bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improved oxidation behavior of Hf0.11Al0.20B0.69 in comparison to Hf0.28B0.72 magnetron sputtered thin films
Authors: Kümmerl Pauline , Lellig Sebastian , Navidi Kashani Amir Hossein , Hans Marcus , Pöllmann Peter J. , Löfler Lukas , Nayak Ganesh Kumar , Holzapfel Damian M. , Kolozsvári Szilárd , Polcik Peter , Schweizer Peter , Primetzhofer Daniel , Michler Johann , Schneider Jochen M. 
Published: September 2024

AbstractThe oxidation resistance of Hf0.28B0.72 and Hf0.11Al0.20B0.69 thin films was investigated comparatively at 700 °C for up to 8 h. Single-phase solid solution thin films were co-sputtered from HfB2 and AlB2 compound targets. After oxidation at 700 °C for 8 h an oxide scale thickness of 31 $$\pm$$
±
2 nm was formed on Hf0.11Al0.20B0.69 which corresponds to 14% of the scale thickness measured on Hf0.28B0.72. The improved oxidation resistance can be rationalized based on the chemical composition and the morphology of the formed oxide scales. On Hf0.28B0.72 the formation of a porous, O, Hf, and B-containing scale and the formation of crystalline HfO2 is observed. Whereas on Hf0.11Al0.20B0.69 a dense, primarily amorphous scale containing O, Al, B as well as approximately 3 at% of Hf forms, which reduces the oxidation kinetics significantly by passivation. Benchmarking Hf0.11Al0.20B0.69 with Ti–Al-based boride and nitride thin films with similar Al concentrations reveals superior oxidation behavior of the Hf-Al-based thin film. The incorporation of few at% of Hf in the oxide scale decelerates oxidation kinetics at 700 °C and leads to a reduction in oxide scale thickness of 21% and 47% compared to Ti0.12Al0.21B0.67 and Ti0.27Al0.21N0.52, respectively. Contrary to Ti–Al-based diborides, Hf0.11Al0.20B0.69 shows excellent oxidation behavior despite B-richness.
Exosomal fragment enclosed polyamine-salt nano-complex for co-delivery of docetaxel and mir-34a exhibits higher cytotoxicity and apoptosis in breast cancer cells
Authors: Basak Moumita , Kulkarni Mrunal , Narisepalli Saibhargav , Chitkara Deepak , Mittal Anupama 
Published: September 2024

AbstractA novel core–shell nanocarrier system has been designed for co-delivery of a small anticancer drug, docetaxel (DTX) and tumor suppressor (TS) miR-34a named as Exo(PAN34a+DTX). The core is formed by pH dependent polyamine salt aggregates (PSA) containing both the payloads and the shell is formed by RAW 264.7 cell derived exosomal fragments. Herein, phosphate driven polyallylamine hydrochloride (PAH, MW:17,500 Da) PSA was formed in presence of miR-34a and DTX to form PAN34a+DTX. The formulation exhibited pH dependent DTX release with only 33.55 ± 2.12% DTX release at pH 7.2 and 75.21 ± 1.8% DTX release till 144 h at pH 5.5. At 1.21 molar ratio of phosphate to the amine (known as R value), efficient complexation of miR-34a (3.6 μM) in the PAN particles was obtained. PAN34a+DTX demonstrated particle size (163.86 ± 12.89 nm) and zeta-potential value of 17.53 ± 5.10 mV which upon exosomal fragment layering changed to − 7.23 ± 2.75 mV which is similar to the zeta-potential of the exosomal fragments, i.e., − 8.40 ± 1.79 mV. The final formulation Exo(PAN34a+DTX), loaded with 40 ng/mL DTX and 50 nM miR-34a exhibited 48.20 ± 4.59% cytotoxicity in triple negative breast cancer (TNBC) cells, 4T1. Co-localization of CM-DiI (red fluorescence) stained exosomal fragments and FAM-siRNA (green fluorescence) in the cytoplasm of 4T1 cells after 6 h of Exo(PANFAM) treatment confirmed the efficiency of the designed system to co-deliver two actives. Exo(PAN34a+DTX) also reduced BCL-2 expression (target gene for miR-34a) by 8.98 folds in comparison to free DTX confirming promising co-delivery and apoptosis inducing effect of Exo(PAN34a+DTX) in 4T1.
Predator exposure early in life shapes behavioral development and individual variation in a clonal fish
Authors: Scherer U. , Laskowski K. L. , Kressler M. M. , Ehlman S. M. , Wolf M. , Bierbach D. 
Published: September 2024

AbstractPredation risk is one of the most important factors generating behavioral differences among populations. In addition, recent attention focusses on predation as a potential driver of patterns of individual behavioral variation within prey populations. Previous studies provide mixed results, reporting either increased or decreased among-individual variation in response to risk. Here, we take an explicit developmental approach to documenting how among-individual variation develops over time in response to predator exposure, controlling for both genetic and experiential differences among individuals. We reared juveniles of naturally clonal Amazon mollies, Poecilia formosa, either with or without a predator visible during feedings over 4 weeks and analyzed activity during feedings, time spent feeding and number of visits to the feeding spot. (I) Predator-exposed fish did not differ from control fish in average feeding behavior, but they were less active during feeding trials. (II) In the absence of the predator, substantial changes in among-individual variation over time were detected: among-individual differences in feeding duration increased whereas differences in activity decreased, but there were no changes in feeder visits. In contrast, in the presence of a predator, among-individual variation in all three behaviors was stable over time and often lower compared to control conditions. Our work suggests that predation risk may have an overall stabilizing effect on the development of individual variation and that differences in predation risk may well lead to population-wide differences in among-individual behavioral variation.
Screening of the Pandemic Response Box library identified promising compound candidate drug combinations against extensively drug-resistant Acinetobacter baumannii
Authors: Boonyalai Nonlawat , Peerapongpaisarn Dutsadee , Thamnurak Chatchadaporn , Oransathid Wilawan , Wongpatcharamongkol Nantanat , Oransathid Wirote , Lurchachaiwong Woradee , Griesenbeck John S. , Waters Norman C. , Demons Samandra T. , Ruamsap Nattaya , Vesely Brian A. 
Published: September 2024

AbstractInfections caused by antimicrobial-resistant Acinetobacter baumannii pose a significant threat to human health, particularly in the context of hospital-acquired infections. As existing antibiotics lose efficacy against Acinetobacter isolates, there is an urgent need for the development of novel antimicrobial agents. In this study, we assessed 400 structurally diverse compounds from the Medicines for Malaria Pandemic Response Box for their activity against two clinical isolates of A. baumannii: A. baumannii 5075, known for its extensive drug resistance, and A. baumannii QS17-1084, obtained from an infected wound in a Thai patient. Among the compounds tested, seven from the Pathogen box exhibited inhibitory effects on the in vitro growth of A. baumannii isolates, with IC50s ≤ 48 µM for A. baumannii QS17-1084 and IC50s ≤ 17 µM for A. baumannii 5075. Notably, two of these compounds, MUT056399 and MMV1580854, shared chemical scaffolds resembling triclosan. Further investigations involving drug combinations identified five synergistic drug combinations, suggesting potential avenues for therapeutic development. The combination of MUT056399 and brilacidin against A. baumannii QS17-1084 and that of MUT056399 and eravacycline against A. baumannii 5075 showed bactericidal activity. These combinations significantly inhibited biofilm formation produced by both A. baumannii strains. Our findings highlight the drug combinations as promising candidates for further evaluation in murine wound infection models against multidrug-resistant A. baumannii. These compounds hold potential for addressing the critical need for effective antibiotics in the face of rising antimicrobial resistance.
Rice yield prediction through integration of biophysical parameters with SAR and optical remote sensing data using machine learning models
Authors: Sah Sonam , Haldar Dipanwita , Singh RN , Das B. , Nain Ajeet Singh 
Published: September 2024

AbstractIn an era marked by growing global population and climate variability, ensuring food security has become a paramount concern. Rice, being a staple crop for billions of people, requires accurate and timely yield prediction to ensure global food security. This study was undertaken across two rice crop seasons in the Udham Singh Nagar district of Uttarakhand state to predict rice yield at 45, 60 and 90 days after transplanting (DAT) through machine learning (ML) models, utilizing a combination of optical and Synthetic Aperture Radar (SAR) data in conjunction with crop biophysical parameters. Results revealed that the ML models were able to provide relatively accurate early yield estimates. For summer rice, eXtreme gradient boosting (XGB) was the best-performing model at all three stages (45, 60, and 90 DAT), while for kharif rice, the best-performing models at 45, 60, and 90 DAT were XGB, Neural network (NNET), and Cubist, respectively. The combined ranking of ML models showed that prediction accuracy improved as the prediction date approaches harvest, and the best prediction of yield was observed at 90 DAT for both summer and kharif rice. Overall rankings indicate that for summer rice, the top three models were XGB, NNET, and Support vector regression, while for kharif rice, these were Cubist, NNET, and Random Forest, respectively. The findings of this study offer valuable insights into the potential of the combined use of remote sensing and biophysical parameters using ML models, which enhances food security planning and resource management by enabling more informed decision-making by stakeholders such as farmers, policy planners as well as researchers.
An intranasal cationic liposomal polysaccharide vaccine elicits humoral immune responses against Streptococcus pneumoniae
Authors: Wei Peng , Romanò Cecilia , Li Chengxin , Clergeaud Gael , Andresen Thomas L. , Henriksen Jonas R. , Hansen Anders E. , Clausen Mads H. 
Published: September 2024

AbstractDiseases caused by S. pneumoniae are the leading cause of child mortality. As antibiotic resistance of S. pneumoniae is rising, vaccination remains the most recommended solution. However, the existing pneumococcal polysaccharides vaccine (Pneumovax® 23) proved only to induce T-independent immunity, and strict cold chain dependence of the protein conjugate vaccine impedes its promotion in developing countries, where infections are most problematic. Affordable and efficient vaccines against pneumococcus are therefore in high demand. Here, we present an intranasal vaccine Lipo+CPS12F&αGC, containing the capsular polysaccharides of S. pneumoniae 12F and the iNKT agonist α-galactosylceramide in cationic liposomes. In BALB/cJRj mice, the vaccine effectively activates iNKT cells and promotes B cells maturation, stimulates affinity-matured IgA and IgG production in both the respiratory tract and systemic blood, and displays sufficient protection both in vivo and in vitro. The designed vaccine is a promising, cost-effective solution against pneumococcus, which can be expanded to cover more serotypes and pathogens.
Direct visualization of viscous dissipation and wetting ridge geometry on lubricant-infused surfaces
Authors: Naga Abhinav , Rennick Michael , Hauer Lukas , Wong William S. Y. , Sharifi-Aghili Azadeh , Vollmer Doris , Kusumaatmaja Halim 
Published: September 2024

AbstractDrops are exceptionally mobile on lubricant-infused surfaces, yet they exhibit fundamentally different dynamics than on traditional superhydrophobic surfaces due to the formation of a wetting ridge around the drop. Despite the importance of the wetting ridge in controlling drop motion, it is unclear how it dissipates energy and changes shape during motion. Here, we use lattice Boltzmann simulations and confocal microscopy to image how the wetting ridge evolves with speed, and construct heatmaps to visualize where energy is dissipated on flat and rough lubricated surfaces. As speed increases, the wetting ridge height decreases according to a power law, and an asymmetry develops between the front and rear sides. Most of the dissipation in the lubricant ( >75%) occurs directly in front and behind the drop. The geometry of the underlying solid surface hardly affects the dissipation mechanism, implying that future designs should focus on optimizing the surface geometry to maximize lubricant retention.
Non-invasive in vivo imaging of changes in Collagen III turnover in myocardial fibrosis
Authors: Chaher Nadia , Lacerda Sara , Digilio Giuseppe , Padovan Sergio , Gao Ling , Lavin Begoña , Stefania Rachele , Velasco Carlos , Cruz Gastão , Prieto Claudia , Botnar René M. , Phinikaridou Alkystis 
Published: September 2024

AbstractHeart failure (HF) affects 64 million people globally with enormous societal and healthcare costs. Myocardial fibrosis, characterised by changes in collagen content drives HF. Despite evidence that collagen type III (COL3) content changes during myocardial fibrosis, in vivo imaging of COL3 has not been achieved. Here, we discovered the first imaging probe that binds to COL3 with high affinity and specificity, by screening candidate peptide-based probes. Characterisation of the probe showed favourable magnetic and biodistribution properties. The probe’s potential for in vivo molecular cardiac magnetic resonance imaging was evaluated in a murine model of myocardial infarction. Using the new probe, we were able to map and quantify, previously undetectable, spatiotemporal changes in COL3 after myocardial infarction and monitor response to treatment. This innovative probe provides a promising tool to non-invasively study the unexplored roles of COL3 in cardiac fibrosis and other cardiovascular conditions marked by changes in COL3.
Feasibility and sustainability of emerging CCU pathways for formic acid production
Authors: Atsbha Tesfalem Aregawi , Yoon Ha-Jun , Cherif Ali , Lee Chul-Jin 
Published: September 2024

The thermo-catalytic pathway can be a competitive alternative to the conventional pathway. CO2 source and electricity source highly affected the GWI for the thermo-catalytic pathway and electrochemical reduction pathway respectively.
Measuring the Effects of Cognitive Capacity on Sentence Comprehension: Evidence From Elementary School-Age Children
Authors: Magimairaj Beula M. , Nagaraj Naveen K. , Gillam Ronald B. 
Published: September 2024

Purpose:
Our aim was to (a) develop a sentence comprehension measure that distinguished between cognitive capacity and syntactic knowledge in school-age children and (b) examine the relationship between comprehension performance and cognitive variables (working memory capacity and retrieval from long-term memory).

Method:
We developed and administered a picture selection sentence comprehension task to 122 school-age children representing varied cognitive abilities. We evaluated comprehension accuracy and response time in two syntactically identical conditions but with different cognitive demands incorporated in picture foils—one with low demand using superfluous adjectives and another with high demand using contrastive adjectives. Children also completed tasks measuring working memory capacity and long-term memory retrieval.

Results:
Comprehension accuracy was significantly lower, and response times were longer in the high–cognitive demand condition compared to the low-demand condition. Errors frequently involved incorrect attribute selection in the high-demand condition that included contrastive adjectives in picture foils, while reversal errors prevailed in the low-demand condition, which included superfluous adjectives. Accuracy correlated positively with the memory variables. Hierarchical regression analysis showed that after adjusting for comprehension in the low–cognitive demand condition (38.60% variance), memory variables accounted for 4.50% additional variance in the high-demand condition with only working memory capacity as the unique predictor.

Conclusions:
The significant role of working memory capacity in comprehending sentences with high cognitive demand indicated the recruitment of active attention and verbal rehearsal. Data support the newly developed measure's potential for assessing cognitive skills integral to sentence comprehension in school-age children.

Supplemental Material:

https://doi.org/10.23641/asha.26767063
Updates on Clinical Language Sampling Practices: A Survey of Speech-Language Pathologists Practicing in the United States
Authors: Wilder Amy , Redmond Sean M. 
Published: September 2024

Purpose:
Language sample analysis (LSA) provides many benefits for assessing, identifying therapy goals, and monitoring the progress of children with language disorders. Despite these widely recognized advantages, previous surveys suggest the declining use of LSA by speech-language pathologists (SLPs). This study aimed to provide updates on clinical LSA use following the recent introduction of two new LSA protocols, namely, the Sampling Utterances and Grammatical Analysis Revised (SUGAR) protocol and the Computerized Language Analysis KIDEVAL program.

Method:

Survey data from SLPs practicing in the United States (
N
= 337) were used to examine rates of LSA use, methods, and protocols. Factors predicting LSA use and reported facilitators and barriers were also examined.

Results:
Results indicated that 60% of SLPs used LSA in the past year. LSA skill level, training, and serving preschool or elementary school children predicted LSA use, whereas workplace, caseload, and years of experience were not significant predictors. Most SLPs reported using self-designed LSA protocols (62%), followed by Systematic Analysis of Language Transcripts (23%) and SUGAR (12%) protocols. SLPs who did not use LSA reported limited time (74%), limited resources (59%), and limited expertise (41%) as barriers and identified additional training on LSA computer programs (52%) and access to automatic speech recognition programs (49%) as facilitators to their adoption of LSA.

Conclusions:
Reported rates of LSA use and methods were consistent with previous survey findings. This study's findings highlight the ongoing needs for more extensive preprofessional training in LSA.
Brain–computer interface for simultaneous dual‐region spatial coding in hippocampal and somatosensory cortex of freely behaving rats
Authors: Li Ming , Xu Wei , Xu Zhaojie , Mo Fan , Yang Gucheng , Lv Shiya , Cao Hanwen , Liu Juntao , Cai Xinxia 
Published: September 2024

AbstractDecoding of spatial information from place cells is currently limited to individual brain regions, severely constraining the understanding of the brain's spatial navigation mechanisms. In this study, synchronized detection of dual‐brain region spatial encoding was conducted using brain–computer interface (BCI). Therefore, an implantable microelectrode array (MEA) was developed tailored for the simultaneous detection of neuronal activities in the CA1 of the hippocampus and the Barrel Cortex (BC) of the somatosensory cortex in rats as BCI. The MEA was improved by modifying the nanocomposite PtNP/PEDOT:PSS to improve their electrical properties (reducing impedance from 1.82 ± 0.17 MΩ to 3.4 ± 0.3 kΩ), facilitating neural recordings in freely behaving rats. The neural activities were obtained from the CA1 and the BC simultaneously and validated the existence of place cells in both brain regions. This study highlighted the potential of PtNP/PEDOT:PSS‐modified MEA as BCI in concurrently detecting neural activity associated with spatial encoding in two brain regions, offering novel perspectives on the processing of tactile stimuli and the formation of cognitive maps for navigation.
Height‐dependent LoS probability model for A2G channels incorporating airframe shadowing under built‐up scenario
Authors: Ali Farman , Pan Yinglan , Zhu Qiuming , Ahmad Naeem , Mao Kai , Ullah Habib 
Published: September 2024

AbstractThe line of sight (LoS) probability is a key factor for the channel modeling of air‐to‐ground (A2G) communication. However, the existing LoS probability models do not account for the effects of airframe shadowing (AS) and building density, which can cause serious link obstruction and performance loss due to the six‐dimensional (6D) mobility and self‐body of unmanned aerial vehicle (UAV). In this article, a new LoS probability model is proposed that considers the AS and building density for different UAV heights. Adding to this, the AS is derived in terms of UAV framework and 6D mobility. Next, the machine learning (ML) based graph neural network (GNN) method is developed to learn the features and structure of the urban environment and predict the LoS probability. Then, the GNN model is trained and evaluated based on the ray tracing (RT) data to establish the relationship between model parameters and UAV heights under the building density and AS factors. The interpretation and explanation of the proposed GNN model and prediction are also discussed in this article. It is shown from the simulation analysis that the GNN model accurately captures the effects of AS, building height distributions, and UAV heights, with high accuracy compared to the baseline 3GPP, GCM and NYU models.
Joint waveform design of radar detection, wireless communication and jamming based on chaotic composite modulation
Authors: Chen Jun , Wang Meng , Wang Jie , Wang Fei , Zhou Huiyu 
Published: September 2024

AbstractIn this letter, we address the problem of designing the joint waveform of radar detection, wireless communication and jamming. In the current most powerful filter‐bank multi‐carrier comb spectrum framework, a parameter‐agile time–frequency structure between symbols is elaborated to improve the uncertainty of waveform generation architecture. Furthermore, a novel composite modulation strategy that combines intra‐symbol chaos‐based radar frequency modulation and inter‐symbol chaos‐based phase modulation is proposed for a substantial jamming performance improvement. Simulation results verify that the proposed joint waveform produces a superior jamming performance while satisfying the requirements of radar detection and wireless communication.