Miracle-dz/UniFAR-FTUs huggingface dataset:
Caterpillars and Fungal Pathogens: Two Co-Occurring Parasites of an Ant-Plant Mutualism

In mutualisms, each interacting species obtains resources from its partner that it would obtain less efficiently if alone, and so derives a net fitness benefit. In exchange for shelter (domatia) and food, mutualistic plant-ants protect their host myrmecophytes from herbivores, encroaching vines and fungal pathogens. Although selective filters enable myrmecophytes to host those ant species most favorable to their fitness, some insects can by-pass these filters, exploiting the rewards supplied whilst providing nothing in return. This is the case in French Guiana for Cecropia obtusa (Cecropiaceae) as Pseudocabima guianalis caterpillars (Lepidoptera, Pyralidae) can colonize saplings before the installation of their mutualistic Azteca ants. The caterpillars shelter in the domatia and feed on food bodies (FBs) whose production increases as a result. They delay colonization by ants by weaving a silk shield above the youngest trichilium, where the FBs are produced, blocking access to them. This probable temporal priority effect also allows female moths to lay new eggs on trees that already shelter caterpillars, and so to occupy the niche longer and exploit Cecropia resources before colonization by ants. However, once incipient ant colonies are able to develop, they prevent further colonization by the caterpillars. Although no higher herbivory rates were noted, these caterpillars are ineffective in protecting their host trees from a pathogenic fungus, Fusarium moniliforme (Deuteromycetes), that develops on the trichilium in the absence of mutualistic ants. Therefore, the Cecropia treelets can be parasitized by two often overlooked species: the caterpillars that shelter in the domatia and feed on FBs, delaying colonization by mutualistic ants, and the fungal pathogen that develops on old trichilia. The cost of greater FB production plus the presence of the pathogenic fungus likely affect tree growth.
Exploiting Friction in Torque Controlled Humanoid Robots

A common architecture for torque controlled humanoid robots consists in two nested loops. The outer loop generates desired joint/motor torques, and the inner loop stabilizes these desired values. In doing so, the inner loop usually compensates for joint friction phenomena, thus removing their inherent stabilizing property that may be also beneficial for high level control objectives. This paper shows how to exploit friction for joint and task space control of humanoid robots. Experiments are carried out on the humanoid robot iCub.
Feature reduction in spectral unmixing using neural networks

Spectral unmixing (SU) is a standard approach to solve the mixed pixel problem in hyperspectral (HS) images. In this study, the application of feature reduction in SU using multi-layer perceptron (MLP) with some data-independent approaches is investigated. MLP is a popular artificial neural network that can learn complex nonlinear relationships between the endmembers and the abundance fractions in HS images if it is properly trained. So far, various approaches have been introduced to extract training samples from the data itself. Since it is not possible to access the actual abundance fractions of materials in real HS images, MLP training becomes complicated. Due to a large number of bands in HS images, complexity and large training time are some of the remaining problems that would be investigated in this study. In order to overcome the problem of unavailability of the actual abundance fractions, a synthetic library is generated based on scene mixture models. And some data-independent approaches, such as discrete cosine transform and discrete wavelet transform are utilized to reduce the complexity and the training time of the MLP. The experimental results are provided using both synthetic and real datasets with different mixture models. The results show the acceptable estimated abundance fractions with root mean square error, up to 0.0008 in the linear dataset and 0.0062 in the nonlinear dataset.
A Scoring Model Based on Neutrophil to Lymphocyte Ratio Predicts Recurrence of HBV-Associated Hepatocellular Carcinoma after Liver Transplantation

Background Neutrophil to lymphocyte ratio (NLR) has been proposed to predict prognosis of hepatocellular carcinoma (HCC). However, the cut-off values are empirical. We determined the optimal cut-off value to predict HCC recurrence after liver transplantation (LT) and further established a scoring model based on NLR. Methodology/Principal Findings We analyzed the outcome of 101 HBV-associated HCC patients undergoing LT. Preoperative risk factors for tumor recurrence were evaluated by univariate analysis. By using ROC analysis, NLR≥3 was considered elevated. The disease-free survival (DFS) and overall survival (OS) for patients with high NLR was significantly worse than that for patients with normal NLR (the 5-year DFS and OS of 28.5% and 19.5% vs. 64.9% and 61.8%, respectively; P<0.001). Univariate analysis revealed that tumor size >5 cm, tumor number >3, macrovascular invasion, AFP≥400 µg/L, NLR≥3, and HBV-DNA level >5 log10 copies/mL were preoperative predictors of DFS. Cox regression analysis showed macrovascular invasion, tumor number, and high NLR were independent prognostic factors. We then established a preoperative prognostic score based on multivariate analysis. Each factor was given a score of 1. Area under the ROC curve of the score was 0.781. All nine patients with score 3 developed recurrence within 6 months after LT. Of 71 patients without vascular invasion, three patients with both tumor number >3 and NLR≥3 developed recurrence within 14 months after LT while the 5-year DFS and OS for patients with a score of 0 or 1 were 68.1% and 62.8%, respectively. Conclusions/Significance Preoperative elevated NLR significantly increases the risk of recurrence in patients underwent LT for HCC. Patients with both NLR≥3 and tumor number >3 are not a good indication for LT. Our score model may aid in the selection of patients that would most benefit from transplantation for HCC.
Subjects with Molecularly Defined Familial Hypercholesterolemia or Familial Defective apoB-100 Are Not Being Adequately Treated

Objectives To study whether subjects with a molecular genetic diagnosis of familial hypercholesterolemia (FH) or familial defective apoB-100 (FDB) are being adequately treated. Design A questionnaire regarding medical history was sent to 2611 subjects who had been provided with a molecular genetic diagnosis of FH or FDB, and a blood sample was obtained for lipid measurements. Results 956 (36.6%) of the 2611 subjects participated. The mean age for starting lipid-lowering therapy was 33.4 (±12.1) years. Among those below 18 years of age, only 20.4% were on lipid-lowering drugs, whereas 89.1% of those aged 18 and above were on lipid-lowering drugs. The mean levels of total serum cholesterol and LDL-cholesterol were 5.7 (±1.5) mmol/l and 3.9 (±1.3) mmol/l, respectively. Among those who were on lipid-lowering drugs, 29.0% and 12.2% had levels of LDL cholesterol below 3.0 mmol/l and 2.6 mmol/l, respectively. Only 47.3% of the 956 subjects were considered as being adequately treated largely due to a failure to titrate their drug regimens. From the use of cholesterol-years score, lipid-lowering therapy must start before the age of 20 in order to prevent the subjects from contracting premature coronary heart disease. Conclusion The majority of FH/FDB subjects are being diagnosed late in life and are not being adequately treated. In order to prevent them from contracting premature coronary heart disease, it is key that levels of LDL cholesterol are normalized from a young age and that sufficient doses of lipid-lowering drugs are being used.
Performance and Scalability Appraisal of Four Directed Weighted Graph Matching Algorithms: A Survey

We conduct an experimental study of four algorithms for the Weighted Graph Matching Problem (WGMP) for directed graphs. The first algorithm is based on Umeyama's Eigen-decomposition approach and provides nearly an optimum solution by means of Hermitian matrices deduced from the adjacency matrices of pairs of directed weighted graphs. The second algorithm is based on Almohamad's Symmetric ploynomial transform approach. The Symmetric polynomial transform is applied to map input data representing polynomial roots into a set of coefficients that are invariant under permutation of the roots. Assuming this transformation, the weights of two nodes can be compared one to one via their resulted invariant coefficients. The third algorithm is inspired from Almohamad's Linear programming approach where the WGMP is initially formulated in a non linear problem and then transformed into a Linear one formulated in L1 norm. In the two first algorithms, the optimum match is given by the Hungarian method when a permutation exists between each two nodes. The fourth algorithm is an improved version of the first one that gives exact results only for graphs satisfying certain conditions.
Abstract pathfinder

We present Abstract Pathfinder, an extension to the Java Pathfinder (JPF) verification tool-set that supports data abstraction to reduce the large data domains of a Java program to small, finite abstract domains, making the program more amenable to verification. We use data abstraction to compute an over-approximation of the original program in such a way that if a (safety) property is true in the abstracted program the property is also true in the original program. Our approach enhances JPF with an abstract interpreter and abstract state-matching mechanisms, together with a library of abstractions from which the user can pick which abstractions to use for a particular application. We discuss the details of our implementation together with some preliminary experiments with analyzing multi-threaded Java programs, where Abstract Pathfinder achieves significant time and memory savings as compared with plain JPF.
Discussion on coagulation of dry-jet wet spinning of polyacrylonitrile precursor

During coagulating the PAN based carbon fiber precursor in temperature as the dominant thermotropic and concentration induced forming process under variable for the double diffusion driven were discussed.and the coagulation bath pH and draft ratio on the coagulation effect of dry and wet spinning,and the quenching film,film inside droplet change,fine neck area stretching etc.were also analyzed,so as to make new interpretation under dry-jet wet spinning coagulation mechanism has certain macro control,for spinning out high quality carbon fiber strand lay a theoretical foundation.
Neural Conditional Gradients

The move from hand-designed to learned optimizers in machine learning has been quite successful for gradient-based and -free optimizers. When facing a constrained problem, however, maintaining feasibility typically requires a projection step, which might be computationally expensive and not differentiable. We show how the design of projection-free convex optimization algorithms can be cast as a learning problem based on Frank-Wolfe Networks: recurrent networks implementing the Frank-Wolfe algorithm aka. conditional gradients. This allows them to learn to exploit structure when, e.g., optimizing over rank-1 matrices. Our LSTM-learned optimizers outperform hand-designed as well learned but unconstrained ones. We demonstrate this for training support vector machines and softmax classifiers.
Use of coronary angiography and revascularization procedures following acute myocardial infarction. A European perspective.

AIMS There is little evidence to inform routine practice in the use of coronary angiography and revascularization procedures after acute myocardial infarction. Large differences in the uptake of these procedures have been reported but representative data are scarce. Outcome studies have produced opposing conclusions concerning the impact of the high rate of these cardiac procedures. METHODS AND RESULTS A population-based patient sampling approach was utilized to identify routine practice in representative samples from 11 European countries. Data were collected retrospectively on treatment in the 6 months following acute myocardial infarction (n=2807). There was wide variation in utilization of coronary angiography and revascularization procedures. Even after restricting the analysis to patients <65 years (n=1262), there remained a 6 13 fold variation in the use of these procedures. A decreased likelihood of undergoing these procedures was associated with older age. In addition, there was an independent and negative association between female sex and utilization of coronary angiography and coronary artery bypass grafting (CABG). CONCLUSION The effect on patient outcome of the observed variation in use of these procedures is not known but has important cost and resource implications for the health services. Outcome research is needed to define patient selection criteria and to measure the cost-utility of different angiography and revascularization rates.
A context-Aware Smart Home Control System based on ZigBee Sensor Network

The applications of Wireless Sensor Networks (WSN) are progressively adopting for various smart home services such as home automation, controlling smart home household appliances, constrained application services in a smart home, etc. However, enabling a seamless and ubiquitous WSN communication between the smart home appliances is still a challenging job. Therefore, in this paper, we propose a smart home control system using an Actuator based ZigBee networking (AZNET). The working of the proposed system is further divided into three phases, 1) an interference avoidance system is adopted to mitigate the effect of interference caused due to the co-existence of IEEE 802.11x based wireless local area networks (WLAN) and WSN, 2) a sensor-based smart light control system is used to fulfill the light requirement in the smart home using the sunlight with light source, and 3) an autonomous home management system is used to regulate the usage time of the electronic appliances in the smart home. The smart is tested in real time environment to use the sunlight with light sources in a various time of the day. Similarly, the performance of the proposed smart home is verified through simulation using C# programming language. The results and analysis revealed that the proposed smart home is less affected by the interference and efficient in reducing the energy consumption of the appliances available in the smart home scenario.
Integration of Spectral Reflectance across the Plumage: Implications for Mating Patterns

Background In complex sexual signaling systems such as plumage color, developmental or genetic links may occur among seemingly distinct traits. However, the interrelations of such traits and the functional significance of their integration rarely have been examined. Methodology/Principal Findings We investigated the parallel variation of two reflectance descriptors (brightness and UV chroma) across depigmented and melanized plumage areas of collared flycatchers (Ficedula albicollis), and the possible role of integrated color signals in mate acquisition. We found moderate integration in brightness and UV chroma across the plumage, with similar correlation structures in the two sexes despite the strong sexual dichromatism. Patterns of parallel color change across the plumage were largely unrelated to ornamental white patch sizes, but they all showed strong assortative mating between the sexes. Comparing different types of assortative mating patterns for individual spectral variables suggested a distinct role for plumage-level color axes in mate acquisition. Conclusions/Significance Our results indicate that the plumage-level, parallel variation of coloration might play a role in mate acquisition. This study underlines the importance of considering potential developmental and functional integration among apparently different ornaments in studies of sexual selection.
A Multiple Radar Approach for Automatic Target Recognition of Aircraft Using Inverse Synthetic Aperture Radar

Following the recent advancements in radar technologies, research on automatic target recognition using Inverse Synthetic Aperture Radar (ISAR) has correspondingly seen more attention and activity. ISAR automatic target recognition researchers aim to fully automate recognition and classification of military vehicles, but because radar images often do not present a clear image of what they detect, it is considered a challenging process to do this. Here we present a novel approach to fully automate a system with Convolutional Neural Networks (CNNs) that results in better target recognition and requires less training time. Specifically, we developed a simulator to generate images with complex values to train our CNN. The simulator is capable of accurately replicating real ISAR configurations and thus can be used to determine the optimal number of radars needed to detect and classify targets. Testing with seven distinct targets, we achieve higher recognition accuracy while reducing the time constraints that the training and testing processes traditionally entail.
Soft Spherical Tensegrity Robot Design Using Rod-Centered Actuation and Control

This paper presents the design, analysis, and testing of a fully actuated modular spherical tensegrity robot for co-robotic and space exploration applications. Robots built from tensegrity structures (composed of pure tensile and compression elements) have many potential benefits including high robustness through redundancy, many degrees-of-freedom in movement and flexible design. However, to take full advantage of these properties, a significant fraction of the tensile elements should be active, leading to a potential increase in complexity, messy cable, and power routing systems and increased design difficulty. Here, we describe an elegant solution to a fully actuated tensegrity robot: The TT-3 (version 3) tensegrity robot, developed at UC Berkeley, in collaboration with NASA Ames, is a lightweight, low cost, modular, and rapidly prototyped spherical tensegrity robot. This robot is based on a ball-shaped six-bar tensegrity structure and features a unique modular rod-centered distributed actuation and control architecture. This paper presents the novel mechanism design, architecture, and simulations of TT-3, an untethered, fully actuated cable-driven six-bar spherical tensegrity robot. Furthermore, this paper discusses the controls and preliminary testing performed to observe the system’s behavior and performance and is evaluated against previous models of tensegrity robots developed at UC Berkeley and elsewhere. [DOI: 10.1115/1.4036014]
Extrinsic regulation of hematopoietic stem cells in development, homeostasis and diseases

Lifelong generation of blood and immune cells depends on hematopoietic stem cells (HSCs). Their function is precisely regulated by complex molecular networks that integrate and respond to ever changing physiological demands of the body. Over the past several years, significant advances have been made in understanding the extrinsic regulation of HSCs during development and in homeostasis. Propelled by technical advances in the field, the cellular and molecular components of the microenvironment that support HSCs in vivo are emerging. In addition, the interaction of HSCs with their niches is appreciated as a critical contributor to the pathogenesis of a number of hematologic disorders. Here, we review these advances in detail and highlight the extrinsic regulation of HSCs in the context of development, homeostasis, and diseases. WIREs Dev Biol 2017, 6:e279. doi: 10.1002/wdev.279
Pseudo-LRU Replacement Policy in Named Data Networking Using Fat Tree DataCenter Network Architecture

Named Data Networking (NDN) is a new content centric architecture for the future Internet aiming to improve communication performance compared to coventional IP. One of the building bricks of NDN is data caching. Various caching strategies were proposed in the literature in order to improve NDN performance. But, it is still unclear which strategy performs better than the others in terms of efficient communication and energy consumption using DataCenter Networking (DCN) architectures.In this paper, we propose to evaluate a new cache replacement scheme based on Pseudo-LRU algorithm. We combine it with NDN inside a Fat Tree based DCN architecture. For that aim, we extended the ndnSIM module developped under NS-3 and ran simulations to evaluate the performance of our proposition. We also combined it with ProbCache placement scheme and compared it to conventional LRU scheme. We used evaluation metrics such as packet delay, hop count, cache hit rate and consumed energy. Simulation results show that our proposed Pseudo-LRU policy based outperforms LRU by reducing packet delay, hop count, consumed energy and increasing cache hit rate indepedently from cache size.
Progress based assist-as-needed control strategy for upper-limb rehabilitation

Assist-as-Needed (AAN) strategy is one strategy of administering robotic assistance which has gained wide acceptance in recent time and has been clinically demonstrated to provoke motor recovery in neurologically impaired patients. The underlying principle in this scheme is to provide assistance to a patient to complete desired movement only when the patient is in need of that assistance, which invariably encourages patient's active participation to provoke neuroplasticity. Effective deployment of this scheme in robot aided therapy still pose some challenges. One current difficulty is finding an appropriate method of estimating patients' functional input, or movement ability, by means on which the robot judges whether to assist or to relax the assistance. Another concern is the repeatability or consistency of the estimated subject's movement ability across a wide range of subjects with different disability level that can warrant a broad clinical adoption. Also, generally overlooked is the influence of subject's recovery progress on the modality of the AAN assistance. In this study, we propose a progress-based assist-as-needed algorithm (pAAN) which rely on subject's real-time functional ability record to drive robotic assistance. We define a novel functional ability index (FAI) on a baseline adaptive inertia related controller which decays the robotic torque assistance according to patients' progress or active participation during therapy session. Simulation studies carried out for the task of lifting a can from table to the mouth, designed in accordance with the Wolf motor function test (WMFT), have demonstrated the feasibility of the pAAN strategy.