominates global oil production, trade, and consumption. Nigeria is one of the leading palm oil producers and consumers. A significant challenge of the palm oil industry is to reduce the environmental impacts (e.g. pollution and carbon footprint) and integrate a circular economy in operation. This study aims to comparatively quantify the environmental impacts of technologies used by different mills. We applied a life cycle assessment in the case of Nigeria. The study covers the reception and processing of fresh fruit bunch (FFB) to end-product palm oil. The inputs include generated empty fruit bunch (EFB), mesocarp fibre, palm kernel shell, palm oil mill effluent, diesel, water and all outputs to the environment for a functional unit of 1-tonne FFB. The results showed that large-scale mills perform worse (468 kg CO2-eq per t FFB) than the semi-mechanised and smallholder mills in effects on climate change but better in the other impact categories, including human toxicity, ecotoxicity, and fine particulate matter formation. In large-scale mills, the climate change impacts decrease by 75% when the raw palm oil mill effluent (POME) is used in composting EFB. Similarly, climate change impacts reduce by 44% when biogas from POME substitutes diesel in the semi-mechanised and smallholder mills. We conclude that regulatory measures are needed to ensure improved management practices in the production processes. Particular attention should be paid to the generation and reuse of biomass and POME. This study provides a handy reference to assist the sustainable energy transition in Nigeria’s and other parts of sub-Saharan Africa’s oil palm industry to mitigate climate change and form a cleaner bioeconomy.
Positive risk balance: a comprehensive framework to ensure vehicle safety
Authors: Kauffmann Nina , Fahrenkrog Felix , Drees Ludwig , Raisch Florian 
Published: February 2022

AbstractThe introduction of automated vehicles promises an increase in traffic safety. Prior to its launch proof of the anticipated reduction in the sense of a positive risk balance compared with human driving performance is required from various stakeholders such as the European Union Commission, the German Ethic Commission, and the ISO TR 4804. To meet this requirement and to generate acceptance by the public and the regulatory authorities, a qualitative Risk- Benefit framework has been defined. This framework is based on literature research on approaches applied in other disciplines. This report depicts the framework, adapted from the pharmaceutical sector called PROACT-URL which serves as a structured procedure to demonstrate a positive risk balance in an understandable and transparent manner. The qualitative framework needs to be turned in quantitative methods once it should be applied. Therefore, two steps of the framework are discussed in more detail: First, the definition of adequate development thresholds that are required at an early stage of the development. Second the simulation-based assessment to prove the positive risk balance prior to the market introduction.
Feature-weighted categorized play across symmetric games
Authors: LiCalzi Marco , Mühlenbernd Roland 
Published: February 2022

AbstractExperimental game theory studies the behavior of agents who face a stream of one-shot games as a form of learning. Most literature focuses on a single recurring identical game. This paper embeds single-game learning in a broader perspective, where learning can take place across similar games. We posit that agents categorize games into a few classes and tend to play the same action within a class. The agent’s categories are generated by combining game features (payoffs) and individual motives. An individual categorization is experience-based, and may change over time. We demonstrate our approach by testing a robust (parameter-free) model over a large body of independent experimental evidence over $$2 \times 2$$

2
×
2

symmetric games. The model provides a very good fit across games, performing remarkably better than standard learning models.
Differences in Barriers to Healthcare and Discrimination in Healthcare Settings Among Undocumented Immigrants by Deferred Action for Childhood Arrivals (DACA) Status
Authors: Woofter Rebecca , Sudhinaraset May 
Published: February 2022

AbstractUndocumented immigrants face barriers to and discrimination in healthcare, but those with Deferred Action for Childhood Arrivals (DACA) status may fare better. This analysis uses the cross-sectional BRAVE Study of young undocumented Latinx and Asian immigrants to examine differences in barriers to and discrimination in healthcare by DACA status. A majority of respondents experienced financial, language, and cultural barriers, and up to half experienced documentation status barriers, discrimination when seeking healthcare or by a health provider, and negative experiences related to documentation status. In multivariable analyses, DACA recipients have over 90% lower odds of language and cultural barriers, approximately 80% lower odds of discrimination when seeking healthcare and by a health provider, and approximately 70% lower odds of documentation status barriers and negative experience related to documentation status compared to nonrecipients. These findings indicate that DACA recipients experience fewer barriers to healthcare and discrimination in healthcare compared to nonrecipients.
Optimal Control Problems with Sparsity for Tumor Growth Models Involving Variational Inequalities
Authors: Colli Pierluigi , Signori Andrea , Sprekels Jürgen 
Published: February 2022

AbstractThis paper treats a distributed optimal control problem for a tumor growth model of Cahn–Hilliard type. The evolution of the tumor fraction is governed by a variational inequality corresponding to a double obstacle nonlinearity occurring in the associated potential. In addition, the control and state variables are nonlinearly coupled and, furthermore, the cost functional contains a nondifferentiable term like the $$L^1$$

L
1

-norm in order to include sparsity effects which is of utmost relevance, especially time sparsity, in the context of cancer therapies as applying a control to the system reflects in exposing the patient to an intensive medical treatment. To cope with the difficulties originating from the variational inequality in the state system, we employ the so-called deep quench approximation in which the convex part of the double obstacle potential is approximated by logarithmic functions. For such functions, first-order necessary conditions of optimality can be established by invoking recent results. We use these results to derive corresponding optimality conditions also for the double obstacle case, by deducing a variational inequality in terms of the associated adjoint state variables. The resulting variational inequality can be exploited to also obtain sparsity results for the optimal controls.
Calcium Enabled Remote Loading of a Weak Acid Into pH-sensitive Liposomes and Augmented Cytosolic Delivery to Cancer Cells via the Proton Sponge Effect
Authors: Yang Mimi M. , Yarragudi Sasi Bhushan , Jamieson Stephen M. F. , Tang Mingtan , Wilson William R. , Wu Zimei 
Published: February 2022

AbstractWhile delivery of chemotherapeutics to cancer cells by nanomedicines can improve therapeutic outcomes, many fail due to the low drug loading (DL), poor cellular uptake and endosomal entrapment. This study investigated the potential to overcome these limitations using pH-sensitive liposomes (PSL) empowered by the use of calcium acetate. An acidic dinitrobenzamide mustard prodrug SN25860 was used as a model drug, with non pH-sensitive liposomes (NPSL) as a reference. Calcium acetate as a remote loading agent allowed to engineer PSL- and NPSL-SN25860 with DL of > 31.1% (w/w). The IC50 of PSL-SN25860 was 21- and 141-fold lower than NPSL and free drug, respectively. At 48 h following injection of PSL-SN25860, NPSL-SN25860 and the free drug, drug concentrations in EMT6-nfsB murine breast tumors were 56.3 µg/g, 6.76 µg/g and undetectable (< 0.015 µg/g), respectively (n = 3). Meanwhile, the ex vivo tumor clonogenic assay showed 9.1%, 19.4% and 42.7% cell survival in the respective tumors. Live-cell imaging and co-localization analysis suggested endosomal escape was accomplished by destabilization of PSL followed by release of Ca2+ in endosomes allowing induction of a proton sponge effect. Subsequent endosomal rupture was observed approximately 30 min following endocytosis of PSL containing Ca2+. Additionally, calcium in liposomes promoted internalization of both PSL and NPSL. Taken together, this study demonstrated multifaceted functions of calcium acetate in promoting drug loading into liposomes, cellular uptake, and endosomal escape of PSL for efficient cytoplasmic drug delivery. The results shed light on designing nano-platforms for cytoplasmic delivery of various therapeutics.
Graphical abstract
Collaborative knowledge: Where the distributed and commitment models merge
Authors: Palermos Spyridon Orestis 
Published: February 2022

AbstractWithin analytic philosophy, the existence of collective knowledge has been motivated by means of two apparently distinct, and in direct competition with one another, theoretical approaches: (i) the commitment model and (ii) the distributed model. This paper agues, however, that to fully account for collaborative knowledge—i.e., a special kind of collective knowledge—both models are required. In other words, there is at least one kind of collective knowledge, the account of which requires treating the two models not as competitors but as complementary to each other. If that’s correct, not only can we gain a deeper understanding of the specifics surrounding collaborative knowledge but also a clearer picture of the broader debate surrounding collective knowledge.
Rapid HILIC-Z ion mobility mass spectrometry (RHIMMS) method for untargeted metabolomics of complex biological samples
Authors: Pičmanová Martina , Moses Tessa , Cortada-Garcia Joan , Barrett Georgina , Florance Hannah , Pandor Sufyan , Burgess Karl 
Published: February 2022

Abstract
Introduction
Recent advances in high-throughput methodologies in the ‘omics’ and synthetic biology fields call for rapid and sensitive workflows in the metabolic phenotyping of complex biological samples.

Objective
The objective of this research was to evaluate a straightforward to implement LC–MS metabolomics method using a commercially available chromatography column that provides increased throughput. Reducing run time can potentially impact chromatography and therefore the effects of ion mobility spectrometry to expand peak capacity were also evaluated. Additional confidence provided via collision cross section measurements for detected features was also explored.

Methods
A rapid untargeted metabolomics workflow was developed with broad metabolome coverage, combining zwitterionic-phase hydrophilic interaction chromatography (HILIC-Z) with drift tube ion mobility-quadrupole time-of-flight (DTIM-qTOF) mass spectrometry. The analytical performance of our method was explored using extracts from complex biological samples, including a reproducibility study on chicken serum and a simple comparative study on a bacterial metabolome.

Results
The method is acronymised RHIMMS for rapid HILIC-Z ion mobility mass spectrometry. We present the RHIMMS workflow starting with data acquisition, followed by data processing and analysis. RHIMMS demonstrates improved chromatographic separation for a selection of metabolites with wide physicochemical properties while maintaining reproducibility at better than 20% over 200 injections at 3.5 min per sample for the selected metabolites, and a mean of 13.9% for the top 50 metabolites by intensity. Additionally, the combination of rapid chromatographic separation with ion mobility allows improved annotation and the ability to distinguish isobaric compounds.

Conclusion
Our results demonstrate RHIMMS to be a rapid, reproducible, sensitive and high-resolution analytical platform that is highly applicable to the untargeted metabolomics analysis of complex samples.
Potentials of post-mortem CT investigations during SARS-COV-2 pandemic: a narrative review
Authors: Filograna Laura , Manenti Guglielmo , Ampanozi Garyfalia , Calcagni Antonello , Ryan Colleen Patricia , Floris Roberto , Thali Michael John 
Published: February 2022

AbstractIn December 2019, a new coronavirus, SARS-COV-2, caused a cluster of cases of pneumonia in China, and rapidly spread across the globe. It was declared a pandemic by the World Health Organization on March 11th, 2020. Virtual autopsy by post-mortem CT (PMCT) and its ancillary techniques are currently applied in post-mortem examinations as minimally or non-invasive techniques with promising results. In this narrative review, we speculate on the potentials of PMCT and its ancillary techniques, as a viable investigation technique for analysis of suspected or confirmed SARS-COV-2 deaths. An online literature search was performed by using three prefix search terms (postmortem, post-mortem, post mortem) individually combined with the suffix radiology, imaging, computed tomography, CT and with the search terms ‘SARS-CoV-2’ and ‘COVID-19’ to identify papers about PMCT and its ancillary techniques in SARS-COV-2 positive cadavers. PMCT findings suggestive for pulmonary COVID-19 in deceased positive SARS-COV-2 infection are reported in the literature. PMCT ancillary techniques were never applied in such cases. PMCT imaging of the lungs has been proposed as a pre-autopsy screening method for SARS-COV-2 infection. Further studies are needed to ascertain the value of PMCT in determining COVID-19 as the cause of death without autopsy histopathological confirmation. We advocate the application of PMCT techniques in the study of ascertained or suspected SARS-COV-2 infected deceased individuals as a screening technique and as a method of post-mortem investigation, to augment the numbers of case examined and significantly reducing infection risk for the operators.
Is robotic lobectomy cheaper? A micro-cost analysis
Authors: Shanahan Ben , Kreaden Usha S. , Sorensen Jan , Stamenkovic Steven , Redmond Karen C. 
Published: February 2022

AbstractHigher capital costs and operating room costs associated with Lobectomy via Robot Assisted Thoracic Surgery (RATS) have previously been suggested as the principal contributors to the elevated overall cost. This study uses a micro-costing approach to a previous analysis of clinical outcomes of RATS, Video-Assisted Thoracic Surgery (VATS) and Open Lobectomy to evaluate the most significant cost drivers for the higher cost of robot-assisted lobectomy. A micro-costing model was developed to reflect the pathway of patients from day of surgery through the first 30 days following lobectomy. Costs were provided for RATS, VATS and Open approaches. Sensitivity analysis was performed specifically in the area of staff costs. A threshold sensitivity analysis of the overall cost components was also performed. Total cost per case for the RATS approach was €13,321 for the VATS approach €11,567, and for the Open approach €12,582. The overall cost differences were driven primarily by the elevated consumable costs associated with RATS Lobectomy. Capital costs account for a relatively small proportion of the per-case cost difference. This study presents a detailed analysis of the cost drivers for lobectomy, modelled for the three primary surgical approaches. We believe this is a useful tool for surgeons, hospital management, and service commissioning agencies to accurately and comprehensively determine where cost savings can be applied in their programme to improve the cost-effectiveness of RATS lobectomy.
Machine tool process monitoring by segmented timeseries anomaly detection using subprocess-specific thresholds
Authors: Netzer Markus , Palenga Yannic , Fleischer Jürgen 
Published: February 2022

AbstractTime series data generated by manufacturing machines during processing is widely used in mass part production to assess if processes run without errors. Systems that make use of this data use machine learning approaches for flagging a time series as a deviation from normal behaviour. In single part production, the amount of data generated is not sufficient for learning-based classification. Here, methods often focus on global signal variance but have trouble finding anomalies that present as local signal deviations. The referencing of the process states of the machine is usually performed by state indexing which, however, is not sufficient in highly flexible production plants. In this paper, a system that learns granular patterns in time series based on mean shift clustering is used for detecting processing segments in varying machine conditions. An anomaly detection then finds deviating patterns based on the previously identified processing segments. The anomalies can then be labeled by a human-in-the-loop approach for enabling future anomaly classification using a combination of machine learning algorithms. The method of anomaly detection is validated using an industrial machine tool and multiple test series.
Immunocompetent cells in durable ventricular assist device-implanted non-ischaemic dilated cardiomyopathy
Authors: Koga-Ikuta Ayumi , Fukushima Satsuki , Ishibashi-Ueda Hatsue , Tadokoro Naoki , Kakuta Takashi , Watanabe Takurya , Fukushima Norihide , Suzuki Ken , Fukui Toshihiro , Fujita Tomoyuki 
Published: February 2022

Abstract
Objective
Because the presence of immunocompetent cells in the myocardium is associated with the pathological stage and/or myocardial viability, we explored relationships between functional recovery after left ventricular assist device implantation and the distribution of immunocompetent cells in non-ischaemic dilated cardiomyopathy patients.

Methods
We reviewed 50 consecutive dilated cardiomyopathy patients implanted with HeartMate II at our institute between April 2013 and December 2018 who were treated with optimal medical therapy during left ventricular assist device support. Patients were stratified by improvement of the left ventricular ejection fraction at 6 months after implantation: ≥ 10% increase (Gr ≥ 10%), 5–10% (Gr 5–10%), and ≤ 5% (Gr ≤ 5%). T cells and macrophages were evaluated in the apical myocardium after left ventricular assist device implantation.

Results
During left ventricular assist device support, 12 patients underwent heart transplantation and 2 patients died. Four patients with Gr ≤ 5% were readmitted because of congestive heart failure, but none with Gr ≥ 10%. Macrophages and T cells in the left ventricular myocardium with Gr ≥ 10% were significantly more present compared to those in other groups.

Conclusions
The distribution of immunocompetent cells in the left ventricular myocardium might predict myocardial viability of this pathology after implantation.
CFD Modeling of the Melting Behavior of a Fayalitic Slag
Authors: Obiso D. , Yasuda K. , Voigt A. D. , Schreiner M. , Massoudi Farid M. , Richter A. 
Published: February 2022

AbstractThe melting behavior of a fayalitic slag was investigated with computational fluid dynamics and validated with experimental data. A heating microscope was employed to perform a typical ash melting behavior (AMB) test, in order to gain information about the melting behavior of the slag. The numerical approach is based on using the volume of fluid (VOF) method, in order to track the interface between the slag and the gas phases, and on the enthalpy–porosity model, in order to simulate the slag as a phase change material (PCM). The combined VOF-PCM model was therefore applied to perform a parameter study on the mushy zone constant $$A_{\rm mushy}$$

A
mushy

, which enters the equations of the enthalpy–porosity sub-model and is an a priori unknown. The goal of the investigation was to determine the correct value for $$A_{\rm mushy}$$

A
mushy

, by comparing the numerical results to the AMB test.