Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of flying, scaling and grabbing in virtual worlds

In a virtual world viewed with a head-mounted display, the user may wish to perform certain actions under the control of a manual input device. The most important of these actions are flying through the world, scaling the world, and grabbing objects. This paper shows how these actions can be precisely specified with Frame-to-frame invariants, and how the code to implement the actions can bc dcrivcd from the invariants by algebraic manipulation. INTRODUCTION Wearing a Head-Mounted Display (HMD) gives a human user the scnsalion of being inside a three-dimensional. computersimulated world. Because the HMD rcplaccs the sights and sounds of the real world with a computer-gencratcd virtual world, this synthesizccl world is called virtual reality. The virtual world surrounding the user is dcfincd by a graphics database called a model, which gives the colors and coordinates for each of the polygons making up the virtual world. The polygons making up the virtual world arc normally grouped into cntitics called obj,jccfs, each of which has its own location and orientation. The human being wearing the HMD is called the user, and also has a location and orientation within the virtual world. To turn the data in the model into the illusion of a surrounding virtual world, the HMD system requires certain hardware components. The tracker measures the position and orientation of the user’s head and hand. The graphics engine gcncratcs the images seen by the user, which arc then displayed on the HMD. The manual input device allows the user to use gcslurcs of the hand to cause things to happen in the virtual world. BASIC ACTIONS An aclinn changes ~hc state of the virtual world or the user’s viewpoint wiLhin it under control of a gcsturc of the hand, as mcasurcd by the manual input d&cc. The hand gesture initiates and tcrminatcs the action, and the changing position Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. Q 1992 ACM 0-89791-471-6/92/000310189. $1.50 and orientation of the hand during the gesture is also used to control what happens as the action progresses. The manual input device may be a hand-held manipulandum with pushbuttons on it, or it may be an instrumented glove. In either case, the position and orientation of the input device must be measured by the tracker to enable manual control of actions. The input device must also allow the user to signal to the system to start and stop actions, and to select among alternative actions. Certain fundamental manually-controlled actions may be implemented for any virtual world. These actions involve changing the location, orientation or scale of either an object or a user, as shown in Table 1.
Spatial distribution and molecular dynamics of dystrophin glycoprotein components at the neuromuscular junction in vivo

ABSTRACT A bimolecular fluorescence complementation (BiFC) approach was used to study the molecular interactions between different components of the postsynaptic protein complex at the neuromuscular junction of living mice. We show that rapsyn forms complex with both α-dystrobrevin and α-syntrophin at the crests of junctional folds. The linkage of rapsyn to α-syntrophin and/or α-dystrobrevin is mediated by utrophin, a protein localized at acetylcholine receptor (AChR)-rich domains. In mice deficient in α-syntrophin, in which utrophin is no longer present at the synapse, rapsyn interaction with α-dystrobrevin was completely abolished. This interaction was completely restored when either utrophin or α-syntrophin was introduced into muscles deficient in α-syntrophin. However, in neuromuscular junctions deficient in α-dystrobrevin, in which utrophin is retained, complex formation between rapsyn and α-syntrophin was unaffected. Using fluorescence recovery after photobleaching, we found that α-syntrophin turnover is 5-7 times faster than that of AChRs, and loss of α-dystrobrevin has no effect on rapsyn and α-syntrophin half-life, whereas the half-life of AChR was significantly altered. Altogether, these results provide new insights into the spatial distribution of dystrophin glycoprotein components and their dynamics in living mice. Summary: Utrophin is a key component bridging rapsyn and AChRs to α-dystrobrevin and α-syntrophin in the AChR-rich domain, and we show that α-syntrophin and rapsyn turn over more rapidly than AChRs at the NMJ.
Field Effectiveness of Ultraviolet Disinfection in Onsite Wastewater Treatment

Field Effectiveness of Ultraviolet Disinfection in Onsite Wastewater Treatment Meagan Jackson Chair of the Supervisory Committee: Tania Busch Isaksen Department of Environmental and Occupational Health Sciences Ultraviolet disinfection (UVD) units provide advanced onsite wastewater treatment, which is essential in regions where soils are unsuitable for conventional onsite sewage systems (OSSs). Although UVD treatment systems provide high-quality effluent under testing conditions, field effectiveness of UVD units is poorly understood. This study aimed to determine the field performance of UVD units installed in Western Washington, their ability to provide high-quality wastewater effluent, and risk factors for UVD unit malfunction. The hypothesis, based on a previous report from Kitsap County, was that 25-50% of UVD units would have malfunctioning UV bulbs and that malfunctioning units would have higher fecal coliform effluent levels than those performing optimally. This study used a mixed-methods approach with original data collection and complimentary analysis of retrospective quarterly compliance samples. 97 UVD units were inspected for indicators of unit performance, and wastewater samples from 53 units were collected and analyzed for physical wastewater quality, fecal coliform concentrations, and, in 21 units, presence of male-specific (F+) coliphage. Data from inspection and sampling reports provided additional insights into provided maintenance and retrospective UVD unit performance.
Learning multiple solution branches for the direct kinematics of parallel manipulators

It is well known that, the direct kinematics of parallel manipulators requires solving highly non-linear equations and it has non-unique multiple sets of solutions referred to the assembly modes. This complexity inhibits the real-time applications of such manipulators, so the Kohonen's self-organizing map (SOM) is proposed in this paper to classify and learn the multiple solution branches of the direct kinematics and then provide a unique real-time solution in among the assembly modes based on a certain class code. Due to not only the classifïcation but also the associative memory learning abilities of the SOM, a passive joint angle variables vector, the output end-effector pose vector and a class code are associated with the active joint angle variables vector as an input vector to the SOM in the off-line learning phase. In the on-line testing phase, only the active joint angle variables vector and the class code, as a subspace of the input vector, are fed to the SOM to obtain the end-effector pose vector. In order to further fine timing the SOM output, the Jacobian matrix calculated at the output layer is used to obtain an accurate end-effector pose vector. Simulations are conducted for 3-RRR planar parallel manipulator to evaluate the performance of the proposed method. The results proved high accuracy of the desired unique solution in real-time.
A Joint Sequence Translation Model with Integrated Reordering

We present a novel machine translation model which models translation by a linear sequence of operations. In contrast to the "N-gram" model, this sequence includes not only translation but also reordering operations. Key ideas of our model are (i) a new reordering approach which better restricts the position to which a word or phrase can be moved, and is able to handle short and long distance re-orderings in a unified way, and (ii) a joint sequence model for the translation and reordering probabilities which is more flexible than standard phrase-based MT. We observe statistically significant improvements in BLEU over Moses for German-to-English and Spanish-to-English tasks, and comparable results for a French-to-English task.
User profiling for computer security

Systems and control theory was largely responsible for realizing the industrial revolution. We believe that systems and control theory also plays a key role in the information revolution underway. In particular, systems and control theory should have much to offer network security. This paper explores the use of queueing theory and logistic regression modeling methods for profiling computer users based on simple temporal aspects of their behavior. The goal is to develop profiles for very specialized groups of users, because of the nature of their work would be expected to use their computers in a very similar and regular way, e.g., bank tellers, insurance adjusters, etc. Encouraging proof-of-concept results suggest the potential of both the idea of user profiling and the use of simple temporal features for grouping users.
Towards Emotion Detection in Educational Scenarios from Facial Expressions and Body Movements through Multimodal Approaches

We report current findings when considering video recordings of facial expressions and body movements to provide affective personalized support in an educational context from an enriched multimodal emotion detection approach. In particular, we describe an annotation methodology to tag facial expression and body movements that conform to changes in the affective states of learners while dealing with cognitive tasks in a learning process. The ultimate goal is to combine these annotations with additional affective information collected during experimental learning sessions from different sources such as qualitative, self-reported, physiological, and behavioral information. These data altogether are to train data mining algorithms that serve to automatically identify changes in the learners' affective states when dealing with cognitive tasks which help to provide emotional personalized support.
Human centromeric alphoid domains are periodically homogenized so that they vary substantially between homologues. Mechanism and implications for centromere functioning

Sequence analysis of alphoid repeats from human chromosomes 17, 21 and 13 reveals recurrent diagnostic variant nucleotides. Their combinations define haplotypes, with higher order repeats (HORs) containing identical or closely-related haplotypes tandemly arranged into separate domains. The haplotypes found on homologues can be totally different, while HORs remain 99.8% homogeneous both intrachromosomally and between homologues. These results support the hypothesis, never before demonstrated, that unequal crossovers between sister chromatids accumulate to produce homogenization and amplification into tandem alphoid repeats. I propose that the molecular basis of this involves the diagnostic variant nucleotides, which enable pairing between HORs with identical or closely-related haplotypes. Domains are thus periodically renewed to maintain high intrachromosomal and interhomologue homogeneity. The capacity of a domain to form an active centromere is maintained as long as neither retrotransposons nor significant numbers of mutations affect it. In the presented model, a chromosome with an altered centromere can be transiently rescued by forming a neocentromere, until a restored, fully-competent domain is amplified de novo or rehomogenized through the accumulation of unequal crossovers.
Stateful bulk processing for incremental analytics

This work addresses the need for stateful dataflow programs that can rapidly sift through huge, evolving data sets. These data-intensive applications perform complex multi-step computations over successive generations of data inflows, such as weekly web crawls, daily image/video uploads, log files, and growing social networks. While programmers may simply re-run the entire dataflow when new data arrives, this is grossly inefficient, increasing result latency and squandering hardware resources and energy. Alternatively, programmers may use prior results to incrementally incorporate the changes. However, current large-scale data processing tools, such as Map-Reduce or Dryad, limit how programmers incorporate and use state in data-parallel programs. Straightforward approaches to incorporating state can result in custom, fragile code and disappointing performance. This work presents a generalized architecture for continuous bulk processing (CBP) that raises the level of abstraction for building incremental applications. At its core is a flexible, groupwise processing operator that takes state as an explicit input. Unifying stateful programming with a data-parallel operator affords several fundamental opportunities for minimizing the movement of data in the underlying processing system. As case studies, we show how one can use a small set of flexible dataflow primitives to perform web analytics and mine large-scale, evolving graphs in an incremental fashion. Experiments with our prototype using real-world data indicate significant data movement and running time reductions relative to current practice. For example, incrementally computing PageRank using CBP can reduce data movement by 46% and cut running time in half.
Conditional VHL Gene Deletion Causes Hypoglycemic Death Associated with Disproportionately Increased Glucose Uptake by Hepatocytes through an Upregulated IGF-I Receptor

Our conditional VHL knockout (VHL-KO) mice, having VHL gene deletion induced by tamoxifen, developed severe hypoglycemia associated with disproportionately increased storage of PAS-positive substances in the liver and resulted in the death of these mice. This hypoglycemic state was neither due to impaired insulin secretion nor insulin receptor hypersensitivity. By focusing on insulin-like growth factor I (IGF-I), which has a similar effect on glucose metabolism as the insulin receptor, we demonstrated that IGF-I receptor (IGF-IR) protein expression in the liver was upregulated in VHL-KO mice compared to that in the mice without VHL deletion, as was the expression of glucose transporter (GLUT) 1. The interaction of the receptor for activated C kinase (RACK) 1, which predominantly binds to VHL, was enhanced in VHL-KO livers with IGF-IR, because VHL deletion increased free RACK1 and facilitated the IGF-IR-RACKI interaction. An IGF-IR antagonist retarded hypoglycemic progression and sustained an euglycemic state. These IGF-IR antagonist effects on restoring blood glucose levels also attenuated PAS-positive substance storage in the liver. Because the effect of IGF-I on HIF-1α protein synthesis is mediated by IGF-IR, our results indicated that VHL inactivation accelerated hepatic glucose storage through the upregulation of IGF-IR and GLUT1 and that IGF-IR was a key regulator in VHL-deficient hepatocytes.
How NLP techniques can improve speech understanding: ROMUS - a robust chunk based message understanding system using link grammars

This paper discusses the issue of how a speech understanding system can be made robust against spontaneous speech phenomena (hesitations and repairs) as well as achieving a detailed analysis of spoken French. The Romus system is presented. It implements speech understanding in a two-stage process. The first stage achieves a finite-state shallow parsing that consists in segmenting the recognized sentence into basic units (spokenadapted chunks). The second one, a Link Grammar parser, looks for inter-chunks dependencies in order to build a rich representation of the semantic structure of the utterance. These dependencies are mainly investigated at a pragmatic level through the consideration of a task concept hierarchy. Discussion about the approach adopted, its benefits and limitations, is based on the results of the system’s assessment carried out under different linguistic phenomena during an evaluation campaign held by the French CNRS.
An efficient multiple object detection and tracking framework for automatic counting and video surveillance applications

Automatic visual object counting and video surveillance have important applications for home and business environments, such as security and management of access points. However, in order to obtain a satisfactory performance these technologies need professional and expensive hardware, complex installations and setups, and the supervision of qualified workers. In this paper, an efficient visual detection and tracking framework is proposed for the tasks of object counting and surveillance, which meets the requirements of the consumer electronics: off-the-shelf equipment, easy installation and configuration, and unsupervised working conditions. This is accomplished by a novel Bayesian tracking model that can manage multimodal distributions without explicitly computing the association between tracked objects and detections. In addition, it is robust to erroneous, distorted and missing detections. The proposed algorithm is compared with a recent work, also focused on consumer electronics, proving its superior performance.
Sensitivity of deformation to activity along the Mill Creek and Mission Creek strands of the southern San Andreas fault

Assessment of seismic hazards in southern California may be improved with more accurate characterization of the active San Andreas fault strands within the San Gorgonio Pass region. Ongoing debate centers on the activity and geometry of the Mill Creek and Mission Creek strands. Here, we investigate crustal deformation models with six geologically plausible geometries of the Mill Creek and Mission Creek strands. Model results suggest that differences in active fault geometry along the San Andreas fault impact slip rates along the San Jacinto fault by up to 3 mm/yr. Each model fits many but none fits all of the available geologic strike-slip rates. The calculated misfits to the geologic strike-slip rates reveal two best-fitting models: the Inactive Mill Creek model and the West Mill Creek model, which incorporate active portions of the Mill Creek, Mission Creek, and Galena Peak strands, consistent with recent studies. The cumulative strike-slip rates across faults of the two best-fitting models differ from each other by ~5 mm/yr, suggesting that fault slip rates do not always sum to the plate rate. Consequently, kinematic slip budgets should consider off-fault deformation. The two best-fitting models produce uplift patterns with significant differences in the hanging walls of dipping faults. New uplift rate data in these regions and additional geologic slip rates along the northern fault strands could further support plausible interpretations of active fault configuration. An assessment of the seismic hazard of the region indicates the potential for a rupture through the San Gorgonio Pass region with Mw ~7.8. Mill The between different geologic interpreta­ three­dimensional boundary­element method that simulate deformation many earthquake cycles to six geologically plausible fault configurations the SGPr to under­ stand the impact of differing fault geometries on slip distributions in the region We compare slip rates from the models to geologic slip­rate data in order to distinguish between the alternative active fault configurations. The results highlight regions where additional uplift and slip­rate constraints could be used to delineate between plausible fault geometries of the San Andreas fault through the SGPr.
Development of handy prototype gas sensors kit for monitoring of ambient green house gases from solid waste disposal sites of Solapur city

Today, gas sensor having ample of applications in various filed such as food, agriculture, domestic, business, industries, traffic control and environment monitoring. The principle of this project is to design and develop handy gas sensor based mobile kit for monitoring of ambient gases. In the present study, MQ 4 and MQ 135 sensors were used for detection of Methane (CH4) and Carbon dioxide (CO2) from the solid waste disposal sites. To make the sensors operate in the alarm system and data monitoring system, Arduino Uno was used as the microcontroller for the whole system. The data received from the sensors were converted into voltage to parts per million concentrations through mathematical conversions method. Random sample method was used for study areas and same locations were represented in the GIS map using GIS software’s and determined the areas / sites having high, medium and low concentration of ambient greenhouse gases.
Theoretical Verification Necessity of Leakage Currents Using Sm Doped Ceria Electrolytes in SOFCs~!2009-01-29~!2009-03-03~!2009-03-19~!

Numerous approaches have been made to solve the basic transport equation that describes a solid oxide fuel cell (SOFC) with mixed conduction. Classically, the open circuit voltage (OCV) is calculated with Wagner's equation, which is right within the limits of linear transport theory. In order to generalize Wagner's equation, many models have been proposed to describe the current-voltage relation in mixed ionic electronic solid conductors (MIEC) using constant field approximation to calculate an electronic current. However, experimental verification necessity of leakage currents in SOFCs using Sm doped Ceria electrolytes has already been pointed out both qualitatively and in quantities. Using the constant field approximation, the limits of linear transport theory can not be clear. In this report, a new model is expressed without using the constant field approximation. This model follows from Wagner's equation and continuity. The calculated electronic current for doped Ceria electrolyte matches the values calculated using conventional models. But the electrical field near the cathode is large enough to cause dielectric breakdown which has never been reported. Continuity is not deniable, so there are limitations in Wagner's equation, coming from the limits of linear transport theory.
A robust method for inverse transport modeling of atmospheric emissions using blind outlier detection

Emissions of harmful substances into the atmo- sphere are a serious environmental concern. In order to un- derstand and predict their effects, it is necessary to estimate the exact quantity and timing of the emissions from sen- sor measurements taken at different locations. There are a number of methods for solving this problem. However, these existing methods assume Gaussian additive errors, making them extremely sensitive to outlier measurements. We first show that the errors in real-world measurement data sets come from a heavy-tailed distribution, i.e., include outliers. Hence, we propose robustifying the existing inverse meth- ods by adding a blind outlier-detection algorithm. The im- proved performance of our method is demonstrated on a real data set and compared to previously proposed methods. For the blind outlier detection, we first use an existing al- gorithm, RANSAC, and then propose a modification called TRANSAC, which provides a further performance improve- ment.