Miracle-dz/UniFAR-FTUs huggingface dataset:
Patterns of User Engagement With the Mobile App, Manage My Pain: Results of a Data Mining Investigation

Background Pain is one of the most prevalent health-related concerns and is among the top 3 most common reasons for seeking medical help. Scientific publications of data collected from pain tracking and monitoring apps are important to help consumers and healthcare professionals select the right app for their use. Objective The main objectives of this paper were to (1) discover user engagement patterns of the pain management app, Manage My Pain, using data mining methods; and (2) identify the association between several attributes characterizing individual users and their levels of engagement. Methods User engagement was defined by 2 key features of the app: longevity (number of days between the first and last pain record) and number of records. Users were divided into 5 user engagement clusters employing the k-means clustering algorithm. Each cluster was characterized by 6 attributes: gender, age, number of pain conditions, number of medications, pain severity, and opioid use. Z tests and chi-square tests were used for analyzing categorical attributes. Effects of gender and cluster on numerical attributes were analyzed using 2-way analysis of variances (ANOVAs) followed up by pairwise comparisons using Tukey honest significant difference (HSD). Results The clustering process produced 5 clusters representing different levels of user engagement. The proportion of males and females was significantly different in 4 of the 5 clusters (all P ≤.03). The proportion of males was higher than females in users with relatively high longevity. Mean ages of users in 2 clusters with high longevity were higher than users from other 3 clusters (all P <.001). Overall, males were significantly older than females (P <.001). Across clusters, females reported more pain conditions than males (all P <.001). Users from highly engaged clusters reported taking more medication than less engaged users (all P <.001). Females reported taking a greater number of medications than males (P =.04). In 4 of 5 clusters, the percentage of males taking an opioid was significantly greater (all P ≤.05) than that of females. The proportion of males with mild pain was significantly higher than that of females in 3 clusters (all P ≤.008). Conclusions Although most users of the app reported being female, male users were more likely to be highly engaged in the app. Users in the most engaged clusters self-reported a higher number of pain conditions, a higher number of current medications, and a higher incidence of opioid usage. The high engagement by males in these clusters does not appear to be driven by pain severity which may, in part, be the case for females. Use of a mobile pain app may be relatively more attractive to highly-engaged males than highly-engaged females, and to those with relatively more complex chronic pain problems.
Nanowire nanoelectronics: Building interfaces with tissue and cells at the natural scale of biology

The interface between nanoscale electronic devices and biological systems enables interactions at length scales natural to biology, and thus should maximize communication between these two diverse yet complementary systems. Moreover, nanostructures and nanostructured substrates show enhanced coupling to artificial membranes, cells, and tissue. Such nano–bio interfaces offer better sensitivity and spatial resolution as compared to conventional planar structures. In this work, we will report the electrical properties of silicon nanowires (SiNWs) interfaced with embryonic chicken hearts and cultured cardiomyocytes. We developed a scheme that allowed us to manipulate the nanoelectronic to tissue/cell interfaces while monitoring their electrical activity. In addition, by utilizing the bottom-up approach, we extended our work to the subcellular regime, and interfaced cells with the smallest reported device ever and thus exceeded the spatial and temporal resolution limits of other electrical recording techniques. The exceptional synthetic control and flexible assembly of nanowires (NWs) provides powerful tools for fundamental studies and applications in life science, and opens up the potential of merging active transistors with cells such that the distinction between nonliving and living systems is blurred.
Analyzing trusted platform communication ?

In this paper we discuss the analysis of trusted platform communication. While the trusted platform module itself is considered reasonably tamper resistant, the communication channel between this module and the rest of the trusted platform turns out to be comparatively insecure. Passive attacks can be mounted on the communication interface with fairly inexpensive equipment and allow eavesdropping of critical information. Performing active manipulation on the communication bus could provide an even stronger attack scenario, resulting in a circumvention of the whole chain of trust provided by trusted platforms. At this stage, our research has been limited to passive attacks.
Robust estimation of human body kinematics from video

Addresses the problem of estimating human body motion from video. Its main contribution is the introduction of a robust optimization framework that leads to reliable and accurate body tracking and posture recovery. The proposed approach is resistant to occlusions and demonstrates that it is possible to treat different problems arising in human motion analysis in a unified way without using many decision thresholds. The implemented system requires only a standard CCD camera and no special markers on the body. We present experimental results showing the reliability of the implemented tracker.
An Intraoperative Visualization System Using Hyperspectral Imaging to Aid in Brain Tumor Delineation

Hyperspectral imaging (HSI) allows for the acquisition of large numbers of spectral bands throughout the electromagnetic spectrum (within and beyond the visual range) with respect to the surface of scenes captured by sensors. Using this information and a set of complex classification algorithms, it is possible to determine which material or substance is located in each pixel. The work presented in this paper aims to exploit the characteristics of HSI to develop a demonstrator capable of delineating tumor tissue from brain tissue during neurosurgical operations. Improved delineation of tumor boundaries is expected to improve the results of surgery. The developed demonstrator is composed of two hyperspectral cameras covering a spectral range of 400–1700 nm. Furthermore, a hardware accelerator connected to a control unit is used to speed up the hyperspectral brain cancer detection algorithm to achieve processing during the time of surgery. A labeled dataset comprised of more than 300,000 spectral signatures is used as the training dataset for the supervised stage of the classification algorithm. In this preliminary study, thematic maps obtained from a validation database of seven hyperspectral images of in vivo brain tissue captured and processed during neurosurgical operations demonstrate that the system is able to discriminate between normal and tumor tissue in the brain. The results can be provided during the surgical procedure (~1 min), making it a practical system for neurosurgeons to use in the near future to improve excision and potentially improve patient outcomes.
Analysis of SNPs and Haplotypes in Vitamin D Pathway Genes and Renal Cancer Risk

In the kidney vitamin D is converted to its active form. Since vitamin D exerts its activity through binding to the nuclear vitamin D receptor (VDR), most genetic studies have primarily focused on variation within this gene. Therefore, analysis of genetic variation in VDR and other vitamin D pathway genes may provide insight into the role of vitamin D in renal cell carcinoma (RCC) etiology. RCC cases (N = 777) and controls (N = 1,035) were genotyped to investigate the relationship between RCC risk and variation in eight target genes. Minimum-p-value permutation (Min-P) tests were used to identify genes associated with risk. A three single nucleotide polymorphism (SNP) sliding window was used to identify chromosomal regions with a False Discovery Rate of <10%, where subsequently, haplotype relative risks were computed in Haplostats. Min-P values showed that VDR (p-value = 0.02) and retinoid-X-receptor-alpha (RXRA) (p-value = 0.10) were associated with RCC risk. Within VDR, three haplotypes across two chromosomal regions of interest were identified. The first region, located within intron 2, contained two haplotypes that increased RCC risk by approximately 25%. The second region included a haplotype (rs2239179, rs12717991) across intron 4 that increased risk among participants with the TC (OR = 1.31, 95% CI = 1.09–1.57) haplotype compared to participants with the common haplotype, TT. Across RXRA, one haplotype located 3′ of the coding sequence (rs748964, rs3118523), increased RCC risk 35% among individuals with the variant haplotype compared to those with the most common haplotype. This study comprehensively evaluated genetic variation across eight vitamin D pathway genes in relation to RCC risk. We found increased risk associated with VDR and RXRA. Replication studies are warranted to confirm these findings.
Transforming growth factor–β and Notch ligands act as opposing environmental cues in regulating the plasticity of type 3 innate lymphoid cells

Opposing signals in the tissue microenvironment balance the number of intestinal group 3 innate lymphoid cells. Plasticity in innate lymphoid cell function Like the T cells and B cells of the adaptive immune system, cells in the innate immune system are key to organismal health. Innate lymphoid cells (ILCs) are a heterogeneous type of innate immune cell that regulates immune responses and tolerance at mucosal surfaces, such as in the gut, by rapidly secreting cytokines. Group 3 ILCs (ILC3s) are characterized by the presence or absence of a cell surface natural cytotoxicity receptor (NCR). Two studies now provide evidence of heterogeneity and plasticity within ILC3s. Chea et al. found that a substantial proportion of mouse NCR− ILC3s differentiated into NCR+ ILC3s in response to stimulation of the receptor Notch2. In mice with defective Notch signaling specifically in lymphoid cells, NCR+ ILC3s were reduced in number and showed impaired cytokine secretion. Viant et al. showed that Notch signaling was required for the maintenance of NCR+ ILC3s. Furthermore, signaling by the cytokine transforming growth factor–β (TGF-β) antagonized Notch signaling, resulting in reduced numbers of NCR+ ILC3s. Together, these studies indicate that ILC3 subset composition in vivo depends on the balance between different signals found in tissue microenvironments, which has implications for whether immune responses or tolerance will prevail. Group 3 innate lymphoid cells (ILC3s) are composed of subsets that are either positive or negative for the natural cytotoxicity receptor (NCR) NKp46 (encoded by Ncr1). ILC3s are located at mucosal sites, such as in the intestine and lung, where they are exposed to billions of commensal microbes and potentially harmful pathogens. Together with T cells, the various ILC3 subsets maintain the balance between homeostasis and immune activation. Through genetic mapping, we identified a previously uncharacterized subset of NCR− ILC3s in mice that transiently express Ncr1, demonstrating previously undescribed heterogeneity within the ILC3 population. In addition, we showed that sustained Notch signaling was required for the maintenance of the NCR+ phenotype and that the cytokine transforming growth factor–β (TGF-β) impaired the development of NCR+ ILC3s. Thus, the plasticity of ILC3s is regulated by the balance between the opposing effects of Notch and TGF-β signaling, maintaining homeostasis in the face of continual challenges.
Incorporating Document Keyphrases in Search Results

Effectiveness and efficiency of searching and returned results presentation is the key to a search engine. Before downloading and examining the document text, users usually first judge the relevance of a return hit to the query by looking at document metadata presented in the return result. However, the metadata coming with the return hit is usually not rich enough for users to predict the content of the document. Keyphrases provide a concise summary of a document’s content, offering subject metadata characterizing and summarizing document. In this paper, we propose a mechanism of enriching the metadata of the return results by incorporating automatically extracted document keyphrases in each return hit. By looking at the keyphrases in each return hit, the user can predict the content of the document more easily, quickly, and accurately. The experimental results show that our solution may save users time up to 32% and users would like to use our proposed search interface with document keyphrases as part of the metadata of a return hit.
Timing Robustness in the Budding and Fission Yeast Cell Cycles

Robustness of biological models has emerged as an important principle in systems biology. Many past analyses of Boolean models update all pending changes in signals simultaneously (i.e., synchronously), making it impossible to consider robustness to variations in timing that result from noise and different environmental conditions. We checked previously published mathematical models of the cell cycles of budding and fission yeast for robustness to timing variations by constructing Boolean models and analyzing them using model-checking software for the property of speed independence. Surprisingly, the models are nearly, but not totally, speed-independent. In some cases, examination of timing problems discovered in the analysis exposes apparent inaccuracies in the model. Biologically justified revisions to the model eliminate the timing problems. Furthermore, in silico random mutations in the regulatory interactions of a speed-independent Boolean model are shown to be unlikely to preserve speed independence, even in models that are otherwise functional, providing evidence for selection pressure to maintain timing robustness. Multiple cell cycle models exhibit strong robustness to timing variation, apparently due to evolutionary pressure. Thus, timing robustness can be a basis for generating testable hypotheses and can focus attention on aspects of a model that may need refinement.
Fast Fourier Transform Networks for Object Tracking Based on Correlation Filter

In this paper, we propose fast Fourier transform networks for object tracking, called FFTNet. FFTNet is a correlation filter (CF)-based tracker that integrates two main components of CF, i.e., auto correlation and cross correlation between the features of two images. Thus, FFTNet takes full advantage of CF: 1) Auto correlation and cross correlation of CF are efficiently computed by FFT so that FFTNet achieves high computational efficiency and 2) FFTNet successfully performs displacement detection even in similar signals so that it achieves good tracking performance. Moreover, FFTNet combines the advantage of CF with convolutional neural networks so that it has strong capabilities of learning feature representation and matching function. FFTNet is trained end-to-end in an off-line manner. First, we input two-input patches of target object and search region into shared convolutional layers to get their features. Then, we calculate auto correlation and cross correlation from two features. Next, we concatenate the results of auto correlation and cross correlation, and put them into another subnetwork to learn a matching function. Finally, we get a response map whose values represent the probability of each pixel belonging to the target. Experimental results demonstrate that FFTNet outperforms state-of-the-arts in both tracking accuracy and computational efficiency.
Scenario‐oriented reverse engineering of complex railway system specifications

In this article, we present a scenario‐oriented modeling methodology dedicated to the analysis and the formalization of complex system specifications. The methodology relies on the SCOLA semiformal notation to describe scenarios and on a formal execution model described in the AltaRica 3.0 modeling language. We designed this methodology because we had to review thousands of pages of natural language specifications of a railway system in view of their validation with respect to safety constraints. We needed therefore some means to understand what the system was supposed to be and to do as well as to support a dialog with experts. This article aims at introducing the methodology and the modeling formalism that supports it as well as at discussing its application to the railway systems.
Spatial models to account for variation in observer effort in bird atlases

Abstract To assess the importance of variation in observer effort between and within bird atlas projects and demonstrate the use of relatively simple conditional autoregressive (CAR) models for analyzing grid‐based atlas data with varying effort. Pennsylvania and West Virginia, United States of America. We used varying proportions of randomly selected training data to assess whether variations in observer effort can be accounted for using CAR models and whether such models would still be useful for atlases with incomplete data. We then evaluated whether the application of these models influenced our assessment of distribution change between two atlas projects separated by twenty years (Pennsylvania), and tested our modeling methodology on a state bird atlas with incomplete coverage (West Virginia). Conditional Autoregressive models which included observer effort and landscape covariates were able to make robust predictions of species distributions in cases of sparse data coverage. Further, we found that CAR models without landscape covariates performed favorably. These models also account for variation in observer effort between atlas projects and can have a profound effect on the overall assessment of distribution change. Accounting for variation in observer effort in atlas projects is critically important. CAR models provide a useful modeling framework for accounting for variation in observer effort in bird atlas data because they are relatively simple to apply, and quick to run.
Protective properties of geniposide against UV-B-induced photooxidative stress in human dermal fibroblasts

Abstract Context: Geniposide (genipin-1-O-β-d-glucoside) is a major bioactive ingredient in the fruits of gardenia [Gardenia jasminoides J. Ellis (Rubiaceae)], a traditional herbal medicine in Asian countries. Objective: This work assesses the skin anti-photoaging potential of geniposide in human dermal fibroblasts under UV-B irradiation. Materials and methods: The anti-photoaging property of geniposide, at varying concentrations (5, 12 and 30 μM) treated for 30 min prior to UV-B irradiation, was evaluated by analysing reactive oxygen species (ROS), promatrix metalloproteinase-2 (proMMP-2), glutathione (GSH), superoxide dismutase (SOD), nuclear factor erythroid 2-related factor 2 (Nrf2) and cellular viability. Results: Geniposide suppressed the ROS elevation under UV-B irradiation, which was revealed using three ROS-sensitive fluorescent dyes. The use of 2′,7′-dichlorodihydrofluorescein diacetate (DCFH-DA), dihydroethidium (DHE) and dihydrorhodamine 123 (DHR-123) elicited the IC50 values of 10.5, 9.8 and 21.0 μM, respectively. Geniposide attenuated proMMP-2 at activity and protein levels that were elevated under UV-B-irradiation. Geniposide at 5, 12 and 30 μM augmented the UV-B-reduced total GSH content to 1.9 ± 0.1-, 2.2 ± 0.2- and 4.1 ± 0.2-fold, respectively. Geniposide at 5, 12 and 30 μM upregulated total SOD activity to 2.3 ± 0.1-, 2.5 ± 0.3- and 3.3 ± 0.3-fold, respectively, under UV-B irradiation. The UV-B-reduced Nrf2 levels were also upregulated by geniposide treatment. Geniposide, at the concentrations used, was unable to interfere with cellular viabilities under UV-B irradiation. Discussion and conclusions: After the skin anti-photoaging potential of geniposide may be further verified, it can be utilized as a safer resource in the manufacture of effective anti-aging cosmetics.
Species-Specific Seed Dispersal in an Obligate Ant-Plant Mutualism

Throughout lowland Amazonia, arboreal ants collect seeds of specific plants and cultivate them in nutrient-rich nests, forming diverse yet obligate and species-specific symbioses called Neotropical ant-gardens (AGs). The ants depend on their symbiotic plants for nest stability, and the plants depend on AGs for substrate and nutrients. Although the AGs are limited to specific participants, it is unknown at what stage specificity arises, and seed fate pathways in AG epiphytes are undocumented. Here we examine the specificity of the ant-seed interaction by comparing the ant community observed at general food baits to ants attracted to and removing seeds of the AG plant Peperomia macrostachya. We also compare seed removal rates under treatments that excluded vertebrates, arthropods, or both. In the bait study, only three of 70 ant species collected P. macrostachya seeds, and 84% of observed seed removal by ants was attributed to the AG ant Camponotus femoratus. In the exclusion experiment, arthropod exclusion significantly reduced seed removal rates, but vertebrate exclusion did not. We provide the most extensive empirical evidence of species specificity in the AG mutualism and begin to quantify factors that affect seed fate in order to understand conditions that favor its departure from the typical diffuse model of plant-animal mutualism.
Comparison of Serum HBsAg Quantitation by Four Immunoassays, and Relationships of HBsAg Level with HBV Replication and HBV Genotypes

Background The decline in hepatitis B virus surface antigen (HBsAg) may be an early predictor of the viral efficacy of Hepatitis B virus (HBV) therapy. The HBsAg levels obtained by different immunoassays now need comparing and the relationships between levels of HBsAg and HBV DNA alongside HBsAg and genotype must be evaluated. Methodology/Principal Findings HBsAg levels were compared among 80 patients using the Abbott Architect assay, a commercial immunoassay approved for HBsAg detection and quantitation, and three other assays derived from immunoassays approved for HBsAg detection (manufactured by Diasorin, Bio-Rad and Roche). Good correlation was found between the Abbot vs. Diasorin, Bio-Rad and Roche assays with narrow 95% limits of agreement and small mean differences: −0.06 to 0.11, −0.09 log10 IU/mL; −0.57 to 0.64, −0.04 log10 IU/mL; −0.09 to 0.45, −0.27 log10 IU/mL, respectively. These agreements were not affected by genotypes A or D. HBsAg was weakly correlated with HBV DNA, whatever the HBsAg assay used: Abbott, ρ = 0.36 p = 0.001, Diasorin ρ = 0.34, p = 0.002; Bio-Rad ρ = 0.37, p<0.001; or Roche ρ = 0.41, p<0.001. This relationship between levels of HBsAg and HBV DNA seemed to depend on genotypes. Whereas HBsAg (Abbott assay) tended to correlate with HBV DNA for genotype A (ρ = 0.44, p = 0.02), no such correlation was significant for genotypes D (ρ = 0.29, p = 0.15). Conclusion/Significance The quantitation of HBsAg in routine clinical samples is comparable between the reference assay and the adapted assays with acceptable accuracy limits, low levels of variability and minimum discrepancy. While HBsAg quantitation is not affected by HBV genotype, the observed association between levels of HBsAg and HBV DNA seems genotype dependent.