Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of an Inactivated Avian Influenza Virus Vaccine against Circulating H9N2 in Chickens and Ducks

Avian influenza virus (AIV) subtype H9N2 is the most widespread AIV in poultry worldwide, causing great economic losses in the global poultry industry. Chickens and ducks are the major hosts and play essential roles in the transmission and evolution of H9N2 AIV. Vaccines are considered an effective strategy for fighting H9N2 infection. However, due to the differences in immune responses to infection, vaccines against H9N2 AIV suitable for use in both chickens and ducks have not been well studied. This study developed an inactivated H9N2 vaccine based on a duck-origin H9N2 AIV and assessed its effectiveness in the laboratory. The results showed that the inactivated H9N2 vaccine elicited significant haemagglutination inhibition (HI) antibodies in both chickens and ducks. Virus challenge experiments revealed that immunization with this vaccine significantly blocked virus shedding after infection by both homogenous and heterologous H9N2 viruses. The vaccine was efficacious in chicken and duck flocks under normal field conditions. We also found that egg-yolk antibodies were produced by laying birds immunized with the inactivated vaccine, and high levels of maternal antibodies were detected in the serum of the offspring. Taken together, our study showed that this inactivated H9N2 vaccine could be extremely favourable for the prevention of H9N2 in both chickens and ducks.
Central moments of ion implantation distributions derived by the backward Boltzmann transport equation compared with Monte Carlo simulations

The authors study solutions to the backward Boltzmann transport equation (BBTE) specialized to equations governing moments of the distribution of ions implanted into amorphous targets. A central moment integral equation set has been derived starting from the classical plane source BBTE for non-central moments. A full generator equation is provided to allow construction of equation sets of an arbitrary size, thus allowing computation of moments of arbitrary order. A BBTE solver program has been written that uses the residual correction technique proposed by Winterbon (1970). A simple means is presented to allow direct incorporation of Biersack's two-parameter 'magic formula' into a BBTE solver program. Results for non-central and central moment integral equation sets are compared with Monte Carlo simulations, using three different formulae for the mean free flight path between collisions. Comparisons are performed for the ions B and As, implanted into the target a-Si, over the energy range 1 keV-1 MeV. The central moment integral equation set is found to have superior convergence properties to the non-central moment equation set. For As ions implanted into a-Si, at energies below approximately 30 keV, significant differences are observed, for third- and fourth-order moments, when using alternative versions for the mean free flight path. Third- and fourth-order moments derived using one- and two-parameter scattering mechanisms also show significant differences over the same energy range.
Symmetry-resolved entanglement of two-dimensional symmetry-protected topological states

Symmetry-resolved entanglement is a useful tool for characterizing symmetry-protected topological states. In two dimensions, their entanglement spectra are described by conformal field theories but the symmetry resolution is largely unexplored. However, addressing this problem numerically requires system sizes beyond the reach of exact diagonalization. Here, we develop tensor network methods that can access much larger systems and determine universal and nonuniversal features in their entanglement. Specifically, we construct one-dimensional matrix product operators that encapsulate all the entanglement data of two-dimensional symmetry-protected topological states. We first demonstrate our approach for the Levin-Gu model. Next, we use the cohomology formalism to deform the phase away from the fine-tuned point and track the evolution of its entanglement features and their symmetry resolution. The entanglement spectra are always described by the same conformal field theory. However, the levels undergo a spectral flow in accordance with an insertion of a many-body Aharonov-Bohm flux.
A Hybrid Approach for Optimal Sizing of Inverter-Based Distributed Generation Unit in Presence of Harmonic Distortion Limit

This paper presents a hybrid approach to calculate the optimal size of inverter-based distributed generation unit located at any given bus of a radial distribution network to minimize the active power loss in the network in presence of limit imposed on the maximum allowable value of total harmonic distortion in bus voltages. The suggested approach combines efficient iterative computations with a rule base developed in the present work, and requires much less computation compared to the evolutionary population based methods reported so far, to reach the desired solution. In support of this claim, the proposed methodology was tested on two bench-mark distribution test systems, and the test results were compared and validated with those obtained using Particle Swarm Optimization technique. PSO has been chosen for comparison as it is one of the most widely used among the evolutionary population based methods due to its simple approach, ease of implementation, and also because of its superiority in terms of precision, robustness and speed of convergence. From the comparative results it has been established that the proposed method can provide solution for the problem undertaken in this work with significantly less computation than is required by the evolutionary computation based methods.
No Time to Die—How Islets Meet Their Demise in Transplantation

Islet transplantation represents an effective treatment for patients with type 1 diabetes mellitus (T1DM) and severe hypoglycaemia unawareness, capable of circumventing impaired counterregulatory pathways that no longer provide protection against low blood glucose levels. The additional beneficial effect of normalizing metabolic glycaemic control is the minimisation of further complications related to T1DM and insulin administration. However, patients require allogeneic islets from up to three donors, and the long-term insulin independence is inferior to that achieved with solid organ (whole pancreas) transplantation. This is likely due to the fragility of islets caused by the isolation process, innate immune responses following portal infusion, auto- and allo-immune-mediated destruction and β-cell exhaustion following transplantation. This review covers the specific challenges related to islet vulnerability and dysfunction that affect long-term cell survival following transplantation.
Study about fractal neural network diagnosis method and application

In This paper, Fractal calculating dimension is firstly put forward. Combined Fractal theory with Neural network, A Fractal Neural network identification methods is built and applied to the state control and fault diagnosis of Mechanical equipment. This network is made of three layers construct: Input layer, hide layer and output layer. Input and output of standard samples are respectively Fractal calculating dimension of different period sampling and the unit matrix equal to sample numbers. Weight and threshold of network is rapidly and correctly computed by conjugate terraced optimization. Rolling bearing fault is perfectly identified by this diagnosis way.
Use of Graphene and Its Derivatives for the Detection of Dengue Virus

Every year, the dengue virus and its principal mosquito vector, Aedes sp. , have caused massive outbreaks, primarily in equatorial countries. The pre-existing techniques available for dengue detection are expensive and require trained personnel. Graphene and its derivatives have remarkable properties of electrical and thermal conductivity, and are flexible, light, and biocompatible, making them ideal platforms for biosensor development. The incorporation of these materials, along with appropriate nanomaterials, improves the quality of detection methods. Graphene can help overcome the difficulties associated with conventional techniques. In this review, we have given comprehensive details on current graphene-based diagnostics for dengue virus detection. We have also discussed state-of-the-art biosensing technologies and evaluated the advantages and disadvantages of the same.
Advances in Assessing the Reliability of Water Distribution Networks: A Bibliometric Analysis and Scoping Review

The reliability of Water Distribution Networks (WDNs) is a critical topic that has been explored by many researchers over the last few decades. Nevertheless, this research domain has gained momentum in the last decade. WDN reliability was addressed in the literature using different approaches and techniques. This study presents a bibliometric analysis and scoping review of the progress and gaps in research on WDN reliability. The analysis was performed on a total of 347 articles from 2000 to 2022, which were retrieved from the SCOPUS database. The bibliometric analysis identified trends and gaps by focusing on articles output, citation network of articles, co-authorship and collaboration analysis, co-citation, and clustering analysis. In addition, coupling keywords analysis with thematic maps analysis helped identify basic, niche, emerging, and declining research themes in the field of WDN reliability. Three major research themes were found: WDN optimization, reliability assessment, and consideration of GHG emissions and energy-cost for WDN expansion. Reliability surrogate measures (RSMs) were found to be one of the most widely researched topics in this field. Performance assessment of various RSMs, as well as the consideration of energy and cost for WDN design and expansion stood out as the emerging trends for future research in the field of WDN reliability.
Titanium Oxyfluoride as a Material for Negative Electrodes of Lithium-Ion Batteries

A study of the electrochemical characteristics of titanium oxyfluoride obtained with the direct interaction of titanium with hydrofluoric acid is reported. Two materials T1 and T2 synthesized under different conditions in which some TiF3 is formed in T1 are compared. Both materials exhibit conversion-type anode properties. Based on the analysis of the charge–discharge curves of the half-cell, a model is proposed according to which the first electrochemical introduction of lithium occurs in two stages: the first stage is the irreversible reaction resulting in a reduction in Ti4+/3+, and the second stage is the reversible reaction with a change in the charge state Ti3+/1.5+. The difference in material behavior is quantitative: T1 has a higher reversible capacity but lower cycling stability and a slightly higher operating voltage. The Li diffusion coefficient determined from the CVA data for both materials averages 1.2–3.0 × 10−14 cm2/s. A distinctive feature of titanium oxyfluoride anodes is the asymmetry in kinetic characteristics that revealed themselves during lithium embedding and extraction. In the long cycling regime, the excess of Coulomb efficiency over 100% was found in the present study.
Solid Lipid Nanoparticles: Multitasking Nano-Carriers for Cancer Treatment

Despite all the advances seen in recent years, the severe adverse effects and low specificity of conventional chemotherapy are still challenging problems regarding cancer treatment. Nanotechnology has helped to address these questions, making important contributions in the oncological field. The use of nanoparticles has allowed the improvement of the therapeutic index of several conventional drugs and facilitates the tumoral accumulation and intracellular delivery of complex biomolecules, such as genetic material. Among the wide range of nanotechnology-based drug delivery systems (nanoDDS), solid lipid nanoparticles (SLNs) have emerged as promising systems for delivering different types of cargo. Their solid lipid core, at room and body temperature, provides SLNs with higher stability than other formulations. Moreover, SLNs offer other important features, namely the possibility to perform active targeting, sustained and controlled release, and multifunctional therapy. Furthermore, with the possibility to use biocompatible and physiologic materials and easy scale-up and low-cost production methods, SLNs meet the principal requirements of an ideal nanoDDS. The present work aims to summarize the main aspects related to SLNs, including composition, production methods, and administration routes, as well as to show the most recent studies about the use of SLNs for cancer treatment.
Plasmon-Assisted Designable Multi-Resonance Photodetection by Graphene via Nanopatterning of Block Copolymer

The photoresponse in graphene has drawn significant attention for potential applications owing to its gapless linear electronic band structure. To enhance both the spectral selectivity and responsivity in graphene, we demonstrate a novel but versatile and simple method of introducing surface plasmons. We utilize block copolymers to fabricate different nanostructured metal nanoparticle arrays on a single graphene surface. The plasmonic resonances could be tuned using Ag, Au, and Cu metal nanoparticles. By extending the synthetic route for the metallic particles, dual surface plasmonic bands from a single material were also successfully realized. Furthermore, enhanced photoresponsivity through the entire visible spectra could be achieved by mixing metallic nanoparticles and by controlling their shapes. Owing to its all-band transition characteristics, the ultrabroad band photocurrent generation in graphene can be tailored for an arbitrary photoresponse, which could be utilized in flexible CMOS image sensors.
A Mie-Grüneisen mixture Eulerian model for underwater explosion

Purpose – The purpose of this paper is to provide an improved Mie-Gruneisen mixture model to simulate underwater explosion (UNDEX). Design/methodology/approach – By using Mie-Gruneisen equations of state (EOS) to model explosive charge, liquid water and solid structure, the whole fluid field is considered as a multi-phases mixture under Mie-Gruneisen EOS. Then by introducing auxiliary variables in Eulerian model and using mass fraction to establish a diffusion balance, a new improved Mie-Gruneisen mixture model is presented here. For the new reconstructed mixture model, a second order MUSCL scheme with TVD limiter is employed to solve the multi-phase Riemann problem. Findings – Numerical examples show that the results obtained by Mie-Gruneisen mixture model are quite closed to theoretical and empirical data. The model can be also used in 2-D fluid-structure problem of UNDEX effectively and it is proved that the deformation of structure can be clearly described by mass fraction. Research limitations/implic.
A Novel Transfer Learning-Based Cell SOC Online Estimation Method for a Battery Pack in Complex Application Conditions

The crucial function of a battery management system is to estimate the state of charge (SOC). However, complex application conditions, such as different temperatures, aging, and inconsistency between cells would cause a distribution difference between data domains and lead to a significant estimation error in the established SOC model. Transfer learning's domain adaptation offers a way to lessen the disparity in distribution across the data domains, and yet it also requires that the target space be the same across domains, which is challenging to do with the SOC online estimate. This article proposes a SOC differential processing method as well as designs a combined transfer learning method. As experiments of actual battery pack provided by China First Automobile Work-based confirmed, the proposed method can obtain precise and robust SOC estimation results with a mean absolute percentage error of less than 1.5%.
Platycodin-D exerts its anti-cancer effect by promoting c-Myc protein ubiquitination and degradation in gastric cancer

Platycodin D (PD) is a triterpene saponin extracted from the root of Platycodon grandiflorum. It has been reported to exhibit multiple pharmacological and biological properties. There is substantial evidence to support that PD displays a wide range of anti-tumor activities. However, the detailed molecular mechanism still needs further elaboration. In the present study, to explore whether PD inhibits gastric cancer (GC) cell viability, eight GC cell lines and the GES-1 cell line (a gastric mucosal cell line) were tested. We found that PD exhibited better inhibitory activity on GC cell lines than on the non-tumor cell line. Besides, treatment with PD led to a significant cell cycle arrest, thereby causing subsequent apoptosis. Regarding the cell growth inhibition mechanism, PD can downregulate the protein level of c-Myc rather than its mRNA level in a dose-dependent manner. Further studies revealed that PD disturbed the overall ubiquitination level in GC cell lines and enhanced the ubiquitination-dependent degradation of c-Myc. Interestingly, the inhibition of cell viability by PD could be restored to a certain extent when the expression of c-Myc was recovered, suggesting that PD-mediated GC cell growth inhibition is closely associated with c-Myc expression. Our study proposes a novel molecular mechanism for PD inhibiting GC cell proliferation and growth by destabilizing the c-Myc protein. This work may lay a preliminary foundation for developing PD as an anti-cancer therapy.
Lockup periods during lockdown periods in the context of Brazilian funds

ABSTRACT This article aimed to test the effect of lockup periods on the performance of Brazilian equity funds and multimarket funds, considering the period affected by the 2019 coronavirus disease (COVID-19). This study contributes to better understanding the effects of redemption restrictions imposed on quotaholders, a relevant subject considering the increase in the number of funds in Brazil. This effect is analyzed with particular focus on the period affected by the COVID-19 pandemic. The results of this study have implications for individual and professional investors and may also interest large families of Brazilian funds, given that the establishment of lockup periods forms part of a long-term decision. The research has the potential to impact planning in the fund industry, the financial planning of small and large investors, as well as the literature on the subject, motivating the undertaking of new research. The sample was composed of 17,417 Brazilian funds, 13,581 of which were multimarket funds and 3,836 were equity funds, covering the period from January of 2018 to December of 2021. Various subsamples were evaluated for robustness purposes. The hypotheses were tested using a difference-in-difference model operationalized through a panel. Fund performance was estimated every quarter based on the four-factor alpha. The main results of the study reveal that lockup periods were positively associated with fund performance. On the other hand, during the period negatively affected by COVID-19, funds with greater lockup periods did not record better performance than the other funds (considering in the comparison the performance of groups with a shorter lockup and that of the funds before the pandemic), a result that may advance the discussion on the effects of redemption restrictions.
scANANSE gene regulatory network and motif analysis of single-cell clusters

The recent development of single-cell techniques is essential to unravel complex biological systems. By measuring the transcriptome and the accessible genome on a single-cell level, cellular heterogeneity in a biological environment can be deciphered. Transcription factors act as key regulators activating and repressing downstream target genes, and together they constitute gene regulatory networks that govern cell morphology and identity. Dissecting these gene regulatory networks is crucial for understanding molecular mechanisms and disease, especially within highly complex biological systems. The gene regulatory network analysis software ANANSE and the motif enrichment software GimmeMotifs were both developed to analyse bulk datasets. We developed scANANSE, a software pipeline for gene regulatory network analysis and motif enrichment using single-cell RNA and ATAC datasets. The scANANSE pipeline can be run from either R or Python. First, it exports data from standard single-cell objects. Next, it automatically runs multiple comparisons of cell cluster data. Finally, it imports the results back to the single-cell object, where the result can be further visualised, integrated, and interpreted. Here, we demonstrate our scANANSE pipeline on a publicly available PBMC multi-omics dataset. It identifies well-known cell type-specific hematopoietic factors. Importantly, we also demonstrated that scANANSE combined with GimmeMotifs is able to predict transcription factors with both activating and repressing roles in gene regulation.
Vapor-Induced Pore-Forming Atmospheric-Plasma-Sprayed Zinc-, Strontium-, and Magnesium-Doped Hydroxyapatite Coatings on Titanium Implants Enhance New Bone Formation—An In Vivo and In Vitro Investigation

Objectives: Titanium implants are regarded as a promising treatment modality for replacing missing teeth. Osteointegration and antibacterial properties are both desirable characteristics for titanium dental implants. The aim of this study was to create zinc (Zn)-, strontium (Sr)-, and magnesium (Mg)-multidoped hydroxyapatite (HAp) porous coatings, including HAp, Zn-doped HAp, and Zn-Sr-Mg-doped HAp, on titanium discs and implants using the vapor-induced pore-forming atmospheric plasma spraying (VIPF-APS) technique. Methods: The mRNA and protein levels of osteogenesis-associated genes such as collagen type I alpha 1 chain (COL1A1), decorin (DCN), osteoprotegerin (TNFRSF11B), and osteopontin (SPP1) were examined in human embryonic palatal mesenchymal cells. The antibacterial effects against periodontal bacteria, including Porphyromonas gingivalis and Prevotella nigrescens, were investigated. In addition, a rat animal model was used to evaluate new bone formation via histologic examination and micro-computed tomography (CT). Results: The ZnSrMg-HAp group was the most effective at inducing mRNA and protein expression of TNFRSF11B and SPP1 after 7 days of incubation, and TNFRSF11B and DCN after 11 days of incubation. In addition, both the ZnSrMg-HAp and Zn-HAp groups were effective against P. gingivalis and P. nigrescens. Furthermore, according to both in vitro studies and histologic findings, the ZnSrMg-HAp group exhibited the most prominent osteogenesis and concentrated bone growth along implant threads. Significance: A porous ZnSrMg-HAp coating using VIPF-APS could serve as a novel technique for coating titanium implant surfaces and preventing further bacterial infection.