bluuebunny/crossref_metadata_2025 huggingface dataset:
In Vivo Biocompatibility of Synechococcus sp. PCC 7002-Integrated Scaffolds for Skin Regeneration
Authors: Fuchs Benedikt , Mert Sinan , Kuhlmann Constanze , Birt Alexandra , Hofmann Daniel , Wiggenhauser Paul Severin , Giunta Riccardo E. , Chavez Myra N. , Nickelsen Jörg , Schenck Thilo Ludwig , Moellhoff Nicholas
Published: October 2024

Cyanobacteria, commonly known as blue-green algae, are prevalent in freshwater systems and have gained interest for their potential in medical applications, particularly in skin regeneration. Among these, Synechococcus sp. strain PCC 7002 stands out because of its rapid proliferation and capacity to be genetically modified to produce growth factors. This study investigates the safety of Synechococcus sp. PCC 7002 when used in scaffolds for skin regeneration, focusing on systemic inflammatory responses in a murine model. We evaluated the following three groups: scaffolds colonized with genetically engineered bacteria producing hyaluronic acid, scaffolds with wild-type bacteria, and control scaffolds without bacteria. After seven days, we assessed systemic inflammation by measuring changes in cytokine profiles and lymphatic organ sizes. The results showed no significant differences in spleen, thymus, and lymph node weights, indicating a lack of overt systemic toxicity. Blood cytokine analysis revealed elevated levels of IL-6 and IL-1β in scaffolds with bacteria, suggesting a systemic inflammatory response, while TNF-α levels remained unaffected. Proteome profiling identified distinct cytokine patterns associated with bacterial colonization, including elevated inflammatory proteins and products, indicative of acute inflammation. Conversely, control scaffolds exhibited protein profiles suggestive of a rejection response, characterized by increased levels of cytokines involved in T and B cell activation. Our findings suggest that Synechococcus sp. PCC 7002 does not appear to cause significant systemic toxicity, supporting its potential use in biomedical applications. Further research is necessary to explore the long-term effects and clinical implications of these responses.
Heart Rate Variability, Blood Pressure and Peripheral Oxygen Saturation during Yoga Adham and Mahat Breathing Techniques without Retention in Adult Practitioners
Authors: Catela David , Santos Júlia , Oliveira Joana , Franco Susana , Mercê Cristiana
Published: October 2024

Background: Heart rate variability (HRV) is the change in time intervals between heart beats, reflecting the autonomic nervous system’s ability to adapt to psychological and physiological demands. Slow breathing enhances parasympathetic activity, increasing HRV. Pranayama, a yoga breathing technique, affords the conscious regulation of respiration frequency. This study aimed to characterize HRV, blood pressure and peripheral oxygen saturation of basic yoga breathing slow techniques with regular yoga practitioners. Methods: In total, 45 yoga practitioners were included in the study (including 7 males, mean age of 54.04 ± 11.97 years) with varying levels of yoga experience (minimum 3 months, maximum 37 years). Participants performed three breathing conditions: baseline (control) and two yoga techniques (abdominal (adham) and complete (mahat)) breathing, each for 10 min in the supine position (i.e., savasana). For each condition, respiratory frequency, heart rate (HR), blood pressure and peripheral oxygen levels were collected. Results: The findings revealed that both abdominal and complete yoga breathing techniques promoted a decrease in respiratory frequency (p < 0.001, r = 0.61; p < 0.001, r = 0.61, respectively), and an increase in peripheral oxygen saturation (p < 0.001, r = 0.50; p < 0.001, r = 0.46, respectively), along with blood pressure decreases in all mean values, and a significant decrease in systolic pressure, considering all conditions (p = 0.034, W = 0.08). There were significant increases in standard deviation of HR during abdominal and complete yoga breathing techniques compared with the baseline (p = 0.003, r = 0.31; p < 0.001, r = 0.47, respectively), indicating enhanced parasympathetic activity. Moreover, the complete breathing technique exhibited the greatest variability in HRV measures, with several significant differences compared with abdominal breathing (standard deviation of HR, p < 0.001, r = 0.42; SD2, standard deviation of points perpendicular to the Poincaré parallel line, p < 0.003, r = 0.31; SD1/SD2, p < 0.003, r = 0.31), suggesting a more profound impact on autonomic modulation. Conclusions: simple, inexpensive and non-intrusive abdominal and complete yoga breathing techniques can effectively and momentarily enhance HRV and oxygen saturation in adults, mature adults and the elderly.
Water Quality in the Ma’an Archipelago Marine Special Protected Area: Remote Sensing Inversion Based on Machine Learning
Authors: Wang Zhixin , Zhang Zhenqi , Li Hailong , Jiang Hong , Zhuo Lifei , Cai Huiwen , Chen Chao , Zhao Sheng
Published: October 2024

Due to the increasing impact of climate change and human activities on marine ecosystems, there is an urgent need to study marine water quality. The use of remote sensing for water quality inversion offers a precise, timely, and comprehensive way to evaluate the present state and future trajectories of water quality. In this paper, a remote sensing inversion model utilizing machine learning was developed to evaluate water quality variations in the Ma’an Archipelago Marine Special Protected Area (MMSPA) over a long-time series of Landsat images. The concentrations of chlorophyll-a (Chl-a), phosphate, and dissolved inorganic nitrogen (DIN) in the sea area from 2002 to 2022 were inverted and analyzed. The spatial and temporal characteristics of these variations were investigated. The results indicated that the random forest model could reliably predict Chl-a, phosphate, and DIN concentrations in the MMSPA. Specifically, the inversion results for Chl-a showed the coefficient of determination (R2) of 0.741, the root mean square error (RMSE) of 3.376 μg/L, and the mean absolute percentage error (MAPE) of 16.219%. Regarding spatial distribution, the concentrations of these parameters were notably elevated in the nearshore zones, especially in the northwest, contrasted with lower concentrations in the offshore and southeast areas. Predominantly, the nearshore regions with higher concentrations were in proximity to the aquaculture zones. Additionally, nutrients originating from land sources, transported via rivers such as the Yangtze River, as well as influenced by human activities, have shaped this nutrient distribution. Over the long term, the water quality in the MMSPA has shown considerable interannual fluctuations during the past two decades. As a sanctuary, preserving superior water quality and a healthy ecosystem is very important. Efforts in protection, restoration, and management will demand considerable labor. Remote sensing has demonstrated its worth as a proficient technology for real-time monitoring, capable of supporting the sustainable exploitation of marine resources and the safeguarding of the marine ecological environment.
The Mesoscale SST–Wind Coupling Characteristics in the Yellow Sea and East China Sea Based on Satellite Data and Their Feedback Effects on the Ocean
Authors: Cui Chaoran , Xu Lingjing
Published: October 2024

The mesoscale interaction between sea surface temperature (SST) and wind is a crucial factor influencing oceanic and atmospheric conditions. To investigate the mesoscale coupling characteristics of the Yellow Sea and East China Sea, we applied a locally weighted regression filtering method to extract mesoscale signals from Quik-SCAT wind field data and AMSR-E SST data and found that the mesoscale coupling intensity is stronger in the Yellow Sea during the spring and winter seasons. We calculated the mesoscale coupling coefficient to be approximately 0.009 N·m−2/°C. Subsequently, the Tikhonov regularization method was used to establish a mesoscale empirical coupling model, and the feedback effect of mesoscale coupling on the ocean was studied. The results show that the mesoscale SST–wind field coupling can lead to the enhancement of upwelling in the offshore area of the East China Sea, a decrease in the upper ocean temperature, and an increase in the eddy kinetic energy in the Yellow Sea. Diagnostic analyses suggested that mesoscale coupling-induced variations in horizontal advection and surface heat flux contribute most to the variation in SST. Moreover, the increase in the wind energy input to the eddy is the main factor explaining the increase in the eddy kinetic energy.
Effects of Coastal Reclamation on the Topographic Changes of an Open Estuary: A Case Study in Taizhou Bay, East China
Authors: Liu Yifei , Xia Xiaoming , Cai Tinglu , Wang Xinkai , Zheng Jun
Published: October 2024

Analyzing the processes and influencing factors of accretion or erosion in estuaries and tidal basins is important for coastal conservation and utilization, planning, and ecosystem maintenance. This study analyzed the process of topographic changes in Taizhou Bay, China over the past five decades by comparing bathymetric datasets from different years. The coastlines were extracted via remote sensing image interpretation, and the coastal reclamation process was analyzed. The results revealed that this bay experienced slow siltation from 1963 to 2004, which mainly occurred on mudflats and shore slopes. It turned into a feature dominated by erosion between 2004 and 2013, and erosion increased between 2013 and 2019. Coastal reclamation has occurred during every 10-year period since the 1960s. Reclamation occupied a portion of the intertidal flat, decreased the tidal prism, and changed tidal asymmetry, causing net sediment to be transported into the bay and accumulate on the intertidal flat and upper part of the subaqueous shore. The drastic reduction in sediment supply caused by the Three Gorges Dam may have been responsible for erosion from 2004 to 2019. A negative feedback process exists between tidal flat expansion and coastal reclamation. The compensatory expansion of the tidal flat is a much slower process than the advance of reclamation.
Advancements in the Programmable Hyperspectral Seawater Scanner Measurement Technology for Enhanced Detection of Harmful Algal Blooms
Authors: Langan John J. , Bae Jungyun
Published: October 2024

The Programmable Hyperspectral Seawater Scanner (PHySS) represents a significant breakthrough in monitoring harmful algal blooms (HABs), specifically targeting the “Florida red tide” caused by Karenia brevis. By utilizing a Fourth-Derivative Spectral Similarity Index (SI), this study establishes a strong positive correlation between the SI and phytoplankton counts, underscoring the PHySS’s potential for early detection and effective management of HABs. Our findings suggest that the PHySS could act as a predictive tool, offering crucial lead time to mitigate the ecological and economic repercussions of blooms. However, this study also identifies certain limitations of the PHySS technology, such as its inability to differentiate among various phytoplankton species without additional physical verification of cell counts. This limitation highlights the need for a multifaceted approach to HAB management. Our research suggests that adopting a multi-modal monitoring strategy could lead to more sophisticated and effective methods for combating HABs, fostering an optimistic outlook for future advancements in this area.
Research on the Identification and Classification of Marine Debris Based on Improved YOLOv8
Authors: Jiang Wenbo , Yang Lusong , Bu Yun
Published: October 2024

Autonomous underwater vehicles equipped with target recognition algorithms are a primary means of removing marine debris. However, due to poor underwater visibility, light scattering by suspended particles, and the coexistence of organisms and debris, current methods have problems such as poor recognition and classification effects, slow recognition speed, and weak generalization ability. In response to these problems, this article proposes a marine debris identification and classification algorithm based on improved YOLOv8. The algorithm incorporates the CloFormer module, a context-aware local enhancement mechanism, into the backbone network, fully utilizing shared and context-aware weights. Consequently, it enhances high- and low-frequency feature extraction from underwater debris images. The proposed C2f-spatial and channel reconstruction (C2f-SCConv) module combines the SCConv module with the neck C2f module to reduce spatial and channel redundancy in standard convolutions and enhance feature representation. WIoU v3 is employed as the bounding box regression loss function, effectively managing low- and high-quality samples to improve overall model performance. The experimental results on the TrashCan-Instance dataset indicate that compared to the classical YOLOv8, the mAP@0.5 and F1 scores are increased by 5.7% and 6%, respectively. Meanwhile, on the TrashCan-Material dataset, the mAP@0.5 and F1 scores also improve, by 5.5% and 5%, respectively. Additionally, the model size has been reduced by 12.9%. These research results are conducive to maintaining marine life safety and ecosystem stability.
Three-Dimensional Marine Magnetotelluric Parallel Forward Modeling in Conductive and Magnetic Anisotropic Medium Using Finite-Element Method Based on Secondary Field
Authors: Zhou Zongyi , Xiao Tiaojie , Zhou Junjun , Zhu Xiaoxiong , Yang Bo , Gong Chunye , Liu Jie , Wang Yun
Published: October 2024

The marine magnetotelluric (MMT) method is a significant tool extensively utilized in offshore studies, including the understanding of the Earth’s tectonics and hydrocarbon exploration. Conductive anisotropy and non-zero magnetic susceptibility are common phenomena observed in the Earth’s subsurface, and MMT forward modeling is the basis of practical inversion. However, numerical modeling that incorporates both conductive anisotropy and magnetic susceptibility has received limited attention. Moreover, both accuracy and efficiency are crucial in developing a 3D MMT modeling algorithm. Therefore, we developed a multi-level parallel MMT forward modeling algorithm that is capable of simultaneously modeling conductive and magnetic arbitrary anisotropic models using the vector finite element method based on the secondary field formula. The algorithm’s accuracy was validated through comparisons with previously published results for an arbitrary anisotropic model. The results show that the maximum relative error is below 2%, and the speedup reaches an impressive value of 552.41 when running with 2048 cores. Furthermore, the MMT responses of conductive anisotropy and magnetic susceptibility were comprehensively analyzed by several typical models. Our findings highlight the importance of considering magnetic susceptibility in magnetite-rich regions, particularly as the MMT responses may exhibit opposite responses for anomalies with lower resistivity and higher magnetic susceptibility compared with the surrounding rocks.
A Credibility Monitoring Approach and Software Monitoring System for VHF Data Exchange System Data Link Based on a Combined Detection Method
Authors: Wang Xiaoye , Fu Leyun , Wang Weichen , Hu Qing
Published: October 2024

Due to VDES’s higher data transmission speed and complex communication protocols, vulnerabilities within its data link infrastructure are more pronounced. To ensure the reliability of VDES data transmission, this manuscript proposes a credibility monitoring approach based on the combined detection method of radio interference detection and spoofing source identification and localization, focusing on key data link vulnerabilities outlined in the IALA G1181 VDES VDL Integrity Guide. Automated monitoring is achieved through VDES data link monitoring software (VDES(AIS 2.0)), which is based on a three-tier architecture and a Client/Server (C/S) model. The software validates monitoring techniques and software against various interference scenarios. Visualization of monitoring results, alarm notifications, and relevant data through the front-end interface enhances understanding of VDES data link credibility. This framework supports effective surveillance and detection of vulnerabilities, such as radio interference and spoofing sources.
Dominant Tree Species and Litter Quality Govern Fungal Community Dynamics during Litter Decomposition
Authors: Meng Wenjing , Chang Lin , Qu Zhaolei , Liu Bing , Liu Kang , Zhang Yuemei , Huang Lin , Sun Hui
Published: October 2024

Litter decomposition is a crucial biochemical process regulated by microbial activities in the forest ecosystem. However, the dynamic response of the fungal community during litter decomposition to vegetation changes is not well understood. Here, we investigated the litter decomposition rate, extracellular enzyme activities, fungal community, and nutrient cycling-related genes in leaf and twig litters over a three-year decomposition period in a pure Liquidamabar formosana forest and a mixed L. formosana/Pinus thunbergii forest. The result showed that during the three-year decomposition, twig litter in the mixed forest decomposed faster than that in the pure forest. In both leaf litter and twig litter, β-cellobiosidase and N-acetyl-glucosamidase exhibited higher activities in the mixed forest, whereas phosphatase, β-glucosidase, and β-xylosidase were higher in the pure forest. The fungal α-diversity were higher in both litters in the pure forest compared to the mixed forest, with leaf litter showing higher α-diversity than twig litter. Fungal species richness and α-diversity within leaf litter increased as decomposition progressed. Within leaf litter, Basidiomycota dominated in the mixed forest, while Ascomycota dominated in the pure forest. Funguild analysis revealed that Symbiotroph and ectomycorrhizal fungi were more abundant in the mixed forest compared to the pure forest. In the third-year decomposition, genes related to phosphorus cycling were most abundant in both forests, with the pure forest having a higher abundance of cex and gcd genes. Fungal community structure, predicted functional structure, and gene composition differed between the two forest types and between the two litter types. Notably, the fungal functional community structure during the first-year decomposition was distinct from that in the subsequent two years. These findings suggest that dominant tree species, litter quality, and decomposition time all significantly influence litter decomposition by attracting different fungal communities, thereby affecting the entire decomposition process.
Identification and Biological Characteristics of Alternaria gossypina as a Promising Biocontrol Agent for the Control of Mikania micrantha
Authors: Feng Lichen , Hu Lianrong , Bo Jingyi , Ji Mei , Ze Sangzi , Ding Yan’e , Yang Bin , Zhao Ning
Published: October 2024

Mikania micrantha is one of the most threatening invasive plant species in the world. Its invasion has greatly reduced the species diversity of the invaded areas. The development of fungal herbicides using phytopathogenic fungi has attracted considerable attention in recent years. In this study, a tissue isolation method was used to isolate and screen the strain SWFU-MM002 with strong pathogenicity to M. micrantha leaves from naturally occurring M. micrantha. Through morphological observation, ITS, GAPDH, and Alta-1 gene sequence homology, we compare and construct a phylogenetic tree to determine their taxonomic status. In addition, the biological characteristics of strain SWFU-MM002 were studied. The results showed that, combined with morphological and molecular biology identification, the strain was identified as Alternaria gossypina; biological characteristic research showed that the optimal medium for the growth of mycelium of this strain is PDA medium. At the optimal temperature of 27 °C and pH between 6 and 10, the mycelium can grow well. The best carbon and nitrogen sources are maltose and peptone, respectively. Analysing the infection process under a light microscope showed that SWFU-MM002 mycelia invaded the leaf tissue through stomata and colonized, eventually causing damage to the host. This is the first report of leaf spot of M. micrantha caused by A. gossypina. This study can lay a solid foundation for the development of A. gossypina as a control agent for M. micrantha.
An Antisense Long Non-Coding RNA, LncRsn, Is Involved in Sexual Reproduction and Full Virulence in Fusarium graminearum
Authors: Fu Zhizhen , Chen Yanjie , Cai Gaolei , Peng Huijuan , Wang Xiaoyu , Li Ping , Gu Aiguo , Li Yanli , Ma Dongfang
Published: October 2024

Fusarium head blight (FHB), primarily caused by Fusarium graminearum, is a devastating crop disease that leads to significant declines in wheat yield and quality worldwide. Long non-coding RNAs (lncRNAs) are found to play significant functions in various biological processes, but their regulatory functions in the sexual reproduction and pathogenicity of F. graminearum have not been studied extensively. This study identified an antisense lncRNA, named lncRsn, located in the transcription initiation site region between the 5′-flanking gene FgSna and the 3′-flanking gene FgPta. A deletion mutant of lncRsn (ΔlncRsn) was constructed through homologous recombination. ΔlncRsn exhibited huge reductions in pathogen and sexual reproduction. Additionally, the deletion of lncRsn disrupted the biosynthesis of deoxynivalenol (DON) and impaired the formation of infection structures. RT-qPCR analysis reveals that lncRsn may negatively regulate the transcription of the target gene FgSna. This study found that lncRsn plays an important role in sexual and asexual reproduction, pathogenicity, virulence, osmotic stress, and cell wall integrity (CWI) in F. graminearum. Further characterization of pathogenesis-related genes and the reaction between lncRsn and protein-coding genes will aid in developing novel approaches for controlling F. graminearum diseases.
Health System and Absenteeism among Nurses in Oman: Root Cause Analysis
Authors: Al Menji Huda , Al Zadjali Asiya , Al Lamki Mustafa , Al Shamsi Zakiya , Al Kiyumi Lamees , Al Harrasi Khadija , Al Rashdi Kawther , Al Salmi Issa
Published: October 2024

Objectives—This study aimed to investigate the factors contributing to increased absenteeism among nurses in primary healthcare institutions in Oman. Methods—A quantitative descriptive cross-sectional design included a structured written questionnaire that uses a quantitative self-repot technique was used. The study was conducted between January 2022 to November 2022 on a random selection of 300 nurses working in the primary and secondary healthcare institutions and regional hospitals in the Muscat governorate. Results—A total of 229 questionnaire were returned with a response rate of 76%. Almost 97% (222) participants were females, and 7 (3.1%) were males. Almost 51% of nurses were 25–34 years old. The respondents considered minor physical alignments, chronic medical conditions, and stress-related factors to be the predominant factors contributing to absenteeism among nurses. In addition, the coercive attitude of the leader, nurses whose performance was always criticized by the leader, and the nurse leader having inadequate support and guidance in performing patient care were considered important factors contributing to absenteeism. Conclusions—Nurses’ absenteeism is considered a threat to the quality of services provided for society at the primary healthcare level. The most common factors leading to increased absenteeism among nurses were found to be linked with demographic, leadership, and work characteristics. The most significant factors were considered to be within work characteristics, specifically the shortage of staff leading to workload, shift duties with limited flexibility, extra tasks, and absence of supportive policies. Additionally, leadership factors such as involvement, regular feedback, respect, and active listening to concerns were among the contributing factors to increased nursing absenteeism.
Commuting Pattern Recognition of Industrial Parks Using Mobile Phone Signaling Data: A Case Study of Nanjing, China
Authors: Yuan Xinguo , Wang Xingping , Wang Yingyu , Li Juan , Zhang Yang , Gao Zhan , Zhang Gai
Published: October 2024

As a novel industrial space to cope with global competition, industrial parks have gradually become important growth poles to promote regional development and provide a large number of employment opportunities. This study utilizes mobile phone signaling data to identify the commuting origins and destinations (OD) of different industrial parks in Nanjing while comparing the distribution of the working population, residential population, and commuting patterns across varying types and levels of industrial parks. The level of coordination of the employment–residential system in each park is quantified by calculating the resident commuting index (HSCi), employee commuting index (WSCi), and their coupling coordination degree. Additionally, geographic detectors are employed to identify the influencing factors and interaction effects that impact the employment–residential balance in industrial parks. Results show that industrial parks located in the central urban area attract more residential and working populations. The commuting volume of national and municipal as well as high-tech industrial parks is higher than other types of industrial parks. Most industrial parks experience more inward than outward commuting, and there is an uneven distribution of commuting flows, resulting in a network-like pattern of “central dense, peripheral sparse”. Various industrial parks exhibit a highly coupled job–housing system, and those with high HSCi tend to have high WSCi as well. The coupling coordination of industrial parks ranged from 0.16 to 0.93, with 13 being primary coordination or above and 3 being disordered. Industrial parks are classified into three types: employment-oriented, residential-oriented, and employment–residential balanced, with the residential-oriented type being predominant. The density of public transportation stops, park area, and land use mix are the primary factors affecting the employment–residential balance. Industrial parks with larger scale, better land allocation, and higher service facility levels are more likely to achieve coordination in the employment–residential system. Our work utilizes mobile signaling data to characterize the commuting patterns of industrial parks, providing insights for industrial park planning and promoting the integration of industry and city.
Effects of Biochar on Soil Organic Carbon in Relation to Soil Nutrient Contents, Climate Zones and Cropping Systems: A Chinese Meta-Analysis
Authors: Tian Longjia , Shao Guangcheng , Gao Yang , Song Enze , Lu Jia
Published: October 2024

Biochar application is an effective way to improve soil organic carbon (SOC) content and ensure food security. However, there were differences in SOC content following biochar application under different conditions. We collected 637 paired comparisons from 101 articles to determine the following: (1) the average effect of biochar application on SOC content and (2) the response of SOC content to different soil nutrient contents, climate zones and cropping systems following biochar application. The results showed that the soil available phosphorus (P) content and soil available potassium (K) content reached the highest level in the category of <10 mg kg−1 and >150 mg kg−1, respectively. Soil total P content subgroups achieved maximum increase in the intermediate category. The Cw zone (temperate, without dry season) obtained the maximum level of SOC content. Compared with plough tillage, rotary tillage presented significantly higher SOC content. Therefore, low available P and K contents, moderate soil total N and P contents, rotary tillage and the Cw zone were more effective in increasing SOC content. Furthermore, the results of a random forest algorithm showed that soil nutrient contents were the most important variables. This study provided a scientific basis for SOC sequestration and improving soil fertility.
Regional Sustainable Management Pathways to Carbon Neutrality
Authors: Wang Chao , Zhan Jinyan , Zeng Xueting
Published: October 2024

With the background of global climate change and rapid economic growth, there are increasing problems threatening regional sustainable development [...]
The Influence of the L1 on L2 Collocation Processing in Tamil-English Bilingual Children
Authors: Leonard Roopa , Joseph Holly , Daller Michael
Published: October 2024

This study examines the influence of Tamil (L1) on the processing of English (L2) collocations during reading for Tamil-English bilingual children. Building on existing research in formulaic language, we used an online processing tool to investigate whether cross-linguistic transfer can be extended beyond single lexical items to collocations in bilingual children, a population that is underrepresented in this research area. Fifty-eight children aged 9–10 years from a school in Chennai, India, took part. Using self-paced reading, children’s reading times were measured for both congruent (with equivalent in L2) and incongruent (without equivalent in L2) English collocations embedded in short passages. There were two reading modes (single and chunk), which allowed reading times for the whole collocations and the individual words of the collocations to be examined. Results showed that children read congruent collocations more quickly than incongruent collocations in both modes. For congruent collocations, children read the second word more quickly than the first word, but the reverse was true for incongruent collocations. These results suggest that the L1 (Tamil) is activated during the processing stage of reading English collocations for Tamil-English bilingual children in this context.
Influence of Family Language Policies on Language Proficiency across Generations: A Study of Russian-Speaking Families in Germany
Authors: Blacher Olia , Brehmer Bernhard
Published: October 2024

This study investigates the influence of selected aspects of family language policies (FLPs) on language proficiency across three generations of Russian-speaking families in Germany using data from a sample of 18 families. The data were collected via questionnaires and a cloze test was used to measure proficiency in Russian. Multiple regression analysis and Dunn’s test were employed to analyze the influence of the selected components of FLP and assess differences in language proficiency between family members. The findings highlight a significant generational shift in language proficiency: parents exhibited the highest proficiency in Russian, followed by grandparents, with children showing the least proficiency and greater variation in their language skills. This pattern reflects the dynamics of language practices in families where older generations predominantly use Russian, whereas children display a greater inclination towards German or enhanced bilingualism. Additionally, this study underscores the positive influence of literacy skills in both Russian and German, reading in Russian, and a positive attitude towards maintaining cultural ties through reading on Russian language proficiency. Although attendance of Russian language lessons was positively correlated with the proficiency scores of children, the statistical models were only partially successful in accounting for their overall impact on proficiency, indicating that other unexplored factors may also play a significant role.
Impact of Drawing Machine Parameters on Force and Energy Consumption in Borosilicate Glass Tube Production
Authors: Liu Peng , Cang Limin , Wan Zhigang , Yang Ke , Chen Ming , Li Rangling , Geng Tie
Published: October 2024

Middle borosilicate glass tubes are critical materials for medical packaging, with the drawing machine playing a pivotal role in their production process. However, the effects of the drawing wheel’s motion parameters on the glass tube remain underexplored. Therefore, based on the finite element method simulation and validation experiment, the effects of experimental factors (angle of upper and lower drawing wheel, AUD; friction factor of glass and rubber, FFGR; and distance of upper and lower drawing wheel, DUD) on experimental indexes (maximum effective stress of glass tube, MES; rotational speed of glass tube, RSG; maximum and average forward driving force, MFDF and AFDF; maximum and average rotational driving force, MRDF and ARDF; total energy consumption and power, TEC and TPD; maximum and average forward driving power, MFDP and AFDP; and maximum and average rotational driving power, MRDP and ARDP) were analyzed. The results indicated that compared to FFGR and AUD, the influence of DUD on experimental indexes was the highest. The positive influence of AUD on RSG, ARDP, and MRDP, the positive influence of FFGR and the negative influence of DUD on MRDF, ARDF, TEC, TPD, ARDP, and MRDP were found, respectively. These findings will provide a theoretical reference for the optimization of drawing machines.
Federation in Digital Twins and Knowledge Transfer: Modeling Limitations and Enhancement
Authors: Papacharalampopoulos Alexios , Christopoulos Dionysios , Karagianni Olga Maria , Stavropoulos Panagiotis
Published: October 2024

Digital twins (DTs) consist of various technologies and therefore require a wide range of data. However, many businesses often face challenges in providing sufficient data due to technical limitations or business constraints. This can result in inadequate data for training or calibrating the models used within a digital twin. This paper aims to explore how knowledge can be generated from federated digital twins—an approach that lies between digital twin networks and collaborative manufacturing—and how this can be used to enhance understanding for both AI systems and humans. Inspired by the concept of federated machine learning, where data and algorithms are shared across different stakeholders, this idea involves different companies collaborating through their respective DTs, a situation which can be referred to as federated twinning. As a result, the models within these DTs can be enriched with more-detailed information, leading to the creation of verified, high-fidelity models. Human involvement is also emphasized, particularly in the transfer of knowledge. This can be applied to the modeling process itself, which is the primary focus here, or to any control design aspect. Specifically, the paradigm of thermal process modeling is used to illustrate how federated digital twins can help refine underlying models. Two sequential cases are considered: the first one is used to study the type of knowledge that is required from modeling and federation; while the second one investigates the creation of a more suitable form of modeling.
End-of-Life Prediction for Milling Cutters Based on an Online Vibro-Acoustic System
Authors: Perrelli Michele , Conte Romina , Zangara Gabriele , Gagliardi Francesco
Published: October 2024

Improving the capabilities of online condition monitoring systems, able to detect arising of catastrophic wear on cutting tools, has been an important target to be pursued for the metal cutting industry. Currently, different systems have been proposed, moved by the rising need of part quality improvements and production cost control. Despite this, cutter wear development, being related to several process variables and conditions, is still really difficult to be predicted accurately. This paper presents a detection wear method based on the time-domain analysis of vibro-acoustic signals. Specifically, cutter wear monitoring, using sound signals of a milling process, was performed at a laboratory level in a well-isolated working room. Sound signals were recorded at fixed main machining parameters, i.e., cutting speed, feed rate and depth of cut. The tests were carried out starting with a new set of inserts with significant wear conditions for the investigated process configuration. Results showed a consistent overlapping between the beginning of the catastrophic wear and an evident increment in the trend of the root mean square of the monitored acoustic signal, showing the potential of the methodology in detecting a suitable time to stop the milling process and to change the worn-out cutters.
Generalized Kelvin–Voigt Creep Model in Fractal Space–Time
Authors: Reyes de Luna Eduardo , Kryvko Andriy , Pascual-Francisco Juan B. , Hernández Ignacio , Samayoa Didier
Published: October 2024

In this paper, we study the creep phenomena for self-similar models of viscoelastic materials and derive a generalization of the Kelvin–Voigt model in the framework of fractal continuum calculus. Creep compliance for the Kelvin–Voigt model is extended to fractal manifolds through local fractal-continuum differential operators. Generalized fractal creep compliance is obtained, taking into account the intrinsic time τ and the fractal dimension of time-scale β. The model obtained is validated with experimental data obtained for resin samples with the fractal structure of a Sierpinski carpet and experimental data on rock salt. Comparisons of the model predictions with the experimental data are presented as the curves of slow continuous deformations.
Learned Query Optimization by Constraint-Based Query Plan Augmentation
Authors: Ye Chen , Duan Haoyang , Zhang Hua , Wu Yifan , Dai Guojun
Published: October 2024

Over the last decades, various cost-based optimizers have been proposed to generate optimal plans for SQL queries. These optimizers are key to achieving good performance in database systems and can speed up query execution. Still, they may need enormous expert efforts and perform poorly on complicated queries. Learning-based optimizers have been shown to achieve high-quality plans by learning from past experiences. However, these solutions treat each query separately and neglect the semantic equivalence among different queries. Intuitively, a high-quality plan may be obtained for a complicated query by discovering a simple equivalent query. Motivated by this, in this paper, we present Celo, a novel constraint-enhanced learned optimizer to directly integrate the equivalent information of queries into the learning-based model. We apply denial constraints to identify equivalent queries by replacing equivalent predicates. Given a query, we augment the query plans generated by the learning-based model with the high-quality plans of its equivalent queries. Then, a more potentially well-performed plan will be predicted among the augmented query plans. Extensive experiments using real-world datasets demonstrated that Celo outperforms the previous state-of-the-art (SOTA) results even with few constraints.
Using Symmetries to Investigate the Complete Integrability, Solitary Wave Solutions and Solitons of the Gardner Equation
Authors: Hereman Willy , Göktaş Ünal
Published: October 2024

In this paper, using a scaling symmetry, it is shown how to compute polynomial conservation laws, generalized symmetries, recursion operators, Lax pairs, and bilinear forms of polynomial nonlinear partial differential equations, thereby establishing their complete integrability. The Gardner equation is chosen as the key example, as it comprises both the Korteweg–de Vries and modified Korteweg–de Vries equations. The Gardner and Miura transformations, which connect these equations, are also computed using the concept of scaling homogeneity. Exact solitary wave solutions and solitons of the Gardner equation are derived using Hirota’s method and other direct methods. The nature of these solutions depends on the sign of the cubic term in the Gardner equation and the underlying mKdV equation. It is shown that flat (table-top) waves of large amplitude only occur when the sign of the cubic nonlinearity is negative (defocusing case), whereas the focusing Gardner equation has standard elastically colliding solitons. This paper’s aim is to provide a review of the integrability properties and solutions of the Gardner equation and to illustrate the applicability of the scaling symmetry approach. The methods and algorithms used in this paper have been implemented in Mathematica, but can be adapted for major computer algebra systems.
Total Synthesis of Talarolide A and atrop-Talarolide A: Hydroxamate H-Bond Bridge Stabilization of Cyclic Peptide Conformers Invokes Non-Canonical Atropisomerism
Authors: Hussein Waleed M. , Zhu Yuxuan , Salim Angela A. , Capon Robert J.
Published: October 2024

The first total synthesis of the Australian marine tunicate fungus-derived cyclic peptide talarolide A (1) has confirmed the structure previously proposed on the basis of spectroscopic and chemical analyses and re-affirmed the importance of the unique hydroxamate H-bond bridge in ring conformer stabilization. The unexpected co-synthesis of atrop-talarolide A (8) revealed, for the first time, that hydroxamate H-bond bridging in the talarolide framework invokes non-canonical atropisomerism and that talarolides A (1), C (3), and D (4) all exist naturally as atropisomers. These discoveries raise the intriguing prospect that comparable functionalisation of other cyclic peptides, including those with commercial value, could provide ready access to new “unnatural atropisomeric” chemical space, with new and/or improved chemical and biological properties.
Exploring Marine-Derived Compounds: In Silico Discovery of Selective Ketohexokinase (KHK) Inhibitors for Metabolic Disease Therapy
Authors: Alturki Mansour S.
Published: October 2024

The increasing prevalence of metabolic diseases, including nonalcoholic fatty liver disease (NAFLD), obesity, and type 2 diabetes, poses significant global health challenges. Ketohexokinase (KHK), an enzyme crucial in fructose metabolism, is a potential therapeutic target due to its role in these conditions. This study focused on the discovery of selective KHK inhibitors using in silico methods. We employed structure-based drug design (SBDD) and ligand-based drug design (LBDD) approaches, beginning with molecular docking to identify promising compounds, followed by induced-fit docking (IFD), molecular mechanics generalized Born and surface area continuum solvation (MM-GBSA), and molecular dynamics (MD) simulations to validate binding affinities. Additionally, shape-based screening was conducted to assess structural similarities. The findings highlight several potential inhibitors with favorable ADMET profiles, offering promising candidates for further development in the treatment of fructose-related metabolic disorders.
Automated Quantification of Simple and Complex Aortic Flow Using 2D Phase Contrast MRI
Authors: Li Rui , Assadi Hosamadin S. , Zhao Xiaodan , Matthews Gareth , Mehmood Zia , Grafton-Clarke Ciaran , Limbachia Vaishali , Hall Rimma , Kasmai Bahman , Hughes Marina , Thampi Kurian , Hewson David , Stamatelatou Marianna , Swoboda Peter P. , Swift Andrew J. , Alabed Samer , Nair Sunil , Spohr Hilmar , Curtin John , Gurung-Koney Yashoda , Geest Rob J. van der , Vassiliou Vassilios S. , Zhong Liang , Garg Pankaj
Published: October 2024

(1) Background and Objectives: Flow assessment using cardiovascular magnetic resonance (CMR) provides important implications in determining physiologic parameters and clinically important markers. However, post-processing of CMR images remains labor- and time-intensive. This study aims to assess the validity and repeatability of fully automated segmentation of phase contrast velocity-encoded aortic root plane. (2) Materials and Methods: Aortic root images from 125 patients are segmented by artificial intelligence (AI), developed using convolutional neural networks and trained with a multicentre cohort of 160 subjects. Derived simple flow indices (forward and backward flow, systolic flow and velocity) and complex indices (aortic maximum area, systolic flow reversal ratio, flow displacement, and its angle change) were compared with those derived from manual contours. (3) Results: AI-derived simple flow indices yielded excellent repeatability compared to human segmentation (p < 0.001), with an insignificant level of bias. Complex flow indices feature good to excellent repeatability (p < 0.001), with insignificant levels of bias except flow displacement angle change and systolic retrograde flow yielding significant levels of bias (p < 0.001 and p < 0.05, respectively). (4) Conclusions: Automated flow quantification using aortic root images is comparable to human segmentation and has good to excellent repeatability. However, flow helicity and systolic retrograde flow are associated with a significant level of bias. Overall, all parameters show clinical repeatability.
Volatile Organic Compounds Produced by Trichoderma asperellum with Antifungal Properties against Colletotrichum acutatum
Authors: Chávez-Avilés Mauricio Nahuam , García-Álvarez Margarita , Ávila-Oviedo José Luis , Hernández-Hernández Irving , Bautista-Ortega Paula Itzel , Macías-Rodríguez Lourdes Iveth
Published: October 2024

Managing plant diseases caused by phytopathogenic fungi, such as anthracnose caused by Colletotrichum species, is challenging. Different methods have been used to identify compounds with antibiotic properties. Trichoderma strains are a source of novel molecules with antifungal properties, including volatile organic compounds (VOCs), whose production is influenced by the nutrient content of the medium. In this study, we assessed the VOCs produced in dual confrontation systems performed in two culture media by Trichoderma strains (T. atroviride IMI206040, T. asperellum T1 and T3, and Trichoderma sp. T2) on Colletotrichum acutatum. We analysed the VOC profiles using gas chromatography coupled with mass spectrometry. The Luria Bertani (LB) medium stimulated the production of VOCs with antifungal properties in most systems. We identified 2-pentyl furan, dimethyl disulfide, and α-phellandrene and determined their antifungal activity in vitro. The equimolar mixture of those VOCs (250 µM ea.) resulted in 14% C. acutatum diametral growth inhibition. The infective ability and disease severity caused by the mycelia exposed to the VOCs mixture were notably diminished in strawberry leaves. Application of these VOCs as biofumigants may contribute to the management of anthracnose. LB represents a feasible strategy for identifying novel VOCs produced by Trichoderma strains with antifungal properties.
The Predatory Properties of Bradymonabacteria, the Representative of Facultative Prey-Dependent Predators
Authors: Wang Shuo , Gong Ya , Chen Guan-Jun , Du Zong-Jun
Published: October 2024

Bradymonabacteria, as the representative of the facultative prey-dependent predators, were re-classified from the preceding Deltaproteobacteria into the phylum Myxococcota and proposed as a novel class named Bradymonadia. However, it was ambiguous whether their predatory pattern and properties were similar to those of the other myxobacterial predators. Therefore, the physiologic features were compared to determine the similarities and differences during the process of group attack and kin discrimination. Comparative genomic analyses were performed to conclude the core genome encoded commonly by bradymonabacteria, Myxococcia, and Polyangia. In conclusion, we proposed that bradymonabacteria have a predation pattern similar to the that of the representative of opportunistic predators like Myxococcus xanthus but with some subtle differences. Their predation was predicted to be initiated by the needle-less T3SS*, and the S-motility mediated by T4P also participated in the process. Meanwhile, their group attacks relied on cell contact and cell destiny. Inter-species (strains) kin discriminations occurred without the existence of T6SS. However, no extracellular lethal substance was detected in the fermentation liquor culture of bradymonabacteria, and the death of prey cells could only be observed when touched by their cells. Moreover, the prey-selective predation was observed when the predator encountered certain prey from Bacillus (G+), Algoriphagus (G−), and Nocardioides (G+). Bradymonabacteria can be regarded as a potential consumer and decomposer, and preying on many sea-dwelling or human pathogenic bacteria allows this group a broad application prospect in marine culture and clinical disease control. Our study will provide more evidence for its exploitations and applications.