Miracle-dz/UniFAR-FTUs huggingface dataset:
Sawtooth Software RESEARCH PAPER SERIES ng with Product Similarity in Conjoint Simulations

Choice simulators have provided very useful ways to allow researchers to project from individual or group preference models to predictions of market share. We propose that effective choice simulators need three properties to effectively mirror market behavior. First, they need to display differential impact so that a marketing action at the individual or homogeneous segment level has maximal impact near a threshold but has minimal impact otherwise. Second, simulators need to reflect differential substitution, assuring that alternatives take proportionately more share from similar than dissimilar competitors. Finally, they need to exhibit differential enhancement, a property whereby a small value difference has a big impact on highly similar competitors but almost none on dissimilar ones. A new method we call Randomized First Choice enables simulators to closely match these properties in market behavior. The method begins with a first choice model in which the item with the highest utility is chosen, but modifies that by adding two kinds of variability. The first, product value variability, adds variability to the alternatives, while the second, attribute value variability, adds variability to attribute part worths. While product variability is mathematically equivalent to the commonly used adjustment for scale, we show that attribute variability is also critical to approximate desired substitution and enhancement properties among similar alternatives. We test the value of adding both kinds of error in a choice-based conjoint study of 352 consumers. Respondents make choices among specially designed holdout sets that include near and perfect duplicates. Comparing predictions against actual choice shares for these stimuli provides a strong test of the predictive ability of various choice simulators. Additionally, we illustrate the way the methods differ in their representation of differential impact, substitution and enhancement. We assess the impact of Randomized First Choice applied to four commonly used models: an aggregate logit model, a latent class model, and individual-level models, Sawtooth Software’s ICE and hierarchical Bayes. The pooled models, aggregate logit and latent class, gain the most. Additionally, we show that the desired properties of differential enhancement and differential substitution require either individual-level data or the addition of attribute variability. We propose that Randomized First Choice provides a general way to adjust conjoint shares to the marketplace. While the addition of product variability has been commonly used as a way to adjust errors in an experimental choice task, the addition of attribute variability provides a new way to account for heterogeneity that preserves the expected impact of item similarity on choice probabilities. The combination of both kinds of variability permits a great deal of flexibility in matching results from choice experiments to market conditions.
QoS analysis of WSN based cluster tree data fusion for integrated public utility management

Recent advances in wireless sensor networks (WSNs) made strong impact on the development of low cost remote information monitoring systems. This paper proposes algorithm and simulates the performance matrices analysis of Quality of Service (QoS) parameters of WSN based on IEEE802.15. 4 cluster topology for integrated automation of public utility management such as electricity, water and gas. It is used for data fusion and data analytics, theft and leakage detection. We investigate performance metrics which include packet delivery ratio (PDR), end_to_end delay (EED), Jitter, Throughput and energy consumption with respect to varying network size. Simulation analysis is done using QUALNET ver 5. 2.
Systems-Based Analyses of Brain Regions Functionally Impacted in Parkinson's Disease Reveals Underlying Causal Mechanisms

Detailed analysis of disease-affected tissue provides insight into molecular mechanisms contributing to pathogenesis. Substantia nigra, striatum, and cortex are functionally connected with increasing degrees of alpha-synuclein pathology in Parkinson's disease. We undertook functional and causal pathway analysis of gene expression and proteomic alterations in these three regions, and the data revealed pathways that correlated with disease progression. In addition, microarray and RNAseq experiments revealed previously unidentified causal changes related to oligodendrocyte function and synaptic vesicle release, and these and other changes were reflected across all brain regions. Importantly, subsets of these changes were replicated in Parkinson's disease blood; suggesting peripheral tissue may provide important avenues for understanding and measuring disease status and progression. Proteomic assessment revealed alterations in mitochondria and vesicular transport proteins that preceded gene expression changes indicating defects in translation and/or protein turnover. Our combined approach of proteomics, RNAseq and microarray analyses provides a comprehensive view of the molecular changes that accompany functional loss and alpha-synuclein pathology in Parkinson's disease, and may be instrumental to understand, diagnose and follow Parkinson's disease progression.
Transcription of Toll-Like Receptors 2, 3, 4 and 9, FoxP3 and Th17 Cytokines in a Susceptible Experimental Model of Canine Leishmania infantum Infection

Canine leishmaniosis (CanL) due to Leishmania infantum is a chronic zoonotic systemic disease resulting from complex interactions between protozoa and the canine immune system. Toll-like receptors (TLRs) are essential components of the innate immune system and facilitate the early detection of many infections. However, the role of TLRs in CanL remains unknown and information describing TLR transcription during infection is extremely scarce. The aim of this research project was to investigate the impact of L. infantum infection on canine TLR transcription using a susceptible model. The objectives of this study were to evaluate transcription of TLRs 2, 3, 4 and 9 by means of quantitative reverse transcription polymerase chain reaction (qRT-PCR) in skin, spleen, lymph node and liver in the presence or absence of experimental L. infantum infection in Beagle dogs. These findings were compared with clinical and serological data, parasite densities in infected tissues and transcription of IL-17, IL-22 and FoxP3 in different tissues in non-infected dogs (n = 10), and at six months (n = 24) and 15 months (n = 7) post infection. Results revealed significant down regulation of transcription with disease progression in lymph node samples for TLR3, TLR4, TLR9, IL-17, IL-22 and FoxP3. In spleen samples, significant down regulation of transcription was seen in TLR4 and IL-22 when both infected groups were compared with controls. In liver samples, down regulation of transcription was evident with disease progression for IL-22. In the skin, upregulation was seen only for TLR9 and FoxP3 in the early stages of infection. Subtle changes or down regulation in TLR transcription, Th17 cytokines and FoxP3 are indicative of the silent establishment of infection that Leishmania is renowned for. These observations provide new insights about TLR transcription, Th17 cytokines and Foxp3 in the liver, spleen, lymph node and skin in CanL and highlight possible markers of disease susceptibility in this model.
Patterns of Variation in Levels of Hsp70 in Natural Rocky Shore Populations from Microscales to Mesoscales1

Abstract An important step in connecting the organismal response to thermal stress to patterns of community structure is determining at what scale discernable levels of variation are manifested. The temperature signal to which organisms may potentially respond varies at many spatial scales including microhabitat, tidal height, site and latitude. A number of studies have taken physiological assessment of the heat shock response (HSR) into the intertidal both as a tool for examining the HSR in nature and for examining the utility of HSR molecules as population or community level indicators. Most commonly, immunodetection of the total pool of the Hsp70 family of isoforms is used. Here we present data on levels of Hsp70 in intertidal organisms from microhabitat to the mesoscale. Our data and previously published work show that Hsp70 levels vary at all scales examined, similar to other physical and biological variables of interest. This demonstrates both the potential utility of Hsp70 detection as a molecular tool for field biologists and to the care that must be taken in assessing scale of variation when looking for potential bioindicator molecules.
Chimeric Infectious Bursal Disease Virus-Like Particles as Potent Vaccines for Eradication of Established HPV-16 E7–Dependent Tumors

Cervical cancer is caused by persistent high-risk human papillomavirus (HR-HPV) infection and represents the second most frequent gynecological malignancy in the world. The HPV-16 type accounts for up to 55% of all cervical cancers. The HPV-16 oncoproteins E6 and E7 are necessary for induction and maintenance of malignant transformation and represent tumor-specific antigens for targeted cytotoxic T lymphocyte–mediated immunotherapy. Therapeutic cancer vaccines have become a challenging area of oncology research in recent decades. Among current cancer immunotherapy strategies, virus-like particle (VLP)–based vaccines have emerged as a potent and safe approach. We generated a vaccine (VLP-E7) incorporating a long C-terminal fragment of HPV-16 E7 protein into the infectious bursal disease virus VLP and tested its therapeutic potential in HLA-A2 humanized transgenic mice grafted with TC1/A2 tumor cells. We performed a series of tumor challenge experiments demonstrating a strong immune response against already-formed tumors (complete eradication). Remarkably, therapeutic efficacy was obtained with a single dose without adjuvant and against two injections of tumor cells, indicating a potent and long-lasting immune response.
Users association in small cell networks with massive MIMO

In this paper, an investigation of the effect of deploying massive MIMO in two-tier cellular networks is presented. In our model, the macrocell base station (BS) as well as femtocell access points (FAPs) are equipped with a very large number of antennas. Each mobile user will attempt to connect to the BS or FAPs. However, it is assumed that the users may be biased to connect to FAPs rather than the BS. A resource allocation problem is formulated to find the optimal bias that maximizes the total system capacity while keeping the transmitted power from the BS and the FAPs within a certain limit. An algorithm for solving the optimization problem is proposed and numerical results are presented to illustrate how deploying massive MIMO can affect the optimal bias value and the total capacity. In addition, the performance of our proposed scheme is evaluated when using different precoding schemes.
Generation of reduced certificates in abstraction-carrying code

Abstraction-Carrying Code (ACC) has recently been proposed as a framework for mobile code safety in which the code supplier provides a program together with an abstraction whose validity entails compliance with a predeflned safety policy. The abstraction plays thus the role of safety certiflcate and its generation is carried out automatically by a flxed-point analyzer. The advantage of providing a (flxed- point) abstraction to the code consumer is that its validity is checked in a single pass of an abstract interpretation-based checker. A main challenge is to reduce the size of certiflcates as much as possible while at the same time not increasing checking time. In this paper, we flrst introduce the notion of reduced certiflcate which characterizes the subset of the abstraction which a checker needs in order to validate (and re-construct) the full certiflcate in a single pass. Based on this notion, we then instrument a generic analysis algorithm with the necessary extensions in order to identify the information relevant to the checker.
WASTE HEAT ENERGY HARVESTING USING OLSEN CYCLE ON 0 : 945 PB(ZN 1 = 3 NB 2 = 3 )O 3 − 0 : 055 PBTIO 3 SINGLE CRYSTALS

This paper reports on direct thermal to electrical energy conversion by performing the Olsen (or Ericsson) cycle on [001]-poled 0.945PbZn 1 = 3 Nb 2 = 3 O 3 -0.055PbTiO 3 (PZN-5.5PT) single crystals. The cycle consists of two isothermal and two constant electric ﬁeld processes. The energy density was found to decrease with increasing cycle frequency while the power density increased. The maximum energy density obtained was 150 J/L/cycle for temperatures between 100 and 190 o C and electric ﬁeld between 0 and 1.2 MV/m at frequency 0.034 Hz. The maximum power density reached 11.7 W/L at 0.1 Hz for temperatures between 100 and 190 o C and electric ﬁelds between 0.2 and 1.5 MV/m. Moreover, the dielectric constant and saturation polarization of PZN-5.5PT are reported for the ﬁrst time at 0.1 Hz for temperatures between 100 and 190 o C. Finally, the experimental results agree relatively well with predictions by a recently developed temperature-dependent property model already validated with PMN-32PT. Inter-sample variability and sample durability are also discussed.
Branes in the bulk of Anti-de Sitter space

We consider (3 + 1)-dimensional N=4 super Yang-Mills theory with a nonvanishing scalar Higgs vacuum expectation value, and compare this theory to AdS supergravity with branes in the bulk. We show that the one-loop effective potential for excitations of the Yang-Mills field agrees with the classical linearized potential for brane waves in the AdS picture in the limit of long wavelengths. This supports the idea that the AdS/CFT correspondance fits into string theory as expected from previous work.
Implications for Promoting Physical Literacy

This study considers the implications for teachers of physical education of adopting physical literacy as the focus of their work. These implications arise from the philosophical underpinning of the concept, from the definition of physical literacy and are in line with the mission of the International Physical Literacy Association. In the first section of this study, recommendations stemming from the philosophical roots of the concept will be outlined in brief. The other three sections will demonstrate how this philosophical basis and the definition of physical literacy should inform, first, lesson and unit content; second, teaching approaches; and, finally, curriculum planning. Unpacking the implications and what physical literacy looks like in practice is essential if teachers are to begin to incorporate physical literacy within their practice.
Heterogeneous Multiprocessor Synthesis under Performance and Reliability Constraints

Utilizing a heterogeneous multiprocessor system has become a popular design paradigm to build an embedded system at a cheap cost. A reliability issue, which is vulnerability to single event upsets (SEUs), has not been taken into account in a conventional IC (integrated circuit) design flow, while chip area, performance, and power consumption have been done. This paper presents a system design paradigm in which a heterogeneous multiprocessor system is synthesized and its chip area is minimized under real-time and reliability constraints. First we define an SEU vulnerability factor for computer systems so that we evaluate reliability of a task over various processor configurations. Next we build a mixed integer linear programming (MILP) model for minimizing chip area of a heterogeneous multiprocessor system under real-time and SEU vulnerability constraints. Finally, we show several experimental results on our synthesis approach. Experimental results show that our design paradigm has achieved automatic generation of cost-competitive and reliable heterogeneous multiprocessor systems.
Localization of Mobile Robot with RFID Technology and Stereo Vision

In this paper, a novel method of localization of mobile robot using RFID (radio frequency identification) technology and stereo vision is proposed as it is inexpensive, flexible and easy to use in practical environment. The proposed method is also helpful to improve dynamic obstacles recognition (such as person) and occlusion problem that are very difficult to solve. This is because the communication between ID reader and ID tags uses radio frequency. Because the radio frequency is not so stable, we can not know the accurate position of obstacle objects with ID even if tag reader detects the tag. In order to localize the ID tags, the Bayes rule was used to calculate probability where the ID tag exists after the tag reader detects a tag. This paper presents the proposed method and some experimental results
Wave scattering by many small bodies and applications

Wave scattering problem by many bodies is studied in the case when the bodies are small, ka ≪ 1, where a is the characteristic size of a body. The limiting case when a → 0 and the total number of the small bodies is M = O(a−(2 − κ)), where κ ∈ (0, 1) is a number, are studied.
Mutation of Ser172 in Yeast β Tubulin Induces Defects in Microtubule Dynamics and Cell Division

Ser172 of β tubulin is an important residue that is mutated in a human brain disease and phosphorylated by the cyclin-dependent kinase Cdk1 in mammalian cells. To examine the role of this residue, we used the yeast S. cerevisiae as a model and produced two different mutations (S172A and S172E) of the conserved Ser172 in the yeast β tubulin Tub2p. The two mutants showed impaired cell growth on benomyl-containing medium and at cold temperatures, altered microtubule (MT) dynamics, and altered nucleus positioning and segregation. When cytoplasmic MT effectors Dyn1p or Kar9p were deleted in S172A and S172E mutants, cells were viable but presented increased ploidy. Furthermore, the two β tubulin mutations exhibited synthetic lethal interactions with Bik1p, Bim1p or Kar3p, which are effectors of cytoplasmic and spindle MTs. In the absence of Mad2p-dependent spindle checkpoint, both mutations are deleterious. These findings show the importance of Ser172 for the correct function of both cytoplasmic and spindle MTs and for normal cell division.
Incremental ARA*: An Incremental Anytime Search Algorithm for Moving-Target Search

Moving-target search, where a hunter has to catch a moving target, is an important problem for video game developers. In our case, the hunter repeatedly moves towards the target and thus has to solve similar search problems repeatedly. We develop Incremental ARA* (I-ARA*) for this purpose, the first incremental anytime search algorithm for moving-target search in known terrain. We provide an error bound on the lengths of the paths found by I-ARA* and show experimentally in known four-neighbor gridworlds that I-ARA* can be used with smaller time limits between moves of the hunter than competing state-of-the-art moving-target search algorithms, namely repeated A*, G-FRA*, FRA*, and sometimes repeated ARA*. The hunter tends to make more moves with I-ARA* than repeated A*, G-FRA* or FRA*, which find shortest paths for the hunter, but fewer moves with I-ARA* than repeated ARA*, which finds suboptimal paths for the hunter like I-ARA*. Also, the error bounds on the lengths of the paths of the hunter tend to be smaller with I-ARA* than repeated ARA*.
Learners Are Losers: Natural Selection and Learning in the Evolution of Communication 1st Draft of Paper Submitted to the Proceedings of the 3rd Conference on the Evolution of Language

Computational simulations of natural selection for communicative success show that natural selection alone is capable of evolving optimal communication systems. Simulations of the interactions between natural selection and learning show that the biases of learners, when placed in the framework of iterated cultural transmission of communication systems, result in cultural selection of communication systems. This cultural selection is the determining factor in the development of communication systems in the simulated populations, with natural selection being relegated to a secondary role. This paper suggests that the role of cultural selection in the evolution of language should not be underestimated.
Investigating Factors Affecting Actual Usage Patterns of Mobile Data Services

Mobile Data Services (MDS) encompass all non-voice value-adding services accessible through mobile networks. The adoption and mass acceptance of MDS has been a subject of discourse among academics and practitioners alike, especially when taking into consideration the non-unitary path that MDS adoption patterns have followed in different parts of the world. In view of this observation, our study draws upon the Triandis theory of explaining human behaviour, which is adjusted to fit the particularities of MDS. We offer preliminary evidence for the legitimacy of introducing the Triandis model by analyzing empirical data collected through a largescale survey (N=365), which was conducted in Greece as part of the fifth Worldwide Mobile Data Services Survey. Results corroborate the model’s capacity to discriminate MDS users from non-users and open up research opportunities for further applying it in cross-cultural surveys of MDS adoption.
3D face recognition using pose invariant nose region detector

The 3D faces matching a challenging problem lying at the core of essential research areas in 3d face recognition systems and requires a crucial registration technique in order to achieve high matching rates. In this work, we address within a new framework, the keypoints detection problem and face registration in 3D partial facial scans (implies missing parts). The major contribution of this work is to improve robust matching approach against wide pose variations (up to 60° around Yaw axis) using nose region extracted. A construction of average nose model is conducted for alignment purpose. The facial representation is formulated using local shape descriptors extracted from surface keypoints of interest regions. Faces similarity is performed by applying first Iterative closest point (ICP) method between each nose subject in the gallery and the probe one, and thus takes the advantageous of minimum alignment error. Second, select minimum alignment errors that related to the first five subjects, and then manage a local shape descriptors comparison to determine matching score. The effectiveness of the proposed approach has been evaluated on GAVADB 3D face database which consists of both frontal and partial facial scans. The proposed approach achieved recognition rate about 94% and 90% for frontal and partial facial scans.
Complete Annotated Genome Sequences of Three Campylobacter jejuni Strains Isolated from Naturally Colonized Farm-Raised Chickens

ABSTRACT Campylobacter jejuni is a leading cause of bacterially derived foodborne illness. Human illness is commonly associated with the handling and consumption of contaminated poultry products. Three C. jejuni strains were isolated from cecal contents of three different naturally colonized farm-raised chickens. The complete genomes of these three isolates are presented here.
Automatic Identification of Samples in Hip Hop Music

Digital sampling can be defined as the use of a fragment of another artist’s recording in a new work, and is common practice in popular music production since the 1980’s. Knowledge on the origins of samples hold valuable musicological information, which could in turn be used to organise music collections. Yet the automatic recognition of samples has not been addressed in the music retrieval community. In this paper, we introduce the problem, situate it in the field of content-based music retrieval and present a first strategy. Evaluation confirms that our modified optimised fingerprinting approach is indeed a viable strategy.