bluuebunny/crossref_metadata_2025 huggingface dataset:
Framing Collective Moral Responsibility for Climate Change: A Longitudinal Frame Analysis of Energy Company Climate Reporting
Authors: Feeney Melanie , Ormiston Jarrod , Gijselaers Wim , Martens Pim , Grohnert Therese
Published: August 2024

Responding to climate change and avoiding irreversible climate tipping points requires radical and drastic action by 2030. This urgency raises serious questions for energy companies, one of the world’s largest emitters of greenhouse gases (GHGs), in terms of how they frame, and reframe, their response to climate change. Despite the majority of energy companies releasing ambitious statements declaring net zero carbon ambitions, this ‘talk’ has not been matched with sufficient urgency or substantive climate action. To unpack the disconnect between talk and action, this paper draws on the literature on framing, organisational hypocrisy, and collective moral responsibility. We conduct a longitudinal qualitative content analysis of the framing of climate change used by the ten largest European investor-owned energy companies and the actions they have taken to shift their business practices. Our findings reveal three main categories of energy companies: (i) deflecting, (ii) stagnating, and (iii) evolving. We show key differences in the relationship between framing and action over time for each category, revealing how deflecting companies have larger and persistent gaps between green talk and concrete action and how stagnating companies are delaying action despite increased green talk, while evolving companies exhibit a closer link between talk and action that tends to be realised over time. Our analysis reveals how competing approaches to framing collective moral responsibility help understand the trajectories of talk and action across the different categories of energy companies. This research makes several contributions to the literature on organisational hypocrisy and collective moral responsibility in the context of climate change. Our analysis highlights the complex relationship between collective moral responsibility, organisational hypocrisy and climate action, revealing how different collective framings—diffuse, teleological, or agential—can both enable and offset substantive climate action. The study also enriches our understanding of the performative nature of collective moral responsibility by examining its temporal dimensions and showing how an agential, backward-looking focus is associated with more meaningful climate action.
Mapping temperate old-growth forests in Central Europe using ALS and Sentinel-2A multispectral data
Authors: Adiningrat Devara P. , Schlund Michael , Skidmore Andrew K. , Abdullah Haidi , Wang Tiejun , Heurich Marco
Published: August 2024

Old-growth forests are essential to preserve biodiversity and play an important role in sequestering carbon and mitigating climate change. However, their existence across Europe is vulnerable due to the scarcity of their distribution, logging, and environmental threats. Therefore, providing the current status of old-growth forests across Europe is essential to aiding informed conservation efforts and sustainable forest management. Remote sensing techniques have proven effective for mapping and monitoring forests over large areas. However, relying solely on remote sensing spectral or structural information cannot capture comprehensive horizontal and vertical structure complexity profiles associated with old-growth forest characteristics. To overcome this issue, we combined spectral information from Sentinel-2A multispectral imagery with 3D structural information from high-density point clouds of airborne laser scanning (ALS) imagery to map old-growth forests over an extended area. Four features from the ALS data and fifteen from Sentinel-2A comprising raw band (spectral reflectance), vegetation indices (VIs), and texture were selected to create three datasets used in the classification process using the random forest algorithm. The results demonstrated that combining ALS and Sentinel-2A features improved the classification performance and yielded the highest accuracy for old-growth class, with an F1-score of 92% and producer’s and user’s accuracies of 93% and 90%, respectively. The findings suggest that features from ALS and Sentinel-2A data sensitive to forest structure are essential for identifying old-growth forests. Integrating open-access satellite imageries, such as Sentinel-2A and ALS data, can benefit forest managers, stakeholders, and conservationists in monitoring old-growth forest preservation across a broader spatial extent.
A Comprehensive Review of Convolutional Neural Networks based Disease Detection Strategies in Potato Agriculture
Authors: Gülmez Burak
Published: August 2024

This review paper investigates the utilization of Convolutional Neural Networks (CNNs) for disease detection in potato agriculture, highlighting their pivotal role in efficiently analyzing large-scale agricultural datasets. The datasets used, preprocessing methodologies applied, specific data collection zones, and the efficacy of prominent algorithms like ResNet, VGG, and MobileNet variants for disease classification are scrutinized. Additionally, various hyperparameter optimization techniques such as grid search, random search, genetic algorithms, and Bayesian optimization are examined, and their impact on model performance is assessed. Challenges including dataset scarcity, variability in disease symptoms, and the generalization of models across diverse environmental conditions are addressed in the discussion section. Opportunities for advancing CNN-based disease detection, including the integration of multi-spectral imaging and remote sensing data, and the implementation of federated learning for collaborative model training, are explored. Future directions propose research into robust transfer learning techniques and the deployment of CNNs in real-time monitoring systems for proactive disease management in potato agriculture. Current knowledge is consolidated, research gaps are identified, and avenues for future research in CNN-based disease detection strategies to sustain potato farming effectively are proposed by this review. This study paves the way for future advancements in AI-driven disease detection, potentially revolutionizing agricultural practices and enhancing food security. Also, it aims to guide future research and development efforts in CNN-based disease detection for potato agriculture, potentially leading to improved crop management practices, increased yields, and enhanced food security.
Comorbidities and Angiogenic Regulators Affect Endothelial Progenitor Cell Subtype Numbers in a Healthy Volunteer Control Group
Authors: Rakkar Kamini , Kadir Rais Reskiawan A. , Othman Othman A. , Sprigg Nikola , Bath Philip M. , Bayraktutan Ulvi
Published: August 2024

Endothelial progenitor cells (EPCs) are stem cells that can repair injured blood vessels through neovascularisation. This is achieved through secretion of growth factors and endothelial maturation. EPC numbers and function have been studied to determine their diagnostic, prognostic and therapeutic potential in many ischaemic diseases such as stroke. However their activation homing and migration is not definitively understood in stroke patients. In this study, we profiled the non-stroke control group recruited into the Dunhill Medical Trust Endothelial Progenitor Cell Study. Demographic, clinical and plasma levels of angiogenic regulators of participants were analysed to determine if there was any correlation with EPC numbers, subtypes and function. Participants with diabetes had significantly supressed EPC numbers (CD45-CD34 + CD133 + KDR+) and CD34 + KDR + and KDR + EPC subtypes. Male participants had significantly lower EPC numbers compared to female participants and the proliferative capacity of endothelial colony forming cells significantly decreased with increasing participant age. Pro-angiogenic proteins such as granulocyte colony-stimulating factor and stromal cell-derived factor were positively correlated with both undifferentiated and endothelial-committed EPC subtype numbers (CD133+, KDR+, CD34 + CD133+, CD34 + KDR+), whereas anti-angiogenic proteins such as thrombospondin-1 showed a negative correlation with undifferentiated EPC subtypes (CD133+, CD34 + CD133+) but a positive correlation with endothelial-committed EPC subtype numbers (KDR+, CD34 + KDR+). These results show that EPC numbers and subtypes are affected by many factors and larger studies which can analyse and deconvolute the interactions between comorbidities, plasma biomarker levels and EPC are needed.

Graphical Abstract
Theory of planned behavior and fast fashion purchasing: an analysis of interaction effects
Authors: Magwegwe Frank M. , Shaik Abdulla
Published: August 2024

The fast fashion industry, characterized by its reliance on rapid consumption cycles, and short-lived garment use, has raised major environmental concerns. This industry generates over 92 million tons of waste and consumes 79 trillion liters of water annually, driven by rising consumer demand for fast fashion. As such, there is a pressing need to transition from the current wasteful fast fashion purchasing behavior to more sustainable behavior. Despite extensive research on sustainable purchasing behavior, there is still a gap in our understanding of the predictors of consumers’ sustainable fast fashion purchasing behavior. To address this gap, our study utilized a survey questionnaire to collect data from a convenience sample of 123 South African consumers. We expanded the theory of planned behavior (TPB) by incorporating sustainability awareness as a background factor in the hypothesized theoretical model. We also investigated the relationships among the TPB constructs (attitude, subjective norm, and perceived behavioral control), sustainability awareness, and sustainable fast fashion purchasing behavior. By employing hierarchical regression within the extended TPB framework, we found that perceived behavioral control mediated the relationship between sustainability awareness and sustainable fast fashion purchasing behavior. Further, perceived behavioral control and its interaction with attitude significantly predicted sustainable fast fashion purchasing behavior, while sustainability awareness significantly predicted perceived behavioral control. Notably, our findings reveal that lower perceived behavioral control is associated with a stronger positive relationship between attitude and sustainable fast fashion purchasing behavior. These findings have important implications for theory and practice, and provide suggestions for future research directions.
Sensing physical properties for subjective meanings: Putting Emergent Consumer Perceived Value (ECPV) into the marketers’ toolbox
Authors: Forsman Laura J. , Luomala Harri
Published: August 2024

Marketers need to understand consumers in both theory and practice to create offerings that are valuable to them. Hence, the marketing discipline has conceptualized consumers’ subjectively perceived value in various ways, using multiple paradigms. Nevertheless, its constituents remain unclear. We argue that this is because the ontological and epistemological premises are both vague and narrow. Consequently, consumers’ value perceptions are still difficult to study or manage. With the aim of making a conceptual leap, our paper is the first to apply a critical realist (CR) approach to the phenomenon. CR’s stratified ontology and subjectivist/pluralist epistemology reconcile the positivist and interpretivist/constructionist paradigms, allowing the simultaneous existence of external socio-natural and internal subjective realities. Using these premises, we examine, from a marketer’s perspective, how consumers perceive value, which is a subjective, phenomenological, and socially constructed act embedded in the natural world. Our CR theorizing deploys Bhaskar’s (2010) RRREIC schema and includes a review of the extant subjective value conceptualizations (consumer perceived value, value-in-use, value-in-experience) and retroduction of the key mechanisms generating the phenomenon: meaning-making and sensory perception. Finally, we propose a novel conceptualization for Emergent Consumer Perceived Value formation (ECPV) as an open system. As its integral component, we introduce the concept of Sensory Value Affordance, explaining how consumers transform physical properties into subjective meanings. These conceptual tools cater especially to B2C managers and account for both the phenomenological and sociocultural as well as the corporeal and perceptual. Finally, we present broader implications for value research, the field of marketing, and society.
Association of ACE and AGTR1 variants with retinopathy of prematurity: a case–control study and meta-analysis
Authors: Durska Anna , Szpecht Dawid , Gotz-Więckowska Anna , Strauss Ewa
Published: August 2024

Retinopathy of prematurity (ROP) is a major cause of childhood blindness worldwide, linked to gene variants in the renin–angiotensin–aldosterone system, including angiotensin-converting enzyme (ACE) and angiotensin II receptor type 1 (AGTR1). This study aims to evaluate the association between ACE insertion/deletion (I/D) and AGTR1 rs5186A > C variants with the occurrence and progression of ROP in a Polish cohort. A total of 377 premature infants were enrolled in the study. The ACE variant was evaluated using PCR, and AGTR1 was assessed using TaqMan probes. Clinical characteristics, including risk factors and comorbidities, were documented. A meta-analysis of the effects of the studied variants on ROP was also conducted. The AGTR1 rs5186C allele was significantly associated with both the progression of ROP and treatment outcomes. Homozygotes exhibited a 2.47-fold increased risk of developing proliferative ROP and a 4.82-fold increased risk of treatment failure. The impact of this allele increased at low birth weight. A meta-analysis, including 191 cases and 1661 controls, indicated an overall risk of 1.7 (95%CI 1.02–2.84) for the recessive effect of the rs5186C allele. The ACE variant did not show a significant association with ROP in our population; however, a meta-analysis of 996 cases and 2787 controls suggested a recessive effect of the insertion allele (an odds ratio of 1.21 (95%CI 1.00–1.60)). These results indicate that gain-of-function AGTR1 variants may play a crucial role in the development of ROP, potentially by promoting angiogenesis and pro-inflammatory effects. Screening for these variants could facilitate the development of personalized risk assessment and treatment strategies for ROP.
Combining cyclic lipopeptides and cinnamon extract enhance antifungal activity against Fusarium oxysporum strains pathogenic to banana and delay Fusarium wilt under greenhouse conditions
Authors: Ramírez-Mejía Julieta M. , Aguilera-Galvez Carolina , Kema Gert H. J. , Valencia-Riascos Luisa M. , Zapata-Henao Sebastián , Gómez Luis A. , Villegas-Escobar Valeska
Published: August 2024

Fusarium wilt of banana (FWB) caused by the soil-borne fungus Fusarium oxysporum f. sp. cubense (Foc) is a widely distributed disease that generates devastating losses in banana production. Foc belongs to the Fusarium oxysporum species complex (FOSC) which includes several evolutionary lineages. Nine of them are pathogenic to banana such as F. phialophorum, F. grosmichelli, F. duoseptatum and the most aggressive F. odoratissimum tropical race 4 (TR4). No control method has been successfully implemented to manage FWB, then enhancing the potential of management approaches can avoid or delay disease epidemics and reduce disease severity. Here we determined the antifungal effect of different plant-based extracts against Foc in vitro, and whether the combination of cinnamon (Cinnamomum zeylanicum) extract and Bacillus tequilensis EA-CB0015 cyclic lipopeptides had an additive effect against different Foc lineages in vitro and against FWB in banana plants in greenhouse. We found, from 17 plant-based natural extracts, that cinnamon was highly active against Foc strain IB (race 1). Furthermore, cinnamon and cyclic lipopeptides inhibited different strains of various evolutionary lineages of Foc belonging to race 1 and TR4, and their combination increased in 1.4-fold the effect of the single extracts in vitro. Our results showed that soil concentration of F. odoratissimum TR4-II5 decreased by 1000-fold when treated with the combination of 488 mg L−1 cinnamon and 128 mg L−1 lipopeptides in a soil microcosm system after 5 days of incubation, followed by a partial population recovery after 21 days. In greenhouse experiments, the combination reduced external but not internal FWB symptoms, and cinnamon extract had a significant impact on internal plant symptoms. Taken together, the effect of cyclic lipopeptides with cinnamon extract on Foc supports their function towards delaying the effect of disease progression and suggests that the combination enhances the effect of the single extracts.
PowerPoint-based lectures and students’ experiences in Eritrean Higher Education Institutions
Authors: Zemuy Mulugeta , Tsegay Samson Maekele , Aihui Peng
Published: August 2024

PowerPoint (PPT) is extensively used in Higher Education Institutions (HEIs), including those in Eritrea, for lecture delivery and student presentations. This raises questions about whether these lectures or student presentations are effectively designed and implemented and encourage students’ participation. This study explores instructors’ use of PPT-based lectures and students’ experience in Eritrean HEIs. Additionally, it seeks to identify and understand the challenges HEIs face in using PPT-based teaching. Data were collected through semi-structured interviews, focus groups, and observations, involving nine instructors and fifteen students from three Eritrean HEIs. The study indicated a relationship between PPT design and delivery and revealed varied outcomes regarding the design and delivery of PPT-based lectures. The study also found discipline-specific differences regarding students’ experiences of PPT-based delivery. Moreover, it identified challenges related to institutional leadership, curriculum flexibility, internet access, and pedagogical expertise and commitment of instructors as key obstacles to the successful integration of PPT-based lectures within these institutions.
Transcending attitudes: teacher responses to professional development in trauma-informed education
Authors: Gherardi Stacy A. , Stoner Allison
Published: August 2024

The adoption of trauma-informed practices in schools is a significant and growing area of school reform efforts. It has been assumed that professional development aimed at influencing teacher attitudes toward trauma-informed care in schools is an important first step in adopting trauma-informed practices and improving student and school outcomes. However, there are gaps in the literature assessing the impact of trauma-informed professional development on teacher attitudes toward trauma-informed care, and there is little evidence linking changes in teacher attitudes to changes in practices. This exploratory study assessed teacher responses to a year-long pilot program providing intensive professional development and consultation on trauma-informed practices in one urban elementary school in the U.S. Southwest. Findings raise questions about the impact of professional development on teacher attitudes and subsequent changes to practice.
The role of cancer-associated fibroblasts and exosomal miRNAs-mediated intercellular communication in the tumor microenvironment and the biology of carcinogenesis: a systematic review
Authors: Nedaeinia Reza , Najafgholian Simin , Salehi Rasoul , Goli Mohammad , Ranjbar Maryam , Nickho Hamid , Haghjooy Javanmard Shaghayegh , A. Ferns Gordon , Manian Mostafa
Published: August 2024

CAFs (cancer-associated fibroblasts) are highly flexible cells of the cancer microenvironment. They produce the extracellular matrix (ECM) constituents that form the structure of the tumor stroma but are also a source of metabolites, growth factors, chemokines, and exosomes that impact every aspect of the tumor, including its response to treatment. It is believed that exosomal miRNAs facilitate intercellular signaling, which is essential for the development of cancer. The role of miRNAs and CAFs in the tumor microenvironment (TME) and carcinogenesis is reviewed in this paper. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines were used to perform a systematic review. Several databases, including Web of Science, Medline, Embase, Cochrane Library, and Scopus, were searched using the following keywords: CAFs, CAF, cancer-associated fibroblasts, stromal fibroblasts, miRNA, exosomal miRNAs, exosome and similar terms. We identified studies investigating exosomal miRNAs and CAFs in the TME and their role in carcinogenesis. A total of 12,572 papers were identified. After removing duplicates (n = 3803), 8774 articles were screened by title and abstract. Of these, 421 were excluded from further analysis. It has been reported that if exosomal miRNAs in CAFs are not functioning correctly, this may influence the secretory phenotype of tip cells and contribute to increased tumor invasiveness, tumor spread, decreased treatment efficacy, and a poorer prognosis. Under their influence, normal fibroblasts (NFs) are transformed into CAFs. Furthermore, they participate in metabolic reprogramming, which allows for fast proliferation of the cancer cell population, adaptation to growing energy demands, and the capacity to avoid immune system identification.
A case of severe Aicardi–Goutières syndrome with a homozygous RNASEH2B intronic variant
Authors: Shibata Yuri , Shibata Akimichi , Mizuguchi Takeshi , Matsumoto Naomichi , Osaka Hitoshi
Published: August 2024

We report a case of severe Aicardi–Goutières syndrome caused by a novel homozygous RNASEH2B intronic variant, NC_000013.10(NM_024570.4):c.65-13G > A p.Glu22Valfs*5. The patient was born with pseudo-TORCH symptoms, including intracranial calcification, cataracts, and hepatosplenomegaly. Furthermore, the patient exhibited profound intellectual impairment and died at 14 months due to aspiration pneumonia accompanied by interstitial lung abnormalities. The severity of the patient’s symptoms underscores the critical role of the C-terminal region of RNase H2B.
Light rain exacerbates extreme humid heat
Authors: Zhang Zhanjie , Wang Yong , Zhang Guang J. , Xing Cheng , Xia Wenwen , Yang Mengmiao
Published: August 2024

Humid heat waves pose significant risks to human health and the ecosystem. Intuitively, rainfall often alleviates extreme humid heat. However, here we show that light rain often accompanies extreme humid heat, exacerbating its frequency and intensity, especially over arid and semi-arid regions compared to no rain and moderate-to-heavy rain cases. This is because light rain does not dramatically reduce solar radiation but increases near-surface humidity through enhanced surface evaporation. The water replenishment from light rain as well as a shallower planetary boundary layer is crucial for consecutive extremes where there are commonly sporadic drizzle days amidst several rain-free days. These extremes last longer than rain-free extremes. Current global climate models (GCMs) overestimate light rain. After reducing this bias in a GCM, underestimations of humid heat waves in energy-limited regions and overestimations in water-limited regions are largely alleviated. These findings underscore the underappreciated impact of light rain on extreme humid heat.
Efficacy and safety of Resmetirom, a selective thyroid hormone receptor-β agonist, in the treatment of metabolic dysfunction-associated steatotic liver disease (MASLD): a systematic review and meta-analysis
Authors: Suvarna Renuka , Shetty Sahana , Pappachan Joseph M.
Published: August 2024

Metabolic dysfunction-associated steatotic liver disease (MASLD) is an important public health problem owing to its high prevalence and associated morbidity and mortality secondary to progressive liver disease and cardiovascular events. Resmetirom, a selective thyroid hormone receptor-β agonist has been developed as a therapeutic modality for MASLD. This systematic review and meta-analysis aimed to evaluate the effectiveness and safety of resmetirom compared to a placebo in the treatment of MASLD. Eligible studies were systematically identified by screening PubMed, Scopus, Web of Science, Cochrane library, Embase, and ClinicalTrials.gov from 2014 to 2024. Only randomized controlled trials comparing the efficacy and safety of resmetirom in the treatment of MASLD against placebo were included in the analysis. Meta-analysis was performed using RevMan 5.4 software. Four studies with low risk of bias and involving a total of 2359 participants were identified. The metanalysis included only three clinical trials with 2234 participants. A significant reduction in MRI-proton density fat fraction (MRI-PDFF) with 80 mg Resmetirom compared to that with placebo [SMD − 27.74 (95% CI − 32.05 to − 32.42), p < 0.00001] at 36–52 weeks as well as at 12–16 weeks [SMD − 30.92 (95% CI − 36.44 to − 25.40), p < 0.00001]. With Resmetirom 100 mg dose at 36–52 weeks [SMD − 36.05 (95% CI − 40.67 to − 31.43), p < 0.00001] and 12–16 weeks [SMD − 36.89 (95% CI − 40.73 to − 33.05), p < 0.00001] were observed. Resmetirom treatment was associated with a significant reduction in LDL-c triglyceride, lipoproteins. and liver enzymes. There was significant reduction FT4 and increase in SHBG and sex steroids with Resmetirom compared to placebo. There was no major difference in the overall treatment emergent adverse events at 80 mg [OR 1.55 (95% CI 0.84 to 2.87), and 100 mg [OR 1.13 (95% CI 0.78 to 1.63), doses of Resmetirom compared to placebo. However, gastrointestinal adverse events diarrhoea and nausea occurred in ≥ 10% in the Resmetirom group compared to placebo at < 12 week. Resmetirom treatment showed modest efficacy in treating MASLD with reduction in MRI-PDFF, LDL-c, triglyceride, lipoproteins, liver enzymes and NASH biomarkers without significant safety concerns. Larger and long-term RCTs may further confirm this promising outcomes of Resmetirom use in MASLD.
Tongue brushing enhances the myoelectric activity of the suprahyoid muscles in older adults: a six-week randomized controlled trial
Authors: Izumi Maya , Sonoki Kazuo , Akifusa Sumio
Published: August 2024

Tongue brushing improves respiratory function in older adults. Considering connection between the respiratory-related and suprahyoid muscles, this study aimed to investigate whether tongue-brushing interventions can improve myoelectric activity during respiration. A six-week randomized controlled trial was conducted in Kitakyushu, Japan, with 50 participants aged ≥ 65 years. The participants were allocated to the intervention (tongue brushing with routine oral hygiene) or control (routine oral hygiene alone) groups. Surface electromyography (sEMG) was used to assess the myoelectric activity of the suprahyoid muscles during inhalation, exhalation, and forced vital capacity (FVC). A survey was conducted at baseline and the end of the follow-up period. Thirty-six participants were recruited for the analysis. The root mean squares (RMS) of sEMG during exhalation increased significantly at the end of the follow-up period compared with that at baseline in the intervention group [48.7 (18.0–177.5) vs. 64.9 (21.6–163.0), p = 0.001], but not in the control group. The generalized linear model revealed that the ratio of change in FVC was correlated with the change in the RMS of sEMG of the suprahyoid muscles during exhalation after adjusting for potential confounders. Tongue brushing enhances the myoelectric activity of the suprahyoid muscle.
Superior catalytic combustion of methane over Pd supported on oxygen vacancy-rich NiAl2O4
Authors: Li Sha , Li Jie , He Zirui , Sheng Yao , Liu Wen
Published: August 2024

The high concentration of oxygen vacancies and the presence of stable PdO nanoparticles collectively enhance the exceptional activity and durability of the Pd/NiAl2O4 catalyst in the methane combustion process.
LaFe1−xNixO3 perovskites in the catalytic reaction of high-temperature decomposition of nitrous oxide
Authors: Isupova L. A. , Ivanova Yu. A. , Prosvirin I. P. , Yu Gerasimov E.
Published: August 2024

LaFe1−xNiO3 are used as catalysts for the decomposition of nitrous oxide (N2O).
Shallow Shell SSTA63 resin: a rapid approach to remediation of hazardous nitrate
Authors: Çendik Elif , Saygı Mügenur , Recepoğlu Yaşar Kemal , Arar Özgür
Published: August 2024

This study explores the potential of Purolite Shallow Shell™ SSTA63 anion exchange resin for mitigating nitrate ion (NO3−) contamination in aqueous environments.
Integrated MXene and metal oxide electrocatalysts for the oxygen evolution reaction: synthesis, mechanisms, and advances
Authors: Lakhan Muhammad Nazim , Hanan Abdul , Wang Yuan , Lee Hiang Kwee , Arandiyan Hamidreza
Published: August 2024

This review summarizes recent advances in MXene and transition metal oxide (TMO) electrocatalysts for enhancing oxygen evolution reaction (OER), concluding with key findings and future research directions for further improvements.
Oxygen-bridged W-Pd atomic pairs enable H2O2 activation for sensitive immunoassays
Authors: Chen Chengjie , Yan Dongbo , Jia Xiangkun , Li Ruimin , Hu Lijun , Li Xiaotong , Jiao Lei , Zhu Chengzhou , Zhai Yanling , Lu Xiaoquan
Published: August 2024

Three-dimensional W-O-Pd sites exhibit excellent H2O2 activation selectivity and efficiency, which is beneficial for increased sensitivity and accuracy in immunoassays.
Serein: A parallel pipeline‐based DAG schema for consensus in blockchain
Authors: Liu Yang , Chen Jingwen , Zhang Miaomiao , Shi Shidong , Wang Feng
Published: August 2024

As the core technology of blockchain, consensus mechanisms play a crucial role in ensuring the consistency and reliability of blockchain systems. In a decentralized and open system environment like blockchain, traditional consensus algorithms are often unsuitable due to their inability to tolerate arbitrary faults such as malicious node behaviour. Consequently, Byzantine fault tolerance consensus algorithms have become a focal point in blockchain systems. However, as Byzantine fault tolerance consensus algorithms have evolved, they still face significant challenges, particularly in addressing issues related to network latency and throughput. This paper proposes a parallel pipeline‐based DAG schema for consensus in blockchain, Serein. Firstly, the Serein algorithm achieves functional partitioning of nodes, enhancing their scalability. Secondly, it employs a pipeline structure, allowing each block to proceed without waiting for the previous block's result, thereby reducing block generation latency. Lastly, the Serein algorithm leverages the advantages of the DAG block structure to achieve concurrent block ordering and submission, improving system throughput. Experimental results demonstrate that the proposed Serein algorithm maintains robust performance under conditions of high transaction volume with multiple nodes, effectively enhancing consensus efficiency while ensuring Byzantine fault‐tolerant security.
Energy regulation of impulse current generator modulated DC arc discharge
Authors: Li Ji , Tang Jingfeng , Lou Yuqing , Zhang Haoran , Wang Lu , Ji Tianyuan , Yu Daren , Zhu Ximing
Published: August 2024

This paper proposes a method of impulse current generator modulated DC arc by combining the advantages of pulse and the RF to solve the low electron energy problem of direct current arc. Through experimental analyzing the electrical, spectral, and optical characteristics of the arc, the effect of impulse current generator (ICG) on improving electron energy is discussed. The results show that the ICG consumes more energy to enhance the strength of arc discharge, and therefore electron energy is increased in a microsecond scale. In addition, it is found that the electron energy of the arc discharge can be adjusted by varying inductance, capacitance, and discharge tube: increasing the inductance or capacitance can increase the electron energy firstly and then decrease it. In adjusting the three adjustable components, adjusting the inductor is the most effective method, followed by adjusting the capacitor, and adjusting the repetition frequency has the least effect. The reason is discussed, and it is believed that the results are related to leakage inductance and distributed capacitance.
Evaluation of maximum power point tracking methods for a marine current energy converter
Authors: Fjellstedt Christoffer , Forslund Johan , Goude Anders , Thomas Karin
Published: August 2024

Marine current power is attracting more attention as a renewable energy option. Similar to wind power, marine current power often requires a maximum power point tracking (MPPT) method to optimize power extraction from the free‐flowing water. Research into MPPT methods for marine current power remains limited. Therefore, this paper presents a comprehensive investigation of MPPT methods for marine current power, building upon similar research in wind power. Three methods, namely the optimal tip speed ratio (OTSR), optimal torque (OT), and two variants of the perturb and observe (P&O) method, are explored. Using a simulation model developed for a specific marine current energy converter, where hydrodynamic calculations are coupled with electrical simulations, the study demonstrates that the OTSR method achieves MPPT with a comparably fast convergence time. After a change in water speed, the OTSR method achieves optimal operation within two turbine rotations. Additionally, the P&O methods are shown to achieve MPPT, albeit with a significantly longer convergence time. However, the P&O methods can be more convenient since no model of the system is required, and no water speed measurements are necessary. The proposed implementation of the OT method underperforms but positions the system close to the optimal operational point.
Grid frequency regulation through virtual power plant of integrated energy systems with energy storage
Authors: Xu Tao , Wang Rujing , Meng He , Li Mengchao , Ji Yu , Zhang Ying , Zhao Jianli , Xiang Jiani
Published: August 2024

Owing to the widespread integration of renewable distributed energy resources (DERs), the system frequency stability has been jeopardized by the non‐inertial and stochastic units caused by power electronic devices. The integrated energy system (IES) that combines multi‐vector energy resources can provide energy compensation among sub‐systems in a coordinated fashion to further alleviate the volatility on the electric grid. Under the framework of IES, a virtual power plant (VPP) can aggregate multi‐entities and multi‐vector energy resources to participate in the frequency regulation service while pursuing profit maximization. A three‐stage optimal scheduling model of IES‐VPP that fully considers the cycle life of energy storage systems (ESSs), bidding strategies and revenue settlement has been proposed in this paper under the modified PJM frequency regulation market framework to motivate the aggregated resources to respond to the frequency regulation market actively. The simulation results under various scenarios have verified the feasibility and effectiveness of the proposed model through techno‐economic analysis, the advantages of IES‐VPP have been demonstrated compared with a single vector energy system.
Resilience enhancement by line hardening for communication routing considering renewable energy sources in cyber‐physical power systems
Authors: Li Xiaolong , Li Wenyi , Wang Nana , Li Le , Gong Xuan
Published: August 2024

Communication routing of cyber‐physical power systems (CPPS) with the high penetration of renewable energy sources (RES) plays an important role in the resilience enhancement against disasters, natural and man‐made alike. Therefore, a trilevel optimization model is proposed for the CPPS resilience enhancement with the RES against extreme events. The upper‐level model identifies optimal hardening lines of both the transmission and communication networks with consideration of the communication routing constraints. The middle‐level model identifies the attacked lines to maximize load shedding of the power system. The effects of RES uncertainty and communication routings on resilience enhancement are analysed. The lower‐level model attains an optimal allocation strategy of power generation to minimize load shedding. The model is solved by the column‐and‐constraint generation algorithm. Case studies are conducted on the IEEE 14‐bus, RTS 24‐bus, and 118‐bus system. The results show that the proposed hardening strategy can effectively ensure the adaptiveness of the transmission network and communication routing to improve the resilience of CPPS to extreme events. Moreover, it is observed that the load loss and total investment cost are heavily affected without and with RES.
Defeating angle tracking: A comprehensive analysis of scan rate modulation jamming against sequential lobing radars
Authors: Kucuk Mustafa , Nuhoglu Mustafa Atahan , Durak‐Ata Lutfiye , Cirpan Hakan Ali
Published: August 2024

The authors analyse the sequential lobing radar (SLR) resistance against the scan rate modulation (SRM) jamming technique. Unlike previous studies, the authors analyse SLRs with sinc antenna patterns, enabling investigation of the sidelobe region's vulnerability. By incorporating second‐order angular tracking loops (SOATLs), the first analysis of break‐lock probability for SLRs under SRM jamming is introduced. The analysis reveals the influence of SOATL parameters (damping ratio and natural frequency) on both angular root‐mean‐square‐error at low jamming‐to‐signal‐ratio (JSR) region and break‐lock probability at high JSR region. Additionally, the impact of squint angle on SLR resistance to SRM jamming is examined. Furthermore, the optimal duty cycle as a function of JSR, which maximises break‐lock probability is presented. Significantly, the theoretical results support the 20 dB JSR requirement for SRM effectiveness, often cited experimentally in literature, and extend the theoretical analysis of the SRM technique carried out for the main lobe region of SLRs. This finding bridges the gap between theoretical analysis and practical observations.
Disentangling the Faraday rotation sky
Authors: Hutschenreuter Sebastian , Haverkorn Marijke , Frank Philipp , Raycheva Nergis C. , Enßlin Torsten A.
Published: August 2024

Context. Magnetic fields permeate the diffuse interstellar medium (ISM) of the Milky Way, and are essential to explain the dynamical evolution and current shape of the Galaxy. Magnetic fields reveal themselves via their influence on the surrounding matter, and as such are notoriously hard to measure independently of other tracers.

Aims. In this work, we attempt to disentangle an all-sky map of the line-of-sight (LoS)-parallel component of the Galactic magnetic field from the Faraday effect, utilizing several tracers of the Galactic electron density, ne. Additionally, we aim to produce a Galactic electron dispersion measure map and quantify several tracers of the structure of the ionized medium of the Milky Way.

Methods. The method developed to reach these aims is based on information field theory, a Bayesian inference framework for fields, which performs well when handling noisy and incomplete data and constraining high-dimensional-parameter spaces. We rely on compiled catalogs of extragalactic Faraday rotation measures and Galactic pulsar dispersion measures, a well as data on bremsstrahlung and the hydrogen α spectral line to trace the ionized medium of the Milky Way.

Results. We present the first full sky map of the LoS-averaged Galactic magnetic field. Within this map, we find LoS-parallel and LoS-averaged magnetic field strengths of up to 4 µG, with an all-sky root mean square of 1.1 µG, which is consistent with previous local measurements and global magnetic field models. Additionally, we produce a detailed electron dispersion measure map that agrees with existing parametric models at high latitudes but suffers from systematic effects in the disk. Further analysis of our results with regard to the 3D structure of ne reveals that it follows a Kolmogorov-type turbulence for most of the sky. From the reconstructed dispersion measure and emission measure maps, we construct several tracers of variability in ne along the LoS.

Conclusions. This work demonstrates the power of consistent joint statistical analysis including multiple datasets and physical quantities and defines a road map toward a full three-dimensional joint reconstruction of the Galactic magnetic field and the ionized ISM.
A Study on the Mechanism of How Beauty Influencers Affect Consumer Purchasing Behavior Taking the Douyin Celebrity Yongzai Leo as an Example
Authors: Gao Yang
Published: August 2024

This research examines the impact of popular beauty blogger Yongzai Leo on Douyin and investigates how beauty influencers affect consumer buying habits by creating and engaging with content. The research gathered Yongzai Leo video interaction data with crawler technology and examined how content quality, trust, and interactivity influence consumers’ purchase intention using structural equation model (SEM). The findings indicate that consumers’ intention to make a purchase is greatly influenced by the quality of content, trustworthiness, and level of interaction, suggesting that high-quality content, genuine recommendations, and engaging interactions can boost fans’ purchase intention. This research uncovers the crucial elements for beauty bloggers to build authority and impact consumer buying habits on social media platforms, offering important insights and ideas for brand promotion.
Seating Zones and Pricing Strategies for Meany Hall
Authors: Fang Wei , Le Rongrong , Lu Chris , Advisor Hanyang Yu , Billey Sara , Wang Alex
Published: August 2024

The Meany Center for Performance Arts is exploring the optimal seating zone arrangement and pricing strategy for its main theater with approximately 1200 seats divided into four zones. Given the historical patron demand, the goal is to maximize net profits by adjusting ticket prices based on zone quality, customers’ sensitivity to pricing, popularity and the type of performance. We first estimate the demand function through linear regression in double log form following the paper “Revenue and attendance simultaneous optimization in performing arts organization” (Baldin, Bille, Ellero, and Favaretto 2018). Using this demand function, we then solve a nonlinear maximization problem through PYTHON’s Gurobi packages to get the optimal value of ticket price for maximal profits. Overall, this project will enhance profit for Meany Hall, provide pricing insights for future performances, and demonstrate the application of economic theories and discrete math modeling to benefit the community.
Stock Price Prediction Using Deep-Learning Models: CNN, RNN, and LSTM
Authors: Cao Ruixun
Published: August 2024

With the rapid development of the economy, stock markets or equity markets have an important role nowadays. More and more people participate in stock investment, the rise or the fall in prices is vital and closely related to investors’ earnings. The basic way uses linear or non-linear algorithms, but the stock market has many factors, so it is highly non-linear prediction, so it is helpless to use one simple model, so this paper proposes to figure out a good deep-learning model to capture and analyze the data of six companies from Yahoo Finance by comparing the fitness of three famous neural network: CNN, RNN, and LSTM. The Sliding-Window model was applied to make future predictions in time series. The results of the models were calculated by using MSE, MAE, and MAPE.
Research on the Application and Optimization of Mathematical Models in Financial Market Risk Management
Authors: Pan Yuyang
Published: August 2024

This paper applied mathematical models to conduct an in-depth discussion and empirical analysis of financial market risk management. The daily rate of return data on the S&P 500 index, selected through data processing, included data cleaning, return calculation, data standardization, construction of the GARCH (1, 1) model, and a Copula model for predicting and analyzing risks. Empirical results indicate that the GARCH model has good simulation in capturing the market volatility change, while the Copula model holds clear advantages in modeling multivariate risk dependencies. In the modern economy, managing risks in the financial market plays a vital role. Optimization algorithms such as genetic algorithms and Bayesian optimization significantly improve the prediction accuracy and computational efficiency of the model. Compared with traditional historical simulation methods, these models perform better in risk prediction indicators (VaR and ES), proving their practicality and effectiveness in actual risk management. The research results verify that advanced mathematical models and optimization methods have important application value in financial market risk management, providing a scientific decision-making basis for investors and risk managers.
Research on the Decision Method of R&D Investment in State Owned Enterprises Considering Multiple Factors
Authors: Zhu Yongjuan , Wang Longfeng , Shang Wenying
Published: August 2024

Research and development investment is a necessary resource guarantee for technological innovation and progress. Increasing research and development investment to promote production efficiency and gain competitive advantages is a strategic choice for many state-owned enterprises in China. The R&D investment of state-owned enterprises is the decision result of balancing external market demand and internal resource environment. Research suggests that state-owned enterprises should increase R&D investment in core business areas and strategic emerging areas, strengthen cooperation with external advantageous technological resources, form a virtuous cycle of “R&D - technological progress - dividend generation - R&D”, and achieve long-term sustainable development.
Current Trends in Hepatocellular Carcinoma Therapies in China
Authors: Zhang Ying , Wang Yong , Guo Jin-He , Lu Jian
Published: August 2024

Hepatocellular carcinoma (HCC) is a malignant tumor that is particularly prevalent in China, making up almost 50% of HCC cases worldwide. Compared to HCC patients in Europe, North America, and the Asia-Pacific region, Chinese patients exhibit unique characteristics in etiology, demographics (age, gender, geographic location, economic status), biological behavior, treatment options, and prognosis. While hepatitis B virus remains a primary cause of HCC in China, there is a growing trend of alcoholic liver disease and nonalcoholic fatty liver disease in the country. A special pathological staging guidance distribution of therapies for HCC was developed by the Chinese Medical Association. In China, there is a diverse array of therapeutic options for treating HCC, including liver resection, liver transplantation, intra-arterial therapies, ablation, radiotherapies, systemic therapies, and traditional Chinese medicine. The treatment of HCC has multiple permutations and combinations of modalities. Due to the varying stages of HCC and individual patient differences, the multidisciplinary team model is often necessary to tailor treatment strategies and optimize clinical outcomes. Meanwhile, to enhance survival benefits and effectively improve the prognosis and life quality of patients with HCC, Chinese experts are actively engaged in conducting clinical trials to identify potential beneficiary populations. This review aims to elaborate on the therapeutic features of HCC in China to present to the world the innovative approaches and comprehensive care offered to Chinese HCC patients.
Fulgence Raymond: from rural life and veterinary medicine to Charcot's successor at La Salpêtrière Hospital
Authors: Teive Hélio A. G. , Correa Catarina Dantas , Coutinho Léo , Camargo Carlos Henrique Ferreira , Walusinski Olivier
Published: August 2024

This paper provides a historical overview of Professor Fulgence Raymond, Charcot's eldest pupil, who was chosen as his successor. It explores Raymond's origins as a veterinary surgeon, his evolution as a neurologist under Charcot's mentorship, and his tenure as the professor's successor at the La Salpêtrière Hospital in Paris, France, from 1894 to 1910.