Miracle-dz/UniFAR-FTUs huggingface dataset:
Design optimization of a morphing flap device using variable stiffness materials

Morphing structures that are both light-weight and remain conformal to the airfoil are promising candidates for the next generation of aircraft high-lift systems. Notably, variable stiffness materials have also been studied for the application in morphing structures for their potential to enhance structural performance. In this study, a design optimization has been conducted for a morphing trailing edge using a honeycomb core of axial variable stiffness. Utilizing variable stiffness materials in morphing trailing edge leads to a possible reduction in the actuation energy requirement and also enables geometric control of the deformed morphing trailing edge, resulting in enhanced aerodynamic and aeroacoustic performance of the airfoil. Firstly, effects of geometric changes in the deformed morphing trailing edge on the aerodynamic performance of airfoils are characterised through wind tunnel tests. A design optimization is then carried out to inversely identify the honeycomb core axial stiffness parameters which match the target trailing edge deformation shape. In the optimization scheme, a layer-wise sandwich beam model is developed to predict the structural behaviour of the flap with the material stiffness variation considered. Twodimensional fluid/structure static aeroelastic interaction analysis coupling the beam model to an aerodynamic routine is performed in the design optimization using chosen material properties. Optimization results indicate that variable stiffness material provides performance improvement for morphing structures and the present model can be used in the preliminary design of morphing trailing edge devices using variable stiffness materials.
Mixtures of Participation and Frequency During Criminal Careers Over the Life Span

Recent advances and debates surrounding general/developmental and static/dynamic theories of crime can be traced to the 1986 National Academy of Science Report on criminal careers and the discussion it generated. A key point of contention lies in the interpretation of the age-crime curve. For Gottfredson and Hirschi, the decline in the agecrime curve in early adulthood reflects decreasing individual offending frequency (λ) after the peak. Blumstein et al. claim that the decline in the aggregate age-crime curve can also be attributable to the termination of criminal careers, and the average value of λ could stay constant (or increase with age) for those offenders who remain active after that peak. Using data from the Criminal Career and Life Course Study including information on criminal convictions over 60 years of almost 5,000 persons convicted in the Netherlands and applying a Two-Part Growth Model that explicitly distinguishes between participation and frequency the paper assesses the participation/frequency debate. Results suggest that the decline in the age-crime curve in early adulthood reflects both decreasing individual offending participation and frequency after the peak, that the probabilities of participation and frequency are significantly related at the individual level, and that sex and marriage influence both participation and frequency.
Revisiting Criteria for Plant MicroRNA Annotation in the Era of Big Data[OPEN]

MicroRNAs (miRNAs) are ∼21-nucleotide-long regulatory RNAs that arise from endonucleolytic processing of hairpin precursors. Many function as essential posttranscriptional regulators of target mRNAs and long noncoding RNAs. Alongside miRNAs, plants also produce large numbers of short interfering RNAs (siRNAs), which are distinguished from miRNAs primarily by their biogenesis (typically processed from long double-stranded RNA instead of single-stranded hairpins) and functions (typically via roles in transcriptional regulation instead of posttranscriptional regulation). Next-generation DNA sequencing methods have yielded extensive data sets of plant small RNAs, resulting in many miRNA annotations. However, it has become clear that many miRNA annotations are questionable. The sheer number of endogenous siRNAs compared with miRNAs has been a major factor in the erroneous annotation of siRNAs as miRNAs. Here, we provide updated criteria for the confident annotation of plant miRNAs, suitable for the era of “big data” from DNA sequencing. The updated criteria emphasize replication and the minimization of false positives, and they require next-generation sequencing of small RNAs. We argue that improved annotation systems are needed for miRNAs and all other classes of plant small RNAs. Finally, to illustrate the complexities of miRNA and siRNA annotation, we review the evolution and functions of miRNAs and siRNAs in plants.
Structure-based Design, Synthesis, Biochemical and Pharmacological Characterization of Novel Salvinorin A Analogues as Active State Probes of the κ -Opioid Receptor

Salvinorin A, the most potent naturally occurring hallucinogen, has gained increasing attention since the κ -opioid receptor (KOR) was identified as its principal molecular target by us (Roth et al, PNAS, 2002). Here we report the design, synthesis and biochemical characterization of novel, irreversible, salvinorin A-derived ligands suitable as active state probes of the KOR. Based on prior substituted cysteine accessibility and molecular modeling studies, C315 7.38 was chosen as a potential anchoring point for covalent labeling of salvinorin A-derived ligands. Automated docking of a series of potential covalently-bound ligands suggested that either a haloacetate moiety or other similar electrophilic groups could irreversibly bind with C315 7.38 . 22-thiocyanatosalvinorin A (RB-64) and 22-chlorosalvinorin A (RB-48) were both found to be extraordinarily potent and selective KOR agonists in vitro and in vivo . As predicted based on molecular modeling studies, RB-64 induced wash-resistant inhibition of binding with a strict requirement for a free cysteine in or near the binding pocket. Mass spectrometry (MS) studies utilizing synthetic KOR peptides and RB-64 supported the hypothesis that the anchoring residue was C315 7.38 and suggested one biochemical mechanism for covalent binding. These studies provide direct evidence for the presence of a free cysteine in the agonist-bound state of KOR and provide novel insights into the mechanism by which salvinorin A binds to and activates KOR. and 16 dB above the 62-dB background, 4 of each intensity, 20 msec in length) that were not paired with startle stimuli (prepulse-only trials), and 32 trials of prepulse stimuli (4, 8, 12, and 16 dB above the 62-dB background, 8 at each intensity) paired with the 120 dB startle stimulus given 100 msec following the onset of the prepulse stimulus. Trials were separated by a variable interval (8–15 10sec) and total test-time lasted 26–30 min for each animal. The data were analyzed with SPSS 11 programs (SPSS Inc.) and are presented as means ± standard error of the mean. Differences in treatment effects on null activity, baseline startle responses, and overall PPI were analyzed with ANOVA, with the main effects of dose nested within compound. Repeated measures ANOVA (RMANOVA) was used to examine the effects of salvinorin A and RB-64 on prepulse-dependent PPI, with prepulse intensity (4, 8, 12, and 16 dB) as the within subjects effect, and compound and dose as the between subjects effects (dose nested within compound). Differences between treatment groups were determined with Bonferroni corrected pair-wise comparisons. In all cases, p < 0.05 was considered statistically significant. < 0.05 compared to vehicle controls; a plus sign (+) p < 0.05 in comparisons of prepulse-dependent PPI at the 4-, 8-, 12-, and 16-dB prepulses within a single treatment.
Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight

Deep reinforcement learning has shown promising results in learning control policies for complex sequential decision-making tasks. However, these neural network-based policies are known to be vulnerable to adversarial examples. This vulnerability poses a potentially serious threat to safety-critical systems such as autonomous vehicles. In this paper, we propose a defense mechanism to defend reinforcement learning agents from adversarial attacks by leveraging an action-conditioned frame prediction module. Our core idea is that the adversarial examples targeting at a neural network-based policy are not effective for the frame prediction model. By comparing the action distribution produced by a policy from processing the current observed frame to the action distribution produced by the same policy from processing the predicted frame from the action-conditioned frame prediction module, we can detect the presence of adversarial examples. Beyond detecting the presence of adversarial examples, our method allows the agent to continue performing the task using the predicted frame when the agent is under attack. We evaluate the performance of our algorithm using five games in Atari 2600. Our results demonstrate that the proposed defense mechanism achieves favorable performance against baseline algorithms in detecting adversarial examples and in earning rewards when the agents are under attack.
V-block refractometer for monitoring the production of optical glasses

Highly chromatic corrected optical systems rely on optical glasses with precise optical positions represented by refractive index and Abbe number. A modern production of optical glasses requires an economical, fast and accurate way of monitoring its fabrication. We demonstrate that an automated Hilger-Chance type refractometer fulfills all these needs. Therefore the uncertainty of a set of optical glasses is analyzed on the basis of a high number and long time reproducibility measurements. It turns out that the standard deviations after several hundreds of measurements taken over almost an decade in refraction is better than 10-5 in refraction and 0.02% in dispersion.
Immunomodulatory effects of foreskin mesenchymal stromal cells on natural killer cells

Foreskin‐mesenchymal stromal cells (FSK‐MSCs) are immune‐privileged thus making them valuable immunotherapeutic cell product. Characterization of the relationship between FSK‐MSCs and natural killer (NK) cells is essential to improve cell‐based therapy. In the present study, we studied for the first time FSK‐MSCs‐NK interaction and showed that the result of such cross talk was robustly dependent on the type of cytokines (IL‐2, IL‐12, IL‐15, and IL‐21) employed to activate NK cells. Distinctly activated‐NK cells showed uneven cytotoxicity against FSK‐MSCs, triggering their death in fine. The expression of different cell‐surface ligands (CD112, CD155, ULPB‐3) and receptors (LAIR, KIRs) ensuring such interaction was altered following co‐culture of both populations. Despite their partial negative effect on NK cell proliferation, FSK‐MSCs boosted the capacity of activated NK‐cells to secrete IFN‐γ and TNF‐α. Moreover, FSK‐MSCs enhanced degranulation of NK cells, reinforced secretion of perforin and granzymes, while only modestly increased ROS production. On the other hand, FSK‐MSCs‐mediated expression of C1 and B9 serpins was significantly lowered in the presence of activated NK cells. Altogether, our results highlight major immunological changes following FSK‐MSCs‐NK interaction. Understanding these outcomes will therefore enhance the value of the therapeutic strategy.
NASA Technical Memorandum 106945 Anny Research Laboratory Memorandum Report ARL-MR-233 Demonstration of a Stabilized AluminalEthanol Colloidal Dispersion Technique for Seeding High Temperature Air Flows

Laser anemometry enables the measurement of complex flow fields via the light scattered from small particles entrained in the flow. In the study of turbomachinery, refractory seed materials are required for seeding the flow due to the high temperatures encountered. In this work we present a pH stabilization technique commonly employed in ceramic processing to obtain stable dispersions for generating aerosols of refractory seed material. By adding submicron alumina particles to a preadjusted pH solution of ethanol , a stable dispersion is obtained which when atomized, produces a high quality aerosol. Commercial grade alumina powder is used with a moderate size distribution. Other metal oxide powders in various polar solvents could also be used once the point of zero charge (pHpzC> of the powder in the solvent has been determined. Laser anemometry measurements obtained using the new seeding technique are compared to measurements obtained using Polystyrene Latex (PSL) spheres as the seed material.
Active skeleton for non-rigid object detection

We present a shape-based algorithm for detecting and recognizing non-rigid objects from natural images. The existing literature in this domain often cannot model the objects very well. In this paper, we use the skeleton (medial axis) information to capture the main structure of an object, which has the particular advantage in modeling articulation and non-rigid deformation. Given a set of training samples, a tree-union structure is learned on the extracted skeletons to model the variation in configuration. Each branch on the skeleton is associated with a few part-based templates, modeling the object boundary information. We then apply sum-and-max algorithm to perform rapid object detection by matching the skeleton-based active template to the edge map extracted from a test image. The algorithm reports the detection result by a composition of the local maximum responses. Compared with the alternatives on this topic, our algorithm requires less training samples. It is simple, yet efficient and effective. We show encouraging results on two widely used benchmark image sets: the Weizmann horse dataset [7] and the ETHZ dataset [16].
Localization of Secondary Metabolites in Marine Invertebrates: Contribution of MALDI MSI for the Study of Saponins in Cuvierian Tubules of H. forskali

Background Several species of sea cucumbers of the family Holothuriidae possess a particular mechanical defense system called the Cuvierian tubules (Ct). It is also a chemical defense system as triterpene glycosides (saponins) appear to be particularly concentrated in Ct. In the present study, the precise localization of saponins in the Ct of Holothuria forskali is investigated. Classical histochemical labeling using lectin was firstly performed but did not generate any conclusive results. Thus, MALDI mass spectrometry Imaging (MALDI-MSI) was directly applied and completed by statistical multivariate tests. A comparison between the tubules of relaxed and stressed animals was realized. Results These analyses allowed the detection of three groups of ions, corresponding to the isomeric saponins of the tubules. Saponins detected at m/z 1287 and 1303 were the most abundant and were apparently localized in the connective tissue of the tubules of both relaxed and stressed individuals. Saponins at m/z 1125 and 1141 were detected in lower amount and were present in tissues of relaxed animals. Finally, saponin ions at 1433, 1449, 1463 and 1479 were observed in some Ct of stressed holothuroids in the outer part of the connective tissue. The saponin group m/z 14xx seems therefore to be stress-specific and could originate from modifications of the saponins with m/z of 11xx. Conclusions All the results taken together indicate a complex chemical defense mechanism with, for a single organ, different sets of saponins originating from different cell populations and presenting different responses to stress. The present study also reflects that MALDI-MSI is a valuable tool for chemical ecology studies in which specific chemical signalling molecules like allelochemicals or pheromones have to be tracked. This report represents one of the very first studies using these tools to provide a functional and ecological understanding of the role of natural products from marine invertebrates.
NBTI-Induced Delay Degradation Analysis of FPGA Routing Structures

Reliability issues, such as soft errors, process variations and Negative Bias Temperature Instability (NBTI), become dominant on Field Programmable Gate Arrays (FPGAs) fabricated in a nanometer process. We focus on aging degradation by NBTI, which causes threshold voltage shifts on PMOS transistors. We characterize delay degradation in the routing structures on FPGAs. The rising and falling delays vary due to NBTI and heavily depend on circuit configurations. In the independent routing switch, the delay fluctuation due to NBTI can be minimized by transistor sizing. The falling delay does not change after 10-years degradation. In the routing structures composed of the routing switches and wires, the delay fluctuation depends on the wire length and can be minimized to optimize the wire length. We also show that the signal flipping can reduce the delay degradation from 11.3% to 2.76% on the routing resources.
Profiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring device

Wearable physiological monitors are becoming increasingly commonplace in the consumer domain, but in literature there exists no substantive studies of their performance when measuring the physiology of ambulatory patients. In this Letter, the authors investigate the reliability of the heart-rate (HR) sensor in an exemplar ‘wearable’ wrist-worn monitoring system (the Microsoft Band 2); their experiments quantify the propagation of error from (i) the photoplethysmogram (PPG) acquired by pulse oximetry, to (ii) estimation of HR, and (iii) subsequent calculation of HR variability (HRV) features. Their experiments confirm that motion artefacts account for the majority of this error, and show that the unreliable portions of HR data can be removed, using the accelerometer sensor from the wearable device. The experiments further show that acquired signals contain noise with substantial energy in the high-frequency band, and that this contributes to subsequent variability in standard HRV features often used in clinical practice. The authors finally show that the conventional use of long-duration windows of data is not needed to perform accurate estimation of time-domain HRV features.
Age and Sex Differences in Long-Term Outcomes Following Implantable Cardioverter-Defibrillator Placement in Contemporary Clinical Practice: Findings From the Cardiovascular Research Network

Background Patient sex and age may influence rates of death after receiving an implantable cardioverter-defibrillator for primary prevention. Differences in outcomes other than mortality and whether these differences vary by heart failure symptoms, etiology, and left ventricular ejection fraction are not well characterized. Methods and Results We studied 2954 patients with left ventricular ejection fraction ≤0.35 undergoing first-time implantable cardioverter-defibrillator for primary prevention within the Cardiovascular Research Network; 769 patients (26%) were women, and 2827 (62%) were aged >65 years. In a median follow-up of 2.4 years, outcome rates per 1000 patient-years were 109 for death, 438 for hospitalization, and 111 for heart failure hospitalizations. Procedure-related complications occurred in 8.36%. In multivariable models, women had significantly lower risks of death (hazard ratio 0.67, 95% CI 0.56 to 0.80) and heart failure hospitalization (hazard ratio 0.82, 95% CI 0.68 to 0.98) and higher risks for complications (hazard ratio 1.38, 95% CI 1.01 to 1.90) than men; patients aged >65 years had higher risks of death (hazard ratio 1.55, 95% CI 1.30 to 1.86) and heart failure hospitalization (hazard ratio 1.25, 95% CI 1.05 to 1.49) than younger patients. Age and sex differences were generally consistent in strata according to symptoms, etiology, and severity of left ventricular systolic dysfunction, except the higher risk of complications in women, which differed by New York Heart Association classification (P=0.03 for sex–New York Heart Association interaction), and the risk of heart failure hospitalization in older patients, which differed by etiology of heart failure (P=0.05 for age–etiology interaction). Conclusions The burden of adverse outcomes after receipt of an implantable cardioverter-defibrillator for primary prevention is substantial and varies according to patient age and sex. These differences in outcome generally do not vary according to baseline heart failure characteristics.
Application of an Improved Ant Colony Algorithm in Vehicle Routing Problem

Ant colony algorithm is prone to falling into local optima during the search process. In order to enhance the exploration ability of the algorithm, a hybrid ant colony algorithm with hierarchical optimization is proposed by combining the ant colony algorithm and neighborhood search strategy. The algorithm is divided into two stages: initial solution and precision optimization. In the initial solution stage, ant colony algorithm is mainly used to find paths, and neighborhood search strategy is combined to perturb and increase the diversity of solutions. After the ant colony algorithm obtains the initial solution, the algorithm enters the accuracy optimization stage and performs deep neighborhood transformation on the initial optimal value to improve the solution accuracy. The performance of the algorithm was verified using a vehicle routing problem test set, and the results showed that the improved ant colony algorithm in this paper can achieve good optimization results in different scale vehicle routing problem examples.
Determination of border irregularity in dermoscopic color images of pigmented skin lesions

Malignant melanoma, which is the most dangerous type of skin cancer, is commonly diagnosed in all people, regardless of age, gender, or race. In the last several years an increasing melanoma incidence and mortality rate has been observed worldwide. In this research we present a new approach to the detection and classification of border irregularity, one of the major parameter in a widely used diagnostic algorithm ABCD rule of dermoscopy. Accurate assessment of irregular borders is clinically important due to a significantly different occurrence in benign and malignant skin lesions. In this paper we describe a complex algorithm containing following steps: image enhancement, lesion segmentation, border irregularity detection as well as classification. The algorithm has been tested on 300 dermoscopic images and achieved a detection of 79% and classification accuracy of 90%. Compared to state-of-the-art, we obtain improved classification accuracy.