Miracle-dz/UniFAR-FTUs huggingface dataset:
Error Analysis of a Finite Element Method for the Space-Fractional Parabolic Equation

We consider an initial boundary value problem for a one-dimensional fractional-order parabolic equation with a space fractional derivative of Riemann--Liouville type and order $\alpha\in (1,2)$. We study a spatial semidiscrete scheme using the standard Galerkin finite element method with piecewise linear finite elements, as well as fully discrete schemes based on the backward Euler method and the Crank--Nicolson method. Error estimates in the $L^2(D)$- and $H^{\alpha/2}(D)$-norm are derived for the semidiscrete scheme and in the $L^2(D)$-norm for the fully discrete schemes. These estimates cover both smooth and nonsmooth initial data and are expressed directly in terms of the smoothness of the initial data. Extensive numerical results are presented to illustrate the theoretical results.
Biofunctionalized Plants as Diverse Biomaterials for Human Cell Culture

The commercial success of tissue engineering products requires efficacy, cost effectiveness, and the possibility of scaleup. Advances in tissue engineering require increased sophistication in the design of biomaterials, often challenging the current manufacturing techniques. Interestingly, several of the properties that are desirable for biomaterial design are embodied in the structure and function of plants. This study demonstrates that decellularized plant tissues can be used as adaptable scaffolds for culture of human cells. With simple biofunctionalization technique, it is possible to enable adhesion of human cells on a diverse set of plant tissues. The elevated hydrophilicity and excellent water transport abilities of plant tissues allow cell expansion over prolonged periods of culture. Moreover, cells are able to conform to the microstructure of the plant frameworks, resulting in cell alignment and pattern registration. In conclusion, the current study shows that it is feasible to use plant tissues as an alternative feedstock of scaffolds for mammalian cells.
PPAR-α, a lipid-sensing transcription factor, regulates blood–brain barrier efflux transporter expression

Lipid sensor peroxisome proliferator-activated receptor alpha (PPAR-α) is the master regulator of lipid metabolism. Dietary release of endogenous free fatty acids, fibrates, and certain persistent environmental pollutants, e.g. perfluoroalkyl fire-fighting foam components, are peroxisome proliferator-activated receptor alpha ligands. Here, we define a role for peroxisome proliferator-activated receptor alpha in regulating the expression of three ATP-driven drug efflux transporters at the rat and mouse blood–brain barriers: P-glycoprotein (Abcb1), breast cancer resistance protein (Bcrp/Abcg2), and multidrug resistance-associated protein 2 (Mrp2/Abcc2). Exposing isolated rat brain capillaries to linoleic acid, clofibrate, or PKAs increased the transport activity and protein expression of the three ABC transporters. These effects were blocked by the PPAR-α antagonist, GW6471. Dosing rats with 20 mg/kg or 200 mg/kg of clofibrate decreased the brain accumulation of the P-glycoprotein substrate, verapamil, by 50% (in situ brain perfusion; effects blocked by GW6471) and increased P-glycoprotein expression and activity in capillaries ex vivo. Fasting C57Bl/6 wild-type mice for 24 h increased both serum lipids and brain capillary P-glycoprotein transport activity. Fasting did not alter P-glycoprotein activity in PPAR-α knockout mice. These results indicate that hyperlipidemia, lipid-lowering fibrates and exposure to certain fire-fighting foam components activate blood–brain barrier peroxisome proliferator-activated receptor alpha, increase drug efflux transporter expression and reduce drug delivery to the brain.
The Mechanical Characterization of Multi-Wall Carbon Nanotubes and Related Interfaces in Nanocomposites

This thesis primarily documents the development and application of a novel technique, which involves the usage of a silicon micro-mechanical device that operates in conjunction with a quantitative nanoindenter within an electron microscope, for the mechanical characterization of nanomaterials and interfaces in composites. The technique was used to conducted tensile tests on individual pristine, nitrogen doped and sidewall fluorinated multi-wall carbon nanotubes (MWNTs), which were found to exhibit varied load-bearing abilities and unique fracture modes. The technique was also used to perform single fiber pullout experiments to study the MWNT/polymer (epoxy) interface. Interfacial failure was found to occur in a brittle fashion, in a manner consistent with the predictions of continuum fracture mechanics models. Although an improvement in the interfacial adhesion was observed upon sidewall fluorination of the MWNT reinforcements, the results of the study essentially highlighted the weak nature of the forces that bind MWNTs to an epoxy matrix.
Self-Adaptive Step Counting on Smartphones under Unrestricted Stepping Modes

Pedometer apps on smartphones and wearable electronics are increasingly popular nowadays, as they are widely used for health monitoring and location-based systems. Most pedometer apps are based on inertial sensors and each step counting algorithm works precisely under restricted stepping modes because steps are detected and validated after comparing their parameters to pre-determined optimal values related to particular conditions. In this paper, we propose self-adaptive step counting in order to improve step counting accuracy under unrestricted stepping modes on smartphones. Based on our human stepping model, we propose self-adaptive method that can detect new steps by monitoring vertical acceleration and validate new steps by comparing to self-adaptive values, which are adjusted dynamically after each step occurs. We show the flexibility of the proposed approach by incorporating it into two existing step counting algorithms WPD and DTW. We also propose a new stepping cycle recognition (SCR) algorithm that is self-adaptive and performs the best under variant stepping modes. With experiments under different stepping modes including fixed and variant modes, we show that self-adaptive methods perform significantly better compared to original methods using fixed optimal values.
Disease Model Distortion in Association Studies

Most findings from genome‐wide association studies (GWAS) are consistent with a simple disease model at a single nucleotide polymorphism, in which each additional copy of the risk allele increases risk by the same multiplicative factor, in contrast to dominance or interaction effects. As others have noted, departures from this multiplicative model are difficult to detect. Here, we seek to quantify this both analytically and empirically. We show that imperfect linkage disequilibrium (LD) between causal and marker loci distorts disease models, with the power to detect such departures dropping off very quickly: decaying as a function of r4, where r2 is the usual correlation between the causal and marker loci, in contrast to the well‐known result that power to detect a multiplicative effect decays as a function of r2. We perform a simulation study with empirical patterns of LD to assess how this disease model distortion is likely to impact GWAS results. Among loci where association is detected, we observe that there is reasonable power to detect substantial deviations from the multiplicative model, such as for dominant and recessive models. Thus, it is worth explicitly testing for such deviations routinely. Genet. Epidemiol. 35: 278‐290, 2011. © 2011 Wiley‐Liss, Inc.
Impact of food, housing, and transportation insecurity on ART adherence: a hierarchical resources approach

ABSTRACT Antiretroviral therapy (ART) has transformed HIV into a manageable illness. However, high levels of adherence must be maintained. Lack of access to basic resources (food, transportation, and housing) has been consistently associated with suboptimal ART adherence. Moving beyond such direct effects, this study takes a hierarchical resources approach in which the effects of access to basic resources on ART adherence are mediated through interpersonal resources (social support and care services) and personal resources (self-efficacy). Participants were 915 HIV-positive men and women living in Atlanta, GA, recruited from community centers and infectious disease clinics. Participants answered baseline questionnaires, and provided prospective data on ART adherence. Across a series of nested models, a consistent pattern emerged whereby lack of access to basic resources had indirect, negative effects on adherence, mediated through both lack of access to social support and services, and through lower treatment self-efficacy. There was also a significant direct effect of lack of access to transportation on adherence. Lack of access to basic resources negatively impacts ART adherence. Effects for housing instability and food insecurity were fully mediated through social support, access to services, and self-efficacy, highlighting these as important targets for intervention. Targeting service supports could be especially beneficial due to the potential to both promote adherence and to link clients with other services to supplement food, housing, and transportation. Inability to access transportation had a direct negative effect on adherence, suggesting that free or reduced cost transportation could positively impact ART adherence among disadvantaged populations.
Examining solutions to missing data in longitudinal nursing research

PURPOSE Longitudinal studies are highly valuable in pediatrics because they provide useful data about developmental patterns of child health and behavior over time. When data are missing, the value of the research is impacted. The study's purpose was to (1) introduce a three-step approach to assess and address missing data and (2) illustrate this approach using categorical and continuous-level variables from a longitudinal study of premature infants. METHODS A three-step approach with simulations was followed to assess the amount and pattern of missing data and to determine the most appropriate imputation method for the missing data. Patterns of missingness were Missing Completely at Random, Missing at Random, and Not Missing at Random. Missing continuous-level data were imputed using mean replacement, stochastic regression, multiple imputation, and fully conditional specification (FCS). Missing categorical-level data were imputed using last value carried forward, hot-decking, stochastic regression, and FCS. Simulations were used to evaluate these imputation methods under different patterns of missingness at different levels of missing data. RESULTS The rate of missingness was 16-23% for continuous variables and 1-28% for categorical variables. FCS imputation provided the least difference in mean and standard deviation estimates for continuous measures. FCS imputation was acceptable for categorical measures. Results obtained through simulation reinforced and confirmed these findings. PRACTICE IMPLICATIONS Significant investments are made in the collection of longitudinal data. The prudent handling of missing data can protect these investments and potentially improve the scientific information contained in pediatric longitudinal studies.
Crohn Disease: FDG PET/CT Before and After Initial Dose of Anti–Tumor Necrosis Factor Therapy to Predict Long-term Response

Purpose Clinical assessments of Crohn disease activity are limited in their capacity to assess treatment response to biologic therapy. The purpose of this study was to determine if changes in FDG activity between baseline PET and repeat PET performed prior to the second dose of induction anti–tumor necrosis factor (TNF) therapy correlate with clinical response. Methods In this prospective, institutional review board–approved, Health Insurance Portability and Accountability Act–compliant pilot study of 8 adult patients with active Crohn disease, FDG activity before and 2 weeks after initiation of anti-TNF therapy was assessed using low-dose PET/CT. FDG activity was measured in the most inflamed bowel loop using an SUVratio (SUVmax/liver SUVmean). Changes in SUVratio were compared with a blinded gastroenterologist assessment of clinical response and steroid-free remission, as well as C-reactive protein (CRP), during a 12-month follow-up period. Results Of 8 patients, 7 showed FDG activity decline at 2 weeks, 5 of whom achieved a clinical response and steroid-free remission at 8, 26, and 52 weeks. The remaining 2 patients with FDG activity decline did not achieve a clinical response or steroid-free remission at these time points, but there were reductions in CRP. The 1 patient without FDG activity decline was a clinical nonresponder, had no reduction in CRP, and did not achieve steroid-free remission. Conclusions A change in FDG activity at FDG PET/CT performed prior to the second induction dose of anti-TNF therapy has the potential to predict clinical response and steroid-free remission in patients with Crohn disease.
Behavioral state classification in epileptic brain using intracranial electrophysiology

Objective. Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. Approach. Data from seven patients (age 34±12, 4 women) who underwent intracranial depth electrode implantation for iEEG monitoring were included. Spectral power features (0.1–600 Hz) spanning several frequency bands from a single electrode were used to train and test a support vector machine classifier. Main results. Classification accuracy of 97.8 ± 0.3% (normal tissue) and 89.4 ± 0.8% (epileptic tissue) across seven subjects using multiple spectral power features from a single electrode was achieved. Spectral power features from electrodes placed in normal temporal neocortex were found to be more useful (accuracy 90.8 ± 0.8%) for sleep-wake state classification than electrodes located in normal hippocampus (87.1 ± 1.6%). Spectral power in high frequency band features (Ripple (80–250 Hz), Fast Ripple (250–600 Hz)) showed comparable performance for AW and SWS classification as the best performing Berger bands (Alpha, Beta, low Gamma) with accuracy ⩾90% using a single electrode contact and single spectral feature. Significance. Automated classification of wake and SWS should prove useful for future implantable epilepsy devices with limited computational power, memory, and number of electrodes. Applications include quantifying patient sleep patterns and behavioral state dependent detection, prediction, and electrical stimulation therapies.
Study on the Calculation Method of One-Dimension Stress Compression for Municipal Solid Waste

The calculation method of one-dimension stress compression for municipal solid waste is studied.The conclusion is that the initial void ratio is a key factor for the one-dimension stress compression of municipal solid waste,but the natural density is little impact to the stress compression of municipal solid waste.The calculation method of one-dimension stress compression for municipal solid waste is determined.The practical process of municipal solid waste landfill is thought-over,therefore,the calculation method is both functional and convenient.
From machine-to-machine communications towards cyber-physical systems

In recent years, cyber-physical systems (CPS) have emerged as a promising direction to enrich the interactions between physical and virtual worlds. In this article, we first present the correlations among machine-to-machine (M2M), wireless sensor networks (WSNs), CPS and internet of things (IoT), and introduce some research activities in M2M, including M2M architectures and typical applications. Then, we review two CPS platforms and systems that have been proposed recently, including a novel prototype platform for multiple unmanned vehicles with WSNs navigation and cyber-transportation systems. Through these reviews, we propose CPS is an evolution of M2M by the introduction of more intelligent and interactive operations, under the architecture of IoT. Also, we especially hope to demonstrate how M2M systems with the capabilities of decision-making and autonomous control can be upgraded to CPS and identify the important research challenges related to CPS designs.
The effects of carbamazepine in the intrahippocampal kainate model of temporal lobe epilepsy depend on seizure definition and mouse strain

Mesial temporal lobe epilepsy (TLE) with hippocampal sclerosis is a predominant form of acquired epilepsy, characterized by recurrent simple and complex partial seizures that are often resistant to treatment. Mice developing spontaneous recurrent nonconvulsive and convulsive seizures after intrahippocampal injection of the excitotoxic glutamate agonist kainate are thought to represent a valuable model of mesial TLE. Epileptic electroencephalogram (EEG) activity recorded in this model from the kainate focus in the ipsilateral hippocampus is resistant to antiseizure drugs such as carbamazepine (CBZ). We compared the efficacy of CBZ in this model in two different mouse strains (FVB/N and NMRI). Furthermore, we evaluated whether changes in the definition of electrographic seizures affect the antiseizure efficacy of CBZ.
Parental supervision for their children's toothbrushing: Mediating effects of planning, self‐efficacy, and action control

OBJECTIVES With 60-90% of children worldwide reportedly experiencing dental caries, poor oral health in the younger years is a major public health issue. As parents are important to children's oral hygiene practices, we examined the key self-regulatory behaviours of parents for supervising their children's toothbrushing using the health action process approach. DESIGN AND METHOD Participants (N = 281, 197 mothers) comprised Australian parents of 2- to 5-year-olds. A longitudinal design was used to investigate the sequential mediation chain for the effect of intention (Time 1) on parental supervision for their youngest child's toothbrushing (Time 3), via self-efficacy and planning (Time 2), and action control (Time 3). RESULTS A latent-variable structural equation model, controlling for baseline behaviour and habit, revealed significant indirect effects from intention via self-efficacy and action control and intention via planning and action control, on parental supervision behaviour. The model was a good fit to the data, explaining 74% of the variance in parents' supervising behaviour for their children's toothbrushing. CONCLUSION While national recommendations are provided to guide parents in promoting good oral hygiene practices with their children, current results show the importance of going beyond simple knowledge transmission to support parents' intentions to supervise their children's toothbrushing actually materialize. Current findings make a significant contribution to the cumulative empirical evidence regarding self-regulatory components in health behaviour change and can inform intervention development to increase parents' participation in childhood oral hygiene practices, thus helping to curb rising oral health conditions and diseases. Statement of contribution What is already known on this subject? Self-regulatory skills are important to translate intentions into behaviour. Self-efficacy, planning, and action control are key self-regulatory skills for behaviour change. What does this study add? Self-regulatory skills are needed for parents to supervise their children's toothbrushings. Self-efficacy, planning, and action control are important self-regulatory skills in this context. Future interventions should map these self-regulatory predictors onto behaviour change techniques.
Green tea extract and catechol‐O‐methyltransferase genotype modify the post‐prandial serum insulin response in a randomised trial of overweight and obese post‐menopausal women

BACKGROUND Green tea extract (GTE) may be involved in a favourable post-prandial response to high-carbohydrate meals. The catechol-O-methyltransferase (COMT) genotype may modify these effects. We examined the acute effects of GTE supplementation on the post-prandial response to a high-carbohydrate meal by assessing appetite-associated hormones and glucose homeostasis marker concentrations in women who consumed 843 mg of (-)-epigallocatechin-3-gallate (EGCG) or placebo capsules for 11-12 months. METHODS Sixty Caucasian post-menopausal women (body mass index ≥ 25.0 kg m-2 ) were included in a randomised, double-blind feeding study. GTE was consumed with a breakfast meal [2784.0 kJ (665.4 kcal); 67.2% carbohydrate]. Blood samples were drawn pre-meal, post-meal, and every 30 min for 4 h. Participants completed six satiety questionnaires. RESULTS Plasma leptin, ghrelin and adiponectin did not differ between GTE and placebo at any time point; COMT genotype did not modify these results. Participants randomised to GTE with the high-activity form of COMT (GTE-high COMT) had higher insulin concentrations at time 0, 0.5 and 1.0 h post-meal compared to all COMT groups randomised to placebo. Insulin remained higher in the GTE-high COMT group at 1.5, 2.0 and 2.5 h compared to Placebo-low COMT (P < 0.02). GTE-high COMT had higher insulin concentrations at times 0, 0.5, 1.0, 1.5 and 2.0 h compared to the GTE-low COMT (P ≤ 0.04). Area under the curve measurements of satiety did not differ between GTE and placebo. CONCLUSIONS GTE supplementation and COMT genotype did not alter acute post-prandial responses of leptin, ghrelin, adiponectin or satiety, although it may be involved in post-meal insulinaemic response of overweight and obese post-menopausal women.
Are Lowered Socioeconomic Circumstances Causally Related to Tooth Loss? A Natural Experiment Involving the 2011 Great East Japan Earthquake

Oral health status is correlated with socioeconomic status. However, the causal nature of the relationship is not established. Here we describe a natural experiment involving deteriorating socioeconomic circumstances following exposure to the 2011 Great East Japan Earthquake and Tsunami. We investigated the relationship between subjective economic deterioration and housing damage due to the disaster and tooth loss in a cohort of community-dwelling residents (n = 3,039), from whom we obtained information about socioeconomic status and health status in 2010 (i.e., predating the disaster). A follow-up survey was performed in 2013 (postdisaster), and 82.1% of the 4,380 eligible survivors responded. We estimated the impact of subjective economic deterioration and housing damage due to the disaster on tooth loss by fitting an instrumental variable probit model. Subjective economic deterioration and housing damage due to the disaster were significantly associated with 8.1% and 1.7% increases in the probability of tooth loss (probit coefficients were 0.469 (95% confidence interval: 0.065, 0.872) and 0.103 (95% confidence interval: 0.011, 0.196), respectively). In this natural experiment, we confirmed the causal relationship between deteriorating socioeconomic circumstances and tooth loss.