bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic Modelling, Simulation, and Sensitive Analysis of Lead Removal in a Fixed-Bed Adsorption Column using Waste-Based Materials
Authors: Gheibi Mohammad , Wacławek Stanisław , Leo Choe Peng , Sadr Seyed , Behzadian Kourosh 
Published: June 2024

Abstract
This study focuses on dynamic modelling and numerical simulation of lead removal from contaminated water using a fixed-bed adsorption column packed with waste-based adsorbents. The pressing need for efficient and sustainable water treatment methods, particularly for heavy metal removal, underscores the significance of this research. Lead contamination in water sources poses severe health risks, necessitating the development of effective removal strategies. The present investigation centres on a comprehensive mathematical model that considers critical parameters, including the column’s physical dimensions, flow rate, initial lead concentration, adsorption rate constant, and adsorbent density. This model is expressed as a partial differential equation (PDE) describing the temporal and spatial evolution of lead concentration along the fixed-bed column. To solve the PDE, the method of lines, a powerful numerical technique that discretises the spatial domain and handles the resulting system of ordinary differential equations (ODEs) using an adaptive solver, is employed. Following that, the effect factors of the simulation process are evaluated by sensitive analysis approach. Simulations are conducted to elucidate the intricate dynamics of lead removal over time and column height. The numerical approach enables the prediction of lead concentration profiles within the column at various time intervals, providing crucial insights into the behavior of the adsorption process.
3D embedded bioprinting of large-scale intestine with complex structural organization and blood capillaries
Authors: Li Yuxuan , Cheng Shengnan , Shi Haihua , Yuan Renshun , Gao Chen , Wang Yuhan , Zhang Zhijun , Deng Zongwu , Huang Jie 
Published: June 2024

Abstract
Accurate reproduction of human intestinal structure and function in vitro is of great significance for understanding the development and disease occurrence of the gut. However, most in vitro studies are often confined to 2D models, 2.5D organ chips or 3D organoids, which cannot fully recapitulate the tissue architecture, microenvironment and cell compartmentalization found in vivo. Herein, a centimeter-scale intestine tissue that contains intestinal features, such as hollow tubular structure, capillaries and tightly connected epithelium with in vivo-like ring folds, crypt-villi, and microvilli is constructed by 3D embedding bioprinting. In our strategy, a novel photocurable bioink composed of methacrylated gelatin, methacrylated sodium alginate and poly (ethylene glycol) diacrylate is developed for the fabrication of intestinal model. The Caco-2 cells implanted in the lumen are induced by the topological structures of the model to derive microvilli, crypt-villi, and tight junctions, simulating the intestinal epithelial barrier. The human umbilical vein endothelial cells encapsulated within the model gradually form microvessels, mimicking the dense capillary network in the intestine. This intestine-like tissue, which closely resembles the structure and cell arrangement of the human gut, can act as a platform to predict the therapeutic and toxic side effects of new drugs on the intestine.
Little prairie under the panel: testing native pollinator habitat seed mix establishment at three utility-scale solar sites in Minnesota
Authors: McCall James , Beatty Brenda , Janski Jake , Doubleday Kate , Martin Jordan , Hartmann Heidi , Walston Leroy J , Macknick Jordan 
Published: June 2024

Abstract
As more land is being utilized for large-scale solar energy projects, there are increasing discussions from stakeholders on how to utilize land under solar panels to promote biodiversity. One path is to plant habitat beneficial to pollinators and other insects, but there have been few long-term studies that examine how different vegetation and seed mixes establish underneath solar panels. This study addresses a scientific gap to determine whether native pollinator seed mixes successfully establish over time under solar arrays using a systematic assessment of eight seed mixes planted at three utility-scale solar sites in Minnesota. We assess establishment with a percent native coverage metric, which is an assessment of native species observations compared to total observations during percent cover analyses in our vegetative test plots. The percent native coverage metric allows for a measurement of how the seed mix established and how the seed mix persists over time. The percent native coverage under and in between the solar photovoltaic (PV) arrays rose from 10% after one year of planting to 58% after three years across all sites, while the native coverage of the full sun control area rose from 9.6% to 70% under the same period, showing that native prairie and pollinator plants successfully established under the array, although to a lesser extent than in full sun conditions. Percent native coverage under the PV arrays rose 5- to 8-fold for each of the three sites from over the course of the study, while the coverage of weeds decreased for all three sites over the same period. Percent native coverage varied by seed mix over the project years, but every seed mix experienced a higher percent native coverage year after year under the PV arrays. Our results did not indicate a difference in establishment across placement within the array; the center, west, and east portions of the areas in between panels had similar establishment rates at two out of three sites, indicating that the same seed mix can be applied throughout the array. Out of 101 plant species seeded, we observed the establishment of 68 species in our vegetative test plots, and we detailed the top 20 observed species to inform future seed mix development. Based on these findings, native pollinator vegetation can establish over time at solar arrays, and it can be suitable for creating habitat at utility-scale solar sites.
Non-invasive stratigraphic analyzes of gelatine-based modern painting materials with linear and nonlinear optical methods
Authors: Quintero Balbas Diego , Maestro-Guijarro Laura , Carmona-Quiroga Paula María , Oujja Mohamed , Castillejo Marta , Bettini Francesca , Porcinai Simone , Striova Jana 
Published: June 2024

Abstract
Stratigraphic analyzes of polychrome surfaces, such as paintings, often need samples to offer consistent results regarding the sequence and composition of the layers. Non-invasive methodologies based on linear and nonlinear optical techniques limit material removal from the objects. Recently, optical coherence tomography (OCT) has become the preferred choice of heritage scientists because it is a safe and fast alternative for studying transparent or semi-transparent layers. Yet, nonlinear optical microscopy (NLOM)) technique in its modality of multiphoton excitation fluorescence (MPEF) has emerged as a promising tool for the same purpose. Here, we explored linear (OCT and confocal Raman microspectroscopy (CRM)) and nonlinear (NLOM-MPEF) optical methods’ capability to investigate gelatine-based layers in mock-up samples and a painting dated 1939 by an artist from the Surrealistic entourage. The optical behavior of mock-up samples that imitate the painting stratigraphy and of six painting fragments detached from the support was also investigated with fiber optics reflectance spectroscopy and laser induced fluorescence (LIF). Thickness values from the mock-ups obtained with OCT, CRM, and MPEF have provided evidence of the complementarity, from a millimetric to a micrometric scale, and the limitations (e.g. strong fluorescence emission in CRM) of the methods. Moreover, the presence of gelatine was ascertained by LIF spectroscopy applied to the painting fragments and NLOM-MPEF confirmed its suitability as a non-invasive technique for investigating gelatine-based stratigraphic systems.
Beyond Moral Fundamentalism
Authors: Fesmire Steven 
Published: June 2024

Abstract
Moral fundamentalism is the habit of acting as though one has access to the exclusively right way to diagnose problems, along with the single approvable practical solution to any particular problem. This approach causes us to oversimplify situations, neglect broader context, take refuge in dogmatic absolutes, ignore possibilities for finding common ground, assume privileged access to the right way to proceed, and shut off honest inquiry. In this way, moral fundamentalism—exacerbated by social media silos—also makes the worst of native impulses toward social bonding and antagonism. This makes it impossible to debate and achieve superordinate social goals, such as public health, justice, security, sustainability, peace, and democracy. Drawing from John Dewey’s pluralistic and pragmatic approach to philosophical questions, this book develops an alternative to both the oversimplification of moral fundamentalism and the arbitrariness of relativism. Pragmatic pluralism is set up as a response to particular conditions and consequences, so it gains practical leverage with complex ethical, political, educational, and policy problems without flattening variability among values or presuming that abstract theories can determine what we ought to do. The book argues that the reductive monistic premise that logically underlies moral fundamentalism is both unwarranted and constrictive, and there is little to be said in favor of the grand philosophical quest for a unifying principle that cannot be accommodated within a wider pluralistic approach. In a concrete and engaging style, the author clarifies and illustrates the promises and challenges of democratic decision-making in societies struggling to grow beyond moral fundamentalism.
Educating for Democracy
Authors: Fesmire Steven 
Published: June 2024

Abstract
Dewey rejected as antidemocratic the notion that we need one educational approach for vocational trainees who will be led, and an essentially different one for elites who will lead. Such an autocratic and class-based approach is fertile ground for moral fundamentalism. Instead, we need to organize schooling so that students gain direct aesthetic fulfillment even as they cultivate competent, forward-looking, open-ended, collaborative, and progressively specialized intelligence. Unfortunately, the increasingly dominant industrial model of education conceives service to the private sector as the overriding goal. It channels energies toward narrow workforce training. This chapter explains, updates, and illustrates Dewey’s alternative, which was to engage occupational callings in a way that contributes to a more humane democratic culture. Nevertheless, even as we continue to debate educational values, the educational pragmatist does not insist upon a shared pre-alignment of ends, diagnoses, and justifications as a prerequisite to participating in public deliberation.
Conclusion
Authors: Fesmire Steven 
Published: June 2024

Abstract
The conclusion recaps the book’s main line of argument. Moral fundamentalist habits, and the reductive monistic philosophical assumption that mostly unintentionally reinforces them, are obstacles to cultivating virtues of inquiry that are suited to dealing with the predicaments that are rapidly transforming our planet. If philosophers and other public intellectuals are to speak more effectively to complex problems in a way that aids public deliberation and social learning, a critical focus on Dewey’s pragmatic pluralism would be salutary. Dewey did not explicitly spell out implications of his approach to ethics and politics for redirecting future theorizing, so the chapter closes with recommendations extrapolated by marrying his writings with a sampling of contemporary pragmatic pluralists who are steeped in his general outlook.
Multidimensional Religiousness and Spirituality Are Associated With Lower Interleukin-6 and C-Reactive Protein at Midlife: Findings From the Midlife in the United States Study
Authors: Vagnini Kaitlyn M , Morozink Boylan Jennifer , Adams Monica , Masters Kevin S 
Published: June 2024

Abstract

Background
Religiousness and spirituality (R/S) are associated with lower morbidity and mortality, yet the physiological mechanisms underlying these associations are under-studied. Chronic inflammation is a plausible biological mechanism linking R/S to downstream health given the sensitivity of the immune system to the social environment and the role of inflammation in many chronic diseases.

Purpose
The purpose of the present study was to examine associations between multiple R/S dimensions and two markers of chronic inflammation, interleukin-6 (IL-6) and C-reactive protein (CRP).

Methods
In this cross-sectional study, data came from biological subsamples of two cohorts from the Midlife in the United States (MIDUS) Study (combined N = 2,118). Predictors include six R/S measures (service attendance, spirituality, private religious practices, daily spiritual experiences, religious coping, and R/S-based mindfulness). Outcomes include log-transformed IL-6 and CRP. Covariates include age, gender, cohort, race, educational attainment, body mass index (BMI), smoking status, and physical activity.

Results
Older adults, women (vs. men), non-White (vs. White) adults, those with higher BMIs, current smokers, and those not meeting physical activity guidelines had significantly higher IL-6 and CRP. In fully adjusted models, greater spirituality, daily spiritual experiences, religious coping, and R/S-based mindfulness were associated with lower IL-6. Higher spirituality was also associated with lower CRP.

Conclusions
Many dimensions of R/S may be health protective for adults given their associations with lower levels of chronic inflammation. Findings underscore the importance of examining multiple dimensions of R/S to understand mechanistic pathways.
Competition and drought affect cleistogamy in a non-additive way in the annual ruderal Lamium amplexicaule
Authors: Stojanova Bojana , Eliášová Anežka , Tureček Tomáš 
Published: June 2024

Abstract
Competition affects mixed-mating strategies by limiting available abiotic or biotic resources such as nutrients, water, space, or pollinators. Cleistogamous species produce closed (cleistogamous, CL), obligately selfed, simultaneously with open (chasmogamous, CH), potentially outcrossed flowers. The effects of intraspecific competition on fitness and cleistogamy variation can range from limiting the production of costly CH flowers because of resource limitation, to favouring CH production because of fitness advantages of outcrossed, CH offspring. Moreover, the effects of competition can be altered when it co-occurs with other environmental variations. We grew plants from seven populations of the ruderal Lamium amplexicaule, originating from different climates and habitats, in a common garden experiment combining drought, interspecific competition, and seasonal variation. All these parameters have been shown to influence the degree of cleistogamy in the species on their own. In spring, competition and drought negatively impacted fitness, but the CL proportion only increased when plants were exposed to both treatments combined. We did not observe the same results in autumn, which can be due to non-adaptive phenotypic variation, or to differences in soil compactness between seasons. The observed responses are largely due to phenotypic plasticity, but we also observed phenotypic differentiation between populations for morphological, phenological, and cleistogamy traits, pointing to the existence of different ecotypes. Our data do not support the hypothesis that CL proportion should decrease when resources are scarce, as plants with reduced growth had relatively low CL proportions. We propose that variation in cleistogamy could be an adaptation to pollinator abundance, or to environment-dependent fitness differences between offspring of selfed and outcrossed seeds, two hypotheses worth further investigation. This opens exciting new possibilities for the study of the maintenance of mixed-mating systems using cleistogamous species as models that combine the effects of inbreeding and reproductive costs.
Characterization of double-stranded RNA and its silencing efficiency for insects using hybrid deep-learning framework
Authors: Cheng Han , Xu Liping , Jia Cangzhi 
Published: June 2024

Abstract
RNA interference (RNAi) technology is widely used in the biological prevention and control of terrestrial insects. One of the main factors with the application of RNAi in insects is the difference in RNAi efficiency, which may vary not only in different insects, but also in different genes of the same insect, and even in different double-stranded RNAs (dsRNAs) of the same gene. This work focuses on the last question and establishes a bioinformatics software that can help researchers screen for the most efficient dsRNA targeting target genes. Among insects, the red flour beetle (Tribolium castaneum) is known to be one of the most sensitive to RNAi. From iBeetle-Base, we extracted 12 027 efficient dsRNA sequences with a lethality rate of ≥20% or with experimentation-induced phenotypic changes and processed these data to correspond to specific silence efficiency. Based on the first complied novel benchmark dataset, we specifically designed a deep neural network to identify and characterize efficient dsRNA for RNAi in insects. The dna2vec word embedding model was trained to extract distributed feature representations, and three powerful modules, namely convolutional neural network, bidirectional long short-term memory network, and self-attention mechanism, were integrated to form our predictor model to characterize the extracted dsRNAs and their silencing efficiencies for T. castaneum. Our model dsRNAPredictor showed reliable performance in multiple independent tests based on different species, including both T. castaneum and Aedes aegypti. This indicates that dsRNAPredictor can facilitate prescreening for designing high-efficiency dsRNA targeting target genes of insects in advance.
racoon_clip—a complete pipeline for single-nucleotide analyses of iCLIP and eCLIP data
Authors: Klostermann Melina , Zarnack Kathi 
Published: June 2024

Abstract

Motivation
A vast variety of biological questions connected to RNA-binding proteins can be tackled with UV crosslinking and immunoprecipitation (CLIP) experiments. However, the processing and analysis of CLIP data are rather complex. Moreover, different types of CLIP experiments like iCLIP or eCLIP are often processed in different ways, reducing comparability between multiple experiments. Therefore, we aimed to build an easy-to-use computational tool for the processing of CLIP data that can be used for both iCLIP and eCLIP data, as well as data from other truncation-based CLIP methods.

Results
Here, we introduce racoon_clip, a sustainable and fully automated pipeline for the complete processing of iCLIP and eCLIP data to extract RNA binding signal at single-nucleotide resolution. racoon_clip is easy to install and execute, with multiple pre-settings and fully customizable parameters, and outputs a conclusive summary report with visualizations and statistics for all analysis steps.

Availability and implementation
racoon_clip is implemented as a Snakemake-powered command line tool (Snakemake version ≥7.22, Python version ≥3.9). The latest release can be downloaded from GitHub (https://github.com/ZarnackGroup/racoon_clip/tree/main) and installed via pip. A detailed documentation, including installation, usage, and customization, can be found at https://racoon-clip.readthedocs.io/en/latest/. The example datasets can be downloaded from the Short Read Archive (SRA; iCLIP: SRR5646576, SRR5646577, SRR5646578) or the ENCODE Project (eCLIP: ENCSR202BFN).
HGTDR: Advancing drug repurposing with heterogeneous graph transformers
Authors: Gharizadeh Ali , Abbasi Karim , Ghareyazi Amin , Mofrad Mohammad R K , Rabiee Hamid R 
Published: June 2024

Abstract

Motivation
Drug repurposing is a viable solution for reducing the time and cost associated with drug development. However, thus far, the proposed drug repurposing approaches still need to meet expectations. Therefore, it is crucial to offer a systematic approach for drug repurposing to achieve cost savings and enhance human lives. In recent years, using biological network-based methods for drug repurposing has generated promising results. Nevertheless, these methods have limitations. Primarily, the scope of these methods is generally limited concerning the size and variety of data they can effectively handle. Another issue arises from the treatment of heterogeneous data, which needs to be addressed or converted into homogeneous data, leading to a loss of information. A significant drawback is that most of these approaches lack end-to-end functionality, necessitating manual implementation and expert knowledge in certain stages.

Results
We propose a new solution, Heterogeneous Graph Transformer for Drug Repurposing (HGTDR), to address the challenges associated with drug repurposing. HGTDR is a three-step approach for knowledge graph-based drug repurposing: (1) constructing a heterogeneous knowledge graph, (2) utilizing a heterogeneous graph transformer network, and (3) computing relationship scores using a fully connected network. By leveraging HGTDR, users gain the ability to manipulate input graphs, extract information from diverse entities, and obtain their desired output. In the evaluation step, we demonstrate that HGTDR performs comparably to previous methods. Furthermore, we review medical studies to validate our method’s top 10 drug repurposing suggestions, which have exhibited promising results. We also demonstrated HGTDR’s capability to predict other types of relations through numerical and experimental validation, such as drug–protein and disease–protein inter-relations.

Availability and implementation
The source code and data are available at https://github.com/bcb-sut/HGTDR and http://git.dml.ir/BCB/HGTDR
FastHPOCR: pragmatic, fast, and accurate concept recognition using the human phenotype ontology
Authors: Groza Tudor , Gration Dylan , Baynam Gareth , Robinson Peter N 
Published: June 2024

Abstract

Motivation
Human Phenotype Ontology (HPO)-based phenotype concept recognition (CR) underpins a faster and more effective mechanism to create patient phenotype profiles or to document novel phenotype-centred knowledge statements. While the increasing adoption of large language models (LLMs) for natural language understanding has led to several LLM-based solutions, we argue that their intrinsic resource-intensive nature is not suitable for realistic management of the phenotype CR lifecycle. Consequently, we propose to go back to the basics and adopt a dictionary-based approach that enables both an immediate refresh of the ontological concepts as well as efficient re-analysis of past data.

Results
We developed a dictionary-based approach using a pre-built large collection of clusters of morphologically equivalent tokens—to address lexical variability and a more effective CR step by reducing the entity boundary detection strictly to candidates consisting of tokens belonging to ontology concepts. Our method achieves state-of-the-art results (0.76 F1 on the GSC+ corpus) and a processing efficiency of 10 000 publication abstracts in 5 s.

Availability and implementation
FastHPOCR is available as a Python package installable via pip. The source code is available at https://github.com/tudorgroza/fast_hpo_cr. A Java implementation of FastHPOCR will be made available as part of the Fenominal Java library available at https://github.com/monarch-initiative/fenominal. The up-to-date GCS-2024 corpus is available at https://github.com/tudorgroza/code-for-papers/tree/main/gsc-2024.