bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-dimensional asymptotics of denoising autoencoders*
Authors: Cui Hugo , Zdeborová Lenka 
Published: October 2024

Abstract
We address the problem of denoising data from a Gaussian mixture using a two-layer non-linear autoencoder with tied weights and a skip connection. We consider the high-dimensional limit where the number of training samples and the input dimension jointly tend to infinity while the number of hidden units remains bounded. We provide closed-form expressions for the denoising mean-squared test error. Building on this result, we quantitatively characterize the advantage of the considered architecture over the autoencoder without the skip connection that relates closely to principal component analysis. We further show that our results accurately capture the learning curves on a range of real data sets.
Open climate science is brave climate science
Authors: Thöle Lena M , Wegmann Martin 
Published: October 2024

Abstract
The pivotal role of climate science in advancing the UN Sustainable Development Goals underscores the urgent need for ample and open climate data sharing. While numerous large-scale endeavours highlight the efficacy of open climate data, we often encounter personal reservations in our scientific community. Here we argue that beyond infrastructure and service availability, a framework of acceptance and courage is needed in progressing data visibility.
Scaffold-based tissue engineering strategies for urethral repair and reconstruction
Authors: Jin Yangwang , Yang Ming , Zhao Weixin , Liu Meng , Fang Wenzhuo , Wang Yuhui , Gao Guo , Wang Ying , Fu Qiang 
Published: October 2024

Abstract
Urethral strictures are common in urology; however, the reconstruction of long urethral strictures remains challenging. There are still unavoidable limitations in the clinical application of grafts for urethral injuries, which has facilitated the advancement of urethral tissue engineering. Tissue-engineered urethral scaffolds that combine cells or bioactive factors with a biomaterial to mimic the native microenvironment of the urethra, offer a promising approach to urethral reconstruction. Despite the recent rapid development of tissue engineering materials and techniques, a consensus on the optimal strategy for urethral repair and reconstruction is still lacking. This review aims to collect the achievements of urethral tissue engineering in recent years and to categorize and summarize them to shed new light on their design. Finally, we visualize several important future directions for urethral repair and reconstruction.
Functional properties of expanded austenite generated on AISI 316L by plasma nitrocarburizing using different active screen materials
Authors: M Jafarpour S , Mandel M , Krüger L , Biermann H , Dalke A 
Published: October 2024

Abstract
This study investigates the functional properties of the expanded austenite layers generated on AISI 316L austenitic stainless steel resulting from active screen plasma nitrocarburizing using different active screen materials, i.e. steel or solid carbon. Treatments were conducted at 460 °C for 5 h in a nitrogen-hydrogen feed gas, whereas for the treatments using a steel active screen, methane was added as a carbon precursor. Additionally, the bias plasma conditions applied at the samples were varied between 0 kW and 1.25 kW. Samples were characterized by complementary microstructural and compositional investigations, surface roughness and hardness measurements, pin-on-disk tribological tests as well as potentiodynamic polarization tests in H2SO4 and NaCl electrolytes. The functional properties of the case are discussed based on the contents of nitrogen and carbon in the expanded austenite and their effective diffusion depths. The results show that the usage of a carbon screen generally produces surfaces with uniform layer thickness, high hardness, improved wear resistance and a delayed tendency to pitting corrosion independent of the bias condition applied to the samples. When applying both screen materials at non-biased condition, the general corrosion resistance is slightly reduced under the conditions used, however, the layers generated using the carbon screen have a wear rate that is 3 times lower. It can be concluded that the carbon screen represents a robust treatment variant for austenitic stainless steels to produce sufficiently thick and wear-resistant surface layers in a short treatment duration, which still have the potential to maintain the corrosion resistance in different environments.
Procedure for reducing cross-resonance gate errors using pulse-level control
Authors: Danin David , Tennie Felix 
Published: October 2024

Abstract
Current implementations of superconducting qubits are often limited by the low fidelities of multi-qubit gates. We present a reproducible and runtime-efficient pulse-level approach for calibrating an improved cross-resonance gate CR(θ) for arbitrary θ. This CR(θ) gate can be used to produce a wide range of other two-qubit gates via the application of standard single-qubit gates. By performing an interleaved randomised benchmarking sequence, we demonstrate that our approach leads to significantly lower incoherent errors than the circuit-level approach currently used by IBM. Hence, our procedure provides a genuine improvement for applications where noise remains a limiting factor.
Gap-filling of land surface temperature in arid regions by combining Landsat 8 and 9 imageries
Authors: Arabi Aliabad Fahime , Ghaderpour Ebrahim , Mazidi Ahmad , Houshmandzade Fatemeh 
Published: October 2024

Abstract
Land surface temperature (LST) is an important factor in land monitoring studies, but due to the presence of clouds, dust and sensor issues, there are missing values. The aims of this research are to determine the optimal parameters for the reconstruction of Landsat-LST images, required in many applications, by the harmonic analysis of time series algorithm (HANTS) and to investigate the possibility of improving LST reconstruction accuracy using Landsat 8 and 9 images simultaneously. For these aims, 91 Landsat 8 and 9 images with 100 m spatial resolution in 2022 and 2023 are employed, covering Yazd-Ardakan plain in Iran. Three methods are used for evaluation. In method one, a part of LST image is considered as a gap and is compared with the initial value after reconstruction. In method two, on a cloudy day and a cloudless day, surface temperature values are measured using thermometers at fifty points in plain lands, and the difference between gap-filled satellite measurements and ground measurements is calculated. In method three, all the reconstructed LST images are compared with the original images. In method one, the root mean square error (RMSE) of reconstructed LST reduces by 1.3 °C when using the combined Landsat 8 and 9 images. In method two, RMSEs of reconstructed LST images are 6.1 °C when using Landsat 8 and 5.4 °C when using the combined Landsat 8 and 9. Method three shows that 41% of the study region has RMSE of less than 2 °C when using only Landsat 8, while this value becomes 72% when combining Landsat 8 and 9. In general, the combined use of Landsat 8 and 9 LST images improves the accuracy of reconstruction using HANTS. The findings of this research are crucial for regional applications and remote monitoring of surface temperature in areas with limited weather stations.
Exploring the potential of contemporary deep learning methods in purifying polluted information
Authors: Wang Mingyu , Li Jianping 
Published: October 2024

Abstract
Accurately predicting chaotic dynamical systems is a crucial task in various fields, and recent advancements have leveraged deep learning for this purpose. However, in the era of big data, the inevitable challenge of data contamination caused by invalid information from other interfering systems becomes increasingly prominent and complicates accurate predictions. Although contemporary deep learning methods have shown their potential, very few studies have focused on developing algorithms specifically designed to address the problem posed by such data contamination. Thus, exploring the ability of contemporary deep learning methods to purify polluted information fills an important gap in the current body of research. This study explores the performance and stability of several modern deep learning techniques for predicting chaotic systems using datasets polluted by invalid information. Our findings reveal that while most of the state-of-the-art deep learning methods exhibit reduced and unstable predictive performance owing to such contamination, the dynamical system deep learning (DSDL) method stands out, remaining unaffected by any interference. This breakthrough illustrates DSDL’s unique ability to purify invalid data and uncover the inherent rules of chaotic systems. As we move forward, DSDL paves the way for a more reliable and interpretable model, ensuring that we can confidently predict chaotic systems with precision even in the most challenging environments.
Revisiting the epidemiological role of a native vector in Northern California vineyards
Authors: Daugherty Matthew P , Cooper Monica L , Smith Rhonda J , Varela Lucia G , Almeida Rodrigo P P 
Published: October 2024

Abstract
Effective disease management hinges on an accurate understanding of the ecological and epidemiological underpinnings of the pathosystem. New epidemics may prompt consideration of whether knowledge gaps or changes to the pathosystem warrant revision of management strategies. Pierce’s disease of grapevines is highly episodic in coastal Northern California vineyards, with modest incidence in most years punctuated by occasionally severe epidemics. To better understand what was driving a developing epidemic in the region, we revaluated what is known about the ecology and epidemiological role of the dominant vector, the blue-green sharpshooter Graphocephala atropunctata. We monitored vector spatiotemporal dynamics at 32 vineyards over three years, surveyed plant community composition in the adjacent habitat to understand its link to vector recruitment, and quantified patterns of natural infectivity for the pathogen Xylella fastidiosa. Overall, the results were consistent with past studies of G. atropunctata ecology. For example, the scale of dispersal from source habitat and seasonal patterns in activity were generally similar to those documented in prior studies. The results also confirmed the influence of adjacent plant community composition on G. atropunctata activity in vineyards, and the role of riparian habitat and select plant taxa as vector sources. Nonetheless, further consideration of the epidemiological significance of certain features of the pathosystem may be warranted, especially those related to seasonality in X. fastidiosa infection in vectors. A marked increase in infected G. atropunctata late in the season likely reflects pathogen acquisition from infected grapevines, which may have implications for disease management strategies.
Periconceptional omega-6 and omega-3 polyunsaturated fatty acid intake plane and postpartum depression: a nationwide birth cohort—the Japan Environment and Children’s Study
Authors: Matsumura Kenta , Hamazaki Kei , Tsuchida Akiko ,   the Japan Environment and Children’s Study (JECS) Group, Inadera Hidekuni 
Published: October 2024

Abstract
Intake of omega-3 polyunsaturated fatty acids (PUFAs) has favorable effects on the prevention of postpartum depression, but fish, the principal source of omega-3 PUFAs, are becoming a depleted resource. We therefore examined whether lower periconceptional intake of omega-6 PUFAs, whose metabolic pathways are antagonistic to those of omega-3 PUFAs, is associated with lower prevalence of postpartum depression while simultaneously considering omega-3 PUFA intake. The participants were 92,595 mothers involved in the ongoing Japan Environment and Children's Study. Periconceptional intakes of omega-6 and -3 PUFA were measured using a food frequency questionnaire. Postpartum depression was assessed using the Edinburgh Postnatal Depression Scale. Generalized additive mixed model analysis was used to draw contour plots of postpartum depression on a plane with omega-6 and omega-3 PUFA intakes on the x- and y-axes, respectively. The adjusted prevalence ranged from 11.0% to 26.3% within the respective 1st to 99th percentile intake ranges and monotonously decreased with decreasing omega-6 PUFA intake. In contrast, the prevalence decreased with increasing omega-3 PUFA intake, but the trend almost disappeared above 2 g/day. Our results highlight the potential importance of focusing on omega-6 PUFAs as well as omega-3 PUFAs prior to conception to reduce postpartum depression.
Recognition Subtests for Form B of the Repeatable Battery for the Assessment of Neuropsychological Status: Preliminary Validation
Authors: Duff Kevin , Turok Nora Grace , Piryatinsky Irene 
Published: October 2024

Abstract

Objective
Develop and preliminarily validate recognition subtests for Form B of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS).

Method
49 older adults with no cognitive impairment were compared to 53 individuals with a primary neurocognitive disorder (e.g., dementia, mild cognitive impairment, and traumatic brain injury) and 22 individuals with a primary psychiatric disorder (e.g., depression and anxiety) on three recognition subtests (list, story, and figure) for Form B of the RBANS in this observational study.

Results
The individuals with a primary neurocognitive disorder performed significantly poorer on most of the recognition scores compared to those with no cognitive impairment and those with a primary psychiatric disorder, with these latter two groups being largely comparable. In the entire sample, for the recognition subtests, education only correlated with figure recognition scores, and neither age nor gender influenced recognition scores. The RBANS indexes correlated with most of the recognition scores in the expected directions.

Conclusions
The group differences in performance on these recognition subtests preliminarily validate these scores on Form B, which were not previously available. Furthermore, these scores tended to not be influenced by age, education, or gender, although they were related to overall cognitive functioning. Additional validation is needed in larger, better clinically-defined, and more diverse samples. Nonetheless, these findings support the inclusion of the newly-developed Form B recognition subtests in future clinical practice and research settings to enhance the accuracy of diagnoses and treatment recommendations.
Paper and Textile Encounters in the Pacific
Authors: Fowler Caroline 
Published: October 2024

Abstract
This essay focuses on an eighteenth-century book, A Catalogue of the Different Specimens of Cloth Collected in the Three Voyages of Captain Cook to the Southern Hemisphere, which opens up alternative histories of paper in the early modern world. The work consists of a letterpress pamphlet describing the production of bark cloth (tapa), bound with samples of tapa, which were acquired from one of Captain Cook’s naval officers. In placing paper and bark cloth into relationship with one another, the work offers another vantage point from which to theorise not only the material history of paper but also the ways in which paper was dependent on an ability to ‘invisibly occupy’. Paper’s material invisibility is both part of its strength while also demonstrating the intellectual blind spots that can occur in attending solely to material histories of paper worlds.
Statistical analysis of multiple regions-of-interest in multiplexed spatial proteomics data
Authors: Samorodnitsky Sarah , Wu Michael C 
Published: October 2024

Abstract
Multiplexed spatial proteomics reveals the spatial organization of cells in tumors, which is associated with important clinical outcomes such as survival and treatment response. This spatial organization is often summarized using spatial summary statistics, including Ripley’s K and Besag’s L. However, if multiple regions of the same tumor are imaged, it is unclear how to synthesize the relationship with a single patient-level endpoint. We evaluate extant approaches for accommodating multiple images within the context of associating summary statistics with outcomes. First, we consider averaging-based approaches wherein multiple summaries for a single sample are combined in a weighted mean. We then propose a novel class of ensemble testing approaches in which we simulate random weights used to aggregate summaries, test for an association with outcomes, and combine the $P$-values. We systematically evaluate the performance of these approaches via simulation and application to data from non-small cell lung cancer, colorectal cancer, and triple negative breast cancer. We find that the optimal strategy varies, but a simple weighted average of the summary statistics based on the number of cells in each image often offers the highest power and controls type I error effectively. When the size of the imaged regions varies, incorporating this variation into the weighted aggregation may yield additional power in cases where the varying size is informative. Ensemble testing (but not resampling) offered high power and type I error control across conditions in our simulated data sets.
A two-task predictor for discovering phase separation proteins and their undergoing mechanism
Authors: Zhou Yetong , Zhou Shengming , Bi Yue , Zou Quan , Jia Cangzhi 
Published: October 2024

Abstract
Liquid–liquid phase separation (LLPS) is one of the mechanisms mediating the compartmentalization of macromolecules (proteins and nucleic acids) in cells, forming biomolecular condensates or membraneless organelles. Consequently, the systematic identification of potential LLPS proteins is crucial for understanding the phase separation process and its biological mechanisms. A two-task predictor, Opt_PredLLPS, was developed to discover potential phase separation proteins and further evaluate their mechanism. The first task model of Opt_PredLLPS combines a convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) through a fully connected layer, where the CNN utilizes evolutionary information features as input, and BiLSTM utilizes multimodal features as input. If a protein is predicted to be an LLPS protein, it is input into the second task model to predict whether this protein needs to interact with its partners to undergo LLPS. The second task model employs the XGBoost classification algorithm and 37 physicochemical properties following a three-step feature selection. The effectiveness of the model was validated on multiple benchmark datasets, and in silico saturation mutagenesis was used to identify regions that play a key role in phase separation. These findings may assist future research on the LLPS mechanism and the discovery of potential phase separation proteins.
Neurodegenerative fluid biomarkers are enriched in human cervical lymph nodes
Authors: Al-Diwani Adam , Provine Nicholas M , Murchison Andrew , Laban Rhiannon , Swann Owen J , Koychev Ivan , Sheerin Fintan , Da Mesquita Sandro , Heslegrave Amanda , Zetterberg Henrik , Klenerman Paul , Irani Sarosh R 
Published: October 2024

Abstract
In animal models, brain neurodegeneration biomarkers drain into cervical lymph nodes (CLNs), and this drainage function is reduced with ageing. If this occurred in humans, CLNs may provide a readily accessible measure of this aspect of protein clearance. We tested this hypothesis in people using ultrasound-guided fine needle aspiration.
We measured amyloid-beta 40 and 42, phosphorylated tau 181 (pTau181), glial fibrillary acidic protein and neurofilament light using single molecule array in CLN aspirates and plasma from: (i) a discovery cohort of 25 autoimmune patients; and (ii) plasma, CLNs and capillary blood in four healthy volunteers, an optimization cohort.
Ultrasound-guided fine needle aspiration was well-tolerated by all participants. In both cohorts, all biomarkers were detected in all plasma and CLN samples, other than neurofilament light (8/17 of discovery cohort). CLN biomarker concentrations were significantly greater than plasma concentrations for all except neurofilament light, most markedly for pTau181 (266-fold; P &lt; 0.02), whose CLN concentrations decreased with age (Spearman r = −0.66, P = 0.001).
This study presents the first evidence that neurodegenerative biomarkers are detectable in human CLNs. Raised CLN:plasma biomarker ratios suggest their concentration in CLNs may offer a distinct compartment for minimally-invasive measurement of brain clearance and lymphatic drainage, with potential applicability to study of ageing and future clinical trials.
Modularity based community detection in hypergraphs
Authors: Kamiński Bogumił , Misiorek Paweł , Prałat Paweł , Théberge François 
Published: October 2024

Abstract
In this paper, we propose a scalable community detection algorithm using hypergraph modularity function, h–Louvain. It is an adaptation of the classical Louvain algorithm in the context of hypergraphs. We observe that a direct application of the Louvain algorithm to optimize the hypergraph modularity function often fails to find meaningful communities. We propose a solution to this issue by adjusting the initial stage of the algorithm via carefully and dynamically tuned linear combination of the graph modularity function of the corresponding two-section graph and the desired hypergraph modularity function. The process is guided by Bayesian optimization of the hyper-parameters of the proposed procedure. Various experiments on synthetic as well as real-world networks are performed showing that this process yields improved results in various regimes.
Dietary salt, vascular dysfunction, and cognitive impairment
Authors: Faraco Giuseppe 
Published: October 2024

Abstract
Excessive salt consumption is a major health problem worldwide leading to serious cardiovascular events including hypertension, heart disease, and stroke. Additionally, high-salt diet has been increasingly associated with cognitive impairment in animal models and late-life dementia in humans. High-salt consumption is harmful for the cerebral vasculature, disrupts blood supply to the brain, and could contribute to Alzheimer’s disease pathology. Although animal models have advanced our understanding of the cellular and molecular mechanisms, additional studies are needed to further elucidate the effects of salt on brain function. Furthermore, the association between excessive salt intake and cognitive impairment will have to be more thoroughly investigated in humans. Since the harmful effects of salt on the brain are independent by its effect on blood pressure, in this review, I will specifically discuss the evidence, available in experimental models and humans, on the effects of salt on vascular and cognitive function in the absence of changes in blood pressure. Given the strong effects of salt on the function of immune cells, I will also discuss the evidence linking salt consumption to gut immunity dysregulation with particular attention to the ability of salt to disrupt T helper 17 (Th17) cell homeostasis. Lastly, I will briefly discuss the data implicating IL-17A, the major cytokine produced by Th17 cells, in vascular dysfunction and cognitive impairment.