bluuebunny/crossref_metadata_2025_split huggingface dataset:
Refractive index measurement of hydrogen isotopologue mixture and applicability for homogeneity of hydrogen solid at cryogenic temperature in fusion fuel system
Authors: Zhang Jiaqi , Iwamoto Akifumi , Shigemori Keisuke , Hara Masanori , Yamanoi Kohei 
Published: April 2023

Abstract
Deuterium (D)-Tritium (T) nuclear fusion reaction has potential as an energy source in the future. In both magnetic confinement and inertial confinement fusion reactors, solid D–T will generally be supplied as fusion fuel. The efficiency of the nuclear fusion reaction depends on the quality of solid D–T fuel, which is related to the composition, homogeneity, helium-3 (3He) content, and so on. However, there is no technique for in-situ examination of solid D–T fuel. In this study, we consider a simple and precise method for the characterization of solid hydrogen isotopologues at cryogenic temperature using refractive index measurement, and evaluate the distribution of hydrogen isotopologue composition and homogeneity. To evaluate without the effect of tritium decay, the homogeneity of the hydrogen (H2)-deuterium (D2) mixture is measured at first. By the in-situ refractive index measurement at cryogenic temperature, the homogeneity of solid H2–D2 mixture is roughly quantified. The phase diagram of the H2–D2 mixture shows a solid solution type. D2-rich crystal first appears from the liquid phase as a primary crystal. The composition of D2 in liquid phase ias homogeneous, whereas it reduces by obeying the liquidus line in the phase diagram with the crystallization. On the other hand, the composition of the H2–D2 mixture in solid phase is inhomogeneous because the mobility of H2 and D2 in solid phase was too slow to be homogeneous and solid. The compositions of H2–D2 mixture in liquid and solid phases could be evaluated by the in-situ refractive index measurement in time. Consequently, the refractive index measurement shows great potential as an inspection method of solid D–T fuel in fusion reactors.
The antimicrobial efficacy of copper, cobalt, zinc and silver nanoparticles: alone and in combination
Authors: Raja Farah N S , Worthington Tony , Martin Richard A 
Published: April 2023

Abstract
With the advent of nanotechnology, there has been an extensive interest in the antimicrobial potential of metals. The rapid and widespread development of antimicrobial-resistant and multidrug-resistant bacteria has prompted recent research into developing novel or alternative antimicrobial agents. In this study, the antimicrobial efficacy of metallic copper, cobalt, silver and zinc nanoparticles was assessed against Escherichia coli (NCTC 10538), S. aureus (ATCC 6538) along with three clinical isolates of Staphylococcus epidermidis (A37, A57 and A91) and three clinical isolates of E. coli (Strains 1, 2 and 3) recovered from bone marrow transplant patients and patients with cystitis respectively. Antimicrobial sensitivity assays, including agar diffusion and broth macro-dilution to determine minimum inhibitory and bactericidal concentrations (MIC/MBC) and time-kill/synergy assays, were used to assess the antimicrobial efficacy of the agents. The panel of test microorganisms, including antibiotic-resistant strains, demonstrated a broad range of sensitivity to the metals investigated. MICs of the type culture strains were in the range of 0.625–5.0 mg ml−1. While copper and cobalt exhibited no difference in sensitivity between Gram-positive and Gram-negative microorganisms, silver and zinc showed strain specificity. A significant decrease (p < 0.001) in the bacterial density of E. coli and S. aureus was demonstrated by silver, copper and zinc in as little as two hours. Furthermore, combining metal nanoparticles reduced the time required to achieve a complete kill.
Monetary compensation for changing forest management practices to increase water availability in Georgia, United States
Authors: Bawa Ranjit , Colson Gregory , Dwivedi Puneet 
Published: April 2023

Abstract
Forests provide many ecological services, including carbon sequestration, biofuel provision, and recreation, yet the influence of forests on water resources is still often debated. While increased forest cover is generally associated with greater water quality, the value-added component of enhanced water services associated with reduced forest cover is less understood. At the same time, ensuring adequate water supplies remain a common goal of many natural resource managers due to growing concerns over freshwater security. This study derives a baseline of willingness-to-accept estimates to supply water flows by investigating the behavior of tree farm owners in Georgia, United States. Little is known about landowner preferences among incentives related to the adoption of different silvicultural practices to increase downstream water yields. A discrete choice experiment was designed to ascertain monetary compensation amounts required to alter established planting densities and thinning intensities likely to result in increased water yields. Results show that landowners may adopt such forest management strategies if appropriately compensated. Specifically, landowners on average, desired approximately $0.06 to $0.19 more per acre per year for every unit decrease in planting density. These are significant findings given that existing relevant stakeholders on the ‘consumer’ side may be ready and willing to fund such practices. We hope our study can contribute towards establishing market-based incentives for private forest landowners to encourage the conservation and improvement of forested watersheds in Georgia and beyond.
Entanglement generation through Markovian feed-back in open two-qubit systems
Authors: Benatti Fabio , Gebbia Francesca , Pisoni Stefano 
Published: April 2023

Abstract
We discuss the generation and the long-time persistence of entanglement in open two-qubit systems whose reduced dissipative dynamics is not a priori engineered but is instead subjected to filtering and Markovian feedback. In particular, we analytically study (1) whether the latter operations may enhance the environment capability of generating entanglement at short times and (2) whether the generated entanglement survives in the long-time regime. We show that, in the case of particularly symmetric Gorini–Kossakowski–Sudarshan–Lindblad it is possible to fully control the convex set of stationary states of the two-qubit reduced dynamics, therefore the asymptotic behaviour of any initial two-qubit state. We then study the impact of a suitable class of feed-back operations on the considered dynamics.
Understanding the chemistry of 2D rhodium trihalide solid solutions: tuning of optical properties and nanocrystal deposition
Authors: Froeschke Samuel , Schroth Karl-Georg , Steiner Udo , Popov Alexey , Schiemenz Sandra , Wolf Daniel , Giebeler Lars , Gräßler Nico , Büchner Bernd , Schmidt Peer , Hampel Silke 
Published: April 2023

Abstract
In the search for novel 2D materials with potentially valuable properties, such as a tunable band gap for optoelectronic or catalytic applications, solid solutions hold the potential to significantly expand the inventory of available 2D nanomaterials. In this study, we present for the first time the synthesis of such 2D rhodium trihalide solid solutions: RhBr
x
Cl3−x
and RhBr
x
I3−x
. We use thermodynamic simulations and simultaneous thermal analysis to predict conditions for their rational synthesis and to investigate suitable chemical vapor transport (CVT) parameters for these solid solutions. The evolution of the lattice parameters was investigated by powder x-ray diffraction, showing an isostructural relationship of the synthesized compounds and only minor deviation from Vegard’s law. The optical band gap of these materials can be tuned in an energy range from 1.5 eV (RhCl3) to 1.2 eV (RhI3) by choosing the composition of the solid solution, while the samples also exhibit photoluminescence in similar energy ranges. Ultimately, the successful deposition of bulk as well as ultrathin 2D nanocrystals of RhBr
x
Cl3−x
by CVT from 925 °C to 850 °C is shown, where the composition of the deposited crystals is precisely controlled by the choice of the starting composition and the initial amount of material. The high quality of the obtained nanocrystals is confirmed by atomic force microscopy, high resolution transmission electron microscopy and selected area electron diffraction. For RhBr
x
I3−x
, the CVT from 900 °C to 825 °C is more difficult and has only been practically demonstrated for an exemplary case. According to the observed properties, these novel solid solutions and nanocrystals show a great potential for an application in optoelectronic devices.
Closed-loop control of a noisy qubit with reinforcement learning
Authors: Ding Yongcheng , Chen Xi , Magdalena-Benedito Rafael , Martín-Guerrero José D 
Published: April 2023

Abstract
The exotic nature of quantum mechanics differentiates machine learning applications in the quantum realm from classical ones. Stream learning is a powerful approach that can be applied to extract knowledge continuously from quantum systems in a wide range of tasks. In this paper, we propose a deep reinforcement learning method that uses streaming data from a continuously measured qubit in the presence of detuning, dephasing, and relaxation. The model receives streaming quantum information for learning and decision-making, providing instant feedback on the quantum system. We also explore the agent’s adaptability to other quantum noise patterns through transfer learning. Our protocol offers insights into closed-loop quantum control, potentially advancing the development of quantum technologies.
Effectiveness of exercise on fall prevention in community-dwelling older adults: a 2-year randomized controlled study of 914 women
Authors: Rikkonen Toni , Sund Reijo , Koivumaa-Honkanen Heli , Sirola Joonas , Honkanen Risto , Kröger Heikki 
Published: April 2023

Abstract

Background
Communal exercise interventions may help prevent falls and injuries. However, pragmatic trials demonstrating the effectiveness of such strategies are sparse.

Methods
We determined whether a cost-free 12-month admission to the city’s recreational sports facilities including initial 6 months of supervised weekly gym and Tai Chi sessions decreases the number of falls and related injuries. The mean (SD) follow-up time was 22·6 (4.8) months in 2016–19. A total of 914 women from a population-based sample with a mean age of 76.5 (SD 3.3, range 71.1–84.8) years were randomized into exercise intervention (n = 457) and control (n = 457) groups. Fall information was collected through biweekly short message (SMS) queries and fall diaries. Altogether 1,380 falls were recorded for the intention-to-treat analysis, with 1,281 (92.8%) being verified by telephone.

Results
A 14.3% fall rate reduction was detected in the exercise group (Incidence rate ratio (IRR) = 0.86; CI 95% 0.77–0.95) compared with the control group. Approximately half of the falls caused moderate (n = 678, 52.8%) or severe (n = 61, 4.8%) injury. In total, 13.2% (n = 166) of falls (including 73 fractures) required medical consultation with a 38% lower fracture rate in the exercise group (IRR = 0.62; CI 95% 0.39–0.99). Overall, the greatest reduction of 41% (IRR = 0.59; CI 95% 0.36–0.99) was observed in falls with severe injury and pain.

Conclusions
A community-based approach for a 6-month exercise period combined with a 12-month free use of sports premises can reduce falls, fractures and other fall-related injuries in aging women.
Formation of phosphatidylethanol and ethylglucuronide after low to moderate alcohol consumption in volunteers with a previous three-week alcohol abstinence
Authors: Herzog Josefine , Skopp Gisela , Musshoff Frank , Hartung Benno 
Published: April 2023

Abstract

Aims
Phosphatidylethanol (PEth) is only formed when ethanol is present in blood. This direct alcohol marker has been widely discussed, including the minimum amount of ethanol being necessary to form as much PEth as to exceed the threshold of 20 ng/mL in previously PEth negative subjects. In order to corroborate hitherto existing results, a drinking study including 18 participants after a 3-week alcohol abstinence was performed.

Methods
They consumed a pre-calculated amount of ethanol to reach a blood alcohol concentration (BAC) of at least 0.6 g/kg. Blood was drawn before and periodically seven times after alcohol administration on day 1. Blood and urine were also collected the next morning. Dried blood spots (DBS) were prepared immediately from collected venous blood. BAC was determined by head space gas chromatography and the concentrations of both PEth (16:0/18:1, 16:0/18:2 and five additional homologues) and ethyl glucuronide (EtG) were analysed using liquid chromatography–tandem mass spectrometry.

Results
Out of 18, 5 participants had concentrations of PEth 16:0/18:1 above the threshold of 20 ng/mL, and 11 out of the 18 subjects had concentrations between 10 and 20 ng/mL. In addition, four persons had PEth 16:0/18:2 concentrations above 20 ng/mL the following morning. All test subjects tested positive for EtG in DBS (≥ 3 ng/mL) and urine (≥100 ng/mL) upon 20–21 h after alcohol administration.

Conclusion
By combining both a lower cutoff of 10 ng/mL and the homologue PEth 16:0/18:2, the sensitivity to detect a single alcohol intake after a 3-week abstinence increases to 72.2%.
Immunostick colorimetric assay for highly sensitive detection of food allergens by bio-nanocapsule-scaffolding technology
Authors: Sasamura Yuto , Yamamoto Seri , Tanabe Akiko , Kera Kota , Kuroda Shun'ichi , Nakayama Tsutomu , Iijima Masumi 
Published: April 2023

ABSTRACT
The detection sensitivity of immunostick colorimetric assay has been increased by using a bio-nanocapsule as a scaffold for oriented immobilization of immunoglobulin Gs. This immunostick produced ∼82-folds stronger coloration in the detection of food allergens and reduced detection time by a factor of 5.
NAD+ enhances the activity and thermostability of S-adenosyl-L-homocysteine hydrolase from Pyrococcus horikoshii OT3
Authors: Iwasaki Ryuichi , Bito Tomohiro , Ishihara Atsushi , Watanabe Fumio , Yabuta Yukinori 
Published: April 2023

ABSTRACT
S-Adenosyl-L-methionine (SAM) and S-adenosyl-L-homocysteine (SAH) are important biochemical intermediates. SAM is the major methyl donor for diverse methylation reactions in vivo. The SAM to SAH ratio serves as a marker of methylation capacity. Stable isotope-labeled SAM and SAH are used to measure this ratio with high sensitivity. SAH hydrolase (EC 3.13.2.1; SAHH), which reversibly catalyzes the conversion of adenosine and L-homocysteine to SAH, is used to produce labeled SAH. To produce labeled SAH with high efficiency, we focused on the SAHH of Pyrococcus horikoshii OT3, a thermophilic archaeon. We prepared recombinant P. horikoshii SAHH using Escherichia coli and investigated its enzymatic properties. Unexpectedly, the optimum temperature and thermostability of P. horikoshii SAHH were much lower than its optimum growth temperature. However, addition of NAD+ to the reaction mixture shifted the optimum temperature of P. horikoshii SAHH to a higher temperature, suggesting that NAD+ stabilizes the structure of the enzyme.
BindingSite-AugmentedDTA: enabling a next-generation pipeline for interpretable prediction models in drug repurposing
Authors: Yousefi Niloofar , Yazdani-Jahromi Mehdi , Tayebi Aida , Kolanthai Elayaraja , Neal Craig J , Banerjee Tanumoy , Gosai Agnivo , Balasubramanian Ganesh , Seal Sudipta , Ozmen Garibay Ozlem 
Published: April 2023

Abstract
While research into drug–target interaction (DTI) prediction is fairly mature, generalizability and interpretability are not always addressed in the existing works in this field. In this paper, we propose a deep learning (DL)-based framework, called BindingSite-AugmentedDTA, which improves drug–target affinity (DTA) predictions by reducing the search space of potential-binding sites of the protein, thus making the binding affinity prediction more efficient and accurate. Our BindingSite-AugmentedDTA is highly generalizable as it can be integrated with any DL-based regression model, while it significantly improves their prediction performance. Also, unlike many existing models, our model is highly interpretable due to its architecture and self-attention mechanism, which can provide a deeper understanding of its underlying prediction mechanism by mapping attention weights back to protein-binding sites. The computational results confirm that our framework can enhance the prediction performance of seven state-of-the-art DTA prediction algorithms in terms of four widely used evaluation metrics, including concordance index, mean squared error, modified squared correlation coefficient ($r^2_m$) and the area under the precision curve. We also contribute to three benchmark drug–traget interaction datasets by including additional information on 3D structure of all proteins contained in those datasets, which include the two most commonly used datasets, namely Kiba and Davis, as well as the data from IDG-DREAM drug-kinase binding prediction challenge. Furthermore, we experimentally validate the practical potential of our proposed framework through in-lab experiments. The relatively high agreement between computationally predicted and experimentally observed binding interactions supports the potential of our framework as the next-generation pipeline for prediction models in drug repurposing.
A strategy combining denoising and cryo-EM single particle analysis
Authors: Zhang Hui , Li Hongjia , Zhang Fa , Zhu Ping 
Published: April 2023

Abstract
In cryogenic electron microscopy (cryo-EM) single particle analysis (SPA), high-resolution three-dimensional structures of biological macromolecules are determined by iteratively aligning and averaging a large number of two-dimensional projections of molecules. Since the correlation measures are sensitive to the signal-to-noise ratio, various parameter estimation steps in SPA will be disturbed by the high-intensity noise in cryo-EM. However, denoising algorithms tend to damage high frequencies and suppress mid- and high-frequency contrast of micrographs, which exactly the precise parameter estimation relies on, therefore, limiting their application in SPA. In this study, we suggest combining a cryo-EM image processing pipeline with denoising and maximizing the signal’s contribution in various parameter estimation steps. To solve the inherent flaws of denoising algorithms, we design an algorithm named MScale to correct the amplitude distortion caused by denoising and propose a new orientation determination strategy to compensate for the high-frequency loss. In the experiments on several real datasets, the denoised particles are successfully applied in the class assignment estimation and orientation determination tasks, ultimately enhancing the quality of biomacromolecule reconstruction. The case study on classification indicates that our strategy not only improves the resolution of difficult classes (up to 5 Å) but also resolves an additional class. In the case study on orientation determination, our strategy improves the resolution of the final reconstructed density map by 0.34 Å compared with conventional strategy. The code is available at https://github.com/zhanghui186/Mscale.
The Working Mechanisms Underpinning Mental Health Experts by Experience Involvement in Direct Teaching: An Abductive Conceptual Framework
Authors: Kraus Eran , Moran Galia Sharon 
Published: April 2023

Abstract
Expert by experience (EBE) involvement in direct teaching is a widespread pedagogical practice in social work education. Whilst the educational outcomes of EBE involvement are established, less is known about the working mechanisms through which these outcomes are obtained. By utilising an abductive approach, this research presents a conceptual framework of the working mechanisms underpinning EBE involvement in the mental health context. Thirty-nine semi-structured interviews were conducted with ten Mental Health Experts By Experience (MHEBE), ten social work educators, ten Bachelor of Social Work students and nine Master of Social Work students. Findings from thematic analysis are combined with previously published knowledge from the EBE involvement literature to construct the conceptual framework. The framework comprised three working mechanisms: (i) sharing experiential knowledge; (ii) meeting and interacting with the MHEBE; and (iii) challenging traditional roles and power/knowledge hierarchies. The relationship between mechanisms and learning outcomes, as well as the interrelationship between the mechanisms themselves are explored and discussed. The conceptual framework advances theoretical understandings of EBE involvement and can contribute to the design and implementation of educationally effective involvement.
Less is more in language production: an information-theoretic analysis of agrammatism in primary progressive aphasia
Authors: Rezaii Neguine , Ren Boyu , Quimby Megan , Hochberg Daisy , Dickerson Bradford C 
Published: April 2023

AbstractAgrammatism is a disorder of language production characterized by short, simplified sentences, the omission of function words, an increased use of nouns over verbs and a higher use of heavy verbs. Despite observing these phenomena for decades, the accounts of agrammatism have not converged. Here, we propose and test the hypothesis that the lexical profile of agrammatism results from a process that opts for words with a lower frequency of occurrence to increase lexical information. Furthermore, we hypothesize that this process is a compensatory response to patients’ core deficit in producing long, complex sentences. In this cross-sectional study, we analysed speech samples of patients with primary progressive aphasia (n = 100) and healthy speakers (n = 65) as they described a picture. The patient cohort included 34 individuals with the non-fluent variant, 41 with the logopenic variant and 25 with the semantic variant of primary progressive aphasia. We first analysed a large corpus of spoken language and found that the word types preferred by patients with agrammatism tend to have lower frequencies of occurrence than less preferred words. We then conducted a computational simulation to examine the impact of word frequency on lexical information as measured by entropy. We found that strings of words that exclude highly frequent words have a more uniform word distribution, thereby increasing lexical entropy. To test whether the lexical profile of agrammatism results from their inability to produce long sentences, we asked healthy speakers to produce short sentences during the picture description task. We found that, under this constrained condition, a similar lexical profile of agrammatism emerged in the short sentences of healthy individuals, including fewer function words, more nouns than verbs and more heavy verbs than light verbs. This lexical profile of short sentences resulted in their lower average word frequency than unconstrained sentences. We extended this finding by showing that, in general, shorter sentences get packaged with lower-frequency words as a basic property of efficient language production, evident in the language of healthy speakers and all primary progressive aphasia variants.