bluuebunny/crossref_metadata_2025_split huggingface dataset:
Toxicity of persistent organic pollutants: a theoretical study
Authors: Martínez Ana 
Published: March 2024

Abstract
Context
Polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) are two families of persistent organic pollutants that are dangerous as they remain in the atmosphere for long periods and are toxic for humans and animals. They are found all over the world, including the penguins of Antarctica. One of the mechanisms that explains the toxicity of these compounds is related to oxidative stress. The main idea of this theoretical research is to use conceptual density functional theory as a theory of chemical reactivity to analyze the oxidative stress that PCBs and PBDEs can produce. The electron transfer properties as well as the interaction with DNA nitrogenous bases of nine PCBs and ten PBDEs found in Antarctic penguins are investigated. From this study, it can be concluded that compounds with more chlorine or bromine atoms are more oxidizing and produce more oxidative stress. These molecules also interact directly with the nitrogenous bases of DNA, forming hydrogen bonds, and this may be an explanation for the toxicity. Since quinone-type metabolites of PCBs and PBDEs can cause neurotoxicity, examples of quinones are also investigated. Condensed Fukui functions are included to analyze local reactivity. These results are important as the reactivity of these compounds helps to explain the toxicity of PCBs and PBDEs.

Methods
All DFT computations were performed using Gaussian16 at M06-2x/6–311 + g(2d,p) level of theory without symmetry constraints. Electro-donating (ω-) and electro-accepting (ω +) powers were used as global response functions and condensed Fukui functions as local parameters of reactivity.
The Impact of External Pressure on Companies’ Responses to Sanctions – an International Comparative Study
Authors: Stępień Beata , Early Bryan R. , Grauvogel Julia , Preble Keith A. , Truskolaski Szymon 
Published: March 2024

AbstractWhat explains the strategies firms adopt in response to economic sanctions? Our study argues that different types of external pressure, such as public shaming, the nature of companies’ business relationships, and national-level legal-regulatory environments affects how firms respond to the sanctions imposed against Russia after its 2022 invasion of Ukraine. We develop a suite of hypotheses about how external pressure affects firms’ compliance behaviors and whether firms adopt reactive and/or proactive strategic responses. We test our hypotheses by analyzing results from a survey of 610 medium-sized companies operating in Germany, Poland, and the United States. Using structural equation modeling (SEM), we find that external pressure is associated with higher levels of compliance and overcompliance with sanctions but is also associated with undercompliant behavior. We also find that compliance with sanctions is associated with a high degree of proactive response, which suggests compliant firms may often seek out legal means of circumventing sanctions. We further observed variation in the effects of external pressure, compliance behavior, and strategic responses on US firms compared to those in European Union members Germany and Poland.
What is conceptual disruption?
Authors: Marchiori Samuela , Scharp Kevin 
Published: March 2024

AbstractRecent work on philosophy of technology emphasises the ways in which technology can disrupt our concepts and conceptual schemes. We analyse and challenge existing accounts of conceptual disruption, criticising views according to which conceptual disruption can be understood in terms of uncertainty for conceptual application, as well as views assuming all instances of conceptual disruption occur at the same level. We proceed to provide our own account of conceptual disruption as an interruption in the normal functioning of concepts and conceptual schemes. Moreover, we offer a multilevel taxonomy thereof, where we distinguish between instances of conceptual disruptions occurring at different levels (conceptual scheme, conceptual clusters, and individual concepts), taking on different forms (conceptual gaps and conceptual conflicts), and leading to different degrees of severity (extending from mild to severe). We also provide detailed accounts through historical examples of how conceptual gaps and conceptual conflicts can occur at different times in the very same process of conceptual disruption. Finally, we make the case that different kinds of conceptual engineering can provide meaningful ways to assess and overcome distinct types of conceptual disruption.
On the Distances Within Cliques in a Soft Random Geometric Graph
Authors: Sönmez Ercan , Stegehuis Clara 
Published: March 2024

AbstractWe study the distances of vertices within cliques in a soft random geometric graph on a torus, where the vertices are points of a homogeneous Poisson point process, and far-away points are less likely to be connected than nearby points. We obtain the scaling of the maximal distance between any two points within a clique of size k. Moreover, we show that asymptotically in all cliques with large distances, there is only one remote point and all other points are nearby. Furthermore, we prove that a re-scaled version of the maximal k-clique distance converges in distribution to a Fréchet distribution. Thereby, we describe the order of magnitude according to which the largest distance between two points in a clique decreases with the clique size.
Pertechnetate removal from aqueous solutions by chitosan/hydroxyapatite composites
Authors: Hagara Pivarčiová Lucia , Rosskopfová Oľga , Hupian Marek , Viglašová Eva , Galamboš Michal , Juračka Dominik , Rajec Pavol 
Published: March 2024

AbstractThis study focuses on the usage of chitosan/hydroxyapatite composites for pertechnetate removal from aqueous solutions. Pertechnetate, a prominent radionuclide in nuclear waste, presents environmental hazards due to its long half-life and mobility. The composites, formed by intergrating hydroxyapatite into chitosan matrices, demonstrate in situ nanohydroxyapatite generation. Investigation of the adsorption process involves assessing parameters like pH, contact time, and the influence of competetive ions. This research provides valuable insights for using composites to mitigate pertechnetate contamination.
Harmonious Mutual Learning for Facial Emotion Recognition
Authors: Gan Yanling , Xu Luhui , Xia Haiying , Liu Gan 
Published: March 2024

AbstractFacial emotion recognition in the wild is an important task in computer vision, but it still remains challenging since the influence of backgrounds, occlusions and illumination variations in facial images, as well as the ambiguity of expressions. This paper proposes a harmonious mutual learning framework for emotion recognition, mainly through utilizing attention mechanisms and probability distributions without utilizing additional information. Specifically, this paper builds an architecture with two emotion recognition networks and makes progressive cooperation and interaction between them. We first integrate self-mutual attention module into the backbone to learn discriminative features against the influence from emotion-irrelevant facial information. In this process, we deploy spatial attention module and convolutional block attention module for the two networks respectively, guiding to enhanced and supplementary learning of attention. Further, in the classification head, we propose to learn the latent ground-truth emotion probability distributions using softmax function with temperature to characterize the expression ambiguity. On this basis, a probability distribution distillation learning module is constructed to perform class semantic interaction using bi-directional KL loss, allowing mutual calibration for the two networks. Experimental results on three public datasets show the superiority of the proposed method compared to state-of-the-art ones.
Density-Based Discriminative Nonnegative Representation Model for Imbalanced Classification
Authors: Li Yanting , Wang Shuai , Jin Junwei , Tao Hongwei , Nan Jiaofen , Wu Huaiguang , Chen C. L. Philip 
Published: March 2024

AbstractRepresentation-based methods have found widespread applications in various classification tasks. However, these methods cannot deal effectively with imbalanced data scenarios. They tend to neglect the importance of minority samples, resulting in bias toward the majority class. To address this limitation, we propose a density-based discriminative nonnegative representation approach for imbalanced classification tasks. First, a new class-specific regularization term is incorporated into the framework of a nonnegative representation based classifier (NRC) to reduce the correlation between classes and improve the discrimination ability of the NRC. Second, a weight matrix is generated based on the hybrid density information of each sample’s neighbors and the decision boundary, which can assign larger weights to minority samples and thus reduce the preference for the majority class. Furthermore, the resulting model can be efficiently optimized through the alternating direction method of multipliers. Extensive experimental results demonstrate that our proposed method is superior to numerous state-of-the-art imbalanced learning methods.
MicroRNA-124-3p Modulates Alpha-Synuclein Expression Levels in a Paraquat-Induced in vivo Model for Parkinson’s Disease
Authors: Esteves Marta , Cristóvão Ana Clara , Vale Ana , Machado-Pereira Marta , Ferreira Raquel , Bernardino Liliana 
Published: March 2024

AbstractParkinson’s disease (PD) is the second most prevalent neurodegenerative disease and the most common movement disorder. Although PD etiology is not fully understood, alpha (α)-synuclein is a key protein involved in PD pathology. MicroRNAs (miRNA), small gene regulatory RNAs that control gene expression, have been identified as biomarkers and potential therapeutic targets for brain diseases, including PD. In particular, miR-124 is downregulated in the plasma and brain samples of PD patients. Recently we showed that the brain delivery of miR-124 counteracts 6-hydroxydopamine-induced motor deficits. However, its role in α-synuclein pathology has never been addressed. Here we used paraquat (PQ)-induced rat PD model to evaluate the role of miR-124-3p in α-synuclein accumulation and dopaminergic neuroprotection. Our results showed that an intranigral administration of miR-124-3p reduced the expression and aggregation of α-synuclein in the substantia nigra (SN) of rats exposed to PQ. NADPH oxidases (NOX), responsible for reactive oxygen species generation, have been considered major players in the development of α-synuclein pathology. Accordingly, miR-124-3p decreased protein expression levels of NOX1 and its activator, small GTPase Rac1, in the SN of PQ-lesioned rats. Moreover, miR-124-3p was able to counteract the reduced levels of pituitary homeobox 3 (PITX3), a protein required for the dopaminergic phenotype, induced by PQ in the SN. This is the first study showing that miR-124-3p decreases PQ-induced α-synuclein levels and the associated NOX1/Rac1 signaling pathway, and impacts PITX3 protein levels, supporting the potential of miR-124-3p as a disease-modifying agent for PD and related α-synucleinopathies.
Transitory shocks, limited attention, and a firm’s decision to exit
Authors: Goldfarb Avi , Xiao Mo 
Published: March 2024

AbstractThis paper investigates the incidence of limited attention in a high-stakes business setting: a bar owner may be unable to purge transitory shocks from noisy profit signals when deciding whether to exit. Combining a 24-year monthly panel on the alcohol revenues from every bar in Texas with weather data, we find suggestive evidence that inexperienced, distantly located owners may overreact to the transitory component of revenue relative to the persistent component. This apparent asymmetric response is muted under higher revenue fluctuations. We formulate and estimate a structural model to endogenize attention allocation by owners with different thinking cost. Under the assumptions of the model, we find that 3.9% bars make incorrect exit decisions due to limited attention. As exits are irreversible, permanent decisions, small mistakes at the margin interpreting profit signals can lead to large welfare losses for entrepreneurs.
Analysis of the influence of emotions on the decision-making of entrepreneurs using neurotechnologies
Authors: Serna-Zuluaga Juan Camilo , Juárez-Varón David , Mengual-Recuerda Ana , Medina-López Ana 
Published: March 2024

AbstractThis study examines the influence of emotional factors on entrepreneurial decision-making, specifically focusing on early-stage entrepreneurs and those with more years of experience in the entrepreneurial process. The aim is to understand how emotional intensity affects business decisions at different stages of entrepreneurship. Neuroqualitative interviews were conducted using a stratified sample of entrepreneurs. The methodology included semi-structured interviews. Galvanic Skin Response (GSR) technology was employed to simultaneously measure participants’ emotional levels during the interviews. The results revealed significant differences in emotional levels between novice and experienced entrepreneurs concerning the analysed emotional factors. Novice entrepreneurs exhibited higher levels of anxiety and fear, especially in questions not previously anticipated, while experienced entrepreneurs showed confidence and a more optimistic outlook, particularly on topics related to long-term consolidation and revenue forecasting. This study highlights originality by demonstrating the importance of emotional factors in entrepreneurial decision-making and their variation over time in the entrepreneurial process. The use of GSR technology in neuroqualitative interviews adds a unique dimension by providing an objective assessment of entrepreneurs’ emotional levels, thus complementing the qualitative richness of verbal responses. These findings contribute to a deeper understanding of emotional complexity in business decision-making and emphasize the need to consider these aspects in entrepreneurship support strategies.
The orthographic representation of a word’s morphological structure: beneficial and detrimental effect for spellers
Authors: Sandra Dominiek , Ravid Dorit , Plag Ingo 
Published: March 2024

AbstractIn this paper we present a review of the literature on the role of a word’s morphological structure in written language processing, with an emphasis on spelling. First, we describe that many orthographies have opted for a representation of a word’s morphological structure. Second, we discuss experiments that have demonstrated the importance of a word’s morphological structure in reading, both in isolated word recognition experiments (so-called blind morphological decomposition) and in reading for meaning. Third, we discuss experimental findings that the written representation of a word’s morphological structure can have beneficial effects in spelling, already in young children with a good morphological awareness. However, several experiments have also shown that, in some circumstances, the speller’s task of representing morphology in written words creates considerable challenges and causes spelling errors rather than providing assistance. Closer inspection of this dissociation between beneficial and harmful effects reveals that two factors play a crucial role in determining the error risk: (a) the distinction between stems and affixes (i.e., morphological accessibility based on semantic transparency) and (b) the frequency with which a morpheme type in a language (stem, affix) must be retrieved in writing texts (accessibility based on type and token frequency). The review offers a theoretical framework against which the other papers in this special issue can be situated.
Short fasting test as a reliable and effective tool to diagnose insulinoma
Authors: Mikovic Nevena , Mazzilli Rossella , Zamponi Virginia , Russo Flaminia , Mancini Camilla , Mori Fedra , Bollanti Lucilla , Conti Francesco , Motta Cecilia , Monti Salvatore , Pugliese Giuseppe , Faggiano Antongiulio 
Published: March 2024

Abstract
Purpose
The diagnosis of insulinoma can be challenging, requiring documentation of hypoglycaemia associated with non-suppressed insulin and C-peptide, often achieved during a prolonged 72 h fast performed in inpatient setting. Our goal is to predict weather a shorter outpatient fasting test initiated overnight and prolonged up until 24 h could be a sensitive method for diagnosing insulinoma.

Methods
We conducted a retrospective monocentric study on subjects admitted to our Unit of Endocrinology from 2019 to 2022 for clinical suspicion of insulinoma and underwent the short fasting test. A comparison between the short test group and the group of subjects who underwent the standard prolonged fasting test (from 2003 to 2018) has also been performed. The short fasting test was initiated by the patient overnight at home and proceeded the following day in outpatient setting (Day Hospital). As in the standard protocol, symptoms and capillary blood glucose (CBG) were strictly monitored. Venous blood was drawn for glycaemia, insulin and C-peptide at admission and at established intervals, in case of symptoms of hypoglycaemia or if CBG ≤ 45 mg/dl, when the fast would be suspended.

Results
The final sample consisted of 37 patients, with mean age of 44.5 ± 12.6 years (17–74). Short and standard tests were performed in 15 and 22 subjects, respectively. Diagnostic values for insulinoma were observed in 12 patients: in 5/15 who underwent the short fasting test, in 6/22 who underwent the prolonged test and in 1 patient who was initially negative on the short test and subsequently showed diagnostic values during the prolonged test. The diagnosis of insulinoma was achieved in 11/12 cases within 24 h of the beginning of the fast (91.7%).

Conclusions
A short fasting test could be a valid, sensitive and reliable first-line workup in diagnosing insulinoma.
Smart system for water quality monitoring utilizing long-range-based Internet of Things
Authors: Murti Muhammad Ary , Saputra Andi Rudi Adhy , Alinursafa Ibnu , Ahmed Ali Najah , Yafouz Ayman , El-Shafie Ahmed 
Published: March 2024

AbstractWater is the most basic need for humans and a source of livelihood for humans. Lack of human awareness to maintain water quality, causing water to become polluted, by both industrial and household waste, impacts on human health and material loss. Thus, it is important to create technology that can monitor water pollution automatically and quickly. This research aims to create a system which utilizes the Internet of Things (IoT) technology that can facilitate quality of water by measuring parameters such as pH and turbidity. The methodology of the system progresses by the usage of a controller which is ATmega328P-AU, pH sensor to measure acidity, turbidity sensor to measure turbidity level, LPWAN LoRa works like a communication of data transmission as well as cloud service, namely Antares, to store data that are sent via Android. Based on the outcomes, the proposed system has achieved a reliable accuracy with percentage error of 99.73% in pH sensor and 99.41% in the turbidity sensor. Also, 2.6 s is the average required time to deliver the results to the cloud service.
Study of the hydrologic and hydrodynamic coupling model (HHDCM) and application in urban extreme flood systems
Authors: Zhou Ke 
Published: March 2024

AbstractBased on urban flood hydrology processes and hydrodynamic principles, the stormwater management model (SWMM) was improved upon. The coupling and implementation methods of the SWMM and two-dimensional hydrodynamic model are proposed. The improved SWMM was coupled with the hydrodynamic model both from the vertical and horizontal directions. The hydrology and hydrodynamic coupling model (HHDCM) was constructed and verified by using extreme rainstorm data. Taking July.20 extreme rainstorms (from July 17 to July 20, 2021, i.e., July.20 extreme rainstorm) in Zhengzhou city, Henan Province, China, as an example and using the HHDCM model, the flood disaster caused by July.20 extreme rainstorm was simulated. Based on the simulation results, an inundation distribution map was drawn for the urban area. A comparison between the simulated and measured results reveals that the maximum relative error in the simulated results is 12.5%. Therefore, the HHDCM model proposed in this paper has desirable accuracy and reliability for simulating extreme urban rainstorms and flood disasters.
Nanocrystals and nanosuspensions: an exploration from classic formulations to advanced drug delivery systems
Authors: Rossier Benjamin , Jordan Olivier , Allémann Eric , Rodríguez-Nogales Carlos 
Published: March 2024

AbstractNanocrystals and nanosuspensions have become realistic approaches to overcome the formulation challenges of poorly water-soluble drugs. They also represent a less-known but versatile platform for multiple therapeutic applications. They can be integrated into a broad spectrum of drug delivery systems including tablets, hydrogels, microneedles, microparticles, or even functionalized liposomes. The recent progresses, challenges, and opportunities in this field are gathered originally together with an informative case study concerning an itraconazole nanosuspension-in-hydrogel formulation. The translational aspects, historical and current clinical perspectives are also critically reviewed here to shed light on the incoming generation of nanocrystal formulations.
Markers for the detection of Lewy body disease versus Alzheimer’s disease in mild cognitive impairment: a systematic review and meta-analysis
Authors: Burgio Marianna Ilarj , Veronese Nicola , Sarà Davide , Saccaro Carlo , Masnata Roberta , Vassallo Giusy , Catania Angela , Catanese Giuseppina , Mueller Christoph , Smith Lee , Dominguez Ligia Juliana , Vernuccio Laura , Barbagallo Mario 
Published: March 2024

Abstract
Background
Mild cognitive impairment (MCI) may evolve into dementia. Early recognition of possible evolution to Alzheimer's disease (AD) and dementia with Lewy Bodies (DLB) is of importance, but actual diagnostic criteria have some limitations. In this systematic review and meta-analysis, we aimed to find the most accurate markers that can discriminate patients with DLB versus AD, in MCI stage.

Methods
We searched several databases up to 17 August 2023 including studies comparing markers that may distinguish DLB-MCI from AD-MCI. We reported data regarding sensitivity, specificity, and the area under the curves (AUCs) with their 95% confidence intervals (CIs).

Results
Among 2219 articles initially screened, eight case–control studies and one cohort study were included for a total of 832 outpatients with MCI. The accuracy of cerebrospinal fluid (CSF) markers was the highest among the markers considered (AUC > 0.90 for the CSF markers), with the AUC of CSF Aβ42/Aβ40 of 0.94. The accuracy for clinical symptom scales was very good (AUC = 0.93), as evaluated in three studies. Although limited to one study, the accuracy of FDG-PET (cingulate island sign ratio) was very good (AUC = 0.95) in discriminating DLB from AD in MCI, while the accuracy of SPECT markers and EEG frequencies was variable.

Conclusions
Few studies have assessed the accuracy of biomarkers and clinical tools to distinguish DLB from AD at the MCI stage. While results are promising for CSF markers, FDG-PET and clinical symptoms scales, more studies, particularly with a prospective design, are needed to evaluate their accuracy and clinical usefulness.
Clinical trial registration: Prospero (CRD42023422600).