Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring Oral Fatty Acid Thresholds, Fat Perception, Fatty Food Liking, and Papillae Density in Humans

Emerging evidence from a number of laboratories indicates that humans have the ability to identify fatty acids in the oral cavity, presumably via fatty acid receptors housed on taste cells. Previous research has shown that an individual's oral sensitivity to fatty acid, specifically oleic acid (C18:1) is associated with body mass index (BMI), dietary fat consumption, and the ability to identify fat in foods. We have developed a reliable and reproducible method to assess oral chemoreception of fatty acids, using a milk and C18:1 emulsion, together with an ascending forced choice triangle procedure. In parallel, a food matrix has been developed to assess an individual's ability to perceive fat, in addition to a simple method to assess fatty food liking. As an added measure tongue photography is used to assess papillae density, with higher density often being associated with increased taste sensitivity.
Effects of equipment variation on speaker recognition error rates

Speaker recognition is one biometric used in identity authentication. As use of biometric systems become more widespread the need for robustness in various environments and applications becomes more significant. One such variable is recording equipment. Speaker recognition systems in distributed environments, such as the internet, are likely to use different microphones to perform identity authentication. The success rates for speaker recognition systems are dependent upon the variability of the recording system performance in a speaker recognition system. This paper investigates how speaker recognition false accept, false reject rates are affected by variations in recording systems.
LRU Cache under Stationary Requests

In this paper we extend an approximation first proposed by Fagin [4] for the LRU cache under the independence reference model to systems where requests for different contents form independent stationary and ergodic processes. We show that this approximation becomes exact as the number of contents goes to infinity while maintaining the fraction of the contents that can populate the cache to be constant. Last, we provide results on the rate of convergence.
A Study of an Augmented Museum Experience

This paper describes the design of a study of visitors to a science museum who are equipped with wirelessly connected handheld devices. The museum exhibits are augmented with information and services in the form of web pages, and the users can access those pages conveniently when in the proximity of the exhibits as well as from their desktops outside the museum. The goal of the study is to examine use of technologies for ‘bridging the physical and virtual worlds’. We describe the museum setting and the technologies deployed. We outline a layered model for describing the user’s activities and a methodology that we propose for our analysis. We explain how the notion of combined virtual and physical navigation is central to the study, which we have just begun.
Presupplementary Motor Area Activation during Sequence Learning Reflects Visuo-Motor Association

In preceding studies (Hikosaka et al., 1996; Sakai et al., 1998) we have shown that the presupplementary motor area (pre-SMA), an anterior part of the medial premotor cortex, is active during visuo-motor sequence learning. However, the paradigm required the subjects first to acquire correct visuo-motor association and then to acquire correct sequence, and it was still unknown which of the two processes the pre-SMA is involved in. To further characterize the role of pre-SMA, we have conducted another series of functional magnetic resonance imaging experiments using three learning paradigms. The three were the same in that they involved a visuo-motor association component, but they differed in terms of the involvement of sequential components; one involved no sequence learning, whereas the other two involved learning of motor sequence or perceptual sequence. Comparison of the learning conditions with the any-order button press condition revealed pre-SMA activation in all three paradigms. The pre-SMA activation remained unchanged during learning of visuo-motor associations but decreased during learning of sequences, suggesting that the pre-SMA is related to visuo-motor association rather than sequence. The decrease of pre-SMA activation in the sequential paradigms may reflect the process by which individual visuo-motor associations were replaced by the formation of sequential procedural memory, which occurs outside the pre-SMA. Thus activation of the pre-SMA was related to the extent to which the task performance depended on conscious visuo-motor associations.
A 3: application-aware acceleration for wireless data networks

A tremendous amount of research has been done toward improving transport layer performance over wireless data networks. The improved transport layer protocols are typically application-unaware. In this paper, we argue that the behavior of applications can and do dominate the actual performance experienced. More importantly, we show that for practical applications, application behavior all but completely negates any improvements achievable through better transport layer protocols. In this context, we motivate an application-aware, but application transparent, solution suite called A 3 (application-aware acceleration) that uses a set of design principles realized in an application specific fashion to overcome the typical behavioral problems of applications. We demonstrate the performance of A3 through emulations using realistic application traffic traces.
Deep Neural Networks with Multistate Activation Functions

We propose multistate activation functions (MSAFs) for deep neural networks (DNNs). These MSAFs are new kinds of activation functions which are capable of representing more than two states, including the N-order MSAFs and the symmetrical MSAF. DNNs with these MSAFs can be trained via conventional Stochastic Gradient Descent (SGD) as well as mean-normalised SGD. We also discuss how these MSAFs perform when used to resolve classification problems. Experimental results on the TIMIT corpus reveal that, on speech recognition tasks, DNNs with MSAFs perform better than the conventional DNNs, getting a relative improvement of 5.60% on phoneme error rates. Further experiments also reveal that mean-normalised SGD facilitates the training processes of DNNs with MSAFs, especially when being with large training sets. The models can also be directly trained without pretraining when the training set is sufficiently large, which results in a considerable relative improvement of 5.82% on word error rates.
Spontaneous and Engineered Compensatory HSV Mutants that Counteract the Host Antiviral PKR Response

A virulent recombinant HSV lacking the diploid γ134. 5 gene (Δγ134.5) have been investigated over the last two decades both for anti-tumor therapy and as vaccine vectors. The first generation vectors, while safe, are incapable of sustained replication in the majority of treated patients. An interferon inducible host antiviral kinase, protein kinase R (PKR), limits late viral protein synthesis and replication of Δγ134. 5 viruses. This review describes the development of new Δγ134. 5 vectors, through serial passage selection and direct viral genome engineering, which demonstrate selective PKR evasion in targeted cells and improved viral replication without restoring neurovirulence.
Recurrent spontaneous subserosal hematoma of ileum causing intestinal obstruction in a patient with menkes disease

Background: Menkes disease (MD) is a disorder of copper metabolism due to ATP7A gene mutation that leads to severe copper deficiency. Deformed blood vessels can be found in many parts of the body, and intracranial hematoma is generally reported. Methods: We report a Taiwanese boy with MD who had recurrent spontaneous subserosal hematoma of ileum presenting as intestinal obstruction, with the 2 episodes 23 months apart. The patient returned to the usual physical status after surgical removal of the hematoma. Results: The defective copper metabolism causes dysfunction of a plenty of copper-dependent enzymes, giving rise to unique kinky hair appearance, progressive neurodegeneration, and connective tissue abnormalities. To our knowledge, this is the first report on recurrent subserosal hemorrhage of intestine in MD. Conclusion: Owing to the fragile structure of blood vessels, subserosal hematoma should be considered when patients with MD having intestinal obstruction.
Learning Method for Extraction of Partial Correspondence from Parallel Corpus

For machine translations using a parallel corpus, it is effective to extract partial correspondences: pairs of phrases of the source language(SL) and target language(TL) in bilingual sentences. However, it is difficult to extract the partial correspondences correctly and efficiently in the data sparse corpus. In this paper, we propose a new learning method that extracts the partial correspondences solely from the parallel corpus without any analytical tools. In the proposed method, the extraction rules are automatically acquired from bilingual sentences using bi-gram statistics in each language sentence and the similarity based on Dice coefficient between SL words and TL words. The acquired extraction rules possess information about the first parts(e.g., "a", "the") or the last parts in phrases. Moreover, the partial correspondences are extracted from the bilingual sentences using the extraction rules correctly and efficiently. Evaluation experiments indicated that our proposed method can improve the translation quality of the learning-type machine translation by correctly and efficiently extracting the partial correspondences in bilingual sentences.
Profit-based unit commitment problem using PSO with modified dynamic programming

This paper proposes a hybrid approach utilizing particle swarm optimization along with dynamic programming to solve unit commitment problem based on the profit under the deregulated power market. In the deregulated market, power and reserve prices are important factors in the decision process for unit commitment scheduling and offer freedom to utilities to schedule their generators to produce less than predicted load as well as reserve to maximize their profit. To solve the profit based unit commitment problem (PBUCP), the model is divided into exterior and interior dependent sub problems, which are discrete and continuous, respectively. The proposed model helps GENCOs to make a decision, how much power and reserve that must be put up for sale in the market, and how to schedule generators in order to receive the maximum profit. GENCOs with 3 and 10 generating units are used to demonstrate the effectiveness of the proposed approach.
Telomerase Mediates Vascular Endothelial Growth Factor-dependent Responsiveness in a Rat Model of Hind Limb Ischemia*

Telomere dysfunction contributes to reduced cell viability, altered differentiation, and impaired regenerative/proliferative responses. Recent advances indicate that telomerase activity confers a pro-angiogenic phenotype to endothelial cells and their precursors. We have investigated whether telomerase contributes to tissue regeneration following hind limb ischemia and vascular endothelial growth factor 165 (VEGF165) treatment. VEGF delivery induced angiogenesis and increased expression of the telomerase reverse transcriptase (TERT) and telomerase activity in skeletal muscles and satellite and endothelial cells. Adenovirus-mediated transfer of wild type TERT but not of a dominant negative mutant, TERTdn, significantly induced capillary but not arteriole formation. However, when co-delivered with VEGF, TERTdn abrogated VEGF-dependent angiogenesis, arteriogenesis, and blood flow increase. This effect was paralleled by in vitro evidence that telomerase inhibition by 3′-azido-3′-deoxythymidine in VEGF-treated endothelial cells strongly reduced capillary density and promoted apoptosis in the absence of serum. Similar results were obtained with adenovirus-mediated expression of TERTdn and AKTdn, both reducing endogenous TERT activity and angiogenesis on Matrigel. Mechanistically, neo-angiogenesis in our system involved: (i) VEGF-dependent activation of telomerase through the nitric oxide pathway and (ii) telomerase-dependent activation of endothelial cell differentiation and protection from apoptosis. Furthermore, detection of TERT in activated satellite cells identified them as VEGF targets during muscle regeneration. Because TERT behaves as an angiogenic factor and a downstream effector of VEGF signaling, telomerase activity appears required for VEGF-dependent remodeling of ischemic tissue at the capillaries and arterioles level.
Distributed Value Functions

Many interesting problems, such as power grids, network switches, and tra(cid:14)c (cid:13)ow, that are candidates for solving with reinforcement learning (RL), also have properties that make distributed solutions desirable. We propose an algorithm for distributed reinforcement learning based on distributing the representation of the value function across nodes. Each node in the system only has the ability to sense state locally, choose actions locally, and receive reward locally (the goal of the system is to maximizethe sum of the rewards over all nodes and over all time). However each node is allowed to give its neighbors the current estimate of its value function for the states it passes through. We present a value function learning rule, using that information,that allows each node to learn a value function that is an estimate of a weighted sum of future rewards for all the nodes in the network. With this representation, each node can choose actions to improve the performance of the overall system. We demonstrate our algorithm on the distributed control of a simulated power grid. We compare it against other methods including: use of a global reward signal, nodes that act locally with no communication, and nodes that share rewards (but not value function) information with each other. Our results show that the distributed value function algorithm outperforms the others, and we conclude with an analysis of what problems are best suited for distributed value functions and the new research directions opened up by this work.
Diagnostic Value of PCR for Detection of Borrelia burgdorferi in Skin Biopsy and Urine Samples from Patients with Skin Borreliosis

ABSTRACT Skin biopsies of 36 patients with erythema migrans and acrodermatitis chronica atrophicans (ACA) before therapy and those of 8 patients after therapy were examined for Borrelia burgdorferi DNA by PCR. Skin biopsies of 27 patients with dermatological diseases other than Lyme borreliosis and those of 10 healthy persons were examined as controls. Two different primer sets targeting 23S rRNA (PCR I) and 66-kDa protein (PCR II) genes were used. PCR was performed with freshly frozen tissue (FFT) and paraffin-embedded tissue (PET). For FFT specimens of erythema migrans, 73% were positive by PCR I, 79% were positive by PCR II, and 88% were positive by combining PCR I and II. For PET specimens, PCR was less sensitive (PCR I, 44%; PCR II, 52%). For FFT specimens of ACA, PCR I was positive for two of five patients and PCR II was positive for four of five patients. B. burgdorferi was cultured from 79% of the erythema migrans specimens but not from any of the ACA lesions. Elevated B. burgdorferi antibodies were detected in sera of 74% of erythema migrans patients and 100% of ACA patients. All urine samples were negative by PCR II, whereas PCR I was positive for 27%. However, hybridization of these amplicons was negative. Sequencing of three amplicons identified nonborrelial DNA. In conclusion, urine PCR is not suitable for the diagnosis of skin borreliosis. A combination of two different primer sets achieves high sensitivity with skin biopsies. In early erythema migrans infection, culture and PCR are more sensitive than serology.
Dual-Band Operation of a Microstrip Patch Antenna on a Duroid 5870 Substrate for Ku- and K-Bands

The dual-band operation of a microstrip patch antenna on a Duroid 5870 substrate for Ku- and K-bands is presented. The fabrication of the proposed antenna is performed with slots and a Duroid 5870 dielectric substrate and is excited by a 50 Ω microstrip transmission line. A high-frequency structural simulator (HFSS) is used which is based on the finite element method (FEM) in this research. The measured impedance bandwidth (2 : 1 VSWR) achieved is 1.07 GHz (15.93 GHz–14.86 GHz) on the lower band and 0.94 GHz (20.67–19.73 GHz) on the upper band. A stable omnidirectional radiation pattern is observed in the operating frequency band. The proposed prototype antenna behavior is discussed in terms of the comparisons of the measured and simulated results.
Study on the Cold Stamping of Oil Sump Tank for the Thickness and Springback

In recent years, the high strength steel has been used widely to prove the advantage of lightweight used in automotive industry. The drawbacks occurred in the stamping procedure are thinning, springback and so on. And many process parameters affect the forming quality significantly, such as friction coefficient and blank holder force (BHF). In this paper, the effect of process parameters on the forming defects is investigated. The design of test was utilized and the finite element model was established and applied. The aim of this study is to get a further understanding on the stamping of high strength steel.
What quantum algorithms outperform classical computation and how do they do it ? BY

notion of the algorithm—the quantum algorithm—whose computational power appears to be fundamentally more efficient at carrying out certain tasks than algorithms written for today’s, nonquantum, computers. Could this possibly be true: that there is a more fundamental notion of algorithmic efficiency for computers built from quantum components? And, if this is true, what exactly is the power of these quantum algorithms? The shot that rang round the computational world announcing the arrival of the quantum algorithm was the 1994 discovery by Peter Shor that quantum computers could efficiently factor natural numbers and compute discrete logarithms. The problem of finding efficient algorithms for factoring has been burning the brains of mathematicians at least as far back as Gauss who commented upon the problem that “the dignity of science seems to demand that every aid to the solution of such an elegant and celebrated problem be zealously cultivated. ” Even more important than the fact that such a simple and central problem has eluded an efficient algorithmic solution is that the lack of such an efficient algorithm has been used as a justification for the security of public key cryptosystems, like RSA encryption. Shor’s algorithm, then, didn’t just solve a problem of pure academic interest, but instead ended up showing how quantum computers could break the vast majority of cryptographic protocols in widespread use today. If we want the content of our publicly key encrypted messages to remain secret not only now, but also in the future, then Shor’s algorithm redefines the scope of our confidence in computer security: we communicate securely, today, given that we cannot build a large scale quantum computer tomorrow. Given the encryption breaking powers promised by quantum computers, it was natural that, in the decade following Shor’s discovery, research has focused largely on whether a it is impossible to imagine today’s technological world without algorithms: sorting, searching, calculating, and simulating are being used every where to make our everyday lives better. But what are the benefits of the more philosophical endeavor of studying the notion of an algorithm through the perspective of the physical laws of the universe? This simple idea, that we desire an understanding of the algorithm based upon physics seems, upon first reflection, to be nothing more than mere plumbing in the basement of computer science. That is, until one realizes that the pipes of the universe do not seem to behave like the standard components out of which we build a computer, but instead obey the counterintuitive laws of quantum theory. And, even more astoundingly, when one puts these Recent Progress in Quantum Algorithms Doi:10.1145/1646353.1646375
Validation of Pair-Potential Models for Use in Simulating Titanate Nanostructures

In this thesis, a potential model for simulating titanium oxides (titanates) is studied. Titanium oxides are of importance for their photo-voltaic properties and their ability to be be synthesized into nanostructures, such as nanoparticles and nanofibers; the ability to synthesize titanates into such nanostructures can benefit their performance in photovoltaic applications. Thus, the construction of a foundation for future simulation work using a charge transfer enabled potential is of importance. The goal here is to understand if an existing potential model can be applied to any given form of titanium oxide or if there are portions of the potential that lack the ability to simulate specific items that are required to move forward with the simulation of zero dimensional (particles), one dimensional (wires and tubes) and two dimensional (sheets) titanate nanostructures.
Subsumption-Based Matching: Bringing Semantics to Goals

Matching a posted goal against a library of rules is a task common in many AI systems. There are matching algorithms that can perform this process with reasonable efficiency. However, they are based on the syntactic features of goals instead of their semantic meaning. Representing the semantic meaning of goals can support additional features in matching algorithms and further reasoning about goals. This paper presents a matching algorithm that uses a semantic goal representation based on description logic. Each goal is translated into a description, and matching relies on the reasoning performed by a classifier to determine which rules unify with the posted goal. An extension of the matcher relaxes the posted goal to retrieve rules that almost match the goal based on the subsumption hierarchies of the domain ontology and the goals. The matching algorithm has been implemented using LOOM as the underlying description logic, and is used routinely as a component of the EXPECT problem-solving architecture. We show how it classifies and retrieves the methods in EXPECT’s domains, and how the relaxed matching mode can be used to support knowledge acquisition.