Miracle-dz/UniFAR-FTUs huggingface dataset:
Extensive Investigation on the Effect of Niobium Insertion on the Physical and Biological Properties of 45S5 Bioactive Glass for Dental Implant

Dental implants have emerged as one of the most consistent and predictable treatments in the oral surgery field. However, the placement of the implant is sometimes associated with bacterial infection leading to its loss. In this work, we intend to solve this problem through the development of a biomaterial for implant coatings based on 45S5 Bioglass® modified with different amounts of niobium pentoxide (Nb2O5). The structural feature of the glasses, assessed by XRD and FTIR, did not change in spite of Nb2O5 incorporation. The Raman spectra reveal the Nb2O5 incorporation related to the appearance of NbO4 and NbO6 structural units. Since the electrical characteristics of these biomaterials influence their osseointegration ability, AC and DC electrical conductivity were studied by impedance spectroscopy, in the frequency range of 102–106 Hz and temperature range of 200–400 K. The cytotoxicity of glasses was evaluated using the osteosarcoma Saos-2 cells line. The in vitro bioactivity studies and the antibacterial tests against Gram-positive and Gram-negative bacteria revealed that the samples loaded with 2 mol% Nb2O5 had the highest bioactivity and greatest antibacterial effect. Overall, the results showed that the modified 45S5 bioactive glasses can be used as an antibacterial coating material for implants, with high bioactivity, being also non-cytotoxic to mammalian cells.
Inhibitory Effects of Extracellular Vesicles from iPS-Cell-Derived Mesenchymal Stem Cells on the Onset of Sialadenitis in Sjögren’s Syndrome Are Mediated by Immunomodulatory Splenocytes and Improved by Inhibiting miR-125b

Extracellular vesicles (EVs) from allogeneic-tissue-derived mesenchymal stem cells (MSCs) are promising to improve Sjögren’s syndrome (SS) treatment, but their application is hindered by high variations in and limited expandability of tissue MSCs. We derived standardized and scalable MSCs from iPS cells (iMSCs) and reported that EVs from young but not aging iMSCs (iEVs) inhibited sialadenitis onset in SS mouse models. Here, we aim to determine cellular mechanisms and optimization approaches of SS-inhibitory effects of iEVs. In NOD.B10. H2b mice at the pre-disease stage of SS, we examined the biodistribution and recipient cells of iEVs with imaging, flow cytometry, and qRT-PCR. Intravenously infused iEVs accumulated in the spleen but not salivary glands or cervical lymph nodes and were mainly taken up by macrophages. In the spleen, young but not aging iEVs increased M2 macrophages, decreased Th17 cells, and changed expression of related immunomodulatory molecules. Loading miR-125b inhibitors into aging iEVs significantly improved their effects on repressing sialadenitis onset and regulating immunomodulatory splenocytes. These data indicated that young but not aging iEVs suppress SS onset by regulating immunomodulatory splenocytes, and inhibiting miR-125b in aging iEVs restores such effects, which is promising to maximize production of effective iEVs from highly expanded iMSCs for future clinical application.
MEASURING STELLAR KINEMATICS IN GALAXIES WITH THE NEAR-INFRARED (2-0) 12CO ABSORPTION BANDHEAD

The shape and strength of the near infrared (2-0) 12CO absorption bandhead provides astronomers with a unique tool for measuring stellar kinematics in galaxies with strong dust obscuration. However, the asymmetric shape of the bandhead introduces complexities when extracting the kinematics from an observed spectrum. This paper discusses the benefits, drawbacks, and observational constraints associated with using this bandhead to measure kinematics in galaxies, focusing on applications in high spectral resolution data. Additionally, we discuss techniques found useful for extracting the kinematics from the absorption feature, and outline our success with two different mothods.
Health Benefits of Key Constituents in Cichorium intybus L.

The genus Cichorium (Asteraceae) that originates from the Mediterranean area consists of six species (Cichorium intybus, Cichorium frisee, Cichorium endivia, Cichorium grouse, Cichorium chico and Cichorium pumilum). Cichorium intybus L. , commonly known as chicory, has a rich history of being known as a medicinal plant and coffee substitute. A variety of key constituents in chicory play important roles as antioxidant agents. The herb is also used as a forage plant for animals. This review highlights the bioactive composition of C. intybus L. and summarizes the antioxidant activity associated with the presence of inulin, caffeic acid derivatives, ferrulic acid, caftaric acid, chicoric acid, chlorogenic and isochlorogenic acids, dicaffeoyl tartaric acid, sugars, proteins, hydroxycoumarins, flavonoids and sesquiterpene lactones. It also covers the plant’s occurrence, agriculture improvement, natural biosynthesis, geographical distribution and waste valorization.
Field-testing of a cost-effective mobile-phone based microscope for screening of Schistosoma haematobium infection (Conference Presentation)

Schistosomiasis is a parasitic and neglected tropical disease, and affects <200-million people across the world, with school-aged children disproportionately affected. Here we present field-testing results of a handheld and cost effective smartphone-based microscope in rural Ghana, Africa, for point-of-care diagnosis of S. haematobium infection. In this mobile-phone microscope, a custom-designed 3D printed opto-mechanical attachment (~150g) is placed in contact with the smartphone camera-lens, creating an imaging-system with a half-pitch resolution of ~0. 87µm. This unit includes an external lens (also taken from a mobile-phone camera), a sample tray, a z-stage to adjust the focus, two light-emitting-diodes (LEDs) and two diffusers for uniform illumination of the sample. In our field-testing, 60 urine samples, collected from children, were used, where the prevalence of the infection was 72.9%. After concentration of the sample with centrifugation, the sediment was placed on a glass-slide and S. haematobium eggs were first identified/quantified using conventional benchtop microscopy by an expert diagnostician, and then a second expert, blinded to these results, determined the presence/absence of eggs using our mobile-phone microscope. Compared to conventional microscopy, our mobile-phone microscope had a diagnostic sensitivity of 72.1%, specificity of 100%, positive-predictive-value of 100%, and a negative-predictive-value of 57.1%. Furthermore, our mobile-phone platform demonstrated a sensitivity of 65.7% and 100% for low-intensity infections (≤50 eggs/10 mL urine) and high-intensity infections (<50 eggs/10 mL urine), respectively. We believe that this cost-effective and field-portable mobile-phone microscope may play an important role in the diagnosis of schistosomiasis and various other global health challenges.
Kind of super-resolution method of CCD image based on wavelet and bicubic interpolation

In order to maintain the original information of the CCD images,to improve the spatial resolution of image,to observe and analyze the details of the images,this paper studied on various super-resolution methods.This paper proposed the improved super-resolution method based on wavelets and bicubic interpolation.It transformed low-resolution images of gray-scale,and considered it as the low-resolution image in an inverse wavelet transform,recoveried the super-resolution image,then got an average of with the image of low-resolution's bicubic interpolation.Applied this method in CCD images,improved the spatial resolution in the visual,and made the peak signal to noise ratio 25.524 4 dB.Experimental results show that using this method in low-resolution image can get higher PSNR and better image's details effect than those only using bicubic interpolation in the whole wavelet domain or those using the original image as the low-frequency image in an inverse wavelet transform of the bicubic interpolation or those only using the bilinear.The experiment results show that this method is an effective way for improving the CCD image's resolution.
Genome-Wide Identiﬁcation and Expression Analysis of NPF Genes in Cucumber ( Cucumis sativus L.)

: The NITRATE TRANSPORTER 1/PEPTIDE TRANSPORTER family (NPF) proteins perform an essential role in regulating plant nitrate absorption and distribution and in improving plant nitrogen use efﬁciency. In this study, cucumber ( Cucumis sativus L.) NPF genes were comprehensively analyzed at the whole genome level, and 54 NPF genes were found to be unevenly distributed on seven chromosomes in the cucumber genome. The phylogenetic analysis showed that these genes could be divided into eight subfamilies. We renamed all CsNPF genes according to the international nomenclature, based on their homology with AtNPF genes. By surveying the expression proﬁles of CsNPF genes in various tissues, we found that CsNPF6.4 was speciﬁcally expressed in roots, indicating that CsNPF6.4 may play a role in N absorption; CsNPF6.3 was highly expressed in petioles, which may be related to NO 3 − storage in petioles; and CsNPF2.8 was highly expressed in fruits, which may promote NO 3 − transport to the embryos. We further examined their expression patterns under different abiotic stress and nitrogen conditions, and found that CsNPF7.2 and CsNPF7.3 responded to salt, cold, and low nitrogen stress. Taken together, our study lays a foundation for further exploration of the molecular and physiological functions of cucumber nitrate transporters.
A Modified Smoothed Finite Element Method for Static and Free Vibration Analysis of Solid Mechanics

The smoothed finite element method (S-FEM) proposed recently is more accurate and has higher convergence rate compared with standard four-node isoparametric finite element method (FEM). In this work, a modified S-FEM using four-node quadrilateral elements is proposed, which greatly reduces further the computation cost while maintaining the high accuracy and convergence rate. The key idea of the proposed modification is that the strain of the element is a weighted average value of the smoothed strains in the smoothing cells (SCs), which means that only one integration point is required to construct the stiffness matrix, similar to the single cell S-FEM. A stabilization item is proposed using the differences of the smoothed strains obtained in four SCs, which installs the stability of algorithm and increases the accuracy. To verify the efficiency, accuracy and stability of the present formulation, a number of numerical examples of static and free vibration problems, are studied in comparison with different existing numerical methods.
Spatial and temporal variability of Aridity Index in Greece

Drought events have deteriorated in most European regions during the last decades in frequency, duration, or intensity. Besides, increased drying associated with higher temperatures and decreased precipitation have contributed to changes in drought. Drought-affected areas are projected to increase in extent, with the potential for adverse impacts on multiple sectors, e.g. agriculture, water supply, energy production and health, according to IPCC.
A Survey on Orthogonal Matching Pursuit Type Algorithms for Signal Compression and Reconstruction

Compressed sensing is an emerging compressive sampling technique for the signal sampling and reconstruction.The sampling number of original signal,based on this theory,is much less than that based on Nyquist theory.CS senses unknown signal and compresses it meanwhile,and it will have broad application prospects in many areas.The issue to tailor the reconstruction algorithms has obtained much attention and been intensively studied.The properties of the existing reconstruction algorithms are fistly analyzed,then this paper has reviewed the theory of greedy pursuit type algorithms,done a large number of experiments on them,given the advantages and disadvantages and the improvement programs for the shortcomings of each orthogonal matching pursuit type algorithms and some other classics reconstruction algorithms,finally,applied them to the image reconstruction.The reconstruction performance,robustness and complexity of various algorithms are given by experimental simulations,and the advantages and disadvantages of various algorithms are validated.
Asymptotics for the moments of the overshoot and undershoot of a random walk

In this paper we obtain some equivalent conditions and sufficient conditions for the local and nonlocal asymptotics of the φ-moments of the overshoot and undershoot of a random walk, where φ is a nonnegative, long-tailed function. By the strong Markov property, it can be shown that the moments of the overshoot and undershoot and the moments of the first ascending ladder height of a random walk satisfy some renewal equations. Therefore, in this paper we first investigate the local and nonlocal asymptotics for the moments of the first ascending ladder height of a random walk, and then give some equivalent conditions and sufficient conditions for the asymptotics of the solutions to some renewal equations. Using the above results, the main results of this paper are obtained.
Editorial: New insights in sepsis pathogenesis and renal dysfunction: Immune mechanisms and novel management strategies

COPYRIGHT © 2023 Stasi and Honore. This is an openaccess article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Editorial PUBLISHED 08 March 2023 DOI 10.3389/fimmu.2023. 1176620
Biological Health Markers Associated with Oxidative Stress in Dairy Cows during Lactation Period

This review aims to summarize and present different biological health markers in dairy cows during the lactation period. Biochemical health markers provide an indicator of how foreign chemical substances, whether external or internal, affect the animal’s health. To understand the relationship between dairy cow health issues and oxidative stress, various biomarkers of oxidative stress must be investigated. Biochemical and hematological factors play a significant role in determining the biological health markers of animals. A variety of biochemical parameters are dependent on various factors, including the animal’s breed, its age, its development, its pregnancy status, and its production status. When assessing the health of cattle, a blood test is conducted to determine the blood chemistry. To diagnose diseases in dairy animals, the blood biochemistry is necessary to determine the cause of many physiological, metabolic, and pathological problems. Observing blood alterations during pregnancy and at peak lactation may determine what factors lift oxidative stress in cows due to disturbances in feed intake and metabolic processes.
The potential impact of wildfire smoke on COVID-19 cumulative deaths in the San Diego-Tijuana border region

2020 broke records for the most active fire year on the West Coast, resulting in the worst air quality observed in decades. Concurrently, the public health threat of COVID-19 caused over 1 million deaths in the United States (US) and Mexico in 2020 and 2021. Due to the effect of air pollution on respiratory diseases, wildfire-specific particulate matter is a hypothesized driver of COVID-19 severity and death. Capitalizing on wildfire smoke that hit the San Diego-Tijuana border region in September 2020, we applied synthetic control methods to explore its potential differential role in affecting COVID-19 mortality on both sides of the border. Daily data on COVID-19 cumulative deaths for US counties were obtained from the CDC COVID tracker and data for Mexican municipalities was obtained from the Mexican Secretary of Health. Counties and municipalities with wildfire smoke exposure were identified using the National Oceanic and Atmospheric Administration hazard mapping smoke product (HMS); a day where 90% of the area was covered by smoke was considered exposed for the main analyses. Unexposed counties/municipalities were considered as potential controls. The San Diego-Tijuana border region was covered by dense smoke by the 7th of September; 707 COVID-19 deaths had occurred in San Diego and 1367 in Tijuana. While a slight increase in cumulative mortality was observed in San Diego, no change was found in Tijuana; neither estimate indicated a strong precise effect of wildfire smoke on COVID-19 mortality. We hope this study will serve as an illustration of how border contexts can be used to investigate differential vulnerability to wildfire smoke for infectious diseases. Examining the interactive effect of COVID-19 and smoke can help in recognizing the implications of these dual health risks which will be increasingly important as wildfires become more frequent and severe in the context of climate change.
Deep Reinforcement Learning for Real-Time Energy Management in Smart Home

Energy management in the smart home can help reduce residential energy costs by scheduling various energy consumption activities. However, accurately modeling factors, such as user behavior, renewable power generation, weather conditions, and real-time electricity prices can be challenging, making the design of an efficient energy management strategy difficult. This article proposes a real-time energy management algorithm based on deep reinforcement learning (DRL) for smart homes equipped with rooftop photovoltaics, energy storage systems, and smart appliances. The algorithm aims to minimize the energy cost while ensuring user comfort. A policy network that can output both discrete and continuous actions is designed to generate actions for different types of devices in a smart home. The proposed DRL-agent is trained using a proximal policy optimization approach with historical data and is used for real-time scheduling. Finally, simulations based on real-world data demonstrate the effectiveness and robustness of the proposed algorithm.
Confidence, Likelihood, Probability: Statistical Inference with Confidence Distributions

This lively book lays out a methodology of confidence distributions and puts them through their paces. Among other merits, they lead to optimal combinations of confidence from different sources of information, and they can make complex models amenable to objective and indeed prior-free analysis for less subjectively inclined statisticians. The generous mixture of theory, illustrations, applications and exercises is suitable for statisticians at all levels of experience, as well as for data-oriented scientists. Some confidence distributions are less dispersed than their competitors. This concept leads to a theory of risk functions and comparisons for distributions of confidence. Neyman–Pearson type theorems leading to optimal confidence are developed and richly illustrated. Exact and optimal confidence distribution is the gold standard for inferred epistemic distributions. Confidence distributions and likelihood functions are intertwined, allowing prior distributions to be made part of the likelihood. Meta-analysis in likelihood terms is developed and taken beyond traditional methods, suiting it in particular to combining information across diverse data sources.
The gaseous environments of double radio galaxies

A detailed investigation is made of the X-ray emission from five 3CR double radio galaxies, and upper limits are set to the X-ray emissivity of the regions around the radio lobes. These limits, when combined with the expected behavior of hot gas in and around the lobes, show that most of the radio-emitting plasma observed is unlikely to be maintained in static pressure-balance with an external medium. The plasma must expand, and the luminosities of double radio galaxies may therefore decrease with time for most of their lifetimes. A lower limit on the magnetic field strength in the lobes of one-tenth the equipartition value is also derived.
Approximate dynamic programming with state aggregation applied to UAV perimeter patrol

One encounters the curse of dimensionality in the application of dynamic programming to determine optimal policies for large‐scale controlled Markov chains. In this paper, we provide a reward‐based aggregation method to construct suboptimal policies for a perimeter surveillance control problem which gives rise to a large scale Markov chain. The novelty of this approach lies in circumventing the need for value iteration over the entire state space. Instead, the state space is partitioned and the value function is approximated by a constant over each partition. We associate a meta‐state with each partition, where the transition probabilities between these meta‐states are known. The state aggregation approach results in a significant reduction in the computational burden and lends itself to value iteration over the aggregated state‐space. We provide bounds to assess the quality of the approximation and give numerical results that support the proposed methodology. Published 2011. This article is a US Government work and is in the public domain in the USA.
Comparative Review of Motor Technologies for Electric Vehicles Powered by a Hybrid Energy Storage System Based on Multi-Criteria Analysis

The modern era of green transportation based on Industry 4.0 is leading the automotive industry to focus on the electrification of all vehicles. This trend is affected by the massive advantages offered by electric vehicles (EV), such as pollution-free, economical and low-maintenance cost operation. The heart of this system is the electric motor powered by lithium-ion batteries; however, due to their many limitations, a hybrid energy storage system (HESS) consisting of batteries and ultracapacitors is currently gaining increased attention. This paper aims to review the distinct motor technologies such as brushless motors, synchronous reluctance and induction motors currently used in EVs. Additionally, through eleven selected criteria, such as regenerative braking efficiency and power density at different load ranges, the motors are classified in terms of their combined ability to operate with a HESS in order to maximize efficiency and sizing. The results show that permanent magnet and induction motors are the best options when all criteria are considered, while synchronous reluctance motor outperforms the induction motor regarding only the main factors affecting the performance of the hybrid storage system.
Pharmacology and Emerging Therapies for Group 3 Pulmonary Hypertension Due to Chronic Lung Disease

Pulmonary hypertension (PH) frequently complicates chronic lung disease and is associated with high morbidity and poor outcomes. Individuals with interstitial lung disease and chronic obstructive pulmonary disease develop PH due to structural changes associated with the destruction of lung parenchyma and vasculature with concurrent vasoconstriction and pulmonary vascular remodeling similar to what is observed in idiopathic pulmonary arterial hypertension (PAH). Treatment for PH due to chronic lung disease is largely supportive and therapies specific to PAH have had minimal success in this population with exception of the recently FDA-approved inhaled prostacyclin analogue treprostinil. Given the significant disease burden of PH due to chronic lung diseases and its associated mortality, a great need exists for improved understanding of molecular mechanisms leading to vascular remodeling in this population. This review will discuss the current understanding of pathophysiology and emerging therapeutic targets and potential pharmaceuticals.