bluuebunny/crossref_metadata_2025_split huggingface dataset:
A critical look at challenges and future scopes of bioactive compounds and their incorporations in the food, energy, and pharmaceutical sector
Authors: Pai Sanidhya , Hebbar Akshatha , Selvaraj Subbalaxmi 
Published: March 2022

AbstractBioactive compounds refer to secondary metabolites extracted from plants, fungi, microbes, or animals. Besides having pharmacological or toxicological effects on organisms leading to utilization in food and pharmaceutical industries, the discovery of novel properties of such compounds has led to the diversification of their applications, ranging from cosmetics and functionalized biomaterials to bioremediation and alternate fuels. Conventional time-consuming and solvent-intensive methods of extraction are increasingly being replaced by green solvents such as ionic liquids, supercritical fluids, and deep eutectic solvents, as well as non-conventional methods of extraction assisted by microwaves, pulse electric fields, enzymes, ultrasound, or pressure. These methods, along with advances in characterization and optimization strategies, have boosted the commercial viability of extraction especially from agrowastes and organic residues, promoting a sustainable circular economy. Further development of microfluidics, optimization models, nanoencapsulation, and metabolic engineering are expected to overcome certain limitations that restrict the growth of this field, in the context of improving screening, extraction, and economy of processes, as well as retaining biodiversity and enhancing the stability and functionality of such compounds. This review is a compilation of the various extraction and characterization methods employed for bioactive compounds and covers major applications in food, pharmacy, chemicals, energy, and bioremediation. Major limitations and scope of improvement are also discussed.
Graphical abstract
The pancreatic exocrine function in patients with pancreatic endocrine insufficiency: the evaluation with cine-dynamic magnetic resonance cholangiopancreatography using a spatially selective inversion-recovery pulse and T1 mapping
Authors: Higashi Mayumi , Tanabe Masahiro , Yonezawa Teppei , Furukawa Matakazu , Iida Etsushi , Ito Katsuyoshi 
Published: March 2022

Abstract
Purpose
To evaluate the association of the pancreatic exocrine function estimated by cine-dynamic magnetic resonance cholangiopancreatography (MRCP) using a spatially selective inversion-recovery (IR) pulse with the pancreatic endocrine function estimated by the T1 relaxation time of the pancreatic parenchyma and HbA1c values.

Materials and methods
Forty-three patients with suspected hepatobiliary or pancreatic diseases were included. Patients were classified into three groups: HbA1c < 5.7% (normal group), 5.7% ≤ HbA1c < 6.5% (prediabetes group), and HbA1c ≥ 6.5% (diabetes group). The frequency of the secretory flow of the pancreatic juice was observed within the area of the IR pulse, and the moving distance (mean secretion grade) of the pancreatic juice inflow within the area of the IR pulse on cine-dynamic MRCP, and the T1 relaxation time of the pancreatic parenchyma on the T1 map images were assessed. The MR imaging measurements were compared using Spearman’s rank correlation coefficient analysis and the Kruskal–Wallis and Mann–Whitney U tests.

Results
Both the mean secretion grade and frequency of the pancreatic secretory inflow had a significant negative correlation with the T1 relaxation time of the pancreatic parenchyma (r = − 0.335, p = 0.028 and r = − 0.305, p = 0.047, respectively) and HbA1c values (r = − 0.308, p = 0.044 and r = − 0.313, p = 0.041, respectively). Both the mean secretion grade and frequency of the pancreatic secretory inflow in the elevated HbA1c (prediabetes and diabetes) group were significantly lower than those in the normal group (p = 0.030 and p = 0.029, respectively).

Conclusion
The pancreatic exocrine function estimated by cine-dynamic MRCP was significantly lower in patients with prediabetes and diabetes than in controls. Cine-dynamic MRCP with a spatially selective IR pulse may be useful for the early diagnosis of pancreatic exocrine insufficiency in patients with pancreatic endocrine insufficiency.
Targeting Features of the Metabolic Syndrome Through Sympatholytic Effects of SGLT2 Inhibition
Authors: Herat Lakshini Y. , Matthews Jennifer , Azzam Omar , Schlaich Markus P. , Matthews Vance B. 
Published: March 2022

AbstractPurpose of ReviewThe moderate glucose-lowering effect of sodium glucose co-transporter 2 (SGLT2) inhibitors is unlikely to explain SGLT2 inhibitor-mediated beneficial outcomes, and unravelling the underlying mechanisms is a high priority in the research community. Given the dominant pathophysiologic role of the sympathetic nervous system activation in conditions such as hypertension and perturbed glucose homeostasis, it is pertinent to postulate that SGLT2 inhibitors may exert their beneficial effects at least in part via sympathetic inhibition.Recent FindingsSGLT2 inhibitors have shown enormous potential to improve cardiovascular outcomes in patients with type 2 diabetes, and their therapeutic potential is currently being investigated in a range of associated comorbidities such as heart failure and chronic kidney disease. Indeed, recent experimental data in relevant animal models highlight a bidirectional interaction between sympathetic nervous system activation and SGLT2 expression, and this facilitates several of the features associated with SGLT2 inhibition observed in clinical trials including improved glucose metabolism, weight loss, increased diuresis, and lowering of blood pressure.SummaryCurrently available data highlight the various levels of interaction between the sympathetic nervous system and SGLT2 expression and explores the potential for SGLT2 inhibition as a therapeutic strategy in conditions commonly characterised by sympathetic activation.
Outcome Prediction of Postanoxic Coma: A Comparison of Automated Electroencephalography Analysis Methods
Authors: Pham Stanley D. T. , Keijzer Hanneke M. , Ruijter Barry J. , Seeber Antje A. , Scholten Erik , Drost Gea , van den Bergh Walter M. , Kornips Francois H. M. , Foudraine Norbert A. , Beishuizen Albertus , Blans Michiel J. , Hofmeijer Jeannette , van Putten Michel J. A. M. , Tjepkema-Cloostermans Marleen C. 
Published: March 2022

AbstractBackgroundTo compare three computer-assisted quantitative electroencephalography (EEG) prediction models for the outcome prediction of comatose patients after cardiac arrest regarding predictive performance and robustness to artifacts.MethodsA total of 871 continuous EEGs recorded up to 3 days after cardiac arrest in intensive care units of five teaching hospitals in the Netherlands were retrospectively analyzed. Outcome at 6 months was dichotomized as “good” (Cerebral Performance Category 1–2) or “poor” (Cerebral Performance Category 3–5). Three prediction models were implemented: a logistic regression model using two quantitative features, a random forest model with nine features, and a deep learning model based on a convolutional neural network. Data from two centers were used for training and fivefold cross-validation (n = 663), and data from three other centers were used for external validation (n = 208). Model output was the probability of good outcome. Predictive performances were evaluated by using receiver operating characteristic analysis and the calculation of predictive values. Robustness to artifacts was evaluated by using an artifact rejection algorithm, manually added noise, and randomly flattened channels in the EEG.ResultsThe deep learning network showed the best overall predictive performance. On the external test set, poor outcome could be predicted by the deep learning network at 24 h with a sensitivity of 54% (95% confidence interval [CI] 44–64%) at a false positive rate (FPR) of 0% (95% CI 0–2%), significantly higher than the logistic regression (sensitivity 33%, FPR 0%) and random forest models (sensitivity 13%, FPR, 0%) (p < 0.05). Good outcome at 12 h could be predicted by the deep learning network with a sensitivity of 78% (95% CI 52–100%) at a FPR of 12% (95% CI 0–24%) and by the logistic regression model with a sensitivity of 83% (95% CI 83–83%) at a FPR of 3% (95% CI 3–3%), both significantly higher than the random forest model (sensitivity 1%, FPR 0%) (p < 0.05). The results of the deep learning network were the least affected by the presence of artifacts, added white noise, and flat EEG channels.ConclusionsA deep learning model outperformed logistic regression and random forest models for reliable, robust, EEG-based outcome prediction of comatose patients after cardiac arrest.
Korean College Students’ Attitudes toward Disability and Inclusive Education: Latent Profile Analysis
Authors: Shin Yun-Jeong , Ji Eun , Park Soyoung 
Published: March 2022

AbstractThe purpose of this study was to explore the differences in cognitive-behavioral attitudes and emotional connectedness toward people with disabilities (PWDs) and the attitudes toward inclusive education. In total, 309 college students from various universities in South Korea aged from 18 to 29 years (177 male and 130 female) voluntarily participated in this study. The participants were completed a set of questionnaires: Social Distance Toward Disabilities scale, Interaction with Disabled Person Scale, and Teachers’ Attitudes toward Inclusive Education Scale. Latent profile analysis (LPA) was used to model four distinct types: distant (3.56%), lukewarm (73.91%), rationalizing (8.41%), and potential proactive (14.12%). The majority of participants were lukewarm type who had a slightly cognitive-behavioral distance with mediocre empathy toward PWDs, which links to vague stands toward inclusive education. Potential proactive type, the second largest group, showed a positive attitude toward inclusive education with a high level of empathy but still had ambivalent perceptions toward PWDs. The rationalizing and distant groups had one thing in common that they had a relatively low level of empathy toward PWDs, but showed a markedly opposite position in inclusive education. The findings indicate that interventions should be tailored based on the type-specific attitudes and experiences with PWDs in public and educational settings.
Measuring state-level infant and toddler well-being in the United States: Gaps in data lead to gaps in understanding
Authors: Ryberg Renee , Wiggins Lisa , Moore Kristin A. , Daily Sarah , Piña Gabriel , Klin Ami 
Published: March 2022

AbstractChildren who are nurtured, protected, and supported in the first years of life tend to have better individual outcomes and are more likely to grow to become healthy, productive adults. Child well-being varies across states, yet the field lacks a comprehensive review of infant and toddler indicators measured at the state-level. This paper reviews indicators of well-being from the prenatal period to three years that meet certain a priori criteria. Most of the child-level indicators identified were in the physical health domain; relatively fewer indicators were found in the early cognition and language or social-emotional-behavioral domains. While some states are making progress toward developing integrated early childhood data systems, more work is needed to provide robust data on infant and toddler development. These results highlight the need to develop a broader range of indicators of infant and toddler well-being and improve measurement sources to better inform policies and programs advancing population health.
LiDAR Datasets Applied to Roman Gold Mining Studies in NW Iberia. Response to Paper: Roman Gold Mining at “Las Miédolas” (NW Spain): Lidar and Photo Interpretation in the Analysis of “Peines”
Authors: Fernández-Lozano Javier , Gutiérrez-Alonso Gabriel , Carrasco Rosa M. , Pedraza Javier 
Published: March 2022

AbstractEarly LiDAR datasets in Spain are available since 2014 (5-m resolution), when the first works were carried out by our team (Fernández-Lozano and Gutiérrez-Alonso Mapping 167:22–29, 2014; Fernández-Lozano et al. J Archaeol Sci 2014:356–373, 2015). The implementation of LiDAR to 1-m resolution was subsequently used and compared by Fernández-Lozano and Gutiérrez-Alonso (J Archaeol Sci 5:509–520, 2016) in combination with UAV-derived (Unmanned Aerial Vehicles) photogrammetry. These works showed different Roman gold mining scenarios that were modeled providing outstanding results even with the poorest resolution LiDAR datasets. Moreover, the implementation of visual enhancement tools, widely used in different fields of archeology, geomorphology, and geology, such as Sky-View, Multi-hillside, Slope, LRM, Openness, and Principal Components have improved notably the interpretation of results in both mining and archeological works. This paper discusses the potential and insights provided by our methodological approach and shows that the results of its application to the study area of Las Miédolas can provide better results than those obtained by Matías and Llamas (Geoheritage 13(2):1–22, 2021).
Commissioning measurements on an Elekta Unity MR-Linac
Authors: Powers Marcus , Baines John , Crane Robert , Fisher Chantelle , Gibson Stephen , Marsh Linda , Oar Bronwyn , Shoobridge Ariadne , Simpson-Page Emily , Van der Walt Marchant , de Vine Glenn 
Published: March 2022

AbstractMagnetic resonance-guided radiotherapy technology is relatively new and commissioning publications, quality assurance (QA) protocols and commercial products are limited. This work provides guidance for implementation measurements that may be performed on the Elekta Unity MR-Linac (Elekta, Stockholm, Sweden). Adaptations of vendor supplied phantoms facilitated determination of gantry angle accuracy and linac isocentre, whereas in-house developed phantoms were used for end-to-end testing and anterior coil attenuation measurements. Third-party devices were used for measuring beam quality, reference dosimetry and during treatment plan commissioning; however, due to several challenges, variations on standard techniques were required. Gantry angle accuracy was within 0.1°, confirmed with pixel intensity profiles, and MV isocentre diameter was < 0.5 mm. Anterior coil attenuation was approximately 0.6%. Beam quality as determined by TPR20,10 was 0.705 ± 0.001, in agreement with treatment planning system (TPS) calculations, and gamma comparison against the TPS for a 22.0 × 22.0 cm2 field was above 95.0% (2.0%, 2.0 mm). Machine output was 1.000 ± 0.002 Gy per 100 MU, depth 5.0 cm. During treatment plan commissioning, sub-standard results indicated issues with machine behaviour. Once rectified, gamma comparisons were above 95.0% (2.0%, 2.0 mm). Centres which may not have access to specialized equipment can use in-house developed phantoms, or adapt those supplied by the vendor, to perform commissioning work and confirm operation of the MRL within published tolerances. The plan QA techniques used in this work can highlight issues with machine behaviour when appropriate gamma criteria are set.
Autonomous maritime operations and the influence of situational awareness within maritime navigation
Authors: Chan Jevon P. , Norman Rose , Pazouki Kayvan , Golightly David 
Published: March 2022

AbstractAs the maritime industry looks to implement autonomous operations, it is key that seafarers can adjust and work alongside the technological strides being made. With the maritime industry being on the brink of a paradigm shift, not seen since the transition from sails to engines, regulations and training need to be implemented before the industry can progress towards autonomous vessel operations. Therefore, the maritime industry must implement methods and training regimes that seafarers can undertake to train skills such as situational awareness, to ensure that the human-automation relationship progresses smoothly and efficiently. The research reported within this paper aims to assess the elements required to aid the development of seafarers, in preparation for the inevitable change to autonomous maritime operations. A study was conducted which analysed the situational awareness of 14 junior navigational officers and 14 navigational officer cadets, by means of a bridge watch simulator and introducing the participants to an autopilot failure. The results of the study found a lack of system understanding, in the event of a fault, among the majority of participants. Additionally, even the participants displaying a satisfactory level of situational awareness required alarms before they could recognise a potential fault. Additionally, participants were given a survey which allowed the assessment of their personal views and opinions of autonomous operations. By assessing the outcome of this study and researching past maritime incidents, this paper has highlighted the necessity for situational awareness training for seafarers which will improve the human automation relationship.
Combining 2D organic and 1D inorganic nanoblocks to develop free-standing hybrid nanomembranes for conformable biosensors
Authors: García-Torres Jose , Lázaro Carmen , Sylla Dioulde , Lanzalaco Sonia , Ginebra Maria-Pau , Alemán Carlos 
Published: March 2022

AbstractWe report a simple approach to fabricate free-standing perforated 2D nanomembranes hosting well-ordered 1D metallic nanostructures to obtain hybrid materials with nanostructured surfaces for flexible electronics. Nanomembranes are formed by alternatively depositing perforated poly(lactic acid) (PLA) and poly(3,4-ethylenedioxythiophene) layers. Copper metallic nanowires (NWs) were incorporated into the nanoperforations of the top PLA layer by electrodeposition and further coated with silver via a transmetallation reaction. The combination of 2D polymeric nanomembranes and aligned 1D metallic NWs allows merging the flexibility and conformability of the ultrathin soft polymeric nanomembranes with the good electrical properties of metals for biointegrated electronic devices. Thus, we were able to tailor the nanomembrane surface chemistry as it was corroborated by SEM, EDX, XPS, CV, EIS and contact angle. The obtained hybrid nanomembranes were flexible and conformable showing sensing capacity towards H2O2 with good linear concentration range (0.35–10 mM), sensitivity (120 µA cm−2 mM−1) and limit of detection (7 μm). Moreover, the membranes showed good stability, reproducibility and selectivity towards H2O2.
Trade Mark Protection for Smells, Tastes and Feels – Critical Analysis of Three Non-Visual Signs in the EU
Authors: Geiregat Simon 
Published: March 2022

AbstractThis article focuses on the ability to protect three non-traditional signs as trade marks in the EU: smell (olfactory marks), taste (gustatory marks) and feel (tactile marks). All three types of subject matter can meet the definition of a sign. According to the majority view in literature and practice, none of the three can currently be represented on the register with sufficient clarity and precision, however. It is argued that the veracity of that finding essentially boils down to a lack of vocabulary and IT solutions, and that it depends on the level of detail that can be expected from non-visual signs. Theoretically, distinctiveness is less of an obstacle to protection. Although some signs need to acquire distinctiveness through use, distinctiveness should be assessed on a case-by-case basis and it cannot be excluded that there are smells, tastes and feels that are inherently distinct. In practice, authorities seem to uphold excessive thresholds for olfactory, gustatory, and especially tactile marks. This is understandable in the light of their potential scope, which lies at the heart of the debate on their eligibility for protection. Indeed, granting protection to these three types of signs carries the risk of depleting and propertising almost anything. Although this might be true, it is contended that more research is needed and that there is no legislative basis for a Freihaltebedürfnis (need to keep signs freely available) in this respect. After considering fundamental rights and public policy as alternative means of channelling that concern, the article concludes that it is for the EU legislator to evaluate whether to exclude certain signs from trade mark law.
Das Konzept der liebevolle Erzähler in Olga Tokarczuks Vorlesung zur Verleihung des Nobelpreises für Literatur
Authors: Bilut-Homplewicz Zofia , Krauz Maria 
Published: March 2022

ZusammenfassungDer Beitrag diskutiert das Konzept des liebevollen Erzählers, das Olga Tokarczuk in ihrer Nobelpreisvorlesung 2019 entwickelt hat. Es wird an die für die Nobelpreisträgerin wichtigen Werte erinnert und die Textaktualisierung dieser Kategorie analysiert. Darüber hinaus wird die Rolle des liebevollen Erzählers für die Interpretation der (textexternen) Wirklichkeit, für die Bewertung der für die zeitgenössische Welt wichtigen Erscheinungen sowie die mit dem liebevollen Erzähler verbundene Möglichkeit, Haltungen, Wahlentscheidungen und das Leben des zeitgenössischen Menschen zu beeinflussen, diskutiert. Da bei der Autorin eine mehrdimensionale Perspektive zum Einsatz kommt, machen wir auf Kontexte der Kategorien czuły und czułość nicht nur aus textorientierter, sondern auch aus einer breiteren, d. h. lexikologischen und semantischen Sicht aufmerksam. Die Analyse der Wörterbucheinträge von czuły und czułość sowie der Art und Weise, wie Tokarczuk den liebevollen Erzähler unmittelbar in der Rede oder in ihren weiteren Ausführungen aktualisiert und charakterisiert, führt zu dem Schluss, dass es sich bei dem postulierten neuen Erzähler in der »vierten Person« nicht um eine grammatische Konstruktion handelt, sondern um die Kategorie eines ›wunderbaren‹ Erzählers, der eine universale Geschichte webt. Ihm werden von der Nobelpreisträgerin folgende Attribute zugeschrieben: Der liebevolle Erzähler kann die Perspektive jeder Figur einnehmen, er sieht weiter und mehr, er kann die Zeit ignorieren und er ist sich der Bedrohungen in der zeitgenössischen Welt bewusst. Der Beitrag unternimmt darüber hinaus den Versuch, eine Antwort darauf zu finden, wie man diese Gestalt und Kategorie mit der Rolle vereinbaren kann, die der Nobelpreisträgerin zufolge die Literatur in der zeitgenössischen Welt spielen soll: in einer Welt, die gespalten ist, die vom Menschen unvermindert zerstört wird und in der die Geistigkeit verschwindet.
Analysis of Line-Edge Roughness Using EUV Scatterometry
Authors: Fernández Herrero Analía , Scholze Frank , Dai Gaoliang , Soltwisch Victor 
Published: March 2022

AbstractSmaller and more complex three-dimensional periodic nanostructures are part of the next generation of integrated electronic circuits. Additionally, decreasing the dimensions of nanostructures increases the effect of line-edge roughness on the performance of the nanostructures. Efficient methods for characterizing three-dimensional nanostructures are required for process control. Here, extreme-ultraviolet (EUV) scatterometry is exploited for the analysis of line-edge roughness from periodic nanostructures. In line with previous observations, differences are observed between line edge and line width roughness. The angular distribution of the diffuse scattering is an interplay of the line shape, the height of the structure, the roughness along the line, and the correlation between the lines. Unfortunately, existing theoretical methods for characterizing nanostructures using scatterometry do not cover all these aspects. Examples are shown here and the demands for future development of theoretical approaches for computing the angular distribution of the scattered X-rays are discussed.