bluuebunny/crossref_metadata_2025 huggingface dataset:
Non-invasive detection and complementary diagnosis of liver metastases via chemokine receptor 4 imaging
Authors: Yang Hua , Tan Shanshan , Qiao Jingjuan , Xu Yiting , Gui Zongxiang , Meng Yuguang , Dong Bin , Peng Guangda , Ibhagui Oluwatosin Y. , Qian Weiping , Lu Jimmy , Li Zezhong , Wang Guimin , Lai Jinping , Yang Lily , Grossniklaus Hans E. , Yang Jenny J.
Published: February 2022

Noninvasive detection of early-stage liver metastases from different primary cancers is a pressing unmet medical need. The lack of both molecular biomarkers and the sensitive imaging methodology makes the detection challenging. In this study, we observed the elevated expression of chemokine receptor 4 (CXCR4) in uveal melanoma (UM) patient liver tissues, and high CXCR4 expression in liver metastases of UM murine models, regardless of the expression levels in the primary tumors. Based on these findings, we identified CXCR4 as an imaging biomarker and exploited a CXCR4-targeted MRI contrast agent ProCA32.CXCR4 for molecular MRI imaging. ProCA32.CXCR4 has strong CXCR4 binding affinity, high metal selectivity, and r1 and r2 relaxivities, which enables the sensitive detection of liver micrometastases. The MRI imaging capacity for detecting liver metastases was demonstrated in three UM models and one ovarian cancer model. The imaging results were validated by histological and immunohistochemical analysis. ProCA32.CXCR4 has strong potential clinical application for non-invasive diagnosis of liver metastases.
Inference on the dynamics of COVID-19 in the United States
Authors: Bhattacharjee Satarupa , Liao Shuting , Paul Debashis , Chaudhuri Sanjay
Published: February 2022

The evolution of the COVID-19 pandemic is described through a time-dependent stochastic dynamic model in discrete time. The proposed multi-compartment model is expressed through a system of difference equations. Information on the social distancing measures and diagnostic testing rates are incorporated to characterize the dynamics of the various compartments of the model. In contrast with conventional epidemiological models, the proposed model involves interpretable temporally static and dynamic epidemiological rate parameters. A model fitting strategy built upon nonparametric smoothing is employed for estimating the time-varying parameters, while profiling over the time-independent parameters. Confidence bands of the parameters are obtained through a residual bootstrap procedure. A key feature of the methodology is its ability to estimate latent unobservable compartments such as the number of asymptomatic but infected individuals who are known to be the key vectors of COVID-19 spread. The nature of the disease dynamics is further quantified by relevant epidemiological markers that make use of the estimates of latent compartments. The methodology is applied to understand the true extent and dynamics of the pandemic in various states within the United States (US).
A predictive model and a field study on heterogeneous slug distribution in arable fields arising from density dependent movement
Authors: Petrovskii Sergei , Ellis John , Forbes Emily , Petrovskaya Natalia , Walters Keith F. A.
Published: February 2022

Factors and processes determining heterogeneous (‘patchy’) population distributions in natural environments have long been a major focus in ecology. Existing theoretical approaches proved to be successful in explaining vegetation patterns. In the case of animal populations, existing theories are at most conceptual: they may suggest a qualitative explanation but largely fail to explain patchiness quantitatively. We aim to bridge this knowledge gap. We present a new mechanism of self-organized formation of a patchy spatial population distribution. A factor that was under-appreciated by pattern formation theories is animal sociability, which may result in density dependent movement behaviour. Our approach was inspired by a recent project on movement and distribution of slugs in arable fields. The project discovered a strongly heterogeneous slug distribution and a specific density dependent individual movement. In this paper, we bring these two findings together. We develop a model of density dependent animal movement to account for the switch in the movement behaviour when the local population density exceeds a certain threshold. The model is fully parameterized using the field data. We then show that the model produces spatial patterns with properties closely resembling those observed in the field, in particular to exhibit similar values of the aggregation index.
Using DNA metabarcoding as a novel approach for analysis of platypus diet
Authors: Hawke Tahneal , Bino Gilad , Shackleton Michael E. , Ross Alexandra K. , Kingsford Richard T.
Published: February 2022

Platypuses (Ornithorhynchus anatinus) forage for macroinvertebrate prey exclusively in freshwater habitats. Because food material in their faeces is well digested and mostly unidentifiable, previous dietary studies have relied on cheek pouch assessments and stable isotope analysis. Given DNA metabarcoding can identify species composition from only fragments of genetic material, we investigated its effectiveness in analysing the diet of platypuses, and to assess variation across seasons and sexes. Of the 18 orders and 60 families identified, Ephemeroptera and Diptera were the most prevalent orders, detected in 100% of samples, followed by Trichoptera, Pulmonata, and Odonata (86.21% of samples). Caenidae and Chironomidae were the most common families. Diptera had a high average DNA read, suggesting it is an important dietary component that may have been underestimated in previous studies. We found no variation in diet between sexes and only minimal changes between seasons. DNA metabarcoding proved to be a highly useful tool for assessing platypus diet, improving prey identification compared to cheek pouch analysis, which can underestimate soft-bodied organisms, and stable isotope analysis which cannot distinguish all taxa isotopically. This will be a useful tool for investigating how platypus prey diversity is impacted by habitat degradation as a result of anthropogenic stressors.
Beyond Dunbar circles: a continuous description of social relationships and resource allocation
Authors: Tamarit Ignacio , Sánchez Angel , Cuesta José A.
Published: February 2022

We discuss the structure of human relationship patterns in terms of a new formalism that allows to study resource allocation problems where the cost of the resource may take continuous values. This is in contrast with the main focus of previous studies where relationships were classified in a few, discrete layers (known as Dunbar’s circles) with the cost being the same within each layer. We show that with our continuum approach we can identify a parameter $$\eta $$
η
that is the equivalent of the ratio of relationships between adjacent circles in the discrete case, with a value $$\eta \sim 6$$

η
∼
6

. We confirm this prediction using three different datasets coming from phone records, face-to-face contacts, and interactions in Facebook. As the sample size increases, the distributions of estimated parameters smooth around the predicted value of $$\eta $$
η
. The existence of a characteristic value of the parameter at the population level indicates that the model is capturing a seemingly universal feature on how humans manage relationships. Our analyses also confirm earlier results showing the existence of social signatures arising from having to allocate finite resources into different relationships, and that the structure of online personal networks mirrors those in the off-line world.
Diffuse optical reconstructions of functional near infrared spectroscopy data using maximum entropy on the mean
Authors: Cai Zhengchen , Machado Alexis , Chowdhury Rasheda Arman , Spilkin Amanda , Vincent Thomas , Aydin Ümit , Pellegrino Giovanni , Lina Jean-Marc , Grova Christophe
Published: February 2022

Functional near-infrared spectroscopy (fNIRS) measures the hemoglobin concentration changes associated with neuronal activity. Diffuse optical tomography (DOT) consists of reconstructing the optical density changes measured from scalp channels to the oxy-/deoxy-hemoglobin concentration changes within the cortical regions. In the present study, we adapted a nonlinear source localization method developed and validated in the context of Electro- and Magneto-Encephalography (EEG/MEG): the Maximum Entropy on the Mean (MEM), to solve the inverse problem of DOT reconstruction. We first introduced depth weighting strategy within the MEM framework for DOT reconstruction to avoid biasing the reconstruction results of DOT towards superficial regions. We also proposed a new initialization of the MEM model improving the temporal accuracy of the original MEM framework. To evaluate MEM performance and compare with widely used depth weighted Minimum Norm Estimate (MNE) inverse solution, we applied a realistic simulation scheme which contained 4000 simulations generated by 250 different seeds at different locations and 4 spatial extents ranging from 3 to 40$$\text {cm}^2$$

cm
2

along the cortical surface. Our results showed that overall MEM provided more accurate DOT reconstructions than MNE. Moreover, we found that MEM was remained particularly robust in low signal-to-noise ratio (SNR) conditions. The proposed method was further illustrated by comparing to functional Magnetic Resonance Imaging (fMRI) activation maps, on real data involving finger tapping tasks with two different montages. The results showed that MEM provided more accurate HbO and HbR reconstructions in spatial agreement with the main fMRI cluster, when compared to MNE.
Occurrence of plasmid-mediated quinolone resistance genes in Pseudomonas aeruginosa strains isolated from clinical specimens in southwest Iran: a multicentral study
Authors: Saki Morteza , Farajzadeh Sheikh Ahmad , Seyed-Mohammadi Sakineh , Asareh Zadegan Dezfuli Aram , Shahin Mojtaba , Tabasi Maryam , Veisi Hojat , Keshavarzi Raziyeh , Khani Parisa
Published: February 2022

This study aimed to assess the presence of qnrA, qnrB, qnrC, qnrD, qnrS, qepA, and aac(6′)-Ib-cr determinants as well as quinolone resistance pattern of clinical isolates of P. aeruginosa in Ahvaz, southwest Iran. A total of 185 clinical isolates of P. aeruginosa were collected from 5 university-affiliated hospitals in Ahvaz, southwest Iran. The disk diffusion method was applied to assess the quinolone resistance pattern. The presence of qnrA, qnrB, qnrC, qnrD, qnrS, qepA, and aac(6′)-Ib-cr genes was investigated by the polymerase chain reaction (PCR) method. Overall, 120 (64.9%) isolates were non-susceptible to quinolones. The most and the less quinolone resistance rates were observed against ciprofloxacin (59.4%) and ofloxacin (45.9%), respectively. The prevalence rates of qnr genes were as follows: qnrA (25.8%), qnrB (29.2%), and qnrS (20.8%). The qnrB gene was the most common type of qnr genes. The qnr genes were occurred in 37.5% (n = 45/120) of quinolne-resistant isolates, simultaneously. The qnrC, qnrD, qepA, and aac(6′)-Ib-cr genes were not recognized in any isolates. In conclusion, the ofloxacin was the most effective quinolone. This study was the first to shed light on the prevalence of PMQR genes among P. aeruginosa isolates in southwest Iran.
Network control by a constrained external agent as a continuous optimization problem
Authors: Nys Jannes , van den Heuvel Milan , Schoors Koen , Merlevede Bruno
Published: February 2022

Social science studies dealing with control in networks typically resort to heuristics or solely describing the control distribution. Optimal policies, however, require interventions that optimize control over a socioeconomic network subject to real-world constraints. We integrate optimisation tools from deep-learning with network science into a framework that is able to optimize such interventions in real-world networks. We demonstrate the framework in the context of corporate control, where it allows to characterize the vulnerability of strategically important corporate networks to sensitive takeovers, an important contemporaneous policy challenge. The framework produces insights that are relevant for governing real-world socioeconomic networks, and opens up new research avenues for improving our understanding and control of such complex systems.
Comparison of mental health outcomes in seropositive and seronegative adolescents during the COVID19 pandemic
Authors: Blankenburg Judith , Wekenborg Magdalena K. , Reichert Jörg , Kirsten Carolin , Kahre Elisabeth , Haag Luise , Schumm Leonie , Czyborra Paula , Berner Reinhard , Armann Jakob P.
Published: February 2022

Post-COVID19 complications such as pediatric inflammatory multisystem syndrome (PIMS) and Long-COVID19 move increasingly into focus, potentially causing more harm in young adolescents than the acute infection. To better understand the symptoms of long-term mental health outcomes in adolescents and distinguish infection-associated symptoms from pandemic-associated symptoms, we conducted a 12 question Long-COVID19 survey. Using this survey, we compared the responses on neurocognitive, general pain and mood symptoms from seropositive and seronegative adolescents in a cross-sectional study design. Since May 2020, students grade 8–12 in fourteen secondary schools in Eastern Saxony were enrolled in the SchoolCovid19 study. Serostatus was assessed regularly in all participants. In March/April 2021, 1560 students with a median age of 15 years participated at the regular study visit after re-opening of the schools in mid-March and responded to our Long-COVID19 survey as part of this visit. 1365 (88%) students were seronegative, 188 (12%) were seropositive. Each symptom asked in the Long-COVID19 survey was present in at least 35% of the students within the last seven days before the survey. With the exception of seropositive students being less sad, there was no significant difference comparing the reported symptoms between seropositive students and seronegative students. The lack of differences comparing the reported symptoms between seropositive and seronegative students suggests that Long-COVID19 might be less common than previously thought and emphasizes on the impact of pandemic-associated symptoms regarding the well-being and mental health of young adolescents.

Clinical Trial Registration: SchoolCoviDD19: Prospektive Erfassung der SARS-CoV-2 Seropositivität bei Schulkindern nach Ende der unterrichtsfreien Zeit aufgrund der Corona-Schutz-Verordnung (COVID-19), DRKS00022455, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00022455
Derivation of healthy hepatocyte-like cells from a female patient with ornithine transcarbamylase deficiency through X-inactivation selection
Authors: Santamaria Ramon , Ballester Maria , Garcia-Llorens Guillem , Martinez Francisco , Blazquez Marina , Ribes-Koninckx Carmen , Castell Jose V. , Wuestefeld Torsten , Bort Roque
Published: February 2022

Autologous cell replacement therapy for inherited metabolic disorders requires the correction of the underlying genetic mutation in patient’s cells. An unexplored alternative for females affected from X-linked diseases is the clonal selection of cells randomly silencing the X-chromosome containing the mutant allele, without in vivo or ex vivo genome editing. In this report, we have isolated dermal fibroblasts from a female patient affected of ornithine transcarbamylase deficiency and obtained clones based on inactivation status of either maternally or paternally inherited X chromosome, followed by differentiation to hepatocytes. Hepatocyte-like cells derived from these clones display indistinct features characteristic of hepatocytes, but express either the mutant or wild type OTC allele depending on X-inactivation pattern. When clonally derived hepatocyte-like cells were transplanted into FRG® KO mice, they were able to colonize the liver and recapitulate OTC-dependent phenotype conditioned by X-chromosome inactivation pattern. This approach opens new strategies for cell therapy of X-linked metabolic diseases and experimental in vitro models for drug development for such diseases.
ILF2 enhances the DNA cytosine deaminase activity of tumor mutator APOBEC3B in multiple myeloma cells
Authors: Kazuma Yasuhiro , Shirakawa Kotaro , Tashiro Yusuke , Yamazaki Hiroyuki , Nomura Ryosuke , Horisawa Yoshihito , Takeuchi Suguru , Stanford Emani , Konishi Yoshinobu , Matsui Hiroyuki , Matsumoto Tadahiko , Tanabe Fumiko , Morishita Ryo , Ito Shinji , Takaori-Kondo Akifumi
Published: February 2022

DNA cytosine deaminase APOBEC3B (A3B) is an endogenous source of mutations in many human cancers, including multiple myeloma. A3B proteins form catalytically inactive high molecular mass (HMM) complexes in nuclei, however, the regulatory mechanisms of A3B deaminase activity in HMM complexes are still unclear. Here, we performed mass spectrometry analysis of A3B-interacting proteins from nuclear extracts of myeloma cell lines and identified 30 putative interacting proteins. These proteins are involved in RNA metabolism, including RNA binding, mRNA splicing, translation, and regulation of gene expression. Except for SAFB, these proteins interact with A3B in an RNA-dependent manner. Most of these interacting proteins are detected in A3B HMM complexes by density gradient sedimentation assays. We focused on two interacting proteins, ILF2 and SAFB. We found that overexpressed ILF2 enhanced the deaminase activity of A3B by 30%, while SAFB did not. Additionally, siRNA-mediated knockdown of ILF2 suppressed A3B deaminase activity by 30% in HEK293T cell lysates. Based on these findings, we conclude that ILF2 can interact with A3B and enhance its deaminase activity in HMM complexes.
Negative impact of the hypopnea index or duration increase after a non-frame work surgery in patients with very severe obstructive sleep apnea
Authors: Huang Ethan I. , Huang Shu-Yi , Lin Yu-Ching , Lin Chieh-Mo , Lin Chin-Kuo , Huang Ying-Chih , Hsu Chia-Yu , Su Jian-An
Published: February 2022

A non-framework surgery could change the postoperative components of breathing disturbances and increase the frequency or duration of hypopnea in patients with very severe obstructive sleep apnea (OSA). Either an increase of hypopnea index, which increases apnea–hypopnea index (AHI), or an increase of its duration raises the concern of worsening the oxygen desaturation and so morbidity and mortality associated with OSA. It is unclear how the oxygen saturation would change in those having increased frequency or duration of hypopneas after the surgery. Here in 17 patients with AHI ≥ 60 events/h, having increased frequency or duration of hypopneas after the non-framework surgery, the results show that the surgery improved oxygen saturation by reducing obstructive-apnea index (36.1 events/h) and duration (8.6 s/event), despite it increased hypopnea index (16.8 events/h) and duration (9.8 s/event). The surgery improved the average of the mean oxyhemoglobin saturation of pulse oximetry (SpO2) by 2.8% (toward a ceiling mean of 94.3%), mean minimal SpO2 by 7.5%, and mean desaturation by 5%. The results suggest sufficient apnea reduction and shift from apnea to hypopnea may mask the negative impact of the increase of hypopnea index or duration and improve postoperative mean SpO2, minimal SpO2, and mean desaturation.
Interaction with the future self in virtual reality reduces self-defeating behavior in a sample of convicted offenders
Authors: van Gelder Jean-Louis , Cornet Liza J. M. , Zwalua Natascha P. , Mertens Esther C. A. , van der Schalk Job
Published: February 2022

In this study, we test an intervention in which convicted offenders interacted with an age-progressed avatar representing their future selves in virtual reality. During the interaction, they reflected on their current lifestyle, alternating between the perspective of their present self and that of their future self. We hypothesized that this embodied experience would increase their ability to imagine themselves in the future and reduce their engagement in self-defeating behavior, as measured with a self-report survey. In line with expectations, results indicated that the interaction increased vividness of the future self compared to baseline and reduced self-defeating behavior, including alcohol use and overspending, one week later. In addition, increases in vividness were associated with a reduction in self-defeating behavior over and above other concepts relating to the future self, including connectedness, similarity, and valence. The results are based on a small sample and should therefore be considered as indicative of the possibilities of our virtual reality paradigm as an intervention tool to reduce self-defeating behavior.
High-efficiency peroxidase mimics for fluorescence detection of H2O2 and l-cysteine
Authors: Qu Xiaodan , Zou Jinhui , Shen Yujie , Zhao Bolin , Liang Jiahui , Wang Zhenxin , Zhang Yuwei , Niu Li
Published: February 2022

A novel fluorescent sensor based on a Au–Ag bimetallic peroxidase-like enzyme was constructed for the sensitive detection of l-cysteine and H2O2.
Bi2O3 nanoparticles exhibit potent broad-spectrum antimicrobial activity and the ability to overcome Ag-, ciprofloxacin- and meropenem-resistance in P. aeruginosa: the next silver bullet of metal antimicrobials?
Authors: Pant Bishnu D. , Benin Bogdan M. , Abeydeera Nalin , Kim Min-Ho , Huang Songping D.
Published: February 2022

The rise of antimicrobial resistance (AMR) toward the conventional antibiotics and Ag compounds has made the search for metallodrugs to combat AMR imperative. Bi compounds such as the one reported in this article may emerge as the next silver bullet of metal antimicrobials.
Self-consistently derived sample permittivity in stabilization of ferroelectricity due to charge accumulated at interfaces
Authors: Teodorescu Cristian M.
Published: February 2022

The dielectric permittivity introduced in the stabilization energy of ferroelectricity by charges accumulated at surfaces or interfaces depends on polarization and temperature.
The role of Ni sites located in mesopores in the selectivity of anisole hydrodeoxygenation
Authors: Yan Penghui , Tian Xinxin , Kennedy Eric M. , Stockenhuber Michael
Published: February 2022

A highly dispersed Ni catalyst with an increased number of Ni sites selectively distributed in the mesopores of HBEA has been developed and applied in anisole hydrodeoxygenation (HDO) in a continuous-flow reactor under high WHSV (2.8 min−1).
Non-salen coumarin Schiff base chiral fluorescent probe turn on circularly polarized luminescence by Mg2+ and Zn2+
Authors: Fu Fubin , Zhang Xueyan , Zhou Shengquan , Shi Wei , Li Jiangmin , Yu Jiajia , Rao Yanzhao , Wu Lei , Cao Jing
Published: February 2022

L1 can be used as highly sensitive dual detection ion probe for Mg2+ and Zn2+. Mg2+ and Zn2+ can turn on the CPL emission of L1. L1 showed reversible fluorescence “on/off” response with Zn2+ and EDTA.
Optimizing the Semisynthesis towards glycosylated interferon-β-polypeptide by utilizing bacterial protein expression and chemical modification
Authors: Chong Yie Kie , Chandrashekar Chaitra , Zhao Donglin , Maki Yuta , Okamoto Ryo , Kajihara Yasuhiro
Published: February 2022

This paper reports the optimized methods that can accelerate the semisynthesis of homogeneous glycoproteins based on recombinant expression and chemical conversion.
A novel electrochemical sensor for glyphosate detection based on Ti3C2Tx/Cu-BTC nanocomposite
Authors: Wang Shan , Yao Yanqing , Zhao Jia , Han Xuhui , Chai Chunpeng , Dai Pei
Published: February 2022

The Ti3C2Tx/Cu-BTC nanocomposite exhibits excellent sensing performance for glyphosate with a low detection limit and wide detection range. Moreover, the electrochemical sensor also shows excellent selectivity, good reproducibility and stability.
Deeply-recursive convolutional neural network for Raman spectra identification
Authors: Zhou Wei , Tang Yujun , Qian Ziheng , Wang Junwei , Guo Hanming
Published: February 2022

Raman spectroscopy has been widely used in various fields due to its unique and superior properties.
Hydrodynamics induce superdiffusive jumps of passive tracers along critical paths of random networks and colloidal gels
Authors: Alcázar-Cano Nerea , Delgado-Buscalioni Rafael
Published: February 2022

We present a numerical study on the effect of hydrodynamic interactions (HI) on the diffusion of inert point tracer particles in several fixed random structures.
Microfluidics-assisted synthesis and functionalization of monodisperse colloidal hydrogel particles for optomechanical biosensors
Authors: Rettke David , Danneberg Christian , Neuendorf Talika Alina , Kühn Sebastian , Friedrichs Jens , Hauck Nicolas , Werner Carsten , Thiele Julian , Pompe Tilo
Published: February 2022

Microfluidic synthesis options of monodisperse poly(ethylene glycol) hydrogel microparticles for microinterferometric biosensing were evaluated with a focus on introducing reactive surface moieties.
Dynamic in vivo monitoring of fracture healing process in response to magnesium implant with multimodal imaging: pilot longitudinal study in a rat external fixation model
Authors: Sun Yu , Helmholz Heike , Will Olga , Damm Timo , Wiese Björn , Luczak Monika , Peschke Eva , Luthringer-Feyerabend Bérengère , Ebel Thomas , Hövener Jan-Bernd , Glüer Claus-Christian , Willumeit-Römer Regine
Published: February 2022

This study introduced a rat model for preclinical investigation of magnesium-based biodegradable materials in bone fracture conditions, allowing longitudinal in vivo monitoring of fracture healing and implant degradation with multimodal imaging.
Size and albedo of the largest detected Oort-cloud object: Comet C/2014 UN271 (Bernardinelli-Bernstein)
Authors: Lellouch E. , Moreno R. , Bockelée-Morvan D. , Biver N. , Santos-Sanz P.
Published: February 2022

Context. The recently announced Oort-cloud comet C/2014 UN271 (Bernardinelli-Bernstein) is remarkable in at least three respects: (i) it was discovered inbound as far as ∼29 au from the Sun (with prediscovery images up to ∼34 au); (ii) it already showed cometary activity at almost 24 au; and (iii) its nuclear magnitude (Hr ∼ 8.0) indicates an exceptionally large object. Detection of gases is expected in the upcoming years as the comet heads toward a perihelion of ∼11 au in 2031.

Aims. The goal is to determine the object’s diameter and albedo from thermal measurements.

Methods. We used ALMA in extended configuration (resolution ∼0.064″) to measure the 1287 μm (233 GHz) continuum flux of the comet. Observations were performed on August 8, 2021, at a 20.0 au distance from the Sun. The high spatial resolution was chosen in order to filter out any dust contribution. We also used a recently published Afρ value to estimate the dust production rate and the expected dust thermal signal for various assumptions on particle size distribution.

Results. We detected the thermal emission of the object at ∼10σ, with a flux of 0.128 ± 0.012 mJy. Based on observational constraints and our theoretical estimates of the dust contribution, the entirety of the measured flux can be attributed to the nucleus. From NEATM modeling combined with the Hr magnitude, we determine a surface-equivalent diameter of 137 ± 17 km and a red geometric albedo of 5.3 ± 1.2%. This confirms that C/2014 UN271 is by far the largest Oort-cloud object ever found (almost twice as large as comet C/1995 O1 Hale-Bopp) and, except for the Centaur 95P/Chiron, which shows outburst-like activity, the largest known comet in the Solar System. On the other hand, the C/2014 UN271 albedo is typical of comets, adding credence to a “universal” comet nucleus albedo.

Conclusions. With its distant perihelion and uniquely large size, C/2014 UN271 (Bernardinelli-Bernstein) is the prominent archetype of distant comets whose activity is driven by hypervolatiles. Monitoring of dust and gas emission as the comet approaches and passes perihelion will permit its activity time pattern to be studied and compared to the distant (outbound) activity of Hale-Bopp. Post-perihelion thermal measurements will permit the study of possible albedo changes, such as a surface brightening compared to pre-perihelion, as was observed for Hale-Bopp.
A novel highly dispersed tetra-metal nano heterogeneous ozone catalyst derived from microbial adsorption and in situ pyrolysis
Authors: Xie Jianping , Fan Wei , Cui Hao , Feng Ningning , Wang Guozhen , Wang Hui , Liu Xinxing , Qiu Guanzhou , Wu Haiyan
Published: February 2022

In recent years, the pyrolysis of microbial biomasses that adsorb various metal ions has enabled the preparation of carbon-based polymetallic nanomaterials with excellent electrocatalytic and electrical energy storage properties. However, the preparation of ozone catalysts by this technique and the corresponding catalytic oxidation mechanism are still unclear. In this study, an Escherichia coli strain (BL21) was used for tetra-metal (Cu, Fe, Mn and Al) absorption and the obtained microbial biomass was pyrolyzed under the protection of a nitrogen flow at 700 °C and activated at 900 °C to prepare a microbial-char-based tetra-metal ozone catalyst (MCOC). This was used to degrade phenol and coking wastewater and exhibited a strong catalytic capability for coking wastewater, whose chemical oxygen demand removal efficiency of 70.86% is 16.7% higher than that of pure ozone and 14.67%, 7.21% and 3.58% higher than that of three commercial catalysts, respectively. It also improved the efficiency of ozonation for phenol by 33%. The MCOC was characterized by x-ray diffraction, x-ray photoelectron spectroscopy, scanning electron microscopy–energy-dispersive spectroscopy, transmission electron microscopy and other methods. The results demonstrated that the spherical metal nanoparticles had sizes ranging from 3 nm to 7 nm and that crystals of Fe2O3 and Fe3P were observed. The study showed that the MCOC promoted the production of more hydroxyl radicals and superoxides from ozone, which attack organics. The oxygen vacancies of the catalyst were also investigated. It was proved that the Lewis acid sites on the surface of metal oxides are the active centers of ozone decomposition. Therefore, this work provides a new method for the synthesis of multi-metal nanocomposites and expands the application of biosynthetic nanomaterials.
Electronic structure and optical properties of non-metallic modified graphene: a first-principles study
Authors: Huang Jing-tao , Liu Yong , Lai Zhong-hong , Hu Jin , Zhou Fei , Zhu Jing-chuan
Published: February 2022

In this paper, the electronic structure and stability of the intrinsic, B-, N-, Si-, S-doped graphene are studied based on first-principles calculations of density functional theory. Firstly, the intrinsic, B-, N-, Si-, S-doped graphene structures are optimized, and then the forming energy, band structure, density of states, differential charge density are analyzed and calculated. The results show that B- and Si-doped systems are p-type doping, while N is n-type doping. By comparing the forming energy, it is found that N atoms are more easily doped in graphene. In addition, for B-, N-, Si-doped systems, it is found that the doping atoms will open the band gap, leading to a great change in the band structure of the doping system. Finally, we systematically study the optical properties of the different configurations. By comparison, it is found that the order of light sensitivity in the visible region is as follows: S-doped> Si-doped> pure > B-doped > N-doped. Our results will provide theoretical guidance for the stability and electronic structure of non-metallic doped graphene.
Dynamics of mixed lump-soliton for an extended (2+1)-dimensional asymmetric Nizhnik–Novikov–Veselov equation
Authors: Shi Kai-Zhong , Shen Shou-Feng , Ren Bo , Wang Wan-Li
Published: February 2022

A new (2+1)-dimensional higher-order extended asymmetric Nizhnik–Novikov–Veselov (eANNV) equation is proposed by introducing the additional bilinear terms to the usual ANNV equation. Based on the independent transformation, the bilinear form of the eANNV equation is constructed. The lump wave is guaranteed by introducing a positive constant term in the quadratic function. Meanwhile, different class solutions of the eANNV equation are obtained by mixing the quadratic function with the exponential functions. For the interaction between the lump wave and one-soliton, the energy of the lump wave and one-soliton can transfer to each other at different times. The interaction between a lump and two-soliton can be obtained only by eliminating the sixth-order bilinear term. The dynamics of these solutions are illustrated by selecting the specific parameters in three-dimensional, contour and density plots.
Efficiently enhanced energy storage performance of Ba2Bi4Ti5O18 film by co-doping Fe3+ and Ta5+ ion with larger radius
Authors: Wu Qiong , Zhao Lei , Chen Xinghao , Zhao Shifeng
Published: February 2022

We present an efficient strategy, that is the co-substitution of Fe3+ and Ta5+ ions with large radius for Ti4+ ion, to enhance energy storage performance of Ba2Bi4Ti5O18 film. For the films co-doped with Fe3+ and Ta5+ ions, the maximum polarization under the same external electric field is improved because the radius of Fe3+ and Ta5+ ions is larger than that of Ti4+ ion. Moreover, due to the composition and chemical disorder, the relaxor properties are also slightly improved, which can not be achieved by the film doped with Fe3+ ions only. What is more, for the films doped with Fe3+ ion only, the leakage current density increases greatly due to the charge imbalance, resulting in a significant decrease in breakdown strength. It is worth mentioning that the breakdown strength of Fe3+ and Ta5+ ions co-doped film does not decrease due to the charge balance. Another important point is the recoverable energy storage density of the films co-doped with Fe3+ and Ta5+ ions has been greatly improved based on the fact that the maximum external electric field does not decrease and the maximum polarization under the same external electric field increases. On top of that, the hysteresis of the polarization has also been improved. Finally, the co-doped films with Fe3+ and Ta5+ ions have good frequency and temperature stability.
Influence of water environment on paint removal and the selection criteria of laser parameters
Authors: Zhang Li-Jun , Zhou Kai-Nan , Feng Guo-Ying , Han Jing-Hua , Xie Na , Xiao Jing
Published: February 2022

Laser paint removal in a water environment does not diffuse ablation pollution products into air. Characteristics of water, such as high specific heat and heat flux, generate different effects of the laser paint removal than in an air environment. In this study, the effects of air and water environments on the mechanism and effect of laser paint removal are analyzed and compared experimentally and theoretically. In air, thermodynamic ablation causes removal of paint, whereas in water, stress coupled with plasma shock waves cause tear and splash removal of paint layers after fracture and damage. Fracture and pressure thresholds of the paint and substrate, respectively, indicate the optimum energy density range for laser paint removal in water, providing a reference for engineering applications.
A Deep Learning Model for Automated Segmentation of Fluorescence Cell images
Authors: Aydın Musa , Kiraz Berna , Eren Furkan , Uysallı Yiğit , Morova Berna , Can Ozcan Selahattin , Acilan Ceyda , Kiraz Alper
Published: February 2022

Deep learning techniques bring together key advantages in biomedical image segmentation. They speed up the process, increase the reproducibility, and reduce the workload in segmentation and classifcation. Deep learning techniques can be used for analysing cell concentration, cell viability, as well as the size and form of each cell. In this study, we develop a deep learning model for automated segmentation of fuorescence cell images, and apply it to fuorescence images recorded with a home-built epi-fuorescence microscope. A deep neural network model based on U-Net architecture was built using a publicly available dataset of cell nuclei images [1]. A model accuracy of 97.3% was reached at the end of model training. Fluorescence cell images acquired with our home-built microscope were then segmented using the developed model. 141 of 151 cells in 5 images were successfully segmented, revealing a segmentation success rate of 93.4%. This deep learning model can be extended to the analysis of diferent cell types and cell viability.
A remarkable dynamical symmetry of the Landau problem
Authors: Dereli Tekin , Nounahon Philippe , Popov Todor
Published: February 2022

We show that the dynamical group of an electron in a constant magnetic feld is the group of symplectomorphisms Sp(4, R). It is generated by the spinorial realization of the conformal algebra so(2,3) considered in Dirac’s seminal paper ”A Remarkable Representation of the 3 + 2 de Sitter Group”. The symplectic groupSp(4,R) is the double covering of the conformal groupSO(2,3) of 2+1 dimensional Minkowski spacetime which is in turn the dynamical group of a hydrogen atom in 2 space dimensions. The Newton-Hooke duality between the 2D hydrogen atom and the Landau problem is explained via the Tits-Kantor-Koecher construction of the conformal symmetries of the Jordan algebra of real symmetric 2 × 2 matrices. The connection between the Landau problem and the 3D hydrogen atom is elucidated by the reduction of a Dirac spinor to a Majorana one in the Kustaanheimo-Stiefel spinorial regularization.
Dark Range of ω In Brans-Dicke Gravity
Authors: Dereli Tekin , Şenikoğlu Yorgo
Published: February 2022

The variational field equations of Brans-Dicke scalar-tensor theory of gravitation that is coupled to a mass-varying sterile neutrino field are presented in Riemannian and non-Riemannian setting in the language of exterior differential forms over four-dimensional spacetime. In a gravitational plane wave geometry in Rosen coordinates, with the scalar field set equal to a constant, the field equations admit ghost neutrino solutions. These correspond to Majorana spinor configurations for which the total neutrino stress-energy-momentum tensor vanishes. We show here that in the absence of a sterile neutrino in the gravitational wave geometry, there are scalar field configurations for which the total scalar field stress-energy-momentum tensor vanishes for negative values of the Brans-Dicke parameter —3/2 < ω < 0.
Statistical geometry and Hessian structures on pre-Leibniz algebroids
Authors: Dogan Keremcan
Published: February 2022

We introduce statistical, conjugate connection and Hessian structures on anti-commutable pre-Leibniz algebroids. Anti-commutable pre-Leibniz algebroids are special cases of local pre-Leibniz algebroids, which are still general enough to include many physically motivated algebroids such as Lie, Courant, metric and higher-Courant algebroids. They create a natural framework for generalizations of differential geometric structures on a smooth manifold. The symmetrization of the bracket on an anti-commutable pre-Leibniz algebroid satisfies a certain property depending on a choice of an equivalence class of connections which are called admissible. These admissible connections are shown to be necessary to generalize aforementioned structures on pre-Leibniz algebroids. Consequently, we prove that, provided certain conditions are met, statistical and conjugate connection structures are equivalent when defined for admissible connections. Moreover, we also show that for ‘projected-torsion-free’ connections, one can generalize Hessian metrics and Hessian structures. We prove that any Hessian structure yields a statistical structure, where these results are completely parallel to the ones in the manifold setting. We also prove a mild generalization of the fundamental theorem of statistical geometry. Moreover, we generalize a-connections, strongly conjugate connections and relative torsion operator, and prove some analogous results.
Echoes from the event horizon of a superfluid vortex
Authors: Güven K , Demirkaya B
Published: February 2022

A vortex formed in the superfluid state of a Bose-Einstein condensate may exhibit superradiance a la blackhole for radially propagating acoustic fluctuations. The analogy is usually based on the so-called draining bathtub model of the vortex, in which an event horizon and ergosphere emerges when the radial velocity of the superfluid exceeds the propagation speed of sound in the condensate. The acoustic fluctuations mimic a massless scalar field in the curved Lorentzian space-time of the vortex and are governed by the Klein-Gordon wave equation. One common main approximation is the constant background density of the superfluid even in the presence of the vortex. This sets a constant relativistic sound speed. However, the vortex state solution of the Gross-Pitaevskii equation clearly shows that both the density and the speed of sound vary radially near the vortex core, where the event horizon and thus the superradiance will take place. What changes would this complex interdependence bring to the formulation and to the outcomes of the superradiance based on constant density approximation? Here, we recount this question posed under the guidance of Prof. Tekin Dereli and present recent results. We show that the self-consistent density modifies the amplification dynamics near the event horizon significantly, thereby altering the temporal and spectral fingerprint of the superradiance of the vortex.
A novel approach to autoparallels for the theories of symmetric teleparallel gravity
Authors: Pala Caglar , Adak Muzaffer
Published: February 2022

Although the autoparallel curves and the geodesics coincide in the Riemannian geometry in which only the curvature is nonzero among the nonmetricity, the torsion and the curvature, they define different curves in the non-Riemannian ones. We give a novel approach to autoparallel curves and geodesics for theories of the symmetric teleparallel gravity written in the coincident gauge. Then we apply our autoparallel equation to a Schwarzschild-type metric and give remarks about dark matter and orbit equation.
Quantum Correlations in Jahn-Teller Molecular Systems Simulated with Superconducting Circuits
Authors: Pedram AH , Pusuluk Onur , Müstecaphog`lu Özgür E.
Published: February 2022

We explore quantum correlations, in particular, quantum entanglement, among vibrational phonon modes as well as between electronic and vibrational degrees of freedom in molecular systems, described by Jahn-Teller mechanism. Specifically, to isolate and simplify the phonon- electron interactions in a complex molecular system, the basis of our discussions is taken to be the proposal of simulating two-frequency Jahn- Teller systems using superconducting circuit quantum electrodynamics systems (circuit QED) by Tekin Dereli and co-workers in 2012. We evaluate the quantum correlations, in particular entanglement between the vibrational phonon modes, and present analytical explanations using a single privileged Jahn-Teller mode picture. Furthermore, spin-orbit entanglement or quantum correlations between electronic and vibrational degrees of freedom are examined. We conclude by discussing experimental feasibility to detect such quantum correlations, considering the dephasing and decoherence in state-of-the-art superconducting two-level systems (qubits).
Persistent spectral based ensemble learning (PerSpect-EL) for protein–protein binding affinity prediction
Authors: Wee JunJie , Xia Kelin
Published: February 2022

Protein–protein interactions (PPIs) play a significant role in nearly all cellular and biological activities. Data-driven machine learning models have demonstrated great power in PPIs. However, the design of efficient molecular featurization poses a great challenge for all learning models for PPIs. Here, we propose persistent spectral (PerSpect) based PPI representation and featurization, and PerSpect-based ensemble learning (PerSpect-EL) models for PPI binding affinity prediction, for the first time. In our model, a sequence of Hodge (or combinatorial) Laplacian (HL) matrices at various different scales are generated from a specially designed filtration process. PerSpect attributes, which are statistical and combinatorial properties of spectrum information from these HL matrices, are used as features for PPI characterization. Each PerSpect attribute is input into a 1D convolutional neural network (CNN), and these CNN networks are stacked together in our PerSpect-based ensemble learning models. We systematically test our model on the two most commonly used datasets, i.e. SKEMPI and AB-Bind. It has been found that our model can achieve state-of-the-art results and outperform all existing models to the best of our knowledge.
Co-offending in context: The role of economic hardship
Authors: Rowan Zachary R
Published: February 2022

Scholars have argued that emergence of co-offending depends on the availability, proximity, and convergence of suitable co-offenders. The current study argues that changes in economic conditions may uniquely alter degree to which offenders are motivated to take on criminal accomplices and make engaging in group behaviour a more viable criminal opportunity. This study examines the between and within-MSA effects of economic hardship between 1990-2004 on the rate of co-offences committed using MSA-level data from the National Crime Victimization Survey. Findings indicate that there are similarities in the relationship between economic hardship and crime generally but portray a much more nuanced relationship when viewed through the lens of group behaviour. The discussion evaluates the results from a series of hybrid decomposition model and considers the utility of situating co-offending within broader socio-structural contexts.
The fornix supports episodic memory during childhood
Authors: Hoffman Linda J , Ngo Chi T , Canada Kelsey L , Pasternak Ofer , Zhang Fan , Riggins Tracy , Olson Ingrid R
Published: February 2022

Episodic memory relies on the coordination of widespread brain regions that reconstruct spatiotemporal details of an episode. These topologically dispersed brain regions can rapidly communicate through structural pathways. Research in animal and human lesion studies implicate the fornix—the major output pathway of the hippocampus—in supporting various aspects of episodic memory. Because episodic memory undergoes marked changes in early childhood, we tested the link between the fornix and episodic memory in an age window of robust memory development (ages 4–8 years). Children were tested on the stories subtest from the Children’s Memory Scale, a temporal order memory task, and a source memory task. Fornix streamlines were reconstructed using probabilistic tractography to estimate fornix microstructure. In addition, we measured fornix macrostructure and computed free water. To assess selectivity of our findings, we also reconstructed the uncinate fasciculus. Findings show that children’s memory increases from ages 4 to 8 and that fornix micro- and macrostructure increases between ages 4 and 8. Children’s memory performance across nearly every memory task correlated with individual differences in fornix, but not uncinate fasciculus, white matter. These findings suggest that the fornix plays an important role in supporting the development of episodic memory, and potentially semantic memory, in early childhood.