bluuebunny/crossref_metadata_2025 huggingface dataset:
MHD flow of time-fractional Casson nanofluid using generalized Fourier and Fick's laws over an inclined channel with applications of gold nanoparticles
Authors: Shah Jamal , Ali Farhad , Khan Naveed , Ahmad Zubair , Murtaza Saqib , Khan Ilyas , Mahmoud Omar
Published: October 2022

Gold nanoparticles are commonly used as a tracer in laboratories. They are biocompatible and can transport heat energy to tumor cells via a variety of clinical techniques. As cancer cells are tiny, properly sized nanoparticles were introduced into the circulation for invasion. As a result, gold nanoparticles are highly effective. Therefore, the current research investigates the magnetohydrodynamic free convection flow of Casson nanofluid in an inclined channel. The blood is considered as a base fluid, and gold nanoparticles are assumed to be uniformly dispersed in it. The above flow regime is formulated in terms of partial differential equations. The system of derived equations with imposed boundary conditions is non-dimensionalized using appropriate dimensionless variables. Fourier's and Fick's laws are used to fractionalize the classical dimensionless model. The Laplace and Fourier sine transformations with a new transformation are used for the closed-form solutions of the considered problem. Finally, the results are expressed in terms of a specific function known as the Mittag-Leffler function. Various figures and tables present the effect of various physical parameters on the achieved results. Graphical results conclude that the fractional Casson fluid model described a more realistic aspect of the fluid velocity profile, temperature, and concentration profile than the classical Casson fluid model. The heat transfer rate and Sherwood number are calculated and presented in tabular form. It is worth noting that increasing the volume percentage of gold nanoparticles from 0 to 0.04 percent resulted in an increase of up to 3.825% in the heat transfer rate.
Discovery of small molecule inhibitors that effectively disrupt IQGAP1-Cdc42 interaction in breast cancer cells
Authors: Sayedyahossein Samar , Smith Jessica , Barnaeva Elena , Li Zhigang , Choe Jun , Ronzetti Michael , Dextras Christopher , Hu Xin , Marugan Juan , Southall Noel , Baljinnyam Bolormaa , Thines Louise , Tran Andy D. , Ferrer Marc , Sacks David B.
Published: October 2022

The small GTPase Cdc42 is an integral component of the cytoskeleton, and its dysregulation leads to pathophysiological conditions, such as cancer. Binding of Cdc42 to the scaffold protein IQGAP1 stabilizes Cdc42 in its active form. The interaction between Cdc42 and IQGAP1 enhances migration and invasion of cancer cells. Disrupting this association could impair neoplastic progression and metastasis; however, no effective means to achieve this has been described. Here, we screened 78,500 compounds using a homogeneous time resolved fluorescence-based assay to identify small molecules that disrupt the binding of Cdc42 to IQGAP1. From the combined results of the validation assay and counter-screens, we selected 44 potent compounds for cell-based experiments. Immunoprecipitation and cell viability analysis rendered four lead compounds, namely NCGC00131308, NCGC00098561, MLS000332963 and NCGC00138812, three of which inhibited proliferation and migration of breast carcinoma cells. Microscale thermophoresis revealed that two compounds bind directly to Cdc42. One compound reduced the amount of active Cdc42 in cells and effectively impaired filopodia formation. Docking analysis provided plausible models of the compounds binding to the hydrophobic pocket adjacent to the GTP binding site of Cdc42. In conclusion, we identified small molecules that inhibit binding between Cdc42 and IQGAP1, which could potentially yield chemotherapeutic agents.
Strength-mass scaling law governs mass distribution inside honey bee swarms
Authors: Shishkov Olga , Chen Claudia , Madonna Claire Allison , Jayaram Kaushik , Peleg Orit
Published: October 2022

To survive during colony reproduction, bees create dense clusters of thousands of suspended individuals. How does this swarm, which is orders of magnitude larger than the size of an individual, maintain mechanical stability? We hypothesize that the internal structure in the bulk of the swarm, about which there is little prior information, plays a key role in mechanical stability. Here, we provide the first-ever 3D reconstructions of the positions of the bees in the bulk of the swarm using x-ray computed tomography. We find that the mass of bees in a layer decreases with distance from the attachment surface. By quantifying the distribution of bees within swarms varying in size (made up of 4000–10,000 bees), we find that the same power law governs the smallest and largest swarms, with the weight supported by each layer scaling with the mass of each layer to the $$\approx 1.5$$

≈
1.5

power. This arrangement ensures that each layer exerts the same fraction of its total strength, and on average a bee supports a lower weight than its maximum grip strength. This illustrates the extension of the scaling law relating weight to strength of single organisms to the weight distribution within a superorganism made up of thousands of individuals.
Global distribution of soil fauna functional groups and their estimated litter consumption across biomes
Authors: Heděnec Petr , Jiménez Juan Jose , Moradi Jabbar , Domene Xavier , Hackenberger Davorka , Barot Sebastien , Frossard Aline , Oktaba Lidia , Filser Juliane , Kindlmann Pavel , Frouz Jan
Published: October 2022

Soil invertebrates (i.e., soil fauna) are important drivers of many key processes in soils including soil aggregate formation, water retention, and soil organic matter transformation. Many soil fauna groups directly or indirectly participate in litter consumption. However, the quantity of litter consumed by major faunal groups across biomes remains unknown. To estimate this quantity, we reviewed > 1000 observations from 70 studies that determined the biomass of soil fauna across various biomes and 200 observations from 44 studies on litter consumption by soil fauna. To compare litter consumption with annual litterfall, we analyzed 692 observations from 24 litterfall studies and 183 observations from 28 litter stock studies. The biomass of faunal groups was highest in temperate grasslands and then decreased in the following order: boreal forest > temperate forest > tropical grassland > tundra > tropical forest > Mediterranean ecosystems > desert and semidesert. Tropical grasslands, desert biomes, and Mediterranean ecosystems were dominated by termites. Temperate grasslands were dominated by omnivores, while temperate forests were dominated by earthworms. On average, estimated litter consumption (relative to total litter input) ranged from a low of 14.9% in deserts to a high of 100.4% in temperate grassland. Litter consumption by soil fauna was greater in grasslands than in forests. This is the first study to estimate the effect of different soil fauna groups on litter consumption and related processes at global scale.
No evidence for intervention-associated DNA methylation changes in monocytes of patients with posttraumatic stress disorder
Authors: Hummel Elisabeth , Elgizouli Magdeldin , Sicorello Maurizio , Leitão Elsa , Beygo Jasmin , Schröder Christopher , Zeschnigk Michael , Müller Svenja , Herpertz Stephan , Moser Dirk , Kessler Henrik , Horsthemke Bernhard , Kumsta Robert
Published: October 2022

DNA methylation patterns can be responsive to environmental influences. This observation has sparked interest in the potential for psychological interventions to influence epigenetic processes. Recent studies have observed correlations between DNA methylation changes and therapy outcome. However, most did not control for changes in cell composition. This study had two aims: first, we sought to replicate therapy-associated changes in DNA methylation of commonly assessed candidate genes in isolated monocytes from 60 female patients with post-traumatic stress disorder (PTSD). Our second, exploratory goal was to identify novel genomic regions with substantial pre-to-post intervention DNA methylation changes by performing whole-genome bisulfite sequencing (WGBS) in two patients with PTSD. Equivalence testing and Bayesian analyses provided evidence against physiologically meaningful intervention-associated DNA methylation changes in monocytes of PTSD patients in commonly investigated target genes (NR3C1, FKBP5, SLC6A4, OXTR). Furthermore, WGBS yielded only a limited set of candidate regions with suggestive evidence of differential DNA methylation pre- to post-therapy. These differential DNA methylation patterns did not prove replicable when investigated in the entire cohort. We conclude that there is no evidence for major, recurrent intervention-associated DNA methylation changes in the investigated genes in monocytes of patients with PTSD.
Factors influencing patient disclosure of cancer diagnosis to the family dentist: online survey in Japan
Authors: Lee Kyunghee , Takase Kozo , Fushimi Kiyohide
Published: October 2022

Oral care during cancer treatment constitutes essential supportive care. We aimed to identify factors associated with cancer patients informing their family dentists about their cancer diagnosis. Using the generated original questionnaire, we conducted a cross-sectional questionnaire study in 500 cancer patients (gastric, colorectal, lung, breast, and prostate cancer) through the Internet from September 10 to 13, 2019. The factors influencing patients’ disclosure of their cancer diagnosis to their family dentist were identified by multivariable logistic regression analysis. Nearly half of the respondents (42.2%) informed their family dentist that they had cancer. The disclosing behavior of cancer patients was distinctively associated with their physician’s advice (odds ratio [OR] 59.3; 95% confidence interval [CI] 7.7–456.3); 8.6% of all respondents were advised to inform their dentist about their cancer diagnosis. In the group without the physician's advice, good relationship with family dentist was associated with disclosing behavior. This study indicates the need for support for cancer patients to receive appropriate oral care; patients' perceptions of the physician’s advice and communication with the family dentist should be motivators for disclosing the cancer diagnosis to dentists. Medical workers involved in cancer care should demonstrate the benefit of medical-dental collaboration in cancer care of patients.
How the Great Plains Dust Bowl drought spread heat extremes around the Northern Hemisphere
Authors: Meehl Gerald A. , Teng Haiyan , Rosenbloom Nan , Hu Aixue , Tebaldi Claudia , Walton Guy
Published: October 2022

Extraordinary heat extremes occurred in the 1930s in areas of the Northern Hemisphere far from the record setting heat over the US associated with the Great Plains Dust Bowl drought. A climate model sensitivity experiment is used to identify a new mechanism involving a warm season circumglobal atmospheric teleconnection pattern that spread heat extremes over far-flung areas of the Northern Hemisphere arising from the intense heating over the desiccated Great Plains themselves. It has only been in the twenty-first century that human populations in these regions of the Northern Hemisphere have experienced heat extremes comparable to the 1930s. This demonstrates that humans influenced Northern Hemisphere temperature and heat extremes through disastrous and unprecedented regional land use practices over the Great Plains, and points to the possibility that future intense regional droughts could affect heat extremes on hemispheric scales.
Tensile strain and altered synovial tissue metabolism in human knee osteoarthritis
Authors: Philpott Holly T. , Birmingham Trevor B. , Fiset Benoit , Walsh Logan A. , Coleman Mitchell C. , Séguin Cheryle A. , Appleton C. Thomas
Published: October 2022

Synovium is critical for maintaining joint homeostasis and may contribute to mechanobiological responses during joint movement. We investigated mechanobiological responses of whole synovium from patients with late-stage knee osteoarthritis (OA). Synovium samples were collected during total knee arthroplasty and assigned to histopathology or cyclic 10% tensile strain loading, including (1) static (control); (2) low-frequency (0.3 Hz); and iii) high-frequency (1.0 Hz) for 30-min. After 6-h incubation, tissues were bisected for RNA isolation and immunostaining (3-nitrotyrosine; 3-NT). RNA sequencing was analyzed for differentially expressed genes and pathway enrichment. Cytokines and lactate were measured in conditioned media. Compared to controls, low-frequency strain induced enrichment of pathways related to interferon response, Fc-receptor signaling, and cell metabolism. High-frequency strain induced enrichment of pathways related to NOD-like receptor signaling, high metabolic demand, and redox signaling/stress. Metabolic and redox cell stress was confirmed by increased release of lactate into conditioned media and increased 3-NT formation in the synovial lining. Late-stage OA synovial tissue responses to tensile strain include frequency-dependent increases in inflammatory signaling, metabolism, and redox biology. Based on these findings, we speculate that some synovial mechanobiological responses to strain may be beneficial, but OA likely disturbs synovial homeostasis leading to aberrant responses to mechanical stimuli, which requires further validation.
Effects of lifestyle risk behaviour clustering on cardiovascular disease among UK adults: latent class analysis with distal outcomes
Authors: Tegegne Teketo Kassaw , Islam Sheikh Mohammed Shariful , Maddison Ralph
Published: October 2022

Lifestyle risk behaviours such as smoking, physical inactivity, and unhealthy diet account for a considerable disease burden globally. These risk behaviours tend to cluster within an individual, which could have detrimental health effects. In this study, we aimed to examine the clustering effect of lifestyle risk behaviours on cardiovascular disease (CVD) and CVD risk among adults in the United Kingdom (UK). We performed a latent class (LC) analysis with distal outcomes using the UK Biobank baseline (2006–2010) data. First, we estimated LC measurement models, followed by an auxiliary model conditional on LC variables. We reported continuous (mean difference—MD) and binary (odds ratio—OR) outcomes with 95% confidence intervals. We included 283,172 and 174,030 UK adults who had data on CVD and CVD risk, respectively. Multiple lifestyle risk behaviour clustering (physically inactive, poor fruit & vegetable intake, high alcohol intake, and prolonged sitting) had a 3.29 mean increase in CVD risk compared to high alcohol intake. In addition, adults with three risk behaviours (physically inactive, poor fruit & vegetable intake, and high alcohol intake) had 25.18 higher odds of having CVD than those with two risk behaviours (physically inactive, and poor fruit and vegetable intake). Social deprivation, gender and age were also associated with CVD. Individuals' LC membership with two or more lifestyle risk behaviours negatively affects CVD. Interventions targeting multiple lifestyle behaviours and social circumstances should be prioritized to reduce the CVD burden.
splitSMLM, a spectral demixing method for high-precision multi-color localization microscopy applied to nuclear pore complexes
Authors: Andronov Leonid , Genthial Rachel , Hentsch Didier , Klaholz Bruno P.
Published: October 2022

Single molecule localization microscopy (SMLM) with a dichroic image splitter can provide invaluable multi-color information regarding colocalization of individual molecules, but it often suffers from technical limitations. Classical demixing algorithms tend to give suboptimal results in terms of localization precision and correction of chromatic errors. Here we present an image splitter based multi-color SMLM method (splitSMLM) that offers much improved localization precision and drift correction, compensation of chromatic distortions, and optimized performance of fluorophores in a specific buffer to equalize their reactivation rates for simultaneous imaging. A novel spectral demixing algorithm, SplitViSu, fully preserves localization precision with essentially no data loss and corrects chromatic errors at the nanometer scale. Multi-color performance is further improved by using optimized fluorophore and filter combinations. Applied to three-color imaging of the nuclear pore complex (NPC), this method provides a refined positioning of the individual NPC proteins and reveals that Pom121 clusters act as NPC deposition loci, hence illustrating strength and general applicability of the method.
Noradrenergic consolidation of social recognition memory is mediated by β-arrestin–biased signaling in the mouse prefrontal cortex
Authors: Cheng Deqin , Wu Junwen , Yan Enhui , Fan Xiaocen , Wang Feifei , Ma Lan , Liu Xing
Published: October 2022

Social recognition memory (SRM) is critical for maintaining social relationships and increasing the survival rate. The medial prefrontal cortex (mPFC) is an important brain area associated with SRM storage. Norepinephrine (NE) release regulates mPFC neuronal intrinsic excitability and excitatory synaptic transmission, however, the roles of NE signaling in the circuitry of the locus coeruleus (LC) pathway to the mPFC during SRM storage are unknown. Here we found that LC-mPFC NE projections bidirectionally regulated SRM consolidation. Propranolol infusion and β-adrenergic receptors (β-ARs) or β-arrestin2 knockout in the mPFC disrupted SRM consolidation. When carvedilol, a β-blocker that can mildly activate β-arrestin-biased signaling, was injected, the mice showed no significant suppression of SRM consolidation. The impaired SRM consolidation caused by β1-AR or β-arrestin2 knockout in the mPFC was not rescued by activating LC-mPFC NE projections; however, the impaired SRM by inhibition of LC-mPFC NE projections or β1-AR knockout in the mPFC was restored by activating the β-arrestin signaling pathway in the mPFC. Furthermore, the activation of β-arrestin signaling improved SRM consolidation in aged mice. Our study suggests that LC-mPFC NE projections regulate SRM consolidation through β-arrestin-biased β-AR signaling.
Reconstruction of ovine axonal cytoarchitecture enables more accurate models of brain biomechanics
Authors: Bernardini Andrea , Trovatelli Marco , Kłosowski Michał M. , Pederzani Matteo , Zani Davide Danilo , Brizzola Stefano , Porter Alexandra , Rodriguez y Baena Ferdinando , Dini Daniele
Published: October 2022

There is an increased need and focus to understand how local brain microstructure affects the transport of drug molecules directly administered to the brain tissue, for example in convection-enhanced delivery procedures. This study reports a systematic attempt to characterize the cytoarchitecture of commissural, long association and projection fibres, namely the corpus callosum, the fornix and the corona radiata, with the specific aim to map different regions of the tissue and provide essential information for the development of accurate models of brain biomechanics. Ovine samples are imaged using scanning electron microscopy combined with focused ion beam milling to generate 3D volume reconstructions of the tissue at subcellular spatial resolution. Focus is placed on the characteristic cytological feature of the white matter: the axons and their alignment in the tissue. For each tract, a 3D reconstruction of relatively large volumes, including a significant number of axons, is performed and outer axonal ellipticity, outer axonal cross-sectional area and their relative perimeter are measured. The study of well-resolved microstructural features provides useful insight into the fibrous organization of the tissue, whose micromechanical behaviour is that of a composite material presenting elliptical tortuous tubular axonal structures embedded in the extra-cellular matrix. Drug flow can be captured through microstructurally-based models using 3D volumes, either reconstructed directly from images or generated in silico using parameters extracted from the database of images, leading to a workflow to enable physically-accurate simulations of drug delivery to the targeted tissue.
COX7A2L genetic variants determine cardiorespiratory fitness in mice and human
Authors: Benegiamo Giorgia , Bou Sleiman Maroun , Wohlwend Martin , Rodríguez-López Sandra , Goeminne Ludger J. E. , Laurila Pirkka-Pekka , Klevjer Marie , Salonen Minna K. , Lahti Jari , Jha Pooja , Cogliati Sara , Enriquez José Antonio , Brumpton Ben M. , Bye Anja , Eriksson Johan G. , Auwerx Johan
Published: October 2022

Mitochondrial respiratory complexes form superassembled structures called supercomplexes. COX7A2L is a supercomplex-specific assembly factor in mammals, although its implication for supercomplex formation and cellular metabolism remains controversial. Here we identify a role for COX7A2L for mitochondrial supercomplex formation in humans. By using human cis-expression quantitative trait loci data, we highlight genetic variants in the COX7A2L gene that affect its skeletal muscle expression specifically. The most significant cis-expression quantitative trait locus is a 10-bp insertion in the COX7A2L 3′ untranslated region that increases messenger RNA stability and expression. Human myotubes harboring this insertion have more supercomplexes and increased respiration. Notably, increased COX7A2L expression in the muscle is associated with lower body fat and improved cardiorespiratory fitness in humans. Accordingly, specific reconstitution of Cox7a2l expression in C57BL/6J mice leads to higher maximal oxygen consumption, increased lean mass and increased energy expenditure. Furthermore, Cox7a2l expression in mice is induced specifically in the muscle upon exercise. These findings elucidate the genetic basis of mitochondrial supercomplex formation and function in humans and show that COX7A2L plays an important role in cardiorespiratory fitness, which could have broad therapeutic implications in reducing cardiovascular mortality.
A phase II study of talazoparib monotherapy in patients with wild-type BRCA1 and BRCA2 with a mutation in other homologous recombination genes
Authors: Gruber Joshua J. , Afghahi Anosheh , Timms Kirsten , DeWees Alyssa , Gross Wyatt , Aushev Vasily N. , Wu Hsin-Ta , Balcioglu Mustafa , Sethi Himanshu , Scott Danika , Foran Jessica , McMillan Alex , Ford James M. , Telli Melinda L.
Published: October 2022

Talazoparib, a PARP inhibitor, is active in germline BRCA1 and BRCA2 (gBRCA1/2)-mutant advanced breast cancer, but its activity beyond gBRCA1/2 is poorly understood. We conducted Talazoparib Beyond BRCA (NCT02401347), an open-label phase II trial, to evaluate talazoparib in patients with pretreated advanced HER2-negative breast cancer (n = 13) or other solid tumors (n = 7) with mutations in homologous recombination (HR) pathway genes other than BRCA1 and BRCA2. In patients with breast cancer, four patients had a Response Evaluation Criteria in Solid Tumors (RECIST) partial response (overall response rate, 31%), and three additional patients had stable disease of ≥6 months (clinical benefit rate, 54%). All patients with germline mutations in PALB2(gPALB2; encoding partner and localizer of BRCA2) had treatment-associated tumor regression. Tumor or plasma circulating tumor DNA (ctDNA) HR deficiency (HRD) scores were correlated with treatment outcomes and were increased in all gPALB2 tumors. In addition, a gPALB2-associated mutational signature was associated with tumor response. Thus, talazoparib has been demonstrated to have efficacy in patients with advanced breast cancer who have gPALB2 mutations, showing activity in the context of HR pathway gene mutations beyond gBRCA1/2.
Zeolitic imidazolate framework-8 modified magnetic halloysite nanotube-based solid phase extraction for the analysis of carbamate pesticides by ultra-high performance liquid chromatography tandem mass spectrometry
Authors: Shi Zhihong , Tian Yuehong , Liu Junjie , Wu Wenwen , Gao Sifan , Zhang Hongyi
Published: October 2022

MHNTs@ZIF-8 based mSPE-UHPLC-MSMS for the analysis of carbamate pesticides in water.
A pH-responsive, endosomolytic liposome functionalized with membrane-anchoring, comb-like pseudopeptides for enhanced intracellular delivery and cancer treatment
Authors: Chen Siyuan , Morrison Gabriella , Liu Wenyuan , Kaur Apanpreet , Chen Rongjun
Published: October 2022

Low intracellular delivery efficiency and multidrug resistance are among major barriers to effective cancer therapy.
Eco design for Ag-based solutions against SARS-CoV-2 and E. coli
Authors: Costa Anna Luisa , Blosi Magda , Brigliadori Andrea , Zanoni Ilaria , Ortelli Simona , Simeone Felice Carlo , Delbue Serena , D'Alessandro Sarah , Parapini Silvia , Vineis Claudia , Varesano Alessio , Toprak Muhammet S. , Hamawandi Bejan , Gardini Davide
Published: October 2022

An effective, eco-friendly and easily scalable nanosilver-based technology offers affordable and broad-spectrum antimicrobial solutions against SARS-CoV-2 and Escherichia coli.
Molecular actions of different functional oligosaccharides on intestinal integrity, immune function and microbial community in weanling pigs
Authors: Gao Hang , Sun Feize , Lin Gang , Guo Yuhan , Zhao Jinbiao
Published: October 2022

This study investigated the effects of different functional oligosaccharides on the growth performance, intestinal barrier function and gut microbiota of weanling piglets.
Elevated serum phosphatidylcholine (16:1/22:6) levels promoted by fish oil and vitamin D3 are highly correlated with biomarkers of non-alcoholic fatty liver disease in Chinese subjects
Authors: Fan Ze-kai , Ma Wen-jun , Zhang Wei , Li Hui , Zhai Jie , Zhao Ting , Guo Xiao-fei , Sinclair Andrew J. , Li Duo
Published: October 2022

Phosphatidylcholine (16:1/22:6) was associated with improving inflammation and lipid metabolism.
DHA-enriched phosphatidylcholine from Clupea harengus roes regulates the gut–liver axis to ameliorate high-fat diet-induced non-alcoholic fatty liver disease
Authors: Qian Li , Tian Shanshan , Jiang Su , Tang Yunping , Han Tao
Published: October 2022

DHA-enriched phosphatidylcholine from Clupea harengus roes could likely be used as a functional food supplement for the prevention of high-fat diet-induced non-alcoholic fatty liver disease via the gut–liver axis.
Preparation of MoS2@AuNP nanocomposite by a self-reduction method and its application for electrochemical glucose sensing
Authors: Wang Jiameng , Zhang Wuyi , Chen Lanlan , Huang Jie , Shi Xiaojia , Han Dong , Wen Jia , Yan Hongyuan
Published: October 2022

A novel nanocomposite consisting of MoS2 and AuNPs was prepared by a simple self-reduction method without a reductant at room temperature. The as-prepared MoS2@AuNP nanocomposites were further used to construct an electrochemical glucose biosensor.
Diverse chemically recyclable polymers obtained by cationic vinyl and ring-opening polymerizations of the cyclic ketene acetal ester “dehydroaspirin”
Authors: Kazama Akane , Kohsaka Yasuhiro
Published: October 2022

Chemically recyclable polymers composed of carbon and/or ester backbones were prepared by vinyl and ring-opening polymerizations of a cyclic ketene acetal ester.
In silico study of inhibitory capacity of sacubitril/valsartan toward neprilysin and angiotensin receptor
Authors: Jovanović Jelena Đorović , Antonijević Marko , Vojinović Radiša , Filipović Nenad D. , Marković Zoran
Published: October 2022

The article presents results obtained from molecular docking and molecular dynamic simulations to examine the inhibitory capacity of Entresto.
Constructing a metal-free 2D covalent organic framework for visible-light-driven photocatalytic reduction of CO2: a sustainable strategy for atmospheric CO2 utilization
Authors: Sarkar Priyanka , Hazra Chowdhury Arpita , Riyajuddin Sk. , Ghosh Swarbhanu , Islam Sk. Manirul
Published: October 2022

A 2D polyimide-linked covalent organic framework (COF) with band gap energy of 2.2 eV is developed as a stable and efficient porous photocatalyst which shows CO2 reduction to formic acid, formaldehyde and methanol.
Effects of static mixers on continuous methyl ester production: comparing four types of 3D-printed mixing elements
Authors: Pongraktham Kritsakon , Somnuk Krit
Published: October 2022

Four types of 3D-printed static mixer were employed in the continuous transesterification process to examine the pressure drop and mixing intensity. Methanol, KOH, and mixer length were also optimized using RSM to obtain the highest biodiesel purity.
Insight into CO selective chemisorption from syngas mixtures through Li2MnO3; a new H2enrichment material
Authors: Hernández-Fontes Carlos , Araiza Daniel G. , Díaz Gabriela , Pfeiffer Heriberto
Published: October 2022

Li2MnO3is able to selectively trap CO in the presence of H2at high temperatures, favoring H2enrichment from syngas flows.
Ligand-free nickel catalyzed perfluoroalkylation of arenes and heteroarenes
Authors: Deolka Shubham , Govindarajan Ramadoss , Vasylevskyi Serhii , Roy Michael C. , Khusnutdinova Julia R. , Khaskin Eugene
Published: October 2022

A ligand-free, room temperature, Ni-catalyzed perfluoroalkylation of heteroarenes produced a diverse array of polyfluorinated adducts; potential in the late-stage functionalization of drugs and peptides is also demonstrated.
Phosphine-catalyzed activation of cyclopropenones: a versatile C3 synthon for (3+2) annulations with unsaturated electrophiles
Authors: He Xin , Ma Pengchen , Tang Yuhai , Li Jing , Shen Shenyu , Lear Martin J. , Houk K. N. , Xu Silong
Published: October 2022

A phosphine-catalyzed (3 + 2) annulation of cyclopropenones with a wide variety of electrophilic π systems has been developed, in which an α-ketenyl phosphorous ylide is validated as the key intermediate used as a versatile C3 synthon.
Ruthenium nanoparticles canopied by heptagon-containing saddle-shaped nanographenes as efficient aromatic hydrogenation catalysts
Authors: Cerezo-Navarrete Christian , David Arthur H. G. , García-Zaragoza Adrián , Codesal Marcos D. , Oña-Burgos Pascual , del Rosal Iker , Poteau Romuald , Campaña Araceli G. , Martínez-Prieto Luis M.
Published: October 2022

Ruthenium nanoparticles stabilized with non-planar polycyclic aromatic hydrocarbons (PAHs) are active catalysts in the hydrogenation of aromatic substrates under mild conditions.
Exploring the configurational space of amorphous graphene with machine-learned atomic energies
Authors: El-Machachi Zakariya , Wilson Mark , Deringer Volker L.
Published: October 2022

Machine-learning models for atomic energies can be used to drive Monte-Carlo structural exploration, and also to obtain new insight into disordered structures – as demonstrated here for amorphous graphene.
Catalytic ammonia reforming: alternative routes to net-zero-carbon hydrogen and fuel
Authors: Caballero Luis C. , Thornburg Nicholas E. , Nigra Michael M.
Published: October 2022

Ammonia is a promising net-zero-carbon energy vector whose hydrogen content is accessible via multiple catalytic pathways. This perspective highlights advances in NH3 reforming catalysis and opportunities for reaction engineering of reformer devices.
Galvanic replacement reaction in perovskite oxide for superior chemiresistors
Authors: Baek Jong Won , Kim Yoon Hwa , Ahn Jaewan , Kim Dong-Ha , Shin Hamin , Ko Jaehyun , Park Seyeon , Park Chungseong , Shin Euichul , Jang Ji-Soo , Kim Il-Doo
Published: October 2022

This work presents the synthesis of LaFeO3/SnO2 nanotubes (NTs) based on the GRR process, with perovskite LaFeO3 NTs prepared by electrospun nanofibers as the starting material resulting in a significantly enhanced catalytic activity.
Electrically powered artificial black body for low-voltage high-speed interfacial evaporation
Authors: Liu Fenghua , Pang Hongru , Gu Yunjiao , Ning Yuesheng , Bradley Robert , Zhao Binyuan , Wu Weiping
Published: October 2022

A record high evaporation rate of 98.7 kg m−2h−1with high energy conversion efficiency (81.1%) was achieved by applying electrical power to an artificial porous black body, enabling the successful creation of practical applications.
Advanced electrolyte systems with additives for high-cell-voltage and high-energy-density lithium batteries
Authors: Liu Jianwen , He Sicong , Liu Shaoqing , Wang Shiquan , Zhang Jiujun
Published: October 2022

Given that battery-powered electric vehicles and other power equipment put forward higher requirements for long recharge mileage, the development of high-performance lithium batteries (LBs) has become necessary.
Preparation of nanoscale cationic metal–organic framework Nano Mn(iii)-TP for theranostics based on valence changes
Authors: Yu Shijiang , Yu Hongliu , Si Panpan , Wang Zhen , Wang Bing , Lin Wenxin
Published: October 2022

Schematic illustrations of the synthesis and working principle of a platform MTXNa@Nano Mn(iii)-TP for tumor theranostics.
Photoresponse of an off-stoichiometry thiol–ene–epoxy (OSTE+) polymer
Authors: Das Sonatan , Singh Akanksha , Rao V. Ramgopal , Kundu Tapanendu
Published: October 2022

The thiol–ene–epoxy polymer-based planar-type photodetector has been fabricated by varying stoichiometric ratios of constituent monomers. This device exhibits light intensity-dependent photo-response that has enormous potential for photonic applications.
Growth characteristics and properties of Ga2O3 films fabricated by atomic layer deposition technique
Authors: Liu Xiangtai , Wang Shaoqing , He Lang , Jia Yifan , Lu Qin , Chen Haifeng , Ma Fei , Hao Yue
Published: October 2022

The review summarizes the precursors, characterization techniques, factors moderating film growth, and the properties such as crystal structure, chemical composition, surface morphology, and optical properties of Ga2O3 films fabricated by ALD.
A pentagonal 2D layered PdSe2-based synaptic device with a graphene floating gate
Authors: Park Eunpyo , Seo Jae Eun , Noh Gichang , Jo Yooyeon , Woo Dong Yeon , Kim In Soo , Park Jongkil , Kim Jaewook , Jeong YeonJoo , Lee Suyoun , Kim Inho , Park Jong-Keuk , Kim Sangbum , Chang Jiwon , Kwak Joon Young
Published: October 2022

Multiple synaptic weight states, a high handwritten digit recognition accuracy, and the spike-timing-dependent plasticity (STDP) biological learning rule are successfully demonstrated by using a pentagonal 2D layered PdSe2-based synaptic device.
Defect formation and carrier compensation in layered oxychalcogenide La2CdO2Se2: an insight from first principles
Authors: Gake Tomoya , Kumagai Yu , Takahashi Akira , Hiramatsu Hidenori , Oba Fumiyasu
Published: October 2022

Theoretical calculations explain that the experimentally reported nearly stoichiometric and electrical insulating behavior of undoped La2CdO2Se2 is due to the formation of Cd vacancies and interstitials.
Phase separation of the microtubule-associated protein tau
Authors: Chakraborty Pijush , Zweckstetter Markus
Published: October 2022

The aggregation and misfolding of the neuronal microtubule-associated protein tau is closely linked to the pathology of Alzheimer’s disease and several other neurodegenerative diseases. Recent evidence suggest that tau undergoes liquid–liquid phase separation in vitro and forms or associates with membrane-less organelles in cells. Biomolecular condensation driven by phase separation can influence the biological activities of tau including its ability to polymerize tubulin into microtubules. In addition, the high concentrations that tau can reach in biomolecular condensates provide a mechanism to promote its aggregation and the formation of amyloid fibrils potentially contributing to the pathology of different tauopathies. Here, the authors discuss the role of tau phase separation in physiology and disease.
Privacy‐preserving generative framework for images against membership inference attacks
Authors: Yang Ruikang , Ma Jianfeng , Miao Yinbin , Ma Xindi
Published: October 2022

Machine learning has become an integral part of modern intelligent systems in all aspects of life. Membership inference attacks (MIAs), as the significant model attacks, also jeopardize the privacy of the intelligent systems. Previous works on defending MIAs concentrate on the model output perturbation or tampering with the training process. However, data and model reuse are common in intelligent systems, which results in the lack of scalability of previous defending works. This paper proposes a new privacy‐preserving framework for images to transform source data into synthetic data to train models against MIAs. The synthetic data makes it easy to defend MIAs during data and model reuse to improve the scheme's scalability. The framework generates synthetic data satisfying differential privacy through the variational autoencoder model's information extraction and data generation capabilities to improve model accuracy. A noise addition mechanism with metric privacy for the latent code generated from source data is proposed, where noise is the product of Γ‐distribution and unit hyper‐sphere samples. Moreover, it is proved that the synthetic data also satisfies metric privacy. The experimental evaluations demonstrate that the framework reduces MIAs' attack accuracy to about 0.5 and maintains higher utility than DP‐SGD under the same setting.
Retracted: Non‐stationary 3‐D GBSM channel model for V2V communications
Authors: Xu Yan , Saleem Asad , Asif Muhammad , Khan Wali Ullah , Akhtar Zain Ul Abiden , Ali Md. Sadek
Published: October 2022

The above article from IET Communications, published online on 17 October 2022 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Interim Editor‐in‐Chief, Jian Ren, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal's peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.
Robust convergence conditions of iterative learning control for time‐delay systems under random non‐repetitive uncertainties
Authors: Shokri‐Ghaleh Hamid , Ganjefar Soheil , Shahri Alireza Mohammad
Published: October 2022

Some of the most fundamental assumptions in the design of iterative learning control (ILC) for uncertain systems are the strict repetitiveness (i.e. iteration‐independence) of uncertainties in all factors of plant dynamic, external disturbances, initial conditions, and reference trajectory, which may not always hold in practical applications. The simultaneous relaxation of all these assumptions is a challenging problem that has been addressed only for delay‐free systems. This problem is still open for time‐delay systems, especially when the time‐delay factor also has non‐repetitive (i.e. iteration‐dependent/varying) uncertainty. Hence, this study extends the problem of robust ILC for a class of time‐delay systems under nonrepetitive uncertainties in not only plant dynamic, external disturbances, initial conditions, and reference trajectory but also time‐delay. By using the ILC scheme introduced in this work, and based on the frequency domain analysis, it is shown that both monotonic convergence and boundedness of the expected tracking error can be achieved (in the sense of L2‐norm) when the non‐repetitiveness (i.e. iteration‐dependence) of all existing uncertainties from a random viewpoint are taken into account. The effectiveness of the proposed strategy is verified by two simulation examples.
A 1.2 V high‐speed low‐power preamplifier latch‐based comparator
Authors: He Yuefeng , Yuan Guoshun
Published: October 2022

The power consumption of chips has emerged as a major concern with the increased integration of analog circuitry. This work focuses on a two‐stage comparator based on a preamplifier with latch for a successive approximation analog‐to‐digital converter. In order to minimize power loss and delay time, the charge steering approach was used in the design of latch as well as preamplifier. The suggested comparator is simulated in SMIC 0.18‐um process in comparison to the comparator without charge steering mode. The results reveal that the average power consumption is only around 22 uW for varied input voltage at a supply voltage of 1.2 V, which is relatively lowered by approximately 30%. Meanwhile, delay time is also reduced by about 25%.
Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach
Authors: Zhang Jiarui , Mu Yunfei , Wu Zeqing , Liu Zhe , Gao Yi , Jia Hongjie , Li Hairun
Published: October 2022

Residential heating faces the challenge of heating interruption when an electric power outage occurs. As a promising heating electrification form, regenerative electric heating (REH) equipped with thermal energy storage (TES) has the flexibility of maintaining the building indoor temperature within the desired range during power outages and reducing the operation cost during normal operation states. However, the allocation and scheduling of the limited thermal energy in TES for the above two purposes is impacted by many uncertainties, for example, outdoor temperature, irradiation, and duration of power outages. Overestimation of the thermal energy required for power outages in the TES can improve the heating supply reliability, but it will also increase the REH operation cost to some extent, and vice versa. To address this problem, an affine arithmetic‐based model predictive control approach (AA‐MPC) for an optimal REH scheduling method is proposed to balance the heating supply reliability during power outages and operation economy of REH at the same time. An REH‐based residential building energy system model is developed to describe the building thermal load associated with the outdoor temperature and irradiation. Then, the required thermal energy for emergency building heating provided by the hot water tank (HWT) is determined using the minimum thermal demand of residents during a power outage, which is constrained by the minimum comfort temperature threshold. Based on this, an AA‐MPC approach that takes the thermal energy for emergency building heating as a time‐varying constraint of the HWT is developed to determine the optimal REH scheduling that considers emergency residential building heating under the above uncertainties. Numerical studies show that the proposed method can maintain minimum thermal demand for at least 2 h when a power outage occurs under uncertainties. At the same time, it can reduce the impact of uncertainties on the operation cost and reduce economic problems caused by emergency heating to a certain extent. Compared to the interval arithmetic‐based model predictive control approach, the operation cost intervals of the proposed method are reduced by 57.3%, 0.3%, and 32.5% under low, middle, and high prediction error levels respectively.
An exact MILP model for joint switch placement and preventive maintenance scheduling considering incentive regulation
Authors: Alizadeh Ali , Kamwa Innocent , Moeini Ali , Mohseni‐Bonab Seyed Masoud
Published: October 2022

Power delivery with high reliability is one of the main objectives of any distribution system. In this regard, system operators are adapting the traditional distribution systems with sectionalized switches and optimal preventive maintenance (PM) scheduling techniques as two effective methods for reliability improvement. However, they suffer due to the lack of a practical model in which switch placement (SP) and PM scheduling problems are considered simultaneously. Furthermore, consideration of incentive regulation schemes, such as reward‐penalty scheme (RPS) is highly questionable in the separated reliability improvement problems. In this paper, a mix‐integer linear programming model is presented wherein both SP and PM scheduling problems are considered. Rather than using conventional methods for linearization, an exact formulation is proposed to avoid the impact of approximations on the final decision. Moreover, RPS is also regarded as an incentive regulation scheme to balance the reliability level and financial performance. The results of test and real network implementation confirm that a higher performance is reached in terms of reliability and financial issues when the proposed model is utilized compared to the other ones. Besides, analysis demonstrates that the proposed model behaves effectively in both mid and long terms.
Improving traffic signal control operations using proximal policy optimization
Authors: Huang Liben , Qu Xiaohui
Published: October 2022

Existing traffic signal control systems present many limitations including fixed signal timing schemes, insufficient efficiency and flexibility, and difficulty in adapting to the changing traffic flows. In recent years, the development of deep reinforcement learning (RL) has shown great research potential and application prospects. This paper proposes an intersection signal control method based on the proximal policy optimization (PPO) method. Specifically, this paper uses the value vector representation method of traffic characteristics to encode the traffic state and then feeds the state encoding into the long short‐term memory (LSTM) network to obtain the signal phase output. Finally, to obtain the optimal signal control strategy, the PPO algorithm is utilized to train the neural network and adjust the signal phase. The proposed algorithm is benchmarked against other classic RL and adaptive signal control schemes in an experimental environment based on the traffic simulation software simulation of urban mobility (SUMO). Experimental results showed that the proposed algorithm greatly improves traffic efficiency. Specifically, the mean velocity of the vehicles increases by 45.09%, and the mean occupancy rate of each lane, the length of the longest jams during each step, and the mean halting duration dropped by 21.38%, 25.86%, and 12.94%, respectively.
Applying a hybrid model considering the interaction between train and power system for energy consumption surveys
Authors: Haghbin Mohammad , Khsoravani Mohammad , Golzar Tehrani Alireza , Farjah Ebrahim
Published: October 2022

Power supply system plays an important role in the operation of urban rail systems. It has to provide high‐quality energy for trains continuously. Train's energy consumption is varied directly with operation conditions such as train's headway, train configuration, line characteristic and many other factors. Therefore, using a powerful simulation tool for estimating energy consumption considering these factors seems inevitable. This paper tries to develop a hybrid model in which the train model is based on acquired data from real measurement and an adapted network electrical model. Train empirical model is based on neural network on the basis of online data measured in line one of Shiraz metro and used for training of model. Then benefiting from optimization algorithms, a novel model of energy supply system of trains, including Traction Substations (TSS) and Overhead Catenary System (OCS), is proposed. Finally, the behaviour of trains during operation in 15‐min headway was simulated and the results under same conditions were compared with practical measurements. Currently, this model helps to determine power system behaviour during different operation conditions, predicting energy consumption for different headways, Train's driver behaviour during acceleration, deceleration and braking and also operation risk analysis during traction substations outages.