bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automatic construction of direction-aware sentiment lexicon using direction-dependent words
Authors: Park Jihye , Lee Hye Jin , Cho Sungzoon 
Published: May 2024

AbstractExplainability, which is the degree to which an interested stakeholder can understand the key factors that led to a data-driven model’s decision, has been considered an essential consideration in the financial domain. Accordingly, lexicons that can achieve reasonable performance and provide clear explanations to users have been among the most popular resources in sentiment-based financial forecasting. Since deep learning-based techniques have limitations in that the basis for interpreting the results is unclear, lexicons have consistently attracted the community’s attention as a crucial tool in studies that demand explanations for the sentiment estimation process. One of the challenges in the construction of a financial sentiment lexicon is the domain-specific feature that the sentiment orientation of a word can change depending on the application of directional expressions. For instance, the word “cost” typically conveys a negative sentiment; however, when the word is juxtaposed with “decrease” to form the phrase “cost decrease,” the associated sentiment is positive. Several studies have manually built lexicons containing directional expressions. However, they have been hindered because manual inspection inevitably requires intensive human labor and time. In this study, we propose to automatically construct the “sentiment lexicon composed of direction-dependent words,” which expresses each term as a pair consisting of a directional word and a direction-dependent word. Experimental results show that the proposed sentiment lexicon yields enhanced classification performance, proving the effectiveness of our method for the automated construction of a direction-aware sentiment lexicon.
A sentiment corpus for the cryptocurrency financial domain: the CryptoLin corpus
Authors: Gadi Manoel Fernando Alonso , Sicilia Miguel Ángel 
Published: May 2024

AbstractThe objective of this paper is to describe Cryptocurrency Linguo (CryptoLin), a novel corpus containing 2683 cryptocurrency-related news articles covering more than a three-year period. CryptoLin was human-annotated with discrete values representing negative, neutral, and positive news respectively. Eighty-three people participated in the annotation process; each news title was randomly assigned and blindly annotated by three human annotators, one in each different cohort, followed by a consensus mechanism using simple voting. The selection of the annotators was intentionally made using three cohorts with students from a very diverse set of nationalities and educational backgrounds to minimize bias as much as possible. In case one of the annotators was in total disagreement with the other two (e.g., one negative vs two positive or one positive vs two negative), we considered this minority report and defaulted the labeling to neutral. Fleiss’s Kappa, Krippendorff’s Alpha, and Gwet’s AC1 inter-rater reliability coefficients demonstrate CryptoLin’s acceptable quality of inter-annotator agreement. The dataset also includes a text span with the three manual label annotations for further auditing of the annotation mechanism. To further assess the quality of the labeling and the usefulness of CryptoLin dataset, it incorporates four pretrained Sentiment Analysis models: Vader, Textblob, Flair, and FinBERT. Vader and FinBERT demonstrate reasonable performance in the CryptoLin dataset, indicating that the data was not annotated randomly and is therefore useful for further research1. FinBERT (negative) presents the best performance, indicating an advantage of being trained with financial news. Both the CryptoLin dataset and the Jupyter Notebook with the analysis, for reproducibility, are available at the project’s Github. Overall, CryptoLin aims to complement the current knowledge by providing a novel and publicly available Gadi and Ángel Sicilia (Cryptolin dataset and python jupyter notebooks reproducibility codes, 2022) cryptocurrency sentiment corpus and fostering research on the topic of cryptocurrency sentiment analysis and potential applications in behavioral science. This can be useful for businesses and policymakers who want to understand how cryptocurrencies are being used and how they might be regulated. Finally, the rules for selecting and assigning annotators make CryptoLin unique and interesting for new research in annotator selection, assignment, and biases.
Review of the cost-effectiveness of surveillance for hereditary pancreatic cancer
Authors: Wang Louise , Levinson Rachel , Mezzacappa Catherine , Katona Bryson W. 
Published: May 2024

AbstractIndividuals with hereditary pancreatic cancer risk include high risk individuals (HRIs) with germline genetic susceptibility to pancreatic cancer (PC) and/or a strong family history of PC. Previously, studies have shown that PC surveillance in HRIs can downstage PC diagnosis and extend survival leading to pancreatic surveillance being recommended for certain HRIs. However, the optimal surveillance strategy remains uncertain, including which modalities should be used for surveillance, how frequently should surveillance be performed, and which sub-groups of HRIs should undergo surveillance. Additionally, in the ideal world PC surveillance should also be cost-effective. Cost-effectiveness analysis is a valuable tool that can consider the costs, potential health benefits, and risks among various PC surveillance strategies. In this review, we summarize the cost-effectiveness of various PC surveillance strategies for HRIs for hereditary pancreatic cancer and provide potential avenues for future work in this field. Additionally, we include cost-effectiveness studies among individuals with new-onset diabetes (NoD), a high-risk group for sporadic PC, as a comparison.
Graphical Abstract
Thermal lensing and photoacoustics as potential tools for nanomaterial characterization: a review
Authors: Swapna M. S. , Sankararaman S. , Korte D. 
Published: May 2024

AbstractThis comprehensive review highlights the versatile applications of photothermal techniques, particularly thermal lens spectrometry (TLS) and photoacoustic spectrometry (PAS), in the field of nanomaterials characterization. TLS is an effective technique in the trace detection of different compounds in liquid samples, photodegradation studies, and analysis of photocatalytic reaction rate, as well as the study of molecular dynamics, impacting both environmental and catalytical research. It enables the optimization of thermal diffusivity in soot nanofluids and offers insights into seed germination and plant yield enhancement in nanobiophotonics. The review also explores the thermal and elastic characterization of Fe2O3 polymorphs by photoacoustic spectroscopy (PAS). Investigating the metal mirror demonstrates PAS’s efficacy in determining its reflection coefficient and thermal diffusivity. ZnO nanoparticles’ strong absorption on diatomite surfaces is revealed through PAS, emphasizing their effectiveness in light absorption enhancement. Furthermore, PA techniques address working frequency limitations in studying silicon-based nanomaterials. Thus, thermal lens and photoacoustic spectroscopy assume pivotal roles in unveiling the nuanced attributes of various nanostructured materials, thereby propelling advancements in the realms of science and technology.
A Self-Applied Psychological Treatment for Gambling-Related Problems via The Internet: A Pilot, Feasibility Study
Authors: Diaz-Sanahuja Laura , Suso-Ribera Carlos , Lucas Ignacio , Jiménez-Murcia Susana , Tur Cintia , Gual-Montolio Patricia , Paredes-Mealla Macarena , García-Palacios Azucena , Bretón-López Juana María 
Published: May 2024

AbstractThe main purpose of this study was to evaluate the feasibility of an online psychological intervention for individuals with gambling-related problems, supported by ecological momentary assessments and interventions (EMAs and EMIs), along with weekly phone-calls, before conducting a randomized controlled trial. Participants were required to complete 3 of the 8 modules of the program based on cognitive-behavioral therapy (CBT) and extensions and innovations of CBT. The study measured the outcomes of feasibility (i.e., reach, appropriateness, technology literacy and technology usability, fidelity, and adherence). In terms of reach, 19.8% (n = 11) of the initial population met the inclusion criteria and completed the three modules (mean age = 41; 90.9% men). The perceived appropriateness and the technology usability after the first use were both excellent, fidelity and adherence to the online treatment (73.3%) were adequate. Adherence to the EMAs and the weekly phone calls were more modest (54.51% and 66.67%, respectively). The results of the present study show that an online treatment for gambling problems enhanced by EMA and EMI might be feasible but challenges were noted in terms of reach and adherence to these assessments and calls. These challenges are important to consider for future trials and the scalability of treatments for individuals with gambling disorders.
Subdivision Schemes Based on Weighted Local Polynomial Regression: A New Technique for the Convergence Analysis
Authors: López-Ureña Sergio , Yáñez Dionisio F. 
Published: May 2024

AbstractThe generation of curves and surfaces from given data is a well-known problem in Computer-Aided Design that can be approached using subdivision schemes. They are powerful tools that allow obtaining new data from the initial one by means of simple calculations. However, in some applications, the collected data are given with noise and most of schemes are not adequate to process them. In this paper, we present new families of binary univariate linear subdivision schemes using weighted local polynomial regression which are suitable for noisy data. We study their properties, such as convergence, monotonicity, polynomial reproduction and approximation and denoising capabilities. We establish conditions that connect the weight function with two essential properties: noise elimination and approximation capability. We propose a multi-objective optimization problem for improving these two capabilities and conclude that only some weight functions are Pareto optimal. For the convergence study, we develop some new theoretical results. Finally, some examples are presented to confirm the proven properties.
Can nudging with descriptive norms help internal auditors stop runaway information systems projects?
Authors: Nuijten Arno L. P. , Verbraak-Kolevska Violeta , Keil Mark 
Published: May 2024

AbstractAlthough internal auditors are expected to play an important role in corporate governance, they are not always effective in bringing their message to management’s attention when they observe that a risky course of action is being taken that could harm the organization. When information systems projects go awry, for example, internal auditors often struggle to get managers to listen to their warnings. Instead, managers may turn a deaf ear to the auditor’s warnings. In this paper, we build on the idea that internal auditors can follow an approach that combines two elements to reduce this so-called deaf effect: (1) the auditor can apply communication techniques to more effectively deliver the message, and (2) the internal auditor can develop a relationship with the manager such that the auditor is viewed as a ‘partner’ rather than an ‘opponent.’Following a mixed method approach, we examined how ‘nudging with a descriptive norm’ as a communication technique could help internal auditors to reduce the deaf effect and how this can be understood in the context of the auditor-manager relationship (AMR). We conducted two experiments showing consistent evidence that both (1) nudging with a descriptive norm and (2) AMR, had significant indirect effects on the deaf effect that were mediated through perceived social norms. A complementary series of ten interviews with Chief Audit Executives shed further light on how internal auditors could apply ‘nudging with a descriptive norm’ as a communication technique, and what should be considered, including the auditor-manager relationship. Implications for both internal audit research and practice are discussed.
Recent advances in the therapeutic applications of selenium nanoparticles
Authors: Ansari Jeba Ajgar , Malik Jonaid Ahmad , Ahmed Sakeel , Manzoor Muntaha , Ahemad Nafees , Anwar Sirajudheen 
Published: May 2024

Abstract
Selenium nanoparticles (SeNPs) are an appealing carrier for the targeted delivery. The selenium nanoparticles are gaining global attention because of the potential therapeutic applications in several diseases e.g., rheumatoid arthritis (RA), inflammatory bowel disease (IBD), asthma, liver, and various autoimmune disorders like psoriasis, cancer, diabetes, and a variety of infectious diseases. Despite the fact still there is no recent literature that summarises the therapeutic applications of SeNPs. There are some challenges that need to be addressed like finding targets for SeNPs in various diseases, and the various functionalization techniques utilized to increase SeNP’s stability while facilitating wide drug-loaded SeNP distribution to tumor areas and preventing off-target impacts need to focus on understanding more about the therapeutic aspects for better understanding the science behind it. Keeping that in mind we have focused on this gap and try to summarize all recent key targeted therapies for SeNPs in cancer treatment and the numerous functionalization strategies. We have also focused on recent advancements in SeNP functionalization methodologies and mechanisms for biomedical applications, particularly in anticancer, anti-inflammatory, and anti-infection therapeutics. Based on our observation we found that SeNPs could potentially be useful in suppressing viral epidemics, like the ongoing COVID-19 pandemic, in complement to their antibacterial and antiparasitic uses. SeNPs are significant nanoplatforms with numerous desirable properties for clinical translation.

Graphical Abstract
Action unit intensity regression for facial MoCap aimed towards digital humans
Authors: Vilchis Carlos , Mendez-Ruiz Mauricio , Perez-Guerrero Carmina , Gonzalez-Mendoza Miguel 
Published: May 2024

AbstractDue to the increasing demand for virtual avatars, there has been a recent growth in the research and development of frameworks for realistic digital humans, which create a demand for realistic and adaptable facial motion capture systems. Most frameworks belong to private companies or represent high investments, which is why the creation of democratized solutions is relevant for the growth of digital human content creation. This research work proposes a facial motion capture framework for digital humans with the use of machine learning for facial codification intensity regression. The main focus is to use coded face movement intensities to generate realistic expressions on a digital human. The ablation studies performed on the regression models show that Neural Networks, using Histogram of Oriented Gradients as features, and with person-specific normalization, present overall better performance against other methods in the literature. With an RMSE of 0.052, the proposed framework offers reliable results that can be rendered in the face of a MetaHuman.
Alimentary Images as Metaphor of Education
Authors: Vydra Anton 
Published: May 2024

AbstractThe aim of this paper is to explore how the history of images and conceptual metaphors resulting from them that we use in educational reflections are formed regardless of if they are problematized in practical life. Insight into history shows how these images are shaped not only by our own experiences and by the context of our lives, but also by the history of such images, which are unconsciously inscribed in our metaphorical speech through so called “residues of meaning”. The paper clarifies this, using the examples of alimentary images, that are a transition from nutrix (wet nurse) to nutritor (teacher). The text offers selected examples of consideration of alimentary images. These are among the most primitive and therefore the deepest images of human experience. This history is an example of a cultural line that goes from ancient educational imagination to the more recent forms of such images, even if always with different accents.
Toxic Effects of Pozzolanic Cement on Egg, Alevine, Fry and Juvenile Rainbow Trout (Oncorhynchus mykiss) Individuals and Some Water Quality Parameters
Authors: Er Akif , Minaz Mert , Kayış Şevki 
Published: May 2024

AbstractCurrent study aims to ascertain the harmful effects of pozzolanic cement (PC) on water quality and several indicators of aquatic life. Also, the effects of PC on different life stages of rainbow trout were investigated. The PC caused an increase in various water quality parameters including pH, suspended particles, turbidity, and conductivity. In rainbow trout, no significant differences were observed between control and experimental groups in terms of enzyme parameters. Also, this study revealed that the PC has impact on various hematological parameters. The PC was linked to histological changes in gills, DNA migration was observed in the rainbow trout exposed to PC. After 24 h, LC50 values of rainbow trout exposed to PC were 499.06, 324.66, and 361.26 mg/L for egg, alevine, and fry respectively. There was adverse relation between temperature and LC50. Consequently, cement pollution in the water and different stages of rainbow trout causes various negative effects.
Charting the Cannabis plant chemical space with computational metabolomics
Authors: Myoli Akhona , Choene Mpho , Kappo Abidemi Paul , Madala Ntakadzeni Edwin , van der Hooft Justin J. J. , Tugizimana Fidele 
Published: May 2024

Abstract
Introduction
The chemical classification of Cannabis is typically confined to the cannabinoid content, whilst Cannabis encompasses diverse chemical classes that vary in abundance among all its varieties. Hence, neglecting other chemical classes within Cannabis strains results in a restricted and biased comprehension of elements that may contribute to chemical intricacy and the resultant medicinal qualities of the plant.

Objectives
Thus, herein, we report a computational metabolomics study to elucidate the Cannabis metabolic map beyond the cannabinoids.

Methods
Mass spectrometry-based computational tools were used to mine and evaluate the methanolic leaf and flower extracts of two Cannabis cultivars: Amnesia haze (AMNH) and Royal dutch cheese (RDC).

Results
The results revealed the presence of different chemical compound classes including cannabinoids, but extending it to flavonoids and phospholipids at varying distributions across the cultivar plant tissues, where the phenylpropnoid superclass was more abundant in the leaves than in the flowers. Therefore, the two cultivars were differentiated based on the overall chemical content of their plant tissues where AMNH was observed to be more dominant in the flavonoid content while RDC was more dominant in the lipid-like molecules. Additionally, in silico molecular docking studies in combination with biological assay studies indicated the potentially differing anti-cancer properties of the two cultivars resulting from the elucidated chemical profiles.

Conclusion
These findings highlight distinctive chemical profiles beyond cannabinoids in Cannabis strains. This novel mapping of the metabolomic landscape of Cannabis provides actionable insights into plant biochemistry and justifies selecting certain varieties for medicinal use.
Effects of voluntary and forced physical exercise on the retinal health of aging Wistar rats
Authors: Szilágyi Anna , Takács Barbara , Szekeres Réka , Tarjányi Vera , Nagy Dávid , Priksz Dániel , Bombicz Mariann , Kiss Rita , Szabó Adrienn Mónika , Lehoczki Andrea , Gesztelyi Rudolf , Juhász Béla , Szilvássy Zoltán , Varga Balázs 
Published: May 2024

Abstract
Aging is accompanied by an increased prevalence of degenerative conditions, including those affecting ocular health, which significantly impact quality of life and increase the burden on healthcare systems. Among these, retinal aging is of particular concern due to its direct link to vision impairment, a leading cause of disability in the elderly. Vision loss in the aging population is associated with heightened risks of cognitive decline, social isolation, and morbidity. This study addresses the critical gap in our understanding of modifiable lifestyle factors, such as physical exercise, that may mitigate retinal aging and its related pathologies. We investigated the effects of different exercise regimens—voluntary (recreational-type) and forced (high-intensity)—on the retinal health of aging Wistar rats (18-month-old), serving as a model for studying the translational potential of exercise interventions in humans. Male Wistar rats were divided into four groups: a young control (3-month-old) for baseline comparison, an aged sedentary control, an aged group engaging in voluntary exercise via a running wheel in their cage, and an aged group subjected to forced exercise on a treadmill for six sessions of 20 min each per week. After a 6-month experimental period, we assessed retinal function via electroretinography (ERG), measured retinal thickness histologically, and analyzed protein expression changes relevant to oxidative stress, inflammation, and anti-aging mechanisms. Our findings reveal that voluntary exercise positively impacts retinal function and morphology, reducing oxidative stress and inflammation markers while enhancing anti-aging protein expression. In contrast, forced exercise showed diminished benefits. These insights underscore the importance of exercise intensity and preference in preserving retinal health during aging. The study highlights the potential of recreational physical activity as a non-invasive strategy to counteract retinal aging, advocating for further research into exercise regimens as preventative therapies for age-related ocular degenerations.
Avidity maturation of humoral response following primary and booster doses of BNT162b2 mRNA vaccine among nursing home residents and healthcare workers
Authors: Oyebanji Oladayo A. , Sundheimer Nicholas , Ragavapuram Vaishnavi , Wilson Brigid M. , Abul Yasin , Gravenstein Stefan , Bosch Jürgen , King Christopher L. , Canaday David H. 
Published: May 2024

AbstractInfections, despite vaccination, can be clinically consequential for frail nursing home residents (NHR). Poor vaccine-induced antibody quality may add risk for such subsequent infections and more severe disease. We assessed antibody binding avidity, as a surrogate for antibody quality, among NHR and healthcare workers (HCW). We longitudinally sampled 112 NHR and 52 HCWs who received the BNT162b2 mRNA vaccine after each dose up to the Wuhan-BA.4/5-based Omicron bivalent boosters. We quantified anti-spike, anti-receptor binding domain (RBD), and avidity levels to the ancestral Wuhan, Delta, and Omicron BA.1 & 4/5 strains. The primary vaccination series produced substantial anti-spike and RBD levels which were low in avidity against all strains tested. Antibody avidity progressively increased in the 6–8 months that followed. Avidity significantly increased after the 1st booster but not for subsequent boosters. This study underscores the importance of booster vaccination among NHR and HCWs. The 1st booster dose increases avidity, increasing vaccine-induced functional antibody. The higher cross-reactivity of higher avidity antibodies to other SARS-CoV-2 strains should translate to better protection from ever-evolving strains. Higher avidities may help explain how the vaccine’s protective effects persist despite waning antibody titers after each vaccine dose.