bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring macrophytes’ microbial populations dynamics to enhance bioremediation in constructed wetlands for industrial pollutants removal in sustainable wastewater treatment
Authors: Ijoma Grace N. , Lopes Teresa , Mannie Thulani , Mhlongo Thandazile N. 
Published: March 2024

AbstractToxic contaminants from intense industrial operations are entering wetlands, harming human health and biodiversity. Macrophytes serve as principal producers in aquatic environments including natural wetlands, providing shelter, food, and, most crucially, intricate relationships with the surrounding microbial assemblage for support and microorganisms attachment. Wetlands have been nature's kidneys, for filtering water. Recent research has examined macrophytes' phytoremediation abilities. With recent improvements focused on engineered wetland technology, microbiological characterization, and genetic engineering, phytoremediation strategies have also benefited. However, little research has examined the role surrounding microbial population play on macrophyte efficiency in pollutant degradation, the extent and even mechanisms of these interactions, and their potential utility in wastewater treatment of diverse industrial effluents. Our bid for greener solutions implies that macrophyte-microorganisms’ interspecific interactions for in situ treatment of effluents should be optimised to remove contaminants before discharge in natural waterbodies or for recycle water usage. This review provides for the varied types of plants and microbial interspecific interactions beneficial to effective phytoremediation processes in artificial wetland design as well as considerations and modifications in constructed wetland designs necessary to improve the bioremediation processes. Additionally, the review discusses the latest advancements in genetic engineering techniques that can enhance the effectiveness of phyto-assisted wastewater treatment. We will also explore the potential utilisation of invasive species for their demonstrated ability to remove pollutants in the controlled setting of constructed wetlands.
Big data meets storytelling: using machine learning to predict popular fanfiction
Authors: Nguyen Duy , Zigmond Stephen , Glassco Samuel , Tran Bach , Giabbanelli Philippe J. 
Published: March 2024

Abstract
Fanfictions are a popular literature genre in which writers reuse a universe, for example to transform heteronormative relationships with queer characters or to bring romance into shows focused on horror and adventure. Fanfictions have been the subject of numerous studies in text mining and network analysis, which used Natural Language Processing (NLP) techniques to compare fanfictions with the original scripts or to make various predictions. In this paper, we use NLP to predict the popularity of a story and examine which features contribute to popularity. This endeavor is important given the rising use of AI assistants and the ongoing interest in generating text with desirable characteristics. We used the main two websites to collect fan stories (Fanfiction.net and Archives Of Our Own) on Supernatural, which has been the subject of numerous scholarly works. We extracted high-level features such as the main character and sentiments from 79,288 of these stories and used the features in a binary classification supported by tree-based methods, ensemble methods (random forest), neural networks, and Support Vector Machines. Our optimized classifiers correctly identified popular stories in four out of five cases. By relating features to classification outcomes using SHAP values, we found that fans prefer longer stories with a wider vocabulary, which can inform the prompts of AI chatbots to continue generating such successful stories. However, we also observed that fans wanted stories unlike the original material (e.g., favoring romance and disliking when characters are hurt), hence AI-powered stories may be less popular if they strictly follow the original material of a show.
Microstructural study of the Praid Salt Diapir (Transylvanian basin, Romania) and its implication on deformation history and hydrogen storage potential
Authors: Gelencsér O. , Szakács A. , Gál Á. , Szabó Á. , Dankházi Z. , Tóth T. , Breitner D. , Szabó-Krausz Zs. , Szabó Cs. , Falus Gy. 
Published: March 2024

AbstractThe Transylvanian basin is one of the major Tertiary sedimentary basins in the Carpathian-Pannonian region. Its thick sedimentary fill contains prominent Middle Miocene age salt that forms major diapir structures at the basin margins. The microstructural characteristics of the rock salt represent one of the main factors that determines the potential of a salt body for storage of hydrogen. The main aim of this study is to extend our understanding of the deformation mechanism of Praid rock salt located at the eastern margin of the Transylvanian basin. Based on petrography, we identified two types of rock salt: (1) layered salt with rather uniform grain size distribution showing alternation of greyish (clay mineral bearing) and white (clear halite) layers, and (2) massive grey salt with large, elongated halite crystals, accompanied by sub-micrometer size grains of halite. To shed light on the microstructure of the rock salt, we performed electron backscatter diffraction (EBSD) mapping, and studied gamma-irradiated samples both in the massive and layered salt samples. Dislocation creep and pressure solution creep were identified which acted concurrently in the Praid rock salt. The total strain rate falls between 1.2 and 1.3×10−10 s−1. The results of this study reveal a complex deformation history of the salt body where coexisting and migrating fluids have played an important role. The outcome of this project contributes to the hydrogen storage potential assessment for the Transylvanian salt and to a better understanding of the structural evolution of the Transylvanian basin.
Practicum Anxiety and English Language Preservice Teacher Preparation in Indonesia: Experiences from the COVID-19 Pandemic
Authors: Lian Ania , Syahdan Syahdan , Manalu Camelia , Natsir MHD 
Published: March 2024

AbstractThe existing literature on practicum anxiety seldom scrutinises the preservice teachers’ experiences to uncover potential links between the sources of these anxieties and the conceptual frameworks they bring into their practicum journeys. This qualitative study interviewed five first-year preservice English language teachers in Indonesia amid COVID-19 lockdowns, exploring sources of their anxiety and coping strategies. The analysis revealed that, while their coping strategies align with those documented in prior international research, it also yielded novel insights. The preservice teachers in the study lacked conceptual frameworks to aid in translating the national ELT curriculum objectives into practice, did not mention utilising relevant professional literature for additional guidance, and appeared unfamiliar with the school culture at their practicum locations. Arguably, these factors are crucial for fostering a sense of ease during the practicum. Although the scope of this study is limited, its findings highlight the significance of this analysis and stress the necessity for more extensive investigations to gain a fuller understanding of the preservice practicum experience.
Response surface optimization design of flexible positioning platform considering its fatigue life
Authors: Zhang Lufan , Jiang Boshi , Zhang Pengqi , Yan Heng , Sun Hehe 
Published: March 2024

AbstractThe research of macro and micro motion platforms has always been committed to realizing the ultra-high acceleration operation of the platform and improving the positioning accuracy of the platform. With the goal of achieving ultra-high-speed, the impact of the increase in speed on key components has also attracted more and more attention. This paper takes a flexible positioning platform of an ultra-high acceleration macro–micro motion platform with adjustable voice coil motor (VCM) number and load as the research object. Perform static analysis, rigid-flexible coupled dynamic analysis, fatigue analysis, and multi-objective response surface optimization design (RSMD). The influence on the acceleration of the platform and the influence on the stress and fatigue life of the flexible positioning platform with the change of the number and load of the VCM were explored. The changes of the acceleration and speed curves of the platform during ultra-high-speed operation are obtained by dynamic analysis, and the position of the dangerous part of the flexible platform during operation is obtained. Finally, the RSMD is carried out to realize its performance optimization. The research conclusions of this paper have great reference value for the development of the macro–micro motion platform and the improvement of its structure.
Impact of acute heat stress on mitochondrial function, ultrastructure and cardiolipin distribution in Arabidopsis
Authors: Wang Yukang , Pan Ronghui , Hu Jianping 
Published: March 2024

AbstractBesides providing energy to sustain life, mitochondria also play crucial roles in stress response and programmed cell death. The mitochondrial hallmark lipid, cardiolipin (CL), is essential to the maintenance of mitochondrial structure and function. However, how mitochondria and CL are involved in stress response is not as well defined in plants as in animal and yeast cells. We previously revealed a role for CL in mitochondrial fission and in heat stress response in Arabidopsis. To further determine the involvement of mitochondria and CL in plant heat response, here we treated Arabidopsis seedlings with varied lengths of acute heat stress. These treatments resulted in decreases in mitochondrial membrane potential, disruption of mitochondrial ultrastructure, accumulation of mitochondrial reactive-oxygen species (ROS), and redistribution of CL to the outer mitochondrial membrane and to a novel type of vesicle. The level of the observed changes correlated with the severeness of the heat stress, indicating the strong relevance of these processes to stress response. Our findings provide the basis for studying mechanisms underpinning the role of mitochondria and CL in plant stress response.
Estimating Recovery in the Evaporation Chemical Space
Authors: Duelge Kaleb J. , Young Joshua A. 
Published: March 2024

AbstractEvaporation is a commonly used extract preparation technique in chemical characterization testing which can greatly impact the observed extractables. Although ideally only solvent is removed and the analytes remain, in practice the analytes evaporate as well, and these losses must be considered when addressing the appropriateness of evaporation as an extract preparation method. This issue is exacerbated when using evaporation before non-targeted analysis (NTA), where the identities of the analytes are not known prior to analysis. Herein, a means of evaluating the extent of evaporative loss in NTA is presented. To achieve this, a model for evaporative loss was adopted and verified experimentally, then applied to a relevant chemical space to determine the impact of experimental parameter selection. The model was used to predict recovery for a range of chemicals under a variety of experimental conditions (volume change, solvent, and temperature). The test solvents were selected to include a range of relevant properties, including molecular weight, density, and vapor pressure. The root-mean-square error of 70 evaporation recovery conditions was 12%. Excess losses, beyond the scope of this model, were found when samples were evaporated to dryness. Also, high recovery was demonstrated for select chemicals (with high air-solvent partition coefficients) at low concentration and with large volume changes. Overall, good agreement was found between the evaporation recovery model and experimental measurements, suggesting that the model can be used to predict the effect on a NTA.
Stable Heuristic Miner 2: Evaluating the Statistical Stability in Event Logs to Discover Business Processes
Authors: Namaki Araghi Sina , Fontanili Franck , Lamine Elyes , Benaben Frederick 
Published: March 2024

AbstractAutomated process discovery as one of the paradigms of process mining has attracted both industries and academic researchers. These methods offer visibility and comprehension out of complex and unstructured event logs. Over the past decade, the classic heuristic miner and applied heuristic-based process discovery algorithms showed promising results in revealing the hidden process patterns in information systems. One of the challenges related to such algorithms is the arbitrary selection of recorded behaviors in an event log. The offered filtering thresholds are manually adjustable, which could lead to the extraction of a non-optimal process model. This is also visible in commercial process mining solutions. Recently, the first version of the stable heuristic miner algorithm targeted this issue by evaluating the statistical stability of an event log. However, the previous version was limited to evaluating only activities’ behaviors. In this article, we’ll be evaluating the statistical stability of both activities and edges of a graph, which could be discovered from an event log. As a contribution, the stable heuristic miner 2 is introduced. Consequently, the definition of the descriptive reference process model has improved. The novel algorithm is evaluated by using two real-world event logs. These event logs are the familiar Sepsis data set and the urology department patients’ pathways event log, which is recorded by monitoring the interpreted location data of patients on hospital premises and is shared with the scientific community in this article.
Policy scenario analysis of achieving the "dual carbon" goal for the road transportation sector in China
Authors: He Ling-Yun , Yang Shuang 
Published: March 2024

AbstractThe goal of "dual carbon" has brought the pressure of reducing carbon emissions to the road transportation sector in China. This study aims to identify and analyze possible policy measures that would help to achieve this goal from the perspective of the whole life cycle. We build a bottom-up computing framework based on the LEAP model. Six policy scenarios are designed to quantitatively assess their effects. The results show that promoting pure electric vehicles (PEV) and plug-in hybrid electric vehicles (PHEV) is appropriate for the passenger vehicles (PV), light-duty trucks (LDT), and mini trucks (MT) sub-sectors, while hydrogen fuel cell vehicles (FCV) are more suitable for the promotion of the heavy-duty trucks (HDT), heavy-duty buses (HDB), and medium-duty buses (MDB) sub-sectors. Additionally, the recycling of vehicle materials can effectively reduce the carbon emissions during the life cycle of motor vehicles. Furthermore, reducing the carbon emissions from the vehicle cycle of PV and the fuel cycle of HDT should be taken seriously. The main contribution of this study lies in establishing a comprehensive list of vehicle cycle carbon emission factors, covering various sub-sectors of China's road transportation sector. Besides, this study considers China's strategic planning and "dual carbon" goal, and proposes policy recommendations specifically tailored to the practical issues faced by China.
Resources needed by critical access hospitals to address identified infection prevention and control program gaps
Authors: Soma Mounica , Scebold Jody , Vasa Angela , Fitzgerald Teresa Ann , Tyner Kate , Lalam Satya Kumar , Beach Sue , Ashraf Muhammad Salman 
Published: March 2024

Abstract

Objective:
The study examined resources needed by Infection Preventionists (IP) to address infection prevention and control (IPC) program gaps.

Design:
A 49-question survey.

Setting:
Licensed Critical Access Hospitals (CAHs) in Federal Emergency Management Area (FEMA) Region VII.

Participants:
IP at licensed CAHs.

Methods:
The survey conducted between December 2020 and January 2021 consisted of questions focusing on four categories including IPC program infrastructure, competency-based training, audit and feedback, and identification of high-risk pathogens/serious communicable diseases (HRP/SCD). An IPC score was calculated for each facility by totaling “Yes” responses (which indicate best practices) to 49 main survey questions. Follow-up questions explored the resources needed by the CAHs to implement or further strengthen best practices and mitigate IPC practice gaps. Welch t-test was used to study differences in IPC practice scores between states.

Results:
50 of 259 (19.3%) CAHs participated in the survey with 37 (14.3%) answering all 49 questions. CAHs responding to all questions had a median IPC score of 35. There was no significant difference between IPC practice scores of CAHs in NE and IA. The top three IPC gaps were absence of drug diversion program (77%), lack of audits and feedback for insertion and maintenance of central venous catheters (76%), and missing laboratory risk assessments to identify tests that can be offered safely for patients under investigation for HRP/SCD (76%). Standardized audit tools, educational resources, and staff training materials were cited as much-needed resources.

Conclusion:
IPC practice gaps exist in CAHs. Various resources are needed for gap mitigation.
Domain adaptation with transfer learning for pasture digital twins
Authors: Pylianidis Christos , Kallenberg Michiel G.J. , Athanasiadis Ioannis N. 
Published: March 2024

Abstract
Domain adaptation is important in agriculture because agricultural systems have their own individual characteristics. Applying the same treatment practices (e.g., fertilization) to different systems may not have the desired effect due to those characteristics. Domain adaptation is also an inherent aspect of digital twins. In this work, we examine the potential of transfer learning for domain adaptation in pasture digital twins. We use a synthetic dataset of grassland pasture simulations to pretrain and fine-tune machine learning metamodels for nitrogen response rate prediction. We investigate the outcome in locations with diverse climates, and examine the effect on the results of including more weather and agricultural management practices data during the pretraining phase. We find that transfer learning seems promising to make the models adapt to new conditions. Moreover, our experiments show that adding more weather data on the pretraining phase has a small effect on fine-tuned model performance compared to adding more management practices. This is an interesting finding that is worth further investigation in future studies.
On the Turán number of the hypercube
Authors: Janzer Oliver , Sudakov Benny 
Published: March 2024

Abstract
In 1964, Erdős proposed the problem of estimating the Turán number of the d-dimensional hypercube

$Q_d$

. Since

$Q_d$

is a bipartite graph with maximum degree d, it follows from results of Füredi and Alon, Krivelevich, Sudakov that

$\mathrm {ex}(n,Q_d)=O_d(n^{2-1/d})$

. A recent general result of Sudakov and Tomon implies the slightly stronger bound

$\mathrm {ex}(n,Q_d)=o(n^{2-1/d})$

. We obtain the first power-improvement for this old problem by showing that

$\mathrm {ex}(n,Q_d)=O_d\left (n^{2-\frac {1}{d-1}+\frac {1}{(d-1)2^{d-1}}}\right )$

. This answers a question of Liu. Moreover, our techniques give a power improvement for a larger class of graphs than cubes.
We use a similar method to prove that any n-vertex, properly edge-coloured graph without a rainbow cycle has at most

$O(n(\log n)^2)$

edges, improving the previous best bound of

$n(\log n)^{2+o(1)}$

by Tomon. Furthermore, we show that any properly edge-coloured n-vertex graph with

$\omega (n\log n)$

edges contains a cycle which is almost rainbow: that is, almost all edges in it have a unique colour. This latter result is tight.
The role of consciousness in Chinese nominal metaphor processing: a psychophysical approach
Authors: Cheng Kaiwen , Chen Yu , Yan Hongmei , Wang Ling 
Published: March 2024

AbstractConceptual metaphor theory (CMT) holds that most conceptual metaphors are processed unconsciously. However, whether multiple words can be integrated into a holistic metaphoric sentence without consciousness remains controversial in cognitive science and psychology. This study aims to investigate the role of consciousness in processing Chinese nominal metaphoric sentences ‘A是B’ (A is[like] B) with a psychophysical experimental paradigm referred to as breaking continuous flash suppression (b-CFS). We manipulated sentence types (metaphoric, literal and anomalous) and word forms (upright, inverted) in a two-staged experiment (CFS and non-CFS). No difference was found in the breakthrough times among all three types of sentences in the CFS stage, while literal sentences were detected more slowly than either metaphoric or anomalous sentences in the non-CFS stage. The results suggest that the integration of multiple words may not succeed without the participation of consciousness, let alone metaphoric processing. These findings may redefine ‘unconscious’ in CMT as ‘preconscious’ and support the indirect access view regarding how the metaphoric meaning is processed in the brain.
‘A sad inheritance of misery’: the cultural life of hereditary scrofula in eighteenth-century England
Authors: Gallagher Noelle Dückmann 
Published: March 2024

AbstractThis essay argues that scrofula was one of several disorders, including gout, rickets, and venereal disease, that were ‘rebranded’ as hereditary in response to broader cultural changes that took place during the Restoration and eighteenth century in England. While the purposes of scrofula’s recategorisation were more political than medical, they resulted in this heretofore relatively obscure childhood ailment assuming a new prominence within both medical and popular discourses of the period. Scrofula became both emblem and proof of the links between sexual promiscuity, financial profligacy, and physiological degeneration, its symbolic status reinforced by the legal and moral language used to model processes of hereditary transmission. By likening the inheritance of scrofula to the inheritance of original sin—or, more commonly, to the inheritance of a ‘docked entail’ or damaged estate—eighteenth-century writers and artists not only made this non-inherited ailment into a sign of catastrophic hereditary decline; they also paved the way for scrofula to be identified as a disease of aristocratic vice, even though its association with crowded, unsanitary living conditions likely made it more common among the poor. By the same token, financial models of disease inheritance facilitated a bias toward paternal transmission, with scrofula often portrayed as passing, like a title or an estate, from father to son rather than from mother to daughter.
L2 to Lp bounds for spectral projectors on the Euclidean two-dimensional torus
Authors: Demeter Ciprian , Germain Pierre 
Published: March 2024

AbstractWe consider spectral projectors associated to the Euclidean Laplacian on the two-dimensional torus, in the case where the spectral window is narrow. Bounds for their L2 to Lp operator norm are derived, extending the classical result of Sogge; a new question on the convolution kernel of the projector is introduced. The methods employed include $\ell^2$ decoupling, small cap decoupling and estimates of exponential sums.