bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of iron oxide contents on photocatalytic performance of nanocomposites based on g-C3N4
Authors: Afkari M. , Masoudpanah S. M. , Hasheminiasari M. , Alamolhoda S. 
Published: April 2023

Abstractα-Fe2O3/Fe3O4/g-C3N4 nanocomposites were prepared in-situ by solution combustion as magnetically separable photocatalysts using ferric nitrate as oxidant, glycine as organic fuel, and g-C3N4. The effects of various amounts of iron oxides, on the magnetic, optical, and photocatalytic properties were explored by different characterization methods. The magnetite (Fe3O4) phase as ferrimagnetic material disappeared with the increase in ferric nitrate contents, leading to the decrease of magnetic properties. The bandgap energy decreased from 2.8 to 1.6 eV with the increase of the hematite (α-Fe2O3) phase.The photocatalytic results showed that the type and amount of iron oxides had a significant effect on the decolorization of methylene blue, rhodamine B and methyl orange dyes under visible-light irradiation. The activity of the nanocomposite sample containing 37 wt. % iron oxides was more effective than that of the pristine g-C3N4 sample to photodegrade the methylene blue, rhodamine B and methyl orange, respectively. Moreover, the nanocomposites exhibited a higher photocurrent density than that of the pristine g-C3N4, mainly due to their lower charge recombination rate.
The simplification of the insomnia severity index and epworth sleepiness scale using machine learning models
Authors: Lee Woodo , Kim Hyejin , Shim Jaekwoun , Kim Dongsin , Hyeon Janghun , Joo Eunyeon , Joo Byung-Euk , Oh Junhyoung 
Published: April 2023

AbstractInsomnia and excessive daytime sleepiness (EDS) are the most common complaints in sleep clinics, and the cost of healthcare services associated with them have also increased significantly. Though the brief questionnaires such as the Insomnia Severity Index (ISI) and Epworth Sleepiness Scale (ESS) can be useful to assess insomnia and EDS, there are some limitations to apply for large numbers of patients. As the researches using the Internet of Things technology become more common, the need for the simplification of sleep questionnaires has been also growing. We aimed to simplify ISI and ESS using machine learning algorithms and deep neural networks with attention models. The medical records of 1,241 patients who examined polysomnography for insomnia or EDS were analyzed. All patients are classified into five groups according to the severity of insomnia and EDS. To develop the model, six machine learning algorithms were firstly applied. After going through normalization, the process with the CNN+ Attention model was applied. We classified a group with an accuracy of 93% even with only the results of 6 items (ISI1a, ISI1b, ISI3, ISI5, ESS4, ESS7). We simplified the sleep questionnaires with maintaining high accuracy by using machine learning models.
Improved YOLOv5 infrared tank target detection method under ground background
Authors: Liang Chao , Yan Zhengang , Ren Meng , Wu Jiangpeng , Tian Liping , Guo Xuan , Li Jie 
Published: April 2023

AbstractThe detection precision of infrared seeker directly affects the guidance precision of infrared guidance system. To solve the problem of low target detection accuracy caused by the change of imaging scale, complex ground background and inconspicuous infrared target characteristics when infrared image seeker detects ground tank targets. In this paper, a You Only Look Once, Transform Head Squeeze-and-Excitation (YOLOv5s-THSE) model is proposed based on the YOLOv5s model. A multi-head attention mechanism is added to the backbone and neck of the network, and deeper target features are extracted using the multi-head attention mechanism. The Cross Stage Partial, Squeeze-and-Exclusion module is added to the neck of the network to suppress the complex background and make the model pay more attention to the target. A small object detection head is introduced into the head of the network, and the CIoU loss function is used in the model to improve the detection accuracy of small objects and obtain more stable training regression. Through these several improvement measures, the background of the infrared target is suppressed, and the detection ability of infrared tank targets is improved. Experiments on infrared tank target datasets show that our proposed model can effectively improve the detection performance of infrared tank targets under ground background compared with existing methods, such as YOLOv5s, YOLOv5s + SE, and YOLOV 5 s + Convective Block Attention Module.
Landscape of co-expressed genes between the myocardium and blood in sepsis and ceRNA network construction: a bioinformatic approach
Authors: Long Qi , Li Gang , Dong Qiufen , Wang Min , Li Jin , Wang Liulin 
Published: April 2023

AbstractSeptic cardiomyopathy is a serious complication of sepsis. The mechanism of disease pathogenesis, which is caused by infection, is well researched. Despite ongoing efforts, there are no viable biological markers in the peripheral blood for early detection and diagnosis of septic cardiomyopathy. We aimed to uncover potential biomarkers of septic cardiomyopathy by comparing the covaried genes and pathways in the blood and myocardium of sepsis patients. Gene expression profiling of GSE79962, GSE65682, GSE54514, and GSE134364 was retrieved from the GEO database. Student’s t-test was used for differential expression analysis. K-means clustering analysis was applied for subgroup identification. Least absolute shrinkage and selection operator (LASSO) and logistic regression were utilized for screening characteristic genes and model construction. Receiver operating characteristic (ROC) curves were generated for estimating the diagnostic efficacy. For ceRNA information prediction, miWalk and lncBase were applied. Cytoscape was used for ceRNA network construction. Inflammation-associated genes were upregulated, while genes related to mitochondria and aerobic metabolism were downregulated in both blood and the myocardium. Three groups with a significantly different mortality were identified by these covaried genes, using clustering analysis. Five characteristic genes—BCL2A1, CD44, ADGRG1, TGIF1, and ING3—were identified, which enabled the prediction of mortality of sepsis. The pathophysiological changes in the myocardium of patients with sepsis were also reflected in peripheral blood to some extent. The co-occurring pathological processes can affect the prognosis of sepsis. Thus, the genes we identified have the potential to become biomarkers for septic cardiomyopathy.
Acrylonitrile adducts: design, synthesis and biological evaluation as antimicrobial, haemolytic and thrombolytic agent
Authors: Das Parineeta , Devi Nirmala , Gaur Nisha , Goswami Swagata , Dutta Dhiraj , Dubey Rama , Puzari Amrit 
Published: April 2023

AbstractIn this work, five acrylonitrile adducts were screened for antibacterial activity against Gram-positive Bacillus subtilis, Microbial Type Culture Collection and Gene Bank (MTCC 1305) and Gram-negative Escherichia coli (MTCC 443). Synthesis was followed by aza-Michael addition reaction, where the acrylonitrile accepts an electron pair from the respective amines and results in the formation of n-alkyliminobis-propionitrile and n-alkyliminopropionitrile under microwave irradiation. Characterization of the compounds were performed using Fourier Transform Infrared (FTIR), Proton Nuclear Magnetic Resonance (1H NMR) and Electrospray Ionisation Mass Spectrometry (ESI–MS). The particle size characterization was done by Dynamic Light Scattering (DLS) technique. The antibacterial study showed higher inhibition rate for both Gram-positive and Gram-negative bacteria. The antibacterial ability was found to be dose dependent. The minimum inhibitory concentration against both bacteria were found to be 1, 3, 0.4, 1, 3 µl/ml for E. coli and 6, 6, 0.9, 0.5, 5 µl/ml for B. subtilis. Time-kill kinetics evaluation showed that the adducts possess bacteriostatic action. Further it was evaluated for high-throughput in vitro assays to determine the compatibility of the adducts for drug delivery. The haemolytic and thrombolytic activity was analysed against normal mouse erythrocytes. The haemolytic activity showed prominent results, and thereby projecting this acrylonitrile adducts as potent antimicrobial and haemolytic agent.
The wider the gap between rich and poor the higher the flood mortality
Authors: Lindersson Sara , Raffetti Elena , Rusca Maria , Brandimarte Luigia , Mård Johanna , Di Baldassarre Giuliano 
Published: April 2023

AbstractEconomic inequality is rising within many countries globally, and this can significantly influence the social vulnerability to natural hazards. We analysed income inequality and flood disasters in 67 middle- and high-income countries between 1990 and 2018 and found that unequal countries tend to suffer more flood fatalities. This study integrates geocoded mortality records from 573 major flood disasters with population and economic data to perform generalized linear mixed regression modelling. Our results show that the significant association between income inequality and flood mortality persists after accounting for the per-capita real gross domestic product, population size in flood-affected regions and other potentially confounding variables. The protective effect of increasing gross domestic product disappeared when accounting for income inequality and population size in flood-affected regions. On the basis of our results, we argue that the increasingly uneven distribution of wealth deserves more attention within international disaster-risk research and policy arenas.
Quantifying label enrichment from two mass isotopomers increases proteome coverage for in vivo protein turnover using heavy water metabolic labeling
Authors: Deberneh Henock M. , Abdelrahman Doaa R. , Verma Sunil K. , Linares Jennifer J. , Murton Andrew J. , Russell William K. , Kuyumcu-Martinez Muge N. , Miller Benjamin F. , Sadygov Rovshan G. 
Published: April 2023

AbstractHeavy water metabolic labeling followed by liquid chromatography coupled with mass spectrometry is a powerful high throughput technique for measuring the turnover rates of individual proteins in vivo. The turnover rate is obtained from the exponential decay modeling of the depletion of the monoisotopic relative isotope abundance. We provide theoretical formulas for the time course dynamics of six mass isotopomers and use the formulas to introduce a method that utilizes partial isotope profiles, only two mass isotopomers, to compute protein turnover rate. The use of partial isotope profiles alleviates the interferences from co-eluting contaminants in complex proteome mixtures and improves the accuracy of the estimation of label enrichment. In five different datasets, the technique consistently doubles the number of peptides with high goodness-of-fit characteristics of the turnover rate model. We also introduce a software tool, d2ome+, which automates the protein turnover estimation from partial isotope profiles.
Scalable set of reversible parity gates for integer factorization
Authors: Lanthaler Martin , Niehoff Benjamin E. , Lechner Wolfgang 
Published: April 2023

AbstractClassical microprocessors operate on irreversible gates, that, when combined with , half-adder and full-adder operations, execute complex tasks such as multiplication of integers. We introduce parity versions of all components of a multiplication circuit. The parity gates are reversible quantum gates based on the recently introduced parity transformation and build on ground-space encoding of the corresponding gate logic. Using a quantum optimization heuristic, e.g., an adiabatic quantum computing protocol, allows one to quantum mechanically reverse the process of multiplication and thus factor integers, which has applications in cryptography. Our parity approach builds on nearest-neighbor constraints equipped with local fields, able to encode the logic of a binary multiplication circuit in a modular and scalable way.
Circularity in Europe strengthens the sustainability of the global food system
Authors: van Zanten H. H. E. , Simon W. , van Selm B. , Wacker J. , Maindl T. I. , Frehner A. , Hijbeek R. , van Ittersum M. K. , Herrero M. 
Published: April 2023

AbstractRedesigning the European food system on the basis of circularity principles could bring environmental benefits for Europe and the world. Here we deploy a biophysical optimization model to explore the effects of adopting three circularity scenarios in the European Union (EU)27 + UK. We calculate a potential reduction of 71% in agricultural land use and 29% per capita in agricultural greenhouse gas emissions, while producing enough healthy food within a self-sufficient European food system. Under global food shortages, savings in agricultural land could be used to feed an additional 767 million people outside the EU (+149%), while reducing per capita greenhouse gas emissions by 38% but increasing overall emissions by 55% due to the increased population served. Transitioning the EU’s food system towards circularity implies sequential changes among all its components and has great potential to safeguard human and planetary health.
The influence of lattice misfit on screw and edge dislocation-controlled solid solution strengthening in Mo-Ti alloys
Authors: Winkens Georg , Kauffmann Alexander , Herrmann Johannes , Czerny Andreas K. , Obert Susanne , Seils Sascha , Boll Torben , Baruffi Carolina , Rao You , Curtin William A. , Schwaiger Ruth , Heilmaier Martin 
Published: April 2023

AbstractMo-Ti alloys form solid solutions over a wide range of compositions, with lattice misfit parameters increasing significantly with titanium content. This indicates a strong increase in the critical stress for edge dislocation motion. Here, we probe the transition from screw to edge dislocation-dominated strengthening in Mo-Ti solid solutions with titanium content up to 80 at%. The alloys were scale-bridging characterized to isolate the impact of substitutional solid solution strengthening. Mechanical testing yielded no significant influence of grain boundaries or grain orientation. The results were corrected for the strengthening by unavoidable interstitial oxygen. Modelling of screw and edge dislocation-controlled solid solution strengthening was applied to the results to evaluate the contributions of both dislocation types. The analysis reveals that screw dislocation motion controls the strength in allows with less than 40 at% titanium, while edge dislocation motion provides comparable strength for 60–80 at% titanium. These results in a system of reduced chemical complexity support the recent investigations of edge dislocation-controlled strengthening found in high-entropy alloys.
Atmospheric rivers that make landfall in India are associated with flooding
Authors: Mahto Shanti Shwarup , Nayak Munir Ahmad , Lettenmaier Dennis P. , Mishra Vimal 
Published: April 2023

AbstractAtmospheric rivers often cause extreme precipitation at landfall, leading to floods. However, the underlying physical mechanism of atmospheric rivers and their linkage with flooding in India remain unrecognized. Here we use reanalysis and observations to diagnose the drivers of atmospheric rivers and unravel their crucial role in extreme precipitation and floods during 1951–2020. Moisture transport has significantly increased during 1951–2020, which is associated with strengthening winds that transport water vapor from the oceans. However, while there is a suggestive corresponding increase in the frequency of atmospheric rivers, it is not statistically significant. The atmospheric river catalogue that we developed shows that about 65% of landfalling atmospheric river were linked to floods during the 1985–2020 period. In addition, seven of India’s ten most severe floods in the summer monsoon season with substantial mortality were associated with atmospheric rivers. Better understanding and prediction of atmospheric rivers is crucial for flood mitigation.
An open-source deep learning network AVA-Net for arterial-venous area segmentation in optical coherence tomography angiography
Authors: Abtahi Mansour , Le David , Ebrahimi Behrouz , Dadzie Albert K. , Lim Jennifer I. , Yao Xincheng 
Published: April 2023

AbstractBackgroundDifferential artery-vein (AV) analysis in optical coherence tomography angiography (OCTA) holds promise for the early detection of eye diseases. However, currently available methods for AV analysis are limited for binary processing of retinal vasculature in OCTA, without quantitative information of vascular perfusion intensity. This study is to develop and validate a method for quantitative AV analysis of vascular perfusion intensity.MethodA deep learning network AVA-Net has been developed for automated AV area (AVA) segmentation in OCTA. Seven new OCTA features, including arterial area (AA), venous area (VA), AVA ratio (AVAR), total perfusion intensity density (T-PID), arterial PID (A-PID), venous PID (V-PID), and arterial-venous PID ratio (AV-PIDR), were extracted and tested for early detection of diabetic retinopathy (DR). Each of these seven features was evaluated for quantitative evaluation of OCTA images from healthy controls, diabetic patients without DR (NoDR), and mild DR.ResultsIt was observed that the area features, i.e., AA, VA and AVAR, can reveal significant differences between the control and mild DR. Vascular perfusion parameters, including T-PID and A-PID, can differentiate mild DR from control group. AV-PIDR can disclose significant differences among all three groups, i.e., control, NoDR, and mild DR. According to Bonferroni correction, the combination of A-PID and AV-PIDR can reveal significant differences in all three groups.ConclusionsAVA-Net, which is available on GitHub for open access, enables quantitative AV analysis of AV area and vascular perfusion intensity. Comparative analysis revealed AV-PIDR as the most sensitive feature for OCTA detection of early DR. Ensemble AV feature analysis, e.g., the combination of A-PID and AV-PIDR, can further improve the performance for early DR assessment.
Compact high‐efficiency c‐band rectifier with high input power for microwave power transmission
Authors: Zeng Hongzheng , Tang Yuzhu , Liu Yunpeng 
Published: April 2023

AbstractThis letter presents a novel C‐band rectifier that is capable of handling high input power. The rectifier consists of a Schottky diode, an impedance matching circuit with a compensation microstrip structure, and an output filter with harmonic suppression and ripple smoothing. The experimental results indicate that the rectifier yields a conversion efficiency exceeding 70% and a peak efficiency of 74.1% over a wide input power range of 20 to 26 dBm (6 dB) at 5.8 GHz, utilizing a single Si‐based Schottky diode. Furthermore, the rectifier has a compact size of 28 mm × 15 mm. Given its cost‐effectiveness and outstanding performance, this rectifier presents an attractive option for large‐scale microwave power applications.
Enhancing time‐frequency resolution via deep‐learning framework
Authors: Wang Zixin , Chen Lixing , Xiao Peng , Xu Lingji , Li Zhenglin 
Published: April 2023

AbstractThe fixed window function used in the short‐time Fourier transform (STFT) does not guarantee both time and frequency resolution, exerting a negative impact on the subsequent study of time‐frequency analysis (TFA). To avoid these limitations, a post‐processing method that enhances the time‐frequency resolution using a deep‐learning (DL) framework is proposed. Initially, the deconvolution theoretical formula is derived and a post‐processing operation is performed on the time‐frequency representation (TFR) of the STFT via deconvolution, a theoretical calculation to obtain the ideal time‐frequency representation (ITFR). Then, aiming at the adverse influence of the window function, a novel fully‐convolutional encoder‐decoder network is trained to preserve effective features and acquire the optimal time‐frequency kernel. In essence, the generation of the optimal time‐frequency kernel can be regarded as a deconvolution process. The authors conducted the qualitative and quantitative analyses of numerical simulations, with experimental results demonstrate that the proposed method achieves satisfactory TFR, possesses strong anti‐noise capabilities, and exhibits high steady‐state generalisation capability. Furthermore, results of a comparative experiment with several TFA methods indicate that the proposed method yields significantly improved performance in terms of time‐frequency resolution, energy concentration, and computational load.
Combined analysis of stellar and planetary absorption lines via global forward-transit simulations
Authors: Dethier W. , Bourrier V. 
Published: April 2023

Context. Transit spectroscopy of exoplanets has led to the detection of many species whose absorption signatures trace their atmospheric structure and dynamics. Improvements in resolution and sensitivity have, however, revealed biases induced by stellar lines occulted by the transiting planet.
Aims. We characterise the planet-occulted line distortions (POLDs) in absorption spectra that arise from proxies used for the occulted stellar lines and investigate the impact of stellar rotation, centre-to-limb variations, and broadband limb-darkening.
Methods. We used the EVaporating Exoplanets (EVE) code to generate realistic stellar spectra during the transit of exoplanets, accounting for the 3D geometry of the system’s architecture and atmospheric transit, as well as for spectral variations over the stellar disc. The absorption spectra were calculated using approaches drawn from the literature and compared to the expected signal.
Results. The POLDs from stellar rotation are dominant for moderate to fast rotating stars, reaching amplitudes comparable to atmospheric signals, but they can be mitigated by shifting the stellar line proxies to the radial velocity of the planet-occulted region. Centre-to-limb variations become dominant for slow rotators and are more easily mitigated at the stellar limb. We re-interpret the ESPRESSO data of two iconic systems and confirm that the sodium signature from HD 209458 b mainly arises from POLDs. However, we unveil a possible contribution from the planetary atmosphere that warrants further observations. For MASCARA-1 b, we did not find evidence for atmospheric sodium absorption and we can fully explain the observed signature by a POLD for super-solar stellar sodium abundance.
Conclusions. We studied POLDs dependency on star and planet properties, and on the proxy used for planet-occulted lines. Distinguishing planetary absorption signatures from POLDs is challenging without access to accurate estimates of the local stellar spectrum and system orbital parameters. We propose a way to mitigate POLDs and improve atmospheric characterisation, by using simultaneous forward modelling of both the star and the planet to simulate the global observed signatures.