Miracle-dz/UniFAR-FTUs huggingface dataset:
Digital Elves as a Racial Other in Video Games

Elves are a long-standing cultural trope in the West, where they have often represented the other and fears associated with otherness. Elves continue to do the same cultural work today and are a fixture of fantasy settings. Fantasy-based video games portray elves in a variety of ways across a few types of elves (high elves, half-elves, and dark elves), but there are consistencies to their portrayal across such spaces. Given the dearth of work on elves in modern narratives, the cultural work of elves as the other in video games is analyzed here. World of Warcraft (WoW), EverQuest II, The Elder Scrolls series, and the Dragon Age series were studied, with Tolkien and Dungeons & Dragons (D&D) as background. Although WoW is somewhat exceptional in its portrayal of elves, digital elves are mostly portrayed similarly to a historically idealized real-world Western minority.
Soluble Epoxide Hydrolase Inhibitors Reduce the Development of Atherosclerosis in Apolipoprotein E-Knockout Mouse Model

To determine whether sEH inhibitors influence atherosclerotic lesion formation, we used an established murine model of accelerated atherogenesis, ApoE knockout (-/-) mice. The sEH inhibitor, 1-adamantan-3-(5-(2-(2-ethylethoxy)ethoxy)pentyl)urea (AEPU) was delivered in drinking water. All animals were fed an atherogenic diet while simultaneously infused with angiotensin II by osmotic minipump to induce atherosclerosis. In AEPU-treated animals, there was a 53% reduction in atherosclerotic lesions in the descending aortae as compared to control aortae. AEPU and its major metabolites were detected in the plasma of animals which received it. As expected from the inhibition of sEH, a significant increase in linoleic and arachidonic acid epoxides, as well as an increase in individual 11,12-EET/DHET and 14,15-EET/DHET ratios, were observed. The reduction in atherosclerotic lesion area was inversely correlated with 11,12- and 14,15- EET/DHET ratios, suggesting that the reduction corresponds to the inhibition of sEH. Our data suggest that orally-available sEH inhibitors may be useful in the treatment of patients with atherosclerotic cardiovascular disease.
Study on Effects of Place Attachment on Cooperative Behavior Local Area

As for the impact of the place attachment, because it has studied mainly in other fields including environmental psychology or sociology, it has not yet well investigated factors concerned about planning of public works. With this recognition, we tried to examine the relationship between place attachment and some relative item with infrastructure planning, such as cooperative behavior in the community, based on the questionnaire survey. The result showed correlation between place attachment and positive attitude toward cooperative behavior in neighborhood and trust in the government.
Possible Errors in the Analysis of Lactic Acid and Volatile Fatty Acids in the Gastrointestinal Tracts of Pigs and Chickens

Recent articles by van Winsen et al. (2001) ([16][1]) and van der Wielen et al. (2000) ([14][2]) have described the measurements of lactate and volatile fatty acids (VFA) in the hind guts (ceca and colons) of pigs and broiler chickens, respectively, in an attempt to link these concentrations with
Circular road sign detection and recognition based on hough transform

In this paper, a new algorithm is proposed to detect and recognize common road signs. Firstly, color segmentation and connected domain analysis are used for region of interest (ROI) detection and then we used the improved two-time Hough transform to separately determinate the circle center and radium of the road sign. Then the Weighted Hausdorff Distance is applied in the recognition of extracted ROI. Compared to the conventional methods, the proposed algorithm has the advantage of small storage, lower time complexity and good robustness towards inclination and occlusion.
Scared Textless: The Influence of Sensation Seeking Tendencies and Need for Cognition on Texting while Driving Fear Appeals

Scared Textless: The Influence of Sensation Seeking Tendencies and Need For Cognition on Texting while Driving Fear Appeals. (August 2011) Madeline Lee Boenker, B.A., Texas A&M University Chair of Advisory Committee: Dr. Michael T. Stephenson Texting is ubiquitous; the International Association for the Wireless Telecommunications Industry reported that 4.1 billion text messages were sent per day in the first half of 2009. In isolation, texting does not injure individuals; however, when combined with driving, lives have changed for the worse. The National Safety Council estimates that 1.6 million crashes per year can be attributed to distracted drivers either talking on cell phones or texting while driving and nearly 28% of all crashes in the United States can be ascribed to these behaviors. An increasing number of texting while driving fear appeal campaigns are being utilized in the media. Therefore, the purpose of this research was to create and test theoretically-based messages aimed at discouraging texting while driving. Formative research along with the Extended Parallel Process Model was used for guidance in the creation of the fear appeal messages. No low threat message was used for the main study after repeated message validations failed. For the study, three high threat messages varied only by a single paragraph which targeted beliefs about benefits, mastery, and ubiquity of texting while driving. 155 undergraduates at Texas A&M
An efficient soft decision decoding algorithm using cyclic permutations and compact genetic algorithm

The compact genetic algorithm cGA is used in this paper to design an efficient soft-decision decoding algorithm, especially for the cyclic codes, because the cGA dramatically reduces the population's size and rapidly converges to the optimal solution compared to classical genetic algorithms. Our main contribution is to exploit the cyclic property of cyclic linear codes to reduce the complexity of the decoding process especially in the test sequences generation and re-encoding stage where we use the generator polynomial instead of the generator matrix. The second idea behind our decoding algorithm is the complexity improvement inside of cGA by decreasing the probability vector's length, which becomes less than the length of the cGA original one. The experiments were carried out on the most popular cyclic codes, and the results show that the performances of our algorithm are better than some famous decoding algorithms in terms of Bit Error Rate.
DC Electrical properties of XLPE insulation with nanostructured-coating

This paper deals with hybrid organic-inorganic coatings having the purpose to improve the electrical properties of host insulating materials. In particular, space charge behavior of coated XLPE specimens is investigated here as a function of temperature. Three different nanocoating designs are tested, showing promising results in terms of space charge reduction with respect to uncoated XLPE specimens. This improvement has been associated with the increase of the injection barrier at the electrode/insulation interface provided by the nanocoating layer which acts as a partially-blocking electrode.
Sensorless Position and Speed Control of Induction Motors Using High-Frequency Injection and Without Offline Precommissioning

This paper addresses the sensorless speed and position control of induction motors using high-frequency injection at zero and low frequencies. A novel algorithm is presented which allows the rejection of saturation and nonlinear inverter effects without the need for an offline precommissioning process. The method is based on a set of synchronous filters to identify the disturbance waveforms and a memory algorithm that refines the quality of the disturbance waveforms as the motor's operational history is increased. The algorithm is entirely sensorless. Experimental results show sensorless low-frequency operation with and without the memory algorithm.
Stream-Related Preferences of Inputs to the Superior Colliculus from Areas of Dorsal and Ventral Streams of Mouse Visual Cortex

Previous studies of intracortical connections in mouse visual cortex have revealed two subnetworks that resemble the dorsal and ventral streams in primates. Although calcium imaging studies have shown that many areas of the ventral stream have high spatial acuity whereas areas of the dorsal stream are highly sensitive for transient visual stimuli, there are some functional inconsistencies that challenge a simple grouping into “what/perception” and “where/action” streams known in primates. The superior colliculus (SC) is a major center for processing of multimodal sensory information and the motor control of orienting the eyes, head, and body. Visual processing is performed in superficial layers, whereas premotor activity is generated in deep layers of the SC. Because the SC is known to receive input from visual cortex, we asked whether the projections from 10 visual areas of the dorsal and ventral streams terminate in differential depth profiles within the SC. We found that inputs from primary visual cortex are by far the strongest. Projections from the ventral stream were substantially weaker, whereas the sparsest input originated from areas of the dorsal stream. Importantly, we found that ventral stream inputs terminated in superficial layers, whereas dorsal stream inputs tended to be patchy and either projected equally to superficial and deep layers or strongly preferred deep layers. The results suggest that the anatomically defined ventral and dorsal streams contain areas that belong to distinct functional systems, specialized for the processing of visual information and visually guided action, respectively.
Machine learning for predictive auto-tuning with boosted regression trees

The rapidly evolving landscape of multicore architectures makes the construction of efficient libraries a daunting task. A family of methods known collectively as “auto-tuning” has emerged to address this challenge. Two major approaches to auto-tuning are empirical and model-based: empirical autotuning is a generic but slow approach that works by measuring runtimes of candidate implementations, model-based auto-tuning predicts those runtimes using simplified abstractions designed by hand. We show that machine learning methods for non-linear regression can be used to estimate timing models from data, capturing the best of both approaches. A statistically-derived model offers the speed of a model-based approach, with the generality and simplicity of empirical auto-tuning. We validate our approach using the filterbank correlation kernel described in Pinto and Cox [2012], where we find that 0.1 seconds of hill climbing on the regression model (“predictive auto-tuning”) can achieve almost the same speed-up as is brought by minutes of empirical auto-tuning. Our approach is not specific to filterbank correlation, nor even to GPU kernel auto-tuning, and can be applied to almost any templated-code optimization problem, spanning a wide variety of problem types, kernel types, and platforms.
The Qual-Quant Distinction (Debate): Understanding the Phenomena

Because the qualitative and quantitative data can be analyzed by both qualitative and quantitative methods, some scholars argue that the combination of theme can be more effective but others argues that the distinction between qualitative and quantitative data have certain utility, though most people draw to hard a distinction. Although, the quantitative-qualitative distinction can lead to some sorts of confusions due to their distinct ontological and measurement related issues; the qual-quant distinction debate is philosophical, not methodological. Hence this paper discusses about the philosophical and practical issues on qual-quant distinction and the interpretation of qualitative and quantitative data in the form of each other.
Multimodal intent recognition for natural human-robotic interaction

The research questions posed for this work were as follows: Can speech recognition and techniques for topic spotting be used to identify spoken intent in unconstrained natural speech? Can gesture recognition systems based on statistical speech recognition techniques be used to bridge the gap between physical movements and recognition of gestural intent? How can speech and gesture be combined to identify the overall communicative intent of a participant with better accuracy than recognisers built for individual modalities? In order to answer these questions a corpus collection experiment for Human-Robotic Interaction was designed to record unconstrained natural speech and 3 dimensional motion data from 17 different participants. A speech recognition system was built based on the popular Hidden Markov Model Toolkit and a topic spotting algorithm based on usefulness measures was designed. These were combined to create a speech intent recognition system capable of identifying intent given natural unconstrained speech. A gesture intent recogniser was built using the Hidden Markov Model Toolkit to identify intent directly from 3D motion data. Both the speech and gesture intent recognition systems were evaluated separately. The output from both systems were then combined and this integrated intent recogniser was shown to perform better than each recogniser separately. Both linear and non-linear methods of multimodal intent fusion were evaluated and the same techniques were applied to the output from individual intent recognisers. In all cases the non-linear combination of intent gave the highest performance for all intent recognition systems. Combination of speech and gestural intent scores gave a maximum classification performance of 76.7% of intents correctly classified using a two layer Multi-Layer Perceptron for non-linear fusion with human transcribed speech input to the speech classifier. When compared to simply picking the highest scoring single modality intent, this represents an improvement of 177.9% over gestural intent classification, 67.5% over a human transcription of speech based speech intent classifier and 204.4% over an automatically recognised speech based speech intent classifier.
Health visiting in rural Gambia.

A British nurse was the 1st health visitor in the village of Keneba in the Gambia. She was at a nutritional research center which provided basic medical services. In addition to visiting mothers in their homes to talk about health education, such as oral rehydration and advice on hand washing, she would also encourage them to bring their children to the infant welfare clinic for immunizations. She told the mothers that the health staff would check the growth and nutritional status of their children and why these activities were important. Staff at the clinic aimed to see all the children 2 years 9 times the 1st year and 4 times the 2nd year. All anthropometric data were forwarded to Cambridge, England to be included in a continuing study on the growth of the population. The clinic referred children with serious illnesses to the pediatrician or, if necessary, took them to a hospital on the coast. Children that came to the clinic with a fever 37.4 degrees Celsius during the wet season had a blood film taken to check for malaria parasites. Indeed cerebral malaria contributed greatly to child deaths in the Gambia. If malaria was present, children received their 1st dose of chloroquine immediately so the staff could determine tolerance. 3 doses followed this dose. The health visitor also organized the health education component of the clinic. The clinic dresser interpreted the British nurse's presentations to eventually conduct them alone. The nurse divided the mothers and fathers into 2 groups. In the future, she would evaluate the 2 groups to determine if weekly education on hand washing and skin hygiene would reduce diarrheal and cutaneous disease incidence in children 3 years old. The other group learned about family planning. Both groups learned about immunization, detection of illness, safety, sanitation, nutritional advice, dental care, and food preparation.
An Analysis Framework Based on Random Subspace Sampling for Speaker Verification

Using Joint Factor Analysis (JFA) supervector for subspace analysis has many problems, such as high processing complexity and over-fitting. We propose an analysis framework based on random subspace sampling to address these problems. In this framework, JFA supervectors are first partitioned equally and each partitioned subvector is projected on to a subspace by PCA. All projected subvectors are then concatenated and PCA is applied again to reduce the dimension by projection onto a low-dimensional feature space. Finally, we randomly sample this feature space and build classifiers for the sampled features. The classifiers are fused to produce the final classification output. Experiments on NIST SRE08 prove the effectiveness of the proposed framework.
Primary mediastinal large B-cell lymphoma: a single-center experience in Korea

Background Primary mediastinal large B-cell lymphoma (PMBL) is a distinct subtype of non-Hodgkin lymphoma, which has no consensus for its ideal treatment or prognosis. Methods We reviewed the clinicopathologic features and clinical outcomes of 25 PMBL cases diagnosed at a single institution between 1993 and 2009 and compared them with 588 cases of non-mediastinal, diffuse large B-cell lymphoma (DLBCL, control group) diagnosed during the same period. Results Thirteen (52.0%) PMBL patients had Ann Arbor stage III or IV disease, and 10 (40.0%) had B symptoms. Thirteen (52%) PMBL patients were classified as high-intermediate/high-risk according to the International Prognostic Index. There was a significant prevalence of young (median: 31 years; range, 15-78 years; P<0.001), female (68%; P=0.014) patients in the PMBL group compared to the control group (median: 56 years; range, 15-85 years; 43.2% female). Bulky disease and elevated levels of lactate dehydrogenase (LDH) were more frequent in the PMBL group (P<0.001 and P=0.003, respectively). Nineteen (76%) PBML patients achieved complete remission, and 18 were alive at the last follow-up (median: 43 months; range, 1-92 months). There was no difference in the 3-year, overall survival rate (72%, 95% confidence interval [CI]: 54.0-83.0 versus 70.1%, 95% CI, 109.0-126.0; P=0.686) between PMBL and control patients, respectively. Conclusion Compared to patients with non-mediastinal DLBCL, Korean patients with PMBL are predominantly young women with bulky disease and high LDH levels but with no significant difference in survival.
Kinect Depth Sensor Evaluation for Computer Vision Applications

This technical report describes our evaluation of the Kinect depth sensor by Microsoft for Computer Vision applications. The depth sensor is able to return images like an ordinary camera, but instead of color, each pixel value represents the distance to the point. As such, the sensor can be seen as a range- or 3D-camera. We have used the sensor in several different computer vision projects and this document collects our experiences with the sensor. We are only focusing on the depth sensing capabilities of the sensor since this is the real novelty of the product in relation to computer vision. The basic technique of the depth sensor is to emit an infrared light pattern (with an IR laser diode) and calculate depth from the reflection of the light at different positions (using a traditional IR sensitive camera). In this report, we perform an extensive evaluation of the depth sensor and investigate issues such as 3D resolution and precision, structural noise, multi-cam setups and transient response of the sensor. The purpose is to give the reader a well-founded background to choose whether or not the Kinect sensor is applicable to a specific problem.
Image based information access for mobile phones

Mobile phones with integrated digital cameras provide new ways to get access to digital information and services. Images taken by the mobile phone camera can be matched to a database of objects or scenes, which enables linking of digital information to the physical world. In this demonstration, we present a prototype system for image based linking of photos taken from pages of magazine. The system is intended not just for the high-end smartphones but for the current mainstream of camera-equipped mobile phones. The proposed system consists of a full architecture for a practical application developed in close collaboration with a magazine publisher.
Three‐dimensional average‐shape atlas of the honeybee brain and its applications

The anatomical substrates of neural nets are usually composed from reconstructions of neurons that were stained in different preparations. Realistic models of the structural relationships between neurons require a common framework. Here we present 3‐D reconstructions of single projection neurons (PN) connecting the antennal lobe (AL) with the mushroom body (MB) and lateral horn, groups of intrinsic mushroom body neurons (type 5 Kenyon cells), and a single mushroom body extrinsic neuron (PE1), aiming to compose components of the olfactory pathway in the honeybee. To do so, we constructed a digital standard atlas of the bee brain. The standard atlas was created as an average‐shape atlas of 22 neuropils, calculated from 20 individual immunostained whole‐mount bee brains. After correction for global size and positioning differences by repeatedly applying an intensity‐based nonrigid registration algorithm, a sequence of average label images was created. The results were qualitatively evaluated by generating average gray‐value images corresponding to the average label images and judging the level of detail within the labeled regions. We found that the first affine registration step in the sequence results in a blurred image because of considerable local shape differences. However, already the first nonrigid iteration in the sequence corrected for most of the shape differences among individuals, resulting in images rich in internal detail. A second iteration improved on that somewhat and was selected as the standard. Registering neurons from different preparations into the standard atlas reveals 1) that the m‐ACT neuron occupies the entire glomerulus (cortex and core) and overlaps with a local interneuron in the cortical layer; 2) that, in the MB calyces and the lateral horn of the protocerebral lobe, the axon terminals of two identified m‐ACT neurons arborize in separate but close areas of the neuropil; and 3) that MB‐intrinsic clawed Kenyon cells (type 5), with somata outside the calycal cups, project to the peduncle and lobe output system of the MB and contact (proximate) the dendritic tree of the PE1 neuron at the base of the vertical lobe. Thus the standard atlas and the procedures applied for registration serve the function of creating realistic neuroanatomical models of parts of a neural net. The Honeybee Standard Brain is accessible at www.neurobiologie. fu‐berlin.de/beebrain. J. Comp. Neurol. 492:1–19, 2005. © 2005 Wiley‐Liss, Inc.