LLukas22/scidocs huggingface dataset:
Assessing User Engagement of an mHealth Intervention: Development and Implementation of the Growing Healthy App Engagement Index

BACKGROUND
Childhood obesity is an ongoing problem in developed countries that needs targeted prevention in the youngest age groups. Children in socioeconomically disadvantaged families are most at risk. Mobile health (mHealth) interventions offer a potential route to target these families because of its relatively low cost and high reach. The Growing healthy program was developed to provide evidence-based information on infant feeding from birth to 9 months via app or website. Understanding user engagement with these media is vital to developing successful interventions. Engagement is a complex, multifactorial concept that needs to move beyond simple metrics.


OBJECTIVE
The aim of our study was to describe the development of an engagement index (EI) to monitor participant interaction with the Growing healthy app. The index included a number of subindices and cut-points to categorize engagement.


METHODS
The Growing program was a feasibility study in which 300 mother-infant dyads were provided with an app which included 3 push notifications that was sent each week. Growing healthy participants completed surveys at 3 time points: baseline (T1) (infant age ≤3 months), infant aged 6 months (T2), and infant aged 9 months (T3). In addition, app usage data were captured from the app. The EI was adapted from the Web Analytics Demystified visitor EI. Our EI included 5 subindices: (1) click depth, (2) loyalty, (3) interaction, (4) recency, and (5) feedback. The overall EI summarized the subindices from date of registration through to 39 weeks (9 months) from the infant's date of birth. Basic descriptive data analysis was performed on the metrics and components of the EI as well as the final EI score. Group comparisons used t tests, analysis of variance (ANOVA), Mann-Whitney, Kruskal-Wallis, and Spearman correlation tests as appropriate. Consideration of independent variables associated with the EI score were modeled using linear regression models.


RESULTS
The overall EI mean score was 30.0% (SD 11.5%) with a range of 1.8% - 57.6%. The cut-points used for high engagement were scores greater than 37.1% and for poor engagement were scores less than 21.1%. Significant explanatory variables of the EI score included: parity (P=.005), system type including "app only" users or "both" app and email users (P<.001), recruitment method (P=.02), and baby age at recruitment (P=.005).


CONCLUSIONS
The EI provided a comprehensive understanding of participant behavior with the app over the 9-month period of the Growing healthy program. The use of the EI in this study demonstrates that rich and useful data can be collected and used to inform assessments of the strengths and weaknesses of the app and in turn inform future interventions.
An Achievability Scheme for the Compound Channel with State Noncausally Available at the Encoder

A new achievability scheme for the compound channel with dis crete memoryless (DM) state noncausally available at the encoder is established. Achievability is proved usin g superposition coding, Marton coding, joint typicality encoding, and indirect decoding. The scheme is shown to achi eve strictly higher rate than the straightforward extensio of the Gelfand-Pinsker coding scheme for a single DMC with DM state, and is optimal for some classes of channels. I. I NTRODUCTION Consider the problem of reliable communication over a compo und channel with discrete memoryless (DM) state, where a sender wishes to communicate a message to a receiver w ith the state sequence available noncausually at the encoder. For simplicity we consider the case when the compou nd channel comprises only two discrete memoryless channels (DMCs) with DM state. This setup is essentially the same as sending a common message over a 2receiver discrete memoryless broadcast channel (DM-BC) wi th DM state when the state in available noncausally at the encoder as shown in Figure 1. As such, we focus our discuss ion throughout the paper on this equivalent setup.
Visual recognition of pointing gestures for human-robot interaction

In this paper, we present an approach for recognizing pointing gestures in the context of human–robot interaction. In order to obtain input features for gesture recognition, we perform visual tracking of head, hands and head orientation. Given the images provided by a calibrated stereo camera, color and disparity information are integrated into a multi-hypothesis tracking framework in order to find the 3D-positions of the respective body parts. Based on the hands’ motion, an HMM-based classifier is trained to detect pointing gestures. We show experimentally that the gesture recognition performance can be improved significantly by using information about head orientation as an additional feature. Our system aims at applications in the field of human–robot interaction, where it is important to do run-on recognition in real-time, to allow for robot egomotion and not to rely on manual initialization. 2006 Elsevier B.V. All rights reserved.
Gifts and Reasons: The Contexts of Peele's Araygnement of Paris

cause it is so characteristic and compendious a production of Elizabethan court culture. The Araygnement has been made to exemplify not only hyperbolic royal entertainment but also humble pastoral retirement; it has been interpreted not only as a glorification of power but as a repudiation of ambition. These divergent critical responses point to the ideological complexity of Elizabethan culture and Peele's play. The play's setting is pastoral, its dramaturgy is spectacular, and its royal sentiments are fulsome. Its action repeatedly involves the humble and the great in rites of homage or strategies of coercion. The Araygnement of Paris recreates the culture which creates it. Acts of gift-giving and relationships of power within the fiction reproduce basic characteristics of the social world in which the play is written and performed. I shall explore some of the symbolic forms which typify Elizabethan court culture and Peele's play: pastoral conventions, myths of royal power, and acts of prestation.* If my exploration of these forms appears as much concerned with the contexts of Peele's play as with the play itself, this is because "text" and "context" define and illuminate each other.
Association of a haplotype for tumor necrosis factor in siblings with late-onset Alzheimer disease: the NIMH Alzheimer Disease Genetics Initiative.

Tumor necrosis factor (TNF), a proinflammatory cytokine, may be involved in the pathogenesis of Alzheimer disease (AD) based on observations that senile plaques have been found to upregulate proinflammatory cytokines. Additionally, nonsteroidal anti-inflammatory drugs have been found to delay and prevent the onset of AD. A collaborative genome-wide scan for AD genes in 266 late-onset families implicated a 20 centimorgan region at chromosome 6p21.3 that includes the TNF gene. Three TNF polymorphisms, a -308 TNF promoter polymorphism, whose TNF2 allele is associated with autoimmune inflammatory diseases and strong transcriptional activity, the -238 TNF promoter polymorphism, and the microsatellite TNFa, whose 2 allele is associated with a high TNF secretion, were typed in 145 families consisting of 562 affected and unaffected siblings. These polymorphisms formed a haplotype, 2-1-2, respectively, that was significantly associated with AD (P = 0.005) using the sibling disequilibrium test. Singly, the TNFa2 allele was also significantly associated (P = 0.04) with AD in these 145 families. This TNF association with AD lends further support for an inflammatory process in the pathogenesis of AD. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 96:823-830, 2000.
Analysis of Two-Phase Stepper Motor Driver Based on FPGA

In order to achieve both high speed and high precision for motion control, a controller with flexible algorithm and programmable logic will be expected. Based on field programmable gate array (FPGA), this paper proposes an approach to subdivide the step to microsteps with required resolution for stepper motor to improve positioning accuracy, the paper also describes the design and implementation of the microstepper motor driver with FPGA residing at the heart. In this paper, sine/cosine microstepper method is adopted to adjust current in each winding of the stepper motor with built-in sine/cosine look-up table in FPGA, hence precise and homogeneous micro steps can be obtained. In addition, the designs of the hardware and software are also proposed in detail to control the currents of the motor precisely, a simulation of FPGA logic to realize microstepper functions has been completed to verify the effectiveness of proposed approach.
Conformations of macromolecules and their complexes from heterogeneous datasets

We describe a new generation of algorithms capable of mapping the structure and conformations of macromolecules and their complexes from large ensembles of heterogeneous snapshots, and demonstrate the feasibility of determining both discrete and continuous macromolecular conformational spectra. These algorithms naturally incorporate conformational heterogeneity without resort to sorting and classification, or prior knowledge of the type of heterogeneity present. They are applicable to single-particle diffraction and image datasets produced by X-ray lasers and cryo-electron microscopy, respectively, and particularly suitable for systems not easily amenable to purification or crystallization.
Acute effects of indacaterol on lung hyperinflation in moderate COPD: a comparison with tiotropium.

BACKGROUND
Evidence has been provided that high-dose indacaterol (300 μg) can reduce lung hyperinflation in moderate-to-severe chronic obstructive pulmonary disease (COPD).


AIM
To study whether low-dose indacaterol (150 μg) also reduces lung hyperinflation in comparison with the recommended dose of tiotropium (18 μg) in moderate COPD.


METHODS
This was a multicenter, randomized, blinded, 3-period cross-over, placebo-controlled study. Spirometry and lung volumes were measured before and 30, 60, 120, 180 and 240 min after the administration of single-doses of indacaterol, tiotropium, or placebo. The primary end-point was the change in peak inspiratory capacity (IC). The area under the 4-h curve (AUC(0-4)) for IC, 1-s forced expiratory volume (FEV(1)) and forced vital capacity (FVC) were secondary variables.


RESULTS
49 patients completed the study. On average, peak IC and AUC(0-4) for IC were significantly greater after indacaterol than placebo by 177 mL (p = 0.007) and 142 mL (p = 0.001), respectively. Differences in peak IC and AUC(0-4) for IC between tiotropium and placebo were 120 mL (p = 0.07) and 85 mL (p = 0.052), respectively. Differences between indacaterol and tiotropium were statistically insignificant. Peak IC increased by >20% in 12 patients with indacaterol and 9 with tiotropium (p = 0.001), and by >30% in 8 patients with indacaterol and 3 with tiotropium (p = 0.001). The effects of indacaterol and tiotropium on FEV(1) and FVC were statistically significant vs placebo.


CONCLUSIONS
Low-dose indacaterol has a bronchodilator effect that is similar to the recommended dose of tiotropium, but it is slightly superior in reducing lung hyperinflation.


TRIAL REGISTRATION
ClinicalTrials.gov number: NCT00999908.
A spicamycin derivative (KRN5500) provides neuropathic pain relief in patients with advanced cancer: a placebo-controlled, proof-of-concept trial.

CONTEXT
Neuropathic pain in patients with cancer can be difficult to treat effectively.


OBJECTIVES
The purpose of the study was to determine safety and efficacy of KRN5500, a novel, spicamycin-derived, nonopioid analgesic agent, in patients with advanced cancer and neuropathic pain of any etiology.


METHODS
The study was a Phase 2a, multicenter, double-blind, placebo-controlled, dose escalation clinical trial. Patients with refractory neuropathic pain and advanced cancer were randomly assigned 2:1 to receive a maximum of eight single escalating doses of KRN5500 or placebo, ranging from 0.6 to 2.2 mg/m(2). The primary objective was safety and tolerability. The secondary objective was efficacy, measured by change in average pain intensity on a 0-10 numeric rating scale administered one week after the patient's final dose.


RESULTS
Nineteen patients received treatment (KRN5500 n=12; placebo n=7). The most frequently reported adverse events were gastrointestinal symptoms, which were more frequent and severe with KRN5500 than placebo; two (17%) KRN5500 patients discontinued the study because of nausea and vomiting. At study endpoint, KRN5500 exhibited a significant median decrease in pain intensity from baseline of 24% compared with 0% for placebo (P=0.03). The median for largest weekly reduction in target pain intensity was 29.5% for KRN5500 and 0% for placebo patients (P=0.02).


CONCLUSION
This proof-of-concept study for KRN5500 in patients with advanced cancer and any type of neuropathic pain found gastrointestinal adverse events to be the predominant safety concern. The results also provided the first indication of clinical and statistical efficacy in reducing pain intensity.
Longitudinal assessment of neuropathy in type 1 diabetes using novel ophthalmic markers (LANDMark): study design and baseline characteristics.

AIMS
Corneal nerve morphology and corneal sensation threshold have recently been explored as potential surrogate markers for the evaluation of diabetic neuropathy. We present the baseline findings of the 'Longitudinal Assessment of Neuropathy in type 1 Diabetes using novel ophthalmic Markers'(LANDMark) study.


METHODS
The LANDMark study is a 4-year, two-site, natural history study of three participant groups: type 1 diabetes with neuropathy (T1W), type 1 diabetes without neuropathy (T1WO) and control participants without diabetes or neuropathy. All participants undergo a detailed annual assessment of neuropathy including corneal nerve parameters measured using corneal confocal microscopy and corneal sensitivity measured using non-contact corneal aesthesiometry.


RESULTS
76 T1W, 166 T1WO and 154 control participants were enrolled into the study. Corneal sensation threshold was significantly higher (i.e., sensitivity was lower) in T1W (1.0±1.1mbars) than T1WO (0.7±0.7mbars) and controls (0.6±0.4mbars) (p<0.001), with no difference between T1WO and controls. Corneal nerve fibre length was lower in T1W (14.0±6.4mm/mm(2)) compared to T1WO (19.1±5.8mm/mm(2)) and controls (23.2±6.3mm/mm(2)) (p<0.001). Corneal nerve fibre length was lower in T1WO compared to controls.


CONCLUSIONS
The LANDMark baseline findings confirm a reduction in corneal sensitivity only in Type 1 patients with neuropathy. However, corneal nerve fibre length is reduced in Type 1 patients without neuropathy with an even greater deficit in Type 1 patients with neuropathy.
Network Forensics Analysis

A network’s physical layer is deceptively quiet. Hub lights blink in response to network traffic, but do little to convey the range of information that the network carries. Analysis of the individual traffic flows and their content is essential to a complete understanding of network usage. Many tools let you view traffic in real time, but real-time monitoring at any level requires significant human and hardware resources, and doesn’t scale to networks larger than a single workgroup. It is generally more practical to archive all traffic and analyze subsets as necessary. This process is known as reconstructive traffic analysis, or network forensics.1 In practice, it is often limited to data collection and packetlevel inspection; however, a network forensics analysis tool (NFAT) can provide a richer view of the data collected, allowing you to inspect the traffic from further up the protocol stack.2 The IT industry’s ever-growing concern with security is the primary motivation for network forensics. A network that has been prepared for forensic analysis is easy to monitor, and security vulnerabilities and configuration problems can be conveniently identified. It also allows the best possible analysis of security violations. Most importantly, analyzing a complete record of your network traffic with the appropriate reconstructive tools provides context for other breach-related events. For example, if your analysis detects a user account and its Pretty Good Privacy (PGP, www.pgp.com/index.php) keys being compromised, good practice requires you to review all subsequent activity by that user, or involving those keys. In some industries, laws such as the Health Insurance Portability and Accountability Act (HIPAA, http://cms.hhs.gov/hipaa) regulate monitoring the flow of information. While it is often difficult to balance what is required by law and what is technically feasible, a forensic record of network traffic is a good first step. Security and legal concerns are not the only reasons to want a fuller understanding of your network traffic, however. Forensics tool users have reported many other applications. If your mail server has lost several hours’ or days’ worth of received messages and traditional backup methods have failed, you can recover the messages from the recorded traffic. Similarly, the forensics record allows unhurried analysis of anomalies such as traffic spikes or application errors that might otherwise have remained hearsay.
Non-Invasive Assessment of Hepatic Steatosis in Patients with NAFLD Using Controlled Attenuation Parameter and 1H-MR Spectroscopy

INTRODUCTION
Non-invasive assessment of steatosis and fibrosis is of growing relevance in non-alcoholic fatty liver disease (NAFLD). 1H-Magnetic resonance spectroscopy (1H-MRS) and the ultrasound-based controlled attenuation parameter (CAP) correlate with biopsy proven steatosis, but have not been correlated with each other so far. We therefore performed a head-to-head comparison between both methods.


METHODS
Fifty patients with biopsy-proven NAFLD and 15 healthy volunteers were evaluated with 1H-MRS and transient elastography (TE) including CAP. Steatosis was defined according to the percentage of affected hepatocytes: S1 5-33%, S2 34-66%, S3 ≥67%.


RESULTS
Steatosis grade in patients with NAFLD was S1 36%, S2 40% and S3 24%. CAP and 1H-MRS significantly correlated with histopathology and showed comparable accuracy for the detection of hepatic steatosis: areas under the receiver-operating characteristics curves were 0.93 vs. 0.88 for steatosis ≥S1 and 0.94 vs. 0.88 for ≥S2, respectively. Boot-strapping analysis revealed a CAP cut-off of 300 dB/m for detection of S2-3 steatosis, while retaining the lower cut-off of 215 dB/m for the definition of healthy individuals. Direct comparison between CAP and 1H-MRS revealed only modest correlation (total cohort: r = 0.63 [0.44, 0.76]; NAFLD cases: r = 0.56 [0.32, 0.74]). For detection of F2-4 fibrosis TE had sensitivity and specificity of 100% and 98.1% at a cut-off value of 8.85 kPa.


CONCLUSION
Our data suggest a comparable diagnostic value of CAP and 1H-MRS for hepatic steatosis quantification. Combined with the simultaneous TE fibrosis assessment, CAP represents an efficient method for non-invasive characterization of NAFLD. Limited correlation between CAP and 1H-MRS may be explained by different technical aspects, anthropometry, and presence of advanced liver fibrosis.
Separate-and-Conquer Rule Learning

This paper is a survey of inductive rule learning algorithms that use a separate-and-conquer strategy. This strategy can be traced back to the AQ learning system and still enjoys popularity as can be seen from its frequent use in inductive logic programming systems. We will put this wide variety of algorithms into a single framework and analyze them along three different dimensions, namely their search, language and overfitting avoidance biases.
The Rise of the City: Adam Smith Versus Henri Pirenne

In recent years a great deal has been written about the problems and processes of economic growth, particularly as they pertain to the econom? ically less developed countries of the world. At the same time, much less attention has been paid to the intellectual legacies of these contemporary theories of economic growth. Consequently, there is some danger of mis? placed emphasis on the contributions of the forerunners in this area of intellectual thought. A good illustration may be the considerable attention given to Henri Pirenne's theory of urban-economic growth,1 while the strikingly similar theory developed by Adam Smith at least a hundred and twenty-five years earlier has been neglected.2 Actually there was little that was new in Pirenne's theory of urban economic development. Not only had Smith presented the same ideas, along with some basic historical analysis in The Wealth of Nations, he also developed his concepts and reasoning in a much more systematic, analytical manner.3 In retrospect, it seems that all Pirenne did was to add a bit of historical evidence to Smith's model of economic-historical growth. Perhaps, had the famous historian been aware of the famous economist's work, he might have taken quite a different approach to the revival of commerce, towns, and general economic growth during the period of the tenth through the thirteenth centuries. The purposes of this paper, therefore, are to place Pirenne's and Smith's respective contribu? tions in a new perspective in this small part of the history of intellectual thought and, in so doing, to state Smith's theory as explicitly as possible.
A robust human activity recognition system using smartphone sensors and deep learning

In last few decades, human activity recognition grabbed considerable research attentions from a wide range of pattern recognition and human-computer interaction researchers due to its prominent applications such as smart home health care. For instance, activity recognition systems can be adopted in a smart home health care system to improve their rehabilitation processes of patients. There are various ways of using different sensors for human activity recognition in a smartly controlled environment. Among which, physical human activity recognition through wearable sensors provides valuable information about an individual’s degree of functional ability and lifestyle. In this paper, we present a smartphone inertial sensors-based approach for human activity recognition. Efficient features are first extracted from raw data. The features include mean, median, autoregressive coefficients, etc. The features are further processed by a kernel principal component analysis (KPCA) and linear discriminant analysis (LDA) to make them more robust. Finally, the features are trained with a Deep Belief Network (DBN) for successful activity recognition. The proposed approach was compared with traditional expression recognition approaches such as typical multiclass Support Vector Machine (SVM) and Artificial Neural Network (ANN) where it outperformed them. Keywords— Activity Recognition, Sensors, Smartphones, Deep Belief Network.
Recent Research Advances in the Glycine-xxx-Glycine Motif of Mammalian Prion Proteins

Prion diseases such as Creutzfeldt–Jakob disease (CJD) in humans and bovine spongiform encephalopathy (‘mad-cow’ disease) in cattle are invariably fatal neurodegenerative diseases. Prions differ from conventional infectious agents in being highly resistant to treatments that destroy the nucleic acids found in bacteria and viruses. The infectious prion is thought to be an abnormally folded isoform (PrPSc) of a host protein known as the prion protein (PrPC). The highly conserved glycine-zipper region PrPC (119-131) of mammalian prion proteins, consisting of 3 repeats GAVVGGLGGYMLG of the GxxxG protein-protein interaction motif (two glycines separated by any three residues), plays a crucial role in the formation or conversion of PrPSc from PrPC. This article will briefly review recent research advances in this motif.