The emotional influences on vendors' residential price perception (The price virus)

The aim of this study is to explore what causes the gap between the asking price and the buying price of houses in Australia. According to 2012 statistics provided by Real Estate Institute of Western Australia, home sales records shows approximately 70 per cent of the homes listed for sale did not achieve their asking price. The research hypothesis adopted in this thesis is that this gap is caused by vendors’ emotional attachment to the home, which in turn influences an unrealistic price. The proposal of this unrealistic price is the focus of the research investigation. The objective is to explore the hypothesis that home vendors are socially and emotionally conditioned to perceive their home to be worth more than its actual market value. The effect of irrational behaviour influenced by vendors’ emotions is deemed to be linked to their unrealistic perception of price. Home ownership is a key sector of the property industry, now Australia’s biggest industry, larger even than mining. The industry contributed $185.5 billion to the economy, equivalent to 11.5 per cent of GDP in the last financial year. The latest data shows that Australian homes are currently worth$5.0 to $5.5 trillion dollars. Depending on the source, the estimate for number of residential properties sold each year in Australia is between 400,000 and 600,000. If indeed unrealistic price perception is influenced by human emotions in an industry as big as this, then there are cogent reasons for exploring this phenomenon. This study employed a questionnaire survey relating to the research question. The survey was hosted on Fairfax Media’s websites and received responses from all over Australia as well as 11 other countries. The participants in the survey were mainly homeowners who had sold or had attempted to sell their homes, which enabled this study to explore the emotional behaviour underlying how homeowners arrive at a value for their homes. Five emotions were assessed as key variables that affect price perception across the emotional stages in decision-making. The results suggests that the strongest factor influencing unrealistic price perception is greed, followed by vendors’ expectation that buyers will negotiate, a lack of trust in the real estate agent and pride in ownership. The findings reveal that the feeling of uniqueness of the home also influences this unrealistic price perception. It is hoped that this study will contribute to the real estate industry by providing a better insight into why vendors tend to overprice their homes. The results of this research could therefore provide an improved understanding of home vendors’ behaviour, and offer an important insight into the implications of emotional attachment in relation to decision-making and the perceived value of the home

Rapid deployment of DNNs for edge computing via structured pruning at initialization

Funding: This research is funded by Rakuten Mobile, Inc., Japan.Edge machine learning (ML) enables localized processing of data on devices and is underpinned by deep neural networks (DNNs). However, DNNs cannot be easily run on devices due to their substantial computing, memory and energy requirements for delivering performance that is comparable to cloud-based ML. Therefore, model compression techniques, such as pruning, have been considered. Existing pruning methods are problematic for edge ML since they: (1) Create compressed models that have limited runtime performance benefits (using unstructured pruning) or compromise the final model accuracy (using structured pruning), and (2) Require substantial compute resources and time for identifying a suitable compressed DNN model (using neural architecture search). In this paper, we explore a new avenue, referred to as Pruning-at-Initialization (PaI), using structured pruning to mitigate the above problems. We develop Reconvene, a system for rapidly generating pruned models suited for edge deployments using structured PaI. Reconvene systematically identifies and prunes DNN convolution layers that are least sensitive to structured pruning. Reconvene rapidly creates pruned DNNs within seconds that are up to 16.21× smaller and 2× faster while maintaining the same accuracy as an unstructured PaI counterpart

Acoustic Phased Array Quantification of Quiet Technology Demonstrator 3 Advanced Inlet Liner Noise Component

Acoustic phased array flyover noise measurements were acquired as part of the Boeing 737 MAX-7 NASA Advanced Inlet Liner segment of the Quiet Technology Demonstrator 3 (QTD3) flight test program. This paper reports on the processes used for separating and quantifying the engine inlet, exhaust and airframe noise source components and provides sample phased array-based comparisons of the component noise source levels associated with the inlet liner treatment configurations. Full scale flyover noise testing of NASA advanced inlet liners was conducted as part of the Quiet Technology Demonstrator 3 flight test program in July and August of 2018. Details on the inlet designs and testing are provided in the companion paper of Reference 1. The present paper provides supplemental details relating to the acoustic phased array portion of the analyses provided in Ref. 1. In brief, the test article was a Boeing 737MAX-7 aircraft with a modified right hand (starboard side) engine inlet, which consisted of either a production inlet liner, a NASA designed inlet liner or a simulated hard wall configuration (accomplished by applying speed tape over the inlet acoustic treatment areas). In all three configurations, the engine forward fan case acoustic panel was replaced with a unperforated (hardwall) panel. No other modifications to any other acoustic treatment areas were made. The left hand (port side) engine was a production engine and was flown at idle thrust for all measurements in order to isolate the effects of the inlet liners to the right hand engine. As described in Ref. 1, the NASA inlet treatment consists of laterally cut slots (cut perpendicular to the flow direction) which are designed to reduce excrescence drag while maintaining or exceeding the liner acoustic noise reduction capabilities. The NASA inlet liner consists of a Multi-Degree of Freedom (MDOF) design with two breathable septum layers inserted into each honeycomb cell [1]. The aircraft noise measurements were acquired for both takeoff (flaps 1 setting, gear up) and approach (flaps 30 gear up and gear down) configurations. The inlet and flight test configurations are summarized in Table 1. Table 1: Inlet Treatment and Flight Configurations Inlet Forward Fan Case Aircraft Production Hardwall Flaps 1, gear up; flaps 30 gear up; flaps 30 gear down NASA Hardwall Flaps 1, gear up; flaps 30 gear up; flaps 30 gear down Hardwall Hardwall Flaps 1, gear up; flaps 30 gear up; flaps 30 gear down III.Test Description and Hardware The flight testing was conducted at the Grant County airport in Moses Lake, WA, between 27 July and 6 August 2018. The noise measurement instrumentation included 8 flush dish microphones arranged in a noise certification configuration as well as an 840 microphone phased array. The flush dish microphones were used to quantify the levels and differences in levels between the various inlet treatments. The phased array was used to separate and quantify the narrowband (tonal) and broadband noise component levels from the engine inlet/exhaust and from the airframe. Phased array extraction of the broadband component was critical to this study because it allowed for the separation of the inlet component from the total airplane level noise even when it was significantly below the total level. Figure 1 provides an overview of the phased array microphone layout as well as a detailed image of an individual phased array microphone mounted in a plate holder (the microphone sensor is the dot in the center of the plate). The ground plane ensemble array microphones (referred to as ensemble array in this paper) were mounted in plates with flower petal edges designed to minimize edge scattering effects. Fig. 1 Flyover test microphone layout. The phased array configuration was the result of a progressive development of concepts originally implemented in Ref. 2 and refined over the following years, consisting namely of multiple multi-arm logarithmic spiral subarrays designed to cover overlapping frequency ranges and optimized for various aircraft emission angles. For the present case, the signals from all 840 microphones were acquired on a single system. The 840 microphones were parsed into 11 primary subarray sets spanning from smallest to largest aperture size and labeled accordingly as a, b, , k, where a corresponds to the smallest fielded subarray and k corresponds to the largest aperture subarray. The apertures ranged from approximately 10 ft to 427 ft in size (in the flight direction) with the subarrays consisting of between 215 and 312 microphones. Figure 2 shows three such subarrays, k, h and a. As done in Ref. 2, microphones were shared between subarrays in order to reduce total channel count. Fig. 2 Sample subarray sizes (20 from overhead refer to Figure 3a discussion). In addition to the above, each of the 11 primary subarray sets consisted of four subarrays optimized to provide near equivalent array spatial resolution in both the flight and lateral directions within 30 degrees of overhead (i.e., airplane directly above the center of the array), namely, at angles of 0, 10, 20 and 30 degrees relative to overhead where angle is defined as shown in Figure 3a. This allowed for optimized aircraft noise measurements from 60 to 120 degree emission angle.6 An example of this pletharray design is shown in Figure 3b for the k subarray. When the aircraft is at overhead, the microphones indicated by the blue markers are used for beamforming. When the aircraft is at angles 10 degrees from overhead, both the blue and red colored microphones are used, and so on for the 20 and 30 degree aircraft locations. See Ref. 3 for extensive details on pletharray design for aeroacoustic phased array testing. 6 In the discussions that follow, emission angle values are used. These are the angles at the time sound is emitted relative to the engine axis and are calculated based on flight path angle, body aircraft body angle with respect to the relative wind direction, and engine axis angle relative to aircraft body angle

H0LiCOW III. Quantifying the effect of mass along the line of sight to the gravitational lens HE 0435-1223 through weighted galaxy counts

Based on spectroscopy and multiband wide-field observations of the gravitationally lensed quasar HE 0435-1223, we determine the probability distribution function of the external convergence $\kappa_\mathrm{ext}$ for this system. We measure the under/overdensity of the line of sight towards the lens system and compare it to the average line of sight throughout the universe, determined by using the CFHTLenS as a control field. Aiming to constrain $\kappa_\mathrm{ext}$ as tightly as possible, we determine under/overdensities using various combinations of relevant informative weighing schemes for the galaxy counts, such as projected distance to the lens, redshift, and stellar mass. We then convert the measured under/overdensities into a $\kappa_\mathrm{ext}$ distribution, using ray-tracing through the Millennium Simulation. We explore several limiting magnitudes and apertures, and account for systematic and statistical uncertainties relevant to the quality of the observational data, which we further test through simulations. Our most robust estimate of $\kappa_\mathrm{ext}$ has a median value $\kappa^\mathrm{med}_\mathrm{ext} = 0.004$ and a standard deviation of $\sigma_\kappa = 0.025$. The measured $\sigma_\kappa$ corresponds to $2.5\%$ uncertainty on the time delay distance, and hence the Hubble constant $H_0$ inference from this system. The median $\kappa^\mathrm{med}_\mathrm{ext}$ value is robust to $\sim0.005$ (i.e. $\sim0.5\%$ on $H_0$) regardless of the adopted aperture radius, limiting magnitude and weighting scheme, as long as the latter incorporates galaxy number counts, the projected distance to the main lens, and a prior on the external shear obtained from mass modeling. The availability of a well-constrained $\kappa_\mathrm{ext}$ makes \hequad\ a valuable system for measuring cosmological parameters using strong gravitational lens time delays.Comment: 24 pages, 17 figures, 6 tables. Submitted to MNRA

Situación actual de la mediana mineria en el Ecuador. cambio de sistema de producción en la mina bonanza

DETALLA TRABAJO REALIZADO EN LA COMPAÑIA EXPOBONANZA S.A. Y EL PROBLEMA QUE SE PLANTEA ES LA PUESTA EN FUNCIONAMIENTO DE UN NUEVO SISTEMA DE PROCESAMINETO DEL MATERIAL QUE SALE DE LA MINA, EN VISTA DE QUE LA CAPACIDAD DEL MOLINO SE VE AMPLIAMENTE SUPERADA Y SE TIENE QUE ALQUILAR OTROS MOLINOS Y ES LO QUE ELEVA SUSTANCIALMENTE LOS COSTOS.Y PARA ELLO SE HA TRATADO DE LLEVAR UN DISEÑO DE INVESTIGACION DONDE SE TRATA DE ANALIZAR Y DEMOSTRAR QUE EL PROBLEMA ES FACTIBLE Y QUE ESTARIA LIMITADO SOLAMENTE POR RESTRICCIONES EN LA INVERSION Y LA BUSQUEDA DEL EQUIPO PESADO. SUS VENTAJAS SERIAN TENER CAPACIDAD DE PROCESAR MATERIAL DE MANERA CONTINUA , LA PRODUCCION SE DETENDRIA UNICAMENTE CUANDO TOQUE L

An Improved Deep Forest Model for Predicting Self-Interacting Proteins From Protein Sequence Using Wavelet Transformation

Self-interacting proteins (SIPs), whose more than two identities can interact with each other, play significant roles in the understanding of cellular process and cell functions. Although a number of experimental methods have been designed to detect the SIPs, they remain to be extremely time-consuming, expensive, and challenging even nowadays. Therefore, there is an urgent need to develop the computational methods for predicting SIPs. In this study, we propose a deep forest based predictor for accurate prediction of SIPs using protein sequence information. More specifically, a novel feature representation method, which integrate position-specific scoring matrix (PSSM) with wavelet transform, is introduced. To evaluate the performance of the proposed method, cross-validation tests are performed on two widely used benchmark datasets. The experimental results show that the proposed model achieved high accuracies of 95.43 and 93.65% on human and yeast datasets, respectively. The AUC value for evaluating the performance of the proposed method was also reported. The AUC value for yeast and human datasets are 0.9203 and 0.9586, respectively. To further show the advantage of the proposed method, it is compared with several existing methods. The results demonstrate that the proposed model is better than other SIPs prediction methods. This work can offer an effective architecture to biologists in detecting new SIPs

Reduced RET expression in gut tissue of individuals carrying risk alleles of Hirschsprung's disease

Receptor tyrosine kinase (RET) single nucleotide polymorphisms (SNPs) are associated with the Hirschsprung's disease (HSCR). We investigated whether the amount of RET expressed in the ganglionic gut of human was dependent on the genotype of three regulatory SNPs (-5G>A rs10900296 and -1A>C rs10900297 in the promoter, and C>T rs2435357 in intron 1). We examined the effects of three regulatory SNPs on the RET gene expression in 67 human ganglionic gut tissues using quantitative real-time PCR. Also, 315 Chinese HSCR patients and 325 ethnically matched controls were genotyped for the three SNPs by polymerase chain reaction (PCR) and direct sequencing. The expression of RET mRNA in human gut tissue did indeed correlate with the genotypes of the individuals. The lowest RET expression was found for those individuals homozygous for the three risk alleles (A-C-T/A-C-T), and the highest for those homozygous for the 'wild-type' counterpart (G-A-C/G-A-C), with expression values ranging from 218.32±125.69 (mean ± SE) in tissues from individuals carrying G-A-C/G-A-C to 31.42±8.42 for individuals carrying A-C-T/A-C-T (P 5 0.018). As expected, alleles -5A, -1C and intron 1 T were associated with HSCR (P 5 5.94 × 10-31, 3.12 3 10-24 and 5.94 × 10-37, respectively) as was the haplotype encompassing the three associated alleles (A-C-T) when compared with the wild-type counterpart G-A-C (χ2 5 155.29, P « 0.0001). To our knowledge, this is the first RET expression genotype-phenotype correlation study conducted on human subjects to indicate common genetic variants in the regulatory region of RET may play a role in mediating susceptibility to HSCR, by conferring a significant reduction of the RET expression. © The Author 2010. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected]

H0LiCOW XII. Lens mass model of WFI2033-4723 and blind measurement of its time-delay distance and H0H_0

We present the lens mass model of the quadruply-imaged gravitationally lensed quasar WFI2033-4723, and perform a blind cosmographical analysis based on this system. Our analysis combines (1) time-delay measurements from 14 years of data obtained by the COSmological MOnitoring of GRAvItational Lenses (COSMOGRAIL) collaboration, (2) high-resolution $\textit{Hubble Space Telescope}$ imaging, (3) a measurement of the velocity dispersion of the lens galaxy based on ESO-MUSE data, and (4) multi-band, wide-field imaging and spectroscopy characterizing the lens environment. We account for all known sources of systematics, including the influence of nearby perturbers and complex line-of-sight structure, as well as the parametrization of the light and mass profiles of the lensing galaxy. After unblinding, we determine the effective time-delay distance to be $4784_{-248}^{+399}~\mathrm{Mpc}$, an average precision of $6.6\%$. This translates to a Hubble constant $H_{0} = 71.6_{-4.9}^{+3.8}~\mathrm{km~s^{-1}~Mpc^{-1}}$, assuming a flat $\Lambda$CDM cosmology with a uniform prior on $\Omega_\mathrm{m}$ in the range [0.05, 0.5]. This work is part of the $H_0$ Lenses in COSMOGRAIL's Wellspring (H0LiCOW) collaboration, and the full time-delay cosmography results from a total of six strongly lensed systems are presented in a companion paper (H0LiCOW XIII).Comment: Version accepted by MNRAS. 29 pages including appendix, 17 figures, 6 tables. arXiv admin note: text overlap with arXiv:1607.0140