Miracle-dz/UniFAR-FTUs huggingface dataset:
Behavior control for a humanoid soccer player using Webots

In this paper the behavior control system developed for a humanoid soccer player is presented, according to the current rules established by the International RoboCup Federation. It is important to point out that this work deals only with field players, excluding the goalkeeper. The behavior control is modeled as a finite-state automaton, which comprises activities as: visual perception (self localization, ball localization, movement estimation), behavior control and game strategies. The developed system is implemented in Webots, which is the official simulation platform used in the RobotStadium league of RoboCup. The results obtained are shown and the path to improve the developed system in our humanoid soccer players is established as future work.
Voting Based Group Recommendation: How Users Vote

It has been shown that social information as group structure or personality characteristics improve the group recommendation. Sometimes no such information is available, specifically when ad-hoc groups are constructed. Moreover, often the items’ content is not available (or users’ preferences are unknown). In this paper we explore the usage of voting based group recommendation and the users preference for such a method settings – we analyze aggregation strategies preferences, sharing preferences and users re-rating consistency.
Segmented spin‐echo pulses to increase fMRI signal: Repeated intrinsic diffusional enhancement

Since its inception, functional magnetic resonance imaging (fMRI) has seen rapid progress in the application to neuroscience. Common gradient‐recalled acquisition methods are susceptible to static field inhomogeneities, resulting in signal loss at the medial temporal area important for memory function or at the basal ganglia area for motor control. In addition, they are susceptible to the contaminating signals of large vein origin, such as the signals from its surrounding cerebrospinal fluid (CSF) leading to false‐positive activation. Spin echoes overcome these drawbacks. However, they are less sensitive to blood oxygenation level dependent (BOLD) susceptibility changes because of their refocusing mechanism. A method is presented here to enhance the spin‐echo fMRI signal by recruiting more spins to participate in the dynamic BOLD process. This method divided a conventional T2 weighting period into several segments separated by blocks of extra free diffusion time. Before the extra diffusion time spins are restored to the longitudinal axis preventing rapid transverse relaxation. This process allows more spin access to the regions that experience the BOLD field gradient. Because of the increased spin population that is modulated by the capillary BOLD field gradient, the functional signal is increased. Spin‐echo echo‐planar imaging (EPI) with this enhancement may be a useful technique for fMRI studies at inhomogeneous areas such as the air/tissue interface. Magn Reson Med 42:631–635, 1999. © 1999 Wiley‐Liss, Inc.
Method to determine optimal hardware platforms in Human Centered Computing based on non functional requirements analysis

Human Centered Computing is a novel paradigm to process context information of human being's environment in which computers are invisible to the subject, providing tools and services depending on the context of each individual. An increasing interest is growing regarding embedded computers since they offer advantages related to portability, dedicated tasks, invisibility, amongst others. However, a plenty of hardware platforms are in the market, so it is complicated to determine which the best for a particular need. Benchmarks make those tasks easier by performing measurements in hardware by running applications and performing comparisons. Nevertheless, they are thought to meet some quite particular kinds of applications. Moreover, if some benchmark applications have to be merged, i.e. voice or images processing, there are not schemes to correctly measure hardware platforms. On the other hand, requirements such as reliability and availability are not commonly assessed as a dependant set in hardware platforms. In this work, we propose a novel method to select hardware architectures for Human Centered Computing based on benchmarking, genetic algorithms, weighted sums and statistical distances in order to consider non-functional requirements.
Quadratic programming-based inverse dynamics control for legged robots with sticking and slipping frictional contacts

Inverse dynamics control is an extremely effective nonlinear control strategy if the inverse dynamics computation can be performed with sufficient speed.We describe our method for inverse dynamics control of legged robots that can deal with both sticking and slipping frictional contacts and mitigates the problems introduced by indeterminate rigid body contact. We improve this work, which previously used quadratically constrained quadratic programs (QCQPs), to use faster-to-solve quadratic programs via linear algebraic simplifications and a nullspace. We also show that Lemke's Algorithm is significantly faster than alternatives and permits multi-stage optimizations within control loops running as fast as 125Hz on commodity hardware.
Real-time clustering of massive geodata for online maps to improve visual analysis

Nowadays, we have a lot of data produced by social media services, but more and more often these data contain information about a location that gives us the wide range of possibilities to analyze them. Since we can be interested not only in the content, but also in the location where this content was produced. For good analyzing geo-spatial data, we need to find the best approaches for geo clustering. And the best approach means real-time clustering of massive geodata with high accuracy. In this paper, we present a new approach of clustering geodata for online maps, such as Google Maps, OpenStreetMap and others. Clustered geodata based on their location improve visual analysis of them and improve situational awareness. Our approach is the server-side online algorithm that does not need the entire data to start clustering. Also, this approach works in real-time and could be used for clustering of massive geodata for online maps in reasonable time. We implemented the proposed approach to prove the concept, and also, we provided experiments and evaluation of our approach.
A MAC contest between LPL (the champion) and Reins-MAC (the challenger, an anarchic TDMA scheduler providing QoS)

LPL [5], or BoX-MAC in its TinyOS implementation, is arguably the most common MAC protocol for WSNs. Its extensive use in real world deployments is justified by a simple implementation, available online, that meets the requirements of a vast majority of monitoring applications. Despite the plethora of competitors, it still remains the reference in the MAC scheduling world. However, its random nature inherently hampers its possibility to support effectively any application driven Quality of Service requirement.
An FPGA-based hardware accelerator for simulating spatiotemporal neurons

Simulating spatiotemporal neurons is fundamental to understanding motion detection mechanisms in the primary visual cortex and cloning these mechanisms in digital systems. We present a hardware accelerator that leverages the parallelism of a modern Field Programmable Gate Array (FPGA) to increase the speed of spatiotemporal computations by 1~2 orders of magnitude for video framebuffer sizes up to 128×128×25 pixels. The accelerator is primarily intended for running simulations of large spatiotemporal neuron populations but can also be used in computer vision applications that require high-speed spatiotemporal processing such as realtime motion detection.
Robust Image Deblurring With an Inaccurate Blur Kernel

Most existing nonblind image deblurring methods assume that the blur kernel is free of error. However, it is often unavoidable in practice that the input blur kernel is erroneous to some extent. Sometimes, the error could be severe, e.g., for images degraded by nonuniform motion blurring. When an inaccurate blur kernel is used as the input, significant distortions will appear in the image recovered by existing methods. In this paper, we present a novel convex minimization model that explicitly takes account of error in the blur kernel. The resulting minimization problem can be efficiently solved by the so-called accelerated proximal gradient method. In addition, a new boundary extension scheme is incorporated in the proposed model to further improve the results. The experiments on both synthesized and real images showed the efficiency and robustness of our algorithm to both the image noise and the model error in the blur kernel.
The “Gini index” in genetics: measuring genetic architecture complexity of quantitative traits

Genetic architecture is a general terminology used and discussed very often in complex traits genetics. It is related to the number of functional loci involved in explaining variation of a complex trait and the distribution of genetic effects across these loci. Understanding the complexity level of the genetic architecture of complex traits is essential for evaluating the potential power of mapping functional loci and prediction of complex traits. However, there has been no quantitative measurement of the genetic architecture complexity, which makes it difficult to link results from genetic data analysis to such terminology. Inspired by the “Gini index” for measuring income distribution in economics, I develop a genetic architecture score (“GA score”) to measure genetic architecture complexity. Simulations indicate that the GA score is an effective measurement of the complexity level of complex traits genetic architecture.
SGA Children with Moderate Catch-Up Growth Are Showing the Impaired Insulin Secretion at the Age of 4

Background Being born small for gestational age (SGA) is a risk factor for later development of type 2 diabetes. The development of glucose tolerance disorders in adults involves insulin resistance and impaired insulin secretion. Objective To evaluate insulin secretion and insulin sensitivity in a 4-yr old cohort of SGA. Methods 85 children were prospectively followed from mid-gestation to 4 years of age. Fetal growth velocity (FGV) was measured using ultrasound measurements. Body composition and hormonal profile were measured at birth, 1 and 4 years. Results 23 SGA babies had lower birth weight compared to 62 AGA (−1.9±0.3 vs. −0.6±0.8 z-score; p<0.0001) and they were thinner at birth (ponderal index 24.8±1.8 vs. 26.3±3.1 kg/m3; p = 0.01 and fat mass 11±2.6 vs. 12.9±3.1%; p = 0.01). No significant differences in other measured metabolic and hormonal parameters were observed between two groups at birth. SGA infants experienced an early catch-up growth in weight (mean gain of 1.1±0.6 SD) during the first year of life. At 4 years, SGA children remain lighter than AGA, but with weight z-score in the normal range (−0.1±1.3 vs. 0.5±1.3 z-score; p = 0.05). No excess of fat mass was observed (19±4.8 vs. 19.7±4.1%; p = 0.45). 120-min plasma glucose was significantly higher (6.2±1.1 vs. 5.6±0.9 mmol/l; p = 0.006) and insulinogenic index was significantly lower (0.28±0.15 vs. 0.40±2.4; p = 0.02) in the SGA group at 4-yrs of life contrasting with a preserved insulin sensitivity (QUICKI 0.47±0.09 vs. 0.43±0.05; p = 0.06). Conclusion SGA children with compensatory catch-up growth in first year of life show mild disturbances of glucose tolerance associated to a lower insulinogenic index at 4-yrs of age suggesting impairment of β-cell function.
An Inflationary Fixed Point in XQuery

We introduce a controlled form of recursion in XQuery, inflationary fixed points, familiar in the context of relational databases. This imposes restrictions on the expressible types of recursion, but we show that inflationary fixed points nevertheless are sufficiently versatile to capture a wide range of interesting use cases, including the semantics of Regular XPath and its core transitive closure construct. While the optimization of general user-defined recursive functions in XQuery appears elusive, we will describe how inflationary fixed points can be efficiently evaluated, provided that the recursive XQuery expressions exhibit a distributivity property. We show how distributivity can be assessed both, syntactically and algebraically, and provide experimental evidence that XQuery processors can substantially benefit during inflationary fixed point evaluation.
Multi-dimensional data analysis of intracerebral hemorrhage from CT images

Intracranial hemorrhage(ICH) is a very life-threatening situation to human beings for the formation of thrombus, blood lipids or brain trauma as well as chronic hypertension, cerebral amyloid angiopathy (CAA), acute changes in blood pressure and blood flow ect. The numerical characterization of ICH are proposed through by multi-dimensional data analysis(MDDA), such as principal component analysis(PCA), locally linear embedding(LLE) algorithm, which are based on level scale of corresponding pixels and the histograms of the computer tomography images in the paper. Numerical experiments are also showed the results exactly, which would be used to segmentation of the data for diagnosis of ICH, quantitative evaluation of treatment and postoperative situation.
C3 peptide enhances recovery from spinal cord injury by improved regenerative growth of descending fiber tracts

Functional recovery and regeneration of corticospinal tract (CST) fibers following spinal cord injury by compression or dorsal hemisection in mice was monitored after application of the enzyme-deficient Clostridium botulinum C3-protein-derived 29-amino-acid fragment C3bot154-182. This peptide significantly improved locomotor restoration in both injury models as assessed by the open-field Basso Mouse Scale for locomotion test and Rotarod treadmill experiments. These data were supported by tracing studies showing an enhanced regenerative growth of CST fibers in treated animals as visualized by anterograde tracing. Additionally, C3bot154-182 stimulated regenerative growth of raphespinal fibers and improved serotonergic input to lumbar α-motoneurons. These in vivo data were confirmed by in vitro data, showing an enhanced axon outgrowth of α-motoneurons and hippocampal neurons cultivated on normal or growth-inhibitory substrates after application of C3bot154-182. The observed effects were probably caused by a non-enzymatic downregulation of active RhoA by the C3 peptide as indicated by pull-down experiments. By contrast, C3bot154-182 did not induce neurite outgrowth in primary cultures of dorsal root ganglion cells. In conclusion, C3bot154-182 represents a novel, promising tool to foster axonal protection and/or repair, as well as functional recovery after traumatic CNS injury.
Innovation determinants in manufacturing firms

In this paper the findings of an empirical study concerning the innovation determinants in manufacturing firms is presented. The empirical study covers 184 manufacturing firms located in the Northern Marmara region of Turkey. In the paper an extensive literature survey on innovation determinants is provided. A model is proposed to explore the probable effects and the amount of contribution of the innovation determinants to firm’s innovativeness level. Despite there is abundant research that analyzes the effects of various innovation determinants, this paper provides a comprehensive model and tests its validity. It is also unique in the sense that the significance of the innovation determinants is studied based on the empirical survey data. Such knowledge is invaluable for the decision makers in order to manage their innovation strategies and provides a guideline for effective allocation of their limited resources to be more innovative. The analysis reveals that among all possible determinants considered, intellectual capital has the highest impact on innovativeness followed by organization culture.
Targeting PDK1 with dichloroacetophenone to inhibit acute myeloid leukemia (AML) cell growth

Pyruvate dehydrogenase kinase-1 (PDK1), a key metabolic enzyme involved in aerobic glycolysis, is highly expressed in many solid tumors. Small molecule compound DAP (2,2-dichloroacetophenone) is a potent inhibitor of PDK1. Whether targeting PDK1 with DAP can inhibit acute myeloid leukemia (AML) and how it works remains unknown. In this study, we evaluated the effect of inhibition of PDK1 with DAP on cell growth, apoptosis and survival in AML cells and identified the underlying mechanisms. We found that treatment with DAP significantly inhibited cell proliferation, increased apoptosis induction and suppressed autophagy in AML cells in vitro, and inhibited tumor growth in an AML mouse model in vivo. We also showed that inhibition of PDK1 with DAP increased the cleavage of pro-apoptotic proteins (PARP and Caspase 3) and decreased the expression of the anti-apoptotic proteins (BCL-xL and BCL-2) and autophagy regulators (ULK1, Beclin-1 and Atg). In addition, we found that DAP inhibited the PI3K/Akt signaling pathway. Furthermore, we demonstrated that PDK1 interacted with ULK1, BCL-xL and E3 ligase CBL-b in AML cells, and DPA treatment could inhibit the interactions. Collectively, our results indicated that targeting PDK1 with DAP inhibited AML cell growth via multiple signaling pathways and suggest that targeting PDK1 may be a promising therapeutic strategy for AMLs.
Soil carbon model alternatives for ECHAM5/JSBACH climate model: Evaluation and impacts on global carbon cycle estimates

Thum, T. , et al. (2011), 'Soil carbon model alternatives for ECHAM5/JSBACH climate model: Evaluation and impacts on global carbon cycle estimates', Journal of Geophysical Research, Vol. 116, G02028, published 29 June 2011. The version of record is available at doi:10.1029/2010JG001612 © 2011 American Geophysical Union.
Microbial Electrosynthesis: Feeding Microbes Electricity To Convert Carbon Dioxide and Water to Multicarbon Extracellular Organic Compounds

ABSTRACT The possibility of providing the acetogenic microorganism Sporomusa ovata with electrons delivered directly to the cells with a graphite electrode for the reduction of carbon dioxide to organic compounds was investigated. Biofilms of S. ovata growing on graphite cathode surfaces consumed electrons with the reduction of carbon dioxide to acetate and small amounts of 2-oxobutyrate. Electrons appearing in these products accounted for over 85% of the electrons consumed. These results demonstrate that microbial production of multicarbon organic compounds from carbon dioxide and water with electricity as the energy source is feasible. IMPORTANCE Reducing carbon dioxide to multicarbon organic chemicals and fuels with electricity has been identified as an attractive strategy to convert solar energy that is harvested intermittently with photovoltaic technology and store it as covalent chemical bonds. The organic compounds produced can then be distributed via existing infrastructure. Nonbiological electrochemical reduction of carbon dioxide has proven problematic. The results presented here suggest that microbiological catalysts may be a robust alternative, and when coupled with photovoltaics, current-driven microbial carbon dioxide reduction represents a new form of photosynthesis that might convert solar energy to organic products more effectively than traditional biomass-based strategies. Reducing carbon dioxide to multicarbon organic chemicals and fuels with electricity has been identified as an attractive strategy to convert solar energy that is harvested intermittently with photovoltaic technology and store it as covalent chemical bonds. The organic compounds produced can then be distributed via existing infrastructure. Nonbiological electrochemical reduction of carbon dioxide has proven problematic. The results presented here suggest that microbiological catalysts may be a robust alternative, and when coupled with photovoltaics, current-driven microbial carbon dioxide reduction represents a new form of photosynthesis that might convert solar energy to organic products more effectively than traditional biomass-based strategies.
Concomitant Inhalation of Cigarette Smoke and Aerosolized Protein Activates Airway Dendritic Cells and Induces Allergic Airway Inflammation in a TLR-Independent Way1

Cigarette smoking is associated with the development of allergic asthma. In mice, exposure to cigarette smoke sensitizes the airways toward coinhaled OVA, leading to OVA-specific allergic inflammation. Pulmonary dendritic cells (DCs) are professional APCs involved in immunosurveillance and implicated in the induction of allergic responses in lung. We investigated the effects of smoking on some of the key features of pulmonary DC biology, including trafficking dynamics and cellular activation status in different lung compartments. We found that cigarette smoke inhalation greatly amplified DC-mediated transport of inhaled Ags to mediastinal lymph nodes, a finding supported by the up-regulation of CCR7 on airway DCs. Pulmonary plasmacytoid DCs, which have been involved in inhalational tolerance, were reduced in number after smoke exposure. In addition, combined exposure to cigarette smoke and OVA aerosol increased surface expression of MHC class II, CD86, and PDL2 on airway DCs, while ICOSL was strongly down-regulated. Although inhaled endotoxins, which are also present in cigarette smoke, have been shown to act as DC activators and Th2-skewing sensitizers, TLR4-deficient and MyD88 knockout mice did not show impaired eosinophilic airway inflammation after concomitant exposure to cigarette smoke and OVA. From these data, we conclude that cigarette smoke activates the pulmonary DC network in a pattern that favors allergic airway sensitization toward coinhaled inert protein. The TLR independency of this phenomenon suggests that alternative immunological adjuvants are present in cigarette smoke.
Space-time code ARQ protocol for wireless networks

Multiuser cooperative communication is a novel transmission technique, where the antennas on adjacent mobile terminals are formed as a virtual antenna array (VAA) to realize spatial diversity gain in a distributed way. A space-time code ARQ protocol exploiting the cooperation capability between nodes in wireless networks is proposed in this paper. Different to the traditional ARQ protocol, the erroneously received packet is retransmitted by the source terminal and a relay terminal simultaneously using space-time code, which results in the realization of transmit diversity. The packet error rate (PER) performance of space-time code ARQ is derived in both correlated and uncorrelated block fading wireless channels, in comparison with the traditional ARQ. Our analysis shows that the space-time code ARQ is capable of extracting second-order diversity and third-order diversity in correlated and uncorrelated block fading channels, respectively, while the traditional ARQ only achieves first-order diversity and second-order diversity, correspondingly.