bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Colonial African: Godwin Mbikusita-Lewanika and His Struggle For and Against Zambian Nationalism
Authors: Sishuwa Sishuwa , Money Duncan 
Published: November 2024

Abstract
Godwin Mbikusita-Lewanika, the founding president of Zambia’s first nationalist organisation, is now remembered as a staunch supporter of colonial rule. Such figures are not uncommon and are often termed “loyalists,” a term that is usually understood in the literature as a fixed category that either dwindled in the face of racial oppression or was a choice shaped and hardened by conflict. Lewanika, however, moved easily between different sides, reinventing himself as an anticolonial nationalist, trade unionist, colonial loyalist, and Lozi traditional monarchist as circumstances warranted. The tumult of the mid-twentieth century opened up new opportunities and Lewanika seized roles that were not previously available. Biographies of anticolonial nationalists often argue they turned to political action when their education and ambitions clashed with the highly-circumscribed roles available under colonialism. Lewanika’s life was the opposite. He carved out a prominent place for himself in the colonial order and then in independent Zambia.
Non-Conceptual Normative Pluralism and the Dualism of Practical Reason
Authors: Hambly Jesse 
Published: November 2024

AbstractAccording to normative pluralists there are no truths about what one ought simpliciter to do, only truths about what one ought to do according to some normative system or standpoint. In contrast with conceptual normative pluralists who argue for this conclusion on the basis that the concept of an ought simpliciter is somehow defective, non-conceptual normative pluralists defend this conclusion on first-order grounds. Non-conceptual normative pluralism has recently received a book-length defence by Mathea Slåttholm Sagdahl. In this article I critique Sagdahl's defence of non-conceptual normative pluralism. Firstly, I challenge Sagdahl's attempt to motivate non-conceptual normative pluralism by appealing to Henry Sidgwick's work on the dualism of practical reason. Secondly, I criticise her response to the most prominent argument against non-conceptual normative pluralism in the philosophical literature, the argument from nominal-notable comparisons. Thirdly, I explore the possibility of a view similar to Sagdahl's position but which accepts the ought simpliciter.
Effects of active compounds and their metabolites associated with coffee consumption on neurodegenerative disease
Authors: Koníčková Dorota , Menšíková Kateřina , Plíhalová Lucie , Kaňovský Petr 
Published: November 2024

Abstract
Coffee is one of the most known and consumed beverages worldwide. Only three species are used in commercial coffee production, that is, Coffea arabica L. (Arabica coffee), Coffea canephora Pierre ex A. Froehner (Robusta coffee) and Coffea liberica Hiern (Excelsa coffee). The world population consumes approximately two billion cups of coffee per day, making it an important commercial resource of bioactive compounds in world markets. High interest in coffee consumption described in the literature is due not only to its organoleptic properties (for example, desirable bitterness, amount of flavours and aromas) but also to its ability to stimulate the central nervous system.
It is now known that there are more than 1000 compounds in coffee beverages, several of which have a bioactive activity. Recent studies show that consuming three to four cups of coffee per day, that is, moderate consumption according to the European Food Safety Authority, may be beneficial for health.
The main objective of the proposed review is to provide a comprehensive overview of bioactive compounds in coffee and other caffeine-containing beverages and their effects on neurodegenerative proteinopathies.
Characterising the lipid profile of paediatric patients with anomalous aortic origins of a coronary artery
Authors: Przybycien Thomas S. , Gray Kimberly , Sidiq Sameer , Mihail Sandra , Doan Tam T. , Sachdeva Shagun , Reaves-O’Neal Dana , Binsalamah Ziyad , Molossi Silvana 
Published: November 2024

AbstractBackground:Lipid levels in paediatric patients with anomalous aortic origin of a coronary artery (AAOCA) have not previously been explored. Patients with CHD have an increased risk of atherosclerotic cardiovascular disease later in life compared to the general population. We aim to characterise the lipid profiles in paediatric patients with AAOCA and explore its relation to diagnosis, race/ethnicity, and exercise.Methods:Single institution retrospective cohort of 180 AAOCA paediatric patients (median age 13.7 years interquartile range 9.7–15.6, 66% male). Total cholesterol, HDL, LDL, triglycerides, total cholesterol to HDL ratio, and non-HDL cholesterol were evaluated across race/ethnicity, sex, type of AAOCA, documented ischaemia on imaging, exercise level, and surgery status. Normality of the data distribution for each lipid parameter was evaluated using Kolmogorov–Smirnov testing. Accordingly, Mann–Whitney U and t-tests were used to compare variables. The proportion of abnormal lipid levels by sex and race/ethnicity was calculated.Results:Total cholesterol was elevated in 29%, (51/177) of patients, HDL 37% (64/174), triglycerides 44% (72/165), LDL 16% (28/170), total cholesterol-HDL ratio 29%, (48/163), and non-HDL cholesterol 28% (47/165). Across subgroups categorised on the basis of surgery status, exercise level, AAOCA type, and sex, the mean and median levels for individual lipid parameters were normal. By race/ethnicity, Hispanic patients had significantly higher triglyceride (median 99, interquartile range 71–136.5, p = <0.001) and total cholesterol to HDL ratios (median 3.2, interquartile range 2.7–4.5, p = 0.014) versus non-Hispanic White and Black patients. Two-thirds of patients exercise recreationally.Conclusion:Hispanic patients have significantly elevated triglycerides and total cholesterol to HDL ratios compared to others. Longitudinal follow-up evaluating differences in long-term lipid status in patients with AAOCA and risk for cardiovascular events is warranted.
Fenestrated closure of an atrial septal defect for left ventricular diastolic dysfunction in an early infant with hypertrophic cardiomyopathy
Authors: Hayashi Ken , Hasegawa Tomomi , Tanaka Toshikatsu 
Published: November 2024

AbstractLeft ventricular diastolic dysfunction is associated with poor prognosis in patients with hypertrophic cardiomyopathy and CHD. We report the case of an infant concomitant with hypertrophic cardiomyopathy, an atrial septal defect, and left ventricular diastolic dysfunction, who was successfully managed with fenestrated closure of the atrial septal defect.
A Machine Learning-Based Approach for Solving Recurrence Relations and Its use in Cost Analysis of Logic Programs
Authors: RUSTENHOLZ LOUIS , KLEMEN MAXIMILIANO , CARREIRA-PERPIÑÁN MIGUEL Á. , LOPEZ-GARCIA PEDRO 
Published: November 2024

AbstractAutomatic static cost analysis infers information about the resources used by programs without actually running them with concrete data and presents such information as functions of input data sizes. Most of the analysis tools for logic programs (and many for other languages), as CiaoPP, are based on setting up recurrence relations representing (bounds on) the computational cost of predicates and solving them to find closed-form functions. Such recurrence solving is a bottleneck in current tools: many of the recurrences that arise during the analysis cannot be solved with state-of-the-art solvers, including computer algebra systems (CASs), so that specific methods for different classes of recurrences need to be developed. We address such a challenge by developing a novel, general approach for solving arbitrary, constrained recurrence relations, that uses machine learning (sparse-linear and symbolic) regression techniques to guess a candidate closed-form function, and a combination of an SMT-solver and a CAS to check whether such function is actually a solution of the recurrence. Our prototype implementation and its experimental evaluation within the context of the CiaoPP system show quite promising results. Overall, for the considered benchmark set, our approach outperforms state-of-the-art cost analyzers and recurrence solvers and can find closed-form solutions, in a reasonable time, for recurrences that cannot be solved by them.
Deep learning–based detection and quantification of weed seed mixtures
Authors: Ahmed Shahbaz , Revolinski Samuel R. , Maughan P. Weston , Savic Marija , Kalin Jessica , Burke Ian C. 
Published: November 2024

AbstractKnowledge of weed seeds present in the soil seedbank is important for understanding population dynamics and forecasting future weed infestations. Quantification of the weed seedbank has historically been laborious, and few studies have attempted to quantify seedbanks on the scale required to make management decisions. An accurate, efficient, and ideally automated method to identify weed seeds in field samples is needed. To achieve sufficient precision, we leveraged YOLOv8, a machine learning object detection to accurately identify and count weed seeds obtained from the soil seedbank and weed seed collection. The YOLOv8 model, trained and evaluated using high-quality images captured with a digital microscope, achieved an overall accuracy and precision exceeding 80% confidence in distinguishing various weed seed species in both images and real-time videos. Despite the challenges associated with species having similar seed morphology, the application of YOLOv8 will facilitate rapid and accurate identification of weed seeds for the assessment of future weed management strategies.
Anthropogenic Aerosols Have Significantly Weakened the Regional Summertime Circulation in the Northern Hemisphere During the Satellite Era
Authors: Kang Joonsuk M. , Shaw Tiffany A. , Sun Lantao 
Published: November 2024

AbstractReanalysis data show a significant weakening of summertime circulation in the Northern Hemisphere (NH) midlatitudes in the satellite era with implications for surface weather extremes. Recent work showed the weakening is not significantly affected by changes in the Arctic, but did not examine the role of different anthropogenic forcings such as aerosols. Here we use the Detection and Attribution Model Intercomparison Project (DAMIP) simulations to quantify the impact of anthropogenic aerosol and greenhouse gas forcing. The DAMIP simulations show aerosols and greenhouse gases contribute equally to zonal‐mean circulation weakening. Regionally, aerosol dominates the Pacific storm track weakening whereas greenhouse gas dominates in the Atlantic. Using a regional energetic framework, we show why the impact of aerosol is the largest in the Pacific. Reduced sulfate aerosol emissions over Eurasia and North America increase (clear‐sky) surface shortwave radiation and turbulent fluxes. This enhances land‐to‐ocean energy contrast and energy transport via stationary circulations to the ocean. Consequently, energy converges poleward of oceanic storm tracks, demanding weaker poleward energy transport storm tracks, and the storm tracks weaken. The impact is larger over the Pacific following the larger emission decrease over Eurasia than North America. Similar yet opposite, increased aerosol emissions over South and East Asia decrease shortwave radiation and weaken land‐to‐ocean energy transport. This diverges energy equatorward of the Pacific storm track, further weakening it. Our results show aerosols are a dominant driver of regional circulation weakening during the NH summertime in the satellite era and a regional energetic framework explaining the underlying processes.
Reversible modulation of polymer chain mobility by selective cage opening and closing of pendant boratrane units
Authors: Takahashi Akira , Yamanishi Masahiro , Kameyama Atsushi , Otsuka Hideyuki 
Published: November 2024

AbstractAs a simple and versatile methodology for large modulation of polymer chain mobility, we report the selective opening and closing reactions of cage-shaped triethanolamine borate (TEAB) at polymer side chains and their effect on the thermal properties of the parent polymers. A series of TEAB-pendant polymethacrylates was synthesized by common free-radical polymerization using TEAB-containing methacrylate. Boron vertex removal from the pendant TEAB groups proceeded quantitatively via hydrolysis at room temperature to afford triethanolamine (TEA), an open cage structure. Differential scanning calorimetry revealed that the pendant TEAB/TEA interconversion induces a large variation in the glass transition temperature (Tg) of the parent polymers up to 166 °C, as a result of the contrasting conformational flexibility of the rigid TEAB and flexible TEA. Regeneration of the pendant TEAB group (cage closing) also proceeded in a highly selective manner by adding a commercially available borate ester to the TEA-pendant polymer. The mechanism underlying the high reaction selectivity was investigated using density functional theory calculations. The borated product showed a comparable Tg to that of the pristine TEAB-pendant polymer, demonstrating the efficiency of TEAB/TEA interconversion for reversible and large modulation of polymer chain flexibility.
Dimerization of ADAR1 modulates site-specificity of RNA editing
Authors: Mboukou Allegra , Rajendra Vinod , Messmer Serafina , Mandl Therese C. , Catala Marjorie , Tisné Carine , Jantsch Michael F. , Barraud Pierre 
Published: November 2024

AbstractAdenosine-to-inosine editing is catalyzed by adenosine deaminases acting on RNA (ADARs) in double-stranded RNA (dsRNA) regions. Although three ADARs exist in mammals, ADAR1 is responsible for the vast majority of the editing events and acts on thousands of sites in the human transcriptome. ADAR1 has been proposed to form a stable homodimer and dimerization is suggested to be important for editing activity. In the absence of a structural basis for the dimerization of ADAR1, and without a way to prevent dimer formation, the effect of dimerization on enzyme activity or site specificity has remained elusive. Here, we report on the structural analysis of the third double-stranded RNA-binding domain of ADAR1 (dsRBD3), which reveals stable dimer formation through a large inter-domain interface. Exploiting these structural insights, we engineered an interface-mutant disrupting ADAR1-dsRBD3 dimerization. Notably, dimerization disruption did not abrogate ADAR1 editing activity but intricately affected editing efficiency at selected sites. This suggests a complex role for dimerization in the selection of editing sites by ADARs, and makes dimerization a potential target for modulating ADAR1 editing activity.
Personalised antimicrobial susceptibility testing with clinical prediction modelling informs appropriate antibiotic use
Authors: Howard Alex , Hughes David M. , Green Peter L. , Velluva Anoop , Gerada Alessandro , Maskell Simon , Buchan Iain E. , Hope William 
Published: November 2024

AbstractAntimicrobial susceptibility testing is a key weapon against antimicrobial resistance. Diagnostic microbiology laboratories use one-size-fits-all testing approaches that are often imprecise, inefficient, and inequitable. Here, we report a personalised approach that adapts laboratory testing for urinary tract infection to maximise the number of appropriate treatment options for each patient. We develop and assess susceptibility prediction models for 12 antibiotics on real-world healthcare data using an individual-level simulation study. When combined with decision thresholds that prioritise selection of World Health Organisation Access category antibiotics (those least likely to induce antimicrobial resistance), the personalised approach delivers more susceptible results (results that encourage prescription of that antibiotic) per specimen for Access category antibiotics than a standard testing approach, without compromising provision of susceptible results overall. Here, we show that personalised antimicrobial susceptibility testing could help tackle antimicrobial resistance by safely providing more Access category antibiotic treatment options to clinicians managing urinary tract infection.
Functional annotation of the Hippo pathway somatic mutations in human cancers
Authors: Han Han , Huang Zhen , Xu Congsheng , Seo Gayoung , An Jeongmin , Yang Bing , Liu Yuhan , Lan Tian , Yan Jiachen , Ren Shanshan , Xu Yue , Xiao Di , Yan Jonathan K. , Ahn Claire , Fishman Dmitry A. , Meng Zhipeng , Guan Kun-Liang , Qi Ruxi , Luo Ray , Wang Wenqi 
Published: November 2024

AbstractThe Hippo pathway is commonly altered in cancer initiation and progression; however, exactly how this pathway becomes dysregulated to promote human cancer development remains unclear. Here we analyze the Hippo somatic mutations in the human cancer genome and functionally annotate their roles in targeting the Hippo pathway. We identify a total of 85 loss-of-function (LOF) missense mutations for Hippo pathway genes and elucidate their underlying mechanisms. Interestingly, we reveal zinc-finger domain as an integral structure for MOB1 function, whose LOF mutations in head and neck cancer promote tumor growth. Moreover, the schwannoma/meningioma-derived NF2 LOF mutations not only inhibit its tumor suppressive function in the Hippo pathway, but also gain an oncogenic role for NF2 by activating the VANGL-JNK pathway. Collectively, our study not only offers a rich somatic mutation resource for investigating the Hippo pathway in human cancers, but also provides a molecular basis for Hippo-based cancer therapy.
Dielectric tensor prediction for inorganic materials using latent information from preferred potential
Authors: Mao Zetian , Li WenWen , Tan Jethro 
Published: November 2024

AbstractDielectrics are crucial for technologies like flash memory, CPUs, photovoltaics, and capacitors, but public data on these materials are scarce, restricting research and development. Existing machine learning models have focused on predicting scalar polycrystalline dielectric constants, neglecting the directional nature of dielectric tensors essential for material design. This study leverages multi-rank equivariant structural embeddings from a universal neural network potential to enhance predictions of dielectric tensors. We develop an equivariant readout decoder to predict total, electronic, and ionic dielectric tensors while preserving O(3) equivariance, and benchmark its performance against state-of-the-art algorithms. Virtual screening of thermodynamically stable materials from Materials Project for two discovery tasks, high-dielectric and highly anisotropic materials, identifies promising candidates including Cs2Ti(WO4)3 (band gap Eg = 2.93eV, dielectric constant ε = 180.90) and CsZrCuSe3 (anisotropic ratio αr = 121.89). The results demonstrate our model’s accuracy in predicting dielectric tensors and its potential for discovering novel dielectric materials.
The shared genetic architecture and evolution of human language and musical rhythm
Authors: Alagöz Gökberk , Eising Else , Mekki Yasmina , Bignardi Giacomo , Fontanillas Pierre ,   23andMe Research Team, Aslibekyan Stella , Auton Adam , Babalola Elizabeth , Bell Robert K. , Bielenberg Jessica , Bowes Jonathan , Bryc Katarzyna , Chaudhary Ninad S. , Coker Daniella , Das Sayantan , DelloRusso Emily , Elson Sarah L. , Eriksson Nicholas , Filshtein Teresa , Freyman Will , Fuller Zach , German Chris , Granka Julie M. , Heilbron Karl , Hernandez Alejandro , Hicks Barry , Hinds David A. , Jewett Ethan M. , Jiang Yunxuan , Kukar Katelyn , Kwong Alan , Liang Yanyu , Lin Keng-Han , Llamas Bianca A. , McIntyre Matthew H. , Micheletti Steven J. , Moreno Meghan E. , Nandakumar Priyanka , Nguyen Dominique T. , O’Connell Jared , Petrakovitz Aaron A. , Poznik G. David , Reynoso Alexandra , Saini Shubham , Schumacher Morgan , Selcer Leah , Shastri Anjali J. , Shelton Janie F. , Shi Jingchunzi , Shringarpure Suyash , Su Qiaojuan Jane , Tat Susana A. , Tran Vinh , Tung Joyce Y. , Wang Xin , Wang Wei , Weldon Catherine H. , Wilton Peter , Wong Corinna D. , Nivard Michel G. , Luciano Michelle , Cox Nancy J. , Fisher Simon E. , Gordon Reyna L. 
Published: November 2024

Abstract
This study aimed to test theoretical predictions over biological underpinnings of previously documented phenotypic correlations between human language-related and musical rhythm traits. Here, after identifying significant genetic correlations between rhythm, dyslexia and various language-related traits, we adapted multivariate methods to capture genetic signals common to genome-wide association studies of rhythm (N = 606,825) and dyslexia (N = 1,138,870). The results revealed 16 pleiotropic loci (P < 5 × 10−8) jointly associated with rhythm impairment and dyslexia, and intricate shared genetic and neurobiological architectures. The joint genetic signal was enriched for foetal and adult brain cell-specific regulatory regions, highlighting complex cellular composition in their shared underpinnings. Local genetic correlation with a key white matter tract (the left superior longitudinal fasciculus-I) substantiated hypotheses about auditory–motor connectivity as a genetically influenced, evolutionarily relevant neural endophenotype common to rhythm and language processing. Overall, we provide empirical evidence of multiple aspects of shared biology linking language and musical rhythm, contributing novel insight into the evolutionary relationships between human musicality and linguistic communication traits.
Stage-based colorectal cancer prediction on uncertain dataset using rough computing and LSTM models
Authors: Supriya K. , Anitha A. 
Published: November 2024

AbstractArtificial intelligence (AI) is an attractive field of Computer Science that helps to classify and to predict various real-time applications. Perhaps AI has a major role in predicting diseases at an early stage based on history. As cancer is one of the most harmful diseases where the mortality rate is high, it is now essential to utilize the benefits of AI to have an early diagnosis of cancer. Among various cancers, Colorectal cancer (CRC) is a common form of gastrointestinal cancer, and its treatment is lengthy and costly, with a high recurrence rate and high fatality rate. Initial disease analysis and prognosis are required to improve the patient’s treatment with a better survival analysis. However, the disease prediction process depends on the collected data, where the data may contain uncertainty. Uncertain data leads to wrong predictions. Thus, it is essential to utilize rough computing, a mathematical tool to deal with uncertainty. This paper has made an effort, to handle uncertainty using a rough set of fuzzy approximation space as pre-processing and utilized Unidirectional and Bidirectional LSTM for the classification and prediction process. Thus, to demonstrate improved predictive accuracy, the proposed model adapted the optimizers and evaluated using benchmarking techniques in predicting stage-based survival rate. The comparative analysis shows that the proposed model performs well against the state-of-the-art models and can help the medical practitioner to detect CRC at an early stage and reduce the mortality rate among human beings.