Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of different estimation methods in growth curve models for categorical data: A simulation study

ABSTRACT This simulation study aims at investigating the performance of maximum likelihood and weighted least-square estimation approaches in growth curve models with categorical data. The goodness-of-fit indices were compared with a number of scenarios (different trajectories, sample sizes, replications, and number of categories). The results show that when the number of categories and replications are small, using weighted least-square estimating methods leads to better goodness-of-fit indices. However, when the number of categories and replications are large, both maximum likelihood and weighted least squares in estimating methods will result in similar fit indices.
Compressive-Sensing-Based Simultaneous Polarimetric HRRP Reconstruction With Random OFDM Pair Radar Signal

Orthogonal waveform design is of great significance for simultaneous polarimetric high-resolution range profile (HRRP) reconstruction. In this paper, a novel waveform called a random orthogonal frequency division multiplexing (R-OFDM) pair is proposed. The proposed signal exploits ideal orthogonality by randomly selecting different subsets of a full-band OFDM signal. The compressive sensing (CS) technique is applied for HRRP reconstruction due to the sparse property of the proposed waveform. To further utilize the information of different polarization channels, the joint CS reconstruction algorithm called a fully polarization-simultaneous orthogonal matching pursuit (FP-SOMP) is proposed instead of the single polarization-OMP algorithm by exploiting row-sparsity of different polarization channels. Both numerical simulations and measured unmanned aerial vehicle data experiments demonstrate that the R-OFDM pair and the CS-based FP-SOMP algorithm are qualified for simultaneous polarimetric HRRP reconstruction.
Towards Pressure-Robust Mixed Methods for the Incompressible Navier–Stokes Equations

Abstract In this contribution, we review classical mixed methods for the incompressible Navier–Stokes equations that relax the divergence constraint and are discretely inf-sup stable. Though the relaxation of the divergence constraint was claimed to be harmless since the beginning of the 1970s, Poisson locking is just replaced by another more subtle kind of locking phenomenon, which is sometimes called poor mass conservation and led in computational practice to the exclusion of mixed methods with low-order pressure approximations like the Bernardi–Raugel or the Crouzeix–Raviart finite element methods. Indeed, divergence-free mixed methods and classical mixed methods behave qualitatively in a different way: divergence-free mixed methods are pressure-robust, which means that, e.g., their velocity error is independent of the continuous pressure. The lack of pressure robustness in classical mixed methods can be traced back to a consistency error of an appropriately defined discrete Helmholtz projector. Numerical analysis and numerical examples reveal that really locking-free mixed methods must be discretely inf-sup stable and pressure-robust, simultaneously. Further, a recent discovery shows that locking-free, pressure-robust mixed methods do not have to be divergence free. Indeed, relaxing the divergence constraint in the velocity trial functions is harmless, if the relaxation of the divergence constraint in some velocity test functions is repaired, accordingly. Thus, inf-sup stable, pressure-robust mixed methods will potentially allow in future to reduce the approximation order of the discretizations used in computational practice, without compromising the accuracy.
Resource Requirements for Reliable Service Function Chaining

In the context of Software-Defined Networks (SDN), Network Function Virtualization (NFV) is a new network paradigm in which network functions are implemented in software as Virtual Network Functions (VNFs). To meet the demand, VNFs are next interconnected to form different complete end-to-end services, also known as a Service Function Chains (SFCs). We study the problem of deploying reliable Service Function Chains over a virtualized network function architecture. While there is a need for reliable service function chaining, there is a high cost to pay for it in terms of bandwidth and VNF processing requirements. We investigate two different protection mechanisms and discuss their resource requirements, as well as the latency of their paths. For each mechanism, we develop a scalable exact mathematical model using column generation.
Lead Sheet Generation and Arrangement by Conditional Generative Adversarial Network

Research on automatic music generation has seen great progress due to the development of deep neural networks. However, the generation of multi-instrument music of arbitrary genres still remains a challenge. Existing research either works on lead sheets or multi-track piano-rolls found in MIDIs, but both musical notations have their limits. In this work, we propose a new task called lead sheet arrangement to avoid such limits. A new recurrent convolutional generative model for the task is proposed, along with three new symbolic-domain harmonic features to facilitate learning from unpaired lead sheets and MIDIs. Our model can generate lead sheets and their arrangements of eight-bar long. Source code and audio samples of the generated result can be found at the project webpage: https://liuhaumin. github.io/LeadsheetArrangement
<inline-formula><tex-math notation="LaTeX">$\mathsf{CHOAMP}$</tex-math><alternatives> <inline-graphic xlink:href="vs-ieq1-2791955.gif"/></alternatives></inline-formula>: Cost Based Hardware Optimization for Asymmetric Multicore Processors

Heterogeneous Multiprocessors (HMPs) are popular due to their energy efficiency over Symmetric Multicore Processors (SMPs). Asymmetric Multicore Processors (AMPs) are a special case of HMPs where different kinds of cores share the same instruction set, but offer different power-performance trade-offs. Due to the computational-power difference between these cores, finding an optimal hardware configuration for executing a given parallel program is quite challenging. An inherent difficulty in this problem stems from the fact that the original program is written for SMPs. This challenge is exacerbated by the interplay of several configuration parameters that are allowed to be changed in AMPs. In this work, we propose a probabilistic method named <inline-formula><tex-math notation="LaTeX"> $\mathsf{CHOAMP}$</tex-math><alternatives><inline-graphic xlink:href="vs-ieq2-2791955.gif"/></alternatives> </inline-formula> to choose the <italic>best</italic> available hardware configuration for a given parallel program. Selection of a configuration is guided by a user-provided <italic>run-time</italic> property such as energy-delay-product (EDP) and <inline-formula><tex-math notation="LaTeX">$\mathsf{CHOAMP}$</tex-math><alternatives> <inline-graphic xlink:href="vs-ieq3-2791955.gif"/></alternatives></inline-formula> aspires to optimize the property in choosing a configuration. The core part of our probabilistic method relies on identifying the behavior of various program constructs in different classes of CPU cores in the AMP, and how it influences the cost function of choice. We implement the proposed technique in a compiler which automatically transforms a code optimized for SMP to run efficiently over an AMP, eliding requirement of any user annotations. <inline-formula><tex-math notation="LaTeX"> $\mathsf{CHOAMP}$</tex-math><alternatives><inline-graphic xlink:href="vs-ieq4-2791955.gif"/></alternatives> </inline-formula> transforms the same source program for different hardware configurations based on different user requirement. We evaluate the efficiency of our method for three different run-time properties: execution time, energy consumption, and EDP, in NAS Parallel Benchmarks for OpenMP. Our experimental evaluation shows that <inline-formula> <tex-math notation="LaTeX">$\mathsf{CHOAMP}$</tex-math><alternatives><inline-graphic xlink:href="vs-ieq5-2791955.gif"/> </alternatives></inline-formula> achieves an average of 65, 28, and 57 percent improvement over baseline HMP scheduling while optimizing for energy, execution time, and EDP, respectively.
Queuing Model for EVs Energy Management: Load Balancing Algorithms Based on Decentralized Fog Architecture

This paper presents a decentralized scheduling architecture for Electric Vehicles (EVs) energy management based on fog computing paradigm, where optimal load balancing algorithms are implemented using priority-queuing model. The proposed architecture consists of multiple decentralized fog operation centers that assist vehicle-to-grid (V2G) communication in order to manage and schedule EVs charging/discharging requests in real-time way and to maintain the electric smart grid stability. We introduce two scheduling algorithms; 1) priority levels assignment, 2) optimal load balancing of EVs requests over fog servers. The extensive simulations and comparisons with different scenarios proved that our proposed model reduces the response time and maximizes EVs utility. In addition, the proposed scheduling algorithms optimize the energy load during peak hours, and maintain the micro grid stability using real scenarios in the city of Toronto.
Static and Dynamic Analysis of Android Malware and Goodware Written with Unity Framework

Unity is the most popular cross-platform development framework to develop games for multiple platforms such as Android, iOS, and Windows Mobile. While Unity developers can easily develop mobile apps for multiple platforms, adversaries can also easily build malicious apps based on the “write once, run anywhere” (WORA) feature. Even though malicious apps were discovered among Android apps written with Unity framework (Unity apps), little research has been done on analysing the malicious apps. We propose static and dynamic reverse engineering techniques for malicious Unity apps. We first inspect the executable file format of a Unity app and present an effective static analysis technique of the Unity app. Then, we also propose a systematic technique to analyse dynamically the Unity app. Using the proposed techniques, the malware analyst can statically and dynamically analyse Java code, native code in C or C ++, and the Mono runtime layer where the C# code is running.
Asteriscus graveolens Extract in Combination with Cisplatin/Etoposide/Doxorubicin Suppresses Lymphoma Cell Growth through Induction of Caspase-3 Dependent Apoptosis

Chemotherapy drugs action against cancer is not selective, lead to adverse reactions and drug resistance. Combination therapies have proven more effective in defeating cancers. We hypothesize that plant extract/fraction contains many/several compounds and as such can target multiple pathways as cytotoxic agent and may also have chemo sensitizing activities. We designed a study in which, Asteriscus graveolens (Forssk.) Less (A. graveolens)-derived fraction that contains sesquiterpene lactone asteriscunolide isomers (AS) will be tested in combination with known chemotherapy drugs. Successful combination will permit to reduce chemotherapy drugs concentration and still get the same impact on cancer cells. Sesquiterpene lactone such as asteriscunolide isomers is a naturally occurring compound found in a variety of fruits, vegetables, and medicinal plants with anti-cancer properties. The experiments presented here showed that adding plant fraction containing AS permit reducing the concentration of cisplatin/etoposide/doxorubicin in order to reduce mouse BS-24-1 lymphoma cells (BS-24-1 cells) survival. It involved enhancing the production of Reactive Oxygen Species (ROS), activation of caspase-3 and inhibition of Topoisomerase I activity. Taken together, the results suggest that A. graveolens fraction sensitized BS-24-1 cells to cisplatin/etoposide/doxorubicin through induction of ROS and caspase-3-dependent apoptosis.
Recovery Failure Probability of Power-Based NOMA on the Uplink of a 5G Cell for an Arbitrary Number of Superimposed Signals

This work puts forth an analytical approach to evaluate the recovery failure probability of power-based Non-Orthogonal Multiple Access (NOMA) on the uplink of a 5G cell, the recovery failure being defined as the unfortunate event where the receiver is unable to decode even one out of the n simultaneously received signals. In the examined scenario, Successive Interference Cancellation (SIC) is considered and an arbitrary number of superimposed signals is present. For the Rayleigh fading case, the recovery failure probability is provided in closed-form, clearly outlining its dependency on the signal-to-noise ratio of the users that are simultaneously transmitting, as well as on their distance from the receiver.
An upper bound for min-max angle of polygons

Let $S$ be a set of points in the plane, $CH$ be the convex hull of $S$, $\wp(S)$ be the set of all simple polygons crossing $S$, $\gamma_P$ be the maximum angle of polygon $P \in \wp(S)$ and $\theta =min_{P\in\wp(S)} \gamma_P$. In this paper, we prove that $\theta\leq 2\pi-\frac{2\pi}{r.m}$ such that $m$ and $r$ are the number of edges and internal points of $CH$, respectively. We also introduce an innovative polynomial time algorithm to construct a polygon with the said upper bound on its angles. Constructing a simple polygon with angular constraint on a given set of points in the plane is highly applicable to the fields of robotics, path planning, image processing, GIS, etc. Moreover, we improve our upper bound on $\theta$ and prove that this is tight.
Handling Fluorescence in a Uni‐directional Spectral Path Tracer

We present two separate improvements to the handling of fluorescence effects in modern uni‐directional spectral rendering systems. The first is the formulation of a new distance tracking scheme for fluorescent volume materials which exhibit a pronounced wavelength asymmetry. Such volumetric materials are an important and not uncommon corner case of wavelength‐shifting media behaviour, and have not been addressed so far in rendering literature. The second one is that we introduce an extension of Hero wavelength sampling which can handle fluorescence events, both on surfaces, and in volumes. Both improvements are useful by themselves, and can be used separately: when used together, they enable the robust inclusion of arbitrary fluorescence effects in modern uni‐directional spectral MIS path tracers. Our extension of Hero wavelength sampling is generally useful, while our proposed technique for distance tracking in strongly asymmetric media is admittedly not very efficient. However, it makes the most of a rather difficult situation, and at least allows the inclusion of such media in uni‐directional path tracers, albeit at comparatively high cost. Which is still an improvement since up to now, their inclusion was not really possible at all, due to the inability of conventional tracking schemes to generate sampling points in such volume materials.
Comparison of intracranial aneurysm flow quantification techniques: standard PIV vs stereoscopic PIV vs tomographic PIV vs phase-contrast MRI vs CFD

Image-based hemodynamic simulations to assess the rupture risk or improve the treatment planning of intracranial aneurysms have become popular recently. However, due to strong modeling assumptions and limitations, the acceptance of numerical approaches remains limited. Therefore, validation using experimental methods is mandatory. In this study, a unique compilation of four in-vitro flow measurements (three particle image velocimetry approaches using a standard (PIV), stereoscopic (sPIV), and tomographic (tPIV) setup, as well as a phase-contrast magnetic resonance imaging (PC-MRI) measurement) were compared with a computational fluid dynamics (CFD) simulation. This was carried out in a patient-specific silicone phantom model of an internal carotid artery aneurysm under steady flow conditions. To evaluate differences between each technique, a similarity index (SI) with respect to the velocity vectors and the average velocity magnitude differences among all involved modalities were computed. The qualitative comparison reveals that all techniques are able to provide a reasonable description of the global flow structures. High quantitative agreement in terms of SI and velocity magnitude differences was found between all PIV methods and CFD. However, quantitative differences were observed between PC-MRI and the other techniques. Deeper analysis revealed that the limited resolution of the PC-MRI technique is a major contributor to the experienced differences and leads to a systematic underestimation of overall velocity magnitude levels inside the vessel. This confirms the necessity of using highly resolving flow measurement techniques, such as PIV, in an in-vitro environment to individually verify the validity of the numerically obtained hemodynamic results.
Code-Mixed Question Answering Challenge: Crowd-sourcing Data and Techniques

Code-Mixing (CM) is the phenomenon of alternating between two or more languages which is prevalent in bi- and multi-lingual communities. Most NLP applications today are still designed with the assumption of a single interaction language and are most likely to break given a CM utterance with multiple languages mixed at a morphological, phrase or sentence level. For example, popular commercial search engines do not yet fully understand the intents expressed in CM queries. As a first step towards fostering research which supports CM in NLP applications, we systematically crowd-sourced and curated an evaluation dataset for factoid question answering in three CM languages - Hinglish (Hindi+English), Tenglish (Telugu+English) and Tamlish (Tamil+English) which belong to two language families (Indo-Aryan and Dravidian). We share the details of our data collection process, techniques which were used to avoid inducing lexical bias amongst the crowd workers and other CM specific linguistic properties of the dataset. Our final dataset, which is available freely for research purposes, has 1,694 Hinglish, 2,848 Tamlish and 1,391 Tenglish factoid questions and their answers. We discuss the techniques used by the participants for the first edition of this ongoing challenge.
Functional Specialization of Duplicated AGAMOUS Homologs in Regulating Floral Organ Development of Medicago truncatula

The C function gene AGAMOUS (AG) encodes for a MADS-box transcription factor required for floral organ identity and floral meristem (FM) determinacy in angiosperms. Unlike Arabidopsis, most legume plants possess two AG homologs arose by an ancient genome duplication event. Recently, two euAGAMOUS genes, MtAGa and MtAGb, were characterized and shown to fulfill the C function activity in the model legume Medicago truncatula. Here, we reported the isolation and characterization of a new mtaga allele by screening the Medicago Tnt1 insertion mutant collection. We found that MtAGa was not only required for controlling the stamen and carpel identity but also affected pod and seed development. Genetic analysis indicated that MtAGa and MtAGb redundantly control Medicago floral organ identity, but have minimal distinct functions in regulating stamen and carpel development in a dose-dependent manner. Interestingly, the stamens and carpels are mostly converted to numerous vexillum-like petals in the double mutant of mtaga mtagb, which is distinguished from Arabidopsis ag. Further qRT-PCR analysis in different mtag mutants revealed that MtAGa and MtAGb can repress the expression of putative A and B function genes as well as MtWUS, but promote putative D function genes expression in M. truncatula. In addition, we found that the abnormal dorsal petal phenotype observed in the mtaga mtagb double mutant is associated with the upregulation of CYCLOIDEA (CYC)-like TCP genes. Taken together, our data suggest that the redundant MtAGa and MtAGb genes of M. truncatula employ a conserved mechanism of action similar to Arabidopsis in determining floral organ identity and FM determinacy but may have evolved distinct function in regulating floral symmetry by coordinating with specific floral dorsoventral identity factors.
Marker versus Markerless Augmented Reality. Which Has More Impact on Users?

ABSTRACT Augmented Reality (AR) platforms are being used for an extensive array of applications. One of the critical moments of online shopping is the choice of product. Ideally, consumers should be able to try the product before pressing on “add to cart” button. The experimental design discussed in the article compares two different optical tracking systems of AR—a marker-based AR (MB) and a markerless AR (ML) for two types of interfaces: tangible and multimodal based on gesture recognition, respectively. Both AR technologies allow the consumer to virtually visualize sport shoes’ features. Although the interface systems affect the facial/body expression of participants, the self-reported arousal does not change. In contrast with the literature, the usability of the MB (tangible) AR is considered better than the ML (gesture-based recognition) AR option. The probability of recommending the displayed brand is higher under ML (gesture-based recognition) AR than the MB (tangible) AR. Some covariates and factors such as positive/negative emotional traits, tendency to adopt innovation, and familiarity with the brand interfere with the impact of both AR technologies on the dependent variables.
Menstrual Cycle Characteristics in Adolescence and Early Adulthood Are Associated With Risk of Early Natural Menopause

Context Early natural menopause (i.e., before age 45 years) is associated with increased risk of adverse outcomes. Associations of earlier menopause with younger age at menarche and short and/or regular cycle length are suggested, but study findings are inconsistent and few address early menopause risk. Objective To evaluate the relationship between menstrual cycle characteristics in early life with incident early natural menopause. Design The prospective Nurses' Health Study 2 (1989 to 2011). Setting and Participants Women ages 25 to 42 years and premenopausal in 1989 (N = 108,811). Main Outcome Measure(s) Risk of early natural menopause not due to surgery, radiation, or chemotherapy (n = 2794) was evaluated with Cox proportional hazards models. Anti-Müllerian hormone (AMH) levels were considered in a nested case-control sample (n = 820). Results In adjusted models, risk was associated with earlier age at menarche (P for trend = 0.05), shorter (P for trend < 0.0001), and more-regular cycles (P for < 0.0001). The hazard ratio (HR) for women with age at menarche ≤9 (vs. 12) years was 1.28 (95% CI, 0.99 to 1.67). Women reporting usual menstrual cycle lengths <25 days at ages 18 to 22 years had substantially higher risk of early menopause (HR, 1.70; 95% CI, 1.47 to 1.96) than women with 26- to 31-day cycles, whereas women with ≥40 day cycles had lower risk (HR, 0.44; 95% CI, 0.34 to 0.58). Women with irregular cycle length had lower risk compared with women with regular cycles (HR, 0.51; 95% CI, 0.43 to 0.60). Associations with AMH concentrations among the nested case-control subset were consistent with these findings. Conclusion Results from this large prospective study of early menopause suggest an influence of accelerated oocyte depletion on risk and may help clarify the etiology of early menopause.