bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anthropogenic effects on tropical cyclones near Western Europe
Authors: Wang Shuai , Murakami Hiroyuki , Cooke William 
Published: July 2024

AbstractThere is less consensus on whether human activities have significantly altered tropical cyclone (TC) statistics, given the relatively short duration of reliable observed records. Understanding and projecting TC frequency change is more challenging in certain coastal regions with lower TC activity yet high exposure, such as Western Europe. Here, we show, with large-ensemble simulations, that the observed increase in TC frequency near Western Europe from 1966 to 2020 is likely linked to the anthropogenic aerosol effect. Under a future scenario featuring regionally controlled aerosol emissions and substantially increased greenhouse gas concentrations (Shared Socioeconomic Pathway 5-85), our simulations show a potential decrease in TC frequency near Western Europe by the end of the 21st century. These contrasting trends in historical and future TC frequencies are primarily due to the rise for 1966–2020 and potentially subsequent fall for 2030–2100 in TC genesis frequency in the North Atlantic. The response of large-scale environmental conditions to anthropogenic forcing is found to be crucial in explaining the historical and future changes in TC frequency near Western Europe.
Secrets of DNA-PKcs beyond DNA repair
Authors: Camfield Sydney , Chakraborty Sayan , Dwivedi Shailendra Kumar Dhar , Pramanik Pijush Kanti , Mukherjee Priyabrata , Bhattacharya Resham 
Published: July 2024

AbstractThe canonical role of the DNA-dependent protein kinase catalytic subunit (DNA-PKcs) in repairing DNA double-strand breaks combined with its reported dysregulation in several malignancies has driven the development of DNA-PKcs inhibitors as therapeutics. However, until recently the relationship between DNA-PKcs and tumorigenesis has been primarily investigated with regard to its role in non-homologous end joining (NHEJ) repair. Emerging research has uncovered non-canonical DNA-PKcs functions involved with transcriptional regulation, telomere maintenance, metabolic regulation, and immune signaling all of which may also impinge on tumorigenesis. This review mainly discusses these non-canonical roles of DNA-PKcs in cellular biology and their potential contribution to tumorigenesis, as well as evaluating the implications of targeting DNA-PKcs for cancer therapy.
Ultrahigh-nickel layered cathode with cycling stability for sustainable lithium-ion batteries
Authors: Yang Tonghuan , Zhang Kun , Zuo Yuxuan , Song Jin , Yang Yali , Gao Chuan , Chen Tao , Wang Hangchao , Xiao Wukun , Jiang Zewen , Xia Dingguo 
Published: July 2024

AbstractNickel-rich layered transition metal oxides are leading cathode candidates for lithium-ion batteries due to their increased capacity, low cost and enhanced environmental sustainability compared to cobalt formulations. However, the nickel enrichment comes with larger volume change during cycling as well as reduced oxygen stability, which can both incur performance degradation. Here we show an ultrahigh-nickel cathode, LiNi0.94Co0.05Te0.01O2, that addresses all of these critical issues by introducing high valent tellurium cations (Te6+). The as-prepared material exhibits an initial capacity of up to 239 milliampere-hours (mAh) per gram and an impressive capacity retention of 94.5% after 200 cycles. The resulting Ah-level lithium metal battery with silicon-carbon anode achieves an extraordinary monomer energy density of 404 watt-hours (Wh) per kilogram with retention of 91.2% after 300 cycles. Advanced characterizations and theoretical calculations show that the introduction of tellurium serves to engineer the particle morphology for a microstructure to better accommodate the lattice strain and enable an intralayer Te–Ni–Ni–Te ordered superstructure, which effectively tunes the ligand energy-level structure and suppresses lattice oxygen loss. This work not only advances the energy density of nickel-based lithium-ion batteries into the realm of 400 Wh kg−1 but suggests new opportunities in structure design for cathode materials without trade-off between performance and sustainability.
Mediodorsal thalamus and ventral pallidum contribute to subcortical regulation of the default mode network
Authors: Zhao Yilei , Kirschenhofer Tobias , Harvey Michael , Rainer Gregor 
Published: July 2024

AbstractHumans and other animals readily transition from externally to internally focused attention, and these transitions are accompanied by activation of the default mode network (DMN). The DMN was considered a cortical network, yet recent evidence suggests subcortical structures are also involved. We investigated the role of ventral pallidum (VP) and mediodorsal thalamus (MD) in DMN regulation in tree shrew, a close relative of primates. Electrophysiology and deep learning-based classification of behavioral states revealed gamma oscillations in VP and MD coordinated with gamma in anterior cingulate (AC) cortex during DMN states. Cross-frequency coupling between gamma and delta oscillations was higher during DMN than other behaviors, underscoring the engagement of MD, VP and AC. Our findings highlight the importance of VP and MD in DMN regulation, extend homologies in DMN regulation among mammals, and underline the importance of thalamus and basal forebrain to the regulation of DMN.
DNA language model GROVER learns sequence context in the human genome
Authors: Sanabria Melissa , Hirsch Jonas , Joubert Pierre M. , Poetsch Anna R. 
Published: July 2024

AbstractDeep-learning models that learn a sense of language on DNA have achieved a high level of performance on genome biological tasks. Genome sequences follow rules similar to natural language but are distinct in the absence of a concept of words. We established byte-pair encoding on the human genome and trained a foundation language model called GROVER (Genome Rules Obtained Via Extracted Representations) with the vocabulary selected via a custom task, next-k-mer prediction. The defined dictionary of tokens in the human genome carries best the information content for GROVER. Analysing learned representations, we observed that trained token embeddings primarily encode information related to frequency, sequence content and length. Some tokens are primarily localized in repeats, whereas the majority widely distribute over the genome. GROVER also learns context and lexical ambiguity. Average trained embeddings of genomic regions relate to functional genomics annotation and thus indicate learning of these structures purely from the contextual relationships of tokens. This highlights the extent of information content encoded by the sequence that can be grasped by GROVER. On fine-tuning tasks addressing genome biology with questions of genome element identification and protein–DNA binding, GROVER exceeds other models’ performance. GROVER learns sequence context, a sense for structure and language rules. Extracting this knowledge can be used to compose a grammar book for the code of life.
Tracking the dynamics of catalytic Pt/CeO2 active sites during water-gas-shift reaction
Authors: Li Gengnan , Zakharov Dmitri N. , Hu Tianhao , Yu Youngseok , Waluyo Iradwikanari , Hunt Adrian , Head Ashley R. , Boscoboinik Jorge Anibal 
Published: July 2024

AbstractUnderstanding the atomistic structure of the active site during catalytic reactions is of paramount importance in both fundamental studies and practical applications, but such studies are challenging due to the complexity of heterogeneous systems. Here, we use Pt/CeO2 as an example to study the dynamic nature of active sites during the water-gas-shift reaction (WGSR) by combining multiple in situ characterization tools. We show that the different concentrations of interfacial Ptδ+ – O – Ce4+ moieties at Pt/CeO2 interfaces are responsible for the rank of catalytic performance of Pt/CeO2 catalysts: Pt/CeO2-rod > Pt/CeO2-cube > Pt/CeO2-oct. For all the catalysts, metallic Pt is formed during the WGSR, leading to the transformation of the active sites to Pt0 – Ov – Ce3+ and interface reconstruction. These findings shed light on the nature of the active site for the WGSR on Pt/CeO2 and highlight the importance of combining complementary in situ techniques for establishing structure-performance relationships.
The increasing water stress projected for China could shift the agriculture and manufacturing industry geographically
Authors: Liu Mengyu , Zhou Xiong , Huang Guohe , Li Yongping 
Published: July 2024

AbstractThe sustainable development of China has been challenged by the misalignment of water demand and supply across regions under varying climate change scenarios. Here we develop a water stress prediction index using a fuzzy decision-making approach, which analyzes spatiotemporal variations of water stress and concomitant effects on the populace within China. Our results indicate that water stress will increase from 2020 to 2099 under both low and high emission scenarios, primarily due to decreased water supplies like surface runoff and snow water content. Seasonal analysis reveals that annual fluctuations in water stress are mainly driven by changes in spring and autumn. Water stress is projected to be considerably lower in southeastern provinces compared to northwestern ones, where, on average, over 20% of the Chinese population could be severely impacted. These changes in water stress could lead to the north-to-south migration of the agriculture sector, manufacturing sector, and human population.
Alpine wetlands degradation leads to soil nutrient imbalances that affect plant growth and microbial diversity
Authors: Xu Ganjun , Kang Xiaoming , Wang Fei , Zhuang Weirong , Yan Wende , Zhang Kerou 
Published: July 2024

AbstractAlpine wetlands degrade rapidly due to climate change and human activities. Studying degradation effects on flora, soil, and microbes, and their mechanisms, can aid wetland management and global carbon dynamic insights. Here, we conducted transect surveys across various levels of degradation in the Qinghai-Tibet Plateau, ranging from non-degraded to severely degraded alpine wetlands. Severe degradation reduced aboveground biomass by 72.5%. As degradation intensified, the abundance of high-quality forage plants, especially Cyperaceae, gradually declined. Degradation resulted in soil nutrient deficiencies and stoichiometric imbalances, which significantly affected plant growth and soil microbial diversity. These changes ultimately led to a decline in carbon sequestration. The diversity of microbial and plant communities’ response to degradation aligned with the “intermediate interference hypothesis.” The altered bacterial community composition, which favors oligotrophic dominance, and its nonlinear response to soil stoichiometry and pH, could explain the maintenance of diversity and species richness of microbial communities under intermediate disturbance.
Do climate acts of EU countries enable the most vulnerable to participate in climate policymaking?
Authors: Honkonen Tuula 
Published: July 2024

AbstractOne way to give recognition to and account for vulnerability in climate policymaking is enhanced public participation. This study examines national climate acts across the EU Member States from this perspective, paying particular attention to those members of the public who are considered most climate vulnerable. The analysis finds that few of the acts address public participation, and none of the acts examined directly provides for the participation of specified groups of people based on their presumed vulnerability to climate change impacts. There are, however, participation mechanisms that take into account climate vulnerable groups. Yet, many states have not regarded the national climate act as the legal instrument of choice for regulating public participation in climate policymaking. However, this paper argues that the institutionalization of public participation in the national climate acts would have added value.
Resilient microgrid formation considering communication interruptions
Authors: Zhong Jian , Chen Chen , Kim Young‐Jin , Huang Yuxiong , Teng Mengjie , Bian Yiheng , Bie Zhaohong 
Published: July 2024

AbstractDistribution system (DS) communication failures following extreme events often degrade monitoring and control functions, thus preventing the acquisition of complete global DS component state information, on which existing post‐disaster DS restoration methods are based. This paper proposes methods of inferring the states of DS components in the case of incomplete component state information. By using the known DS information, the operating states of unobservable DS branches and buses can be inferred, providing complete information for DS performance restoration before full communication recovery.
Unambiguous acquisition algorithm based on sub‐correlation functions combination for semi‐integer CPM signals
Authors: Xie Mingming , Xue Rui 
Published: July 2024

AbstractDue to the nonlinear nature of continuous phase modulation (CPM), most existing unambiguous acquisition algorithms are ineffective in eliminating the ambiguity threat faced by semi‐integer CPM signals. To address this issue, this letter proposes an unambiguous acquisition algorithm based on sub‐correlation functions combination (SCFC). The main idea of this algorithm is to decompose the first pulse amplitude modulation waveform derived from the Laurent decomposition into sub‐signal waveforms that are appropriate for CPM signals. The final unambiguous function is obtained by combining the autocorrelation function of the received CPM signal with the sub‐correlation functions derived from the sub‐signal waveforms and the received CPM signal. Simulation results demonstrate that the SCFC algorithm can eliminate the ambiguity threat of semi‐integer CPM signals with relatively minor detection loss. Moreover, the proposed algorithm successfully retains a narrow main peak and exhibits superior multipath resistance.
Reinforcement learning layout‐based optimal energy management in smart home: AI‐based approach
Authors: Afroosheh Sajjad , Esapour Khodakhast , Khorram‐Nia Reza , Karimi Mazaher 
Published: July 2024

AbstractThis research addresses the pressing need for enhanced energy management in smart homes, motivated by the inefficiencies of current methods in balancing power usage optimization with user comfort. By integrating reinforcement learning and a unique column‐and‐constraint generation strategy, the study aims to fill this gap and offer a comprehensive solution. Furthermore, the increasing adoption of renewable energy sources like solar panels underscores the importance of developing advanced energy management techniques, driving the exploration of innovative approaches such as the one proposed herein. The constraint coordination game (CCG) method is designed to efficiently manage the power usage of each appliance, including the charging and discharging of the energy storage system. Additionally, a deep learning model, specifically a deep neural network, is employed to forecast indoor temperatures, which significantly influence the energy demands of the air conditioning system. The synergistic combination of the CCG method with deep learning‐based indoor temperature forecasting promises significant reductions in homeowner energy expenses while maintaining optimal appliance performance and user satisfaction. Testing conducted in simulated environments demonstrates promising results, showcasing a 12% reduction in energy costs compared to conventional energy management strategies.
Mutual inductance parameter measurement and experimental research of double circuit based on different frequency method
Authors: Lei Zeyang , Zhang Xiaojun , Zhuang Wenbing , Liu Wei , Wu Suzhou , Qi Siyi 
Published: July 2024

AbstractIn order to improve the measurement accuracy of mutual inductance parameters of transmission lines in the environment of double circuit power lines without power outage, this paper establishes simulation models for measuring mutual inductance parameters of transmission lines using the different frequency method in two modes: equal and unequal zero sequence self‐parameters of two circuit lines, using a parallel zero sequence coupling model of double circuit power lines. In the article, simulation analysis is conducted on the line parameters with a coupling coefficient between 0.4 and 0.6 and a line length of 20–50 km. In order to further verify the correctness of the simulation model and measurement methods, a test bench was established based on the principle of line mutual inductance parameter testing in a laboratory dual circuit line without a power outage environment for experimental testing. By comparing the test values under experimental conditions with the standard values, it has been proven that the model and method can meet the actual measurement requirements of engineering.
Robust distributed observer for uncertain systems
Authors: Tatafi Saeid Eslahi , Ataei Mohammad , Ekramian Mohsen 
Published: July 2024

AbstractThis paper proposes a robust distributed observer for uncertain systems where some unknown, unstructured, and bounded uncertainties exist in system matrices. In distributed observer, each node includes an observer which directly estimates a part of the system states by its limited measurements and further, the estimation of other states indirectly obtains via exchanging information with neighbouring nodes. It is shown that whole states convergence achieves if the LTI system is observable as well as the network graph is strongly connected. Also, in the proposed distributed observer, by applying a new term in dynamic equation, the robust performance is achieved in dealing with uncertainties in system matrices. The observer gains synthesis is then formulated in terms of linear matrix inequalities. Finally, the simulation results are presented to illustrate the effectiveness of the proposed distributed observer to handle system uncertainties.
Investigating the nature of the 2.4 h-period eclipsing cataclysmic variable W2 in 47 Tuc
Authors: Amato R. , La Palombara N. , Imbrogno M. , Israel G. L. , Esposito P. , de Martino D. , Webb N. A. , Iaria R. 
Published: July 2024

Context. W2 (CXOGlb J002415.8–720436) is a cataclysmic variable (CV) in the Galactic globular cluster 47 Tucanae. Its modulation was discovered within the CATS@BAR project. The source shows all the properties of magnetic CVs, but whether it is a polar or an intermediate polar is still a matter of debate.
Aims. This paper investigates the spectral and temporal properties of the source, using all archival X-ray data from Chandra and eROSITA Early Data Release, to establish whether the source falls within the category of polars or intermediate polars.
Methods. We fitted Chandra archival spectra with three different models: a power law, a bremsstrahlung and an optically thin thermal plasma. We also explored the temporal properties of the source with searches for pulsations with a power spectral density analysis and a Rayleigh test (Zn2).
Results. W2 displays a mean luminosity of ∼1032 erg s−1 over a 20-year span, despite lower values in a few epochs. The source is not detected in the latest observation, taken with Chandra in 2022, and we infer an X-ray luminosity ≤7 × 1031 erg s−1. The source spectral shape does not change over time and can be equally well fitted with each of the three models, with a best-fit photon index of 1.6 for the power law and best-fit temperatures of 10 keV for both the bremsstrahlung and the thermal plasma models. We confirm the previously detected period of 8649 s, ascribed to the binary orbital period, and found a cycle-to-cycle variability associated with this periodicity. No other significant pulsation is detected.
Conclusions. Considering the source orbital period, luminosity, spectral characteristics, long-term evolution and strong cycle-to-cycle variability, we suggest that W2 is a magnetic CV of the polar type.
TESS observations of non-Be fast rotators
Authors: Nazé Yaël , Britavskiy Nikolay , Labadie-Bartz Jonathan 
Published: July 2024

Context. The variability of fast-rotating Oe/Be stars has been reported in detail in recent years. However, much less is known about the behaviour of fast-rotating OB stars without known decretion disks, and hence it is difficult to identify the commonalities and differences in the photometric variability of these two populations, especially with regards to their pulsational properties and their link with the presence of circumstellar material.
Aims. Via an in-depth literature search, we identified a set of fast-rotating (vsin(i) > 200 km s−1) early B-type stars not known to have disks. TESS and Kepler light curves were built for 58 stars that appear isolated (no bright neighbour within 1′ and no known companion) to avoid contamination of the light curves. Frequency spectra were calculated and then analysed to determine the noise level and the presence of significant signals above the noise.
Methods. Red noise is detected in all targets, without obvious correlations between noise and stellar parameters. Long-term changes are much less frequent than in Be stars, with only 12% of our targets having the variability below 0.5 d−1 dominating their frequency spectrum. In contrast, strong frequency groups are detected in about a third of targets, as in Be stars. These groups generally occur in pairs with harmonic frequencies, as is usually seen in Be stars, but with the first group more often displaying larger amplitudes. Finally, the most frequent variability is due to isolated frequencies in the 0.5–6. d−1 range (which is found in two-thirds of cases and dominates the spectra in 42% of the sample). Higher-frequency signals (up to 40 d−1) are sometimes also detected but rarely (only 12% of stars) appear as the strongest ones of the frequency spectra. Overall, fast-rotating B-type stars, with or without disks, display similar photometric properties, except as regards their longer-term behaviour.
Cocoa Butter: Evolution from Natural Food Ingredient to Pharmaceutical Excipient and Drug Delivery System
Authors: Loke Ying Hui , Phang Hiu Ching , Mohamad Najwa , Kee Phei Er , Chew Yik-Ling , Lee Siew-Keah , Goh Choon Fu , Yeo Chien Ing , Liew Kai Bin 
Published: July 2024

AbstractFor decades, cocoa butter has been extensively used in food industries, particularly in the production of chocolate confectioneries. The composition of fats within cocoa butter, such as stearic acid, palmitic acid, and oleic acid, determines its properties. Studies have indicated the existence of at least six polymorphic forms of cocoa butter, each possessing distinct characteristics and melting points. Recently, cocoa butter has garnered attention for its potential as a delivery system for pharmaceutical products. This review thoroughly explores cocoa butter, encompassing its production process, composition, properties, and polymorphism. It delves into its diverse applications across various industries including food, cosmetics, and pharmaceuticals. Additionally, the review investigates cocoa butter alternatives aiming to substitute cocoa butter and their roles in different drug delivery systems. The unique properties of cocoa butter have sparked interest in pharmaceutical
industries, particularly since its introduction as a drug delivery system and excipient. This has prompted researchers and industry stakeholders to explore novel formulations and delivery methods, thereby expanding the range of options available to consumers in the pharmaceutical market.