bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adaptive neural network-based sliding mode control for trajectory tracking control of cable-driven continuum robots with uncertainties
Authors: Chen Qi , Ming Chengjun , Qin Yanan 
Published: November 2024

Abstract
In this paper, a novel fast nonsingular integral terminal sliding mode controller based on an adaptive neural network (ANN-FNITSMC) is proposed for the trajectory tracking control of cable-driven continuum robots (CDCRs) in complex underwater environments with uncertainties. First, a novel fast nonsingular integral terminal sliding mode control (FNITSMC) is designed to solve the chattering and singularity problems of the conventional terminal sliding mode control (TSMC). Second, an adaptive neural network (ANN) based on a radial basis function (RBF) is established to derive the uncertainties and compensate for the control input of CDCRs, enabling high-stable accuracy and strong robustness trajectory tracking in complex underwater environments. Simulation results are presented to demonstrate the high accuracy and strong robustness of the ANN-FNITSMC. Finally, the high accuracy, high stability, and strong robustness of the proposed trajectory tracking strategy are verified through an underwater experiment platform.
Response of corn to reduced rates of tiafenacil applied at vegetative growth stages
Authors: Miller Donnie K. , Barber Tom L. , Bond Jason A. , Steckel Lawrence E. , Stephenson Daniel O. , Foster Matthew R. , Butts Thomas R. , Kouame Koffi Badou-Jeremie 
Published: November 2024

Abstract
Tiafenacil is a new nonselective protoporphyrinogen IX oxidase (PPO)–inhibiting herbicide with both grass and broadleaf activity labeled for preplant application to corn, cotton, soybean, and wheat. Early-season corn emergence and growth often coincides in the mid-South with preplant herbicide application in cotton and soybean, thereby increasing opportunity for off-target herbicide movement from adjacent fields. Field studies were conducted in 2022 to identify the impacts of reduced rates of tiafenacil (12.5% to 0.4% of the lowest labeled application rate of 24.64 g ai ha–1) applied to two- or four-leaf corn. Corn injury 1 wk after treatment (WAT) for the two- and four-leaf growth stages ranged from 31% to 6% and 37% to 9%, respectively, whereas at 2 WAT these respective ranges were 21.7% to 4% and 22.5% to 7.2%. By 4 WAT, visible injury following the two- and four-leaf exposure timing was no greater than 8% in all instances except the highest tiafenacil rate applied at the four-leaf growth stage (13%). Tiafenacil had no negative season-long impact, as the early-season injury observed was not manifested in a reduction in corn height 2 WAT or yield. Application of tiafenacil directly adjacent to corn in early vegetative stages of growth should be avoided. In cases where off-target movement does occur, however, affected corn should be expected to fully recover with no impact on growth and yield, assuming adequate growing conditions and agronomic/pest management practices are provided.
Observed Pathways and Interannual Variability of the Warm Inflow Onto the Continental Shelf in the Southern Weddell Sea
Authors: Steiger N. , Sallée J. B. , Darelius Elin , Janout Markus , Østerhus Svein 
Published: November 2024

AbstractModel projections suggest that the continental shelf in the southern Weddell Sea may experience a shift from today's near‐freezing temperature to a much warmer state, where warm water floods the shelf and basal melt rates beneath the Filchner Ronne Ice Shelf increase dramatically. Today, the Filchner Trough serves as a conduit for the southward flow of Warm Deep Water (WDW) during summer and, thus, requires continuous monitoring of its hydrographic conditions. An extensive network of moorings was installed at key sites along the inflow pathway from 2017 to 2021, to expand on existing mooring records starting in 2014. The moorings complemented with under‐ice profiling floats reveal two inflow pathways, where WDW enters along the eastern flank of the Filchner Trough as well as through a smaller trough east of there. Within the observed period, 2017 and 2018 feature anomalously warm inflows. The inflow is regulated by the heaving of isopycnals over the continental slope, and the southward propagation toward Filchner Ice Shelf is two times faster during these warm years. Furthermore, the warm years coincide with low summer sea ice concentration, which enhances surface stratification through increased freshwater input and modifies sea ice‐ocean stresses that both act to lift the warm water layer and increase the temperatures on the continental shelf. Finally, the recent record low sea ice conditions around the Antarctic emphasize the importance of our findings and raise concerns regarding a potentially increasing presence of WDW on the southern Weddell Sea shelf.
Impact‐Based Skill Evaluation of Seasonal Precipitation Forecasts
Authors: Nikraftar Zahir , Mbuvha Rendani , Sadegh Mojtaba , Landman Willem A. 
Published: November 2024

AbstractWe introduce an impact‐based framework to evaluate seasonal forecast model skill in capturing extreme weather and climate events over regions prone to natural disasters such as floods and wildfires. Forecasting hydroclimatic extremes holds significant importance in an era of increasing hazards such as wildfires, floods, and droughts. We evaluate the performance of five Copernicus Climate Change Service (C3S) seasonal forecast models (CMCC, DWD, ECCC, UK‐Met, and Météo‐France) in predicting extreme precipitation events from 1993 to 2016 using 14 indices reflecting timing and intensity (using absolute and locally defined thresholds) of precipitation at a seasonal timescale. Performance metrics, including Percent Bias, Kendall Tau Rank Correlation Score, and models' discrimination capacity, are used for skill evaluation. Our findings indicate that the performance of models varies markedly across regions and seasons. While models generally show good skill in the tropical regions, their skill in extra‐tropical regions is markedly lower. Elevated precipitation thresholds (i.e., higher intensity indices) correlate with heightened model biases, indicating deficiencies in modeling severe precipitation events. Our analysis using an impact‐based framework highlights the superior predictive capabilities of the UK‐Met and Météo‐France models in capturing the underlying processes that drive precipitation events, or lack thereof, across many regions and seasons. Other models exhibit strong performance in specific regions and/or seasons, but not globally. These results advance our understanding of an impact‐based framework in capturing a broad spectrum of extreme weather and climatic events, and inform strategic amalgamation of diverse models across different regions and seasons, thereby offering valuable insights for disaster management and risk analysis.
Distinct Propagation to Agricultural Drought Between Two Severe Meteorological Droughts in the Korean Peninsula
Authors: Ham Yoo‐Geun , Jeong Yerim , Seo Eunkyo 
Published: November 2024

AbstractDistinct responses in the soil moisture (SM) between the two most severe meteorological droughts in Korea are examined. Although total accumulated precipitation deficit during 1994–1996 drought was slightly less than in the 2013–2017 drought, 1994–1996 drought showed a record‐breaking negative SM anomalies, while the accumulated negative SM anomalies during 2013–2017 were less than half of those in 1994–1996. In 1994–1996 case, robust precipitation deficits occurred early in the event, leading to subsequent precipitation shortages under dry conditions. In addition, precipitation deficit was observed not only during wet seasons but also throughout dry seasons. This amplifies the SM response, as the runoff volume remains relatively constant despite reduced precipitation in arid soil conditions, which eventually reduces soil water retention led by the precipitation deficit. Conversely, in 2013–2017 case, precipitation deficit occurred during later period of the event and wet seasons, which leads a moderate SM drying signals.
Factors Affecting the Weakening Rate of Landfalling Tropical Cyclones Over China
Authors: Liu Lu , Liang Zhaoming , Wang Yuqing 
Published: November 2024

AbstractBased on the 6‐hourly tropical cyclone best track and global reanalysis data, statistical analyses and a machine learning approach are used to identify/quantify factors that affect the relative weakening rate (RWR) of landfalling TCs (LTCs) over China mainland during 1980–2020. Results show that the enhanced RWR of LTC events usually occurs when LTCs move into regions with large environmental vertical wind shear (VWS), large surface roughness (SURR), high land surface soil temperature (SOILT), low surface latent heat flux (SLHF), and with relatively faster translational speeds (SPD). The SPD and SURR are dominant factors determining the RWR of LTCs over China mainland, contributing about 20% and 18.5% to the RWR of LTCs. VWS is also a key factor affecting RWR of LTCs with mid‐level VWS contributing 17.8% to RWR of LTCs and low‐ and deep‐level VWS contributing about 12.9% and 11.2%, respectively. Furthermore, factors affecting the LTC weakening rate in south and north China are different. In north China, the VWS at different levels are all highly correlated with LTC RWR after landfall, whereas the influence of mid‐layer VWS shows significant correlation with LTC RWR in south China. In addition, surface characteristics, including SURR, SLHF, and SOILT, have significant correlation with LTC RWR in south China. But the relationships between surface characteristics and LTC RWR in north China are not statistically significant. It is worth noting that although the correlation between DIV200 and LTC RWR is insignificant for the whole China mainland, it presents highly negative and positive correlations in south and north China, respectively.
p63 affects distinct metabolic pathways during keratinocyte senescence, evaluated by metabolomic profile and gene expression analysis
Authors: Piro Maria Cristina , Pecorari Rosalba , Smirnov Artem , Cappello Angela , Foffi Erica , Lena Anna Maria , Shi Yufang , Melino Gerry , Candi Eleonora 
Published: November 2024

AbstractUnraveling the molecular nature of skin aging and keratinocyte senescence represents a challenging research project in epithelial biology. In this regard, depletion of p63, a p53 family transcription factor prominently expressed in human and mouse epidermis, accelerates both aging and the onset of senescence markers in vivo animal models as well as in ex vivo keratinocytes. Nonetheless, the biochemical link between p63 action and senescence phenotype remains largely unexplored. In the present study, through ultrahigh performance liquid chromatography–tandem mass spectroscopy (UPLC–MS/MS) and gas chromatography/mass spectrometry (GC/MS) metabolomic analysis, we uncover interesting pathways linking replicative senescence to metabolic alterations during p63 silencing in human keratinocytes. Integration of our metabolomic profiling data with targeted transcriptomic investigation empowered us to demonstrate that absence of p63 and senescence share similar modulation profiles of oxidative stress markers, pentose phosphate pathway metabolites and lyso-glycerophospholipids, the latter due to enhanced phospholipases gene expression profile often under p63 direct/indirect gene control. Additional biochemical features identified in deranged keratinocytes include a relevant increase in lipids production, glucose and pyruvate levels as confirmed by upregulation of gene expression of key lipid synthesis and glycolytic enzymes, which, together with improved vitamins uptake, characterize senescence phenotype. Silencing of p63 in keratinocytes instead, translates into a blunted flux of metabolites through both glycolysis and the Krebs cycle, likely due to a p63-dependent reduction of hexokinase 2 and citrate synthase gene expression. Our findings highlight the potential role of p63 in counteracting keratinocyte senescence also through fine regulation of metabolite levels and relevant biochemical pathways. We believe that our research might contribute significantly to the discovery of new implications of p63 in keratinocyte senescence and related diseases.
Ally or traitor: the dual role of p62 in caspase-2 regulation
Authors: Volik Pavel I. , Zamaraev Alexey V. , Egorshina Aleksandra Y. , Pervushin Nikolay V. , Kapusta Anastasia A. , Tyurin-Kuzmin Pyotr A. , Lipatova Anastasia V. , Kaehne Thilo , Lavrik Inna N. , Zhivotovsky Boris , Kopeina Gelina S. 
Published: November 2024

AbstractCaspase-2 is a unique and conserved cysteine protease that is involved in several cellular processes, including different forms of cell death, maintenance of genomic stability, and the response to reactive oxygen species. Despite advances in caspase-2 research in recent years, the mechanisms underlying its activation remain largely unclear. Although caspase-2 is activated in the PIDDosome complex, its processing could occur even in the absence of PIDD1 and/or RAIDD, suggesting the existence of an alternative platform for caspase-2 activation. Here, we show that caspase-2 undergoes ubiquitination and interacts with scaffolding protein p62/sequestosome-1 (SQSTM1) under normal conditions and in response to DNA damage. p62 promotes proteasomal but not autophagic caspase-2 degradation as well as its dimerization and activation that triggers the caspase cascade and, subsequently, cell death. Inhibition of p62 expression attenuates cisplatin-induced caspase-2 processing and apoptosis. Notably, the ZZ domain of p62 is critical for caspase-2 binding, whereas the UBA domain is seemingly required to stabilize the p62–caspase-2 complex. Thus, we have uncovered the dual role of p62 in regulating caspase-2 activity: it can foster the degradation of caspase-2 in the proteasome or facilitate its activation by acting as a scaffold platform.
Glial maturation factor-β deficiency prevents oestrogen deficiency-induced bone loss by remodelling the actin network to suppress adipogenesis of bone marrow mesenchymal stem cells
Authors: Xu Jun , Huang Zhongyue , Shi Si , Xia Jiangni , Chen Guangnan , Zhou Kaifeng , Zhang Yiming , Bian Chong , Shen Yuqin , Yin Xiaofan , Lu Lixia , Gu Huijie 
Published: November 2024

AbstractAn imbalance between the adipogenesis and osteogenesis of bone marrow mesenchymal stem cells (BMSCs) is considered the basic pathogenesis of osteoporosis. Although actin cytoskeleton remodelling plays a crucial role in the differentiation of BMSCs, the role of actin cytoskeleton remodelling in the adipogenesis of BMSCs and postmenopausal osteoporosis (PMOP) has remained elusive. Glia maturation factor-beta (GMFB) has a unique role in remodelling the polymerization/depolymerization cycles of actin. We observed that GMFB expression was increased in bone tissue from both ovariectomized (OVX) rats and PMOP patients. GMFB knockout inhibited the accumulation of bone marrow adipocytes and increased bone mass in the OVX rat model. The inhibition of adipocyte differentiation in GMFB knockout BMSCs was mediated via actin cytoskeleton remodelling and the Ca2+-calcineurin-NFATc2 axis. Furthermore, we found that GMFB shRNA treatment in vivo had favourable effects on osteoporosis induced by OVX. Together, these findings suggest a pathological association of the GMFB with PMOP and highlight the potential of the GMFB as a therapeutic target for osteoporosis patients.
Genetic basis of right and left ventricular heart shape
Authors: Burns Richard , Young William J. , Aung Nay , Lopes Luis R. , Elliott Perry M. , Syrris Petros , Barriales-Villa Roberto , Sohrabi Catrin , Petersen Steffen E. , Ramírez Julia , Young Alistair , Munroe Patricia B. 
Published: November 2024

AbstractHeart shape captures variation in cardiac structure beyond traditional phenotypes of mass and volume. Although observational studies have demonstrated associations with cardiometabolic risk factors and diseases, its genetic basis is less understood. We utilised cardiovascular magnetic resonance images from 45,683 UK Biobank participants to construct a heart shape atlas from bi-ventricular end-diastolic surface mesh models through principal component (PC) analysis. Genome-wide association studies were performed on the first 11 PCs that captured 83.6% of shape variance. We identified 43 significant loci, 14 were previously unreported for cardiac traits. Genetically predicted PCs were associated with cardiometabolic diseases. In particular two PCs (2 and 3) linked with more spherical ventricles being associated with increased risk of atrial fibrillation. Our study explores the genetic basis of multidimensional bi-ventricular heart shape using PCA, reporting new loci and biology, as well as polygenic risk scores for exploring genetic relationships of heart shape with cardiometabolic diseases.
Reintroduction of resistant frogs facilitates landscape-scale recovery in the presence of a lethal fungal disease
Authors: Knapp Roland A. , Wilber Mark Q. , Joseph Maxwell B. , Smith Thomas C. , Grasso Robert L. 
Published: November 2024

AbstractVast alteration of the biosphere by humans is causing a sixth mass extinction, driven in part by an increase in infectious diseases. The emergence of the lethal fungal pathogen Batrachochytrium dendrobatidis (Bd) has devastated global amphibian biodiversity. Given the lack of any broadly applicable methods to reverse these impacts, the future of many amphibians appears grim. The Sierra Nevada yellow-legged frog (Rana sierrae) is highly susceptible to Bd infection and most R. sierrae populations are extirpated following disease outbreaks. However, some populations persist and eventually recover, and frogs in these recovering populations have increased resistance against infection. Here, we conduct a 15-year reintroduction study and show that frogs collected from recovering populations and reintroduced to vacant habitats can reestablish populations despite the presence of Bd. In addition, the likelihood of establishment is influenced by site, cohort, and frog attributes. Results from viability modeling suggest that many reintroduced populations have a low probability of extinction over 50 years. These results provide a rare example of how reintroduction of resistant individuals can allow the landscape-scale recovery of disease-impacted species, and have broad implications for amphibians and other taxa that are threatened with extinction by novel pathogens.
DHX36 binding induces RNA structurome remodeling and regulates RNA abundance via m6A reader YTHDF1
Authors: Zhang Yuwei , Zhao Jieyu , Chen Xiaona , Qiao Yulong , Kang Jinjin , Guo Xiaofan , Yang Feng , Lyu Kaixin , Ding Yiliang , Zhao Yu , Sun Hao , Kwok Chun-Kit , Wang Huating 
Published: November 2024

AbstractRNA structure constitutes a new layer of gene regulatory mechanisms. RNA binding proteins can modulate RNA secondary structures, thus participating in post-transcriptional regulation. The DEAH-box helicase 36 (DHX36) is known to bind and unwind RNA G-quadruplex (rG4) structure but the transcriptome-wide RNA structure remodeling induced by DHX36 binding and the impact on RNA fate remain poorly understood. Here, we investigate the RNA structurome alteration induced by DHX36 depletion. Our findings reveal that DHX36 binding induces structural remodeling not only at the localized binding sites but also on the entire mRNA transcript most pronounced in 3’UTR regions. DHX36 binding increases structural accessibility at 3’UTRs which is correlated with decreased post-transcriptional mRNA abundance. Further analyses and experiments uncover that DHX36 binding sites are enriched for N6-methyladenosine (m6A) modification and YTHDF1 binding; and DHX36 induced structural changes may facilitate YTHDF1 binding to m6A sites leading to RNA degradation. Altogether, our findings uncover the structural remodeling effect of DHX36 binding and its impact on RNA abundance through regulating m6A dependent YTHDF1 binding.
Face cells encode object parts more than facial configuration of illusory faces
Authors: Sharma Saloni , Vinken Kasper , Jagadeesh Akshay V. , Livingstone Margaret S. 
Published: November 2024

AbstractHumans perceive illusory faces in everyday objects with a face-like configuration, an illusion known as face pareidolia. Face-selective regions in humans and monkeys, believed to underlie face perception, have been shown to respond to face pareidolia images. Here, we investigated whether pareidolia selectivity in macaque inferotemporal cortex is explained by the face-like configuration that drives the human perception of illusory faces. We found that face cells responded selectively to pareidolia images. This selectivity did not correlate with human faceness ratings and did not require the face-like configuration. Instead, it was driven primarily by the “eye” parts of the illusory face, which are simply object parts when viewed in isolation. In contrast, human perceptual pareidolia relied primarily on the global configuration and could not be explained by “eye” parts. Our results indicate that face-cells encode local, generic features of illusory faces, in misalignment with human visual perception, which requires holistic information.
Predicting rainfall using machine learning, deep learning, and time series models across an altitudinal gradient in the North-Western Himalayas
Authors: Wani Owais Ali , Mahdi Syed Sheraz , Yeasin Md. , Kumar Shamal Shasang , Gagnon Alexandre S. , Danish Faizan , Al-Ansari Nadhir , El‑Hendawy Salah , Mattar Mohamed A. 
Published: November 2024

AbstractPredicting rainfall is a challenging and critical task due to its significant impact on society. Timely and accurate predictions are essential for minimizing human and financial losses. The dependence of approximately 60% of agricultural land in India on monsoon rainfall implies the crucial nature of accurate rainfall prediction. Precise rainfall forecasts can facilitate early preparedness for disasters associated with heavy rains, enabling the public and government to take necessary precautions. In the North-Western Himalayas, where meteorological data are limited, the need for improved accuracy in traditional modeling methods for rainfall forecasting is pressing. To address this, our study proposes the application of advanced machine learning (ML) algorithms, including random forest (RF), support vector regression (SVR), artificial neural network (ANN), and k-nearest neighbour (KNN) along with various deep learning (DL) algorithms such as long short-term memory (LSTM), bi-directional LSTM, deep LSTM, gated recurrent unit (GRU), and simple recurrent neural network (RNN). These advanced techniques hold the potential to significantly improve the accuracy of rainfall prediction, offering hope for more reliable forecasts. Additionally, time series techniques, including autoregressive integrated moving average (ARIMA) and trigonometric, Box-Cox transform, arma errors, trend, and seasonal components (TBATS), are proposed for predicting rainfall across the altitudinal gradients of India’s North-Western Himalayas. This approach can potentially revolutionise how we approach rainfall forecasting, ushering in a new era of accuracy and reliability. The effectiveness and accuracy of the proposed algorithms were assessed using meteorological data obtained from six weather stations at different elevations spanning from 1980 to 2021. The results indicate that DL methods exhibit the highest accuracy in predicting rainfall, as measured by the root mean squared error (RMSE) and mean absolute error (MAE), followed by ML algorithms and time series techniques. Among the DL algorithms, the accuracy order was bi-directional LSTM, LSTM, RNN, deep LSTM, and GRU. For the ML algorithms, the accuracy order was ANN, KNN, SVR, and RF. These findings suggest that altitude significantly affects the accuracy of the models, highlighting the need for additional weather stations in this mountainous region to enhance the precision of rainfall prediction.