bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanistic insights into vascular biology via methyltransferase-like 3-driven N6-adenosine methylation of RNA
Authors: Zhang Deshuang , Gou Zhixian , Qu Yi , Su Xiaojuan
Published: January 2025

Recent advancements in the mechanistic comprehension of vascular biology have concentrated on METTL3-mediated N6-methyladenosine modification of RNA, which modulates a spectrum of RNA functionalities with precision. Despite extensive investigations into the roles and mechanisms of METTL3 within vascular biology, a holistic review elucidating their interconnections remains absent. This analysis endeavors to meticulously scrutinize the involvement of METTL3 in both the physiological and pathological paradigms of vascular biology. The findings of this review indicate that METTL3 is indispensable for vascular development and functionality, predominantly through its regulatory influence on pericytes, endothelial cells, vascular smooth muscle cells, and hematopoietic stem cells. Conversely, aberrant METTL3 activity is implicated as a risk factor, diagnostic biomarker, and therapeutic target for vascular pathologies. This comprehensive review offers an exhaustive synthesis of METTL3’s role in vascular biology, addressing existing knowledge gaps and serving as an essential reference for future research and potential clinical applications.
A phase-transited lysozyme coating doped with strontium on titanium surface for bone repairing via enhanced osteogenesis and immunomodulatory
Authors: Zhang Yu , Chen Yu , Shi Yidan , Hu Hongkun , Dai Zhongyu , Liu Zhichen , Li Xuanan
Published: January 2025

Introduction

Titanium is currently recognized as an excellent orthopedic implant material, but it often leads to poor osseointegration of the implant, and is prone to aseptic loosening leading to implant failure. Therefore, biofunctionalization of titanium surfaces is needed to enhance their osseointegration and immunomodulation properties to reduce the risk of implant loosening. We concluded that the utilization of PTL-Sr is a direct and effective method for the fabrication of multifunctional implants.

Methods

In this Study, phase-transited lysozyme (PTL) is deposited onto the surface of titanium (Ti) to construct a functional coating and strontium chloride solution was utilized to produce PTL coatings with Sr2+. The characterization of the strontium-doped PTL coatings (PTL-Sr) was tested by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and inductively coupled plasma atomic emission spectroscopy (ICP-AES). A series of cell and animal experiments were conducted to investigate the biological functions of PTL-Sr coatings.

Results

The characterization indicates the successful preparation of PTL-Sr coatings. In vitro cellular experiments have demonstrated that it promotes M2 macrophage polarization and reduces inflammatory mediator production while promoting osteogenic differentiation of bone merrow mesenchymal stem cells (BMSCs). The in vivo subcutaneous implantation model demonstrated its good immunomodulatory and angiogenic properties.

Discussion

Titanium with PTL-Sr coatings promote biomineralization and immunomodulation, which is suitable for orthopedic applications. Further mechanistic exploration and studies using animal models is necessary to enhance the understanding of the clinical applicability of modified titanium.
Surface characteristics and molecular interactions of thin films between bubbles by molecular simulations
Authors: Peng Tiefeng , Huai Yangyang
Published: January 2025

Introduction

Whether in industrial production or daily life, froth plays an important role in many processes. Sometimes, froth exists as a necessity and is also regarded as the typical characteristic of products, e.g., froth on shampoo. Froth often makes an important contribution to product performance, such as in cleaning operations. On the other hand, froth may destroy the production process, such as in the textile and paper industry. Another example, ultra-stable froth accumulates on the thickener from flotation brings a series of difficulties to pumping, settling and dewatering operations, and would lead to pollution to the industrial circulating water treatment, thus it must be prevented.

Methods

In this work, the factors affecting the stability of froth, and relationship of bubble coalescence and film rupture was investigated, and molecular simulations (MD) were performed to study the aqueous molecular formation and surface characteristics of thin films between bubbles that contribute to the froth stability.

Results

The detailed interfacial structure, molecular formation along Z-axis, angle distribution within the first and second layer, and also critical thickness were studied and discussed. The film rupture was validated and interpreted by the water-water interactions within the thin film, and these surface interactions were also examined using binding energy, dipole autocorrelation function (DAF). These simulations explicitly utilize polarizable potential model, incorporating many-body interactions, in which induced polarization plays a critical role in reproducing experimental observables and understanding physical behavior.

Discussion

The results provide beneficial insight for ultra-stable removal from microscopic view, and have direct benefits in dissolved air flotation used in mining industry, to develop efficient and sustainable processes for industries to minimize water and chemical usage.
Human milk oligosaccharides: bridging the gap in intestinal microbiota between mothers and infants
Authors: Sun Wen , Tao Lin , Qian Chen , Xue Pei-pei , Du Si-si , Tao Ying-na
Published: January 2025

Breast milk is an essential source of infant nutrition. It is also a vital determinant of the structure and function of the infant intestinal microbial community, and it connects the mother and infant intestinal microbiota. Human milk oligosaccharides (HMOs) are a critical component in breast milk. HMOs can reach the baby’s colon entirely from milk and become a fermentable substrate for some intestinal microorganisms. HMOs can enhance intestinal mucosal barrier function and affect the intestinal function of the host through immune function, which has a therapeutic effect on specific infant intestinal diseases, such as necrotizing enterocolitis. In addition, changes in infant intestinal microbiota can reflect the maternal intestinal microbiota. HMOs are a link between the maternal intestinal microbiota and infant intestinal microbiota. HMOs affect the intestinal microbiota of infants and are related to the maternal milk microbiota. Through breastfeeding, maternal microbiota and HMOs jointly affect infant intestinal bacteria. Therefore, HMOs positively influence the establishment and balance of the infant microbial community, which is vital to ensure infant intestinal function. Therefore, HMOs can be used as a supplement and alternative therapy for infant intestinal diseases.
Human-AI collaboration is not very collaborative yet: a taxonomy of interaction patterns in AI-assisted decision making from a systematic review
Authors: Gomez Catalina , Cho Sue Min , Ke Shichang , Huang Chien-Ming , Unberath Mathias
Published: January 2025

Leveraging Artificial Intelligence (AI) in decision support systems has disproportionately focused on technological advancements, often overlooking the alignment between algorithmic outputs and human expectations. A human-centered perspective attempts to alleviate this concern by designing AI solutions for seamless integration with existing processes. Determining what information AI should provide to aid humans is vital, a concept underscored by explainable AI's efforts to justify AI predictions. However, how the information is presented, e.g., the sequence of recommendations and solicitation of interpretations, is equally crucial as complex interactions may emerge between humans and AI. While empirical studies have evaluated human-AI dynamics across domains, a common vocabulary for human-AI interaction protocols is lacking. To promote more deliberate consideration of interaction designs, we introduce a taxonomy of interaction patterns that delineate various modes of human-AI interactivity. We summarize the results of a systematic review of AI-assisted decision making literature and identify trends and opportunities in existing interactions across application domains from 105 articles. We find that current interactions are dominated by simplistic collaboration paradigms, leading to little support for truly interactive functionality. Our taxonomy offers a tool to understand interactivity with AI in decision-making and foster interaction designs for achieving clear communication, trustworthiness, and collaboration.
Prognostic nutritional index as a predictor of cardiovascular and all-cause mortality in American adults with hypertension: results from the NHANES database
Authors: Tang Jing , Yang Long , Yang Guan-Ying , Li Yan-Hong , Zhu You-Sen , Li Hui , Gao Xiao-Ming
Published: January 2025

Background

Few studies have examined the relationship between nutritional status, as assessed by the Prognostic Nutrition Index (PNI), and incident cardiovascular mortality and all-cause mortality, particularly in hypertensive patients. This study aimed to examine the association between PNI and cardiovascular mortality and all-cause mortality in Americans with hypertension.

Methods

Data from this retrospective cohort study were obtained from the National Health and Nutrition Examination (NHANES) 1999–2016. Using data of The NHANES Public-Use Linked Mortality Files to assess all-cause mortality (ACM) and cardiovascular mortality (CVM). After excluding participants younger than 18 years, without hypertension, and with missing follow-up data, a total of 18,189 cases were included in this study. Persons with hypertension were divided by PNI into 4 groups: Q1 (PNI < 49.0), Q2 (PNI: 49.0–52.5), Q3 (PNI: 52.5–55.5), and Q4 (PNI > 55.5). We used the Cox proportional hazard regression model to explore the predictive role of PNI on ACM and CVM in American adults with hypertension. Restricted cubic spline (RCS) curves to investigate the existence of a dose-response linear relationship between them.

Result

During a median follow-up period of 89 months, a total of 1,444 (7.94%) cardiovascular deaths occurred and 5,171 (28.43%) all-cause deaths occurred. Multifactorial COX regression analysis showed all-cause mortality [hazard ratio (HR): 0.584, 95% CI: 0.523–0.652, p < 0.001] and cardiovascular mortality (HR: 0.435, 95% CI: 0.349–0.541, p < 0.001) associated with Q4 group risk of malnutrition in PNI compared to Q1 group. RCS curves showed a nonlinear relationship between PNI and all-cause mortality and cardiovascular mortality (both non-linear p < 0.001).

Conclusions

Lower PNI levels are associated with mortality in patients with hypertension. PNI may be a predictor of all-cause mortality and cardiovascular mortality risk in patients with hypertension.
Cardioattentionnet: advancing ECG beat characterization with a high-accuracy and portable deep learning model
Authors: He Youfu , Zhou Yu , Qian Yu , Liu Jingjie , Zhang Jinyan , Liu Debin , Wu Qiang
Published: January 2025

Introduction

The risk of mortality associated with cardiac arrhythmias is considerable, and their diagnosis presents significant challenges, often resulting in misdiagnosis. This situation highlights the necessity for an automated, efficient, and real-time detection method aimed at enhancing diagnostic accuracy and improving patient outcomes.

Methods

The present study is centered on the development of a portable deep learning model for the detection of arrhythmias via electrocardiogram (ECG) signals, referred to as CardioAttentionNet (CANet). CANet integrates Bi-directional Long Short-Term Memory (BiLSTM) networks, Multi-head Attention mechanisms, and Depthwise Separable Convolution, thereby facilitating its application in portable devices for early diagnosis. The architecture of CANet allows for effective processing of extended ECG patterns and detailed feature extraction without a substantial increase in model size.

Results

Empirical results indicate that CANet outperformed traditional models in terms of predictive performance and stability, as confirmed by comprehensive cross-validation. The model demonstrated exceptional capabilities in detecting cardiac arrhythmias, surpassing existing models in both cross-validation and external testing scenarios. Specifically, CANet achieved high accuracy in classifying various arrhythmic events, with the following accuracies reported for different categories: Normal (97.37 ± 0.30%), Supraventricular (98.09 ± 0.25%), Ventricular (92.92 ± 0.09%), Atrial Fibrillation (99.07 ± 0.13%), and Unclassified arrhythmias (99.68 ± 0.06%). In external evaluations, CANet attained an average accuracy of 94.41%, with the area under the curve (AUC) for each category exceeding 99%, thereby demonstrating its substantial clinical applicability and significant advancements over traditional models.

Discussion

The deep learning model proposed in this study has the potential to enhance the accuracy of early diagnosis for various types of arrhythmias. Looking ahead, this technology is anticipated to provide improved medical services for patients with heart disease through continuous, non-invasive monitoring and timely intervention.
Effects of dapagliflozin on heart rate variability, cardiac function, and short-term prognosis in early-onset post-myocardial infarction heart failure
Authors: Zhou Le , Niu Mingyuan , Chen Wei , Hu Qian , Chen Yi , Geng Xiaohong , Gu Jiani
Published: January 2025

Objective

To investigate the effects of dapagliflozin, in addition to standard therapy, on heart rate variability (HRV), soluble growth stimulation expressed gene 2 protein (sST2), N-terminal pro B-type natriuretic peptide (NT-proBNP), and echocardiographic parameters in patients with early-onset post-myocardial infarction heart failure (HF).

Methods

A total of 98 patients with early-onset post-myocardial infarction HF were enrolled and randomly divided into a control group (n = 48, receiving standard therapy) and an observation group (n = 50, receiving standard therapy plus dapagliflozin 10 mg daily). HRV, cardiac function, and echocardiographic parameters were measured at baseline and after 24 weeks of treatment. Short-term prognosis and adverse events were also monitored.

Results

Compared with the control group, the observation group showed significantly greater improvements in SDNN and SDANN (P < 0.05). Significant improvements were also observed in sST2 and NT-proBNP levels in the observation group compared to the control group (P < 0.05). Additionally, echocardiographic parameters, including EF, LVESD, LVEDD, IVST, LVMI, and E/e’, showed greater improvement in the observation group (P < 0.05). The incidence of major adverse cardiovascular events was lower in the observation group (P < 0.05). Multivariate logistic regression model revealed that dapagliflozin use was independently associated with a reduced risk of MACE (OR = 0.265, 95% CI: 0.097–0.724, P = 0.010).

Conclusion

Early administration of dapagliflozin 10 mg, in addition to standard therapy, can improve autonomic function, cardiac function, and short-term prognosis in patients with early-onset post-myocardial infarction heart failure.
Male-assisted training and injury patterns: hypergraph-enhanced analysis of injuries in women’s water polo
Authors: Feng Xuehui , Wang Zhibin , Wang Zheng , He Chen , Xun Hongxing , Chen Yuanfa , Ding Jie , Chen Gen , Liu Zhe
Published: January 2025

Introduction

The aim of this study is to compare the injury patterns of female water polo players before and after the implementation of the Male-Assisted Female Training (MAFT) program. The study seeks to identify key factors influencing these changes and propose corresponding injury prevention measures.

Methods

We utilized pattern analysis and classification techniques to explore the injury data. A Hypergraph Neural Network (HGNN) was employed for pattern extraction, where each athlete was represented as a node in a hypergraph, with node dimensions capturing high-order relational embedding information. We applied the graph Laplacian operator to aggregate neighborhood features and visualize structural and feature differences in hypergraphs based on different influencing factors. Additionally, we introduced graph structure regularization to improve classification accuracy and prevent overfitting in the relatively small dataset, enhancing our ability to identify critical factors affecting injury types.

Results

The analysis revealed significant differences in injury patterns before and after the MAFT program, with specific influencing factors being identified through both pattern recognition and classification techniques. The classification models, supported by graph structure regularization, achieved improved accuracy in distinguishing key features that contributed to changes in injury types.

Discussion

These findings provide insights into the critical factors influencing injury patterns in female water polo players and highlight the effectiveness of the MAFT program in mitigating certain injury risks. Based on the identified features, we propose targeted preventive measures to reduce injury incidence, particularly in relation to changes brought about by the MAFT training mode. Further research is needed to refine these measures and explore their long-term effectiveness.
Description of the root anatomy of the primary molars using high resolution computed microtomography (Micro-CT). An analysis of three-dimensional root canal system
Authors: Vidi Benedetta , Gil-Valcarcel Ana María , Obispo-Diaz Cristina , Sanchez-Jorge Isabel , Mena-Álvarez Jesús , Aragoneses-Lamas Juan Manuel , Rico-Romano Cristina
Published: January 2025

Background/purpose

This study aimed to describe the root canal morphology of primary molars using Micro-CT and analyse the three-dimensional images of the internal root canal system.

Material and methods

One hundred and twenty extracted primary molars with one or more completed roots were scanned with Micro-CT. Three fixed heights of the roots were determined at axial level and the analysed criteria were: dentine thickness, diameter of roots canals, presence of lateral canals, isthmus and number of foramina. Vertucci's classification was also studied.

Results

Vertucci Type I was more prevalent in palatal and mesio-buccal root of superior molar and distal root of inferior molars. Type IV was more frequent in the mesial root. Dentine thickness was studied at three levels and for all the surfaces of the root canal. In the mesiobuccal root, in the middle and apical third, the mean in the upper molars is significantly higher than in the lower molars. The mesio-lingual canal has the major mean in mesio-distal and bucco-lingual diameter at coronal third. Isthmus were found mostly in the mesial root in all three levels. The high number of foramina and lateral canals were located at apical third of the mesial and mesio-buccal roots.

Conclusion

This study showed the complexity and variability of the root canal morphology of primary molars. The Micro-CT images gave important information about the internal anatomy of the primary molars.
Short-term seismic precursor anomalies in hydrogen concentration at fault gas stations along the Northern Margin Fault of the Yanqing Basin of Beijing, China
Authors: Yang Mingbo , Liu Guiping , Chen Yuxuan , Hua Peixue , Hu Leyin , Wang Zhiguo , Wang Shanshan , Sun Xiaoru , Zhou Yonggang , Zhang Haichun , Feng Gang , Gao Xiang , Zhang Yuqi
Published: January 2025

The Northern Margin Fault of the Yanqing Basin (NMYB Fault) is an important active fault at the intersection of the Zhangjiakou–Bohai (Zhang-Bo) Belt and the Shanxi Belt in North China. The Yanqing Basin, controlled by the NMYB Fault, is rich in escaping gas from hot springs, and previous investigations have indicated that the Yanqing Basin is located in the peak area of upwelling deep fluids from the mantle source material within the Zhang-Bo Belt. Hence, the site is suitable for geochemical gas precursor observations; to facilitate this, five new fault soil gas continuous stations were built on different segments of the NMYB Fault to carry out observations of fault gas (H2 and CO2) concentrations. The five new stations were approximately 50–60 m deep in the bedrock to monitor the release of gas from the depths of the fault. This was the first time that such geochemical station arrays were deployed in the same fault zone at a high density and depth. The results of the deep-hole observations of fault gas within the Yanqing Fault zone show that the time series of the hydrogen (H2) escape gas concentration has a close relationship with recent seismic activities, reflecting different physical processes of YFBF fault activity. The H2 concentration at the observatory was more sensitive to the stress-loading response of the NMYB Fault system.
Physical and chemical characteristics of pyrogenic carbon from peatland vegetation fires differ across burn severities
Authors: Kennedy-Blundell Oscar J. , Shuttleworth Emma L. , Rothwell James J. , Clay Gareth D.
Published: January 2025

Introduction

Vegetation fires lead to the formation of charred materials, often referred to as pyrogenic carbon (PyC), which are recalcitrant and have a high carbon densitymeaning they have the potential to act as a long-term carbon store. In the United Kingdom, peatlands are periodically subject to fire, both management burns and wildfires, which generate PyC. However, in the United Kingdom context, the characterisation of physical and chemical properties of PyC is limited.

Methods

In this study, samples of peatland vegetation (Calluna vulgaris, Polytrichum juniperinum, Vaccinium myrtillus and Eriophorum vaginatum) were burnt in laboratory conditions across typical ranges of characteristics from United Kingdom peatland vegetation fires (250°C–800°C and 2–10 min burn duration). Four broad severity groupings were established (low, moderate, high, very high) corresponding to 60, 70, 80% and 90% mass loss respectively. The PyC samples were then analysed using Brunauer-Emmett-Teller (BET) surface area analysis, CHNO elemental analysis, and Fouriertransform infrared spectroscopy (FTIR) to gain a greater understanding of their physiochemical characteristics.

Results

While there was a good degree of similarity between samples within each severity group, there were significant differences between severity groups. Low to high severity samples had relatively low surface areas compared to the very high severity samples, which exhibited the greatest surface areas and a high degree of variability. O/C and H/C ratios decreased with increasing severity. FTIR showed that distinct spectra were produced between severity groups, reflecting increased sample aromaticity with burn severity.

Discussion

The findings of this study suggest that burn severity is a good predictor of PyC physiochemical characteristics.
Macro-meso failure mechanism and strength criterion of frozen weakly cemented sandstone under triaxial unloading
Authors: Deng Qinghai , Fu Hao , Wang Junchao , An Xiaobiao , Lyu Xianzhou
Published: January 2025

Introduction

In the excavation engineering of tunnels and mines in the western cold region, the unloading failure zone is mainly caused by stress release. This study aimed to investigate the deformation and failure mechanism of frozen weakly cemented sandstone (FWCS) when the initial principal stress σ3 was 3, 6, or 10 MPa.

Methods

A conventional triaxial compression test and a triaxial unloading test with an unloading rate of 0.05 MPa/s were carried out. Based on the experimental data and mathematical analysis methods, the non-linear criterion was constructed and analyzed. The microfracture characteristics of the damaged surface were studied by scanning electron microscopy (SEM).

Results

The results show that compared with conventional triaxial compression and room temperature triaxial compression tests, the strength and plastic deformation characteristics of FWCS during unloading were significantly weakened, with transverse deformation and volume strain increased, showing obvious dilatancy characteristics. Unloading reduced the cohesion of FWCS, increased the internal friction angle, and increased the risk of rock failure. Macroscopic and microscopic analysis revealed the failure mechanism of FWCS. The unloading stress ratio was introduced to establish relationships. A non-linear criterion based on the Mohr–Coulomb strength criterion was established, with the power function strength criterion being more accurate in describing the failure of FWCS.

Discussion

This study provides valuable insights into the mechanical properties and failure mechanism of FWCS under unloading conditions, which is beneficial for the excavation engineering of tunnels and mines in the western cold region.
Navigating climate awareness in academia: a study of air travel attitudes among international students in Austria
Authors: Prandner Dimitri , Hasengruber Katrin
Published: January 2025

The urgent need to address climate change has prompted universities to reassess their impact on the environment, as the tension between academic internationalization and sustainability presents a complex challenge on multiple levels; including the organizations themselves, researchers or faculty, and students. The article explores the perceptions and attitudes of international students toward climate change, their personal environmental impact, and their perceptions of internationalization and mobility. To do so a qualitative case study was conducted in Austria (interview study; n = 29), including both bachelor’s and master’s program students. The study aimed to investigate the attitudes of international students toward air travel and identified five distinct types of students with varying levels of awareness and willingness to reflect on their personal impact on climate change. While some students prioritize their personal right to fly and gain experience, neglecting their contribution to climate change, others demonstrate a clear understanding of the need for change. The findings suggest that universities can play a key role in promoting environmental awareness by integrating climate change education into international study programs, providing transparent information about environmental impacts, and incentivizing sustainable mobility. Our aim is to contribute to the ongoing discussions regarding the intersection of higher education, internationalization, and climate change. We emphasize the need for significant institutional changes to address the complexities involved.
Microstructure of the human metastatic vertebral body
Authors: Cavazzoni Giulia , Dall’Ara Enrico , Palanca Marco
Published: January 2025

Introduction

Bone spinal metastases disrupt the bone homeostasis, inducing a local imbalance in the bone formation and/or resorption, with consequent loss of the structural optimisation of the vertebrae and increase of the risk of fracture. Little is known about the microstructure of the metastatic tissue, the microstructure of the tissue surrounding the lesion, and how it does compare with vertebrae with no lesions observed on the biomedical images. A comprehensive assessment of the microstructural properties of the entire vertebral body can be obtained with micro computed tomography. In this study, we evaluated to what extent the vertebral body is affected by the presence of a metastatic lesion, the properties of the metastatic lesions, and whether the tissue surrounding the lesion has microstructural features similar to those of healthy tissue.

Methods

A total of 30 metastatic vertebrae, including lytic (N = 12), blastic (N = 10), and mixed (N = 8) metastases, and 20 control vertebrae with no visible lesions on computed tomography were scanned using micro computed tomography (voxel size = 39 mm). The images were segmented and analysed to evaluate the microstructural properties in the entire vertebral body, in the lesion, and in the bone surrounding the lesion.

Results

The microstructural properties evaluated on the entire vertebral bodies showed remarkable differences between metastatic and control vertebral bodies (p < 0.034) in terms of bone volume fraction, trabecular thickness, degree of anisotropy, connectivity density, and trabecular pattern factor. On the other hand, when the tissue surrounding the lesion was considered, no differences were found between metastatic and control vertebral bodies, except for differences in the degree of anisotropy (p = 0.008). All microstructural parameters measured in the regions including the lytic or the blastic metastases significantly differed (p < 0.001) from those in the tissues surrounding the lesions. The lytic lesions minimally affected the regions closest to the metastases, with significant differences only in the connectivity density. On the other hand, blastic metastases also affected the trabecular separation, the bone surface density, and the connectivity density in the closest tissue surrounding the lesion.

Discussion

Most of the microstructural features of the trabecular bone in metastatic vertebrae were locally affected by lytic and blastic metastases, whereas the surrounding tissue showed a microstructure similar to that of adjacent vertebrae without visible lesions
Blockchain-driven demand side management in P2P energy markets for islanded microgrid systems
Authors: Umar Abdullah , Jha Sumit Kumar , Kumar Deepak , Ghose Tirthadip , Samantaray Subhransu Ranjan
Published: January 2025

In isolated microgrids, distributed energy resources (DERs) such as small-scale generators, energy storage systems, and flexible loads operate independently from the main grid. The challenge is to optimize these resources to minimize user costs while ensuring microgrid stability and efficiency. This paper presents an optimization framework for DERs, leveraging a game-theoretical approach to demand-side management (DSM) in an isolated microgrid environment. Each participant aims to minimize their total cost by strategically managing renewable energy generation, storage, and consumption. The framework models the DSM problem as a noncooperative game, identifying equilibrium points where no user can unilaterally reduce costs. The proximal decomposition algorithm is employed to iteratively update user strategies, ensuring convergence to a Nash equilibrium. Furthermore, a blockchain-based system with smart contracts is integrated to automate critical processes, including registration, event detection, DSM actions, and incentive distribution. This integration enhances transparency, security, and efficiency in the microgrid. During the registration phase, all devices are authenticated and authorized through a secure, transparent blockchain ledger. Event detection is managed by the microgrid Energy Management System (EMS), which continuously monitors voltage and frequency levels, triggering predefined smart contract responses to maintain stability. DSM actions are automatically executed by smart contracts, adjusting energy loads, generation, and storage to balance supply and demand dynamically. The smart contracts also manage the economic incentives that drive participant engagement. They calculate and distribute incentives based on predefined criteria, ensuring accurate and prompt allocation. This process is recorded on the blockchain, providing an immutable and auditable trail of actions and rewards. By leveraging blockchain technology and a game-theoretical approach, the proposed framework ensures continuous optimal operation despite fluctuations in energy demand and renewable generation. This dynamic and adaptive model promotes decentralized and efficient energy management within the microgrid, fostering a resilient and sustainable energy ecosystem.
A two-stage flexible scheduling method for power systems with wind power considering the coordination of multiple resources
Authors: Lei Aoyu , Zhao Ligang , Mei Yong , Zhen Hongyue , Gao Yongqiang , Zhou Tinghui
Published: January 2025

The intermittency and uncertainty of renewable energy generations, such as wind power, present great challenges to the secure and stable operation of power grids. To accommodate a high penetration of renewable energy, it is vital to coordinate multiple flexible resources to deal with the intermittency and uncertainty of renewable energy and ensure the network security. In this paper, we propose a two-stage stochastic flexible dispatching method for power systems with large-scale wind power, which considers the coordination of unit commitment, optimal transmission switching, and optimal control of phase-shifting transformers within a unified framework. On the grid side, flexibility is improved through phase-shifting transformer regulation and optimal transmission switching. On the source side, flexibility is fully exploited through two-stage stochastic unit commitment. In the day-ahead scheduling stage, transmission topology optimization and unit commitment schemes are determined based on the predicted load demand and renewable energy output. In the real-time dispatching stage, phase-shifting transformers and unit outputs are adjusted and dispatched based on the possible scenarios of load demand and renewable energy output. The effectiveness of the proposed method is verified through case studies on the IEEE RTS-24 system and IEEE 118-bus system.
Learning the factors controlling mineral dissolution in three-dimensional fracture networks: applications in geologic carbon sequestration
Authors: Pachalieva Aleksandra A. , Hyman Jeffrey D. , O’Malley Daniel , Srinivasan Gowri , Viswanathan Hari
Published: January 2025

We perform a set of high-fidelity simulations of geochemical reactions within three-dimensional discrete fracture networks (DFN) and use various machine learning techniques to determine the primary factors controlling mineral dissolution. The DFN are partially filled with quartz that gradually dissolves until quasi-steady state conditions are reached. At this point, we measure the quartz remaining in each fracture within the domain as our primary quantity of interest. We observe that a primary sub-network of fractures exists, where the quartz has been fully dissolved out. This reduction in resistance to flow leads to increased flow channelization and reduced solute travel times. However, depending on the DFN topology and the rate of dissolution, we observe substantial variability in the volume of quartz remaining within fractures outside of the primary subnetwork. This variability indicates an interplay between the fracture network structure and geochemical reactions. We characterize the features controlling these processes by developing a machine learning framework to extract their relevant impact. Specifically, we use a combination of high-fidelity simulations with a graph-based approach to study geochemical reactive transport in a complex fracture network to determine the key features that control dissolution. We consider topological, geometric and hydrological features of the fracture network to predict the remaining quartz in quasi-steady state. We found that the dissolution reaction rate constant of quartz and the distance to the primary sub-network in the fracture network are the two most important features controlling the amount of quartz remaining. This study is a first step towards characterizing the parameters that control carbon mineralization using an approach with integrates computational physics and machine learning.
How does social capital facilitate community disaster resilience? A systematic review
Authors: Zhao Guanhu , Hui Xu , Zhao Fazhen , Feng Lufang , Lu Yao , Zhang Yuting
Published: January 2025

Introduction

Community disaster resilience has emerged as a significant research topic within the domain of disaster risk management. One promising approach to enhance community disaster resilience lies in fostering social capital participation within the framework of community disaster risk management. However, there is currently limited systematic evidence illustrating how social capital facilitates community disaster resilience.

Methods

A comprehensive search of the electronic databases yielded a total of 1,021 papers deemed to be relevant to the topic under investigation. Using rigorous inclusion criteria, this study identified 24 studies that met the final review requirements. Based on this foundation, this paper demonstrates how social capital facilitates community disaster resilience through a systematic review utilizing thematic content analysis.

Results

This study identifies five critical mechanisms through which social capital facilitates community disaster resilience, including (1) social learning, (2) collective action, (3) disaster preparedness, (4) information communication, and (5) moral or civic responsibility. Furthermore, social capital mechanisms for enhancing community disaster resilience are observed across social (man-made) and natural disaster scenarios.

Conclusion

These findings provide valuable guidelines for risk management practice by social capital to improve community disaster resilience: (1) enhance community residents’ risk perception and social learning capacity; (2) reinforcing offline face-to-face and social media-based disaster risk communication; (3) placing greater emphasis on the capacity for community collective action and disaster preparedness.
Green finance and urban carbon emission dual control: an empirical evidence from China
Authors: Zhang Tian , Zhang Yao , Zhang Yumin
Published: January 2025

The Chinese government has proposed shifting the regulation of energy consumption and intensity towards a dual control system of total carbon emissions and carbon emission intensity gradually, aiming to promote the continued role of green finance in optimizing resource allocation. To reveal the impact and mechanism of green finance on urban carbon emissions and intensity in China, this paper constructs a general equilibrium model based on endogenous growth theory and employs a two-way fixed effects model for empirical testing. The study finds that: (1) The development of green finance significantly inhibits both the total carbon emissions and carbon emission intensity of Chinese cities. (2) The impact of green finance on urban carbon emissions and intensity exhibits significant regional heterogeneity. In the northeastern regions of China, southeastern regions of the Hu Line, non-resource-based cities, and areas with higher financial efficiency, green finance can significantly reduce both urban carbon emissions and carbon emission intensity. However, in central and western regions and resource-based cities, green finance only suppresses urban carbon emission intensity. (3) Green finance can reduce urban carbon emissions and intensity through two channels: economic scale expansion and technological advancement, while the channel of industrial structure optimization has not yet shown a significant effect. Through research, it can be found that balancing the differences in green finance and carbon emission functions across regions, while fully optimizing the use and allocation mechanisms of resource elements from aspects such as technological innovation, environmental protection, and energy conservation, can enhance the quality and efficiency of economic development. This is of significant importance for green finance in promoting the realization of dual carbon control.
Advancing economic sustainability in E7 economies: the impact of green finance, environmental benefits, and natural resource management
Authors: Dai Xulong , Wu Junyu , Fan Suqing , Zhou Yanqi
Published: January 2025

Green finance (GFN) plays a critical role in reducing greenhouse gas emissions and air pollution, serving as a key financial mechanism to promote green growth and economic sustainability (ESS). This paper explores how GFN, along with fintech (FNT), environmental benefits (ENB), urbanization (URB), and natural resource management (NRM), influences ESS in E7 countries from 2000 to 2022. While fintech’s rapid technological advancements offer significant economic potential, they also introduce increased complexity and systemic risks. Using rigorous methods such as method of moments quantile regression (MMQR) and Westerlund analysis, this study validates the relationships and heterogeneity among these variables through preliminary tests, including matrix correlation, cross-sectional dependence (CSD), slope heterogeneity (SH), and CIPS unit root tests. The findings indicate that GFN, ENB, and FNT positively contribute to ESS, while URB and NRM have an inverse relationship with ESS. These insights not only deepen our understanding of how ecological factors influence economic sustainability but also provide practical policy recommendations for E7 countries. The study’s conclusions offer valuable guidance for optimizing ESS and advancing toward sustainable development goals (SDGs).
Exploring the prognostic significance of lactate-mitochondria-related genes in prostate cancer
Authors: Wang Yuan , Chen Ronghui , Jiang Feng-Le , Jiang Xin , Zhou Yuehong , Zhou Yingying , Hong Xinyi , Lin Chaoying , Wang Wei-Jia , Qiu Sufang
Published: January 2025

Prostate cancer (PCa) is a common and serious health issue among older men globally. Metabolic reprogramming, particularly involving lactate and mitochondria, plays a key role in PCa progression, but studies linking these factors to prognosis are limited. To identify novel prognostic markers of PCa based on lactate-mitochondria-related genes (LMRGs), RNA sequencing data and clinical information of PCa from The Cancer Genome Atlas (TCGA) and the cBioPortal database were used to construct a lactate-mitochondria-related risk signature. Here, we established a novel nine-LMRG risk signature for PCa, and Kaplan-Meier curves confirmed a worse prognosis for high-risk subgroups in the TCGA dataset. Meanwhile, a nomogram that effectively predicts the prognosis of PCa patients was also constructed. Next, close associations between the lactate-mitochondria-related signature and the immune microenvironment were examined to clarify the role of LMRGs in shaping the immune landscape. Furthermore, as the only lactate-related gene among the nine key prognostic risk genes, myeloperoxidase (MPO) was identified as a key factor that mediates lactate production in vitro and in vivo through attenuation of the glycolytic pathway. More importantly, MPO significantly inhibited PCa cell migration, invasion, and epithelial–mesenchymal transition (EMT), indicating its potential as an anticancer gene. Additionally, PCa with high MPO expression is highly sensitive to chemotherapeutic agents and mitochondrial inhibitors, highlighting its potential as an improved therapeutic strategy for PCa management.
Prenatal vitamin utilization and its determinants among pregnant women in south Gondar zone: multicenter cross-sectional study
Authors: Mekuriaw Begizew Yimenu , Addisu Dagne , Yazie Ferede Wassie , Sisay Fillorenes Ayalew , Mitiku Assefa kebie , Belachew Tegegne Wale , Seid Yimer Tigist , Wubet Habtie Bantider , Tadesse Selamawit Girma , Gobezie Negesse Zurbachew , Mebratie Alemie Fentie , Alachew Moges Kefale , Mengistu Temesgen Dessie , Yiregu Yonas Zenebe , Arage Rahel Birhanu , Dessie Anteneh Mengist , Gebeyehu Fikadu Geremew , Bishaw Mekonen Geremew , Alemayehu Habtam Desse , Ayalew Abeba Belay , Goshu Yitayal Ayalew , Berihun Erega Besfat
Published: January 2025

Background

Prenatal vitamin and mineral supplements are commonly advised as clinical practice standard of care. In spite of Ethiopian government focus on maternal nutrition programmes targeting pregnant and lactating women, Micronutrient deficiencies are still quite common and are regarded as a serious public health issue and also little is known regarding utilization and barriers to prenatal vitamin use during pregnancy. This study aimed to assess utilization and associated factors of prenatal vitamins among pregnant women attending antenatal care at public hospitals in the south Gondar zone, 2024

Methods

Multi center crossectional study design was conducted among 416 pregnant women from March 1 to May 30, 2024. Systematic sampling technique was used to select the study participants. Data was collected using Interviewer administered questionnaire. After data, SPSS version 26 software was used for analysis. Factors associated with utilization of prenatal vitamins were identified using bi-variable and multi variable logistic regression models. Statistical significance was declared at 95%CI and p-value < 0.05.

Result

In this study, we found that 87.5% (95% CI: 84.31, 90.34) of pregnant women did not use prenatal vitamins. Women not having formal education (AOR = 2.72, 95%CI: 1.44–5.15), being unplanned pregnancy (AOR = 2.58, 95%CI: 1.76–3.78), husband being decision maker in health care (AOR = 1.71, 95%CI:1.09–2.68), having poor knowledge (AOR = 3.27, 95%CI: 1.44–7.42) and unfavorable attitude (AOR = 3.63, 95%CI: 1.61–8.18) on prenatal vitamins were significantly associated with non-users of prenatal vitamins.

Conclusion

The proportion of non-users of prenatal vitamin were higher. Educational level of women, pregnancy plan, decision on health care, knowledge and attitude on prenatal vitamins had statistically significant with utilization of prenatal vitamins. Developing and implementing targeted educational programs to increase awareness about the importance and benefits of prenatal vitamins and encouraging women to take an active role in their healthcare decisions is recommended to improve the utilization of prenatal vitamins.
Current methods for detecting and assessing HIV-1 antibody resistance
Authors: Odidika Stanley , Pirkl Martin , Lengauer Thomas , Schommers Philipp
Published: January 2025

Antiretroviral therapy is the standard treatment for HIV, but it requires daily use and can cause side effects. Despite being available for decades, there are still 1.5 million new infections and 700,000 deaths each year, highlighting the need for better therapies. Broadly neutralizing antibodies (bNAbs), which are highly active against HIV-1, represent a promising new approach and clinical trials have demonstrated the potential of bNAbs in the treatment and prevention of HIV-1 infection. However, HIV-1 antibody resistance (HIVAR) due to variants in the HIV-1 envelope glycoproteins (HIV-1 Env) is not well understood yet and poses a critical problem for the clinical use of bNAbs in treatment. HIVAR also plays an important role in the future development of an HIV-1 vaccine, which will require elicitation of bNAbs to which the circulating strains are sensitive. In recent years, a variety of methods have been developed to detect, characterize and predict HIVAR. Structural analysis of antibody-HIV-1 Env complexes has provided insight into viral residues critical for neutralization, while testing of viruses for antibody susceptibility has verified the impact of some of these residues. In addition, in vitro viral neutralization and adaption assays have shaped our understanding of bNAb susceptibility based on the envelope sequence. Furthermore, in vivo studies in animal models have revealed the rapid emergence of escape variants to mono- or combined bNAb treatments. Finally, similar variants were found in the first clinical trials testing bNAbs for the treatment of HIV-1-infected patients. These structural, in vitro, in vivo and clinical studies have led to the identification and validation of HIVAR for almost all available bNAbs. However, defined assays for the detection of HIVAR in patients are still lacking and for some novel, highly potent and broad-spectrum bNAbs, HIVAR have not been clearly defined. Here, we review currently available approaches for the detection, characterization and prediction of HIVAR.