Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding collective play in an urban screen game

In recent years there has been a growing interest in Urban Screen applications. While there have been several deployments of these technologies in our urban environments, surprisingly little research effort has aimed to explore the detailed material practice of people's engagement and interaction with these urban screen applications. In this paper, we present a study of collaborative game play on large urban displays situated in three city locations in the UK. The study highlights ways in which collaborative play is initiated and coordinated within the context of an urban environment. These experiences are related to physical characteristics of the architectural spaces, the people populating these spaces and the interactive properties of the game itself. The study moves on to discuss issues relating to audience and spectatorship, an inherent feature of interaction in urban environments. The issues of audience and spectatorship are discussed in their own right but also in terms of their relationship to the playing experience. Finally the study considers these interactive experiences in the contexts of being hosted by a professional compere and also with no host present. Through the study we highlight factors to consider in the design of collaborative urban screen applications.
Induction as knowledge integration

Accuracy and efficiency are the two main evaluation criteria for induction algorithms. One of the most powerful ways to improve performance along these dimensions is by integrating additional knowledge into the induction process. However, integrating knowledge that differs significantly from the knowledge already used by the algorithm usually requires rewriting the algorithm. This dissertation presents KII, a Knowledge Integration framework for Induction that provides a straightforward method for integrating knowledge into induction, and provides new insights into the effects of knowledge on the accuracy and complexity of induction. The idea behind KII is to express all knowledge uniformly as constraints and preferences on hypotheses. Knowledge is integrated by conjoining constraints and disjoining preferences. A hypothesis is induced from the integrated knowledge by finding a hypothesis consistent with all of the constraints and maximally preferred by the preferences. Theoretically, just about any knowledge can be expressed in this manner. In practice, the constraint and preference languages determine both the knowledge that can be expressed and the complexity of identifying a consistent hypothesis. RS-KII, an instantiation of KII based on a very expressive set representation, is described. RS-KII can utilize the knowledge of at least two disparate induction algorithms--AQ-11 and CEA ("version spaces")--in addition to knowledge that neither algorithm can utilize. It seems likely that RS-KII can utilize knowledge from other induction algorithms, as well as novel kinds of knowledge, but this is left for future work. RS-KII's complexity is comparable to these algorithms when using only the knowledge of a given algorithm, and in some cases RS-KII's complexity is dramatically superior. KII also provides new insights into the effects of knowledge on induction that are used to derive classes of knowledge for which induction is not computable.
United we Stand: Improving Sentiment Analysis by Joining Machine Learning and Rule Based Methods

In the past, we have succesfully used machine learning approaches for sentiment analysis. In the course of those experiments, we observed that our machine learning method, although able to cope well with figurative language could not always reach a certain decision about the polarity orientation of sentences, yielding erroneous evaluations. We support the conjecture that these cases bearing mild figurativeness could be better handled by a rule-based system. These two systems, acting complementarily, could bridge the gap between machine learning and rule-based approaches. Experimental results using the corpus of the Affective Text Task of SemEval 07, provide evidence in favor of this direction.
DNA methylation shows genome-wide association of NFIX, RAPGEF2 and MSRB3 with gestational age at birth.

BACKGROUND Gestational age at birth strongly predicts neonatal, adolescent and adult morbidity and mortality through mostly unknown mechanisms. Identification of specific genes that are undergoing regulatory change prior to birth, such as through changes in DNA methylation, would increase our understanding of developmental changes occurring during the third trimester and consequences of pre-term birth (PTB). METHODS We performed a genome-wide analysis of DNA methylation (using microarrays, specifically CHARM 2.0) in 141 newborns collected in Baltimore, MD, using novel statistical methodology to identify genomic regions associated with gestational age at birth. Bisulphite pyrosequencing was used to validate significant differentially methylated regions (DMRs), and real-time PCR was performed to assess functional significance of differential methylation in a subset of newborns. RESULTS We identified three DMRs at genome-wide significance levels adjacent to the NFIX, RAPGEF2 and MSRB3 genes. All three regions were validated by pyrosequencing, and RAGPEF2 also showed an inverse correlation between DNA methylation levels and gene expression levels. Although the three DMRs appear very dynamic with gestational age in our newborn sample, adult DNA methylation levels at these regions are stable and of equal or greater magnitude than the oldest neonate, directionally consistent with the gestational age results. CONCLUSIONS We have identified three differentially methylated regions associated with gestational age at birth. All three nearby genes play important roles in the development of several organs, including skeletal muscle, brain and haematopoietic system. Therefore, they may provide initial insight into the basis of PTB's negative health outcomes. The genome-wide custom DNA methylation array technology and novel statistical methods employed in this study could constitute a model for epidemiologic studies of epigenetic variation.
The Application of Users' Collective Experience for Crafting Suitable Search Engine Query Recommendations

Search engines have turned into one of the most important services of the Web that are frequently visited by any user. They assist their users in finding appropriate information. Among the many challenging issues in the design of Web search engines that is mostly related to the design of an adaptive interface is recommending suitable query phrases to the end-users. This has two major benefits: firstly the users can more easily interact with the Web search engine and secondly get hints on what is more apt to look for in cases where they may not have any clue. In this paper, we propose a graph based query recommendation algorithm that sequentially recommends query terms to its users. The most important notion behind the design of the algorithm is that the past behavior of previous users of a search engine is mined and a multi-segmented graph is built. Recommendation is made based on the relative similarity of query terms, their frequency and conceptual closeness in the graph.
Automatic object detection using shape information in ultrasound images

A method is presented for segmentation of anatomical structures that incorporates prior information about shape. The method iteratively applies steps, which find object's border considering its properties independently from shape. The boundary is regularized taking in account the shape being extracted. Detection is not directly performed in the image but in a "shape space" referred to the shape in each step. The problem is reduced to work in this new coordinate system where the border is approximately a horizontal line. Shape information is introduced through a higher dimensional map similar to a distance map of a mean shape. Segmentation results are demonstrated on ultrasound imagery to measure meat quality of bovine and ovine livestock.
Subjective cognitive decline in memory clinic patients - characteristics and clinical relevance

Subjective cognitive decline (SCD) refers to concerns – symptoms regarding one’s cognitive functioning, in the absence of objective evidence of impairment. SCD has been described as a possible stage preceding mild cognitive impairment (MCI) and dementia. The characteristics and clinical relevance in relation to subsequent objective cognitive decline is however still unclear. We developed a patient-based comprehensive questionnaire on everyday cognitive difficulties. Patients with SCD were followed over time, to analyze the associations between SCD and cognitive outcome. Furthermore, we investigated the associations between SCD and stress, depressive symptoms and CSF AD profiles, and evaluated newly published international criteria for SCD, ‘preclinical AD’ and subcategories, involving both clinical features and neurochemical biomarkers. All participants in the current thesis were patients or healthy volunteers at the Sahlgrenska memory clinic in Mölndal. We identified specific SCD symptoms that were more frequently reported by subjectively impaired patients seeking help for cognitive problems, compared to healthy elderly. The self-report instrument SASCI-Q is a useful research tool to investigate cognitive symptoms further. SCD patients were characterized by relatively young age, high educational attainment, high prevalence of stress conditions and depressive symptoms, and a family history of dementia. About 40 % of patients with SCD declined cognitively over 4±2.9 years – one fourth of them converted to dementia. When CSF biomarkers were added, the ability to predict MCI, dementia and AD dementia clearly increased. A specific profile of subjective cognitive symptoms could not be associated with cognitive decline in a mixed SCD+MCI patient sample. However, when groups were analysed separately, reporting more symptoms was associated with subsequent decline in the SCD group whilst reporting less symptoms was associated with subsequent decline in the MCI group. Cognitive symptoms reported by the patient may signify many different conditions, and their associations with subsequent dementia should not be overstated when there are no objective signs present.
Psychological distress and homeless duration*

Abstract We examine whether psychological distress levels vary with homeless and housed duration. We do this using longitudinal data from a national survey of persons facing housing insecurity that, unlike prior studies, is not restricted to those who are currently homeless (or to particular subsets of the homeless), but instead follows a nationally representative sample of Australians experiencing housing insecurity. This allows us to use methods that isolate the effects of changes in time spent homeless and time spent housed on psychological distress holding constant all unobserved person-specific effects that are time invariant. We find that the relationship between psychological distress and homelessness varies by gender and by type of homelessness. Males recently experiencing literal homelessness (i.e. sleeping rough or in crisis accommodation) exhibit the highest levels of distress, but consistent with the adaptation hypothesis, distress levels decline as homeless duration increases. This pattern is not seen when examining a broader notion of homelessness for males. Likewise, there is no clear pattern with regard to homeless duration for females.
The latest generation Whegs™ robot features a passive-compliant body joint

Current autonomous and semi-autonomous robotic platforms are limited to functioning in highly structured environments such as buildings and roads. Autonomous robots that could explore and navigate rugged terrain and highly unstructured environments such as collapsed buildings would have large dividends in civilian and military applications. In this work, we present the next generation of Whegstrade robots, DAGSI Whegstrade, which has been completed and extensively field tested. Several innovations have made the robot more rugged and well suited to autonomous operation. Specifically, an actively controlled, passively compliant body joint has been tested in three different modes of operation to judge the usefulness of the mechanism. A two-dimensional dynamic simulation of the robot has also been constructed, and has been used to study the effects of weight distribution on obstacle climbing and to investigate future autonomous climbing strategies. Moving the center of mass forward allowed the robot to climb taller obstacles. DAGSI Whegstrade can climb rectangular obstacles as tall as 2.19 times the length of a leg.
Chandra Observation of Abell 2142: Survival of Dense Subcluster Cores in a Merger

We use Chandra data to map the gas temperature in the central region of the merging cluster A2142. The cluster is markedly nonisothermal; it appears that the central cooling flow has been disturbed but not destroyed by a merger. The X-ray image exhibits two sharp, bow-shaped, shocklike surface brightness edges or gas density discontinuities. However, temperature and pressure profiles across these edges indicate that these are not shock fronts. The pressure is reasonably continuous across these edges, while the entropy jumps in the opposite sense to that in a shock (i.e., the denser side of the edge has lower temperature, and hence lower entropy). Most plausibly, these edges delineate the dense subcluster cores that have survived a merger and ram pressure stripping by the surrounding shock-heated gas.
Executive function measured by Stroop test and mood for elderly people in a facility for the elderly

Trichard et al. [1] showed that cognitive functions of those with clinical depression are lower than healthy people. This suggests relationships between cognitive function and mood. Sugimoto [2] also showed that the performance of the correct response measured by the Stroop of the not-well mental health group was lower than those of the healthy group. This also suggests relationships between cognitive function and mood.
Gold Nanoparticles as the Catalyst of Single-Walled Carbon Nanotube Synthesis

Gold nanoparticles have been proven to act as efficient catalysts for chemical reactions, such as oxidation and hydrogen production. In this review we focus on a different aspect of the catalysis of gold nanoparticles; single-walled carbon nanotube (SWCNT) synthesis. This is not a traditional meaning of catalytic reaction, but SWCNTs cannot be synthesized without nanoparticles. Previously, gold was considered as unsuitable metal species as the catalyst of SWCNT synthesis. However, gold nanoparticles with diameters smaller than 5 nm were found to effectively produce SWCNTs. We discuss the catalysis of gold and related metals for SWCNT synthesis in comparison with conventional catalysts, such as iron, cobalt, and nickel.
Predicting vowel substitution in code-switched speech

The accuracy of automatic speech recognition (ASR) systems typically degrades when encountering code-switched speech. Some of this degradation is due to the unexpected pronunciation effects introduced when languages are mixed. Embedded (foreign) phonemes typically show more variation than phonemes from the matrix language: either approximating the embedded language pronunciation fairly closely, or realised as any of a set of phonemic counterparts from the matrix language. In this paper we describe a technique for predicting the phoneme substitutions that are expected to occur during code-switching, using non-acoustic features only. As case study we consider Sepedi/English code switching and analyse the different realisations of the English schwa. A code-switched speech corpus is used as input and vowel substitutions identified by auto-tagging this corpus based on acoustic characteristics. We first evaluate the accuracy of our auto-tagging process, before determining the predictability of our auto-tagged corpus, using non-acoustic features.
Taxes, Cigarette Consumption, and Smoking Intensity: Reply

This paper shows that smoking intensity, i.e. the amount of nicotine extracted per cigarette smoked, responds to changes in excise taxes and tobacco prices. We exploit NHANES data covering the period 1988 to 2006 across many US states. Moreover, using panel data from the Coronary Artery Risk Development in Young Adults (CARDIA) study, we provide new evidence on the importance of cotinine measures in explaining long-run smoking behavior. We show the importance of smoking intensity as a long-run determinant of smoking cessation. We also investigate the sensitivity of smoking cessation to changes in excise taxes and their interaction with smoking intensity.
A search for microquasar candidates at low galactic latitudes

Recent studies of relativistic jet sources in the Galaxy, also known as microquasars, have been very useful in trying to understand the accretion/ejection processes that take place near compact objects. However, the number of sources involved in such studies is still small. In an attempt to increase the number of known microquasars we have carried out a search for new Radio Emitting X-ray Binaries (REXBs). These sources are the ones to be observed later with VLBI techniques to unveil their possible microquasar nature. To this end, we have performed a cross-identification between the X-ray ROSAT all sky survey Bright Source Catalog (RBSC) and the radio NRAO VLA Sky Survey (NVSS) catalogs under very restrictive selection criteria for sources with |b| < 5 ◦ . We have also conducted a deep observational radio and optical study for six of the selected candidates. At the end of this process two of the candidates appear to be promising, and deserve additional observations aimed to confirm their proposed microquasar nature.
Sixty-three Years of Land Alteration in Erie Township

ABSTRACT Land use and land cover (LULC) was mapped using historical aerial photos (1940) and contemporary QuickBird satellite imagery (2003) for a 100 km2 area covering portions of Erie Township, Michigan, and Toledo, Ohio on the western end of Lake Erie. This area serves as a microcosm of conditions elsewhere on the Great Lakes coast, containing a range of human-altered to natural landscapes. Geographic information system analysis was used to measure LULC change within the study area based on the 1940 and 2003 maps, and to illustrate the use of historical aerial photos and data to quantify changes in anthropogenic pressures to coastal ecosystems. Agriculture was and is the main land use in the study site, constituting 78% and 55% of upland area in 1940 and 2003, respectively. Most conversions to other land uses originated as agricultural lands. Transportation changes over the time period included the loss of two major railroad yards and the gain of an interstate highway. The area of commercial and industrial development increased 12-fold, from 20 ha in 1940 to 246 ha by 2003. Major industries built after 1940 included an electrical power plant and a sanitary landfill. Residential development approximately doubled from 353 ha in 1940 to 717 ha in 2003, consistent with an 80% increase in population. Coastal ecosystems within the study area included a coastal spit (Woodtick Peninsula) and a large, partially-diked wetland behind it (Erie Marsh), both of which changed extensively over the time period studied. This approach offers a means of incorporating long-term observations into the evaluation of environmental condition in coastal wetlands.
SSS-V2: Secure Similarity Search

Encrypting information has been regarded as one of the most substantial approaches to protect users’ sensitive information in radically changing internet technology era. In prior research, researchers have considered similarity search over encrypted documents infeasible, because the single-bit difference of a plaintext would result in an enormous bits difference in the corresponding ciphertext. However, we propose a novel idea of Security Similarity Search (SSS) over encrypted documents by applying character-wise encryption with approximate string matching to keyword index search systems. In order to do this, we define the security requirements of similarity search over encrypted data, propose two similarity search schemes, and formally prove the security of the schemes. The first scheme is more efficient, while the second scheme achieves perfect similarity search privacy. Surprisingly, the second scheme turns out to be faster than other keyword index search schemes with keywordwise encryption, while enjoying the same level of security. The schemes of SSS support “like query(‘ab%’)” and a query with misprints in that the character-wise encryption preserves the degree of similarity between two plaintexts, and renders approximate string matching between the corresponding ciphertexts possible without decryption.
Study of the Ground-State Geometry of Silicon Clusters Using Artificial Neural Networks

Theoretical determination of the ground-state geometry of Si clusters is a difficult task. As the number of local minima grows exponentially with the number of atoms, to find the global minimum is a real challenge. One may start the search procedure from a random distribution of atoms but it is probably wiser to make use of any available information to restrict the search space. Here, we introduce a new approach, the Assisted Genetic Optimization (AGO) that couples an Artificial Neural Network (ANN) to a Genetic Algorithm (GA). Using available information on small Silicon clusters, we trained an ANN to predict good starting points (initial population) for the GA. AGO is applied to Si10 and Si20 and compared to pure GA. Our results indicate: i) AGO is, at least, 5 times faster than pure GA in our test case; ii) ANN training can be made very fast and successfully plays the role of an experienced investigator; iii) AGO can easily be adapted to other optimization problems.
Atpg padding and ate vector repeat per port for reducing test data volume

paper presents an approach for reducing the test data volume that has to be stored in ATE vector memory for IC manufacturing testing. We exploit the capabilities of pre- sent ATE to assign groups of input pins to ports and to perform vector repeat per port. This allows run-length encoding of test stimuli per port. We improve the encoding byjlling the don't-care bits in the test stimuli, such that longer run-lengths are obtained. We provide a probabilis- tic analysis of the performance of vector repeat per port with various ATPG padding types. We further discuss the impact of ATE architectures. The paper provides experi- mental data for a set of large industrial circuits, which shows an average reduction of the test stimulus data vol- ume by a factor of 13.
Diagnosing Spatio-Temporal Internet Congestion Properties

The ability to accurately detect congestion events in the Internet and reveal their spatial (where they happen) and temporal (how long they last) properties would significantly improve our understanding of how the Internet operates. In this paper we presentPong, a novel measurement tool capable of effectively diagnosing congestion events over short time-scales (∼ 50 ms or longer), and simultaneously locating multiple congested points on an end-to-end path at the granularity of a single link. Pong (i) uses queuing delay as indicative of congestion, and (ii) strategically coordinates router-targeted probes with end-toend probes. Moreover, it (iii) has small measurement overhead, (iv) achieves high sampling frequency by sending probes to all intermediate nodes, including un-congested ones, ( v) dramatically improves spatial detection granularity (i.e., from path segments to individual links), by using short-term congestion history, (vi) considerably enhances the measurement quality by adjusting the probing methodology (e.g., send 4-, 3-, or 2-packet probes) based on the observed path topology, and ( vii) deterministically detects moments of its own inaccuracy. We conduct a large-scale measurement study on over 21,000 Internet paths and present their spatio-temporal properties as inferred by Pong.