Miracle-dz/UniFAR-FTUs huggingface dataset:
Stigma, Work, and “Unseen” Illness: A Case and Notes to Enhance Understanding

Phenomenological research into life and work for people with invisible chronic illness has revealed many examples of stigmatization. In trying to make sense of one particular case, the available literature on stigma is helpful yet unsatisfying, especially when considering life and work for those with unseen illness. The article presents a review of the stigma literature followed by the presentation of a taxonomy of potential determinants and detriments of stigma for those with invisible chronic illness. It would seem that stigmatization is influenced by numerous issues: knowledge of the diagnosis, moral judgments, and incorrect knowledge held about the disease as distinct from an absence of or incomplete knowledge. The proposed taxonomy is suggested to have been helpful in explaining one person's poignant comments and is advocated for use in the analysis and interpretation of future stories of those with invisible illness.
Effects of seasons and hunting on space use by female white‐tailed deer in a developed landscape in southeastern Nebraska

White-tailed deer (Odocoileus virginianus) were extirpated from a 1,800-ha natural area along the Missouri River near Omaha, Nebraska, USA shortly after settlement in the mid-1800s, but they recolonized the area in the early 1960s. In absence of hunting and predators, the population of deer became overabundant in the 1980s and 1990s. Deer impacted plant communities at Fontenelle Forest (FF) and Gifford Point (GP) and a 200-300% increase in deer-vehicle collisions was observed in the area. We radiocollared female white-tailed deer in this region during February 1995-March 1996 to determine the effects of phenological seasons and archery and muzzleloader hunting on space use. Mean size of annual home ranges of 50 radiocollared female deer was 275 ha (range ¼ 18-4,265 ha, SE ¼ 88). Forty-one of 50 deer (82%) maintained high fidelity to their small annual home ranges (x ¼ 115 ha, SE ¼ 13) and made short seasonal movements (<1.0 km). Seven deer dispersed and exhibited large seasonal shifts in centers of home ranges (x ¼ 3.2 km, range ¼ 1-7 km) and 2 deer exhibited migratory behavior. We observed no spatial patterns associated with seasonal dispersal or migration that would subject deer in unhunted areas to harvest in hunted areas. Controlled deer hunts were implemented in the upland areas adjacent to Bellevue residential area and the lowlands of FF and GP. Effects of archery hunting on deer use areas were minimal. Deer subjected to muzzleloader hunting increased the size of use areas by 88-97% and shifted centers of use areas a mean of 666 m (SE ¼ 211, range ¼ 121-1,932 m), but they did not leave the lowland areas of FF or GP. Controlled hunts enabled the removal of resident deer from populations adjacent to the Bellevue residential area. Where practical, we suggest that regulated hunting be used as part of an overall plan to manage densities of deer and associated impacts in developed landscapes. 2011 The Wildlife Society.
A Cell-Based High-Throughput Screen Validates the Plasmodial Surface Anion Channel As an Antimalarial Target

The plasmodial surface anion channel (PSAC) is an unusual small-conductance ion channel induced on erythrocytes infected with plasmodia, including parasites responsible for human malaria. Although broadly available inhibitors produce microscopic clearance of parasite cultures at high concentrations and suggest that PSAC is an antimalarial target, they have low affinity for the channel and may interfere with other parasite activities. To address these concerns, we developed a miniaturized assay for PSAC activity and carried out a high-throughput inhibitor screen. Approximately 70,000 compounds from synthetic and natural product libraries were screened, revealing inhibitors from multiple structural classes including two novel and potent heterocyclic scaffolds. Single-channel patch-clamp studies indicated that these compounds act directly on PSAC, further implicating a proposed role in transport of diverse solutes. A statistically significant correlation between channel inhibition and in vitro parasite killing by a family of compounds provided chemical validation of PSAC as a drug target. These new inhibitors should be important research tools and may be starting points for much-needed antimalarial drugs.
Thickness-Optimized Multilevel Resistive Switching of Silver Programmable Metallization Cells With Stacked SiOx/SiO2 Solid Electrolytes

Multilevel resistive switching (RS) characteristics of silver programmable metallization cells (Ag-PMCs) with stacked SiOx/SiO2 solid electrolytes have been investigated. Combined with conventional high/low resistance states and additional two middle resistance states (MRS1/MRS2), a multilevel cell operation of stacked-solid-electrolyte Ag-PMCs is achieved and optimized by the film thickness. Furthermore, the RS mechanism at middle resistance states has been proposed to be locally discontinuous Ag conductive filament (Ag-CF) within the stacked solid electrolytes by examining the carrier transportation and two-frequency calibrated capacitance. The stacked silicon oxide layers can prevent the Ag-CF from regeneration during the multilevel retention test, contributing to the superior retention properties to more than 104 s at 125 °C. In addition, a sequentially multilevel cycling test of more than 103 times with a resistance ratio of two orders of magnitude between each resistance state is realized by the stacked-solid-electrolyte Ag-PMCs, suitable for future high-density nonvolatile memory applications.
Clustering Classes in Packages for Program Comprehension

During software maintenance and evolution, one of the important tasks faced by developers is to understand a system quickly and accurately. With the increasing size and complexity of an evolving system, program comprehension becomes an increasingly difficult activity. Given a target system for comprehension, developers may first focus on the package comprehension. The packages in the system are of different sizes. For small-sized packages in the system, developers can easily comprehend them. However, for large-sized packages, they are difficult to understand. In this article, we focus on understanding these large-sized packages and propose a novel program comprehension approach for large-sized packages, which utilizes the Latent Dirichlet Allocation (LDA) model to cluster large-sized packages. Thus, these large-sized packages are separated as small-sized clusters, which are easier for developers to comprehend. Empirical studies on four real-world software projects demonstrate the effectiveness of our approach. The results show that the effectiveness of our approach is better than Latent Semantic Indexing- (LSI-) and Probabilistic Latent Semantic Analysis- (PLSA-) based clustering approaches. In addition, we find that the topic that labels each cluster is useful for program comprehension.
Causal mediation analysis with failure time outcome and error-prone longitudinal covariate

Causal Mediation Analysis with failure time outcome and error-prone longitudinal covariate Cheng Zheng Chair of the Supervisory Committee: Professor Ross L. Prentice Biostatistics Mediation analyses are important for understanding the biological mechanisms whereby a treatment/exposure influences an outcome of interest. For example, one may be interested in whether body fat accumulation mediates an association of certain dietary patterns with chronic diseases risk. Similarly mediation analyses may aim to achieve an understanding of which elements of a multi-faceted dietary modification intervention were most influential in affecting disease incidence. Several challenges occur in mediation analysis: (1) the longitudinal and observational nature of the dietary variables and BMI/weight; (2) the measurement error in dietary variables which are often assessed using food frequency questionnaires; (3) control of measured/unmeasured confounders. In this dissertation, we proposed a general potential outcome framework for causal mediation analysis with failure time outcome and longitudinal mediator/exposure with measurement error. We proposed a method to correct for the systematic bias in longitudinal self-reported dietary data and use the calibrated data to estimate parameters in the survival model. We also proposed a robust estimator of key survival model parameters that can accommodate the existence of certain types of unmeasured confounders. We studied the performance of regression calibration methods for multiple choices of survival models numerically. We analyzed some important epidemiologic data and provided scientific information on the interplay between dietary exposures, physical activity and BMI in relation to site-specific cancer and other chronic diseases.
Inductive benchmarking for purely functional data structures

Every designer of a new data structure wants to know how well it performs in comparison with others. But finding, coding and testing applications as benchmarks can be tedious and time-consuming. Besides, how a benchmark uses a data structure may considerably affect its apparent efficiency, so the choice of applications may bias the results. We address these problems by developing a tool for inductive benchmarking. This tool, Auburn, can generate benchmarks across a wide distribution of uses. We precisely define ‘the use of a data structure’, upon which we build the core algorithms of Auburn: how to generate a benchmark from a description of use, and how to extract a description of use from an application. We then apply inductive classification techniques to obtain decision trees for the choice between competing data structures. We test Auburn by benchmarking several implementations of three common data structures: queues, random-access lists and heaps. These and other results show Auburn to be a useful and accurate tool, but they also reveal some limitations of the approach.
A transmission gate flip-flop based on dual-threshold CMOS techniques

In present CMOS circuits, the power dissipation caused by leakage current cannot be neglected anymore. An effective way to reduce the leakage power is dual-threshold techniques. Low-threshold transistors are assigned to critical paths of the circuits to enhance the performance, while high-threshold transistors are assigned to non-critical paths to reduce the leakage current. This paper proposes a new transmission gate flip-flop based on dual-threshold CMOS technique to reduce its leakage power. Simulation results show that the proposed transmission gate dual-threshold flip-flop saves 20- 30% power and 40–50% leakage power compared with the single-threshold transmission gate one and gate-length biasing one, respectively. The proposed flip-flop is an excellent candidate for low-power VLSI designs in deep sub-micro ICs.
WALRUS: a similarity retrieval algorithm for image databases

Approaches for content-based image querying typically extract a single signature from each image based on color, texture, or shape features. The images returned as the query result are then the ones whose signatures are closest to the signature of the query image. While efficient for simple images, such methods do not work well for complex scenes since they fail to retrieve images that match the query only partially, that is, only certain regions of the image match. This inefficiency leads to the discarding of images that may be semantically very similar to the query image since they may contain the same objects. The problem becomes even more apparent when we consider scaled or translated versions of the similar objects. We propose WALRUS (wavelet-based retrieval of user-specified scenes), a novel similarity retrieval algorithm that is robust to scaling and translation of objects within an image. WALRUS employs a novel similarity model in which each image is first decomposed into its regions and the similarity measure between a pair of images is then defined to be the fraction of the area of the two images covered by matching regions from the images. In order to extract regions for an image, WALRUS considers sliding windows of varying sizes and then clusters them based on the proximity of their signatures. An efficient dynamic programming algorithm is used to compute wavelet-based signatures for the sliding windows. Experimental results on real-life data sets corroborate the effectiveness of WALRUS'S similarity model.
Microindentation for In Vivo Measurement of Bone Tissue Mechanical Properties in Humans

Bone tissue mechanical properties are deemed a key component of bone strength, but their assessment requires invasive procedures. Here we validate a new instrument, a reference point indentation (RPI) instrument, for measuring these tissue properties in vivo. The RPI instrument performs bone microindentation testing (BMT) by inserting a probe assembly through the skin covering the tibia and, after displacing periosteum, applying 20 indentation cycles at 2 Hz each with a maximum force of 11 N. We assessed 27 women with osteoporosis‐related fractures and 8 controls of comparable ages. Measured total indentation distance (46.0 ± 14 versus 31.7 ± 3.3 µm, p = .008) and indentation distance increase (18.1 ± 5.6 versus 12.3 ± 2.9 µm, p = .008) were significantly greater in fracture patients than in controls. Areas under the receiver operating characteristic (ROC) curve for the two measurements were 93.1% (95% confidence interval [CI] 83.1–100) and 90.3% (95% CI 73.2–100), respectively. Interobserver coefficient of variation ranged from 8.7% to 15.5%, and the procedure was well tolerated. In a separate study of cadaveric human bone samples (n = 5), crack growth toughness and indentation distance increase correlated (r = –0.9036, p = .018), and scanning electron microscope images of cracks induced by indentation and by experimental fractures were similar. We conclude that BMT, by inducing microscopic fractures, directly measures bone mechanical properties at the tissue level. The technique is feasible for use in clinics with good reproducibility. It discriminates precisely between patients with and without fragility fracture and may provide clinicians and researchers with a direct in vivo measurement of bone tissue resistance to fracture. © 2010 American Society for Bone and Mineral Research
Helping among kin vs. non-kin: The role of psychological closeness

This study explored the moderating effects of perceived kinship status (kin vs. non-kin) in the link between closeness and willingness to help. The participants of the study were 270 undergraduate students recruited from online and regular class periods. Moderated regression analysis confirmed that psychological closeness moderates the relationship between perceived kinship status and willingness to help. Specifically, the relationship between closeness and helping increased for non-kin, but decreased for kin. Results may imply that psychological closeness is an important determinant in helping a non-kin, and less important in helping a kin.
Ubiquity: Designing a Multilingual Natural Language Interface

This paper describes the design and implementation of Ubiquity, a multilingual textual interface for the Firefox browser developed at Mozilla Labs. The Ubiquity interface facilitates rapid information retrieval and task execution in the browser, leveraging existing open web APIs. The importance of offering equivalent user experiences for speakers of different languages is reflected in the design of Ubiquity’s new natural language parser, described here. This paper also aims to advocate the further development of equipotent multilingual interfaces for information access.
Reduced Support Vector Machine Based on Margin Vectors

Reduced Support Vector Machine (RSVM) was proposed as an alternate of the standard SVM. Motivated by resolving the difficulty on handling large data sets using SVM, it pre-extracts a subset of data as 'support vectors' and solves a smaller optimization problem. But it selects 'support vectors' randomly from the training set, and this will affect the result. A new method called reduced support vector machine based on margin vectors is presented in this paper, some margin vectors were extracted as 'support vectors' via center distance ratio, then were applied in the RSVM . The new method can be used to unbalanced data and reduce the effects of outliers. So the new method improves the ability of RSVM to classify and the training speed of SVM greatly.
DBExplorer: Exploratory Search in Databases

A traditional relational database can evaluate complex queries but requires users to precisely express their information need. But users often do not know what information is available in a database, and hence cannot correctly express their information need. Traditional databases do not provide convenient means for users to gain familiarity with the data. In this paper, we study the problem of exploratory search, which a user may wish to perform to get an understanding of the data set. We note that users often have some decisions already made, so what they need is not an overall database summary, but rather a summary “in context” of the relevant portion of the database. Towards this end, we devise a novel data summarization technique called the Conditional Attribute Dependency (CAD) View, which shows the conditional dependencies between attribute values conditioned on applied selections. The CAD View can help users to gain familiarity with structured datasets in an attribute-wise manner. To evaluate the CAD View, we perform a user study comprising three complex exploratory tasks on a real dataset. Our studies show that users are able to do all the tasks about 4-5 times faster and with better accuracy using the CAD View compared to the data summary shown in faceted navigation, which is currently the most popular search interface for e-commerce and has support for exploratory search.
An Introduction to Arithmetic Coding

Arithmetic coding is a data compression technique that encodes data (the data string) by creating a code string which represents a fractional value on the number line between 0 and 1. The coding algorithm is symbolwise recursive; i.e., it operates upon and encodes (decodes) one data symbol per iteration or recursion. On each recursion, the algorithm successively partitions an interval of the number line between 0 and 1, and retains one of the partitions as the new interval. Thus, the algorithm successively deals with smaller intervals, and the code string, viewed as a magnitude, lies in each of the nested intervals. The data string is recovered by using magnitude comparisons on the code string to recreate how the encoder must have successively partitioned and retained each nested subinterval. Arithmetic coding differs considerably from the more familiar compression coding techniques, such as prefix (Huffman) codes. Also, it should not be confused with error control coding, whose object is to detect and correct errors in computer operations. This paper presents the key notions of arithmetic compression coding by means of simple examples.
Several Required OWL Features for Indigenous Knowledge Management Systems

This paper describes the features required of OWL to realise and enhance Indigenous Knowledge (IK) digital repositories. Several needs for Indigenous Knowledge management systems (IKMSs) are articulated, based on extensive stakeholder input, and analysed on the suitability of semantic web technologies in addressing them. Based on their potential for impact and maturity, several possible applications are recommended for further investigation and inclusion into current or new IKMSs, including: ontology based querying and browsing; a natural language independent ontology for multilingual data access; support for collaborative knowledge generation; and the formalisation of IK for scientific discovery. For each of these possible applications, the required OWL features are discussed, which include representation of vagueness, mereotopology, modularisation, and extended support for internationalisation and annotation.
Inherited IL-12 Unresponsiveness Contributes to the High LPS Resistance of the Lpsd C57BL/10ScCr Mouse1

Lpsd mouse strains are characterized by the presence of a defective Lps/tlr4 gene that make them refractory to the biological activity of LPS. One of the mouse strains commonly used to study LPS defects is the C57BL/10ScCr (Cr) strain. However, unlike other Lpsd strains, the Cr strain also has a heavily impaired IFN-γ response to micro-organisms. As a consequence, unlike other Lpsd mouse strains, they do not acquire a partial LPS susceptibility when treated with sensitizing bacteria. Because IL-12 is important for the microbial induction of IFN-γ, we investigated whether the production or function of IL-12 might be defective in Cr mice. IL-12 mRNA (p35 and p40) was present in the spleen of untreated Cr mice, IL-12p40 mRNA was inducible in mice injected with live or killed Salmonella typhimurium, and IL-12 (p70) was inducible in macrophages by bacteria. Thus, Cr mice exhibit normal IL-12 responses. In functional tests, splenocytes of untreated or of S. typhimurium-infected mice failed to produce IFN-γ when stimulated with murine rIL-12 or with a combination of IL-12 and murine rIL-18 or Con A. Furthermore, Cr mice were identical with IL-12p35/p40 and IL-12 receptor β1 knockout mice in their impaired in vivo and in vitro IFN-γ responses to bacteria. Thus, Cr mice carry a second genetic defect unrelated to the Lps/tlr4 mutation that underlies the IL-12 unresponsiveness and contributes to the LPS resistance and impaired innate immune response in this strain.
Learning codebook weights for action detection

In this work we present a discriminative codebook weighting approach for action detection. We learn global and local weights for the codewords by considering the spatio-temporal Hough voting space of the training sequences. In contrast to the Implicit Shape Model (ISM) where all the codewords that are matched to a local descriptor cast votes with uniform weights, we learn local weights for the matched codewords. In order to learn the local weights we employ Locality-constrained Linear Coding (LLC). Further, we formulate the learning of the global weights as a convex quadratic programming and use alternating optimization to solve for the weights. We demonstrate the performance of the algorithm on KTH action dataset where we compare with the Hough detector using kmeans codebook.
Chronic but not intermittent infection with Pseudomonas aeruginosa is associated with global changes of the lung microbiome in cystic fibrosis

Chronic pulmonary infection with Pseudomonas aeruginosa that triggers chronic airway inflammation and structural lung damage remains a key risk factor for morbidity and mortality in patients with cystic fibrosis (CF) [1]. Previously, culture-based diagnostics considered airway infections in CF patients as mono-pathogenic, but recent approaches using culture-independent methods showed that bacterial infection of the CF lung involves a polymicrobial community [2–4]. Chronic infection with typical CF pathogens like P. aeruginosa is associated with a decline in lung function and correlates with a decrease of diversity in the lung microbiota. However, the interactions between pathogens and the microbiota remains poorly understood, and it has been hypothesised that dysbiosis of the microbiota may pre-exist and facilitate growth of pathogens such as P. aeruginosa in the CF lung. The aim of the current study was to evaluate the influence of P. aeruginosa infection on the dysbiosis of the microbiota in the CF lung. Chronic but not intermittent P. aeruginosa infection results in dysbiosis of lung microbiota in cystic fibrosis http://ow.ly/cDKO30eOnx5