Miracle-dz/UniFAR-FTUs huggingface dataset:
Making Problems in Design Research: The Case of Teen Shoplifters on Tumblr

HCI draws on a variety of traditions but recently there have been calls to consolidate contributions around the problems researchers set out to solve. However, with this comes the assumption that problems are tractable and certain, rather than constructed and framed by researchers. We take as a case study a Tumblr community of teen shoplifters who post on how to steal from stores, discuss shoplifting as political resistance, and share jokes and stories about the practice. We construct three different "problems" and imagine studies that might result from applying different design approaches: Design Against Crime; Critical Design and Value Sensitive Design. Through these studies we highlight how interpretations of the same data can lead to radically different design responses. We conclude by discussing problem making as a historically and politically contingent process that allow researchers to connect data and design according to certain moral and ethical principles.
Balanced application-specific processor system for efficient SIFT-feature detection

Due to its computational complexity, the Scale-Invariant Feature Transform (SIFT) algorithm poses a challenge for use in embedded applications. To meet real-time at low power, hardware acceleration is necessary. This paper presents an FPGA-based balanced processor system for real-time SIFT feature detection, containing a dedicated hardware coprocessor coupled to a custom VLIW soft-core processor using a FIFO memory. The coprocessor calculates the scale-space and performs the extrema detection for the extraction of feature candidates, whereas the VLIW soft-core processor performs sub-pixel localization and stability checks to get stable SIFT-features. The system achieves a peak frame rate of up to 338 fps on 1,024×376 px images at less than 3 W on a Xilinx Virtex-6 FPGA. The filters within the Gaussian pyramid operate in a time-multiplexed scheme on clock frequencies up to 400 MHz. Furthermore, this paper presents a comprehensive design space exploration, evaluating architectural performance, hardware resources and power consumption trade-offs as well as exposing performance-balanced and pareto-optimal design variants.
Investigation on Application of Local Cluster Analysis and Part of Speech Tagging on Persian Text

In this research we applied Local Cluster Analysis (LCA) in tandem with Part-of-Speech tagging to monolingual task. We study different Persian POS tags and select a set of designated tags to reduce the size of our index and store the rich content of the documents. In addition, we applied LCA on the retrieved documents to detect the relevant and irrelevant documents to the user query. The clustering method is an important part in our approach. So we address the problem of building effective and meaningful clustering and evaluate different well-known and state of the art clustering methods for better efficiency and effectiveness in the proposed approach.
New computational method for three-fingered force-closure test

SUMMARY This paper proposes an efficient implementation of a force-closure test for frictional three-finger grasps. The implementation is based on a condition that transforms force-closure testing into the problem of convex hull intersection in projective space. The proposed implementation further reduces the problem into the problem of computing whether a line segment intersects a convex hull of at most four points. Implementation results are presented along with a thorough performance analysis and comparison with several existing methods. The results are also verified with arbitrary precision floating point computation. This provides comparison of qualitative error resulting from floating point roundoff. The result shows that the proposed implementation outperforms other methods in terms of speed and precision.
Dendritic Discrimination of Temporal Input Sequences in Cortical Neurons

Discriminating Dendrites Can dendrites read out spatiotemporal input sequences? Combining two-photon glutamate uncaging and two-photon calcium imaging, electrophysiology, and computational modeling, Branco et al. (p. 1671, published online 12 August; see the Perspective by Destexhe) discovered that single dendrites were indeed sensitive to both the direction and velocity of synaptic inputs. This direction- and velocity-sensitivity was measurable with only a few inputs and should thus be engaged frequently during normal brain function. Dendrites of neurons are sensitive to the sequence of synaptic activation and can implement cortical computation. The detection and discrimination of temporal sequences is fundamental to brain function and underlies perception, cognition, and motor output. By applying patterned, two-photon glutamate uncaging, we found that single dendrites of cortical pyramidal neurons exhibit sensitivity to the sequence of synaptic activation. This sensitivity is encoded by both local dendritic calcium signals and somatic depolarization, leading to sequence-selective spike output. The mechanism involves dendritic impedance gradients and nonlinear synaptic N-methyl-d-aspartate receptor activation and is generalizable to dendrites in different neuronal types. This enables discrimination of patterns delivered to a single dendrite, as well as patterns distributed randomly across the dendritic tree. Pyramidal cell dendrites can thus act as processing compartments for the detection of synaptic sequences, thereby implementing a fundamental cortical computation.
Evaluating the impact of execution parameters on program vulnerability in GPU applications

While transient faults continue to be a major concern for the High Performance Computing (HPC) community, we still lack a clear understanding of how these faults propagate in applications. This paper addresses two particular aspects of the vulnerabilities of HPC applications as run on Graphics Processing Units (GPUs): their dependence on input data and on thread-block size. To characterize fault propagation as a function of input parameters, we leverage an ISA-level fault injection framework and carry out an extensive fault injection campaign to characterize the vulnerability of a suite of GPU applications. Our results show that the vulnerability of most of the programs studied are insensitive to changes in input values, except in less common cases when input values were highly biased, i.e., values that exhibit a special vulnerability behavior. For example, the multiplication property of any value with a zero value (zero times any number is equal to zero) makes it a biased input for multiplication operations. Our study also examines the effects of changing the GPU thread-block size and its impact on vulnerability. We found that, similar to performance, the vulnerability of an application can depend on the block size of the kernels in the application. In some applications, we found that the silent data corruption rate can vary by as much as 8% when changing the block size of a kernel.
Collecting reliable clades using the Greedy Strict Consensus Merger

Supertree methods combine a set of phylogenetic trees into a single supertree. Similar to supermatrix methods, these methods provide a way to reconstruct larger parts of the Tree of Life, potentially evading the computational complexity of phylogenetic inference methods such as maximum likelihood. The supertree problem can be formalized in different ways, to cope with contradictory information in the input. Many supertree methods have been developed. Some of them solve NP-hard optimization problems like the well-known Matrix Representation with Parsimony, while others have polynomial worst-case running time but work in a greedy fashion (FlipCut). Both can profit from a set of clades that are already known to be part of the supertree. The Superfine approach shows how the Greedy Strict Consensus Merger (GSCM) can be used as preprocessing to find these clades. We introduce different scoring functions for the GSCM, a randomization, as well as a combination thereof to improve the GSCM to find more clades. This helps, in turn, to improve the resolution of the GSCM supertree. We find this modifications to increase the number of true positive clades by 18% compared to the currently used Overlap scoring.
Trends in Topics in Software Engineering Conferences, 1992 to 2016

Context: The very rapid pace of change in Software Engineering(SE) research makes it very difficult to gain an overview of the entire field or track trends in specific areas of SE. Objective: Develop a very rapid "overview tool" that can help humans understand how topics are evolving in SE. Method: Perform a topic modelling analysis using Tuned Latent Dirichlet Allocation of abstracts and titles of 15121 papers over the last 25 years. Results: (a)Eleven topics are identified as the dominant themes in modern SE. (b)Publication trends for topics in SE are not static; in fact, some of them become less prominent over time while others become very prominent indeed. (c) Clustering conferences on the topics they usually publish, it is observed that SE conferences fall into six large groups. (d) Considering that the Program Committee (PC) constitutes to less than a quarter of authors with published papers, the topics of papers published by the PC almost exactly match with the topics seen in all the published papers. (e) Successful authors in SE explore a diverse range of topics rather than focus on a niche set. Conclusion: Based on the results, recommendations are offered on how to(a)plan on an individual's research career, (b) intelligently make new conferences or merge older ones,(c) better recruit PCs & (d) encourage a broader range of topics at SE conferences.
Interactive Web Information Retrieval Using WordBars

It is common for Web searchers to have difficulties crafting queries to fulfil their information needs. Even when they provide a good query, users often find it challenging to evaluate the results of their Web searches. Sources of these problems include the lack of support for query refinement, and the static nature of the list-based representations of Web search results. To address these issues, we have developed WordBars, an interactive tool for Web information retrieval. WordBars visually represents the frequencies of the terms found in the first 100 document surrogates returned from the initial query. This system allows the users to interactively re-sort the search results based on the frequencies of the selected terms within the document surrogates, as well as to add and remove terms from the query, generating a new set of search results. Examples illustrate how WordBars can provide valuable support for query refinement and search results exploration, both when specific and vague initial queries are provided
The Index of Pupillary Activity: Measuring Cognitive Load vis-à-vis Task Difficulty with Pupil Oscillation

A novel eye-tracked measure of the frequency of pupil diameter oscillation is proposed for capturing what is thought to be an indicator of cognitive load. The proposed metric, termed the Index of Pupillary Activity, is shown to discriminate task difficulty vis-a-vis cognitive load (if the implied causality can be assumed) in an experiment where participants performed easy and difficult mental arithmetic tasks while fixating a central target (a requirement for replication of prior work). The paper's contribution is twofold: full documentation is provided for the calculation of the proposed measurement which can be considered as an alternative to the existing proprietary Index of Cognitive Activity (ICA). Thus, it is possible for researchers to replicate the experiment and build their own software which implements this measurement. Second, several aspects of the ICA are approached in a more data-sensitive way with the goal of improving the measurement's performance.
Identification of microRNAs specifically expressed in hepatitis C virus‐associated hepatocellular carcinoma

Although several studies have investigated the association of miRNAs with hepatocellular carcinoma (HCC), the data published so far are not concordant. A reason for these discrepancies may be the fact that most studies used the nontumorous tissue surrounding the HCC lesion as a control, which is almost invariably affected by cirrhosis or chronic hepatitis, as well as other pathological conditions such as hepatitis B virus (HBV) or hepatitis C virus (HCV) infection. Moreover, HCC is often analyzed as a single group regardless of the different viral etiologies. The miRNAs differentially expressed in HCV‐related HCC were investigated by comparing the tumorous tissues to a wide range of liver specimens, including healthy livers obtained from liver donors and patients who underwent liver resection for angioma, in addition to tissues from various acute and chronic liver diseases, including HCV‐related cirrhosis not associated with HCC, HCV‐related cirrhosis associated with HCC and HBV‐associated acute liver failure. The whole set of 2,226 human miRNAs were examined, including 1,121 pre‐miRNAs and 1,105 mature miRNAs, available in a microarray platform. Stringent statistical methods were applied to reduce the risk of false discoveries to less than 1%. These data identified 18 miRNAs exclusively expressed in HCV‐associated HCC, characterized by high specificity and selectivity versus all other liver diseases and healthy conditions and connected into a regulatory network pivoting on p53, phosphatase and tensin homolog and all‐trans retinoic acid signaling.
Purification and Characterization of a Novel Hypersensitive Response-Inducing Elicitor from Magnaporthe oryzae that Triggers Defense Response in Rice

Background Magnaporthe oryzae, the rice blast fungus, might secrete certain proteins related to plant-fungal pathogen interactions. Methodology/Principal Findings In this study, we report the purification, characterization, and gene cloning of a novel hypersensitive response-inducing protein elicitor (MoHrip1) secreted by M. oryzae. The protein fraction was purified and identified by de novo sequencing, and the sequence matched the genomic sequence of a putative protein from M. oryzae strain 70-15 (GenBank accession No. XP_366602.1). The elicitor-encoding gene mohrip1 was isolated; it consisted of a 429 bp cDNA, which encodes a polypeptide of 142 amino acids with a molecular weight of 14.322 kDa and a pI of 4.53. The deduced protein, MoHrip1, was expressed in E. coli. And the expression protein collected from bacterium also forms necrotic lesions in tobacco. MoHrip1 could induce the early events of the defense response, including hydrogen peroxide production, callose deposition, and alkalization of the extracellular medium, in tobacco. Moreover, MoHrip1-treated rice seedlings possessed significantly enhanced systemic resistance to M. oryzae compared to the control seedlings. The real-time PCR results indicated that the expression of some pathogenesis-related genes and genes involved in signal transduction could also be induced by MoHrip1. Conclusion/Significance The results demonstrate that MoHrip1 triggers defense responses in rice and could be used for controlling rice blast disease.
What Makes an Automated Vehicle a Good Driver?

An automated vehicle needs to learn how human road users experience the intentions of other drivers and understand how they communicate with each other in order to avoid misunderstandings and prevent giving a negative external image during interactions. The aim of the present study is to identify a cooperative lane change indication which other drivers understand unambiguously and prefer when it comes to lane change announcements in a dense traffic situation on the highway. A fixed-base driving simulator study is conducted with N = 66 participants in Germany in a car-following scenario. Participants rated, from the lag driver's perspective, different lane change announcements of another driver which varied in lateral movements (i.e., duration, lateral offset). Main findings indicate that a medium offset and moderate duration of lateral movement is experienced as most cooperative. The results are crucial for the development of lane change strategies for automated vehicles.
Closest coset decoding of |u|u+v| codes

The general concept of closest coset decoding (CCD) is presented, and a soft-decoding technique for block codes that is based on partitioning a code into a subcode and its cosets is described. The computational complexity of the CCD algorithm is significantly less than that required if a maximum-likelihood detector (MLD) is used. A set-partitioning procedure and details of the CCD algorithm for soft decoding of mod u mod u+v mod codes are presented. Upper bounds on the bit-error-rate (BER) performance of the proposed algorithm are combined, and numerical results and computer simulation tests for the BER performance of second-order Reed-Muller codes of length 16 and 32 are presented. The algorithm is a suboptimum decoding scheme and, in the range of signal-to-noise-power-density ratios of interest, its BER performance is only a few tenths of a dB inferior to the performance of the MLD for the codes examined. >
Your Eyes Tell: Leveraging Smooth Pursuit for Assessing Cognitive Workload

A common objective for context-aware computing systems is to predict how user interfaces impact user performance regarding their cognitive capabilities. Existing approaches such as questionnaires or pupil dilation measurements either only allow for subjective assessments or are susceptible to environmental influences and user physiology. We address these challenges by exploiting the fact that cognitive workload influences smooth pursuit eye movements. We compared three trajectories and two speeds under different levels of cognitive workload within a user study (N=20). We found higher deviations of gaze points during smooth pursuit eye movements for specific trajectory types at higher cognitive workload levels. Using an SVM classifier, we predict cognitive workload through smooth pursuit with an accuracy of 99.5% for distinguishing between low and high workload as well as an accuracy of 88.1% for estimating workload between three levels of difficulty. We discuss implications and present use cases of how cognition-aware systems benefit from inferring cognitive workload in real-time by smooth pursuit eye movements.
Diagnostic Yield of Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration Cytological Smears and Cell Blocks: A Single-Institution Experience

Background and Objective: Endobronchial ultrasound (EBUS) is a minimally invasive endobronchial technique, which uses ultrasound along with a bronchoscope to visualize the airway wall and structures that are adjacent to it. Indications for endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) are samplings of mediastinal, hilar lymph nodes, and tumors adjacent to airway walls. EBUS-TBNA has been used in our clinic since 2009. The aim of the study is to evaluate the sensitivity, specificity, positive and negative predictive value, and diagnostic accuracy of cytological and histological specimens, and the safety of EBUS-TBNA in an unselected patient population that has been referred to our hospital. Materials and Methods: We have retrospectively analyzed the medical documentation of 215 patients who had EBUS-TBNA performed in our clinic from April 2009 to February 2014. Results: There were 215 patients who underwent EBUS-TBNA. A total of 296 lymph nodes were sampled. EBUS-TBNA was diagnostic in 176 (81.9%) cases of cytological, 147 (68.4%) cases of histological, and 191 (88.9%) cases of the combined evaluation. In the lung cancer patients, EBUS-TBNA cytology had a sensitivity of 72.9% and histology of 72.9%, and in the sarcoidosis group, it had a cytology of 55.8% and histology of 64.5%. As all positive cytology and histology specimens were assumed to be true positive, specificity and positive predictive value (PPV) were 100%. The sensitivity and diagnostic accuracy was significantly higher when cytology and histology specimens were combined, compared with cytology or histology results evaluated separately (p < 0.05) (for lung cancer 84.1% and for sarcoidosis 78.8%). The sensitivity and diagnostic accuracy of EBUS-TBNA procedures increased significantly over time, with increased experience. There were no complications with EBUS-TBNA in our clinical practice. Conclusions: EBUS-TBNA had a high diagnostic yield and was safe in the diagnosis of lung cancer and sarcoidosis. It was most informative when cytology and histology were combined. The informative value of EBUS-TBNA histology increased with our experience.
p38‐MAPK‐ and caspase‐3‐mediated superoxide‐induced apoptosis of rat hepatic stellate cells: Reversal by retinoic acid

Reactive oxygen species (ROS) activate retinoid‐containing quiescent hepatic stellate cells (qHSCs) to retinoid‐deficient fibrogenic myofibroblast‐like cells (aHSCs). However, ROS also cause apoptosis of aHSCs, and apoptotic aHSCs are observed in inflammatory fibrotic liver. Here, we investigated mechanisms of the effects of oxidative stress on the survival of qHSCs and aHSCs. HSCs from normal rat liver were used after overnight culture (qHSCs), or in 3–5 passages (aHSCs). For in vivo induction of oxidative stress, tert‐butylhydroperoxide was injected into control and CCl4‐induced cirrhotic rats. Spontaneous caspase‐3 activation and apoptosis, observed in cultured qHSCs, decreased with time and were unaffected by superoxide. In contrast, superoxide caused caspase‐3 and p38‐MAPK activation, reduction in Bcl‐xL expression, and apoptosis in aHSCs. Inhibition of caspase‐3 and p38‐MAPK did not affect the viability of qHSCs in the absence or presence of superoxide, but inhibited superoxide‐induced death of aHSCs. Glutathione (GSH) level and activities of superoxide dismutase (SOD), catalase and glutathione peroxidase (GPx) were lower in aHSCs than qHSCs. Superoxide increased GSH content, and activities of SOD, catalase and GPx in qHSCs but not in aHSCs. Incubation of 13‐cis‐retinoic acid (RA)‐treated aHSCs with superoxide increased their GSH content significantly, and prevented superoxide‐induced p38‐MAPK and caspase‐3 activation while dramatically reducing the extent of apoptosis. Finally, oxidative stress induced in vivo caused apoptosis of aHSCs in cirrhotic but not of qHSCs in control rats. These results suggest that the absence of retinoids render aHSCs susceptible to superoxide‐induced apoptosis via caspase‐3 and p38‐MAPK activation. J. Cell. Physiol. 218: 157–166, 2009. © 2008 Wiley‐Liss, Inc.
Body Localization in Still Images Using Hierarchical Models and Hybrid Search

We present a 3-level hierarchical model for localizing human bodies in still images from arbitrary viewpoints. We first fit a simple tree-structured model defined on a small landmark set along the body contours by Dynamic Programming (DP). The output is a series of proposal maps that encode the probabilities of partial body configurations. Next, we fit a mixture of view-dependent models by Sequential Monte Carlo (SMC), which handles self-occlusion, anthropometric constraints, and large viewpoint changes. DP and SMC are designed to search in opposite directions such that the DP proposals are utilized effectively to initialize and guide the SMC inference. This hybrid strategy of combining deterministic and stochastic search ensures both the robustness and efficiency of DP, and the accuracy of SMC. Finally, we fit an expanded mixture model with increased landmark density through local optimization. The model hierarchy is trained on a large number of gait images. Extensive tests on cluttered images with varying poses including walking, dancing and various types of sports activities demonstrate the feasibility of the proposed approach.