Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Chewing Paneer and Cheese on Salivary Acidogenicity: A Comparative Study

ABSTRACT Aim: The aim was to evaluate the salivary pH reversal phenomenon by chewing paneer and processed cheese after a chocolate challenge. Materials and methods: Thirty caries-free children were randomly selected and divided into 2 groups: Control group was given processed cheese (Amul) and the experimental group was given paneer (Amul) after a chocolate challenge. After determining the resting salivary pH using GC pH strips, the subjects were asked to eat the test foods and salivary pH was measured at time intervals of 5, 10, 15, 30 and 60 minutes to record the time taken for the salivary pH to return to baseline values after an acidogenic challenge. Results: The data was analyzed and intergroup comparison was done using paired student’s t-test. The test meals increased salivary pH after chocolate challenge significantly from baseline values and neutralized the fall in pH after a chocolate challenge. The protective effect was evident after 5 minutes of consuming chocolate and was highest up to 30 minutes after which the salivary pH gradually fell but had not returned to baseline values even at 60 minutes. Conclusion: The findings suggest that chewing of paneer like cheese abolishes the fall in salivary pH caused by sugar consumption and maybe recommended as a protective food in pediatric diet counseling. How to cite this article: Tayab T, Rai K, Kumari V, Thomas E. Effect of Chewing Paneer and Cheese on Salivary Acidogenicity: A Comparative Study. Int J Clin Pediatr Dent 2012;5(1):20-24.
Analyzing cacheability in the access network with HACkSAw

Web traffic is growing, and the need for accurate traces of HTTP traffic is therefore also rising, both for operators and researchers, as accurate HTTP traffic traces allow to analyse and characterize the traffic and the clients, and to analyse the performance of the network and the perceived quality of service for the final users. Since most ICN proposals also advocate for pervasive caching, it's imperative to measure the cacheability of traffic to assess the impact and/or the potential benefits of such solutions. This demonstration will show a both a tool to collect HTTP traces that is both fast and accurate and that overcomes the limitations of existing tools, and a set of important statistics that can be computed in post processing, like aggregate/demultiplexed cacheability figures.
Network on Chip optimization based on surrogate model assisted evolutionary algorithms

Network-on-Chip (NoC) design is attracting more and more attention nowadays, but there is a lack of design optimization method due to the computationally very expensive simulations of NoC. To address this problem, an algorithm, called NoC design optimization based on Gaussian process model assisted differential evolution (NDPAD), is presented. Using the surrogate model-aware evolutionary search (SMAS) framework with the tournament selection based constraint handling method, NDPAD can obtain satisfactory solutions using a limited number of expensive simulations. The evolutionary search strategies and training data selection methods are then investigated to handle integer design parameters in NoC design optimization problems. Comparison shows that comparable or even better design solutions can be obtained compared to standard EAs, and much less computation effort is needed.
Modeling Best-Effort and FEC Streaming of Scalable Video in Lossy Network Channels

Video applications that transport delay-sensitive multimedia over best-effort networks usually require special mechanisms that can overcome packet loss without using retransmission. In response to this demand, forward-error correction (FEC) is often used in streaming applications to protect video and audio data in lossy network paths; however, studies in the literature report conflicting results on the benefits of FEC over best-effort streaming. To address this uncertainty, we start with a baseline case that examines the impact of packet loss on scalable (FGS-like) video in best-effort networks and derive a closed-form expression for the loss penalty imposed on embedded coding schemes under several simple loss models. Through this analysis, we find that the utility (i.e., usefulness to the user) of unprotected video converges to zero as streaming rates become high. We then study FEC-protected video streaming, re-derive the same utility metric, and show that for all values of loss rate inclusion of FEC overhead substantially improves the utility of video compared to the best-effort case. We finish the paper by constructing a dynamic controller on the amount of FEC that maximizes the utility of scalable video and show that the resulting system achieves a significantly better PSNR quality than alternative fixed-overhead methods
iGenoPri: Privacy-preserving genomic data processing with integrity and correctness proofs

Nowadays, governmental and non-governmental health organisations and insurance companies invest in integrating an individual's genetic information to their daily practices. In this paper, we focus on an emerging area of genome analysis, called Disease Susceptibility (DS), from which an individual's susceptibility to a disease is calculated by using her genetic information. Recent work by Danezis et al. [1] presents an approach for calculating DS in a privacy-preserving manner. However, the proposed solution has two drawbacks. First, it does not provide a mechanism to check the integrity of genomic data that is used to calculate the susceptibility and more importantly the computed result. Second, it lacks a mechanism to check the correctness of the performed DS test. In this paper, we present iGenoPri that aims at addressing both problems by employing the Message Authentication Code (MAC) and verifiable computing.
A leader peptide is sufficient to direct mitochondrial import of a chimeric protein.

Most mitochondrial proteins are encoded in the nucleus and synthesized in the cytoplasm as larger precursors containing NH2‐terminal ‘leader’ peptides. To test whether a leader peptide is sufficient to direct mitochondrial import, we fused the cloned nucleotide sequence encoding the leader peptide of the mitochondrial matrix enzyme ornithine transcarbamylase (OTC) with the sequence encoding the cytosolic enzyme dihydrofolate reductase (DHFR). The fused sequence, joined with SV40 regulatory elements, was introduced along with a selectable marker into a mutant CHO cell line devoid of endogenous DHFR. In stable transformants, the predicted 26‐K chimeric precursor protein and two additional proteins, 22 K and 20 K, were detected by immunoprecipitation with anti‐DHFR antiserum. In the presence of rhodamine 6G, an inhibitor of mitochondrial import, only the chimeric precursor was detected. Immunofluorescent staining of stably transformed cells with anti‐DHFR antiserum produced a pattern characteristic of mitochondrial localization of immunoreactive material. When the chimeric precursor was synthesized in a cell‐free system and incubated post‐translationally with isolated rat liver mitochondria, it was imported and converted to a major product of 20 K that associated with mitochondria and was resistant to proteolytic digestion by externally added trypsin. Thus, both in intact cells and in vitro, a leader sequence is sufficient to direct the post‐translational import of a chimeric precursor protein by mitochondria.
Multilingual Joint Parsing of Syntactic and Semantic Dependencies with a Latent Variable Model

Current investigations in data-driven models of parsing have shifted from purely syntactic analysis to richer semantic representations, showing that the successful recovery of the meaning of text requires structured analyses of both its grammar and its semantics. In this article, we report on a joint generative history-based model to predict the most likely derivation of a dependency parser for both syntactic and semantic dependencies, in multiple languages. Because these two dependency structures are not isomorphic, we propose a weak synchronization at the level of meaningful subsequences of the two derivations. These synchronized subsequences encompass decisions about the left side of each individual word. We also propose novel derivations for semantic dependency structures, which are appropriate for the relatively unconstrained nature of these graphs. To train a joint model of these synchronized derivations, we make use of a latent variable model of parsing, the Incremental Sigmoid Belief Network (ISBN) architecture. This architecture induces latent feature representations of the derivations, which are used to discover correlations both within and between the two derivations, providing the first application of ISBNs to a multi-task learning problem. This joint model achieves competitive performance on both syntactic and semantic dependency parsing for several languages. Because of the general nature of the approach, this extension of the ISBN architecture to weakly synchronized syntactic-semantic derivations is also an exemplification of its applicability to other problems where two independent, but related, representations are being learned.
Privacy vulnerability of published anonymous mobility traces

Mobility traces of people and vehicles have been collected and published to assist the design and evaluation of mobilee networks, such as large-scale urban sensing networks. Although the published traces are often made anonymous in that the true identities of nodes are replaced by random identifiers, the privacy concern remains. This is because in real life, nodes are open to observations in public spaces, or they may voluntarily or inadvertently disclose partial knowledge of their whereabouts. Thus, snapshots of nodes' location information can be learned by interested third parties, e.g., directly through chance/engineered meetings between the nodes and their observers, or indirectly through casual conversations or other information sources about people. In this paper, we investigate how an adversary, when equipped with a small amount of the snapshot information termed as side information, can infer an extended view of the whereabouts of a victim node appearing in an anonymous trace. Our results quantify the loss of victim nodes' privacy as a function of the nodal mobility (captured in both real and synthetic traces), the inference strategies of adversaries, and any noise that may appear in the trace or the side information. Generally, our results indicate that the privacy concern is significant in that a relatively small amount of side information is sufficient for the adversary to infer the true identity (either uniquely or with high probability) of a victim in a set of anonymous traces.
Evaluation of severity of Parkinson's disease using stride interval variability

Parkinson's disease (PD) is a neurodegenerative disorder by degeneration of dopamine neurons, affecting motor controls related to basal ganglia. Because severe movement disorders such as gait disturbances are often observed, evaluation from gait analysis is useful. From such a background, Coefficient of Variation (CV) and Detrended Fluctuation Analysis (DFA) comes to be used as one of the methods for analyzing the variability of the stride interval in recent years. However classification of the severity of PD by stride interval variability has not been reached to practical use enough. In this paper, in order to clarify the difference in age and the severity of PD patients, variability of stride interval were analyzed by CV and DFA. As a first step, we performed analysis of stride interval in three minutes' walk of 17 PD patients, 13 healthy elderly and 12 healthy young people. Particularly, we divided PD patients based on the Hoehn and Yahr (HY) scale into an HY2 group (n=9) and an HY3 group (n=8) in order to examine the relation to disease severity. Results indicate that CV seemed to distinguish PD patients from healthy people and that DFA fractal exponent tended to be related to the age and the disease severity. From these results, gait analysis using both CV and DFA is suggested to classify participants into healthy young, healthy elderly, HY2 and HY3 groups. For future direction, there are possibilities for seeing the progression from healthy people to PD patients.
1 Pragmatic enrichment

The phrase "pragmatic enrichment" is sometimes used in a broad sense to refer to the process in virtue of which the content conveyed by an utterance comes to include all sorts of elements which are contextually implied without being part of what the utterance literally means. In his class notes "Pragmatic Enrichment : Introduction by Examples," Chris Potts gives examples like the following: (1) John and Mary have recently started going together. Valentino is Mary's ex-boyfriend. One evening, John asks Mary, ―Have you seen Valentino this week? ‖ Mary answers, ―Valentino's been sick with mononucleosis for the past two weeks. ‖ Valentino has in fact been sick with mononucleosis for the past two weeks, but it is also the case that Mary had a date with Valentino the night before. Mary's utterance clearly suggests a negative (and false) answer to the question : "Have you seen Valentino this week ? " Literally, however, she only says that Valentino has been sick with mononucleosis for the past two weeks, and that is true. In his William James Lectures delivered at Harvard in the late sixties, Grice described the mechanism through which one can mean one thing by saying another (Grice 1989). The term of art coined by Grice for that mechanism is "conversational implicature. " Thus, in (1), Mary ‗says' that Valentino has been sick with mononucleosis for the past two weeks, and ‗conversationally implicates' that she has not seen him this week. On Grice's account, implicatures are derived through an inference which enables the interpreter to grasp the speaker's communicative intention despite the fact that it's not articulated in words. The inference makes use of two crucial premisses (in addition to background knowledge): (1) the fact that the speaker has said what she has said (here, that Valentino has been sick etc.), and (2) the fact that the speaker, qua communicator, obeys (or is supposed to obey) the rules of communication or, as Grice puts it, the "maxims of conversation. " Because of the role played by the first premiss in the inference through which they are derived, conversational implicatures belong to the ‗post-semantic' layer of interpretation. This means that, in order to derive the implicatures of an utterance, an interpreter must start by identifying what the speaker literally says. (The properly semantic layer of interpretation corresponds to the identification of what is said — the proposition literally expressed.) It is customary in the literature …
ImpBench: A novel benchmark suite for biomedical, microelectronic implants

So far, design and deployment of microelectronic, implantable devices has largely had a strongly ldquoad-hocrdquo character. The majority of existing devices has been custom-tailored to the specific application in mind, in an effort to abide by strict design constraints on safety as well as power and size. However, an enabling technology and the fact that implants are gradually becoming mainstream market products calls for a more structured design approach. Towards that end, in this paper we present ImpBench, a novel benchmark suite meant for designing and evaluating new digital processors for microelectronic implants. In an application field as wide as the various pathoses of the human body, we have conceptualized this suite based on common-sense and market-driven indicators, and we have established its usefulness and uniqueness based on extensive experimental measurement. The suite consists of eight carefully selected programs, chosen on the basis of popularity among contemporary and emerging implant applications. MiBench being the closest to our application field, that is embedded systems, has been used for a detailed comparative study. Since implants are required to perform control-, processing- or I/O-intensive tasks, various benchmark characteristics have been studied, namely: performance (IPC), cache and branch-prediction behavior, instruction distribution and power consumption. Results display significant variation from existing benchmarks to justify the need for and usefulness of ImpBench.
Rapid Processing and Unsupervised Learning in a Model of the Cortical Macrocolumn

We study a model of the cortical macrocolumn consisting of a collection of inhibitorily coupled minicolumns. The proposed system overcomes several severe deficits of systems based on single neurons as cerebral functional units, notably limited robustness to damage and unrealistically large computation time. Motivated by neuroanatomical and neurophysiological findings, the utilized dynamics is based on a simple model of a spiking neuron with refractory period, fixed random excitatory interconnection within minicolumns, and instantaneous inhibition within one macrocolumn. A stability analysis of the system's dynamical equations shows that minicolumns can act as monolithic functional units for purposes of critical, fast decisions and learning. Oscillating inhibition (in the gamma frequency range) leads to a phase-coupled population rate code and high sensitivity to small imbalances in minicolumn inputs. Minicolumns are shown to be able to organize their collective inputs without supervision by Hebbian plasticity into selective receptive field shapes, thereby becoming classifiers for input patterns. Using the bars test, we critically compare our system's performance with that of others and demonstrate its ability for distributed neural coding.
A Power-Aware Virtual Machine Mapper Using Firefly Optimization

The optimal virtual machine (VM) provisioning is important for improving power efficiency and resource utilization in a cloud service, where the resource pool is basically characterized by high resource dynamics caused by non-linear variation in the availability of processing, memory size, storage capacity, bandwidth and power drawn resulting from the sporadic nature of workload. In this paper, we develop a novel meta-scheduler (PAFA) that makes use of multi-objective discrete firefly algorithm to efficiently obtain a set of non-dominated solutions to detect and track the changing optimal target servers for the virtual machine provisioning, that considers resource dynamics and the power consumption of the servers with different loads or in different sleep states, which are unconsidered to existing methods, that the total resource wastage and total incremental power drawn by the server pool are simultaneously minimum without compromising the performance objectives. The experimental analysis and comparisons with other methods have shown that the proposed algorithm is efficient and promising method in a resource monitor to find the rate of change in the resource pool and to maintain the supply and demand in equilibrium.
Community-Based Prevalence of Genital Human Papilloma Virus (HPV) Infection: a Systematic Review and Meta-Analysis

Introduction: Cervical cancer probably represents the best-studied human cancer caused by a viral infection and the causal association of this preventable cancer with human papilloma virus (HPV) is well established. Worldwide there is a scarcity of data regarding HPV prevalence with vast differences existing among populations. Objective: The aim of this meta-analysis was to determine the community-based HPV prevalence estimates among asymptomatic women from urban and rural set ups and in participants of cancer screening clinics. Study design: Systematic review and meta-analysis. Methods: PubMed-Medline, CINAHL, Scopus, and Google scholar were systematically searched for studies providing prevalence data for HPV infection among asymptomatic women between 1986 and 2016. Results: The final analysis included 32 studies comprising a population of 224,320 asymptomatic women. The overall pooled HPV prevalence was 11% (95% confidence interval (CI), 9%-12%). The pooled HPV prevalence of 11% (95% CI, 9%-11%) was observed among women attending cervical cancer screening clinics. The pooled HPV prevalences were 10% (95% CI 8%-12%) and 11% (95% CI 4%-18%) from urban and rural areas respectively, indicating higher infection rates among the rural women with the least access to cancer screening and cancer care. Conclusion: The prevalence rates in this systematic quantitative review provide a reliable estimate of the burden of HPV infection among asymptomatic women from developed as well as developing nations. Rural women and women attending cervical cancer screening programmes feature higher genital HPV prevalences compared to their urban counterparts.
History-Based Dynamic Voltage Scaling with Few Number of Voltage Modes for GALS NoC

In this paper, we propose a history-based dynamic voltage scaling (DVS) scheme for a GALS NoC which is suitable for MPSoC architectures. The DVS scheme exploits the link utilization and adjusts the router voltages among few number of voltage modes. The introduced architecture is simulated in 90nm CMOS technology with accurate Spice simulations. Experimental results show that history-based DVS successfully adjusts router voltages to track actual link utilization over time. In comparison to the system in which the voltage is fixed at 1.0v, in a 91% saturated network, the proposed DVS scheme saves dynamic and leakage power about 3.3 and 2.3 times, respectively. In addition, 17% energy-delay saving is achieved in the same traffic load.
Multi-Moment Approximate Option Pricing Models: A General Comparison (Part 1)

After the seminal paper of Jarrow and Rudd (1982), several authors have proposed to use different statistical series expansion to price options when the risk-neutral density is asymmetric and leptokurtic. Amongst them, one can distinguish the Gram-Charlier Type A series expansion (Corrado and Su, 1996-b and 1997-b), the log-normal Gram- Charlier series expansion (Jarrow and Rudd, 1982) and the Edgeworth series expansion (Rubinstein, 1998). The purpose of this paper is to compare these different multimoment approximate option pricing models. We first recall the link between the riskneutral density and moments in a general statistical series expansion framework under the martingale hypothesis. We then derive analytical formulae for several four-moment approximate option pricing models, namely, the Jarrow and Rudd (1982), Corrado and Su (1996-b and 1997-b) and Rubinstein (1998) models. We investigate in particular the conditions that ensure the respect of the martingale restriction (see Longstaff, 1995) and consequently revisit the approximate option pricing models under study. We also get for these models the analytical expressions of implied probability densities, implied volatility smile functions and several hedging parameters of interest.
Turkomatic: automatic recursive task and workflow design for mechanical turk

Completing complex tasks on crowdsourcing platforms like Mechanical Turk currently requires significant up-front investment into task decomposition and workflow design. We present a new method for automating task and workflow design for high-level, complex tasks. Unlike previous approaches, our strategy is recursive, recruiting workers from the crowd to help plan out how problems can be solved most effectively. Our initial experiments suggest that this strategy can successfully create workflows to solve tasks considered difficult from an AI perspective, although it is highly sensitive to the design choices made by workers.