Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward a common ground: practice and research in HCI

A popular definition of HCI as a discipline (ACM SIGCHI Curricula for Human-Computer Interaction, 1996) reflects a duality: HCI is a discipline concerned on the one hand with practice, and on the other, with the research into phenomena associated with this practice. But if one would ask practitioners engaged in the design, evaluation , and/or implementation of interactive computing systems if they benefit from research into phenomena associated with these systems, many would probably agree with the following quote: " There are very few, if any, research articles published in scientific and academic journals that can be utilized effectively in the practice of HCI design " (anonymous practitioner, present). Moreover, if one asked researchers engaged in studying behavioral, social, organizational, and other phenomena associated with interactive computing systems whether they are concerned with the actual design, evaluation, and/or implementation of such systems, many would probably indicate that there is not much linkage between their research and the actual practice in HCI. Such responses represent a gap between the practice and research sides of HCI. Does such a gap represent a problem? Yes. Imagine you are a practitioner asked to examine an application. If you find it ineffective , you'll need to propose what needs to be redesigned in the user interface to improve its effectiveness. You are then faced with the question of why it is ineffective. In other words, you have a question that requires relevant research findings that can inform you of why or why not things work in your application. Such understanding can drive better design decisions. The need for research, what kind of research, where to locate that research, and how to use it all depends on how HCI research is defined and how the research question is formulated. In this essay I delineate different levels of research in HCI, and given such taxonomy, how research can inform practice. I propose adopting the following definition of research: any systematic endeavor to find an answer to a practical or theoretical question. Within such a definition, usability tests can be considered a type of research. A common strategy in a case similar to that mentioned above would be to employ some form of a usability test. While usability tests are very good at determining if a product is effective or efficient, or whether it provides appropriate user experience, usability tests are not very good at offering an explanation …
Cellular and Regional Distribution of the Glutamate Transporter GLAST in the CNS of Rats: Nonradioactive In SituHybridization and Comparative Immunocytochemistry

Oligonucleotide and cRNA probes were used for nonradioactivein situ hybridizations carried out to identify the neural cell types expressing the glutamate transporter GLAST mRNA in the rat CNS. Additionally, the regional distribution of GLAST mRNA-expressing cells was studied, and the results were complemented by immunocytochemical investigations using an antibody against a synthetic GLAST peptide. The findings documented that GLAST is expressed by Bergmann glia and by astrocytes throughout the CNS. The glial localization of GLAST mRNA was verified unequivocally by double-labeling with an astrocytic marker protein. Additionally, GLAST mRNA reactivity and GLAST immunoreactivity were found in ependymal cells. In other neural cell types of the CNS, GLAST expression was not detectable. A high level of astrocytic immunolabeling was observed in the entire gray matter of the brain, with variations in intensity in different regions. Those brain areas that are known to possess high glutamatergic activity and astrocytic glutamate metabolism stained intensely for both GLAST mRNA and GLAST protein. The latter observation suggests that the GLAST glutamate transporter participates in the regulation of extracellular glutamate concentrations, especially in brain areas receiving an intense glutamatergic innervation.
Moving Right Along: A Computational Model of Metaphoric Reasoning about Events

This paper describes the results of an implemented computational model that cashes out the belief that reasoning about abstract events and actions relies on metaphoric projections of embodied primitives. The specific task addressed is the interpretation of simple causal narratives taken from newspaper articles in the domains of Politics and Economics. When presented with a surface-parsed version of these narratives as input, the system described is able to generate commonsense inferences consistent with the input.
Design of unimodular sequences using generalized receivers

This paper reviews recent advances in designing unimodular sequences with good auto/cross correlation properties along with a new approach that emphasizes on independent receiver design. The general problem is to design single or multiple sequences with constant modulus in the timedomain such that their respective matched filter outputs ideally resemble delta functions and the cross-matched filter outputs are zeros. In this context CAN (cyclic-algorithm new) and WeCAN (Weighted CAN) have been proposed for designing such sequences with good auto-cross correlation properties. In this paper, the equivalence of the CAN algorithms and the classic Gerchberg-Saxton (GS) algorithm involving the sequential magnitude substitution operations in the time and frequency domain is demonstrated. The design of unimodular sequences is further generalized here by considering the receiver design to be more general than the respective matched input sequences. The receiver design is carried out by taking care of the desired output requirements and the freedom present at the input can be used to further minimize the output side-lobe level.
Immunogenicity and Efficacy of a Commercial Feline Leukemia Virus Vaccine

Twenty young adult specific pathogen‐free cats were randomly divided into two groups of 10 animals each. One group was vaccinated with two doses of feline leukemia virus vaccine according to the manufacturer's recommendations. All 20 cats were challenge exposed oronasally (4 times over a 1‐week period), beginning 3 weeks after immunization, with a virulent subgroup A strain of FeLV (CT600‐FeLV). The severity of the FeLV infection was enhanced by treating the cats with methylprednisolone acetate at the time of the last FeLV exposure. Ten of 10nonvaccinated cats became persistently viremic compared with 0/10 of the vaccinates. ELISA antibodies to whole FeLV were present at high concentrations after immunization in all of the vaccinated cats, and there was no observable anamnestic antibody response after challenge exposure. ELISA antibodies to whole FeLV appeared at low concentrations in the serum of nonvaccinated cats after infection but disappeared as the viremia became permanently established. Virus neutralizing antibodies were detected in 3/10 vaccinates and 0/10 nonvaccinates immediately before FeLV challenge exposure, and in 8/10 vaccinates and 1/10 nonvaccinates 5 weeks later. Although vaccination did not consistently evoke virus neutralizing antibodies, it appeared to immunologically prime cats for a virus‐neutralizing antibody response after infection. Active FeLV infection was detected in bone marrow cells taken 14 weeks after infection from 10/10 nonvaccinates and 0/10 vaccinates. Latent FeLV infection was not detected in bone marrow cells from any of the vaccinated cats 14 weeks after challenge exposure.
Versatile Construction of Single-Tailed Giant Surfactants with Hydrophobic Poly(ε-caprolactone) Tail and Hydrophilic POSS Head

Giant surfactants refer to a new kind of amphiphile by incorporating functional molecular nanoparticles with polymer tails. As a size-amplified counterpart of small-molecule surfactants, they serve to bridge the gap between small-molecule surfactants and amphiphilic block copolymers. This work reports the design and synthesis of single-tailed giant surfactants carrying a hydrophobic poly(ε-caprolactone) (PCL) as the tail and a hydrophilic cage-like polyhedral oligomeric silsesquioxane (POSS) nanoparticle as the head. The modular synthetic strategy features an efficient “growing-from” and “click-modification” approach. Starting from a monohydroxyl and heptavinyl substituted POSS (VPOSS-OH), a PCL chain with controlled molecular weight and narrow polydispersity was first grown by the ring-opening polymerization (ROP) of ε-CL under the catalysis of stannous octoate, leading to a PCL chain end-capped with heptavinyl substituted POSS (VPOSS-PCL). To endow the POSS head with adjustable polarity and functionality, three kinds of hydrophilic groups, including hydroxyl groups, carboxylic acids, and amine groups, were installed to the periphery of POSS molecule by a high-efficiency thiol-ene “click” reaction. The compounds were fully characterized by NMR, gel permeation chromatography (GPC), MALDI-TOF mass spectrometry, and TGA analysis. In addition, the preliminary self-assembly study of these giant surfactants was also investigated by TEM and dynamic laser light scattering (DLS), which indicated that they can form spherical nanoparticles with different diameters in aqueous solution. This work affords a straightforward and versatile way for synthesizing single-tailed giant surfactants with diverse head surface functionalities.
An examination of recovery time of an integrated limiter/LNA

GaAs monolithic microwave integrated circuits (MMICs) are widely used in commercial and military microwave systems. Due to the fine geometry used in MMIC transistors, these circuits are susceptible to damage from high-power spurious electromagnetic (EM) radiation, either from microwave transmitters or nuclear electromagnetic pulse. Especially, low noise amplifiers (LNAs) in the front-end of microwave systems need high power protection because these amplifiers can sustain only low input power levels in the range of 10-20 dBm continuous wave (CW). To protect these circuits and maintain low noise figure, a high power and low loss limiter is required. The purpose of this application note is to document the test methodology employed and test results achieved measuring the small-signal gain recovery time of a balanced LNA with an integrated Schottky diode limiter and high power load.
Robust channel estimator for MIMO-OFDM systems with FPGA implementation

Multiple-input multiple- output (MIMO) and orthogonal frequency division multiplexing (OFDM) are two key techniques for broadband wireless mobile communications. In order to provide accurate channel state information (CSI) to support MIMO-OFDM transmission in doubly-selective fading channels, we propose the robust channel estimator based on two-dimensional enhanced discrete-time Fourier transform interpolation (2D-EDFTI), which needs no channel statistics and can improve the channel estimation accuracy significantly. In order to validate its performance in practice, we implement it into our real-time FPGA testbed of 4-by-4 MIMO-OFDM. Also, channel estimator based on two-dimensional linear interpolation (2D-LI) is implemented for comparison. Experiments demonstrate that our proposed 2D-EDFTI channel estimator is robust to doubly-selective fading channels and its performance is always superior to 2D-LI channel estimator. Therefore, MIMO-OFDM transmission by spatial multiplexing with different kinds of MIMO detector, i.e., zero-forcing (ZF) and dynamic layer-ordering m-path detection (DOM), can be well supported.
A Method for Stock Trading Strategy Combining Technical Analysis and Particle Swarm Optimization

Accurate stock trend prediction is a difficult job because various intricate and complex factors affect changes in price, trading volume and trends of a stock market. On a macro scale, the factors could be the overall global economic environment, industry trends, individual economic environment (business operation and competitors’ development), the amount of floating capital in the market, etc. Likewise, on a micro scale, the factors could be investors’ decision-making behaviors, their psychology, the weather, and so on. How to apply these real trading information from the stock market to establish and construct an accurate forecasting model to identify correct trading signals and noises is a mammoth challenge. This research utilizes the Particle Swarm Optimization (PSO) Method and combines the Technical Analysis tools Simple Moving Average(SMA) and the principles of crossover trading decisions to establish a stock trend prediction model and a trading decision model. The target identified for this research is Taiwan Stock Market and the prediction model is compared with the buyand-hold strategy. The experimental results indicate that most of the stocks in the forecasting model strategy perform better than in the buy-and-hold strategy and thus, this forecasting model strategy is a valid investment strategy.
Measuring the perception of light inconsistencies

In this paper we explore the ability of the human visual system to detect inconsistencies in the illumination of objects in images. We specifically focus on objects being lit from different angles as the rest of the image. We present the results of three different tests, two with synthetic objects and a third one with digitally manipulated real images. Our results seem to agree with previous publications exploring the topic, but we extend them by providing quantifiable data which in turn suggest approximate perceptual thresholds. Given that light detection in single images is an ill-posed problem, these thresholds can provide valid error limits to related algorithms in different contexts, such as compositing or augmented reality.
Capacity-achieving distributions of impulsive ambient noise channels

This paper studies the characterization of the optimal input for impulsive ambient noise channels under average power constraint. Our focus is on the two-term Gaussian mixture complex noise model, which has been widely used to model impulsive noise arising in various communication channels. We first demonstrate that there exists a unique input distribution that achieves the channel capacity and the capacity-achieving input distribution has a uniformly distributed phase. By examining the Kuhn-Tucker conditions (KTC), we further show that if the optimal amplitude input distribution contains an infinite number of mass points on a bounded interval, the channel output must be Gaussian distributed. However, by using Bernstein's theorem to examine the completely monotonic condition, it is shown that the assumption of a Gaussian distributed output is not valid. As a result, there is always a finite number of mass points on any bounded interval in the optimal amplitude distribution. In addition, by applying a novel bounding technique on the KTC and using the Envelop Theorem, we demonstrate that the optimal amplitude distribution cannot have an infinite number of mass points. That gives us a unique solution of the optimal input having discrete amplitude with a finite number of mass points. Given such interesting results, we also develop an efficient way to compute the discrete optimal input and the corresponding capacity.
Investigating links between probation enforcement and reconviction Home Office online report 41/03

These findings aim to examine how different enforcement strategies affect the reconviction rates of offenders under probation supervision in the community. The main purpose was to explore how reconviction rates vary amongst areas with different patterns of enforcement. For this purpose, data were gathered on 882 offenders drawn from eleven probation areas, five of which had harsher than average responses to non-compliance and six of which were more lenient than average. The findings also explored how reconviction rates vary between offenders exposed to different enforcement strategies.
Integrated VCSEL Trap Arrays for Microfluidic Particle Separation and Sorting

Microfluidic systems have evolved into an important tool in cell analysis, especially on the single-cell level, where conventional flow cytometry techniques are no longer convenient. Here, high throughput operation is not essential but small sample volumes and a possible integration of serial analysis steps. A basic analysis process is the sorting and separation of particles, where the use of optical forces has gained increasing interest owing to their independence on electrical charges and the compatibility to biological material [1]–[4]. To avoid the bulky and expensive optics commonly used to create optical traps, different approaches have been published which enable an integration into the microfluidic system [5, 6]. Here, the use of vertical-cavity surface-emitting lasers (VCSELs) offers not only small dimensions, high beam quality and low costs, but also a direct transfer of the sorting scheme presented in [1] and [2] into the microfluidic system. The concept is based on tilted arrays of optical traps, where the drag caused by the fluid medium is of the same size as the trapping force of each trap. Therefore, the traps will not fix a particle completely, but only deflect it from its initial flow direction as it passes by. So, while passing the traps, the particle follows the tilt of the array as it moves from the domain of one trap to the next. In this article we present a new approach based on one-dimensional VCSEL arrays directly integrated beneath microchannels to realize this sorting scheme in compact devices [7].
Improving robustness and fairness on BitTorrent-Like P2P systems

Recent studies have shown that BitTorrent, one of the most popular peer-to-peer file-sharing systems, is confronted with two serious problems: robustness and fairness. In this paper, a partially decentralized trust management system for BitTorrent is presented to deal with the two problems. By extending and modifying the functionality of the Tracker in BitTorrent swarm, the extended Tracker serves as an authoritative trust computation agent (TCA) to calculate and disseminate global trust values for all peers, which complement with local trust values to identify and isolate malicious and selfish peers. Simulations show that the proposed trust management system significantly decreases the impact of malicious peers on the swarm performance, and also achieves a much fairer block allocation among peers in heterogeneous scenarios.
An efficient chain code based face identification system for biometrics

Presently, face detection has become an important aspect in biometric identification systems. Among many other facial features like position of nose, lips, eye, face contour acts as an important classifier in face detection. It requires huge memory space to store reference images of face in face recognition. Thus memory space can be optimized if the contour of a face is stored instead of complete image of the face. In this paper we propose a face identification methodology where contour of a face is encoded by chain codes and the database is formed and an algorithm has been developed for face recognition. Further, a complexity analysis has been done in both time and space aspects, and have been found more efficient than conventional template matching methods in face detection.
The Role of Teacher in Medical Student Self-Directed Learning Process

Self-directed learning (SDL) is essential in medical education. The rapid development of medical science and the expansion of health problems need a physician who can meet that challenges. A physician must have lifelong learning ability. SDL is one of the important requirements for lifelong learning ability. In SDL, learners are the controller of learning and learners have the freedom to learn according to their needs. Therefore, it is necessary to explore the role of the teacher in the SDL process, particularly in medical education. This study used a qualitative exploratory design. Twelve teachers and 23 medical students were selected by purposive sampling. There were seven themes that emerged from the analysis. The role of teacher in the SDL process includes: (1) Competent; (2) Concern; (3) Creative; (4) Facilitator; (5) Motivator; (6) Partners; and (7) Role Model.
Direct finite-element solver of linear complexity for system-level signal and power integrity co-analysis

In this paper, we develop a fast direct finite-element solver of linear (optimal) complexity for solving large-scale system-level signal and power integrity problems. The proposed direct solver has successfully analyzed an industry product-level full-package problem and correlated with measurements in time domain. The finite-element matrix of over 15.8 million unknowns resulting from the analysis of the package, including both signal lines and power delivery structures, is directly solved in less than 1.6 hours on a single core running at 3 GHz. Comparisons with the finite element methods that employ the most advanced direct sparse solvers have demonstrated the clear advantages of the proposed high-capacity linear-complexity direct solver.
Desiderata for exploratory search interfaces to Web archives in support of scholarly activities

Web archiving initiatives around the world capture ephemeral web content to preserve our collective digital memory. In this paper, we describe initial experiences in providing an exploratory search interface to web archives for humanities scholars and social scientists. We describe our initial implementation and discuss our findings in terms of desiderata for such a system. It is clear that the standard organization of a search engine results page (SERP), consisting of an ordered list of hits, is inadequate to support the needs of scholars. Shneiderman's mantra for visual information seeking (“overview first, zoom and filter, then details-on-demand”) provides a nice organizing principle for interface design, to which we propose an addendum: “Make everything transparent”. We elaborate on this by highlighting the importance of the temporal dimension of web pages as well as issues surrounding metadata and veracity.
Using density peaks sentence clustering for update summary generation

Update summarization can be a daunting task in automatic text summarization. It aims to distill evolved messages from a collection of new articles, under the assumption that the reader has already browsed the previous articles. In this paper, a number of state-of-the-art approaches were reviewed for extracting update summarization and then a method called DPC-TS was proposed. This approach is derived from the DPC-based multidocuments summarization method, which was developed in 2015. In our study, a model was established by using the topic signature algorithm, to evaluate the novelty of sentences in update documents set. In addition, the scheme of calculating similarities between sentences and sentence selection approach was improved to ensure there are diversity topics in the summary. DPC-TS update documents summarization method is a simple and effective approach, which can be reproduced and deployed in real environment. Keywords—update summarization; DPC; topic signature;
Quality drift within a narrative of investment in early childhood education

This study contributes to the discussion of the policy discourses related to the investment narrative in early childhood education. The article begins by contextualizing the concept of ‘quality’ in a narrative of investing in early childhood education. Employing techniques drawn from the tradition of discourse analysis, the paper highlights the fact that the era of the OECD's inclusive liberalism is fading. Additionally, the study illuminates the fact that the transparent conceptualization of ‘quality’ resonates poorly with these new directions. Finally, the consequences of the inconsistent use of the concept of ‘quality’ will be discussed. In all, this study addresses the need for a profound empirical analysis of the investment narrative that current international early childhood educational policies have adopted and provides a more nuanced understanding of the construction of the concept of ‘quality’ within it.