bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of alkaline earth metal doping on the structural, electronic, and optical properties of all inorganic lead-free CsSnX3 (X = I, Br) perovskites: a first-principles study
Authors: Saikia Dibyajyoti , Alam Mahfooz , Betal Atanu , Das Chayan , Gandi Appala Naidu , Sahu Satyajit 
Published: December 2023

Abstract
Recently, researchers have focused on developing more stable, Pb-free perovskites with improved processing efficiency and notable light harvesting ability. In this regard, Sn-based (Sn-b) perovskites have gained considerable interest in developing eco-friendly perovskite solar cells (PSCs). However, the oxidation of Sn2+ to Sn4+ deteriorates the performance of Sn-b PSCs. Nevertheless, this issue could be mitigated by doping alkaline earth (AE) metal. Herein, we have studied the significance of AE doping on CsSnX3 (X = Br, I) perovskites using density functional theory based calculations. The structural, electronic, and optical properties of CsAE
y
Sn1−y
X3 (y = 0, 0.25; AE = Be, Mg, Ca, Sr) compounds were systematically investigated to explore potential candidate materials for photovoltaic applications. Formation energy calculations suggested that the synthesis of other AE-doped compounds is energetically favorable except for the Be-doped compounds. The band gaps of the materials were calculated to be in the range of 0.12–1.02 eV using the generalized gradient approximation. Furthermore, the AE doping considerably lowers the exciton binding energy while remarkably enhancing the optical absorption of CsSnX3, which is beneficial for solar cells. However, in the case of Be and Mg doping, an indirect band gap is predicted. Our theoretical findings demonstrate the potential of executing AE-doped perovskites as absorber material in PSCs, which could deliver better performance than pristine CsSnX3 PSCs.
Robot motion visual measurement based on RANSAC and weighted constraints method
Authors: Wu Lulu , Deng Xianglin , Wang Yuan , Du Xin , Jiang Benchi 
Published: December 2023

Abstract
Precision of the coordinate transformation model parameters is crucial for the accuracy of the vision-based robot spatial motion measurement method. In this work, an optimization algorithm integrating RANSAC and iterative weighted singular value decomposition (IR-SVD) is proposed for improving the coordinate transformation model solution precision, aiming at enhancing the spatial motion measurement accuracy of the binocular vision system. Considering noises existing in reference transformation point pairs, the RANSAC algorithm is introduced to filter the raw measurement point pairs and extract inliers, thereby eliminating potential gross errors and realizing the cluster of advantageous points. An enhanced SVD method based on iterative weighted constraints is proposed to substitute traditional SVD. After calculating the coordinate transformation model parameters, the measurement errors of inliers are solved synchronously, and the weights are reallocated in light of the measurement errors value, subsequently recalculating the coordinate transformation model parameters repeatedly until the errors converge. The validation experiments are conducted on the self-built three-degree-of-freedom rectangular coordinate robot platform. The experimental results of discrete point-to-point motion and continuous trajectory motion measurement show that the proposed method can improve the coordinate transformation model parameters solution accuracy effectively, comparing with the traditional SVD method. Comparative experiment with existing commonly used coordinate transformation methods including Quaternion and iterative closest point indicates that the proposed method exhibits the best applicability and minimal errors in robot motion visual measurement. Both accuracy of the coordinate transformation model solution and the visual system’s motion measurement are enhanced with this newly-proposed, optimized method.
High-performance monolayer MoS2 nanosheet GAA transistor
Authors: Chou Bo-Jhih , Chung Yun-Yan , Yun Wei-Sheng , Hsu Chen-Feng , Li Ming-Yang , Su Sheng-Kai , Liew San-Lin , Hou Vincent Duen-Huei , Chen Chien-Wei , Kei Chi-Chung , Shen Yun-Yang , Chang Wen-Hao , Lee T Y , Cheng Chao-Ching , Radu Iuliana P , Chien Chao-Hsin 
Published: December 2023

Abstract
In this article, a 0.7 nm thick monolayer MoS2 nanosheet gate-all-around field effect transistors (NS-GAAFETs) with conformal high-κ metal gate deposition are demonstrated. The device with 40 nm channel length exhibits a high on-state current density of ~410 μA μm−1 with a large on/off ratio of 6 × 108 at drain voltage = 1 V. The extracted contact resistance is 0.48 ± 0.1 kΩ μm in monolayer MoS2 NS-GAAFETs, thereby showing the channel-dominated performance with the channel length scaling from 80 to 40 nm. The successful demonstration of device performance in this work verifies the integration potential of transition metal dichalcogenides for future logic transistor applications.
In vivo characterization of the optical and hemodynamic properties of the human sternocleidomastoid muscle through ultrasound-guided hybrid near-infrared spectroscopies
Authors: Cortese Lorenzo , Fernández Esteberena Pablo , Zanoletti Marta , Lo Presti Giuseppe , Aranda Velazquez Gloria , Ruiz Janer Sabina , Buttafava Mauro , Renna Marco , Di Sieno Laura , Tosi Alberto , Dalla Mora Alberto , Wojtkiewicz Stanislaw , Dehghani Hamid , de Fraguier Sixte , Nguyen-Dinh An , Rosinski Bogdan , Weigel Udo M , Mesquida Jaume , Squarcia Mattia , Hanzu Felicia A , Contini Davide , Mora Porta Mireia , Durduran Turgut 
Published: December 2023

Abstract

Objective. In this paper, we present a detailed in vivo characterization of the optical and hemodynamic properties of the human sternocleidomastoid muscle (SCM), obtained through ultrasound-guided near-infrared time-domain and diffuse correlation spectroscopies. Approach. A total of sixty-five subjects (forty-nine females, sixteen males) among healthy volunteers and thyroid nodule patients have been recruited for the study. Their SCM hemodynamic (oxy-, deoxy- and total hemoglobin concentrations, blood flow, blood oxygen saturation and metabolic rate of oxygen extraction) and optical properties (wavelength dependent absorption and reduced scattering coefficients) have been measured by the use of a novel hybrid device combining in a single unit time-domain near-infrared spectroscopy, diffuse correlation spectroscopy and simultaneous ultrasound imaging. Main results. We provide detailed tables of the results related to SCM baseline (i.e. muscle at rest) properties, and reveal significant differences on the measured parameters due to variables such as side of the neck, sex, age, body mass index, depth and thickness of the muscle, allowing future clinical studies to take into account such dependencies. Significance. The non-invasive monitoring of the hemodynamics and metabolism of the sternocleidomastoid muscle during respiration became a topic of increased interest partially due to the increased use of mechanical ventilation during the COVID-19 pandemic. Near-infrared diffuse optical spectroscopies were proposed as potential practical monitors of increased recruitment of SCM during respiratory distress. They can provide clinically relevant information on the degree of the patient's respiratory effort that is needed to maintain an optimal minute ventilation, with potential clinical application ranging from evaluating chronic pulmonary diseases to more acute settings, such as acute respiratory failure, or to determine the readiness to wean from invasive mechanical ventilation.
Influence of ‘period four’ transition metal doping in graphene on adsorption and transduction characteristics for CO gas- A detailed ab-initio perspective
Authors: Tiwari Aditya , Bahadursha Naresh , Chakraborty Sudipta , Kanungo Sayan 
Published: December 2023

Abstract
This work analyses the comparative effects of period-four transition metal (TM) dopants for CO molecular adsorption on the monolayer Graphene (Gr) supercell using the density functional theory (DFT) based ab initio method for the first time. Ten different TM dopant species (Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cr, Zn) have been incorporated and extensively studied in the context of Carbon Monoxide (CO) adsorption. The study elaborates on the effects of metallic doping in Gr on structural stability, electronic properties, adsorption strength, transduction efficacy, and CO recovery time. The study reveals that introducing each period-four TM dopant in the Gr lattice changes the semi-metallic nature, wherein distinct modulations in the energy band structure and the total density of state profiles can be observed after CO adsorption in each doped Gr matrix. The C atom of the polar CO molecule preferentially adsorbed on the doped TM, forming physical C-X (X: metal) bonds and resulting in slight vertical displacement of the dopant towards adsorbed CO. The results exhibit that depending on the strength of CO adsorption, the metallic dopants can be placed in the following order: Ti > V > Cr > Mn > Fe > Co > Ni > Cu > Zn > Sc, with a significant improvement in charge transfer during CO adsorption after Sc, Co, Ni, V, and Zn doping in Gr. Specifically, the Ni, Zn, and Sc-doped Gr ensures an efficient trade-off between adsorption stability and recovery time with high selectivity in CO2 and N2 environments.
Theoretical study on the structural, electronic, mechanical, vibrational, thermodynamical, and optical properties of the two-dimensional PbC nanomaterials
Authors: Muñoz H , Escamilla R O , Cervantes J M , León-Flores J , Romero M , Arévalo-López E P , Carvajal E , Escamilla R 
Published: December 2023

Abstract
Two-dimensional structures have attracted attention for application in nanoelectronics and optical devices; then, in this work, we are reporting the predicted physical properties (from first-principles calculations) for the two-dimensional PbC systems. Those physical properties reveal that the PbC monolayers (M-PbCs) in crystallographic planes (111) and (100); moreover, the PbC2 structures (paramagnetic and anisotropic compounds) are thermodynamical, structural, and mechanically stable but energetically and dynamically unstable at T = 0 K. However, the PbC2 non-magnetic (NM) is the most stable system at high temperatures. The M-PbCs exhibit sp

2
hybridization while the PbC2 NM shows sp

3

d

2
hybridization, forming a hexagonal lattice; meanwhile, the strong interaction at the C’s double bond in the PbC2 ferro and antiferromagnetic configurations (MAG) generates a rectangular lattice. These systems are ductile materials; however, the PbC2 (with metallic bonds) is more ductile than the M-PbCs due to the pronounced participation of the Pb 6p-orbitals. The M-PbCs have associated greater values for the hardness (than those for the PbC2 systems), but at high temperatures, the PbC2 MAG exhibits the highest mechanical resistance. The calculated optical data show that the M-PbCs and the PbC2 NM are promising as refractory materials. At the same time, the PbC2 MAG could be helpful in optical and optoelectronic devices capable of operating in the low frequencies of the UV region and in the infrared and visible regions.
Quantum gate-assisted teleportation in noisy environments: robustness and fidelity improvement
Authors: Harraz Sajede , Zhang Jiaoyang , Cong Shuang 
Published: December 2023

Abstract
Quantum teleportation as the key strategy for quantum communication requires pure maximally shared entangled states among quantum nodes. In practice, quantum decoherence drastically degrades the shared entanglement during entanglement distribution, which is a serious challenge for the development of quantum networks. However, most of the decoherence control strategies proposed thus far are either resource-intensive or time-consuming. To overcome this obstacle, we enable noise-resistant teleportation through a noisy channel with a limited number of qubits and without applying time-consuming weak measurements. We apply a quantum gate control unit consisting of a controlled NOT gate and a rotation gate after the original teleportation protocol is accomplished. Furthermore, we demonstrate that a teleportation fidelity of unity is attainable when environment-assisted measurement is added to the proposed teleportation protocol via quantum gates. Moreover, we present an entanglement distribution process by employing the designed quantum gate control unit followed by the deterministic standard teleportation protocol to improve teleportation fidelity by establishing improved shared entanglement. Our performance analysis indicates that the proposed teleportation schemes offer a competitive fidelity and success probability compared with the conventional schemes and a recent weak measurement-based teleportation protocol.
DROD: bio-robotic drill/sampler for planetary subterranean exploration: experiments and challenges
Authors: Alkalla Mohamed , Pitcher Craig 
Published: December 2023

Abstract
Key features for space exploration equipment, and in particular drills and sampling mechanisms, are low weight, small size, and energy efficiency. These characteristics are substantially required not only in reducing the spaceship flight cost, but also in extending the exploration time on the extraterrestrial bodies. This article experimentally investigates the feasibility of a novel drill bioinspired by wood-wasp and sand-fish lizard as an integrated robotic solution for rover exploration tasks. A new penetration depth of 820 mm in terms of reciprocation drilling technique has been achieved by the proposed dual reciprocation and oscillation drill (DROD), especially with the new enhancements such as miniature sample compartment and toothed stems. Additionally, a first sampling experiment with DROD has been performed and a sample amount of 20 g and size of 30 cm3 has been collected successfully. Finally, the article provides developments for integration of DROD with rovers for future exploration missions and potentials for horizontal drilling for subterranean applications.
Elevation-dependence of warming due to aerosol-induced snow darkening over the Himalayan-Tibetan region
Authors: Nair Vijayakumar S , Usha K H , Babu S Suresh 
Published: December 2023

Abstract
Temperature trends over the high-altitude mountains depict an increase with elevation during recent years. These stratified warming trends observed over the Himalayan-Tibetan (HT) regions are higher than the mean warming trends observed over low-elevation regions of South and East Asia, which is attributed to several factors including snow albedo feedback, clouds and water vapor feedback. In this study, we demonstrate the effects of deposition of absorbing aerosols like black carbon and dust on snow albedo and its implications for elevation-dependent warming (EDW). Though the aerosol concentration decreases with elevation, warming due to aerosol-induced snow darkening increases with elevation. Further, surface cooling due to the direct radiative effects (DRE) of aerosols is found to decrease with elevation, which also favors higher warming at high altitudes. The effects of both the deposition of absorbing aerosols on snow albedo and the surface cooling due to the DRE of atmospheric aerosols could strengthen EDW. This study clearly shows the potential of albedo feedback due to aerosol-cryosphere interaction as one of the physical mechanisms contributing to the observed EDW over the HT region.
Long-ranged spectral correlations in eigenstate phases
Authors: Prasad Mahaveer , Prakash Abhishodh , Pixley J H , Kulkarni Manas 
Published: December 2023

Abstract
We study non-local measures of spectral correlations and their utility in characterizing and distinguishing between the distinct eigenstate phases of quantum chaotic and many-body localized systems. We focus on two related quantities, the spectral form factor and the density of all spectral gaps, and show that they furnish unique signatures that can be used to sharply identify the two phases. We demonstrate this by numerically studying three one-dimensional quantum spin chain models with (i) quenched disorder, (ii) periodic drive (Floquet), and (iii) quasiperiodic detuning. We also clarify in what ways the signatures are universal and in what ways they are not. More generally, this thorough analysis is expected to play a useful role in classifying phases of disorder systems.
Environmental and occupational exposures and prognosis in patients with non–muscle-invasive bladder cancer in the Be-Well Study
Authors: Wang Zinian , Kwan Marilyn L , Haque Reina , Pratt Rachel , Lee Valerie S , Roh Janise M , Ergas Isaac J , Cannavale Kimberly L , Loo Ronald K , Aaronson David S , Quesenberry Charles P , Ambrosone Christine B , Kushi Lawrence H , Tang Li 
Published: December 2023

Abstract
Bladder cancer is primarily diagnosed as non–muscle-invasive bladder cancer (NMIBC), with high recurrence and progression rates. Environmental and occupational exposures to carcinogens are well-known risk factors for developing bladder cancer, yet their effects on prognosis remain unknown. In the Be-Well Study, a population-based prospective cohort study of 1472 Kaiser Permanente patients newly diagnosed with NMIBC in California from 2015 to 2019, we examined history of environmental and occupational exposures in relation to tumor stage and grade at initial diagnosis by multivariable logistic regression, and subsequent recurrence and progression by Cox proportional hazards regression. Exposure to environmental and occupational carcinogens was significantly associated with increased risk of progression (hazard ratio (HR) = 1.79; 95% CI, 1.04-3.09), specifically with increased progression to muscle-invasive disease (HR = 2.28; 95% CI, 1.16-4.50). Exposures to asbestos and arsenic were associated with increased odds of advanced stage at diagnosis (asbestos: odds ratio (OR) = 1.43 [95% CI, 1.11-1.84]; arsenic: OR = 1.27 [95% CI, 1.01-1.63]), and formaldehyde exposure was associated with increased risk of recurrence (HR = 1.38; 95% CI, 1.12-1.69). Our findings suggest that considering a patient’s history of these exposures may benefit current risk stratification systems in better tailoring clinical care and improving prognosis among patients with NMIBC.
Advancing the accuracy of SARS-CoV-2 phosphorylation site detection via meta-learning approach
Authors: Pham Nhat Truong , Phan Le Thi , Seo Jimin , Kim Yeonwoo , Song Minkyung , Lee Sukchan , Jeon Young-Jun , Manavalan Balachandran 
Published: December 2023

Abstract
The worldwide appearance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has generated significant concern and posed a considerable challenge to global health. Phosphorylation is a common post-translational modification that affects many vital cellular functions and is closely associated with SARS-CoV-2 infection. Precise identification of phosphorylation sites could provide more in-depth insight into the processes underlying SARS-CoV-2 infection and help alleviate the continuing COVID-19 crisis. Currently, available computational tools for predicting these sites lack accuracy and effectiveness. In this study, we designed an innovative meta-learning model, Meta-Learning for Serine/Threonine Phosphorylation (MeL-STPhos), to precisely identify protein phosphorylation sites. We initially performed a comprehensive assessment of 29 unique sequence-derived features, establishing prediction models for each using 14 renowned machine learning methods, ranging from traditional classifiers to advanced deep learning algorithms. We then selected the most effective model for each feature by integrating the predicted values. Rigorous feature selection strategies were employed to identify the optimal base models and classifier(s) for each cell-specific dataset. To the best of our knowledge, this is the first study to report two cell-specific models and a generic model for phosphorylation site prediction by utilizing an extensive range of sequence-derived features and machine learning algorithms. Extensive cross-validation and independent testing revealed that MeL-STPhos surpasses existing state-of-the-art tools for phosphorylation site prediction. We also developed a publicly accessible platform at https://balalab-skku.org/MeL-STPhos. We believe that MeL-STPhos will serve as a valuable tool for accelerating the discovery of serine/threonine phosphorylation sites and elucidating their role in post-translational regulation.
CellTICS: an explainable neural network for cell-type identification and interpretation based on single-cell RNA-seq data
Authors: Yin Qingyang , Chen Liang 
Published: December 2023

Abstract
Identifying cell types is crucial for understanding the functional units of an organism. Machine learning has shown promising performance in identifying cell types, but many existing methods lack biological significance due to poor interpretability. However, it is of the utmost importance to understand what makes cells share the same function and form a specific cell type, motivating us to propose a biologically interpretable method. CellTICS prioritizes marker genes with cell-type-specific expression, using a hierarchy of biological pathways for neural network construction, and applying a multi-predictive-layer strategy to predict cell and sub-cell types. CellTICS usually outperforms existing methods in prediction accuracy. Moreover, CellTICS can reveal pathways that define a cell type or a cell type under specific physiological conditions, such as disease or aging. The nonlinear nature of neural networks enables us to identify many novel pathways. Interestingly, some of the pathways identified by CellTICS exhibit differential expression “variability” rather than differential expression across cell types, indicating that expression stochasticity within a pathway could be an important feature characteristic of a cell type. Overall, CellTICS provides a biologically interpretable method for identifying and characterizing cell types, shedding light on the underlying pathways that define cellular heterogeneity and its role in organismal function. CellTICS is available at https://github.com/qyyin0516/CellTICS.
A Bayesian multivariate factor analysis model for causal inference using time-series observational data on mixed outcomes
Authors: Samartsidis Pantelis , Seaman Shaun R , Harrison Abbie , Alexopoulos Angelos , Hughes Gareth J , Rawlinson Christopher , Anderson Charlotte , Charlett André , Oliver Isabel , De Angelis Daniela 
Published: December 2023

Summary
Assessing the impact of an intervention by using time-series observational data on multiple units and outcomes is a frequent problem in many fields of scientific research. Here, we propose a novel Bayesian multivariate factor analysis model for estimating intervention effects in such settings and develop an efficient Markov chain Monte Carlo algorithm to sample from the high-dimensional and nontractable posterior of interest. The proposed method is one of the few that can simultaneously deal with outcomes of mixed type (continuous, binomial, count), increase efficiency in the estimates of the causal effects by jointly modeling multiple outcomes affected by the intervention, and easily provide uncertainty quantification for all causal estimands of interest. Using the proposed approach, we evaluate the impact that Local Tracing Partnerships had on the effectiveness of England’s Test and Trace programme for COVID-19.