bluuebunny/crossref_metadata_2025 huggingface dataset:
A ribosomally synthesised and post-translationally modified peptide containing a β-enamino acid and a macrocyclic motif
Authors: Wang Shan , Lin Sixing , Fang Qing , Gyampoh Roland , Lu Zhou , Gao Yingli , Clarke David J. , Wu Kewen , Trembleau Laurent , Yu Yi , Kyeremeh Kwaku , Milne Bruce F. , Tabudravu Jioji , Deng Hai
Published: August 2022

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are structurally complex natural products with diverse bioactivities. Here we report discovery of a RiPP, kintamdin, for which the structure is determined through spectroscopy, spectrometry and genomic analysis to feature a bis-thioether macrocyclic ring and a β-enamino acid residue. Biosynthetic investigation demonstrated that its pathway relies on four dedicated proteins: phosphotransferase KinD, Lyase KinC, kinase homolog KinH and flavoprotein KinI, which share low homologues to enzymes known in other RiPP biosynthesis. During the posttranslational modifications, KinCD is responsible for the formation of the characteristic dehydroamino acid residues including the β-enamino acid residue, followed by oxidative decarboxylation on the C-terminal Cys and subsequent cyclization to provide the bis-thioether ring moiety mediated by coordinated action of KinH and KinI. Finally, conserved genomic investigation allows further identification of two kintamdin-like peptides among the kin-like BGCs, suggesting the occurrence of RiPPs from actinobacteria.
Association between BNT162b2 vaccination and reported incidence of post-COVID-19 symptoms: cross-sectional study 2020-21, Israel
Authors: Kuodi Paul , Gorelik Yanay , Zayyad Hiba , Wertheim Ofir , Wiegler Karine Beiruti , Abu Jabal Kamal , Dror Amiel A. , Nazzal Saleh , Glikman Daniel , Edelstein Michael
Published: August 2022

The effectiveness of Coronavirus disease 2019 (COVID-19) vaccines against the long-term COVID-19 symptoms expressed by a substantial proportion of patients is not well understood. We determined whether vaccination with the BNT162b2 mRNA vaccine was associated with incidence of reporting long-term symptoms post-SARS-CoV-2 infection. We invited individuals PCR-tested for SARS-CoV-2 infection at participating hospitals between March 2020 and November 2021 to fill an online questionnaire that included information about demographics, acute COVID-19 episode and symptoms they were currently experiencing. Using binomial regression, we compared vaccinated individuals with those unvaccinated and those uninfected, in terms of post-acute self-reported symptoms. Of the 951 infected, 637(67%) were vaccinated. In the study population, the most prevalent symptoms were: fatigue (22%), headache (20%), weakness of limbs (13%), and persistent muscle pain (10%). After adjusting for age, time from beginning of symptoms to responding to the survey, and baseline symptoms, those who received two vaccine doses were less likely than unvaccinated individuals to report any of these symptoms (fatigue, headache, weakness of limbs, persistent muscle pain) by 62%, 50%, 62%, and 66% respectively, (Risk ratios 0.38, 0.50, 0.38, 0.34,p < 0.04 in the listed sequence). Compared to the 2447 included individuals who never reported SARS-CoV-2 infection, double-vaccinated participants were no more likely to report any of the mentioned symptoms. Vaccination with 2+ doses of BNT162b2 was associated with a reduced risk of reporting most of the common post-acute COVID-19 symptoms. Our results suggest that BNT162b2 vaccination may have a protective effect against longer term COVID-19 symptoms.
Irrelevant positive emotional information facilitates response inhibition only under a high perceptual load
Authors: Pandey Shubham , Gupta Rashmi
Published: August 2022

Response inhibition involves suppressing those responses that are no longer needed. Previous research has separately studied the role of attentional resources and emotional information in response inhibition. Here, we simultaneously manipulate attentional resources and emotional information to investigate the interactive role of emotional information and attentional resources. Attentional resources were manipulated by changing the levels of perceptual load (low and high) of go signals. Emotional information was manipulated by changing the emotional content (irrelevant positive and negative emotional information) of the stop signals. Participants made a go response based on searching for a target letter in conditions of either low perceptual load or high perceptual load. They withheld their response on the presentation of a stop signal. The stop-signal stimulus was selected from two classes: arousal matched positive and negative IAPS images (Experiment 1) and happy, angry, and neutral faces (Experiment 2). The result showed a consistent interaction pattern of perceptual load and emotional information across the two experiments, such that irrelevant positive emotional information consistently improved inhibitory control, albeit only under high load. These results have theoretical implications for understanding the nature of emotional information and their interaction with attentional resources in cognitive control functions.
Polyp segmentation with consistency training and continuous update of pseudo-label
Authors: Park Hyun-Cheol , Poudel Sahadev , Ghimire Raman , Lee Sang-Woong
Published: August 2022

Polyp segmentation has accomplished massive triumph over the years in the field of supervised learning. However, obtaining a vast number of labeled datasets is commonly challenging in the medical domain. To solve this problem, we employ semi-supervised methods and suitably take advantage of unlabeled data to improve the performance of polyp image segmentation. First, we propose an encoder-decoder-based method well suited for the polyp with varying shape, size, and scales. Second, we utilize the teacher-student concept of training the model, where the teacher model is the student model’s exponential average. Third, to leverage the unlabeled dataset, we enforce a consistency technique and force the teacher model to generate a similar output on the different perturbed versions of the given input. Finally, we propose a method that upgrades the traditional pseudo-label method by learning the model with continuous update of pseudo-label. We show the efficacy of our proposed method on different polyp datasets, and hence attaining better results in semi-supervised settings. Extensive experiments demonstrate that our proposed method can propagate the unlabeled dataset’s essential information to improve performance.
3D transcranial ultrasound localization microscopy for discrimination between ischemic and hemorrhagic stroke in early phase
Authors: Chavignon Arthur , Hingot Vincent , Orset Cyrille , Vivien Denis , Couture Olivier
Published: August 2022

Early diagnosis is a critical part of the emergency care of cerebral hemorrhages and ischemia. A rapid and accurate diagnosis of strokes reduces the delays to appropriate treatments and a better functional recovery. Currently, CTscan and MRI are the gold standards with constraints of accessibility, availability, and possibly some contraindications. The development of Ultrasound Localization Microscopy (ULM) has enabled new perspectives to conventional transcranial ultrasound imaging with increased sensitivity, penetration depth, and resolution. The possibility of volumetric imaging has increased the field-of-view and provided a more precise description of the microvascularisation. In this study, rats (n = 9) were subjected to thromboembolic ischemic stroke or intracerebral hemorrhages prior to volumetric ULM at the early phases after onsets. Although the volumetric ULM performed in the early phase of ischemic stroke revealed a large hypoperfused area in the cortical area of the occluded artery, it showed a more diffused hypoperfusion in the hemorrhagic model. Respective computations of a Microvascular Diffusion Index highlighted different patterns of perfusion loss during the first 24 h of these two strokes’ subtypes. Our study provides the first proof that this methodology should allow early discrimination between ischemic and hemorrhagic stroke with a potential toward diagnosis and monitoring in clinic.
Comparison of leg dynamic models for quadrupedal robots with compliant backbone
Authors: Parra Ricaurte E. A. , Pareja J. , Dominguez S. , Rossi C.
Published: August 2022

Many quadrupeds are capable of power efficient gaits, especially trot and gallop, thanks to their flexible trunk. The oscillations of the system that includes the backbone, the tendons and musculature, store and release elastic energy, helping a smooth deceleration and a fast acceleration of the hindquarters and forequarters, which improves the dynamics of running and its energy efficiency. Forelegs and hindlegs play a key role in generating the bending moment in the trunk. In this paper we present our studies aimed at modeling and reproducing such phenomena for efficient quadrupedal robot locomotion. We propose a model, called mass-mass-spring model, that overcomes the limitation of existing models, and demonstrate that it allows studying how the masses of the legs generate a flexing force that helps the natural bending of the trunk during gallop. We apply our model to six animals, that adopt two different galloping patterns (called transverse androtatory), and compare their energy efficiency.
Spatiotemporal multi-scale modeling of radiopharmaceutical distributions in vascularized solid tumors
Authors: Kiani Shahvandi Mohammad , Soltani M. , Moradi Kashkooli Farshad , Saboury Babak , Rahmim Arman
Published: August 2022

We present comprehensive mathematical modeling of radiopharmaceutical spatiotemporal distributions within vascularized solid tumors. The novelty of the presented model is at mathematical level. From the mathematical viewpoint, we provide a general modeling framework for the process of radiopharmaceutical distribution in the tumor microenvironment to enable an analysis of the effect of various tumor-related parameters on the distribution of different radiopharmaceuticals. We argue that partial differential equations (PDEs), beyond conventional methods, including ODE-based kinetic compartment modeling, can be used to evaluate radiopharmaceutical distribution in both time and space. In addition, we consider the spatially-variable dynamic structure of tumor microvascular networks to simulate blood flow distribution. To examine the robustness of the model, the effects of microvessel density (MVD) and tumor size, as two important factors in tumor prognosis, on the radiopharmaceutical distribution within the tumor are investigated over time (in the present work, we focus on the radiopharmaceutical [18F]FDG, yet the framework is broadly applicable to radiopharmaceuticals). Results demonstrate that the maximum total uptake of [18F]FDG at all time frames occurs in the tumor area due to the high capillary permeability and lack of a functional lymphatic system. As the MVD of networks increases, the mean total uptake in the tumor is also enhanced, where the rate of diffusion from vessel to tissue has the highest contribution and the rate of convection transport has the lowest contribution. The results of this study can be used to better investigate various phenomena and bridge a gap among cancer biology, mathematical oncology, medical physics, and radiology.
N-glycosylation is crucial for trafficking and stability of SLC3A2 (CD98)
Authors: Console Lara , Scalise Mariafrancesca , Salerno Simona , Scanga Raffaella , Giudice Deborah , De Bartolo Loredana , Tonazzi Annamaria , Indiveri Cesare
Published: August 2022

The type II glycoprotein CD98 (SLC3A2) is a membrane protein with pleiotropic roles in cells, ranging from modulation of inflammatory processes, host–pathogen interactions to association with membrane transporters of the SLC7 family. The recent resolution of CD98 structure in complex with LAT1 showed that four Asn residues, N365, N381, N424, N506, harbour N-glycosylation moieties. Then, the role of N-glycosylation on CD98 trafficking and stability was investigated by combining bioinformatics, site-directed mutagenesis and cell biology approach. Single, double, triple and quadruple mutants of the four Asn exhibited altered electrophoretic mobility, with apparent molecular masses from 95 to 70 kDa. The quadruple mutant displayed a single band of 70 kDa corresponding to the unglycosylated protein. The presence in the membrane and the trafficking of CD98 were evaluated by a biotinylation assay and a brefeldin assay, respectively. Taken together, the results highlighted that the quadruple mutation severely impaired both the stability and the trafficking of CD98 to the plasma membrane. The decreased presence of CD98 at the plasma membrane, correlated with a lower presence of LAT1 (SLC7A5) and its transport activity. This finding opens new perspectives for human therapy. Indeed, the inhibition of CD98 trafficking would act synergistically with LAT1 inhibitors that are under clinical trial for anticancer therapy.
Automated segmentation and feature discovery of age-related macular degeneration and Stargardt disease via self-attended neural networks
Authors: Wang Ziyuan , Sadda Srinivas Reddy , Lee Aaron , Hu Zhihong Jewel
Published: August 2022

Age-related macular degeneration (AMD) and Stargardt disease are the leading causes of blindness for the elderly and young adults respectively. Geographic atrophy (GA) of AMD and Stargardt atrophy are their end-stage outcomes. Efficient methods for segmentation and quantification of these atrophic lesions are critical for clinical research. In this study, we developed a deep convolutional neural network (CNN) with a trainable self-attended mechanism for accurate GA and Stargardt atrophy segmentation. Compared with traditional post-hoc attention mechanisms which can only visualize CNN features, our self-attended mechanism is embedded in a fully convolutional network and directly involved in training the CNN to actively attend key features for enhanced algorithm performance. We applied the self-attended CNN on the segmentation of AMD and Stargardt atrophic lesions on fundus autofluorescence (FAF) images. Compared with a preexisting regular fully convolutional network (the U-Net), our self-attended CNN achieved 10.6% higher Dice coefficient and 17% higher IoU (intersection over union) for AMD GA segmentation, and a 22% higher Dice coefficient and a 32% higher IoU for Stargardt atrophy segmentation. With longitudinal image data having over a longer time, the developed self-attended mechanism can also be applied on the visual discovery of early AMD and Stargardt features.
Regularity of colour statistics in explaining colour composition preferences in art paintings
Authors: Nakauchi Shigeki , Tamura Hideki
Published: August 2022

This study explores the role of colour statistics in painting preferences and tests the ‘matching-to-nature’ hypothesis which posits that the preference for the colour composition of paintings depends on the extent to which the paintings resemble the colour statistics of natural scenes. A preference judgement experiment was conducted with 31,353 participants using original and hue-rotated versions of 1,200 paintings. Multiple regression analyses were performed between the measured preferences and paintings’ colour statistics to reveal which colour statistics explained the preference data and to what extent. The colour statistics of art paintings that explained the preference data were compared to the colour statistics of natural scenes. The results identified the colour statistics that significantly contributed to explaining painting preferences, and the distributions of the paintings’ colour statistics systematically differed from those of natural scenes. These findings suggest that the human visual system encodes colour statistics to make aesthetic judgements based on the artistic merit of colour compositions, and not on their similarity to natural scenes.
Shared regulation and functional relevance of local gene co-expression revealed by single cell analysis
Authors: M. Ribeiro Diogo , Ziyani Chaymae , Delaneau Olivier
Published: August 2022

Most human genes are co-expressed with a nearby gene. Previous studies have revealed this local gene co-expression to be widespread across chromosomes and across dozens of tissues. Yet, so far these studies used bulk RNA-seq, averaging gene expression measurements across millions of cells, thus being unclear if this co-expression stems from transcription events in single cells. Here, we leverage single cell datasets in >85 individuals to identify gene co-expression across cells, unbiased by cell-type heterogeneity and benefiting from the co-occurrence of transcription events in single cells. We discover >3800 co-expressed gene pairs in two human cell types, induced pluripotent stem cells (iPSCs) and lymphoblastoid cell lines (LCLs) and (i) compare single cell to bulk RNA-seq in identifying local gene co-expression, (ii) show that many co-expressed genes – but not the majority – are composed of functionally related genes and (iii) using proteomics data, provide evidence that their co-expression is maintained up to the protein level. Finally, using single cell RNA-sequencing (scRNA-seq) and single cell ATAC-sequencing (scATAC-seq) data for the same single cells, we identify gene-enhancer associations and reveal that >95% of co-expressed gene pairs share regulatory elements. These results elucidate the potential reasons for co-expression in single cell gene regulatory networks and warrant a deeper study of shared regulatory elements, in view of explaining disease comorbidity due to affecting several genes. Our in-depth view of local gene co-expression and regulatory element co-activity advances our understanding of the shared regulatory architecture between genes.
A computational approach to analyzing climate strategies of cities pledging net zero
Authors: Sachdeva Siddharth , Hsu Angel , French Ian , Lim Elwin
Published: August 2022

Cities have become primary actors on climate change and are increasingly setting goals aimed at net-zero emissions, which warrants closer examination to understand how they intend to meet these goals. The incomplete and heterogeneous nature of city climate policy documents, however, has made systemic analysis challenging. We analyze 318 climate action documents from cities with net-zero targets using machine learning-based natural language processing (NLP) techniques. We aim to accomplish two goals: (1) determine text patterns that predict ‘ambitious’ net-zero targets; and (2) perform a sectoral analysis to identify patterns and trade-offs in climate action themes. We find that cities with ambitious climate actions tend to emphasize quantitative metrics and specific high-emitting sectors in their plans. Cities predominantly emphasize energy-related actions in their plans, but often at the expense of other sectors, including land-use and climate impacts. The method presented in this paper provides a replicable, scalable approach to analyzing climate action plans and a first step towards facilitating cross-city learning.
Abrupt drainage of Lago Greve, a large proglacial lake in Chilean Patagonia, observed by satellite in 2020
Authors: Hata Shuntaro , Sugiyama Shin , Heki Kosuke
Published: August 2022

Glacial lakes are increasing in number and extent under a warming climate. Despite demand for lake monitoring and understanding outburst mechanisms, studies of large outburst events are sparse. Here we report an outburst of Lago Greve, a large proglacial lake in Chilean Patagonia. During the event in April–July 2020, the lake level dropped by 18.3 ± 1.2 m and the area decreased by 14.5 ± 0.02 km2. The total water discharge was 3.7 ± 0.2 km3, which is one of the largest glacial lake outbursts ever reported in satellite era. Satellite data indicated the collapse of a bump near the lake outlet triggered the event, by initiating erosion of the bank and bed of the outlet stream. Satellite gravimetry captured a signal of the event, although the magnitude of the corresponding mass change was inconsistent with the drained water mass. Our study demonstrated the potential for observing lake outburst using satellite imagery, altimetry, photogrammetry, and gravimetry.
A label-free electrochemical aptasensor based on NH2-MIL-235(Fe) for the sensitive detection of citrinin
Authors: Yan Haoyang , He Baoshan , Xie Lingling , Cao Xiaoyu
Published: August 2022

(A) Synthesis of an NH2–Fe-MOF; (B) preparation of an Apt-Fe-MOF; (C) preparation of an aptasensor for CIT detection.
Unravelling the synthesis of a rare-earth cluster-based metal–organic framework with spn topology
Authors: Bicalho Hudson A. , Saraci Felix , Velazquez-Garcia Jose de J. , Titi Hatem M. , Howarth Ashlee J.
Published: August 2022

A novel rare-earth analogue of MOF-808 with 6-connected nodes is synthesized, shining light on the potential for open metal sites in rare-earth cluster-based MOFs.
Stern–Volmer analysis of photocatalyst fluorescence quenching within hollow-core photonic crystal fibre microreactors
Authors: Gentleman Alexander S. , Lawson Takashi , Ellis Matthew G. , Davis Molly , Turner-Dore Jacob , Ryder Alison S. H. , Frosz Michael H. , Ciaccia Maria , Reisner Erwin , Cresswell Alexander J. , Euser Tijmen G.
Published: August 2022

Optofluidic microreactors enable Stern–Volmer analysis on nanolitre-scale photocatalyst–quencher mixtures. The method is used to measure bimolecular quenching coefficients for a photoredox-catalysed α-C–H alkylation reaction of primary alkylamines.
l-Lysine derived fabrication of Cu@Ni core–satellite nanoassemblies as efficient non-Pt catalysts for the methanol oxidation reaction
Authors: Yang Anzhou , Huang Qiuzi , Wei Ziqi , Yu Zehan , Cui Meifeng , Lei Wu , Tang Yawen , Qiu Xiaoyu
Published: August 2022

With assistance of l-lysine, Cu@Ni core–satellite nanoassemblies were fabricated, which could serve as efficient non-Pt electrocatalysts for the methanol oxidation reaction due to both the component effects and structural features.
Interaction between two polyelectrolytes in monovalent aqueous salt solutions
Authors: Yang Xiang , Scacchi Alberto , Vahid Hossein , Sammalkorpi Maria , Ala-Nissila Tapio
Published: August 2022

The authors have addressed the interactions between two PEs by using the recently developed soft-potential-enhanced Poisson–Boltzmann theory.
Coherent vibrational modes promote the ultrafast internal conversion and intersystem crossing in thiobases
Authors: Teles-Ferreira Danielle Cristina , van Stokkum Ivo HM , Conti Irene , Ganzer Lucia , Manzoni Cristian , Garavelli Marco , Cerullo Giulio , Nenov Artur , Borrego-Varillas Rocío , de Paula Ana Maria
Published: August 2022

The relaxation to the triplet state in thiobases is mediated by conical intersections promoted by vibrational coherences through the population of an intermediate singlet state.
Formation of the quasi-planar B56 boron cluster: topological path from B12 and disk aromaticity
Authors: Buendía Fernando , Pham Hung Tan , Barquera-Lozada José Enrique , Beltrán Sanchez Marcela R. , Nguyen Minh Tho
Published: August 2022

B56 a system with a magenetic ring current that flows in the opposite direction of most of the aromatic systems.
Phase transitions induced by exchange coupling, magnetic field, and temperature in a strongly correlated molecular trimer with a triangular topology
Authors: Nan Nan , Zhou Wang-Huai , Zhang Jun , Li Wei , Yang Jun-Tao , Chen Jie , Xiong Yong-Chen , Tan Guo-Long
Published: August 2022

Phase transitions and Kondo behaviors in a molecular trimer device with a triangular topology manipulated by inter-monomer exchange coupling with and without magnetic fields and at zero and nonzero temperatures.
Origin of the analytical 183W effect and its implications for tungsten isotope analyses
Authors: Budde Gerrit , Archer Gregory J. , Tissot François L. H. , Tappe Sebastian , Kleine Thorsten
Published: August 2022

We provide critical new insights into the nature and origin of a widespread isotope effect for W: it is inconsistent with a nuclear field shift, induced during the chemical separation procedure, and also controlled by the amount of W processed.
Assembly of 5H-dibenzo[a,d]cycloheptenes by a formal [5 + 2] annulation of ortho-aryl alkynyl benzyl alcohols with arenes
Authors: Zhang Zhebing , Cai Tao , Zhan Zhaohui , Xu Huiting , Yu Lemao , Luo Xiang , Li Chunmei , Gao Yuzhen , Wei Xuemei , Chen Xinzhi , Shen Runpu
Published: August 2022

We developed a protocol for the preparation of valuable 5H-dibenzo[a,d]cycloheptenes by a formal [5 + 2] annulation of ortho-aryl alkynyl benzyl alcohols with arenes. Structurally diverse 5H-dibenzo[a,d]cycloheptenes were achieved in moderate to good yields.
Compound green tea (CGT) regulates lipid metabolism in high-fat diet induced mice
Authors: Zhou Caibi , Hu Liuhong , Mu Ren , Mei Xin , Wu Xingli , Wang Chuanming , Zhou Xiaolu
Published: August 2022

Compound green tea is able to decrease the body weight and regulate the plasma lipid indexes, as well as make the abnormal metabolic state return to normal by intervening in different metabolic pathways to partially reverse the lipid metabolism disorder.
Oxa-376 and Oxa-530 variants of β-lactamase: computational study uncovers potential therapeutic targets ofAcinetobacter baumannii
Authors: Halder Sajal Kumar , Mim Maria Mulla , Alif Md. Meharab Hassan , Shathi Jannatul Fardous , Alam Nuhu , Shil Aparna , Himel Mahbubul Kabir
Published: August 2022

Determining novel therapeutic targets ofAcinetobacter baumannii. Deleterious variants, causing antibiotic resistance, were identified by molecular docking and molecular dynamics simulation suggesting new therapeutic targets Oxa-376 and Oxa-530.
Exploring the evolution patterns of melem from thermal synthesis of melamine to graphitic carbon nitride
Authors: Yi Yuhui , Wang Jie , Niu Yingli , Yu Yu , Wu Songmei , Ding Kejian
Published: August 2022

In the exploration of synthesizing graphitic carbon nitride (g-C3N4), the existence of secondary anime bridging units shows the incompleteness of related theories.
Controllable particle migration in liquid crystal flows
Authors: Lesniewska Magdalena , Mottram Nigel , Henrich Oliver
Published: August 2022

We observe novel positional control of a colloidal particle in microchannel flow of a nematic liquid crystal.
Robust adaptive finite‐time control design for the generation of stable oscillations in the strict‐feedback form non‐linear systems with input dead‐zone non‐linearity
Authors: Azhdari Meysam , Binazadeh Tahereh
Published: August 2022

This paper presents a novel finite‐time limit cycle control for a class of strict‐feedback non‐linear systems with input dead‐zone non‐linearity, parameter uncertainties, and unknown disturbances. Creating attractive limit cycles in the phase plane of dynamical systems leads to generating sustained oscillations in the system's output. Achieving the finite‐time limit cycle is an extremely challenging problem because existing finite‐time theorems cannot be applied directly. To solve this difficulty, a novel structure of the sliding surface is introduced concerning the shape of the desired limit cycle. Then, to achieve the control objective, the sliding mode and backstepping control techniques are employed throughout the finite‐time stability concept. Simultaneously, to deal with the parameter uncertainties in the system's dynamic, the adaptive scheme is utilized. Moreover, a finite‐time command filter is introduced to cope with the trouble of the explosion of complexity in the backstepping method. The presented method rigorously ensures that the trajectories of the closed‐loop system converge to a small boundary region of the desired stable limit cycle within a finite time and equivalently the system's output reaches the desired periodic oscillation after a finite time. The applicability and effectiveness of the proposed method are validated by providing the comparative simulation results.
Analysis and optimization of batteries powering inductive pulsed power supplies
Authors: Sun Hao , Yu Xinjie , Li Zhen , Li Bei , Liu Zhizhen , Yang Songheng , He Hongzhuang
Published: August 2022

Inductive pulsed power supply (IPPS) is a promising type of power supplies for electromagnetic launch, but its advantage in energy density is strongly restricted by the primary power source. Fortunately, batteries become a suitable and practical choice for the primary source. In this paper, the working process of battery powering IPPS is analysed in detail. Various indicators of the charging performance are calculated, which are then proved to be irrelevant to most of the parameters of IPPS. Based on this, an optimization method for battery and IPPS system is proposed, in which the charging and discharging processes can be decoupled. And for the decoupled battery charging process, the bi‐objective optimization model is suggested. Several examples illustrate the feasibility and effectiveness of the proposed optimization methods. In order to further improve the performance of the battery and IPPS system, the inherent time constant of the inductors and the output power density of the battery cell should be increased.
Investigation on the optimal operation and control strategy of a wide‐range switched‐capacitor/switched‐inductor DC/DC converter
Authors: Qi Jingjing , Wu Xuezhi , He Shan , Xu Wenzheng , Liu Jingdou
Published: August 2022

Wide‐range DC/DC converters are widely used in telecommunications, electric vehicles, and e‐bikes. In this paper, the operation characteristics of the wide‐range cascaded buck converter with two duty cycles are investigated. The operation principle of switched‐capacitor and switched‐inductor is analyzed to ensure that there are no current or voltage spikes in the system and no additional control is required for them. Based on the volume and efficiency performance indexes, the optimal operating region of the converter should be selected to the left side of the minimum sum point of the two duty cycles. The small signal model of the converter is established, then a control strategy is proposed that the first‐stage duty cycle is directly given based on the optimal operating region, and the second‐stage duty cycle is determined by double closed‐loop control, which has good control performance, economy, and simplicity. The prototype achieved the conversion of 32 to80 V to 5 V/6 A with peak efficiencies of 92.4%/80 V, 93.8%/48 V, 94.5%/32 V. The results proved that the control strategy enables the converter to realize high efficiency and rapid dynamic regulation even in the condition of high voltage gain and wide input range.
Deciphering the radio–star formation correlation on kpc scales
Authors: Vollmer B. , Soida M. , Dallant J.
Published: August 2022

Given the multiple energy-loss mechanisms of cosmic-ray (CR) electrons in galaxies, the tightness of the infrared (IR)–radio continuum correlation is surprising. As the radio continuum emission at GHz frequencies is optically thin, this offers the opportunity to obtain unbiased star formation rates (SFRs) from radio-continuum flux-density measurements. The calorimeter theory can naturally explain the tightness of the far-infrared (FIR)–radio correlation but makes predictions that do not agree with observations. Noncalorimeter models often have to involve a conspiracy to maintain the tightness of the FIR–radio correlation. We extended a published analytical model of galactic disks by including a simplified prescription for the synchrotron emissivity. The galactic gas disks of local spiral galaxies, low-z starburst galaxies, high-z main sequence star-forming galaxies, and high-z starburst galaxies are treated as turbulent clumpy accretion disks. The magnetic field strength is determined by the equipartition between the turbulent kinetic and the magnetic energy densities. Our fiducial model, which includes neither galactic winds nor CR electron secondaries, reproduces the observed radio continuum spectral energy distributions of most (∼70%) of the galaxies. Except for the local spiral galaxies, fast galactic winds can potentially make the conflicting models agree with observations. The observed IR–radio correlations are reproduced by the model within 2σ of the joint uncertainty of model and data for all datasets. The model agrees with the observed SFR–radio correlations within ∼4σ. Energy equipartition between the CR particles and the magnetic field only approximately holds in our models of main sequence star-forming galaxies. If a CR electron calorimeter is assumed, the slope of the IR–radio correlation flattens significantly. Inverse Compton losses are not dominant in the starburst galaxies because in these galaxies not only the gas density but also the turbulent velocity dispersion is higher than in normal star-forming galaxies. Equipartition between the turbulent kinetic and magnetic field energy densities then leads to very high magnetic field strengths and very short synchrotron timescales. The exponents of our model SFR–radio correlations at 150 MHz and 1.4 GHz are very close to one.
Cosmological simulations of self-interacting Bose-Einstein condensate dark matter
Authors: Hartman S. T. H. , Winther H. A. , Mota D. F.
Published: August 2022

Fully 3D cosmological simulations of scalar field dark matter with self-interactions, also known as Bose-Einstein condensate dark matter, are performed using a set of effective hydrodynamic equations. These are derived from the non-linear Schrödinger equation by performing a smoothing operation over scales larger than the de Broglie wavelength, but smaller than the self-interaction Jeans’ length. The dynamics on the de Broglie scale become an effective thermal energy in the hydrodynamic approximation, which is assumed to be subdominant in the initial conditions, but become important as structures collapse and the fluid is shock-heated. The halos that form have Navarro-Frenk-White envelopes, while the centers are cored due to the fluid pressures (thermal + self-interaction), confirming the features found by Dawoodbhoy et al. (2021, MNRAS, 506, 2418) using 1D simulations under the assumption of spherical symmetry. The core radii are largely determined by the self-interaction Jeans’ length, even though the effective thermal energy eventually dominates over the self-interaction energy everywhere, a result that is insensitive to the initial ratio of thermal energy to interaction energy, provided it is sufficiently small to not affect the linear and weakly non-linear regimes. Scaling relations for the simulated population of halos are compared to Milky Way dwarf spheroidals and nearby galaxies, assuming a Burkert halo profile, and are found to not match, although they conform better with observations compared to fuzzy dark matter-only simulations.
Potential Drug Delivery Pathways for Treatment of Alzheimer’s Disease
Authors: Wang Xinying
Published: August 2022

Alzheimer’s Disease (AD) has been one of the most prevalent neurodegenerative disorders that majorly affect patients older than 65 years old. The treatment of the disease costs over 1% of the global GDP [1], yet not many new drugs have been developed which can effectively treat AD based on its pathological characteristics. The major challenge in treating brain disorders such as AD is the Blood-Brain Barrier (BBB) which refrains most of the drug molecules from entering the brain. Through reviewing multiple papers from PubMed Central®(PMC), which is an archive of biomedical and life sciences journal literature at the U.S. National Institutes of Health’s National Library of Medicine (NIH/NLM), three promising drug delivery pathways have been investigated regarding their capabilities and effectivenesses of transporting drug molecules into the brain, which are inorganic nanoparticles, multifunctional liposomes, and transdermal delivery system. In this paper, brief introductions regarding each delivery pathway were offered, and specific experiment that supported the delivery method was presented. The advantages, as well as drawbacks of each type of delivery pathway, were also discussed in this paper.
Analysis on the Pathogenesis and Nursing of Alzheimer’s Disease
Authors: Wang Yuehan
Published: August 2022

Alzheimer’s disease is a neurodegenerative disease that occurs mainly in the elderly population, and as medical advances and human lifespan grows, the impact of Alzheimer’s disease on the quality of human life is gradually expanding. This paper mainly discusses the Pathogenesis and the patients’ nursing issues of Alzheimer’s disease, hoping to help people understand more about the Alzheimer’s disease and get to grips with the treatment and care available to alleviate the impact of Alzheimer’s disease on patients’ life.
Research on Multiple Control Methods for Bionic Hands
Authors: Jiang Haolun
Published: August 2022

With the continuous development of society, the demand of patients for highly accurate and intelligent bionic hands has been increasing, and the control of bionic hands has been greatly improved at this stage, but it is still lacking in precision and sensitivity, and the manufacturing cost is also high. This paper focuses on the most mainstream research on various control methods for bionic hand, lists the specific advantages and disadvantages of different control methods by reading the literature, summarizing and comparing them, and making an in-depth prediction on the future development of the bionic hand. In conclusion, the control mode of the bionic hand still needs to be further studied and combined with different control modes to solve existing problems.
The New Developing Treatment of Parkinson’s Disease
Authors: You Hanlin
Published: August 2022

Parkinson’s disease (PD) is the second most common neurodegenerative illness that affects the central nervous system, especially the motor nervous system and it is marked clinically by movement impairment. Its symptoms usually arise gradually over time. Tremors, limb stiffness and abnormal gait are all obvious in the early phase, and some PD patients also have non-motor symptoms like behavioral problems. Besides, decline of cognition is common in severely ill patients. While the pathogenesis of PD has not been fully studied, genetic and environmental factors are generally thought to play a role. There are a lot of potential mechanisms like mitochondrial dysfunction, neuroinflammation and abnormal metabolism. Drugs therapy is the major treatment for PD. But drugs may bring some side effects, it is urgent to find new treatment targeting at specific sites. This review introduces the current drugs and new developing drugs for PD.
Ultra Wide Band Technology and Indoor Precise Positioning
Authors: Liu Chenming
Published: August 2022

UWB technology is a wireless carrier communication technology that uses frequency bandwidth above 1GHz. This essay mainly focuses on the theory of UWB and one of its most important applications, which is indoor positioning. It will explore some possibilities of UWB in the field of precise positioning. Based on the literature, the theory of UWB and the algorithm of positioning will be shown in a relatively simple way. The result shows that Ultra Wide Band (UWB) technology has the advantages of low system complexity, low power spectral density of transmitted signal, and insensitivity to channel fading. The positioning system based on UWB can be used for the real-time location management of personnel, equipment, and vehicles, as well as to view the real-time location and distribution area of the target., such as nursing home elderly positioning monitoring, to prevent the elderly from getting lost, location management of chemical plant operators, security of dangerous areas, location management of vehicles and equipment, etc.
Analysis of the Future of Ultra-Wideband
Authors: Chen Yibo
Published: August 2022

UWB (ultra broadband wireless communication technology) is the core of the impact radio technology. It has become the focus of attention in the field of wireless communication. This paper aims to analyze the future of ultra-wideband. The definition, principles, and performance characteristics of UWB technology are introduced. The result shows that its bandwidth is greater than all other communication technologies’ bandwidth, and it has the advantages of anti-interference performance, high transmission rate. It has shown great application potential not only in military applications, but also in civil and other fields. UWB shows its advantages in some small and medium-sized enterprises and home environments. It meets the social demands. The research result demonstrates the popularization and prospects of this technology.
The Study on Hardware Security and Its Defense Measures
Authors: He Yang
Published: August 2022

With the globalization of the IC design supply chain and the universal interconnection of computers, the problem of hardware security has become increasingly prominent. The increasing number of hardware security attacks in recent years shows that integrated circuit hardware has become an effective entry point for launching cross-layer and long-range attacks, and it is urgent for academia and industry to propose effective solutions to hardware security problems. This paper focuses on the threat models, defense measures and metrics of hardware attacks including Hardware Trojans, Reverse Engineering and SAT attacks (using algorithms based on satisfiability checking) by literature analysis and comparative analysis. The result shows that most of the protection against Hardware Trojans should be planned at the design stage. Camouflage, logic confusion and watermarking are good ways to defend Reverse Engineering, and for SAT attacks, it is necessary to improve the existing logical encryption technology and use an anti-SAT module.
M-ISDS: A Mobilized Intrusion and Spam Detection System
Authors: Li Yuyang
Published: August 2022

As the world strides into the digital world, cybersecurity has become an indispensable part of connected devices. Although we have developed cybersecurity measures that can effectively defend against malicious software, we don’t have an accurate solution against attacks like social engineering attack, scam calls or phishing. In this work, a novel detection system called m-isds(mobilized intrusion and spam detection system) architecture is proposed, borrowing ideas from the widely utilized advanced hybrid intrusion detection system(ids), combining with some novel concepts including machine learning, advanced hashing technologies and pattern-matching technologies that are secure and cryptographically safe to provide a solution to the proposed system with low false-positive rate and privacy infringement while remaining responsive and flexible against all types of attacks. The system aims to scan the content of the whole terminal on the fly, not only containing and defending against the threat of malicious softwares but also alerting the user of possible scams and spams, bringing the security goal of mobile devices to a whole new level.
The Application of Artificial Intelligence in the Field of Transportation
Authors: Mi Shuo , Yang Lanqi
Published: August 2022

Urban traffic is the lifeblood of urban economic activities and plays a very important role in the development of the urban economy and the improvement of people’s living standards. Although the automobile industry brings convenience, it also brings a heavy burden to urban traffic. The imbalance of urban traffic supply and demand has become a serious problem faced by major cities, especially in large cities, the phenomenon of traffic congestion. This not only affects the normal operation of the city, but also reduces the daily work efficiency of people. This paper is based on mature scientific principles and physical devices, such as dynamic Bayesian network, machine vision, machine learning, pattern recognition technology, temperature sensor, optical fiber sensor, etc. The application of artificial intelligence technology in highway traffic is discussed in detail, which lays a theoretical foundation for the development of intelligent traffic in the future.
Research on the Application of Artificial Intelligence in the Film Industry
Authors: Li Yaxing
Published: August 2022

With the rapid development of technology today, artificial intelligence is inevitably involved in numerous fields including the film production industry, and helps the industry from all periods of the production cycle. This paper focuses on three areas: script writing, special effects production and video restoration, and highlights the application of technologies such as Benjamin, flux system and ESRGAN in these three areas. By analyzing the positive impacts and potential risks, this paper points out that AI technology and human artistic creation are indispensable for the healthy development of the film industry only when they complement to each other, hoping to offer some references for the future research of the the application of artificial intelligence in the film industry.
Stellar Classification by Machine Learning
Authors: Qi Zhuliang
Published: August 2022

As an emerging subject with strong comprehensiveness, machine learning has made varying degrees of progress in various fields. In the field of astronomy, it has also been generally used, and there have been quantities of research using machine learning for data processing and model prediction. The paper has used three algorithms (Decision Tree, Random Forest and Support Vector Machine) to build prediction models to classify stars, galaxies, and quasars in the universe and make a comparison among three models. The results of the test have shown that the prediction accuracy of the Random Forest model reaches roughly 98 percent with a great computing efficiency, which performs the best.
A Comparison of Greedy Algorithm and Dynamic Programming Algorithm
Authors: Chen Xiaoxi
Published: August 2022

Two algorithms to handle the problem include greedy algorithms and dynamic programming. Because of their simplicity, intuitiveness, and great efficiency in addressing problems, they are frequently employed in a variety of circumstances. The connection and difference of the two algorithms are compared by introducing the essential ideas of the two algorithms. The knapsack problem is a classic problem in computer science. In the application of solving the backpack problem, greedy algorithm is faster, but the resulting solution is not always optimal; dynamic programming results in an optimal solution, but the solving speed is slower. The research compares the application properties and application scope of the two strategies, with the greedy approach being the better approach in solving the knapsack problem.
Review on String-Matching Algorithm
Authors: Zhang Zhaoyang
Published: August 2022

String-matching algorithm is one of the most researched algorithms in computer science which has become an important factor in many technologies. This field aims at utilizing the least time and resources to find desired sequence of character in complex data content. The most classical and famous string-search algorithms are Knuth-Morris-Pratt (KMP) algorithm and Boyer-Moore (DM) algorithm. These two algorithms provide efficient heuristic jump rules by prefix or suffix. Bitap algorithm was the first to introduce bit-parallelism into string-matching field. Backward Non-Deterministic DAWG Matching (BNDM) algorithm is a modern practical algorithm that is an outstanding combination of theoretical research and practical application. Those meaningful algorithms play a guiding role in future research in string-search algorithm to improve the average performance of the algorithm and reduce resource consumption.