Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influence of Picture Size on Recognition and Exploratory Behaviour in Raised-Line Drawings

We demonstrate the influence of picture size on haptic recognition and exploratory behaviour. The stimuli were raised-line drawings of everyday objects. Participants were instructed to think aloud during haptic exploration of the pictures. We measured the delay between initial correct speculation and final correct response. The results indicate that picture size influences accuracy but not response latency: large drawings are recognised more often but not faster. By analysing video recordings of the experiment we found that two-handed exploration increases when picture size increases and that, on average, 83% of the exploration time involves the use of two hands. The thinking-aloud data showed that the average time difference between the initial correct speculation and final correct response amounted to 23% of the total reaction time. We discuss our results with respect to the design of tactile aids and the ecological validity of single-finger exploration.
Free-form surface reconstruction from 3D multi-resolution data on spherical space

Over the last two decades, the 3D scanning technology has evolved steadily and facilitated the reconstruction of complex engineering parts. Using a 3D laser scanner, a physical object can be copied and stored in the form of a computer model. Based on the sampled points on the object's surface, called `points cloud', the object can be reconstructed via triangulation and surface meshing to a 3D solid model. There are various surface reconstruction methods exist. Unfortunately, most of those methods require the reconstruction process should always begin from the 2-dimensional Euclidean (ℝ2) space. This condition limits the ability for fast reconstruction. This paper introduces a new surface reconstruction approach. The proposed method transforms the vertices into spherical polar coordinates instead of Euclidean coordinates, and triangulation begins directly on the S space. Thus, the whole process works in a faster and more efficient fashion. The proposed algorithm has been implemented using C++ in combination with OpenGL and Qt 4.7 graphic libraries, and a test-bed is performed for verification.
On‐line qualitative market research: interviewing the world at a fingertip

This paper describes an experimental study into the validity and reliability of international qualitative market research through the Internet. Is it possible to generate valuable and valid qualitative market information from several countries, on the basis of on‐line research organised from one country? The results of face‐to‐face research and on‐line research in Singapore, the United Kingdom and Sweden are compared. The study clarifies the opportunities and limitations in using this type of market research in an international context.
Multiview Semi-Supervised Learning with Consensus

Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications. Semi-supervised learning aims to improve the performance of a classifier trained with limited number of labeled data by utilizing the unlabeled ones. This paper demonstrates a way to improve the transductive SVM, which is an existing semi-supervised learning algorithm, by employing a multiview learning paradigm. Multiview learning is based on the fact that for some problems, there may exist multiple perspectives, so called views, of each data sample. For example, in text classification, the typical view contains a large number of raw content features such as term frequency, while a second view may contain a small but highly informative number of domain specific features. We propose a novel two-view transductive SVM that takes advantage of both the abundant amount of unlabeled data and their multiple representations to improve classification result. The idea is straightforward: train a classifier on each of the two views of both labeled and unlabeled data, and impose a global constraint requiring each classifier to assign the same class label to each labeled and unlabeled sample. We also incorporate manifold regularization, a kind of graph-based semi-supervised learning method into our framework. The proposed two-view transductive SVM was evaluated on both synthetic and real-life data sets. Experimental results show that our algorithm performs up to 10 percent better than a single-view learning approach, especially when the amount of labeled data is small. The other advantage of our two-view semi-supervised learning approach is its significantly improved stability, which is especially useful when dealing with noisy data in real-world applications.
Inherited Transgene Expression of the uidA and bar Genes in Lilium longiflorum cv . ‘ Nellie White ’

The expression of two transgenes, bar and uidA, was studied in Lilium longiflorum cv. ‘Nellie White’ plants. ‘Nellie White’ had been transformed using the gene gun to bombard with pDM327 that contains the bar-uidA fusion gene under control of the CaMV 35S promoter. PCR analysis verified that eight T0 plant lines were probably not chimeric. Crosses using the eight T0 plants were made to L. longiflorum cvs. ‘Sakai’, ‘Yin tung’, ‘Snow Queen’, ‘White Europe’, and ‘Flavo’. The bar gene was transmitted to 15% of the 151 T1 seedlings analyzed with transmission success rates ranging from 0-100% depending on the T0 plant line. Only 13 of the 22 T1 seedlings with the bar gene also contained the uidA gene. Expression of the bar gene as determined by immunological detection of phosphinothricin acetyltransferase occurred in all six T1 plant lines that contained the bar gene. One T0 parent line had a notably high level of both bar and GUS expression, and this high level expression continued in the T1 plants. This study indicates that transmission of these transgenes to progeny occurred with low frequency, and expression of both transgenes occurred in the T1 generation. _____________________________________________________________________________________________________________
Effective use of sequence correlation and conservation in fold recognition.

Protein families are a rich source of information; sequence conservation and sequence correlation are two of the main properties that can be derived from the analysis of multiple sequence alignments. Sequence conservation is related to the direct evolutionary pressure to retain the chemical characteristics of some positions in order to maintain a given function. Sequence correlation is attributed to the small sequence adjustments needed to maintain protein stability against constant mutational drift. Here, we showed that sequence conservation and correlation were each frequently informative enough to detect incorrectly folded proteins. Furthermore, combining conservation, correlation, and polarity, we achieved an almost perfect discrimination between native and incorrectly folded proteins. Thus, we made use of this information for threading by evaluating the models suggested by a threading method according to the degree of proximity of the corresponding correlated, conserved, and apolar residues. The results showed that the fold recognition capacity of a given threading approach could be improved almost fourfold by selecting the alignments that score best under the three different sequence-based approaches.
THE DOCUMENTATION OF THE MEDIEVAL ENTRANCE OF THE RHODES FORTIFICATION COMPLEX

The documentation and reconstruction of cultural heritage monuments represents a permanent record of the real world object in its original position and has been greatly facilitated with the technological advancements in data collection and processing using digital photogrammetry and terrestrial laser scanning. This paper presents an example of a monumental complex requiring detailed documentation. The purpose is to examine the complete workflow of documenting the Sea Gate of the Rhodes medieval fortification complex. It presents interesting aspects such as complex spatiality, different building materials and architectural decay. A multisensor approach was considered as the most suitable for such a complex structure and therefore, surveying, photogrammetric and terrestrial laser scanning techniques were employed. The process to obtain the orthophotomosaic from merging the different data types is explained. Also, the photorealistic texturing of the object is investigated and the resulted orthophoto products are given.
Incidental Bequests: Bequest Motives and the Choice to Self-Insure Late-Life Risks

Despite facing significant uncertainty about how long they will live and how much costly health care they will require, few retirees buy life annuities or long-term care insurance. Low rates of long-term care insurance coverage are often interpreted as evidence against the importance of bequest motives since failing to buy insurance exposes bequests to significant risk. In this paper, however, I find that low rates of long-term care insurance coverage, especially in combination with the slow rate at which many retirees draw down their wealth, constitute evidence in favor of bequest motives. Retirees' saving and long-term care insurance choices are highly inconsistent with standard life cycle models in which people care only about their own consumption but match well models in which bequests are luxury goods. Bequest motives tend to reduce the value of insurance by reducing the opportunity cost of precautionary saving. Buying insurance reduces one's need to engage in precautionary saving, which is most valuable to individuals without bequest motives who wish to consume all of their wealth. The results suggest that bequest motives significantly increase saving and significantly decrease purchases of long-term care insurance and annuities.
Knowledge Tracing with Sequential Key-Value Memory Networks

Can machines trace human knowledge like humans? Knowledge tracing (KT) is a fundamental task in a wide range of applications in education, such as massive open online courses (MOOCs), intelligent tutoring systems, educational games, and learning management systems. It models dynamics in a student's knowledge states in relation to different learning concepts through their interactions with learning activities. Recently, several attempts have been made to use deep learning models for tackling the KT problem. Although these deep learning models have shown promising results, they have limitations: either lack the ability to go deeper to trace how specific concepts in a knowledge state are mastered by a student, or fail to capture long-term dependencies in an exercise sequence. In this paper, we address these limitations by proposing a novel deep learning model for knowledge tracing, namely Sequential Key-Value Memory Networks (SKVMN). This model unifies the strengths of recurrent modelling capacity and memory capacity of the existing deep learning KT models for modelling student learning. We have extensively evaluated our proposed model on five benchmark datasets. The experimental results show that (1) SKVMN outperforms the state-of-the-art KT models on all datasets, (2) SKVMN can better discover the correlation between latent concepts and questions, and (3) SKVMN can trace the knowledge state of students dynamics, and a leverage sequential dependencies in an exercise sequence for improved predication accuracy.
Ecological Conditions Affect Evolutionary Trajectory in a Predator-Prey System

The arms race of adaptation and counter adaptation in predator-prey interactions is a fascinating evolutionary dynamic with many consequences, including local adaptation and the promotion or maintenance of diversity. Although such antagonistic coevolution is suspected to be widespread in nature, experimental documentation of the process remains scant, and we have little understanding of the impact of ecological conditions. Here, we present evidence of predator-prey coevolution in a long-term experiment involving the predatory bacterium Bdellovibrio bacteriovorus and the prey Pseudomonas fluorescens, which has three morphs (SM, FS, and WS). Depending on experimentally applied disturbance regimes, the predator-prey system followed two distinct evolutionary trajectories, where the prey evolved to be either super-resistant to predation (SM morph) without counter-adaptation by the predator, or moderately resistant (FS morph), specialized to and coevolving with the predator. Although predation-resistant FS morphs suffer a cost of resistance, the evolution of extreme resistance to predation by the SM morph was apparently unconstrained by other traits (carrying capacity, growth rate). Thus we demonstrate empirically that ecological conditions can shape the evolutionary trajectory of a predator-prey system.
Space millimeter-wavelength very long baseline interferometry simulation software

The Strategic Priority Research Program on Space Science of the Chinese Academy of Sciences, “Space Millimeter-wavelength VLBI Array (SMVA)”, aims to build the first space millimeter-wavelength Very Long Baseline Interferometry (VLBI) array in the world. The SMVA, which has the ultra-high spatial resolution with a best of 20 micro-arcsecond that a ground-based VLBI array can not attain, is a powerful tool in imaging the hyperfine emission structure surrounding the black holes and other compact celestial objects. The simulations, such as UV coverage simulation, numerical simulation and image simulation, play a crucial role in all phases of the project, so a space VLBI simulation software was designed and implemented. This software has all the necessary and auxiliary simulation functions. And it has many advantages compared to other similar software packages: its interface is more friendly, the software package is robust and independent of operation system, the code is much easier to expand and scalable.
Testing the Limits LDT considerations when selecting laser optics

In addition to being monochromatic, directional, and coherent, laser light can emit high energies which can damage optics. Optics for use with lasers often contain dielectric reflective or anti-reflective (AR) coatings consisting of alternating layers of high and low indices which can easily be damaged by the high energy and power densities associated with laser light. Failures in the bulk optical substrate itself are rare. These coatings generally break down before optical materials do. Damage can manifest in many ways and may be stable or grow in number or size over time, with most failure mechanisms occurring within the coating or at the coating/ glass interface. These failure mechanisms can reduce the LDT of an optic by a factor of 100 or more depending on many variables. LDT testing certifies that optics and their coatings are capable of withstanding the extreme radiation and thermal energy densities of high power lasers without being damaged. Since the laser damage threshold of the optic is typically the limiting factor for the peak power that can be used in a laser system, a close look at LDT is critical before selecting the right components.
Impact of Security and Privacy Concerns among Medicare Patients on Sharing Health Information Online T

— The use of Internet for sharing health-related information has served to empower patients, improve self-health management knowledge and provide emotional support to patients. This paper investigates the factors that influence the use of Internet to share health-related information by patients covered under Medicare, especially, the impact of security and privacy concern. This paper adapts the Information System Success Model to health care context. The paper proposes that information quality, system security and privacy, physician patient communication, negative emotions and perceived health status are related to share health-related information online. We also examine the impact of education level on health information sharing online. The paper utilizes the 2012 Health Information National Trends Survey (HINTS) to draw conclusions.
Economic small-scale spatial dependencies and segregations : A multi-level analysis with indirect closure

Theories and approaches on regional economic development are characterised by an overwhelming plurality and a missing coherent unifying conceptual framework. Consequently, in politics and applied science regional economic development is often discussed in a simplified manner as judged by the following two criteria. Firstly, regions are conceptualised as separable entities, irrespective of scale and neglecting their potential dependence and interrelatedness. Secondly, the discussion often concentrates on one of the many theoretical concepts at a time.
Measuring students' thermal comfort and its impact on learning

Thermal comfort (TC) – how comfortable or satisfied a person is with the temperature of her/his surroundings – is one of the key factors influencing the indoor environmental quality of schools, libraries, and offices. We conducted an experiment to explore how TC can impact students’ learning. University students (n = 25) were randomly assigned to different temperature conditions in an office environment (25◦C → 30◦C, or 30◦C → 25◦C) that were implemented using a combination of heaters and air conditioners over a 1.25 hour session. The task of the participants was to learn from tutorial videos on three different topics, and a test was given after each tutorial. The results suggest that (1) changing the room temperature by a few degrees Celsius can stat. sig. impact students’ self-reported TC; (2) the relationship between TC and learning exhibited an inverted U-curve, i.e., should be neither too uncomfortable nor too comfortable. We also explored different computer vision and sensor-based approaches to measure students’ thermal comfort automatically. We found that (3) TC can be predicted automatically either from the room temperature or from an infra-red (IR) camera of the face; however, (4) TC prediction from a normal (visible-light) web camera is highly challenging, and only limited predictive power was found in the facial expression features to predict thermal comfort.
The Tail at Scale: How to Predict It?

Scale-out applications have emerged as the dominant Internet services today. A request in a scale-out workload generally involves task partitioning and merging with barrier synchronization, making it difficult to predict the request tail latency to meet stringent tail Service Level Objectives (SLOs). In this paper, we find that the request tail latency can be faithfully predicted, in the high load region, by a prediction model using only the mean and variance of the task response time as input. The prediction errors for the 99th percentile request latency are found to be consistently within 10% at the load of 90%for both model and measurement-based testing cases. Consequently, the work in this paper establishes an important link between the request tail SLOs and the low order task statistics in a high load region, where the resource provisioning is desired. Finally, we discuss how the prediction model may facilitate highly scalable, tail-constrained resource provisioning for scaleout workloads.
Emission-line activity in type 2 quasars from the Sloan Digital Sky Survey

We have compared the optical emission line ratios of type 2 quasars from Zakamska et al. with standard AGN photoionization model predictions, Seyfert 2s, HII galaxies, and narrow line FRII radio galaxies. Moderate to high ionization narrow line radio galaxies and Seyfert 2s are indistinguishable from type 2 quasars based on their optical line ratios. The standard AGN photoionization models, widely discussed for other type 2 AGNs, can reproduce successfully the loci and trends of type 2 quasars in some of the main diagnostic diagrams. These models are not exempt of problems and the discrepancies with the data are the same encountered for other type 2 AGNs. As for these, realistic models must take into account a range of cloud properties, as widely demonstrated in the literature. The Zakamska et al. sample is strongly biased towards objects with high line luminosities (L[OIII]>10 42 erg s 1 ). We have found that stellar photoionization is obvious in a fraction of objects (3 out of 50) which are characterized by low [OIII] luminosities compared with most type 2 quasars in the sample. We suggest that if the sample were expanded towards lower line luminosities (�10 40 42 erg s 1 ) stellar photoionization might be evident much more frequently. We explore an alternative scenario to pure AGN photoionization in which a varying contribution of stellar ionized gas contributes to the line flux es. Although the models presented here are rather simplistic and not strong quantitative resu lts can be extracted regarding the relative contribution of stellar vs. AGN photoionization, our results suggest that adding a varying contribution of stellar photoionized gas works in the right direction to solve most of the problems affecting the standard AGN photoionization models. The “temperature problem”, on the other hand remains.
Chemistry of the Fe2O3/BiFeO3 Interface in BiFeO3 Thin Film Heterostructures

We investigate the interfacial chemistry of secondary Fe2O3 phases formed in a BiFeO3 (BFO) layer in BFO/ La0.67Sr0. 33MnO3 (LSMO)/SrTiO3 (STO) heterostructures. A combination of high-resolution spherical aberration corrected scanning TEM and spectroscopy results, reveals that specific chemical and crystallographic similarities between Fe2O3 and BFO, enable the BFO layer to form a facile host for Fe2O3.
Quantization and Feedback of Spatial Covariance Matrix for Massive MIMO Systems With Cascaded Precoding

In this paper, we investigate the quantization and the feedback of downlink spatial covariance matrix for massive multiple-input multiple-output (MIMO) systems with cascaded precoding. Massive MIMO has gained a lot of attention recently because of its ability to significantly improve the network performance. To reduce the overhead of downlink channel estimation and uplink feedback in frequency-division duplex massive MIMO systems, cascaded precoding has been used to convert high-dimensional physical channels into low-dimensional effective channels. For the cascaded precoding, the inner precoder is determined by the downlink spatial covariance matrix, which is unknown in the base station (BS). To address this issue, we propose a spatial spectrum-based approach for the quantization and the feedback of the spatial covariance matrix. In this manner, the BS can obtain partial information on the downlink spatial covariance matrix. Our result shows that the inner precoder based on the proposed approach can be viewed as modulated discrete prolate spheroidal sequences and thus achieves much smaller spatial leakage than the traditional discrete Fourier transform submatrix-based precoding. Practical issues for the application of the proposed approach are also addressed in this paper.
Riemannian Metric Learning for Symmetric Positive Definite Matrices

Over the past few years, symmetric positive definite (SPD) matrices have been receiving considerable attention from computer vision community. Though various distance measures have been proposed in the past for comparing SPD matrices, the two most widely-used measures are affine-invariant distance and log-Euclidean distance. This is because these two measures are true geodesic distances induced by Riemannian geometry. In this work, we focus on the log-Euclidean Riemannian geometry and propose a data-driven approach for learning Riemannian metrics/geodesic distances for SPD matrices. We show that the geodesic distance learned using the proposed approach performs better than various existing distance measures when evaluated on face matching and clustering tasks.