bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine Learning Discrimination and Ultrasensitive Detection of Fentanyl Using Gold Nanoparticle‐Decorated Carbon Nanotube‐Based Field‐Effect Transistor Sensors
Authors: Shao Wenting , Sorescu Dan C. , Liu Zhengru , Star Alexander 
Published: April 2024

AbstractThe opioid overdose crisis is a global health challenge. Fentanyl, an exceedingly potent synthetic opioid, has emerged as a leading contributor to the surge in opioid‐related overdose deaths. The surge in overdose fatalities, particularly due to illicitly manufactured fentanyl and its contamination of street drugs, emphasizes the urgency for drug‐testing technologies that can quickly and accurately identify fentanyl from other drugs and quantify trace amounts of fentanyl. In this paper, gold nanoparticle (AuNP)‐decorated single‐walled carbon nanotube (SWCNT)‐based field‐effect transistors (FETs) are utilized for machine learning‐assisted identification of fentanyl from codeine, hydrocodone, and morphine. The unique sensing performance of fentanyl led to use machine learning approaches for accurate identification of fentanyl. Employing linear discriminant analysis (LDA) with a leave‐one‐out cross‐validation approach, a validation accuracy of 91.2% is achieved. Meanwhile, density functional theory (DFT) calculations reveal the factors that contributed to the enhanced sensitivity of the Au‐SWCNT FET sensor toward fentanyl as well as the underlying sensing mechanism. Finally, fentanyl antibodies are introduced to the Au‐SWCNT FET sensor as specific receptors, expanding the linear range of the sensor in the lower concentration range, and enabling ultrasensitive detection of fentanyl with a limit of detection at 10.8 fg mL−1.
A novel defect prediction method based on semantic feature enhancement
Authors: Zhang Chi , Wang Xiaoli , Chen Jinfu , Cai Saihua , Nii Ayitey Sosu Rexford 
Published: April 2024

SummaryAlthough cross‐project defect prediction (CPDP) techniques that use traditional manual features to build defect prediction model have been well‐developed, they usually ignore the semantic and structural information inside the program and fail to capture the hidden features that are critical for program category prediction, resulting in poor defect prediction results. Researchers have proposed using deep learning to automatically extract the semantic features of programs and fuse them with traditional features as training data. However, in practice, it is important to explore the effective representation of the semantic features in the programs and how the fusion of a reasonable ratio between the two types of features can maximize the effectiveness of the model. In this paper, we propose a semantic feature enhancement‐based defect prediction framework (SFE‐DP), which augments the semantic feature set extracted from the program code with data. We also introduce a layer of self‐attentive mechanism and a matching layer to filter low‐efficiency and non‐critical semantic features in the model structure. Finally, we combine the idea of hybrid loss function to iteratively optimize the model parameters. Extensive experiments validate that SFE‐DP can outperform the baseline approaches on 90 pairs of CPDP tasks formed by 10 open‐source projects.
Blast Furnace Slag Formation Prediction Model Using Classical Thermodynamics
Authors: Kumar Bhupendra , Hazra Sujan , Sahoo Manisha , Pal Padma , Paliwal Manas , Nag Samik 
Published: April 2024

Blast furnace (BF) ironmaking is the most widely used technology for hot metal production. In steelmaking industry, 80% of the steel in the world is produced in the BF‐basic oxygen furnace route. It is well known that poor quality of the raw material i.e., high gangue content in the iron ore affects the BF process performance and the cohesive zone formation, which is the most critical zone in the BF operations. Increased gangue content in the iron ore causes variation in the slag formation and slag volume thus affecting the fuel rate and BF performance. Therefore, in this study, the slag formation is studied to understand the slag properties at different locations inside the BF. The model is based on classical thermodynamics and is implemented using ChemApp linked with FactSage databases. The model aids in understanding the slag formation in the BF for various burden chemistry, fuel, and flux inputs. The final hot metal and slag composition along with the exit gas volume and composition predicted from this model are compared with industrial BF plant data operating across different conditions.
Narratives of Ukraine on the Information Battlefields of Global Media
Authors: Chaban Natalia , Zhabotynska Svitlana 
Published: April 2024

AbstractContributing to the debate of how narratives organize and serve information to exert influence beyond national borders, we answer an urgent call for comparative narrative analysis in International Relations (IR). To explore the changing global narratives of Ukraine, we engage with commentators who argue a certain unity in sensemaking about Ukraine in the West (including the EU) vis-à-vis the non-Western world, and we also examine how Western narratives on Ukraine/war against Ukraine are divided. Empirically, we engage with the media narratives framing Ukraine in 2022–2023 in the selected countries of Europe, Global South and in China. These narratives are compared to the results of the representative public surveys in the respective locations and the overview of the knowledge-producing outputs (think tanks and academia) in the selected countries. We engage with the concept of “antagonistic narrative strategies” and dissect pro-Kremlin narratives directed towards diverse receivers around the world in general, and the EU in particular. Finally, we highlight six “takeaways” for the EU facing an uncertain world at this time of war against Ukraine. Building on our previous work, we argue the impact of the constructed image in the narrative can be reinforced by the interplay of two projection properties: (1) content accentuation and priming, through iterations and content contextualization and (2) historical and cultural resonance with the receivers.
Introduction
Authors: Moreno-Ortiz Antonio 
Published: April 2024

AbstractThis chapter contextualizes the book in terms of aims, methods, contents, and audience. It first discusses the impact of the COVID-19 pandemic on all aspects of society, and the crucial role that social networks played as a means to disseminate information and share feelings and ideas between users. Finally, a comprehensive summary of the most outstanding research related to this book is offered, focusing on those works that employ similar techniques to the ones used here.
Managing Large Twitter Datasets
Authors: Moreno-Ortiz Antonio 
Published: April 2024

AbstractThis chapter provides a thorough discussion of Twitter/X corpora in terms of compilation and management. Twitter corpora differ from other types of corpora in many aspects, as they are composed of a very large number of very small documents (tweets), each with a slew of metadata, that can be downloaded through scripts that make use of available APIs, which calls for certain tools and techniques. The type of language used in social media is also very different from other, more standard genres, both in form and content. When this is coupled with large-size corpora, effective sampling techniques are necessary, which are discussed at length in this chapter. Finally, a description is given of using geotagged data and subcorpora creation and management.
Once-weekly insulins: a promising approach to reduce the treatment burden in people with diabetes
Authors: Trevisan Roberto , Conti Matteo , Ciardullo Stefano 
Published: April 2024

AbstractDespite the availability of new classes of glucose-lowering drugs that improve glycaemic levels and minimise long-term complications, at least 20–25% of people with type 2 diabetes require insulin therapy. Moreover, a substantial proportion of these individuals do not achieve adequate metabolic control following insulin initiation. This is due to several factors: therapeutic inertia, fear of hypoglycaemia and/or weight gain, poor communication, complexity of insulin titration, and the number of injections needed, with the associated reduced adherence to insulin therapy. Once-weekly insulins provide a unique opportunity to simplify basal insulin therapy and to allow good glycaemic control with a low risk of hypoglycaemia. Several approaches to developing a stable and effective once-weekly insulin have been proposed, but, to date, insulin icodec and basal insulin Fc (insulin efsitora alfa) are the only two formulations for which clinical studies have been reported. The results of Phase I and II studies emphasise both efficacy (in term of glucose levels) and potential risks and adverse events. Phase III studies involving insulin icodec are reassuring regarding the risk of hypoglycaemia compared with daily basal insulin analogues. Despite some concerns raised in ongoing clinical trials, the available data suggest that weekly insulins may also be an option for individuals with type 1 diabetes, especially when adherence is suboptimal. For the first time there is an opportunity to make an important breakthrough in basal insulin therapy, particularly in people with type 2 diabetes, and to improve not only the quality of life of people with diabetes, but also the practice of diabetologists.
Graphical Abstract
Length of hospital stay in involuntary admissions in Greece: a 10-year retrospective observational study
Authors: Bakola Maria , Peritogiannis Vaios , Kitsou Konstantina Soultana , Gourzis Philippos , Hyphantis Thomas , Jelastopulu Eleni 
Published: April 2024

Abstract
Purpose
The treatment of mental disorders has shifted from inpatient wards to community-based settings in recent years, but some patients may still have to be admitted to inpatient wards, sometimes involuntarily. It is important to maintain the length of hospital stay (LoS) as short as possible while still providing adequate care. The present study aimed to explore the factors associated with the LoS in involuntarily admitted psychiatric patients.

Methods
A ten-year retrospective chart review of 332 patients admitted involuntarily to the inpatient psychiatric ward of the General University Hospital of Ioannina, Northwestern Greece, between 2008 and 2017 was conducted.

Results
The mean LoS was 23.8 (SD = 33.7) days and was relatively stable over the years. Longer-stay hospitalization was associated with schizophrenia-spectrum disorder diagnosis, previous hospitalizations and the use of mechanical restraint, whereas patients in residential care experienced significantly longer LoS (52.6 days) than those living with a caregiver (23.5 days) or alone (19.4 days). Older age at disease onset was associated with shorter LoS, whereas no statistically significant differences were observed with regard to gender.

Conclusion
While some of our findings were in line with recent findings from other countries, others could not be replicated. It seems that multiple factors influence LoS and the identification of these factors could help clinicians and policy makers to design more targeted and cost-effective interventions. The optimization of LoS in involuntary admissions could improve patients’ outcomes and lead to more efficient use of resources.
Analysis of the scientific knowledge structure on automation in the wine industry: a bibliometric and systematic review
Authors: Martínez-Falcó Javier , Sánchez-García Eduardo , Marco-Lajara Bartolome , Millán-Tudela Luis A. 
Published: April 2024

AbstractThe objective of this research is to analyze the knowledge structure of the academic literature indexed in the Core Collection of the Web of Science on automation in the wine industry, from the first registered article in 1996 to 2022, in order to identify the latest trends in the study of this subject. A bibliometric and systematic analysis of the literature was carried out. First, for the quantitative analysis of the scientific production, the bibliometric study was conducted, using the WoS database for data collection and the VosViewer and Bibliometrix applications to create the network maps. Second, once the literature had been examined quantitatively, content analysis was undertaken using the PRISMA methodology. The results show, among other aspects, the uneven distribution of the examined scientific production from 1996 to 2022, that computer vision, data aggregation, life cycle assessment, precision viticulture, extreme learning machine and collaborative platforms are the major current keywords and the predominance of Spain and Italy in terms of scientific production in the field. There are various justifications which support the originality of this study. First, it contributes to the understanding of academic literature and the identification of the most recent trends in the study of automation in the wine industry. Second, to the best of our knowledge, no prior bibliometric studies have considered this topic. Third, this research evaluates the literature from the first record to the year 2022, thereby providing a comprehensive analysis of the scientific production.
In vitro and in vivo fermentation models to study the function of dietary fiber in pig nutrition
Authors: Huangfu Weikang , Cao Shixi , Li Shouren , Zhang Shuhang , Liu Mengqi , Liu Boshuai , Zhu Xiaoyan , Cui Yalei , Wang Zhichang , Zhao Jiangchao , Shi Yinghua 
Published: April 2024

Abstract
The importance of dietary fiber (DF) in animal diets is increasing with the advancement of nutritional research. DF is fermented by gut microbiota to produce metabolites, which are important in improving intestinal health. This review is a systematic review of DF in pig nutrition using in vitro and in vivo models. The fermentation characteristics of DF and the metabolic mechanisms of its metabolites were summarized in an in vitro model, and it was pointed out that SCFAs and gases are the important metabolites connecting DF, gut microbiota, and intestinal health, and they play a key role in intestinal health. At the same time, some information about host-microbe interactions could have been improved through traditional animal in vivo models, and the most direct feedback on nutrients was generated, confirming the beneficial effects of DF on sow reproductive performance, piglet intestinal health, and growing pork quality. Finally, the advantages and disadvantages of different fermentation models were compared. In future studies, it is necessary to flexibly combine in vivo and in vitro fermentation models to profoundly investigate the mechanism of DF on the organism in order to promote the development of precision nutrition tools and to provide a scientific basis for the in-depth and rational utilization of DF in animal husbandry.

Key points
• The fermentation characteristics of dietary fiber in vitro models were reviewed.
• Metabolic pathways of metabolites and their roles in the intestine were reviewed.
• The role of dietary fiber in pigs at different stages was reviewed.

Graphical Abstract
How useful are indirect radiographic measurements of hip instability in borderline hip dysplasia? An MRI-based comparison to a healthy cohort
Authors: Andronic Octavian , Germann Christoph , Jud Lukas , Imhoff Florian B. , Fröhlich Stefan , Scherr Johannes , Spörri Jörg , Zingg Patrick O. 
Published: April 2024

Abstract
Purpose
Symptomatic hips with borderline hip dysplasia (BHD) morphology pose a challenge in differentiating stable from unstable hips. The current study aims to compare indirect radiographic signs of instability in a symptomatic BHD population to those in a healthy cohort.

Methods
The study group consisted of patients with a lateral centre–edge angle (LCEA) with values 18° ≤ LCEA < 25° who underwent corrective periacetabular osteotomy (PAO) and reported an improvement in patient-reported outcome measures (PROMs). The comparison group consisted of a healthy cohort of athletes who did not complain of any hip-related symptoms and who had normal values of their hip morphological parameters (LCEA, acetabular index (AI°), alpha angle (α°), femoral version, acetabular version). Indirect signs of instability consisting of the femoro-epiphyseal acetabular roof index (FEAR), iliocapsularis-to-rectus-femoris (IC/RF) ratio and labral dimensions (height-to-length ratio) were assessed in both groups. Partial Pearson correlation, logistic multiple regression analysis and Receiver-Operating Characteristic (ROC) curve analysis were performed to determine correlations, as well as the sensitivity and specificity of these signs to differentiate between healthy hips and BHD.

Results
On binary logistic multiple regression analysis, the FEAR Index was the only independent predictor to differentiate between BHD and healthy hips (p < 0.001). The IC/RF ratio did not achieve significance. The calculated area under the curve (AUC) was 0.93 (0.87 – 0.99, CI 95%, p < 0.001) for the FEAR Index and 0.81 (0.70 – 0.92, CI 95%, p < 0.001) for the height-length ratio. Using the predefined cut-off values (dysplastic—FEAR Index ≥ 5° or labral height-to-length ratio ≤ 0.5), 27% sensitivity/100% specificity and 20% sensitivity/ 100% specificity, were achieved. ROC analysis provided the following new thresholds: FEAR Index ≥ -5° (73% sensitivity/97% specificity); labral height-to-length ratio ≤ 0.8 (70% sensitivity, 79% specificity).

Conclusion
In our cohort, the FEAR index was an independent parameter that could differentiate between borderline dysplastic and asymptomatic hips. The previously published values for both the FEAR index and labral hypertrophy ratio had a poor sensitivity in differentiating symptomatic unstable BHD from healthy hips. The cut-off values of ≥ -5° (FEAR index) and ≤ 0.8 (labral height-to-length ratio) provided acceptable sensitivity and specificity when comparing to morphological healthy hips.
The exercise-app Axia for axial spondyloarthritis enhances the home-based exercise frequency in axial spondyloarthritis patients – A cross-sectional survey
Authors: Strunz Patrick-Pascal , Le Maire Maxime , Heusinger Tobias , Klein Juliana , Labinsky Hannah , Fleischer Anna , Luetkens Karsten Sebastian , Possler Patricia , Gernert Michael , Leppich Robert , Schmieder Astrid , Hammel Ludwig , Schulz Evelin , Sperlich Billy , Froehlich Matthias , Schmalzing Marc 
Published: April 2024

AbstractBackground: Patients with axial spondyloarthritis (axSpA) benefit from regular home-based exercise (HbE). In spite of recommendations, a relevant proportion of German axSpA patients does not adhere to recommended HbE practices. To enhance HbE care, we developed the novel digital therapeutic (DTx) “Axia” compliant with the European medical device regulation (MDR). Axia offers a modern app-based HbE solution with patient educative content and further integrated features. Objective: We aimed to assess Axia’s efficacy, attractiveness, and functionality through a survey among axSpA-patients involved in the first user tests. Methods: A mixed-method online questionnaire with 38 items was administered to 37 axSpA volunteers after using Axia. Numeric rating scales (NRS) and likelihood scales were primarily used. Results: HbE frequency significantly increased from a median of 1 day/week to 6 days/week (p < 0.001) by using Axia. Existing HbE practitioners also increased their frequency (median of 4 days/week before, 6 days/week with Axia, p < 0.05). Axia received a median rating of 5 out of 5 stars. On NRS scales, Axia scored a median of 9 for intuitiveness and design, and a median of 8 for entertainment. 64.9% reported improved range of motion, 43.2% reported reduced pain, and 93.6% enhanced disease-specific knowledge. All users recommended Axia to other patients. Conclusion: Axia increases axSpA patients HbE frequency, possibly due to its good intuitiveness and design, leading to reduction in pain and subjective improvement of range of motion. This warrants further investigation in large randomized controlled interventional trials to establish its efficacy conclusively and patients adherence to HbE.
Multi-year mesozooplankton flux trends in Kongsfjorden, Svalbard
Authors: D’Angelo Alessandra , Mayers Kyle , Renz Jasmin , Conese Ilaria , Miserocchi Stefano , Giglio Federico , Giordano Patrizia , Langone Leonardo 
Published: April 2024

AbstractWe conducted this study to investigate the relationship between environmental stressors and mesozooplankton fluxes in inner Kongsfjorden, Svalbard. The ongoing Arctic amplification, characterized by phenomena such as increased temperatures, glacial and watershed runoff, and diminishing ice cover, poses significant challenges to marine ecosystems. Our multi-year time-series analysis (2010–2018) of mesozooplankton, collected from a moored automatic sediment trap at approximately 87 m depth, aims to elucidate seasonal and interannual variations in fluxes within this Arctic fjord. We integrate meteorological, hydrological, and chemical datasets to assess their influence on zooplankton populations. Principal component analysis reveals the impact of seawater characteristics on mesozooplankton fluxes and composition, while two-way ANOVA highlights the role of seasonality in driving variations in our dataset. We observe a decrease in swimmer fluxes following the maxima mass flux event (from 2013 onwards), coupled with an increase in community diversity, possibly attributed to copepod decline and functional diversity. Notably, sub-Arctic boreal species such as Limacina retroversa have been detected in the sediment trap since 2016. Our continuous multi-year dataset captures the physical, chemical, and biological dynamics in this extreme environment. With Arctic amplification in Kongsfjorden and increasing submarine and watershed runoff, we anticipate significant shifts in mesozooplankton communities in the medium to long-term. This underscores the urgency for further research on their adaptation to changing environmental conditions and the potential introduction of alien species.
Prenatal diagnosis of meningomyelocele resolves as a mature cystic teratoma in the thoracolumbar region
Authors: Chen-Carrington Annie , Leonard Dean , Goodreau Adam , Rhodes Jennifer , Tye Gary W. 
Published: April 2024

AbstractA mature cystic teratoma is a mass with heterogeneous appearance, consisting of adult tissue with two or three layers: endoderm, mesoderm, and ectoderm. It is a rare, benign transformation of somatic tissue most commonly found in the sacrococcygeal region and may resemble an uncomplicated spina bifida on prenatal ultrasonography. In this case report, we describe a female newborn with an extremely rare mature cystic teratoma in the thoracolumbar region. She presented prenatally with a preliminary diagnosis of meningomyelocele, diastematomyelia, and Chiari II malformation and a possible teratoma. However, a mass containing solid glandular tissues and bony calcifications approximately 3 × 4 cm in size was observed in the thoracolumbar region upon birth. During surgical resection, no nerve roots were found in the associated meningocele. The patient retained full lower body function postoperatively following surgical excision of the thecal sac and teratoma.