bluuebunny/crossref_metadata_2025 huggingface dataset:
Pyrolysis Kinetics of Herbaceous Biomass Feedstocks Using Isoconversion Methods
Authors: Oginni Oluwatosin , Tingi Kaushlendra Singh
Published: February 2025

Pyrolysis is a major thermochemical conversion technology utilized in converting biomass to liquid fuel and bioproducts. A major process in this technology is the thermal decomposition of biomass which determines the pyrolysis products distribution. In order to optimize the distribution of these pyrolysis products, it is imperative to understand the thermal decomposition behaviors of the biomass feedstocks. The objective of this study was to investigate the thermal decomposition behaviors of Public Miscanthus and Kanlow Switchgrass using isoconversional methods. Thermogravimetric analysis was carried out by heating the biomass samples from room temperature to 700 ⁰C in an inert condition at heating rates of 5, 15, and 25 ºC/min. Three isoconversional methods (Friedman, Ozawa-Flynn-Wall, and Kissinger-Akhira-Sunrose) were used in estimating the kinetic parameters. The thermal decomposition process for the biomass samples was divided into three broad stages based on the temperature range, namely, moisture & light volatile release (< 200 ℃), devolatilization & biochar formation (200 – 400 ℃), and poly-condensation & biochar aromatization (> 400 ℃). The estimated activation energy values were influenced by the fractional conversion. There was a variation in the activation energy values estimated by the isoconversional methods, which is due to the difference in their estimation approach.
Affinity and Subtypes Analysis of the Anti-Nucleocapsid Antibodies in SARS-CoV-2 Vaccinated and Non-Vaccinated Individuals
Authors: Eltayeb Ahmed , Rubio-Casillas Alberto , Uversky Vladimir N. , Fathuldeen Suzan M. , Redwan Elrashdy M
Published: February 2025

The COVID-19 pandemic has underscored the critical need to understand immune responses arising from both natural infection and vaccination. This study examines the affinity and subclass distribution of anti-nucleocapsid (anti-N) antibodies in 60 participants, comprising 30 vaccinated and 30 non-vaccinated individuals. Using enzyme-linked immunosorbent assays (ELISA), we quantified total IgG (tIgG) and its subclasses (IgG1, IgG2, IgG3, and IgG4) in serum samples. Antibody affinity was assessed using ammonium thiocyanate to evaluate the strength of antigen-antibody interactions. We observed significantly elevated levels of tIgG and its subclasses in the vaccinated participants compared to the non-vaccinated controls, indicating a more robust immune response post-vaccination. In vaccinated individuals, the mean levels of tIgG, IgG1, IgG2, IgG3, and IgG4 were 2.59, 1.02, 0.055, 0.061, and 0.095 (OD), respectively, while non-vaccinated individuals showed lower mean levels at 0.512, 0.11, 0.052, 0.051, and 0.048 (OD) for tIgG, IgG1, IgG2, IgG3, and IgG4, respectively. This notable difference suggests that vaccination promotes not only higher production of these antibody subclasses but also, as shown by the corresponding affinity tests, an increased binding strength of anti-N antibodies. These results indicate that vaccination induces a more robust and higher-quality immune response, contributing to improved immune protection against SARS-CoV-2. The study highlights the critical role of anti-N antibodies in vaccine efficacy and long-term immunity. Our findings offer valuable insights into immune dynamics, informing future vaccine development and strategies for pandemic control, potentially leading to better management of emerging variants and more effective public health interventions.
Anticholinergic Load and Fibromyalgia Treatment Analysis: Guidelines and Drug Alerts
Authors: López de Coca Teresa , Sebastian-Morello Maria , González-Mazarío Roxana , Moreno Lucrecia
Published: February 2025

Background: This study examines the challenges associated with pharmacological management in fibromyalgia (FM), a multifaceted syndrome characterized by widespread pain, cognitive impairment and fatigue. A comparative analysis of drug usage, potential drug interactions, and adherence to clinical guidelines highlights the critical need to evaluate how medications may contribute to symptoms such as fibro-fog and affect overall quality of life, with the aim of optimizing patient` well-being. Objectives: The primary aim of this study was to assess medication usage, identify potential drug interactions, and evaluate treatment suitability in FM patients, with a particular focus on recent pharmacological advancements and their impact on symptom management. Methods: This cross-sectional study analyzed medication usage and potential drug interactions in women with FM. Tools such as CheckTheMeds® and the CRIDECO Anticholinergic Load Scale were employed to assess the pharmacological appropriateness of treatments in alignment with clinical guidelines, as well as to evaluate the anticholinergic burden and its potential cognitive impacts. Results: The study included 108 women with FM, with a mean age of 54.06 ± 8.43 years. Pain management medications accounted for 72.94% of total medication prescribed. The analysis revealed a significant anticholinergic burden in 50.93% of the patients, and a total of (881 alerts were recorded for potential drug interactions). Conclusions: Pharmacological reviews are essential in the management of FM, as they enhance treatment safety, minimize risks such as CNS depression and high anticholinergic burden, and help to alleviate symptoms like fibro-fog or cognitive impairment. Personalized medication approaches can improve patient outcomes and quality of life, particularly given the complexities and lack of consensus regarding FM treatment strategies.
AI-Driven Integrated Optimization for Virtual Power Plants in Smart Grids
Authors: Xinfa Tang , Jingjing Wang , Shengyuan Zhong
Published: February 2025

This paper delves into the potential of AI-driven optimization algorithm for integrating virtual power plant (VPP) into the electrical grid, aiming to enhance grid efficiency and maximize the utilization of renewable energy sources. By examining the fundamental principles of these advanced algorithms and their crucial role in enhancing power systems, this study demonstrates how artificial intelligence (AI) can improve both the accuracy and efficiency of optimization processes. Through a comprehensive comparative analysis of existing optimization techniques, our research highlights their inherent strengths and limitations, thereby providing a solid foundation for informed and innovative algorithm design. We propose a sophisticated AI-centric optimization framework that underscores the critical importance of robust data acquisition and pro-cessing mechanisms. The implementation, testing, and validation of our algorithm demonstrate its efficacy, indicating sig-nificant potential to enhance VPP operations. This work reinforces the theoretical foundation necessary for advancing the intelligence of VPP and offers valuable technical insights. It serves as a guiding beacon in promoting sustainable energy uti-lization while deepening our understanding of AI's profound impact on power system integration and optimization. Fur-thermore, our research provides novel perspectives and practical recommendations for future advancements in Smart Grid, contributing meaningfully to this burgeoning field.
p-adic Delsarte-Goethals-Seidel-Kabatianskii-Levenshtein-Pfender Bound
Authors: Krishna K. Mahesh
Published: February 2025

We introduce the notion of p-adic spherical codes (in particular, p-adic kissing number problem). We show that the one-line proof for a variant of the Delsarte-Goethals-Seidel-Kabatianskii-Levenshtein upper bound for spherical codes, obtained by Pfender, extends to p-adic Hilbert spaces.
Anglers Perceptions About European Catfish Silurus glanis in a Newly Invaded Region
Authors: Gago João , Rivaes Rui , Ribeiro Diogo , Dias Diogo , Castagné Paul , Santoul Frédéric , Ribeiro Filipe
Published: February 2025

To avoid the spread and environmental impacts of the European catfish (Silurus glanis), which have arrived to Portugal around 2006, it is fundamental to understand anglers’ behaviors and perceptions. To address this need 339 Portuguese anglers were surveyed online and face-to-face and divided into two groups (catfish anglers, n=115; and non-catfish anglers, n=224). The majority of surveyed anglers were males (> 95%) who consider that catfish is not beneficial to the development of angling (>62%) and acknowledge its negative impact on other fish species (> 84%), mainly by predation (> 89%). Catfish anglers perceive the species as more positive for angling and for other fish species. Principal Component Analysis showed that anglers behaviors are mainly driven by their awareness of the impacts of European catfish and by their angling ex-perience. Regression modelling inferred the probabilities of two anglers’ behavior (targeting catfish and practice of catch & release) and one perception (catfish is benefi-cial to angling), which are considered promoters of catfish invasion, and detected strong correlations among these three variables. Therefore, it is strongly advised to implement an educational and law enforcement programme to stop illegal practices that promote dissemination of invasive fish species like European catfish.
Optimal Experiments for Hybrid Modeling of Methanol Synthesis Kinetics
Authors: Kaps Lothar , Leipold Johannes , Plate Christoph , Martensen Carl Julius , Kortuz Wieland , Seidel-Morgenstern Andreas , Kienle Achim , Sager Sebastian
Published: February 2025

The transition of the chemical industry towards the utilization of feedstocks based on renewable energies results in a more dynamic process behavior. Advanced mathematical methods are a key factor to handle this complexity. In this contribution, methanol synthesis from hydrogen, carbon dioxide and carbon monoxide is investigated as promising power-2-X technology. Optimal experimental design is used to recalibrate an existing mechanistic kinetic model. Subsequently, the most uncertain sub-model, namely the reversible catalyst dynamics, is partially replaced by neural networks. Several architectures were evaluated, and optimal experimental design was applied to enhance the performance of a chosen architecture. All experiments were realized in an experimental setup able to acquire time-resolved data. A commercial CuO/ZnO/Al2O3 catalyst was used in a well-mixed Berty type reactor. The combination of optimal experimental design with hybrid modeling led to an improved quality of the kinetic model needed for process control and optimization.
Chemical Optimisation and Microbial Analysis of Biogas Production Process Parameters
Authors: Adedire Samuel Adebisi , Babajide Adebola Christiana , Adesina Rukayat Olubunmi , Kalu Elizabeth Oyidiriya , Buhari Fatai Ayofe , Aransiola Elizabeth Funmilayo , Momodu Abiodun Suleiman
Published: February 2025

This study characterised and adjusted certain production process parameters (pH, C/N ratio and temperature) critical to increasing the process efficiency, stability and sustainability to optimise biogas yield. The optimised setup was a 20L biodigester filled with 4.46kg of cow manure, 4.46kg of cassava water, and 4.46kg of cow rumen as inoculum in a ratio 1:1:1 respectively. Microbial analysis was also performed using standard procedures on the substrate and digestates of the optimised set-up. Physical and chemical pre-treatments were done on the substrates to ensure favourable conditions for anaerobic digestion. After a retention period of 19 days, a cumulative volume of 0.03913m³ (39.13L) of biogas was obtained. The microbial analysis on the substrates allowed the following microorganisms to be isolated; Bacillus sp Escherichia coli, Pseudomonas sp Proteus sp., Klebsiella sp., Lactobacillus sp Staphylococcus aureus. Microbial analysis from the substrate (Cow rumen and Cassava water) revealed no presence of Lactic acid bacteria while digestate (Cow dung with Cow rumen and cassava water) showed the presence of lactic acid bacteria. Isolates from both digestates were glucose fermenters with the production of carbon dioxide. The presence of these microorganisms indicated possible anaerobic activities in the generation of biogas.
Systematic Review and Meta-Analysis of 16S rRNA and Cancer Microbiome Atlas Datasets to Characterize Microbiota Signatures in Normal Breast, Mastitis and Breast Cancer
Authors: Rad Sima Kianpour , Yeo Kenny K. L. , Wu Fangmeinuo , Li Runhao , Nourmohammadi Saeed , Tomita Yoko , Price Timothy J. , Ingman Wendy V. , Townsend Amanda R. , Smith Eric
Published: February 2025

The breast tissue microbiome has been increasingly recognized as a potential contributor to breast cancer development and progression. However, inconsistencies in microbial composition across studies have hindered the identification of definitive microbial signatures. To address these gaps, we conducted a systematic review and meta-analysis of 11 studies employing 16S rRNA sequencing to characterize the bacterial microbiome across 1,260 fresh breast tissue samples, including normal, mastitis-affected, benign, cancer-adjacent, and cancerous tissues. We also incorporated microbiome data from The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort to enhance our analyses. Our meta-analysis identified Proteobacteria, Firmicutes, Actinobacteriota, and Bacteroidota as the dominant phyla in breast tissue, with Staphylococcus and Corynebacterium frequently detected across studies. While microbial diversity was similar between cancer and cancer-adjacent tissues, both exhibited lower diversity compared to normal and mastitis-affected tissues. Variability in bacterial genera was observed across primer sets and studies, emphasizing the need for standardized methodologies in microbiome research. Analysis of TCGA-BRCA data confirmed the dominance of Staphylococcus and Corynebacterium, which was associated with breast cancer proliferation-related gene expression programs. Notably, high Staphylococcus abundance was associated with a 4.1-fold increased mortality risk. These findings underscore the potential clinical relevance of the breast microbiome in tumor progression and emphasize the importance of methodological consistency. Future studies to establish causal relationships, elucidate underlying mechanisms, and assess microbiome-targeted interventions are warranted.
Multisensory Museums, Hybrid Realities, Narration and Technological Innovation: A Discussion Around New Perspectives in Experience Design and Sense of Authenticity
Authors: Pietroni Eva
Published: February 2025

This paper focuses on the topic of multisensory museums, conceived as extended or hybrid realities where real and digital coexist to offer cognitive and emotional engaging experiences to the public and increase the sense of authenticity. Multisensory communication can increase accessibility, as it conveys the content through multiple perceptual channels, and it can solicit more inclusive, participatory, and creative audience engagement through the stimulation of emotions. A methodological approach to digitisation, communication strategies, interaction, creative storytelling, immersive technologies and accessibility issues are discussed in depth, in relation to novel museological practices. Machine learning and generative AI are opening new scenarios in management practices and decision-making processes, in data analyses and in natural language processing, and in the creation of customized content addressed to the audiences. A short overview about how these algorithms evolve and work is presented, considering challenges, threats, expectations and ethical implications they pose. Another topic is the sense of authenticity. How is it changing in today users? How phygital realities, storytelling and user experience design in museums can influence it? The paper will discuss these issues, presenting also some case studies, which have cultural, social, philosophical, and ethical implications, at a time when museums are redesigning their role in a society undergoing profound transformation.
Biotechnological Applications of the Ubiquitous Fungus Penicillium sp. 8L2: Biosorption of Zn(II) and Synthesis of ZnO Nanoparticles as Biocidal Agents
Authors: Cobo Antonio Jesús Muñoz , Lozano Francisco Espínola , Vilar Manuel Moya , Valenzuela Celia Martín , Ramos Encarnación Ruiz
Published: February 2025

The capacity of the ubiquitous filamentous fungus Penicillium sp. 8L2 to remove Zn(II) ions pre-sent in synthetic solutions was studied and the optimal operating conditions were obtained based on a response surface methodology (RSM). The contact time was optimized by kinetic tests. Equilibrium tests were then carried out, which allowed the biosorption isotherms to be obtained for several mathematical models. At the same time, the capacity of the fungal cell ex-tract to transform metal ions into ZnO nanoparticles with biocidal capacity was evaluated. Its inhibitory capacity on five microbial strains was then determined. The biosorption mechanisms and nanoparticle synthesis were characterized by different crystallographic, spectrophotometric and microscopic analytical techniques. The kinetics showed that the biosorption of Zn(II) oc-curred in two stages, the first very fast and the second slower. Equilibrium tests dentified a maximum biosorption capacity of 52.14 mg/g for the Langmuir model under optimized condi-tions: Contact time of 5 days, pH 5.6 and 0.2 g/L biomass dose. The success of the biological syn-thesis route was confirmed and ZnO nanoparticles with an average size of 18 nm were obtained, which showed good inhibition data against the tested microorganisms, with values ranging from 62.5 to 1000 µg/mL. Penicillium sp. 8L2 is a promising ubiquitous microorganism in the field of heavy metal biosorption and applied biotechnology
A Computational Analysis Based on Automatic Digitization of Movement Tracks Reveals the Altered Diurnal Behavior of the Western Flower Thrips, Frankliniella occidentalis, Suppressed in PKG Expression
Authors: Xia Chunlei , Jin Gahyeon , Khan Falguni , Kim Hye-Won , Jang Yong-Hyeok , Jung Nam , Kim Yonggyun , Chon Tae-Soo
Published: February 2025

The western flower thrips, Frankliniella occidentalis, a worldwide insect pest with its polyphagous feeding behavior and transmitting virus, follows a diurnal rhythmicity driven by expression of the circadian clock genes. However, it remained unclear how the clock signal triggers the thrips behaviors. This study posed a hypothesis that the clock signal modulates cGMP-dependent protein kinase (PKG) activity to mediate the diurnal behaviors. A PKG gene is encoded in F. occidentalis and exhibits high sequence homologies with those of honeybee and fruit fly. Interestingly, its expression followed a diel pattern with high expression during photophase in larvae and adults of F. occidentalis. It is noteworthy that PKG expression was clearly observed in the midgut during photophase but not in scotophase from our fluorescence in situ hybridization analysis. A prediction of protein-protein interaction suggested its functional association with clock genes. To test this functional link, RNA interference (RNAi) of the gene expression was performed by feeding a gene-specific double stranded RNA and led to significant alteration of the two clock genes (Clock and Period) in their expression levels. The RNAi treatment gave adverse effects on immature development and adult fecundity. To further analyze the role of PKG in implementing the diurnal behavior, the adult females was continuously observed for 24 h-period with an automatic digitization device to obtain movement parameters and durations (%) in different micro-areas in the observation arena. Diel difference was observed with speed in RNAi-control females at 0.16 mm/s and 0.08 mm/s, in photo- and scoto-phase, respectively, whereas diel difference was not observed for the PKG-specific RNAi-treated females by showing 0.07 mm/s and 0.06 mm/s, respectively. The diel difference was also observed in durations (%) in the control females, more strongly in the intermediate area in the observation arena. Speed and durations in the different micro-areas in mid-scotophase were significantly different from most photophase in the control females, while speed was significantly different mainly during late photophase in comparing effects of control and RNAi treatments in each light phase. Three sequential stages consisting of high activity followed by feeding and visiting to micro-areas were observed for the control females. For RNAi-treated females the three phases were disturbed with irregular speed and visits to micro-areas. These results suggest that PKG is associated with implementing the diurnal behavior of F. occidentalis under the oscillating expressions of the clock genes.
Global Attractors for the Generalized Wave Fronts in Chemical Reactions and Kuramoto-Sivashinsky Equations
Authors: Cunha Alysson
Published: February 2025

We consider a generalization of the evolution equation for wave fronts in chemical reactions. For this equation, we establish global well-posedness in weighted Sobolev spaces, Zs,1/2(R), s ≥ 1, and prove the existence of a global attractor in these spaces. In particular, our results also imply the existence of a global attractor for the Kuramoto-Sivashinsky (KS) equation in these spaces.
Citric Acid-Catalyzed Three-Component Synthesis of (E)-3-Aryl-2-Styryl-2,3-Dihydroquinazolin-4-(1H)-Ones and Their Mild Oxidation with I2/DMSO System into (E)-3-Aryl-2-Styrylquinazolin-4(3H)-Ones
Authors: Kouznetsov Vladimir V. , Peñaranda Gómez Angélica , Puerto Galvis Carlos E.
Published: February 2025

We hereby report a simple and efficient method for the preparation of (E)-3-aryl-2-styryl-2,3-dihydroquinazolin-4-(1H)-ones, from isatoic anhydride, anilines and cin-namaldehydes in the presence of 20 mol% citric acid in methanol at 60 °C for 2 h. The styryl-dihydroquinazolin-4-(1H)-one products were obtained in moderate and good yields (30-80 %) through the three-component condensation reaction, under an environment-friendly protocol. The latter were easily transformed into styrylquinazolin-4-(3H)-one derivatives with 57-91 % yields using a mild oxidation with I2/DMSO system for less than 60 min.
Antioxidative Supplementation Has Minimal Impact on the Initiation of Inflammation but May Instead Facilitate Its Resolution
Authors: Hagn Gerhard , Bileck Andrea , Mohr Thomas , Schmidl Doreen , Baron David , Jilma Bernd , Schmetterer Leopold , Garhöfer Gerhard , Gerner Christopher
Published: February 2025

Systemic molecular responses to pathogen-associated molecular patterns and their modulation via antioxidants have hardly been determined in humans. Here, we present a dual stage clinical interventional study in healthy humans challenged with lipopolysaccharide. In a first stage, the kinetics of inflammatory modulators within eight hours was investigated by plasma proteomics and lipidomics. In a second stage, the effects of a placebo-controlled antioxidative intervention on the individual responses prior to another lipopolysaccharide challenge were determined. Plasma proteomics indicated the early involvement of the endothelium and platelets, followed by the induction of liver-derived acute phase proteins and an innate immune cell response. Untargeted lipidomics demonstrated the early release of fatty acids and taurocholic acid, followed by complex regulatory events exerted by oxylipins. The consistent lipopolysaccharide-induced downregulation of lysophospholipids indicated the involvement of the Lands cycle, and the downregulation of deoxycholic acid reinforced emerging associations between inflammasome and bile acids. Groups of molecules with similar kinetics upon lipopolysaccharide challenge were observed to have common precursors, synthesizing enzymes or cellular origin. Dietary supplementation with antioxidants before the lipopolysaccharide challenge did not detectably affect the kinetics of proteins but significantly downregulated pro-inflammatory sphingosine-1-phosphate and increased the levels of oxylipins described to facilitate the resolution of inflammation, 20-HEPE and 22-HDoHE. The present study identified a complex network of lipids deregulated in plasma upon lipopolysaccharide challenge and highlighted the role of platelets and erythrocytes as potent inflammatory modulators. While dietary antioxidant supplementation had minimal impact on inflammatory responses, it was shown to support the resolution of inflammation.
Dynamic Evolution of EEG Complexity in Schizophrenia Across Cognitive Tasks
Authors: Molina Rosa , Crespo-Cobo Yasmina , Esteban Francisco J. , Arias Ana Victoria , Rodríguez-Árbol Javier , Soriano Maria Felipa , Ibañez-Molina Antonio J. , Iglesias-Parro Sergio
Published: February 2025

Schizophrenia is characterized by widespread disruptions in neural connectivity and dynamic modulation. Traditional EEG analyses often rely on static or averaged measures, which may overlook the temporal evolution of neural complexity across cognitive demands. This study employed Higuchi Fractal Dimension, a non-linear measure of signal complexity, to examine the temporal dynamics of EEG activity across five cortical regions (central, frontal, occipital, parietal, and temporal lobes) during an attentional and a memory-based task in individuals diagnosed with schizophrenia and healthy controls.
A permutation-based Topographic Analysis of Variance, revealed significant differences in neural complexity between tasks and groups. In the control group, results showed a consistent pattern of higher neural complexity during the attentional task across the different brain regions (except during a few moments in temporal and occipital regions. This pattern of differentiation in complexity between the attentional and memory task reflects healthy individuals' ability to dynamically modulate neural activity based on task-specific requirements.
In contrast, the group of patients with schizophrenia exhibited inconsistent patterns of differences in complexity between tasks over time across all neural regions. That is, differences in complexity between tasks varies across time intervals, being sometimes higher in the attentional task and other times higher in the memory task (especially in central, frontal and temporal regions). This inconsistent pattern in patients can explain reduced differentiation in complexity across tasks in schizophrenia, and suggests a disruption in the modulation of neural activity on function of task demands.
These findings underscore the importance of analyzing the temporal dynamics of EEG complexity to capture task-specific neural modulation.
Three Methods for Combining Probability Distributions and an Alternative to Random-Effects Meta-Analysis
Authors: Huang Hening
Published: February 2025

Many fields or disciplines (e.g. uncertainty analysis in measurement science) require a combination of probability distributions. This paper examines three methods for combining probability distributions: weighted linear pooling, geometric pooling, and the law of combination of distributions (LCD). It provides insights into these three methods under the normality assumption. It shows that the weighted linear pooling method preserves all the variability (including heterogeneity) information in the original distributions; neither the geometric pooling method nor the LCD method preserves all the variability information, leading to information loss. We propose an index for measuring the information loss of a method with respect to the weighted linear pooling method. This paper also shows that the weighted linear pooling method can be used as an alternative to random-effects meta-analysis. Three examples are presented: the combination of two normal distributions, the combination of three discrete distributions, and the determination of the Newtonian constant of gravitation.
Ground up Citizenship: Rooted Children
Authors: Padilla-Deborst James
Published: February 2025

This paper explores how rights and protections, even citizenship, could be constructed around the vulnerable child, rather than being derived solely from state or nation. It provides examples of emerging ‘alternative communities’ doing just this and asks what role the church could have in reimagining and modelling communities that transcend borders, proclaim the gospel, and redefine family and mission.
Research on Green Warehousing Logistics Site Selection Optimization and Path Planning based on Deep Learning
Authors: Meng Qian , Wang Junbo , He Jingwen , Zhao Shenghan
Published: February 2025

When it comes to e-commerce and logistics industry developing rapidly, the location and path planning of green warehousing and logistics have attracted more and more attention, and how to improve efficiency and reduce environmental impact has become the focus of research. This paper presents a new optimization approach based on Deep Neural Network (DNN), which is used to solve the multi-objective optimization problem in the warehouse location and path planning. We propose to use a deep neural network model to optimize the weights and parameters of the network as a whole through the combined PSO method, so that the dynamic and diverse needs of the logistics environment can be better adapted to changes. Unlike traditional methods based on heuristics or simple machine learning models, this paper adopts the principle of minimizing the transportation cost, while achieving the minimization of energy consumption and the limited carbon emissions in path planning, i.e. optimizing the particle swarm of DNN. Empirical results indicate that, when compared to classical optimization techniques, our approach enhances transportation cost and environmental sustainability by 18% and 12%.
An Update on Neuroaging on Earth and in Spaceflight
Authors: Kuznetsov Nik , Statsenko Yauhen , Ljubisavljevic Milos
Published: February 2025

Over 400 articles on the pathophysiology of brain aging, neuroaging and neurodegeneration were reviewed, with a particular focus on epigenetic mechanisms and numerous non-coding RNAs, in particular microRNAs, the discovery of whose pivotal role in gene regulation was recognized by the 2024 Nobel Prize in Physiology or Medicine. Aging is not a gradual process that can be easily modeled and described. Instead, multiple temporal processes occur during aging, and they can lead to mosaic changes that are not uniform in pace. The rate of change depends on a combination of external and internal factors and can be boosted in accelerated aging. The rate can decrease in decelerated aging due to individual structural and functional reserves created by cognitive, physical training or pharmacological interventions. Neuroaging can be caused by genetic changes, epigenetic modifications, oxidative stress, inflammation, lifestyle, and environmental factors, which is especially noticeable in space environments where adaptive changes can trigger aging-like processes. Numerous candidate molecular biomarkers specific for neuroaging need to be validated to develop diagnostics and countermeasures.
Water Sustainability Criteria to Regulate the Proliferation of Pig Farms on a Karst Aquifer
Authors: Pedrozo-Acuña Adrián , Ramírez-Salinas Norma , Vázquez-Bustos Camilo
Published: February 2025

This study employs a thorough methodology to define water sustainability criteria for the development of new pig farms on the karst aquifer of Yucatan, Mexico. The integrated approach entails a field campaign to assess water quality from the aquifer (wells and cenotes) and effluents from designated pig farms to evaluate adherence to environmental regulations, alongside the utilisation of an extensive pig farm database that includes pig populations by municipality in Yucatan. To analyse the water sustainability of pig farming in Yucatan, we analysed the nitrogen grey water footprint and water pollution levels for this sector by municipality. The intensive pig farming practices in Yucatan significantly contribute to water contamination through nutrient runoff, namely nitrogen and phosphorus. Moreover, the breach of environmental regulations concerning pig farm effluents is demonstrated. This highlights the urgent need to regulate and monitor the expansion of new pig farms in Yucatan. Results introduce evidence-based criteria and their thresholds for achieving water sustainability in the pig sector at the municipal level (Pigs/ha=1.0 and WPL <1.1). This facilitated a concerted effort between national and state authorities to limit the proliferation of pig farms in order to safeguard the aquifer's water quality.
Autoethnography in education research
Authors: Souza Jonas dos Reis
Published: February 2025

This text is born from an autoethnographic reflection on the academic trajectory and experiences of a gay researcher in higher education, discussing the challenges imposed by heteronormativity and LGBTphobia in the university. Starting from the silent and marginalized place where lived experiences and narratives are exiled by heteronormativity and positivist methods of doing science, autoethnography, as an alternative route, is used as a methodological tool to integrate subjectivity and critical analysis, breaking with positivist paradigms and valuing individual experiences as sources of scientific knowledge. Based on the approaches of Ellis et al. (2015), Lopez-Cano and Opazo (2014), McLaurin (2003) and Oliveira Neto (2022), the text explores memory, self-observation and self-reflection as research strategies. The research demonstrates how autoethnography enables academic resistance and expands spaces for dissident narratives, promoting a more inclusive production of knowledge. Thus, it is concluded that this methodology contributes to the understanding of the dynamics of exclusion and belonging at the university, reinforcing the need for more welcoming academic environments for LGBTQIAPN+ identities.
Effects of dietary Moringa oleifera leaf extract on growth performance, enzyme activity and non-specific immune parameters in rohu Labeo rohita (Hamilton, 1822)
Authors: Choudhary Pushpa , Muddalingaiah S. G. , Mohanty Snatashree , Paul Anirban , Mishra S. S. , Das Rakesh
Published: February 2025

A 60-day study was conducted to evaluate the effect of dietary Moringa oleifera leaf extract (MLE) on growth, enzyme activity and non-specific immune parameters in rohu Labeo rohita. To ascertain this, 180 fingerlings of L. rohita (average weight 12.24±0.5 g) were randomly distributed into four groups based on the level of inclusion of M. oleifera leaf extract viz., control (C): basal diet without extract, T1: 2.5 g (0.25%), T2: 5 g (0.5%) and T3: 10 g (1%) extract per kg of basal feed per day respectively. After 60 days, results revealed that experimental fish significantly (p<0.05) improved growth, digestive enzymes viz., amylase and total protease activity in all the treatments compared to the control with the highest performance in T3. In addition, serum antioxidative enzymes viz., superoxide dismutase and catalase activity were also significantly (p<0.05) enhanced in the treatment groups. Myeloperoxidase, respiratory burst activity, alternative complement activity and total serum protein were significant (p<0.05) in fish administered 10 g of M. oleifera leaf extract via basal diet. Conclusively, dietary supplementation of M. oleifera leaf extract at 0.5% ~1% through basal feed significantly improved growth, enzyme activity and important immunological parameters in L. rohita.
Keywords: Antioxidant, Aquaculture, Dietary supplement, Growth, Immunity, Indian major carp
New Method for Nuclear Magnetic Resonance Dual Echo Time Logging Interpretation and Fluid Identification in Tight Sandstone Gas Reservoirs
Authors: Li Bo , Yin Guofeng , Wang Anlong , Tan Maojin
Published: February 2025

For tight sandstone gas reservoirs, conventional logging has great uncertainty, and fluid identification is difficult. Nuclear magnetic resonance (NMR) dual echo time (TE) logging has good application potential in identifying tight sandstone gas layers. The original NMR logging spectrum and diffusion analysis (DIFAN) methods both assume that the diffusion coefficients of gas and water are known and reflect gas information. However, the existing methods cannot be applied to complex gas layers. In this paper, we propose a new NMR dual TE logging interpretation method combining particle swarm optimization (PSO) with least squares (LSQR) algorithm inversion. Based on the principle of NMR dual TE logging activation, we analyze its relaxation mechanism and derive the equations between the echo train amplitude difference and fluid type, fluid content, and fluid diffusion coefficient. Based on the PSO inversion method, we perform nonlinear inversion of the constructed objective function to obtain parameters, such as the diffusion coefficient of the fluid, and generate an echo train difference that reflects the fluid information. We then use the LSQR method to invert the generated echo train differences to obtain a difference spectrum that reflects hydrocarbon information, and then calculate the gas volume and gas saturation of the reservoir’s flushed zone. We verify the correctness of the new method by building a rock model and conducting numerical simulations. Based on the calculation results, the gas-containing porosity in the flushed zone calculated by the new method and the gas-containing porosity in the flushed zone calculated by the time domain analysis (TDA) method crossplot are constructed. We applied the above method to the Huagang formation in a basin in eastern China. The results show that this idea and the inversion method can effectively realize the NMR dual TE logging data processing of tight sandstone gas reservoirs, and the fluid identification crossplot established based on the processing results improves the accuracy of gas layer identification.
Sturge-Weber Syndrome in a Multinational Paediatric Cohort: A Systematic Analysis of Different Types
Authors: Disse Sigrid , Ramantani Georgia , Küpper Hanna , Bock Annette , Korenke Georg-Christoph , Weidner Birgit , Preisel Martin , Trollmann Regina , Wiemer-Kruel Adelheid , Wellmann Sven , Brockmann Knut , Schröder Simone , Meyer Sascha
Published: February 2025

Background
Sturge-Weber Syndrome (SWS) is a rare neurocutaneous disease, characterized by cerebral capillary-venous malformation, glaucoma, and facial vascular birthmark. Different types are reflected in the Roach classification. Most previous studies have focussed on classic SWS Type I, but Type III cases, lacking facial birthmark, were mostly described in case reports. We systematically compare cases with and without facial birthmark, with a focus on epilepsy variables, cerebral involvement, use of aspirin, and overall outcome.
Methods
Using a cross-sectional observational study conducted through a well-established child neurologists’ network, we recruited paediatric patients with clinically diagnosed SWS from Germany, Switzerland, and Austria. The patients’ guardians and attending child neurologists filled in detailed questionnaires. All patients were classified according to the Roach classification by both attending child neurologists and the study team.
Results
Out of 111 paediatric SWS patients identified, 47 participated (43.2%). 35 cases (74.5%) fulfilled the criteria for classic SWS (Roach Type I); six cases (12.8%) showed no skin involvement (Roach Type III), the remaining six cases had overlap/atypical phacomatoses with capillary-venous malformation. Cases without facial birthmark were older at diagnosis (p = 0.005), and none showed ophthalmologic involvement. Age at first seizure did not differ significantly after adjustment for multiple comparisons. No significant differences were observed in seizure frequency, seizures types, number of used antiseizure medication (ASM), epilepsy surgery, cerebral involvement including atrophy and calcifications, SWS neuroscores or use of supportive therapies. Multivariable logistic regression showed seizure frequency was independent of SWS type and epilepsy surgery, but positively associated with the number of ASM required for seizure control (p = 0.0056). Half of operated patients were seizure-free at inclusion.
Conclusions
In our multinational cohort, Type I and Type III cases showed comparable epilepsy features, SWS neuroscores, number of required ASM and supportive therapy requirements. Type III patients were older at diagnosis and showed no ophthalmologic involvement, indicating a milder phenotype. Irrespective of SWS type, patients with uncontrolled epilepsy were 3.8-times more likely to require additional ASM. Despite uncontrolled epilepsy, only few patients underwent surgical evaluation or intervention. Larger cohorts are needed to evaluate surgical outcomes across SWS subtypes.
High Living Costs, Urban Agglomeration, and Inequality: Lessons from the Spatial Geo-Economic Politics of Urban Out-Migration in Sub-Saharan African Cities.
Authors: Nzabirinda Etienne
Published: February 2025

This paper examines how high living costs, urban agglomeration, and inequality interact in Sub-Saharan African cities, focusing on the urban out-migration aspect of the spatial geo-economic politics involved. Using data from the World Bank and the GMM technique, the study identifies income inequality, rapid urbanization, and rising living costs as the main determinants of migration. The analysis reveals a net migration rate of 1.092 in large cities like Lagos, Kinshasa, and Johannesburg, driven by urban growth and economic opportunities that attract people. However, due to increasing living costs, high housing costs, and congestion, individuals are forced to move to more affordable and less crowded areas, resulting in out-migration. Income inequality, with a Gini coefficient of 0.81, where a few urban areas accumulate wealth while leaving a large portion of the population in poverty, is also linked to migration dynamics. Rapid urbanization, with an average growth rate of 4.403%, exacerbates spatial disparities and encourages migration towards peri-urban and secondary cities. The study also explores the influence of economic indicators on migration trends, using GDP per capita and GNI growth to show that economic growth and inequality play significant roles. Policy recommendations such as affordable housing, economic decentralization, slum upgrading, and improved access to services are suggested to address migration challenges and promote sustainable urban development.
JEL Classification R23, O18, D31
Integrated UPLC-Q-TOF-MS, network pharmacology and experimental approach to evaluate the effects of blood stasis constitution ointment on lung cancer
Authors: Wang Qiaozhi , Wang Juhe , Dai Chuanhao , Lu Tianming , Xiong Xingjiang , Shen Shuo , Guo Qiuyan , You Hu , Du Maobo
Published: February 2025

Background
Blood stasis constitution ointment (BSCO) is based on the classic formulas Xuefu Zhuyu and Buyang Huanwu decoctions described in Yilin Gaicuo by Wang Qingren of the Qing Dynasty. These formulas have been used to effectively treat blood stasis, which is identified as a pathological factor of lung cancer in traditional Chinese medicine theory.
Aim of the study
: To analyze the chemical components of BSCO, predict target pathways, and evaluate its effects on lung cancer through in vivo and in vitro experiments.
Methods
Ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry was used to identify components of BSCO, and network pharmacology was used to predict their targets and signaling pathways associated with lung cancer. A Lewis lung cancer model was established in mice to evaluate the effects of BSCO by observing tissue morphology, whole animal imaging, and determination of serum biochemical indicators. The effects of BSCO on Lewis cancer cells in vitro were assessed using a CCK-8 cell proliferation assay.
Results
Twenty major chemical components of BSCO were identified, with 341 potential targets identified by network pharmacology. BSCO effectively inhibited tumor growth in the Lewis lung cancer mouse model and normalized serum markers of cancer to varying degrees. The IC50 of BSCO on Lewis cell proliferation was 173 mg/mL. Low- and high-dose BSCO-containing drug serum inhibited proliferation of Lewis cells after 24 and 48 h incubation.
Conclusion
The results suggest that BSCO may exert anticancer effects through targets including GAPDH, AKT1, TP53, TNF, IL6, and the PI3K-Akt signaling pathway, providing a reference for its clinical application in the prevention and treatment of lung cancer.
Learning neuroimaging models from health system-scale data
Authors: Hollon Todd , Lyu Yiwei , Chowdury Asadur , Banerjee Soumyanil , Gologorsky Rachel , Liu Shixuan , Meissner Anna-Katharina , Rao Akshay , Kondepudi Akhil , Jiang Cheng , Hou Xinhai , Joshi Rushekish , Neuschmelting Volker , Sriniva Ashok , Kleindorfer Dawn , Gulani Vikas , Pandey Aditya , Lee Honglak , Athey Brian
Published: February 2025

Neuroimaging is a ubiquitous tool for evaluating patients with neurological diseases. The global demand for magnetic resonance imaging (MRI) studies has risen steadily, placing significant strain on health systems, prolonging turnaround times, and intensifying physician burnout. These challenges disproportionately impact patients in low-resource and rural settings. Here, we utilized a large academic health system as a data engine to develop Prima, the first vision-language model (VLM) serving as an AI foundation for neuroimaging that supports real-world, clinical MRI studies as input. Trained on over 220,000 MRI studies, Prima uses a hierarchical vision architecture that provides general and transferable MRI features. Prima was tested in a 1-year, prospective, health system-wide study that included 30K MRI studies. Across 52 radiologic diagnoses from the major neurologic disorders, including neoplastic, inflammatory, infectious, and developmental lesions, Prima achieved a mean diagnostic area under the ROC curve of 90.1 +/- 5.0%, outperforming other state-of-the-art general and medical VLMs by a large margin. Prima offers explainable differential diagnoses, worklist priority for radiologists, and clinical referral recommendations across diverse patient demographics and MRI systems. Prima demonstrates algorithmic fairness across sensitive groups and can help mitigate health system biases, such as prolonged turnaround times for at-risk populations. These findings highlight the transformative potential of health system-scale VLMs and Prima's role in advancing AI-driven healthcare.
Chemically Programmable DNA Nanostructures for Multiplexed High-Throughput Screening of Cardiovascular Therapeutics
Authors: Wu Ke-Jia
Published: February 2025

The development of small-molecule therapeutics for cardiac hypertrophy is limited by the lack of high-throughput screening platforms capable of multiplexed molecular detection. Here, we present the Multifunctional Nucleic-acid-label-free hESC-CMs Molecular Evolution (MNCME) platform, which integrates tetrahedral DNA nanostructures with human embryonic stem cell-derived cardiomyocytes (hESC-CMs) for chemically programmable, label-free detection of DNA, RNA, proteins, and small molecules. By dynamically substituting three label-free primers, MNCME enables flexible molecular profiling and rapid target adaptation. Machine learning-assisted analysis of known anti-hypertrophic compounds identified key molecular signatures, optimizing high-throughput screening workflows. Structurally organized into five functional zones, MNCME screened a 600-compound library, identifying nine bioactive molecules, including caffeic acid (CA), previously unrecognized for its cardioprotective potential. Mechanistic studies revealed that CA modulates ATP synthesis, Ca²⁺ homeostasis, and Mucin-1 signaling, with validation in cellular and in vivo models. By integrating DNA nanotechnology, chemical biology, and high-throughput phenotypic screening, MNCME provides a scalable and versatile platform for accelerating the discovery of small-molecule modulators targeting cardiac hypertrophy. This approach has the potential to transform therapeutic development for cardiovascular diseases and other complex pathologies, offering a powerful tool for both fundamental research and clinical translation.