Miracle-dz/UniFAR-FTUs huggingface dataset:
Adversarial Code Learning for Image Generation

We introduce the "adversarial code learning" (ACL) module that improves overall image generation performance to several types of deep models. Instead of performing a posterior distribution modeling in the pixel spaces of generators, ACLs aim to jointly learn a latent code with another image encoder/inference net, with a prior noise as its input. We conduct the learning in an adversarial learning process, which bears a close resemblance to the original GAN but again shifts the learning from image spaces to prior and latent code spaces. ACL is a portable module that brings up much more flexibility and possibilities in generative model designs. First, it allows flexibility to convert non-generative models like Autoencoders and standard classification models to decent generative models. Second, it enhances existing GANs' performance by generating meaningful codes and images from any part of the prior. We have incorporated our ACL module with the aforementioned frameworks and have performed experiments on synthetic, MNIST, CIFAR-10, and CelebA datasets. Our models have achieved significant improvements which demonstrated the generality for image generation tasks.
Weak convergence of a measure-valued process for social networks.

In this article we formalize the problem of modeling social networks into a measure-valued process and interacting particle system. We obtain a model that describes in continuous time each vertex of the graph at a latent spatial state as a Dirac measure. We describe the model and its formal design as a Markov process on finite and connected geometric graphs with values in path space. A careful analysis of some microscopic properties of the underlying process is provided. Moreover, we study the long time behavior of the stochastic particle system. Using a renormalization technique, which has the effect that the density of the vertices must grow to infinity, we show that the rescaled measure-valued process converges in law towards the solution of a deterministic equation. The strength of our general continuous time and measure-valued dynamical system is that their results are context-free, that is, that hold for arbitrary sequences of graphs.
Candida albicans exhibits distinct cytoprotective responses to anti-fungal drugs that facilitate the evolution of drug resistance

We developed a modified protocol for nanolitre droplet-based single cell sequencing appropriate for fungal settings, and used it to transcriptionally profiled several thousands cells from a prototrophic Candida albicans population and several drug exposed colonies (incl. fluconazole, caspofungin and nystatin). Thousands of cells from each colony were profiled both at early and late time points post-treatment in order to infer survival trajectories from initial drug tolerance to drug resistance. We find that prototrophic C. albicans populations differentially and stochastically express cytoprotective epigenetic programs. For all drugs, there is evidence that tolerant individuals partition into distinct subpopulations, each with a unique survival strategy involving different regulatory programs. These responses are weakly related to changes in morphology (shift from white to opaque forms, or shift from yeast to filamentous forms). In turn, those subpopulations that successfully reach resistance each have a distinct multivariate epigenetic response that coordinates the expression of efflux pumps, chaperones, transport mechanisms, and cell wall maintenance. Live cell fluorescent imaging was used to validate predictions of which molecular responses most often led to survival after drug exposure. Together our findings provide evidence that C. albicans has a robust toolkit of short-term epigenetic cytoprotective responses designed to “buy time” and increase the chance of acquiring long-term resistance.
Modeling the thermomechanical behavior of carbon fiber–reinforced shape memory polymer composites under the finite deformation

In this article, a thermoviscoelastic constitutive model is introduced to describe the unidirectional continuous elastic fiber–reinforced shape memory polymer composites under the finite deformation. Although the shape memory polymers can be used in finite deformations, only a small strain can be applied on the carbon fiber for its small failure tensile strain (about 2%). Using the model, the effective strain of the carbon fiber for the unidirectional continuous carbon fiber–reinforced shape memory polymer composites can be derived. It is found that the carbon fiber–reinforced shape memory polymer composites with the fiber inclination angle in a typical range can be used in the finite deformation, without failure of the carbon fiber. Besides, a simplified buckling model is proposed to predict the fiber buckling under axial compression. It is calculated that the buckling critical stress is rather small. Therefore, it should be avoided in application. As for carbon fiber–reinforced shape memory polymer composites, the bending driving capacity is the crucial property in their applications. Hence, the shape memory effect of the carbon fiber–reinforced shape memory polymer composite beam under the finite deformation is also studied here. The findings can be used to provide guidance for the design and application of the carbon fiber–reinforced shape memory polymer composites and their structures.
Can Dietary Intake of Vitamin C-Oriented Foods Reduce the Risk of Osteoporosis, Fracture, and BMD Loss? Systematic Review With Meta-Analyses of Recent Studies

Background: Several epidemiological studies have been performed to evaluate the association of dietary intake of vitamin C-oriented foods (DIVCF) with risk of fracture and bone mineral density (BMD) loss, but the results remain controversial. Therefore, we conducted a systematic meta-analysis to assess this correlation. Methods: We searched EmBase, PubMed, Web of Science, and the Chinese database CNKI for relevant articles published up to August 2019. Pooled relative risks (RRs) with 95% confidence intervals (CIs) were calculated using the random- or fixed-effects model. Discrepancies were resolved by consultation with a third expert. Results: A total of 13 eligible articles (including 17 studies) with 19,484 subjects were identified for the present meta-analysis. The pooled RR of hip fracture for the highest vs. lowest category was 0.66 (95% CI, 0.47–0.94) for DIVCF, i.e., people with a greater frequency of Vitamin C uptake had a 34% (95% CI, 6%−53%) lower prevalence of hip fracture. In subgroup analyses stratified by study design, gender, and age, the negative associations were statistically significant. Furthermore, the statistical analysis of the association between DIVCF and risk of osteoporosis (RR, 0.66; 95% CI, 0.48–0.92), BMD at the lumbar spine (pooled r, 0.15; 95% CI, 0.09–0.23), and BMD at the femoral neck (pooled r, 0.20; 95% CI, 0.11–0.34) showed beneficial effects of DIVCF. Conclusion: Our meta-analysis indicates that DIVCF is negatively associated with the risk of hip fracture, osteoporosis, and BMD loss, suggesting that DIVCF decreases the risk of hip fracture, osteoporosis, and BMD loss.
Case Report: Optical Coherence Tomography Angiography of Idiopathic Foveal Hypoplasia and Its Correlation With Visual Acuity.

SIGNIFICANCE Foveal hypoplasia is described clinically by the absence of a foveal pit and subsequent reduction in visual acuity. Optical coherence tomography angiography provides precise segmentation of the retinal vascular supply demonstrating the vascular perfusion in affected patients. Preservation of perfusion is linked to visual acuity and function. PURPOSE This case report describes a patient with foveal hypoplasia and preservation of visual acuity with preserved retinal capillary density of the superficial and deep capillary plexuses on optical coherence tomography angiography. In addition, the diagnostic findings of foveal hypoplasia as seen on optical coherence tomography angiography will be described. CASE REPORT A 25-year-old Caucasian female with history of foveal hypoplasia presented to the clinic for evaluation. She had no other visual, ocular, or systemic complaints. Her ocular history included Duane syndrome, accommodative insufficiency, and traumatic brain injury. Her medical history included cardiac ablation secondary to supraventricular tachycardia, gall bladder removal, maxillary sinus cyst, and a history of migraines. Best-corrected visual acuity was 20/15 in the right and left eyes. Funduscopic examination was unremarkable. Spectral domain optical coherence tomography revealed absence of the anatomical foveal pit with normal inner retinal morphology. Optical coherence tomography angiography confirmed a decreased foveal avascular zone; however, a vascular density analysis showed normal perfusion to the inner retinal plexuses. CONCLUSIONS Optical coherence tomography angiography is a rapid, noninvasive imaging modality that provides excellent insight into the microvasculature supply to the retina and choroid. As such, it allows for an in-depth analysis into the pathophysiology behind certain conditions such as foveal hypoplasia.
Relative Property A for Discrete Metric Space

Yu introduced Property A on discrete metric spaces. In this paper, a relative Property A for a discrete metric space X with respect to a set Y and a map ρX,Y is defined. Some characterizations for relative Property A are given. In particular, a discrete metric space with relative Property A can be coarse embedding into a Hilbert space under certain condition.
Wearable multi-modal interfaces for mixed-initiative interaction in human multi-robot teams

In a mixed team, humans and one or more, possibly heterogeneous, robots share the same physical environment and work ‘”shoulder-to-shoulder” to perform a common mission. To allow a smooth and effective collaboration in such spatially distributed and heterogeneous system, interaction plays a fundamental role and needs to be suitably designed. When the physical environment is that of a search and rescue mission, then the scenario poses specific challenges that need to be addressed when designing interaction: usually, the embedding environment is unstructured and possibly harsh/hostile (e.g., after a natural disaster), communication infrastructure is hardly available and light and visibility conditions can vary very much. There, human agents are professionals who need to focus on their job (e.g., rather than focusing on how to “talk” to the robots. However, in spite of the many practical challenges that arise, it is apparent that the deployment of a fleet of heterogeneous robots can result in a net advantage while performing the mission, as long as it is possible to effectively use their artificial sensory-motor and processing capabilities. In typical search and rescue operations global mission planner assigns to the individual agents the task to be performed, possibly with an associated time schedule. A task assignment could consist in telling rescuers A,B,C to search for survivors in a specific mission area (e.g., inside a collapsed house) for the next 30 minutes, and telling flying robots R1, R2 to collect aerial images of another area. However, the same resources could be used in a mixed group of humans-robots, to search for survivors in the same area. Assuming that robots have enough locomotion and decisional autonomy to implement the search request from the global planner, this would be a basic example of a mixed team in action. However, in order to get the best out of the deployed resources, and locally create a coalition among humans and robots, some explicit interaction can be profitably used. E.g. the human can use his/her own superior cognitive abilities to locally direct the actions of the robots. This would amount to a form of local, high-level action planning that would complement the global mission planning. On the other side, robots could explicitly ask for support from the human to execute complex actions (e.g., open the door) or to decide where to search next. In more general terms, a mixed
Visualization in the Cloud

This paper focuses on the effect of visualization on two Linux machines, each equipped with different Nvidia GPUs. The study used: two of Nvidia‘s GPUs (the K5000 and K2200), ParaView 5.3. 0 for the visualization processes, and the nvidia monitoring tool in Linux command line for recording the amount of resources being used.
Determination of resonance energies and widths of Mg 3pn 1De and 1Fo doubly excited states by the stabilization method with the B-spline-based configuration interaction approach

The resonance energies and widths of Mg 3pn 1De and 1Fo doubly excited states are determined by calculating the density of resonance states using the stabilization method with the B-spline-based configuration interaction (BSCI) approach. The effects due to the intrashell core excitation and intershell core-valence interactions are taken into account in the BSCI calculation by using a parametrized long-range core-polarization potential. Comparisons are made with the existing theoretical and experimental results.
Regression analysis of case-cohort studies in the presence of dependent interval censoring

The case-cohort design is widely used as a means of reducing the cost in large cohort studies, especially when the disease rate is low and covariate measurements may be expensive, and has been discussed by many authors. In this paper, we discuss regression analysis of case-cohort studies that produce interval-censored failure time with dependent censoring, a situation for which there does not seem to exist an established approach. For inference, a sieve inverse probability weighting estimation procedure is developed with the use of Bernstein polynomials to approximate the unknown baseline cumulative hazard functions. The proposed estimators are shown to be consistent and the asymptotic normality of the resulting regression parameter estimators is established. A simulation study is conducted to assess the finite sample properties of the proposed approach and indicates that it works well in practical situations. The proposed method is applied to an HIV/AIDS case-cohort study that motivated this investigation.
The pathway of regenerative spinal motoneurons after brachial plexus injury in rats

Objective:To observe the pathway of regenerative axons of spinal motoneurons following differently injury of brachial plexus and to investigate the correlation of the pathway of regenerative axons and the recovery of motor function.Method:A total of sixty adult male SD rats were randomly divided into five groups:nerve root cut group (rct),nerve root crush group (rch),neural stem cut group (sct),neral stem crush group (sch) and the control group.Two months later,the functional recovery was evaluated by using grooming test.Fluorogold labled regenerative motoneurons retrogradely when injected into the motor or sensory branch of musculocutaneous nerve.Three days later,the C5-7 spinal cord were harvested and then the regenerative motoneurons were numbered.Result:The regenerative motoneurons reinnervated motor branch were much more than that sensory branch in all five groups.With the functional recovery,the percentage of above grading 4 in the four injured groups rct,rch,sch,sct is 0,17%,50%,75%,respectively.Conclusion:Regenerative axons of spinal motoneurons reinnervate the motor branch after BPI.The extent of motor functional recovery is different after different injuries,and it is correlated with the pathway and the numbers of regenerative axons.
In-situ re-optimization for new levels of process control in optical thin films

This paper presents the benefits of using a magnetron sputter deposition tool equipped with broadband optical monitor and a new “online re-optimization capability” for high volume, high accuracy production . While conventional layer termination by the optical monitor relies on a comparison of the actual measured reflection spectrum with a pre-calculated target spectrum, for “in-situ re-optimization” spectra recorded after each and every deposited layer are analyzed by the re-optimization module and – in case of significant deviations – layer thicknesses and target spectra for the remaining layers are recalculated automatically. This new technique significantly improves the performance and reproducibility in case of highly demanding coating designs
Semi-Local Analysis and Real Life Applications of Higher-Order Iterative Schemes for Nonlinear Systems

Our aim is to improve the applicability of the family suggested by Bhalla et al. (Computational and Applied Mathematics, 2018) for the approximation of solutions of nonlinear systems. Semi-local convergence relies on conditions with first order derivatives and Lipschitz constants in contrast to other works requiring higher order derivatives not appearing in these schemes. Hence, the usage of these schemes is improved. Moreover, a variety of real world problems, namely, Bratu’s 1D, Bratu’s 2D and Fisher’s problems, are applied in order to inspect the utilization of the family and to test the theoretical results by adopting variable precision arithmetics in Mathematica 10. On account of these examples, it is concluded that the family is more efficient and shows better performance as compared to the existing one.
EXPLORING GAME TASKS TO PRODUCE HIGH LEVELS OF IMMERSION IN VIRTUAL REALITY: AN EXPERIMENT IN THE SCOPE OF SAFETY WARNINGS EVALUATION

Considerable research regarding safety warnings has been conducted using conventional, mostly questionnaire-based methods. Little research has focused warnings compliance behavior assessment due to some ethical and methodological limitations because users cannot be exposed to real risks situations. Virtual Reality (VR) is starting to be used as a new research approach, based on the possibility of overcoming such constraints. However, there is a need to understand how people react to VR-based hazardous situations. At this respect some questions need to be clarified. One question is how to simulate realistic and believable dangerous situations where safety warnings are needed. Other issue is how to produce, in such studies, an adequate sense of presence level. The hypothesis of this paper is that a game task can raise presence levels in order to promote a naturalistic behavior in the participants. In this sense, this study evaluated the effect of two trial conditions game trial and non-game trial on safety exit signs effectiveness evaluation and in the sense of presence reported by participants. The data revealed no significant effects for game trial but revealed significant effects for participants’ game expertise. Previous findings concerning game effect were not supported. Findings suggest that subject’s expertise with video games should be considered when conducting VR-based studies.
Lecture Notes on Set-Valued Dynamical Systems

In these notes, we study the theory of set-valued dynamical systems, with applications in mind to population game dynamics, especially to the best response dynamics (Gilboa and Matsui (1991) and Hofbauer (1995)) and the sampling best response dynamics (Oyama et al. (2009, OST henceforth)). These classes of dynamics are defined by differential inclusions, and they naturally induce set-valued dynamical systems. In Section 1, we consider a specific class of differential inclusions relevant for our applications and present the existence and key properties of their solutions. In Sections 2–6, we review stability concepts defined through a set-valued dynamical system. These sections are based on Benäım et al. (2005, BHS henceforth), while here we only allow for systems with forward time. Section 7 and Section 8 present theorems that play important roles in the study of the sampling best response dynamics in OST. In Section 7, we prove the transitivity property of asymptotic stability for nested sets, where we extend the result by Conley (1978) to set-valued dynamical systems that are defined only for forward time. Section 8 contains a result on the partial order of solutions to dynamical systems satisfying a certain monotonicity property that corresponds to the supermodularity in games. Definitions and theorems about correspondences and function spaces that are needed along our study are available in the Appendix.
Short Group Signature without Random Oracles

Group signature is a central tool for privacy-preserving protocols, ensuring authentication, anonymity and accountability. It has been massively used in cryptography, either directly or through variants such as direct anonymous attestations. However, it remains a complex tool, especially if ones wants to avoid proving security in the random oracle model. In this work, we propose a new group signature scheme proven secure without random oracles which significantly decreases the complexity in comparison with the state-of-the-art. More specifically, we halve both the size and the computational cost compared to the most efficient alternative in the same model. Moreover, our construction is also competitive against the most efficient ones in the random oracle model. Our construction is based on a tailored combination of two popular signatures, which avoids the explicit use of encryption schemes or zeroknowledge proofs while signing. It is flexible enough to achieve security in different models and is thus suitable for most contexts.
A Residential Load Scheduling with the Integration of On-Site PV and Energy Storage Systems in Micro-Grid

The smart grid (SG) has emerged as a key enabling technology facilitating the integration of variable energy resources with the objective of load management and reduced carbon-dioxide (CO 2 ) emissions. However, dynamic load consumption trends and inherent intermittent nature of renewable generations may cause uncertainty in active resource management. Eventually, these uncertainties pose serious challenges to the energy management system. To address these challenges, this work establishes an efficient load scheduling scheme by jointly considering an on-site photo-voltaic (PV) system and an energy storage system (ESS). An optimum PV-site matching technique was used to optimally select the highest capacity and lowest cost PV module. Furthermore, the best-fit of PV array in regard with load is anticipated using least square method (LSM). Initially, the mathematical models of PV energy generation, consumption and ESS are presented along with load categorization through Zero and Finite shift methods. Then, the final problem is formulated as a multiobjective optimization problem which is solved by using the proposed Dijkstra algorithm (DA). The proposed algorithm quantifies day-ahead electricity market consumption cost, used energy mixes, curtailed load, and grid imbalances. However, to further analyse and compare the performance of proposed model, the results of the proposed algorithm are compared with the genetic algorithm (GA), binary particle swarm optimization (BPSO), and optimal pattern recognition algorithm (OPRA), respectively. Simulation results show that DA achieved 51.72% cost reduction when grid and renewable sources are used. Similarly, DA outperforms other algorithms in terms of maximum peak to average ratio (PAR) reduction, which is 10.22%.