Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of human perception In Cluster-Based Visual Analysis Of Multidimensional Data Projections

Visualization of high-dimensional data requires a mapping to a visual space. Whenever the goal is to preserve similarity relations, multidimensional projections or other dimension reduction techniques are commonly used to project high-dimensional data point to a 2D point using a certain strategy for the 2D layout.Typical analysis tasks for projected multidimensional data do not necessarily match the expectations of human perception. Learning more about the effectiveness of projection layouts from a users perspective is an important step towards consolidating their role in supporting visual analytics tasks. Those tasks often involve detecting and correlating clusters. To understand the role of orientation and cluster properties of size, shape and density, we first conducted a study with synthetic 2D scatter plots, where we can set the respective properties manually. Then we picked five projection methods representative of different approaches to generate layouts of high dimensional data for two domains, image and document data. The users were asked to identify the clusters on real-world data and answers to questions were compared for correctness against ground truth computed directly from the data. Our results offer interesting insight on the use of projection layouts in data visualization tasks.
Modeling and analysis of composite network embeddings

In a composite network, a piece of information traveling through links in a social network may have to travel over multiple links in an associated communication network. In this paper, we propose a model of composite networks that consists of two networks and an embedding between them, and several composite metrics that characterize information flow under a particular type of embedding. We present analytic results for the scaling behavior of "constrained composite stretch" of a path, "constrained composite diameter" of a graph, and "constrained composite broadcast time" of a tree, under random uniform embeddings onto various communication network structures. We validate our analytical results on composite stretch using two data sets consisting of a friendship social network geographically spread across Western Europe and a historical deployment of a military chain of command. We also present a randomized model of field deployment consistent with real-world data, and use simulations over this model to explore the distribution of constrained composite broadcast time. Finally, we show that our analytical bounds for composite broadcast time agree well with the simulation results.
Enabling Portable Building Applications through Automated Metadata Transformation

Sensor network research has facilitated advancements in various domains, such as industrial monitoring, environmental sensing, etc., and research challenges have shifted from creating infrastructure to utilizing it. Commercial buildings provide a valuable setting for investigating automated metadata acquisition and augmentation, as they typically comprise large sensor networks, but have limited, obscure ’tags’ that are often meaningful only to the facility managers. Moreover, this primitive metadata is imprecise and varies across vendors and deployments. Extracting meaningful information from a building’s sensor data, or control applications using the data, depends on the metadata available to interpret it, whether provided by novel networks or legacy instrumentation. This state-of-the-art is a fundamental barrier to scaling analytics or intelligent control across the building stock, as even the basic steps involve labor intensive manual efforts by highly trained consultants. Writing building applications on its sensor network remains largely intractable as it involves extensive help from an expert in each building’s design and operation to identify the sensors of interest and create the associated metadata. This process is repeated for each application development in a particular building, and across different buildings. This results in customized building-specific application queries which are not portable or scalable across buildings. We present a synthesis technique that learns how to transform a building’s primitive sensor metadata to a common namespace by using a small number of examples from an expert, such as the building manager. Once the transformation rules are learned for one building, it can be applied across buildings with a similar metadata structure. This ∗ Primary Author. common and understandable namespace can enable analytics applications that do not require apriori building-specific knowledge. Initial results show that learning the rules to transform 70% of the primitive metadata of two buildings (with completely different metadata structure), comprising 1600 and 2600 sensors, into a common namespace ([13]) took only 21 and 27 examples respectively. The learned rules were able to transform similar primitive metadata in close to 60 other buildings as well, enabling writing of portable applications across these buildings.
Predictors of “Liking” Three Types of Health and Fitness-Related Content on Social Media: A Cross-Sectional Study

Background Adolescence and young adulthood are key periods for developing norms related to health behaviors and body image, and social media can influence these norms. Social media is saturated with content related to dieting, fitness, and health. Health and fitness–related social media content has received significant media attention for often containing objectifying and inaccurate health messages. Limited research has identified problematic features of such content, including stigmatizing language around weight, portraying guilt-related messages regarding food, and praising thinness. However, no research has identified who is “liking” or “following” (ie, consuming) such content. Objective This exploratory study aimed to identify demographics, mental health, and substance use–related behaviors that predicted consuming 3 types of health and fitness–related social media content—weight loss/fitness motivation pages (ie, “fitspiration”), detox/cleanse pages, and diet/fitness plan pages—among young social media users. Methods Participants (N=1001; age: median 21.06, IQR 17.64-24.64; female: 723/1001, 72.23%) completed a cross-sectional 112-question online survey aimed at social media users aged between 15-29 years residing in Victoria, Australia. Logistic regression was used to determine which characteristics predicted consuming the 3 types of health and fitness–related social media content. Results A total of 378 (37.76%) participants reported consuming at least 1 of the 3 types of health and fitness–related social media content: 308 (30.77%) fitspiration pages, 145 (14.49%) detox pages, and 235 (23.48%) diet/fitness plan pages. Of the health and fitness–related social media content consumers, 85.7% (324/378) identified as female and 44.8% (324/723) of all female participants consumed at least 1 type of health and fitness–related social media content. Predictors of consuming at least one type of health and fitness–related social media content in univariable analysis included female gender (OR 3.5, 95% CI 2.5-4.9, P<.001), being aged 15-17 years (OR 3.0, 95% CI 2.2-4.0, P<.001), residing outside a major city (OR 2.0, 95% CI 1.4-2.9, P<.001), having no post–high school education (OR 2.2, 95% CI 1.7-2.9, P<.001), being born in Australia (OR 2.0, 95% CI 1.2-3.2, P=.006), having a self-reported eating disorder (OR 2.4, 95% CI 1.5-3.9, P<.001), being a victim of bullying (OR 1.7, CI 1.3-2.3, P<.001), misusing detox/laxative teas or diet pills (OR 4.6, 95% CI 2.8-7.6, P<.001), never using illegal drugs (OR 1.6, 95% CI 1.2-2.0, P=.001), and not engaging in risky single occasion drinking on a weekly basis (OR 2.0, 95% CI 1.3-3.0, P=.003). Conclusions Consumers of health and fitness–related social media content were predominantly teenaged girls. There is a need to ensure that this social media content portrays responsible health messages and to research further the role of fitspiration pages, detox pages, and diet/fitness plan pages in influencing body image and health behaviors.
Zero-shot semantic parser for spoken language understanding

Machine learning algorithms are now common in the state-of-the-art spoken language understanding models. But to reach good performance they must be trained on a potentially large amount of data which are not available for a variety of tasks and languages of interest. In this work, we present a novel zero-shot learning method, based on word embeddings, allowing to derive a full semantic parser for spoken language understanding. No annotated in-context data are needed, the ontological description of the target domain and generic word embedding features (learned from freely available general domain data) sufﬁce to derive the model. Two versions are studied with respect to how the model parameters and decoding step are handled, including an extension of the proposed approach in the context of conditional random ﬁelds. We show that this model, with very little supervision, can reach instantly performance comparable to those obtained by either state-of-the-art carefully handcrafted rule-based or trained statistical models for extraction of dialog acts on the Dialog State Tracking test datasets (DSTC2 and 3).
Parallel Computation Still Needs a Unifying Model to Play in the Mainstream

Parallel computation in the last twenty years has been effectively used to solve many significant problems in several application areas of applied science and engineering. The research and development work both in parallel hardware and software showed as parallel computers allow the implementation of high-performance applications that cannot eff iciently implemented in sequential computers [1]. However, until today parallel computing did not become a methodology used in all the areas of computer science applications. It has not yet one of the most significant portion of the mainstream of computing. Even if parallelism met important goals, to reach its maturity this goal should be a major challenge of parallel computing in the next years for assuring itself a future in the next century.
The Speedup Model for Manycore Processor

Integrating a large number of simple cores on the chip to provide the desired performance and throughput, microprocessor has entered the many core era. In order to fully extract the ability of the many core processor, we propose speedup models for many core architecture in this paper. Under the assumption of Hill-Marty model, we deduce our formulas based on Gustafson's Law and Sun-Ni's Law. Then, compared with the Hill-Marty model, we theoretically analyze the best allocation under the given resources. Furthermore, we apply the conclusions of our models to evaluate current many core processors and predict concrete future architecture. Our results show that the many core architecture is capable of extensive scalability and being beneficial to promote the performance, especially heterogeneous one. By using simple analytical models, we provide a better understanding of architecture design and our work complement existing studies.
Visual Analytics for Digital Radiotherapy: Towards a Comprehensible Pipeline

Prostate cancer is one of the most frequently occurring types of cancer in males. It is often treated with radiation therapy, which aims at irradiating tumors with a high dose, while sparing the surrounding healthy tissues. In the course of the years, radiotherapy technology has undergone great advancements. However, tumors are not only different from each other, they are also highly heterogeneous within, consisting of regions with distinct tissue characteristics, which should be treated with different radiation doses. Tailoring radiotherapy planning to the specific needs and intra-tumor tissue characteristics of each patient is expected to lead to more effective treatment strategies. Currently, clinical research is moving towards this direction, but an understanding of the specific tumor characteristics of each patient, and the integration of all available knowledge into a personalizable radiotherapy planning pipeline are still required. The present work describes solutions from the field of Visual Analytics, which aim at incorporating the information from the distinct steps of the personalizable radiotherapy planning pipeline, along with eventual sources of uncertainty, into comprehensible visualizations. All proposed solutions are meant to increase the – up to now, limited – understanding and exploratory capabilities of clinical researchers. These approaches contribute towards the interactive exploration, visual analysis and understanding of the involved data and processes at different steps of the radiotherapy planning pipeline, creating a fertile ground for future research in radiotherapy planning.
Biochemical and biological characterization of lymphocyte regulatory molecules. V. Identification of an interleukin 2-producing human leukemia T cell line

To isolate a stable tumor cell line capable of producing human interleukin 2 (IL-2; formerly referred to as T cell growth factor), 16 human T and B leukemia cell lines were screened for constitutive and mitogen-stimulated IL-2 production. We found that the T cell leukemia line designated Jurkat-FHCRC produced > 200 U/ml of IL-2 activity after a 24-h stimulation with T cell mitogens. Peak mitogen-induced IL-2 activity was found in supernates harvested from 24-h Jurkat-FHCRC cell cultures stimulated with either 1% phytohemagglutinin or 20 microgram/ml concanavalin A. Addition of the fatty acid derivative phorbol myristate acetate to mitogen-stimulated cultures increased Jurkat-FHCRC IL-2 production to concentrations > 400 U/ml. IL-2 activity observed in such cases represented between 100--300 times that produced in conventional cultures of mitogen- or alloantigen-stimulated normal human peripheral blood or splenic lymphocytes. Jurkat-FHCRC- derived conditioned medium demonstrated equal capacity to promote the sustained in vitro proliferation of either murine or human activated T cell lines confirming the ability of Jurkat-FHCRC cells to produce human IL-2. These studies identify a new source of human IL-2 and establish a valuable reagent for the isolation and further molecular characterization of this immunoregulatory molecule.
Discovering the truth by conducting experiments

Prolusion Paul Vitányi's 2003 Kolmogorov complexity lecture included a computer exercise in which a polynomial relation had to be learnt from samples. 1 The following data were provided: a sequence of pairs of numbers (h 1 , d 1), supposedly noisy measurements of a classical urn, h i being the height from the floor and d i being the diameter of the urn at the height h i. The goal was to infer a polynomial that represented the relation between height and diameter. For a given degree, this can easily be done using linear algebra. The crux of the exercise was finding the best degree. An example is shown in Figure 1. To me, learning from given data is only part of a more general concept of learning, and I started to wonder whether the techniques that I learnt during my studies could be adapted to an interactive setting, allowing the learner to perform experiments. For example, when learning polynomials, the learner could be allowed to choose a point, and she would then receive the value of the polynomial at that point. For this thesis, I started working on the interactive polynomial learning problem, but it turned out to be much too hard. I then devised the balance scale problem (see Chapter 4), a toy problem that conserves the important features of the polynomial learning problem: it is interactive, probabilistic, model-based, but finite. I had by then developed a slight aversion to subjective Bayesian methods, for my initial work on the polynomial learning problem suggested that they are not robust. It seemed that a subjective Bayesian learner can be tricked into assigning high posterior probability to a certain proposition while Figure 1 Urn example 1 The exercise by Troy Lee is still available online at i this proposition is false, and additionally, great confidence in this proposition leads to great confidence in the usefulness of experiments that in fact do not help to determine that this proposition is false. With this in mind, I decided to perform a worst-case analysis of the balance scale problem, and of similar problems in general. This problem naturally decomposed into the truth-finding problem, where we want to find the true model from given data, and the experiment-design problem, where experiments have to be selected, whose outcomes subsequently serve as the data for truth finding. I have yet to solve the balance scale problem completely. …
The normal Lactobacillus flora of healthy human rectal and oral mucosa

The Lactobacillus flora of the rectal and oral mucosa was sampled from 42 healthy volunteers. Species identification was carried out by numerically comparing API 50CH fermentation patterns with type strains, using an SJ‐similarity cut‐off level of 79%. For the largest groups, identity was further confirmed by DNA‐DNA hybridizations against the type strain of the species. Seventeen lactobacilli clusters were defined, of which most were found both on rectal and oral mucosa. The largest taxa were Lactobacillus plantarum, Lact. rhamnosus and Lact. paracasei ssp. paracasei, which were isolated from 52%, 26% and 17% of the individuals, respectively. Most isolates were tested for their capacity to adhere to the human colonic cell line HT‐29 in the absence and presence of methyl‐α‐ D‐mannoside. Mannose‐sensitive adherence to HT‐29 cells was encountered in two‐thirds of the Lact. plantarum isolates, but infrequently among isolates of other taxa. The results suggest that Lact. plantarum is a major colonizer of the human gastrointestinal mucosa, and that its capacity to adhere to mannose‐containing receptors may be of some ecological importance.
Immuno-protective effect of tumor cell vaccine on Kunming mice bearing Ehrlich ascites tumor.

AIM:To evaluate the immunity of chemically modified tumor cell vaccine.METHODS:Tumor cell vaccines (TCV) were prepared by incubating the live Ehrlich ascites tumor cells with concanavalin A-mitomycin C (ConA-MMC), mitomycin C (MMC), concanavalin A-glutaraldehyde (ConA-Glu), glutaraldehyde (Glu), or paraformaldehyde (Para), respectively. The whole cell or soluble forms of the vaccines were administered intraperitoneally into Kunming mice once a week for three times prior to the intraperitoneal inoculation of a lethal dose of live tumor cells. A second challenge with live tumor cells was given four weeks later. Survival and antibody production of the mice were analyzed.RESULTS:After the first challenge, the mice, received whole TCV of ConA-MMC, MMC (P < 0.01) and Glu (P < 0.05) promoted survival incidence than the controls. All the treated mice had the survival time prolonged. ConA-MMC vaccine treated mice had longer survival days than that of ConA-Glu ones (P < 0.05). For the soluble TCV immunized mice,those treated with vaccines of Para (P < 0.01), ConA-Para and ConA-Glu (P < 0.05) had longer survival periods compared with that of the controls. Following the second challenge, survival incidence of the mice received vaccines of ConA-MMC, MMC, ConA-Glu or Glu was significantly increased (P < 0.01). Moreover, all the treated mice had the survival time prolonged, and ConA-MMC vaccine treated mice had longer survival days than that of Para treated ones (P < 0.05). Antibodies against Ehrlich ascites tumor cells were found to be positive in sera of the mice treated with whole TCV of ConA-MMC.CONCLUSION:Ehrlich ascites tumor cells are immunogenic when treated with ConA-MMC, MMC, ConA-Glu, Glu or Para, which might act as safe and effective tumor vaccines with safety and effectiveness.
T-Cell Immunoglobulin and Mucin Domain 3 Acts as a Negative Regulator of Atherosclerosis

Objective—Atherosclerosis is a chronic autoimmune-like disease in which lipids and fibrous elements accumulate in the arterial blood vessels. T cells are present within atherosclerotic plaques, and their activation is partially dependent on costimulatory signals, which can either provide positive or negative signals that promote T-cell activation or limit T-cell responses, respectively. T-cell immunoglobulin and mucin domain 3 (Tim-3) is a coinhibitory type 1 transmembrane protein that affects the function of several immune cells involved in atherosclerosis, such as monocytes, macrophages, effector T cells, and regulatory T cells. In the present study, we determined the role of Tim-3 in the development of atherosclerosis. Approach and Results—Western-type diet–fed low-density lipoprotein receptor–deficient (LDLr−/−) mice were treated with an anti–Tim-3 antibody for 3 and 8 weeks. Anti–Tim-3 administration increased fatty streak formation with 66% and increased atherosclerotic plaque formation after 8 weeks with 35% in the aortic root and with 50% in the aortic arch. Furthermore, blockade of Tim-3 signaling increased percentages of circulating monocytes with 33% and lesional macrophages with 20%. In addition, anti–Tim-3 administration increased CD4+ T cells with 17%, enhanced their activation status, and reduced percentages of regulatory T cells with 18% and regulatory B cells with 37%. Conclusions—It is known that Tim-3 acts as a negative regulator of both innate and adaptive immune responses, and in the present study, we show that anti–Tim-3 treatment augments lesion development, accompanied by an increase in the number of monocytes/macrophages and CD4+ T cells and by decreased regulatory T cells and regulatory B cells.
An empirical test of stage models of e-government development: Evidence from Dutch municipalities

ABSTRACT In this article we empirically test stage models of e-government development. We use Lee's classification to make a distinction between four stages of e-government: informational, requests, personal, and e-democracy. We draw on a comprehensive data set on the adoption and development of e-government activities in 510 Dutch municipalities over the period 2004–2009. Our results show that progression through stages of e-government is mostly linear. However, it seems that a single dimension is insufficient to explain e-government development at the level of more specific features of e-government. Our analysis demonstrates that municipalities sometimes adopt certain e-government features at a later stage even if features of an earlier stage are not adopted at all. These findings suggest that municipalities can—at the level of e-government features—immediately proceed to later stages without having to pass through earlier stages. We conclude that stage models may have some value for benchmarking municipalities at the level of stages, but are inadequate in explaining or predicting the development of features at the different e-government stages.