Miracle-dz/UniFAR-FTUs huggingface dataset:
Purchase Intention of Residential Property in Greater Kuala Lumpur, Malaysia

High housing prices in the urban area have posted a challenge for potential first-time home buyers to own a house. This study aims to investigate factors that influence Malaysians to purchase a residential property in Greater Kuala Lumpur (KL). This study examines the effect of attitude, subjective norm, perceived behaviour control, location, living space and financial factors on the intention to purchase residential property based on the Theory of Planned Behavior. The findings indicated that there are positive relationships between attitude, subjective norm, perceived behaviour control and financial factors toward purchase intention for residential property, while location and living space were found to have no relationship on consumers? purchase intention of residential property in Greater KL. These findings will provide insightful information to the housing developer in their venture on new housing projects, marketing strategies and be meeting the homeownership needs as well as to the policy maker and bankers? decision for economic development. The limitation of the current study is arising from its focus on the selected geographical area of the Klang Valley property market only.
Understanding the Role of Rural Entrepreneurs in Telecentre Sustainability: A Comparative Study of the Akshaya and eSeva Projects in India

Information and communication technologies (ICTs) are hailed as important tools for rural development and are considered essential for enhancing livelihoods of people in rural areas (Gilbert et al., 2008). According to Geldof and Unwin (2005), ICT can be used as a tool for strengthening education, improving public services and governance as well as for supporting agriculture and the service industry. Telecentres are seen as one of the most successful means to promote ICT diffusion in developing countries because they increase the access of ICT to people, particularly the poor people living in remote rural areas (Gopakumar, 2006).
Assessment of Government Incentives for Energy from Waste in Colombia

This work evaluates the prefeasibility of energy from waste projects in Colombia under the guidelines of Law 1715. That piece of legislation proposes tax incentives for non-conventional energy initiatives, such as deductions of up to 50% on the investment through income tax, VAT exemption, tariff exemption, and accelerated depreciation of assets. Pasto, Colombia, was selected as the case study. Subsequently, incineration, gasification, anaerobic digestion, and landfill gas technologies were evaluated. The potential of electric power generation from municipal solid waste (MSW) of each conversion technology was estimated with mathematical models. Additionally, the economic evaluation considered five cases that combine loan options, accelerated depreciation, and income deductions. Finally, the prefeasibility analysis of each case and technology was based on the internal rate of return (IRR) and levelized cost of electricity (LCOE). The results reveal that only anaerobic digestion and landfill gas technologies constitute viable projects in case of traditional investment with and without loans, because they present IRRs greater than the discount rate, of 6.8%. However, by including the incentives in Law 1715 in the economic evaluation, IRRs of 11.18%, 7.96%, 14.27%, and 13.59% were obtained for incineration, gasification, anaerobic digestion, and landfill gas, respectively. These results make all four technologies feasible in this context.
Steering wheel behavior based estimation of fatigue

This paper examined a steering behavior based fatigue monitoring system. The advantages of using steering behavior for detecting fatigue are that these systems measure continuously, cheaply, non-intrusively, and robustly even under extremely demanding environmental conditions. The expected fatigue induced changes in steering behavior are a pattern of slow drifting and fast corrective counter steering. Using advanced signal processing procedures for feature extraction, we computed 3 feature set in the time, frequency and state space domain (a total number of 1251 features) to capture fatigue impaired steering patterns. Each feature set was separately fed into 5 machine learning methods (e.g. Support Vector Machine, K-Nearest Neighbor). The outputs of each single classifier were combined to an ensemble classification value. Finally we combined the ensemble values of 3 feature subsets to a of meta-ensemble classification value. To validate the steering behavior analysis, driving samples are taken from a driving simulator during a sleep deprivation study (N=12). We yielded a recognition rate of 86.1% in classifying slight from strong fatigue.
Allelic Variation in the VMD 2 Gene in Best Disease and Age-Related Macular Degeneration

METHODS. Three hundred twenty-one AMD patients, 192 ethnically similar control subjects, 39 unrelated probands with familial Best disease, and 57 unrelated probands with the ophthalmoscopic findings of Best disease but no family history were screened for sequence variations in the VMD2 gene by single-strand conformation polymorphism (SSCP) analysis. Amplimers showing a bandshift were reamplified and sequenced bidirectionally. In addition, the coding regions of the VMD2 gene were completely sequenced in six probands with familial Best disease who showed no SSCP shift.
Quantum Kitchen Sinks: An algorithm for machine learning on near-term quantum computers

Noisy intermediate-scale quantum computing devices are an exciting platform for the exploration of the power of near-term quantum applications. Performing nontrivial tasks in such devices requires a fundamentally different approach than what would be used on an error-corrected quantum computer. One such approach is to use hybrid algorithms, where problems are reduced to a parameterized quantum circuit that is often optimized in a classical feedback loop. Here we describe one such hybrid algorithm for machine learning tasks by building upon the classical algorithm known as random kitchen sinks. Our technique, called quantum kitchen sinks, uses quantum circuits to nonlinearly transform classical inputs into features that can then be used in a number of machine learning algorithms. We demonstrate the power and flexibility of this proposal by using it to solve binary classification problems for synthetic datasets as well as handwritten digits from the MNIST database. Using the Rigetti quantum virtual machine, we show that small quantum circuits provide significant performance lift over standard linear classical algorithms, reducing classification error rates from 50% to $<0.1\%$, and from $4.1\%$ to $1.4\%$ in these two examples, respectively. Further, we are able to run the MNIST classification problem, using full-sized MNIST images, on a Rigetti quantum processing unit, finding a modest performance lift over the linear baseline.
The Effects of Rosemary (Rosemarinus officinalis) Extract on Wound Healing in Rabbits

In the present study, we examined the effects of 5% Rosemarinus officinalis (rosemary) extract on wound healing as compared to those of povidone-iodine and isotonic saline solution by daily visual observation, histopathological and statistical methods. Six male and six female New Zealand rabbits were used in the study. On dorsal aspect of each rabbits, experimentally 3.14 cm in diameter, three full-thickness wounds was constituted. One of these wounds received daily 5% rosemary extract, another one received 10% povidone-iodine solution and the last one received 0.9% isotonic saline solution containing the gauze tampon for control purposes. Size of each wound was measured on days 4, 7, 10 and 14 using a caliper and biopsies were taken from different regions in clockwise direction proceedingly. Wound healings were assessed histopathologically in terms of neutrophil and macrophage infiltration with fibrocyte and fibroblast proliferation, collagen deposition, epithelialization, and vascularization. The aim of this study was to investigate the effect of rosemary extract on wound healing compared to povidone-iodine and isotonic saline solution.
Correlation between inter-model similarities in spatial pattern for present and projected future mean climate

When an averaging method is used for model future projection with weights determined according to the model performance in the present climate, generally, the stationarity of the model performance between present and future is implicitly assumed. Here we investigate this assumption using multi-model data. We consider the correlation between inter-model similarities in the spatial pattern for the present-day climate and future climate change for surface air temperature, precipitation and sea level pressure on global and zonal domains in the seasonal time scale. We further extend previous work by devising a bootstrap method to estimate the statistical significance of all correlations, which have previously not been estimated. Most of the correlation coefficients for precipitation were significant, but moderate or low in the absolute value. Many of those for the other variables were not significant. Also, we discuss the magnitude of the inter-model similarity used in this work.
Analysis of systemic complement in experimental renal injury and disease

Experimental mouse models have been extensively used to elucidate the role of the complement system in different diseases and injuries. Contribution of gender has revealed an intriguing gender specific difference; female mice often show protection against most complement driven injuries such as ischemia/ reperfusion injury, graft rejection and sepsis. Interestingly, early studies to the mouse complement system revealed that female mice have very low total complement activity (CH50), which is related to androgen regulation of hepatic complement synthesis. Here, our aim was to understand at which level the female specific differences in mouse complement resides. We have used recently developed complement assays to study the functional activities of female and male mice at the level of C3 and C9 activation, and furthermore assayed key complement factor levels in serum of age-matched female and male C57BL/6 mice. Our results show that the female mice have normal complement cascade functionality at the level of C3 activation, which was supported by determinations of early complement factors. However, all pathways are strongly reduced at the level of C9 activation, suggesting a terminal pathway specific difference. This was in line with C6 and C9 measurements, showing strongly decreased levels in females. Furthermore, similar gender differences were also found in BALB/cJ mice, but not in CD-1 mice. Our results clearly demonstrate that the complement system in females of frequently used mouse strains is restricted by the terminal pathway components and that the perceived female specific protection against experimental disease and injury might be in part explained by the inability promote inflammation through C5b-9.
Horse, Butler or Elevator? Metaphors and enactment as a catalyst for exploring interaction with autonomous technology

As technology becomes increasingly intelligent and progressively gains agency, the relationship between system and human is redefined. Conventional interaction design methodologies cannot fully encompass the emerging new types of relationships, and new methods are necessary to address interaction at early stages in the design process. Both design metaphors and enactment techniques have been suggested as a way forward, and this paper explores whether a combination of the two can support the design of interaction with future autonomous systems. In three workshops, 27 participants in total utilised this combination of methods to design the interaction with an autonomous vehicle. The analysis of the workshops shows that the combination of the methods manages to support the imagining and design, where the metaphors aided the creation of a joint conceptual vision of the relationship, and the enactment created tangible experiences and contextualisation of the design concepts. Nine guidelines for the use of the methods when designing intelligent systems are defined, based on the insights from the workshops.
Wireless Sensor Network and Internet of Things in Precision Agriculture

Internet of Things is one of the most popular subjects nowadays where sensors and smart devices facilitate the provision of information and communication. In IoT, one of the main concepts is wireless sensor networks in which data is collected from all the sensors in a network characterized by low power consumption and a wide range of communication. In this study, an architecture to monitor soil moisture, temperature and humidity on small farms is provided. The main motivation for this study is to decrease water consumption whilst increasing productivity on small agricultural farms and precisions on them. This motivation is further propelled by the fact that agriculture is the backbone of some towns and most villages in most of the countries. Furthermore, some countries depend on farming as the main source of income. Putting the above-mentioned factors into consideration, the farm is divided into regions; the proposed system monitors soil moisture, humidity and temperature in the respective regions using wireless sensor networks, internet of things and sends a report to the end user. The report contains, as part of the information, a 10-day weather forecast. We believe that with the above information, the end user (farmer) can more efficiently schedule farm cultivation, harvesting, irrigation, and fertilization.
Human-Robot Interaction Requires More Than Slot Filling - Multi-Threaded Dialogue for Collaborative Tasks and Social Conversation

—Work on spoken dialogue systems (SDS) has largely been dominated by “slot ﬁlling” applications for the past decade or more, where information-gathering tasks such as restaurant search and ﬂight booking have been the main focus of research. An important class of dialogues, about planning and executing tasks, has correspondingly been somewhat neglected. However, planning and execution dialogues become very important when we consider Human-Robot Interaction (HRI), as does the ability to carry out “social” open-domain conversation. This paper describes a new architecture that supports complex multi-threaded task planning and execution dialogues, interleaved with “social” dialogue with an open-domain chatbot.
Milking the spherical cow – on aspherical dynamics in spherical coordinates

Galaxies and the dark matter halos that host them are not spherically symmetric, yet spherical symmetry is a helpful simplifying approximation for idealised calculations and analysis of observational data. The assumption leads to an exact conservation of angular momentum for every particle, making the dynamics unrealistic. But how much does that inaccuracy matter in practice for analyses of stellar distribution functions, collisionless relaxation, or dark matter core-creation? We provide a general answer to this question for a wide class of aspherical systems; specifically, we consider distribution functions that are "maximally stable", i.e. that do not evolve at first order when external potentials (which arise from baryons, large scale tidal fields or infalling substructure) are applied. We show that a spherically-symmetric analysis of such systems gives rise to the false conclusion that the density of particles in phase space is ergodic (a function of energy alone). Using this idea we are able to demonstrate that: (a) observational analyses that falsely assume spherical symmetry are made more accurate by imposing a strong prior preference for near-isotropic velocity dispersions in the centre of spheroids; (b) numerical simulations that use an idealised spherically-symmetric setup can yield misleading results and should be avoided where possible; and (c) triaxial dark matter halos (formed in collisionless cosmological simulations) nearly attain our maximally-stable limit, but their evolution freezes out before reaching it.
Topology changes in (2+1)-dimensional quantum gravity.

We study topology-changing processes in (2+1)-dimensional quantum gravity with a negative cosmological constant. By playing the gluing-many-polyhedra game'' for hyperbolic geometry, we explicitly construct an infinite number of different instantonlike solutions. These solutions can be used to evaluate various topology-changing amplitudes in the WKB approximation.
R&D Production Team Organization and Firm-Level Innovation

How should a firm organize the diversity of technical experience contained within its pool of inventive human capital when firm-level innovation is a desired performance outcome? Using a sample of biotechnology start-ups observed from their founding onwards we examine the implications of alternate firm-level design regimes, drawing on both a firm-year panel structure, as well as an inventor-year difference-in-differences empirical approach. Our results suggest that organizing a firm’s human capital with greater across-team diversity yields increased firm-level innovation benefits as compared to when the firm’s human capital is organized with greater within-team diversity. We find that the benefits of across-team diversity stem mainly from the influence of that particular diversity regime on team stability.
Tripartite mutual information, entanglement, and scrambling in permutation symmetric systems with an application to quantum chaos

Many-body states that are invariant under particle relabelling, the permutation symmetric states, occur naturally when the system dynamics is described by symmetric processes or collective spin operators. We derive expressions for the reduced density matrix for arbitrary subsystem decomposition for these states and study properties of permutation symmetric states and their subsystems when the joint system is picked randomly and uniformly. Thus defining a new random matrix ensemble, we find the average linear entropy and von Neumann entropy which implies that random permutation symmetric states are marginally entangled and as a consequence the tripartite mutual information (TMI) is typically positive, preventing information from being shared globally. Applying these results to the quantum kicked top viewed as a multi-qubit system we find that entanglement, mutual information and TMI all increase for large subsystems across the Ehrenfest or log-time and saturate at the random state values if there is global chaos. During this time the out-of-time order correlators (OTOC) evolve exponentially implying scrambling in phase space. We discuss how positive TMI may coexist with such scrambling.
Paradigmatic Morphology Splinters, Combining Forms, and Secreted Affixes

Splinters, combining forms, and secreted affixes are three morpheme (or morphemelike) elements which are often conflated in the literature on English word-formation. Scholars have differently focused on their morphological origin (i.e. blending, paradigmatic substitution, analogy) or on their semantics (i.e. secretion vs. mere abbreviation) (Warren 1990; Fradin 2000; Mattiello 2007; Bauer et al. 2013). This paper investigates these phenomena as part of paradigmatic morphology, or similarity among words. In particular, the investigation of five case studies (i.e. (a)holic, docu-, -exit, -umentary, -zilla) shows that they are frequently used to create new words and even to produce series, through analogy via schema (cf. Köpcke 1993, 1998). In the paper, diachronic study combined with corpus-based analysis help us 1) categorise these phenomena as ‘marginal’ vs. ‘extra-grammatical’, and as ‘productive’ vs. ‘creative’, and 2) shed some light on their role in the development of morphological rules and in the expansion of the English lexicon.
Extreme Learning to Rank via Low Rank Assumption

We consider the setting where we wish to perform ranking for hundreds of thousands of users which is common in recommender systems and web search ranking. Learning a single ranking function is unlikely to capture the variability across all users while learning a ranking function for each person is time-consuming and requires large amounts of data from each user. To address this situation, we propose a Factorization RankSVM algorithm which learns a series of k basic ranking functions and then constructs for each user a local ranking function that is a combination of them. We develop a fast algorithm to reduce the time complexity of gradient descent solver by exploiting the low-rank structure, and the resulting algorithm is much faster than existing methods. Furthermore, we prove that the generalization error of the proposed method can be significantly better than training individual RankSVMs. Finally, we present some interesting patterns in the principal ranking functions learned by our algorithms.
A Case of Cardiac Arrest due to Multivessel, Diffuse Coronary Spasm in Moyamoya Disease

Moyamoya disease is a rare cerebrovascular disease involving stenosis of the bilateral internal carotid arteries and the development of an abnormal vascular network (moyamoya vessel) in the vicinity of the arterial occlusions, which may lead to stroke. There have been several reports of involvement of extracranial vessels, especially the renal and coronary arteries, in moyamoya disease. Whether ischemic heart disease in moyamoya disease is concomitant or simply coexistent remains a subject of debate. Recent reports considered moyamoya disease as a systemic arterial disease, because coronary plaque is pathologically similar to the cerebral arterial lesions, with soft intimal proliferation and minimum lipid deposition. Patients with coronary artery disease in moyamoya disease are younger and have few coronary risk factors, in contrast to those with atherosclerotic coronary artery disease. Although a few cases of variant angina with focal spontaneous and pharmacologically induced spasm have been reported in moyamoya disease4, multivessel, diffuse coronary spasm leading to cardiac arrest and myocardial infarction mimicking stress-induced cardiomyopathy (SIC) is rarely reported. Here, we report a case of diffuse, multivessel coronary spasm leading to cardiac arrest and myocardial infarction in a 47-year-old man with moyamoya disease, with no underlying emotional or physical stress. Kosin Medical Journal 2017;32:111-117. https://doi.org/10.7180/kmj.2017. 32.1. 111 KMJ Case Report