Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact of social constraints on insomnia among African‐American breast cancer survivors: The mediating role of fear of recurrence

Insomnia is a significant concern among African‐American breast cancer survivors (BCS). Social constraints (SC)—receiving unsupportive or critical responses when expressing trauma‐related emotions—and fear of recurrence (FOR) have been associated with insomnia. We examined FOR as a mediator in the relationship between SC and insomnia in African‐American BCS. We hypothesized a direct effect of SC on insomnia, and an indirect effect of SC on insomnia through FOR.
Viable populations for conservation

Abstract How many individuals are enough to ensure long term survival of a species? What are the effects of chance on demographic structure and genetic variability? How can we work together to ensure viable populations? These questions and others are explored in this excellent little book. It concentrates on theory, especially aspects of viability analysis, although there is a case study, and also examples of interagency activities. As in any book, readers can find passages that support their pre-existing views, but taken as a whole this one provides considerable balance. The editor admits that in places he is arguing for his personal preference. Other authors stress that many decisions in conservation biology rightly belong to the community and not just the scientists for whom this book is primarily intended.
Robust Stereo Visual Inertial Navigation System Based on Multi-Stage Outlier Removal in Dynamic Environments

Robotic mapping and odometry are the primary competencies of a navigation system for an autonomous mobile robot. However, the state estimation of the robot typically mixes with a drift over time, and its accuracy is degraded critically when using only proprioceptive sensors in indoor environments. Besides, the accuracy of an ego-motion estimated state is severely diminished in dynamic environments because of the influences of both the dynamic objects and light reflection. To this end, the multi-sensor fusion technique is employed to bound the navigation error by adopting the complementary nature of the Inertial Measurement Unit (IMU) and the bearing information of the camera. In this paper, we propose a robust tightly-coupled Visual-Inertial Navigation System (VINS) based on multi-stage outlier removal using the Multi-State Constraint Kalman Filter (MSCKF) framework. First, an efficient and lightweight VINS algorithm is developed for the robust state estimation of a mobile robot by practicing a stereo camera and an IMU towards dynamic indoor environments. Furthermore, we propose strategies to deal with the impacts of dynamic objects by using multi-stage outlier removal based on the feedback information of estimated states. The proposed VINS is implemented and validated through public datasets. In addition, we develop a sensor system and evaluate the VINS algorithm in the dynamic indoor environment with different scenarios. The experimental results show better performance in terms of robustness and accuracy with low computation complexity as compared to state-of-the-art approaches.
High-Capacity Adenoviral Vectors: Expanding the Scope of Gene Therapy

The adaptation of adenoviruses as gene delivery tools has resulted in the development of high-capacity adenoviral vectors (HC-AdVs), also known, helper-dependent or “gutless”. Compared with earlier generations (E1/E3-deleted vectors), HC-AdVs retain relevant features such as genetic stability, remarkable efficacy of in vivo transduction, and production at high titers. More importantly, the lack of viral coding sequences in the genomes of HC-AdVs extends the cloning capacity up to 37 Kb, and allows long-term episomal persistence of transgenes in non-dividing cells. These properties open a wide repertoire of therapeutic opportunities in the fields of gene supplementation and gene correction, which have been explored at the preclinical level over the past two decades. During this time, production methods have been optimized to obtain the yield, purity, and reliability required for clinical implementation. Better understanding of inflammatory responses and the implementation of methods to control them have increased the safety of these vectors. We will review the most significant achievements that are turning an interesting research tool into a sound vector platform, which could contribute to overcome current limitations in the gene therapy field.
Assessing the Influence of Buried Archaeology on Equine Locomotion Comparison with Ground Penetrating Radar Results

The aim of this trial project was to identify whether buried archaeological remains may have an influence on equine locomotion, through comparison with a non-invasive Ground Penetrating Radar (GPR) survey. This study was conducted at the world-renowned Burghley Horse Trials site, near Stamford, City of Peterborough, U.K. that has a diverse range of heritage assets throughout the wider park land centred on the Grade 1 listed Elizabethan Burghley House. The initial aim of the research was to first use geophysical survey to identify and characterise archaeological remains, and then to determine a suitable location to conduct an equine locomotion study. This trial was conducted with five event type horses with their gaits recorded through the use of three axis, wireless, Inertial Measurement Units, and high speed video capture. It was hoped that this study might indicate an association between the presence of well preserved archaeological remains and changes in the gait of the horses, similar to those shown by studies of dressage horses over different riding surfaces. The results from the equine locomotion study did demonstrate a correlation between the presence of surviving archaeological remains and the alteration in the horses’ gait and, although this is only a preliminary study, the results may well be of interest during the design and construction of equine event facilities. Geophysical survey could, for example, be considered during the design of new or alteration to existing equine courses to allow some mitigation in the location of the course with respect to any archaeological remains, or through the appropriate use of a protective artificial surface.
Evaluation of Antioxidant Activity of Alcoholic Extract from Peanut Hulls

In this article, the antioxidant activity of the crude extract from peanut hulls was tested with phosphomolybdenum complex method, the reduction of K3Fe(CN)6 and DPPH assay. The IC50 value for DPPH radical scavenging lied 14. 86μg ml-1, and 28 μg mL-1 of PHF exhibited total antioxidant activity and reducing power which were comparable to that of the ascorbic acid standard at 52.41 and 15.41 μg mL-1, respectively.
Development and Validation of a Tool to Assess the Quality of Clinical Practice Guideline Recommendations

Key Points Question Is it possible to create a tool to specifically evaluate the quality of clinical practice guideline recommendations? Findings In this cross-sectional study of 322 international stakeholders, the Appraisal of Guidelines Research and Evaluation–Recommendations Excellence (AGREE-REX) tool was developed to appraise guidelines for clinical practice. All participants rated the tool as usable and agreed that it represents a valuable addition to the clinical practice guidelines enterprise. Meaning A panel of stakeholders agrees that the AGREE-REX tool may provide information about the methodologic quality of guideline recommendations and may help in the implementation of clinical practice guidelines.
The effect of photoperiod on the circadian rhythm of mating responsiveness in the fruit fly, Dacus tryoni

ABSTRACT. The daily fluctuation in mating responsiveness of Dacus tryoni was recorded through a range of light cycles. Evidence was obtained of strict control of the fluctuation by a circadian clock. The phase setting of the fluctuation in the different light cycles was in conformity with Aschoff's (1965) generalizations about circadian rhythms, and had no relationship to overt sexual behaviour occurring during the cycles. The amplitude of the fluctuation in mating responsiveness varied between cycles, suggesting possible variation in the amplitude of the oscillation of the circadian clock.
A genetic risk assessment for prostate cancer influences patients’ risk perception and use of repeat PSA testing: a cross-sectional study in Danish general practice

Background Prostate cancer (PC) is the most common cancer among men in the western world. Genetic lifetime risk assessment could alleviate controversies about prostate specific antigen (PSA) testing for early diagnosis. Aim To determine how men interpret information about their lifetime risk for PC and how this can affect their choice of having a repeated PSA test. Design & setting A genetic test was offered for assessment of individual PC lifetime risk in general practices in Denmark, with the purpose of promoting appropriate use of PSA testing. Method Participants had a genetic lifetime risk assessment for PC diagnosis (either high or normal risk). A month after receiving the result, participants answered a questionnaire about their perceived risk of getting or dying from PC compared with other men, as well as their intentions for repeated PSA testing. Results Nearly half (44.7%) of 555 participants who received the genetic risk assessment were not aware they had a genetic test. Nevertheless, compared with men with a normal genetic risk, those with high genetic risk reported higher perceived risk for PC (mean difference of 0.74 [95% confidence interval {CI} = 0.56 to 0.96] on a 5-point scale), higher perceived risk of dying from PC (mean difference of 0.48 [95% CI = 0.29 to 0.66] on a 5-point scale), and increased intention for repeated PSA testing (mean difference of 0.48 [95% CI = 0.30 to 0.65] on a 4-point scale). Conclusion Despite low awareness and/or understanding of the test result, a high genetic risk for PC made participants more aware of their risk, and it increased their intention and probability for repeated PSA testing.
The role of measurement error on the interpretation of otolith increment width in the study of growth in larval fish

Patterns in increment widths and the associated measurement error were studied in the otoliths of radiated shanny (Ulvaria subbifurcata) larvae sampled from the field. Mean increment widths increased with larval age, whereas the relative measurement error decreased. Furthermore, the level of serial correlation in increment widths showed a clear increase with age. When measurement error was taken into consideration, the pattern of serial correlation indicates that an individual's growth increments did not show the effect of changes in local environmental conditions for at least 3 days, independent of age. Only after that period can we hope to detect the effect of environmental influences on increment widths (and by inference growth rates). The patterns of measurement error and serial correlation will have direct impacts on our ability to find the influence of environmental conditions on growth rates of individual larvae and determine patterns of selective loss in a population of larval fish.
Parallel Semantic Trajectory Similarity Join

Matching similar pairs of trajectories, called trajectory similarity join, is a fundamental functionality in spatial data management. We consider the problem of semantic trajectory similarity join (STS-Join). Each semantic trajectory is a sequence of Points-of-interest (POIs) with both location and text information. Thus, given two sets of semantic trajectories and a threshold θ, the STS-Join returns all pairs of semantic trajectories from the two sets with spatio-textual similarity no less than θ. This join targets applications such as term-based trajectory near-duplicate detection, geo-text data cleaning, personalized ridesharing recommendation, keyword-aware route planning, and travel itinerary recommendation.With these applications in mind, we provide a purposeful definition of spatio-textual similarity. To enable efficient STS-Join processing on large sets of semantic trajectories, we develop trajectory pair filtering techniques and consider the parallel processing capabilities of modern processors. Specifically, we present a two-phase parallel search algorithm. We first group semantic trajectories based on their text information. The algorithm’s per-group searches are independent of each other and thus can be performed in parallel. For each group, the trajectories are further partitioned based on the spatial domain. We generate spatial and textual summaries for each trajectory batch, based on which we develop batch filtering and trajectory-batch filtering techniques to prune unqualified trajectory pairs in a batch mode. Additionally, we propose an efficient divide-and-conquer algorithm to derive bounds of spatial similarity and textual similarity between two semantic trajectories, which enable us prune dissimilar trajectory pairs without the need of computing the exact value of spatio-textual similarity. Experimental study with large semantic trajectory data confirms that our algorithm of processing semantic trajectory join is capable of outperforming our well-designed baseline by a factor of 8–12.
Summarizing Hierarchical Multidimensional Data

Data scientists typically analyze and extract insights from large multidimensional data sets such as US census data, enterprise sales data, and so on. But before sophisticated machine learning and statistical methods are employed, it is useful to build and explore concise summaries of the data set. While a variety of summaries have been proposed over the years, the goal of creating a concise summary of multidimensional data that can provide worst-case accuracy guarantees has remained elusive. In this paper, we propose Tree Summaries, which attain this challenging goal over arbitrary hierarchical multidimensional data sets. Intuitively, a Tree Summary is a weighted "embedded tree" in the lattice that is the cross-product of the dimension hierarchies; individual data values can be efficiently estimated by looking up the weight of their unique closest ancestor in the Tree Summary. We study the problems of generating lossless as well as (given a desired worst-case accuracy guarantee a) lossy Tree Summaries. We develop a polynomial-time algorithm that constructs the optimal (i.e., most concise) Tree Summary for each of these problems; this is a surprising result given the NP-hardness of constructing a variety of other optimal summaries over multidimensional data. We complement our analytical results with an empirical evaluation of our algorithm, and demonstrate with a detailed set of experiments on real and synthetic data sets that our algorithm outperforms prior methods in terms of conciseness of summaries or accuracy of estimation.
Raw Material Characteristic Prediction for Packing Media Preparation in Canned Pineapple Production Line

The quality standard is an important, especially in the food industry. In canned pineapple production under the uncertain quality of raw materials (i.e., pineapples), preparing packing medium (PM) with a suitable degree of Brix is important because the sweetness of the canned pineapple must match with a standard degree of Brix. This paper develops a support vector machine (SVM), a machine learning technique, to predict the degree of Brix of the pineapples. Response surface method (RSM) is applied to investigate the best hyperparameters setting of SVM. For estimating the model performance, mean absolute error (MAE) is used as the measurement. Finally, the experimental results show that the SVM hyperparameters should be set that the value of C equal to −1, convergence equal to 0.001 and kernel function is anova. This setting can provide the minimum MAE which equals to 1.10.
A High-Throughput Screening System Based on Droplet Microfluidics for Glucose Oxidase Gene Libraries

Glucose oxidase (GOx) is an important industrial enzyme that can be optimized for specific applications by mutagenesis and activity-based screening. To increase the efficiency of this approach, we have developed a new ultrahigh-throughput screening platform based on a microfluidic lab-on-chip device that allows the sorting of GOx mutants from a saturation mutagenesis library expressed on the surface of yeast cells. GOx activity was measured by monitoring the fluorescence of water microdroplets dispersed in perfluorinated oil. The signal was generated via a series of coupled enzyme reactions leading to the formation of fluorescein. Using this new method, we were able to enrich the yeast cell population by more than 35-fold for GOx mutants with higher than wild-type activity after two rounds of sorting, almost double the efficiency of our previously described flow cytometry platform. We identified and characterized novel GOx mutants, the most promising of which (M6) contained a combination of six point mutations that increased the catalytic constant kcat by 2.1-fold compared to wild-type GOx and by 1.4-fold compared to a parental GOx variant. The new microfluidic platform for GOx was therefore more sensitive than flow cytometry and supports comprehensive screens of gene libraries containing multiple mutations per gene.
Conidial concentration as an important factor determining the type of prepenetration structures formed by Botrytis cinerea on leaves of French bean (Phaseolus vulgaris)

inoculations of primary leaves of French bean (Phaseolus vulgaris) with conidia of Botrytis cinerea, suspended in 0.11 or 0.28 M glucose supplemented with 0.067 M KH2PO4 or 1 mM Na-ATP as infection stimulants, yielded mostly spreading lesions. Light microscopy revealed that the fungus could develop three types of prepenetration structures from which penetration started: germ tube apices (GA) either non-swollen or appearing as an appressorium-like swelling; appressoria (HA) of different forms produced on branched germ tubes or superficial liyphae; and infection cushions (IC). These structures were also formed on leaves of cucumber and tomato. Penetration from the prepenetration structures was not markedly influenced by the glucose concentration in the inoculum or by host plant species, and varied only slightly with the isolate of B. cinerea. Penetration occurring from GA was greatly enhanced at high conidial concentrations. Low conidial concentrations, however, enhanced penetration starting from HA or IC, penetration from these structures also being dependent on the nature of the stimulant added to the glucose in the inoculum. The high proportion of GA in inocula with a high conidial concentration was associated with a rapid penetration and a rapid formation of spreading lesions.
Neighbor Profile: Bagging Nearest Neighbors for Unsupervised Time Series Mining

Unsupervised time series mining has been attracting great interest from both academic and industrial communities. As the two most basic data mining tasks, the discoveries of frequent/rare subsequences have been extensively studied in the literature. Specifically, frequent/rare subsequences are defined as the ones with the smallest/largest 1-nearest neighbor distance, which are also known as motif/discord. However, discord fails to identify rare subsequences when it occurs more than once in the time series, which is widely known as the twin freak problem. This problem is just the "tip of the iceberg" due to the 1-nearest neighbor distance based definitions. In this work, we for the first time provide a clear theoretical analysis of motif/discord as the 1-nearest neighbor based nonparametric density estimation of subsequence. Particularly, we focus on matrix profile, a recently proposed mining framework, which unifies the discovery of motif and discord under the same computing model. Thereafter, we point out the inherent three issues: low-quality density estimation, gravity defiant behavior, and lack of reusable model, which deteriorate the performance of matrix profile in both efficiency and subsequence quality.To overcome these issues, we propose Neighbor Profile to robustly model the subsequence density by bagging nearest neighbors for the discovery of frequent/rare subsequences. Specifically, we leverage multiple subsamples and average the density estimations from subsamples using adjusted nearest neighbor distances, which not only enhances the estimation robustness but also realizes a reusable model for efficient learning. We check the sanity of neighbor profile on synthetic data and further evaluate it on real-world datasets. The experimental results demonstrate that neighbor profile can correctly model the subsequences of different densities and shows superior performance significantly over matrix profile on the real-world arrhythmia dataset. Also, it is shown that neighbor profile is efficient for massive datasets.
Magnetostrictive Performance of Electrodeposited TbxDy(1−x)Fey Thin Film with Microcantilever Structures

The microfabrication with a magnetostrictive TbxDy(1−x)Fey thin film for magnetic microactuators is developed, and the magnetic and magnetostrictive actuation performances of the deposited thin film are evaluated. The magnetostrictive thin film of TbxDy(1−x)Fey is deposited on a metal seed layer by electrodeposition using a potentiostat in an aqueous solution. Bi-material cantilever structures with the Tb0.36Dy0. 64Fe1.9 thin-film are fabricated using microfabrication, and the magnetic actuation performances are evaluated under the application of a magnetic field. The actuators show large magnetostriction coefficients of approximately 1250 ppm at a magnetic field of 11000 Oe.
Carnosic acid exhibits antiproliferative and proapoptotic effects in tumoral NCI-H460 and nontumoral IMR-90 lung cells

ABSTRACT Carnosic acid (CA) is a phenolic diterpene with many important biological activities including antimicrobial, antioxidant, anti-inflammatory properties, and anti-proliferative properties. The aim of the present study was to investigate cytotoxic activity, cell cycle, apoptotic, and molecular effects attributed to CA in non-tumoral IMR-90 (human fetal lung fibroblasts), as well as tumoral NCI-H460 (human non–small-cell lung cancer) cell lines. Cell proliferation was evaluated by Real-Time Cell Analysis system, while apoptosis and cell cycle were assessed using flow cytometry. RT-qPCR was used to estimate the relative expression of genes involved in cell cycle regulation, DNA damage and repair, and apoptosis induction. CA inhibited proliferation of IMR-90 and NCI-H460 cells via cell cycle arrest at G0/G1 and G2/M phases, according to the treatment concentration. The mRNA levels of genes encoding cyclins A2, B1, and B2 were downregulated in response to CA treatment of IMR-90 cells. Apoptosis was induced and proapoptotic gene PUMA was upregulated in both cell lines. mRNA levels of genes ATR, CCND1, CHK1, CHK2, MYC, GADD45A, H2AFX, MTOR, TP53, and BCL2, CASP3 were not markedly changed following CA treatments. Although CA exerted antiproliferative activity against NCI-H460 tumor cells, this phytochemical induced toxic effects in non-tumoral cells, and thus needs to be considered carefully prior to pharmacological use therapeutically.