Miracle-dz/UniFAR-FTUs huggingface dataset:
Causal Inference in Hybrid Intervention Trials Involving Treatment Choice

Randomized allocation of treatments is a cornerstone of experimental design but has drawbacks when a limited set of individuals are willing to be randomized, or the act of randomization undermines the success of the treatment. Choice-based experimental designs allow a subset of the participants to choose their treatments. We discuss here causal inferences for hybrid experimental designs in which some participants are randomly allocated to treatments and others receive their treatment preference. This work was motivated by the Women Take Pride (WTP) study, a doubly randomized preference trial (DRPT) that assessed behavioral interventions for women with heart disease. We propose a model for estimating the causal effects in the subpopulations defined by treatment preferences, and thus preference effects. We describe an EM algorithm for computing maximum likelihood estimates of the model parameters. We illustrate the method by analyzing sickness impact profile (SIP) scores and treatment adherence in the WTP data. Our results show some evidence that SIP scores were improved when women received their preferred treatment and strong preference effects on program adherence; that is, women assigned to their preferred treatment were more likely to adhere to the program. We also provide a framework for assessing the DRPT and other hybrid trial designs and discuss some alternative designs from the perspective of the strength of assumptions required to make causal inferences. Please see the supplemental material for a correction to this article.
Digital Technology Distraction for Acute Pain in Children: A Meta-analysis

This is a systematic review of digital technology distraction for children’s pain suggesting that health care providers should consider digital and nondigital distractors to reduce procedural pain and distress. BrightcoveDefaultPlayer10.1542/6138649155001PEDS-VA_2019-1139 Video Abstract CONTEXT: Digital distraction is being integrated into pediatric pain care, but its efficacy is currently unknown. OBJECTIVE: To determine the effect of digital technology distraction on pain and distress in children experiencing acutely painful conditions or procedures. DATA SOURCES: Medline, Embase, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature, PsycINFO, Institute of Electrical and Electronics Engineers Xplore, Ei Compendex, Web of Science, and gray literature sources. STUDY SELECTION: Quantitative studies of digital technology distraction for acutely painful conditions or procedures in children. DATA EXTRACTION: Performed by 1 reviewer with verification. Outcomes were child pain and distress. RESULTS: There were 106 studies (n = 7820) that reported on digital technology distractors (eg, virtual reality and video games) used during common procedures (eg, venipuncture, dental, and burn treatments). No studies reported on painful conditions. For painful procedures, digital distraction resulted in a modest but clinically important reduction in self-reported pain (standardized mean difference [SMD] −0.48; 95% confidence interval [CI] −0.66 to −0.29; 46 randomized controlled trials [RCTs]; n = 3200), observer-reported pain (SMD −0.68; 95% CI −0.91 to −0.45; 17 RCTs; n = 1199), behavioral pain (SMD −0.57; 95% CI −0.94 to −0.19; 19 RCTs; n = 1173), self-reported distress (SMD −0.49; 95% CI −0.70 to −0.27; 19 RCTs; n = 1818), observer-reported distress (SMD −0.47; 95% CI −0.77 to −0.17; 10 RCTs; n = 826), and behavioral distress (SMD −0.35; 95% CI −0.59 to −0.12; 17 RCTs; n = 1264) compared with usual care. LIMITATIONS: Few studies directly compared different distractors or provided subgroup data to inform applicability. CONCLUSIONS: Digital distraction provides modest pain and distress reduction for children undergoing painful procedures; its superiority over nondigital distractors is not established. Context, preferences, and availability should inform the choice of distractor.
Bounded Swipe: Swipe Gesture Inside a Target

Touch input has the problem that the input vocabulary is limited. In this paper, we propose the bounded swipe as a new touch gesture for solving this problem. In the bounded swipe, which extends the commonly used swipe action, the start and end points are inside a target. To test the feasibility of this gesture, we first investigated whether a bounded swipe is ever performed accidentally when a user swipes normally on a target; in 99.2% of swipes performed, the end point of the swipe was outside the target. Under the bounded swipe, the success rate was 96.7%. Therefore, the bounded swipe is a touch gesture that does not conflict with the conventional swipe.
Effect of Feature Hashing on Fair Classification

Learning new representations of data to reduce correlation with sensitive attributes is one method to tackle algorithmic bias. In this paper, we explore the possibility of using feature hashing as a method for learning new representations of data for fair classification. Using Difference of Equal Odds as our metric to measure fairness, we observe that using feature hashing on the Adult Dataset leads to 5.4x improvement in metric score while losing an accuracy of 6.1% compared to when the data is used as is.
Histological and genetic characteristics associated with the seed-shattering habit of weedy rice (Oryza sativa L.) from Okayama, Japan

We aimed to elucidate the molecular nature of the seed-shattering habit of weedy rice Oryza sativa L. in Okayama Prefecture, Japan, which seems to be an “off-type” of the main rice varieties in Okayama. We performed time-course analyses of breaking tensile strength (BTS) and analyzed the histological features of pedicels; we also genotyped the seed-shattering genes qSH1 and sh4 of weedy rice accessions and rice cultivars. The BTS of weedy accessions and cultivars began to decrease simultaneously at three weeks after heading. The weedy accessions showed complete loss of BTS and grain dispersal at five weeks after heading. In contrast, the cultivars maintained a certain degree of BTS and did not exhibit grain dispersal. Pedicel structures, which affect BTS, differed between the weedy accessions and the cultivars. The weedy accessions had complete and cracked abscission layers, while the cultivars had incomplete and uncracked abscission layers; however, the qSH1 and sh4 sequences that influence the formation of the abscission layer showed no differences between the weedy accessions and cultivars. We surmise that the shattering habit of weedy rice in Okayama is caused by formation and degeneration of the abscission layer, mediated by unidentified shattering-related gene(s).
Preparation, Characterization and Application of a Low Water-Sensitive Artemisia sphaerocephala Krasch. Gum Intelligent Film Incorporated with Anionic Cellulose Nanofiber as a Reinforcing Component

A low-water-sensitive Artemisia sphaerocephala Krasch. gum (ASKG) based intelligent film was developed. Red cabbage extracts (RCE) was selected as a natural pH-sensitive indicator, and anionic cellulose nanofiber (ACNF) was added as a hydrophobic and locking host. The zeta potential, rheology, Fourier-transform infrared spectroscopy, X-ray diffractometry, and release results indicated that the RCE was locked by the ACNF via electrostatic interactions, moreover, broke the original complicated network and ordered arrangement of polymer molecules in the developed intelligent films. RCE addition decreased the tensile strength, oxygen, and water vapor barrier properties and light transmission of the developed intelligent films, while increasing the elongation at break. The films could respond to buffer solutions and NH3 through different color changes. The developed intelligent film was hydrophobic, which could precisely detect the freshwater shrimp freshness in real time via color changes, which indicated that the films have potential in intelligent packaging and gas-sensing label fields.
Educational attainment is associated with unconditional helping behaviour

Abstract Abstract Altruism is a universal human trait, but little is known about its within-population variation. Socio-economic status (SES) has been found to positively impact altruism, but the specific socio-economic variables behind this relationship have remained elusive. This study aimed to determine which facets of SES predict altruism using a lost letter paradigm and a novel lost letter method. Six hundred letters (half dropped on the pavement, half sent to residential addresses) were distributed in 20 suburbs of Perth (Australia) differing in socio-economic variables. Letters distributed in high-SES neighbourhoods were more likely to be returned than letters distributed in low-SES neighbourhoods. Educational attainment and occupation status were the specific socio-economic variables underlying this association, while economic resources and crime rate were not associated with the likelihood of a letter being returned. These results suggest that altruism blossoms in neighbourhoods that are populated with highly educated individuals working in high-status jobs. The relationship between education and prosocial inclinations may be mediated by cognitive ability, self-control and high levels of socialization. Having experienced sustained exposure to norm-abiding models, more educated people may also be better at internalizing cultural norms of helping behaviour, thus creating a more altruistic environment where they reside.
Accuracy and clinical utility of comprehensive dysphagia screening assessments in acute stroke: A systematic review and meta-analysis.

INTRODUCTION Nurses and other non-specialists in dysphagia are often trained to screen swallowing post-stroke. There are many basic tools that test water only, they are usually conservative and patients that fail the test remain nil by mouth until a speech and language therapy assessment. More comprehensive tests also allow non-specialists to recommend modified oral intake. Little is known about the accuracy, clinical utility and cost effectiveness of these tests. METHODS Following PRISMA guidelines, a systematic review was conducted to describe comprehensive swallowing tests that are available for use in acute stroke by nurses or other non-specialists in dysphagia. A meta-analysis was performed to evaluate accuracy and considered their clinical utility. Searches and analyses, conducted by two reviewers, included MEDLINE, EMBASE, trial registries, and grey literature up to December 2018. Validated studies were assessed for quality and risk of bias using QUADAS-2. RESULTS Twenty studies were included, describing five different tests, three of which had undergone validation. The tests varied in content, recommendations and use. There was no test superior in accuracy and clinical utility. Three studies validating the Gugging Swallow Screen provided sufficient data for meta-analysis, demonstrating high sensitivity; 96% (95%CI 0.90-0.99) but low specificity, 65% (95%CI 0.47-0.79) in line with many water swallow tests. Results should be interpreted with caution as study quality and applicability to the acute stroke population was poor. CONCLUSIONS There is no comprehensive nurse dysphagia assessment tool that has robustly demonstrated good accuracy, clinical utility and cost effectiveness in acute stroke. RELEVANCE TO CLINICAL PRACTICE Nurses and other clinicals can develop competencies in screening swallowing and assessing for safe oral intake in those with post stroke dysphagia. It is important to use a validated assessment tool that demonstrates good accuracy, clinical utility and cost effectiveness.
Degenerative Cervical Myelopathy : Introduction , Rationale , and Scope

Degenerative cervical myelopathy (DCM) is a progressive spine disease and the most common cause of spinal cord dysfunction in adults worldwide. Patients with DCM may present with common signs and symptoms of neurological dysfunction, such as paresthesia, abnormal gait, decreased hand dexterity, hyperreflexia, increased tone, and sensory dysfunction. Clinicians across several specialties encounter patients with DCM, including primary care physicians, rehabilitation specialists, therapists, rheumatologists, neurologists, and spinal surgeons. Currently, there are no guidelines that outline how to best manage patients with mild (defined as a modified Japanese Orthopedic Association (mJOA) score of 15-17), moderate (mJOA 1⁄4 12-14), or severe (mJOA 11) myelopathy, or nonmyelopathic patients with evidence of cord compression. This guideline provides evidencebased recommendations to specify appropriate treatment strategies for these populations. The intent of our recommendations is to (1) help identify patients at high risk of neurological deterioration, (2) define the role of nonoperative and operative management in each patient population, and (3) determine which patients are most likely to benefit from surgical intervention. The ultimate goal of these guidelines is to improve outcomes and reduce morbidity in patients with DCM by promoting standardization of care and encouraging clinicians to make evidence-informed decisions.
Selection of resistance sources to common bean anthracnose by field phenotyping and DNA marker-assisted screening

The main goal of this work was to select resistance sources to common bean anthracnose by field phenotyping and DNA marker-assisted screening. Fifty-five common bean genotypes, including differential varieties, characterized resistance sources, elite lines, cultivars and controls, were evaluated in a field inoculation trial and screened with SCAR markers linked to resistance genes that are important in Brazil. The field trial was carried out in Santo Antonio de Goias, GO, Brazil, during the fall/winter growing season of 2014, using artificial inoculation with a mixture of six races of Colletotrichum lindemuthianum, selected based on their high virulence and prevalence in Brazil. Amplification reactions with the SCAR markers previously identified as linked to important anthracnose resistance genes on Brazil followed standard procedures. Twenty-eight of the 58 genotypes were resistant to anthracnose (mean severity score ≤ 3.5). Ten of these 28 resistant genotypes stood out because they presented a mean anthracnose severity score of 1.0. Four of the six SCAR markers tested shown to be useful for the assisted selection of their respective target genes (SH18 and SAS13 for Co-42, SAB03 for Co-5, and SAZ20 for Co-6). Two carioca seeded elite lines were highlighted by the phenotypic and molecular screening: K10 (Co-34, Co-42, Co-5 and Co-6) and K13 (Co-4²). The phenotypic and molecular characterization of candidate resistance sources to common bean anthracnose based on their disease reaction in field inoculation trials and on the analysis with molecular markers linked to resistance genes has shown to be a useful strategy. These results aid in the selection of donor parents and resistant lines to be preferably explored by common bean breeding programs in Brazil.
First-principles based multiscale model of piezoelectric nanowires with surface effects

A continuum model of nanowires incorporating surface piezoelectricity is proposed which extends the electric enthalpy energy with surface terms. The corresponding equations are solved by a numerical method using finite elements technique. A methodology is introduced to compute the surface piezoelectric coefficients by first-principles calculations through the Berry phase theory. We provide the e33s, e31s, and e15s piezoelectric coefficients of (101¯0) surfaces for hexagonal wurtzite nanowires made of GaN, ZnO, and AlN. The effective piezoelectric coefficient along the axis of the nanowire is found to increase when the diameter decreases, for the three studied materials. Finally, the solution of the continuum model is compared with large-size first-principles calculations on piezoelectric nanowires.
Chapter 2 Palette of fluorinated voltage-sensitive hemicyanine dyes

Author contributions P.Y. , C.D. A. , P.L. , C.B. , A.N. , L.S. , S.D. A. , P.K. , H.D. M. , F.S. P., and L.M. L. designed research; P.Y. , C.D. A. , W.L. Z. , P.L. , C.B. , A.N. , J.L. , and L.S. performed research; P.Y. contributed new reagents/analytic tools; P.Y. , C.D. A. , W.L. Z. , P.L. , C.B. , A.N. , J.L. , L.S. , S.D. A. , P.K. , H.D. M. , F.S. P., and L.M. L. analyzed data; and P.L. , C.B. , A.N. , L.S. , P.K. , and L.M. L. wrote the paper.
CROSS-PLATFORM RECOGNISATION OF UNKNOWN IDENTICAL USERS IN MULTIPLE SOCIAL MEDIA NETWORKS

From very recent past years have witnessed the requirement and evolution of a vibrant research Crew on a large variation of online Social Media Network (SMN) platforms. Recognizing anonymous, same yet identical users among multiple SMNs is still a major problem. Clearly, saying that cross-platform exploration may help solve too many problems in social computing in both theory and applications. Up to now public profiles can be duplicated and easily impersonated by users with different purposes, most current user identification resolutions, which mainly focus on text mining of users ‘public profiles, fragile. Some studies have attempted to match users based on the location and timing of user content as well as writing style. However, the locations are sparse in the majority of SMNs, and writing style is difficult to discern from the short sentences of leading SMNs such as, Sina Micro blog and Twitter. Moreover, up to now online SMNs are quite symmetric, existing user identification schemes based on network structure are not effective. The real-world friend cycle is highly individual and virtually no two users share a congruent friend cycle. So that, it is more accurate to use a friendship structure to analyze cross-platform SMNs. Up to now anonymous users were influenced to set up similar friendship structures in the different SMNs, here they proposed the Friend Relationship-Based User Identification (FRUI) algorithm. FRUI Algorithm calculates a match degree for all candidate User Matched Pairs (UMPs) only, UMP with top ranks are considered as identical users. We also developed two propositions to improve the efficiency of the algorithm. The Results of these extensive experiments demonstrate that FRUI performs much better than current network structure-based algorithms.
Comparative chemistry and biological properties of the solid residues from hydrodistillation of Spanish populations of Rosmarinus officinalis L.

Solid residues from the hydrodistillation of selected Spanish populations of rosemary (Rosmarinus officinalis L.) have been analyzed for their polyphenol composition, and antioxidant and bioplaguicide activities. The objective was to evaluate and select the most suitable plant materials as sources of natural antioxidants and crop protectants. Total polyphenol content and polyphenol composition of rosemary populations were very dependent on the growth location: populations from Aranjuez showed a higher content of total polyphenols and were richer in rosmarinic acid as compared with their equivalent populations from Cuenca, whereas these latter were characterized by an overall higher content in genkwanin and carnosol. Most of the antioxidant activities were highly correlated with the total content of polyphenols although some polyphenols like carnosic acid and carnosol seemed to favor such activities. The extracts from R. officinalis were strong antifeedants against Leptinotarsa decemlineata Say and moderate against Spodoptera littoralis Boisd and Myzus persicae Sulzer, according to their feeding ecologies. The biological effects of the active samples cannot be accounted by their chemical composition, suggesting additive or synergistic effects. Both the phytotoxic and stimulating effects on Lactuca sativa L. , and Lolium perenne L. leaf and/or root growth were observed.
Low-Complexity Rate-Distortion Optimization of Sampling Rate and Bit-Depth for Compressed Sensing of Images

Compressed sensing (CS) offers a framework for image acquisition, which has excellent potential in image sampling and compression applications due to the sub-Nyquist sampling rate and low complexity. In engineering practices, the resulting CS samples are quantized by finite bits for transmission. In circumstances where the bit budget for image transmission is constrained, knowing how to choose the sampling rate and the number of bits per measurement (bit-depth) is essential for the quality of CS reconstruction. In this paper, we first present a bit-rate model that considers the compression performance of CS, quantification, and entropy coder. The bit-rate model reveals the relationship between bit rate, sampling rate, and bit-depth. Then, we propose a relative peak signal-to-noise ratio (PSNR) model for evaluating distortion, which reveals the relationship between relative PSNR, sampling rate, and bit-depth. Finally, the optimal sampling rate and bit-depth are determined based on the rate-distortion (RD) criteria with the bit-rate model and the relative PSNR model. The experimental results show that the actual bit rate obtained by the optimized sampling rate and bit-depth is very close to the target bit rate. Compared with the traditional CS coding method with a fixed sampling rate, the proposed method provides better rate-distortion performance, and the additional calculation amount amounts to less than 1%.
Scan B-statistic for kernel change-point detection

Abstract Detecting the emergence of an abrupt change-point is a classic problem in statistics and machine learning. Kernel-based nonparametric statistics have been used for this task, which enjoys fewer assumptions on the distributions than the parametric approach and can handle high-dimensional data. In this article, we focus on the scenario when the amount of background data is large and propose a computationally efficient kernel-based statistics for change-point detection, inspired by the recently developed B-statistics. A novel theoretical result of the article is the characterization of the tail probability of these statistics using the change-of-measure technique, which focuses on characterizing the tail of the detection statistics rather than obtaining its asymptotic distribution under the null distribution. Such approximations are crucial to controlling the false alarm rate, which corresponds to the average run length in online change-point detection. Our approximations are shown to be highly accurate. Thus, they provide a convenient way to find detection thresholds for online cases without the need to resort to the more expensive simulations. We show that our methods perform well on both synthetic data and real data.
Human Emotion Recognition: Review of Sensors and Methods

Automated emotion recognition (AEE) is an important issue in various fields of activities which use human emotional reactions as a signal for marketing, technical equipment, or human–robot interaction. This paper analyzes scientific research and technical papers for sensor use analysis, among various methods implemented or researched. This paper covers a few classes of sensors, using contactless methods as well as contact and skin-penetrating electrodes for human emotion detection and the measurement of their intensity. The results of the analysis performed in this paper present applicable methods for each type of emotion and their intensity and propose their classification. The classification of emotion sensors is presented to reveal area of application and expected outcomes from each method, as well as their limitations. This paper should be relevant for researchers using human emotion evaluation and analysis, when there is a need to choose a proper method for their purposes or to find alternative decisions. Based on the analyzed human emotion recognition sensors and methods, we developed some practical applications for humanizing the Internet of Things (IoT) and affective computing systems.