Miracle-dz/UniFAR-FTUs huggingface dataset:
A Systematic Review and Meta-Analysis on the Efficacy of Locally Delivered Adjunctive Curcumin (Curcuma longa L.) in the Treatment of Periodontitis

This meta-analysis intended to assess evidence on the efficacy of locally delivered curcumin/turmeric as an adjunctive to scaling and root planing (SRP), on clinical attachment level (CAL) and probing pocket depth (PPD), compared to SRP alone or in combination with chlorhexidine (CHX). RCTs were identified from PubMed, Cochrane Library, BASE, LIVIVO, Dentistry Oral Sciences Source, MEDLINE Complete, Scopus, ClinicalTrials.gov, and eLibrary, until August 2022. The risk of bias (RoB) was assessed with the Cochrane Risk of Bias tool 2.0. A random-effects meta-analysis was performed by pooling mean differences with 95% confidence intervals. Out of 827 references yielded by the search, 23 trials meeting the eligibility criteria were included. The meta-analysis revealed that SRP and curcumin/turmeric application were statistically significantly different compared to SRP alone for CAL (−0.33 mm; p = 0.03; 95% CI −0.54 to −0.11; I2 = 62.3%), and for PPD (−0.47 mm; p = 0.024; 95% CI −0.88 to −0.06; I2 = 95.5%); however, this difference was considered clinically meaningless. No significant differences were obtained between patients treated with SRP and CHX, compared to SRP and curcumin/turmeric. The RoB assessment revealed numerous inaccuracies, thus raising concerns about previous overestimates of potential treatment effects.
Fixed and Variable Constraints in Sensitivity Analysis

Sufficient conditions are obtained for the $\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{C} ^1 $ dependence on a parameter of a local minimizes and associated Lagrange multipliers for parametrized families of nonlinear programming problems in which some constraints do not vary with the parameter. A class of sets, called “cyrtohedra”, with properties suitable for the representation of fixed constraint sets is discussed.
Negative refraction by a uniaxial wire medium with suppressed spatial dispersion

Here, we show that a structure formed by an array of metallic wires loaded with metallic patches may enable strong negative refraction even when the conductivity of the metal is very large, e.g., in the microwave regime. It is shown that the composite structure may be regarded as a uniaxial indefinite material loaded with impedance sheets, and that the negative refraction effect may be characterized using homogenization methods.
Estimation of pH on total scale in coastal environments for the understanding of the variability of the carbonate system in the context of ocean acidification

Most of the theoretical and practical development of the ocean acidification (OA) phenomenon involves the open ocean, and not much is known of the significance of variation in pH and carbonate system in coastal environments and the effect, if any, of OA. Traditional potentiometric pH measurements are carried out on the NBS scale (pHNBS), developed for freshwaters, but for OA it is necessary to use the total scale (pHT), which includes the additional ions of seawater. Using a series of in-situ measurements of potential, carried out with a pHNBS electrode in the artificial coastal lagoon La Escollera in Santa Marta (Colombia), a methodology to calculate pHT was tested. For this, the equation pHT(X) = pHT(TRIS) - EX-ETRISR*T*ln10/F was used, which calculates pHT(X) of the sample from the pHT(TRIS) of the TRIS standard solution, the potentials E measured at temperature T, and the constants R and F. ETRIS was determined experimentally for the lagoon temperature range, and the linear regression showed a coefficient of determination (R2) of 0.9977. In a first qualitative analysis, it was verified that pH variations during the day-night cycle are closely associated with those of oxygen, from the production and consumption of CO2 by photosynthesis and respiration. These high-frequency variations are of greater magnitude than those of the open ocean, raising questions about the real effect of OA on coastal ecosystems.
Chemical Constituents and Biological Activities of Essential Oils from Four Species of Bamboo Genus Schizostachyum

Volatile chemical constituents of four species of local bamboo (Schizostachyum blumei Nees., Schizostachyum brachycladum Nees., Schizostachyum lima (Blanco) Merrill and Schizostachyum pilosum S.Dransf. ) were investigated. The oils were obtained from bamboo culm through steam distillation and profiled using Gas Chromatography-Mass Spectrometry (GCMS). A total of 59 volatile constituents were identified, and these contained oxygenated sesquiterpene, Î±-elemol (8.2~21.1 %), coumaran (6.7~32.3 %), guaiacol-4-vinyl (0.6~0.9 %), palmitic acid (1.5~25.6 %), pentacosane (0.1~0.2 %), phytol (1.0~12.6 %), phytol acetate (0.5~1.7 %) and trans-squalene (0.2~1.6 %) consistently in the specimens studied. Based on the observation, S. pilosum exhibited wider diameter of inhibition against Escherchia coli and Staphylococcus aureus compared to the other species of Schizostachyum essential oil.
Change in the Nature of ZSM-5 Zeolite Depending on the Type of Metal Adsorbent—The Analysis of DOS and Orbitals for Iron Species

Transition-metal-modified zeolites have recently gained the greatest interest among scientists. Ab initio calculations within the density functional theory were used. The exchange and correlation functional was approximated with the Perdew–Burke–Ernzerhof (PBE) functional. Cluster models of ZSM-5 (Al2Si18O53H26) zeolites were used with Fe particles adsorbed above aluminum. The adsorption of three iron adsorbates inside the pores of the ZSM-5 zeolite—Fe, FeO and FeOH—was carried out with different arrangements of aluminum atoms in the zeolite structure. The DOS diagram and the HOMO, SOMO and LUMO molecular orbitals for these systems were analyzed. It has been shown that depending on the adsorbate and the position of aluminum atoms in the pore structure of the zeolite, the systems can be described as insulators or conductors, which significantly affects their activity. The main aim of the research was to understand the behavior of these types of systems in order to select the most efficient one for a catalytic reaction.
A Review of: “Models for Discrete Longitudinal Data”, by G. Molenberghs and G. Verbeke

Previously, Verbeke and Molenberghs (2000) presented a comprehensive text on the linear mixed model that was devoted to the analysis of continuous longitudinal data. Their current work considers non-Gaussian data, including repeated, clustered, and multivariate data that are binary, ordinal, or represent counts. This is very important from a practical standpoint because study outcomes are often longitudinal and discrete, or even if the primary outcomes are continuous, discrete versions will often be considered. For example, the percentage reduction from baseline in tumor size, a continuous outcome, might also be viewed as a repeated binary outcome that indicates whether or not a 50% reduction since baseline has occurred. The analysis of longitudinal discrete data also represents an active and broad area of current research, stemming in part from the fact that there is no discrete analog of the multivariate normal distribution. As a result, extending the development of theory for linear mixed models to discrete outcomes typically cannot be accomplished by applying standard likelihoodbased approaches for multivariate normal data to one appropriate counterpart for discrete outcomes. The authors write that they “attempt to fill this gap (resulting from prior focus on Gaussian data) with the current text. ” Their intended audience includes “applied statisticians and biomedical researchers, particularly in the biopharmaceutical industry, medical and public health research organizations, contract research organizations, and academic departments. ” The book is organized as follows. The introduction (Chapter 1) provides an overview and outline for the six sections of the text. Part I (Introductory Material) describes several interesting motivating studies that the authors refer to repeatedly (Chapter 2); provides a brief review of generalized linear models that includes an example of logistic and Poisson regression analysis for the Toenail and Epilepsy motivating studies (Chapter 3); reviews some of the key concepts for analysis of Gaussian longitudinal data using the linear mixed model (Chapter 4); and then describes three important families of models for repeated non-Gaussian data: the marginal models, conditionally specified models, and the subject-specific models (Chapter 5). Part II focuses on marginal models, with a description and application of association models for bivariate outcomes and cross-classified data (Chapter 6); an overview of models based on fully specified likelihoods, including the Bahadur model for correlated binary data (Chapter 7); a description of alternatives to likelihood-based approaches that include generalized estimating equations (GEE) of Liang and Zeger (1986) and methods based on GEE, including GEE1 (Prentice, 1988), GEE2 (Liang et al., 1992; Zhao and Prentice, 1990), and the alternating
Heavy Ion Acceleration by Nonlinear Magnetosonic Waves in a Two-Ion-Species Plasma

The ion dynamics in perpendicular nonlinear magnetosonic waves in a plasma containing two ion species is studied through theory and simulation using a one dimension, electromagnetic particle code with full ion and electron dynamics; in the simulations the density of heavier ions was set to be 10% of that of lighter ions. As in a single-ion-species plasma, some of the light ions can be accelerated by the longitudinal electric field formed in a wave. It is found that the bulk of heavy ions are accelerated by the transverse electric field. For a large-amplitude wave, the maximum speed of heavy ions is about the wave propagation speed, which exceeds the Alfven speed. Theoretical estimates of maximum speeds are given for small- and large- amplitude waves. They are in good agreement with the simulation results.
Shifting Mobility Behaviors in Unprecedented Times: A Multigroup MIMIC Model Investigating Intentions to Use On-Demand Ride Services During the COVID-19 Pandemic

The spread of COVID-19 has been a major disruptive force in people’s everyday lives and mobility behavior. The demand for on-demand ride services, such as taxis and ridehailing, has been specifically affected given both restrictions in service operations and users’ concerns about virus transmission in shared vehicles. In the early months of the pandemic, demand for these modes decreased by as much as 80%. This study examines intentions to use on-demand ride services in the early lockdown stage of the pandemic in the United States, a period of unprecedented mobility reductions, changing household routines and transforming travel behaviors. Using data from a survey disseminated in June 2020 to 700 U.S. respondents, we use multigroup MIMIC (Multiple Indicator Multiple Cause) models to investigate the stated shift in intentions to use on-demand modes of travel. By using group-based segmentation we control for variation in ridership intentions according to personal, household, attitudinal factors, and pandemic experiences. The results point to a reduction across the board in the likelihood of using on-demand mobility associated with a significant COVID-19 effect. Beyond this general decrease, several groups are found to have more positive intentions, including younger adults, urban residents, graduate-degree holders, and people of Hispanic, Latino, Asian, and Pacific Islander ethnicities/races. The attitudinal effect of “tech-savviness” drives higher user intentions, revealing indirect effects of gender, education, and age. Multigroup analysis provides further evidence of potential COVID-triggered shifts in on-demand ridership intentions. The most significant drops in likelihood are observed for younger respondents (below 45), Black compared with all other racial/ethnic status, and for past users of on-demand mobility. This latter result is somewhat surprising, as riders who are younger and more experienced with on-demand travel are more likely to have been users in the past, but also more likely to reduce use during the pandemic. To conclude, we discuss the need to investigate pandemic experiences, risk attitudes, and circumstances to understand evolving mobility behavior and specific service model impacts.
Structural Features Governing the Metabolic Stability of Tetraethyl-Substituted Nitroxides in Rat Liver Microsomes

Nitroxides are potent tools for studying biological systems by electron paramagnetic resonance (EPR). Whatever the application, a certain stability is necessary for successful detection. Since conventional tetramethyl-substituted cyclic nitroxides have insufficient in vivo stability, efforts have recently been made to synthesize more stable, tetraethyl-substituted nitroxides. In our previous study on piperidine nitroxides, the introduction of steric hindrance around the nitroxide moiety successfully increased the resistance to reduction into hydroxylamine. However, it also rendered the carbon backbone susceptible to modifications by xenobiotic metabolism due to increased lipophilicity. Here, we focus on a new series of three nitroxide candidates with tetraethyl substitution, namely with pyrrolidine, pyrroline, and isoindoline cores, to identify which structural features afford increased stability for future probe design and application in in vivo EPR imaging. In the presence of rat liver microsomes, pyrrolidine and pyrroline tetraethyl nitroxides exhibited a higher stability than isoindoline nitroxide, which was studied in detail by HPLC-HRMS. Multiple metabolites suggest that the aerobic transformation of tetraethyl isoindoline nitroxide is initiated by hydrogen abstraction by P450-FeV = O from one of the ethyl groups, followed by rearrangement and further modifications by cytochrome P450, as supported by DFT calculations. Under anaerobic conditions, only reduction by rat liver microsomes was observed with involvement of P450-FeII.
On the blowup of solutions of a Schrödinger equation with an inhomogeneous damping coefficient

We consider the Cauchy problem for the nonlinear self-focusing Schrodinger equation in ℝN with an inhomogeneous smooth damping coefficient and we prove, for suitable initial data, and in the spirit of the seminal work of R. Glassey, a blowup result for the corresponding local solutions. We also give some lower bound estimates for the blowing-up solutions.
Long-Range Underwater Acoustic Channel Estimation

Long-range underwater acoustic communication (LR-UWAC) is an essential technique for applications such as the control of unmanned underwater vehicles, gliders, or tactical submarines for long-term monitoring tasks. While techniques for estimating the channel impulse response (CIR) of short-range UWAC have been successfully applied, this is not the case for LR-UWAC. Here, the main challenge is to handle the diverse channel structure, which can be of a sparse or a non-sparse structure. In this paper, we propose a robust channel estimator for LR-UWAC. Our solution includes a switching mechanism to classify the channel as either sparse or non-sparse. In its sparse form, the LR-UWAC channel is characterized by a long time delay spread, time-invariant characteristics, and a block structure. Thus, we propose a non-trivial combination of the block subspace pursuit and the distributed subspace pursuit algorithms to exploit the channel’s block structure. For non-sparse LR-UWAC channel structures, we approximate the received signal as Gaussian, and derive a maximum-likelihood (ML) estimator to separate the non-resolvable multipath. Extensive numerical simulation and results from two long-range sea experiments demonstrate the efficiency of our approach in identifying the channel’s structure, and to accurately estimate the channel compared to state-of-the-art benchmarks.
ILD-GAP Combined with the Charlson Comorbidity Index Score (ILD-GAPC) as a Prognostic Prediction Model in Patients with Interstitial Lung Disease

Background The ILD-GAP scoring system has been widely used to predict the prognosis of patients with interstitial lung disease (ILD). The ability of the ILD-GAP scoring system combined with the Charlson Comorbidity Index score (CCIS) (ILD-GAPC) to predict ILD prognosis was investigated. Methods In ILD patients, including idiopathic pulmonary fibrosis (IPF), idiopathic nonspecific interstitial pneumonia (iNSIP), collagen vascular disease-related interstitial pneumonia (CVD-IP), chronic hypersensitivity pneumonitis (CHP), and unclassifiable ILD (UC-ILD), treated between April 2013 and April 2017, the relationships between baseline clinical parameters, including age, sex, CCIS, ILD diagnosis, pulmonary function test results, and disease outcomes, were retrospectively assessed, and the ability to predict prognosis was compared between the ILD-GAP and ILD-GAPC models, respectively. Results A total of 185 patients (mean age, 71.9 years), all of whom underwent pulmonary function testing, including percentage predicted diffusion capacity for carbon monoxide, were assessed. ILD diagnosis consisted of IPF in 57 cases, iNSIP and CVD-IP in 117 cases, CHP in 6 cases, and UC-ILD in 5 cases. The ILD-GAPC provided a greater area under the receiver operating characteristic curve (0.758) for predicting 3-year ILD-related events than the ILD-GAP (0.721). In addition, log-rank tests showed that the Kaplan−Meier curves differed significantly among low, middle, and high ILD-GAPC scores (P < 0.001), unlike ILD-GAP scores (P = 0.083). Conclusions The ILD-GAPC model could provide more accurate information for predicting prognosis in patients with ILD than the ILD-GAP model.
Low-frequency lessons from the 74-MHz Very Large Array

The 74 MHz system on the National Radio Astronomy Observatory's Very Large Array (VLA) has opened a high-resolution, high-sensitivity window on the electromagnetic spectrum at low frequencies. It provides us with a unique glimpse into both the possibilities and challenges of planned low-frequency radio interferometers such as LOFAR, the LWA, and the SKA. Observations of bright, resolved radio sources at 74 MHz provide new scientific insights into the structure, history, and energy balances of these systems. However many of these scientifically motivated observations will also be critical to testing the scientific fidelity of new instruments, by providing a set of well-known standard sources. We are also using the 74 MHz system to conduct a sky survey, called the VLA Low-frequency Sky Survey (VLSS). When complete it will cover the entire sky above -30 degrees declination, at a 5σ sensitivity of 0.5 Jy/bm-1, and a resolution of 80" (B-configuration). Among its various uses, this survey will provide an initial grid of calibrator sources at low frequency. Finally, practical experience with calibration and data reduction at 74 MHz has helped to direct and shape our understanding of the design needs of future instruments. In particular, we have begun experimenting with angle-variant calibration techniques which are essential to properly calibrate the wide field of view at low frequencies.
Output feedback stabilization of fully linearizable systems

An observer-based controller is designed to stabilize a fully linearizable nonlinear system. The system is assumed to be left-invertible and minimum-phase. The controller is robust to uncertainties in modelling the nonlinearities of the system. The design of the controller and the stability analysis employs the techniques of singular perturbations. A new ‘Tikhonov-like’ theorem is presented and used to analyse the system when the control is globally bounded.
Enhanced Boiling of FC-72 on Silicon Chips with Micro-Pin-Fins and Submicron-Scale Roughness

Experiments were conducted to study the effects of micro-pin-fins and submicron-scale roughness on the boiling heat transfer from a silicon chip immersed in a pool of degassed and gas-dissolved FC-72. Square pin-fins with fin dimensions of 50×50×60 μm 3 (width ×thickness×height) and submicron-scale roughness (RMS roughness of 25 to 32 nm) were fabricated on the surface of square silicon chip (10×10×0.5 mm 3 ) by use of microelectronic fabrication techniques. Experiments were conducted at the liquid subcoolings of 0, 3, 25, and 45 K. Both the micro-pin-finned chip and the chip with submicron-scale roughness showed a considerable heat transfer enhancement as compared to a smooth chip in the nucleate boiling region. The chip with submicron-scale roughness showed a higher heat transfer performance than the micro-pin-finned chip in the low-heat-flux region
Central Sensitization and Chronic Pain Personality Profile: Is There New Evidence? A Case-Control Study

Background: Personality traits are relevant for pain perception in persistent pain disorders, although they have not been studied in depth in sensitized and nonsensitized patients with knee osteoarthritis (OA). Objective: To explain and compare the personality profile of patients with OA, with and without central sensitization (CS), and fibromyalgia (FM). Setting: Participants were selected at the Rheumatology Department in two major hospitals in Spain. Participants: Case-control study where the sample consists of 15 patients with OA and CS (OA-CS), 31 OA without CS (OA-noCS), 47 FM, and 22 controls. We used a rigorous and systematic process that ensured the sample strictly fulfilled all the inclusion/exclusion criteria, so the sample is very well delimited. Primary outcome measures: Personality was assessed by the Temperament and Character Inventory of Cloninger. Results: The percentile in harm-avoidance dimension for the FM group is higher compared to OA groups and controls. The most frequent temperamental profiles in patients are cautious, methodical, and explosive. Patients with FM are more likely to report larger scores in harm-avoidance, with an increase in logistic regression adjusted odds ratio (ORadj) between 4.2% and 70.2%. Conclusions: Harm-avoidance seems to be the most important dimension in personality patients with chronic pain, as previously found. We found no differences between OA groups and between sensitized groups, but there are differences between FM and OA-noCS, so harm-avoidance might be the key to describe personality in patients with CS rather than the presence of prolonged pain, as found in the literature before.
Psychological Benefits of Self-Guided Forest Healing Program Using Campus Forests

Forest healing, also known as forest therapy, has been documented as preventive therapy to enhance health. Primarily, many studies have indicated the benefits of a guided forest-healing program operated under the guidance of a forest therapist. However, little is known about the benefits of a self-guided forest healing program carried out alone, without a guide. Therefore, the purpose of the current study was to investigate the psychological benefits of a self-guided forest healing program. We designed a randomized 3 × 3 crossover study. Twenty-three university students were randomly exposed to three different conditions: a self-guided forest healing program, a guided forest-healing program, and routine activities. Measures included the Profile of Mood State (POMS) and the State-Trait Anxiety Inventory-X1 (STAI-X1). As a result, self-guided and guided forest-healing programs significantly improved subjects’ mood states and anxiety symptoms compared to routine activities. Participating in a forest healing program with guides and participating in a self-guided forest healing program both provided psychological benefits for subjects, showing that self-guided programs can be effectively combined with forest healing. These findings suggest new ways to utilize forest healing to improve mental health. Therefore, the self-guided forest healing program proposes a complementary use of the guided forest-healing program in a modern urbanized society.