bluuebunny/crossref_metadata_2025 huggingface dataset:
AI outperformed every dermatologist in dermoscopic melanoma diagnosis, using an optimized deep-CNN architecture with custom mini-batch logic and loss function
Authors: Pham Tri-Cong , Luong Chi-Mai , Hoang Van-Dung , Doucet Antoine
Published: September 2021

Melanoma, one of the most dangerous types of skin cancer, results in a very high mortality rate. Early detection and resection are two key points for a successful cure. Recent researches have used artificial intelligence to classify melanoma and nevus and to compare the assessment of these algorithms to that of dermatologists. However, training neural networks on an imbalanced dataset leads to imbalanced performance, the specificity is very high but the sensitivity is very low. This study proposes a method for improving melanoma prediction on an imbalanced dataset by reconstructed appropriate CNN architecture and optimized algorithms. The contributions involve three key features as custom loss function, custom mini-batch logic, and reformed fully connected layers. In the experiment, the training dataset is kept up to date including 17,302 images of melanoma and nevus which is the largest dataset by far. The model performance is compared to that of 157 dermatologists from 12 university hospitals in Germany based on the same dataset. The experimental results prove that our proposed approach outperforms all 157 dermatologists and achieves higher performance than the state-of-the-art approach with area under the curve of 94.4%, sensitivity of 85.0%, and specificity of 95.0%. Moreover, using the best threshold shows the most balanced measure compare to other researches, and is promisingly application to medical diagnosis, with sensitivity of 90.0% and specificity of 93.8%. To foster further research and allow for replicability, we made the source code and data splits of all our experiments publicly available.
Wavelet geographically weighted regression for spectroscopic modelling of soil properties
Authors: Song Yongze , Shen Zefang , Wu Peng , Viscarra Rossel R. A.
Published: September 2021

Soil properties, such as organic carbon, pH and clay content, are critical indicators of ecosystem function. Visible–near infrared (vis–NIR) reflectance spectroscopy has been widely used to cost-efficiently estimate such soil properties. Multivariate modelling, such as partial least squares regression (PLSR), and machine learning are the most common methods for modelling soil properties with spectra. Often, such models do not account for the multiresolution information presented in the vis–NIR signal, or the spatial variation in the data. To address these potential shortcomings, we used wavelets to decompose the vis–NIR spectra of 226 soils from agricultural and forested regions in south-western Western Australia and developed a wavelet geographically weighted regression (WGWR) for estimating soil organic carbon content, clay content and pH. To evaluate the WGWR models, we compared them to linear models derived with multiresolution data from a wavelet decomposition (WLR) and PLSR without multiresolution information. Overall, validation of the WGWR models produced more accurate estimates of the soil properties than WLR and PLSR. Around 3.5–49.1% of the improvement in the estimates was due to the multiresolution analysis and 1.0–5.2% due to the integration of spatial information in the modelling. The WGWR improves the modelling of soil properties with spectra.
Quantitative analysis of metastatic breast cancer in mice using deep learning on cryo-image data
Authors: Liu Yiqiao , Gargesha Madhusudhana , Qutaish Mohammed , Zhou Zhuxian , Qiao Peter , Lu Zheng-Rong , Wilson David L.
Published: September 2021

Cryo-imaging sections and images a whole mouse and provides ~ 120-GBytes of microscopic 3D color anatomy and fluorescence images, making fully manual analysis of metastases an onerous task. A convolutional neural network (CNN)-based metastases segmentation algorithm included three steps: candidate segmentation, candidate classification, and semi-automatic correction of the classification result. The candidate segmentation generated > 5000 candidates in each of the breast cancer-bearing mice. Random forest classifier with multi-scale CNN features and hand-crafted intensity and morphology features achieved 0.8645 ± 0.0858, 0.9738 ± 0.0074, and 0.9709 ± 0.0182 sensitivity, specificity, and area under the curve (AUC) of the receiver operating characteristic (ROC), with fourfold cross validation. Classification results guided manual correction by an expert with our in-house MATLAB software. Finally, 225, 148, 165, and 344 metastases were identified in the four cancer mice. With CNN-based segmentation, the human intervention time was reduced from > 12 to ~ 2 h. We demonstrated that 4T1 breast cancer metastases spread to the lung, liver, bone, and brain. Assessing the size and distribution of metastases proves the usefulness and robustness of cryo-imaging and our software for evaluating new cancer imaging and therapeutics technologies. Application of the method with only minor modification to a pancreatic metastatic cancer model demonstrated generalizability to other tumor models.
Selectivity of direct plasma treatment and plasma-conditioned media in bone cancer cell lines
Authors: Hamouda Inès , Labay Cédric , Cvelbar Uroš , Ginebra Maria-Pau , Canal Cristina
Published: September 2021

Atmospheric pressure plasma jets have been shown to impact several cancer cell lines, both in vitro and in vivo. These effects are based on the biochemistry of the reactive oxygen and nitrogen species generated by plasmas in physiological liquids, referred to as plasma-conditioned liquids. Plasma-conditioned media are efficient in the generation of reactive species, inducing selective cancer cell death. However, the concentration of reactive species generated by plasma in the cell culture media of different cell types can be highly variable, complicating the ability to draw precise conclusions due to the differential sensitivity of different cells to reactive species. Here, we compared the effects of direct and indirect plasma treatment on non-malignant bone cells (hOBs and hMSCs) and bone cancer cells (SaOs-2s and MG63s) by treating the cells directly or exposing them to previously treated cell culture medium. Biological effects were correlated with the concentrations of reactive species generated in the liquid. A linear increase in reactive species in the cell culture medium was observed with increased plasma treatment time independent of the volume treated. Values up to 700 µM for H2O2 and 140 µM of NO2− were attained in 2 mL after 15 min of plasma treatment in AdvDMEM cell culture media. Selectivity towards bone cancer cells was observed after both direct and indirect plasma treatments, leading to a decrease in bone cancer cell viability at 72 h to 30% for the longest plasma treatment times while maintaining the survival of non-malignant cells. Therefore, plasma-conditioned media may represent the basis for a potentially novel non-invasive technique for bone cancer therapy.
A virus-free cellular model recapitulates several features of severe COVID-19
Authors: Lavorgna Giovanni , Cavalli Giulio , Dagna Lorenzo , Gregori Silvia , Larcher Alessandro , Landoni Giovanni , Ciceri Fabio , Montorsi Francesco , Salonia Andrea
Published: September 2021

As for all newly-emergent pathogens, SARS-CoV-2 presents with a relative paucity of clinical information and experimental models, a situation hampering both the development of new effective treatments and the prediction of future outbreaks. Here, we find that a simple virus-free model, based on publicly available transcriptional data from human cell lines, is surprisingly able to recapitulate several features of the clinically relevant infections. By segregating cell lines (n = 1305) from the CCLE project on the base of their sole angiotensin-converting enzyme 2 (ACE2) mRNA content, we found that overexpressing cells present with molecular features resembling those of at-risk patients, including senescence, impairment of antibody production, epigenetic regulation, DNA repair and apoptosis, neutralization of the interferon response, proneness to an overemphasized innate immune activity, hyperinflammation by IL-1, diabetes, hypercoagulation and hypogonadism. Likewise, several pathways were found to display a differential expression between sexes, with males being in the least advantageous position, thus suggesting that the model could reproduce even the sex-related disparities observed in the clinical outcome of patients with COVID-19. Overall, besides validating a new disease model, our data suggest that, in patients with severe COVID-19, a baseline ground could be already present and, as a consequence, the viral infection might simply exacerbate a variety of latent (or inherent) pre-existing conditions, representing therefore a tipping point at which they become clinically significant.
Exploring the links between volcano flank collapse and the magmatic evolution of an ocean island volcano: Fogo, Cape Verde
Authors: Cornu Mélodie-Neige , Paris Raphaël , Doucelance Régis , Bachélery Patrick , Bosq Chantal , Auclair Delphine , Benbakkar Mhammed , Gannoun Abdel-Mouhcine , Guillou Hervé
Published: September 2021

Mass-wasting of ocean island volcanoes is a well-documented phenomenon. Massive flank collapses may imply tens to hundreds of km3 and generate mega-tsunamis. However, the causal links between this large-scale, low-frequency instability, and the time–space evolution of magma storage, crystal fractionation/accumulation, lithospheric assimilation, and partial melting remains unclear. This paper aims at tracking time variations and links between lithospheric, crustal and surface processes before and after a major flank collapse (Monte Amarelo collapse ca. 70 ka) of Fogo volcano, Cape Verde Islands, by analysing the chemical composition (major, trace elements, and Sr–Nd–Pb isotopes) and age-controlled stratigraphy (K–Ar and Ar–Ar dating) of lavas along vertical sections (Bordeira caldera walls). The high-resolution sampling allows detecting original variations of composition at different time-scales: (1) a 60 kyrs-long period of increase of magma differentiation before the collapse; (2) a 10 kyrs-long episode of reorganization of magma storage and evacuation of residual magmas (enriched in incompatible elements) after the collapse; and (3) a delayed impact at the lithospheric scale ~ 50 kyrs after the collapse (increasing EM1-like materiel assimilation).
Psychological stress induced bladder overactivity in female mice is associated with enhanced afferent nerve activity
Authors: Mills Kylie A. , West Eliza G. , Sellers Donna J. , Chess-Williams Russ , McDermott Catherine
Published: September 2021

Psychological stress has been linked to the development and exacerbation of overactive bladder symptoms, as well as afferent sensitisation in other organ systems. Therefore, we aimed to investigate the effects of water avoidance stress on bladder afferent nerve activity in response to bladder filling and pharmaceutical stimulation with carbachol and ATP in mice. Adult female C57BL/6J mice were exposed to either water avoidance stress (WAS) for 1 h/day for 10 days or normal housing conditions. Voiding behaviour was measured before starting and 24-h after final stress exposure and then animals were euthanised to measure afferent nerve activity in association with bladder compliance, spontaneous phasic activity, contractile responses, as well as release of urothelial mediators. WAS caused increased urinary frequency without affecting urine production. The afferent nerve activity at low bladder pressures (4–7 mmHg), relevant to normal physiological filling, was significantly increased after stress. Both low and high threshold nerves demonstrated enhanced activity at physiological bladder pressures. Urothelial ATP and acetylcholine release and bladder compliance were unaffected by stress as was the detrusor response to ATP (1 mM) and carbachol (1 µM). WAS caused enhanced activity of individual afferent nerve fibres in response bladder distension. The enhanced activity was seen in both low and high threshold nerves suggesting that stressed animals may experience enhanced bladder filling sensations at lower bladder volumes as well as increased pain sensations, both potentially contributing to the increased urinary frequency seen after stress.
Development and validation of a rapidly deployable CT-guided stereotactic system for external ventricular drainage: preclinical study
Authors: Barath Abhijeet S. , Rusheen Aaron E. , Cabrera Juan M. Rojas , Shin Hojin , Blaha Charles D. , Bennet Kevin E. , Goerss Stephan J. , Lee Kendall H. , Oh Yoonbae
Published: September 2021

External ventricular drainage (EVD) is an emergency neurosurgical procedure to decrease intracranial pressure through a catheter mediated drainage of cerebrospinal fluid. Most EVD catheters are placed using free hands without direct visualization of the target and catheter trajectory, leading to a high rate of complications- hemorrhage, brain injury and suboptimal catheter placement. Use of stereotactic systems can prevent these complications. However, they have found limited application for this procedure due to their long set-up time and expensive hardware. Therefore, we have developed and pre-clinically validated a novel 3D printed stereotactic system for rapid and accurate implantation of EVD catheters. Its mechanical and imaging accuracies were found to be at par with clinical stereotactic systems. Preclinical trial in human cadaver specimens revealed improved targeting accuracy achieved within an acceptable time frame compared to the free hand technique. CT angiography emulated using cadaver specimen with radio-opaque vascular contrast showed vessel free catheter trajectory. This could potentially translate to reduced hemorrhage rate. Thus, our 3D printed stereotactic system offers the potential to improve the accuracy and safety of EVD catheter placement for patients without significantly increasing the procedure time.
iTRAQ-based quantitative proteomic analysis of the improved effects of total flavones of Dracocephalum Moldavica L. in chronic mountain sickness
Authors: Abudouwayiti Aihaidan , Nijiati Yiliyaer , Zhang Xiangyang , Maimaitiyiming Dilinuer , Aikemu Ainiwaer
Published: September 2021

To use isobaric tags for relative and absolute quantification (iTRAQ) technology to study the pathogenesis of chronic mountain sickness (CMS), identify biomarkers for CMS, and investigate the effect of total flavones of Dracocephalum moldavica L. (TFDM) on a rat model of CMS. We simulated high altitude hypobaric hypoxia conditions and generated a rat model of CMS. Following the administration of TFDM, we measured the pulmonary artery pressure and serum levels of hemoglobin (Hb), the hematocrit (Hct), and observed the structure of the pulmonary artery in experimental rats. Furthermore, we applied iTRAQ-labeled quantitative proteomics technology to identify differentially expressed proteins (DEPs) in the serum, performed bioinformatics analysis, and verified the DEPs by immunohistochemistry. Analysis showed that the pulmonary artery pressure, serum levels of Hb, and the Hct, were significantly increased in a rat model of CMS (P < 0.05). Pathological analysis of lung tissue and pulmonary artery tissue showed that the alveolar compartment had obvious hyperplasia and the pulmonary artery degree of muscularization was enhanced. Both pulmonary artery pressure and tissue morphology were improved following the administration of TFDM. We identified 532 DEPs by quantitative proteomics; gene ontology (GO)and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis further revealed that metabolic pathways associated with coagulation and complement play crucial roles in the occurrence of CMS. Immunohistochemistry verified that several DEPs (α-1-acid glycoprotein, collagen, fibulin, haptoglobin, PLTP, and TAGLN2) are important biological markers for CMS. Our analyses demonstrated that TFDM can improve CMS and exert action by influencing the metabolic pathways associated with coagulation and complement. This process relieves pulmonary artery pressure and improves lung function. We also identified that α-1-acid glycoprotein, collagen, fibulin, haptoglobin, PLTP, and TAGLN2 may represent potential biomarkers for CMS.
3D cephalometric landmark detection by multiple stage deep reinforcement learning
Authors: Kang Sung Ho , Jeon Kiwan , Kang Sang-Hoon , Lee Sang-Hwy
Published: September 2021

The lengthy time needed for manual landmarking has delayed the widespread adoption of three-dimensional (3D) cephalometry. We here propose an automatic 3D cephalometric annotation system based on multi-stage deep reinforcement learning (DRL) and volume-rendered imaging. This system considers geometrical characteristics of landmarks and simulates the sequential decision process underlying human professional landmarking patterns. It consists mainly of constructing an appropriate two-dimensional cutaway or 3D model view, then implementing single-stage DRL with gradient-based boundary estimation or multi-stage DRL to dictate the 3D coordinates of target landmarks. This system clearly shows sufficient detection accuracy and stability for direct clinical applications, with a low level of detection error and low inter-individual variation (1.96 ± 0.78 mm). Our system, moreover, requires no additional steps of segmentation and 3D mesh-object construction for landmark detection. We believe these system features will enable fast-track cephalometric analysis and planning and expect it to achieve greater accuracy as larger CT datasets become available for training and testing.
Effects of cerebral small vessel disease on the outcomes in cryptogenic stroke with active cancer
Authors: Nam Ki-Woong , Kwon Hyung-Min , Lee Yong-Seok , Kim Jeong-Min , Ko Sang-Bae
Published: September 2021

Cerebral small vessel diseases (cSVDs) affect the prognosis of various types of ischemic stroke. Therefore, we evaluated the association between cSVD and the prognosis of cryptogenic stroke patients with active cancer. We enrolled patients diagnosed with cryptogenic stroke and active cancer from 2010 to 2016. Early neurological deterioration (END) was defined as a ≥ 2-point increase in the total NIHSS score or a ≥ 1-point increase in the motor NIHSS score within the first 72 h. We defined an unfavorable outcome as the modified Rankin Scale (mRS) score ≥ 3 points. We analyzed cSVD separately for each subtype including white matter hyperintensity (WMH), silent brain infarct (SBI), and cerebral microbleed (CMB). A total of 179 cryptogenic stroke patients with active cancer were evaluated. In the multivariable analysis, SBI was significantly associated with END (adjusted odds ratio = 3.97, 95% confidence interval: 1.53–10.33). This close relationship between SBI and END increased proportionally with an increase in SBI burden. However, WMH and CMB showed no significant association with END. None of the cSVD subtypes showed a statistically significant relationship with the 3-month unfavorable outcome. SBI was the only parameter closely associated with END in cryptogenic stroke patients with active cancer.
Frontoparietal network resilience is associated with protection against cognitive decline in Parkinson’s disease
Authors: Cascone Arianna D. , Langella Stephanie , Sklerov Miriam , Dayan Eran
Published: September 2021

Though Parkinson’s disease is primarily defined as a movement disorder, it is also characterized by a range of non-motor symptoms, including cognitive decline. The onset and progression of cognitive decline in individuals with Parkinson’s disease is variable, and the neurobiological mechanisms that contribute to, or protect against, cognitive decline in Parkinson’s disease are poorly understood. Using resting-state functional magnetic resonance imaging data collected from individuals with Parkinson’s disease with and without cognitive decline, we examined the relationship between topological brain-network resilience and cognition in Parkinson’s disease. By leveraging network attack analyses, we demonstrate that relative to individuals with Parkinson’s disease experiencing cognitive decline, the frontoparietal network in cognitively stable individuals with Parkinson’s disease is significantly more resilient to network perturbation. Our findings suggest that the topological robustness of the frontoparietal network is associated with the absence of cognitive decline in individuals with Parkinson’s disease.
Heimdallarchaea encodes profilin with eukaryotic-like actin regulation and polyproline binding
Authors: Survery Sabeen , Hurtig Fredrik , Haq Syed Razaul , Eriksson Jens , Guy Lionel , Rosengren K. Johan , Lindås Ann-Christin , Chi Celestine N.
Published: September 2021

It is now widely accepted that the first eukaryotic cell emerged from a merger of an archaeal host cell and an alphaproteobacterium. However, the exact sequence of events and the nature of the cellular biology of both partner cells is still contentious. Recently the structures of profilins from some members of the newly discovered Asgard superphylum were determined. In addition, it was found that these profilins inhibit eukaryotic rabbit actin polymerization and that this reaction is regulated by phospholipids. However, the interaction with polyproline repeats which are known to be crucial for the regulation of profilin:actin polymerization was found to be absent for these profilins and was thus suggested to have evolved later in the eukaryotic lineage. Here, we show that Heimdallarchaeota LC3, a candidate phylum within the Asgard superphylum, encodes a putative profilin (heimProfilin) that interacts with PIP2 and its binding is regulated by polyproline motifs, suggesting an origin predating the rise of the eukaryotes. More precisely, we determined the 3D-structure of Heimdallarchaeota LC3 profilin and show that this profilin is able to: i) inhibit eukaryotic actin polymerization in vitro; ii) bind to phospholipids; iii) bind to polyproline repeats from enabled/vasodilator‐stimulated phosphoprotein; iv) inhibit actin from Heimdallarchaeota from polymerizing into filaments. Our results therefore provide hints of the existence of a complex cytoskeleton already in last eukaryotic common ancestor.
Flexible and high precision thermal metasurface
Authors: Wang Jiyao , Qin Ling , Xu Wei
Published: September 2021

Thermal metamaterials are artificial materials used to manipulate heat flow in many applications, such as thermal protection, thermal camouflage, and precise temperature control. Most of the existing thermal metamaterials are mainly based on metal, which makes their fabrication complex and time-consuming, and limits their flexibility. Here, we show a strategy to simplify the fabrication process, improve machining accuracy, and realize flexibility in thermal metasurfaces. Our proposed thermal metasurface is fabricated by laser engraving of copper-graphene coating surface, utilizing graphene coating with high thermal conductivity instead of the traditional filling materials of low thermal conductivity. It maintains the integrity of copper substrate, giving the metasurface a good heat dispersion. Controlled temperature gradient patterns are established, and the metasurface can be bent without changing its features, except for a slight variation in its thermal gradient. Finally, its cloaking ability is demonstrated by camouflaging the same heat source in the shape of different objects. Our designed metasurface mitigates the limitations in design and fabrication of existing thermal metamaterials, and can be used in applications requiring large flexibility, thermal illusion, and large thermal gradients on small scales.
Highly recyclable Ti0.97Ni0.03O1.97 catalyst coated on cordierite monolith for efficient transformation of arylboronic acids to phenols and reduction of 4-nitrophenol
Authors: Prasanna  , Usha K. M. , Hegde M. S.
Published: September 2021

An efficient catalyst, Pd2+ substituted TiO2 coated on cordierite monolith for rapid transformation of arylboronic acid to phenol and reduction of 4-nitrophenol.
Reversible transformation of all-inorganic copper halide perovskite nanocrystals for anti-counterfeiting
Authors: Wang Yueming , Yan Yuchen , Li Dan , Zhao Wenbo , Chen Shuhua , Zhong Qixuan , Liu Jun , Diarra Fousseyni , Cao Muhan , Zhang Qiao
Published: September 2021

CsI stripping/insertion enable the reversible transformation between blue-emissive Cs3Cu2I5 and yellow-emissive CsCu2I3 upon moisture/evaporation treatment.
Study of an EuBO3–ScBO3 system and EuSc3(BO3)4, EuSc(BO3)2 orthoborates
Authors: Kuznetsov Artem B. , Kokh Konstantin A. , Kaneva Eketerina V. , Svetlichnyi Valery A. , Kononova Nadezda G. , Shevchenko Vyacheslav S. , Rashchenko Sergey V. , Kokh Alexander E.
Published: September 2021

Luminescence properties of the compounds in the EuBO3–ScBO3 system were studied.
Enterobacter aerogenes ZDY01 inhibits choline-induced atherosclerosis through CDCA-FXR-FGF15 axis
Authors: Tang Jinghui , Qin Manman , Tang Le , Shan Dan , Zhang Cheng , Zhang Yifeng , Wei Hua , Qiu Liang , Yu Jun
Published: September 2021

ZDY01 utilized TMA and reduced TMAO level, increased abundance of gut microbiota, accelerated resorption of bile acids into blood by upregulating Asbt and Ostα/β expression, and inactivated FXR-FGF15 axis resulting in increased CYP7A1 expression.
Akkermansia muciniphila and its outer protein Amuc_1100 regulates tryptophan metabolism in colitis
Authors: Gu Zhenyang , Pei Wenlong , Shen Yonghua , Wang Lijuan , Zhu Jun , Zhang Yi , Fan Shengxian , Wu Qian , Li Lei , Zhang Zhan
Published: September 2021

A. muciniphila and its outer membrane protein Amuc_1100 restored the aberrant tryptophan metabolism in colitis.
The application of amine-based materials for carbon capture and utilisation: an overarching view
Authors: Hamdy Louise B. , Goel Chitrakshi , Rudd Jennifer A. , Barron Andrew R. , Andreoli Enrico
Published: September 2021

An account of the fundamental chemical and engineering principles of solid amine-based CO2 adsorbents and their industrial application, with discussion of the relevance of amine chemistry in CO2 utilisation technology.
A β-cyclodextrin enhanced polyethylene terephthalate film with improved contact charging ability in a high humidity environment
Authors: Wang Nannan , Liu Yizhe , Wu Yang , Li Zibiao , Wang Daoai
Published: September 2021

A new type of polyethylene terephthalate (PET) based TENG which can work stably in a high humidity environment with high output performance is fabricated. The electrical output of this TENG increases with the increase of environmental humidity.
Emergence of cationic polyamine dendrimersomes: design, stimuli sensitivity and potential biomedical applications
Authors: Laskar Partha , Dufès Christine
Published: September 2021

Emergence of surface-modified polyamine dendrimer-based vesicles (or dendrimersomes) as promising alternatives to lipid vesicles for biomedical applications.
Laser-induced convection shifts size distributions in nanoparticle tracking analysis
Authors: Hoffmann William H. , Mulkerns Niall M. C. , Hall Simon R. , Gersen Henkjan
Published: September 2021

In nanoparticle tracking analysis, laser-induced convection increases the error on individual particle sizing.
High shear in situ exfoliation of 2D gallium oxide sheets from centrifugally derived thin films of liquid gallium
Authors: Vimalanathan Kasturi , Palmer Timotheos , Gardner Zoe , Ling Irene , Rahpeima Soraya , Elmas Sait , Gascooke Jason R. , Gibson Christopher T. , Sun Qiang , Zou Jin , Andersson Mats R. , Darwish Nadim , Raston Colin L.
Published: September 2021

Ultrathin gallium oxide sheets formed under continuous flow from gallium metal are highly insulating with electrocatalytic activity for hydrogen evolution.
Macrophage-hitchhiking supramolecular aggregates of CuS nanoparticles for enhanced tumor deposition and photothermal therapy
Authors: Li Junyan , Cheng Qian , Yue Ludan , Gao Cheng , Wei Jianwen , Ding Yuanfu , Wang Yitao , Zheng Ying , Wang Ruibing
Published: September 2021

A macrophage-hitchhiking delivery system based on intracellular self-assembly of CuS nanoparticles was developed for reducing premature loss and specifically releasing nanomedicine in the tumor in response to the inflammatory microenvironment.
High-quality WS2 film as a hole transport layer in high-efficiency non-fullerene organic solar cells
Authors: Wang Xiaojing , Liu Peng , Yap Boonkar , Xia Ruidong , Wong Wai-Yeung , He Zhicai
Published: September 2021

By comprehensively controlling the preparation conditions of WS2, this paper has achieved a high yield and high quality WS2 film and used it to realize high-efficiency PEDOT-free non-fullerene organic solar cells.
Transition-metal-catalyzed C–H bond activation/functionalization and annulation of phthalazinones
Authors: Sivaraj Chandrasekaran , Ramkumar Alagumalai , Sankaran Nagesh , Gandhi Thirumanavelan
Published: September 2021

Heteroatoms (O and N) on the phthalazinones are exploited for diverse functionalization with high regioselectivity by the intervention of transition-metal catalysts like Rh, Ru, Pd, & Ir and, thus augmenting its value.
The effect of size, charge state and composition on the binding of propene to yttrium-doped gold clusters
Authors: Barabás Júlia , Ferrari Piero , Kaydashev Vladimir , Vanbuel Jan , Janssens Ewald , Höltzl Tibor
Published: September 2021

The catalytic activity of metal clusters can be easily tuned by their size, charge state, or the introduction of dopant atoms.
Deciphering the interaction of flavones with calf thymus DNA and octamer DNA sequence (CCAATTGG)2
Authors: Kumar Shailendra , Nair Maya S.
Published: September 2021

Binding of flavones induce conformational changes in double stranded DNA.
A review on convenient synthesis of substituted coumarins using reuseable solid acid catalysts
Authors: Gulati Susheel , Singh Rajvir , Sangwan Suman
Published: September 2021

Due to growing concern about chemicals and their impact on the environment, cleaner reaction conditions are needed to be incorporated into chemical synthetic procedures.
Aptamer-functionalized pH-sensitive liposomes for a selective delivery of echinomycin into cancer cells
Authors: Lafi Zainab , Alshaer Walhan , Hatmal Ma'mon M. , Zihlif Malek , Alqudah Dana A. , Nsairat Hamdi , Azzam Hanan , Aburjai Talal , Bustanji Yasser , Awidi Abdalla
Published: September 2021

Echinomycin was loaded into PEGylated pH-sensitive liposomes and functionalized with anti-nucleolin aptamer for selective targeting and pH-responsive release of echinomycin into cancer cells.
Luminescence properties of [Ir(C^N)2(N^N)]+ complexes: relations between DFT computation results and emission band-shape analysis data
Authors: Kapturkiewicz Andrzej , Kamecka Anna
Published: September 2021

For two series of [Ir(C^N)2(N^N)]+ luminophores, the computed DFT quantities remain in nice agreement with those available from the emission band-shape analyses.
Temperature and salt controlled tuning of protein clusters
Authors: Beck Christian , Grimaldo Marco , Braun Michal K. , Bühl Lena , Matsarskaia Olga , Jalarvo Niina H. , Zhang Fajun , Roosen-Runge Felix , Schreiber Frank , Seydel Tilo
Published: September 2021

The formation of molecular assemblies in protein solutions is of strong interest both from a fundamental viewpoint and for biomedical applications.
A review on the recent advancements in graphene-based membranes and their applications as stimuli-responsive separation materials
Authors: Austria Hannah Faye M. , T. M. Subrahmanya , Setiawan Owen , Widakdo Januar , Chiao Yu-Hsuan , Hung Wei-Song , Wang Chih-Feng , Hu Chien-Chieh , Lee Kueir-Rarn , Lai Juin-Yih
Published: September 2021

Graphene and its derivatives that are key players in the field of membrane technology, have amassed a huge amount of publications in the past years regarding their fabrication, properties, applications, and most recently, their utilization as smart membranes.
Polyluminol-polyoxometalate hybrid hydrogels as flexible and soft supercapacitor electrodes
Authors: AL-Ghaus Zahraa , Akbarinejad Alireza , Zhu Bicheng , Travas-Sejdic Jadranka
Published: September 2021

A flexible supercapacitor based on polyluminol-polyoxometalate hybrid hydrogel electrodes is fabricated with excellent capacitance retention over 1000 charge–discharge cycles and outstanding performance stability upon significant bending deformation.
Morphology engineering of atomic layer defect-rich CoSe2 nanosheets for highly selective electrosynthesis of hydrogen peroxide
Authors: Ji Yuan , Liu Yundan , Zhang Bin-Wei , Xu Zhongfei , Qi Xiang , Xu Xun , Ren Long , Du Yi , Zhong Jianxin , Dou Shi Xue
Published: September 2021

Self-grown ultra-thin and defect-rich CoSe2 nanosheets show up to 92% selectivity in electrosynthesis of hydrogen peroxide, with ideal yields in electrolytes with different pH.
Toward high-temperature thermal tolerance in solar selective absorber coatings: choosing high entropy ceramic HfNbTaTiZrN
Authors: He Cheng-Yu , Gao Xiang-Hu , Yu Dong-Mei , Zhao Shuai-Sheng , Guo Hui-Xia , Liu Gang
Published: September 2021

The most recent advances in high-entropy materials provide impetus for the development of high-performance materials, simultaneously providing high-temperature robustness and excellent functional properties owing to the high configurational entropy and distorted lattices.
Pressure-induced chemical decomposition of copper orthovanadate (α-Cu3V2O8)
Authors: Díaz-Anichtchenko Daniel , Turnbull Robin , Bandiello Enrico , Anzellini Simone , Achary Srungarpu Nagabhusan , Errandonea Daniel
Published: September 2021

Out of the large family of orthovanadates, α-Cu3V2O8 is found to be most compressible (B0 = 52 GPa) and it is the only one to undergo pressure-induced chemical decomposition at very low pressures (~1.35 GPa).
Negative electron affinity of the GaN photocathode: a review on the basic theory, structure design, fabrication, and performance characterization.
Authors: Wang Xiaohui , Wang Mengbo , Liao Yulong , Yang Lifeng , Ban Qipei , Zhang Xiang , Wang Zhenying , Zhang Shibo
Published: September 2021

A comprehensive review is provided on the basic theory, structure design, fabrication, and performance characterization of the NEA GaN photocathode.
Nuclear atypia grading in breast cancer histopathological images based on CNN feature extraction and LSTM classification
Authors: Karimi Jafarbigloo Sanaz , Danyali Habibollah
Published: September 2021

Early diagnosis of breast cancer, the most common disease among women around the world, increases the chance of treatment and is highly important. Nuclear atypia grading in histopathological images plays an important role in the final diagnosis and grading of breast cancer. Grading images by pathologists is a time consuming and subjective task. Therefore, the existence of a computer‐aided system for nuclear atypia grading is very useful and necessary. In this study, two automatic systems for grading nuclear atypia in breast cancer histopathological images based on deep learning methods are proposed. A patch‐based approach is introduced due to the large size of the histopathological images and restriction of the training data. In the proposed system I, the most important patches in the image are detected first and then a three‐hidden‐layer convolutional neural network (CNN) is designed and trained for feature extraction and to classify the patches individually. The proposed system II is based on a combination of the CNN for feature extraction and a two‐layer Long short‐term memory (LSTM) network for classification. The LSTM network is utilised to consider all patches of an image simultaneously for image grading. The simulation results show the efficiency of the proposed systems for automatic nuclear atypia grading and outperform the current related studies in the literature.
Capturing semantic features to improve Chinese event detection
Authors: Ma Xiaobo , Liu Yongbin , Ouyang Chunping
Published: September 2021

Current Chinese event detection methods commonly use word embedding to capture semantic representation, but these methods find it difficult to capture the dependence relationship between the trigger words and other words in the same sentence. Based on the simple evaluation, it is known that a dependency parser can effectively capture dependency relationships and improve the accuracy of event categorisation. This study proposes a novel architecture that models a hybrid representation to summarise semantic and structural information from both characters and words. This model can capture rich semantic features for the event detection task by incorporating the semantic representation generated from the dependency parser. The authors evaluate different models on kbp 2017 corpus. The experimental results show that the proposed method can significantly improve performance in Chinese event detection.
HCISNet: Higher‐capacity invisible image steganographic network
Authors: Li Yafeng , Liu Ju , Liu Xiaoxi , Wang Xuejing , Gao Xuesong , Zhang Yuyi
Published: September 2021

Information hiding as a crucial method for multimedia security and privacy protection, has received a substantial amount of attention. However, the most existing methods focus on the resistance of steganalysis and the robustness of information, resulting in low capacity. In this paper, to further increase the capacity of information hiding, a high‐capacity adversarial image steganography model with end‐to‐end manner, termed as HCISNet is proposed. First, an enhanced Dense Atrous Spatial Pyramid Pooling module is presented to learn more semantic information in cover image, which can adaptively embed more message in redundant regions with rich textures. Then, a modified discriminator network with lightweight residual block is employed to assist the encoder network with optimal high‐capacity solution. Meanwhile, the multiple objective function with the perceptual loss and several training tricks are developed, which can improve the visual and perceptual consistency of the original and the steganographic image, further enhancing the capacity. Finally, experiments and analysis are conducted on three public datasets, where this model has better imperceptibility, higher security and greater capacity. Under same experimental conditions, the cover image can embed 5.68 bits per pixel (BPP), far exceeding the previous highest value of 4.4 BPP in state‐of‐the‐art methods in the authors' knowledge.
An unbiased NOEMA 2.6 to 4 mm survey of the GG Tau ring: First detection of CCS in a protoplanetary disk
Authors: Phuong N. T. , Dutrey A. , Chapillon E. , Guilloteau S. , Bary J. , Beck T. L. , Coutens A. , Denis-Alpizar O. , Di Folco E. , Diep P. N. , Majumdar L. , Melisse J.-P. , Lee C.-W. , Pietu V. , Stoecklin T. , Tang Y.-W.
Published: September 2021

Context. Molecular line surveys are among the main tools to probe the structure and physical conditions in protoplanetary disks (PPDs), the birthplace of planets. The large radial and vertical temperature as well as density gradients in these PPDs lead to a complex chemical composition, making chemistry an important step to understand the variety of planetary systems.

Aims. We aimed to study the chemical content of the protoplanetary disk surrounding GG Tau A, a well-known triple T Tauri system.

Methods. We used NOEMA with the new correlator PolyFix to observe rotational lines at ∼2.6 to 4 mm from a few dozen molecules. We analysed the data with a radiative transfer code to derive molecular densities and the abundance relative to 13CO, which we compare to those of the TMC1 cloud and LkCa 15 disk.

Results. We report the first detection of CCS in PPDs. We also marginally detect OCS and find 16 other molecules in the GG Tauri outer disk. Ten of them had been found previously, while seven others (13CN, N2H+, HNC, DNC, HC3N, CCS, and C34S) are new detections in this disk.

Conclusions. The analysis confirms that sulphur chemistry is not yet properly understood. The D/H ratio, derived from DCO+/HCO+, DCN/HCN, and DNC/HNC ratios, points towards a low temperature chemistry. The detection of the rare species CCS confirms that GG Tau is a good laboratory to study the protoplanetary disk chemistry, thanks to its large disk size and mass.
Fast solver for quasi-periodic 2D-Helmholtz scattering in layered media
Authors: Pinto José , Aylwin Ruben , Jerez-Hanckes Carlos
Published: September 2021

We present a fast spectral Galerkin scheme for the discretization of boundary integral equations arising from two-dimensional Helmholtz transmission problems in multi-layered periodic structures or gratings. Employing suitably parametrized Fourier basis and excluding cut-off frequencies (also known as Rayleigh-Wood frequencies), we rigorously establish the well-posedness of both continuous and discrete problems, and prove super-algebraic error convergence rates for the proposed scheme. Through several numerical examples, we confirm our findings and show performances competitive to those attainedviaNyström methods.
Penalty function method for the minimal time crisis problem
Authors: Boumaza Kenza , Bayen Térence , Rapaport Alain
Published: September 2021

In this note, we propose a new method to approximate the minimal time crisis problem using an auxiliary control and a penalty function, and show its convergence to a solution to the original problem. The interest of this approach is illustrated on numerical examples for which optimal trajectories can leave and enter the crisis set tangentially.
Survey of sequential convex programming and generalized Gauss-Newton methods
Authors: Messerer Florian , Baumgärtner Katrin , Diehl Moritz
Published: September 2021

We provide an overview of a class of iterative convex approximation methods for nonlinear optimization problems with convex-over-nonlinear substructure. These problems are characterized by outer convexities on the one hand, and nonlinear, generally nonconvex, but differentiable functions on the other hand. All methods from this class use only first order derivatives of the nonlinear functions and sequentially solve convex optimization problems. All of them are different generalizations of the classical Gauss-Newton (GN) method. We focus on the smooth constrained case and on three methods to address it: Sequential Convex Programming (SCP), Sequential Convex Quadratic Programming (SCQP), and Sequential Quadratically Constrained Quadratic Programming (SQCQP). While the first two methods were previously known, the last is newly proposed and investigated in this paper. We show under mild assumptions that SCP, SCQP and SQCQP have exactly the same local linear convergence – or divergence – rate. We then discuss the special case in which the solution is fully determined by the active constraints, and show that for this case the KKT conditions are sufficient for local optimality and that SCP, SCQP and SQCQP even converge quadratically. In the context of parameter estimation with symmetric convex loss functions, the possible divergence of the methods can in fact be an advantage that helps them to avoid some undesirable local minima: generalizing existing results, we show that the presented methods converge to a local minimum if and only if this local minimum is stable against a mirroring operation applied to the measurement data of the estimation problem. All results are illustrated by numerical experiments on a tutorial example.
Goal-oriented adaptive sampling under random field modelling of response probability distributions
Authors: Gautier Athénaïs , Ginsbourger David , Pirot Guillaume
Published: September 2021

In the study of natural and artificial complex systems, responses that are not completely determined by the considered decision variables are commonly modelled probabilistically, resulting in response distributions varying across decision space. We consider cases where the spatial variation of these response distributions does not only concern their mean and/or variance but also other features including for instance shape or uni-modality versus multi-modality. Our contributions build upon a non-parametric Bayesian approach to modelling the thereby induced fields of probability distributions, and in particular to a spatial extension of the logistic Gaussian model. The considered models deliver probabilistic predictions of response distributions at candidate points, allowing for instance to perform (approximate) posterior simulations of probability density functions, to jointly predict multiple moments and other functionals of target distributions, as well as to quantify the impact of collecting new samples on the state of knowledge of the distribution field of interest. In particular, we introduce adaptive sampling strategies leveraging the potential of the considered random distribution field models to guide system evaluations in a goal-oriented way, with a view towards parsimoniously addressing calibration and related problems from non-linear (stochastic) inversion and global optimisation.
Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine
Authors: Guo Lin Lawrence , Pfohl Stephen R. , Fries Jason , Posada Jose , Fleming Scott Lanyon , Aftandilian Catherine , Shah Nigam , Sung Lillian
Published: September 2021

Objective The change in performance of machine learning models over time as a result of temporal dataset shift is a barrier to machine learning-derived models facilitating decision-making in clinical practice. Our aim was to describe technical procedures used to preserve the performance of machine learning models in the presence of temporal dataset shifts.

Methods Studies were included if they were fully published articles that used machine learning and implemented a procedure to mitigate the effects of temporal dataset shift in a clinical setting. We described how dataset shift was measured, the procedures used to preserve model performance, and their effects.

Results Of 4,457 potentially relevant publications identified, 15 were included. The impact of temporal dataset shift was primarily quantified using changes, usually deterioration, in calibration or discrimination. Calibration deterioration was more common (n = 11) than discrimination deterioration (n = 3). Mitigation strategies were categorized as model level or feature level. Model-level approaches (n = 15) were more common than feature-level approaches (n = 2), with the most common approaches being model refitting (n = 12), probability calibration (n = 7), model updating (n = 6), and model selection (n = 6). In general, all mitigation strategies were successful at preserving calibration but not uniformly successful in preserving discrimination.

Conclusion There was limited research in preserving the performance of machine learning models in the presence of temporal dataset shift in clinical medicine. Future research could focus on the impact of dataset shift on clinical decision making, benchmark the mitigation strategies on a wider range of datasets and tasks, and identify optimal strategies for specific settings.