bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nonadiabatic simulations of photoisomerization and dissociation in ethylene using ab initio classical trajectories
Authors: Miyazaki K. , Ananth N. 
Published: September 2023

We simulate the nonadiabatic dynamics of photo-induced isomerization and dissociation in ethylene using ab initio classical trajectories in an extended phase space of nuclear and electronic variables. This is achieved by employing the linearized semiclassical initial value representation method for nonadiabatic dynamics, where discrete electronic states are mapped to continuous classical variables using either the Meyer–Miller–Stock–Thoss representation or a more recently introduced spin mapping approach. Trajectory initial conditions are sampled by constraining electronic state variables to a single initial excited state and by drawing nuclear phase space configurations from a Wigner distribution at a finite temperature. An ensemble of classical ab initio trajectories is then generated to compute thermal population correlation functions and analyze the mechanisms of isomerization and dissociation. Our results serve as a demonstration that this parameter-free semiclassical approach is computationally efficient and accurate, identifying mechanistic pathways in agreement with previous theoretical studies and also uncovering dissociation pathways observed experimentally.
Bandgaps of long-period polytypes of IV, IV-IV, and III-V semiconductors estimated with an Ising-type additivity model
Authors: Ramakrishnan Raghunathan , Jain Shruti 
Published: September 2023

We apply an Ising-type model to estimate the bandgaps of the polytypes of group IV elements (C, Si, and Ge) and binary compounds of groups: IV–IV (SiC, GeC, and GeSi), and III–V (nitride, phosphide, and arsenide of B, Al, and Ga). The models use reference bandgaps of the simplest polytypes comprising 2–6 bilayers calculated with the hybrid density functional approximation, HSE06. We report four models capable of estimating bandgaps of nine polytypes containing 7 and 8 bilayers with an average error of ≲0.05 eV. We apply the best model with an error of &lt;0.04 eV to predict the bandgaps of 497 polytypes with up to 15 bilayers in the unit cell, providing a comprehensive view of the variation in the electronic structure with the degree of hexagonality of the crystal structure. Within our enumeration, we identify four rhombohedral polytypes of SiC—9R, 12R, 15R(1), and 15R(2)—and perform detailed stability and band structure analysis. Of these, 15R(1) that has not been experimentally characterized has the widest bandgap (&gt;3.4 eV); phonon analysis and cohesive energy reveal 15R(1)-SiC to be metastable. Additionally, we model the energies of valence and conduction bands of the rhombohedral SiC phases at the high-symmetry points of the Brillouin zone and predict band structure characteristics around the Fermi level. The models presented in this study may aid in identifying polytypic phases suitable for various applications, such as the design of wide-gap materials, that are relevant to high-voltage applications. In particular, the method holds promise for forecasting electronic properties of long-period and ultra-long-period polytypes for which accurate first-principles modeling is computationally challenging.
Non-uniform orientation of H2 molecules in a magnetic field as a critical condition for the appearance of partially negative NMR lines of o-H2 in hyperpolarization experiments using p-H2
Authors: Bernatowicz P. , Ratajczyk T. , Szymański S. 
Published: September 2023

In hyperpolarization experiments using parahydrogen, a partially negative line (PNL) of o-H2 is occasionally spotted in the nuclear magnetic resonance (NMR) spectra. This is a manifestation of the two-spin order (TSO) of the proton spins, appearing transiently in o-H2 molecules freshly derived from p-H2. For the TSO to be observable, the o-H2 NMR signal must be split into a doublet. In the literature, the splitting is believed to originate from a slow exchange of the dissolved dihydrogen with the dihydride moiety bound to a catalyst present in the reaction mixture. Because this hypothesis may be debatable, in this work a different splitting mechanism is proposed. It employs a residual dipolar coupling (RDC) between the hydrogen protons, originating from a partial orientation of the H2 molecules by the external magnetic field. The orientation effect is due to the anisotropic magnetic polarizability of H2. In a magnetic field of 11.74 T at room temperature, the currently predicted value of the RDC is −0.0024 Hz. Even such small RDC values are sufficient for the PNL effect to be clearly visible in NMR spectra for physically reasonable levels of the TSO in the o-H2 molecules. For RDC values much smaller than the natural linewidth of o-H2, the theoretical frequency distance between the minimum and maximum of PNL proves to be practically independent of the RDC and is of the order of the linewidth. The calculated amplitudes of the PNLs are proportional to the RDC values used in the calculations.
A new generation of non-diagonal, renormalized self-energies for calculation of electron removal energies
Authors: Opoku Ernest , Pawłowski Filip , Ortiz J. V. 
Published: September 2023

A new generation of diagonal self-energies for the calculation of electron removal energies of molecules and molecular ions that has superseded its predecessors with respect to accuracy, efficiency, and interpretability is extended to include non-diagonal self-energies that permit Dyson orbitals to be expressed as linear combinations of canonical Hartree–Fock orbitals. In addition, an improved algorithm for renormalized methods eliminates the convergence difficulties encountered in the first studies of the new, diagonal self-energies. A dataset of outer-valence, vertical ionization energies with almost full-configuration-interaction quality serves as a standard of comparison in numerical tests. The new non-diagonal, renormalized methods are slightly more accurate than their diagonal counterparts, with mean absolute errors between 0.10 and 0.06 eV for outer-valence final states. This advantage is procured at the cost of an increase in the scaling of arithmetic bottlenecks that accompany the inclusion of non-diagonal self-energy terms. The new, non-diagonal, renormalized self-energies are also more accurate and efficient than their non-diagonal predecessors.
Fatal architectures and death by design: the infrastructures of state-sponsored climate disasters in Angola and Mozambique
Authors: Blanes Ruy Llera 
Published: September 2023

ABSTRACT
This article addresses how African states respond to climate crisis, arguing that, beyond the agency and impact of climate phenomena such as drought and cyclones, they are active participants in the production of climate disasters and emergencies, mostly through infrastructural processes that affect land and resource use, and subsequently livelihoods. To demonstrate this, it uses the cases of the drought in southwestern Angola and cyclones in northern and central Mozambique, where such climate phenomena have exposed ‘fatal architectures’ that have dramatically raised the toll of climate victims and refugees. Both extractivist, agro-industrial and hydroelectric projects, as well as other, more deferred infrastructural designs (roads, communication networks, etc.) have challenged the traditional agency and resilience of local communities. Such new infrastructural projects also illustrate how certain perceived long-term solutions to address the climate crisis with industrial and energy reconversion towards greener energies can still become fatal architectures in the context of climate emergencies.
GiftBTE: an efficient deterministic solver for non-gray phonon Boltzmann transport equation
Authors: Hu Yue , Jia Ru , Xu Jiaxuan , Sheng Yufei , Wen Minhua , Lin James , Shen Yongxing , Bao Hua 
Published: September 2023

Abstract
Advances in nanotechnology have facilitated the exploration of submicron thermal transport. At this scale, Fourier’s law is no longer applicable, and the governing equation for thermal transport is the phonon Boltzmann transport equation (BTE). However, the availability of open-source solvers for the phonon BTE is limited, impeding progress in this field. This study introduces an open-source package, GiftBTE, for numerically solving the non-gray phonon BTE. GiftBTE employs deterministic solutions and provides both steady-state and transient solvers. For the steady-state solver, GiftBTE employs the implicit discrete ordinates method (DOM) with second-order spatial accuracy and the synthetic iterative scheme. For the transient solver, GiftBTE employs the explicit DOM with second-order spatial accuracy. This package demonstrates excellent computational efficiency, enabling realistic three-dimensional simulations of devices and materials. By interfacing with first-principles calculations, this solver enables parameter-free computation of submicron thermal transport. The application of GiftBTE includes, but is not limited to, computing the thermal conductivity of nanostructures, predicting temperature rises in transistors, and simulating laser heating processes.
Multiple-order singularity expansion method
Authors: Ben Soltane I , Colom R , Dierick F , Stout B , Bonod N 
Published: September 2023

Abstract
Physical systems and signals are characterized by complex functions of the frequency in the harmonic domain. The extension of such functions to the complex frequency plane, and in particular expansions and factorized forms of the harmonic-domain functions in terms of their poles and zeros, is of high interest to describe the physical properties of a system, and study its response dynamics in the temporal and harmonic domains. In this work, we start from a general property of continuity and differentiability of the complex functions to derive the multiple-order singularity expansion method. We rigorously derive the common singularity and zero expansion and factorization expressions, and generalize them to the case of singularities of arbitrary order, while deducing the behavior of these complex frequencies from the simple hypothesis that we are dealing with physically realistic signals.
Socially Acquired Nocebo Effects Generalize but Are Not Attenuated by Choice
Authors: Saunders Cosette , Colagiuri Ben , Barnes Kirsten 
Published: September 2023

Abstract

Background
Socially observing a negative treatment-related experience has been shown to modulate our own experience with the same intervention, leading to worsened health outcomes. However, whether this social learning generalizes to similar but distinct interventions has not been explored nor what manipulations can reduce these effects.

Purpose
To determine whether socially acquired nocebo effects can be generated by observing a negative experience with a similar, but distinct intervention, and whether choice can reduce these effects.

Methods
Across three experiments, a community sample of healthy adults (N = 336) either watched a confederate report cybersickness to the same Virtual Reality (VR) activity they were assigned to (Social Modeling: Consistent); a similar, but different VR activity (Social Modeling: Inconsistent); or did not view the confederate (No Social Modeling). Participants were either given choice over the VR (Choice) or assigned by the experimenter (No Choice).

Results
Across the experiments, there was significantly greater cybersickness in both Social Modeling groups relative to No Social Modeling, while the two Social Modeling groups did not differ. There was no significant effect of Choice or a Choice by Social Modeling interaction. Social Modeling elicited greater anxiety and expectancies for cybersickness. Furthermore, these mechanisms mediated the association between social modeling and cybersickness.

Conclusions
Socially acquired side-effects were demonstrated to generalize to similar, but distinct interventions, highlighting the diffuse and robust effect social modeling can have on our experiences. However, choice did not attenuate the experience of cybersickness, highlighting the need for alternative methods to counteract the effect of social modeling.
Simulating structurally variable nuclear pore complexes for microscopy
Authors: Theiss Maria , Hériché Jean-Karim , Russell Craig , Helekal David , Soppitt Alisdair , Ries Jonas , Ellenberg Jan , Brazma Alvis , Uhlmann Virginie 
Published: September 2023

Abstract

Motivation
The nuclear pore complex (NPC) is the only passageway for macromolecules between nucleus and cytoplasm, and an important reference standard in microscopy: it is massive and stereotypically arranged. The average architecture of NPC proteins has been resolved with pseudoatomic precision, however observed NPC heterogeneities evidence a high degree of divergence from this average. Single-molecule localization microscopy (SMLM) images NPCs at protein-level resolution, whereupon image analysis software studies NPC variability. However, the true picture of this variability is unknown. In quantitative image analysis experiments, it is thus difficult to distinguish intrinsically high SMLM noise from variability of the underlying structure.

Results
We introduce CIR4MICS (‘ceramics’, Configurable, Irregular Rings FOR MICroscopy Simulations), a pipeline that synthesizes ground truth datasets of structurally variable NPCs based on architectural models of the true NPC. Users can select one or more N- or C-terminally tagged NPC proteins, and simulate a wide range of geometric variations. We also represent the NPC as a spring-model such that arbitrary deforming forces, of user-defined magnitudes, simulate irregularly shaped variations. Further, we provide annotated reference datasets of simulated human NPCs, which facilitate a side-by-side comparison with real data. To demonstrate, we synthetically replicate a geometric analysis of real NPC radii and reveal that a range of simulated variability parameters can lead to observed results. Our simulator is therefore valuable to test the capabilities of image analysis methods, as well as to inform experimentalists about the requirements of hypothesis-driven imaging studies.

Availability and implementation
Code: https://github.com/uhlmanngroup/cir4mics. Simulated data: BioStudies S-BSST1058.
Splicing transcriptome-wide association study to identify splicing events for pancreatic cancer risk
Authors: Liu Duo , Bae Ye Eun , Zhu Jingjing , Zhang Zichen , Sun Yanfa , Deng Youping , Wu Chong , Wu Lang 
Published: September 2023

Abstract
A large proportion of the heritability of pancreatic cancer risk remains elusive, and the contribution of specific mRNA splicing events to pancreatic cancer susceptibility has not been systematically evaluated. In this study, we performed a large splicing transcriptome-wide association study (spTWAS) using three modeling strategies (Enet, LASSO and MCP) to develop alternative splicing genetic prediction models for identifying novel susceptibility loci and splicing introns for pancreatic cancer risk by assessing 8275 pancreatic cancer cases and 6723 controls of European ancestry. Data from 305 subjects of whom the majority are of European descent in the Genotype-Tissue Expression Project (GTEx) were used and both cis-acting and promoter–enhancer interaction regions were considered to build these models. We identified nine splicing events of seven genes (ABO, UQCRC1, STARD3, ETAA1, CELA3B, LGR4 and SFT2D1) that showed an association of genetically predicted expression with pancreatic cancer risk at a false discovery rate ≤0.05. Of these genes, UQCRC1 and LGR4 have not yet been reported to be associated with pancreatic cancer risk. Fine-mapping analyses supported likely causal associations corresponding to six splicing events of three genes (P4HTM, ABO and PGAP3). Our study identified novel genes and splicing events associated with pancreatic cancer risk, which can improve our understanding of the etiology of this deadly malignancy.
Effects of BNT162b2 Messenger RNA Vaccine and ChAdOx1 Adenovirus Vector Vaccine on Deaths From COVID-19 in Adults Aged ≥70 Years
Authors: Lopez Bernal Jamie , Andrews Nick , Gower Charlotte , Stowe Julia , Tessier Elise , Simmons Ruth , Ramsay Mary 
Published: September 2023

Abstract
We estimated the risk of death from coronavirus disease 2019 in vaccinated compared with unvaccinated patients. The risk of death was reduced 44% after 1 dose of the Pfizer-BioNTech BNT162b2 vaccine, 55% after 1 dose of the Oxford-Astrazeneca ChAdOx1 vaccine, and 69% after 2 doses of the BNT162b2 vaccine. This is above the protection provided against infection.
A-030 Indicators Generated from Salivary Cortisol Measurement to Assess Circadian Rhythm: Comparison of Immunoassay and Liquid Chromatography-Tandem Mass Spectrometry
Authors: Lee A , Jang S , Kim J , Jang J , Kim I , Lee S , Seok J 
Published: September 2023

Abstract

Background
Salivary cortisol is considered a reliable alternative to serum-free cortisol for evaluating hypothalamic-pituitary-adrenal axis rhythmicity. Its advantages include free hormone measurement, non-invasiveness, precision, and cost-effectiveness. Several cortisol indicators in serially collected saliva have been used in research studies to evaluate the circadian rhythm. We aimed to find if the distribution of those indicators is affected by the specific assay platform used.

Methods
Four-time points of saliva specimens were obtained immediately after awakening, 30 min and 60 min post-awakening, and in the nighttime from 49 subjects (aged between 19 and 25, mean ± SD: 28.9 ± 8.4 years). Salivary cortisol was analyzed by ELISA method using the Cortisol Saliva ELISA kit (IBL, Hamburg, Germany). Liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay was performed on the API 4000 triple quadrupole mass spectrometer coupled with an Agilent 1200 liquid chromatography system. Four cortisol indicators (DCS (diurnal cortisol slope), CARi (cortisol awakening response by an absolute increase within 30 min of awakening), AUCg (area under the curve with respect to ground), and AUCi (AUC with respect to increasing)) were calculated from each patient by the method. Correlation between the two methods was evaluated for overall cortisol concentrations, DCS, CARi, AUCg, and AUCi.

Results
The cortisol concentrations between the two methods strongly correlated (r = 0.973) but with a mean bias of 3.4 nmol/L (95% CI −3.8 to −2.9). Four cortisol indicators strongly correlated between the two methods, but showed significant differences. DCS data generated from LC-MS/MS measurement was more broadly distributed than those from ELISA. On the contrary, CARi data generated from ELISA measurement dispersed more than those from LC-MS/MS.

Conclusion
The concentrations of salivary cortisol strongly correlated between ELISA and LC-MS/MS, though considerable proportional bias between the two methods. The cortisol indicators generated from different methods can affect its distribution, therefore possibly affecting its discrimination power.
A-031 Global Discovery of Serological Metabolome Uncovers Unique Molecular Signature for Early Onset of Type 2 Diabetes Mellitus: A Retrospective Study in Chinese Population
Authors: Zhu L , Wu Y 
Published: September 2023

Abstract

Background
Type 2 diabetes mellitus (T2DM) is a multifaceted disorder affecting epidermic proportion at global scope. Defective insulin secretion by pancreatic β-cells and the inability of insulin-sensitive tissues to respond appropriately to insulin are the primary causes of T2DM. Early detection of people at high risk of developing T2DM is of great importance as interventions such as dietary control and intentional weight loss can effectively improve the insulin sensitivity and prevent the disease incidence. However, circulating biomarkers that are indicative of early diabetic onset at asymptomatic stage have not been well described. Here, we aim to identify new serological markers indicating early asymptomatic onset of T2DM by MS-based metabolomic discovery.

Methods
Three independent cohorts were assembled for the study. The discovery cohort included sera from 25 patients with T2DM and 25 healthy controls. The validation cohort included sera from 15 patients with T2DM and 15 healthy controls. The testing cohort included sera from 111 patients with pre-diabetes and 89 healthy controls. Untargeted approach was used to characterize the serological metabolome by high performance liquid chromatography-high resolution mass spectrometry.

Results
The univariate analysis identified 11 metabolites that were significantly altered in patients with T2DM across discovery and validation cohorts. After evaluated by the testing cohort, 8 of 11 metabolites, such as hexose, N-acetyl-glucosamine, and alpha-ketobutyrate, remained statistically significant in patients with prediabetes as compared to healthy controls. The multivariate analysis based on 8 significant metabolites revealed distinct patterns of metabolic perturbation at the early onset of T2DM. To gain mechanistic insights into the disease pathophysiology, pathway enrichment and correlation network analyses were conducted to unveil the molecular crosstalk underlying the disturbed metabolic network in the pathogenesis of T2DM.

Conclusion
Our study not only identified serological biomarkers detecting early asymptomatic onset of T2DM but also provided additional insights into the disease pathophysiology.
A-087 Relationship among Different Inflammatory Markers in Patients with COVID-19 Infections
Authors: Yadav R , Chopra P , Sehgal T , Datta S K , Ningombam A , Ahirwar A 
Published: September 2023

Abstract

Introduction
Acute phase reactants (APRs) are inflammation biomarkers that exhibit significant changes in their serum concentrations due to infectious and noninfectious conditions. APRs such as C-reactive protein (CRP), Interleukin-6 (IL-6), Ferritin, Lactate dehydrogenase (LDH); coagulation biomarkers such as D-dimer, Fibrinogen; cardiac biomarkers such as Creatine kinase-MB (CK-MB), and hematological biomarkers such as Neutrophil to Lymphocyte ratio (NLR) have been used extensively during the COVID-19 pandemic for early diagnosis, monitoring of response to treatment and prognostication. Amongst these, CRP, although a non-specific marker of inflammation has been widely used in COVID-19 patients.

Objectives
In this study, we tried to evaluate the relationship of the other markers like IL-6, Ferritin, LDH, D-dimer, Fibrinogen, CK-MB and NLR with CRP levels in COVID-19 patients.

Methods
This cross-sectional study was carried out in a tertiary care hospital, New Delhi India, July 2020 to Dec 2020. Total 282 adults, confirmed COVID positive by RT-PCR were included in the study. The investigations were performed on day 0 or day 1 of COVID positivity. Correlation of CRP with other markers was studied by regression analysis using Minitab ver.17.

Results
Among the 282 patients, gender distribution was 190 males to 92 females with an average age of 52.5 ± 15.1 years. All the markers were observed to have non-parametric distribution. CRP was raised in 92.5% cases (n = 239), IL-6 in 83.2% (n = 279), Ferritin in 66.8% (n = 238), LDH in 99.1% (n = 233), D-dimer in 96.6% (n = 30), Fibrinogen in 68.4% (n = 19), CK-MB in 84.6% (n = 98) and NLR of more than 4 in 82.8% (n = 280). The median and range for the different markers were as follows: CRP (44.8 U/L; 15.6–736), IL-6 (67.3 pg/mL; 0.8–1624), LDH (608.0 U/L; 161–6705), Ferritin (643.5 ng/mL; 7.9–11 932), D-dimer (7 µg/mL; 0–5250), NLR (9.43; 0.05–157.17); Fibrinogen (475 mg/dL; 285–759) CK-MB (9.9 mg/L; 0.1–46.7) respectively. Significant correlation was not observed between CRP and any of the inflammatory markers.

Conclusion
Inflammatory markers are raised in most patients with COVID-19, however, all markers are not raised in all patients. Sequential evaluation of these markers may be beneficial rather than at one time point.