bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Bond Energy of the Carbon Skeleton in Polyaromatic Halohydrocarbon Molecules
Authors: Chan Bun , Karton Amir 
Published: October 2024

AbstractWe have investigated the thermochemical stability of the carbon skeleton in polycyclic aromatic (halo) hydrocarbons using a systematic collection of molecules (the PAHH343 set). With high‐level quantum chemistry methods such as W1X‐2, we have obtained chemically accurate (i. e.,±~5 kJ mol−1) “normalized carbon skeleton” bond energies. They are calculated by removing the C−H and C−X (X=F, Cl) bond energies from the total atomization energy, and then normalizing on a per‐carbon basis. For species with isomeric halogen‐substitution pattern, the energetic variation is generally small, though larger difference can also be seen due to structural distortion from steric repulsion. The skeleton energy becomes smaller with an increasing number of halogen atoms due to the withdrawal of electron density from the bonding orbitals, mainly through the σ‐bonds. We have further assessed the performance of some low‐cost quantum chemistry methods for the PAHH343 set. The deviations from reference values are largely systematic, and can thus be compensated for, yielding errors that are on average below 10 kJ mol−1. This provides the prospect for the study of an even wider range of PAHH and related systems.
Targeting CD38 with monoclonal antibodies disrupts key survival pathways in paediatric Burkitt's lymphoma malignant B cells
Authors: Kläsener Kathrin , Herrmann Nadja , Håversen Liliana , Sundell Timothy , Sundqvist Martina , Lundqvist Christina , Manna Paul T , Jonsson Charlotte A , Visentini Marcella , Ljung Sass Diana , McGrath Sarah , Grimstad Kristoffer , Aranburu Alaitz , Mellgren Karin , Fogelstrand Linda , Forsman Huamei , Ekwall Olov , Borén Jan , Gjertsson Inger , Reth Michael , Mårtensson Inga‐Lill , Camponeschi Alessandro 
Published: October 2024

AbstractObjectivesPaediatric Burkitt's lymphoma (pBL) is the most common childhood non‐Hodgkin B‐cell lymphoma. Despite the encouraging survival rates for most children, treating cases with relapse/resistance to current therapies remains challenging. CD38 is a transmembrane protein highly expressed in pBL. This study investigates the effectiveness of CD38‐targeting monoclonal antibodies (mAbs), daratumumab and isatuximab, in impairing crucial cellular processes and survival pathways in pBL malignant cells.MethodsIn silico analyses of patient samples, combined with in vitro experiments using the Ramos cell line, were conducted to assess the impact of daratumumab and isatuximab on cellular proliferation, apoptosis and the phosphoinositide 3‐kinase (PI3K) pathway.ResultsIsatuximab was found to be more effective than daratumumab in disrupting B‐cell receptor signalling, reducing cellular proliferation and inducing apoptosis. Additionally, isatuximab caused a significant impairment of the PI3K pathway and induced metabolic reprogramming in pBL cells. The study also revealed a correlation between CD38 and MYC expression levels in pBL patient samples, suggesting CD38 involvement in key oncogenic processes.ConclusionThe study emphasises the therapeutic potential of CD38‐targeting mAbs, particularly isatuximab, in pBL.
Structural inequality and temporal brain dynamics across diverse samples
Authors: Baez Sandra , Hernandez Hernan , Moguilner Sebastian , Cuadros Jhosmary , Santamaria‐Garcia Hernando , Medel Vicente , Migeot Joaquín , Cruzat Josephine , Valdes‐Sosa Pedro A. , Lopera Francisco , González‐Hernández Alfredis , Bonilla‐Santos Jasmin , Gonzalez‐Montealegre Rodrigo A. , Aktürk Tuba , Legaz Agustina , Altschuler Florencia , Fittipaldi Sol , Yener Görsev G. , Escudero Javier , Babiloni Claudio , Lopez Susanna , Whelan Robert , Lucas Alberto A Fernández , Huepe David , Soto‐Añari Marcio , Coronel‐Oliveros Carlos , Herrera Eduar , Abasolo Daniel , Clark Ruaridh A. , Güntekin Bahar , Duran‐Aniotz Claudia , Parra Mario A. , Lawlor Brian , Tagliazucchi Enzo , Prado Pavel , Ibanez Agustin 
Published: October 2024

AbstractBackgroundStructural income inequality – the uneven income distribution across regions or countries – could affect brain structure and function, beyond individual differences. However, the impact of structural income inequality on the brain dynamics and the roles of demographics and cognition in these associations remains unexplored.MethodsHere, we assessed the impact of structural income inequality, as measured by the Gini coefficient on multiple EEG metrics, while considering the subject‐level effects of demographic (age, sex, education) and cognitive factors. Resting‐state EEG signals were collected from a diverse sample (countries = 10; healthy individuals = 1394 from Argentina, Brazil, Colombia, Chile, Cuba, Greece, Ireland, Italy, Turkey and United Kingdom). Complexity (fractal dimension, permutation entropy, Wiener entropy, spectral structure variability), power spectral and aperiodic components (1/f slope, knee, offset), as well as graph‐theoretic measures were analysed.FindingsDespite variability in samples, data collection methods, and EEG acquisition parameters, structural inequality systematically predicted electrophysiological brain dynamics, proving to be a more crucial determinant of brain dynamics than individual‐level factors. Complexity and aperiodic activity metrics captured better the effects of structural inequality on brain function. Following inequality, age and cognition emerged as the most influential predictors. The overall results provided convergent multimodal metrics of biologic embedding of structural income inequality characterised by less complex signals, increased random asynchronous neural activity, and reduced alpha and beta power, particularly over temporoposterior regions.ConclusionThese findings might challenge conventional neuroscience approaches that tend to overemphasise the influence of individual‐level factors, while neglecting structural factors. Results pave the way for neuroscience‐informed public policies aimed at tackling structural inequalities in diverse populations.
DNA barcoding and cryptic diversity in fishes from the Ili River Valley in China, Xinjiang
Authors: Zheng Ling‐Ling , Yu Dan , Sun Ning , Wang Cheng , Chen Wen‐Jun , Ding Zu‐Fa , He Shun‐Ping , Yang Lian‐Dong 
Published: October 2024

AbstractThe Ili River Valley, located in the northwest of China, serves as a vital repository for fish genetic resources. Its extensive water network and diverse climate have given rise to a unique fish composition and endemic species. In this study, we collected the cytochrome c oxidase subunit I (COI) sequences from 660 fish specimens in the Ili River Valley. The effectiveness of DNA barcoding in identifying fish species in the area was assessed by examining genetic distances, constructing phylogenetic trees, and performing ABGD (Automatic Barcode Gap Discovery) analyses, among other methods. In total, 20 species were identified, including one unidentified species (Silurus sp.). Except for Silurus asotus and Hypophthalmichthys molitrix (only one sample), the maximum intraspecific genetic distance among the remaining species was smaller than the minimum interspecific distance, which proves that the species exhibit obvious barcode gaps. In the Neighbor‐Joining trees, 20 species formed separate monophyletic branches. According to ABGD analysis, 660 sequences were categorized into 19 Operational Taxonomic Units, with Silurus sp. and S. asotus grouped into a single OTU. The Silurus in this study exhibits shared haplotypes and significant genetic divergence, suggesting the potential presence of cryptic species. Furthermore, the nucleotide diversity across all species fell below the threshold level, indicating that the local fish population is gradually declining. In conclusion, this study has demonstrated the effectiveness of DNA barcoding in identifying fish species in the Ili River Valley, providing valuable data to support the conservation of local fish resources.
Navigating the light and shadow of scientific publishing faced with machine learning and generative AI
Authors: Palmisani Federico , Segelcke Daniel , Vollert Jan 
Published: October 2024

AbstractBackgroundThe public release of ChatGPT in November 2022 sparked a boom and public interest in generative artificial intelligence (AI) that has led to journals and journal families hastily releasing generative AI policies, ranging from asking authors for acknowledgement or declaration to the outright banning of use.ResultsHere, we briefly discuss the basics of machine learning, generative AI, and how it will affect scientific publishing. We focus especially on potential risks and benefits to the scientific community as a whole and journals specifically.ConclusionWhile the concerns of editors, for example about manufactured studies, are valid, some recently implemented or suggested policies will not be sustainable in the long run. The quality of generated text and code is quickly becoming so high that it will not only be impossible to detect the use of generative AI but would also mean taking a powerful tool away from researchers that can make their life easier every day.SignificanceWe discuss the history and current state of AI and highlight its relevance for medical publishing and pain research. We provide guidance on how to act now to increase good scientific practice in the world of ChatGPT and call for a task force focusing on improving publishing pain research with use of generative AI.
Efficacy and safety of stiripentol in the prevention and cessation of status epilepticus: A systematic review
Authors: Specchio Nicola , Auvin Stéphane , Strzelczyk Adam , Brigo Francesco , Villanueva Vicente , Trinka Eugen 
Published: October 2024

AbstractStatus epilepticus (SE) is a life‐threatening emergency with high morbidity and mortality. In people with epilepsy, the management of SE is focused on early medical treatment. Stiripentol is a third‐generation antiseizure medication (ASM) approved for refractory generalized tonic–clonic seizures in Dravet syndrome. The aim of this systematic review was to evaluate the effectiveness and safety of stiripentol in reducing the incidence of SE in patients with Dravet syndrome or any epilepsy characterized by recurrent SE. The PubMed and Cochrane databases were systematically searched, and gray literature was hand‐searched. Search results were screened by title and abstract; studies with data on the effect of stiripentol on SE outcomes, including the cessation of SE, reduction in number of SE episodes, or reduction in hospitalizations, were included. Of 66 records identified, 17 studies were eligible for inclusion, of which 15 were human studies (n = 474; aged 1.1–78 years), and two were animal experiments. Results of retrospective or prospective observational studies showed that stiripentol as add‐on therapy to ASMs such as clobazam or valproate reduced the incidence of SE in patients with Dravet syndrome or other developmental and epileptic encephalopathies (DEEs). A mean of 68% of patients (range 41%–100%) had a ≥50% reduction in SE episodes from baseline, and 26%–100% of patients (mean 77%) became SE‐free after stiripentol initiation. Moreover, this review found stiripentol, used as acute treatment, may also be effective for the cessation of super‐refractory SE, but data are limited to three retrospective case series. Stiripentol was generally well‐tolerated. In conclusion, stiripentol reduces the incidence of SE episodes in patients with Dravet syndrome and potentially other DEEs, and it promotes cessation of super‐refractory SE in patients with and without a history of seizures.Plain Language SummaryStatus epilepticus (SE) is a life‐threatening, long‐lasting seizure occurring in patients with/without epilepsy. This article analyzed 15 published studies that investigated the effects and safety of the anti‐seizure medication stiripentol for preventing SE in epilepsy patients (prevention) or stopping an SE episode (cessation), and two animal studies that investigated how stiripentol works. In epilepsy patients, stiripentol halved the number of SE episodes in 41–100% of patients, 26–100% of patients became SE‐free, and stiripentol was considered to be well tolerated. In patients with/without epilepsy, stiripentol may stop the SE episode after other drugs like anesthetics have not worked.
Simultaneously planning of transmission line expansion and energy storage in order to maximize the capacity of wind farms
Authors: Nazeri Milad , Najafi Mojtaba , Hosseinpour Majid , Simab Mohsen 
Published: October 2024

AbstractThe speed of using renewable resources is expanding day by day. Renewable energy systems have many benefits for energy supply that do not include diesel, natural gas, or coal. Despite the many advantages, the use of renewable resources also includes basic challenges. With the presence of these sources, many technical issues must be considered in the network, the most important of which are voltage quality and network losses. The presence of these power plants can reduce fossil fuel costs and help reduce emissions. However, the high‐capacity connection of these types of power plants in the transmission networks despite the uncertainty may cause the congestion of transmission lines, increase losses and decrease voltage quality. Therefore, to reduce the need to build transmission lines, energy storage devices can be installed and energy can be stored and returned to the network in certain hours. The purpose of this paper is to build the maximum capacity of wind power plants in the transmission network in such a way that its profitability is guaranteed. For this purpose, in addition to considering the costs related to the power plant, the costs of storage devices and the construction of possible new lines have been considered. Also, improving the technical conditions of the network and reducing the maximum emission after installing these units is considered as a multiobjective function. The problem tested on the standard IEEE test transmission network and the results show that it is possible to determine the maximum profitable capacity of wind power plants.
Mechanical properties of gypsum mine rock around a strategic petroleum reserve (SPR) cavern under the crude oil seepage condition
Authors: Zhang Nan , Jia Qianjun , Lai Xingping , Zhang Yun , Ji Songtao , Yan Baoxu , Gu Helong 
Published: October 2024

AbstractAs China's demand for imported oil continues to grow, large‐scale oil storage facilities have become increasingly important. Currently, China primarily uses underground salt cavern spaces and newly excavated underground water‐sealed caverns for oil storage, which places high demands on the rock formations. China has abundant and widely distributed gypsum mineral resources, and utilizing abandoned gypsum mines for oil storage could not only turn waste into treasure by controlling underground space but also generate significant economic and social value. This article aims to systematically evaluate the mechanical properties of gypsum rock through long‐term immersion tests in crude oil to assess the impact of crude oil immersion on the mechanical performance of gypsum rock and explore the feasibility of using gypsum mines as long‐term stable oil storage caverns. The results show that oil immersion treatment reduces the uniaxial tensile strength of gypsum samples, but has little effect on their compressive strength and long‐term strength. From a mechanical performance perspective, it is feasible to use gypsum mine voids for crude oil storage.
CFD analysis of the impact of air gap width on Trombe wall performance
Authors: Friji Khaoula , Ghriss Ons , Bouabidi Abdallah , Cuce Erdem , Alshahrani Saad 
Published: October 2024

AbstractIn recent years, there has been a lot of research and debate on how solar energy can be used instead of conventional sources of heating to power residential heating. In this study, the Trombe wall (TW) technique, based on natural convection and energy storage, was examined to predict mass flow rate, temperature field, and velocity field for the TW system under steady conditions. A numerical simulation model was investigated for further validation using k‐ε turbulence and discrete ordinates (DO) radiation models. Independent grid studies were conducted to ensure that there were no changes after varying the grid numbers. The effect of the air gap was carried out to enhance TW thermal performance. CFD simulation shows good agreement with published data in the literature, and the optimum air gap was set at 0.1 m. The results pave the way for future studies to improve passive solar heating systems, which will eventually help move towards more sustainable residential heating solutions.
Experimental study on characteristics of gas seepage in broken coal and rock
Authors: Hao Dingyi , Tu Shihao , Zhang Lei , Zhao Hongbin , Xu Shikun 
Published: October 2024

AbstractThe characteristics of gas seepage in broken coal and rock composed of different particle sizes and grades were investigated in this study. On the basis of Darcy's law and non‐Darcy seepage theory, equations of gas permeability in the nonlinear seepage of broken coal and rock, as well as the porosity of broken coal and rock, under triaxial compression were determined. The stress loading path of gas seepage in broken coal and rock was developed. The characteristics of gas seepage in broken coal and rock composed of different particle sizes and grades were analyzed, and the results showed that the gas permeability after compression was proportional to the particle size of the broken coal and rock. Under triaxial compression, the gas permeability of the broken coal and rock composed of graded‐particle sizes was lower than that of the broken coal and rock composed of different single‐particle sizes. The gas permeability of the broken coal was lower than that of the broken rock mass, and the gas permeability and porosity of the broken coal and rock can be described by the exponential decay function. At a constant porosity, the gas permeability of the broken coal and rock was proportional to the size grading index under triaxial compression. The coefficient of viscosity and gravity of the flow are key factors influencing the flow permeability in broken coal and rock. This study provides a reference for on‐site practice such as the efficient extraction of gas in goafs.
Eco‐friendly ultrasonic‐assisted appraisal of herbal‐based yellow natural colorant for silk dyeing
Authors: Habib Noman , Adeel Shahid , Ibrahim Muhammad , Rehman Fazal‐ur , Naveed Muhammad , Ali Aamir , Mia Rony , Mansour Rym 
Published: October 2024

AbstractThe global recognition of eco‐friendly products like plant‐based dyes is escalating, driven by their exceptional biological and Ayurvedic attributes. This study isolates colorants from mango turmeric (Curcuma aromatica) using ultrasonic irradiation, supplemented with bio‐mordants to enhance color retention. Through the utilization of Response Surface Methodology and Central Composite Design, a technique that was optimized was completed to maximize coloring variables using statistical analysis. Results from 32 experimental runs reveal that optimal color depth (K/S = 19.399) was achieved with ultrasonic‐treated silk fabric (20 min exposure) using 65 mL of irradiated aqueous extract (20 min) with a pH of 5, supplemented with 1.5 g/100 mL salt of sodium chloride, maintained the temperature 75°C for the 45 min. Precoloring treatment with acacia, pomegranate, and pistachio extracts at specified concentrations enhanced colorfastness. Postdyeing, alterations in the concentrations of these extracts led to further improvements in colorfastness. Notably, adding Al+3 and Fe+2 salts, alongside tannic acid, exhibited notable effects in both pre‐ and postdyeing stages. While the colorfastness properties of unmordated silk fabric was lower than mordanted dyed silk fabric. Irradiation with ultrasonic waves significantly boosted the amount of dye that could be extracted from rhizomes of mango turmeric. Moreover, the application of bio and synthetic mordants in a strategic manner led to colorfastness ratings on silk fabric that ranged from excellent to satisfactory. This research underscores ultrasonic technologies and bio‐mordants' efficacy in sustainable dyeing processes, offering insights for developing eco‐friendly textile coloration methods.
Environmental impact assessment of alternative technologies for production of biofuels from spent coffee grounds
Authors: Kisiga Wilberforce , Chetty Manimagalay , Rathilal Sudesh 
Published: October 2024

AbstractIn the strategy to combat climate change that has been caused by the world's overdependence on fossil fuels, current research is focusing on the decarbonisation of the energy sector through the production of renewable cleaner energy, such as biofuels. Spent coffee grounds (SCGs), the waste stream of the coffee brewing industry, are a potential feedstock for the production of valuable products, including biofuels. However, the environmental implications for the valorisation of this valuable waste need to be investigated. This study assesses the environmental impacts of six biomass‐to‐fuel processing technologies using SCGs as a feedstock, with the aim of identifying the most environmentally friendly technology. A cradle‐to‐gate life‐cycle assessment (LCA) was conducted on fast pyrolysis, fermentation, anaerobic digestion (AD), hydrothermal liquefaction (HTL), gasification, and biodiesel production. The mass and energy balances obtained from Aspen Plus simulations served as the life‐cycle inventory data. Using the ReCiPe 2016 midpoint (H) and Eco‐Indicator 99 as the assessment methods, potential environmental impacts were calculated in OpenLCA software. Electricity generation and carbon dioxide emissions were the biggest contributors of environmental impacts. For each category, the maximum result was set to 100% and the results of the other variants were displayed in relation to this result. AD, with the smallest total weighted score (160), was the most environmentally friendly biomass‐to‐fuel processing route, while HTL, with the biggest total weighted score (893), was the worst. A sensitivity analysis indicated that the environmental performance of biofuel production from SCGs was highly influenced by energy input flows and the source of energy generation.
A Multifrequency Data Fusion Deep Learning Model for Carbon Price Prediction
Authors: Xiao Canran , Liu Yongmei 
Published: October 2024

ABSTRACTIn response to the global need for effective management of carbon emissions and alignment with sustainable development goals, predicting carbon trading prices accurately is critical. This study introduces a multifrequency data fusion carbon price prediction model (MFF‐CPPM), addressing the nonlinear characteristics of carbon trading prices and inconsistent feature factor frequencies. The MFF‐CPPM consists of a feature‐extraction frontend, a multifrequency data fusion transformer, and a fusion regression layer, offering a novel methodological approach in forecasting studies. The model's validity was tested in Guangdong, China's largest carbon trading pilot market. The results demonstrated that the MFF‐CPPM outperformed baseline models in terms of carbon price‐prediction accuracy and trend forecasting. Additional trials conducted in Hubei and Beijing confirmed the model's robustness and generalization capabilities, providing valuable evidence of its effectiveness and reliability across varying market contexts. This study presents a novel predictive model for carbon trading prices, with a unique capability to harness data at differing frequencies. The MFF‐CPPM not only enhances forecasting accuracy but also offers an innovative approach to effectively incorporate multifrequency information. This advancement paves the way for flexible forecasting models in any scenario where data arrive at differing frequencies.