Miracle-dz/UniFAR-FTUs huggingface dataset:
Phylogeny of the Turneraceae clade (Passifloraceae s.l.): Trans-Atlantic disjunctions and two new genera in Africa

Turneraceae, with just over 200 species in 10 genera, is today often included in a widely circumscribed Passifloraceae. The vast majority of the species are found in the New World, whereas generic diversity is largest in the Old World. According to current circumscriptions, three of the genera show trans-Atlantic disjunctions: Turnera with over 135 species in America and two species in Africa (one in the south-western and one in the north-eastern part), Piriqueta with 44 species in America and one in southern Africa, and Erblichia with one species in Central America and four in Madagascar. The phylogeny of Turneraceae is reconstructed based on DNA sequences from plastid trnL-F and nuclear ITS and sampling for all genera, including both New and Old World species for the trans-Atlantic groups to test their monophyly. The genera of Turneraceae form a strongly supported monophyletic group, the Turneraceae clade, within Passifloraceae s.l. The phylogeny is geographically structured, with one clade comprising American species only, except for the two African species of Turnera, and another clade with all other African species plus the Central American Erblichia odorata. Turnera is retrieved as monophyletic with the two African species appearing as close relatives of T. ulmifolia, the type of Turnera. The existence of a trans-Atlantic disjunction in Turnera is therefore supported. It is most likely caused by long-distance dispersal and estimated to be not older than late Miocene. In Piriqueta only the American species are supported as a monophyletic group, whereas the single African species is resolved as a member of the African clade. The trans-Atlantic disjunction in Piriqueta is therefore not supported and the African species is proposed to be placed in a genus of its own, Afroqueta gen. nov., as Afroqueta capensis comb. nov. Erblichia on Madagascar is supported as sister to Mathurina, a genus endemic to Rodrigues Island in the Mascarenes, and does not group with E. odorata in Central America, the type of Erblichia. The trans-Atlantic disjunction in Erblichia is therefore not supported either and the genus Arboa gen. nov. is proposed to accommodate the four Malagasy species, Arboa integrifolia comb. nov., Arboa berneriana comb. nov., Arboa madagascariensis comb. nov., and Arboa antsingyae comb. nov.
Faster Algorithms for k-Regret Minimizing Sets via Monotonicity and Sampling

Regret-based queries are a complement of top-k and skyline queries when users cannot specify accurate utility functions while must output a controllable size of the query results. Various regret-based queries are proposed in last decade for multi-criteria decision making. The k-regret minimizing set (k-RMS) query which returns r points from the dataset and minimizes the maximum k-regret ratio has been extensively studied. However, existing state-of-art algorithms to find k-regret minimizing sets are very time-consuming and unapplicable. In this paper, we propose a faster algorithm SAMPGREED for k-RMS queries by utilizing the monotonicity of the regret ratio function with sampling techniques. We provide the theoretical analysis of our SAMPGREED algorithm and experiments on synthetic and real datasets verify our proposed algorithm is superior to existing state-of-art approaches.
Generalizing Energy-based Generative ConvNets from Particle Evolution Perspective

Compared with Generative Adversarial Networks (GAN), the Energy-Based generative Model (EBM) possesses two appealing properties: i) it can be directly optimized without requiring an auxiliary network during the learning and synthesizing; ii) it can better approximate underlying distribution of the observed data by learning explicitly potential functions. This paper studies a branch of EBMs, i.e., the energy-based Generative ConvNet (GCN), which minimizes its energy function defined by a bottom-up ConvNet. From the perspective of particle physics, we solve the problem of unstable energy dissipation that might damage the quality of the synthesized samples during the maximum likelihood learning. Specifically, we establish a connection between FRAME model [1] and dynamic physics process and provide a generalized formulation of FRAME in discrete flow with a certain metric measure from particle perspective. To address KL-vanishing issue, we generalize the reformulated GCN from the KL discrete flow with KL divergence measure to a Jordan-Kinderleher-Otto (JKO) discrete flow with Wasserastein distance metric and derive a Wasserastein GCN (w-GCN). To further minimize the learning bias and improve the model generalization, we present a Generalized GCN (GGCN). GGCN introduces a hidden space mapping strategy and employs a normal distribution as hidden space for the reference distribution. Besides, it applies a matching trainable non-linear upsampling function for further generalization. Considering the limitation of the efficiency problem in MCMC based learning of EBMs, an amortized learning are also proposed to improve the learning efficiency. Quantitative and qualitative experiments are conducted on several widely-used face and natural image datasets. Our experimental results surpass those of the existing models in both model stability and the quality of generated samples.
Nondestructive Reading and Refreshment Circuit for Memristor-based Neuromorphic Synapse

Memristor, the fourth circuit element found ten years ago, has attracted most scientific and engineering community pioneers. Its proficiency in nanoscale devices makes it very useful in todays new fast circuit applications. Neuromorphic computing is the new processing technique which is brain-inspired rather than old von-Neumann processors. The main advantage of using memristor in neuromorphic is that it contains both the processing and storing blocks in one place. The main components of any neural networks are the neuron and synapse. In this paper, a recent memristor-based synapse used in literature is introduced with rather a nondestructive reading mechanism for the stored weight in the memristor.
Co-Limbs: An Intuitive Collaborative Control for Wearable Robotic Arms

The promising possibilities offered by supernumerary robotic wearable arms are limited by the lack of an intuitive and robust user interface to control them. Here, utilizing admittance control, we propose a ’Collaborative limbs’, or ’Co-limbs’ user interface for wearable robot arms. The key feature of this user interface is its intuitiveness enabling even first time users to immediately move and use the, normally stiff, robot arms for assistive tasks and even teach the robot simple and useful movements. We demonstrate the diverse range of applications enabled by this simple but powerful user interface through example demonstrations in the Passive Assist, Power Assist and Playback modes.
Television Performance as Interaction

Face-to-face communication is usually considered as a fundamental form of communication. Therefore, all other forms of communication are often compared to it. Consequently, one-way direction and absence of a negotiable dimension, or in other words, lack of interactivity, have been seen to be characteristic for television communication. Interactivity is also said to be one of the most remarkable differences between the new communication technology and the traditional media (e.g. Rogers 1986). Traditionally television is, thus, considered as a noninteractive medium. Currently, however, the notion of interactive television has been gaining attention. Normally, this notion refers to a combination of a computer and a television. Still, certain programs of traditional television are also called interactive. In these programs, a viewer is able to interact with a presenter, or participate in the program by telephone. The interactive programs have been reported to increase rapidly in Finnish television (Eerikainen 1994, Hietala 1994) and they were also common in the US during the presidential election (Diamond, McKay & Silverman 1993, Newhagen 1994). Additionally, the television companies all over the world seem to believe in the capacity of the interactive programs to attract viewers, as new programs are being developed and their number increased. However, there is also evidence for the view that the interactive forms do not necessarily please the audience (Barwise & Ehrenberg 1988: 84, Isotalus & Porhola 1994, Jaasaari & Savinen 1995). Poster (1994) has argued that, despite the telephone call-ins, television communication is still unidirectional, and thus, basically a monologue. Also Eerikainen (1994) has criticized Finnish interactive programs for not being genuine conversations with viewers, as they follow a preplan, and the viewers have to adapt to the rules. Eerikainen (1994) sees the present interactive forms of television as an opportunity of feedback or participation rather than as actual interaction. He also questions whether the interaction, in this case, indicates the media-relationship, or the relationship between persons. This relates to the fact that interaction can be considered from three different perspectives: interaction between persons, interaction between a text and a person and interaction between a machine and a person (e.g. Jensen 1997). Evidently, there seem to be different viewpoints about what is interactive and what is not, and, furthermore where the television may be located on this dimension. However, it is fully possible to consider television from the perspective of interactivity. The aim of this paper is to develop a model to illustrate the interaction between a television presenter and a viewer. Therefore, the first and the most essential question is to try to define interaction.
Emotion-aware Chat Machine: Automatic Emotional Response Generation for Human-like Emotional Interaction

The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions. However, this challenge is not well addressed in the literature, since most of the approaches neglect the emotional information conveyed by a post while generating responses. This article addresses this problem by proposing a unified end-to-end neural architecture, which is capable of simultaneously encoding the semantics and the emotions in a post for generating more intelligent responses with appropriately expressed emotions. Extensive experiments on real-world data demonstrate that the proposed method outperforms the state-of-the-art methods in terms of both content coherence and emotion appropriateness.
Africa's digital divide: Geography, policy, and implications

This exploratory empirical study examines the extent of differences in information and communication technology (ICT) utilization among the various countries of Africa. This paper also enhances understanding of factors that impact ICT utilization and the digital divide in African countries. In contrast to previous empirical studies, we include more advanced forms of ICT such as broadband and social media technologies. In our conceptual model of ICT utilization, known as Spatially Aware Technology Utilization Model (SATUM), five dependent variables are posited to be associated with eighteen demographic, socio-economic, education, technology tariff, societal openness, infrastructure, and ICT services competitiveness variables. ICT utilization dependent variables are spatially analyzed to determine patterns of agglomeration or randomness, and regression residuals are tested for the presence of spatial bias. We determine that laws that relate to the use of ICTs is a dominant predictor of all forms of ICT utilization, a novel finding. The effectiveness of a national parliament/congress as a lawmaking institution is significantly associated with modern (broadband) as well as legacy forms (fixed telephones) of ICT. This is consistent with prior literature which emphasizes the role of national governments in Africa in framing ICT sector policies for investment, privatization, deregulation, and providing access in underserved areas. For a smaller sample of nations that excludes high utilization ICT nations of Africa, ICT laws have a somewhat reduced effect for two forms of ICT. However gross national income per capita is determined to a dominant predictor for three ICTs and mobile tariffs is negatively associated with mobile cellular subscribers. The findings are intuitive and mostly well supported by previous literature. Policy implications for African nations are provided.
A Hybrid Interference Alignment Scheme in Two-tiered MIMO Heterogeneous Network

Interference alignment (IA) is thought to be an effective technique on reducing interference in wireless communications. To mitigate the interference and improve the system performance, this paper proposes a two-stage hybrid interference alignment (THIA) scheme for the two-tiered multi-user multiple-input-multiple-output (MIMO) heterogeneous network (HetNet). Specifically, we focus on the downlink transmission of two-tiered HetNet. Firstly, we align the cross-tier interference from macro base station (MBS) to the users in the same small cell to a specific subspace, through which the first-stage transmit beamforming matrix at MBS is designed. Then, an equivalent virtual distributed method is applied to mitigate the co-tier interference among macro users. Numerical results demonstrate that the proposed THDIA scheme outperforms the conventional schemes in degrees of freedom and system sum rate.
Beyond Product Architecture: Division of Labour and Competence Accumulation in Complex Product Development

This paper considers the trade-off between leveraging external sources of innovation by outsourcing design and engineering activities and the ability to develop internal product development competences. The trade-off arises because the division of labor within and across firms' boundaries has a crucial role in shaping competence development processes, especially because the division of labor also influences opportunities for learning by doing. In new product development projects, learning by doing appears to be both a key determinant of competence development and a difficult-to-substitute form of learning. While the division of development tasks is often considered as guided by product architecture, we show that by decoupling the decisions concerning the product architecture and the allocation of development tasks, firms can realize the benefits of outsourcing such tasks while developing new internal competences. Drawing on a longitudinal case study in the automotive industry, we also identify a new organizational lever for shaping competence development paths and for designing firm boundaries. This lever consists in alternating different task allocation schemes over time for different types of development projects. We show why this is a novel solution, what its underlying logic is, and how it enables alleviating the trade-off between the benefits of leveraging external sources of innovation and the opportunities for competence development provided by in-house design and engineering. We discuss implications for theories of organizational boundary design and innovation management.
Making space and place for knowledge communities : lessons for Australian practice

This paper aims to shed light on the planning and development processes of the knowledge-based urban development phenomenon, with respect to the construction of knowledge community precincts. We undertake policy and best practice analyses to learn from the planning and development processes of internationally renowned knowledge community precincts—from Copenhagen, Eindhoven and Singapore. In the light of this, we scrutinise major Australian knowledge community precinct initiatives—from Sydney, Melbourne and Brisbane—to better understand the dynamics of national practices, and benchmark them against the international best practice cases. The paper concludes with a discussion on the study findings and successfully establishing space and place for both knowledge economy and society in Australian cities.
Experimental study on flocculation performance of Chitosan-Based Flocculant using a Novel Jar Tester

The effectiveness of chitosan as a flocculant was tested with a novel experimental apparatus. Using a newly developed flocculation tester, a large number of flocculation rate processes were measured. The novel jar tester included a photocoupler and switching timer. Mixing was paused for a period and the floc-settling velocity and residual turbidity were measured during this period. The relation between the turbidity of the supernatant (i.e., the residual turbidity) and chitosan dose was measured over a wide range of initial turbidities. The chitosan showed two windows for the optimum dose: (1) a dose close to that used with ordinary inorganic flocculants, at which the residual turbidity showed complicated behavior under the influence of various factors, and (2) an optimum dose in the order of 10−4 of the initial turbidity. The latter optimum-dose range is very narrow, and simple chargeneutralization plays an important role in the flocculation.
Interference Alignment Beamforming and Power Allocation for Cognitive MIMO-NOMA Downlink Networks

This paper addresses the beamforming and power allocation problem in the downlink multi-input multi-output (MIMO) non-orthogonal multiple access (NOMA) based cognitive radio (CR) network. In particular, we consider a secondary base station (BS) located at cell-edge of a primary BS assists far away secondary users that do not have direct link with the primary BS. Random user pairing is performed among primary users (PUs) and secondary user (SUs) respectively, to reduce successive interference cancellation (SIC) complexity and inter-user interference. In order to eliminate inter-cluster interference and interference from the secondary BS, interference alignment (IA)-based coordinated beamforming (CBF) is proposed. We then provide an optimal power allocation method to maximize the sum rate of each network while guaranteeing a minimum quality of service for users with weaker channel gain inside each cluster. We show that compared to two baseline beamforming schemes for NOMA, the proposed scheme improves the system throughput significantly.
Directivity Optimization in Omnidirectional Volumetric Antenna Arrays

Directivity pattern is a paramount performance measure in antenna array configurations. Applications such as heterogeneous MIMO wireless cellular communication can greatly benefit in exploring antenna directivity improvement. The problem of directivity optimization, which leads to a highly increasing in directivity gain on a certain desired angle of arrive/departure (AoA/AoD), is considered in this work. A new formulation on the volumetric array directivity problem is proposed using the rectangular coordinates to describe each antenna element, and the desired angle in spherical coordinates ($\theta_{0}, \phi_{0}$), with a general element pattern given by $\sin^{u}\theta\ \cos^{v}\theta$. To solve the associated optimization problem, the omnidirectional ($\cos\theta$) configuration was selected; besides, generalized scenarios, i.e $\forall u, v\neq 0$, can easily be considered deploying a similar formulation. A well-defined genetic algorithm (GA) was selected to expeditiously solve the resultant non-convex optimization problem. Numerical results comparing achieved directivity for $N=6,7$ and 8 antenna-elements demonstrate gains of ∼ 5 dB compared to the regular beamforming technique, using steering vector for uniform linear arrays (ULA) and uniform circular arrays (UCA).
What is Fair? Exploring Pareto-Efficiency for Fairness Constrained Classifiers

The potential for learned models to amplify existing societal biases has been broadly recognized. Fairness-aware classifier constraints, which apply equality metrics of performance across subgroups defined on sensitive attributes such as race and gender, seek to rectify inequity but can yield non-uniform degradation in performance for skewed datasets. In certain domains, imbalanced degradation of performance can yield another form of unintentional bias. In the spirit of constructing fairness-aware algorithms as societal imperative, we explore an alternative: Pareto-Efficient Fairness (PEF). Theoretically, we prove that PEF identifies the operating point on the Pareto curve of subgroup performances closest to the fairness hyperplane, maximizing multiple subgroup accuracy. Empirically we demonstrate that PEF outperforms by achieving Pareto levels in accuracy for all subgroups compared to strict fairness constraints in several UCI datasets.
Microscopic derivation of the Jaynes-Cummings model with cavity losses

In this paper we provide a microscopic derivation of the master equation for the Jaynes-Cummings model with cavity losses. We single out both the differences with the phenomenological master equation used in the literature and the approximations under which the phenomenological model correctly describes the dynamics of the atom-cavity system. Some examples wherein the phenomenological and the microscopic master equations give rise to different predictions are discussed in detail.
An Investigation into the Poor Academic Performance of Students at Selected Public Basic Schools in Obuasi Municipality

The study investigated the poor academic performance of students at three selected junior high schools in Obuasi Municipality, seeking to determine the inputs and processes that contributed to such an outcome. Based on the study’s research questions and aims, the researchers chose an exploratory design that combined both qualitative and quantitative methods for collecting and analysing the data. The target population for the study comprised students, teachers and parents in respect of all basic schools in Obuasi Municipality. However, the accessible population was limited to students, parents and teachers in Obuasi West Circuit. The study employed both simple random and stratified sampling techniques. Questionnaires and past records were used as data sources. Cross tabulation was adopted for analysis of the relationship between inputs and processes, and performance outputs. The study found that most respondents accepted that all inputs and processes contributed moderately to very significantly to poor academic performance. It is therefore concluded that there is a need for all stakeholders- government departments, teachers, parents and students,etc- to play their respective parts in addressing the factors that contribute to poor student performance in the schools under study if it is to be improved.
360Drops: Mixed Reality Remote Collaboration using 360 Panoramas within the 3D Scene*

Mixed Reality (MR) remote guidance has become a practical solution for collaboration that includes nonverbal communication. This research focuses on integrating different types of MR remote collaboration systems together allowing a new variety for remote collaboration to extend its features and user experience. In this demonstration, we present 360Drops, a MR remote collaboration system that uses 360 panorama images within 3D reconstructed scenes. We introduce a new technique to interact with multiple 360 Panorama Spheres in an immersive 3D reconstructed scene. This allows a remote user to switch between multiple 360 scenes “live/static, past/present,” placed in a 3D reconstructed scene to promote a better understanding of space and interactivity through verbal and nonverbal communication. We present the system features and user experience to the attendees of SIGGRAPH Asia 2019 through a live demonstration.