Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis and modeling of "focus" in context

This paper uses a crowd-sourced definition of a speech phenomenon we have called “focus”. Given sentences, text and speech, in isolation and in context, we asked annotators to identify what we term the “focus” word. We present their consistency in identifying the focused word, when presented with text or speech stimuli. We then build models to show how well we predict that focus word from lexical (and higher) level features. Also, using spectral and prosodic information, we show the differences in these focus words when spoken with and without context. Finally, we show how we can improve speech synthesis of these utterances given focus information. Index Terms: Focus, Context, Speech Synthesis, Prominence, Emphasis, Prosody
PsychSim: Agent-based Modeling of Social Interactions and Influence

Agent-based modeling of human social behavior is an increasingly important research area. For example, it is critical to designing virtual humans, human-like autonomous agents that interact with people in virtual worlds. A key factor in human social interaction is our beliefs about others, in particular a theory of mind. Whether we believe a message depends not only on its content but also on our model of the communicator. The actions we take are influenced by how we believe others will react. However, theory of mind is usually ignored in computational models of social interaction. In this paper, we present PsychSim, an implemented multiagent-based simulation tool for modeling interactions and influence among groups or individuals. Each agent has its own decision-theoretic model of the world, including beliefs about its environment and recursive models of other agents. Having thus given the agents a theory of mind, PsychSim also provides them with a psychologically motivated mechanism for updating their beliefs in response to actions and messages of other agents. We discuss PsychSim and present an example of its operation.
Generalizing Word Lattice Translation

Word lattice decoding has proven useful in spoken language translation; we argue that it provides a compelling model for translation of text genres, as well. We show that prior work in translating lattices using finite state techniques can be naturally extended to more expressive synchronous context-free grammarbased models. Additionally, we resolve a significant complication that non-linear word lattice inputs introduce in reordering models. Our experiments evaluating the approach demonstrate substantial gains for ChineseEnglish and Arabic-English translation.
Use of Protek-PSB as structural material for MEMS: Measurement of elastic modulus

Protek-PSB is a polymer spin-on coating designed to replace silicon oxide and silicon nitride as hard mask in bulk wet anisotropic etch of silicon. The possibility of application of this material as structural material joins the benefits of low cost fabrication using wet etch with the polymer low cost and mechanical properties. To better evaluate the applicability of this material, we measured the elastic modulus of Protek-PSB coatings using the beam bending method with cantilevered beams of Protek-PSB. We found that the elastic modulus of this material is estimated in 3,10 ± 0,47 GPa, compatible with other polymeric coatings like SU-8.
Sketching stencils

Performance of stencil computations can be significantly improved through smart implementations that improve memory locality, computation reuse, or parallelize the computation. Unfortunately, efficient implementations are hard to obtain because they often involve non-traditional transformations, which means that they cannot be produced by optimizing the reference stencil with a compiler. In fact, many stencils are produced by code generators that were tediously handcrafted. In this paper, we show how stencil implementations can be produced with sketching. Sketching is a software synthesis approach where the programmer develops a partial implementation--a sketch--and a separate specification of the desired functionality given by a reference (unoptimized) stencil. The synthesizer then completes the sketch to behave like the specification, filling in code fragments that are difficult to develop manually. Existing sketching systems work only for small finite programs, i.e.,, programs that can be represented as small Boolean circuits. In this paper, we develop a sketching synthesizer that works for stencil computations, a large class of programs that, unlike circuits, have unbounded inputs and outputs, as well as an unbounded number of computations. The key contribution is a reduction algorithm that turns a stencil into a circuit, allowing us to synthesize stencils using an existing sketching synthesizer.
Optimal Signal Processing in Small Stochastic Biochemical Networks

We quantify the influence of the topology of a transcriptional regulatory network on its ability to process environmental signals. By posing the problem in terms of information theory, we do this without specifying the function performed by the network. Specifically, we study the maximum mutual information between the input (chemical) signal and the output (genetic) response attainable by the network in the context of an analytic model of particle number fluctuations. We perform this analysis for all biochemical circuits, including various feedback loops, that can be built out of 3 chemical species, each under the control of one regulator. We find that a generic network, constrained to low molecule numbers and reasonable response times, can transduce more information than a simple binary switch and, in fact, manages to achieve close to the optimal information transmission fidelity. These high-information solutions are robust to tenfold changes in most of the networks' biochemical parameters; moreover they are easier to achieve in networks containing cycles with an odd number of negative regulators (overall negative feedback) due to their decreased molecular noise (a result which we derive analytically). Finally, we demonstrate that a single circuit can support multiple high-information solutions. These findings suggest a potential resolution of the “cross-talk” phenomenon as well as the previously unexplained observation that transcription factors that undergo proteolysis are more likely to be auto-repressive.
Efficient Synthesis of Peptide and Protein Functionalized Pyrrole-Imidazole Polyamides Using Native Chemical Ligation

The advancement of DNA-based bionanotechnology requires efficient strategies to functionalize DNA nanostructures in a specific manner with other biomolecules, most importantly peptides and proteins. Common DNA-functionalization methods rely on laborious and covalent conjugation between DNA and proteins or peptides. Pyrrole-imidazole (Py–Im) polyamides, based on natural minor groove DNA-binding small molecules, can bind to DNA in a sequence specific fashion. In this study, we explore the use of Py–Im polyamides for addressing proteins and peptides to DNA in a sequence specific and non-covalent manner. A generic synthetic approach based on native chemical ligation was established that allows efficient conjugation of both peptides and recombinant proteins to Py–Im polyamides. The effect of Py–Im polyamide conjugation on DNA binding was investigated by Surface Plasmon Resonance (SPR). Although the synthesis of different protein-Py–Im-polyamide conjugates was successful, attenuation of DNA affinity was observed, in particular for the protein-Py–Im-polyamide conjugates. The practical use of protein-Py–Im-polyamide conjugates for addressing DNA structures in an orthogonal but non-covalent manner, therefore, remains to be established.
Evaluation of localization and activity recognition systems for ambient assisted living: The experience of the 2012 EvAAL competition

EvAAL is an annual international competition that addresses the “grand” challenge of evaluation and comparison of Ambient Assisted Living AAL systems and platforms, with the final goal to assess the autonomy, independent living and quality of life that AAL systems may grant to their end users. The 2012 Edition was focused on two pillars of AAL: Indoor localization and activity recognition. Results from both competitions suggest that there is still space for other editions not only to improve accuracy of such systems, but also their user acceptance and interoperability. This paper describes the organization and results of the 2012 edition.
Run-time Soft Error Injection and Testing of a Microprocessor using FPGAs

Nowadays, soft errors in logic circuits are becoming increasingly important. This is especially true in the ever shrinking nanometer technologies, and aerospace applications where soft errors are more prevalent. Previous soft error injection simulation methods using FPGAs have usually been limited to small test circuits such as ISCAS89, or parts of a larger circuit. Other software approaches have been proposed that simulate soft errors by adding extra instructions that the processor must execute. In this paper, we introduce our FPGA based transient fault injection system that can handle all memory elements of an entire microprocessor (MIPS32) while connected and running within a complete system. This allows us to perform fault injection and analysis when the system is live and actually running arbitrary applications on the processor. We test our implementation, and the effects that soft errors have on a software filter used in aviation for probabilistic sensor data fusion, as this algorithm would be run at higher altitudes where soft errors are more frequent. Our experimental results not only show that our method is extremely fast and versatile, but that it also allows us to test how software applications perform under a wide range of fault conditions.
STRUCTURE TAILORED PROPERTIES AND FUNCTIONALITIES OF ZERO-DIMENSIONAL NANOSTRUCTURES

Title of Document: STRUCTURE TAILORED PROPERTIES AND FUNCTIONALITIES OF ZERO-DIMENSIONAL NANOSTRUCTURES Yun Tang, Ph.D., 2009 Directed By: Professor Min Ouyang, Department of Physics The field of nanoscience and nanotechnology has achieved significant progress over last thirty years. Complex nanostructures with tunable properties for novel applications have been successfully fabricated and characterized. In this thesis, I will focus on our recent efforts on precise controlled synthesis of zero-dimensional nanostructures as well as fundamental understanding of the physical behavior of assynthesized nanostructures. Particularly, three topics are presented: (1) Nanoscale crystallinity engineering: we have achieved nanoscale crystallinity control of noble metal nanoparticles with 100% yield by molecular engineering. We have used silver nanoparticles as example to demonstrate synthetic strategy and importance of such control in nanoscale chemical transformation, fundamental electron and phonon couplings and surface plasmon resonance based biological sensors. Such nanoscale crystallinity engineering provides a new pathway for design of complex nanostructures, tailoring nanoscale electronic and mechanical properties as well as controlling classical and quantum coupling interactions; (2) Precise control of core@shell nanostructures: we have developed a new universal strategy denoted as intermediated phase assisted phase exchange and reaction (iPAPER) to achieve layerby-layer control of shell components in core@shell structures. Tunable plasmonic, optical and magnetic properties of core@shell structures enabled by our iPAPER strategy are further demonstrated. These characterizations are promising for understanding and manipulating nanoscale phenomena as well as assembling nanoscale devices with desirable functionality; and (3) Fundamental spin and structure manipulation of semiconductor quantum dots by hydrostatic pressure. Pressure provides a unique means of modifying materials properties. By measuring dependence of spin dynamics on pressure, we revealed that the spin states of semiconductor quantum dots are very robust. We further provided the first experimental evidence for the existence of a metastable intermediate state before the first-order phase transition of semiconductor quantum dots. Our results are crucial for the future development of quantum information processing based on spin qubits of
Mutants That Alter the Covalent Structure of Catalase Hydroperoxidase II from Escherichia coli*

The three-dimensional structures of two HPII variants, V169C and H392Q, have been determined at resolutions of 1.8 and 2.1 Å, respectively. The V169C variant contains a new type of covalent bond between the sulfur atom of Cys169 and a carbon atom on the imidazole ring of the essential His128. This variant enzyme has only residual catalytic activity and contains heme b. The chain of water molecules visible in the main channel may reflect the organization of the hydrogen peroxide substrates in the active enzyme. Two alternative mechanisms, involving either compound I or free radical intermediates, are presented to explain the formation of the Cys-His covalent bond. The H392Q and H392E variants exhibit 75 and 25% of native catalytic activity, respectively. The Gln392 variant contains only heme b, whereas the Glu392 variant contains a mixture of heme b andcis and trans isomers of heme d, suggesting of a role for this residue in heme conversion. Replacement of either Gln419 and Ser414, both of which interact with the heme, affected the cis:trans ratio of spirolactone heme d. Implications for the heme oxidation mechanism and the His-Tyr bond formation in HPII are considered.
Safe Sequential Path Planning of Multi-Vehicle Systems Under Presence of Disturbances and Imperfect Information

Recently, there has been an immense surge of interest in using unmanned aerial vehicles (UAVs) for civil purposes. Multi-UAV systems are safety-critical, and safety guarantees must be made to ensure no undesirable configurations such as collisions occur. Hamilton-Jacobi (HJ) reachability is ideal for analyzing such safety-critical systems because it provides safety guarantees and is flexible in terms of system dynamics; however, its direct application is limited to small-scale systems of no more than two vehicles because of the exponential-scaling computation complexity. By assigning vehicle priorities, the sequential path planning (SPP) method allows multi-vehicle path planning to be done with a computation complexity that scales linearly with the number of vehicles. Previously the SPP method assumed no disturbances in the vehicle dynamics, and that every vehicle has perfect knowledge of the position of higher-priority vehicles. In this paper, we make SPP more practical by providing three different methods for accounting for disturbances in dynamics and imperfect knowledge of higher-priority vehicles. Each method has advantages and disadvantages with different assumptions about information sharing. We demonstrate our proposed methods in simulations.
Intensity of Aphasia Therapy, Impact on Recovery

Background— It has been speculated that the conflicting results demonstrated across poststroke aphasia therapy studies might be related to differences in intensity of therapy provided across studies. The aim of this study is to investigate the relationship between intensity of aphasia therapy and aphasia recovery. Methods— A MEDLINE literature search was conducted to retrieve clinical trials investigating aphasia therapy after stroke. Changes in mean scores from each study were recorded. Intensity of therapy was recorded in terms of length of therapy, hours of therapy provided per week, and total hours of therapy provided. Pearson correlation was used to assess the relationship between changes in mean scores of outcome measures and intensity of therapy. Results— Studies that demonstrated a significant treatment effect provided 8.8 hours of therapy per week for 11.2 weeks versus the negative studies that only provided ≈2 hours per week for 22.9 weeks. On average, positive studies provided a total of 98.4 hours of therapy, whereas negative studies provided 43.6 hours of therapy. Total length of therapy time was found to be inversely correlated with hours of therapy provided per week (P =0.003) and total hours of therapy provided (P =0.001). Total length of therapy was significantly inversely correlated with mean change in Porch Index of Communicative Abilities (PICA) scores (P =0.0001). The number of hours of therapy provided in a week was significantly correlated to greater improvement on the PICA (P =0.001) and the Token Test (P =0.027). Total number of hours of therapy was significantly correlated with greater improvement on the PICA (P <0.001) and the Token Test (P <0.001). Conclusions— Intense therapy over a short amount of time can improve outcomes of speech and language therapy for stroke patients with aphasia.
5-HT2A and 5-HT2C receptors as hypothalamic targets of developmental programming in male rats

Although obesity is a global epidemic, the physiological mechanisms involved are not well understood. Recent advances reveal that susceptibility to obesity can be programmed by maternal and neonatal nutrition. Specifically, a maternal low-protein diet during pregnancy causes decreased intrauterine growth, rapid postnatal catch-up growth and an increased risk for diet-induced obesity. Given that the synthesis of the neurotransmitter 5-hydroxytryptamine (5-HT) is nutritionally regulated and 5-HT is a trophic factor, we hypothesised that maternal diet influences fetal 5-HT exposure, which then influences development of the central appetite network and the subsequent efficacy of 5-HT to control energy balance in later life. Consistent with our hypothesis, pregnant rats fed a low-protein diet exhibited elevated serum levels of 5-HT, which was also evident in the placenta and fetal brains at embryonic day 16.5. This increase was associated with reduced levels of 5-HT2CR, the primary 5-HT receptor influencing appetite, in the fetal, neonatal and adult hypothalamus. As expected, a reduction of 5-HT2CR was associated with impaired sensitivity to 5-HT-mediated appetite suppression in adulthood. 5-HT primarily achieves effects on appetite by 5-HT2CR stimulation of proopiomelanocortin (POMC) peptides within the arcuate nucleus of the hypothalamus (ARC). We show that 5-HT2ARs are also anatomically positioned to influence the activity of ARC POMC neurons and that mRNA encoding 5-HT2AR is increased in the hypothalamus of in utero growth-restricted offspring that underwent rapid postnatal catch-up growth. Furthermore, these animals at 3 months of age are more sensitive to appetite suppression induced by 5-HT2AR agonists. These findings not only reveal a 5-HT-mediated mechanism underlying the programming of susceptibility to obesity, but also provide a promising means to correct it, by treatment with a 5-HT2AR agonist.
Mining streaming tweets for real-time event credibility prediction in Twitter

Social media like Twitter has been widely adopted for information dissemination due to its convenience and efficiency. However, false information and rumors on social media are undermining its utility as a valuable real-time information source. Existing works for information credibility analysis are based on offline batch analysis, often incurring a long lag since the event first occurs. In this paper, we develop a generative probabilistic model for real-time event credibility prediction in Twitter. We propose an online prediction algorithm based on streaming tweets, without storing or reprocessing the past tweets. We evaluate both the offline batch prediction and online streaming prediction performance of the proposed model on the Twitter dataset. The empirical results show that its batch prediction performance outperforms other algorithms based on aggregation analysis, and the online prediction performance quickly approaches that of the batch prediction with only a few hundred tweets.
Handling Conflicts in Depth-First Search for LTL Tableau to Debug Compliance Based Languages

Providing adequate tools to tackle the problem of inconsistent compliance rules is a critical research topic. This problem is of paramount importance to achieve automatic support for early declarative design and to support evolution of rules in contract-based or service-based systems. In this paper, we investigate the problem of extracting temporal unsatisfiable cores in order to detect the inconsistent part of a specification. We extend conflict-driven SAT-solver to provide a new conflict-driven depth-first-search solver for temporal logic. We use this solver to compute LTL unsatisfiable cores, whithout re-exploring the history of the solver. We provide sound and complete proofs together with complexity results.
An Articulatory Feature-Based Tandem Approach and Factored Observation Modeling

The so-called tandem approach, where the posteriors of a multilayer perceptron (MLP) classifier are used as features in an automatic speech recognition (ASR) system has proven to be a very effective method. Most tandem approaches up to date have relied on MLPs trained for phone classification, and appended the posterior features to some standard feature hidden Markov model (HMM). In this paper, we develop an alternative tandem approach based on MLPs trained for articulatory feature (AF) classification. We also develop a factored observation model for characterizing the posterior and standard features at the HMM outputs, allowing for separate hidden mixture and state-tying structures for each factor. In experiments on a subset of Switchboard, we show that the AF-based tandem approach is as effective as the phone-based approach, and that the factored observation model significantly outperforms the simple feature concatenation approach while using fewer parameters.
Computing multi-party trust privately: in O(n) time units sending one (possibly large) message at a time

Schemes for multi-party trust computation are presented. The schemes do not make use of a Trusted Authority. The schemes are more efficient than previous schemes by the number of messages exchanged which is proportional to the number of participants rather than to a quadratic number of the participants. We note that in our schemes the length of each message may be larger than the message length of previous schemes. The calculation of a trust, in a specific user by a group of community members, starts upon a request of an initiating user. The trust computation is provided in a completely distributed manner, while each user calculates its trust value privately. Given a community <i>C</i> and its members (users) <i>U</i><sub>1</sub>, . , <i>U</i><sub><i>n</i></sub>, we present computationally secure schemes for trust computation. The first Accumulated Protocol <i>AP</i> computes the average trust in a specific user <i>U</i><sub><i>t</i></sub> upon the trust evaluation request initiated by a user <i>U</i><sub><i>n</i></sub>. The exact trust values of each queried user are not disclosed to <i>U</i><sub><i>n</i></sub>. The next Weighted Accumulated protocol <i>WAP</i> generates the average weighted trust in a specific user <i>U</i><sub><i>t</i></sub> taking into consideration the unrevealed trust that <i>U</i><sub><i>n</i></sub> has in each user participating in the trust process evaluation. We extend our schemes to the case when the initiating user <i>U</i><sub><i>n</i></sub> can be compromised by the adversary, and we introduce the Multiple Private Keys <i>M P K P</i> and the Multiple Private Keys Weighted <i>M P W P</i> protocols for computing average unweighted and weighted trust, respectively. The computation of all our algorithms requires the transmission of <i>O</i>(<i>n</i>) (possibly large) messages.