Miracle-dz/UniFAR-FTUs huggingface dataset:
Interference Suppression Technique using Edge-removal Filter , Nulling Filter and Turbo Equalizer for Single Carrier Based Broadband Wireless Transmission

This paper proposes an interference suppression technique using edge-removal filter in the transmitter, as well as, nulling filter and turbo equalizer in the receiver for carrier interferometry (CI) based one-cell reuse single-carrier time division multiple access (TDMA) systems. In the proposed system, the desired signals in the reference cell are interfered by interference including adjacent-channel interference (ACI), cochannel interference (CCI) and intersymbol interference (ISI). At the transmitter, a CI technique is employed to generate CI signal which is equivalent to single-carrier signal with its roll-off factor of zero. After that, ACI components are eliminated by edge-removal filter. At the receiver, the received signal is transformed into frequency-domain signal by a fast Fourier transform (FFT). Co-channel interference (CCI) from adjacent cell is suppressed by applying a frequency-domain nulling filter. Then a soft canceller with minimum mean square error (SC/MMSE) based turbo equalizer is utilized to compensate for channel induced intersymbol interference (ISI) as well as extra ISI produced by the nulling filter. Computer simulation confirms that the proposed scheme can effectively suppress ACI, CCI and ISI. Keywords-interference suppression; carrier interferometry; edge-removal filter; nulling filter; turbo equalizer
An Adaptive Greedy Algorithm with Application to Sparse Narma Identification

Greedy algorithms form an essential tool for compressed sensing. However, their inherent batch mode discourages their use in time-varying environments due to significant complexity and storage requirements. In this paper a powerful greedy scheme developed in [1, 2] is converted into an adaptivealgorithmwhich is appliedto estimationof nonlinear channels. Performance is assessed via computer simulations on a variety of linear and nonlinear channels; all confirm significant improvements over conventional methods.
Elastic behavior of connectin filaments during thick filament movement in activated skeletal muscle

Connectin (also called titin) is a huge, striated muscle protein that binds to thick filaments and links them to the Z-disc. Using an mAb that binds to connectin in the I-band region of the molecule, we studied the behavior of connectin in both relaxed and activated skinned rabbit psoas fibers by immunoelectron microscopy. In relaxed fibers, antibody binding is visualized as two extra striations per sarcomere arranged symmetrically about the M-line. These striations move away from both the nearest Z-disc and the thick filaments when the sarcomere is stretched, confirming the elastic behavior of connectin within the I- band of relaxed sarcomeres as previously observed by several investigators. When the fiber is activated, thick filaments in sarcomeres shorter than 2.8 microns tend to move from the center to the side of the sarcomere. This translocation of thick filaments within the sarcomere is accompanied by movement of the antibody label in the same direction. In that half-sarcomere in which the thick filaments move away from the Z-disc, the spacings between the Z-disc and the antibody and between the antibody and the thick filaments both increase. Conversely, on the side of the sarcomere in which the thick filaments move nearer to the Z-line, these spacings decrease. Regardless of whether I-band spacing is varied by stretch of a relaxed sarcomere or by active sliding of thick filaments within a sarcomere of constant length, the spacings between the Z-line and the antibody and between the antibody and the thick filaments increase with I-band length identically. These results indicate that the connectin filaments remain bound to the thick filaments in active fibers, and that the elastic properties of connectin are unaltered by calcium ions and cross-bridge activity.
Advanced Respiratory Motion Compensation for Coronary MR Angiography

Despite technical advances, respiratory motion remains a major impediment in a substantial amount of patients undergoing coronary magnetic resonance angiography (CMRA). Traditionally, respiratory motion compensation has been performed with a one-dimensional respiratory navigator positioned on the right hemi-diaphragm, using a motion model to estimate and correct for the bulk respiratory motion of the heart. Recent technical advancements has allowed for direct respiratory motion estimation of the heart, with improved motion compensation performance. Some of these new methods, particularly using image-based navigators or respiratory binning, allow for more advanced motion correction which enables CMRA data acquisition throughout most or all of the respiratory cycle, thereby significantly reducing scan time. This review describes the three components typically involved in most motion compensation strategies for CMRA, including respiratory motion estimation, gating and correction, and how these processes can be utilized to perform advanced respiratory motion compensation.
Trajectory generation for multi-contact momentum control

Simplified models of the dynamics such as the linear inverted pendulum model (LIPM) have proven to perform well for biped walking on flat ground. However, for more complex tasks the assumptions of these models can become limiting. For example, the LIPM does not allow for the control of contact forces independently, is limited to co-planar contacts and assumes that the angular momentum is zero. In this paper, we propose to use the full momentum equations of a humanoid robot in a trajectory optimization framework to plan its center of mass, linear and angular momentum trajectories. The model also allows for planning desired contact forces for each end-effector in arbitrary contact locations. We extend our previous results on linear quadratic regulator (LQR) design for momentum control by computing the (linearized) optimal momentum feedback law in a receding horizon fashion. The resulting desired momentum and the associated feedback law are then used in a hierarchical whole body control approach. Simulation experiments show that the approach is computationally fast and is able to generate plans for locomotion on complex terrains while demonstrating good tracking performance for the full humanoid control.
METHODS FOR INCREMENTAL LEARNING: A SURVEY

Incremental learning is a machine learning paradigm where the learning process takes place whenever new example/s emerge and adjusts what has been learned according to the new example/s. The most prominent difference of incremental learning from traditional machine learning is that it does not assume the availability of a sufficient training set before the learning process, but the training examples appear over time. In this paper we discuss the methods of incremental learning which are currently available. This paper gives the overview of the current research in the incremental learning which will be beneficial to the research scalars.
The Core Extrusion Schema–Revised

Cognitive behavioral models of social anxiety disorder (SAD) suggest that fear of negative evaluation is a core fear or vulnerability for SAD. However, why negative evaluation is feared is not fully understood. It is possible that core beliefs contribute to the relationship between fear of negative evaluation and SAD. One of these beliefs may be a core extrusion schema: a constellation of beliefs that one’s true self will be rejected by others and therefore one should hide one’s true self. In the current study (N = 699), we extended research on the Core Extrusion Schema and created a shortened and revised version of the measure called the Core Extrusion Schema–Revised. The Core Extrusion Schema–Revised demonstrated good factor fit for its two subscales (Hidden Self and Rejection of the True Self) and was invariant across gender and ethnicity. The Hidden Self subscale demonstrated excellent incremental validity within the full sample as well as in participants diagnosed with generalized SAD. Specifically, the Hidden Self subscale may help explain severity of social interaction anxiety. This measure could be used with individuals diagnosed with generalized SAD to design exposures targeting these core beliefs.
N-Gram Based Authorship Attribution in Urdu Poetry

Authorship attribution is an interesting problem in Computational Linguistics. Traditional author recognition systems for electronic text rely on techniques which train the system to the specific vocabulary and writing style of the writer and apply stochastic methods to judge a given text at byte, letter or word levels. In this paper we have developed a software system to apply one existing and one modified authorship attribution technique to Urdu poetry. This paper discusses the results of this exercise and also presents the issues and procedures related to the language model training and word level n-gram based recognition system development.
Building together digital archives for research in social sciences and humanities

In order to help understand the possible interplay between transmission and digitization, a pilot project for the long-term preservation of research data in the social sciences and humanities (SSH) is presented by its two coordinators. The article provides some background context on transmission in digital form of past and present research in SSH. It shows the discrepancy between the increasing role of digital information and its fragility. It presents the standard abstract model for archival information systems and the way it was instantiated in the pilot project. It ends with some reflexive remarks on the factors that are bound to act upon the future of such projects: organizational behaviours, role of data and knowledge, communities of users, institutional issues and status of collective memory in SSH. Pour permettre de comprendre les interactions possibles entre transmission et numérisation, un projet pilote d’archivage numérique pérenne est présenté par ses deux coordinateurs. L’article évoque le contexte actuel de transmission sous forme numérique des recherches passées et présentes en sciences humaines et sociales (SHS). Il souligne l’écart entre le rôle croissant des données numériques et leur fragilité. Il présente le modèle abstrait standard d’archivage numérique pérenne et la manière dont il a été instancié dans le projet pilote. Il termine par un retour réflexif sur les facteurs qui vont conditionner l’avenir de projets similaires: choix et comportements organisationnels, rôles respectifs des données et des connaissances, constitution et comportement des communautés d’utilisateurs, statut de la mémoire collective en SHS.
Task decomposition with neuroevolution in extended predator-prey domain

Learning complex behaviour is a difficult task for any artificial agent. Decomposing a task into multiple sub-tasks, learning the sub-tasks separately, and then learning to use them as a whole is a natural way to reduce the dimensionality and complexity of the task function. This approach is demonstrated on a predator agent in the predator-prey-hunter domain. This extended domain has a new agent, a ‘hunter’, that chases the predators. The evading and chasing behaviours are learnt as separate sub-tasks by separate networks using the NEAT neuro-evolution method. A separate network is then evolved to use these networks based on the situation. Task decomposition using this approach performs significantly better in the predator-prey-hunter domain compared to a monolithic network evolved directly on the whole task.
Generation of Hydrogen Peroxide d-Amino Acid Oxidase for Antitumor Therapy via Enzymatic Tumor-targeted Delivery of Polyethylene Glycol-conjugated Updated

Hydrogen peroxide (H2O2) is a strong oxidant that induces apoptosis of tumor cells in vitro. Here, we investigated the antitumor activity of an H2O2-generating enzyme, D-amino acid oxidase (DAO), and its conjugate with polyethylene glycol (PEG; PEG-DAO). Compared with DAO, PEG-DAO showed improved pharmacokinetic parameters in mice after i.v. injection. PEG-DAO administered i.v. accumulated selectively in tumor tissue with insignificant accumulation in normal organs and tissues. To generate cytotoxic H2O2 at the tumor site, PEG-DAO was first administrated i.v. to tumor-bearing mice. After an adequate lag time, the substrate of DAO, D-proline, was injected i.p. This treatment resulted in significant suppression of tumor growth compared with tumor growth in control animals (not given treatment; P < 0.001). Similar treatment with native DAO showed no effect under the same conditions. Oxidative metabolites were significantly increased in solid tumors by administration of PEG-DAO followed by D-proline (P < 0.002, compared with the group receiving no treatment), as evidenced by thiobarbituric acid-reactive substance assay. This treatment did not affect results from the metabolites in the liver and kidney. These findings suggest that tumor-targeted delivery of DAO is accomplished by using pegylated enzyme and thereby taking advantage of the enhanced permeability and retention effect in solid tumor. PEG-DAO thus delivered together with D-proline produces remarkable antitumor activity via extensive generation of H2O2.
Dietary trans-10,cis-12 conjugated linoleic acid induces hyperinsulinemia and fatty liver in the mouse DOI 10.1194/jlr.M20008-JLR200

Conjugated linoleic acids (CLA) are a class of positional, geometric, conjugated dienoic isomers of linoleic acid (LA). Dietary CLA supplementation results in a dramatic decrease in body fat mass in mice, but also causes considerable liver steatosis. However, little is known of the molecular mechanisms leading to hepatomegaly. Although c9,t11- and t10,c12-CLA isomers are found in similar proportions in commercial preparations, the respective roles of these two molecules in liver enlargement has not been studied. We show here that mice fed a diet enriched in t10,c12-CLA (0.4% w/w) for 4 weeks developed lipoatrophy, hyperinsulinemia, and fatty liver, whereas diets enriched in c9,t11-CLA and LA had no significant effect. In the liver, dietary t10,c12-CLA triggered the ectopic production of peroxisome proliferator-activated receptor γ (PPARγ), adipocyte lipid-binding protein and fatty acid transporter mRNAs and induced expression of the sterol responsive element-binding protein-1a and fatty acid synthase genes. In vitro transactivation assays demonstrated that t10,c12- and c9,t11-CLA were equally efficient at activating PPARα, β/δ, and γ and inhibiting liver-X-receptor. Thus, the specific effect of t10,c12-CLA is unlikely to result from direct interaction with these nuclear receptors. Instead, t10,c12-CLA-induced hyperinsulinemia may trigger liver steatosis, by inducing both fatty acid uptake and lipogenesis.
Citation " for His Outstanding Discoveries on the Role of the Cerebral Cortex in Perception and Behavior. Charles G. Gross Has

radically expanded our view of the workings of the primate visual system by finding that neurons in the inferior temporal cortex respond selectively to complex features of visual objects, including faces and hands. These remarkable findings have had a major influence in the field of neuro-science and have contributed greatly to our understanding of sensory processing and pattern recognition. His research has attracted many students to his laboratory, several of whom are now outstanding investigators in their own right. His collaborative work has contributed to a better understanding of 'blindsight' and sensorimotor integration. " Biography Charlie Gross was born in Brooklyn, New York, on a Febru-ary 29th, of Communist intellectuals. His elementary school experience was a disaster, inducing hyperactivity and attention disorder. His frustrated academic drive was channeled into earning Boy Scout merit badges, making him the youngest Eagle Scout in Brooklyn. At Erasmus Hall High School, a large heterogeneous school, he fell in with a group of very smart students, which transformed him into a good student. Charlie edited the school math and science magazines and was an editor of the newspaper. He was a finalist in the West-inghouse Science Talent Search for a project in ecology— plant succession—a natural choice of topic because he had spent every summer up to that point camping with his parents on an island in Lake George, New York. At about the time that Charlie's father began to lose teaching jobs because of his politics, Charlie went off to Harvard. He would have liked to have majored in history but soon found that his politics were inconsistent with getting As, so he majored in biology. As a freshman, he took a graduate seminar in the history of biology with I. B. Cohen, and this subject has continued to be a major interest. He took physiological psychology with Phil Teitelbaum, history of psychology with E. G. Boring, and " Skinner " with B. F. Skinner, all of which had profound and permanent effects on him. Charlie researched bird navigation and published his first scientific paper with Don Griffin, codiscoverer of bat echolocation and one of the great experimental naturalists of our time. One day Griffin said, " Gross, bring me the car battery from the next room, " and Charlie replied, " What does a car battery look like? " — confirming that " you can take the boy out of Brooklyn but you …
Primary central nervous system lymphoma and glioblastoma differentiation based on conventional magnetic resonance imaging by high-throughput SIFT features

ABSTRACT Purpose of the study: Due to the totally different therapeutic regimens needed for primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM), accurate differentiation of the two diseases by noninvasive imaging techniques is important for clinical decision-making. Materials and methods: Thirty cases of PCNSL and 66 cases of GBM with conventional T1-contrast magnetic resonance imaging (MRI) were analyzed in this study. Convolutional neural networks was used to segment tumor automatically. A modified scale invariant feature transform (SIFT) method was utilized to extract three-dimensional local voxel arrangement information from segmented tumors. Fisher vector was proposed to normalize the dimension of SIFT features. An improved genetic algorithm (GA) was used to extract SIFT features with PCNSL and GBM discrimination ability. The data-set was divided into a cross-validation cohort and an independent validation cohort by the ratio of 2:1. Support vector machine with the leave-one-out cross-validation based on 20 cases of PCNSL and 44 cases of GBM was employed to build and validate the differentiation model. Results: Among 16,384 high-throughput features, 1356 features show significant differences between PCNSL and GBM with p < 0.05 and 420 features with p < 0.001. A total of 496 features were finally chosen by improved GA algorithm. The proposed method produces PCNSL vs. GBM differentiation with an area under the curve (AUC) curve of 99.1% (98.2%), accuracy 95.3% (90.6%), sensitivity 85.0% (80.0%) and specificity 100% (95.5%) on the cross-validation cohort (and independent validation cohort). Conclusions: Since the local voxel arrangement characterization provided by SIFT features, proposed method produced more competitive PCNSL and GBM differentiation performance by using conventional MRI than methods based on advanced MRI.
Single Molecule Analysis of Serotonin Transporter Regulation Using Antagonist-Conjugated Quantum Dots Reveals Restricted, p38 MAPK-Dependent Mobilization Underlying Uptake Activation

The presynaptic serotonin (5-HT) transporter (SERT) is targeted by widely prescribed antidepressant medications. Altered SERT expression or regulation has been implicated in multiple neuropsychiatric disorders, including anxiety, depression and autism. Here, we implement a generalizable strategy that exploits antagonist-conjugated quantum dots (Qdots) to monitor, for the first time, single SERT proteins on the surface of serotonergic cells. We document two pools of SERT proteins defined by lateral mobility, one that exhibits relatively free diffusion, and a second, localized to cholesterol and GM1 ganglioside-enriched microdomains, that displays restricted mobility. Receptor-linked signaling pathways that enhance SERT activity mobilize transporters that, nonetheless, remain confined to membrane microdomains. Mobilization of transporters arises from a p38 MAPK-dependent untethering of the SERT C terminus from the juxtamembrane actin cytoskeleton. Our studies establish the utility of ligand-conjugated Qdots for analysis of the behavior of single membrane proteins and reveal a physical basis for signaling-mediated SERT regulation.
Parallel Probing of Web Databases for Top-k Query Processing

A “top-k query” specifies a set of preferredvalues for the attributes of a relation and expects as a result thek objects that are “closest” to the given preferences according to some distance function. In many web applications, the relation attributes are only available viaprobesto autonomous webaccessible sources. Probing these sources sequentially to process a topk query is inefficient, since web accesses exhibit high and variable latency. Fortunately, web sources can be probed in parallel, and each source can typically process concurrent requests, although sources may impose some restrictions on the type and number of probes that they are willing to accept. These characteristics of web sources motivate the introduction of parallel top-k query processing strategies, which are the focus of this paper. We present efficient techniques that maximize source-access parallelism to minimize query response time, while satisfying source access constraints. A thorough experimental evaluation over both synthetic and real web sources shows that our techniques can be significantly more efficient than previously proposed sequential strategies. In addition, we adapt our parallel algorithms for the alternate optimization goal of minimizing source load while still exploiting source-access parallelism.
Assistant Personal Robot (APR): Conception and Application of a Tele-Operated Assisted Living Robot

This paper presents the technical description, mechanical design, electronic components, software implementation and possible applications of a tele-operated mobile robot designed as an assisted living tool. This robotic concept has been named Assistant Personal Robot (or APR for short) and has been designed as a remotely telecontrolled robotic platform built to provide social and assistive services to elderly people and those with impaired mobility. The APR features a fast high-mobility motion system adapted for tele-operation in plain indoor areas, which incorporates a high-priority collision avoidance procedure. This paper presents the mechanical architecture, electrical fundaments and software implementation required in order to develop the main functionalities of an assistive robot. The APR uses a tablet in order to implement the basic peer-to-peer videoconference and tele-operation control combined with a tactile graphic user interface. The paper also presents the development of some applications proposed in the framework of an assisted living robot.
Trust-Based Recommendation Based on Graph Similarity

Trust networks are directed weighted graphs whose nodes represent agents and edges represent trust between agents. This paper proposes a trust-based recommendation approach, which can recommend trustworthy agents to a requester in a trust network. We consider a good recommendation as one to an agent that the requester’s trusted neighbors trust highly. We relate the recommendation problem to the graph similarity problem, and define the similarity measurement as a mutually reinforcing relation. By calculating the vertex similarity between the trust network and a structure graph (a path graph of length three), we can produce a recommendation based on similarity scores that reflect both the link structure and the trust values on the edges.