Miracle-dz/UniFAR-FTUs huggingface dataset:
How Do People Tag Picture ?-A Pilot Study with Facebook Application

Acknowledgement First and foremost I would like give my best appreciation to my supervisor, Lexing Xie who offers a lot of support during the project development and composing this report. In the development process, she provides us a clear guidance of project direction and makes lots of useful suggestions towards problems encountered. Secondly, I would like show my thankfulness to my teammate Li Li. As teamwork, this project requires coordination along development. He is always friendly in our discussion and willing to listen to my opinions. Li Li's intelligence in design and analysis is really important in the successful of our project. Finally, I would like to thank all the participants that contribute the data collection of our project. Without your help, our project would not be possible. Abstract Photo tagging has been popularized by the increasing photo capture devices and diverse content sharing services. Considerable research topics have been achieved in this area: understanding motivations and usage of tags, the accuracy and value of machine generated tags, and using human brainpower to collect large scale photos tags via ESP games. In this project we try to figure out the differences between authors' tags and viewers' tags. To achieve this goal, a Facebook application called " Tag Expert " is designed and implemented to collect tags for Flickr photos by Facebook users. Then we designed several data collection methods and only choose one of them to evaluate due to the limited time and participants. The evaluation shows that GWAP principals could affect the correctness and efficiency of data collections for our application. Together with the experience in our developing process, the evaluation and untried data collection methods could be a very useful pilot study for future development in this area.
Inhibition of Viral Pathogenesis and Promotion of the Septic Shock Response to Bacterial Infection by IRF-3 Are Regulated by the Acetylation and Phosphorylation of Its Coactivators

ABSTRACT Interferon (IFN) is required for protecting mice from viral pathogenesis; reciprocally, it mediates the deleterious septic shock response to bacterial infection. The critical transcription factor for IFN induction, in both cases, is IRF-3, which is activated by TLR3 or RIG-I signaling in response to virus infection and TLR4 signaling in response to bacterial infection. Here, we report that IRF-3’s transcriptional activity required its coactivators, β-catenin and CBP, to be modified by HDAC6-mediated deacetylation and protein kinase C isozyme β (PKC-β)-mediated phosphorylation, respectively, so that activated nuclear IRF-3 could form a stable transcription initiation complex at the target gene promoters. β-Catenin bridges IRF-3 and CBP, and the modifications were required specifically for the interaction between β-catenin and CBP but not β-catenin and IRF-3. Consequently, like IRF-3−/− mice, HDAC6−/− mice were resistant to bacterial lipopolysaccharide-induced septic shock. Conversely, they were highly susceptible to pathogenesis caused by Sendai virus infection. Thus, HDAC6 is an essential component of the innate immune response to microbial infection. IMPORTANCE It is important to understand how we protect ourselves against microbial infection. Specific receptors present in mammalian cells, called Toll-like receptors, are assigned to sense different microbial chemicals, such as bacterial lipopolysaccharides or viral double-stranded RNA. Activation of these receptors leads to the activation of a critical transcription factor, IRF-3, which drives the induced synthesis of interferon, a secreted protein required for our protection. Here, we report that interferon synthesis is regulated not only by IRF-3 activation but also by activation of two proteins, β-catenin and CBP, which function together with IRF-3. β-Catenin is activated by its deacetylation by HDAC6, and CBP is activated by its phosphorylation by protein kinases C isozyme β (PKC-β). These regulations are operative not only in cell cultures but also in mice. It is important to understand how we protect ourselves against microbial infection. Specific receptors present in mammalian cells, called Toll-like receptors, are assigned to sense different microbial chemicals, such as bacterial lipopolysaccharides or viral double-stranded RNA. Activation of these receptors leads to the activation of a critical transcription factor, IRF-3, which drives the induced synthesis of interferon, a secreted protein required for our protection. Here, we report that interferon synthesis is regulated not only by IRF-3 activation but also by activation of two proteins, β-catenin and CBP, which function together with IRF-3. β-Catenin is activated by its deacetylation by HDAC6, and CBP is activated by its phosphorylation by protein kinases C isozyme β (PKC-β). These regulations are operative not only in cell cultures but also in mice.
Loss of Cartilage Structure, Stiffness, and Frictional Properties in Mice Lacking PRG4

Objective To assess the role of the glycoprotein PRG4 in joint lubrication and chondroprotection by measuring friction, stiffness, surface topography, and subsurface histology of the hip joints of Prg4−/− and wild-type (WT) mice. Methods Friction and elastic modulus were measured in cartilage from the femoral heads of Prg4−/− and WT mice ages 2, 4, 10, and 16 weeks using atomic force microscopy, and the surface microstructure was imaged. Histologic sections of each femoral head were stained and graded. Results Histologic analysis of the joints of Prg4−/− mice showed an enlarged, fragmented surface layer of variable thickness with Safranin O–positive formations sometimes present, a roughened underlying articular cartilage surface, and a progressive loss of pericellular proteoglycans. Friction was significantly higher on cartilage of Prg4−/− mice at age 16 weeks, but statistically significant differences in friction were not detected at younger ages. The elastic modulus of the cartilage was similar between cartilage surfaces of Prg4−/− and WT mice at young ages, but cartilage of WT mice showed increasing stiffness with age, with significantly higher moduli than cartilage of Prg4−/− mice at older ages. Conclusion Deletion of the gene Prg4 results in significant structural and biomechanical changes in the articular cartilage with age, some of which are consistent with osteoarthritic degeneration. These findings suggest that PRG4 plays a significant role in preserving normal joint structure and function.
Simultaneous Time-of-Flight sensing and photometric stereo with a single ToF sensor

We present a novel system which incorporates photometric stereo with the Time-of-Flight depth sensor. Adding to the classic ToF, the system utilizes multiple point light sources that enable the capturing of a normal field whilst taking depth images. Two calibration methods are proposed to determine the light sources' positions given the ToF sensor's relatively low resolution. An iterative refinement algorithm is formulated to account for the extra phase delays caused by the positions of the light sources. We find in experiments that the system is comparable to the classic ToF in depth accuracy, and it is able to recover finer details that are lost due to the noise level of the ToF sensor.
Prolonging the Lifetime and Optimizing the Energy of Wireless Sensor Network System using Mobile Sensor Nodes

As the technology of wireless sensor networks become increasingly matured and supported by small, micro-mobile devices fully, wireless sensor network has gradually become an effective tool for gathering data in various situations. It has very broad application prospects and great potential value in many areas such as in the military & national defense, environmental monitoring, biomedical, remote monitoring dangerous areas & so on. In this paper, we developed simulated an energy efficient mobile sensor node clustering protocol for WSN systems – EEMSNCP, a protocol architecture for energy efficiency, data aggregation & transmitting aggregated data to base station to achieve good performance in terms of energy efficiency and network lifetime. EEMSNCP includes self organization of sensor nodes, rotation of cluster head positions to evenly distribute energy load among all the nodes, TDMA scheduling for energy efficiency & replacement of cluster head with mobile sensor node when its energy gets depleted to improve system lifetime. Our results show that EEMSNCP improves system lifetime by an order of magnitude compared with LEACH.
A THESIS SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY Daniel Showers IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE

System identification techniques are powerful tools that help improve modeling capabilities of real world dynamic systems. These techniques are well established and have been successfully used on countless systems in many areas. However, wind turbines provide a unique challenge for system identification because of the difficulty in measuring its primary input: wind. This thesis first motivates the problem by demonstrating the challenges with wind turbine system identification using both simulations and real data. It then suggests techniques toward successfully identifying a dynamic wind turbine model including the notion of an effective wind speed and how it might be measured. Various levels of simulation complexity are explored for insights into calculating an effective wind speed. In addition, measurements taken from the University of Minnesota’s Clipper Liberty C96 research wind turbine are used for a preliminary investigation into the effective wind speed calculation and system identification of a real world wind turbine.
Visual servoing control of robot manipulator with Jacobian matrix estimation

Visual servoing system is a system to control a robot by visual feedback. This paper presents a visual servoing control that drives the end-effector of a real robot manipulator from any arbitrary start position to the desired positions. The control law is obtained using inverse Jacobian matrix. Since there is not access to the model of the robot, artificial neural networks are used to estimate of inverse Jacobian matrix. There are many challenges in practical implementation such as: how to calculate Jacobian matrix, determining the intelligent structure for estimation of Jacobian matrix, recognition coordinate of each joint with image processing and changes in illumination. We proposed appropriate solutions to solve the mentioned challenges. The experimental results in the real robot show that the control system can move the end-effector to target positions from any arbitrary start position with good accuracy.
SOCIAL CONSTRUCTION AND POLITICAL DECISION MAKING IN THE AMERICAN PRISON SYSTEM(S)

OF DISSERTATION SOCIAL CONSTRUCTION AND POLITICAL DECISION MAKING IN THE AMERICAN PRISON SYSTEM(S) With over two million inmates, the United States’ prison population is the largest in the world. Nearly one in one hundred Americans are behind bars, either in prisons or pre-trial detention facilities. The rapid growth in incarceration is well-documented. However, social science explanations often stop at the prison gates, with little work on treatment inside prisons. This black box approach ignores important bureaucratic decisions, including the provision of rehabilitative services and the application of punishment. This dissertation offers a systematic analysis of treatment decisions inside the American prisons. I use a mixed methods approach, combining multiple quantitative datasets with environmental observation at four prisons, and original interviews of twenty-three correctional staff members. I offer the only large-n comparative analysis of American state prisons. Characteristics of the inmates as well as characteristics of staff are explored. I am able to analyze data at the state, facility and individual level. All of this is to answer a crucial and somewhat overlooked question; how do prison staff decide who should be punished and who should receive rehabilitative treatment? I find that theories of social construction offer insight into the treatment of American prison inmates. Specifically, I find that socially constructed racial categories offer explanatory value for inmate treatment. Black and Hispanic inmates are less likely to receive important rehabilitative programs, including access to mental health and medical care. Black and Hispanic inmates are also more likely to receive punishment including the use of solitary confinement in administrative segregation units. I find, consistent with theories of representative bureaucracy that staffing characteristics also impact treatment decisions, with black and Hispanic staff members expressing lower preferences for punishment and prisons with higher percentages of black staff members utilize administrative segregation less. I provide a historical overview of the changing social constructions of crime and prisons inside the United States, from colonial to present day America. I argue that the treatment of prisoners changes as our conception of crime changes. I discuss recent bipartisan attempts at prison reform and offer my own suggestions for reform of the American prison system.
Summary Estimates of Cholesterol Used to Predict Coronary Heart Disease

The relationships of total cholesterol and the proportion of cholesterol in individual lipoprotein classes to coronary heart disease are complex. To help simplify these relationships, cholesterol values are often combined into one summary estimate to form a single risk factor with a relationship to disease that is more easily described. Although summary estimates result in convenient expressions relating cholesterols to coronary heart disease, there is the potential for sacrificing information by ignoring the joint configuration of cholesterols that make up these estimates. We investigated the extent of this possibility for the ratio of total cholesterol to high-density lipoprotein cholesterol and the ratio of low-density lipoprotein cholesterol to high-density lipoprotein cholesterol. The findings suggest that the summary estimates are useful expressions for combining cholesterol information and are strong predictors of coronary heart disease. Clinicians who choose to use a summary estimate for screening purposes should recognize that a single ratio estimate is not always as informative as the joint configuration of the cholesterols that make up the estimate. This possibility is most clearly exhibited for the ratio of low-density lipoprotein cholesterol to high-density lipoprotein cholesterol, and it may become more apparent in future studies as the capabilities of exploring lipoprotein cholesterol relationships improve.
Real-time Human Hair Modeling and Animation

Various methods have been employed to model human hair, including modeling hair strands individually [1, 4]; using trigonal prisms with 2D hair distribution maps [3, 9] and more recently, volumetric visualization techniques [6, 7]. These approaches concentrate mainly on modeling hair accurately, and often require specialized rendering algorithms. As such, hardware acceleration is unlikely to be available for the above approaches, making them more suitable for off-line graphics system.
An energy efficient double cluster head routing scheme for motorway vehicular networks

We propose a novel double cluster-head routing scheme for motorway vehicular networks which is generically modelled (can be applied o single or multiple cluster-head routing schemes) to save a significant amount of energy through adaptive sleep cycles while maintaining he required quality of service (QoS). Real vehicular and data traffic measurements are utilised o evaluate the performance of he double cluster-head (DCH) scheme and compare with he existing (a single cluster-head (SCH)) scheme. The results, also verified with he simulations, reveal that the DCH scheme is able to achieve 2× lower packet blocking probability compared o he SCH scheme. Furthermore, on an average energy saving of 94% with service-tolerant delay during the whole day is achieved. In addition, we found ha with a lower market penetration ratio (MPR), which represents he near future vehicular communication rend, more than 4× energy is saved during peak hours in a motorway vehicular environment.
Optimizing Decision Quality with Contract Algorithms

Contract algorithms offer a tradeoff between output quality and computation time provided that the amount of computation time is determined prior to their activation Originally they were introduced as an intermediate step in the composition of interruptible anytime algorithms However for many real-time tasks such as information gathering game playing, and a large class of planning problems contract algorithms offer an ideal mechanism to optimize decision quality This paper extends previous results regarding the meta-level control of contract algorithms by handling a more general type of performance description. The output quality of each contract algorithm is described by a probabilistic (rather than deterministic) conditional performance profile. Such profiles map input quality and computation time to a probability distribution of output quality. The composition problem is solved by an efficient off-line compilation technique that simplifies the run-time monitoring task.
Network-Aware Workload Scheduling for Scalable Linked Data Stream Processing

In order to cope with the ever-increasing data volume, distributed stream processing systems have been proposed. To ensure scalability most distributed systems partition the data and distribute the workload among multiple machines. This approach does, however, raise the question how the data and the workload should be partitioned and distributed. A uniform scheduling strategy—a uniform distribution of computation load among available machines—typically used by stream processing systems, disregards network-load as one of the major bottlenecks for throughput resulting in an immense load in terms of inter-machine communication. We propose a graph-partitioning based approach for workload scheduling within stream processing systems. We implemented a distributed triple-stream processing engine on top of the Storm realtime computation framework and evaluate its communication behavior using two real-world datasets. We show that the application of graph partitioning algorithms can decrease inter-machine communication substantially (by 40% to 99%) whilst maintaining an even workload distribution, even using very limited data statistics. We also find that processing RDF data as single triples at a time rather than graph fragments (containing multiple triples), may decrease throughput indicating the usefulness of semantics.
Independent quantization: an index compression technique for high-dimensional data spaces

Two major approaches have been proposed to efficiently process queries in databases: speeding up the search by using index structures, and speeding up the search by operating on a compressed database, such as a signature file. Both approaches have their limitations: indexing techniques are inefficient in extreme configurations, such as high-dimensional spaces, where even a simple scan may be cheaper than an index-based search. Compression techniques are not very efficient in all other situations. We propose to combine both techniques to search for nearest neighbors in a high-dimensional space. For this purpose, we develop a compressed index, called the IQ-tree, with a three-level structure: the first level is a regular (flat) directory consisting of minimum bounding boxes, the second level contains data points in a compressed representation, and the third level contains the actual data. We overcome several engineering challenges in constructing an effective index structure of this type. The most significant of these is to decide how much to compress at the second level. Too much compression will lead to many needless expensive accesses to the third level. Too little compression will increase both the storage and the access cost for the first two levels. We develop a cost model and an optimization algorithm based on this cost model that permits an independent determination of the degree of compression for each second level page to minimize expected query cost. In an experimental evaluation, we demonstrate that the IQ-tree shows a performance that is the "best of both worlds" for a wide range of data distributions and dimensionalities.
Differential Proteomics Identifies Protein Biomarkers That Predict Local Relapse of Head and Neck Squamous Cell Carcinomas

Purpose: The 5-year survival rates of head and neck squamous cell carcinomas (HNSCC) remain disappointing. HNSCCs develop in precursor fields of genetically altered cells that are often not completely resected when the tumor is excised, causing local relapse. These precursor fields are mostly recognized as dysplasia, but histologic grading cannot reliably predict malignant transformation. Our aim was to discover and validate protein biomarkers that can detect precursor fields and predict local relapse in HNSCC using immunostaining of surgical margins. Experimental Design: We compared paired and genetically characterized normal, precursor, and tumor tissues of eight patients by proteome analysis to identify differentially expressed proteins. The prognostic value of candidate protein biomarkers was evaluated by immunohistochemical analysis of 222 surgical margins of 46 HNSCC patients who developed local relapse or remained disease free. Significant associations were determined by Kaplan-Meier survival analysis and Cox-proportional hazards models. Results: Forty proteins showed significant differential expression (false discovery rate–corrected P < 0.05). Most discriminative markers suited for immunostaining were keratin 4 and cornulin. Low expression in the surgical margins of keratin 4 (hazard ratio, 3.8; P = 0.002), cornulin (hazard ratio, 2.7; P = 0.025), and their combination (hazard ratio, 8.8; P = 0.0005) showed a highly significant association with the development of local relapse. Dysplasia grading had no prognostic relevance. Conclusions: Immunohistochemical assessment of keratin 4 and cornulin expression in surgical margins of HNSCC patients outperforms histopathologic grading in predicting the risk for local relapse. These markers can be used to initiate more frequent and lifelong surveillance of patients at high risk of local relapse, and enable selection for adjuvant treatment or tertiary prevention trials. (Clin Cancer Res 2009;15(24):7666–75)
Tuning of the Outer Hair Cell Motor by Membrane Cholesterol*

Cholesterol affects diverse biological processes, in many cases by modulating the function of integral membrane proteins. We observed that alterations of cochlear cholesterol modulate hearing in mice. Mammalian hearing is powered by outer hair cell (OHC) electromotility, a membrane-based motor mechanism that resides in the OHC lateral wall. We show that membrane cholesterol decreases during maturation of OHCs. To study the effects of cholesterol on hearing at the molecular level, we altered cholesterol levels in the OHC wall, which contains the membrane protein prestin. We show a dynamic and reversible relationship between membrane cholesterol levels and voltage dependence of prestin-associated charge movement in both OHCs and prestin-transfected HEK 293 cells. Cholesterol levels also modulate the distribution of prestin within plasma membrane microdomains and affect prestin self-association in HEK 293 cells. These findings indicate that alterations in membrane cholesterol affect prestin function and functionally tune the outer hair cell.