Miracle-dz/UniFAR-FTUs huggingface dataset:
"Be Careful; Things Can Be Worse than They Appear": Understanding Biased Algorithms and Users' Behavior Around Them in Rating Platforms

Awareness of bias in algorithms is growing among scholars and users of algorithmic systems. But what can we observe about how users discover and behave around such biases? We used a cross-platform audit technique that analyzed online ratings of 803 hotels across three hotel rating platforms and found that one site’s algorithmic rating system biased ratings, particularly low-to-medium quality hotels, significantly higher than others (up to 37%). Analyzing reviews of 162 users who independently discovered this bias, we seek to understand if, how, and in what ways users perceive and manage this bias. Users changed the typical ways they used a review on a hotel rating platform to instead discuss the rating system itself and raise other users’ awareness of the rating bias. This raising of awareness included practices like efforts to reverse-engineer the rating algorithm, efforts to correct the bias, and demonstrations of broken trust. We conclude with a discussion of how such behavior patterns might inform design approaches that anticipate unexpected bias and provide reliable means for meaningful bias discovery and response.
A QoS Model Based on NSIS Signalling Applied to IEEE 802.16 Networks

IEEE 802.16 networks provide mechanisms for QoS support at MAC level, but end-to-end QoS issues are not addressed in detail in the standards. This paper presents an analysis and an experimental validation of a comprehensive solution that describes and implements end-to-end QoS in networks with IEEE802.16e segments. A complete QoS model has been specified, defining the traffic descriptors, the QoS parameters and the resource management functions for networks with WiMAX access. This QoS model has been applied to the next step in signalling (NSIS) protocol suite and its impact has been evaluated on end-to-end QoS when heterogeneous network domains are involved. This work is based on the of results of activities focussed on the study of signalling protocols, carried out within the EU Integrated Project WEIRD (WiMAX extension to isolated research data networks).
Simulation and Performance Analysis of Adaptive Filtering Algorithms in Noise Cancellation

Noise problems in signals have gained huge attention due to the need of noise-free output signal in numerous communication systems. The principal of adaptive noise cancellation is to acquire an estimation of the unwanted interfering signal and subtract it from the corrupted signal. Noise cancellation operation is controlled adaptively with the target of achieving improved signal to noise ratio. This paper concentrates upon the analysis of adaptive noise canceller using Recursive Least Square (RLS), Fast Transversal Recursive Least Square (FTRLS) and Gradient Adaptive Lattice (GAL) algorithms. The performance analysis of the algorithms is done based on convergence behavior, convergence time, correlation coefficients and signal to noise ratio. After comparing all the simulated results we observed that GAL performs the best in noise cancellation in terms of Correlation Coefficient, SNR and Convergence Time. RLS, FTRLS and GAL were never evaluated and compared before on their performance in noise cancellation in terms of the criteria we considered here.
A ug 2 00 4 A Dynamic model for the Lagrangian Averaged Navier-Stokes-α Equations

A dynamic procedure for the Lagrangian Averaged Navier-Stokes-α (LANS-α) equations is developed where the variation in the parameter α in the direction of anisotropy is determined in a self-consistent way from data contained in the simulation itself. In order to derive this model, the incompressible Navier-Stokes equations are Helmholtz-filtered at the grid and a test filter levels. A Germano type identity is derived by comparing the filtered subgrid scale stress terms with those given in the LANS-α equations. Assuming constant α in homogenous directions of the flow and averaging in these directions, results in a nonlinear equation for the parameter α, which determines the variation of α in the non-homogeneous directions or in time. Consequently, the parameter α is calculated during the simulation instead of a pre-defined value. The dynamic model is initially tested in forced and decaying isotropic turbulent flows where α is constant in space but it is allowed to vary in time. It is observed that by using the dynamic LANS-α procedure a more accurate simulation of the isotropic homogeneous turbulence is achieved. The energy spectra and the total kinetic energy decay are captured more accurately as compared with the LANS-α simulations using a fixed α. In order to evaluate the applicability of the dynamic LANS-α model in anisotropic turbulence, a priori test of a turbulent channel flow is performed. It is found that the parameter α changes in the wall normal direction. Near a solid wall, the length scale α is seen to depend on the distance from the wall with a vanishing value at the wall. On the other hand, away from the wall, where the turbulence is more isotropic, α approaches an almost constant value. Furthermore, the behavior of the subgrid scale stresses in the near wall region is captured accurately by the dynamic LANS-α model. The dynamic LANS-α model has the potential to extend the applicability of the LANS-α equations to more complicated anisotropic flows.
Time‐dependent estimates of molecular evolutionary rates: evidence and causes

We are writing in response to a recent critique by Emerson & Hickerson ( ), who challenge the evidence of a time‐dependent bias in molecular rate estimates. This bias takes the form of a negative relationship between inferred evolutionary rates and the ages of the calibrations on which these estimates are based. Here, we present a summary of the evidence obtained from a broad range of taxa that supports a time‐dependent bias in rate estimates, with a consideration of the potential causes of these observed trends. We also describe recent progress in improving the reliability of evolutionary rate estimation and respond to the concerns raised by Emerson & Hickerson ( ) about the validity of rates estimated from time‐structured sequence data. In doing so, we hope to dispel some misconceptions and to highlight several research directions that will improve our understanding of time‐dependent biases in rate estimates.
Hardware/Software Co-design Approach for an ADALINE Based Adaptive Control System

In this paper, we report some results on hard- ware and software co-design of an adaptive linear neuron (ADALINE) based control system. A discrete-time Pro- portional-Integral-Derivative (PID) controller is designed based on the mathematical model of the plant. The pa- rameters of the plant model are identified on-line by an ADALINE neural network. In order to efficiently and economically implement the designed control system, a Field Programmable Gate Array (FPGA) chip is em- ployed to process the measured data and generate control signals. Moreover, a microprocessor is exploited to per- form the core computation of the ADALINE algorithm. Throughout the paper, we design and test the control system for a permanent magnetic DC motor. Our ex- periment results demonstrate the effectiveness of the pro- posed approach. It is worth noting that the experimental bed in the present paper can also be used as a low-cost general prototype to satisfactorily test adaptive control systems, owing to the benefit of software and hardware co-design.
Exploiting a New Domain About Urban Plan Promoting Employment

Analyzing the theory of urban plan and its experiences and lessons in history, it is found that urban plan should and can promote employment directly. In China, every city is emending urban plan and the central government of Chinese communist party denotes that urban planning should consider "more employment". In such background, the traditional opinion "urban plan can not promote employment directly" should be changed and a new research domain about urban plan promoting employment should be exploited. Through exploiting this new domain, on one hand, we can find a new way about employment, decrease the serious pressure of employment in cities of China, perfect and develop employment theory. On the other hand, it redound to lead residual labor forces in the countryside transfer in a reasonable way and shun "the fault of big city" as it happened in Africa where a great deal of peasants swarm into big cities out-of-order, perfect and develop urban plan theory.
Urinary Polycyclic Aromatic Hydrocarbon Metabolites and Attention/Deficit Hyperactivity Disorder, Learning Disability, and Special Education in U.S. Children Aged 6 to 15

Exposure to polycyclic aromatic hydrocarbons (PAHs) adversely affects child neurodevelopment, but little is known about the relationship between PAHs and clinically significant developmental disorders. We examined the relationship between childhood measures of PAH exposure and prevalence of attention deficit/hyperactivity disorder (ADHD), learning disability (LD), and special education (SE) in a nationally representative sample of 1,257 U.S. children 6–15 years of age. Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 2001–2004. PAH exposure was measured by urinary metabolite concentrations. Outcomes were defined by parental report of (1) ever doctor-diagnosed ADHD, (2) ever doctor- or school representative-identified LD, and (3) receipt of SE or early intervention services. Multivariate logistic regression accounting for survey sampling was used to determine the associations between PAH metabolites and ADHD, LD, and SE. Children exposed to higher levels of fluorine metabolites had a 2-fold increased odds (95% C.I. 1.1, 3.8) of SE, and this association was more apparent in males (OR 2.3; 95% C.I. 1.2, 4.1) than in females (OR 1.8; 95% C.I. 0.6, 5.4). No other consistent pattern of developmental disorders was associated with urinary PAH metabolites. However, concurrent exposure to PAH fluorine metabolites may increase use of special education services among U.S. children.
A 4.5-mW Closed-Loop Micro-Gravity CMOS SOI Accelerometer

In this paper, design, implementation and character- ization of a 3-V switched-capacitor (SC) CMOS interface cir- cuit for the closed-loop operation of a lateral capacitive micro- gravity silicon-on-insulator (SOI) accelerometer is presented. The interface circuit is based on a front-end programmable reference- capacitorlessSCcharge amplifierandaback-end second-order SC modulator. The accelerometer is fabricated through a dry-re- lease high aspect-ratio reduced-gap process. By incorporating the low- transfer function of the microaccelerometer in a feedback loop, the system's dynamic range is improved by 20 dB, leading to a measured resolution of 4 g Hz and an output dynamic range of 95 dB at 20 Hz. The bias instability is 2 to 8 g for 12 hours. The chip is fabricated in the 0.5- m standard CMOS process with an area of 2.25 mm . The integrated circuit (IC) consumes 4.5 mW of power.
A micropower learning vector quantizer for parallel analog-to-digital data compression

An analog VLSI architecture for learning vector quantization (LVQ), with on-chip adaptation and dynamic storage of the analog templates, is presented. The architecture extends to fuzzy ART and Kohonen self-organizing maps through digital programming. The analog memory and adaptive element of the LVQ cell comprise 6 MOS transistors and one capacitor, and provide for robust self-refresh of the dynamic analog storage. Total cell size including distance and adaptive computations is 80/spl times/70 lambda in scalable MOSIS technology. Experimental results from a fabricated 16/spl times/16 cell prototype in 2 /spl mu/m CMOS are included.
Extended Abstract Object Recognition via Robust Learning

Visual learning for object and scene recognition is a challenging task. Recently, many different methods mainly rooted in statistical pattern recognition have been proposed. Visual information is in most cases, treated in a direct manner, therefore these methods are not limited by object geometric complexity, texture, or surface markings. This direct representation and the link to statistical pattern recognition make these methods very suitable for learning. One can characterize the methods if a local or a global image representation is used. Typical global approaches are Principal component analysis (PCA), linear discriminant analysis (LDA), Independent Component Analysis (ICA) etc. Recently proposed local approaches are based on detection of interest points (e.g., Harris, Difference of Gaussians, Maximally Stable Regions, etc.) and the description of their local grey-value neighborhood (e.g. SIFT, Shape context, Steerable filters, etc.). Another characterization of the learning approaches is, if they use a generative model (i.e., ability of reconstruction and generation of samples), or if a discriminative model is employed. Each of them offering distinctive advantages (e.g., generative models enable robustness in model construction, whereas discriminative methods achieve in general higher recognition rates). Whereas both local and global methods have recently demonstrated how robust recognition can be obtained, the problem of robust learning has been hardly addressed. The main question is how we can learn an object model despite a significant amount of noise and/or occlusion and other disturbances in the training images. This extended abstract will briefly outline one approach and show how it can be used in a learning a pedestrian detection system.
Analytical Investigation of Availability in a Vision Cloud Storage Cluster

The goal of VISION Cloud, a European Commission funded project, is to design a new scalable and flexible storage cloud architecture able to provide data-intensive storage cloud services. The proposed environment employs a distributed file system on top of a set of storage rich nodes composing a cluster. Several clusters constitute a data center, while multiple geographically distributed data centers form a single storage cloud. In this paper, we focus on a single VISION Cloud storage cluster, providing a stochastic reward net model for an investigation of its availability. The proposed model is a first attempt at obtaining a quantification of the availability level of the cloud storage provided by the VISION Cloud architecture.
Lymphocyte Early Activation Thrombospondin-1 Inhibits TCR-Mediated T

3 Biological activities of the matrix glycoprotein thrombospondin-1 (TSP1) are cell type speciﬁc and depend on the relative expression or activation of several TSP1 receptors. Although engaging individual TSP1 receptors in T lymphocytes can elicit costimulating signals, in this study we show that intact TSP1 inhibits TCR-mediated T cell activation, assessed globally using cDNA microarrays. TSP1 signaling suppressed expression of several genes induced in Jurkat T cells, including the T cell activation markers CD69, early growth response gene-1 (Egr-1), and phosphatase of activated cells (PAC-1). TCR-stimulated and CD47-costimulated IL-2 secretion and cell surface CD69 expression were also inhibited by TSP1. The speciﬁc inhibitory effect of TSP1 was veriﬁed in freshly isolated human PBMCs. TSP1 inhibited TCR-mediated but not protein kinase C-mediated T cell activation. Using CD69 expression as a marker, we demonstrated that the inhibitory activity of TSP1 depended on two TSP1 receptors, CD47 and integrin-associated protein heparan sulfate proteoglycans. Signals from these receptors inhibited TCR signaling downstream of ZAP70, but upstream of NF-AT. Therefore, the expression of TSP1 induced during wound repair and in tumor stroma may limit T cell activation at these sites. The Journal of Immunology, 2001, 166: 2427–2436.
FlatFitFab: interactive modeling with planar sections

We present a comprehensive system to author planar section structures, common in art and engineering. A study on how planar section assemblies are imagined and drawn guide our design principles: planar sections are best drawn in-situ, with little foreshortening, orthogonal to intersecting planar sections, exhibiting regularities between planes and contours. We capture these principles with a novel drawing workflow where a single fluid user stroke specifies a 3D plane and its contour in relation to existing planar sections. Regularity is supported by defining a vocabulary of procedural operations for intersecting planar sections. We exploit planar structure properties to provide real-time visual feedback on physically simulated stresses, and geometric verification that the structure is stable, connected and can be assembled. This feedback is validated by real-world fabrication and testing. As evaluation, we report on over 50 subjects who all used our system with minimal instruction to create unique models.
Beyond 100 million entities: large-scale blocking-based resolution for heterogeneous data

A prerequisite for leveraging the vast amount of data available on the Web is Entity Resolution, i.e., the process of identifying and linking data that describe the same real-world objects. To make this inherently quadratic process applicable to large data sets, blocking is typically employed: entities (records) are grouped into clusters - the blocks - of matching candidates and only entities of the same block are compared. However, novel blocking techniques are required for dealing with the noisy, heterogeneous, semi-structured, user-generateddata in the Web, as traditional blocking techniques are inapplicable due to their reliance on schema information. The introduction of redundancy, improves the robustness of blocking methods but comes at the price of additional computational cost. In this paper, we present methods for enhancing the efficiency of redundancy-bearing blocking methods, such as our attribute-agnostic blocking approach. We introduce novel blocking schemes that build blocks based on a variety of evidences, including entity identifiers and relationships between entities; they significantly reduce the required number of comparisons, while maintaining blocking effectiveness at very high levels. We also introduce two theoretical measures that provide a reliable estimation of the performance of a blocking method, without requiring the analytical processing of its blocks. Based on these measures, we develop two techniques for improving the performance of blocking: combining individual, complementary blocking schemes, and purging blocks until given criteria are satisfied. We test our methods through an extensive experimental evaluation, using a voluminous data set with 182 million heterogeneous entities. The outcomes of our study show the applicability and the high performance of our approach.
Demo Abstract: Distributed and Synchronized Measurements with FLOCKLAB

1 Motivation and Overview Developing, testing, debugging, and evaluating communication protocols for low-power wireless networks is a long and cumbersome task. Simulators can be helpful in the early stages of development, but their models of hardware components and the wireless channel are often rather simplistic and hence cannot substitute experiments on real sensor node platforms. The resources available on common platforms are however very limited, and so are the possibilities for non-intrusive debugging and testing. With most existing testbeds it is only possible to collect information from the serial port, which requires adding highly intrusive logging statements that alter the timing behavior of the software running on the nodes. This is particularly detrimental to the operation of time-critical components, such as radio drivers, media access control (MAC) protocols, and certain flooding protocols [2], hindering their testbed-assisted development. To overcome the limitations of current testbeds, we have been developing the FLOCKLAB testbed over the past years. This demo abstract describes the architecture of FLOCKLAB and highlights the benefits it brings for non-intrusive testing and profiling of sensor network protocols and applications. For example, it is possible to take synchronized power measurements and capture changes in the state of General Purpose Input/Output (GPIO) pins on every FLOCKLAB node simultaneously. The FLOCKLAB architecture is highly scalable and allows for easy integration of future node platforms. As FLOCKLAB is publicly accessible, the demonstration will provide a hands-on experience for potential testbed users. 2 The FLOCKLAB Testbed FLOCKLAB consists of several observer nodes (currently 30) that are connected to a server through a wired or wireless local area network (LAN). The observer nodes are deployed both indoors and outdoors of an ETH office building. Compared with a typical sensor node, a FLOCKLAB observer is more powerful: it is based on a Gumstix Verdex pro XL6P that features a 600MHz XScale processor, 128MB SDRAM, 32MB flash, and runs OpenEmbedded Linux. Sensor nodes, called targets, are attached to the observers through target adapter boards; up to four targets can be attached to a single observer, as shown in Fig. 1. This approach
Interferon gamma inhibits apoptotic cell death in B cell chronic lymphocytic leukemia

The malignant, CD5+ B lymphocytes of B cell chronic lymphocytic leukemia (B-CLL) die by apoptosis in vitro. This is in contrast to the prolonged life span of the leukemic cells in vivo and likely reflects the lack of essential growth factors in the tissue culture medium. We found that interferon gamma (IFN-gamma) inhibits programmed cell death and promotes survival of B-CLL cells in culture. This effect may also be important in vivo: increased serum levels of IFN-gamma, ranging from 60 to > 2,200 pg/ml, were found in 7 of 10 B-CLL samples tested, whereas the sera of 10 healthy individuals did not contain detectable levels of this cytokine (< 20 pg/ml). High levels of IFN-gamma message were detected in RNA from T cell-depleted B-CLL peripheral blood samples by Northern blot analysis. Synthesis of IFN-gamma by B-CLL lymphocytes was confirmed by in situ hybridization and flow cytometry. The majority of B-CLL cells (74-82%) expressed detectable levels of IFN- gamma mRNA, and CD19+ B-CLL cells were labeled with anti-IFN-gamma monoclonal antibodies. These results show that IFN-gamma inhibits programmed cell death in B-CLL cells and suggest that the malignant cells are able to synthesize this cytokine. By delaying apoptosis, IFN- gamma may extend the life span of the malignant cells and thereby contribute to their clonal accumulation.