bluuebunny/crossref_metadata_2025_split huggingface dataset:
Heat transport in crystalline organic semiconductors: coexistence of phonon propagation and tunneling
Authors: Legenstein Lukas , Reicht Lukas , Wieser Sandro , Simoncelli Michele , Zojer Egbert 
Published: February 2025

Abstract
Understanding heat transport in organic semiconductors is of fundamental and practical relevance. Therefore, we study the lattice thermal conductivities of a series of (oligo)acenes, where an increasing number of rings per molecule leads to a systematic increase of the crystals’ complexity. Temperature-dependent thermal conductivity experiments in these systems disagree with predictions based on the traditional Peierls–Boltzmann framework, which describes heat transport in terms of particle-like phonon propagation. We demonstrate that accounting for additional phonon-tunneling conduction mechanisms through the Wigner Transport Equation resolves this disagreement and quantitatively rationalizes experiments. The pronounced increase of tunneling transport with temperature explains several unusual experimental observations, such as a weak temperature dependence in naphthalene’s thermal conductivity and an essentially temperature-invariant conductivity in pentacene. While the anisotropic thermal conductivities within the acene planes are essentially material-independent, the tunneling contributions (and hence the total conductivities) significantly increase with molecular length in the molecular backbone direction. This, for pentacene results in a surprising minimum of the thermal conductivity at 300 K.
Divergence in cellular markers observed in single-cell transcriptomics datasets between cultured primary trabecular meshwork cells and tissues
Authors: Tian Alice , Kim Sangbae , Baidouri Hasna , Li Jin , Cheng Xuesen , Vranka Janice , Li Yumei , Chen Rui , Raghunathan VijayKrishna 
Published: February 2025

Abstract
The trabecular meshwork within the outflow apparatus is critical in maintaining intraocular pressure homeostasis. In vitro studies employing primary cell cultures of the human trabecular meshwork (hTM) have conventionally served as surrogates for investigating the pathobiology of TM dysfunction. Despite its abundant use, translation of outcomes from in vitro studies to ex vivo and/or in vivo studies remains a challenge. Given the cell heterogeneity, performing single-cell RNA sequencing comparing primary hTM cell cultures to hTM tissue may provide important insights on cellular identity and translatability, as such an approach has not been reported before. In this study, we assembled a total of 14 primary hTM in vitro samples across passages 1–4, including 4 samples from individuals diagnosed with glaucoma. This dataset offers a comprehensive transcriptomic resource of primary hTM in vitro scRNA-seq data to study global changes in gene expression in comparison to cells in tissue in situ. We have performed extensive preprocessing and quality control, allowing the research community to access and utilize this public resource.
MEGA PROTAC, MEGA DOCK-based PROTAC mediated ternary complex formation pipeline with sequential filtering and rank aggregation
Authors: Ugurlu Sadettin Y. , McDonald David , Enisoglu Ramazan , Zhu Zexuan , He Shan 
Published: February 2025

Abstract
Proteolysis-targeting chimaeras (PROTACs), which induce proteolysis by recruiting an E3 ligase to dock into a target protein, are acquiring popularity as a novel pharmacological modality because of the unique features of PROTAC, including high potency, low dosage, and effective on undruggable targets. While PROTACs are promising prospects as chemical probes and therapeutic agents, their discovery usually necessitates the synthesis of numerous analogues to explore variations on the chemical linker structure exhaustively. Without extensive trial and error, it is unknown how to link the two protein-recruiting moieties to facilitate the formation of a productive ternary complex. Although molecular docking-based and optimization pipelines have been designed to predict ternary complexes, guiding rational PROTAC design, they have suffered from limited predictive performance in the quality of the ternary structure and their ranks. Here, MEGA PROTAC has been designed to enhance the performance in quality and ranking of ternary structures. MEGA PROTAC employs MEGADOCK to execute docking for protein-protein complexes (PPCs). The docking establishes an initial exploration area for PPCs. A sequential filtration strategy combined with rank aggregation is employed to choose a subset of PPCs for grid search. Once candidate PPCs are selected, a grid search method is used separately for translation and rotation. The remaining proteins have been grouped into clusters, and MEGA PROTAC further filters these clusters based on the energy score of the proteins within each cluster. MEGA PROTAC utilises rank aggregation to choose the best clusters and then employs MEGADOCK to dock PROTAC into the selected PPCs, forming a ternary structure. Finally, MEGA PROTAC was tested on 22 cases to compare with the state-of-the-art method, Bayesian optimisation for ternary complex prediction (BOTCP). MEGA PROTAC outperformed BOTCP on 16 test cases out of 22 cases, achieving a higher maximum DockQ score with an 18% higher mean and 35% higher median. Also, MEGA PROTAC exhibited 75% superior ranks and a reduced cluster number for maximum DockQ score compared to BOTCP. Also, MEGA PROTAC outperforms BOTCP by achieving a twofold improvement in locating the first acceptable DockQ scores, with a more significant proportion of near-native structures within the detected cluster.
The internal and external cost of motor vehicle crashes
Authors: Dai Shian , Yu Liqiang , Liu Zhaoran , Cui Mengying , Levinson David 
Published: February 2025

Abstract
Crash cost estimates are essential for evaluating road safety management policies and assessing the economic benefits of safety improvements. Existing studies often rely on aggregated crash data, assuming an even distribution of incidents, which overlooks significant spatial variations influenced by road characteristics and traffic conditions. This research presents a methodological framework for link-based crash cost analysis that considers both internal and external costs, enabling detailed quantification at a localized level. By employing safety performance functions and ordered probit models, we estimate on-road crash rates by crash type and injury severity, distinguishing between internal costs borne by individuals involved in crashes and external costs that impact victims, insurers, and government agencies. This framework is applied to the Minneapolis-St. Paul metropolitan area for a proof-of-concept. Our findings reveal that the costs incurred by drivers are higher than those imposed on others, and that highways are generally safer than surface streets. However, these crash costs are too low compared to the value of travel time to significantly influence route choices, even when drivers are aware of these costs. To enhance effective decision-making, related policies should consider offering incentives for safe driving practices. Future research on the practical applications of this framework is encouraged to maintain a dynamic dataset that reflects ongoing changes in road safety conditions.
Process optimization of jet electrodeposition Ni–Co–P alloy coating using response surface methodology and the tribological behavior of Ni–Co–P nanocomposite coatings
Authors: Zhang Yin , Wang Yonggang , Yao Liang , Chen Lingling 
Published: February 2025

Abstract
A novel Ni–Co–P alloy coating and Ni–Co–P nanocomposite coating were prepared by jet electrodeposition. The influence of jet electrodeposition processing parameters on the microhardness and wear track width of the Ni–Co–P alloy coating was investigated. Additionally, the cross-section morphology, EDS spectra, XRD patterns, microhardness and wear resistance of the coatings under the optimum jet electrodeposition parameters were evaluated. The BBD analysis results revealed that the established mathematical model was reliable. Furthermore, the optimum Ni–Co–P alloy coating parameters optimized through the response surface method were as follows: jet voltage: 12.14 V, plating solution temperature: 61.60 °C, reciprocating sweep speed: 173.19 mm·s−1, jet gap: 2.05 mm, pulse frequency: 4.06 kHz and duty cycle: 0.81. Under the optimum jet electrodeposition parameters, the results revealed that the significant influence of nano BN(h) and Al2O3 particles on the coatings’ thickness, Co contents, crystallite size, microhardness and wear resistance of Ni–Co–P nanocomposite coating. In addition, compared with the Ni–Co–P alloy coating and Ni–Co–P–BN(h) nanocomposite coating, the Ni–Co–P–Al2O3 composite coating exhibited a larger thickness (18.16 µm) and Co element contents (39.51 wt·%), a smaller crystallite size (16.440 nm), a higher microhardness (676.5 HV0.2), a more excellent wear resistance (402.9 µm).
Protocol for evaluation of iTEST, a novel blended intervention to enhance introspective accuracy in psychotic disorders
Authors: Berretta Sarah A. , Abaya Nicole , Parrish Emma , McBride Lauren E. , Moore Raeanne C. , Ackerman Robert , Harvey Philip D. , Pinkham Amy E. , Depp Colin A. 
Published: February 2025

Abstract
Poor introspective accuracy (IA), defined as inaccurate judgments of one’s abilities and performance, is a strong and independent predictor of functional impairment in people with psychotic disorders. However, there are currently no treatments that directly target IA in this population as a primary outcome. We describe a protocol for a clinical trial to test a newly developed blended digital intervention, Improving Thinking through Everyday SelfAssessment Training (iTEST), aimed at improving IA in people with psychotic disorders to improve functional outcomes. iTEST involves daily training consisting of feedback on IA in mobile cognitive tests, coupled with individual coaching that applies improved IA to participant-identified recovery goals. Following the NIMH experimental therapeutics paradigm, the first step in the evaluation of iTEST is an open trial in 60 individuals with psychotic disorders to assess 1) feasibility and acceptability, and 2) whether the intervention leads to clinically significant improvement in an objective target: IA on trained tasks along with transfer to an untrained task-based measure of IA. After programming of the mobile intervention and the creation of treatment manuals, enrollment for an open trial started in November 2023 and will be completed by April 2025. If effective, iTEST could be integrated with cognitive training and other rehabilitative interventions to boost the impact on functional outcomes. Trial registration: ClinicalTrials.gov NCT05899348.
Functional assessment of autologous tissue expansion grafts for vaginal reconstruction in a rabbit model
Authors: Willacy Oliver , Juul Nikolai , Olsen August , Egeland Charlotte , Hu Tu , Amoushahi Mahboobeh , Jensen Thomas , Ajalloueian Fatemeh , Litman Thomas , Chamorro Clara I. , Fossum Magdalena 
Published: February 2025

Abstract
This study explores a novel approach to vaginal reconstructive surgery using autologous tissue grafts, which may provide new therapeutic options for women with congenital or acquired vaginal anomalies. Using a small autologous vaginal tissue segment, we engineered a six-fold expanded graft perioperatively, leveraging the body as a bioreactor and avoiding preoperative tissue culture. In adolescent White New Zealand rabbits, a vaginal defect was created and repaired using a PLATE graft (perioperative, layered, autologous, tissue-expansion graft) containing mucosa, smooth muscle, collagen, and surgical mesh. After seven months, PLATE grafts were well integrated with native tissues, exhibited reduced fibrosis, and enhanced muscle regeneration compared to acellular grafts. Gene analysis revealed upregulation of smooth muscle and ECM organisation markers. Functional validation included successful breeding and vaginal delivery of live pups. PLATE grafts proved safe for vaginal reconstruction in rabbits, presenting a new direction in tissue engineering and expanding surgical options for women.
Egocentric action anticipation from untrimmed videos
Authors: Rodin Ivan , Furnari Antonino , Farinella Giovanni Maria 
Published: February 2025

AbstractEgocentric action anticipation involves predicting future actions performed by the camera wearer from egocentric video. Although the task has recently gained attention in the research community, current approaches often assume that input videos are ‘trimmed’, meaning that a short video sequence is sampled a fixed time before the beginning of the action. However, trimmed action anticipation has limited applicability in real‐world scenarios, where it is crucial to deal with ‘untrimmed’ video inputs and the exact moment of action initiation cannot be assumed at test time. To address these limitations, an untrimmed action anticipation task is proposed, which, akin to temporal action detection, assumes that the input video is untrimmed at test time, while still requiring predictions to be made before actions take place. The authors introduce a benchmark evaluation procedure for methods designed to address this novel task and compare several baselines on the EPIC‐KITCHENS‐100 dataset. Through our experimental evaluation, testing a variety of models, the authors aim to better understand their performance in untrimmed action anticipation. Our results reveal that the performance of current models designed for trimmed action anticipation is limited, emphasising the need for further research in this area.
Implementation of an Ultra‐Low Profile High‐Purity OAM Generator
Authors: Peng Songtao , Pu Youlei 
Published: February 2025

ABSTRACTThis letter presents an orbital angular momentum (OAM) generator based on a uniform circular array (UCA) micro‐integrated structure that produces ultra‐high purity OAM vortex beams at Ka‐band while maintaining a low profile. Utilizing cut‐angle microstrip patch elements, the UCA excites circularly polarized waves and generates OAM modes with () through specific amplitude and phase signal inputs. A key feature of this design is the integration of a substrate‐integrated waveguide (SIW) radial feed network with the UCA, significantly lowering fabrication costs and reducing the overall thickness to only 1.1 mm (0.11 at 30.0 GHz). Measurements of the Ka‐band prototype reveal an OAM mode purity of 93% for () and a 10 dB bandwidth of approximately 1.8 GHz.
Optimizing recovery: the impact of training load in elite volleyball
players
Authors: Rebelo André , Pereira João R , Broek Gert Vande , Coelho-e-Silva Manuel J , Elferink-Gemser Marije T , Valente-dos-Santos João 
Published: February 2025

AbstractThis study aimed to analyze the relationships between training load metrics and
various dimensions of recovery over the course of 105 days during the
competitive season. This study included 14 elite male volleyball players who
participated in 95 training sessions and 18 matches. The session rating of
perceived exertion and inertial measurement units were utilized to measure
internal and external training loads, respectively. Biological recovery was
assessed using the countermovement jump test, while social and psychological
recoveries were measured through the RESTQ-Sport. Relationships were examined
using linear mixed-effect models to account for repeated measures across players
and time points. The results revealed that chronic external training loads
negatively influenced the biological recovery, with increases in chronic
external training loads associated with a longer time to take-off
(β=− 0.008, p=0.03) and a reduced modified reactive strength index
(β=− 0.008, p=0.047). Social recovery was influenced by
internal training load metrics, with acute internal training loads increasing
social stress (β=− 3.512, p=0.034). For psychological recovery,
chronic internal training loads and the acute:chronic internal training load
ratio were linked to higher emotional exhaustion (β=− 0.013,
p=0.029; β=0.021, p<0.001, respectively). These findings
highlight the critical role of external load management in the biological
recovery and the relevance of subjective internal load measures in monitoring
social and psychological recovery dimensions. Coaches are encouraged to
integrate time-based neuromuscular metrics and perceptual load assessments into
their recovery monitoring protocols to optimize athletes’ well-being and
performance.
Postharvest management of mycotoxins in supply chains of agricultural produces
Authors: Agriopoulou Sofia , Smaoui Slim , Varzakas Theodoros 
Published: February 2025

Abstract
Mycotoxins are secondary metabolites produced by filamentous fungi responsible for the contamination of food and feedstuffs. The presence of mycotoxins causes relevant economic losses and negative effects on both human and animal health. Strategies related to good agricultural and processing practices offer satisfactory results in the reduction of mycotoxins. Practices such as good agriculture practices, good manufacturing practice, good storage practices and the application of hazard analysis and monitoring of critical points must be implemented. The need for effective detoxification and the availability of products safe from mycotoxins is becoming more and more imperative, from all links of the supply chain and of course from the final consumers of these products. In addition to the traditional techniques that have been used in the attempt to detoxify mycotoxins, innovative nanotechnological and biotechnological approaches have emerged with increasingly promising results. The main goal of this review is to highlight the main economic impacts that mycotoxins have and to suggest postharvest management approaches for production and marketing of mycotoxin-free products. Traditional and innovative physical, chemical and microbiological methods have been discussed for preventing contamination by and degradation of mycotoxins in food and feed products.
Enhancing automatic pothole detection in non-motorized corridors using smartphones: an integrated algorithm
Authors: Qiao Yaning , Wang Jia , Zhang Ximeng , Huang Jiandong , He Liang , Zhang Runhua 
Published: February 2025

Abstract
Potholes present a significant safety risk on non-motorized vehicle lanes, especially under low-visibility conditions. Effective pothole detection on non-motorized vehicle lanes is crucial to improve public transportation safety. This study proposes an integrated algorithm that harnesses smartphone sensors to enhance pothole detection accuracy. The algorithm begins with data processing, incorporating techniques such as the quaternion algorithm, synthetic minority over-sampling technique, and wavelet-domain denoising. This preprocessing addresses challenges such as significant smartphone placement uncertainty, limited pothole data, and intense noise signals, all of which severely affect the prediction accuracy of machine learning models. The processed data is subsequently used to train machine learning models for pothole detection, including artificial neural networks (ANNs), bootstrap forest, and Naïve Bayes. The accuracy and precision of the models are evaluated and compared. The results show that the accuracy of pothole detection with the integrated algorithm improved to 92%–97%, surpassing the 70%–90% accuracy reported in previous studies. Using the ANN prediction model, the integrated algorithm achieved the highest overall accuracy of 97.02%, with an F-measure of 95.15%. Additionally, the Naïve Bayes model effectively addresses the class imbalance in pothole detection, achieving the highest precision (97.93%). These results confirm the effectiveness and improved accuracy of the proposed integrated pothole detection algorithm.
Non-intrusive radio frequency polarimetry measurements of rotor whirl using artificial neural networks
Authors: Inoue Yuko , Perez Luis E , Kelly Ryan T , Jemcov Aleksandar , Pratt Thomas G , Morris Scott C 
Published: February 2025

Abstract
Fault diagnosis in rotating machinery, especially in aviation, is an active research area. RF sensors have the potential to provide on-wing information for fault diagnosis for gas turbine engines. A dual-polarized, distributed RF sensor system was tested in an axial compressor to determine if the measurement system could detect and predict rotor offset and whirl. A magnetic bearing system was used to dynamically control the rotor position. The RF polarimetry data were used as the input data to simple, multilayer neural networks. Regression analysis was performed to predict the rotor shaft centerline position and rotor whirl orbits’ major and minor axis lengths. Typical neural network error was within 5 μm for whirl orbits up to 175 μm. The quality of the neural network prediction as a function of the number of features was studied. The results suggest that a final configuration may only require a single transmit-receive antenna pair and one RF tone.
Integrals of Products of Bessel Functions: A Perspective from the Physics of Bloch Electrons
Authors: Covey Joshua , Maslov Dmitrii 
Published: February 2025

Abstract
Integrals of products of Bessel functions exhibit an intriguing feature: they may vanish identically, not due to an orthogonality property, but rather when certain conditions on the parameters specifying the integrand are satisfied. We provide a physical interpretation of this feature in the context of both single-particle and many-body properties of electrons on a lattice ("Bloch electrons"), namely, in terms of their density of states and umklapp scattering rate. (In an umklapp event, the change in the momentum of two colliding electrons is equal to a reciprocal lattice vector, which gives rise to a finite resistivity due to electron-electron interaction.) In this context, the vanishing of an integral follows simply from the condition that either the density of states vanishes due to the electron energy lying outside the band in which free propagation of electron waves is allowed, or that an umklapp process is kinematically forbidden due to the Fermi surface being smaller than a critical value.
Investigations on the frictional performance of laser surface textured piston rings in an automotive engine test rig under different coolant and lubricant temperature
Authors: Nazeer Basha D , Ramalingam Vaira Vignesh , GL Samuel , Bathe Ravi 
Published: February 2025

Abstract
Research in the field of internal combustion engines are focused on improving its fuel efficiency and reducing its emissions. Reduction of frictional losses, which constitute 40% of energy loss in a typical engine, would pave a way for economic fuel consumption. In this work, patterning of micro geometries on the piston rings has been identified as a viable technology for reducing friction between piston rings and cylinder liners. Also, the results indicate that the lubricant oil consumption reduced by ~12.35%, if textured rings are utilized in the engines. It is observed that homogeneous distribution of the texture and flow of oil (viscosity) between the contact surfaces under the boundary lubrication regime influences the engine performance.&#xD;