bluuebunny/crossref_metadata_2025_split huggingface dataset:
Student attentiveness analysis in virtual classroom using distraction, drowsiness and emotion detection
Authors: Kaewkaisorn Khwanchai , Pintong Krisna , Bunyang Songpol , Tansawat Teerarat , Siriborvornratanakul Thitirat 
Published: May 2024

AbstractElectronic Learning (E-Learning) played a significant role in education during the Covid-19 pandemic. It is a way to teach and learn online, and it is an efficient method of knowledge transfer for the instructors and students, who must practice social distancing and have less interaction during the pandemic. However, although multimedia applications have provided convenience for online learning, they still present challenges for instructors to measure and assess students' attentiveness during online classes. This study aims to develop an assessment framework based on machine learning methods to analyze students' attentiveness in online sessions and provide a guiding solution for instructors to manage their online classes. The framework detects the behavior of learners and analyzes signs of distraction, drowsiness, and varied emotions while they participate in online classes. These three signs have been used as features to train the Long Short-Term Memory (LSTM) model for predicting whether learners are 'Focused' or 'Not Focused' during their online classes. The developed model achieves an accuracy of 90.2% on the test dataset based on the experiment results. However, this project could be further developed for more efficient research. It can also serve as a foundational guideline for the efficacy of online teaching systems, which can play a key role in helping instructors adopt suitable teaching methods for learners in the future.
Attachment theory: survival, trauma, and war through the eyes of Bowlby
Authors: Twohig Aoife , Lyne John , McNicholas Fiona 
Published: May 2024

AbstractChildren are no strangers to war and conflict, and for as long as history has been documented, so too has the negative impact of war on children. Attachment theory, which has shone a light upon the ways in which early life experiences can impact individuals across the lifespan, is a helpful lens through which we can view the consequences of war. Similar to the aftermath of war leading to lifelong and transgenerational suffering due to deaths and physical health issues, attachment difficulties created during war further compound long-term damage. Yet, despite our theoretical understanding of the detrimental impact of war on children and on humankind, humanity has failed to find ways to avert, or at least minimise, this unfortunate risk. Instead in this century, we see a growing number of conflicts globally with increasing asylum seekers. In this editorial, we argue that the large-scale disruption to attachment relationships caused by conflict and war is an important consideration for global policy, and that the healthcare community must show leadership in highlighting this serious impact of war.
Geometric random intersection graphs with general connection probabilities
Authors: Deijfen Maria , Michielan Riccardo 
Published: May 2024

AbstractLet
$\mathcal{V}$
and
$\mathcal{U}$
be the point sets of two independent homogeneous Poisson processes on
$\mathbb{R}^d$
. A graph
$\mathcal{G}_\mathcal{V}$
with vertex set
$\mathcal{V}$
is constructed by first connecting pairs of points (v, u) with
$v\in\mathcal{V}$
and
$u\in\mathcal{U}$
independently with probability
$g(v-u)$
, where g is a non-increasing radial function, and then connecting two points
$v_1,v_2\in\mathcal{V}$
if and only if they have a joint neighbor
$u\in\mathcal{U}$
. This gives rise to a random intersection graph on
$\mathbb{R}^d$
. Local properties of the graph, including the degree distribution, are investigated and quantified in terms of the intensities of the underlying Poisson processes and the function g. Furthermore, the percolation properties of the graph are characterized and shown to differ depending on whether g has bounded or unbounded support.
INVARIANT KEISLER MEASURES FOR
$\omega $
-CATEGORICAL STRUCTURES
Authors: MARIMON PAOLO 
Published: May 2024

Abstract
A recent article of Chernikov, Hrushovski, Kruckman, Krupinski, Moconja, Pillay, and Ramsey finds the first examples of simple structures with formulas which do not fork over the empty set but are universally measure zero. In this article we give the first known simple

$\omega $

-categorical counterexamples. These happen to be various

$\omega $

-categorical Hrushovski constructions. Using a probabilistic independence theorem from Jahel and Tsankov, we show how simple

$\omega $

-categorical structures where a formula forks over

$\emptyset $

if and only if it is universally measure zero must satisfy a stronger version of the independence theorem.
CAN THE UK ACHIEVE NET ZERO GREENHOUSE GAS EMISSIONS BY 2050?
Authors: Castle Jennifer L. , Hendry David F. 
Published: May 2024

AbstractNet zero greenhouse gas emissions by 2050, the UK’s current target, requires bridging a dramatic energy transition and eliminating all other net sources of emissions while ensuring a just transition. Key components like renewable electricity generation and electric vehicles are well developed, but many issues remain. Public support for a green economy may wane if the economic costs are too high or seen as unfair. Therefore, although renewable energy is cheaper than fossil fuels, it is essential to maintain employment, real per capita growth and reduced inequality. Decarbonizing the UK economy requires an integrated sequential approach and need not be delayed while dealing with the aftermath of the COVID-19 pandemic, energy crisis and resulting inflation.
Person-specific and pooled prediction models for binge eating, alcohol use and binge drinking in bulimia nervosa and alcohol use disorder
Authors: Leenaerts N. , Soyster P. , Ceccarini J. , Sunaert S. , Fisher A. , Vrieze E. 
Published: May 2024

AbstractBackgroundMachine learning could predict binge behavior and help develop treatments for bulimia nervosa (BN) and alcohol use disorder (AUD). Therefore, this study evaluates person-specific and pooled prediction models for binge eating (BE), alcohol use, and binge drinking (BD) in daily life, and identifies the most important predictors.MethodsA total of 120 patients (BN: 50; AUD: 51; BN/AUD: 19) participated in an experience sampling study, where over a period of 12 months they reported on their eating and drinking behaviors as well as on several other emotional, behavioral, and contextual factors in daily life. The study had a burst-measurement design, where assessments occurred eight times a day on Thursdays, Fridays, and Saturdays in seven bursts of three weeks. Afterwards, person-specific and pooled models were fit with elastic net regularized regression and evaluated with cross-validation. From these models, the variables with the 10% highest estimates were identified.ResultsThe person-specific models had a median AUC of 0.61, 0.80, and 0.85 for BE, alcohol use, and BD respectively, while the pooled models had a median AUC of 0.70, 0.90, and 0.93. The most important predictors across the behaviors were craving and time of day. However, predictors concerning social context and affect differed among BE, alcohol use, and BD.ConclusionsPooled models outperformed person-specific models and the models for alcohol use and BD outperformed those for BE. Future studies should explore how the performance of these models can be improved and how they can be used to deliver interventions in daily life.
Effectiveness of a digital alcohol intervention as an add-on to depression treatment for young adults: results of a pragmatic randomized controlled trial
Authors: Schouten Maria J. E. , Goudriaan Anna E. , Schaub Michael P. , Dekker Jack J. M. , Blankers Matthijs 
Published: May 2024

AbstractBackgroundProblematic drinking frequently co-occurs with depression among young adults, but often remains unaddressed in depression treatment. Evidence is insufficient on whether digital alcohol interventions can be effective in this young comorbid population. In a randomized controlled trial, we examined the effectiveness of Beating the Booze (BtB), an add-on digital alcohol intervention to complement depression treatment for young adults.MethodsParticipants were randomized to BtB + depression treatment as usual (BTB + TAU, n = 81) or TAU (n = 82). The primary outcome was treatment response, a combined measure for alcohol and depression after 6-month follow-up. Secondary outcomes were number of weekly drinks (Timeline Follow-back) and depressive symptoms (Center for Epidemiologic Studies Depression scale). Treatment response was analyzed using generalized linear modeling and secondary outcomes using robust linear mixed modeling.ResultsLow treatment response was found due to lower than expected depression remission rates. No statistically significant between-group effect was found for treatment response after 6-month follow-up (odds ratio 2.86, p = 0.089, 95% confidence interval [CI] 0.85–9.63). For our secondary outcomes, statistically significant larger reductions in weekly drinks were found in the intervention group after 3-month (B = −4.00, p = 0.009, 95% CI −6.97 to −1.02, d = 0.27) and 6-month follow-up (B = −3.20, p = 0.032, 95% CI −6.13 to −0.27, d = 0.23). We found no statistically significant between-group differences on depressive symptoms after 3-month (B = −0.57, p = 0.732, 95% CI −3.83 to 2.69) nor after 6-month follow-up (B = −0.44, p = 0.793, 95% CI −3.69 to 2.82).ConclusionsThe add-on digital alcohol intervention was effective in reducing alcohol use, but not in reducing depressive symptoms and treatment response among young adults with co-occurring depressive disorders and problematic alcohol use.Trial registration:Pre-registered on October 29, 2019 in the Overview of Medical Research in the Netherlands (OMON), formerly the Dutch Trial Register(https://onderzoekmetmensen.nl/en/trial/49219).
Age-dependent association of cannabis use with risk of psychotic disorder
Authors: McDonald André J. , Kurdyak Paul , Rehm Jürgen , Roerecke Michael , Bondy Susan J. 
Published: May 2024

AbstractBackgroundEpidemiologic research suggests that youth cannabis use is associated with psychotic disorders. However, current evidence is based heavily on 20th-century data when cannabis was substantially less potent than today.MethodsWe linked population-based survey data from 2009 to 2012 with records of health services covered under universal healthcare in Ontario, Canada, up to 2018. The cohort included respondents aged 12–24 years at baseline with no prior psychotic disorder (N = 11 363). The primary outcome was days to first hospitalization, ED visit, or outpatient visit related to a psychotic disorder according to validated diagnostic codes. Due to non-proportional hazards, we estimated age-specific hazard ratios during adolescence (12–19 years) and young adulthood (20–33 years). Sensitivity analyses explored alternative model conditions including restricting the outcome to hospitalizations and ED visits to increase specificity.ResultsCompared to no cannabis use, cannabis use was significantly associated with psychotic disorders during adolescence (aHR = 11.2; 95% CI 4.6–27.3), but not during young adulthood (aHR = 1.3; 95% CI 0.6–2.6). When we restricted the outcome to hospitalizations and ED visits only, the strength of association increased markedly during adolescence (aHR = 26.7; 95% CI 7.7–92.8) but did not change meaningfully during young adulthood (aHR = 1.8; 95% CI 0.6–5.4).ConclusionsThis study provides new evidence of a strong but age-dependent association between cannabis use and risk of psychotic disorder, consistent with the neurodevelopmental theory that adolescence is a vulnerable time to use cannabis. The strength of association during adolescence was notably greater than in previous studies, possibly reflecting the recent rise in cannabis potency.
Centering Black Women’s Labor History in Latin America
Authors: Harrington Jaira J. 
Published: May 2024

AbstractThis review article surveys recent books that explore black women’s integral role in the labor history of Latin America and the Caribbean. As emancipated Latin American and Caribbean black women transitioned away from slave labor, they faced intense, enduring racial and gender discrimination in the labor market. Despite these hostile conditions, these black women tirelessly resisted and rebelled against oppression. Moving beyond the framework of black women as mere contributors to social, political, and economic systems, the reviewed books’ authors center black women as historically inextricable from these foundational elements that sustain the region.
From the Great Goddess to the Storm God: Cosmic transformations at the boundary between the dry and rainy seasons in Classic Teotihuacan
Authors: González Block Miguel A. 
Published: May 2024

AbstractClassic Teotihuacan's mural tradition evidences a Great Goddess and a Storm God in a cult of rain and fertility, yet their identity and relationship is problematic. This article reads the mural iconography as a myth of passage where the Great Goddess transited through portals uniting the planes of the cosmos at the boundary between the dry and rainy seasons to transform into the Storm God. Slate and pyrite mirrors and murals are analyzed as sacred artifacts with agency to invoke passage. The species of animals and plants symbolizing portals are identified to decode their symbolism of passage as symbolic transformations.The Great Goddess transited from the underworld to the sea, entered mountain caves, and transformed her head-summit into a primordial cloud. The goddess created the axis mundi through her sacrifice, integrating the plants used for the manufacture of the Mesoamerican rubber olli. Mediated by the metamorphic powers of butterflies and olli, the goddess transformed greenstone into sacred water to become the Storm God. He commanded his helpers from his cave dwelling to produce rain and fertility clouds. Ruler-priests and warriors used mirrors to access the axis mundi and to transform into Storm God avatars with powers over rain and fertility.
STRONG COMPLETENESS OF A FIRST-ORDER TEMPORAL LOGIC FOR REAL TIME
Authors: GOLDBLATT ROBERT 
Published: May 2024

Abstract
Propositional temporal logic over the real number time flow is finitely axiomatisable, but its first-order counterpart is not recursively axiomatisable. We study the logic that combines the propositional axiomatisation with the usual axioms for first-order logic with identity, and develop an alternative “admissible” semantics for it, showing that it is strongly complete for admissible models over the reals. By contrast there is no recursive axiomatisation of the first-order temporal logic of admissible models whose time flow is the integers, or any scattered linear ordering.
Maternal birth weight is an indicator of preterm delivery: the Japan environment and children’s study
Authors: Kudo Rie , Iwama Noriyuki , Hamada Hirotaka , Tomita Hasumi , Tagami Kazuma , Kumagai Natsumi , Sato Naoto , Izumi Seiya , Sakurai Kasumi , Watanabe Zen , Ishikuro Mami , Obara Taku , Tatsuta Nozomi , Hoshiai Tetsuro , Metoki Hirohito , Saito Masatoshi , Sugawara Junichi , Kuriyama Shinichi , Arima Takahiro , Yaegashi Nobuo ,   The Japan Environment and Children’s Study Group
Published: May 2024

Abstract
This study aimed to investigate the association between maternal birth weight (MBW) with preterm delivery (PTD) in the Japanese population. To this end, a total of 78,972 Japanese pregnant women were included in a prospective birth cohort study. Multiple logistic regression and multinominal logistic regression models were applied to investigate the associations of MBW with PTD (delivery from 22 to < 37 weeks of gestation), early PTD (delivery from 22 to < 34 weeks), and late PTD (delivery from 34 to < 37 weeks). The results showed that MBW was inversely associated with PTD, early PTD, and late PTD (p-for-trend < 0.0001, 0.0014, and < 0.0001, respectively). The adjusted odds ratios per each 500 g of MBW decrease were 1.167 (95% confidence interval [CI]: 1.118–1.218) for PTD, 1.174 (95% CI: 1.070–1.287) for early PTD and 1.151 (95% CI: 1.098–1.206) for late PTD. The effect size of the association of MBW with early PTD was similar to that with late PTD. This study demonstrated for the first time an association of a low MBW with PTD, early PTD, and late PTD in a Japanese nationwide cohort.
The Power of Characters: Evaluating Machine Learning-Modified Bayesian Improved Surname Geocoding Inference of Race in Redistricting
Authors: Curiel John A. , DeLuca Kevin 
Published: May 2024

AbstractIdentifying racial disparities in policy and politics is a pressing area of research within the United States. Where early work made use of identifying potentially noisy correlations between county or precinct demographics and election outcomes, the advent of Bayesian Improved Surname Geocoding (BISG) vastly improved estimation of race by employing voter lists. Machine Learning (ML)-modified BISG in turn offers accuracy gains over the static – and potentially outdated – surname dictionaries present in traditional BISG. However, the extent to which ML might substantively alter the policy and political implications of redistricting is unclear given its improvements in voter race estimation. Therefore, we ascertain the potential gains of ML-modified BISG in improving the estimation of race for the purpose of redistricting majority-minority districts. We evaluate an ML-modified BISG program against traditional BISG estimates in correctly estimating the race of voters for creating majority-minority congressional districts within North Carolina and Georgia, and in state assembly districts in Wisconsin. Our results demonstrate that ML-modified BISG offers substantive gains over traditional BISG, especially in diverse political geographic units. Further, we find meaningful improvements in accuracy when estimating majority-minority district racial composition. We conclude with recommendations on when and how to use the two methods, in addition how to ensure transparency and confidence in BISG-related research.
Are Workers Effective Lawmakers?
Authors: Lollis Jacob M. 
Published: May 2024

AbstractAre workers effective lawmakers? Throughout American history, some politicians and elites have argued that white-collar Americans are more qualified than working-class Americans to govern. To date, however, we know relatively little about the legislative effectiveness of working-class lawmakers. I develop a theory of class-based electoral selection that links class-based discrimination in elections to legislators’ performance in office. I argue that working-class candidates face class-based biases in elections that make it more difficult to emerge and successfully win elective office. As a result, I expect the working-class candidates who do become lawmakers to be equally or more effective than their white-collar colleagues. To test these expectations, I create a data set merging the occupational background of more than 14,000 individual state legislators with their state legislative effectiveness score (SLES). The resulting data set includes more than 50,000 state legislator-term specific observations. Consistent with my expectations, I find that working-class lawmakers do not underperform white-collar lawmakers. Further, I provide evidence that, across various models and specifications, the gap between working-class and white-collar legislators’ effectiveness is negligible.
High‐Resolution Mantle Transition Zone Imaging Using Multi‐Dimensional Reconstruction of SS Precursors
Authors: Innocent Oboué Yapo Abolé Serge , Chen Yunfeng , Wang Jingchuan , Jiang Xiuxuan , Dokht Ramin M. H. , Gu Yu Jeffrey , Koroni Maria , Chen Yangkang 
Published: May 2024

AbstractThe SS precursors have been extensively utilized in mapping the mantle transition zone (MTZ). However, their applications are often challenged by weak phases that arise from small impedance contrasts of the mantle discontinuities, noise contamination, and localized thermal/compositional heterogeneities. We develop a new data processing workflow for more reliable MTZ imaging by adopting the recently proposed robust damped rank‐reduction (RDRR) method from exploration seismology. This method exploits the signal coherency in the four‐dimensional data and allows simultaneously attenuating noise and interpolating missing traces. We utilize synthetic data sets generated with realistic earth structures and MTZ topography to evaluate the capability of the proposed workflow. Our test results show that the RDRR method can well capture the topographic variation of mantle discontinuities, improving the SNR of the SS precursor data by an order of magnitude. The application to SS precursors from the western Pacific successfully removes contaminating noises, mitigates imaging artifacts of small‐scale anomalies, and improves the lateral coherency of the MTZ structure, revealing a clear first‐order structural transition. Compared with earlier global and regional models, our model reveals more structural details including a localized thin MTZ near the Changbai volcano in East Asia. This observation, in conjunction with the reported low‐velocity structure in the MTZ in earlier tomographic studies, may support the presence of deep mantle up‐welling through a slab gap. In summary, our work enables resolving MTZ structures with high fidelity and highlights the importance of advanced array methods in improving SS precursor imaging.
Metabolic profiling of galectin-1 and galectin-3: a cross-sectional, multi-omics, association study
Authors: Fryk Emanuel , Rodrigues Silva Vagner Ramon , Strindberg Lena , Strand Robin , Ahlström Håkan , Michaëlsson Karl , Kullberg Joel , Lind Lars , Jansson Per-Anders 
Published: May 2024

Abstract
Objectives
Experimental studies indicate a role for galectin-1 and galectin-3 in metabolic disease, but clinical evidence from larger populations is limited.

Methods
We measured circulating levels of galectin-1 and galectin-3 in the Prospective investigation of Obesity, Energy and Metabolism (POEM) study, participants (n = 502, all aged 50 years) and characterized the individual association profiles with metabolic markers, including clinical measures, metabolomics, adipose tissue distribution (Imiomics) and proteomics.

Results
Galectin-1 and galectin-3 were associated with fatty acids, lipoproteins and triglycerides including lipid measurements in the metabolomics analysis adjusted for body mass index (BMI). Galectin-1 was associated with several measurements of adiposity, insulin secretion and insulin sensitivity, while galectin-3 was associated with triglyceride-glucose index (TyG) and fasting insulin levels. Both galectins were associated with inflammatory pathways and fatty acid binding protein (FABP)4 and -5-regulated triglyceride metabolic pathways. Galectin-1 was also associated with several proteins related to adipose tissue differentiation.

Conclusions
The association profiles for galectin-1 and galectin-3 indicate overlapping metabolic effects in humans, while the distinctly different associations seen with fat mass, fat distribution, and adipose tissue differentiation markers may suggest a functional role of galectin-1 in obesity.