bluuebunny/crossref_metadata_2025 huggingface dataset:
Gender disparities in prevalence by diagnostic criteria, treatment and mortality of newly diagnosed acute myocardial infarction in Korean adults
Authors: Kim So Ree , Bae SungA , Lee Ji Yoon , Kim Min Sun , Kim Mi-Na , Chung Wook-Jin , Bae Jang-Ho , Lee Juneyoung , Park Seong-Mi
Published: March 2023

Acute myocardial infarction (AMI) is highly prevalent and remains the leading cause of mortality. Particularly in women, under-recognition and management of AMI have been raised. The aim of this study was to investigate the long-term trends of prevalence, treatment methodologies, and mortality of AMI by gender. The subjects of this study were patients hospitalized for AMI according to the Korean National Health Insurance Claims Database from 2002 to 2018. Total 633,097 AMI patients were hospitalized, 40% women. The incidence of AMI has been increasing since 2011, with a lower incidence in women. Overall, 53.1% of patients underwent CAG, with a lower tendency in women than in men (39.8% vs. 62.3%). Furthermore, fewer women underwent PCI than men (77.5% vs. 85.8% in 2018, p < 0.0001). Of the 336,463 AMI patients undergoing CAG, women were undertreated with a lower prescription rate of beta-blockers or statins at discharge. When adjusted for age, women showed higher 7-day mortality but lower 1-year mortality relative to men. According to the Korean National Health Insurance Claims Database, women with AMI have been under-recognized, underdiagnosed, and undertreated in terms of revascularization or medical therapy for years suggesting that efforts to close the gender gap are necessary.
Spatial–temporal distribution of incidence, mortality, and case-fatality ratios of coronavirus disease 2019 and its social determinants in Brazilian municipalities
Authors: Raymundo Carlos Eduardo , Oliveira Marcella Cini , de Araujo Eleuterio Tatiana , de Arruda Santos Junior Édnei César , da Silva Marcele Gonçalves , André Suzana Rosa , Sousa Ana Inês , de Andrade Medronho Roberto
Published: March 2023

The COVID-19 pandemic caused impact on public health worldwide. Brazil gained prominence during the pandemic due to the magnitude of disease. This study aimed to evaluate the spatial–temporal dynamics of incidence, mortality, and case fatality of COVID-19 and its associations with social determinants in Brazilian municipalities and epidemiological week. We modeled incidence, mortality, and case fatality rates using spatial–temporal Bayesian model. “Bolsa Família Programme” (BOLSAFAM) and “proportional mortality ratio” (PMR) were inversely associated with the standardized incidence ratio (SIR), while “health insurance coverage” (HEALTHINSUR) and “Gini index” were directly associated with the SIR. BOLSAFAM and PMR were inversely associated with the standardized mortality ratio (SMR) and standardized case fatality ratio (SCFR). The highest proportion of excess risk for SIR and the SMR started in the North, expanding to the Midwest, Southeast, and South regions. The highest proportion of excess risk for the SCFR outcome was observed in some municipalities in the North region and in the other Brazilian regions. The COVID-19 incidence and mortality in municipalities that most benefited from the cash transfer programme and with better social development decreased. The municipalities with a higher proportion of non-whites had a higher risk of becoming ill and dying from the disease.
Consequences of reprogramming acetyl-CoA metabolism by 2,3,7,8-tetrachlorodibenzo-p-dioxin in the mouse liver
Authors: Cholico Giovan N. , Orlowska Karina , Fling Russell R. , Sink Warren J. , Zacharewski Nicholas A. , Fader Kelly A. , Nault Rance , Zacharewski Tim
Published: March 2023

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a persistent environmental contaminant that induces the progression of steatosis to steatohepatitis with fibrosis in mice. Furthermore, TCDD reprograms hepatic metabolism by redirecting glycolytic intermediates while inhibiting lipid metabolism. Here, we examined the effect of TCDD on hepatic acetyl-coenzyme A (acetyl-CoA) and β-hydroxybutyrate levels as well as protein acetylation and β-hydroxybutyrylation. Acetyl-CoA is not only a central metabolite in multiple anabolic and catabolic pathways, but also a substrate used for posttranslational modification of proteins and a surrogate indicator of cellular energy status. Targeted metabolomic analysis revealed a dose-dependent decrease in hepatic acetyl-CoA levels coincident with the phosphorylation of pyruvate dehydrogenase (E1), and the induction of pyruvate dehydrogenase kinase 4 and pyruvate dehydrogenase phosphatase, while repressing ATP citrate lyase and short-chain acyl-CoA synthetase gene expression. In addition, TCDD dose-dependently reduced the levels of hepatic β-hydroxybutyrate and repressed ketone body biosynthesis gene expression. Moreover, levels of total hepatic protein acetylation and β-hydroxybutyrylation were reduced. AMPK phosphorylation was induced consistent with acetyl-CoA serving as a cellular energy status surrogate, yet subsequent targets associated with re-establishing energy homeostasis were not activated. Collectively, TCDD reduced hepatic acetyl-CoA and β-hydroxybutyrate levels eliciting starvation-like conditions despite normal levels of food intake.
New insights into APCVD grown monolayer MoS2 using time-domain terahertz spectroscopy
Authors: Sharma Saloni , Chauhan Pooja , Rane Shreeya , Raj Utkarsh , Srivastava Shubhda , Ansari Z. A. , Roy Chowdhury Dibakar , Gupta Bipin Kumar
Published: March 2023

In modern era, wireless communications at ultrafast speed are need of the hour and search for its solution through cutting edge sciences is a new perspective. To address this issue, the data rates in order of terabits per second (TBPS) could be a key step for the realization of emerging sixth generation (6G) networks utilizing terahertz (THz) frequency regime. In this context, new class of transition metal dichalcogenides (TMDs) have been introduced as potential candidates for future generation wireless THz technology. Herein, a strategy has been adopted to synthesize high-quality monolayer of molybdenum di-sulfide (MoS2) using indigenously developed atmospheric pressure chemical vapor deposition (APCVD) set-up. Further, the time-domain transmission and sheet conductivity were studied as well as a plausible mechanism of terahertz response for monolayer MoS2 has been proposed and compared with bulk MoS2. Hence, the obtained results set a stepping stone to employ the monolayer MoS2 as potential quantum materials benefitting the next generation terahertz communication devices.
Exposure to hate speech deteriorates neurocognitive mechanisms of the ability to understand others’ pain
Authors: Pluta Agnieszka , Mazurek Joanna , Wojciechowski Jakub , Wolak Tomasz , Soral Wiktor , Bilewicz Michał
Published: March 2023

The widespread ubiquity of hate speech affects people's attitudes and behavior. Exposure to hate speech can lead to prejudice, dehumanization, and lack of empathy towards members of outgroups. However, the impact of exposure to hate speech on empathy and propensity to attribute mental states to others has never been directly tested empirically. In this fMRI study, we examine the effects of exposure to hate speech on neural mechanisms of empathy towards ingroup (Poles) versus outgroup members (Arabs). Thirty healthy young adults were randomly assigned to 2 groups: hateful and neutral. During the fMRI study, they were initially exposed to hateful or neutral comments and subsequently to narratives depicting Poles and Arabs in pain. Using whole-brain and region of interest analysis, we showed that exposure to derogatory language about migrants attenuates the brain response to someone else’s pain in the right temporal parietal junction (rTPJ), irrespective of group membership (Poles or Arabs). Given that rTPJ is associated with processes relevant to perspective-taking, its reduced activity might be related to a decreased propensity to take the psychological perspective of others. This finding suggests that hate speech affects human functioning beyond intergroup relations.
Medical image captioning via generative pretrained transformers
Authors: Selivanov Alexander , Rogov Oleg Y. , Chesakov Daniil , Shelmanov Artem , Fedulova Irina , Dylov Dmitry V.
Published: March 2023

The proposed model for automatic clinical image caption generation combines the analysis of radiological scans with structured patient information from the textual records. It uses two language models, the Show-Attend-Tell and the GPT-3, to generate comprehensive and descriptive radiology records. The generated textual summary contains essential information about pathologies found, their location, along with the 2D heatmaps that localize each pathology on the scans. The model has been tested on two medical datasets, the Open-I, MIMIC-CXR, and the general-purpose MS-COCO, and the results measured with natural language assessment metrics demonstrated its efficient applicability to chest X-ray image captioning.
Blind spectral unmixing for characterization of plaque composition based on multispectral photoacoustic imaging
Authors: Cano Camilo , Matos Catarina , Gholampour Amir , van Sambeek Marc , Lopata Richard , Wu Min
Published: March 2023

To improve the assessment of carotid plaque vulnerability, a comprehensive characterization of their composition is paramount. Multispectral photoacoustic imaging (MSPAI) can provide plaque composition based on their absorption spectra. However, although various spectral unmixing methods have been developed to characterize different tissue constituents, plaque analysis remains a challenge since its composition is highly complex and diverse. In this study, we employed an adapted piecewise convex multiple-model endmember detection method to identify carotid plaque constituents. Additionally, we explore the selection of the imaging wavelengths in linear models by conditioning the coefficient matrix and its synergy with our unmixing approach. We verified our method using plaque mimicking phantoms and performed ex-vivo MSPAI on carotid endarterectomy samples in a spectral range from 500 to 1300 nm to identify the main spectral features of plaque materials for vulnerability assessment. After imaging, the samples were processed for histological analysis to validate the photoacoustic decomposition. Results show that our approach can perform spectral unmixing and classification of highly heterogeneous biological samples without requiring an extensive fluence correction, enabling the identification of relevant components to assess plaque vulnerability.
A coupled agent-based model for France for simulating adaptation and migration decisions under future coastal flood risk
Authors: Tierolf Lars , Haer Toon , Botzen W. J. Wouter , de Bruijn Jens A. , Ton Marijn J. , Reimann Lena , Aerts Jeroen C. J. H.
Published: March 2023

In this study, we couple an integrated flood damage and agent-based model (ABM) with a gravity model of internal migration and a flood risk module (DYNAMO-M) to project household adaptation and migration decisions under increasing coastal flood risk in France. We ground the agent decision rules in a framework of subjective expected utility theory. This method addresses agent’s bounded rationality related to risk perception and risk aversion and simulates the impact of push, pull, and mooring factors on migration and adaptation decisions. The agents are parameterized using subnational statistics, and the model is calibrated using a household survey on adaptation uptake. Subsequently, the model simulates household adaptation and migration based on increasing coastal flood damage from 2015 until 2080. A medium population growth scenario is used to simulate future population development, and sea level rise (SLR) is assessed for different climate scenarios. The results indicate that SLR can drive migration exceeding 8000 and 10,000 coastal inhabitants for 2080 under the Representative Concentration Pathways 4.5 and 8.5, respectively. Although household adaptation to flood risk strongly impacts projected annual flood damage, its impact on migration decisions is small and falls within the 90% confidence interval of model runs. Projections of coastal migration under SLR are most sensitive to migration costs and coastal flood protection standards, highlighting the need for better characterization of both in modeling exercises. The modeling framework demonstrated in this study can be upscaled to the global scale and function as a platform for a more integrated assessment of SLR-induced migration.
Utilizing photonic band gap in triangular silicon carbide structures for efficient quantum nanophotonic hardware
Authors: Saha Pranta , Majety Sridhar , Radulaski Marina
Published: March 2023

Silicon carbide is among the leading quantum information material platforms due to the long spin coherence and single-photon emitting properties of its color center defects. Applications of silicon carbide in quantum networking, computing, and sensing rely on the efficient collection of color center emission into a single optical mode. Recent hardware development in this platform has focused on angle-etching processes that preserve emitter properties and produce triangularly shaped devices. However, little is known about the light propagation in this geometry. We explore the formation of photonic band gap in structures with a triangular cross-section, which can be used as a guiding principle in developing efficient quantum nanophotonic hardware in silicon carbide. Furthermore, we propose applications in three areas: the TE-pass filter, the TM-pass filter, and the highly reflective photonic crystal mirror, which can be utilized for efficient collection and propagating mode selection of light emission.
An efficient antenna system with improved radiation for multi-standard/multi-mode 5G cellular communications
Authors: Parchin Naser Ojaroudi , Mohamed Heba G. , Moussa Karim H. , See Chan Hwang , Abd-Alhameed Raed A. , Alwadai Norah Muhammad , Amar Ahmed S. I.
Published: March 2023

This paper introduces a multi-input multiple-output (MIMO) antenna array system that provides improved radiation diversity for multi-standard/multi-mode 5G communications. The introduced MIMO design contains four pairs of miniaturized self-complementary antennas (SCAs) fed by pairs of independently coupled structures which are symmetrically located at the edge corners of the smartphone mainboard with an overall size of 75 × 150 (mm2). Hence, in total, the design incorporates four pairs of horizontally and vertically polarized resonators. The elements have compact profiles and resonate at 3.6 GHz, the main candidate bands of the sub-6 GHz 5G spectrum. In addition, despite the absence of decoupling structures, adjacent elements demonstrate high isolation. To the best of the authors’ knowledge, it is the first type of smartphone antenna design using dual-polarized self-complementary antennas that could possess anti-interference and diversity properties. In addition to exhibiting desirable radiation coverage, the presented smartphone antenna also supports dual polarizations on different sides of the printed circuit board (PCB). It also exhibits good isolation, high-gain patterns, improved radiation coverage, low ECC/TARC, and sufficient channel capacity. The introduced antenna design was manufactured on a standard smartphone board and its main characteristics were experimentally measured. Simulations and measurement results are generally in good agreement with each other. Moreover, the presented antenna system delivers low SAR with adequate efficiency when it comes to the appearance of the user. Hence, the design could be adapted to 5G hand-portable devices. As an additional feature, a new ultra-compact phased array millimeter-wave antenna with super-wide bandwidth and end-fire radiation is being introduced for integration into the MIMO antenna systems. As a result, the proposed antenna system design with improved radiation and multi-standard operation is a good candidate for future multi-mode 5G cellular applications.
The predictive model for COVID-19 pandemic plastic pollution by using deep learning method
Authors: Nanehkaran Yaser A. , Licai Zhu , Azarafza Mohammad , Talaei Sona , Jinxia Xu , Chen Junde , Derakhshani Reza
Published: March 2023

Pandemic plastics (e.g., masks, gloves, aprons, and sanitizer bottles) are global consequences of COVID-19 pandemic-infected waste, which has increased significantly throughout the world. These hazardous wastes play an important role in environmental pollution and indirectly spread COVID-19. Predicting the environmental impacts of these wastes can be used to provide situational management, conduct control procedures, and reduce the COVID-19 effects. In this regard, the presented study attempted to provide a deep learning-based predictive model for forecasting the expansion of the pandemic plastic in the megacities of Iran. As a methodology, a database was gathered from February 27, 2020, to October 10, 2021, for COVID-19 spread and personal protective equipment usage in this period. The dataset was trained and validated using training (80%) and testing (20%) datasets by a deep neural network (DNN) procedure to forecast pandemic plastic pollution. Performance of the DNN-based model is controlled by the confusion matrix, receiver operating characteristic (ROC) curve, and justified by the k-nearest neighbours, decision tree, random forests, support vector machines, Gaussian naïve Bayes, logistic regression, and multilayer perceptron methods. According to the comparative modelling results, the DNN-based model was found to predict more accurately than other methods and have a significant predominance over others with a lower errors rate (MSE = 0.024, RMSE = 0.027, MAPE = 0.025). The ROC curve analysis results (overall accuracy) indicate the DNN model (AUC = 0.929) had the highest score among others.
Human footprint is associated with shifts in the assemblages of major vector-borne diseases
Authors: Skinner Eloise B. , Glidden Caroline K. , MacDonald Andrew J. , Mordecai Erin A.
Published: March 2023

Predicting how increasing intensity of human–environment interactions affects pathogen transmission is essential to anticipate changing disease risks and identify appropriate mitigation strategies. Vector-borne diseases (VBDs) are highly responsive to environmental changes, but such responses are notoriously difficult to isolate because pathogen transmission depends on a suite of ecological and social responses in vectors and hosts that may differ across species. Here we use the emerging tools of cumulative pressure mapping and machine learning to better understand how the occurrence of six medically important VBDs, differing in ecology from sylvatic to urban, respond to multidimensional effects of human pressure. We find that not only is human footprint—an index of human pressure, incorporating built environments, energy and transportation infrastructure, agricultural lands and human population density—an important predictor of VBD occurrence, but there are clear thresholds governing the occurrence of different VBDs. Across a spectrum of human pressure, diseases associated with lower human pressure, including malaria, cutaneous leishmaniasis and visceral leishmaniasis, give way to diseases associated with high human pressure, such as dengue, chikungunya and Zika. These heterogeneous responses of VBDs to human pressure highlight thresholds of land-use transitions that may lead to abrupt shifts in infectious disease burdens and public health needs.
Placental cell type deconvolution reveals that cell proportions drive preeclampsia gene expression differences
Authors: Campbell Kyle A. , Colacino Justin A. , Puttabyatappa Muraly , Dou John F. , Elkin Elana R. , Hammoud Saher S. , Domino Steven E. , Dolinoy Dana C. , Goodrich Jaclyn M. , Loch-Caruso Rita , Padmanabhan Vasantha , Bakulski Kelly M.
Published: March 2023

The placenta mediates adverse pregnancy outcomes, including preeclampsia, which is characterized by gestational hypertension and proteinuria. Placental cell type heterogeneity in preeclampsia is not well-understood and limits mechanistic interpretation of bulk gene expression measures. We generated single-cell RNA-sequencing samples for integration with existing data to create the largest deconvolution reference of 19 fetal and 8 maternal cell types from placental villous tissue (n = 9 biological replicates) at term (n = 40,494 cells). We deconvoluted eight published microarray case–control studies of preeclampsia (n = 173 controls, 157 cases). Preeclampsia was associated with excess extravillous trophoblasts and fewer mesenchymal and Hofbauer cells. Adjustment for cellular composition reduced preeclampsia-associated differentially expressed genes (log2 fold-change cutoff = 0.1, FDR < 0.05) from 1154 to 0, whereas downregulation of mitochondrial biogenesis, aerobic respiration, and ribosome biogenesis were robust to cell type adjustment, suggesting direct changes to these pathways. Cellular composition mediated a substantial proportion of the association between preeclampsia and FLT1 (37.8%, 95% CI [27.5%, 48.8%]), LEP (34.5%, 95% CI [26.0%, 44.9%]), and ENG (34.5%, 95% CI [25.0%, 45.3%]) overexpression. Our findings indicate substantial placental cellular heterogeneity in preeclampsia contributes to previously observed bulk gene expression differences. This deconvolution reference lays the groundwork for cellular heterogeneity-aware investigation into placental dysfunction and adverse birth outcomes.
Quantitative proteomic landscape of unstable atherosclerosis identifies molecular signatures and therapeutic targets for plaque stabilization
Authors: Chen Yung-Chih , Smith Meaghan , Ying Ya-Lan , Makridakis Manousos , Noonan Jonathan , Kanellakis Peter , Rai Alin , Salim Agus , Murphy Andrew , Bobik Alex , Vlahou Antonia , Greening David W. , Peter Karlheinz
Published: March 2023

Atherosclerotic plaque rupture leading to myocardial infarction is a major global health burden. Applying the tandem stenosis (TS) mouse model, which distinctively exhibits the characteristics of human plaque instability/rupture, we use quantitative proteomics to understand and directly compare unstable and stable atherosclerosis. Our data highlight the disparate natures and define unique protein signatures of unstable and stable atherosclerosis. Key proteins and pathway networks are identified such as the innate immune system, and neutrophil degranulation. The latter includes calprotectin S100A8/A9, which we validate in mouse and human unstable plaques, and we demonstrate the plaque-stabilizing effects of its inhibition. Overall, we provide critical insights into the unique proteomic landscape of unstable atherosclerosis (as distinct from stable atherosclerosis and vascular tissue). We further establish the TS model as a reliable preclinical tool for the discovery and testing of plaque-stabilizing drugs. Finally, we provide a knowledge resource defining unstable atherosclerosis that will facilitate the identification and validation of long-sought-after therapeutic targets and drugs for plaque stabilization.
The angiopoietin receptor Tie2 is atheroprotective in arterial endothelium
Authors: Anisimov Andrey , Fang Shentong , Hemanthakumar Karthik Amudhala , Örd Tiit , van Avondt Kristof , Chevre Raphael , Toropainen Anu , Singha Prosanta , Gilani Huda , Nguyen Su D. , Karaman Sinem , Korhonen Emilia A. , Adams Ralf H. , Augustin Hellmut G. , Öörni Katariina , Soehnlein Oliver , Kaikkonen Minna U. , Alitalo Kari
Published: March 2023

Leukocytes and resident cells in the arterial wall contribute to atherosclerosis, especially at sites of disturbed blood flow. Expression of endothelial Tie1 receptor tyrosine kinase is enhanced at these sites, and attenuation of its expression reduces atherosclerotic burden and decreases inflammation. However, Tie2 tyrosine kinase function in atherosclerosis is unknown. Here we provide genetic evidence from humans and from an atherosclerotic mouse model to show that TIE2 is associated with protection from coronary artery disease. We show that deletion of Tie2, or both Tie2 and Tie1, in the arterial endothelium promotes atherosclerosis by increasing Foxo1 nuclear localization, endothelial adhesion molecule expression and accumulation of immune cells. We also show that Tie2 is expressed in a subset of aortic fibroblasts, and its silencing in these cells increases expression of inflammation-related genes. Our findings indicate that unlike Tie1, the Tie2 receptor functions as the dominant endothelial angiopoietin receptor that protects from atherosclerosis.
A hybrid plasmonic nanoprobe using polyvinylpyrrolidone-capped bimetallic silver–gold nanostars for highly sensitive and reproducible solution-based SERS sensing
Authors: Atta Supriya , Vo-Dinh Tuan
Published: March 2023

This work describes a highly sensitive and reproducible solution-based SERS sensing platform utilizing polyvinylpyrrolidone (PVP) capped bimetallic silver–gold nanostars.
Palladium-catalyzed highly selectivegem-difluoroallylation of propargyl sulfonates withgem-difluoroallylboron
Authors: Li Hao-Wen , Luo Yun-Cheng , Yu Ling-Chao , Zhang Xingang
Published: March 2023

A palladium-catalyzedgem-difluoroallylation of propargyl sulfonates withgem-difluoroallylboron has been developed. The resulting products can serve as versatile synthons for diversified transformations.
Revelation of potential bioactive water-soluble Boc-l-valine and imidazole appended metal complexes {M = Co(ii), Cu(ii) & Zn(ii)}: synthesis, characterization, ct-DNA binding, pBR322 cleavage, SOD mimetic, and cytotoxicity studies
Authors: Akhter Suffora , Khursheed Salman , Arjmand Farukh , Tabassum Sartaj
Published: March 2023

Water-soluble conjugates of Co(ii), Cu(ii) and Zn(ii) (1–3), were synthesized and comprehensively characterized by various spectroscopic techniques (UV-visible, FT-IR, ESI-MS, EPR, 1H NMR, 13C NMR) and single crystal X-ray diffraction.
Postbiotics from Pichia kudriavzevii promote intestinal health performance through regulation of Limosilactobacillus reuteri in weaned piglets
Authors: Zhang Zhenting , Guo Qiujin , Wang Jing , Tan Hongyan , Jin Xuexia , Fan Yurong , Liu Jiali , Zhao Shumiao , Zheng Jinshui , Peng Nan
Published: March 2023

The Pichia kudriavzevii FZ12 are attractive as alternatives to antibiotics against post-weaning diarrhea. We identified cytochrome c from FZ12 postbiotics that presented a positive effect on the growth and colonization of Limosilactobacillus reuteri.
Polymer-based microfluidic device for on-chip counter-diffusive crystallization and in situ X-ray crystallography at room temperature
Authors: Saha Sarthak , Özden Can , Samkutty Alfred , Russi Silvia , Cohen Aina , Stratton Margaret M. , Perry Sarah L.
Published: March 2023

Here we have reported novel polymeric devices to control fluid flow using surface forces and capillary action to facilitate counter-diffusive, on-chip protein crystallization.
Silicon quantum dots: surface matter, what next?
Authors: Beri Deski
Published: March 2023

Silicon quantum dots (SiQDs) are of great interest because they are believed to be harmless to living organisms, mainly due to their low toxicity.
Chemotherapeutic-caused liver toxicity hinders nanomedicine development
Authors: Wu Pengfei , Zhang Yuhang , Zhu Shiyao , Wang Mo , Zhou Peng , Wang Guishuan , Li Wenqing
Published: March 2023

Cisplatin-induced hepatotoxicity reduces the liver clearance of AuNPs, which increases AuNP accumulation in the damaged liver than in the normal liver.
Probing the donor strength of yldiide ligands: synthesis, structure and reactivity of rhodium complexes with a PCylideN pincer ligand
Authors: Lapointe Sébastien , Duari Prakash , Gessner Viktoria H.
Published: March 2023

A series of rhodium carbonyl complexes with a PCy(H)N pincer ligand featuring a central ylide as donor site has been isolated to quantify the donor strength of yldiides in comparison to related ligands.
Oxygen vacancy engineered tin dioxide/tungsten disulfide heterostructure construction for effective NO sensing
Authors: Lv Baofeng , Pei Yongyong , Wu Shuo-En , Xu Tingting , Huang Xiaowen , Tian Yongtao , Wang Xinchang , Zeng Longhui , Li Xinjian
Published: March 2023

Oxygen vacancy engineered SnO2/WS2 heterostructures are constructed by an effective hydrothermal process to improve the sensitivity/selectivity and realize low operating temperature. The response (Rg/Ra) of the hybrid to 5 ppm NO was 6.24 at 75 °C.
Flux induced highly efficient and stable phosphor Sr2ScSbO6:Mn4+ for plant growth lighting
Authors: Meng Xue , Wang Zhijun , Yan Zekang , Guo Dongxu , Liu Mengdi , Gong Jie , Feng Xiuxiu , Zhang Ting , Li Xiaojie , Li Panlai
Published: March 2023

Sr2ScSbO5.6F0.4:Mn4+ presents excellent thermal stability and higher internal/external quantum efficiency with application prospects in indoor plant cultivation.
Elimination of grain boundary resistance in vanadoborate electrolyte via the hydrogen-bond interaction of glycerol
Authors: Zhang Shan , Lu Ying , Sun Xiu-Wei , Tian Hong-Rui , Bai Xue , Liu Shu-Xia
Published: March 2023

The addition of glycerol into a pellet of VB electrolyte can effectively eliminate its grain boundary resistance and make its proton conductivity approach the intrinsic conductivity indicated by a VB single crystal.
Fuelling electrocatalysis at a single nanoparticle by ion flow in a nanoconfined electrolyte layer
Authors: Godeffroy Louis , Shkirskiy Viacheslav , Noël Jean-Marc , Lemineur Jean-François , Kanoufi Frédéric
Published: March 2023

Electrocatalysis at an isolated nanoparticle induces the growth of an electrolyte nanodroplet by ion pumping across a nanochannel.
Electrochemical hydrogen isotope exchange of amines controlled by alternating current frequency
Authors: Behera Nibedita , Gunasekera Disni , Mahajan Jyoti P. , Frimpong Joseph , Liu Zhen-Fei , Luo Long
Published: March 2023

Here, we report an electrochemical protocol for hydrogen isotope exchange (HIE) at α-C(sp3)–H amine sites.
Review on comprehending and enhancing the initial coulombic efficiency of Li-rich Mn-based cathode materials in lithium-ion batteries
Authors: Wang Bo , Cui Jing , Li Zhaojin , Wang Huan , Zhang Di , Wang Qiujun , Sun Huilan , Wu Yimin A.
Published: March 2023

The reasons for the low initial coulomb efficiency in Li-rich Mn-based materials and its modification strategies are outlined and reviewed.
A post-synthetically modified porous organic polymer for photocatalytic water purification
Authors: Choi Minhyeok , Singh Nem , Son Subin , Kim Ji Hyeon , Kang Minjung , Park Su Hong , Choi Dong Hoon , Hong Chang Seop , Kim Jong Seung
Published: March 2023

We present the advancement of the photocatalytic water pollutant degradation efficiency of a porous organic polymer material via post-synthetic modification with platinum clusters.
Interfacial S–O bonds specifically boost Z-scheme charge separation in a CuInS2/In2O3 heterojunction for efficient photocatalytic activity
Authors: Fu Xiaofei , Tao Junwu , Zhao Zizhou , Sun Siwen , Zhao Lin , He Zuming , Gao Yong , Xia Yongmei
Published: March 2023

Schematic representation of the proposed photocatalytic mechanism on CuInS2/In2O3 for LOM degradation and Cr(vi) reduction under visible light irradiation.
Free-standing TiO2nanograssy tubular hybrid membrane for polysulfide trapping in Li–S battery
Authors: Dasarathan Suriyakumar , Sung Junghwan , Hong Jeong-Won , Jo Yung-Soo , Kim Byung Gon , Lee You-Jin , Choi Hae-Young , Park Jun-Woo , Kim Doohun
Published: March 2023

The growth of anodic TiO2nanotubes with a high layer thickness of greater than 20 μm, “nanograss” structures are typically formed on the outermost surface of TNT walls.
Advances in the synthesis of nitrogen-containing heterocyclic compounds byin situbenzyne cycloaddition
Authors: Yu Hui , Xu Feng
Published: March 2023

Benzyne is a relatively active intermediate, which can be used to construct diverse compounds with complex structures and potential applicationsviathe cyclization reaction of benzyne generatedin situfrom various precursors.
Towards hard-magnetic behavior of CoFe2O4 nanoparticles: a detailed study of crystalline and electronic structures, and magnetic properties
Authors: Manh D. H. , Thanh T. D. , Phan T. L. , Yang D. S.
Published: March 2023

We have used X-ray diffraction and absorption, and Raman spectroscopy to study impacts of the milling time tm (particle size d) on the structural characterization, electronic structure, and magnetic properties of CoFe2O4 nanoparticles.
α-Glucosidase inhibitory activities of flavonoid derivatives isolated from Bouea macrophylla: in vitro and in silico studies
Authors: Nguyen Ngoc-Hong , Tran Nguyen-Minh-An , Duong Thuc-Huy , Vo Giau Van
Published: March 2023

In continuation of our search for bioactive compounds from the Bouea macrophylla (B. macrophylla) plant, herein we describe some flavonoid-type compounds with the aim of investigating their antidiabetic properties.
Palladium Schiff base complex-modified Cu(BDC-NH2) metal–organic frameworks for C–N coupling
Authors: Rabiei Khadijeh , Mohammadkhani Zahra , Keypour Hassan , Kouhdareh Jamal
Published: March 2023

In this study, the synthesis of a novel functionalized metal–organic-framework (MOF) [Cu(BDC-NH2)@Schiff-base-Pd(ii)] catalyst via post-synthetic modification of Cu(BDC-NH2) is reported.
Each side chain of cyclosporin A is not essential for high passive permeability across lipid bilayers
Authors: Ono Takahiro , Tabata Kazuhito V. , Noji Hiroyuki , Morimoto Jumpei , Sando Shinsuke
Published: March 2023

Cyclosporin A showed lipid bilayer permeability even after the deletion of a side chain.
Rational design of a genetically encoded NMR zinc sensor
Authors: Zhao Zhuangyu , Zhou Mingyang , Zemerov Serge D. , Marmorstein Ronen , Dmochowski Ivan J.
Published: March 2023

Elucidating the biochemical roles of the essential metal ion, Zn2+, motivates detection strategies that are sensitive, selective, quantitative, and minimally invasive in living systems.
Sub-10 nm anatase TiO2 nanoparticles for rapid photocatalytic H2 production from lignocellulosic biomass
Authors: Huang Ze-Xin , Ma Chi , Zhang Fu-Guang , Cheng Quan , Liu Qing-Yu , Yuan Yong-Jun , Zhang Xuefeng
Published: March 2023

Sub-10 nm anatase TiO2 nanoparticle-modified Pt nanoclusters were constructed as highly-efficient photocatalysts for H2 production from lignocellulosic biomass, including rice straw, corncob, polar wood chip, bamboo, rice hull and wheat straw.
Impregnation of KOAc on PdAu/SiO2 causes Pd-acetate formation and metal restructuring
Authors: Jacobs Hunter P. , Elias Welman C. , Heck Kimberly N. , Dean David P. , Dodson Justin J. , Zhang Wenqing , Arredondo Jacob H. , Breckner Christian J. , Hong Kiheon , Botello Christopher R. , Chen Laiyuan , Mueller Sean G. , Alexander Steven R. , Miller Jeffrey T. , Wong Michael S.
Published: March 2023

During catalyst preparation, the simple wet impregnation of KOAc on bimetallic PdAu/SiO2 catalysts forms various Pd-acetate complexes, particularly at increasing concentrations of KOAc and AcOH, causing Pd leaching and metal restructuring.
Intense 1400–1600 nm circularly polarised luminescence from homo- and heteroleptic chiral erbium complexes
Authors: Willis Oliver G. , Pucci Andrea , Cavalli Enrico , Zinna Francesco , Di Bari Lorenzo
Published: March 2023

Efficient near-infrared circularly polarised luminescence (CPL) between 1400 and 1600 nm of four enantiomer pairs of homo- and heteroleptic complexes have been successfully measured.
DeepOCL: A deep neural network for Object Constraint Language generation from unrestricted nature language
Authors: Yang Yilong , Liu Yibo , Bao Tianshu , Wang Weiru , Niu Nan , Yin Yongfeng
Published: March 2023

Object Constraint Language (OCL) is one kind of lightweight formal specification, which is widely used for software verification and validation in NASA and Object Management Group projects. Although OCL provides a simple expressive syntax, it is hard for the developers to write correctly due to lacking knowledge of the mathematical foundations of the first‐order logic, which is approximately half accurate at the first stage of development. A deep neural network named DeepOCL is proposed, which takes the unrestricted natural language as inputs and automatically outputs the best‐scored OCL candidates without requiring a domain conceptual model that is compulsively required in existing rule‐based generation approaches. To demonstrate the validity of our proposed approach, ablation experiments were conducted on a new sentence‐aligned dataset named OCLPairs. The experiments show that the proposed DeepOCL can achieve state of the art for OCL statement generation, scored 74.30 on BLEU, and greatly outperformed experienced developers by 35.19%. The proposed approach is the first deep learning approach to generate the OCL expression from the natural language. It can be further developed as a CASE tool for the software industry.
Stable data‐driven Koopman predictive control: Concentrated solar collector field case study
Authors: Gholaminejad Tahereh , Khaki‐Sedigh Ali
Published: March 2023

Non‐linearity is an inherent feature of practical systems. Although there have been significant advances in the control of nonlinear systems, the proposed methods often require considerable computational resources or rely on local linearization around equilibrium points. The Koopman operator is an infinite‐dimensional linear operator that fully captures a system's non‐linear dynamics. However, one of the major problems is identifying a Koopman finite dimensional linear model for a nonlinear system. Initiated by the Willems’ fundamental Lemma, a class of data‐driven control methods has been developed for linear systems without the need to identify the system's matrices. Motivated by these two ideas, a data‐driven Koopman‐based predictive control scheme for non‐linear systems is proposed for unknown disturbed non‐linear systems utilising a finite‐length dataset. Then, considering the uncertainty in the Koopman state variables, a robust data‐driven Koopman predictive control structure is presented. Also, the results led to the design of a data‐driven Koopman predictive control strategy with terminal components to ensure the closed‐loop stability of nonlinear systems. The proposed scheme is tested on the distributed‐parameter model of the ACUREX solar collector field (located at Almería, Spain) to regulate the field outlet temperature around a desired value. Finally, simulation results show the effectiveness of the proposed approach.
Chitosan application towards the improvement of grapevine performance and wine quality
Authors: Soares Bruno , Barbosa Catarina , Oliveira Manuel João
Published: March 2023

Intensification of agrochemicals application in vineyards has raised several concerns in Viticulture and Oenology value chain. Efforts have been developed to optimize grapevine health and productivity, assuring that viticulture is sustainable and competitive in today’s wine market. Viticulture practices have constantly been improved for a more sustainable and environment-friendly production, reducing the application of agrochemicals, replacing them by natural compounds that can have a double effect: protect grapevine against pathogens and improve compounds related to grape organoleptic quality. In this context, the development and optimization of alternative strategies to improve and enhance plant defences and grape/wine quality is becoming a necessity. Since the 1980s, chitosan has become a compound of special interest due to its double effect as elicitor and grapevine biostimulant, representing a complement to soil fertilisation, and reducing the negative effects nutrients leaching into the groundwater. The present review aims to present the wide possibilities of chitosan applications on grapevines to prevent and combat the main diseases and to improve wine quality. In this way, relevant studies about chitosan application will be presented as well as some concerns and limitations in order to cover the knowledge gaps inherent to its application in vineyard and wine as well.
Guide clinique des défauts primaires d’éruption
Authors: Choukroune Chloé
Published: March 2023

Le défaut primaire d’éruption (DPE) est un trouble de l’éruption d’origine génétique. Il a été décrit pour la première fois en 1981 par William Proffit et Katherine Vig. Il peut être mis en évidence par l’association d’un interrogatoire précis, de la présence de signes cliniques et d’un examen radiologique. Toutefois, son diagnostic reste complexe, notamment en l’absence de test génétique destiné à l’usage quotidien des professionnels de santé.

La prise en charge n’est pas aisée, puisque les dents tendent à s’ankyloser. Elle requiert systématiquement une réfléxion pluridisciplinaire.

Cet article propose un guide clinique afin d’identifier les signes de ce trouble de l’éruption pour faciliter son diagnostic et sa prise en charge.
Our Voyage from Catalytic Cross-Hydroalkenylation to Transfer-Dehydroaromatization of Cyclic π-Systems: Reactivity and Selectivity Changes Enabled by NHC-Ni and NHC-Pd Hydride Equivalents
Authors: Chen Yang , Chen Weihao , Ho Chun-Yu , Gu Xiao
Published: March 2023

N-Heterocyclic carbene ligated transition-metal catalysts often show interesting properties and reactivity as compared to conventional ligand systems. In (NHC)Ni and (NHC)Pd hydrides, a dramatic reactivity changed from cross-hydroalkenylation to transfer-dehydroaromatization was observed under optimized conditions. This account summarizes our recent efforts and stories behind this serendipitous discovery. The mechanistic studies revealed that the keys to divert the desired reactivity are the differences in the olefin insertion selectivity and the hydrometallated species reactivity.
An algorithm for predicting job vacancies using online job postings in Australia
Authors: Evans David , Mason Claire , Chen Haohui , Reeson Andrew
Published: March 2023

Timely and accurate statistics on the labour market enable policymakers to rapidly respond to changing economic conditions. Estimates of job vacancies by national statistical agencies are highly accurate but reported infrequently and with time lags. In contrast, online job postings provide a high-frequency indicator of vacancies with less accuracy. In this study we develop a robust signal averaging algorithm to measure job vacancies using online job postings data. We apply the algorithm using data on Australian job postings and show that it accurately predicts changes in job vacancies over a 4.5-year period. We also show that the algorithm is significantly more accurate than using raw counts of job postings to predict vacancies. The algorithm therefore offers a promising approach to the timely and reliable measurement of changes in vacancies.
A computational study of pseudo-filamentary nanosecond pulsed dielectric barrier discharge in atmospheric air
Authors: Li Yanru , Guo Yulin , Zhu Yifei , Sun Anbang
Published: March 2023

The formation and propagation of pseudo-filamentary dielectric barrier discharge in atmospheric air are investigated through a 2D fluid model. The discharge development can be divided into three stages: the volume streamer stage, the surface streamer stage, and the reverse discharge stage. The simulations show that the streamer head becomes wider and the electron density of the volume streamer head increases six times when the volume streamer interacts with the dielectric, and the volume streamer transforms into the surface streamer after the interaction. Compared with volume streamers, surface streamers have a smaller radius, a higher electric field, and a higher electron density. Furthermore, the parameters that may influence the discharge characteristics are also studied. It is found that a larger dielectric permittivity, a thinner dielectric, or a shorter voltage rise time leads to earlier inception of volume streamers, faster propagation of surface streamers, and higher current density. It is observed that the velocity of the surface streamer increases first, and then, decreases with the accumulated charges on the surface.
Existence results for fractional Kirchhoff problems with magnetic field and supercritical growth
Authors: Gao Liu , Tan Zhong
Published: March 2023

In this paper, we investigate a class of fractional Kirchhoff problems with a magnetic field and supercritical growth. By employing a truncation argument and Moser iterative method, we obtain the existence of nontrivial solutions. Our results are new and supplement the previous ones in the literature.
High-speed CMOS-free purely spintronic asynchronous recurrent neural network
Authors: Mathews Pranav O. , Duffee Christian B. , Thayil Abel , Stovall Ty E. , Bennett Christopher H. , Garcia-Sanchez Felipe , Marinella Matthew J. , Incorvia Jean Anne C. , Hassan Naimul , Hu Xuan , Friedman Joseph S.
Published: March 2023

The exceptional capabilities of the human brain provide inspiration for artificially intelligent hardware that mimics both the function and the structure of neurobiology. In particular, the recent development of nanodevices with biomimetic characteristics promises to enable the development of neuromorphic architectures with exceptional computational efficiency. In this work, we propose biomimetic neurons comprised of domain wall-magnetic tunnel junctions that can be integrated into the first trainable CMOS-free recurrent neural network with biomimetic components. This paper demonstrates the computational effectiveness of this system for benchmark tasks and its superior computational efficiency relative to alternative approaches for recurrent neural networks.
From memristive devices to neuromorphic systems
Authors: Huang Yi , Kiani Fatemeh , Ye Fan , Xia Qiangfei
Published: March 2023

Progress in hardware and algorithms for artificial intelligence (AI) has ushered in large machine learning models and various applications impacting our everyday lives. However, today's AI, mainly artificial neural networks, still cannot compete with human brains because of two major issues: the high energy consumption of the hardware running AI models and the lack of ability to generalize knowledge and self-adapt to changes. Neuromorphic systems built upon emerging devices, for instance, memristors, provide a promising path to address these issues. Although innovative memristor devices and circuit designs have been proposed for neuromorphic computing and applied to different proof-of-concept applications, there is still a long way to go to build large-scale low-power memristor-based neuromorphic systems that can bridge the gap between AI and biological brains. This Perspective summarizes the progress and challenges from memristor devices to neuromorphic systems and proposes possible directions for neuromorphic system implementation based on memristive devices.
Alteration in skin mycobiome due to atopic dermatitis and seborrheic dermatitis
Authors: Jung Won Hee
Published: March 2023

A microbiome consists of viruses, bacteria, archaea, fungi, and other microeukaryotes. It influences host immune systems and contributes to the development of various diseases, such as obesity, diabetes, asthma, and skin diseases, including atopic dermatitis and seborrheic dermatitis. The skin is the largest organ in the human body and has various microorganisms on its surface. Several studies on skin microbiomes have illustrated the effects of their composition, metabolites, and interactions with host cells on diseases. However, most studies have focused on the bacterial microbiome rather than the fungal microbiome, namely, mycobiome, although emerging evidence indicates that fungi also play a critical role in skin microbiomes through interactions with the host cells. I briefly summarize the current progress in the analysis of mycobiomes on human skin. I focused on alteration of the skin mycobiome caused by atopic and seborrheic dermatitis, with an emphasis on the Malassezia genus, which are the most dominant fungi residing here.