Miracle-dz/UniFAR-FTUs huggingface dataset:
SplitSR

Super-resolution (SR) is a coveted image processing technique for mobile apps ranging from the basic camera apps to mobile health. Existing SR algorithms rely on deep learning models with significant memory requirements, so they have yet to be deployed on mobile devices and instead operate in the cloud to achieve feasible inference time. This shortcoming prevents existing SR methods from being used in applications that require near real-time latency. In this work, we demonstrate state-of-the-art latency and accuracy for on-device super-resolution using a novel hybrid architecture called SplitSR and a novel lightweight residual block called SplitSRBlock. The SplitSRBlock supports channel-splitting, allowing the residual blocks to retain spatial information while reducing the computation in the channel dimension. SplitSR has a hybrid design consisting of standard convolutional blocks and lightweight residual blocks, allowing people to tune SplitSR for their computational budget. We evaluate our system on a low-end ARM CPU, demonstrating both higher accuracy and up to 5× faster inference than previous approaches. We then deploy our model onto a smartphone in an app called ZoomSR to demonstrate the first-ever instance of on-device, deep learning-based SR. We conducted a user study with 15 participants to have them assess the perceived quality of images that were post-processed by SplitSR. Relative to bilinear interpolation --- the existing standard for on-device SR --- participants showed a statistically significant preference when looking at both images (Z=-9.270, p<0.01) and text (Z=-6.486, p<0.01).
Bolder is Better: Raising User Awareness through Salient and Concise Privacy Notices

This paper addresses the question whether the recently proposed approach of concise privacy notices in apps and on websites is effective in raising user awareness. To assess the effectiveness in a realistic setting, we included concise notices in a fictitious but realistic fitness tracking app and asked participants recruited from an online panel to provide their feedback on the usability of the app as a cover story. Importantly, after giving feedback, users were also asked to recall the data practices described in the notices. The experimental setup included the variation of different levels of saliency and riskiness of the privacy notices. Based on a total sample of 2,274 participants, our findings indicate that concise privacy notices are indeed a promising approach to raise user awareness for privacy information when displayed in a salient way, especially in case the notices describe risky data practices. Our results may be helpful for regulators, user advocates and transparency-oriented companies in creating or enforcing better privacy transparency towards average users that do not read traditional privacy policies.
Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments

Exploration under sparse reward is a long-standing challenge of model-free reinforcement learning. The state-of-the-art methods address this challenge by introducing intrinsic rewards to encourage exploration in novel states or uncertain environment dynamics. Unfortunately, methods based on intrinsic rewards often fall short in procedurally-generated environments, where a different environment is generated in each episode so that the agent is not likely to visit the same state more than once. Motivated by how humans distinguish good exploration behaviors by looking into the entire episode, we introduce RAPID, a simple yet effective episode-level exploration method for procedurally-generated environments. RAPID regards each episode as a whole and gives an episodic exploration score from both per-episode and long-term views. Those highly scored episodes are treated as good exploration behaviors and are stored in a small ranking buffer. The agent then imitates the episodes in the buffer to reproduce the past good exploration behaviors. We demonstrate our method on several procedurally-generated MiniGrid environments, a first-person-view 3D Maze navigation task from MiniWorld, and several sparse MuJoCo tasks. The results show that RAPID significantly outperforms the state-of-the-art intrinsic reward strategies in terms of sample efficiency and final performance. The code is available at https://github.com/daochenzha/rapid
Collision-Free Flocking with a Dynamic Squad of Fixed-Wing UAVs Using Deep Reinforcement Learning

—Developing the collision-free ﬂocking behavior for a dynamic squad of ﬁxed-wing UAVs is still a challenge due to kinematic complexity and environmental uncertainty. In this paper, we deal with the decentralized leader-follower ﬂocking control problem through deep reinforcement learning (DRL). Speciﬁcally, we formulate a decentralized DRL-based decision making framework from the perspective of every follower, where a collision avoidance mechanism is integrated into the ﬂocking controller. Then, we propose a novel reinforcement learning algorithm CACER-II for training a shared control policy for all the followers. Besides, we design a plug-n-play embedding module based on convolutional neural networks and the attention mechanism. As a result, the variable-length system state can be encoded into a ﬁxed-length embedding vector, which makes the learned DRL policies independent with the number or the order of followers. Finally, numerical simulation results demonstrate the effectiveness of the proposed method, and the learned policies can be directly transferred to semi-physical simulation without any parameter ﬁnetuning.
Prediction of the Interaction Potential of Microgel Particles from Rheometric Data. Comparison with Different Models

This work is concerned with the determination of the effective particle−particle interaction in colloidal suspensions from rheology. In particular, a concentrated microgel suspension is considered, in which particles interact through a repulsive polymer−polymer potential. The rheological modeling of this suspension was carried out by the authors in a recent work. Here, the interaction potential provided by that model is compared with the ones resulting from different models found in the literature. In this sense, a series of approaches relating the pair potential to rheological data such as dynamic modulus, viscosity, and yield stress is examined. Then the results of applying these models to experimental data are discussed, showing the advantages and limitations of each approach for the particular case of concentrated microgel suspensions. de Gennes' theoretical pair potential for polymer-covered particles is also included for comparison. The proposed viscosity model appears rather general and it is expec.
Back and forth directed plasma bullets in a helium atmospheric pressure needle-to-plane discharge with oxygen admixtures

A sinusoidally driven needle-to-plane discharge in flowing helium at atmospheric pressure was investigated by means of electrical, optical and spectroscopic (VUV, UV and OES) measurements. ‘Bullet-like’ behaviour of the discharge was observed and investigated with special interest towards velocities and size of the ‘forward bullet’. The influence of the discharge gap and oxygen admixture on the discharge properties was analysed. The focus of this paper is on experimental results, showing discharge development within six phases. Among these, four types of bullets are observed with respect to the direction of the gas flow and applied voltage polarity. Temporally resolved photography shows the formation of an atmospheric pressure glow discharge subsequent to the propagation of the ‘forward bullet’. For the greatest gap of 15 mm, the plasma activity was restricted towards the positive voltage polarity. The discharge development under the oxygen admixture showed a delayed current pulse for the negative voltage slope, with a steep rising flank. We conclude that the main movement of the bullets in our setup does not depend on the gas flow but on the electrical field direction.
Review of Machine Learning Applications in Wireless Communications

This paper looks at various aspects of Machine Learning (ML) applications in wireless communication technologies, focusing mainly on fifth-generation (5G) and millimeter wave (mmWave) technologies. This paper includes the summaries of 3 papers on machine learning applications in wireless communication technology. The paper deals with the need for integration of machine learning in wireless communication, types of machine learning techniques used in wireless communication, advantages and potential of ML in wireless communication, and implementation parameters of ML in wireless communication, as well as a study on RSS-Based Classification of usage in indoor millimeter-wave wireless networks.
Mathematical foundations of moral preferences

One-shot anonymous unselfishness in economic games is commonly explained by social preferences, which assume that people care about the monetary pay-offs of others. However, during the last 10 years, research has shown that different types of unselfish behaviour, including cooperation, altruism, truth-telling, altruistic punishment and trustworthiness are in fact better explained by preferences for following one's own personal norms—internal standards about what is right or wrong in a given situation. Beyond better organizing various forms of unselfish behaviour, this moral preference hypothesis has recently also been used to increase charitable donations, simply by means of interventions that make the morality of an action salient. Here we review experimental and theoretical work dedicated to this rapidly growing field of research, and in doing so we outline mathematical foundations for moral preferences that can be used in future models to better understand selfless human actions and to adjust policies accordingly. These foundations can also be used by artificial intelligence to better navigate the complex landscape of human morality.
Two-Dimensional Ferroelectric Topological Insulators in Bilayer Heterostructures

Jiawei Huang, Xu Duan, Sunam Jeon, Youngkuk Kim, Jian Zhou, Jian Li, 5, 6, ∗ and Shi Liu 5, 6, † School of Science, Westlake University, Hangzhou, Zhejiang 310024, China Department of Energy Science, Sungkyunkwan University, Suwon 16419, Korea Department of Physics Sungkyunkwan University, Suwon 16419, Korea Center for Alloy Innovation and Design, State Key Laboratory for Mechanical Behavior of Materials, Xi’an Jiaotong University, Xi’an 710049, China Institute of Natural Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China Key Laboratory for Quantum Materials of Zhejiang Province, Hangzhou Zhejiang 310024, China (Dated: January 21, 2021)
Alternative to collective coordinates

Collective coordinates provide a powerful tool for separating collective and elementary excitations, allowing both to be treated in the full quantum theory. The price is a canonical transformation which leads to a complicated starting point for subsequent calculations. Sometimes the collective behavior of a soliton is simple but nontrivial, and one is interested in the elementary excitations. We show that in this case an alternative prescription suffices, in which the canonical transformation is not necessary. The use of a nonperturbative operator which creates a soliton state allows the theory to be constructed perturbatively in terms of the soliton normal modes. We show how translation invariance may be perturbatively imposed. We apply this to construct the two-loop ground state of an arbitrary scalar kink.
Voltage Inference for and Coordination of Distributed Voltage Controls in Extremely-High DER-Penetration Distribution Networks

The unique problems and phenomena in the distributed voltage control of large-scale power distribution systems with extremely-high DER-penetration are targeted in this paper. First, a DER-explicit distribution network model and voltage sensitivity are derived. Based on that, a voltage inference method is implemented to fill the gap of measurement insufficiency in the grid-edge areas. Then, autonomous Q control being implemented in each local area, a $\overline{Q}$-coordinated P control is designed to coordinate the reactive and real power controls. All the algorithms have been tested in standard and synthetic systems, and have expected results. Moreover, an open-source software platform, which integrates the modeling of communication networks, DER controls, and power networks, is developed to enable the distributed control and optimization algorithms in the grid simulation of the large-scale distribution systems.
Longitudinal changes in the bioactive proteins in human milk of the Chinese population: A systematic review

Abstract This systematic review aimed at investigating longitudinal changes in human milk bioactive protein concentrations in Chinese population. Both English and Chinese databases were searched. The data were pooled into six defined lactation stages. Weighted means of protein concentrations in each stage and the statistical significance of means of different lactation stages were calculated. The data of 11 bioactive proteins were retrieved. Concentrations of sIgA, IgM, and IgG decreased sharply during the first 14 days of lactation. The levels of α‐lactalbumin, lactoferrin, and β‐casein also decreased throughout lactation. Conversely, lysozyme levels increased over lactation. The changing patterns of the serum albumin, osteopontin, and bile salt‐stimulated lipase (BSSL) were not conclusive. This study represents the most comprehensive summary of bioactive proteins in Chinese human milk. In the future, mass spectrometry‐based analysis of human milk proteomics may be used to investigate the longitudinal changes of many more bioactive proteins.
Effects of Future Information and Trajectory Complexity on Kinematic Signal and Muscle Activation during Visual-Motor Tracking

Visual-motor tracking movement is a common and essential behavior in daily life. However, the contribution of future information to visual-motor tracking performance is not well understood in current research. In this study, the visual-motor tracking performance with and without future-trajectories was compared. Meanwhile, three task demands were designed to investigate their impact. Eighteen healthy young participants were recruited and instructed to track a target on a screen by stretching/flexing their elbow joint. The kinematic signals (elbow joint angle) and surface electromyographic (EMG) signals of biceps and triceps were recorded. The normalized integrated jerk (NIJ) and fuzzy approximate entropy (fApEn) of the joint trajectories, as well as the multiscale fuzzy approximate entropy (MSfApEn) values of the EMG signals, were calculated. Accordingly, the NIJ values with the future-trajectory were significantly lower than those without future-trajectory (p-value < 0.01). The smoother movement with future-trajectories might be related to the increasing reliance of feedforward control. When the task demands increased, the fApEn values of joint trajectories increased significantly, as well as the MSfApEn of EMG signals (p-value < 0.05). These findings enrich our understanding about visual-motor control with future information.
The C‐degron pathway eliminates mislocalized proteins and products of deubiquitinating enzymes

Protein termini are determinants of protein stability. Proteins bearing degradation signals, or degrons, at their amino‐ or carboxyl‐termini are eliminated by the N‐ or C‐degron pathways, respectively. We aimed to elucidate the function of C‐degron pathways and to unveil how normal proteomes are exempt from C‐degron pathway‐mediated destruction. Our data reveal that C‐degron pathways remove mislocalized cellular proteins and cleavage products of deubiquitinating enzymes. Furthermore, the C‐degron and N‐degron pathways cooperate in protein removal. Proteome analysis revealed a shortfall in normal proteins targeted by C‐degron pathways, but not of defective proteins, suggesting proteolysis‐based immunity as a constraint for protein evolution/selection. Our work highlights the importance of protein termini for protein quality surveillance, and the relationship between the functional proteome and protein degradation pathways.
Two- and Three-Photon Luminescence of Au Nanoparticles and Resonant Energy Transfer from CdSe Quantum Dots

The relative probability of two- and three-photon absorption in Au nanoparticles was adjusted by tuning the surface-plasmon-resonance (SPR) wavelength and the excitation intensity. Consequently, highly efficient three-photon luminescence from Au nanoparticles with strong SPR enhancement was observed. The decay rate and polarization of two- and three-photon luminescence from Au nanoparticles were comparatively studied. Furthermore, the multiphoton luminescence from Au nanoparticles was used to investigate the resonant energy transfer from CdSe semiconductor quantum dots.
Drosophila melanogaster Y Chromosome Genes Affect Male Sensitivity to Microbial Infections

Simple Summary This manuscript focuses on the protein-encoding genes of the Drosophila melanogaster Y chromosome and their role in immunity. Since their discovery, these genes have mainly been studied for their role(s) in male fertility, such as spermatogenesis. Two previously published papers have linked the polymorphism within the Y chromosome and immunity. Currently, there is no research article to our knowledge that has studied the effect of the individual genes of the Y chromosome on fly immunity. Here, we aim to address the lack of immunity-related knowledge of Y chromosome genes by determining the effect of many of these genes on male sensitivity to microbial infections. We challenged loss-of-function gene mutants with bacterial and fungal pathogens orally and observed any significant fly survival changes. We discovered several genes affecting male sensitivity to both bacterial and fungal infections. While most of the Y chromosome genes were found to reduce sensitivity, we found one gene increases sensitivity to fungal infection. Because several genes were found to increase male sensitivity to microbial infections, inhibitors for such genes could be introduced in areas where fruit flies are pests. Amid declining bee populations, Diptera pollinators could be protected from fungal infections with Y-gene inhibitors. Abstract The genders of Drosophila melanogaster vary in their sensitivities to microbial pathogens. While many of the immunity-related genes are located on the X chromosome, the polymorphisms within the Y chromosome were also shown to affect the immunity of flies. In this study, we investigated the necessity of individual genes on the Y chromosome (Y-genes) for male sensitivity to microbes. We identified several Y-genes whose genetic inactivation either increases or decreases the sensitivity of males to gastrointestinal infections with fungal Saccharomyces cerevisiae and bacterial Serratia liquefaciens. Specifically, the loss of function mutations in fly kl-5 and Ppr-Y Y-genes lead to increased and decreased sensitivity of males to fungal challenge, respectively, compared to female sensitivity. In contrast, mutations in Drosophila Pp1-Y1, kl-5, kl-3, Ppr-Y, CCY, and FDY Y-genes lead to increased sensitivity of males to bacterial infection, compared to females. Moreover, while these Y-genes are necessary, the Y chromosome is not sufficient for the sensitivity of males to microbes, since the sensitivity of XXY females to fungal and bacterial challenges was not different from the sensitivity of wild-type female flies, compared to males. This study assigns a new immunity-related function to numerous Y-genes in D. melanogaster.
Accumulation of styrene oligomers alters lipid membrane phase order and miscibility

Significance Accumulation of nanopollutants in lifeforms has become the subject of increasing concern, but effects are not understood. Biological systems are inherently complex, and therefore any small variations on the membrane properties can potentially perturb cell functionality. In this study we observe that the presence of styrene oligomers in lipid membranes alters their phase behavior, with stronger changes occurring in more complex systems, which could translate into potential cellular disruption. This study provides evidence that the presence of nanopollutants in the membrane may alter its fundamental properties and affect cell viability. Growth of plastic waste in the natural environment, and in particular in the oceans, has raised the accumulation of polystyrene and other polymeric species in eukyarotic cells to the level of a credible and systemic threat. Oligomers, the smallest products of polymer degradation or incomplete polymerization reactions, are the first species to leach out of macroscopic or nanoscopic plastic materials. However, the fundamental mechanisms of interaction between oligomers and polymers with the different cell components are yet to be elucidated. Simulations performed on lipid bilayers showed changes in membrane mechanical properties induced by polystyrene, but experimental results performed on cell membranes or on cell membrane models are still missing. We focus here on understanding how embedded styrene oligomers affect the phase behavior of model membranes using a combination of scattering, fluorescence, and calorimetric techniques. Our results show that styrene oligomers disrupt the phase behavior of lipid membranes, modifying the thermodynamics of the transition through a spatial modulation of lipid composition.
Metastatic-prone telomerase reverse transcriptase (TERT) promoter and v-Raf murine sarcoma viral oncogene homolog B (BRAF) mutated tall cell variant of papillary thyroid carcinoma arising in ectopic thyroid tissue

Abstract Rationale: Mutations of the v-Raf murine sarcoma viral oncogene homolog B (BRAF) oncogene and telomerase reverse transcriptase (TERT) promoter region are indicators of poor prognosis in papillary thyroid carcinoma (PTC) and might predict future occurrences of distant metastases. However, the clinical significance of these genetic aberrancies in PTCs arising in ectopic locations is not well established. Patient concerns: We describe a patient with a previous history of radioiodine (RAI)-treated hyperthyroidism and a surgically resected right-sided follicular thyroid adenoma. In 2013, a 6 mm follicular variant papillary thyroid carcinoma was diagnosed following a left-sided thyroid lobectomy. The central compartment displayed 9 tumor-free lymph nodes, and no adjuvant treatment was planned. Diagnoses: Three years later, a 26 mm pre-tracheal relapse was noted, however, the excised lesion was consistent with a tall cell variant of papillary thyroid carcinoma (TCV-PTC) arising in ectopic thyroid tissue. RAI treatment was commenced. Four years later, a 5 mm subcutaneous lesion in the anterior neck was surgically removed and diagnosed as metastatic TCV-PTC with a codon 600 BRAF mutation and a C228T TERT promoter mutation. Interventions: RAI treatment was re-initiated. Molecular re-examination of the primary follicular variant papillary thyroid carcinoma demonstrated a codon 600 BRAF mutation and a TERT promoter wildtype sequence, while the primary TCV-PTC was positive for mutations in both codon 600 of BRAF as well as the TERT promoter. Outcomes: The patient is alive and well without signs of relapse 7 months after the latest round of RAI. Lessons: We conclude that the occurrence of combined BRAF and TERT promoter mutations in the primary lesion from 2016 was associated to the manifestation of distant metastases 4 years later, strengthening the benefit of mutational screening of these genes in clinical routine for thyroid carcinomas arising in aberrant locations.