bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying and understanding cognitive profiles in multiple sclerosis: a role for visuospatial memory functioning
Authors: van Dam Maureen , Krijnen Eva A. , Nauta Ilse M. , Fuchs Tom A. , de Jong Brigit A. , Klein Martin , van der Hiele Karin , Schoonheim Menno M. , Hulst Hanneke E. 
Published: February 2024

Abstract
Background
The heterogeneous nature of cognitive impairment in people with multiple sclerosis (PwMS) hampers understanding of the underlying mechanisms and developing patient-tailored interventions. We aim to identify and classify cognitive profiles in PwMS, comparing these to cognitive status (preserved versus impaired).

Methods
We included 1213 PwMS (72% female, age 45.4 ± 10.7 years, 83% relapsing–remitting MS). Cognitive test scores were converted to Z-scores compared to healthy controls for the functions: attention, inhibition, information processing speed (IPS), verbal fluency and verbal/visuospatial memory. Concerning cognitive status, impaired cognition (CI) was defined as performing at Z ≤ − 1.5 SD on ≥ 2 functions. Cognitive profiles were constructed using latent profile analysis on all cognitive functions. Cognitive profiles or status was classified using gradient boosting decision trees, providing the importance of each feature (demographics, clinical, cognitive and psychological functioning) for the overall classification.

Results
Six profiles were identified, showing variations in overall performance and specific deficits (attention, inhibition, IPS, verbal fluency, verbal memory and visuospatial memory). Across the profiles, IPS was the most impaired function (%CI most preserved profile, Profile 1 = 22.4%; %CI most impaired profile, Profile 6 = 76.6%). Cognitive impairment varied from 11.8% in Profile 1 to 95.3% in Profile 6. Of all cognitive functions, visuospatial memory was most important in classifying profiles and IPS the least (area under the curve (AUC) = 0.910). For cognitive status, IPS was the most important classifier (AUC = 0.997).

Conclusions
This study demonstrated that cognitive heterogeneity in MS reflects a continuum of cognitive severity, distinguishable by distinct cognitive profiles, primarily explained by variations in visuospatial memory functioning.
Serum neurofilament light chain associates with symptom burden in Lyme neuroborreliosis patients: a longitudinal cohort study from Norway
Authors: Skarstein Ingerid , Ulvestad Elling , Solheim Anne Marit , Vedeler Christian , Ljøstad Unn , Mygland Åse , Eikeland Randi , Reiso Harald , Lorentzen Åslaug Rudjord , Bos Steffan Daniel 
Published: February 2024

Abstract
Objectives
Serum neurofilament light chain (sNfL), an indicator of neuronal damage, is increasingly recognized as a potential biomarker for disease activity in neurodegenerative disorders. In this study, we wanted to investigate sNfL as a prognostic marker in a large, well-defined population of 90 patients with Lyme neuroborreliosis (LNB). In addition, we sought to explore associations between symptoms and sNfL levels during the acute phase of LNB.

Materials and methods
Patients diagnosed with definite or possible LNB were recruited from a double-blinded, placebo-controlled, multi-center trial, in which the participants were randomly assigned to 2 or 6 weeks of oral doxycycline treatment. The sNfL levels were measured using a single molecule array assay at both diagnosis and 6-month follow-up, and analysed against clinical parameters, variations in symptom burden and long-term complaints as assessed by a composite clinical score.

Results
At the time of diagnosis, approximately 60% of the patients had elevated sNfL levels adjusted for age. Notably, mean sNfL levels were significantly higher at diagnosis (52 pg/ml) compared to 6 months after treatment (12 pg/ml, p < 0.001), when sNfL levels had normalized in the majority of patients. Patients with objective signs of spinal radiculitis had significantly higher baseline sNfL levels compared to patients without spinal radiculitis (p = 0.033).

Conclusion
Our findings suggest that sNfL can serve as a biomarker for peripheral nerve tissue involvement in the acute phase of LNB. As found in an earlier study, we confirm normalization of sNfL levels in blood after treatment. We found no prognostic value of acute-phase sNfL levels on patient outcome.
Modified Archimedes optimization algorithm for global optimization problems: a comparative study
Authors: Nurmuhammed Mustafa , Akdağ Ozan , Karadağ Teoman 
Published: February 2024

AbstractArchimedes Optimization Algorithm (AOA) is a recent optimization algorithm inspired by Archimedes’ Principle. In this study, a Modified Archimedes Optimization Algorithm (MDAOA) is proposed. The goal of the modification is to avoid early convergence and improve balance between exploration and exploitation. Modification is implemented by a two phase mechanism: optimizing the candidate positions of objects using the dimension learning-based (DL) strategy and recalculating predetermined five parameters used in the original AOA. DL strategy along with problem specific parameters lead to improvements in the balance between exploration and exploitation. The performance of the proposed MDAOA algorithm is tested on 13 standard benchmark functions, 29 CEC 2017 benchmark functions, optimal placement of electric vehicle charging stations (EVCSs) on the IEEE-33 distribution system, and five real-life engineering problems. In addition, results of the proposed modified algorithm are compared with modern and competitive algorithms such as Honey Badger Algorithm, Sine Cosine Algorithm, Butterfly Optimization Algorithm, Particle Swarm Optimization Butterfly Optimization Algorithm, Golden Jackal Optimization, Whale Optimization Algorithm, Ant Lion Optimizer, Salp Swarm Algorithm, and Atomic Orbital Search. Experimental results suggest that MDAOA outperforms other algorithms in the majority of the cases with consistently low standard deviation values. MDAOA returned best results in all of 13 standard benchmarks, 26 of 29 CEC 2017 benchmarks (89.65%), optimal placement of EVCSs problem and all of five real-life engineering problems. Overall success rate is 45 out of 48 problems (93.75%). Results are statistically analyzed by Friedman test with Wilcoxon rank-sum as post hoc test for pairwise comparisons.
Software Development of an Integrated Water Management Optimisation Model: the Roy Hill Mine Case Study Application
Authors: Firmani Giovanni 
Published: February 2024

AbstractThis case study utilizes data from the Roy Hill iron ore mine, which has a daily water balance of abstraction, use, and surplus disposal, to address the problem of water management prediction at a global level by analysing the results of each modelling task and evaluating the presence of potential critical scenarios with an automated, mathematically rigorous tool. This paper describes the development of a software application that aggregates the results of the various water management models built for each task and provides the optimal utilisation of water to minimise water disposal and thereby maximise water usage. The business benefits of this work include the ability to calculate the net present cost (NPC) for new water infrastructure configurations in an integrated way. Investing in capital projects for water management and evaluating various scenarios helps determine the optimal water infrastructure configuration, minimizing operational impact. Traditionally, water has not been viewed as a significant cost; however, the cost of water infrastructure is now one of the highest business investments in the mining industry of the Pilbara region of Western Australia. Introducing the concept of NPC for water in the mining industry is a novel approach to making informed decisions on water expenses and investments. The key to success lies in using automated modelling to achieve the most efficient environmental and operational balance. This approach reduces individual decision-making and leads to a more cost-effective and beneficial production outcome.
Mitigating the curse of dimensionality using feature projection techniques on electroencephalography datasets: an empirical review
Authors: Anuragi Arti , Sisodia Dilip Singh , Pachori Ram Bilas 
Published: February 2024

AbstractElectroencephalography (EEG) is commonly employed to diagnose and monitor brain disorders, however, manual analysis is time-consuming. Hence, researchers nowadays are increasingly leveraging artificial intelligence (AI) techniques for automatic analysis of EEG, involving task-specific feature extraction and classification. Extracting multiple non-linear features from multiple EEG channels enhances the performance of classification, but it also results in high-dimensional features. However, the presence of the "curse of dimensionality" poses challenges for classifiers in AI-based EEG analyzers, leading to overfitting and complexity in classification. Therefore, in this empirical review, the effectiveness of the existing dimensionality reduction techniques to mitigate the curse of dimensionality in EEG feature sets is analyzed. We begin this study, by overviewing the extracted high-dimensional features from EEG signals related to disorders such as schizophrenia, alcoholism, focal seizures, focal seizures with deep features, and depression. Subsequently, 23 reduction techniques were reviewed, which transform the high-dimensional EEG features into a new reduced feature space to improve the classification. The impact of the reduced features was evaluated using traditional AI-based classifiers (support vector machine (SVM) and k-nearest neighbor (k-NN)). 10-fold cross-validation was performed for training and testing, and the performance was evaluated using accuracy, selected features, and dimensionality reduction rate (DRR) metrics. Comprehensive analysis of projection techniques on diverse EEG datasets offers valuable insights to assist researchers in selecting the most suitable technique. The hybrid projection technique termed principal component analysis-based t-distributed stochastic neighbor embedding (PCA+t-SNE) achieved an impressive average accuracy of 93.36%, surpassing the k-NN classifier without reduction techniques.
Applying earth system justice to phase out fossil fuels: learning from the injustice of adopting 1.5 °C over 1 °C
Authors: Gupta Joyeeta , Chen Yang , Mckay David I. Armstrong , Fezzigna Paola , Gentile Giuliana , Karg Aljoscha , van Vliet Luc , Lade Steven J. , Jacobson Lisa 
Published: February 2024

AbstractThe Paris Agreement has seen the adoption of a 1.5° to 2 °C climate target, based on the belief that climate change becomes ‘dangerous’ above this level. Since then, the scientific community and the countries most affected by global warming have reiterated that the maximum limit to be reached should be 1.5 °C. This paper goes one step further by questioning the reasoning behind the adoption of these targets, arguing that the fossil fuel-dependent political context in which they were adopted has undermined justice concerns. We highlight the political influence of the fossil fuels industry within target-setting negotiations, analyzing the evolution of climate targets and fossil fuel lobbying. We then harness published scientific evidence and the Earth System Justice framework to analyze the impacts of the 1.5 °C target, and the injustices that have so far been implicitly deemed acceptable. We argue that 1 °C would have been a far more just target and was undermined by vested interests and status quo maintenance. Finally, we propose just supply-side policies to ensure an adequate placement of responsibility on the fossil fuel industry. This way we (a) identify political influences and scientific blind spots that have and could continue to hinder climate action, (b) reveal how these influences delayed more ambitious climate objectives, contributing to the adoption of an unjust climate target, and (c) promote a focus on supply-side measures and polluting industries in order to break free from the impasse in the energy transition and foster more just outcomes.
Modulating spectral response of raw photosynthetic pigments via ternary cadmium chalcogenide quantum dots: simultaneous enhancement at green spectrum and inhibition at UV region
Authors: Aykut Sümeyye , Ük Nida , Coşkun İbrahim Yağız , Keskin Sultan Şahin , Nar Ilgın , Trabzon Levent , Ünlü Caner 
Published: February 2024

AbstractPhotosynthesis relies on the absorption of sunlight by photosynthetic pigments (PPs) such as chlorophylls and carotenoids. While these pigments are outstanding at harvesting light, their natural structure restricts their ability to harvest light at specific wavelengths. In this study, Oleic acid-capped CdSeS and CdTeS ternary quantum dots (QDs) were synthesized using a novel two-phase synthesis method. Then, these QDs were used to interact with raw PPs, a mixture of chlorophylls and carotenoids isolated from spinach. Our findings revealed the following: (1) Interacting QDs with raw PPs effectively inhibited the chlorophyll fluorescence of the pigments upon excitation in UV light region (250–400 nm) without causing any damage to their structure. (2) By forming an interaction with QDs, the chlorophyll fluorescence of raw PPs could be induced through excitation with green-light spectrum. (3) The composition of the QDs played a fundamental role in their interaction with PPs. Our study demonstrated that the photophysical properties of isolated PPs could be modified by using cadmium-based QDs by preserving the structure of the pigments themselves.
Covalent organic frameworks modified with silver nanoparticles as substrates for label-free SERS detection of fungicides
Authors: Wei Qingyi , Shao Liya , Pu Hongbin , Sun Da-Wen 
Published: February 2024

AbstractDespite prohibition in many countries, malachite green (MG) and crystal violet (CV) are illegally used in aquaculture, endangering both human health and the environment. Therefore, it is crucial to develop a method to accurately detect MG and CV. Surface-enhanced Raman spectroscopy (SERS) technology based on noble metal materials has attracted considerable attention for detecting food contaminations. However, noble metal materials are of poor stability and have a very low affinity for organic molecules. Herein, in this study, covalent organic frameworks (COFs) modified with silver nanoparticles (Ag NPs) were used as SERS substrates for the adsorption and detection of fungicides. COFs prepared by the Schiff base reaction of 1,3,5-tris (4-aminophenyl) benzene (TAPB) and 2,5-dimethoxybenzene-1,4-dicarboxaldehyde (DMTA) had a huge specific surface area and could provide sufficient adsorption sites and Ag NPs grown on the surface of COFs not only generated dense SERS “hot spots” but also improved their stability. The results showed that COF@Ag NPs exhibited a high enhancement factor (1.4 × 106), high reproducibility (RSD = 6.18%), and good stability within 50 days (RSD = 8.88%). Regression analyses in the ranges of 0.0001–10.0 mg/L and 0.0002–10.0 mg/L showed that the limits of detection (LOD) for the standard solutions of MG and CV were 3.8 × 10−5 mg/L and 1.8 × 10−5 mg/L, respectively. Furthermore, for MG and CV in fish samples, significant recoveries of 90.83–107.91% and 98.60–116.69% were achieved. Hence, it is hoped that this work could expand the application of COF materials for trace detection in SERS analyses.
miR-324-3p Suppresses Hepatic Stellate Cell Activation and Hepatic Fibrosis Via Regulating SMAD4 Signaling Pathway
Authors: Chen Si-Yu , Chen Xin , Zhu Sai , Xu Jin-Jin , Li Xiao-Feng , Yin Na-Na , Xiao Yan-Yan , Huang Cheng , Li Jun 
Published: February 2024

AbstractIn hepatic fibrosis (HF), hepatic stellate cells (HSCs) form the extracellular matrix (ECM), and the pathological accumulation of ECM in the liver leads to inflammation. Our previous research found that miR-324-3p was down-regulated in culture-activated human HSCs. However, the precise effect of miR-324-3p on HF has not been elucidated. In this study, the HF mouse models were induced through directly injecting carbon tetrachloride (CCl4) into mice; the HF cell models were constructed using TGF-β1-treated LX-2 cells. Next, real-time-quantitative polymerase chain reaction (RT-qPCR), western blot (WB) and immunohistochemistry (IHC) were applied to assess the expression levels of miR-324-3p, α-smooth muscle actin (α-SMA), Vimentin or SMAD4; hematoxylin and eosin (H&E), Masson’ s trichrome and Sirius red staining to evaluate the liver injury; luciferase reporter assay to verify the targeting relationship between miR-324-3p and SMAD4; enzyme-linked immunosorbent assay (ELISA) to determine the levels of serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST); and cell counting kit-8 (CCK-8) and flow cytometry to evaluate the effects of miR-324-3p on cell proliferation and cycle/apoptosis, respectively. The experimental results showed a reduction in miR-324-3p level in CCl4-induced HF mice as well as transforming growth factor (TGF)-β1-activated HSCs. Interestingly, the miR-324-3p level was rescued following the HF recovery process. In HF mice induced by CCl4, miR-324-3p overexpression inhibited liver tissue damage, decreased serum ALT and AST levels, and inhibited fibrosis-related biomarkers (α-SMA, Vimentin) expression, thereby inhibiting HF. Similarly, miR-324-3p overexpression up-regulated α-SMA and Vimentin levels in HF cells, while knockdown of miR-324-3p had the opposite effect. Besides, miR-324-3p played an antifibrotic role through inhibiting the proliferation of hepatocytes. Further experiments confirmed that miR-324-3p targeted and down-regulated SMAD4 expression. SMAD4 was highly expressed in HF cells, and silencing SMAD4 significantly decreased the α-SMA and Vimentin levels in HF cells. Collectively, the miR-324-3p may suppress the activation of HSCs and HF by targeting SMAD4. Therefore, miR-324-3p is identified as a potential and novel therapeutic target for HF.
Authorship and ChatGPT: a Conservative View
Authors: van Woudenberg René , Ranalli Chris , Bracker Daniel 
Published: February 2024

AbstractIs ChatGPT an author? Given its capacity to generate something that reads like human-written text in response to prompts, it might seem natural to ascribe authorship to ChatGPT. However, we argue that ChatGPT is not an author. ChatGPT fails to meet the criteria of authorship because it lacks the ability to perform illocutionary speech acts such as promising or asserting, lacks the fitting mental states like knowledge, belief, or intention, and cannot take responsibility for the texts it produces. Three perspectives are compared: liberalism (which ascribes authorship to ChatGPT), conservatism (which denies ChatGPT's authorship for normative and metaphysical reasons), and moderatism (which treats ChatGPT as if it possesses authorship without committing to the existence of mental states like knowledge, belief, or intention). We conclude that conservatism provides a more nuanced understanding of authorship in AI than liberalism and moderatism, without denying the significant potential, influence, or utility of AI technologies such as ChatGPT.
Morphological and molecular evidence for considering Xylocopa nigrocincta as the senior synonym of Xylocopa suspecta (Apidae: Xylocopini)
Authors: Agostini Júlia Colombelli , Françoso Elaine , Arias Maria Cristina , Zanella Fernando César Vieira 
Published: February 2024

AbstractXylocopa nigrocincta Smith, 1854, and Xylocopa suspecta Moure & Camargo, 1988, are two nominal species within the subgenus Neoxylocopa and have a sympatric geographic distribution in South America. While X. nigrocincta is recognized by the presence of reddish metasomatic bands, X. suspecta is entirely black. Although morphologically distinct in terms of metasomal band colour, other morphological characters suggest that both species could be the same evolutionary entity and therefore synonymous. The aim of this research was to review both nigrocincta and suspecta morphotypes using an integrative approach (morphological and molecular) to evaluate if they are truly two different evolutionary lineages. Females of both species were obtained from field collections and museums, representing a large part of their morphotype distribution. Additional diagnostic characters of the external morphology were investigated, such as metasomal band colour, metasomal punctuation, wing colours, and apical regions of the basitibial plate. Mitochondrial gene sequences (COI and CytB) were used for phylogenetic reconstructions. Our results showed that both nigrocincta and suspecta morphotypes are undistinguished based on morphology, although the metasomal band colour, together with the geographic distribution, revealed the presence of three distinct morphogroups, including an intermediate one with a variable number of reddish bands. Nonetheless, the three morphogroups are not supported by molecular data and therefore represent intra-specific variations. In conclusion, our results do not support the hypothesis that the two nominal species are distinct evolutionary lineages, and we propose a synonym between X. nigrocincta and X. suspecta.
Assessing Multidimensional Vulnerability of Rural Areas to Flooding: An Index-Based Approach
Authors: Rasool Samavia , Rana Irfan Ahmad , Waseem Hassam Bin 
Published: February 2024

AbstractVulnerability assessment is essential for understanding and launching effective flood risk reduction strategies. This study aimed to examine the vulnerability of flood-prone rural communities in southern Punjab, Pakistan to external shocks. The concept of vulnerability encompasses a range of dimensions, including physical, social, institutional, environmental, economic, and attitudinal. Using a composite index method, indices were developed for each dimension and combined to create a multidimensional measure of vulnerability. A sample of 365 communities was selected using the Yamane sampling technique, and data were collected through a questionnaire containing 65 indicators across all dimensions. Descriptive statistics and ANOVA tests were used to analyze the data. The results show that communities near the Chenab River had higher attitudinal and institutional vulnerability compared to other communities. High attitudinal vulnerabilities were associated with poorly perceived flood risks and low preparedness measures, whereas institutional vulnerabilities were driven by conventional flood protection strategies, lack of institutional trust, and lack of flood risk awareness. This research provides insights into the various components of vulnerability in flood-prone rural communities in Pakistan and demonstrates a useful methodology that can be applied to other disasters at different spatial scales.