Miracle-dz/UniFAR-FTUs huggingface dataset:
Smart friction driven systems

Vibration properties of most assembled mechanical systems depend on frictional damping in joints. The nonlinear transfer behavior of the frictional interfaces often provides the dominant damping mechanism in a built-up structure and plays an important role in the vibratory response of the structure (Gaul and Nitsche 2001 Appl. Mech. Rev. 54 93–105). For improving the performance of systems, many studies have been carried out to predict, measure and/or enhance the energy dissipation of friction. To enhance the friction damping in joint connections a semi-active joint is investigated. A rotational joint connection is designed and manufactured such that the normal force in the friction interface can be influenced with a piezoelectric stack disc. With the piezoelectric device the normal force and thus the friction damping in the joint connection can be controlled. A control design method, namely semi-active control, is investigated. The recently developed LuGre friction model is used to describe the nonlinear transfer behavior of joints. This model is based on a bristle model and turns out to be highly suitable for systems assembled by such smart joints. Those systems can also be regarded as friction driven systems, since the energy flow is controlled by smart joints. The semi-active method is well suited for large space structures since the friction damping in joints turned out to be a major source of damping. To show the applicability of the proposed concept to large space structures a two-beam system representing a part of a large space structure is considered. Two flexible beams are connected with a semi-active joint connection. It can be shown that the damping of the system can be improved significantly by controlling the normal force in the semi-active joint connection. Experimental results validate the damping improvement due to the semi-active friction damping.
Antigens from Actinomyces Species and Their Value in Identification

Actinomyces have a complex antigenic structure that includes neutral cell wall carbohydrate and some polypeptide containing charged antigens. Wall carbohydrate can be prepared in a relatively pure form from cell walls or by DEAE Sephadex chromatography of acid extracts and supernatant culture fluid. Charged antigens are generally eluted in groups by batch-elution from columns. Cell wall carbohydrate can be responsible for species-specific reactions and cross-reactions, and strains may possess more than one cell wall carbohydrate determinant. The charged antigens also can be species specific, but they cause some cross-reactions, particularly those between the A israelii serotypes. Autoclave extracts of strains, tested against antiserums reacting with cell wall carbohydrate, may be valuable in routine identification of isolates.
On the solvability of the localization problem in robot networks

This paper contributes to the problem of deterministic localization of robot networks using local and relative observations only. This is an important issue in collective and cooperative robotics where global positioning systems are not available, and the basic premise is the localization ability of the group. We prove that, giving a set of relative observations made by the robots, the unique non ambiguous pose estimation of the robot network in a deterministic way, is a NP-hard problem. This means that no polynomial-time algorithm can deterministically solve the unique pose estimation problem based on relative observations. The consequence is that no guaranty can be provided, in a polynomial time, that the possibly estimated poses of the robots, will correspond to the effective (actual) ones. The proof is based on complexity theory. We build appropriate polynomial-time reductions acting on the localization problem and leading to well known NP-hard problems. The paper gives some tracks to overcome this issue.
USING ARTHROSCOPY TO OBSERVE THE EFFECT OF LIVER-SOFTENING MEDICINE ON KNEE OSTEOARTHRITIS

Background: Arthroscopy was used to observe the clinical effect of liver-softening medicine for treating knee osteoarthritis (OA). Materials and Methods: Forty knee OA patients with cartilage classifications of Outerbridge grade II, III, or II plus III determined via arthroscopy were randomly assigned to a treatment of liver-softening medicine plus glucosamine or a control treatment of glucosamine alone. Clinical observation and determination of the comprehensive effect score were performed at 60, 120, and 180 days. A second arthroscopy was performed at 180 days. Results: Signs and symptoms significantly improved at different time points in the treatment group. The effects in the treatment group were better than those in the control group. When analyzing the cartilage during the second arthroscopy, no further degeneration was observed. Conclusions: After arthroscopic debridement, the treatment of knee OA with liver-softening medicine in conjunction with glucosamine is a feasible and effective solution.
Identifying the Main Mosquito Species in China Based on DNA Barcoding

Mosquitoes are insects of the Diptera, Nematocera, and Culicidae families, some species of which are important disease vectors. Identifying mosquito species based on morphological characteristics is difficult, particularly the identification of specimens collected in the field as part of disease surveillance programs. Because of this difficulty, we constructed DNA barcodes of the cytochrome c oxidase subunit 1, the COI gene, for the more common mosquito species in China, including the major disease vectors. A total of 404 mosquito specimens were collected and assigned to 15 genera and 122 species and subspecies on the basis of morphological characteristics. Individuals of the same species grouped closely together in a Neighborhood-Joining tree based on COI sequence similarity, regardless of collection site. COI gene sequence divergence was approximately 30 times higher for species in the same genus than for members of the same species. Divergence in over 98% of congeneric species ranged from 2.3% to 21.8%, whereas divergence in conspecific individuals ranged from 0% to 1.67%. Cryptic species may be common and a few pseudogenes were detected.
End to End Delay Analysis of Prominent On-demand Routing Protocols

An ad hoc network is a collection of wireless mobile nodes forming a dynamic network topology without the use of any pre-existing network infrastructure. As the wireless links are highly error prone and can go down frequently due to mobility of nodes, therefore, efficient routing is a very critical task due to highly dynamic environment. In this research paper, the behavioural study of DSR and AODV, prominent on-demand routing protocols, has been done by varying the network size over network simulator NS-2. An effort has been made to perform simulation using a new random way point self created network scenario. The performance of either protocol has been analyzed using end to end delay by varying pause time. Based on the performance analysis, recommendations have been made about the significance of either protocol under different circumstances. The analysis conclude that both protocols are good in performance in their own categories but still the emphasis of efficient routing can be on AODV as it performs better than DSR in all circumstances.
Facility‐Level Percutaneous Coronary Intervention Readmission Rates Are Not Associated With Facility‐Level Mortality: Insights From the VA Clinical Assessment, Reporting, and Tracking (CART) Program

Background Thirty‐day readmission after percutaneous coronary intervention (PCI) is common, costly, and linked to poor patient outcomes. Accordingly, facility‐level 30‐day readmission rates have been considered as a potential quality measure. However, it is unknown whether facility‐level 30‐day readmission rates are associated with facility‐level mortality. We sought to determine the effect of 30‐day readmissions after PCI on mortality at both the patient and facility level in the Veterans Administration hospital system. Methods and Results We included all patients who underwent PCI in the Veterans Administration hospital system nationally from October 2007 through August 2012, comparing all‐cause mortality rates between patients with and without 30‐day readmissions following PCI. Patients were then aggregated at the hospital level to evaluate the correlation between hospital‐level readmission rates with hospital‐level 1‐year mortality rates. Among 41 069 patients undergoing PCI at 62 sites, 12.2% were readmitted within 30 days of discharge. Patients with 30‐day readmission had higher risk‐adjusted mortality (hazard ratio 1.53, 95% CI 1.44–1.63, P<0.0001). Facilities varied widely in 30‐day readmission rates (systemwide range of 6.6–19.4%, median 11.8%, interquartile range 10.0–13.2%); however, adjusted facility‐level readmission rates were not correlated with adjusted 1‐year mortality rates. Conclusions Thirty‐day readmissions after PCI are common and are a significant risk factor for mortality for individual patients even after robust statistical adjustment for clinical confounding. However, lack of correlation between readmission and mortality at the facility level suggests that quality improvement based on facility‐level readmission rates will not modify mortality in this high‐risk group.
Long-term effects of a partially supervised conditioning programme in cystic fibrosis

Little is known about the long-term persistence of positive effects induced by a physical conditioning programme in cystic fibrosis. Therefore, this study determined the effects of a 6-month conditioning programme on peak oxygen uptake (primary outcome) and other markers of fitness, physical activity, anthropometry, lung function and quality of life (secondary outcomes), 18 and 24 months after the programme was initiated. Patients with cystic fibrosis aged 12–40 yrs were randomly assigned to an intervention (n = 23) and a control (n = 15) group. The intervention group consented to add 3 h of sports per week for ≥6 months to their previous activities. Controls were asked to maintain their level of activity for 12 months. Patients were seen at baseline and after 3, 6, 12, 18 and 24 months. There was no significant difference between groups at baseline. The intervention induced positive effects on peak oxygen uptake (difference in changes from baseline to the 18- and 24-month assessments between groups: 3.72±1.23 mL·min−1·kg−1; p<0.01), maximal workload (0.37±0.11 W·kg−1; p<0.01), vigorous physical activity (1.63±0.82 h·week−1; p<0.05), forced vital capacity (6.06±2.87% predicted; p<0.05) and perceived health (9.89±4.72; p<0.05). A home-based partially supervised physical conditioning programme can improve physical fitness, lung function and perceived health long after the intervention has ended.
Dynamic Wordclouds and Vennclouds for Exploratory Data Analysis

The wordcloud is a ubiquitous visualization of human language, though it falls short when used for exploratory data analysis. To address some of these shortcomings, we give the viewer explicit control over the creation of the wordcloud, allowing them to interact with it in real time‐ a dynamic wordcloud. This allows iterative adaptation of the visualization to the data and inference task at hand. We next present a principled approach to visualization which highlights the similarities and differences between two sets of documents ‐ a Venncloud. We make all the visualization code (primarily JavaScript) freely available.
Modeling Of Microstructure Evolution Of BCC Metals Subjected To Severe Plastic Deformation

Prediction of microstructure evolution and properties of ultrafine‐grained materials is one of the most significant, current problems in materials science. Several advanced methods of analysis can be applied for this issue: vertex models, phase field models, Monte Carlo Potts, finite element method (FEM) discrete element method (DEM) and finally cellular automata (CA). The main asset of the CA is ability for a close correlation of the microstructure with the mechanical properties in micro‐ and meso‐scale simulation. Joining CA with the DEM undoubtedly improves accuracy of modeling of coupled phenomena during the innovative forming processes in both micro‐ and macro‐scale. Deformation in micro‐scale shows anisotropy, which connected with that the polycrystalline material contains grains with different crystallographic orientation, and grain deformation is depended from configuration of directions of main stresses and axis of grain. Then, CA and DEM must be joint solutions of crystal plasticity theory. In t.
Experience-Driven Plasticity of Visual Cortex Limited by Myelin and Nogo Receptor

Monocular deprivation normally alters ocular dominance in the visual cortex only during a postnatal critical period (20 to 32 days postnatal in mice). We find that mutations in the Nogo-66 receptor (NgR) affect cessation of ocular dominance plasticity. In NgR–/– mice, plasticity during the critical period is normal, but it continues abnormally such that ocular dominance at 45 or 120 days postnatal is subject to the same plasticity as at juvenile ages. Thus, physiological NgR signaling from myelin-derived Nogo, MAG, and OMgp consolidates the neural circuitry established during experience-dependent plasticity. After pathological trauma, similar NgR signaling limits functional recovery and axonal regeneration.
Field Spectroscopy Measurements over Asprokremmos Dam in Cyprus Intended for Water Quality Monitoring

High concentrations of suspended particulate matter in reservoir waters directly affect the water treatment plants by occurring damages to the filters during the pretreatment. The objective of this project is to define the support that can be derived from the use of remote sensing techniques in order to determine the spatial variations of Total Suspended Solids (TSS) in Asprokremmos Dam in Paphos District in Cyprus. Such techniques have been successfully applied to the retrieval of TSS concentration and other water quality parameters in various geographical locations and environmental settings. This paper describes the results obtained by an existing running campaign in which in-situ spectroradiometric measurements and water sampling measurements of turbidity have been acquired at the study area. A GER-1500 field sperctro-radiometer equipped with a fibre optic probe is used to retrieve the spectral signatures of the Asprokremmos Dam and a portable turbidity meter is used for the determination of turbidity values. Ground-truth data based on the spectro-radiometric measurements were simulated to comply with the Landsat TM/ETM+ visible and infrared bands, so that identification of the ‘best-suited’ spectral region in which turbidity can be retrieved, was performed.
Progressive Clustering with Learned Seeds: An Event Categorization System for Power Grid

Advances in computational intelligence provide improved solutions to many challenging software engineering problems. Software has long been deployed for infrastructure management of utilities, such as the electric power grid. System intelligence is in increasing demand for system control and resource allocation. We present a model for electrical event categorization in a power grid system: Progressive Clustering with Learned Seeds (PCLS) – a learning method that provides stable and promising categorization results from a very small labeled data. It benefits from supervision but maximally allows patterns be discovered by the data itself. We find it effectively captures the dynamics of a real world system over time.
Ant colony clustering based on sampling for community detection

Community structure detection in large-scale complex networks has been intensively investigated in recent years. In this paper, we propose a new framework which employs the ant colony clustering algorithm based on sampling to discover communities in large-scale complex networks. The algorithm firstly samples a small number of representative nodes from the large-scale network; secondly it uses the ant colony clustering algorithm to cluster the sampled nodes; thirdly it assigns the un-sampled nodes into the detected communities according to the similarity metric; finally it merges the initial clustering result to sustainably increase the modularity function value of the detection results. A significant advantage of our algorithm is that the sampling method greatly reduces the scale of the problem. Experimental results on computer-generated and real-world networks show the efficiency of our method.
Application of computational geometry in coordinate measurement

Algorithms for calculating the minimum zone deviation for various geometric forms like straightness, flatness, circularity, spherecity and cylindricity have been successfully established by a number. This paper presents simple and robust algorithms based on computational geometric techniques and discusses them from another point of view. The complexity issues are also mentioned.
B‐spline Based Multi‐organ Detection in Magnetic Resonance Imaging

In the context of the female pelvic medicine, non‐invasive magnetic resonance imaging is widely used for the diagnosis of pelvic floor disorders. Nowadays, in the clinical routine, diagnoses rely largely on human interpretation of medical images, on the experience of physicians, with sometimes subjective interpretations. Hence, image correlation methods would be an alternative way to assist physicians to provide more objective analyses with standard procedures and parametrisation for patient‐specific cases. Moreover, the main symptoms of pelvic system pathologies are abnormal mobilities. The finite element model simulation is a powerful tool for understanding such mobilities. Both the patient‐specific simulation and the image analysis require accurate and smooth geometries of the pelvic organs. This paper introduces a new method that can be classified as a model‐to‐image correlation approach. The method performs fast semi‐automatic detection of the bladder, vagina and rectum from magnetic resonance images for geometries reconstruction and further study of the mobilities. The approach consists of fitting a B‐spline model to the organ shapes in real images via a generated virtual image. We provided efficient, adaptive and consistent segmentation on a dataset of 19 patient images (healthy and pathological).
Multiple-Submicron Channel Array Gate-Recessed AlGaN/GaN Fin-MOSHEMTs

In this paper, the multiple-submicron channel array gate-recessed AlGaN/GaN fin-metal-oxide-semiconductor high-electron mobility transistors (fin-MOSHEMTs) were fabricated using the photoelectrochemical oxidation method, the photoelectrochemical etching method, and the He-Cd laser interference photolithography method. The multiple-submicron channel array was formed using the He-Cd laser interference photolithography system. The gate-recessed structure and the directly grown gate oxide layer were performed using the photoelectrochemical etching method and the photoelectrochemical oxidation method, respectively. The subthreshold swing and the extrinsic transconductance were improved in the resulting devices with a narrower channel width. Furthermore, the unit gain cutoff frequency and the maximum oscillation frequency were also enhanced using a narrower channel width in the multiple-submicron channel array AlGaN/GaN fin-MOSHEMTs.
Combining Co-Training and Co-Testing for Interactive Image Segmentation

This paper presents an elastic framework with human interactions for image segmentation. Under this framework, we extract color and texture features for each pixel and consider them as two independent views. Based on pixel classification, the image segmentation can be accomplished through combining multi-view semi-supervised and active learning with human interactions. Experiments on various color images show the feasibility and effectiveness of our framework.
Analysis of a social network

Paper presents an analysis of a social network using a graph, and also taking into account the 802 post that are created by 114 users representing a social network interaction among the users. Input parameters are represented by the adjacency matrix, which is a kind of relationship between users who are nodes of social networks. Data analysis used the software UCINET 6, which is the adjacency matrix input parameter. Obtained results, as well as their interpretation, are related to the following measures: centrality (degree, betweeness, closeness) clustering coefficient, density, reach, geodesic distance, eigenvector.
From Data towards Knowledge: Revealing the Architecture of Signaling Systems by Unifying Knowledge Mining and Data Mining of Systematic Perturbation Data

Genetic and pharmacological perturbation experiments, such as deleting a gene and monitoring gene expression responses, are powerful tools for studying cellular signal transduction pathways. However, it remains a challenge to automatically derive knowledge of a cellular signaling system at a conceptual level from systematic perturbation-response data. In this study, we explored a framework that unifies knowledge mining and data mining towards the goal. The framework consists of the following automated processes: 1) applying an ontology-driven knowledge mining approach to identify functional modules among the genes responding to a perturbation in order to reveal potential signals affected by the perturbation; 2) applying a graph-based data mining approach to search for perturbations that affect a common signal; and 3) revealing the architecture of a signaling system by organizing signaling units into a hierarchy based on their relationships. Applying this framework to a compendium of yeast perturbation-response data, we have successfully recovered many well-known signal transduction pathways; in addition, our analysis has led to many new hypotheses regarding the yeast signal transduction system; finally, our analysis automatically organized perturbed genes as a graph reflecting the architecture of the yeast signaling system. Importantly, this framework transformed molecular findings from a gene level to a conceptual level, which can be readily translated into computable knowledge in the form of rules regarding the yeast signaling system, such as “if genes involved in the MAPK signaling are perturbed, genes involved in pheromone responses will be differentially expressed. ”
Working Paper Submodularity and the Evolution of Walrasian Behavior

Vega-Redondo (1997) showed that imitation leads to the Walrasian outcome in Cournot Oligopoly. We generalize his result to aggregative quasi-submodular games. Examples are the Cournot Oligopoly, Bertrand games with differentiated complementary products, CommonPool Resource games, Rent-Seeking games and generalized Nash-Demand games. JEL-Classifications: C72, D21, D43, L13.
Efficient and wideband envelope amplifiers for envelope tracking and polar transmitters

Envelope tracking provides the potential for achieving high efficiency in power amplifiers for next generation wireless transmitters with high peak-to-average ratio signals such as OFDMA. Envelope modulators with high fidelity, high efficiency and wide bandwidth are critical enablers for the widespread application of envelope tracking. This presentation reviews the development of various envelope amplifiers for applications in basestation and handset power amplifiers. Requirements of voltage swing, bandwidth, and accuracy are first described. Various technologies for envelope modulators achieving voltages as high as 50V are presented, for operation in basestations with Si-LDMOS, HVHBT, GaN RF power transistors. CMOS-based Si envelope modulator ICs for operation in wireless handsets are also discussed. Envelope tracking microwave power amplifiers that achieve overall efficiency greater than 45% for LTE in handsets and greater than 64 % efficiency in basestations are presented.