bluuebunny/crossref_metadata_2025 huggingface dataset:
Roman Witold Ingarden’s discussions on artistic style: A contribution
Authors: Garlej Beata
Published: July 2024

The present article attempts to reconstruct Polish philosopher and aesthetician Roman Witold Ingarden’s views concerning his understanding of the concept of artistic style. Starting from the hypotheses provided by the content of the outline of his ultimately unwritten work, Poetics, I have chosen selected threads of the discussions held by Ingarden in Lviv before the war, supplemented by the content of the phenomenologist’s lectures from the 1960s, as essential substantive background. Analyzing the material indicated, I demonstrate that it is appropriate for Ingarden’s understanding of artistic style to correlate this concept with the category of aesthetic concretization. Consequently, I draw a conclusion as to the primary role of some aspects of a literary work – appearances, which allow us to inquire into the properties of artistic style practically as a result of their function of decorativeness and polyphony. A condensed comparative analysis of the two functions, as related to excerpts from Gustave Flaubert’s Madame Bovary and Stanisław Ignacy Witkiewicz’s Insatiability, concludes the account of Ingarden’s conception of artistic style, which turns out to be a unique aphenomenal phenomenon.
Peer relationships and study wellbeing: upper secondary students’ experiences
Authors: Tikkanen Lotta , Anttila Henrika , Ulmanen Sanna , Pyhältö Kirsi
Published: July 2024

The role of peer relationships in a student’s study wellbeing has been emphasised in research. However, the development of functional relationships with peers in educational settings cannot be taken for granted. In this study, we aimed to understand the variations in upper secondary school students’ experiences of peer relationships in terms of sense of relatedness, cognitive and affective empathy skills and peer support for studying, and whether variation in these regards are related to study wellbeing. Two hundred and eighty Finnish upper secondary education students participated in the study. The data were analysed using latent profile analysis (LPA). Three distinct peer relationship profiles were detected among the students. Most of the students belonged to the functional peer relationship profile, while a minority belonged to either isolated or emotionally unrelated profiles. The students in the latter two profiles had a higher risk of experiencing challenges in study wellbeing in terms of reduced levels of study engagement and higher levels of study burnout symptoms. The findings imply that students in upper secondary education might need different kinds of support in building functional peer relationships. For example, some of them might benefit from learning empathy skills, while others might need support to meet their need for a sense of relatedness among peers.
Arbuscular mycorrhizal fungi affect early phenological stages of three secondary vegetation species in a temperate forest
Authors: Vázquez-Santos Yasmin , Castillo-Argüero Silvia , Montaño Noé Manuel , Espinosa-García Francisco Javier , Flores-Ortiz César , Martínez-Orea Yuriana
Published: July 2024

The relationship between arbuscular mycorrhizal fungi (AMF) and secondary vegetation (SV) species at early phenological stages is critical for the successful establishment of these plants on disturbance sites in temperate forests. The main objective of this research is to evaluate the effect of AMF colonization on the early phenological stages (germination and early growth) of three shrub species present in the SV of a temperate forest in central Mexico. We collected soil from different sites in theAbies religiosaforest in central Mexico. We collected seeds ofAcaena elongata,Ageratina glabrata, andSolanum pubigerum. We used a controlled experimental design with pasteurized soil (-AMF treatments) and unpasteurized soil (+ AMF treatments). We monitored germination percentage, growth (shoot and root weight and total biomass), AMF root colonization, and the mycorrhizal response index (MRI) for each plant species. All three species tested benefited by AMF, showing higher germination rates. Shoot and root weight and total biomass were significantly higher in the + AMF treatment.Solanum pubigerumshowed greater stem length andAgeratina glabratashowed greater root development due to AMF.Ageratina glabrataandAcaena elongatawere the most responsive to AMF as indicated by MRI. This research underscores the critical role of AMF in the early phenological stages of SV and highlights the potential ecological benefits of AMF in supporting plant germination and plant growth. These results suggest that AMF enhance germination and early growth of secondary vegetation species, which can be considered in management plans for forest ecosystems.
Determination of persistent organic pollutants in urban and peri-urban wastewater sludge: environmental and carcinogenic human risk assessment in the case of land application
Authors: Bruzzoniti Maria Concetta , Tumiatti Vander , Quazzo Armando , Beldean-Galea Mihail Simion , Del Bubba Massimo , Rivoira Luca
Published: July 2024

The management of digested sludge derived from treatment water plants is a problem worldwide due to the possible transfer of contamination from sludge to amended soil and, in turn, to humans. Within this work, through a chemometric experimental design, a robust GC–MS method for the simultaneous determination of two classes of micropollutants of concern (polycyclic aromatic hydrocarbons—PAHs—and polychlorinated biphenyls—PCBs—including dioxin-like compounds) was developed using microwave-assisted extraction (MAE). The method, which showed interesting greenness features in compliance with the 12 principles of Green Chemistry, allowed PCB and PAH extraction with recoveries higher than 75% (RSD < 14%) with method detection limits between 4.6 and 11.5 µg kg−1 (PAHs) and between 6.9 and 13.7 µg kg−1 (PCBs), without preconcentration. The matrix effect was below 20%. The validated protocol allowed the characterization of two digested sludges sampled in an urban and a peri-urban district, representative models of two scenarios of different anthropic impacts. This study highlighted higher contamination for the sludge derived from the urban area, accounted for by the 4-ring PAHs. In addition, since carcinogenic PAHs were detected, the environmental risk (by mean of the comparison of predicted vs predicted no-effect concentrations) and the carcinogenic human risk from dermal contact (through the calculation of the adsorbed lifetime average daily dose) were assessed in the case of soils amended with the sludges considered, pointing out that the measured concentrations do not pose a risk.
The effect of spatial lag on modeling geomatic covariates using analysis of variance
Authors: Aquiles E. Darghan C. , Darlley S. Taborda L. , Nair J. González S. , Carlos A. Rivera M. , Jesús E. Ospina N.
Published: July 2024

In recent years, statistical methods have been developed that include spatial considerations, for example, those that incorporate data with georeferencing. The descriptive part of geographical information systems currently provides many visualization and analysis tools; however, in terms of analysis, these systems are still quite limited, therefore, ignorance of these limitations may result in data with spatial effects being treated with conventional statistical methods for non-spatial use, which can certainly invalidate the excellent work of data capture with advanced tools such as those that are used daily in the geomatic context. This prompted the current document, drawing attention to how geomatic information analyzed with statistical methods that imply independence in modeled observations can be invalid. The Moran index is compared with a proposal for a spatial lag coefficient in the context of experimental design so that users of variance analysis do not apply this well-known procedure in a ritualistic way, perhaps revising some assumptions and perhaps ignoring more important ones. The distortion of the p value generated from the analysis of variance is clear in the presence of spatial dependence. In this case, it is associated with the lag or spatial overlap. The methodology is easy to apply in other designs with the development of the design matrix, its reparameterization and the choice of the respective weight matrix. This may cause users to reconsider the traditional method of analysis and incorporate some appropriate analysis methodology to address spatial effects present in data or in outputs from the modeling process.
Reindeer prey mobility and seasonal hunting strategies in the late Gravettian mammoth steppe
Authors: Pryor A. J. E. , Nesnídalová T. , Šída P. , Lengyel G. , Standish C. D. , Milton J. A. , Cooper M. J. , Hambach B. , Crowley J. , Wilczyński J.
Published: July 2024

Reindeer are part of the faunal suite that dominated central Europe during the last glacial cycle. Their importance to Late Gravettian hunters as prey and a source of raw materials (hide, bone, antler) is well attested, however the context of Late Gravettian reindeer predation is lesser understood. This paper presents an investigation of human and reindeer predator-prey interactions at the Late Gravettian kill-butchery site of Lubná VI, Czech Republic. We reconstruct seasonal mobility (87Sr/86Sr, δ18O), diet (δ13C, δ15N) and season of death (dental cementum) of up to nine reindeer prey, to inform on the strategic choices made by Late Gravettian hunters. Results indicate that most hunted reindeer lived year-round in the foothills of the Bohemian-Moravian highlands near where Lubná is located, at altitudes between ~ 200–450 m above present sea level, while a smaller number showed evidence of seasonal migration between this area and the open plains of the Elbe river corridor (Bohemian Cretaceous basin). No evidence for long distance migration of reindeer was detected, indicating that productive local environments were supporting reindeer herds within a single annual territory. Meanwhile, areas higher than ~ 450 m above present sea level were avoided entirely by all analysed individuals, consistent with these areas being topographic barriers to movement due to climate severity. We conclude that hunters visited Lubná as part of a logistically-organised subsistence strategy, deliberately targeting reindeer in late autumn when fat supplies, hides and antler are in prime condition knowing that they would reliably encounter their prey at this location.
Educator wellbeing and family engagement in Australian early learning settings: perspectives of early childhood educators and families
Authors: Murray Lisa , Eadie Patricia , Fong Maria , Liley Kate , Markham Penny , Hardy Kirsten
Published: July 2024

While the COVID-19 pandemic brought with it multiple challenges for families and the Early Childhood Education and Care (ECEC) workforce, it also highlighted the essential role of ECEC in the lives of children and families and presented unique opportunities for innovation and learning. The current study sought to explore learnings from this uniquely challenging period, including the factors and strategies that best supported educator wellbeing and family engagement in ECEC settings, from the perspectives of families, centre directors and educators. In 2021, 104 Centre Directors/Educators and 102 families completed online surveys exploring wellbeing and educator–family relationships. Correlations suggest that robust professional wellbeing and resilience are potential enabling factors for strong family engagement, and that supportive organisational structures in ECEC settings are a protective factor for both educator wellbeing and family engagement. In addition, five effective family engagement strategies were derived from the qualitative data: (1) drawing on personal and professional knowledges to enrich children’s learning at home; (2) prioritising regular and reliable communication with families; (3) maintaining familiar relationships and a sense of community; (4) providing person-centred support and a bridge to other services; and (5) nurturing mutually supportive educator–family relationships. Learnings provide important insights that may inform ongoing quality improvements across different ECEC contexts, and to help safeguard against the negative impacts of future global crises.
Household transmission of Omicron variant of SARS-CoV-2 under conditions of hybrid immunity—a prospective study in Germany
Authors: Klee Bianca , Diexer Sophie , Xu Chao , Gottschick Cornelia , Hartmann Carla , Meyer-Schlinkmann Kristin Maria , Kuhlmann Alexander , Rosendahl Jonas , Binder Mascha , Gekle Michael , Girndt Matthias , Höll Jessica I. , Moor Irene , Sedding Daniel , Moritz Stefan , Frese Thomas , Mikolajczyk Rafael
Published: July 2024

Purpose

We investigated the protection offered by vaccinations and previous infections for the household transmission of Omicron variant of SARS-CoV-2.

Methods

34,666 participants of the German DigiHero cohort study with two or more household members were invited to a prospective household transmission study between June and December 2022. In case of a positive SARS-CoV-2 test in a household, symptom diaries were completed for at least 14 days. Dry blood spots (DBS) were taken from all household members at the beginning and six to eight weeks later. DBS were analyzed for SARS-CoV-2 antibodies.

Results

1191 individuals from 457 households participated. The risk of acquiring a SARS-CoV-2 infection decreased with higher S-titer levels at the time of exposure (from 80% at titer of 0 binding antibody units (BAU)/ml to 20% at titer of 3000 BAU/ml) and increased linearly with the time since vaccination/previous infection (20% for less than one month to 80% at one year). Transmission probability was also reduced when the symptoms of the primary case were mild and if preventive measures were implemented.

Conclusion

Vaccinations/previous infections offer a high protection against infection with the Omicron variant for a few months only, supporting the notion of seasonal circulation of the virus.
L*—An index for evaluating long range performance of autonomous underwater vehicles (AUVs)
Authors: Zhu Manfu , Ma Liran , Luo Jianbin
Published: July 2024

Autonomous underwater vehicles (AUVs) have various applications in both military and civilian fields. A wider operation area and more complex tasks require better overall range performance of AUVs. However, until recently, there have been few unified criteria for evaluating the range performance of AUVs. In the present work, a unified range index, i.e., L*, considering the cruising speed, the sailing distance, and the volume of an AUV, is proposed for the first time, which can overcome the shortcomings of previous criteria using merely one single parameter, and provide a uniform criterion for the overall range performance of various AUVs. After constructing the expression of the L* index, the relevant data of 49 AUVs from 12 countries worldwide have been collected, and the characteristics of the L* range index in different countries and different categories were compared and discussed. Furthermore, by analyzing the complex factors affecting the range index, methods to enhance the L* range index value, such as efficiency enhancement and drag reduction, have been introduced and discussed. Under this condition, the work proposes a unified and scientific criterion for evaluating the range performance of AUVs for the first time, provides valuable theoretical insight for the development of AUVs with higher performance, and then arouses more attention to the application of the cutting-edge superlubricity technology to the field of underwater vehicles, which might greatly help to accelerate the coming of the era of the superlubricitive engineering.
Recent developments in functional organic polymer coatings for biomedical applications in implanted devices
Authors: Yang Yinuo , Jia Yiran , Zhao Yanran , Wang Haimang , Zhang Hongyu
Published: July 2024

Organic polymer coatings have been commonly used in biomedical field, which play an important role in achieving biological antifouling, drug delivery, and bacteriostasis. With the continuous development of polymer science, organic polymer coatings can be designed with complex and advanced functions, which is conducive to the construction of biomedical materials with different performances. According to different physical and chemical properties of materials, biomedical organic polymer coating materials are classified into zwitterionic polymers, non-ionic polymers, and biomacromolecules. The strategies of combining coatings with substrates include physical adsorption, chemical grafting, and self-adhesion. Though the coating materials and construction methods are different, many biomedical polymer coatings have been developed to achieve excellent performances, i.e., enhanced lubrication, anti-inflammation, antifouling, antibacterial, drug release, anti-encrustation, anti-thrombosis, etc. Consequently, a large number of biomedical polymer coatings have been used in artificial lungs, ureteral stent, vascular flow diverter, and artificial joints. In this review, we summarize different types, properties, construction methods, biological functions, and clinical applications of biomedical organic polymer coatings, and prospect future direction for development of organic polymer coatings in biomedical field. It is anticipated that this review can be useful for the design and synthesis of functional organic polymer coatings with various biomedical purposes.
Predictive air combat decision model with segmented reward allocation
Authors: Li Yundi , Yuan Yinlong , Cheng Yun , Hua Liang
Published: July 2024

In air combat missions, unmanned combat aerial vehicles (UCAVs) must take strategic actions to establish combat advantages, enabling effective tracking and attacking of enemy UCAVs. Currently, a lot of reinforcement learning algorithms are applied to the air combat mission of unmanned fighter aircraft. However, most algorithms can only select policies based on the current state of both sides. This leads to the inability to effectively track and attack when the enemy performs large angle maneuvering. Additionally, these algorithms cannot adapt to different situations, resulting in the unmanned fighter aircraft being at a disadvantage in some cases. To solve these problems, this paper proposes predictive air combat decision model with segmented reward allocation for air combat tracking and attacking. On the basis of the air combat environment, we propose the prediction soft actor-critic (Pre-SAC) algorithm, which combines the prediction of enemy states with the states of UCAV for model training. This enables the UCAV to predict the next move of the enemy UCAV in advance and establish a greater air combat advantage for us. Furthermore, by adopting a segmented reward allocation model and combining it with the Pre-SAC algorithm, we propose the segmented reward allocation soft actor-critic (Sra-SAC) algorithm, which solves the problem of UCAVs being unable to adapt to different situations. The results show that the prediction-based segmented reward allocation the Sra-SAC algorithm outperforms the traditional soft actor-critic (SAC) algorithm in terms of overall reward, travel distance, and relative advantage.
Feature selection for hybrid information systems based on fuzzy $$\beta $$ covering and fuzzy evidence theory
Authors: Ma Xiaoqin , Hu Huanhuan , Zhang Qinli , Xu Yi
Published: July 2024

Feature selection plays a crucial role in machine learning, as it eliminates data noise and redundancy, thereby significantly reducing computational complexity and enhancing the overall performance of the model. The challenges of feature selection for hybrid information systems stem from the difficulty in quantifying the disparities among nominal attribute values. Furthermore, a significant majority of the current methodologies exhibit sensitivity to noise. This paper introduces techniques that address the aforementioned issues from the perspective of fuzzy evidence theory. First of all, a new distance incorporating decision attributes is defined, and then a relation between fuzzy evidence theory and fuzzy $$\beta $$
β
covering with an anti-noise mechanism is established. In this framework, two robust feature selection algorithms for hybrid data are proposed based on fuzzy belief and fuzzy plausibility. Experiments on 10 data sets of various types show that compared with the other 6 state-of-the-art algorithms, the proposed algorithms improve the anti-noise ability by at least 6% with higher average classification accuracy. Therefore, it can be concluded that the proposed algorithms have excellent anti-noise ability while maintaining good feature selection ability.
Monetary incentives and the contagion of unethical behavior
Authors: Le Maux Benoît , Masclet David , Necker Sarah
Published: July 2024

We examine how monetary incentives and information about others’ dishonesty affect lying decisions and whether these two dimensions interact with each other. Our experiment consists of a repeated cheating game where we vary the monetary incentives (Low, High, and Very High) and information about others’ dishonesty (With or Without information). We find that dishonesty decreases when payoffs are Very High. Information has only a weak positive effect on average. Conditioning on beliefs, we find that those who overestimate (underestimate) cheating reduce (increase) dishonesty. Information and payoffs do not interact with each other.
Theorie und Empirie der Vergleichenden Koalitionsforschung: Stand und Ausblick
Authors: Bräuninger Thomas , Debus Marc
Published: July 2024

Das Regieren in Mehrparteienkabinetten hat sich zum Normalfall in modernen Demokratien entwickelt. Daher verwundert es nicht, dass die Analyse des Prozesses der Bildung, des Regierens in und der Beendigung von Koalitionsregierungen zu einem Schwerpunkt der Vergleichenden Politikwissenschaft geworden ist. Wir legen in diesem Literature Review den Stand der Forschung zu Koalitionsregierungen dar, indem wir die jüngere Entwicklung in der Koalitionstheorie betrachten, um anschließend die Erkenntnisse insbesondere in den Bereichen der Analyse von Koalitionen zu beleuchten, die in den letzten Jahren deutlich an Beachtung gewonnen haben. Dazu zählen die Auswirkungen der institutionellen Merkmale politischer Systeme, etwa das Bestehen und die Ausgestaltung von Mehrebenenstrukturen oder die Kompetenzen von Parlamenten insbesondere im Kontext der Investitur einer neuen Regierung, sowie die Perzeption des Regierens in Koalitionen durch die Wähler und die Analyse der Koalitionsverhandlungsdauer und der Koalitionsabkommen. Abschließend diskutieren wir Ansätze für Fragestellungen, die vielversprechend für die weitere Entwicklung der wissenschaftlichen Analyse von Koalitionsregierungen sein können, insbesondere aufgrund der massiven Fortschritte im Bereich der quantitativen Daten- und Textanalyse.
Molecular mechanism of a coastal cyanobacterium Synechococcus sp. PCC 7002 adapting to changing phosphate concentrations
Authors: Sun Qiao-Wei , Gao Yu , Wang Jordan , Fu Fei-xue , Yong Cheng-Wen , Li Shuang-Qing , Huang Hai-Long , Chen Wei-Zhong , Wang Xin-Wei , Jiang Hai-Bo
Published: July 2024

Phosphorus concentration on the surface of seawater varies greatly with different environments, especially in coastal. The molecular mechanism by which cyanobacteria adapt to fluctuating phosphorus bioavailability is still unclear. In this study, transcriptomes and gene knockouts were used to investigate the adaptive molecular mechanism of a model coastal cyanobacterium Synechococcus sp. PCC 7002 during periods of phosphorus starvation and phosphorus recovery (adding sufficient phosphorus after phosphorus starvation). The findings indicated that phosphorus deficiency affected the photosynthesis, ribosome synthesis, and bacterial motility pathways, which recommenced after phosphorus was resupplied. Even more, most of the metabolic pathways of cyanobacteria were enhanced after phosphorus recovery compared to the control which was kept in continuous phosphorus replete conditions. Based on transcriptome, 54 genes potentially related to phosphorus-deficiency adaptation were selected and knocked out individually or in combination. It was found that five mutants showed weak growth phenotype under phosphorus deficiency, indicating the importance of the genes (A0076, A0549-50, A1094, A1320, A1895) in the adaptation of phosphorus deficiency. Three mutants were found to grow better than the wild type under phosphorus deficiency, suggesting that the products of these genes (A0079, A0340, A2284–86) might influence the adaptation to phosphorus deficiency. Bioinformatics analysis revealed that cyanobacteria exposed to highly fluctuating phosphorus concentrations have more sophisticated phosphorus acquisition strategies. These results elucidated that Synechococcus sp. PCC 7002 have variable phosphorus response mechanisms to adapt to fluctuating phosphorus concentration, providing a novel perspective of how cyanobacteria may respond to the complex and dynamic environments.
Implementation and insights from the MedXMentor structured mentorship program for undergraduate health science students at Mbarara University, Uganda
Authors: Tamale Elvis , Atuhairwe Irene , Ssemwogerere Arnold , Muhimbura Brian , Atimango Lorna , Malinga Paddy Derrick , Mulungi Jonathan , Ssekitto Joseph , Naigaga Josephine , Kintu Timothy Mwanje , Masood Kiran Mitha , Ohuruogu Victor , Ngonzi Joseph
Published: July 2024

Background

Mentorship is essential for education and career development in health-related fields, yet Sub-Saharan African universities often lack structured programs. To address this, the MedXMentor program was established at Mbarara University of Science and Technology (MUST) to provide structured mentorship to undergraduate health sciences students in Uganda. This paper outlines insights gained from implementing the MedXMentor hybrid mentorship program.

Methods

Using a mixed-methods approach, the study employed the Kirkpatrick Model of Evaluation to assess mentees’ reactions, learning, behavior, and goal achievement. Data were collected via Google Form surveys, feedback forms, mentoring logs, and session attendance records. Descriptive statistics and thematic analysis provided a comprehensive understanding of the program’s impact.

Results

The program served 80 mentees, with 48 participating in one-on-one mentorship and 32 in group sessions. It enlisted 24 mentors, mainly from the medical field. Between April and September 2022, eight online group sessions were held, with an average attendance rate of 52%. These sessions focused on project planning, grant writing, and soft skills development, resulting in improved mentee comprehension and skill acquisition. Mentees reported an enhanced understanding of project planning, grant writing, communication, leadership, and teamwork. Their experiences were categorized into four themes: Mentor Engagement, Goal-Oriented Study, Skills and Professional Development, and High-Yield Mentor–Mentee Engagements.

Conclusion and recommendations

Implementing the MedXMentor program proved effective in providing crucial mentorship and equipping students with vital academic and professional skills. The program highlighted its potential to bridge the mentorship gap in low-resource settings. By empowering future healthcare professionals in Africa, MedXMentor exemplifies how mentorship initiatives can drive significant advancements in healthcare education and practice.
Towards more effective summative assessment in OBE: a new framework integrating direct measurements and technology
Authors: Ali Qutaiba I.
Published: July 2024

This paper contributes to the ongoing efforts aimed at enhancing Outcome-Based Education (OBE) assessment methodologies by addressing some critical gaps and exploring new solutions. Our work focuses on two main areas: firstly, this study proposes an improved assessment method for OBE. It refines traditional approaches by classifying course materials according to their relevance to learning outcomes, weighting them by importance, connecting these outcomes to student goals and assigning difficulty levels to modules. All modules are directly assessed through a final exam with a consistent rubric, and student success is measured by a holistic score that considers the weighted attainment levels across all learning outcomes and modules. Secondly, this paper provides theoretical guidance for integrating Generative Artificial Intelligence (AI) and blockchain technologies into OBE assessment. It examines the potential impact of these technologies at various assessment stages, laying the groundwork for practical implementation.
Improving CONUS Convective‐Scale Forecasting With Simultaneous Multiscale Data Assimilation
Authors: Wang Yongming , Wang Xuguang
Published: July 2024

Accurate initialization of CONUS convective‐scale forecasting requires a proper estimate of all resolved scales. This study further develops and examines a simultaneous multiscale data assimilation (MDA) approach in EnVar with modulated cross‐scale and cross‐variable covariances. The method is examined using 10 retrospective cases with the assimilation of both in situ and radar reflectivity observations (hereafter, SimMDA). The necessity of the modulated and therefore weakened cross‐covariances in simultaneous MDA for CONUS convective‐scale forecasting is first demonstrated. The relative benefits of increasing the decomposed‐scale number with increased computational cost in SimMDA are also discussed. The impact of the further developed simultaneous MDA method is revealed by comparing it with a commonly adopted DA approach (Baseline), which separately assimilates in situ and reflectivity observations using individual single‐scale localization. During DA cycling, SimMDA improves analysis accuracy for temperature and reflectivity and reduces biases in all variables compared to Baseline. SimMDA yields significantly better forecasts than Baseline for most lead times. Additional experiments are conducted to attribute such improvements in a case study. Specifically, an experiment the same as Baseline except using simultaneous MDA for reflectivity assimilation enhances cold pools and inflows and thus improves storms by making larger‐scale increments. An experiment the same as Baseline except using simultaneous MDA for in situ assimilation more properly constrains small‐scale covariances, leading to more reasonable correlations along the front and more accurate moisture near the dryline and consequently improved analyses and forecasts. Both effects together largely contribute to the overall improvements of SimMDA compared to Baseline.
Magma Differentiation, Contamination/Mixing and Eruption Modulated by Glacial Load—The Volcanic Complex of The Pleiades, Antarctica
Authors: Agostini Samuele , Leone Noemi , Smellie John L. , Rocchi Sergio
Published: July 2024

The Pleiades Volcanic Field is made up of some 20 monogenetic, partly overlapping scoria and spatter cones, erupted in the last 900 ka, cropping out from the ice close to the head of the Mariner Glacier in northern Victoria Land, Antarctica. Erupted products vary from hawaiite to trachyte, defining a complete mild Na‐alkaline differentiation trend. Mafic samples are characterized by multi‐elemental patterns typical of OIB magmas, moderately low 87Sr/86Sr (0.7037) and high 143Nd/144Nd (0.51284), with a clear within‐plate affinity, indicating a subcontinental lithospheric source. With increasing SiO2, 87Sr/86Sr ratios increase up to 0.7052 and 143Nd/144Nd decrease to 0.51277, supporting the hypothesis of open‐system evolution, with significant crustal assimilation during fractional crystallization. The erupted volume of most evolved products (∼7 km3), according to fractionation models, suggests that primitive magmas should have been more than 10 times larger, indicating the occurrence of a large magma plumbing system, unexpected for a volcanic field of monogenetic scoria cones. The occurrence of a complete fractionation trend with large magma chambers and large assimilation rate is unusual, if not unique, among the alkali basaltic volcanic fields and it is matched by a climax of activity during the last glacial maximum (30 ka), as indicated by new 40Ar‐39Ar ages (30 ± 3 ka and 25 ± 2 ka) for samples from the two most prominent edifices. Therefore, we hypothesize a role of a thick ice cap in suppressing eruptions and ultimately leading to prolonged magma residence time in the subsurface, favoring significant fractionation coupled with unusual high rates of crustal assimilation.
The Direct Radiative Effect of CO2 Increase on Summer Precipitation in North America
Authors: Liang Wengui , Zhao Ming , Tan Zhihong , Knutson Thomas , Dong Wenhao , Zhang Bosong
Published: July 2024

Precipitation changes in full response to CO2 increase are widely studied but confidence in future projections remains low. Mechanistic understanding of the direct radiative effect of CO2 on precipitation changes, independent from CO2‐induced SST changes, is therefore necessary. Utilizing global atmospheric models, we identify robust summer precipitation decreases across North America in response to direct CO2 forcing. We find that spatial distribution of CO2 forcing at land surface is likely shaped by climatological distribution of water vapor and clouds. This, coupled with local feedback processes, changes in convection, and moisture supply resulting from CO2‐induced circulation changes, could determine North American hydroclimate changes. In central North America, increasing CO2 may decrease summertime precipitation by warming the surface and inducing dry advection into the region to reduce moisture supply. Meanwhile, for the southwest and the east, CO2‐induced shift of subtropical highs generates wet advection, which might mitigate the drying effect from warming.
Erianin induces ferroptosis in GSCs via REST/LRSAM1 mediated SLC40A1 ubiquitination to overcome TMZ resistance
Authors: Mansuer Maierdan , Zhou Lin , Wang Chengbin , Gao Liang , Jiang Yang
Published: July 2024

In recent studies, erianin, a natural product isolated from Dendrobium chrysotoxum Lindl, has exhibited notable anticancer properties. Ferroptosis, a novel form of programmed cell death, holds potential as a strategy to overcome Temozolomide (TMZ) resistance in glioma by inducing ferroptosis in TMZ-resistant glioma cells. Here, utilizing various phenotyping experiments, including cell counting kit-8 (CCK-8) assays, EdU assays, transwell assays, neurosphere formation assays and extreme limiting dilution (ELDA) assays, we demonstrated that erianin exerts its anticancer activity on both TMZ sensitive and TMZ-resistant glioma stem cells (GSCs). Furthermore, we made an exciting discovery that erianin enhances TMZ sensitivity in TMZ-resistant GSCs. Subsequently, we demonstrated that erianin induced ferroptosis in TMZ-resistant GSCs and enhances TMZ sensitivity through inducing ferroptosis, which was confirmed by intracellular measurements of ROS, GSH, and MDA, as well as through the use of BODIPY (581/591) C11 and transmission electron microscopy. Conversely, the ferroptosis inhibitor ferrostatin-1 (Fer-1) blocked the effects of erianin. The underlying mechanism of ferroptosis induced by erianin was further explored through co-immunoprecipitation (Co-IP) assays, ubiquitination assays, protein stability assessments, chromatin immunoprecipitation (ChIP) assays and luciferase reporter gene assays. We found that erianin specifically targets REST, inhibiting its transcriptional repression function without altering its expression levels. Consequently, this suppression of REST’s role leads to an upregulation of LRSAM1 expression. In turn, LRSAM1 ubiquitinates and degrades SLC40A1, a protein that inhibits ferroptosis by exporting ferrous ions. By downregulating SLC40A1, erianin ultimately induces ferroptosis in TMZ-resistant GSCs. Taken together, our research demonstrates that the natural product erianin inhibits the malignant phenotype of GSCs and increases the sensitivity of TMZ in TMZ-resistant GSCs by inducing ferroptosis. These findings suggest erianin as a prospective compound for the treatment of TMZ-resistant glioma.
Characterization of brain transduction capability of a BBB-penetrant AAV vector in mice, rats and macaques reveals differences in expression profiles
Authors: Bunuales María , Garduno Angeles , Chillon Miguel , Bosch Assumpció , Gonzalez-Aparicio Manuela , Espelosin Maria , Garcia-Gomara Marta , Rico Alberto J. , Garcia-Osta Ana , Cuadrado-Tejedor Mar , Lanciego Jose L. , Hernandez-Alcoceba Ruben
Published: July 2024

Different screening methods are being developed to generate adeno-associated viral vectors (AAV) with the ability to bypass the blood-brain barrier (BBB) upon intravenous administration. Recently, the AAV9P31 stood out as the most efficient version among a library of peptide-displaying capsids selected in C57BL/6 mice using RNA-driven biopanning. In this work we have characterized in detail its biodistribution in different mouse strains (C57BL/6 and Balb/c), as well as in Sprague Dawley rats and non-human primates (Macaca fascicularis). Using GFP and NanoLuc reporter genes, we confirmed homogeneous infection and transgene expression across the CNS of mice injected intravenously with AAV9P31. A more restricted pattern was observed upon either intracerebroventricular or intraparenchymal injection. Following intravenous delivery, region- and cell-specific differential patterns of transduction were observed in the mouse brain, including a preferential transduction of astrocytes and neurons in the cerebral cortex and striatum, whereas neurons were the only transduced cell type in subcortical locations across the hippocampus, thalamus, hypothalamus, mesencephalon, brainstem and cerebellum. Furthermore, transduced microglial cells were never found in any CNS location. Peripheral organs transduced upon intravenous administration included lung, liver, peritoneum, heart and skeletal muscle. However, a comparable performance of AAV9P31 to bypass the BBB in rats and macaques was not observed, although a more limited neuronal transduction was found in the brainstem of rats upon intravenous delivery. Finally, intracerebroventricular delivery in macaques resulted in neuronal transduction in cortical, subcortical structures and cerebellum following a patchy pattern. In conclusion, the widespread CNS transduction obtained in mice upon intravenous delivery of AAV9P31 represents a powerful tool for modeling a wide variety of neurological disorders as well as an appealing choice for the evaluation of gene therapy-based therapeutics.
Dielectrophoretic bead-droplet reactor for solid-phase synthesis
Authors: Padhy Punnag , Zaman Mohammad Asif , Jensen Michael Anthony , Cheng Yao-Te , Huang Yogi , Wu Mo , Galambos Ludwig , Davis Ronald Wayne , Hesselink Lambertus
Published: July 2024

Solid-phase synthesis underpins many advances in synthetic and combinatorial chemistry, biology, and material science. The immobilization of a reacting species on the solid support makes interfacing of reagents an important challenge in this approach. In traditional synthesis columns, this leads to reaction errors that limit the product yield and necessitates excess consumption of the mobile reagent phase. Although droplet microfluidics can mitigate these problems, its adoption is fundamentally limited by the inability to controllably interface microbeads and reagent droplets. Here, we introduce Dielectrophoretic Bead-Droplet Reactor as a physical method to implement solid-phase synthesis on individual functionalized microbeads by encapsulating and ejecting them from microdroplets by tuning the supply voltage. Proof-of-concept demonstration of the enzymatic coupling of fluorescently labeled nucleotides onto the bead using this reactor yielded a 3.2-fold higher fidelity over columns through precise interfacing of individual microreactors and beads. Our work combines microparticle manipulation and droplet microfluidics to address a long-standing problem in solid-phase synthesis with potentially wide-ranging implications.
Energy-saving hydrogen production by seawater electrolysis coupling tip-enhanced electric field promoted electrocatalytic sulfion oxidation
Authors: Li Tongtong , Wang Boran , Cao Yu , Liu Zhexuan , Wang Shaogang , Zhang Qi , Sun Jie , Zhou Guangmin
Published: July 2024

Hydrogen production by seawater electrolysis is significantly hindered by high energy costs and undesirable detrimental chlorine chemistry in seawater. In this work, energy-saving hydrogen production is reported by chlorine-free seawater splitting coupling tip-enhanced electric field promoted electrocatalytic sulfion oxidation reaction. We present a bifunctional needle-like Co3S4 catalyst grown on nickel foam with a unique tip structure that enhances the kinetic rate by improving the current density in the tip region. The assembled hybrid seawater electrolyzer combines thermodynamically favorable sulfion oxidation and cathodic seawater reduction can enable sustainable hydrogen production at a current density of 100 mA cm−2 for up to 504 h. The hybrid seawater electrolyzer has the potential for scale-up industrial implementation of hydrogen production by seawater electrolysis, which is promising to achieve high economic efficiency and environmental remediation.
Highly efficient pure-blue organic light-emitting diodes based on rationally designed heterocyclic phenophosphazinine-containing emitters
Authors: Xing Longjiang , Wang Jianghui , Chen Wen-Cheng , Liu Bo , Chen Guowei , Wang Xiaofeng , Tan Ji-Hua , Chen Season Si , Chen Jia-Xiong , Ji Shaomin , Zhao Zujin , Tang Man-Chung , Huo Yanping
Published: July 2024

Multi-resonance thermally activated delayed fluorophores have been actively studied for high-resolution photonic applications due to their exceptional color purity. However, these compounds encounter challenges associated with the inefficient spin-flip process, compromising device performance. Herein, we report two pure-blue emitters based on an organoboron multi-resonance core, incorporating a conformationally flexible donor, 10-phenyl-5H-phenophosphazinine 10-oxide (or sulfide). This design concept selectively modifies the orbital type of high-lying excited states to a charge transfer configuration while simultaneously providing the necessary conformational freedom to enhance the density of excited states without sacrificing color purity. We show that the different embedded phosphorus motifs (phosphine oxide/sulfide) of the donor can finely tune the electronic structure and conformational freedom, resulting in an accelerated spin-flip process through intense spin-vibronic coupling, achieving over a 20-fold increase in the reverse intersystem crossing rate compared to the parent multi-resonance emitter. Utilizing these emitters, we achieve high-performance pure-blue organic light-emitting diodes, showcasing a top-tier external quantum efficiency of 37.6% with reduced efficiency roll-offs. This proposed strategy not only challenges the conventional notion that flexible electron-donors are undesirable for constructing narrowband emitters but also offer a pathway for designing efficient narrow-spectrum blue organic light-emitting diodes.
Chemical language modeling with structured state space sequence models
Authors: Özçelik Rıza , de Ruiter Sarah , Criscuolo Emanuele , Grisoni Francesca
Published: July 2024

Generative deep learning is reshaping drug design. Chemical language models (CLMs) – which generate molecules in the form of molecular strings – bear particular promise for this endeavor. Here, we introduce a recent deep learning architecture, termed Structured State Space Sequence (S4) model, into de novo drug design. In addition to its unprecedented performance in various fields, S4 has shown remarkable capabilities to learn the global properties of sequences. This aspect is intriguing in chemical language modeling, where complex molecular properties like bioactivity can ‘emerge’ from separated portions in the molecular string. This observation gives rise to the following question: Can S4 advance chemical language modeling for de novo design? To provide an answer, we systematically benchmark S4 with state-of-the-art CLMs on an array of drug discovery tasks, such as the identification of bioactive compounds, and the design of drug-like molecules and natural products. S4 shows a superior capacity to learn complex molecular properties, while at the same time exploring diverse scaffolds. Finally, when applied prospectively to kinase inhibition, S4 designs eight of out ten molecules that are predicted as highly active by molecular dynamics simulations. Taken together, these findings advocate for the introduction of S4 into chemical language modeling – uncovering its untapped potential in the molecular sciences.
A dataset for deep learning based detection of printed circuit board surface defect
Authors: Lv Shengping , Ouyang Bin , Deng Zhihua , Liang Tairan , Jiang Shixin , Zhang Kaibin , Chen Jianyu , Li Zhuohui
Published: July 2024

Printed circuit board (PCB) may display diverse surface defects in manufacturing. These defects not only influence aesthetics but can also affect the performance of the PCB and potentially damage the entire board. Thus, achieving efficient and highly accurate detection of PCB surface defects is fundamental for quality control in fabrication. The rapidly advancing deep learning (DL) technology holds promising prospects for providing accurate and efficient detection methods for surface defects on PCB. To facilitate DL model training, it is imperative to compile a comprehensive dataset encompassing diverse surface defect types found on PCB at a significant scale. This work categorized PCB surface defects into 9 distinct categories based on factors such as their causes, locations, and morphologies and developed a dataset of PCB surface defect (DsPCBSD+). In DsPCBSD+, a total of 20,276 defects were annotated manually by bounding boxes on the 10,259 images. This openly accessible dataset is aimed accelerating and promoting further researches and advancements in the field of DL-based detection of PCB surface defect.
Experimental analysis of enhanced finite set model predictive control and direct torque control in SRM drives for torque ripple reduction
Authors: M Deepak , Samithas Devakirubakaran , Balachandran Praveen Kumar , Selvarajan Shitharth
Published: July 2024

The magnet-less switched reluctance motor (SRM) speed-torque characteristics are ideally suited for traction motor drive characteristics and its advantage to minimize the overall cost of on-road EVs. The main drawbacks are torque and flux ripple, which have produced high in low-speed operation. However, the emerging direct torque control (DTC) operated magnitude flux and torque estimation with voltage vectors (VVs) gives high torque ripples due to the selection of effective switching states and sector partition accuracy. On the other hand, the existing model predictive control (MPC) with multiple objective and optimization weighting factors produces high torque ripples due to the system dynamics and constraints. Therefore, existing DTC and MPC can result in high torque ripples. This paper proposed a finite set (FS)-MPC with a single cost function objective without weighting factor: the predicted torque considered to evaluate VVs to minimize the ripples further. The selected optimal VV minimizes the SRM drive torque and flux ripples in steady and dynamic state behaviour. The classical DTC and proposed model were developed, and simulation results were verified using MATLAB/Simulink. The proposed model operated in SRM drives experimental results to prove the effective minimization of torque and flux ripples compared to the existing DTC.