bluuebunny/crossref_metadata_2025_split huggingface dataset:
An experimental investigation examining the usage of a hybrid nanofluid in an automobile radiator
Authors: Hassaan Amr M. 
Published: November 2024

AbstractSeveral modifications have been made to the radiator’s dimensions and materials as part of the evolution of the automotive cooling cycle. Coolant is an important factor that greatly affects the efficiency of the cooling cycle. In applications involving heat transmission, nanofluids have become a viable possibility coolant. Two distinct types of nanoparticles floating in the base fluid make up the hybrid nanofluid, a newly invented class of nanofluids. Tests of hybrid nanofluids as a working fluid substitute for conventional fluids have been assisted by the current study. In the radiator of a 2005 Honda, the MWCNT–Al2O3/water nanofluid was tested at various volumetric concentrations (Φ) using a 50:50 mixing ratio. The outcomes of the experiments were compared with those obtained by using pure water. The radiator’s performance was evaluated by adjusting the fluid flow rate and operating the fluid at two distinct temperatures (60, 80 °C). The outcomes demonstrated that the convection heat transfer coefficient increased with a ratio reached 28.5% over the distilled water at the same temperature and flow rate. Both effectiveness and the Nusselt number had improved, coming in at 22.54% and 23.74%, respectively. Depending on the fluid concentration there is an increase in the pressure drop up to 24% than ordinary fluid. It discovered considerable agreement between the research outcomes by comparing them with earlier publications. An experimental correlation was inferred from the results to estimate the Nusselt number as a function of the Reynolds number and (Φ).
Discovery of key molecular signatures for diagnosis and therapies of glioblastoma by combining supervised and unsupervised learning approaches
Authors: Sarker Arnob , Aziz Md. Abdul , Hossen Md. Bayazid , Mollah Md. Manir Hossain , Al-Amin  , Mollah Md. Nurul Haque 
Published: November 2024

AbstractGlioblastoma (GBM) is the most malignant brain cancer and one of the leading causes of cancer-related death globally. So, identifying potential molecular signatures and associated drug molecules are crucial for diagnosis and therapies of GBM. This study suggested GBM-causing ten key genes (ASPM, CCNB2, CDK1, AURKA, TOP2A, CHEK1, CDCA8, SMC4, MCM10, and RAD51AP1) from nine transcriptomics datasets by combining supervised and unsupervised learning results. Differential expression patterns of key genes (KGs) between GBM and control samples were verified by different independent databases. Gene regulatory network (GRN) detected some important transcriptional and post-transcriptional regulators for KGs. The KGs-set enrichment analysis unveiled some crucial GBM-causing molecular functions, biological processes, cellular components, and pathways. The DNA methylation analysis detected some hypo-methylated CpG sites that might stimulate the GBM development. From the immune infiltration analysis, we found that almost all KGs are associated with different immune cell infiltration levels. Finally, we recommended KGs-guided four repurposable drug molecules (Fluoxetine, Vatalanib, TGX221 and RO3306) against GBM through molecular docking, drug likeness, ADMET analyses and molecular dynamics simulation studies. Thus, the discoveries of this study could serve as valuable resources for wet-lab experiments in order to take a proper treatment plan against GBM.
Simulated misuse of large language models and clinical credit systems
Authors: Anibal James T. , Huth Hannah B. , Gunkel Jasmine , Gregurick Susan K. , Wood Bradford J. 
Published: November 2024

AbstractIn the future, large language models (LLMs) may enhance the delivery of healthcare, but there are risks of misuse. These methods may be trained to allocate resources via unjust criteria involving multimodal data - financial transactions, internet activity, social behaviors, and healthcare information. This study shows that LLMs may be biased in favor of collective/systemic benefit over the protection of individual rights and could facilitate AI-driven social credit systems.
Durability of carbon dioxide removal is critical for Paris climate goals
Authors: Brunner Cyril , Hausfather Zeke , Knutti Reto 
Published: November 2024

Abstract
Carbon Dioxide Removal is essential for achieving net zero emissions, as it is required to neutralize any residual CO2 emissions. The scientifically recognized definition of Carbon Dioxide Removal requires removed atmospheric CO2 to be stored “durably”; however, it remains unclear what is meant by durably, and interpretations have varied from decades to millennia. Using a reduced-complexity climate model, here we examined the effect of Carbon Dioxide Removal with varying CO2 storage durations. We found that storage duration substantially affects whether net zero emissions achieve the desired temperature outcomes. With a typical 100-year storage duration, net zero CO2 emissions with 6 GtCO2 per year residual emissions result in an additional warming of 0.8 °C by 2500 compared to permanent storage, thus putting the internationally agreed temperature limits at risk. Our findings suggest that a CO2 storage period of less than 1000 years is insufficient for neutralizing remaining fossil CO2 emissions under net zero emissions. These results reinforce the principle that credible neutralization claims using Carbon Dioxide Removal in a net zero framework require balancing emissions with removals of similar atmospheric residence time and storage reservoir, e.g., geological or biogenic.
A comprehensive guide for accurate conformational energies of microsolvated Li+ clusters with organic carbonates
Authors: Otlyotov Arseniy A. , Moshchenkov Andrey D. , Rozov Timofey P. , Tuma Anna A. , Ryzhako Alexander S. , Minenkov Yury 
Published: November 2024

A new database of conformational energies (semi-empirical, DFT and reference RI-SCS-MP2/CBS) of Li+ clusters with organic carbonates, LICARB806, is introduced. Representative low-energy conformers of these systems are determined.
Validating the Influences of Methodological Decisions on Assessing the Spatiotemporal Stability of Speech Movement Sequences Using Children's Speech Data
Authors: Wisler Alan , Teplansky Kristin , Berlin Janna , Wang Jun , Goffman Lisa 
Published: November 2024

Purpose:
Prior research introduced quantifiable effects of three methodological parameters (number of repetitions, stimulus length, and parsing error) on the spatiotemporal index (STI) using simulated data. Critically, these parameters often vary across studies. In this study, we validate these effects, which were previously only demonstrated via simulation, using children's speech data.

Method:
Kinematic data were collected from 30 typically developing children and 15 children with developmental language disorder, all spanning the ages of 6–8 years. All children repeated the sentence “buy Bobby a puppy” multiple times. Using these data, experiments were designed to mirror the previous simulated experiments as closely as possible to assess the effects of analytic decisions on the STI. Experiment 1 manipulated number of repetitions, Experiment 2 manipulated stimulus length (or the number of movement units in the target phrase), and Experiment 3 manipulated precision of parsing of the articulatory trajectories.

Results:
The findings of all three experiments closely mirror those of the prior simulation. Experiment 1 showed consistent underestimation of STI values from smaller repetition counts consistent with the theoretical model for all three participant groups. Experiment 2 found speech segments containing fewer movements yield lower STI values than longer ones. Finally, Experiment 3 showed even small parsing errors are found to significantly increase measured STI values.

Conclusions:
The results of this study are consistent with the findings of prior simulations in showing that the number of repetitions, length of stimuli, and amount of parsing error can all strongly influence the STI independent of behavioral factors. These results further confirm the importance of closely considering the design of experiments, which employ the STI.
Professional Identity in Speech-Language Pathology Students
Authors: Daughrity Belinda , Sun Lei , Fitzgerald Anita , Konrad Sharon 
Published: November 2024

Purpose:
Professional identity (PI) serves to aid preprofessionals by contributing to a sense of purpose as students pursue their academic requirements. The importance of PI has been explored across other allied health fields including nursing, social work, and medicine. However, this topic has not been thoroughly investigated in communication sciences and disorders (CSD), and there is limited information on perceptions of PI among CSD students.

Method:

The current study is a secondary analysis of existing data. An adapted version of the PI Five-Factor Scale was administered via an anonymous online survey. Student participants self-reported perceptions of PI and perceived program support. Differences on the factors were tested using
t
tests and analysis of variance to explore differences between groups.

Results:
Significant differences were found between monolingual and multilingual students, with monolingual English-speaking students reporting higher perceptions of PI. There were no significant differences in PI between genders, racial groups, or first-generation students versus students of parents with varying educational backgrounds. Participant responses skewed toward a positive PI. Similar results were found for participants' perceptions of program support for PI across the five factors.

Conclusions:
PI has been extensively explored in allied health fields, but the topic has not been explored in speech-language pathology. Study findings can be used to help better serve students, particularly those from underrepresented groups. These data can support the recruitment and retention of culturally and linguistically diverse students with goals to increase the diversity of the pipeline of future professionals.
Frequency-domain instrument with custom ASIC for dual-slope near-infrared spectroscopy
Authors: Kılıç Alper , Blaney Giles , Tavakoli Fatemeh , Frias Jodee , Sassaroli Angelo , Fantini Sergio , Koomson Valencia 
Published: November 2024

Real-time and non-invasive measurements of tissue concentrations of oxyhemoglobin (HbO2) and deoxyhemoglobin (HbR) are invaluable for research and clinical use. Frequency-domain near-infrared spectroscopy (FD-NIRS) enables non-invasive measurement of these chromophore concentrations in human tissue. We present a small form factor, dual-wavelength, miniaturized FD-NIRS instrument for absolute optical measurements, built around a custom application-specific integrated circuit and a dual-slope/self-calibrating (DS/SC) probe. The modulation frequency is 55 MHz, and the heterodyning technique was used for intensity and phase readout, with an acquisition rate of 0.7 Hz. The instrument consists of a 14 × 17 cm2 printed circuit board (PCB), a Raspberry Pi 4, an STM32G491 microcontroller, and the DS/SC probe. The DS/SC approach enables this instrument to be selective to deeper tissue and conduct absolute measurements without calibration. The instrument was initially validated using a tissue-mimicking solid phantom, and upon confirming its suitability for in vivo, a vascular occlusion experiment on a human subject was conducted. For the phantom experiments, an average of 0.08° phase noise and 0.10% standard deviation over the mean for the intensities was measured at a source–detector distance of 35 mm. The absorption and reduced scattering coefficients had average precisions (variation of measurement over time) of 0.5% and 0.9%, respectively, on a window of ten frames. Results from the in vivo experiment yielded the expected increase in HbO2 and HbR concentration for all measurement types tested, namely SC, DS intensity, and DS phase.
Rydberg electromagnetically induced transparency based laser lock to Zeeman sublevels with 0.6 GHz scanning range
Authors: Vylegzhanin Alexey , Nic Chormaic Síle , Brown Dylan J. 
Published: November 2024

We propose a technique for frequency locking a laser to the Zeeman sublevel transitions between the 5P3/2 intermediate and 32D5/2 Rydberg states in 87Rb. This method allows for continuous frequency tuning over 0.6 GHz by varying an applied external magnetic field. In the presence of the applied field, the electromagnetically induced transparency (EIT) spectrum of an atomic vapor splits via the Zeeman effect according to the strength of the magnetic field and the polarization of the pump and probe lasers. We show that the 480 nm pump laser, responsible for transitions between the Zeeman sublevels of the intermediate state and the Rydberg state, can be locked to the Zeeman-split EIT peaks. The short-term frequency stability of the laser lock is 0.15 MHz, and the long-term stability is within 0.5 MHz. The linewidth of the laser lock is ∼0.8 and ∼1.8 MHz in the presence and absence of the external magnetic field, respectively. In addition, we show that in the absence of an applied magnetic field and adequate shielding, the frequency shift of the lock point has a peak-to-peak variation of 1.6 MHz depending on the polarization of the pump field, while when locked to Zeeman sublevels, this variation is reduced to 0.6 MHz. The proposed technique is useful for research involving Rydberg atoms, where large continuous tuning of the laser frequency with stable locking is required.
A theoretical study on muoniated N-heterocyclic carbenes using path integral molecular dynamics
Authors: Orikono Satoshi , Kuwahata Kazuaki , Shimazaki Tomomi , Tachikawa Masanori 
Published: November 2024

Several N-heterocyclic carbenes (NHCs) are experimentally observed upon the addition of muonium (Mu), and the hyperfine coupling constants (HFCCs) of muon are measured. Theoretical investigation of Mu has been challenging due to significant quantum effects. Herein, we performed an ab initio path integral molecular dynamics (PIMD) simulation, which accurately considers multi-dimensional quantum effects, to theoretically investigate muoniated 1,3-dihydro-2H-imidazole-2-ylidene (Mu-IY). Our findings indicate that quantum effects have two contradictory contributions: the quantum effect of bond vibrations increases the HFCC values, whereas that of out-of-plane angular vibrations decreases the HFCC values. Moreover, we show that the HFCC values of other NHCs can be predicted without the PIMD simulations by applying the structural changes caused by the quantum effect derived from the PIMD simulations of Mu-IY.
Slow global motions in biosolids studied by the deuteron stimulated echo NMR experiment
Authors: Krushelnitsky Alexey , Shahsavan Farhad , Hempel Günter , Fatkullin Nail 
Published: November 2024

Recent 15N R1ρ-relaxation studies have shown that proteins in the solid state undergo slow, low amplitude global motion in the sub-millisecond time range. This range is at the edge of the time window for R1ρ experiments and, therefore, the motional parameters obtained by this method are not precise or reliable. In this paper, we present a 2H stimulated echo study of this type of molecular dynamics. The 2H stimulated echo experiments on a static sample allow for direct measurement of the correlation function in the time range of 10−6–10−1 s, making them well suited to study this type of molecular mobility. We have conducted a detailed analytical and numerical comparison of the correlation functions obtained from the relaxation and stimulated echo experiments, which are generally different. We have identified conditions and algorithms that enable a direct comparison of the relaxation and stimulated echo experimental results. Using the protein GB1 in the form of a lyophilized powder, we have demonstrated that 15N R1ρ-relaxation and 2H stimulated echo experiments yield essentially the same slow-motion correlation function. Surprisingly, this type of motion is observed not only in the protein sample but also in the tripeptide and single amino acid solid samples. The comparison of data measured in these three samples at different temperatures led us to conclude that this slow motion is, in fact, ultrasonic phonons, which seem to be inherent to all rigid biological solids.
Overexpression of HvVDE gene improved light protection in transgenic tobacco (Nicotiana tabacum)
Authors: Qu Xiaojie , Che Deyu , Qin Fangting , Huang Guang , Liu Hongzhang 
Published: November 2024

Hosta is commonly acknowledged as a popular and preferred plant for landscaping and gardening. The ‘sunburn’ caused by prolonged exposure to strong sunlight is reducing the ornamental values of Hosta plants. However, there is a scarcity of research focusing on the genetic components linked to light-induced harm in Hosta. Here, the violaxanthin de-epoxidase (VDE) homolog from Hosta ventricosa was isolated and functionally identified through conducting HvVDE-overexpression tobacco (Nicotiana tabacum) lines. The results showed that HvVDE encodes a putative protein comprising 481 amino acids with a molecular weight of 54.304 kDa. The phylogenetic analysis found that HvVDE exhibited close similarity to JcVDE. Besides, the expression patterns of HvVDE found that HvVDE was expressed differently across tissues, withexpression induced by high light intensities. And overexpression of HvVDE led to the restoration of non-photochemical quenching in tobacco, suggesting that HvVDE plays a role in dissipating excess light energy as thermal energy in H. ventricosa. These findings underscore the significance of HvVDE in mitigating photoinhibition and enhancing photoprotection mechanisms in H. ventricosa.
Stabilizing effect of the spacetime expansion on the Euler–Poisson equations in Newtonian cosmology
Authors: Gong Xinyu , Wei Changhua 
Published: November 2024

Abstract
The validity of the cosmic no-hair theorem for polytropic perfect fluids has been established by (Brauer et al 1994 Class. Quantum Grav. 11 2283) within the context of Newtonian cosmology, specifically under conditions of exponential expansion. This paper extends the investigation to assess the nonlinear stability of homogeneous Newtonian cosmological models under general accelerated expansion for perfect fluids. With appropriate assumptions regarding the expansion rate and decay properties of the homogeneous solution, our results demonstrate that the Euler–Poisson system admits a globally classical solution for initial data that are small perturbations to the homogeneous solution. Additionally, we establish that the solution asymptotically approaches the homogeneous solution as time tends to infinity. The theoretical framework is then applied to various types of perfect fluids, including isothermal gases, Chaplygin gases, and polytropic gases.
Efficient cross-domain fault diagnosis via distributed multi-source domain deep transfer learning
Authors: Wan Lanjun , Ning Jiaen , Li Yuanyuan , Li Changyun 
Published: November 2024

Abstract
In actual industrial production, the working conditions of rotating machinery are complex and changeable, and the health-state monitoring data are increasingly large and difficult to label, which will seriously restrict the accuracy and efficiency of the cross-domain fault diagnosis (CDFD) of rotating machinery. Therefore, an efficient multi-source domain deep transfer learning (MDDTL) method for CDFD of rotating machinery is proposed. First, an MDDTL model is constructed to improve the accuracy of CDFD. In the model, a dual-phase domain alignment strategy is designed, which considers the alignment of feature distributions between each source and target domain pair in the feature space and that of the prediction probabilities between domain-specific fault classifiers in the output space. The fault prediction results from multiple different fault classifiers are merged dynamically by the proposed imbalanced adaptive prediction strategy. Secondly, a data-parallel distributed training scheme for the MDDTL model is proposed. Based on the idea of data parallelism, the distributed parallel training of the MDDTL model is performed with a Horovod-graphics processing unit platform, and the parameters are synchronously updated with the bandwidth-optimal Ring-AllReduce architecture. Under the premise of ensuring the accuracy of FD, the training time of the MDDTL model is significantly reduced. Finally, extensive experiments are conducted to verify the effectiveness of the proposed MDDTL method. The results demonstrate that the proposed method not only effectively improves the accuracy of CDFD of rotating machinery but also significantly improves the training efficiency of the MDDTL model. After adopting the proposed method, the diagnosis accuracies achieved under two different cross-working condition scenarios reach 97.09% and 97.87% respectively, and the model training time is reduced by 73.62% when facing a large-scale rotating machinery training set.
Three-dimensional reconstruction and damage localization of bridge undersides based on close-range photography using UAV
Authors: Jiang Shang , Zhang Yufeng , Wang Feiyu , Xu Yichao 
Published: November 2024

Abstract
Damage inspection on the undersides of bridges is an important and challenging part of routine bridge inspections. A method for 3D reconstruction and damage localization of bridge undersides based on close-range photography by unmanned aerial vehicle (UAV) and stereo vision combined with deep learning algorithms is proposed, the specific contributions include: (1) proposing a close-range photography method for acquiring high-resolution images from multiple perspectives of the bridge underside by UAVs, serving as the data source for damage analysis; (2) applying a deep learning-assisted segmentation method to optimize the multi-view geometry-based 3D reconstruction method, improving the efficiency of three-dimensional reconstruction, and defining the projection direction from the 3D reconstruction results to obtain ultra-high-resolution panoramic images of the bridge underside; (3) addressing the issue of detecting minor damages in large panoramic images by using a slice-assisted reasoning module and a lightweight convolutional YOLO v8 network to identify exposed steel bars corroded due to concrete damage in the panoramic images, and defining a coordinate system to localize the damages on the bridge underside. The proposed method was applied to damage detection and localization on the underside of a 160 m span main span of an in-service concrete bridge. The results demonstrate that the proposed method can quickly and accurately identify exposed steel bar corrosion on the bridge underside and output reports, proving the practicality of the proposed method.