bluuebunny/crossref_metadata_2025 huggingface dataset:
Robotic monitoring of grasslands: a dataset from the EU Natura2000 habitat 6210* in the central Apennines (Italy)
Authors: Angelini Franco , Pollayil Mathew J. , Bonini Federica , Gigante Daniela , Garabini Manolo
Published: June 2023

Despite the remarkable growth of the global market for robotics, robotic monitoring of habitats is still an understudied topic. This is true, among others, for the species-rich EU Annex I habitat “6210 - Semi-natural grasslands and scrubland facies on calcareous substrates”. This habitat is typically surveyed by human operators. In this work, we present a dataset concerning relevés performed through the quadrupedal robot ANYmal C. The dataset contains information from three plots, which include the robot state, videos, and images acquired to assess the habitat conservation status. Additionally, a collection of videos and pictures about two typical and one early warning species of habitat 6210 is also presented. This database is publicly available in the provided Zenodo repository and will aid researchers in several fields. Robot state information can be used by engineers to validate their algorithms, while data gathered by the robot can be used to design new methodologies and new metrics to assess the habitat conservation status or train/test classifiers (e.g. neural networks) for plant classification.
A large-scale fMRI dataset for human action recognition
Authors: Zhou Ming , Gong Zhengxin , Dai Yuxuan , Wen Yushan , Liu Youyi , Zhen Zonglei
Published: June 2023

Human action recognition is a critical capability for our survival, allowing us to interact easily with the environment and others in everyday life. Although the neural basis of action recognition has been widely studied using a few action categories from simple contexts as stimuli, how the human brain recognizes diverse human actions in real-world environments still needs to be explored. Here, we present the Human Action Dataset (HAD), a large-scale functional magnetic resonance imaging (fMRI) dataset for human action recognition. HAD contains fMRI responses to 21,600 video clips from 30 participants. The video clips encompass 180 human action categories and offer a comprehensive coverage of complex activities in daily life. We demonstrate that the data are reliable within and across participants and, notably, capture rich representation information of the observed human actions. This extensive dataset, with its vast number of action categories and exemplars, has the potential to deepen our understanding of human action recognition in natural environments.
Prognostication and risk factor stratification for survival of patients with hepatocellular carcinoma: a nationwide big data analysis
Authors: Choi Jin Woo , Kang Soohee , Lee Juhee , Choi Yunhee , Kim Hyo-Cheol , Chung Jin Wook
Published: June 2023

This study was conducted to identify risk factors affecting overall survival (OS) and provide prognostication for patients with hepatocellular carcinoma (HCC) using nationwide big data. Between January 2008 and December 2014, 10,573 adult patients with new HCC were registered in a nationwide database. Among them, 6830 patients without missing data were analyzed to construct a prognostication system. A validation cohort of 4580 patients was obtained from a tertiary hospital. All patients were assumed to have received the best treatment. A conditional inference tree analysis was performed to establish a prognostic system. The C-index and calibration plot for 5-year survival were estimated for validation. As a result, the tumor burden (TB) grade was the most significant factor in determining OS, and the cutoff was TB3 (TB1‒3 versus TB4). The patients were ultimately divided into 13 prognosis groups. The C-indexes were 0.714 and 0.737 (95% confidence interval, 0.733–0.742) in the nationwide (derivation) and hospital (validation) cohorts, respectively. In the calibration plot, the 5-year survival of the validation cohort largely matched the 45-degree line. In conclusion, the proposed prognostication system with a simple tree structure enabled the detailed stratification of patient prognosis and visualized the strata of risk factors affecting OS.
Prevalence and proportion estimate of asymptomatic Plasmodium infection in Asia: a systematic review and meta-analysis
Authors: Kotepui Manas , Kotepui Kwuntida Uthaisar , Masangkay Frederick Ramirez , Mahittikorn Aongart , Wilairatana Polrat
Published: June 2023

Asymptomatic Plasmodium infection raises a problem for the persistent transmission of malaria in low-endemic areas such as Asia. This systematic review was undertaken to estimate the prevalence and proportion of asymptomatic Plasmodium infection in Asia. The systematic review was registered at PROSPERO (ID: CRD42022373664). The research followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. A comprehensive search of five databases, Ovid, Scopus, MEDLINE, PubMed, and Embase, was conducted to identify studies of asymptomatic Plasmodium infection in Asian countries. The pooled prevalence of asymptomatic Plasmodium infection, the pooled proportion of asymptomatic Plasmodium infection among all parasitised individuals, and the associated 95% confidence intervals were estimated using a random-effects model. A total of 916 articles were retrieved, and 87 articles that met the criteria were included in the systematic review. The pooled prevalence of asymptomatic Plasmodium infection among enrolled participants in Southeast Asia, South Asia, and Western Asia was 5.8%, 9.4%, and 8.4%, respectively. The pooled proportion of asymptomatic Plasmodium infection among all parasitised individuals in Southeast Asia, South Asia, and Western Asia was 89.3%, 87.2%, and 64.8%, respectively. There was a low prevalence of asymptomatic Plasmodium infection, but there was a high proportion of asymptomatic Plasmodium infection per all parasitised individuals in different parts of Asia. These results may support and facilitate elimination and control programs for asymptomatic Plasmodium infection in Asia.
A tunnel coaxial 3D hyperspectral scanning system for underground mine investigation
Authors: Baik Hyunseob , Son Young-Sun , Kim Kwang-Eun
Published: June 2023

A hyperspectral scanning system was developed for three-dimensional (3D) surface mapping in underground spaces, such as mine shafts and tunnels. A hyperspectral line-scanning camera was mounted on the rotating driver unit coaxial with the tunnel to image both the mine wall and the ceiling. Uniform light was illuminated on the target surface to be imaged using a halogen lamp rotating together with the hyperspectral imaging sensor. Inertial Measuring Unit (IMU) was also attached to the sensor unit together with the hyperspectral camera so that sensor’s geometric information could be acquired simultaneously during imaging. All sensor and controller units were mounted on a cart-type platform for easy movement in the tunnel, and a battery mounted on the platform supplied power for system operation and the halogen light source. The developed scanning system was tested in an actual mine, and 3D hyperspectral images of the internal surface of the mine shaft were successfully obtained.
Ag2(0) dimers within a thioether-functionalized MOF catalyze the CO2 to CH4 hydrogenation reaction
Authors: Zheng Yongkun , Martín Nuria , Boronat Mercedes , Ferrando-Soria Jesús , Mon Marta , Armentano Donatella , Pardo Emilio , Leyva-Pérez Antonio
Published: June 2023

Ultrasmall silver clusters in reduced state are difficult to synthesize since silver atoms tend to rapidly aggregate into bigger entities. Here, we show that dimers of reduced silver (Ag2) are formed within the framework of a metal–organic framework provided with thioether arms in their walls (methioMOF), after reduction with NaBH4of the corresponding Ag+-methioMOF precursor. The resulting Ag2-methioMOF catalyzes the methanation reaction of carbon dioxide (CO2to CH4hydrogenation reaction) under mild reaction conditions (1 atm CO2, 4 atm H2, 140 °C), with production rates much higher than Ag on alumina and even comparable to the state-of-the-art Ru on alumina catalyst (Ru–Al2O3) under these reaction conditions, according to literature results.
Chiral molecule induced valley polarization enhancement of MoS2
Authors: Gao Guangcun , Zhu Jintong , Wei Songrui , Cao Yang , Huang Wei , Liu Zhongxin , Wang Jieqiong , Shen Yijun
Published: June 2023

After being loaded with d-histidine, the valley polarization of the MoS2 monolayer is increased, which is attributed to the selective enhancement of the excitation and emission rate due to the chirality-induced spin selectivity (CISS) effect.
Recent progress and strategic perspectives of inorganic solid electrolytes: fundamentals, modifications, and applications in sodium metal batteries
Authors: Huang Jiawen , Wu Kuan , Xu Gang , Wu Minghong , Dou Shixue , Wu Chao
Published: June 2023

A thorough overview and strategic guideline of inorganic solid-state electrolytes, focusing on the ionic conductivity and interfacial stability, for future sodium-metal batteries.
Boosting mineralized organic pollutants by using a sulfur-vacancy CdS photocatalyst
Authors: Wang Huijie , Wan Yang , Yin Shikang , Xu Mengyang , Zhao Xiaoxue , Liu Xin , Song Xianghai , Wang Huiqin , Zhu Chen , Huo Pengwei
Published: June 2023

S-vacancies CdS photocatalysts induced by Ce-doping were developed for organic pollutant mineralization and CO production in a two-in-one self-recycling system. S-vacancies and Ce3+/Ce4+ as active sites significantly increased the reduction activity.
Computational insights into CO2binding reactions by intramolecular geminal group-IV+/phosphorus- and zirconium+/group-15-based frustrated Lewis pairs
Authors: Wu Chi-Shiun , Su Ming-Der
Published: June 2023

The theoretical evidence reveals that only the controlling factors, which can greatly determine the activation barriers, are quantitatively analyzed in detail using several sophisticated methods.
Difunctional terahertz metasurface with switchable polarization conversion and absorption by VO2 and photosensitive silicon
Authors: Wang Guan , Zuo Shiyi , Liu Jia , Zhang Xin , Li Meichen , Yang Shuang , Jia Yang , Gao Yachen
Published: June 2023

The proposed metasurface with double broadband polarization conversion, absorber, and near-field imaging is realized.
Preferred microenvironments of halogen bonds and hydrogen bonds revealed using statistics and QM/MM calculation studies
Authors: Zhou Liping , Li Jintian , Shi Yulong , Wu Leyun , Zhu Weiliang , Xu Zhijian
Published: June 2023

Halogen bonds (XBs) show preference toward hydrophobic microenvironments compared to hydrogen bonds (HBs). The interaction energies of HBs and XBs are decreased to varying degrees given their specific microenvironments.
The electronic structure of a strongly bound sandwich MoS2–WS2heterobilayer
Authors: Zewdie Getasew Mulualem , Boujnah Mourad , Kim Ju Yeon , Kang Hong Seok
Published: June 2023

A Ca-intercalated Nb-doped MoS2–WS2bilayer is a semiconductor with electron–hole separated into different layers under strain, exhibiting strong interlayer interaction.
Stack bonding in polyaromatic hydrocarbons
Authors: Bayse Craig A.
Published: June 2023

Stack bonding interactions are investigated for coronene and larger polyaromatic hydrocarbon dimers to develop rules governing the preference for parallel displacement and/or twisting in aromatic dimers.
Microplastic-sorbed persistent organic pollutants in coastal Mediterranean Sea areas of Tunisia
Authors: Barhoumi Badreddine , Metian Marc , Zaghden Hatem , Derouiche Abdelkader , Ben Ameur Walid , Ben Hassine Sihem , Oberhaensli François , Mora Janeth , Mourgkogiannis Nikolaos , Al-Rawabdeh Abdulla M. , Chouba Lassaad , Alonso-Hernández Carlos M. , Karapanagioti Hrissi K. , Driss Mohamed Ridha , Mliki Ahmed , Touil Soufiane
Published: June 2023

Microplastic-sorbed POPs were documented for the first time in North Africa. Fragments can be used alongside the pellets for the monitoring of POPs in the marine environment.
Deploying a molecular copper catalyst for efficient degradation of commercial and industrial dyes under practical conditions
Authors: Ali Afsar , Meena Badri Vishal , Shah Naseer Ahmed , Kaushik Tannu , Dolkar Thinles , Ghoroi Chinmay , Dutta Arnab
Published: June 2023

A two-stage process for a sustainable degradation method for industrial dye effluents. The chemical process is triggered by a bio-inspired copper catalyst.
Chemical element variation in fungi-induced coating degradation using laser-induced breakdown spectroscopy combined with Raman spectroscopy, mass spectrometry, and multivariate analyses
Authors: Huang Xi , Liu Lei , Lu Yao , Dong Haoyu , Mao Aofei , Li Peizi , Cui Bai , Silvain Jean-Francois , Lu Yongfeng
Published: June 2023

Chemical element variation in fungi-induced coating degradation.
Facile synthesis of high-entropy alloy nanoparticles on germanane, Ge nanoparticles and wafers
Authors: Ni Chuyi , O’Connor Kevin M. , Trach Jonathan , Butler Cole , Rieger Bernhard , Veinot Jonathan G. C.
Published: June 2023

High-entropy alloy nanoparticles (HEA NPs) can be synthesized on germanane (GeNSs), Ge nanoparticles (GeNPs) and bulk Ge.
N,N′,N′′-Trisubstituted guanidine derivatives as DNA-intercalators: synthesis, crystal structures and biophysical investigations
Authors: Durga Priyadharshini R. , Sathishkumar P. N. , Bensingh M. , Bhuvanesh N. , Vennila K. N. , Karvembu R. , Elango Kuppanagounder P.
Published: June 2023

Biophysical and metadynamics simulation studies indicated partial intercalation of one of the phenyl rings of N,N′,N′′-trisubstituted guanidine derivatives between the base pairs of DNA.
Design, synthesis, and in vitro and in silico studies of 1,3,4-thiadiazole-thiazolidinone hybrids as carbonic anhydrase inhibitors
Authors: Hosseini Nasab Narges , Raza Hussain , Eom Young Seok , Hassan Mubashir , Kloczkowski Andrzej , Chetty Lloyd Christopher , Kruger Hendrik Gert , Kim Song Ja
Published: June 2023

A series of 1,3,4-thiadiazole–thiazolidinones (7a–7j) were synthesized as carbonic anhydrase inhibitors, and based on in vitro analysis the most potent compound was 7i. The kinetic mechanism analysis, MTT assay, and molecular docking studies were also performed.
Green synthesis of fluorescent copper nanoclusters stabilized by epigallocatechin gallate and their applications as a novel troxerutin (trihydroxyethylrutin) and temperature sensor
Authors: Tai Yanfang , Li Lu , Tang Huaiqing , Wang Qitao
Published: June 2023

Schematic representation of the synthesis and the applications of EGCG–Cu NCs for troxerutin sensing and temperature sensing.
Conversion of Phaseolus vulgaris into chemically functionalized biocomposites for efficient methylene blue removal: kinetics, isothermal, and thermodynamics analysis
Authors: Saeed Komal , Kamran Urooj , Khan Amina , Jamal Hasan , Bhatti Haq Nawaz
Published: June 2023

PEG@MG/BB and Ppy/BB biocomposites were designed from Phaseolus vulgaris (bean biomass) for the efficient adsorption of methylene blue from an aqueous stream.
Synthesis of Fe3O4/ZrO2/CuO magnetic nanohybrids and their applications in reducing chromium(vi) and degrading methylene blue under sunlight
Authors: Arayesh Mohammad Amin , Kianfar Ali Hossein , Mohammadnezhad Gholamhossein
Published: June 2023

Using Fe3O4/ZrO2/CuO nanocomposite, MB degradation and Cr(vi) reduction at mild conditions were achieved.
Efficient synthesis of ynones from carboxylic acids and terminal alkynes via Pd/Cu catalysis using 2-chloroimidazolium chloride as the activation reagent
Authors: Zheng Weixiang , Liang Nengde , Fu Yi , Zhong Jing , Zhang Yan , Wang Li , Wang Yuanhua , Wang Qiwei
Published: June 2023

Pd/Cu-catalyzed ynone synthesis uses IPrCl-Cl as an activation reagent, enabling reaction between carboxylic acids & terminal alkynes.
Understanding the Raman enhancement of carbon nanohorns labelled with organic dyes
Authors: Iglesias Daniel , Martín Raúl , Álvarez-Sánchez Miguel Á. , Badía-Domínguez Irene , Vázquez Ester , Carmen Ruiz Delgado M. , Prieto Pilar , Antonia Herrero M.
Published: June 2023

Carbon nanohorns were non-covalently functionalized with organic dyes exhibiting remarkable Raman enhancement highlighting their potential for Raman-based applications. Extensive physico-chemical characterization and in silico studies were performed.
An anthraquinone-based oxime ester as a visible-light photoinitiator for 3D photoprinting applications
Authors: Elian Christine , Sanosa Nil , Bogliotti Nicolas , Herrero Christian , Sampedro Diego , Versace Davy-Louis
Published: June 2023

An anthraquinone-based oxime ester photoinitiating system as a new Type I photoinitiator for 3D photoprinting under LEDs@405 nm irradiation.
Recent developments in the cleavage, functionalization, and conjugation of proteins and peptides at tyrosine residues
Authors: Zhang Shengping , De Leon Rodriguez Luis M. , Li Freda F. , Brimble Margaret A.
Published: June 2023

This review covers recent progress in tyrosine-selective cleavage, functionalization, and conjugation of peptides and proteins. Key applications of Tyr modification are highlighted, demonstrating its great potential for chemistry and biology.
ViCTORIA project: MeerKAT H I observations of the ram pressure stripped galaxy NGC 4523
Authors: Boselli A. , Serra P. , de Gasperin F. , Vollmer B. , Amram P. , Edler H. W. , Fossati M. , Consolandi G. , Côté P. , Cuillandre J. C. , Ferrarese L. , Gwyn S. , Postma J. , Boquien M. , Braine J. , Combes F. , Gavazzi G. , Hensler G. , Miville-Deschenes M. A. , Murgia M. , Roediger J. , Roehlly Y. , Smith R. , Zhang H. X. , Zabel N.
Published: June 2023

We present the first results of a 21 cm H I line pilot observation carried out with the MeerKAT radio telescope in preparation for the ViCTORIA (Virgo Cluster multi Telescope Observations in Radio of Interacting galaxies and AGN) project, an untargeted survey of the Virgo galaxy cluster. The extraordinary quality of the data in terms of sensitivity and angular resolution (rms ∼ 0.65 mJy beam−1 at ∼27″ × 39″ and 11 km s−1 resolution) allowed us to detect an extended (∼10 kpc projected length) low column density (N(HI)≲2.5 × 1020 cm−2) H I gas tail associated with the dwarf (Mstar = 1.6 × 109 M⊙) irregular galaxy NGC 4523 at the northern edge of the cluster. The morphology of the tail and of the stellar disc suggest that the galaxy is suffering a hydrodynamic interaction with the surrounding hot intracluster medium (ICM; ram pressure stripping). The orientation of the trailing tail, the gradient in the H I gas column density at the interface between the cold interstellar medium (ISM) and the hot ICM, the velocity of the galaxy with respect to that of the cluster, and its position indicate that NGC 4523 is infalling for the first time into Virgo from the north-north-west background of the cluster. Using a grid of hydrodynamic simulations, we derive the impact parameters with the surrounding ICM, and estimate that the galaxy will be at pericentre (D ∼ 500–600 kpc) in ∼1 Gyr, where ram pressure stripping will be able to remove most, if not all, of its gas. The galaxy is located on the star formation main sequence when its star formation rate is derived using Hα narrow-band images obtained during the VESTIGE survey, suggesting that NGC 4523 is only at the beginning of its interaction with the surrounding environment. A few H II regions are detected in the deep Hα narrow-band images within the H I gas tail outside the stellar disc. Their ages, derived by comparing their Hα, far-ultraviolet (ASTROSAT/UVIT), near-ultraviolet (GALEX/GUViCS), and optical (NGVS) colours with the predictions of spectral energy distribution fitting models, are ≲30 Myr, and suggest that these H II regions have formed within the stripped gas.
Prediction of secondary cooling water flow and cast slab surface temperature based on wavelet weighted twin support vector machine
Authors: Shi Chunyang , Zhong Ruxin , Sun Peng , Ma Zhicai , Wang Baoshuai , Yin Xinxin , Guo Shiyu
Published: June 2023

The secondary cooling water flow and the cast slab surface temperature can directly affect the quality of the slab. To address the above problems, the group has developed a wavelet weight-twin support vector machine (WTWTSVR) based model for predicting the secondary cooling water flow and the cast slab surface temperature. Compared with traditional machine learning algorithms, the model has the advantages of strong generalization ability, fast computation speed, and good fitting effect, effectively overcoming the disadvantages of multiple locally optimal solutions, equal weights, and easy overfitting that may exist in traditional neural network forecasting algorithms. To reduce the influence of noise interference on the actual data, a wavelet transform-based weighted algorithm (WTW) is introduced on the basis of a twin support vector machine algorithm, and the data is processed by noise reduction using wavelet analysis, while the reconstructed signal is given weights to avoid the overfitting phenomenon. The production practice shows that the prediction accuracy of the model is 92.6% and 93.5% for 200 furnace times (200 groups of samples); the prediction accuracy is 96.2% and 96.3% for secondary cooling water flow rate and casting slab surface temperature within the error range of ±5% and ±10%, respectively. The double hit rate within different error ranges within 10 °C reached 90.4%, which can fully meet the actual production requirements of a steel mill, and also provide guidance for the forecast of the flow rate of the secondary cooling water and the cast slab surface temperature.
A new algorithm of the scheduling of a flexible manufacturing system based on genetic algorithm
Authors: Bao Bizhen , Duan Zhao , Xu Ningbo , Zhang Hongzhou , Luo Yiheng , Wang Wei , Yu Xin , Luo Yang , Liu Xiaoyu
Published: June 2023

In the flexible manufacturing system, a reasonable production scheduling is crucial in shortening the processing completion time and improving the equipment utilization. Traditional manual scheduling cannot effectively solve the complex workshop scheduling problems and cannot provide a scheduling solution that meets the requirements in a short period of time, which can lead to a decrease in processing efficiency. Aiming at the complex job shop scheduling problem, the genetic algorithm is used to find the optimal scheduling solution in this study, taking the number of overdue jobs, the total overdue time, the job completion time, the comprehensive load rate and the maximum load rate of the machine tool as the performance indicators of the scheduling algorithm. The chromosomes are designed as process gene chain and equipment gene chain to improve the diversity and the robustness to scheduling problems of chromosome through crossover, variation, selection and other processes. The impact of different parameter settings on the performance indicators of each scheduling algorithm is researched by adjusting the four algorithm-related parameters, and there has been a certain improvement in the results of the scheduling problems. This study provides a reference for the design and optimization of production scheduling algorithm based on genetic algorithm.
Der Badearzt D.J.E. Trampel und seine Sicht auf rheumatische
Erkrankungen in der zweiten Hälfte des 18. Jahrhunderts
Authors: Schäfer Christoph
Published: June 2023

Unter dem Titel „Beobachtungen und Erfahrungen medicinischen und
chirurgischen Inhalts über die Gicht und über einige Mittel
gegen dieselbe“ veröffentlicht der Badearzt D.J.E. Trampel in
den Jahren 1788 und 1789 ein zweibändiges Werk. Dieses bietet einen
interessanten Einblick in die rheumatologischen Vorstellungen in der zweiten
Hälfte des 18. Jahrhunderts. Trampel differenziert in seinen
„Beobachtungen“ unterschiedliche Verläufe arthritischer
Erkrankungen: Neben dem „Rheumatismus“ und der „Gicht
mit dem Fieber“ beschreibt er eine „kalte Gicht“, die
deutliche Ähnlichkeit mit dem Krankheitsbild der rheumatoiden Arthritis
aufweist. Die physiologischen Vorstellungen und therapeutischen Konzepte sind
humoralpathologisch geprägt. Viele der in der damaligen Zeit
gebräuchlichen Therapien werden von Trampel jedoch aufgrund ihrer
Nebenwirkungen abgelehnt. Zur Behandlung der „kalten Gicht“
empfiehlt er unter anderem den Einsatz der „Fieberrinde“. Auch
wenn die „kalte Gicht“ viele Merkmale der uns bekannten
rheumatoiden Arthritis aufweist, scheitert die klare Abgrenzung als neues und
eigenständiges Krankheitsbild an humoralpathologischen
ätiologischen Vorstellungen. Medizinhistorisch tritt die rheumatoide
Arthritis als eigenständige Entität erst im 19. Jahrhundert
auf.
Synthesis of Halogen-Bond-Donor-Site-Introduced Functional Monomers through Wittig Reaction of Perfluorohalogenated Benzaldehydes: Toward Digitalization as Reliable Strategy in Small-Molecule Synthesis
Authors: Momiyama Norie , Hori Tatsuaki , Kakinuma Shuya , Ohtsuka Naoya , Fujinami Takeshi , Suzuki Toshiyasu
Published: June 2023

The Wittig reaction of perfluoromonohalobenzaldehydes was systematically studied to synthesize 2,3,5,6-tetrafluoro-4-halostyrene (TFXSs) as functional monomers bearing halogen-bond donor sites. The reaction proceeded efficiently in tetrahydrofuran using 1,1,3,3-tetramethylguanidine as an organic base. Correlation analysis quantitatively identified three key factors required to obtain TFXSs in reasonable yields. The present approach not only contributes to the study of halogen-bond-based functional molecules, but also presents digitalization as a potential strategy in small-molecule synthesis.
Exploiting 1,1-Dibromoalkenes as Direct Precursors to 5-Substituted 1,2,3-Triazoles
Authors: Boyer Alistair , Williams Matthew B. , Martin Matthew L. , Wiedmann Steffen
Published: June 2023

1,1-Dibromoalkenes can be used as direct precursors to three classes of 5-substituted 1,2,3-triazoles. Three different approaches to 1,2,3-triazole products were developed, linked to the N1-substituent. Treatment of 1,1-dibromoalkenes with n-butyllithium and reaction with a sulfonyl azide gave 5-substituted 1-sulfonyl-1,2,3-triazoles. The use of lithium base followed by transmetalation to zinc and reaction with aryl azides allowed access to 1-aryl-1,2,3-triazoles. Finally, the use of EtMgBr as base and reaction with an alkyl azide formed 1-alkyl-1,2,3-triazoles.
Management of Pulmonary Arterial Hypertension
Authors: Weatherald Jason , Varughese Rhea A. , Liu Jonathan , Humbert Marc
Published: June 2023

Pulmonary arterial hypertension (PAH) is a rare pulmonary vascular disease characterized by progressive pulmonary arterial remodeling, increased pulmonary vascular resistance, right ventricular dysfunction, and reduced survival. Effective therapies have been developed that target three pathobiologic pathways in PAH: nitric oxide, endothelin-1, and prostacyclin. Approved therapies for PAH include phosphodiesterase type-5 inhibitors, soluble guanylate cyclase stimulators, endothelin receptor antagonists, prostacyclin analogs, and prostacyclin receptor agonists. Management of PAH in the modern era incorporates multidimensional risk assessment to guide the use of these medications. For patients with PAH and without significant comorbidities, current guidelines recommend two oral medications (phosphodiesterase type-5 inhibitor and endothelin receptor antagonist) for low- and intermediate-risk patients, with triple therapy including a parenteral prostacyclin to be considered in those at high or intermediate-high risk. Combination therapy may be poorly tolerated and less effective in patients with PAH and cardiopulmonary comorbidities. Thus, a single-agent approach with individualized decisions to add-on other PAH therapies is recommended in older patients and those with significant comorbid conditions. Management of PAH is best performed in multidisciplinary teams located in experienced centers. Other core pillars of PAH management include supportive and adjunctive treatments including oxygen, diuretics, rehabilitation, and anticoagulation in certain patients. Patients with PAH who progress despite optimal treatment or who are refractory to best medical care should be referred for lung transplantation, if eligible. Despite considerable progress, PAH is often fatal and new therapies that reverse the disease and improve outcomes are desperately needed.
Pseudo-spin order of Wigner crystals in multi-valley electron gases
Authors: Calvera Vladimir , Kivelson Steven A. , Berg Erez
Published: June 2023

We study multi-valley electron gases in the low density (rs ≫ 1) limit. Here the ground-state is always a Wigner crystal (WC), with additional pseudo-spin order where the pseudo-spins are related to valley occupancies. Depending on the symmetries of the host semiconductor and the values of the parameters such as the anisotropy of the effective mass tensors, we find a striped or chiral pseudo-spin antiferromagnet, or a time-reversal symmetry breaking orbital loop-current ordered pseudo-spin ferromagnet. Our theory applies to the recently-discovered WC states in AlAs and in mono and bilayer transition metal dichalcogenides. We identify a set of interesting electronic liquid crystalline phases that could arise by continuous quantum melting of such WCs.
Regularity of the density of states for random Dirac operators
Authors: Zalczer Sylvain
Published: June 2023

We consider random Dirac operators for which we have proved Anderson localization in the work of J.-M. Barbaroux, H. D. Cornean, and S. Zalczer [“Localization for gapped Dirac Hamiltonians with random perturbations: Application to graphene antidot lattices,” Doc. Math. 24, 65–93 (2019)]. We use the Wegner estimate we have got in that paper to prove Lipschitz regularity of the density of states. We use a method based on the Helffer–Sjöstrand formula to get information on the density of states from the Wegner estimate we have proven in the first article.
Modeling directed weighted network based on event coincidence analysis and its application on spatial propagation characteristics
Authors: Wang L. N. , Li M. , Zang C. R.
Published: June 2023

The problem of synchronicity quantification, based on event occurrence time, has become the research focus in different fields. Methods of synchrony measurement provide an effective way to explore spatial propagation characteristics of extreme events. Using the synchrony measurement method of event coincidence analysis, we construct a directed weighted network and innovatively explore the direction of correlations between event sequences. Based on trigger event coincidence, the synchrony of traffic extreme events of base stations is measured. Analyzing topology characteristics of the network, we study the spatial propagation characteristics of traffic extreme events in the communication system, including the propagation area, propagation influence, and spatial aggregation. This study provides a framework of network modeling to quantify the propagation characteristics of extreme events, which is helpful for further research on the prediction of extreme events. In particular, our framework is effective for events that occurred in time aggregation. In addition, from the perspective of a directed network, we analyze differences between the precursor event coincidence and the trigger event coincidence and the impact of event aggregation on the synchrony measurement methods. The precursor event coincidence and the trigger event coincidence are consistent when identifying event synchronization, while there are differences when measuring the event synchronization extent. Our study can provide a reference for the analysis of extreme climatic events such as rainstorms, droughts, and others in the climate field.
Perspective on unconventional computing using magnetic skyrmions
Authors: Lee Oscar , Msiska Robin , Brems Maarten A. , Kläui Mathias , Kurebayashi Hidekazu , Everschor-Sitte Karin
Published: June 2023

Learning and pattern recognition inevitably requires memory of previous events, a feature that conventional CMOS hardware needs to artificially simulate. Dynamical systems naturally provide the memory, complexity, and nonlinearity needed for a plethora of different unconventional computing approaches. In this perspective article, we focus on the unconventional computing concept of reservoir computing and provide an overview of key physical reservoir works reported. We focus on the promising platform of magnetic structures and, in particular, skyrmions, which potentially allow for low-power applications. Moreover, we discuss skyrmion-based implementations of Brownian computing, which has recently been combined with reservoir computing. This computing paradigm leverages the thermal fluctuations present in many skyrmion systems. Finally, we provide an outlook on the most important challenges in this field.
High-performance fixed-bed in situ mass analyzer—ISMA
Authors: Karlsson Arne , Lødeng Rune , Haugholt Karl Henrik , Myhrvold Elisabeth , Plassen Martin , Thorshaug Knut
Published: June 2023

We demonstrate a newly developed high-performance fixed-bed reactor combined with an in situ mass analyzer (ISMA). The ISMA is particularly relevant to sub-second time-resolved studies where mass changes occur due to, e.g., chemical reactions and process conditions such as choice of solid, temperature, gas atmosphere, and pressure. The mass is determined from the optically measured oscillation frequency of a quartz element, yielding a mass resolution below 10 μg—typically 2–3 μg—for samples up to ∼500 mg. By placing the quartz element and optical sensor inside stainless steel pipes and providing heat from the outside, the instrument is applicable up to ∼62 bars and 700 °C. By surrounding this core part of the instrument with a suitable feed system and product analysis instruments, in combination with computer control and logging, time-resolved studies are enabled. The instrument with surrounding feed and product analysis infrastructure is fully automated. Emphasis has been put on making the instrument robust, safe, operationally simple, and user-friendly. We demonstrate the ISMA instrument on selected samples.
Real-space solution to the electronic structure problem for nearly a million electrons
Authors: Dogan Mehmet , Liou Kai-Hsin , Chelikowsky James R.
Published: June 2023

We report a Kohn–Sham density functional theory calculation of a system with more than 200 000 atoms and 800 000 electrons using a real-space high-order finite-difference method to investigate the electronic structure of large spherical silicon nanoclusters. Our system of choice was a 20 nm large spherical nanocluster with 202 617 silicon atoms and 13 836 hydrogen atoms used to passivate the dangling surface bonds. To speed up the convergence of the eigenspace, we utilized Chebyshev-filtered subspace iteration, and for sparse matrix–vector multiplications, we used blockwise Hilbert space-filling curves, implemented in the PARSEC code. For this calculation, we also replaced our orthonormalization + Rayleigh–Ritz step with a generalized eigenvalue problem step. We utilized all of the 8192 nodes (458 752 processors) on the Frontera machine at the Texas Advanced Computing Center. We achieved two Chebyshev-filtered subspace iterations, yielding a good approximation of the electronic density of states. Our work pushes the limits on the capabilities of the current electronic structure solvers to nearly 106 electrons and demonstrates the potential of the real-space approach to efficiently parallelize large calculations on modern high-performance computing platforms.
Stochastic domain wall-magnetic tunnel junction artificial neurons for noise-resilient spiking neural networks
Authors: Leonard Thomas , Liu Samuel , Jin Harrison , Incorvia Jean Anne C.
Published: June 2023

The spatiotemporal nature of neuronal behavior in spiking neural networks (SNNs) makes SNNs promising for edge applications that require high energy efficiency. To realize SNNs in hardware, spintronic neuron implementations can bring advantages of scalability and energy efficiency. Domain wall (DW)-based magnetic tunnel junction (MTJ) devices are well suited for probabilistic neural networks given their intrinsic integrate-and-fire behavior with tunable stochasticity. Here, we present a scaled DW-MTJ neuron with voltage-dependent firing probability. The measured behavior was used to simulate a SNN that attains accuracy during learning compared to an equivalent, but more complicated, multi-weight DW-MTJ device. The validation accuracy during training was also shown to be comparable to an ideal leaky integrate and fire device. However, during inference, the binary DW-MTJ neuron outperformed the other devices after Gaussian noise was introduced to the Fashion-MNIST classification task. This work shows that DW-MTJ devices can be used to construct noise-resilient networks suitable for neuromorphic computing on the edge.
Investigation of an improved FitzHugh–Rinzel neuron and its multiplier-less circuit implementation
Authors: Tabekoueng Zeric Njitacke , Sriram Balakrishnan , Rajagopal Karthikeyan , Karthikeyan Anitha , Awrejcewicz Jan
Published: June 2023

Circuit implementation of the mathematical model of neurons represents an alternative approach for the validation of their dynamical behaviors for their potential applications in neuromorphic engineering. In this work, an improved FitzHugh–Rinzel neuron, in which the traditional cubic nonlinearity is swapped with a sine hyperbolic function, is introduced. This model has the advantage that it is multiplier-less since the nonlinear component is just implemented with two diodes in anti-parallel. The stability of the proposed model revealed that it has both stable and unstable nodes around its fixed points. Based on the Helmholtz theorem, a Hamilton function that enables the estimation of the energy released during the various modes of electrical activity is derived. Furthermore, numerical computation of the dynamic behavior of the model revealed that it was able to experience coherent and incoherent states involving both bursting and spiking. In addition, the simultaneous appearance of two different types of electric activity for the same neuron parameters is also recorded by just varying the initial states of the proposed model. Finally, the obtained results are validated using the designed electronic neural circuit, which has been analyzed in the Pspice simulation environment.
Diversity of plant DNA in stool is linked to dietary quality, age, and household income
Authors: Petrone Brianna L. , Aqeel Ammara , Jiang Sharon , Durand Heather K. , Dallow Eric P. , McCann Jessica R. , Dressman Holly K. , Hu Zhengzheng , Tenekjian Christine B. , Yancy William S. , Lin Pao-Hwa , Scialla Julia J. , Seed Patrick C. , Rawls John F. , Armstrong Sarah C. , Stevens June , David Lawrence A.
Published: June 2023

Eating a varied diet is a central tenet of good nutrition. Here, we develop a molecular tool to quantify human dietary plant diversity by applying DNA metabarcoding with the chloroplast
trnL
-P6 marker to 1,029 fecal samples from 324 participants across two interventional feeding studies and three observational cohorts. The number of plant taxa per sample (plant metabarcoding richness or pMR) correlated with recorded intakes in interventional diets and with indices calculated from a food frequency questionnaire in typical diets (ρ = 0.40 to 0.63). In adolescents unable to collect validated dietary survey data,
trnL
metabarcoding detected 111 plant taxa, with 86 consumed by more than one individual and four (wheat, chocolate, corn, and potato family) consumed by >70% of individuals. Adolescent pMR was associated with age and household income, replicating prior epidemiologic findings. Overall,
trnL
metabarcoding promises an objective and accurate measure of the number and types of plants consumed that is applicable to diverse human populations.
The spread of participial clauses in Biblical Greek
Authors: Nardi Edoardo
Published: June 2023

In this study, a construction marginally found in Ancient Greek is addressed, namely the participial clause, which is a clause whose main verb is a participle. This construction displays a considerable increase in frequency in Biblical Greek (mainly between the 2nd century bce and the 2nd century ce), which is the language found in Judaeo-Christian literature and which features, in various ways and to various degrees, the influence of Semitic languages. Since the participial clause is a very common construction in these tongues, wherein it even exhibits increasing productivity and frequency at the time at issue, I suggest that the frequency increase observed in Greek should be attributed to the influence of these Semitic languages, with a crucial role played by multilingualism. The issue is addressed from the perspective of language contact, which provides the theoretical and terminological frame by which the phenomenon is individuated and defined.
Distinct inflammatory Th17 subsets emerge in autoimmunity and infection
Authors: Bouch Ronald J. , Zhang Jing , Miller Brandi C. , Robbins Caroline J. , Mosher Timothy H. , Li Wencheng , Krupenko Sergey A. , Nagpal Ravinder , Zhao Jun , Bloomfeld Richard S. , Lu Yong , Nikiforov Mikhail A. , Song Qianqian , He Zhiheng
Published: June 2023

Th17 cells play a critical role in both tissue homeostasis and inflammation during clearance of infections as well as autoimmune and inflammatory disorders. Despite numerous efforts to distinguish the homeostatic and inflammatory roles of Th17 cells, the mechanism underlying the divergent functions of inflammatory Th17 cells remains poorly understood. In this study, we demonstrate that the inflammatory Th17 cells involved in autoimmune colitis and those activated during colitogenic infection are distinguishable populations characterized by their differential responses to the pharmacological molecule, clofazimine (CLF). Unlike existing Th17 inhibitors, CLF selectively inhibits proautoimmune Th17 cells while preserving the functional state of infection-elicited Th17 cells partially by reducing the enzyme ALDH1L2. Overall, our study identifies two distinct subsets within the inflammatory Th17 compartment with distinct regulatory mechanisms. Furthermore, we highlight the feasibility to develop disease-promoting Th17 selective inhibitor for treating autoimmune diseases.
Data-driven discovery of stochastic dynamical equations of collective motion
Authors: Nabeel Arshed , Jadhav Vivek , M Danny Raj , Sire Clément , Theraulaz Guy , Escobedo Ramón , Iyer Srikanth K , Guttal Vishwesha
Published: June 2023

Coarse-grained descriptions of collective motion of flocking systems are often derived for the macroscopic or the thermodynamic limit. However, the size of many real flocks falls within ‘mesoscopic’ scales (10 to 100 individuals), where stochasticity arising from the finite flock sizes is important. Previous studies on mesoscopic models have typically focused on non-spatial models. Developing mesoscopic scale equations, typically in the form of stochastic differential equations, can be challenging even for the simplest of the collective motion models that explicitly account for space. To address this gap, here, we take a novel data-driven equation learning approach to construct the stochastic mesoscopic descriptions of a simple, spatial, self-propelled particle (SPP) model of collective motion. In the spatial model, a focal individual can interact with k randomly chosen neighbours within an interaction radius. We consider k = 1 (called stochastic pairwise interactions), k = 2 (stochastic ternary interactions), and k equalling all available neighbours within the interaction radius (equivalent to Vicsek-like local averaging). For the stochastic pairwise interaction model, the data-driven mesoscopic equations reveal that the collective order is driven by a multiplicative noise term (hence termed, noise-induced flocking). In contrast, for higher order interactions (k > 1), including Vicsek-like averaging interactions, models yield collective order driven by a combination of deterministic and stochastic forces. We find that the relation between the parameters of the mesoscopic equations describing the dynamics and the population size are sensitive to the density and to the interaction radius, exhibiting deviations from mean-field theoretical expectations. We provide semi-analytic arguments potentially explaining these observed deviations. In summary, our study emphasises the importance of mesoscopic descriptions of flocking systems and demonstrates the potential of the data-driven equation discovery methods for complex systems studies.
A scoping review of current and emerging techniques for evaluation of peripheral nerve health, degeneration and regeneration: part 2, non-invasive imaging
Authors: Mandeville Ross , Deshmukh Swati , Tan Ek Tsoon , Kumar Viksit , Sanchez Benjamin , Dowlatshahi Arriyan S , Luk Justin , See Reiner Henson B , Leochico Carl Froilan D , Thum Jasmine A , Bazarek Stanley , Johnston Benjamin , Brown Justin , Wu Jim , Sneag Darryl , Rutkove Seward
Published: June 2023

Peripheral neuroregenerative research and therapeutic options are expanding exponentially. With this expansion comes an increasing need to reliably evaluate and quantify nerve health. Valid and responsive measures of the nerve status are essential for both clinical and research purposes for diagnosis, longitudinal follow-up, and monitoring the impact of any intervention. Furthermore, novel biomarkers can elucidate regenerative mechanisms and open new avenues for research. Without such measures, clinical decision-making is impaired, and research becomes more costly, time-consuming, and sometimes infeasible. Part 1 of this two-part scoping review focused on neurophysiology. In part 2, we identify and critically examine many current and emerging non-invasive imaging techniques that have the potential to evaluate peripheral nerve health, particularly from the perspective of regenerative therapies and research.
Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes
Authors: Romeni Simone , Losanno Elena , Koert Elisabeth , Pierantoni Luca , Delgado-Martinez Ignacio , Navarro Xavier , Micera Silvestro
Published: June 2023

Objective. Peripheral nerve interfaces have the potential to restore sensory, motor, and visceral functions. In particular, intraneural interfaces allow targeting deep neural structures with high selectivity, even if their performance strongly depends upon the implantation procedure and the subject’s anatomy. Currently, few alternatives exist for the determination of the target subject structural and functional anatomy, and statistical characterizations from cadaveric samples are limited because of their high cost. We propose an optimization workflow that can guide both the pre-surgical planning and the determination of maximally selective multisite stimulation protocols for implants consisting of several intraneural electrodes, and we characterize its performance in silico. We show that the availability of structural and functional information leads to very high performances and allows taking informed decisions on neuroprosthetic design. Approach. We employ hybrid models (HMs) of neuromodulation in conjunction with a machine learning-based surrogate model to determine fiber activation under electrical stimulation, and two steps of optimization through particle swarm optimization to optimize in silico implant geometry, implantation and stimulation protocols using morphological data from the human median nerve at a reduced computational cost. Main results. Our method allows establishing the optimal geometry of multi-electrode transverse intra-fascicular multichannel electrode implants, the optimal number of electrodes to implant, their optimal insertion, and a set of multipolar stimulation protocols that lead in silico to selective activation of all the muscles innervated by the human median nerve. Significance. We show how to use effectively HMs for optimizing personalized neuroprostheses for motor function restoration. We provide in-silico evidences about the potential of multipolar stimulation to increase greatly selectivity. We also show that the knowledge of structural and functional anatomies of the target subject leads to very high selectivity and motivate the development of methods for their in vivo characterization.