Miracle-dz/UniFAR-FTUs huggingface dataset:
The Case for Non-Cooperative Multihoming of Users to Access Points in IEEE 802.11 WLANs

In many cases, a mobile user has the option of connecting to one of several IEEE 802.11 access points (APs),each using an independent channel. User throughput in each AP is determined by the number of other users as well as the frame size and physical rate being used. We consider the scenario where users could multihome, i.e., split their traffic amongst all the available APs, based on the throughput they obtain and the price charged. Thus, they are involved in a non-cooperative game with each other. We convert the problem into a fluid model and show that under a pricing scheme, which we call the cost price mechanism, the total system throughput is maximized,i.e., the system suffers no loss of efficiency due to selfish dynamics. We also study the case where the Internet Service Provider (ISP) could charge prices greater than that of the cost price mechanism. We show that even in this case multihoming outperforms unihoming, both in terms of throughput as well as profit to the ISP.
Determinants of self-rated health of Warsaw inhabitants.

BACKGROUND Self-rated health is a one-point measure commonly used for recognising subjectively perceived health and covering a wide range of individual's health aspects. OBJECTIVE The aim of our study was to examine the extent to which self-rated health reflects the differences due to demographic characteristics, physical, psychical and social well-being, health disorders, occurrence of chronic disease and negative life events in Polish social and cultural conditions. MATERIAL AND METHOD Data were collected by non-addressed questionnaire methods from 402 Warsaw inhabitants. The questionnaire contained the questions concerning self-rated health, physical, psychical and social well-being, the use of health care services, occurrence of chronic disease and contact with negative life events. RESULTS The analysis showed that worse self-rated health increased exponentially with age and less sharply with lower level of education. Pensioners were more likely to assess their own health worse then employed or students. Such difference was not found for unemployed. Compared to married, the self-rated health of divorced or widowed respondents was lower. Gender does not differentiate self-rated health. In regard to well-being, self-rated health linearly decreased for physical well-being, for social and, especially, for psychical well-being the differences were significant, but more complicated. Hospitalisation, especially repeated, strongly determined worse self-rated health. In contrast, relationship between self-rated health and sickness absence or frequency of contact with physician were lower. Chronic diseases substantially increased the risk of poorer self-rated health, and their co-morbidity increased the risk exponentially. The patients with cancer were the group, in which the risk several times exceeded that reported for the patients of other diseases. Regarding negative life events, only experience with violence and financial difficulties were resulted in worse self-rated health. CONCLUSIONS Our findings confirmed the usefulness of self-rated health for public health research.
Learning people co-occurrence relations by using relevance feedback for retrieving group photos

This paper proposes an image retrieval method which retrieves images of a specific person from group photos. Many query-by-example methods have focused only on the visual features of the queried person. However, since socially related people such as family and friends are often taken photos together, their co-occurrence relations can be useful information. Thus, we propose an image retrieval method which uses the visual features of not only the queried person but also those who co-occur with the queried person in the same images. Relevance feedback is used to learn who co-occur with the queried person, their faces, and how strong their co-occurrence relations are. When retrieving the images of 19 persons in total from 158 images, after five feedback iterations, the recall rate of 50% was obtained by considering the people co-occurrence relations, as against 33% when considering only the queried person. With human errors in giving relevance feedback, the recall rate still improved to 40%.
ParaFPGA 2013: Harnessing Programs, Power and Performance in Parallel FPGA applications

Future computing systems will require dedicated accelerators to achieve high-performance. The mini-symposium ParaFPGA explores parallel computing with FPGAs as an interesting avenue to reduce the gap between the architecture and the application. Topics discussed are the power of functional and dataflow languages, the performance of high-level synthesis tools, the automatic creation of hardware multi-cores using C-slow retiming, dynamic power management to control the energy consumption, real-time reconfiguration of streaming image processing filters and memory optimized event image segmentation.
Resonant bits: controlling digital musical instruments with resonance and the ideomotor effect

Resonant Bits proposes giving digital information resonant dynamic properties, requiring skill and concerted effort for interaction. This paper applies resonant interaction to musical control, exploring musical instruments that are controlled through both purposeful and subconscious resonance. We detail three exploratory prototypes, the first two illustrating the use of resonant gestures and the third focusing on the detection and use of the ideomotor (subconscious micro-movement) effect.
Development of Robust and Standardized Cantilever Sensors Based on Biotin/Neutravidin Coupling for Antibody Detection

A cantilever-based protein biosensor has been developed providing a customizable multilayer platform for the detection of antibodies. It consists of a biotin-terminated PEG layer pre-functionalized on the gold-coated cantilever surface, onto which NeutrAvidin is adsorbed through biotin/NeutrAvidin specific binding. NeutrAvidin is used as a bridge layer between the biotin-coated surface and the biotinylated biomolecules, such as biotinylated bovine serum albumin (biotinylated BSA), forming a multilayer sensor for direct antibody capture. The cantilever biosensor has been successfully applied to the detection of mouse anti-BSA (m-IgG) and sheep anti-BSA(s-IgG) antibodies. As expected, the average differential surface stress signals of about 5.7 ± 0.8 × 10−3 N/m are very similar for BSA/m-IgG and BSA/s-IgG binding, i.e., they are independent of the origin of the antibody. A statistic evaluation of 112 response curves confirms that the multilayer protein cantilever biosensor shows high reproducibility. As a control test, a biotinylated maltose binding protein was used for detecting specificity of IgG, the result shows a signal of bBSA layer in response to antibody is 5.8 × 10−3 N/m compared to bMBP. The pre-functionalized biotin/PEG cantilever surface is found to show a long shelf-life of at least 40 days and retains its responsivity of above 70% of the signal when stored in PBS buffer at 4 °C. The protein cantilever biosensor represents a rapid, label-free, sensitive and reliable detection technique for a real-time protein assay.
Multi-modal Language Models for Lecture Video Retrieval

We propose Multi-modal Language Models (MLMs), which adapt latent variable techniques for document analysis to exploring co-occurrence relationships in multi-modal data. In this paper, we focus on the application of MLMs to indexing text from slides and speech in lecture videos, and subsequently employ a multi-modal probabilistic ranking function for lecture video retrieval. The MLM achieves highly competitive results against well established retrieval methods such as the Vector Space Model and Probabilistic Latent Semantic Analysis. When noise is present in the data, retrieval performance with MLMs is shown to improve with the quality of the spoken text extracted from the video.
TeamRooms: groupware for shared electronic spaces

Teams whose members are in close physical proximity often rely on team rooms to serve both as meeting places and repositories of the documents and artifacts that support the team’s projects. TeamRooms is a prototype groupware system designed to fill the role of a team room for groups whose members can work both co-located and at a distance. Facilities in TeamRooms allow team members to collaborate either in real-time or asynchronously, and to customize their shared electronic space to suit their needs.
TEDQuiz: Automatic Quiz Generation for TED Talks Video Clips to Assess Listening Comprehension

In the last few years, researchers in the field of e-learning and Natural Language Processing (NLP) have shown an increased interest in automatic question generation. However, little research has discussed the automatic evaluation of listening comprehension in multimedia learning. In this work, we present an automatic quiz generation for TED Talks video clips, called TED Quiz. TED Quiz generates multiple-choice questions in two question types, gist-content questions and detail questions. We use a graph-based algorithm, Lex Rank, to identify the most important part of a talk, as the main concept of a gist-content question. We also proposed an approach to distractor selection for detail question generation that generates grammatically correct but semantically wrong sentences as distractors. The experimental results demonstrated that the measured results from automatically generated questions are comparable with that from manually generated questions because their scores were significantly correlated. Moreover, most subjects agreed that the generated listening comprehension questions were of quality and usefulness.
A Neural Network Model Based on Graph Matching and Annealing : Application to Hand-Written Digits Recognition

We present a neural network model based on graph matching and an annealing technique, one-variable stochastic simulated annealing(OSSA) which makes it possible to evaluate the spin average value effectively by Markov process in case of many real applications. In order to demonstrate the capability of our model we implemented a program that can segment and recognize hand-written digits. Input and object digits, memorized objects, are represented by graph, whose edges are labeled by geometrical distance, and whose vertices are labeled by position in the graph domain. Pattern recognition can be formulated as elastic graph matching, which is performed here by stochastic optimization of a matching cost function. Our approach provides not only the function of recognition but also the segmentation ability such that input characters are correctly recognized and segmented even if they are touching, connected, and defected by noise. Some results of computer experiments are reported to show the feasibility of our approach. Keywords—Pattern recognition, Segmentation, Optimization, Annealing neural networks
A Simulation Tool for Managing Intelligent Ensembles

A general framework is presented for the design and development of an integrated system of ensemble network generation, storage, analysis and retrieval. The system is comprised of two independent components: 1) a simulation tool for generating ensembles of neural network classifiers, and, 2) a scientific database for storing classifiers, predictions, trial conditions, performance-related data, and meta-data. A model implementation is discussed.
Sizing charts of helical capillary tubes used in refrigeration and air conditioning

This paper presents new selection and correction factor charts for the sizing of adiabatic helical capillary tubes operating with alternative refrigerants. The mathematical model is based on the conservation of mass, energy, and momentum of fluids in capillary tubes. In the two-phase flow region, the developed model is based on the homogenous flow assumption. It is verified by the accuracy of the results of comparison between simulation results and experimental data in open literature. After the developed model is validated, selection and correction charts that include the important parameters are proposed for sizing adiabatic helical capillary tube. The present charts are proposed for R-134a, R-404A, R-407B, R-407C, and R-410A, and a wide range of operation. These newly developed selection and correction charts can be used to select helical capillary tube size from flow conditions and the mass flow rate or to predict the mass flow rate from capillary tube size and flow condition.
IntelligShop: Enabling Intelligent Shopping in Malls through Location-Based Augmented Reality

Shopping experience is important for both citizens and tourists. We present IntelligShop, a novel location-based augmented reality application that supports intelligent shopping experience in malls. As the key functionality, IntelligShop provides an augmented reality interface -- people can simply use ubiquitous smartphones to face mall retailers, then IntelligShop will automatically recognize the retailers and fetch their online reviews from various sources (including blogs, forums and publicly accessible social media) to display on the phones. Technically, IntelligShop addresses two challenging data mining problems, including robust feature learning to support heterogeneous smartphones in localization and learning to query for automatically gathering the retailer content from the Web for augmented reality. We demonstrate the system effectiveness via a test bed established in a real mall of Singapore.
METscout: a pathfinder exploring the landscape of metabolites, enzymes and transporters

METscout (http://metscout.mpg.de) brings together metabolism and gene expression landscapes. It is a MySQL relational database linking biochemical pathway information with 3D patterns of gene expression determined by robotic in situ hybridization in the E14.5 mouse embryo. The sites of expression of ∼1500 metabolic enzymes and of ∼350 solute carriers (SLCs) were included and are accessible as single cell resolution images and in the form of semi-quantitative image abstractions. METscout provides several graphical web-interfaces allowing navigation through complex anatomical and metabolic information. Specifically, the database shows where in the organism each of the many metabolic reactions take place and where SLCs transport metabolites. To link enzymatic reactions and transport, the KEGG metabolic reaction network was extended to include metabolite transport. This network in conjunction with spatial expression pattern of the network genes allows for a tracing of metabolic reactions and transport processes across the entire body of the embryo.
Learning deterministic regular expressions for the inference of schemas from XML data

Inferring an appropriate DTD or XML Schema Definition (XSD) for a given collection of XML documents essentially reduces to learning deterministic regular expressions from sets of positive example words. Unfortunately, there is no algorithm capable of learning the complete class of deterministic regular expressions from positive examples only, as we will show. The regular expressions occurring in practical DTDs and XSDs, however, are such that every alphabet symbol occurs only a small number of times. As such, in practice it suffices to learn the subclass of regular expressions in which each alphabet symbol occurs at most k times, for some small k. We refer to such expressions as k-occurrence regular expressions (k-OREs for short). Motivated by this observation, we provide a probabilistic algorithm that learns k-OREs for increasing values of k, and selects the one that best describes the sample based on a Minimum Description Length argument. The effectiveness of the method is empirically validated both on real world and synthetic data. Furthermore, the method is shown to be conservative over the simpler classes of expressions considered in previous work.
Direct Methanolysis of Oleaginous Yeast Biomass (Pseudozyma parantarctica) to Microbial Biodiesel

In this study, intracellular lipids of a novel oleaginous biomass of P. parantarctica were converted to biodiesel directly using simple acid catalyst methanolysis. The optimum condition of this method was investigated. Under optimum conditions (0.1 M H2SO4, 10 h reaction time, 65°C reaction temperature, and 1:20 (w/v) biomass-to-methanol ratio), the yield of crude biodiesel was 93.18 ± 2.09% based on total cellular lipids. The composition of crude biodiesel was C16:C18 fatty acid methyl esters (FAMEs) for 91.91%. Especially, the C18:1 methyl ester was the main FAME (47.10%). In addition, the result showed that this technique could produce the microbial biodiesel from biomass containing high free fatty acids (FFAs) without soap formation. The predicted cetane number and kinematic viscosity of biodiesel were characterized according to ASTM D6751 and EN 14214 standards. Our results indicated that this process produces a good quality biodiesel. Moreover, it can decrease the manufacturing costs of microbial biodiesel production from oleaginous yeast biomass without cell disruption and lipid extraction.
Host Glycosaminoglycan Confers Susceptibility to Bacterial Infection in Drosophila melanogaster

ABSTRACT Many pathogens engage host cell surface glycosaminoglycans, but redundancy in pathogen adhesins and host glycosaminoglycan-anchoring proteins (heparan sulfate proteoglycans) has limited the understanding of the importance of glycosaminoglycan binding during infection. The alpha C protein of group B streptococcus, a virulence determinant for this neonatal human pathogen, binds to host glycosaminoglycan and mediates the entry of bacteria into human cells. We studied alpha C protein-glycosaminoglycan binding in Drosophila melanogaster, whose glycosaminoglycan repertoire resembles that of humans but whose genome includes only three characterized membrane heparan sulfate proteoglycan genes. The knockdown of glycosaminoglycan polymerases or of heparan sulfate proteoglycans reduced the cellular binding of alpha C protein. The interruption of alpha C protein-glycosaminoglycan binding was associated with longer host survival and a lower bacterial burden. These data indicate that the glycosaminoglycan-alpha C protein interaction involves multiple heparan sulfate proteoglycans and impairs bacterial killing. Host glycosaminoglycans, anchored by multiple proteoglycans, thereby determine susceptibility to infection. Because there is homology between Drosophila and human glycosaminoglycan/proteoglycan structures and many pathogens express glycosaminoglycan-binding structures, our data suggest that interfering with glycosaminoglycan binding may protect against infections in humans.
Immunogenicity and Immunomodulatory Properties of Umbilical Cord Lining Mesenchymal Stem Cells

We here present an immunologic head-to-head comparison between human umbilical cord lining mesenchymal stem cells (clMSCs) and adult bone marrow MSCs (bmMSCs) from patients >65 years of age. clMSCs had significantly lower HLA class I expression, higher production of tolerogenic TGF-β and IL-10, and showed significantly faster proliferation. In vitro activation of allogeneic lymphocytes and xenogeneic in vivo immune activation was significantly stronger with bmMSCs, whereas immune recognition of clMSCs was significantly weaker. Thus, bmMSCs were more quickly rejected in immunocompetent mice. IFN-γ at 25 ng/ml increased both immunogenicity by upregulation of HLA class I/HLA-DR expression and tolerogenicity by increasing intracellular HLA-G and surface HLA-E expression, augmenting TGF-β and IL-10 release, and inducing indoleamine 2,3-dioxygenase (IDO) expression. Higher concentrations of IFN-γ (>50 ng/ml) further enhanced the immunosuppressive phenotype of clMSCs, more strongly downregulating HLA-DR expression and further increasing IDO production (at 500 ng/ml). The net functional immunosuppressive efficacy of MSCs was tested in mixed lymphocyte cultures. Although both clMSCs and bmMSCs significantly reduced in vitro immune activation, clMSCs were significantly more effective than bmMSCs. The veto function of both MSC lines was enhanced in escalating IFN-γ environments. In conclusion, clMSCs show a more beneficial immunogeneic profile and stronger overall immunosuppressive potential than aged bmMSCs.
Multizone Speech Reinforcement

In this article, we address speech reinforcement (near-end listening enhancement) for a scenario where there are several playback zones. In such a framework, signals from one zone can leak into other zones (crosstalk), causing intelligibility and/or quality degradation. An optimization framework is built by exploring a signal model where effects of noise, reverberation and zone crosstalk are taken into account simultaneously. Through the symbolic usage of a general smooth distortion measure, necessary optimality conditions are derived in terms of distortion measure gradients and the signal model. Subsequently, as an illustrative example of the framework, the conditions are applied for the mean-square error (MSE) expected distortion under a hybrid stochastic-deterministic model for the corruptions. A crosstalk cancellation algorithm follows, which depends on diffuse reverberation and across zone direct path components. Simulations validate the optimality of the algorithm and show a clear benefit in multizone processing, as opposed to the iterated application of a single-zone algorithm. Also, comparisons with least-squares crosstalk cancellers in literature show the profit of using a hybrid model.
Deletion of ABCA1 and ABCG1 Impairs Macrophage Migration Because of Increased Rac1 Signaling

Rationale: Reduced plasma cholesterol and increased high-density lipoprotein (HDL) levels promote regression of atherosclerosis, in a process characterized by lipid unloading and emigration of macrophages from lesions. In contrast free cholesterol loading of macrophages leads to imbalanced Rac1/Rho activities and impaired chemotaxis. Objective: To study the role of HDL and the ATP-binding cassette transporters ABCA1 and ABCG1 in modulating the chemotaxis of macrophages. Methods and Results: Abca1−/−Abcg1−/− mouse macrophages displayed profoundly impaired chemotaxis both in a Transwell chamber assay and in the peritoneal cavity of wild-type (WT) mice. HDL reversed impaired chemotaxis in free cholesterol–loaded WT macrophages but was without effect in Abca1−/−Abcg1−/− cells, whereas cyclodextrin was effective in both. Abca1−/−Abcg1−/− macrophages had markedly increased Rac1 activity and increased association of Rac1 with the plasma membrane (PM). Their defective chemotaxis was reversed by a Rac1 inhibitor. To gain a better understanding of the role of transporters in PM cholesterol movement, we measured transbilayer PM sterol distribution. In WT macrophages, the majority of cholesterol was located on the inner leaflet, whereas on upregulation of transporters by liver X receptor activation, PM sterol was shifted to the outer leaflet, where it could be removed by HDL. Abca1−/−Abcg1−/− macrophages showed increased PM sterol content and defective redistribution of sterol to the outer leaflet. Conclusions: Deletion of ABCA1 and ABCG1 causes an increased cholesterol content on the inner leaflet of the PM, associated with increased Rac1 PM localization, activation, and impairment of migration. ABCA1 and ABCG1 facilitate macrophage chemotaxis by promoting PM transbilayer cholesterol movement and may contribute to the ability of HDL to promote regression of atherosclerosis.