Miracle-dz/UniFAR-FTUs huggingface dataset:
The Predictability of Phytophagous Insect Communities: Host Specialists as Habitat Specialists

The difficulties specialized phytophagous insects face in finding habitats with an appropriate host should constrain their dispersal. Within the concept of metacommunities, this leads to the prediction that host-plant specialists should sort into local assemblages according to the local environmental conditions, i.e. habitat conditions, whereas assemblages of host-plant generalists should depend also on regional processes. Our study aimed at ranking the importance of local environmental factors and species composition of the vegetation for predicting the species composition of phytophagous moth assemblages with either a narrow or a broad host range. Our database consists of 351,506 specimens representing 820 species of nocturnal Macrolepidoptera sampled between 1980 and 2006 using light traps in 96 strict forest reserves in southern Germany. Species were grouped as specialists or generalists according to the food plants of the larvae; specialists use host plants belonging to one genus. We used predictive canonical correspondence and co-correspondence analyses to rank the importance of local environmental factors, the species composition of the vegetation and the role of host plants for predicting the species composition of host-plant specialists and generalists. The cross-validatory fit for predicting the species composition of phytophagous moths was higher for host-plant specialists than for host-plant generalists using environmental factors as well as the composition of the vegetation. As expected for host-plant specialists, the species composition of the vegetation was a better predictor of the composition of these assemblages than the environmental variables. But surprisingly, this difference for specialized insects was not due to the occurrence of their host plants. Overall, our study supports the idea that owing to evolutionary constraints in finding a host, host-plant specialists and host-plant generalists follow two different models of metacommunities: the species-sorting and the mass-effect model.
Feature extraction and real-time recognition of hand motion intentions from EMGs via artificial neural networks

Electromyography (EMG) signal analysis is one of the key determinants of the effectiveness of prosthetic devices. Modern researchers provide various methods of detection of different hand movements and postures. In this work, we examined the possibility to produce efficient detection of hand movement to a specific posture with the minimum possible number of electrodes. The data acquisition is produced with 1 channel BiTalino EMG sensor based on bipolar differential measurement. Using feature extraction and artificial neural network we achieved 82% of offline classification accuracy for 8 hand motions and 91% accuracy for 6 hand motions based on 200 ms of EMG signal. Also, the motion detection algorithm was developed and successfully tested that allowed to implement the algorithm for real-time classification and that showed sufficient accuracy for 2 and 4 motion classes cases.
Patterns and management of chronic obstructive pulmonary disease in urban and rural China: a community-based survey of 25 000 adults across 10 regions

Introduction Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide, with COPD deaths in China accounting for one-third of all such deaths. However, there is limited available evidence on the management of COPD in China. Methods A random sample of 25 011 participants in the China Kadoorie Biobank, aged 38–87 years, from 10 regions in China was surveyed in 2013–2014. Data were collected using interviewer-administered questionnaires on the diagnosis (‘doctor-diagnosed’ or ‘symptoms-based’) and management of COPD (including use of medication and other healthcare resources), awareness of diagnosis and severity of symptoms in COPD cases. Results Overall, 6.3% of the study population were identified as COPD cases (doctor-diagnosed cases: 4.8% and symptom-based cases: 2.4%). The proportion having COPD was higher in men than in women (7.9% vs 5.3%) and varied by about threefold (3.7%–10.0%) across the 10 regions. Among those with COPD, 54% sought medical advice during the last 12 months, but <10% reported having received treatment for COPD. The rates of hospitalisation for COPD, use of oxygen therapy at home and influenza or pneumococcal vaccinations in the previous year were 15%, 3% and 4%, respectively. Of those with COPD, half had moderate or severe respiratory symptoms, and over 80% had limited understanding of their disease and need for treatment. Conclusion Despite a high prevalence of COPD in China and its substantial impact on activities of daily living, knowledge about COPD and its management were limited.
An Aggregate Measure of Sleep Health Is Associated With Prevalent and Incident Clinically Significant Depression Symptoms Among Community-Dwelling Older Women

Objectives Sleep can be characterized along multiple dimensions. We investigated whether an aggregate measure of sleep health was associated with prevalent and incident clinically significant depression symptoms in a cohort of older women. Methods Participants were older women (mean age 80.1 years) who completed baseline (n = 6485) and follow-up (n = 3806) visits, approximately 6 years apart, in the Study of Osteoporotic Fractures (SOF). Self-reported sleep over the past 12 months was categorized as "good" or "poor" across 5 dimensions: satisfaction with sleep duration, daytime sleepiness, mid-sleep time, sleep onset latency, and sleep duration. An aggregate measure of sleep health was calculated by summing the number of "poor" dimensions. Clinically significant depression symptoms were defined as a score ≥6 on the Geriatric Depression Scale. Relationships between sleep health and depression symptoms were evaluated with multivariate logistic regression, adjusting for health measures and medications. Results Individual sleep health dimensions of sleep satisfaction, daytime sleepiness, mid-sleep time, and sleep onset latency were significantly associated with prevalent depression symptoms (odds ratios [OR] = 1.26-2.69). Sleep satisfaction, daytime sleepiness, and sleep onset latency were significantly associated with incident depression symptoms (OR = 1.32-1.79). The number of "poor" sleep health dimensions was associated in a gradient fashion with greater odds of prevalent (OR = 1.62-5.41) and incident (OR = 1.47-3.15) depression symptoms. Conclusion An aggregate, multidimensional measure of sleep health was associated with both prevalent and incident clinically-significant depression symptoms in a gradient fashion. Future studies are warranted to extend these findings in different populations and with different health outcomes.
Pharmacokinetic and pharmacodynamics of xylazine administered to exercised thoroughbred horses.

There is limited data describing xylazine serum concentrations in the horse and no reports of concentrations beyond 24 hours. The primary goal of the study reported here was to update the pharmacokinetics of xylazine following intravenous (IV) administration in order to assess the applicability of current regulatory recommendations. Pharmacodynamic parameters were determined using PK-PD modeling. Sixteen exercised adult Thoroughbred horses received a single IV dose of 200 mg of xylazine. Blood and urine samples were collected at time 0 and at various times for up to 96 hours and analyzed using liquid chromatography tandem mass spectrometry. Xylazine serum concentrations were best fit by a 3-compartment model. Mean ± SEM systemic clearance, volume of distribution at steady state, beta half-life and gamma half-life were 12.7 ± 0.735 mL/min/kg, 0.660 ± 0.053 L/kg, 2.79 ± 0.105 hours and 26.0 ± 1.9, respectively. Immediately following administration, horses appeared sedate as noted by a decrease in chin-to-ground distance, decreased locomotion and decreased heart rate (HR). Sedation lasted approximately 45 minutes. Glucose concentrations were elevated for 1-hour post administration. The EC50 (IC50) was 636.1, 702.2, 314.1 and 325.7 ng/mL for HR, atrioventricular block, chin-to-ground distance and glucose concentrations, respectively. The Emax (Imax) was 27.3 beats per minute, 47.5%, 42.4 cm and 0.28 mg/dL for HR, atrioventricular block, chin-to-ground distance and glucose concentrations, respectively. Pharmacokinetic parameters differ from previous reports and a prolonged detection time suggests that an extended withdrawal time, beyond current regulatory recommendations, is warranted to avoid inadvertent positive regulatory findings in performance horses. Copyright © 2016 John Wiley & Sons, Ltd.
Low Sensitivity of the Mini-Mental State Examination for Cognitive Assessment of Brazilian Patients With Parkinson Disease

Introduction: Recent publications have highlighted the low sensitivity of the Mini-Mental State Examination (MMSE) for the cognitive assessment of patients with Parkinson disease (PD). The Montreal Cognitive Assessment (MoCA), otherwise, has shown greater sensitivity when compared to the MMSE. Based on this, we have searched for the cognitive impairment measurable by the MoCA and the functional performance on activities of daily living in a sample of Brazilian patients with PD and normal MMSE. We hypothesized that the low sensitivity of the MMSE, already shown by other authors, could be replicated in a low-income country. Objective: To describe the performance on the MoCA and the dependence on third parties for activities of daily living in a sample of Brazilian patients with PD and normal MMSE. Methods: We evaluated 43 volunteers with PD and normal MMSE considering the Brazilian cutoffs. Cognitive performance was assessed through the MoCA and functional performance through a modified version of the Disability Assessment for Dementia Scale. Results: Despite normal score on the MMSE, considering the Brazilian cutoffs, 62.7% of the volunteers performed below the literature cutoff for the MoCA (26 points). Furthermore, 30.2% had dependence on third party for activities of daily living. By using a strict cutoff for the MMSE (26 points), 56.7% performed below the MoCA cutoff and 24.3% had dependence for activities of daily living. Conclusions: Our findings confirm the limitations of the MMSE for the cognitive screening of patients with PD in a low-income country.
Trends in incidence, mortality and survival of penile squamous cell carcinoma in Norway 1956–2015

We examine trends in incidence, mortality and survival of penile squamous cell carcinoma (SCC) in Norway over 60 years. Data on all cases of penile cancer diagnosed in Norway during 1956–2015 were obtained from the Cancer Registry of Norway. Trends in age‐standardized rates of penile SCC incidence, mortality and 5‐year relative survival were assessed by the annual percentage change statistic and joinpoint regression. A total of 1,596 penile cancer cases were diagnosed during 1956–2015, among which 1,474 (92.4%) were SCC. During 2011–2015, the age‐standardized incidence and mortality of penile SCC were 0.91 (95% confidence interval (CI): 0.78; 1.05) and 0.50 (0.42; 0.60) per 100,000, respectively, and the 5‐year relative survival was 61.6% (41.9; 76.4). The incidence of SCC increased during 1956–2015, with an average annual percentage change (AAPC) of 0.80% (0.46; 1.15). The increase was strongest among men diagnosed at a relatively early age (age<=64 years; AAPC: 1.47% (0.90; 2.05)). Mortality also increased over the study period (AAPC: 0.47% (0.10; 0.85)), whereas 5‐year relative survival did not change (AAPC: 0.08% (−0.19; 0.36)). We conclude that the incidence of penile SCC has increased at a moderate and constant rate during 1956–2015, and that the most consistent increase occurred among younger men. Mortality also increased during the study period. However, survival did not change, thus changes in diagnostics and treatment had little impact on survival from penile SCC. Since a substantial proportion of penile SCC is caused by human papillomavirus (HPV), the incidence increase may in part be attributed to increased exposure to HPV in the population.
Gold nanoparticles crosslinking by peptides and amino acids: A tool for the colorimetric identification of amino acids

Gold nanoparticles are known to aggregate in the presence of proper multifunctional compounds. For those larger than 3 nm, the process can be followed with the naked eye because the surface plasmon absorption band of the particles shifts to longer wavelengths and the solution color changes from red to blue. To exploit this property, we have used amino acids and peptides as crosslinking agents in ethanol at low µM concentrations. In the case of amino acids, we report a straightforward protocol for their colorimetric identification. We also report that the presence of precise secondary structure and conformational constraints in oligopeptides, directly influence their crosslinking ability. A discussion on the nature of the interactions that induce these phenomena is also reported.
Time of presentation affects auditory distraction: Changing-state and deviant sounds disrupt similar working memory processes

Four experiments tested conflicting predictions about which components of the serial-recall task are most sensitive to auditory distraction. Changing-state (Experiments 1a and 1b) and deviant distractor sounds (Experiments 2a and 2b) were presented in one of four different intervals of the serial-recall task: (1) during the first half of encoding, (2) during the second half of encoding, (3) during the first half of retention, or (4) during the second half of retention. According to the embedded-processes model, both types of distractors should interfere with the encoding and rehearsal of targets in the focus of attention. According to the duplex-mechanism account, changing-state distractors should interfere only with rehearsal, whereas deviant distractors should interfere only with encoding. Inconsistent with the latter view, changing-state and deviant distractor sounds interfered with both the encoding and the retention of the targets. Both types of auditory distraction were most pronounced during the second half of encoding when the increasing rehearsal demands had to be coordinated with the continuous updating of the rehearsal set. These findings suggest that the two types of distraction disrupt similar working memory mechanisms.
Memorization Precedes Generation: Learning Unsupervised GANs with Memory Networks

We propose an approach to address two issues that commonly occur during training of unsupervised GANs. First, since GANs use only a continuous latent distribution to embed multiple classes or clusters of data, they often do not correctly handle the structural discontinuity between disparate classes in a latent space. Second, discriminators of GANs easily forget about past generated samples by generators, incurring instability during adversarial training. We argue that these two infamous problems of unsupervised GAN training can be largely alleviated by a learnable memory network to which both generators and discriminators can access. Generators can effectively learn representation of training samples to understand underlying cluster distributions of data, which ease the structure discontinuity problem. At the same time, discriminators can better memorize clusters of previously generated samples, which mitigate the forgetting problem. We propose a novel end-to-end GAN model named memoryGAN, which involves a memory network that is unsupervisedly trainable and integrable to many existing GAN models. With evaluations on multiple datasets such as Fashion-MNIST, CelebA, CIFAR10, and Chairs, we show that our model is probabilistically interpretable, and generates realistic image samples of high visual fidelity. The memoryGAN also achieves the state-of-the-art inception scores over unsupervised GAN models on the CIFAR10 dataset, without any optimization tricks and weaker divergences.
Patients With Heart Failure Readmitted to the Original Hospital Have Better Outcomes Than Those Readmitted Elsewhere

Background Up to one fifth of readmissions after a heart failure hospitalization occur at a different hospital. This negatively impacts information continuity, but whether site of readmission impacts subsequent outcomes is unclear. Methods and Results Retrospective cohort study of all patients discharged with a primary diagnosis of heart failure in Canada between April 2004 and December 2013. We compared patients readmitted within 30 days to the original hospital versus a different hospital. Of the 217 039 heart failure patients (mean age, 76.8 years, 50.1% male), 39 368 (18.1%) were readmitted within 30 days—32 771 (83.2%) to the original hospital and 6597 (16.8%) to a different hospital (increasing over time from 15.6% in 2004 to 18.5% by 2013; P for trend=0.001). Patients readmitted to different hospitals were younger and were more likely to be male, have a rural residence, a more‐recent discharge year, an index hospitalization at a teaching hospital, and to be brought in by ambulance at the time of the readmission. Readmissions to the original hospital were substantially shorter (mean, 10.4 days [95% CI, 10.3–10.6] versus 11.6 days [95% CI, 11.3–12.0]; adjusted means, 11.0 versus 12.0; P<0.0001) and had lower mortality (14.4% versus 15.0%; adjusted odds ratio, 0.89; 95% CI, 0.82–0.96) than readmissions to different hospitals. Conclusions Readmissions to a different hospital are becoming more frequent over time and are associated with longer stays and higher mortality rates than readmissions to the original hospital. Our findings provide further evidence that care fragmentation may be deleterious for patients with heart failure.
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning

Deep neural networks (DNNs) enable innovative applications of machine learning like image recognition, machine translation, or malware detection. However, deep learning is often criticized for its lack of robustness in adversarial settings (e.g., vulnerability to adversarial inputs) and general inability to rationalize its predictions. In this work, we exploit the structure of deep learning to enable new learning-based inference and decision strategies that achieve desirable properties such as robustness and interpretability. We take a first step in this direction and introduce the Deep k-Nearest Neighbors (DkNN). This hybrid classifier combines the k-nearest neighbors algorithm with representations of the data learned by each layer of the DNN: a test input is compared to its neighboring training points according to the distance that separates them in the representations. We show the labels of these neighboring points afford confidence estimates for inputs outside the model's training manifold, including on malicious inputs like adversarial examples--and therein provides protections against inputs that are outside the models understanding. This is because the nearest neighbors can be used to estimate the nonconformity of, i.e., the lack of support for, a prediction in the training data. The neighbors also constitute human-interpretable explanations of predictions. We evaluate the DkNN algorithm on several datasets, and show the confidence estimates accurately identify inputs outside the model, and that the explanations provided by nearest neighbors are intuitive and useful in understanding model failures.
CHARRING RATE OF COMPOSITE TIMBER PRODUCTS

Increasingly, wood members used in wood structures are structural composite lumber products. Such products include laminated veneer lumber, parallel strand lumber, and laminated strand lumber (Green 1998). To apply the calculation procedures to composite timber products, it is critical that char rate data for such products be available in the public domain. Charring data on composite lumber products in the public domain has been limited (Mikkola 1991, Getto 1998, Uesugi and others 1999). The test program reported in this paper provides these char rate data. Laminated veneer lumber (LVL) is produced by laminating veneers with the grain of each veneer parallel to the longitudinal direction of the member. Approximately 3-mm-thick laminates are glued together. Laminated strand lumber (LSL) is produced by gluing and pressing strands of wood together to form the lumber product. The strands are oriented to be parallel to the logitudinal direction of the member. In parallel strand lumber (PSL), veneers are clipped to produce 19-mm-wide strands that are aligned and pressed into the lumber product
An Event Related Potentials Study of Semantic Coherence Effect during Episodic Encoding in Schizophrenia Patients

The objective of this electrophysiological study was to investigate the processing of semantic coherence during encoding in relation to episodic memory processes promoted at test, in schizophrenia patients, by using the N400 paradigm. Eighteen schizophrenia patients and 15 healthy participants undertook a recognition memory task. The stimuli consisted of pairs of words either semantically related or unrelated to a given category name (context). During encoding, both groups exhibited an N400 external semantic coherence effect. Healthy controls also showed an N400 internal semantic coherence effect, but this effect was not present in patients. At test, related stimuli were accompanied by an FN400 old/new effect in both groups and by a parietal old/new effect in the control group alone. In the patient group, external semantic coherence effect was associated with FN400, while, in the control group, it was correlated to the parietal old/new effect. Our results indicate that schizophrenia patients can process the contextual information at encoding to enhance familiarity process for related stimuli at test. Therefore, cognitive rehabilitation therapies targeting the implementation of semantic encoding strategies can mobilize familiarity which in turn can overcome the recollection deficit, promoting successful episodic memory performance in schizophrenia patients.
Turtle Carapace Anomalies: The Roles of Genetic Diversity and Environment

Background Phenotypic anomalies are common in wild populations and multiple genetic, biotic and abiotic factors might contribute to their formation. Turtles are excellent models for the study of developmental instability because anomalies are easily detected in the form of malformations, additions, or reductions in the number of scutes or scales. Methodology/Principal Findings In this study, we integrated field observations, manipulative experiments, and climatic and genetic approaches to investigate the origin of carapace scute anomalies across Iberian populations of the European pond turtle, Emys orbicularis. The proportion of anomalous individuals varied from 3% to 69% in local populations, with increasing frequency of anomalies in northern regions. We found no significant effect of climatic and soil moisture, or climatic temperature on the occurrence of anomalies. However, lower genetic diversity and inbreeding were good predictors of the prevalence of scute anomalies among populations. Both decreasing genetic diversity and increasing proportion of anomalous individuals in northern parts of the Iberian distribution may be linked to recolonization events from the Southern Pleistocene refugium. Conclusions/Significance Overall, our results suggest that developmental instability in turtle carapace formation might be caused, at least in part, by genetic factors, although the influence of environmental factors affecting the developmental stability of turtle carapace cannot be ruled out. Further studies of the effects of environmental factors, pollutants and heritability of anomalies would be useful to better understand the complex origin of anomalies in natural populations.