Miracle-dz/UniFAR-FTUs huggingface dataset:
Prognostic Significance of HPV and p16 Status in Men Diagnosed with Penile Cancer: A Systematic Review and Meta-analysis

It has been shown that human papillomavirus (HPV) and p16 status has prognostic value in some HPV-associated cancers. However, studies examining survival in men with penile cancer according to HPV or p16 status are often inconclusive, mainly because of small study populations. The aim of this systematic review and meta-analysis was to examine the association between HPV DNA and p16 status and survival in men diagnosed with penile cancer. Multiple electronic databases were searched. Twenty studies were ultimately included and study-specific and pooled HRs of overall survival and disease-specific survival (DSS) were calculated using a fixed effects model. In the analysis of DSS, we included 649 men with penile cancer tested for HPV (27% were HPV-positive) and 404 men tested for p16 expression (47% were p16-positive). The pooled HRHPV of DSS was 0.61 [95% confidence interval (CI), 0.38–0.98], and the pooled HRp16 of DSS was 0.45 (95% CI, 0.30–0.69). In conclusion, men with HPV or p16-positive penile cancer have a significantly more favorable DSS compared with men with HPV or p16-negative penile cancer. These findings point to the possible clinical value of HPV and p16 testing when planning the most optimal management and follow-up strategy. Cancer Epidemiol Biomarkers Prev; 27(10); 1123–32. ©2018 AACR.
Hacking the Human: The Prevalence Paradox in Cybersecurity

Objective: This work assesses the efficacy of the “prevalence effect” as a form of cyberattack in human-automation teaming, using an email task. Background: Under the prevalence effect, rare signals are more difficult to detect, even when taking into account their proportionally low occurrence. This decline represents diminished human capability to both detect and respond. As signal probability (SP) approaches zero, accuracy exhibits logarithmic decay. Cybersecurity, a context in which the environment is entirely artificial, provides an opportunity to manufacture conditions enhancing or degrading human performance, such as prevalence effects. Email cybersecurity prevalence effects have not previously been demonstrated, nor intentionally manipulated. Method: The Email Testbed (ET) provides a simulation of a clerical email work involving messages containing sensitive personal information. Using the ET, participants were presented with 300 email interactions and received cyberattacks at rates of either 1%, 5%, or 20%. Results: Results demonstrated the existence and power of prevalence effects in email cybersecurity. Attacks delivered at a rate of 1% were significantly more likely to succeed, and the overall pattern of accuracy across declining SP exhibited logarithmic decay. Application: These findings suggest a “prevalence paradox” within human-machine teams. As automation reduces attack SP, the human operator becomes increasingly likely to fail in detecting and reporting attacks that remain. In the cyber realm, the potential to artificially inflict this state on adversaries, hacking the human operator rather than algorithmic defense, is considered. Specific and general information security design countermeasures are offered.
A coding and non-coding transcriptomic perspective on the genomics of human metabolic disease

Abstract Genome-wide association studies (GWAS), relying on hundreds of thousands of individuals, have revealed >200 genomic loci linked to metabolic disease (MD). Loss of insulin sensitivity (IS) is a key component of MD and we hypothesized that discovery of a robust IS transcriptome would help reveal the underlying genomic structure of MD. Using 1,012 human skeletal muscle samples, detailed physiology and a tissue-optimized approach for the quantification of coding (>18,000) and non-coding (>15,000) RNA (ncRNA), we identified 332 fasting IS-related genes (CORE-IS). Over 200 had a proven role in the biochemistry of insulin and/or metabolism or were located at GWAS MD loci. Over 50% of the CORE-IS genes responded to clinical treatment; 16 quantitatively tracking changes in IS across four independent studies (P = 0.0000053: negatively: AGL, G0S2, KPNA2, PGM2, RND3 and TSPAN9 and positively: ALDH6A1, DHTKD1, ECHDC3, MCCC1, OARD1, PCYT2, PRRX1, SGCG, SLC43A1 and SMIM8). A network of ncRNA positively related to IS and interacted with RNA coding for viral response proteins (P < 1 × 10−48), while reduced amino acid catabolic gene expression occurred without a change in expression of oxidative-phosphorylation genes. We illustrate that combining in-depth physiological phenotyping with robust RNA profiling methods, identifies molecular networks which are highly consistent with the genetics and biochemistry of human metabolic disease.
A Survey of the Common Mutations and IVS8-Tn Polymorphism of Cystic Fibrosis Transmembrane Conductance Regulator Gene in Infertile Men with Nonobstructive Azoospermia and CBAVD in Iranian Population

Background: Studies have revealed a strong association between mutations of CFTR gene and the congenital bilateral absence of the vas deferens (CBAVD), but the role of this gene in other types of male infertility is still unclear. The purpose of this study was to investigate the frequency of the most common mutations of the CFTR gene (F508, G542X, N1303K, G551D, and W1282X) in a population of infertile men with nonobstructive azoospermia (NOA) and CBAVD in Iran. Methods: Blood samples were obtained from 50 NOA, 50 CBAVD, and 100 normal males (control). Genomic DNA was isolated from whole blood leukocytes, and the presence of common mutations of the CFTR gene was assessed by an amplification refractory mutation system-polymerase chain reaction (ARMS-PCR). Restriction fragment length polymorphism (PCR-RFLP) was also used to analyze IVS8-Tn polymorphism. Results: It was found that 16%, 8%, and 8% of patients with CBAVD were heterozygote for F508, G542X, and N1303K, respectively. The frequency of the 5T allele was 34% and higher than the normal group (p < 0.001). None of the common CFTR gene mutations were detected in NOA patients, and no significant difference was found in the distribution of the 5T allele between the NOA patients and the control group (5 vs. 3 p = 0.721). Conclusion: Based on the present case-control study, the CFTR gene mutations and IVS8-Tn polymorphisms are correlated with CBAVD; however, extensive investigations are necessary to determine the exact relationship between the gene mutations and other forms of male infertility.
Integrating spirituality into the care of older adults

ABSTRACT We examine how to sensibly integrate spirituality into the care of older adult medical and psychiatric patients from a multi-cultural perspective. First, definitions of spirituality and spiritual integration are provided. Second, we examine the logic that justifies spiritual integration, including research that demonstrates an association between religious/spiritual (R/S) involvement and health in older adults and research that indicates widespread spiritual needs in later life and the consequences of addressing or ignoring them. Third, we describe how and when to integrate spirituality into the care of older adults, i.e. taking a spiritual history to identify spiritual needs and then mobilizing resources to meet those needs. Fourth, we examine the consequences of integrating spirituality on the well-being of patients and on the doctor–patient relationship. Finally, we describe boundaries in addressing R/S issues that clinicians should be cautious about violating. Resources will be provided to assist with all of the above.
Synthesizing Pattern Programs from Examples

We describe a programming-by-example system that automatically generates pattern programs from examples. Writing pattern programs, which produce various patterns of characters, is one of the most popular programming exercises for entry-level students. However, students often find it difficult to write correct solutions by themselves. In this paper, we present a method for synthesizing pattern programs from examples, allowing students to improve their programming skills efficiently. To that end, we first design a domain-specific language that supports a large class of pattern programs that students struggle with. Next, we develop a synthesis algorithm that efficiently finds a desired program by combining enumerative search, constraint solving, and program analysis. We implemented the algorithm in a tool and evaluated it on 40 exercises gathered from online forums. The experimental results and user study show that our tool can synthesize instructive solutions from 1–3 example patterns in 1.2 seconds on average.
Anxiety and depressive symptoms during pregnancy, perceived control and posttraumatic stress symptoms after childbirth: A longitudinal mediation analysis

This longitudinal study evaluated the mediating role of sense of control during labour in the association between anxiety and depression levels during pregnancy and postpartum posttraumatic stress disorder symptoms. Participants were 57 women. Anxiety and depression were assessed during pregnancy; sense of control and childbirth-related posttraumatic stress disorder symptoms were collected 6–8 weeks after childbirth. Higher levels of anxiety and depression were associated with more postpartum posttraumatic stress disorder symptoms through lack of perceived control. For depression, this happened only for primiparous. Interventions targeting mechanisms enhancing perceptions/feelings of control should be offered to these women to prevent/minimize childbirth-related posttraumatic stress disorder.
An RBFNN-Based Direct Inverse Controller for PMSM with Disturbances

Considering the system uncertainties, such as parameter changes, modeling error, and external uncertainties, a radial basis function neural network (RBFNN) controller using the direct inverse method with the satisfactory stability for improving universal function approximation ability, convergence, and disturbance attenuation capability is advanced in this paper. The weight adaptation rule of the RBFNN is obtained online by Lyapunov stability analysis method to guarantee the identification and tracking performances. The simulation example for the position tracking control of PMSM is studied to illustrate the effectiveness and the applicability of the proposed RBFNN-based direct inverse control method.
Design, Synthesis and Characterization of Novel Co-Polymers Decorated with Peptides for the Selective Nanoparticle Transport across the Cerebral Endothelium

The development of new strategies for enhancing drug delivery to the brain represents a major challenge in treating cerebral diseases. In this paper, we report on the synthesis and structural characterization of a biocompatible nanoparticle (NP) made up of poly(lactic-co-glycolic acid) (PLGA)-polyethylene glycol (PEG) co-polymer (namely PELGA) functionalized with the membranotropic peptide gH625 (gH) and the iron-mimicking peptide CRTIGPSVC (CRT) for transport across the blood-brain barrier (BBB). gH possesses a high translocation potency of the cell membrane. Conversely, CRT selectively recognizes the brain endothelium, which interacts with transferrin (Tf) and its receptor (TfR) through a non-canonical ligand-directed mechanism. We hypothesize that the delivery across the BBB of PELGA NPs should be efficiently enhanced by the NP functionalization with both gH and CRT. Synthesis of peptides and their conjugation to the PLGA as well as NP physical-chemical characterization are performed. Moreover, NP uptake, co-localization, adhesion under dynamic conditions, and permeation across in vitro BBB model are evaluated as a function of gH/CRT functionalization ratio. Results establish that the cooperative effect of CRT and gH may change the intra-cellular distribution of NPs and strengthen NP delivery across the BBB at the functionalization ratio 33% gH–66% CRT.
Shifting through the forest: home range, movement patterns, and diet of the eastern chimpanzee (Pan troglodytes schweinfurthii) in Nyungwe National Park, Rwanda

Populations of the endangered eastern chimpanzee (Pan troglodytes schweinfurthii) are declining throughout their range. Although Nyungwe National Park (NNP) harbors the largest remaining eastern chimpanzee population in Rwanda, we know little about their space use and dietary patterns. We studied home range, movement, and diet of two communities of chimpanzees in NNP using daily tracking data (6:00 am to 6:00 pm) collected from 2000 to 2015. One community, Mayebe, resided in the forest center, and the other community, Cyamudongo, inhabited a forest fragment located about 10 km from the main forest. Home range estimated with the 95% kernel density estimation (KDE) method was 21 km2 for the Mayebe community and 4 km2 for the Cyamudongo community. Chimpanzee home range sizes were smaller during the dry versus wet season and varied monthly throughout the year. The Mayebe community had an average hourly step length of 75 ± SE 5 m with a daily movement range of 987 ± SE 71 m, while the Cyamudongo community had a shorter hourly step length of 52 ± SE 3 m with a daily movement range of 651 ± SE 71 m. Both chimpanzee communities fed primarily on Ficus spp. Other important dietary items included fruits of Symphonia globulifera, Syzygium guineense, and Chrysophyllum gorungosanum for the Mayebe community and Trilepisium madagascariense for the Cyamudongo community. Food choice varied monthly and seasonally for each chimpanzee community. Our study provides the first estimates of home range size and movement parameters for chimpanzees in Rwanda and documents their food habits and seasonal variations therein. We also identified the 50% core home range for each chimpanzee community and suggest this area as the focus of management actions. These results could help park management reduce threats to chimpanzees and other sympatric species by improving the efficiency of ranger patrols.
Learning Pose-Aware Models for Pose-Invariant Face Recognition in the Wild

We propose a method designed to push the frontiers of unconstrained face recognition in the wild with an emphasis on extreme out-of-plane pose variations. Existing methods either expect a single model to learn pose invariance by training on massive amounts of data or else normalize images by aligning faces to a single frontal pose. Contrary to these, our method is designed to explicitly tackle pose variations. Our proposed Pose-Aware Models (PAM) process a face image using several pose-specific, deep convolutional neural networks (CNN). 3D rendering is used to synthesize multiple face poses from input images to both train these models and to provide additional robustness to pose variations at test time. Our paper presents an extensive analysis of the IARPA Janus Benchmark A (IJB-A), evaluating the effects that landmark detection accuracy, CNN layer selection, and pose model selection all have on the performance of the recognition pipeline. It further provides comparative evaluations on IJB-A and the PIPA dataset. These tests show that our approach outperforms existing methods, even surprisingly matching the accuracy of methods that were specifically fine-tuned to the target dataset. Parts of this work previously appeared in [1] and [2] .
Characterizing the 3D structure and dynamics of chromosomes and proteins in a common contact matrix framework

Any conformational ensemble of biopolymers, whether they are proteins or chromosomes, can be described using contact matrices derived from experimental or computational studies. One powerful approach to extract meaningful information from these contact matrices is to perform principal component analysis (PCA) on the covariance matrix of the contact data. Indeed, PCA on Hi-C chromosome contact matrices has revealed the spatial segregation of active and inactive chromatin. Separately, PCA on contact matrices from snapshots of protein conformations has characterized correlated fluctuations of protein domains. However, despite the similarities of these data and analyses, there has been little synergy between the PCA approaches and the comparison of resulting biological insights obtained for protein and chromosome structures. We note that, to date, different styles of analyses were applied exclusively to each biomolecule type: explicit contact correlation analysis (E-PCA) for proteins and implicit contact correlation (I-PCA) for chromosomes. In this work, we compare the results of applying both methods to both classes of biopolymers. While I-PCA reveals only average features of 3D chromosome structure, we find that applying E-PCA to an ensemble of chromosome structures from microscopy data reveals the dominant motion (concerted fluctuation) of the chromosome. Applying E-PCA to Hi-C data across the human blood cell lineage isolates the aspects of chromosome structure that most strongly differentiate cell types. Conversely, when we apply I-PCA to simulation snapshots of two protein complexes, the major component reports the consensus features of the structure, while the previously applied E-PCA characterizes correlated deviations from the mean structure.
Solving 3-D PDEs by Tensor B-Spline Methodology: A High Performance Approach Applied to Optical Diffusion Tomography

Solutions of 3-D elliptic PDEs form the basis of many mathematical models in medicine and engineering. Solving elliptic PDEs numerically in 3-D with fine discretization and high precision is challenging for several reasons, including the cost of 3-D meshing, the massive increase in operation count, and memory consumption when a high-order basis is used, and the need to overcome the “curse of dimensionality. ” This paper describes how these challenges can be either overcome or relaxed by a Tensor B-spline methodology with the following key properties: 1) the tensor structure of the variational formulation leads to regularity, separability, and sparsity, 2) a method for integration over the complex domain boundaries eliminates meshing, and 3) the formulation induces high-performance and memory-efficient computational algorithms. The methodology was evaluated by application to the forward problem of Optical Diffusion Tomography (ODT), comparing it with the solver from a state-of-the-art Finite-Element Method (FEM)-based ODT reconstruction framework. We found that the Tensor B-spline methodology allows one to solve the 3-D elliptic PDEs accurately and efficiently. It does not require 3-D meshing even on complex and non-convex boundary geometries. The Tensor B-spline approach outperforms and is more accurate than the FEM when the order of the basis function is > 1, requiring fewer operations and lower memory consumption. Thus, the Tensor B-spline methodology is feasible and attractive for solving large elliptic 3-D PDEs encountered in real-world problems.
Ristretto: A Framework for Empirical Study of Resource-Efficient Inference in Convolutional Neural Networks

Convolutional neural networks (CNNs) have led to remarkable progress in a number of key pattern recognition tasks, such as visual scene understanding and speech recognition, that potentially enable numerous applications. Consequently, there is a significant need to deploy trained CNNs to resource-constrained embedded systems. Inference using pretrained modern deep CNNs, however, requires significant system resources, including computation, energy, and memory space. To enable efficient implementation of trained CNNs, a viable approach is to approximate the network with an implementation-friendly model with only negligible degradation in classification accuracy. We present Ristretto, a CNN approximation framework that enables empirical investigation of the tradeoff between various number representation and word width choices and the classification accuracy of the model. Specifically, Ristretto analyzes a given CNN with respect to numerical range required to represent weights, activations, and intermediate results of convolutional and fully connected layers, and subsequently, it simulates the impact of reduced word width or lower precision arithmetic operators on the model accuracy. Moreover, Ristretto can fine-tune a quantized network to further improve its classification accuracy under a given number representation and word width configuration. Given a maximum classification accuracy degradation tolerance of 1%, we use Ristretto to demonstrate that three ImageNet networks can be condensed to use 8-bit dynamic fixed point for network weights and activations. Ristretto is available as a popular open-source software project1 and has already been viewed over 1 000 times on Github as of the submission of this brief.1https://github.com/pmgysel/caffe
Does the structure of working memory in EL children vary across age and two language systems?

ABSTRACT This study examined the cross-sectional structure of working memory (WM) among elementary school English learners (ELs). A battery of WM tasks was administered in Spanish (L1) and English (L2) within five age groups (ages 6, 7, 8, 9, & 10). Confirmatory factor analysis showed a three-factor structure of WM emerged in both L1 and L2 administrations for each age group. The important findings, however, were: (1) the separation between the executive component and storage component (phonological loop) structure of WM increased as a function of age within both language systems, (2) the structure of WM supported a domain general phonological storage component and a domain general executive system across both language systems, and (3) the visual-spatial WM system shared minimal variance with the executive system. Taken together, the findings support Baddeley’s multicomponent model (e.g., Baddeley & Logie, 1999. The multiple-component model. In A. Miyake & P. Shah (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 28–61). Cambridge: Cambridge University Press) as a good fit to the structure of WM in EL children’s English and Spanish language system.
An Entity Theory of Intelligence Predicts Higher Cortisol Levels When High School Grades Are Declining.

Grades often decline during the high school transition, creating stress. The present research integrates the biopsychosocial model of challenge and threat with the implicit theories model to understand who shows maladaptive stress responses. A diary study measured declines in grades in the first few months of high school: salivary cortisol (N = 360 students, N = 3,045 observations) and daily stress appraisals (N = 499 students, N = 3,854 observations). Students who reported an entity theory of intelligence (i.e., the belief that intelligence is fixed) showed higher cortisol when grades were declining. Moreover, daily academic stressors showed a different lingering effect on the next day's cortisol for those with different implicit theories. Findings support a process model through which beliefs affect biological stress responses during difficult adolescent transitions.
Network-Based T–S Fuzzy Dynamic Positioning Controller Design for Unmanned Marine Vehicles

This paper is concerned with a Takagi–Sugeno (T–S) fuzzy dynamic positioning controller design for an unmanned marine vehicle (UMV) in network environments. Network-based T–S fuzzy dynamic positioning system (DPS) models for the UMV are first established. Then, stability and stabilization criteria are derived by taking into consideration an asynchronous difference between the normalized membership function of the T–S fuzzy DPS and that of the controller. The proposed stabilization criteria can stabilize states of the UMV. The dynamic positioning performance analysis verifies the effectiveness of the networked modeling and the controller design.