bluuebunny/crossref_metadata_2025_split huggingface dataset:
Endosome mediated nucleocytoplasmic trafficking and endomembrane allocation is crucial to polyglutamine toxicity
Authors: Nan Yuyu , Chen Wenfeng , Chen Fei , Wei Lili , Zeng Aiyuan , Lin Xiaohui , Zhou Wenbin , Yang Yufeng , Li Qinghua 
Published: June 2024

AbstractAggregation of aberrant proteins is a common pathological hallmark in neurodegeneration such as polyglutamine (polyQ) and other repeat-expansion diseases. Here through overexpression of ataxin3 C-terminal polyQ expansion in Drosophila gut enterocytes, we generated an intestinal obstruction model of spinocerebellar ataxia type3 (SCA3) and reported a new role of nuclear-associated endosomes (NAEs)–the delivery of polyQ to the nucleoplasm. In this model, accompanied by the prominently increased RAB5-positive NAEs are abundant nucleoplasmic reticulum enriched with polyQ, abnormal nuclear envelope invagination, significantly reduced endoplasmic reticulum, indicating dysfunctional nucleocytoplasmic trafficking and impaired endomembrane organization. Consistently, Rab5 but not Rab7 RNAi further decreased polyQ-related NAEs, inhibited endomembrane disorganization, and alleviated disease model. Interestingly, autophagic proteins were enriched in polyQ-related NAEs and played non-canonical autophagic roles as genetic manipulation of autophagic molecules exhibited differential impacts on NAEs and SCA3 toxicity. Namely, the down-regulation of Atg1 or Atg12 mitigated while Atg5 RNAi aggravated the disease phenotypes both in Drosophila intestines and compound eyes. Our findings, therefore, provide new mechanistic insights and underscore the fundamental roles of endosome-centered nucleocytoplasmic trafficking and homeostatic endomembrane allocation in the pathogenesis of polyQ diseases.
Graphical Abstract
Dried nanocellulose/xanthan as reinforcing fillers in thermoplastic starch
Authors: Hoek Zian , du Toit Elizabeth L. , Niemand Danielle , Wesley-Smith James , Focke Walter W. 
Published: June 2024

AbstractNanocellulose fibres are known to enhance the mechanical properties of biopolymers when added as a filler. Nanocellulose irreversibly agglomerates upon drying and is therefore sold as an aqueous gel or suspension, increasing shipping cost and limiting application. This work studied the utility of xanthan gum as a dispersant aid for dried nanocellulose fibres. At levels as low as 15% xanthan gum addition, based on the mass of nanocellulose, prior to drying, agglomeration was significantly decreased. Mild shear rates could disperse the dried nanocellulose to a similar degree as ultrasonication when xanthan gum was present. Several complementary techniques, such as rheology, turbidimetry, and SEM- and TEM-imaging, proved that the native nanocellulose properties could be recovered after drying. Xanthan gum and nanocellulose, when incorporated into thermoplastic starch, showed a synergistic effect regarding the increase in tensile strength of the resultant biopolymer film. The addition of previously dried nanocellulose/xanthan, in a 4:1 ratio, to thermoplastic starch at a starch-cellulose ratio of 20:1, increased the tensile strength from 5.4 to 23.0 MPa. The ability to produce a dispersible and dry nanocellulose product that retains its properties has clear commercial benefits.
Series2vec: similarity-based self-supervised representation learning for time series classification
Authors: Foumani Navid Mohammadi , Tan Chang Wei , Webb Geoffrey I. , Rezatofighi Hamid , Salehi Mahsa 
Published: June 2024

AbstractWe argue that time series analysis is fundamentally different in nature to either vision or natural language processing with respect to the forms of meaningful self-supervised learning tasks that can be defined. Motivated by this insight, we introduce a novel approach called Series2Vec for self-supervised representation learning. Unlike the state-of-the-art methods in time series which rely on hand-crafted data augmentation, Series2Vec is trained by predicting the similarity between two series in both temporal and spectral domains through a self-supervised task. By leveraging the similarity prediction task, which has inherent meaning for a wide range of time series analysis tasks, Series2Vec eliminates the need for hand-crafted data augmentation. To further enforce the network to learn similar representations for similar time series, we propose a novel approach that applies order-invariant attention to each representation within the batch during training. Our evaluation of Series2Vec on nine large real-world datasets, along with the UCR/UEA archive, shows enhanced performance compared to current state-of-the-art self-supervised techniques for time series. Additionally, our extensive experiments show that Series2Vec performs comparably with fully supervised training and offers high efficiency in datasets with limited-labeled data. Finally, we show that the fusion of Series2Vec with other representation learning models leads to enhanced performance for time series classification. Code and models are open-source at https://github.com/Navidfoumani/Series2Vec
Detecting mining impacts on freshwater ecosystems using replicated sampling before and after the impact
Authors: Mykrä Heikki , Aroviita Jukka , Tolonen Kimmo , Turunen Jarno , Weckström Kaarina , Weckström Jan , Hellsten Seppo 
Published: June 2024

AbstractDetecting human impact on freshwater ecosystems is problematic without rigorous assessment of temporal changes. Assessments of mining impacts are further complicated by the strong influence of local catchment geology on surface waters even in unmined environments. Such influence cannot be effectively considered by using broad-scale reference frameworks based on regionalization and stream types. Using the BACI (Before-After Control-Impact) design, we examined the impact of mining discharges on freshwater algae and macroinvertebrate communities resulting from the rerouting of treated wastewaters through a pipeline to larger water bodies in Northern and North-Eastern Finland. Impacted sites and control sites were sampled 1 to 2 years before and 1 to 3 years after the pipelines became operational. Stream diatom communities recovered from past loadings upstream of the pipeline (which was no longer impacted by wastewaters) after rerouting of the wastewaters, while no changes downstream from the pipeline were detected. Upstream from the pipeline, diatom species richness increased and changes in relative abundances of the most common diatom taxa as well as in the overall community composition were observed. The effects of the pipeline were less evident for stream macroinvertebrate communities. There was an indication that regional reference conditions used in national biomonitoring may not represent diatom communities in areas with a strong geochemical background influence. Lake profundal macroinvertebrate communities were impacted by past loadings before the construction of the pipeline, and the influence of the pipeline was observed only as changes in the abundances of a few individual species such as phantom midges (which increased in abundance in response to discharges directed through the pipeline). Our results highlight the variable influence of mining discharges on aquatic communities. Statistically strong monitoring programmes, such as BACI designs, are clearly needed to detect these influences.
On the Growing Universe of Causal Set Theory—An Order-Type Approach
Authors: Placek Tomasz , Wroński Leszek 
Published: June 2024

AbstractWe investigate a model of becoming—classical sequential growth (CSG)—that has been proposed within the framework of causal sets (causets), with the latter defined as order types of certain partial orderings. To investigate how causets grow, we introduce special sequences of causets, which we call “csg-paths”. We prove a number of results concerning relations between csg-paths and causets. These results paint a highly non-trivial picture of csg-paths. There are uncountably many csg-paths, all of them sharing the same beginning, after which they branch. Every infinite csg-path achieves in the limit an infinite causet, and vice versa, every infinite causet is achieved in the limit by an infinite csg-path. However, coalescing csg-paths, i.e., ones that achieve the same causet even after forking off at some point, are ubiquitous.
Growth and fatty acid profile of Nannochloropsis oceanica cultivated on nano-filtered whey permeate
Authors: Kiani Hossein , Ma Qinge , Xiao Mengsong , Li Yuchen , Brooke Felix Joel , Mulcahy Shane , Miros Svitlana , Halim Ronald 
Published: June 2024

AbstractNano-filtered whey permeate (WP), a major by-product of dairy industry, is produced by membrane filtration of whey. The oleaginous microalga Nannochloropsis oceanica was successfully cultivated on WP without salinity and nutrient amendments. Growth, cell characteristics, and fatty acid profile of the cultures were analyzed using microscopy, flow cytometry, and GC analysis. WP was nitrogen limited, comprising primarily protein as a nitrogen source and only small amounts of free inorganic nitrogen (in the form of nitrate). Nannochloropsis oceanica (and associated bacteria) efficiently removed nitrate (100%), protein (87%), and phosphate (74%) from the whey permeate. Microscopic and flow cytometric analysis revealed diverse size distributions in whey permeate cultures, with significant cell aggregation attributed to low-salinity acclimatization and nitrogen limitation. Autofluorescence analysis revealed reduced photosynthetic activity in whey permeate-grown cells, possibly as a consequence of heightened mixotrophic activities on carbon source in the medium. Low nitrogen availability in whey permeate resulted in biomass with a fatty acid profile enriched in saturated fatty acids. Despite this, a considerable level of the omega-3 polyunsaturated fatty acid (in the form of eicosapentanoic acid or EPA) was detected at ca. 16% of total fatty acids. Whey permeate proved beneficial for the growth of N. oceanica and yielded high concentrations of eicosapentaenoic acid in the extracted lipids for potential applications in the feed/food industries.
Exploring agricultural landscape change from the second half of the twentieth century onwards: combining aerial imagery with farmer perspectives
Authors: Mohr Franziska , Pazur Robert , Debonne Niels , Dossche Rebekka , Helfenstein Julian , Hepner Samuel , Levers Christian , Verburg Peter H. , Bürgi Matthias 
Published: June 2024

Abstract
Context
Anthropogenic landscape change is an important driver shaping our environment. Historical landscape analysis contributes to the monitoring and understanding of these change processes. Such analyses are often focused on specific spatial scales and single research methods, thus covering only limited aspects of landscape change.

Objectives
Here, we aim to assess the potential of combining the analysis of historical aerial imagery and local stakeholder interviews for landscape change studies using a standardized mapping and interviewing approach.

Methods
We compared six agricultural landscapes across Europe and mapped land-cover using historical aerial imagery (starting between 1930 and 1980, depending on data availability, until recent years) with an object-based image analysis and random forest classification. For local perspectives of landscape change, we conducted oral history interviews (OHIs) with (almost) retired farmers. Comparing recorded landscape changes from both approaches provided insight into advantages of combining these two methods.

Results
Object-based analysis enabled the identification of high-resolution land-cover dynamics, with scale enlargement and cropland/grassland expansion being the most commonly recurring trends across European landscapes. Perceived landscape changes identified in the OHIs included changes in farm management, landscape structure, and infrastructure. Farmers also reported drivers and personal values associated with landscape change. Combining the two historical landscape analysis tools resulted in a qualitative and quantitative understanding of changes in land-cover, land use, and land management.

Conclusions
Comparing physical land-cover change with local farmer perspectives is key to a comprehensive understanding of landscape change. There are different ways the two methods can be combined, leading to different venues for science and policy making.
Fluctuation Moments for Regular Functions of Wigner Matrices
Authors: Reker Jana 
Published: June 2024

AbstractWe compute the deterministic approximation for mixed fluctuation moments of products of deterministic matrices and general Sobolev functions of Wigner matrices. Restricting to polynomials, our formulas reproduce recent results of Male et al. (Random Matrices Theory Appl. 11(2):2250015, 2022), showing that the underlying combinatorics of non-crossing partitions and annular non-crossing permutations continue to stay valid beyond the setting of second-order free probability theory. The formulas obtained further characterize the variance in the functional central limit theorem given in the recent companion paper (Reker in Preprint, arXiv:2204.03419, 2023). and thus allow identifying the fluctuation around the thermal value in certain thermalization problems.
Key points trajectory and multi-level depth distinction based refinement for video mirror and glass segmentation
Authors: Wang Ziyue , Liu Yanchao , Cheng Xina , Ikenaga Takeshi 
Published: June 2024

AbstractMirror and glass are ubiquitous materials in the 3D indoor living environment. However, the existing vision system always tends to neglect or misdiagnose them since they always perform the special visual feature of reflectivity or transparency, which causes severe consequences, i.e., a robot or drone may crash into a glass wall or be wrongly positioned by the reflections in mirrors, or wireless signals with high frequency may be influenced by these high-reflective materials. The exploration of segmenting mirrors and glass in static images has garnered notable research interest in recent years. However, accurately segmenting mirrors and glass within dynamic scenes remains a formidable challenge, primarily due to the lack of a high-quality dataset and effective methodologies. To accurately segment the mirror and glass regions in videos, this paper proposes key points trajectory and multi-level depth distinction to improve the segmentation quality of mirror and glass regions that are generated by any existing segmentation model. Firstly, key points trajectory is used to extract the special motion feature of reflection in the mirror and glass region. And the distinction in trajectory is used to remove wrong segmentation. Secondly, a multi-level depth map is generated for region and edge segmentation which contributes to the accuracy improvement. Further, an original dataset for video mirror and glass segmentation (MAGD) is constructed, which contains 9,960 images from 36 videos with corresponding manually annotated masks. Extensive experiments demonstrate that the proposed method consistently reduces the segmentation errors generated from various state-of-the-art models and reach the highest successful rate at 0.969, mIoU (mean Intersection over Union) at 0.852, and mPA (mean Pixel Accuracy) at 0.950, which is around 40% - 50% higher on average on an original video mirror and glass dataset.
Effects of tumor treating fields (TTFields) on human mesenchymal stromal cells
Authors: Strack Maren , Kückelhaus Jan , Diebold Martin , Wuchter Patrick , Huber Peter E. , Schnell Oliver , Sankowski Roman , Prinz Marco , Grosu Anca-Ligia , Heiland Dieter Henrik , Nicolay Nils H. , Rühle Alexander 
Published: June 2024

Abstract
Purpose
Mesenchymal stromal cells (MSCs) within the glioblastoma microenvironment have been shown to promote tumor progression. Tumor Treating Fields (TTFields) are alternating electric fields with low intensity and intermediate frequency that exhibit anti-tumorigenic effects. While the effects of TTFields on glioblastoma cells have been studied previously, nothing is known about the influence of TTFields on MSCs.

Methods
Single-cell RNA sequencing and immunofluorescence staining were employed to identify glioblastoma-associated MSCs in patient samples. Proliferation and clonogenic survival of human bone marrow-derived MSCs were assessed after TTFields in vitro. MSC’ characteristic surface marker expression was determined using flow cytometry, while multi-lineage differentiation potential was examined with immunohistochemistry. Apoptosis was quantified based on caspase-3 and annexin-V/7-AAD levels in flow cytometry, and senescence was assessed with ß-galactosidase staining. MSCs’ migratory potential was evaluated with Boyden chamber assays.

Results
Single-cell RNA sequencing and immunofluorescence showed the presence of glioblastoma-associated MSCs in patient samples. TTFields significantly reduced proliferation and clonogenic survival of human bone marrow-derived MSCs by up to 60% and 90%, respectively. While the characteristic surface marker expression and differentiation capacity were intact after TTFields, treatment resulted in increased apoptosis and senescence. Furthermore, TTFields significantly reduced MSCs’ migratory capacity.

Conclusion
We could demonstrate the presence of tumor-associated MSCs in glioblastoma patients, providing a rationale to study the impact of TTFields on MSCs. TTFields considerably increase apoptosis and senescence in MSCs, resulting in impaired survival and migration. The results provide a basis for further analyses on the role of MSCs in glioblastoma patients receiving TTFields.
Dominant patterns in small directed bipartite networks: ubiquitous generalized tripod gait
Authors: Lozano Álvaro , Vigara Rubén , Mayora-Cebollero Carmen , Barrio Roberto 
Published: June 2024

AbstractThe synchronization patterns exhibited by small networks of neurons that regulate biological processes (CPGs) have aroused growing scientific interest. In many of these networks there is a main behavioral pattern within the parameter space. In particular, in the context of insect locomotion, tripod walking stands out as a predominant pattern, both in natural observations (where insects walk on tripod gait) and in mathematical models. This predominance appears to be stable under parameter variations within the network, suggesting a possible correlation with the underlying network topology. Tripod walking can be naturally extended to all CPGs with a bipartite connectivity. Then a natural question arises: Are “generalized tripod gaits” equally dominant among synchronization patterns within those networks? To investigate this, we carried out a comprehensive study covering all bipartite networks of up to nine neurons. For each of those networks we numerically explore the phase space using a quasi-MonteCarlo method to see what are the main synchronization patterns that the network can achieve. Then, all those patterns are grouped according to their dynamics. Generalized tripod gait was observed in all cases examined as the dominant pattern again. However, certain cases revealed additional stable patterns, mainly associated with the 3-colorings of the respective graph structures.
Modeling Study of Chemical Kinetics and Vibrational Excitation in a Volumetric DBD in Humid Air at Atmospheric Pressure
Authors: Pierotti Giacomo , Popoli Arturo , Pintassilgo Carlos Daniel , Cristofolini Andrea 
Published: June 2024

AbstractA zero-dimensionl model is developed to study the chemical kinetics of a volumetric dielectric barrier discharge (DBD) reactor operating with humid air at atmospheric pressure. This work focuses on the relation between molecular vibrational excitation, the plasma reactor input power and the number densities of several species that are known to play an important role in biomedical applications (e.g. $$\textrm{O}_{3},\textrm{NO, NO}_{2}$$

O
3

,
NO,

NO
2

, ...). A preliminary study is carried out to observe the influence of water molecules on the electron energy distribution function for different values of water concentration and reduced electric field. A simplified approach is then adopted to quantify the contribution of vibrationally-excited $$\textrm{O}_{2}$$

O
2

molecules to $$\textrm{NO}$$
NO
formation. The results obtained using our detailed model suggest that for the physical conditions considered in this work $$\textrm{O}_{2}$$

O
2

vibrational kinetics can be neglected without compromising the overall accuracy of the simulation. Finally, a reaction set is coupled with an equivalent circuit model to simulate the E-I characteristic of a typical DBD reactor. Different simulations were carried out considering different values of the average plasma input power densities. A particular focus was given to the influence of the Zeldovich mechanism on $$\textrm{O}_{3}$$

O
3

and $$\textrm{NO}_\textrm{X}$$

NO
X

production performing simulations where this reaction is not considered. The obtained results are shown and the role of vibrationally excited $$\textrm{N}_{2}$$

N
2

molecules is discussed. The simulation results indicate also that $$\textrm{N}_{2}$$

N
2

vibrational excitation, and more precisely the Zeldovich mechanism, has a larger effect on $$\textrm{O}_{3}$$

O
3

and $$\textrm{NO}_\textrm{X}$$

NO
X

production at intermediate input power levels.
Complementing or competing with public transit? Evaluating the parameter sensitivity of potential Mobility-as-a-Service (MaaS) urban users in Germany, the Czech Republic, Poland, and the United Kingdom with a mixed choice model
Authors: Matowicki Michal , Pecherkova Pavla , Amorim Marco , Kern Mira , Motzer Nicolaj , Pribyl Ondrej 
Published: June 2024

AbstractIn this study, we conducted a comprehensive survey involving a substantial sample size (n = 6,405) of urban daily commuters across four European nations (Germany, the United Kingdom, Poland, and the Czech Republic). Our investigation contributes to an enriched comprehension of the user dynamics associated with Mobility-as-a-Service alternatives and their interrelation with public transit modalities in the context of travel preferences. Specifically, we researched the responsiveness of participants to variations in pricing and travel durations. Additionally, we examine the tendencies of various participant categories, stratified into distinct segments based on shared attributes, toward the adoption of public transportation, MaaS solutions, or private vehicular transport. Our findings highlight the essential role fundamental mobility determinants, such as price and travel time, play in influencing the likelihood of opting for a specific transportation modality. This phenomenon was particularly discernible within the "Unspecified Users" group, which gives us options to alter their behavior. The analytical framework used in our study that combined several mathematical modeling tools provided insight into the choices people make when choosing between different travel options, and our findings may be used by decision makers to create better and more informed approaches to promote sustainable alternatives to the use of cars in urban settings.