bluuebunny/crossref_metadata_2025 huggingface dataset:
Dimeric DNA Aptamers for the Spike Protein of SARS‐CoV‐2 Derived from a Structured Library with Dual Random Domains
Authors: Amini Ryan , Ma Jian , Zhang Zijie , Wang Qing , Gu Jimmy , Soleymani Leyla , Li Yingfu
Published: December 2024

Multimeric aptamer strategies are often adopted to improve the binding affinity of an aptamer toward its target molecules. In most cases, multimeric aptamers are constructed by connecting pre‐identified monomeric aptamers derived from in vitro selection. Although multimerization provides an added benefit of enhanced binding avidity, the characterization of different aptamer pairings adds more steps to an already lengthy procedure. Therefore, an aptamer engineering strategy that directly selects for multimeric aptamers is highly desirable. Here, an in vitro selection strategy is reported on using a pre‐structured DNA library that forms dimeric aptamers. Rather than using a library containing a single random region, which is nearly ubiquitous in existing aptamer selections, the library contains two random regions separated by a flexible poly‐thymidine linker. Following sixteen rounds of selection against the SARS‐CoV‐2 spike protein, a relevant model target protein due to the COVID‐19 pandemic, the top aptamers displayed superb affinity with KD values as low as 150 pM. Further analysis reveals that each random region functions as a distinct binding moiety and works together to achieve higher affinity. The demonstrated strategy provides an accelerated method to obtain high‐affinity aptamers, which may prove useful in future aptamer diagnostic and therapeutic applications.
Influence of High‐MnO on Viscous Properties of CaO‐SiO2‐MgO‐Al2O3‐BaO‐MnO Slag
Authors: Liu Wenguo , Zuo Haibin
Published: December 2024

The viscosity of CaO‐SiO2‐MgO‐Al2O3‐BaO‐MnO slag with a varying MnO content of 0–8 wt% is continuously measured, and the polymerized network changes are clarified by Fourier transform infrared reflection spectroscopy and X‐ray photoelectron spectroscopy. Thermodynamic calculation and X‐ray diffraction analysis are conducted to determine crystal phases variations. Finally, the relationship between viscosity and different structural parameters is discussed. The results indicate that an increase in MnO content decreases the viscosity from about ≈0.55 to 0.41 Pa·s at 1500 °C, and from 1.3 to 0.87 Pa·s at 1400 °C. The free running temperature also decreases. Ba2+ and Ca2+ are used for charge compensation of [AlO4], and Mn2+ mainly connects nonbridging oxygen to depolymerize the silicate network. The precipitation of crystal phases significantly increases the viscosity of the slag, and Mn2+ is mainly involved in the formation of silicate phases. Structure analyses suggest that an increase in MnO leads to a decrease in the amount of bridging oxygen, which reduces the degree of polymerization. In the composition range of blast furnace slag, the structural parameters change within a narrow range, and the viscosity has a negative correlation with NBO/T and optical basicity, yet a positive correlation with Q.
Shedding light on truck driver supply and demand: Heterogeneous state‐level recovery of trucking employment following the COVID‐19 employment shock
Authors: Phares Jonathan , Miller Jason W. , Burks Stephen V.
Published: December 2024

Is there a long‐term systemic shortage of truck drivers? We throw light on the underlying context—the demand for and supply of truck drivers—by investigating why states within the contiguous United States showed vastly different rates of recovery of state‐level truck transportation payrolls for May 2020–December 2021 following the negative employment shock brought about by COVID‐19 lockdowns in April 2020. We focus on heterogeneity in the industries that create demand for trucking services: state‐level natural resource extraction, warehousing, and container port activity. We create a state‐level archival data set of truck transportation establishment payrolls from the Quarterly Census of Employment and Wages, which we combine with other archival sources. We test our hypotheses via discontinuous growth curve models estimated using the mixed effects modeling framework. We find states that saw greater declines in natural resource extraction activity had much slower growth in trucking payrolls for May 2020–December 2021, whereas states that saw more warehousing activity growth or were home to large container ports saw faster growth in trucking payrolls. Our work extends theories regarding labor market dynamics in truck transportation and factor market rivalry, in addition to having important implications for managers and policy makers.
Predicting disease‐specific survival in patients undergoing active surveillance for papillary thyroid carcinoma
Authors: Nielsen Stanton , Kuchta Kristine , Huang Grace , Zuber Samuel , Holoubek Simon , Karcioglu Amanda , Khokar Amna , Prinz Richard , Moo‐Young Tricia
Published: December 2024

Background

American Thyroid Association guidelines support active surveillance (AS) for low‐risk papillary thyroid cancer (PTC). We developed a calculator to aid patient selection.

Methods

From 2004 to 2020, 148,904 PTC patients were selected from the surveillance, epidemiology, and end results (SEER) database. Univariable and multivariable analysis evaluated patient and treatment characteristics. Patients were randomly allocated into training (80%) or validation sets (20%). Coefficients generated a mathematical model to predict 5‐ and 10‐year disease‐specific survival (DSS).

Results

The mean DSS was 15.5 years with a 5‐ and 10‐year DSS of 99.3% and 98.6%, respectively. Age, sex, race, median household income (MHI), tumor size, and nodal status were significant on multivariable analysis (p ≤ 0.05) and included variables in our calculator. 2404 patients underwent non‐operative management (NOM) and were more likely older, male, higher MHI, larger tumor size, and less nodal positivity. Area under the curve (AUC) for 5‐ and 10‐year DSS were 0.83 and 0.81, respectively, for the training set and 0.81 and 0.79, respectively, for the validation set.

Example

65‐year‐old White female with a 0.8 cm PTC, cN0 with a MHI ≥ $75,000, had a 10‐year predicted DSS was 95.6% with NOM and 99.3% with surgery. Alternatively, changing the patient's race to Hispanic, the 10‐year predicted DSS was 94.1% with NOM and 99.0% with surgery.

Conclusions

As awareness of AS for PTC expands, it is important to consider objective data to guide informed decision making. This validated calculator is a useful tool to predict DSS for patients considering AS for PTC.
Sulfonation of IAA in Urtica eliminates its DR5 auxin activity
Authors: Supikova Klara , Žukauskaitė Asta , Kosinova Andrea , Pěnčík Aleš , De Diego Nuria , Spíchal Lukáš , Fellner Martin , Skorepova Katerina , Gruz Jiri
Published: December 2024

Key message

N-Sulfonated IAA was discovered as a novel auxin metabolite in Urtica where it is biosynthesized de novo utilizing inorganic sulfate. It showed no auxin activity in DR5::GUS assay, implying possible inactivation/storage mechanism.

A novel auxin derivative, N-sulfoindole-3-acetic acid (IAA-N-SO3H, SIAA), was discovered in stinging nettle (Urtica dioica) among 116 sulfonated metabolites putatively identified by a semi-targeted UHPLC–QqTOF-MS analysis of 23 plant/algae/fungi species. These sulfometabolites were detected based on the presence of a neutral loss of sulfur trioxide, as indicated by the m/z difference of 79.9568 Da in the MS2 spectra. The structure of newly discovered SIAA was confirmed by synthesizing its standard and comparing retention time, m/z and MS2 spectrum with those of SIAA found in Urtica. To study its natural occurrence, 73 species in total were further analyzed by UHPLC–QqTOF-MS or targeted UHPLC–MS/MS method with a limit of detection of 244 fmol/g dry weight. However, SIAA was only detected in Urtica at a concentration of 13.906 ± 9.603 nmol/g dry weight. Its concentration was > 30 times higher than that of indole-3-acetic acid (IAA), and the SIAA/IAA ratio was further increased under different light conditions, especially in continuous blue light. In addition to SIAA, structurally similar metabolites, N-sulfoindole-3-lactic acid, 4-(sulfooxy)phenyllactic acid and 4-(sulfooxy)phenylacetic acid, were detected in Urtica for the first time. SIAA was biosynthesized from inorganic sulfate in seedlings, as confirmed by the incorporation of exogenous 34S-ammonium sulfate (1 mM and 10 mM). SIAA exhibited no auxin activity, as demonstrated by both the Arabidopsis DR5::GUS assay and the Arabidopsis phenotype analysis. Sulfonation of IAA may therefore be a mechanism for IAA deactivation and/or storage in Urtica, similar to sulfonation of the jasmonates in Arabidopsis.
Coronary calcium score and emphysema extent on different CT radiation dose protocols in lung cancer screening
Authors: Ledda Roberta Eufrasia , Milanese Gianluca , Balbi Maurizio , Sabia Federica , Valsecchi Camilla , Ruggirello Margherita , Ciuni Andrea , Tringali Giulia , Sverzellati Nicola , Marchianò Alfonso Vittorio , Pastorino Ugo
Published: December 2024

Objectives

To assess the consistency of automated measurements of coronary artery calcification (CAC) burden and emphysema extent on computed tomography (CT) images acquired with different radiation dose protocols in a lung cancer screening (LCS) population.

Materials and methods

The patient cohort comprised 361 consecutive screenees who underwent a low-dose CT (LDCT) scan and an ultra-low-dose CT (ULDCT) scan at an incident screening round. Exclusion criteria for CAC measurements were software failure and previous history of CVD, including coronary stenting, whereas for emphysema assessment, software failure only. CT images were retrospectively analyzed by a fully automated AI software for CAC scoring, using three predefined Agatston score categories (0–99, 100–399, and ≥ 400), and emphysema quantification, using the percentage of low attenuation areas (%LAA). Demographic and clinical data were obtained from the written questionnaire completed by each participant at the first visit. Agreement for CAC and %LAA categories was measured by the k-Cohen Index with Fleiss-Cohen weights (Kw) and Intraclass Correlation Coefficient (ICC) with 95% Confidence Interval (CI).

Results

An overlap of CAC strata was observed in 275/327 (84%) volunteers, with an almost perfect agreement (Kw = 0.86, 95% CI 0.82–0.90; ICC = 0.86, 95% CI 0.79–0.90), while an overlap of %LAA strata was found in 204/356 (57%) volunteers, with a moderate agreement (Kw = 0.57, 95% CI 0.51–0.63; ICC = 0.57, 95% CI 0.21–0.75).

Conclusion

Automated CAC quantification on ULDCT seems feasible, showing similar results to those obtained on LDCT, while the quantification of emphysema tended to be overestimated on ULDCT images.

Key Points

QuestionEvidence demonstrating that coronary artery calcification and emphysema can be automatedly quantified on ultra-low-dose chest CT is still awaited.

FindingsCoronary artery calcification and emphysema measurements were similar among different CT radiation dose protocols; their automated quantification is feasible on ultra-low-dose CT.

Clinical relevanceUltra-low-dose CT-based LCS might offer an opportunity to improve the secondary prevention of cardiovascular and respiratory diseases through automated quantification of both CAC burden and emphysema extent.
Individual differences in processing multisensory information predict presence in different virtual reality environments
Authors: Glenn Callum P. , Coxon Matthew
Published: December 2024

One of the most notable aspects of using a head mounted display is the feeling of being ‘within’ the digitally created virtual world. Technological advances across the fields of computer science and engineering have helped to increase this sense of presence. However, there remain wide variations between individuals, which are only just beginning to be captured at a theoretical level. One potential explanation for these individual differences may be how individuals process multisensory information. In this paper we detail two studies which explored whether performance on two different multisensory tasks (the pip and pop and a redundant signals task), predict some of these differences in self-reported presence. In study 1 (N = 32), clear correlations between the multisensory task (pip and pop) and presence scores were found using an underwater simulation. This provided the first indication that individuals that were positively influenced by illusory audiovisual conjunctions were also those that had the strongest sense of presence. Study 2 (N = 68) expanded upon these results, finding again that multisensory integration (within a redundant signals task) was related to self-reports of presence using a different VR experience. In addition, it was found that this relationship could be moderated by either providing a unisensory or multisensory VR experience. Together these results suggest that individual differences in the efficiency of multisensory integration may provide an additional level of explanation not currently accounted for within theoretical models of presence formation.
Beyond the S&P 500: examining the role of external volatilities in market forecasting
Authors: Korkusuz Burak
Published: December 2024

This study examines the impact of various exogenous volatilities on S&P 500 volatility using HAR-RV-type models. In this regard, a diverse range of exogenous volatilities—including assets, commodities, oil, gold, bonds, interest rates, the CBOE Volatility Index (VIX), and the Economic Policy Uncertainty (EPU) index—are incorporated into the Heterogenous Autoregressive (HAR) model. The exogenous volatilities are classified into three groups: European Market Information, U.S. Market Information, and U.S. Financial and Policy-Related Information. The study aims to determine which group of information contributes most effectively to forecasting S&P 500 stock market volatility. The results reveal several noteworthy points. First, the predictive accuracy of the baseline HAR-RV model is improved by incorporating exogenous explanatory variables. Second, the combination and the kitchen-sink approaches outperform models with single exogenous regressors, particularly for the U.S. Market Information group. Third, the U.S. Market Information group demonstrates superior predictive power compared to the other two groups, highlighting the interconnected nature of U.S. financial markets.
Environmentally Resistant Flax Fiber-Reinforced Composites for Aircraft Applications: Aviation Stress Tests with Optical and Mechanical Analyses
Authors: Schulte Sarina , Schäfer Hannes , Vogel Christoph , Shah Vineet , Kroll Stephen , Siebert-Raths Andrea
Published: December 2024

Flax fiber-reinforced composites (FFRCs) must be resistant to environmental conditions to use them for external components in aviation. It was investigated how contact with typical aviation liquids, i.e. water, jet fuel and hydraulic oil, affects the optical and mechanical properties of twill fabric epoxy resin-based FFRCs. These influences were compared to the effect of UV weathering. Samples were exposed to these conditions for up to 28 days at RT. Uncoated samples with different fiber contents served as references and were compared with coated samples. A polyurethane/epoxy-based aircraft coating system and a partially biobased automotive interior coating as a more sustainable alternative were examined. The main damage for the uncoated samples was caused by UV weathering and water. UV light leads to photo-oxidation, causing material erosion. Water is absorbed by the hydrophilic flax fibers. Subsequent swelling leads to deformation and delamination. Thus, the damage was more severe for a higher fiber content. No effect could be demonstrated by immersion in jet fuel and hydraulic oil, as they are hardly absorbed by the fibers. Both coatings showed good protection against UV weathering and delayed water absorption. Nevertheless, mechanical damage was found for the FFRC covered with the fossil coating after 28 days of immersion in water. FFRC with an appropriate coating could therefore be suitable for use in aviation, but prolonged contact with water should be avoided. Protective measures should focus on preventing water uptake and UV irradiation, as these cause significantly more damage than jet fuel and hydraulic oil.
Big data analysis: examination of the relationship between candidates’ sociodemographic characteristics and performance in the UK’s Membership of the Royal College of Physicians Part 1 examination
Authors: Johnston Peter W. , Vieira Rute , Cameron Isobel M. , Kumwenda Ben , Walker Kim A. , Cleland Jennifer A.
Published: December 2024

Big datasets and data analytics enable granular analyses examining group differences in performance. Our focus is on differential attainment (DA) in postgraduate College (Board) examinations. We asked: Are candidates’ sociodemographic characteristics associated with performance on the UK’s Membership of the Royal College of Physicians (MRCP) Part 1 after adjusting for medical school performance (MSP) and type of medical programme? This was a retrospective longitudinal cohort study of 6040 medical graduates with linked sociodemographic data in the UK Medical Education Database qualifying from a UK medical school (2012–2014) and sitting MRCP Part 1 before October 2019. Chi-squared tests established univariable associations with MRCP performance (pass/fail first sitting MRCP Part 1). Multivariable mixed-effects logistic regression identified independent explanatory factors of success, adjusted for medical school. The odds (95% CI) of passing MRCP Part 1 exams on first sitting were greater for men (OR = 1.61, CI 1.42–1.81, p < 0.001) and those on a graduate entry programme (OR = 1.44, 1.05–1.99, p < 0.001). The odds of passing were lower as age increases (OR = 0.87, 0.85–0.90, p < 0.001), for minority ethnic (OR = 0.61, CI 0.53–0.7, p < 0.001), and gateway to medicine (OR = 0.49, CI 0.27–0.90, p = 0.02) candidates. After adjusting for MSP, odds were greater for passing in men (OR = 1.62, CI 1.24–2.11, p < 0.001) and candidates with higher MSP (OR = 4.12, CI 3.40–4.96, p < 0.001). Our findings illustrate how performance on MRCP part 1 is associated with group-level social and educational factors. This DA may be due to aspects of the assessment itself, and/or the persistent nature of social and educational disadvantage.
Staying ahead of phishers: a review of recent advances and emerging methodologies in phishing detection
Authors: Kavya S. , Sumathi D.
Published: December 2024

The escalating threat of phishing attacks poses significant challenges to cybersecurity, necessitating innovative approaches for detection and mitigation. This paper addresses this need by presenting a comprehensive review of state-of-the-art methodologies for phishing detection, spanning traditional machine learning techniques to cutting-edge deep learning frameworks. The review encompasses a diverse range of methods, including list-based approaches, machine learning algorithms, graph-based analysis, deep learning models, network embedding techniques, and generative adversarial networks (GANs). Each method is meticulously scrutinized, highlighting its rationale, advantages, and empirical results. For instance, deep learning models, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), demonstrate superior detection performance, leveraging their ability to extract complex patterns from phishing data. Ensemble learning techniques and GANs offer additional benefits by enhancing detection accuracy and resilience against adversarial attacks. The impact of this review extends beyond academic discourse, informing practitioners and policymakers about the evolving landscape of phishing detection. By elucidating the strengths and limitations of existing methods, this paper guides the development of more robust and effective cybersecurity solutions. Moreover, the insights gleaned from this review lay the groundwork for future research endeavors, such as integrating contextual information, user behavior analysis, and explainable AI techniques into phishing detection systems. Ultimately, this work contributes to the collective effort to fortify digital defenses against sophisticated phishing threats, safeguarding the integrity of online ecosystems.
Criteria definition for digital requirements using hesitant fuzzy linguistic terms sets: an application to the automotive industry
Authors: Fronte Pietro , Agell Núria , Torrens Marc , Mesa Diana
Published: December 2024

Managing a portfolio of digital products is challenging, particularly in a context of limited economic resources and workforce. Therefore, prioritization of activities and new developments is crucial. In Software Development environment, almost all well-known prioritization techniques are based on experts’ knowledge and opinion, leaving little room for a data-driven, objective approach. In this paper, we propose a methodology that adopts the Delphi framework and Hesitant Fuzzy Linguistic Term Sets for collecting experts’ opinions, evaluating perceived importance, and computing group consensus. The objective is to provide a framework to define a group-consensual set of relevant criteria that would represent the basis for a data-driven prioritization process for digital requirements. Implementation and results from a real case application in a European automotive company are presented to understand the relevance of criteria and suggest their inclusion or exclusion for prioritization purposes.
Influence of antibody–drug conjugate cleavability, drug-to-antibody ratio, and free payload concentration on systemic toxicities: A systematic review and meta-analysis
Authors: Tang Shou-Ching , Wynn Carrie , Le Tran , McCandless Martin , Zhang Yunxi , Patel Ritesh , Maihle Nita , Hillegass William
Published: December 2024

While in theory antibody drug conjugates (ADCs) deliver high-dose chemotherapy directly to target cells, numerous side effects are observed in clinical practice. We sought to determine the effect of linker design (cleavable versus non-cleavable), drug-to-antibody ratio (DAR), and free payload concentration on systemic toxicity. Two systematic reviews were performed via PubMed search of clinical trials published between January 1998—July 2022. Eligible studies: (1) clinical trial for cancer therapy in adults, (2) ≥ 1 study arm included a single-agent ADC, (3) ADC used was commercially available/FDA-approved. Data was extracted and pooled using generalized linear mixed effects logistic models. 40 clinical trials involving 7,879 patients from 11 ADCs, including 9 ADCs with cleavable linkers (N = 2,985) and 2 with non-cleavable linkers (N = 4,894), were included. Significantly more composite adverse events (AEs) ≥ grade 3 occurred in patients in the cleavable linkers arm (47%) compared with the non-cleavable arm (34%). When adjusted for DAR, for grade ≥ 3 toxicities, non-cleavable linkers remained independently associated with lower toxicity for any AE (p = 0.002). Higher DAR was significantly associated with higher probability of grade ≥ 3 toxicity for any AE. There was also a significant interaction between cleavability status and DAR for any AE (p = 0.002). Finally, higher measured systemic free payload concentrations were significantly associated with higher DARs (p = 0.043). Our results support the hypothesis that ADCs with cleavable linkers result in premature payload release, leading to increased systemic free payload concentrations and associated toxicities. This may help to inform future ADC design and rational clinical application.
Constructing understanding: on the constructional information encoded in large language models
Authors: Bonial Claire , Tayyar Madabushi Harish
Published: December 2024

We review research related to both Construction Grammar (CxG) and Natural Language Processing showing that recent advances in probing Large Language Models (LLMs) for certain types of linguistic knowledge align with the tenets of CxG. However, our survey leads us to hypothesize that LLM constructional information may be limited to the constructions within the lower levels of postulated taxonomical “constructicons” enumerating a particular language’s constructions. Specifically, probing studies show that the constructions at the lower levels of the taxonomy, which are more substantive constructions with fixed elements corresponding to frequently used words within that construction, are a type of linguistic information accessible to LLMs. In contrast, more general, abstract constructions with schematic slots that can be filled by a variety of different words are not included in the linguistic knowledge of LLMs. We test this hypothesis on a collection of 10 distinct constructions, each of which is exhibited in 50 or more corpus instances. Our experimental results strongly support our hypothesis and lead us to conclude that, in order for LLMs to generalize to the point where purely schematic constructions can be recognized regardless of the frequency of the instantiating words (as psycholinguistic experimentation has shown people can), additional semantic resources are needed to make explicit the semantic role of the schematic slot. To ensure transparency and reproducibility, we publicly release our experimental data, including the prompts used with the model.
Historical and future winter chill for temperate fruit and nut trees in Afghanistan
Authors: Shinwari Atifullah , Caspersen Lars , Schiffers Katja , Luedeling Eike
Published: December 2024

Temperate fruit trees require exposure to chill and heat conditions to overcome the dormant period in winter and resume growth in spring. Rising temperatures due to climate change have already impacted winter chill accumulation in horticulturally vital growing regions worldwide. Afghanistan’s intra-regional differences make the country favorable for producing a wide range of fruits and nuts, which constitute approximately 30% of the country’s total export earnings. However, expected future temperature increases may be detrimental to the trees’ ability to fulfill their chilling requirements. To quantify this risk, we computed and mapped historical and future chill accumulation in Afghanistan. For this purpose, we used long-term daily temperature data from 1980 to 2020 for 51 hydrometeorological stations across the country. Based on the temperature data, we produced four future Shared Socioeconomic Pathway (SSP) scenarios (SSP126, SSP245, SSP370, and SSP585) for five General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We used the RMAWGEN weather generator to produce 100 synthetic realizations of weather records for historical (1980, 1990, 2000, 2010, and 2020) and future conditions (2035–2065 and 2070–2100). We quantified winter chill using the Dynamic Model. Additionally, we computed Safe Winter Chill (SWC), which is defined as the level of chill that is expected to be exceeded in 90% of years. We find that SWC has decreased in historical scenarios in the low-lying regions mainly in the eastern, southern, and parts of the northern regions, and is projected to further decrease in the future. This reveals a possible future chill risk for high chill-requiring cultivars of different fruit and nut species, including apricot, peach, plum, pistachio and almond, in these regions. In contrast, we record an increase in SWC in the northern and central regions, suggesting these regions as potentially favorable for high-chill species in the future. Our findings support fruit and nut growers in Afghanistan in adapting their orchards to match chill requirements of species and cultivars to the expected future winter chill.
Phase constituent of an as-cast Co–Ni–Al–W–Re–Ti alloy: correlation of DTA results with CALPHAD and map structure simulations
Authors: Tomaszewska A. , Moskal G. , Homa M. , Kierat M. , Liśkiewicz M. , Mikuszewski T. , Witala B. , Szczotok A. , Kolakowski P. , Maciąg T.
Published: December 2024

Designing the chemical composition of new heat-resistant materials, including a new group of cobalt-based materials strengthened with the L12 phase with the general formula Co3(Al,X), requires the introduction of numerous alloy components, stabilizing the strengthening phase into the base composition. Typically, these are elements of high melting metals, whose main role is to stabilize the interphase boundary between the matrix and L12 precipitates and, in some way, strengthen the solid solution. These elements are characterized by high bond energy. On the other hand, the high content of this type of alloy addition increases the tendency of the alloy to release undesirable topologically compact phases, which rapidly deteriorate the mechanical properties of the alloy. These phases usually form in interdendritic areas, generating the so-called melting onset temperature, which deviates significantly from the solidus value. Therefore, the ability to predict the type and number of topologically compact phases being formed allows for the skilful design of the chemical composition of the alloy and its heat treatment, ensuring full dissolution of the mentioned phases in the matrix. This topic is the area of research in this article and concerns the Co–20Ni–9Al–7W–3Re–2Ti alloy in its immediately as-cast state. The scope of the research included simulations using the CALPHAD method and prediction of the phase composition of precipitates using two-dimensional structure maps. The obtained theoretical results were verified in microstructural tests using the STEM method and correlated with the results of DTA tests.
Risk-taking, knowledge, and mindset: unpacking the antecedents of entrepreneurial intention
Authors: Caputo Andrea , Nguyen Vu Huu Anh , Delladio Silvia
Published: December 2024

This paper expands the existing literature on entrepreneurial intentions by employing the integrated model of external factors, personality characteristics, the theory of planned behavior, and social cognitive theory to explore the effects of risk-taking, entrepreneurial knowledge, entrepreneurial mindset, and cognitive antecedents on entrepreneurial intention. Adopting a cross-sectional approach, this study collected data from 422 respondents using questionnaires, and the findings were analyzed using partial least squares-structural equation modeling. The results suggest that risk-taking is closely related to opportunities and shapes entrepreneurial self-efficacy; entrepreneurial knowledge is crucial in developing entrepreneurial intention by shaping cognitive antecedents. The effect mechanism of the entrepreneurial mindset can change the coping defense mechanism by boosting attitude and self-confidence. Attitude towards entrepreneurship is one of the best factors in driving entrepreneurial intention and will subsequently directly affect behavior. Unleashing entrepreneurial competencies is vital for enhancing entrepreneurial intention. Furthermore, entrepreneurial passion can act as a moderator among attitudes toward entrepreneurship, entrepreneurial self-efficacy, and entrepreneurial intention. The findings also provide seminal insights into external factors, cognitive antecedents, and entrepreneurial intentions for policymakers to design education programs.
The Readability Study: A Randomised Trial of Health Information Written at Different Grade Reading Levels
Authors: Mac Olivia , Ayre Julie , McCaffery Kirsten , Boroumand Farzaneh , Bell Katy , Muscat Danielle M.
Published: December 2024

Background

Despite increasing attention on health literacy and the inclusion of grade reading level recommendations in guidelines, it remains unclear if lowering the grade reading level of written health information to specific target grades improves patient-related outcomes.

Objective

To assess whether grade reading level of written information affects knowledge, perceived reading ease, acceptability and trustworthiness of information and, to explore whether information written at a lower grade reading level reduces disparities in outcomes across health literacy levels.

Design

We conducted a 4-arm online randomized trial with a community sample of adults living in Australia from 31 July to 20 September 2023.

Experimental Arms

Participants were randomised to one of four arms: Information about sciatica and knee osteoarthritis written at a grade 8, 10, 12 or 14 reading level. Readability was assessed using the SMOG Index and iteratively revised to each lower grade.

Measures

Primary outcome was knowledge of health conditions. Secondary outcomes were brief knowledge, perceived reading ease, acceptability (i.e., perceived usefulness and likelihood to recommend) and trustworthiness of information.

Results

2235 participants were randomised and included in the analysis. Mean age was 41 years and 54.5% identified as female. Low health literacy was identified in 28.2% of participants. We found no evidence of a main effect of grade reading level on knowledge (grade 8: 9.0 (SD = 2.7), grade 10: 9.1 (SD = 2.6), grade 12: 8.9, grade 14: 9.1 (SD = 2.7). Participants with high health literacy had higher knowledge scores overall, however, there was no evidence that health literacy modified the effect of grade reading level. There were no significant differences in any of the secondary outcomes.

Conclusions

Our study showed no difference in knowledge when grade reading level was manipulated alone. Our findings indicate there is limited value in reducing grade reading level without attention to other health literacy principles.

ANZCTR trial registry number

ACTRN12623000224628p.
Predictors for national junior squad selection in the German Volleyball Federation
Authors: Cermak N. , Wittenbrink P. , Rosenkötter M. , Zentgraf K.
Published: December 2024

Introduction

More and more studies recommend combining holistic coaches’ assessments (CA) with multidimensional measurements for selection decisions to enhance predictive value for talent development. The so-called coach’s eye is one of the most used criteria for talent selection, especially in sports games. Few studies have analyzed predictors for talent selection in volleyball, particularly among female athletes. Therefore, the aim of this study was to study predictors for being selected to the first German junior national squad in volleyball, both in female and male players.

Methods

Data of 106 athletes (female n = 53, male n = 53), participating in the national selection camps for the under 17 (U17) national squad, were analyzed in this study. Anthropometrics, motor performance, motor–cognitive and cognitive data, as well as CA were collected during the camp. In a first step, these data were reduced using a principal component analysis; resulting components were then analyzed in a binomial logistic regression (stepwise backwards) to predict selection.

Results

For both sexes, the CA were found to predict selection, with 86.8% of female athletes (Nagelkerke’s R2 = 0.53) and 81.1% of male athletes (Nagelkerke’s R2 = 0.61) correctly classified. No other data were found to be predictive for the German national squads.

Conclusion

Accordingly, the CA play a particularly important role in talent selection as they were the only predictors for selection to both national squads. Combining the per se multidimensional coach’s eye with further assessments and tests seems to be a valid approach.
How advocacy coalitions in Sweden explain the policy gap between Swedish and EU eel fishery policies
Authors: Nilsson Jens , Sandström Annica
Published: December 2024

Our study explores governing of European eel in Sweden. The paper aims to analyze and tentatively explain the degree of policy coherence between different political levels and discuss implications for management. The study focuses on the Advocacy Coalition Framework and a qualitative methodology. Results show that EU and Swedish eel fishery policies are based on partly different beliefs about prioritized groups, problem descriptions, and policy preferences. Swedish policy is more considerate of fishery, attentive to the problems of hydropower, and hesitant toward fishery closures, than is the EU. These differences can be understood by the positions and power of the two advocacy coalitions competing for influence at the national level. National decisions align more with the coalition that includes fishery organizations, the Swedish Board of Agriculture, and coastal municipalities than with the beliefs of the coalition involving environmental—and sport fishing organizations and the Swedish Environmental Protection Agency.
Insights into pubertal development: a narrative review on the role of epigenetics
Authors: Shulhai Anna-Mariia , Munerati Anna , Menzella Marialaura , Palanza Paola , Esposito Susanna , Street Maria Elisabeth
Published: December 2024

Purpose

Puberty is a key phase of growth and development, characterized by psychophysical transformations. It is driven by a combination of genetic, hormonal, and environmental variables. Epigenetic mechanisms, including histone post-translational modifications and chromatin remodeling, microRNAs, and DNA methylation, play important roles in orchestrating the developmental processes. We describe environmental factors that may interact with genetics, and factors influencing puberty onset, focusing in particular on epigenetic mechanisms that can help understand the timing and variations that lead to precocious or delayed puberty.

Methods

We conducted a narrative review of associations between puberty and epigenetic mechanisms through a comprehensive search of PubMed, Scopus, and Web of Science databases.

Results

The chromatin landscape of genes as KISS1 has revealed dynamic changes in histone modifications as puberty approaches, influencing the stimulation or inhibition of gene expression critical for reproductive maturation. MiRNAs regulate gene expression, whereas DNA methylation affects activation or repression of gene transcription of genes involved in pubertal timing. Moreover, studies in animal models have provided insights into the role of DNA methylation and miRNAs in brain sexual differentiation, highlighting the active involvement of epigenetic mechanisms in shaping sexually dimorphic brain structures.

Conclusion

This review highlights the importance of understanding the complex interplay between epigenetic regulation and pubertal development, which can lead to new therapeutic options and shed light on the fundamental processes driving reproductive maturation.
Relation Semantic Guidance and Entity Position Location for Relation Extraction
Authors: Chen Guojun , Chen Panfeng , Li Hui , Wang Xibin , Zhou Xin , Yu Aihua , Deng Xingzhi , Wang Qi
Published: December 2024

Relation extraction is a research hot-spot in the field of natural language processing, and aims at structured knowledge acquirement. However, existing methods still grapple with the issue of entity overlapping, where they treat relation types as inconsequential labels, overlooking the fact that relation type has a great influence on entity type hindering the performance of these models from further improving. Furthermore, current models are inadequate in handling the fine-grained aspect of entity positioning, which leads to ambiguity in entity boundary localization and uncertainty in relation inference, directly. In response to this challenge, a relation extraction model is proposed, which is guided by relational semantic cues and focused on entity boundary localization. The model uses an attention mechanism to align relation semantics with sentence information, so as to obtain the most relevant semantic expression to the target relation instance. It then incorporates an entity locator to harness additional positional features, thereby, enhancing the capability of the model to pinpoint entity start and end tags. Consequently, this approach effectively alleviates the problem of entity overlapping. Extensive experiments are conducted on the widely used datasets NYT and WebNLG. The experimental results show that the proposed model outperforms the baseline ones in F1 scores of the two datasets, and the improvement margin is up to 5.50% and 2.80%, respectively.
Public Willingness to Pay for Sustainable Consumption: Case of Bioplastic Medical Masks
Authors: Zeng Ke , Murayama Takehiko , Nishikizawa Shigeo , Suwanteep Kultip
Published: December 2024

Bioplastics have the potential to mitigate plastic pollution and contribute to the achievement of the UN Sustainable Development Goals (UN-SDGs). However, the proportion of bioplastics in total plastic production is still comparatively low. Understanding consumers’ willingness to pay (WTP) and influencing factors is essential as consumers’ demands drive the need for production. A discrete choice experiment (DCE) was conducted to investigate consumers’ WTP and identify underlying drivers and barriers to sustainable purchase intention. Results showed that 89% of the time consumers chose the bioplastic medical masks while 11% of the time chose not to purchase. Biodegradability was the most valued attributes which reflected on the highest premium price for product that are biodegradable under six months. Consumers preferred first generation raw material rather than second and third generation raw material. Moreover, greater bioplastic percentage and free of pollutants information were preferred properties. By estimating the influence of covariates, results showed that education level, income, personal innovativeness, subjective norm, and influence of COVID-19 acted as drivers, whereas age and perceived policy effectiveness acted as barriers to sustainable consumption of bioplastic products. Based on the results, policy implications include highlighting sustainable attributes that consumers value, providing quality and reliability information, informing and educating targeted consumer groups, enhancing policy publicity, and adjusting policies based on feedback. These results can be used to develop market promotion strategies for bioplastic products and to increase bioplastic market shares and penetration.
LGBTQIA+ medical student sexual healthcare workshop: peer learning and student leadership
Authors: Dullea Elizabeth J. , Steffens Karly A. , Phillips Keeley I. , Rogers Sydney N. , Highland Krista B.
Published: December 2024

Purpose

To address the absence of medical education curriculum focused on LGBTQ+ inclusive healthcare, this performance improvement project evaluated a medical student-developed and -led workshop focused on inclusive healthcare, including aspects of sexual health and well-being care.

Approach

The project utilized a peer-to-peer and community engaged approach to ensure inclusiveness and effectiveness in improving learner knowledge, confidence, and motivation to engage in evidence-based, patient-centered care. Over two years, the health professions student LGBTQIA+ interest group, Spectrum, hosted two voluntary workshops to support medical students’ sexual health history-taking skills. The 2022 Spectrum leadership team wrote three LGBTQIA+ standardized patient scenarios set within the students’ training hospitals focused on using the Centers for Disease Control and Prevention’s 5Ps, using inclusive language, and recognizing institutional barriers to healthcare. Workshops included a 10-min discussion highlighting best practices, 45 min of small group practice with standardized patient-facilitator dyads, and a 10-min reflection. Project evaluation incorporated quantitative and qualitative feedback from participants and facilitators.

Results

Quantitative feedback reflected consistently positive ratings, with learners reporting increased comfort, satisfaction, perceived applicability, and confidence. Qualitative feedback highlighted the benefits of including representative patients, practicing inclusive language, and receiving real-time feedback. Peer-led facilitation contributed to a supportive learning environment, emphasizing the importance of curricular co-production and experiential leadership development. Facilitators described feeling empowered to develop cases reflecting genuine lived experiences and not simplified scenarios.

Conclusions

This study emphasizes the value of increased medical student engagement in sexual healthcare education and advocates for further integration of LGBTQ+ inclusive curriculum into the medical curriculum.
Nigerian journals, publishers, and libraries: a response to Hans Zell
Authors: Limb Peter
Published: December 2024

An important and timely recent article by Hans Zell on Nigerian university presses prompts wider questions about the state of Nigerian scholarly publishing, how universities in general and journal publishers in particular adapt, and how libraries access scholarly outputs. This brief response to the article seeks to widen the discussion and encourage further research and action on the subject.
A Machine Learning architecture to forecast Irregular Border Crossings and Asylum requests for policy support in Europe: a case study
Authors: Bosco Claudio , Minora Umberto , Rosińska Anna , Teobaldelli Maurizio , Belmonte Martina
Published: December 2024

Anticipating future migration trends is instrumental to the development of effective policies to manage the challenges and opportunities that arise from population movements. However, anticipation is challenging. Migration is a complex system, with multifaceted drivers, such as demographic structure, economic disparities, political instability, and climate change. Measurements encompass inherent uncertainties, and the majority of migration theories are either under-specified or hardly actionable. Moreover, approaches for forecasting generally target specific migration flows, and this poses challenges for generalisation.

In this paper, we present the results of a case study to predict Irregular Border Crossings (IBCs) through the Central Mediterranean Route and Asylum requests in Italy. We applied a set of Machine Learning techniques in combination with a suite of traditional data to forecast migration flows. We then applied an ensemble modelling approach for aggregating the results of the different Machine Learning models to improve the modelling prediction capacity.

Our results show the potential of this modelling architecture in producing forecasts of IBCs and Asylum requests over 6 months. The explained variance of our models through a validation set is as high as 80%. This study offers a robust basis for the construction of timely forecasts. In the discussion, we offer a comment on how this approach could benefit migration management in the European Union at various levels of policy making.
A feminist framework for urban AI governance: addressing challenges for public–private partnerships
Authors: McCrory Laine
Published: December 2024

This analysis provides a critical account of AI governance in the modern “smart city” through a feminist lens. Evaluating the case of Sidewalk Labs’ Quayside project—a smart city development that was to be implemented in Toronto, Canada—it is argued that public–private partnerships can create harmful impacts when corporate actors seek to establish new “rules of the game” regarding data regulation. While the Quayside project was eventually abandoned in 2020, it demonstrates key observations for the state of urban algorithmic governance both within Canada and internationally. Articulating the need for a revitalised and participatory smart city governance programme prioritizes meaningful engagement in the forms of transparency and accountability measures. Taking a feminist lens, it argues for a two-pronged approach to governance: integrating collective engagement from the outset in the design process and ensuring the civilian data protection through a robust yet localized rights-based privacy regulation strategy. Engaging with feminist theories of intersectionality in relation to technology and data collection, this framework articulates the need to understand the broader histories of social marginalization when implementing governance strategies regarding artificial intelligence in cities.