bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Role of Deposition of Cosmogenic 10Be for the Detectability of Solar Proton Events
Authors: Schaar K. , Spiegl T. , Langematz U. , Sato T. , Mekhaldi F. , Kunze M. , Miyake F. , Yoden S. 
Published: May 2024

AbstractThe manifestation of extreme solar proton events (SPEs) in Beryllium‐10 (10Be) ice core data contains valuable information about the strength and incidence of SPEs or local characteristics of the atmosphere. To extract this information, the signals of enhanced production of cosmogenic 10Be due to the SPEs have to be detected, hence distinguished from the variability of the background production by galactic cosmic rays (GCRs). Here, we study the transport and deposition of 10Be from GCRs, using the ECHAM/MESSy Atmospheric Chemistry climate model, and discuss the detectability of extreme SPEs (similar to the CE 774/775 SPE) in 10Be ice core data depending on the ice core location, seasonal appearance of the SPE, atmospheric aerosol size distribution and phase of the 11‐year solar cycle. We find that sedimentation can be a major deposition mechanism of GCR generated 10Be, especially at high latitudes, depending on the aerosols to which 10Be attaches after production. The comparison of our results to four ice core records of 10Be from Greenland and Antarctica shows good agreement for both 10Be from GCRs and solar energetic particles (SEP). From our results we deduce that the location of detection and the season of occurrence of the SPE have a considerable effect on its detectability, as well as the aerosol size distribution the produced cosmogenic nuclides meet in the atmosphere. Furthermore, we find that SPEs occurring in the phase of highest activity during the 11‐year solar cycle are more detectable than SPEs that arise in the phase of lowest activity.
Why Do Oceanic Nonlinearities Contribute Only Weakly to Extreme El Niño Events?
Authors: Liu Fangyu , Vialard Jérôme , Fedorov Alexey V. , Éthé Christian , Person Renaud , Zhang Wenjun , Lengaigne Matthieu 
Published: May 2024

AbstractExtreme El Niño events have outsized global impacts and control the El Niño Southern Oscillation (ENSO) warm/cold phases asymmetries. Yet, a consensus regarding the relative contributions of atmospheric and oceanic nonlinearities to their genesis remains elusive. Here, we isolate the contribution of oceanic nonlinearities by conducting paired experiments forced with opposite wind stress anomalies in an oceanic general circulation model, which realistically simulates extreme El Niño events and oceanic nonlinearities thought to contribute to ENSO skewness (Tropical Instability Waves (TIWs), Nonlinear Dynamical Heating (NDH)). Our findings indicate a weak contribution of oceanic nonlinearities to extreme El Niño events in the eastern Pacific, owing to compensatory effects between lateral (NDH and TIWs) and vertical processes. These results hold across different vertical mixing schemes and modifications of the upper‐ocean heat budget mixed layer criterion. Our study reinforces previous research underscoring the pivotal role of atmospheric nonlinearities in shaping extreme El Niño events.
Multichannel microneedle dry electrode patches for minimally invasive transdermal recording of electrophysiological signals
Authors: Liu Zhengjie , Xu Xingyuan , Huang Shuang , Huang Xinshuo , Liu Zhibo , Yao Chuanjie , He Mengyi , Chen Jiayi , Chen Hui-jiuan , Liu Jing , Xie Xi 
Published: May 2024

AbstractThe collection of multiple-channel electrophysiological signals enables a comprehensive understanding of the spatial distribution and temporal features of electrophysiological activities. This approach can help to distinguish the traits and patterns of different ailments to enhance diagnostic accuracy. Microneedle array electrodes, which can penetrate skin without pain, can lessen the impedance between the electrodes and skin; however, current microneedle methods are limited to single channels and cannot achieve multichannel collection in small areas. Here, a multichannel (32 channels) microneedle dry electrode patch device was developed via a dimensionality reduction fabrication and integration approach and supported by a self-developed circuit system to record weak electrophysiological signals, including electroencephalography (EEG), electrocardiogram (ECG), and electromyography (EMG) signals. The microneedles reduced the electrode–skin contact impedance by penetrating the nonconducting stratum corneum in a painless way. The multichannel microneedle array (MMA) enabled painless transdermal recording of multichannel electrophysiological signals from the subcutaneous space, with high temporal and spatial resolution, reaching the level of a single microneedle in terms of signal precision. The MMA demonstrated the detection of the spatial distribution of ECG, EMG and EEG signals in live rabbit models, and the microneedle electrode (MNE) achieved better signal quality in the transcutaneous detection of EEG signals than did the conventional flat dry electrode array. This work offers a promising opportunity to develop advanced tools for neural interface technology and electrophysiological recording.
Targeting the autophagy-NAD axis protects against cell death in Niemann-Pick type C1 disease models
Authors: Kataura Tetsushi , Sedlackova Lucia , Sun Congxin , Kocak Gamze , Wilson Niall , Banks Peter , Hayat Faisal , Trushin Sergey , Trushina Eugenia , Maddocks Oliver D. K. , Oblong John E. , Miwa Satomi , Imoto Masaya , Saiki Shinji , Erskine Daniel , Migaud Marie E. , Sarkar Sovan , Korolchuk Viktor I. 
Published: May 2024

AbstractImpairment of autophagy leads to an accumulation of misfolded proteins and damaged organelles and has been implicated in plethora of human diseases. Loss of autophagy in actively respiring cells has also been shown to trigger metabolic collapse mediated by the depletion of nicotinamide adenine dinucleotide (NAD) pools, resulting in cell death. Here we found that the deficit in the autophagy-NAD axis underpins the loss of viability in cell models of a neurodegenerative lysosomal storage disorder, Niemann-Pick type C1 (NPC1) disease. Defective autophagic flux in NPC1 cells resulted in mitochondrial dysfunction due to impairment of mitophagy, leading to the depletion of both the reduced and oxidised forms of NAD as identified via metabolic profiling. Consequently, exhaustion of the NAD pools triggered mitochondrial depolarisation and apoptotic cell death. Our chemical screening identified two FDA-approved drugs, celecoxib and memantine, as autophagy activators which effectively restored autophagic flux, NAD levels, and cell viability of NPC1 cells. Of biomedical relevance, either pharmacological rescue of the autophagy deficiency or NAD precursor supplementation restored NAD levels and improved the viability of NPC1 patient fibroblasts and induced pluripotent stem cell (iPSC)-derived cortical neurons. Together, our findings identify the autophagy-NAD axis as a mechanism of cell death and a target for therapeutic interventions in NPC1 disease, with a potential relevance to other neurodegenerative disorders.
Deep brain stimulation of symptom-specific networks in Parkinson’s disease
Authors: Rajamani Nanditha , Friedrich Helen , Butenko Konstantin , Dembek Till , Lange Florian , Navrátil Pavel , Zvarova Patricia , Hollunder Barbara , de Bie Rob M. A. , Odekerken Vincent J. J. , Volkmann Jens , Xu Xin , Ling Zhipei , Yao Chen , Ritter Petra , Neumann Wolf-Julian , Skandalakis Georgios P. , Komaitis Spyridon , Kalyvas Aristotelis , Koutsarnakis Christos , Stranjalis George , Barbe Michael , Milanese Vanessa , Fox Michael D. , Kühn Andrea A. , Middlebrooks Erik , Li Ningfei , Reich Martin , Neudorfer Clemens , Horn Andreas 
Published: May 2024

AbstractDeep Brain Stimulation can improve tremor, bradykinesia, rigidity, and axial symptoms in patients with Parkinson’s disease. Potentially, improving each symptom may require stimulation of different white matter tracts. Here, we study a large cohort of patients (N = 237 from five centers) to identify tracts associated with improvements in each of the four symptom domains. Tremor improvements were associated with stimulation of tracts connected to primary motor cortex and cerebellum. In contrast, axial symptoms are associated with stimulation of tracts connected to the supplementary motor cortex and brainstem. Bradykinesia and rigidity improvements are associated with the stimulation of tracts connected to the supplementary motor and premotor cortices, respectively. We introduce an algorithm that uses these symptom-response tracts to suggest optimal stimulation parameters for DBS based on individual patient’s symptom profiles. Application of the algorithm illustrates that our symptom-tract library may bear potential in personalizing stimulation treatment based on the symptoms that are most burdensome in an individual patient.
Quantum computation of frequency-domain molecular response properties using a three-qubit iToffoli gate
Authors: Sun Shi-Ning , Marinelli Brian , Koh Jin Ming , Kim Yosep , Nguyen Long B. , Chen Larry , Kreikebaum John Mark , Santiago David I. , Siddiqi Irfan , Minnich Austin J. 
Published: May 2024

AbstractThe quantum computation of molecular response properties on near-term quantum hardware is a topic of substantial interest. Computing these properties directly in the frequency domain is desirable, but the circuits require large depth if the typical hardware gate set consisting of single- and two-qubit gates is used. While high-fidelity multipartite gates have been reported recently, their integration into quantum simulation and the demonstration of improved accuracy of the observable properties remains to be shown. Here, we report the application of a high-fidelity multipartite gate, the iToffoli gate, to the computation of frequency-domain response properties of diatomic molecules. The iToffoli gate enables a ~50% reduction in circuit depth and ~40% reduction in circuit execution time compared to the traditional gate set. We show that the molecular properties obtained with the iToffoli gate exhibit comparable or better agreement with theory than those obtained with the native CZ gates. Our work is among the first demonstrations of the practical usage of a native multi-qubit gate in quantum simulation, with diverse potential applications to near-term quantum computation.
Integrated omics of Saccharomyces cerevisiae CENPK2-1C reveals pleiotropic drug resistance and lipidomic adaptations to cannabidiol
Authors: Jordan Erin Noel , Shirali Hossein Zade Ramin , Pillay Stephanie , van Lent Paul , Abeel Thomas , Kayser Oliver 
Published: May 2024

AbstractYeast metabolism can be engineered to produce xenobiotic compounds, such as cannabinoids, the principal isoprenoids of the plant Cannabis sativa, through heterologous metabolic pathways. However, yeast cell factories continue to have low cannabinoid production. This study employed an integrated omics approach to investigate the physiological effects of cannabidiol on S. cerevisiae CENPK2-1C yeast cultures. We treated the experimental group with 0.5 mM CBD and monitored CENPK2-1C cultures. We observed a latent-stationary phase post-diauxic shift in the experimental group and harvested samples in the inflection point of this growth phase for transcriptomic and metabolomic analysis. We compared the transcriptomes of the CBD-treated yeast and the positive control, identifying eight significantly overexpressed genes with a log fold change of at least 1.5 and a significant adjusted p-value. Three notable genes were PDR5 (an ABC-steroid and cation transporter), CIS1, and YGR035C. These genes are all regulated by pleiotropic drug resistance linked promoters. Knockout and rescue of PDR5 showed that it is a causal factor in the post-diauxic shift phenotype. Metabolomic analysis revealed 48 significant spectra associated with CBD-fed cell pellets, 20 of which were identifiable as non-CBD compounds, including fatty acids, glycerophospholipids, and phosphate-salvage indicators. Our results suggest that mitochondrial regulation and lipidomic remodeling play a role in yeast’s response to CBD, which are employed in tandem with pleiotropic drug resistance (PDR). We conclude that bioengineers should account for off-target product C-flux, energy use from ABC-transport, and post-stationary phase cell growth when developing cannabinoid-biosynthetic yeast strains.
Polyanhydride nanovaccine against H3N2 influenza A virus generates mucosal resident and systemic immunity promoting protection
Authors: Lopez Christopher E. , Zacharias Zeb R. , Ross Kathleen A. , Narasimhan Balaji , Waldschmidt Thomas J. , Legge Kevin L. 
Published: May 2024

AbstractInfluenza A virus (IAV) causes significant morbidity and mortality worldwide due to seasonal epidemics and periodic pandemics. The antigenic drift/shift of IAV continually gives rise to new strains and subtypes, aiding IAV in circumventing previously established immunity. As a result, there has been substantial interest in developing a broadly protective IAV vaccine that induces, durable immunity against multiple IAVs. Previously, a polyanhydride nanoparticle-based vaccine or nanovaccine (IAV-nanovax) encapsulating H1N1 IAV antigens was reported, which induced pulmonary B and T cell immunity and resulted in cross-strain protection against IAV. A key feature of IAV-nanovax is its ability to easily incorporate diverse proteins/payloads, potentially increasing its ability to provide broad protection against IAV and/or other pathogens. Due to human susceptibility to both H1N1 and H3N2 IAV, several H3N2 nanovaccines were formulated herein with multiple IAV antigens to examine the “plug-and-play” nature of the polyanhydride nanovaccine platform and determine their ability to induce humoral and cellular immunity and broad-based protection similar to IAV-nanovax. The H3N2-based IAV nanovaccine formulations induced systemic and mucosal B cell responses which were associated with antigen-specific antibodies. Additionally, systemic and lung-tissue resident CD4 and CD8 T cell responses were enhanced post-vaccination. These immune responses corresponded with protection against both homologous and heterosubtypic IAV infection. Overall, these results demonstrate the plug-and-play nature of the polyanhydride nanovaccine platform and its ability to generate immunity and protection against IAV utilizing diverse antigenic payloads.
Gender board diversity across Europe throughout four decades
Authors: Drazkowski Hubert , Tyrowicz Joanna , Zalas Sebastian 
Published: May 2024

AbstractWe present a Gender Board Diversity Dataset (GBDD), which provides a cross-country perspective on women in management and supervisory boards that spans between 1985 and 2020. The data covers 43 European countries and accounts for private companies in addition to the stock-listed ones. GBBD was created using firm-level Orbis data. Our measures are based on a sample of more than 28 million unique firms observed for nearly seven years on average and reporting data about nearly 59 million individuals on management and supervisory boards. We provide the measures at the level of industry, country and year (firm-level data is proprietary). We provide three measures. The first is the share of women among all board members in a given industry, country, and year. The second one is the average of the shares of women across firms in a given industry, country and year. We also provide a new measure: the share of firms in a given industry, country and year which report no single woman on their board(s).
Using explainable machine learning and fitbit data to investigate predictors of adolescent obesity
Authors: Kiss Orsolya , Baker Fiona C. , Palovics Robert , Dooley Erin E. , Pettee Gabriel Kelley , Nagata Jason M. 
Published: May 2024

AbstractSociodemographic and lifestyle factors (sleep, physical activity, and sedentary behavior) may predict obesity risk in early adolescence; a critical period during the life course. Analyzing data from 2971 participants (M = 11.94, SD = 0.64 years) wearing Fitbit Charge HR 2 devices in the Adolescent Brain Cognitive Development (ABCD) Study, glass box machine learning models identified obesity predictors from Fitbit-derived measures of sleep, cardiovascular fitness, and sociodemographic status. Key predictors of obesity include identifying as Non-White race, low household income, later bedtime, short sleep duration, variable sleep timing, low daily step counts, and high heart rates (AUCMean = 0.726). Findings highlight the importance of inadequate sleep, physical inactivity, and socioeconomic disparities, for obesity risk. Results also show the clinical applicability of wearables for continuous monitoring of sleep and cardiovascular fitness in adolescents. Identifying the tipping points in the predictors of obesity risk can inform interventions and treatment strategies to reduce obesity rates in adolescents.
Low density phases of TiO2 by cluster self-assembly
Authors: Aguilera-Granja Faustino , Ayuela Andres 
Published: May 2024

AbstractThe interest in titanium dioxide (TiO$$_2$$

2

) phases is growing due to the number of applications in cosmetics, food industry and photocatalysis, an increase that is driven by its exceptional properties when engineered at the nanoscale like in the form of nanoparticles. Our goal is to discover unknown low-density phases of TiO$$_2$$

2

, with potential for applications in various fields. We then use well-known TiO$$_2$$

2

clusters as fundamental building blocks to be self-assembled into unique structures to study their distinct characteristics. Density functional calculations are employed to relax the structures and identify the most stable TiO$$_2$$

2

structures within an energy range of 0.1 eV per atom from the rutile and anatase phases, which are confirmed, validating our methodology. Going beyond conventional phases, we found two-dimensional TiO$$_2$$

2

structures, previously explored in separate studies, and showing typical structures of transition metal dichalcogenide layers, that forge a bridge between different TiO$$_2$$

2

structures. It is noteworthy that our investigation uncovered an entirely novel class of TiO$$_2$$

2

structures featuring hexagonal cages like beehive channels, opening novel phases with huge potential. These discovered low-density phases are interesting, particularly the hexagonal cage structures with remarkable large gaps, because they introduce other dimensions for uncharted applications in the ever-growing TiO$$_2$$

2

landscape.
Passive and low-energy strategies to improve sleep thermal comfort and energy resilience during heat waves and cold snaps
Authors: Aijazi Arfa , Parkinson Thomas , Zhang Hui , Schiavon Stefano 
Published: May 2024

AbstractSleep is a pillar of human health and wellbeing. In high- and middle-income countries, there is a great reliance on heating, ventilation, and air conditioning systems (HVAC) to control the interior thermal environment in the bedroom. However, these systems are expensive to buy, maintain, and operate while being energy and environmentally intensive—problems that may increase due to climate change. Easily-accessible passive and low-energy strategies, such as fans and electrical heated blankets, address these challenges but their comparative effectiveness for providing comfort in sleep environments has not been studied. We used a thermal manikin to experimentally show that many passive and low-energy strategies are highly effective in supplementing or replacing HVAC systems during sleep. Using passive strategies in combination with low-energy strategies that elevate air movement like ceiling or pedestal fans enhances the cooling effect by three times compared to using fans alone. We extrapolated our experimental findings to estimate heating and cooling effects in two historical case studies: the 2015 Pakistan heat wave and the 2021 Texas power crisis. Passive and low-energy strategies reduced sleep-time heat or cold exposure by 69–91%. The low-energy strategies we tested require one to two orders of magnitude less energy than HVAC systems, and the passive strategies require no energy input. These strategies can also help reduce peak load surges and total energy demand in extreme temperature events. This reduces the need for utility load shedding, which can put individuals at risk of hazardous heat or cold exposure. Our results may serve as a starting point for evidence-based public health guidelines on how individuals can sleep better during heat waves and cold snaps without relying on HVAC.
Recurrence plot embeddings as short segment nonlinear features for multimodal speaker identification using air, bone and throat microphones
Authors: Nawas K. Khadar , Shahina A. , Balachandar Keshav , Maadeshwaran P. , Devanathan N. G. , Kumar Navein , Khan A. Nayeemulla 
Published: May 2024

AbstractSpeech is produced by a nonlinear, dynamical Vocal Tract (VT) system, and is transmitted through multiple (air, bone and skin conduction) modes, as captured by the air, bone and throat microphones respectively. Speaker specific characteristics that capture this nonlinearity are rarely used as stand-alone features for speaker modeling, and at best have been used in tandem with well known linear spectral features to produce tangible results. This paper proposes Recurrent Plot (RP) embeddings as stand-alone, non-linear speaker-discriminating features. Two datasets, the continuous multimodal TIMIT speech corpus and the consonant-vowel unimodal syllable dataset, are used in this study for conducting closed-set speaker identification experiments. Experiments with unimodal speaker recognition systems show that RP embeddings capture the nonlinear dynamics of the VT system which are unique to every speaker, in all the modes of speech. The Air (A), Bone (B) and Throat (T) microphone systems, trained purely on RP embeddings perform with an accuracy of 95.81%, 98.18% and 99.74%, respectively. Experiments using the joint feature space of combined RP embeddings for bimodal (A–T, A–B, B–T) and trimodal (A–B–T) systems show that the best trimodal system (99.84% accuracy) performs on par with trimodal systems using spectrogram (99.45%) and MFCC (99.98%). The 98.84% performance of the B–T bimodal system shows the efficacy of a speaker recognition system based entirely on alternate (bone and throat) speech, in the absence of the standard (air) speech. The results underscore the significance of the RP embedding, as a nonlinear feature representation of the dynamical VT system that can act independently for speaker recognition. It is envisaged that speech recognition too will benefit from this nonlinear feature.