Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Spherical Quasiconformal Parameterization of Genus-0 Closed Surfaces with Application to Adaptive Remeshing

In this work, we are concerned with the spherical quasiconformal parameterization of genus-0 closed surfaces. Given a genus-0 closed triangulated surface and an arbitrary user-defined quasiconformal distortion, we propose a fast algorithm for computing a spherical parameterization of the surface that satisfies the prescribed distortion. The proposed algorithm can be effectively applied to adaptive surface remeshing for improving the visualization in computer graphics and animations. Experimental results are presented to illustrate the effectiveness of our algorithm.
Hybridization and extinction

Hybridization may drive rare taxa to extinction through genetic swamping, where the rare form is replaced by hybrids, or by demographic swamping, where population growth rates are reduced due to the wasteful production of maladaptive hybrids. Conversely, hybridization may rescue the viability of small, inbred populations. Understanding the factors that contribute to destructive versus constructive outcomes of hybridization is key to managing conservation concerns. Here, we survey the literature for studies of hybridization and extinction to identify the ecological, evolutionary, and genetic factors that critically affect extinction risk through hybridization. We find that while extinction risk is highly situation dependent, genetic swamping is much more frequent than demographic swamping. In addition, human involvement is associated with increased risk and high reproductive isolation with reduced risk. Although climate change is predicted to increase the risk of hybridization‐induced extinction, we find little empirical support for this prediction. Similarly, theoretical and experimental studies imply that genetic rescue through hybridization may be equally or more probable than demographic swamping, but our literature survey failed to support this claim. We conclude that halting the introduction of hybridization‐prone exotics and restoring mature and diverse habitats that are resistant to hybrid establishment should be management priorities.
Tracing the potential planet-forming regions around seven pre-main-sequence stars

Aims. We investigate the nature of the innermost regions with radii of several AUs of seven circumstellar disks around pre-main-sequence stars, T Tauri stars in particular. Our object sample contains disks apparently at various stages of their evolution. Both single stars and spatially resolved binaries are considered. In particular, we search for inner disk gaps as proposed for several young stellar objects (YSOs). When analyzing the underlying dust population in the atmosphere of circumstellar disks, the shape of the 10 μ m feature should additionally be investigated. Methods. We performed interferometric observations in N band (8-13 μ m) with the Mid-Infrared Interferometric Instrument (MIDI) at the Very Large Telescope Interferometer (VLTI) using baseline lengths of between 54 m and 127 m. The data analysis is based on radiative-transfer simulations using the Monte Carlo code MC3D by modeling simultaneously the spectral energy distribution (SED), N band spectra, and interferometric visibilities. Correlated and uncorrelated N band spectra are compared to investigate the radial distribution of the dust composition of the disk atmosphere. Results. Spatially resolved mid-infrared (MIR) emission was detected in all objects. For four objects (DR Tau, RU Lup, S CrA N, and S CrA S), the observed N band visibilities and corresponding SEDs could be simultaneously simulated using a parameterized active disk-model. For the more evolved objects of our sample, HD 72106 and HBC 639, a purely passive disk-model provides the closest fit. The visibilities inferred for the source RU Lup allow the presence of an inner disk gap. For the YSO GW Ori, one of two visibility measurements could not be simulated by our modeling approach. All uncorrelated spectra reveal the 10 μ m silicate emission feature. In contrast to this, some correlated spectra of the observations of the more evolved objects do not show this feature, indicating a lack of small silicates in the inner versus the outer regions of these disks. We conclude from this observational result that more evolved dust grains can be found in the more central disk regions.
A novel application model and an offloading mechanism for efficient mobile computing

This paper presents a new application model and a novel execution path-based algorithm for offloading in Mobile Cloud Computing (MCC) environments. Application offloading is the mechanism by which parts or modules of the application are executed in cloud remote computational services. Such operation saves resources in the mobile device but also incurs costs of accessing the cloud and using the communication network connecting the mobile device and cloud. The offloading problem is to find an offloading decision that minimizes the total cost of executing the application. Previous solutions find a single offloading decision per module. However, the total cost of executing a module also depends on the sequence of module calls leading to its execution. We present a fine grained application model and a fast optimal offloading decision algorithm where multiple offloading decisions are made per module based on the execution paths leading to the module. We evaluate our solution for a face detection mobile applications in multiple network scenarios. We show that our model and algorithm offer offloading decisions that are significant faster than offloading decision by traditional offloading schemes.
Being networked and being engaged: the impact of social networking on ecommerce information behavior

Teenagers and young adults born between 1981 and 2000 are a critical demographic group economically and are one of the first demographics presented with an array of Internet social networking services just as their online habits are forming. Based on a survey of 34,514 teen and young adult respondents, the research reported in this paper is a descriptive and inferential analysis of reported ecommerce information behaviors on four social networking sites (Facebook, MySpace, myYearbook, and Twitter). We use k-means clustering analysis to find groups of these users based on their levels of being networked on and being engaged with social networking services. Results show that the majority of this demographic have accounts on multiple social networking sites and specific sites result in different information behaviors. More than 40% engage in three social networking sites and an additional 20% have four social networking accounts. We also found that there are distinct information behavioral differences among eight distinct clusters of users, indicating that companies may need to employ advanced analytical techniques to segment the youth market. We also investigate the motivations for using different social media sites. Findings show that this young demographic has complex ecommerce information behaviors that call for nuanced approaches in advertising, marketing, or other areas of information targeting.
Raptor codes-based energy-efficient screen mirroring system

In this work, we propose a Raptor codes-based energy-efficient screen mirroring system. To mitigate the video quality degradation caused by wireless network error, the proposed system employs systematic Raptor codes as forward error correction scheme. For energy saving at the mobile device, the proposed system not only shapes screen mirroring traffic, but also determines the Raptor encoding parameters including the symbol size, the number of source symbols, and the code rate. The proposed system is fully implemented on single board computers, and examined over real wireless network.
Who participates in research on adherence to treatment in insulin-dependent diabetes mellitus? Implications and recommendations for research.

OBJECTIVE Examine the implications of nonparticipation in studies of treatment adherence among adolescents with chronic health conditions. METHODS Empirical data from an adherence study with adolescents with diabetes were used to demonstrate the influence of family participation on demographic and health outcome variables. Ninety-four families were categorized into one of three groups: (1) families that declined to participate in the study at recruitment (nonconsenters), (2) families that agreed to participate, but failed to return the study questionnaires (nonreturners), and (3) families that had at least one family member return the questionnaires (participants). RESULTS Despite being similar demographically, nonreturners had significantly lower treatment adherence scores and the adolescents tested their blood sugar less frequently than participants. Participants and non-consenters did not differ on any available data. CONCLUSIONS We discuss the implications of these group differences on the generalizability of research findings, offer suggestions about how to maximize and maintain participation in research studies, and suggest directions for future research.
Minority Nationalist Parties and European Integration: A comparative study

1. Introduction: minority nationalist parties and European integration 2. Theorising the European attitudes of minority nationalist parties 3. Wales: Plaid Cymru 4. Galicia: the Bloque Nacionalista Galego 5. Corsica: a comparison of moderate and radical Corsican nationalist parties 6. Conclusions: a comparative analysis of minority nationalist party attitudes towards European integration
Work in progress paper: Utility based clustering algorithm for VANET

Clustering is expected to be one of the most efficient and promising solutions for data transmission in Vehicular Ad hoc NETworks (VANET). The particular characteristics of VANET, including highly dynamic network topology, unstable transmission channel, and various service requirements, pose challenges and difficulties on clustering algorithm design. In this paper, a clustering algorithm based on utility function is proposed for VANET. The utility function of vehicles is formulated which jointly considers current state of vehicles characterized by the vehicle degree, relative velocity and position between adjacent vehicles, and long-term transmission performance of vehicles, defined as credit history function, which is characterized by the average available bandwidth, queue length and the duration for being a cluster head (CH) in a past period. The process of cluster forming is presented, and the vehicles with large utility function are selected as CHs successively. Numerical simulations demonstrate that comparing to previously proposed algorithms, the proposed algorithm offers better performance in terms of packet delivery rate, average transmission delay and total throughput.
La misión de la universidad en el siglo XXI: comprender su origen para proyectar su futuro

Este artículo es el resultado de la revisión de la literatura relevante sobre la idea de universidad. Defiende que el estudio sobre la génesis y la evolución de la institución universitaria aporta luz sobre su incierto futuro. A partir de un esquema argumentativo, reflexiona sobre su origen en la Edad Media, el sentido de la universidad como centro de investigación, para, finalmente, plantear tensiones y desafíos que enfrenta la universidad contemporánea. Pero esta institución debe armonizar las nuevas demandas que se le están exigiendo, sin renunciar a la identidad a la que se debe, si quiere seguir siendo universitas.
Chaotic Braided Solutions via Rigorous Numerics: Chaos in the Swift-Hohenberg Equation

We prove that the stationary Swift–Hohenberg equation has chaotic dynamics on a critical energy level for a large (continuous) range of parameter values. The first step of the method relies on a computer assisted, rigorous, continuation method to prove the existence of a periodic orbit with certain geometric properties. The second step is topological: we use this periodic solution as a skeleton, through which we braid other solutions, thus forcing the existence of infinitely many braided periodic orbits. A semiconjugacy to a subshift of finite type shows that the dynamics is chaotic.
A three-dimensional image processing program for accurate, rapid, and semi-automated segmentation of neuronal somata with dense neurite outgrowth

Three-dimensional (3-D) image analysis techniques provide a powerful means to rapidly and accurately assess complex morphological and functional interactions between neural cells. Current software-based identification methods of neural cells generally fall into two applications: (1) segmentation of cell nuclei in high-density constructs or (2) tracing of cell neurites in single cell investigations. We have developed novel methodologies to permit the systematic identification of populations of neuronal somata possessing rich morphological detail and dense neurite arborization throughout thick tissue or 3-D in vitro constructs. The image analysis incorporates several novel automated features for the discrimination of neurites and somata by initially classifying features in 2-D and merging these classifications into 3-D objects; the 3-D reconstructions automatically identify and adjust for over and under segmentation errors. Additionally, the platform provides for software-assisted error corrections to further minimize error. These features attain very accurate cell boundary identifications to handle a wide range of morphological complexities. We validated these tools using confocal z-stacks from thick 3-D neural constructs where neuronal somata had varying degrees of neurite arborization and complexity, achieving an accuracy of ≥95%. We demonstrated the robustness of these algorithms in a more complex arena through the automated segmentation of neural cells in ex vivo brain slices. These novel methods surpass previous techniques by improving the robustness and accuracy by: (1) the ability to process neurites and somata, (2) bidirectional segmentation correction, and (3) validation via software-assisted user input. This 3-D image analysis platform provides valuable tools for the unbiased analysis of neural tissue or tissue surrogates within a 3-D context, appropriate for the study of multi-dimensional cell-cell and cell-extracellular matrix interactions.
Studying Software Implementations of Elliptic Curve Cryptography

Elliptic curve cryptography (ECC) provides a similar level of security to conventional integer-based public-key algorithms, but with much shorter keys. ECC over binary field is of special interest because the operations in binary field are thought more space and time efficient. However, the software implementations of ECC over binary field are still slow, especially on low-end processors that are used in small computing devices such as sensor nodes. In this paper, we study the software implementations of ECC on processors with different word sizes. With a set of algorithms that we identified, we can perform 163-bit ECC in 13.9 seconds on an 8-bit processor at a clock rate of 8 MHz
High ionic strength and low pH detain activated skinned rabbit skeletal muscle crossbridges in a low force state

The effects of varying pH and ionic strength on the force-velocity relations and tension transients of skinned rabbit skeletal muscle were studied at 1-2 degrees C. Both decreasing pH from 7.35 to 6.35 and raising ionic strength from 125 to 360 mM reduced isometric force by about half and decreased sarcomere stiffness by about one-fourth, so that the stiffness/force ratio was increased by half. Lowering pH also decreased maximum shortening velocity by approximately 29%, while increasing ionic strength had little effect on velocity. These effects on velocity were correlated with asymmetrical effects on stiffness. The increase in the stiffness/force ratio with both interventions was manifest as a greater relative force change associated with a sarcomere length step. This force difference persisted for a variable time after the step. At the high ionic strength the force difference was long- lasting after stretches but relaxed quickly after releases, suggesting that the structures responsible would not impose much resistance to steady-state shortening. The opposite was found in the low pH experiments. The force difference relaxed quickly after stretches but persisted for a long time after releases. Furthermore, this force difference reached a constant value of approximately 8% of isometric force with intermediate sizes of release, and was not increased with larger releases. This value was almost identical to the value of an internal load that would be sufficient to account for the reduction in maximum velocity seen at the low pH. The results are interpreted as showing that both low pH and high ionic strength inhibit the movement of crossbridges into the force-generating parts of their cycle after they have attached to the actin filaments, with very few other effects on the cycle. The two interventions are different, however, in that detained bridges can be detached readily by shortening when the detention is caused by high ionic strength but not when it is caused by low pH.
Using Evolving Graphs to evaluate DTN routing protocols.

One of the main challenges of Delay-Tolerant Networks (DTNs) is on how to define effective routing protocols. Contrarily to traditional networks, which use static routing protocols and guarantee end-to-end paths between nodes of the network, connectivity is intermittent in DTNs. A routing path between two nodes is dynamically built over the time, i.e., a connection between two intermediate nodes of a routing path is not necessarily established beforehand. Hence, it may happen that at a given time or period there is no direct path between two given nodes, however further future temporary connections between some intermediary nodes may provide a path over time, also called journey, between those two nodes. Temporary connections between nodes, denoted contacts, is thus strongly exploited by DTN routing protocols for message delivery.
Spray and Routing for Message Delivery in Challenged Networks

In the challenged networks, such as interplanetary networks, satellite networks, military networks and so on, a complete path from the source to the destination does not exist for most of the time. The lack of end-to-end path makes the message delivery a great challenge in these networks. In this paper, we propose the spray and routing message delivery mechanism, which combines the simplicity of epidemic routing and the efficiency of direct routing. We evaluate the performance of Spray and Routing via simulation using the ONE simulator, in comparison with the traditional Epidemic, Prophet and Spray and Waiting protocols. The simulation results show that our method can achieve better performance.
On the correlation analysis of antennas in adaptive MIMO systems with 3-D multipath scattering

The performance of multiple-input multiple-output (MIMO) systems improves substantially with the adaptation techniques like power allocation and antenna selection. These algorithms can he enhanced by considering characteristics of spatial correlation. In this study, the spatial correlation in MIMO systems is investigated to fully expose the parameters affecting it. The correlation analysis is performed by taking the effect of angle-of-arrival (AoA) statistics in three-dimensional (3-D) multipath scattering, mutual coupling, and near-field scatterers (NFS). The analysis shows that a valid model of the AoA statistics is the key parameter in the correlation analysis. Mutual coupling analysis for patch antennas reveals that coupling can reduce the correlation between antenna elements. On the other hand, the analysis on NFS suggest continuous correlation estimation. Fortunately, the rate of change of NFS is much slower than the MIMO channel variation. It is concluded that the performance of MIMO systems can be improved with accurate AoA models and tracking correlation changes.
Learning symbolic forward models for robotic motion planning and control

Physiological studies suggest that humans have internal dynamics models for both themselves as well as their environment, which are integral components in motion planning and control. Although robotic systems rely on similar models, a primary constraint for robotic applications is how such models are acquired and developed. Traditionally human engineers derive the dynamics models for robots; this approach is not scalable for increasingly complex designs. As a result, there is growing interest in model inference methods, which automate the modeling process and extends the design range of robots. This paper proposes a novel method that infers dynamics models as mathematical expressions via Symbolic Regression and applies them for robotic motion planning and control tasks. The advantage of this expression is not only the accuracy but also the computational efficiency. Experimental results on underpowered pendulum domains validate that our inferred models enable fast motion planning and real-time control based on rapid re-planning, with significantly superior results over Support Vector Regression and Gaussian Process Regression.
Association between tooth loss and the development of mild memory impairment in the elderly: the Fujiwara-kyo Study.

BACKGROUND Tooth loss may be a modifiable risk factor for memory disorders, but the causal relationship has not been evaluated sufficiently. OBJECTIVE This 5-year prospective cohort study investigated the effect of tooth loss on the development of mild memory impairment (MMI) among the elderly. METHODS Data are from the baseline and follow-up examinations of 2,335 community residents who were cognitively intact at baseline. The number of remaining teeth at baseline was classified as zero, 1-8, 9-16, 17-24, and 25-32. The main outcome for the analysis was the development of MMI at follow-up. RESULTS After adjustment for potential confounding factors in multivariable logistic regression analysis, the odds ratio of per 1 tooth loss at baseline was 1.02 (95% confidence interval, 1.00-1.03). The odds ratio of edentulism for MMI was 2.39 (1.48-3.86) compared to 25-32 teeth. The odds ratio of becoming edentulous compared to retaining 1-8 teeth in the 1-8 teeth group at baseline was 4.68 (1.50-14.58). CONCLUSION Tooth loss predicts the development of MMI among the elderly.
Cascading outbreak prediction in networks: a data-driven approach

Cascades are ubiquitous in various network environments such as epidemic networks, traffic networks, water distribution networks and social networks. The outbreaks of cascades will often bring bad or even devastating effects. How to accurately predict the cascading outbreaks in early stage is of paramount importance for people to avoid these bad effects. Although there have been some pioneering works on cascading outbreaks detection, how to predict, rather than detect, the cascading outbreaks is still an open problem. In this paper, we attempt harnessing historical cascade data, propose a novel data driven approach to select important nodes as sensors, and predict the outbreaks based on the cascading behaviors of these sensors. In particular, we propose Orthogonal Sparse LOgistic Regression (OSLOR) method to jointly optimize node selection and outbreak prediction, where the prediction loss are combined with an orthogonal regularizer and L1 regularizer to guarantee good prediction accuracy, as well as the sparsity and low-redundancy of selected sensors. We evaluate the proposed method on a real online social network dataset including 182.7 million information cascades. The experimental results show that the proposed OSLOR significantly and consistently outperform topological measure based method and other data driven methods in prediction performances.