bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validation of a new instrument for assessing attitudes on psychedelics in the general population
Authors: Žuljević Marija Franka , Buljan Ivan , Leskur Mia , Kaliterna Mariano , Hren Darko , Duplančić Darko 
Published: October 2022

AbstractAlthough there is research interest to assess attitudes on psychedelics, no validated instrument exists for this purpose. We aimed to develop and examine the psychometric properties of the Attitudes on Psychedelics Questionnaire (APQ) in a sample of the Croatian general population. A cross-sectional, web-based survey among the general population was conducted on 1153 participants (62.1% female, 77.7% with a graduate or high school degree, 15.1% health care workers). We assessed participants’ ability to recognize psychedelic substances using a short knowledge test. The APQ consists of 20 items with four sub-scales: Legal Use of Psychedelics, Effects of Psychedelics, Risk Assessment of Psychedelics, and Openness to Psychedelics. This model demonstrated best fit in a confirmatory factor analysis. Total scale reliability was excellent (McDonald’s ω = 0.949, 95% CI = 0.944–0.953). A strong correlation with a similar unvalidated measure (r = 0.885, P < 0.001) demonstrated convergent validity. We observed an association between attitudes and knowledge on psychedelics (r = 0.494, P < 0.001). Younger age, male gender, and lower educational status were associated with higher APQ scores. The APQ is valid, reliable, and could be applied in assessing educational interventions, patients’ treatment outcomes, and the attitudes of different groups of experts. We encourage further validation of the APQ in English.
Identification and antibacterial evaluation of endophytic actinobacteria from Luffa cylindrica
Authors: Mahdi Ramzy Ali , Bahrami Yadollah , Kakaei Elham 
Published: October 2022

AbstractThe emergence of antibiotic-resistant bacteria has limited treatment options and led to the untreatable infections, thereby necessitating the discovery of new antibiotics to battel against bacteria. Natural products from endophytic actinobacteria (EA) serve as a reservoir for discovery of new antibiotics. Therefore, the current study focused on the isolation and antibacterial properties of EA isolated from Luffa cylindrica. Six strains were identified using morphological characterization, SEM analyses and 16S rRNA gene sequencing from the roots and leaves of the plant. They were taxonomically classified as Streptomycetaceae family. This is the first report on EA form L. cylindrica. The strains produced a chain of oval, cubed or cylindrical shaped spores with spiny or smooth surfaces. Three strains; KUMS-B3, KUMS-B4 and KUMS-B6 were reported as endophytes for the first time. Fifty percent of isolates were isolated from leaves samples using YECD medium. Our results showed that the sampling time and seasons may affect the bacterial diversity. All six strains had antibacterial activity against at least one of the tested bacteria S. aureus, P. aeruginosa, and E. coli. Among the strains, KUMS-B6 isolate, closely related to S. praecox, exhibited the highest antibacterial activity against both gram-positive and negative bacteria. KUMS-B6, KUMS-B5 and KUMS-B4 isolates strongly inhibited the growth of P. aeruginosa. Interestingly, the strains, isolated from leaves exhibited stronger antagonist activities compared to those isolated from the roots. The study revealed that the isolated strains from Luffa produce a plethora of bioactive substances that are potential source of new drug candidates for the treatment of infections.
Ultrafast photoinduced dynamics of a donor-($$\mathrm \pi$$)bridge-acceptor based merocyanine dye
Authors: Shen Jianwei , Jha Ajay , Lv Meng , Jiang Guanyu , Zhao Qixu , Liu Zihui , Chen Jinquan , Yang Yan , Sun Haitao , Duan Hong-Guang , Sun Zhenrong 
Published: October 2022

AbstractMerocyanine dyes are of great interest amongst researchers due to their nonlinear optical (NLO) properties and solvatochromism. Molecular structure of these dyes constitutes conjugated pathway between the donor and acceptor substituents, with lowest energy transition of $$\mathrm \pi$$
π
–$$\mathrm \pi$$
π
* character. To rationalize the design of these dyes and deduce structure-property relationship, it is eminent to unravel the excited state dynamics in these complex molecular structures in different solvents. Here we have studied excited state dynamics of a merocyanine dye known as HB194, which has shown commendable efficiency in small molecule based bulk heterojuction solar cells. We have employed femtosecond transient absorption in combination with the quantum chemistry calculations to unravel the solvent dependent charge transfer dynamics of HB194. The excited state decays of the HB194 in different solvents show multi-exponential components. The analysis of the time-resolved data reveals that the polar solvents induce conformationally relaxed intramolecular charge transfer state. In non-polar solvent cyclohexane, only solvent-stabilized ICT state is observed. Additionally, we observe an anomalously red-shifted emission in ethylene glycol centred at $$\sim$$
∼
750 nm. Our computational calculations suggest the presence of molecular dimers resulting into observed red-shifted emission band. Our work therefore underscores the importance of gathering molecular-level insight into the system-bath interactions for designing next generation merocynanine-based solvatochromic dyes.
In-sensor neural network for high energy efficiency analog-to-information conversion
Authors: Sadasivuni Sudarsan , Bhanushali Sumukh Prashant , Banerjee Imon , Sanyal Arindam 
Published: October 2022

AbstractThis work presents an on-chip analog-to-information conversion technique that utilizes analog hyper-dimensional computing based on reservoir-computing paradigm to process electrocardiograph (ECG) signals locally in-sensor and reduce radio frequency transmission by more than three orders-of-magnitude. Instead of transmitting the naturally sparse ECG signal or extracted features, the on-chip analog-to-information converter analyzes the ECG signal through a nonlinear reservoir kernel followed by an artificial neural network, and transmits the prediction results. The proposed technique is demonstrated for detection of sepsis onset and achieves state-of-the-art accuracy and energy efficiency while reducing sensor power by$$159\times $$159×with test-chips prototyped in 65 nm CMOS.
Glyphosate and glyphosate-based herbicides (GBHs) induce phenotypic imipenem resistance in Pseudomonas aeruginosa
Authors: Háhn Judit , Kriszt Balázs , Tóth Gergő , Jiang Dongze , Fekete Márton , Szabó István , Göbölös Balázs , Urbányi Béla , Szoboszlay Sándor , Kaszab Edit 
Published: October 2022

AbstractGBHs are the most widely used herbicides for weed control worldwide that potentially affect microorganisms, but the role of their sublethal exposure in the development of antibiotic resistance of Pseudomonasaeruginosa is still not fully investigated. Here, the effects of glyphosate acid (GLY), five glyphosate-based herbicides (GBHs), and POE(15), a formerly used co-formulant, on susceptibility to imipenem, a potent carbapenem-type antibiotic, in one clinical and four non-clinical environmental P.aeruginosa isolates were studied. Both pre-exposure in broth culture and co-exposure in solid media of the examined P.aeruginosa strains with 0.5% GBHs resulted in a decreased susceptibility to imipenem, while other carbapenems (doripenem and meropenem) retained their effectiveness. Additionally, the microdilution chequerboard method was used to examine additive/antagonistic/synergistic effects between GLY/POE(15)/GBHs and imipenem by determining the fractional inhibitory concentration (FIC) indexes. Based on the FIC index values, glyphosate acid and Total demonstrated a potent antagonistic effect in all P.aeruginosa strains. Dominator Extra 608 SL and Fozat 480 reduced the activity of imipenem in only one strain (ATCC10145), while POE(15) and three other GBHs did not have any effect on susceptibility to imipenem. Considering the simultaneous presence of GBHs and imipenem in various environmental niches, the detected interactions between these chemicals may affect microbial communities. The mechanisms of the glyphosate and GBH-induced imipenem resistance in P.aeruginosa are yet to be investigated.
Quantitative myocardial perfusion during stress using CMR is impaired in healthy Middle Eastern immigrants without CV risk factors
Authors: Jablonowski Robert , Bennet Louise , Engblom Henrik , Aletras Anthony H. , Xue Hui , Kellman Peter , Carlsson Marcus , Arheden Håkan 
Published: October 2022

AbstractMiddle Eastern immigrants constitute a growing proportion of the European population and compared to native Swedes are more insulin resistant, which can contribute to atherosclerosis. Quantitative first pass perfusion (qFPP) using cardiovascular magnetic resonance (CMR) can detect early signs of cardiovascular disease (CVD). The aim was to study if myocardial perfusion differs between healthy male Middle Eastern immigrants and native male Swedes. Eighteen Iraqi- and twelve Swedish born controls, all males, never smokers with no CVD risk factors were included. Global myocardial perfusion at rest and stress was assessed using qFPP and by phase-contrast CMR imaging of coronary sinus flow. Quantitative first pass perfusion analysis (mean ± SD) demonstrated no difference at rest between Iraqi and Swedish males (0.8 ± 0.2 vs 1.0 ± 0.4 ml/min/g, P = 0.38) but lower perfusion during adenosine in Iraqi males (2.9 ± 0.7 vs 3.5 ± 0.7 ml/min/g, P = 0.02). Myocardial perfusion assessed by coronary sinus flow demonstrated similar results with no difference in resting perfusion between groups (0.7 ± 0.2 vs 0.8 ± 0.2 ml/min/g, P = 0.21) but a lower perfusion during adenosine in the Iraqi group (3.0 ± 0.2 vs 3.7 ± 0.6 ml/min/g, P = 0.01. Myocardial perfusion during adenosine stress was lower in healthy Iraqi immigrants compared to Swedish controls suggesting impaired microvascular function and risk of underestimating CVD risk in healthy individuals of Middle Eastern origin.
Toxicology evaluation of overdose hydroxychloroquine on zebrafish (Danio rerio) embryos
Authors: Luo Min , Xie Dan , Lin Ziyuan , Sun Huaqin , Liu Yanyan 
Published: October 2022

AbstractPotential risks of treatment with hydroxychloroquine (HCQ) include QT interval prolongation, hypoglycemia, a wide range of neuropsychiatric manifestations, hematotoxicity, and potential genetic defects. HCQ is extremely toxic when used in overdose and can lead to tachycardia, hypotension, known central nervous system, transmission defects, hypokalemia and other manifestations in individuals. The mechanism of excessive HCQ leading to these manifestations is still unclear. In this paper, overdose HCQ at different concentrations was used to treat zebrafish embryos, and the phenomena like human beings were obtained, such as increased heart rate and nervous system inhibition. With the increase of concentration to 100 μM, embryo mortality and malformation rate increased and hatching rate decreased, in situ hybridization showed abnormal differentiation of embryo germ layers and formation of vital organs. We selected embryos treated with 50 μM HCQ, in which concentration the mortality rate, hatching rate and malformation rate of the embryos were like those of the control group, for transcriptome analysis. Although the above indexes did not change significantly, the molecular changes related to the development of the heart, eye, nerve and other important organs were significant. This study provides useful information for further research on the toxicity mechanism of HCQ overdose, and provides some insight that can guide future studies in humans.
Evidence of sweet corn yield losses from rising temperatures
Authors: Dhaliwal Daljeet S. , Williams Martin M. 
Published: October 2022

AbstractCrop production is sensitive to anomalous weather conditions, but vegetable crops can be highly sensitive to environmental changes. Using sweet corn data collected on 16,040 fields over a 27-year period, we: (a) estimate yield sensitivities to changes in growing season temperature and total precipitation, (b) estimate critical thresholds in non-linear temperature effects on sweet corn yield across diverse environments, and (c) quantify yield losses from surpassing the upper temperature threshold during anthesis in sweet corn. Our results show growing-season temperatures exceeding 30 $$^\circ{\rm C} $$∘Cwere detrimental to crop yield. Each additional degree day spent above 30 $$^\circ{\rm C} $$∘Cduring anthesis reduced crop yields by 0.5% and 2% in irrigated and rainfed fields, respectively. This study shows evidence for sweet corn yield losses across broad spatial domains in the wake of climate change and underscores the urgency to accelerate crop adaptation strategies to sustain production of this highly popular crop.
A complete blood count-based multivariate model for predicting the recovery of patients with moderate COVID-19: a retrospective study
Authors: Wang Yiting , Li Xuewen , Xu Jiancheng , Zhou Qi 
Published: October 2022

AbstractMany resource-limited countries need an efficient and convenient method to assess disease progression in patients with coronavirus disease 2019 (COVID-19). This study developed and validated a complete blood count-based multivariate model for predicting the recovery of patients with moderate COVID-19. We collected the clinical data and laboratory test results of 86 patients with moderate COVID-19. These data were categorized into two subgroups depending on the laboratory test time. Univariate logistic regression and covariance diagnosis were used to screen for independent factors, and multifactorial logistic regression was used for model building. Data from 38 patients at another hospital were collected for external verification of the model. Basophils (OR 6.372; 95% CI 3.284–12.363), mean corpuscular volume (OR 1.244; 95% CI 1.088–1.422), red blood cell distribution width (OR 2.585; 95% CI 1.261–5.297), and platelet distribution width (OR 1.559; 95% CI 1.154–2.108) could be combined to predict recovery of patients with moderate COVID-19. The ROC curve showed that the model has good discrimination. The calibration curve showed that the model was well-fitted. The DCA showed that the model is clinically useful. Small increases in the above parameters within the normal range suggest an improvement in patients with moderate COVID-19.
Experimental and theoretical studies of native deep-level defects in transition metal dichalcogenides
Authors: Kim Jun Young , Gelczuk Łukasz , Polak Maciej P. , Hlushchenko Daria , Morgan Dane , Kudrawiec Robert , Szlufarska Izabela 
Published: October 2022

AbstractTransition metal dichalcogenides (TMDs), especially in two-dimensional (2D) form, exhibit many properties desirable for device applications. However, device performance can be hindered by the presence of defects. Here, we combine state of the art experimental and computational approaches to determine formation energies and charge transition levels of defects in bulk and 2D MX2 (M = Mo or W; X = S, Se, or Te). We perform deep level transient spectroscopy (DLTS) measurements of bulk TMDs. Simultaneously, we calculate formation energies and defect levels of all native point defects, which enable identification of levels observed in DLTS and extend our calculations to vacancies in 2D TMDs, for which DLTS is challenging. We find that reduction of dimensionality of TMDs to 2D has a significant impact on defect properties. This finding may explain differences in optical properties of 2D TMDs synthesized with different methods and lays foundation for future developments of more efficient TMD-based devices.
Emergence of explosive synchronization bombs in networks of oscillators
Authors: Arola-Fernández Lluís , Faci-Lázaro Sergio , Skardal Per Sebastian , Boghiu Emanuel-Cristian , Gómez-Gardeñes Jesús , Arenas Alex 
Published: October 2022

AbstractResearch on network percolation and synchronization has deepened our understanding of abrupt changes in the macroscopic properties of complex engineered and natural systems. While explosive percolation emerges from localized structural perturbations that delay the formation of a connected component, explosive synchronization is usually studied by fine-tuning of global parameters. Here, we introduce the concept of synchronization bombs as large networks of heterogeneous oscillators that abruptly transit from incoherence to phase-locking (or vice-versa) by adding (or removing) one or a few links. We build these bombs by optimizing global synchrony with decentralized information in a competitive percolation process driven by a local rule, and show their occurrence in systems of Kuramoto –periodic– and Rössler –chaotic– oscillators and in a model of cardiac pacemaker cells, providing an analytical characterization in the Kuramoto case. Our results propose a self-organized approach to design and control abrupt transitions in adaptive biological systems and electronic circuits, and place explosive synchronization and percolation under the same mechanistic framework.
High interstadial sea levels over the past 420ka from the Huon Peninsula, Papua New Guinea
Authors: de Gelder Gino , Husson Laurent , Pastier Anne-Morwenn , Fernández-Blanco David , Pico Tamara , Chauveau Denovan , Authemayou Christine , Pedoja Kevin 
Published: October 2022

AbstractThe history of sea level across the Quaternary is essential for assessing past and future climate. Global sea-level reconstructions are typically derived from oxygen isotope curves, but require calibration with geological constraints that are scarce prior to the last glacial cycle (>130 thousand years ago). Here we show that the coral reef terrace sequence at the Huon Peninsula (Papua New Guinea) provides such constraints up to ∼420 thousand years ago, through a geometric analysis of high-resolution topographic data. We derive a northward tectonic tilt as regional deformation pattern, and estimate relative sea level for 31 Quaternary periods, including several periods for which no relative sea level data exists elsewhere. Supported by numerical reef models, these estimates suggest that oxygen isotope-based global mean sea-level curves systematically underestimate interstadial sea-level elevations, by up to ∼20 m. Compared to those curves, our results imply a stronger degree of non-linearity between ice-sheet volumes and global temperatures within Quaternary glacial cycles.
Basaltic Plinian eruptions at Las Sierras-Masaya volcano driven by cool storage of crystal-rich magmas
Authors: Bamber Emily C. , La Spina Giuseppe , Arzilli Fabio , de’ Michieli Vitturi Mattia , Polacci Margherita , Hartley Margaret E. , Petrelli Maurizio , Fellowes Jonathan , Burton Mike 
Published: October 2022

AbstractAlthough rare, basaltic Plinian eruptions represent a considerable volcanic hazard. The low viscosity of crystal-poor basaltic magma inhibits magma fragmentation; however, Las Sierras-Masaya volcano, Nicaragua, has produced multiple basaltic Plinian eruptions. Here, we quantify the geochemistry and volatile concentrations of melt inclusions in samples of the Fontana Lapilli and Masaya Triple Layer eruptions to constrain pre-eruptive conditions. Combining thermometry and geochemical modelling, we show that magma cooled to ~1000 °C prior to eruption, crystallising a mush that was erupted and preserved in scoriae. We use these data in a numerical conduit model, which finds that conditions most conducive to Plinian eruptions are a pre-eruptive temperature <1100 °C and a total crystal content >30 vol.%. Cooling, crystal-rich, large-volume basaltic magma bodies may be hazardous due to their potential to erupt with Plinian magnitude. Rapid ascent rates mean there may only be some minutes between eruption triggering and Plinian activity at Masaya.
A globally robust relationship between water table decline, subsidence rate, and carbon release from peatlands
Authors: Ma Lei , Zhu Gaofeng , Chen Bolong , Zhang Kun , Niu Shuli , Wang Jinsong , Ciais Phillipe , Zuo Hongchao 
Published: October 2022

AbstractPeatland ecosystems are globally important carbon stores. Disturbances, such as drainage and climate drying, act to lower peatland water table depths, consequently enhancing soil carbon release and subsidence rates. Here, we conduct a global meta-analysis to quantify the relationship among water table depth, carbon release and subsidence. We find that the water table decline stimulated heterotrophic, rather than autotrophic, soil respiration, which was associated with an increase in subsidence rate. This relationship held across different climate zones and land uses. We find that 81% of the total annual soil respiration for all drained peatlands was attributable to tropical peatlands drained for agriculture and forestry and temperate peatlands drained for agriculture. Globally, we estimate that, drained peatlands release 645 Mt C yr–1(401–1025 Mt C yr–1) through soil respiration, equivalent to approximately 5% of global annual anthropogenic carbon emissions. Our findings highlight the importance of conserving pristine peatlands to help mitigate climate change.
Incipient detection of stator inter‐turn short‐circuit faults in a Doubly‐Fed Induction Generator using deep learning
Authors: Alipoor Ghasem , Mirbagheri Seyed Jafar , Moosavi Seyed Mohammad Mahdi , Cruz Sérgio M. A. 
Published: October 2022

AbstractWind turbines are increasingly expanding worldwide and Doubly‐Fed Induction Generator (DFIG) is a key component of most of them. Stator winding fault is a major fault in this equipment and its incipient detection is of vital importance. However, there is a paucity of research in this field. In this study, a novel machine learning‐based method is proposed for incipient detection of inter‐turn short‐circuit fault (ITF) in the DFIG stator based on the current signals of the stator. The proposed method makes use of state‐of‐the‐art deep learning methods along with conventional signal processing tools and general machine learning techniques. More specifically, the incipient fault detection problem is regarded as a multi‐class classification problem and a Long Short‐Term Memory network, which is more appropriate for time‐series data is utilised for inference. Furthermore, a variant of the celebrated Empirical mode Decomposition analysis tool is used to extract some well‐known statistical features among which the most informative ones are selected using a new feature selection method. Our tests using experimental data in steady‐state conditions show that the proposed method can accurately detect ITF fault at its initial stage when only one turn is shorted. Moreover, its performance is considerably higher than that of a variety of machine learning‐based methods.