bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epistemic ownership and the practical/epistemic parallelism
Authors: Navarro Jesús 
Published: May 2024

AbstractWe may succed in the fulfilment of our desires but still fail to properly own our practical life, perhaps because we acted as addicts, driven by desires that are alien to our will, or as “wantons,” satisfying the desires that we simply happen to have (Frankfurt, 1988). May we equally fail to own the outcomes of our epistemic life? If so, how may we attain epistemic ownership over it? This paper explores the structural parallellism between practical and epistemic rationality, building on Williamson’s (2002) suggestion that we should commence with successful performances as the foundation for both domains, be it action or knowledge. By highlighting the limitations of higher-order regulative approaches in epistemology, exemplified by Sosa (2007, 2011, 2015, 2021), the paper introduces a form of teleological epistemic constitutivism inspired by Velleman (2000, 2009). The proposal is that epistemic ownership is not attained in the mere pursuit of truth or knowledge, but requires furthermore a struggle to understand what we know.
Microwave-Assisted Hydrothermal Synthesis of Zinc-tin Based Nanoflower for the Adsorptive Removal of Cadmium from Synthetic Wastewater
Authors: Toprak Münevver , Yıldız Barış , Zaman Buse Tuğba , Bozyiğit Gamze Dalgıç , Temuge İlknur Durukan , Çetin Gülten , Bakırdere Sezgin 
Published: May 2024

AbstractThe present study utilized zinc-tin nanoflowers (ZT-NFs) in a batch adsorption treatment process to effectively remove cadmium from synthetic wastewater. The batch adsorption strategy was optimized using the univariate approach to enhance the efficiency of the adsorption process. The dominant parameters examined in the optimization experiments were pH/volume of buffer solution, nanoflower amount, and sample agitation type/period. After determining the optimal batch adsorption conditions, equilibrium studies were performed by adding cadmium to synthetic wastewater at concentrations in the range of 1.0 – 40 mg/L. The quantification accuracy for cadmium was improved by developing the calibration plot with spiked sample matrix. The equilibrium data were subjected to mathematical modelling utilizing the Langmuir adsorption isotherm model. The calculated isotherm constants indicated a well-fitted isotherm model to the experimental data. The reported ZT-NFs-based adsorptive removal strategy was effectively employed to remove cadmium from synthetic wastewater.
Evolving Improved Sampling Protocols for Dose–Response Modelling Using Genetic Algorithms with a Profile-Likelihood Metric
Authors: Lam Nicholas N. , Murray Rua , Docherty Paul D. 
Published: May 2024

AbstractPractical limitations of quality and quantity of data can limit the precision of parameter identification in mathematical models. Model-based experimental design approaches have been developed to minimise parameter uncertainty, but the majority of these approaches have relied on first-order approximations of model sensitivity at a local point in parameter space. Practical identifiability approaches such as profile-likelihood have shown potential for quantifying parameter uncertainty beyond linear approximations. This research presents a genetic algorithm approach to optimise sample timing across various parameterisations of a demonstrative PK-PD model with the goal of aiding experimental design. The optimisation relies on a chosen metric of parameter uncertainty that is based on the profile-likelihood method. Additionally, the approach considers cases where multiple parameter scenarios may require simultaneous optimisation. The genetic algorithm approach was able to locate near-optimal sampling protocols for a wide range of sample number (n = 3–20), and it reduced the parameter variance metric by 33–37% on average. The profile-likelihood metric also correlated well with an existing Monte Carlo-based metric (with a worst-case r > 0.89), while reducing computational cost by an order of magnitude. The combination of the new profile-likelihood metric and the genetic algorithm demonstrate the feasibility of considering the nonlinear nature of models in optimal experimental design at a reasonable computational cost. The outputs of such a process could allow for experimenters to either improve parameter certainty given a fixed number of samples, or reduce sample quantity while retaining the same level of parameter certainty.
Evaluation of augmented reality training for a navigation device used for CT-guided needle placement
Authors: Stauffer T. , Lohmeyer Q. , Melamed S. , Uhde A. , Hostettler R. , Wetzel S. , Meboldt M. 
Published: May 2024

Abstract
Purpose
Numerous navigation devices for percutaneous, CT-guided interventions exist and are, due to their advantages, increasingly integrated into the clinical workflow. However, effective training methods to ensure safe usage are still lacking. This study compares the potential of an augmented reality (AR) training application with conventional instructions for the Cube Navigation System (CNS), hypothesizing enhanced training with AR, leading to safer clinical usage.

Methods
An AR-tablet app was developed to train users puncturing with CNS. In a study, 34 medical students were divided into two groups: One trained with the AR-app, while the other used conventional instructions. After training, each participant executed 6 punctures on a phantom (204 in total) following a standardized protocol to identify and measure two potential CNS procedural user errors: (1) missing the coordinates specified and (2) altering the needle trajectory during puncture. Training performance based on train time and occurrence of procedural errors, as well as scores of User Experience Questionnaire (UEQ) for both groups, was compared.

Results
Training duration was similar between the groups. However, the AR-trained participants showed a 55.1% reduced frequency of the first procedural error (p > 0.05) and a 35.1% reduced extent of the second procedural error (p < 0.01) compared to the conventionally trained participants. UEQ scores favored the AR-training in five of six categories (p < 0.05).

Conclusion
The AR-app enhanced training performance and user experience over traditional methods. This suggests the potential of AR-training for navigation devices like the CNS, potentially increasing their safety, ultimately improving outcomes in percutaneous needle placements.
Enhancing surgical instrument segmentation: integrating vision transformer insights with adapter
Authors: Wei Meng , Shi Miaojing , Vercauteren Tom 
Published: May 2024

Abstract
Purpose
In surgical image segmentation, a major challenge is the extensive time and resources required to gather large-scale annotated datasets. Given the scarcity of annotated data in this field, our work aims to develop a model that achieves competitive performance with training on limited datasets, while also enhancing model robustness in various surgical scenarios.

Methods
We propose a method that harnesses the strengths of pre-trained Vision Transformers (ViTs) and data efficiency of convolutional neural networks (CNNs). Specifically, we demonstrate how a CNN segmentation model can be used as a lightweight adapter for a frozen ViT feature encoder. Our novel feature adapter uses cross-attention modules that merge the multiscale features derived from the CNN encoder with feature embeddings from ViT, ensuring integration of the global insights from ViT along with local information from CNN.

Results
Extensive experiments demonstrate our method outperforms current models in surgical instrument segmentation. Specifically, it achieves superior performance in binary segmentation on the Robust-MIS 2019 dataset, as well as in multiclass segmentation tasks on the EndoVis 2017 and EndoVis 2018 datasets. It also showcases remarkable robustness through cross-dataset validation across these 3 datasets, along with the CholecSeg8k and AutoLaparo datasets. Ablation studies based on the datasets prove the efficacy of our novel adapter module.

Conclusion
In this study, we presented a novel approach integrating ViT and CNN. Our unique feature adapter successfully combines the global insights of ViT with the local, multi-scale spatial capabilities of CNN. This integration effectively overcomes data limitations in surgical instrument segmentation. The source code is available at: https://github.com/weimengmeng1999/AdapterSIS.git.
XTP8 Promotes Ovarian Cancer Progression by Activating AKT/AMPK/mTOR Pathway to Regulate EMT
Authors: Zhao Ruixue , Ning Xin , Lu Hongping , Xu Wei , Ma Jiaxin , Cheng Jun , Ma Rong 
Published: May 2024

AbstractOvarian cancer (OC) ranks as the fifth leading cause of cancer-related death in women. The main contributors to the poor prognosis of ovarian cancer are the high rates of recurrence and metastasis. Studies have indicated a crucial role for hepatitis B virus X Ag-Transactivated Protein 8 (XTP8), a protein containing the DEP domain, in various cellular processes, including cell growth, movement, and differentiation, across several types of cancers. However, the role of XTP8 in ovarian cancer remains unclear. We observed elevated expression of XTP8 in ovarian cancer. Silencing XTP8 inhibited cell proliferation, promoted apoptosis, and yielded contrasting results in cells overexpressing XTP8. Furthermore, XTP8 facilitated ovarian cancer invasion and migration, triggering epithelial-mesenchymal transition (EMT). Mechanistically, XTP8 silencing led to reduced phosphorylation levels of AKT, increased p-AMPK levels, and decreased p-mTOR levels, while XTP8 overexpression exerted the opposite effects. Additionally, the activation of p-AMPK rescued the promoting effect of XTP8 on EMT in ovarian cancer cell lines, indicating that XTP8 acts as an oncogene by modulating the AKT/AMPK/mTOR pathway. Through transcriptome sequencing to identify downstream targets of XTP8, we found that XTP8 influences the expression of Caldesmon (CALD1) at both transcriptional and translational levels. CALD1 can be considered a downstream target of XTP8. The collaborative action of XTP8 and CALD1 activates the AKT/AMPK/mTOR pathway, regulating EMT to promote ovarian cancer progression. Inhibiting this signaling axis might represent a potential therapeutic target for ovarian cancer.
Landfill cap models under simulated climate change precipitation: assessing long-term infiltration using the HELP model
Authors: Sinnathamby G. , Phillips D. H. , Paksy A. , Halim M. 
Published: May 2024

AbstractThe Hydrologic Evaluation of Landfill Performance (HELP) model (v 3.04) was used to assess the hydrological performance of two large-scale (~ 80 × 80 × 90 cm) laboratory-based landfill cap models. Desiccation cracking under simulated climate change precipitation (CCP) events was modelled to predict the performance of landfill caps over a 50-year period in Cumbria England, UK. Cumulative infiltration values under different climate conditions were highly sensitive to macro-pore development in the clay liner which is represented by the changing hydraulic conductivity in HELP simulations. Simulation results of cap design 1 (a clay barrier layer only) show that cumulative annual infiltration under normal precipitation (NP) and CCP events, with the initial hydraulic conductivity, ranged between 1 and 2% of the annual precipitation; however, cumulative annual infiltration was 10 to 68% when maximum (degraded) hydraulic conductivity values were used in simulations. A geosynthetic clay liner (GCL) included in cap design 2 significantly reduce cumulative infiltration.
TA-YOLO: a lightweight small object detection model based on multi-dimensional trans-attention module for remote sensing images
Authors: Li Minze , Chen Yuling , Zhang Tao , Huang Wu 
Published: May 2024

AbstractObject detection plays a vital role in remote sensing applications. Although object detection has achieved proud results in natural images, these methods are difficult to be directly applied to remote sensing images. Remote sensing images often have complex backgrounds and small objects, which results in a highly unbalanced distribution of foreground and complex background information. In order to solve the above problems, this paper proposes a multi-head channel and spatial trans-attention (MCSTA) module, which performs remote pixel interaction from the channel and spatial dimensions respectively to complete the attention feature capture function. It is a plug-and-play module that can be easily embedded in any other natural image object detection convolutional neural network, making it quickly applicable to remote sensing images. First, in order to reduce computational complexity and improve feature richness, we use a special linear convolution to obtain three projection features instead of the simple matrix multiplication transformation in Transformer. Second, we obtain trans-attention maps in different dimensions in a manner similar to the self-attention mechanism to capture the interrelationships of features in channels and spaces. In this process, we use a multi-head mechanism to perform parallel operations to improve speed. Furthermore, in order to avoid large-scale matrix operations, we specially designed an attention blocking mode to reduce computer memory usage and increase operation speed. Finally, we embedded the trans-attention module into YOLOv8, added a new detection head and optimized the feature fusion method, thus designing a lightweight small object detection model named TA-YOLO for remote sensing images. It has fewer parameters than the benchmark model YOLOv8, and its mAP on the PASCAL VOC and VisDrone data sets increased by 1.3% and 6.2% respectively. The experimental results prove the powerful function of the trans-attention module and the excellent performance of TA-YOLO.
Urine polymerase chain reaction tests: stewardship helper or hinderance?
Authors: Zering Jessica , Stohs Erica J. 
Published: May 2024

Abstract
Urine polymerase chain reaction is a laboratory test promoted to healthcare professionals working in long-term care facilities as a rapid diagnostic platform for urinary tract infection. Little is known about the place of this testing and its potential impact on antimicrobial stewardship programs. In this commentary, we review the currently available literature and provide recommendations for long-term care stewardship programs to consider.
On invariant holonomies between centers
Authors: SAGHIN RADU 
Published: May 2024

AbstractWe prove that for
$C^{1+\theta }$
,
$\theta $
-bunched, dynamically coherent partially hyperbolic diffeomorphisms, the stable and unstable holonomies between center leaves are
$C^1$
, and the derivative depends continuously on the points and on the map. Also for
$C^{1+\theta }$
,
$\theta $
-bunched partially hyperbolic diffeomorphisms, the derivative cocycle restricted to the center bundle has invariant continuous holonomies which depend continuously on the map. This generalizes previous results by Pugh, Shub, and Wilkinson; Burns and Wilkinson; Brown; Obata; Avila, Santamaria, and Viana; and Marin.
Weighted topological pressure revisited
Authors: ALIBABAEI NIMA 
Published: May 2024

Abstract
Feng and Huang [Variational principle for weighted topological pressure. J. Math. Pures Appl. (9)106 (2016), 411–452] introduced weighted topological entropy and pressure for factor maps between dynamical systems and established its variational principle. Tsukamoto [New approach to weighted topological entropy and pressure. Ergod. Th. & Dynam. Sys.43 (2023), 1004–1034] redefined those invariants quite differently for the simplest case and showed via the variational principle that the two definitions coincide. We generalize Tsukamoto’s approach, redefine the weighted topological entropy and pressure for higher dimensions, and prove the variational principle. Our result allows for an elementary calculation of the Hausdorff dimension of affine-invariant sets such as self-affine sponges and certain sofic sets that reside in Euclidean space of arbitrary dimension.
Gut protozoa of wild rodents – a meta-analysis
Authors: Hunter-Barnett Simon , Viney Mark 
Published: May 2024

AbstractProtozoa are well-known inhabitants of the mammalian gut and so of the gut microbiome. While there has been extensive study of a number of species of gut protozoa in laboratory animals, particularly rodents, the biology of the gut protozoa of wild rodents is much less well-known. Here we have systematically searched the published literature to describe the gut protozoa of wild rodents, in total finding records of 44 genera of protozoa infecting 228 rodent host species. We then undertook meta-analyses that estimated the overall prevalence of gut protozoa in wild rodents to be 24%, with significant variation in prevalence among some host species. We investigated how host traits may affect protozoa prevalence, finding that for some host lifestyles some protozoa differed in their prevalence. This synthesis of existing data on wild rodent gut protozoa provides a better understanding of the biology of these common gut inhabitants and suggests directions for their future study.
Non-invertible planar self-affine sets
Authors: KÄENMÄKI ANTTI , NISSINEN PETTERI 
Published: May 2024

AbstractWe compare the dimension of a non-invertible self-affine set to the dimension of the respective invertible self-affine set. In particular, for generic planar self-affine sets, we show that the dimensions coincide when they are large and differ when they are small. Our study relies on thermodynamic formalism where, for dominated and irreducible matrices, we completely characterise the behaviour of the pressures.
Endothall and 2,4-D activity in milfoil hybrid (Myriophyllum spicatum × M. sibiricum) when applied alone and in combination
Authors: Ortiz Mirella F. , Nissen Scott J. , Dayan Franck E. 
Published: May 2024

AbstractEurasian watermilfoil (Myriophyllum spicatum L.) is an invasive aquatic plant that can hybridize with the native northern watermilfoil (M. sibiricum Kom.). These milfoil hybrids (M. spicatum × M. sibiricum) are becoming more prevalent in many lakes where the invasive and the native milfoil co-occur. Hybrid plants are more vigorous than either parent with a faster growth rate and lower sensitivity to some herbicides. The aquatic herbicides endothall and 2,4-D provide two effective modes of action for management of the hybrids. For more than a decade, these two herbicides have been used in combination as an effective control option and a resistance management strategy. How this combination impacts herbicide movement and efficacy is unknown. Therefore, the objective of this research was to determine the activity of endothall and 2,4-D combined compared with activity applied alone. Absorption and translocation of endothall, 2,4-D, and the combination was determined in hybrid plants over a 96-h time course. Endothall accumulation was not impacted when these herbicides were applied in combination; however, 2,4-D accumulation increased by 80%, relative to when 2,4-D was applied alone. Endothall translocation from shoots to roots decreased by almost 50% when applied in combination with 2,4-D (alone = 16.7% ± 2.6%; combination = 9.2% ± 1.2%). Shoot-to-root translocation of 2,4-D also decreased when the two herbicides were applied in combination (24.8% ± 2.6% when applied alone to only 3.93% ± 0.4% when in the presence of endothall). This research demonstrates that combining herbicides can significantly impact herbicide activity in plants. Future research is needed to determine whether this reduced translocation negatively impacts operational effectiveness when these herbicides are applied in combination.
Resistance patterns and molecular basis to ACCase-inhibiting herbicides
Authors: Yang Qian , Deng Wei , Liu Longwei , Wei Tian , Yang Xia , Zhu Jinlei , Lv Min , Li Yongfeng 
Published: May 2024

AbstractDigitaria ciliaris var. chrysoblephara (Fig. & De Not.) R.R. Stewart is an annual xeromorphic weed that severely infests direct-seeded rice fields in China. Herbicide resistance is emerging in D. ciliaris var. chrysoblephara owing to extensive and recurrent use of the acetyl-CoA carboxylase (ACCase)-inhibiting herbicide metamifop. In this study, a total of 53 D. ciliaris var. chrysoblephara populations randomly sampled from direct-seeded rice fields across Jiangsu Province were investigated for metamifop resistance and potential resistance-endowing mutations. Single-dose assays revealed that 17 (32.1%) populations evolved resistance to metamifop and 5 (9.4%) populations were in the process of developing resistance. The resistance index (RI) of metamifop-resistant populations ranged from 2.7 to 32.1. Amino acid substitutions (Ile-1781-Leu, Trp-2027-Cys/Ser, and Ile-2041-Asn) in ACCase genes were detected in resistant D. ciliaris var. chrysoblephara plants and caused various cross-resistance patterns to ACCase-inhibiting herbicides. All of four resistant populations (YC07, YZ09, SQ03, and HA06), with different ACCase mutations, exhibited cross-resistance to the aryloxyphenoxypropionate (APP) herbicides cyhalofop-butyl (RI values: 10.0 to 19.9), fenoxaprop-P-ethyl (RI values: 53.7 to 132.8), and haloxyfop-P-methyl (RI values: 6.2 to 62.6), and the phenylpyrazoline (DEN) pinoxaden (RI values: 2.3 to 5.4), but responded differently to the cyclohexanedione (CHD) herbicides clethodim and sethoxydim. It is noteworthy that four postemergence herbicides used for rice cropping, including bispyribac-sodium, pyraclonil, quinclorac, and anilofos, showed poor control effect against D. ciliaris var. chrysoblephara, suggesting few alternations for managing this weed in rice fields except ACCase inhibitors. In conclusion, this work demonstrated that the D. ciliaris var. chrysoblephara had developed resistance to ACCase-inhibiting herbicides in rice cultivation of China, and target-site amino acid substitutions in ACCase were primarily responsible for metamifop resistance.
Nitric Oxide Concentration: A New Data Set Derived From SABER Measurements
Authors: Wang Ningchao , Mlynczak Martin G. , Emmert John T. , López‐Puertas Manuel , Funke Bernd 
Published: May 2024

AbstractVertical profiles of nitric oxide (NO) concentration are derived between 120 and 250 km using updated NO emission rates measured by Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on the NASA Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite. The Naval Research Laboratory Mass Spectrometer Incoherent Scatter Radar (MSIS) 2.1 model is used to provide the required parameters of temperature, atomic oxygen number density, and molecule oxygen number density needed to derive the NO concentrations using a non‐local thermodynamic equilibrium (non‐LTE) model. The SABER NO concentration shows a significant correlation with solar activity with larger peak NO concentrations and higher altitude extent during solar maximum years compared to those during the solar minimum years. The SABER NO agrees well with the MSIS 2.1 NO at altitudes above 120 km for all latitudes, while the pronounced SABER‐MSIS NO discrepancy below 120 km is likely due to the temperature underestimation by MSIS 2.1. A detailed error analysis is presented and considers systematic and random errors in all the terms in the non‐LTE model used to derive the NO concentration. Random error in MSIS 2.1 temperature and atomic oxygen dominates the uncertainty in single NO profiles above 120 km. We estimated a systematic error up to ∼36% between 120 and 250 km during solar maximum years.