Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of reminder systems on patients’ adherence to treatment

Background: Patient adherence is an important component of the treatment of chronic disease. An understanding of patient adherence and its modulating factors is necessary to correctly interpret treatment efficacy and barriers to therapeutic success. Purpose: This meta-analysis aims to systematically review published randomized controlled trials of reminder interventions to assist patient adherence to prescribed medications. Methods: A Medline search was performed for randomized controlled trials published between 1968 and June 2011, which studied the effect of reminder-based interventions on adherence to self-administered daily medications. Results: Eleven published randomized controlled trials were found between 1999 and 2009 which measured adherence to a daily medication in a group receiving reminder interventions compared to controls receiving no reminders. Medication adherence was measured as the number of doses taken compared to the number prescribed within a set period of time. Meta-analysis showed a statistically significant increase in adherence in groups receiving a reminder intervention compared to controls (66.61% versus 54.71%, 95% CI for mean: 0.8% to 22.4%). Self-reported and electronically monitored adherence rates did not significantly differ (68.04% versus 63.67%, P = 1.0). Eight of eleven studies showed a statistically significant increase in adherence for at least one of the reminder group arms compared to the control groups receiving no reminder intervention. Limitations: The data are limited by imperfect measures of adherence due to variability in data collection methods. It is also likely that concomitant educational efforts in the study populations, such as instructions regarding proper administration and importance of correct dosing schedules, contributed to improved patient adherence, both in reminder and control arms. The search strategy could have missed relevant studies which were categorized by disease rather than adherence. Conclusions: Reminder-based interventions may improve adherence to daily medications. However, the interventions used in these studies, which included reminder phone calls, text messages, pagers, interactive voice response systems, videotelephone calls, and programmed electronic audiovisual reminder devices, are impractical for widespread implementation, and their efficacy may be optimized when combined with alternative adherence-modifying strategies. More practical reminder-based interventions should be assessed to determine their value in improving patient adherence and treatment outcomes.
Sep]ration-Free Super-Resolution from Compressed Measurements is Possible: an Orthonormal Atomic Norm Minimization Approach

We consider the problem of recovering the superposition of $R$ distinct complex exponential functions from compressed non-uniform time-domain samples. Total Variation (TV) minimization or atomic norm minimization was proposed in the literature to recover the $R$ frequencies or the missing data. However, in order for TV minimization and atomic norm minimization to recover the missing data or the frequencies, the underlying $R$ frequencies are required to be well-separated, even when the measurements are noiseless. This paper shows that the Hankel matrix recovery approach can super-resolve the $R$ complex exponentials and their frequencies from compressed nonuniform measurements, regardless of how close their frequencies are to each other. We propose a new concept of orthonormal atomic norm minimization (OANM), and demonstrate that the success of Hankel matrix recovery in separation-free super-resolution comes from the fact that the nuclear norm of a Hankel matrix is an orthonormal atomic norm. More specifically, we show that, in traditional atomic norm minimization, the underlying parameter values must be well separated to achieve successful signal recovery, if the atoms are changing continuously with respect to the continuously-valued parameter. In contrast, for the OANM, it is possible the OANM is successful even though the original atoms can be arbitrarily close.
Scholarship at UWindsor Scholarship at UWindsor Diversity of judgments: reason and emotions in forensic practice Diversity of judgments: reason and emotions in forensic practice

: The paper questions the role of emotions in judicial persuasion: first, we will provide a brief overview of the affective states, focusing on the structure of the s.c. epistemic feelings; then, we will present some experiments which are going to be developed in a current research-project in a local court in Italy, to understand the interpersonal effects of epistemic feelings on judicial persuasion; finally, we will draw conclusive reflections on the relationship between forensic rhetoric and emotion.
High Dynamic Range Image Compression with Improved Logarithmic Transformation

: High dynamic range (HDR) images have been developed to have almost the same dynamic range as human eye, but the huge amount of data brings a problem in storage and transmission. To compress HDR images, an e ﬃ cient coding method using logarithmic transformation had been proposed in [4]. In this letter, we improve the logarithmic transformation and then derive the optimal parameter to minimize the coding error in HDR region. It is experimentally con ﬁ rmed that the improved coding method has less coding error in HDR region than other existing methods.
complex interventions required to comprehensively educate allied health practitioners on evidence-based practice

: There is currently no strong evidence regarding the most effective training approach for allied health professionals that will support them to consistently apply the best research evidence in daily practice. Current evidence-based practice training tends to be ‘one size fits all’, and is unlikely to be appropriate for all allied health disciplines because of the variability in their tasks and scope of practice. The scant body of evidence regarding the effectiveness of evidence-based practice training for allied health practitioners provides some support for improving knowledge and skills, but equivocal evidence about influencing behaviors and attitudes. We propose a new model of evidence-based practice training, based on the concept of complex interventions reported in the literature. We believe that by offering training in evidence-based practice based on complex interventions relevant to the needs of the attendees, using fixed and variable components, there may be greater success in significantly influencing knowledge skills, attitudes, and behaviors.
Bifurcation From Infinity Induced by a Degeneracy in Semilinear Equations

Abstract We show that for a class of semilinear elliptic eigenvalue problems, including the model case -Δu = λu - h(x) - h(x)|u|p-1u, u|∂Ω = 0, where p > 1 and the nonnegative function h(x) vanishes on a proper subset of Ω, global bifurcation branches from higher eigenvalues are unbounded and blow up at parameter values determined by the vanishing set Ω0 of h(x). In particular, we prove that bifurcation from infinity is possible only at λ ∈ {λk(Ω0) : k ≥ 1}. Moreover, when Ω is an interval, for each k ≥ 1, there is a pair of continuous solution curves that bifurcate out of (λk(Ω0), ∞). For various cases, we demonstrate that there is a global bifurcation branch connecting (λk(Ω), 0) and(λk(Ω0), ∞). Most of our results do not require the nonlinear term to be odd.
Interoception and the Neurovisceral Axis as a Modal Basis for Computational Neuroecology

The defining parameters of neuroecology stand to benefit from a phenomenological expansion that includes the role of affect qua interoception as entailing a multimodal storehouse for specialized signal processing and brain architecture within the neurovisceral axis. The relationship between the gut and the brain represents an integral axis of communication drawing from the ecosystem of the microbiome as an environment for nerve-cell processes reflecting our habits of living and the influence of the luminal environment in higher-ordered cognition. This is shown to apply in both feedforward and inferential models of interoception. A surplus of evidence in recent years indicates that interoception and interoceptive awareness play a key role in influencing adaptive behavioral strategies, cognition, homeostatic regulation, decision-making, social relations and action. The groundwork for this expansion has already been positioned by preliminary efforts to offer a physiological basis for computational neuroecology and emotion qua somatic markers. Building off of their maiden report, this paper develops the richer neuroscientific landscape underwriting somatic markers in the context of the neurovisceral axis qua interoception and biological intuition. In the process we encounter an evolutionarily-rare and morphologically-specialized type of neuron conjectured to provide an advantage for social processing that eclipses the rudimentary notion of somatic markers, alone, and thereby enriches the descriptive landscape of neuroecological phenomena. Finally, we examine the inherent signal processing dynamics in cortical laminar layers as rendered in a newly-fashioned predictive coding account of interoception as a “limbic workspace theory” that interfaces with sensory signals between agranular and granular cells. Advances in predictive coding models and the free-energy principle stand poised to provide a unified model of neural signal processing encompassing sensory coding as well as adaptation in neurons, mood and behavior.The incorporation of interoceptive inference sheds critical light on anticipatory (feedback) signal-processing mechanisms in the brain. This suggests that an incorporation of interoceptive affect-in combination with cognition and adaptation-will shed critical light on further efforts to organize the driving epistemic structure and phenomenology associated with neuroecology.
Kent Academic Repository

While complex systems have been studied now for more than two decades, there still is no agreement on what complexity actually is. This lack of a definition might be a problem when asking questions about the evolution of complexity. In this article criteria against which candidate measures of complexity can be assessed are discussed. The main conclusion of this article is that because of the absence of a basic consensus on what complexity is, there is no criterion that can be used to decide whether or not a proposed measure actually measures complexity. The main recommendation is to abandon complexity as a formal notion; instead, research into the evolution of complexity should use well-understood proxy notions (as is sometimes done in the literature). For the time being ‘‘complexity’’ should remain an informal notion. Research into evolutionary trends of these proxy notions might eventually lead to an emergent community consensus on what complexity is.
Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study

Importance The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation. Objective To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases. Data Sources Genomewide association studies (GWAS) published up to January 15, 2015. Study Selection GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available. Data Extraction and Synthesis Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population. Main Outcomes and Measures Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation. Results Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]). Conclusions and Relevance It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.
A novel angular filter based LiDAR point cloud classification

We consider the problem of ground filtering of LiDAR point cloud by utilizing geometric properties of the scene area. We propose a new approach for detecting man-made object edges from the elevation profile using a novel angle filtering method. This method analyzes neighbors from two nearby tiers, which alleviates the need for multiple gradient calculations from different directions. A subsequent connected component and convex– hull analysis separate all planar surfaces from the detected edges. These separated planar surfaces provide information about objects’ geometry. All objects are separately analyzed to reduce the error around the border region, which is prominent in several existing ground filtering algorithms. Experimental results are shown for a complex urban scene, where complicated building structure is present.
Exponential complexity lower bounds for depth 3 arithmetic circuits in algebras of functions over finite fields

A depth 3 arithmetic circuit can be viewed as a sum of products of linear functions. We prove an exponential complexity lower bound on depth 3 arithmetic circuits computing some natural symmetric functions over a finite field F. Also, we study the complexity of the functions f: D/sup n//spl rarr/F for subsets D/spl sub/F. In particular, we prove an exponential lower bound on the complexity of a depth 3 arithmetic circuit which computes the determinant or the permanent of a matrix considered as functions f:(F*)n/sup 2//spl rarr/F.
Development of Higher Order Thinking Skills Assessment Refer the Theory of Bloom in Laboratory Work

Higher-order thinking skills (HOTS) are one of the important components that students must master to be successful in the 21st century. The HOTS of students in several regions in Indonesia is low because HOTS-based learning and the instruments are not appropriate. This study aims to determine the validity and reliability of the HOTS assessment content, empirical, and constructs referring to bloom theory in laboratory work. The development model used is the Plomp development model, which consists of five stages: initial investigation, design, realization/construction, test, evaluation and revision, and implementation. The HOTS assessment was proven relevant by experts and then distributed to 70 Physics Education students. The HOTS assessment was analyzed by rash model theory analysis with the Winstep program to obtain empirical validity. SEM (Structural Equation Model) was used to obtain construct validity. The results showed that the HOTS assessment was valid and reliable. The results show that the assessment has been able to measure every aspect of HOTS well in laboratory work so that it can be used.
Understanding the Cognition Related to Mathematics Difficulties: A Meta-Analysis on the Cognitive Deficit Profiles and the Bottleneck Theory

The current study investigated the cognitive deficit profiles among individuals with mathematics difficulties (MD) and potential moderators and mechanism for these profiles. Seventy-five cognitive profiling studies on MD were included, representing a total of 13,001 individuals and 126 independent samples. Results showed that compared with typically developing individuals, individuals with MD showed deficits (from most severe to less severe) in phonological processing, processing speed, working memory, attention, short-term memory, executive functions, and visuospatial skills. Moderation analyses indicated that comorbidity (with reading disabilities) and types of MD screening affected the cognitive deficits. Severity of MD was related to processing speed deficits. Deficits in phonological processing and attention were more severe in younger individuals with MD. Deficits in processing speed and working memory were most severe in the numerical domain. Deficits in low-level cognitive skills (i.e., processing speed and short-term memory) could not completely explain the deficits in high-level skills (i.e., working memory, attention, and executive functions), partially supporting the bottleneck theory. These findings, taken together, suggest that (a) deficits in processing speed and working memory are most salient and stable cognitive markers of MD, (b) numerical-processing deficit and the cognitive deficits of MD are relatively independent from each other, and (c) MD may be a discrete construct with heterogeneity reflected by MD subtypes and age. Implications for incorporating cognition in the diagnosis and the interventions for MD are discussed.
of New Hampshire Scholars' Repository University of New Hampshire Scholars

] Thermal analysis of aerosol size distributions provided size resolved volatility up to temperatures of 400 (cid:1) C during extensive flights over North America (NA) for the INTEX/ICARTT experiment in summer 2004. Biomass burning and pollution plumes identified from trace gas measurements were evaluated for their aerosol physiochemical and optical signatures. Measurements of soluble ionic mass and refractory black carbon (BC) mass, inferred from light absorption, were combined with volatility to identify organic carbon at 400 (cid:1) C (VolatileOC) and the residual or refractory organic carbon, RefractoryOC. This approach characterized distinct constituent mass fractions present in biomass burning and pollution plumes every 5–10 min. Biomass burning, pollution and dust aerosol could be stratified by their combined spectral scattering and absorption properties. The ‘‘nonplume’’ regional aerosol exhibited properties dominated by pollution characteristics near the surface and biomass burning aloft. VolatileOC included most water-soluble organic carbon. RefractoryOC dominated enhanced shortwave absorption in plumes from Alaskan and Canadian forest fires. The mass absorption efficiency of this RefractoryOC was about 0.63 m 2 g (cid:1) 1 at 470 nm and 0.09 m 2 g (cid:1) 1 at 530 nm. Concurrent measurements of the humidity dependence of scattering, g , revealed the OC component to be only weakly hygroscopic resulting in a general decrease in g with increasing OC mass fractions. Under ambient humidity conditions, the systematic relations between physiochemical properties and g lead to a well-constrained dependency on the absorption per unit dry mass for these plume types that may be used to challenge remotely sensed and modeled optical properties.
Proton acceleration from magnetized overdense plasmas

Proton acceleration by an ultraintense short pulse circularly polarized laser from an overdense three dimensional (3D) particle-in-cell (PIC) 3D-PIC simulations. The axial magnetic field modifies the dielectric constant of the plasma, which causes a difference in the behaviour of ponderomotive force in case of left and right circularly polarized laser pulse. When the laser is right circularly polarized, the ponderomotive force gets enhanced due to cyclotron effects generating high energetic electrons, which, on reaching the target rear side accelerates the protons via target normal sheath acceleration process. On the other hand, in case of left circular polarization, the effects get reversed causing a suppression of the ponderomotive force at a short distance and lead towards a rise in the radiation pressure, which results in the effective formation of laser piston. Thus, the axial magnetic field enhances the effect of radiation pressure in case of left circularly polarized laser resulting in the generati.
Active disturbance rejection in switched neutral-delay systems based on equivalent-input-disturbance approach

This study presents a new configuration and a design method for the control of a switched neutral-delay system. The equivalent-input-disturbance (EID) approach is used to construct an EID estimator to estimate the influence of exogenous disturbances on the system. A new control law is constructed that incorporates an EID estimate to ensure satisfactory disturbance rejection performance. A sufficient condition for uniformly ultimate boundedness is derived in term of linear matrix inequalities (LMIs) to guarantee the stability of the system. Moreover, state feedback control laws and state observers are designed based on the LMIs for arbitrary switching rules. A numerical example demonstrates the validity of the method.
on Intelligent Manufacturing and Automation , 2013 Development of an Inspection System for Defect Detection in Pressed Parts using Laser Scanned Data

In past few decades several researches have been conducted in the field of 3D parts inspection system. The accuracy level of manufactured parts has been improved remarkably within this period. The use of laser sensors in 3D part measurement process has introduced a significant improvement in data acquisition process regarding time and cost. However for quality control process, due to lack of appropriate technique to process and inspect the scanned point cloud data, high accuracy level could not have been achieved so far. Therefore the industries are still compelled to use same traditional coordinate measuring machines (CMMs) despite of being very slow. In this paper, a robust inspecting technique to detect defects in 3D pressed parts has been proposed. Point cloud data are segmented for the extraction of features. These segmented features are used for shape matching during feature based registration process to localize them with the respective CAD model and bring into same coordinate frame. A modified Iterative closest point (ICP) algorithm is proposed for the registration process. After the registration has been completed these scanned model and CAD model are compared to find defects in the manufactured parts. © 2014 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of DAAAM International Vienna.