### Recent Submissions

• #### EMF-Aware Cellular Networks in RIS-Assisted Environments

(2021-01-21) [Preprint]
The dense deployment of the 5th-generation cellular networks (5G) and beyond has triggered health concerns due to the electric and magnetic fields (EMF) exposure. In this paper, we propose minimizing the populations’ exposure to EMF by considering a smart radio environment with a reconfigurable intelligent surface (RIS). We propose a novel algorithm for the RIS phase design that minimizes an exposure index (EI), in terms of the specific absorption rate (SAR), while maintaining a minimum target quality of service (QoS). The proposed algorithm achieves up to 60% and 50% reduction in EI compared to schemes without RISs and with non-optimized RIS, respectively.
• #### Wide range tunable bandgap and composition β-phase (AlGa)2O3 thin film by thermal annealing

(Applied Physics Letters, AIP Publishing, 2021-01-18) [Article]
We have demonstrated wide bandgap and composition range b-(AlxGa1x)2O3 thin films by employing thermal annealing of b-Ga2O3/ sapphire templates. With proper annealing conditions at 1000–1500 C, the b-Ga2O3 thin films transformed to the b-(AlxGa1x)2O3 thin films with different bandgaps and compositions due to the Al diffusion from sapphire. Meanwhile, the Ga atoms diffused into sapphire. The interdiffusion process caused an increased film thickness, which was enhanced in proportion to the annealing temperature. It was confirmed by secondary ion mass spectrometry (SIMS) and transmission electron microscopy. Thus, higher temperatures resulted in high Al contents in the b-(AlxGa1x)2O3 films. Also, the SIMS measurements show highly homogeneous Al contents throughout the b-(AlxGa1x)2O3 films annealed at 1200 C and above. Evaluated by x-ray diffraction (XRD), the Al content range of the samples is 0–0.81 for the b-Ga2O3 templates without annealing and with annealing up to 1500 C. Evaluated by UV-Vis spectroscopy, the optical bandgap range of the samples is 4.88–6.38 eV for the b-Ga2O3 templates without annealing and with annealing up to 1400 C, translating to the Al content range of 0–0.72. Moreover, the crystal quality of b-(AlxGa1x)2O3 improved as the Al composition became larger due to higher annealing temperatures. The proposed technique is promising for the preparation of b-(AlxGa1x)2O3 thin films without employing “direct-growth” techniques.
• #### Change-point detection using spectral PCA for multivariate time series

(arXiv, 2021-01-12) [Preprint]
We propose a two-stage approach Spec PC-CP to identify change points in multivariate time series. In the first stage, we obtain a low-dimensional summary of the high-dimensional time series by Spectral Principal Component Analysis (Spec-PCA). In the second stage, we apply cumulative sum-type test on the Spectral PCA component using a binary segmentation algorithm. Compared with existing approaches, the proposed method is able to capture the lead-lag relationship in time series. Our simulations demonstrate that the Spec PC-CP method performs significantly better than competing methods for detecting change points in high-dimensional time series. The results on epileptic seizure EEG data and stock data also indicate that our new method can efficiently {detect} change points corresponding to the onset of the underlying events.
• #### MAAS: Multi-modal Assignation for Active Speaker Detection

(arXiv, 2021-01-11) [Preprint]
Active speaker detection requires a solid integration of multi-modal cues. While individual modalities can approximate a solution, accurate predictions can only be achieved by explicitly fusing the audio and visual features and modeling their temporal progression. Despite its inherent muti-modal nature, current methods still focus on modeling and fusing short-term audiovisual features for individual speakers, often at frame level. In this paper we present a novel approach to active speaker detection that directly addresses the multi-modal nature of the problem, and provides a straightforward strategy where independent visual features from potential speakers in the scene are assigned to a previously detected speech event. Our experiments show that, an small graph data structure built from a single frame, allows to approximate an instantaneous audio-visual assignment problem. Moreover, the temporal extension of this initial graph achieves a new state-of-the-art on the AVA-ActiveSpeaker dataset with a mAP of 88.8\%.
• #### Coating of Conducting and Insulating Threads with Porous MOF Particles through Langmuir-Blodgett Technique

(Nanomaterials, MDPI AG, 2021-01-10) [Article]
• #### Towards Analyzing Semantic Robustness of Deep Neural Networks

(Springer International Publishing, 2021-01-10) [Conference Paper]
Despite the impressive performance of Deep Neural Networks (DNNs) on various vision tasks, they still exhibit erroneous high sensitivity toward semantic primitives (e.g. object pose). We propose a theoretically grounded analysis for DNN robustness in the semantic space. We qualitatively analyze different DNNs’ semantic robustness by visualizing the DNN global behavior as semantic maps and observe interesting behavior of some DNNs. Since generating these semantic maps does not scale well with the dimensionality of the semantic space, we develop a bottom-up approach to detect robust regions of DNNs. To achieve this, we formalize the problem of finding robust semantic regions of the network as optimizing integral bounds and we develop expressions for update directions of the region bounds. We use our developed formulations to quantitatively evaluate the semantic robustness of different popular network architectures. We show through extensive experimentation that several networks, while trained on the same dataset and enjoying comparable accuracy, do not necessarily perform similarly in semantic robustness. For example, InceptionV3 is more accurate despite being less semantically robust than ResNet50. We hope that this tool will serve as a milestone towards understanding the semantic robustness of DNNs.
• #### An efficient and stable solar flow battery enabled by a single-junction GaAs photoelectrode.

(Nature communications, Springer Science and Business Media LLC, 2021-01-09) [Article]
Converting and storing solar energy and releasing it on demand by using solar flow batteries (SFBs) is a promising way to address the challenge of solar intermittency. Although high solar-to-output electricity efficiencies (SOEE) have been recently demonstrated in SFBs, the complex multi-junction photoelectrodes used are not desirable for practical applications. Here, we report an efficient and stable integrated SFB built with back-illuminated single-junction GaAs photoelectrode with an n-p-n sandwiched design. Rational potential matching simulation and operating condition optimization of this GaAs SFB lead to a record SOEE of 15.4% among single-junction SFB devices. Furthermore, the TiO2 protection layer and robust redox couples in neutral pH electrolyte enable the SFB to achieve stable cycling over 408 h (150 cycles). These results advance the utilization of more practical solar cells with higher photocurrent densities but lower photovoltages for high performance SFBs and pave the way for developing practical and efficient SFBs.
• #### Chromatin phosphoproteomics unravels a function for AT-hook motif nuclear localized protein AHL13 in PAMP-triggered immunity

(Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, 2021-01-08) [Article]
In many eukaryotic systems during immune responses, mitogen-activated protein kinases (MAPKs) link cytoplasmic signaling to chromatin events by targeting transcription factors, chromatin remodeling complexes, and the RNA polymerase machinery. So far, knowledge on these events is scarce in plants and no attempts have been made to focus on phosphorylation events of chromatin-associated proteins. Here we carried out chromatin phosphoproteomics upon elicitor-induced activation of Arabidopsis. The events in WT were compared with those in mpk3, mpk4, and mpk6 mutant plants to decipher specific MAPK targets. Our study highlights distinct signaling networks involving MPK3, MPK4, and MPK6 in chromatin organization and modification, as well as in RNA transcription and processing. Among the chromatin targets, we characterized the AT-hook motif containing nuclear localized (AHL) DNA-binding protein AHL13 as a substrate of immune MAPKs. AHL13 knockout mutant plants are compromised in pathogen-associated molecular pattern (PAMP)-induced reactive oxygen species production, expression of defense genes, and PAMP-triggered immunity. Transcriptome analysis revealed that AHL13 regulates key factors of jasmonic acid biosynthesis and signaling and affects immunity toward Pseudomonas syringae and Botrytis cinerea pathogens. Mutational analysis of the phosphorylation sites of AHL13 demonstrated that phosphorylation regulates AHL13 protein stability and thereby its immune functions.
• #### Transcriptomic analysis identifies organ-specific metastasis genes and pathways across different primary sites.

(Journal of translational medicine, Springer Science and Business Media LLC, 2021-01-08) [Article]
BackgroundMetastasis is the most devastating stage of cancer progression and often shows a preference for specific organs.MethodsTo reveal the mechanisms underlying organ-specific metastasis, we systematically analyzed gene expression profiles for three common metastasis sites across all available primary origins. A rank-based method was used to detect differentially expressed genes between metastatic tumor tissues and corresponding control tissues. For each metastasis site, the common differentially expressed genes across all primary origins were identified as organ-specific metastasis genes.ResultsPathways enriched by these genes reveal an interplay between the molecular characteristics of the cancer cells and those of the target organ. Specifically, the neuroactive ligand-receptor interaction pathway and HIF-1 signaling pathway were found to have prominent roles in adapting to the target organ environment in brain and liver metastases, respectively. Finally, the identified organ-specific metastasis genes and pathways were validated using a primary breast tumor dataset. Survival and cluster analysis showed that organ-specific metastasis genes and pathways tended to be expressed uniquely by a subgroup of patients having metastasis to the target organ, and were associated with the clinical outcome.ConclusionsElucidating the genes and pathways underlying organ-specific metastasis may help to identify drug targets and develop treatment strategies to benefit patients.
• #### Strong enhancement of Penning ionisation in cold Rydberg gases II: Tom and Jerry pairs for alkali-metal atoms

(Journal of Physics B: Atomic, Molecular and Optical Physics, IOP Publishing, 2021-01-08) [Article]
Penning ionisation (PI) processes involving pairs of Rydberg alkali-metal atoms, excited to different quantum states and experiencing dipole-dipole interactions, have a wide range of important properties in atomic physics. Within the framework of the semi-classical approximation, we have used both numerical and analytical approaches to examine the Penning autoionisation width dependence on the state quantum numbers in a quasi-molecule formed by the interacting partner atoms. We described the characteristics of optimal quantum numbers that lead to enhanced PI widths for the interacting Rydberg atom pairs of all alkali-metal atoms. The excited states of atoms in these pairs are asymmetric, resulting in a large atomic shell size difference: inspired by [1], we call such pair "Tom" and "Jerry" (for "big" and "small"). Compared to symmetric pairs, the optimal asymmetric pairs display a significant (by several orders of magnitude) increase in the PI rate. This property makes PI a relevant source for producing charged particles in cold Rydberg systems that spontaneously evolve into cold plasma. Contrary to hydrogen atoms examined in [1], the difference of quantum defects in alkali-metal atoms results in a strong Penning width dependence on the orbital quantum numbers l of the quasi-molecule. In particular, alkali-metal atoms exhibit two PI channels associated with bound-bound optical transitions showing ∆l = ±1 - individual and closely spaced (doublet-like) configurations of optimal pairs. Furthermore, we demonstrate that the presence of Förster resonances can lead to a notable (up to 5 times) increase of the PI efficiency.
• #### Laser-scribed Graphene Electrodes as an Electrochemical Immunosensing Platform for Cancer Biomarker ‘eIF3d’

(Electroanalysis, Wiley, 2021-01-08) [Article]
eIF3d is a protein biomarker which has a potential for the diagnosis of various cancers. Herein, a bio-platform was constructed for eIF3d sensing by using LSG and surface functionalization with anti eIF3d antibody via EDC/NHS chemistry. Following the surface modifications, XPS and several electrochemical methods were used. Difference in the signals were related to biomarker amounts between 75–500 ng/mL. LOD was calculated as 50.4 ng/mL. Selectivity of biosensor was tested by using of various interference molecules. EIF3d was also successfully detected in synthetic biological samples. Thus, to the best of our knowledge, this study is one of the rare studies on use of LSGs in immunosensor studies.
• #### Molecular basis for the adaptive evolution of environment sensing by H-NS proteins

(eLife, eLife Sciences Publications, Ltd, 2021-01-07) [Article]
The DNA-binding protein H-NS is a pleiotropic gene regulator in gram-negative bacteria. Through its capacity to sense temperature and other environmental factors, H-NS allows pathogens like Salmonella to adapt their gene expression to their presence inside or outside warm-blooded hosts. To investigate how this sensing mechanism may have evolved to fit different bacterial lifestyles, we compared H-NS orthologs from bacteria that infect humans, plants, and insects, and from bacteria that live on a deep-sea hypothermal vent. The combination of biophysical characterization, high-resolution proton-less NMR spectroscopy and molecular simulations revealed, at an atomistic level, how the same general mechanism was adapted to specific habitats and lifestyles. In particular, we demonstrate how environment-sensing characteristics arise from specifically positioned intra- or intermolecular electrostatic interactions. Our integrative approach clarified the exact modus operandi for H-NS–mediated environmental sensing and suggests that this sensing mechanism resulted from the exaptation of an ancestral protein feature.
• #### Landslide size matters: a new spatial predictive paradigm

(California Digital Library (CDL), 2021-01-07) [Preprint]
The standard definition of landslide hazard requires the estimation of where, when (or how frequently) and how large a given landslide event may be. The geomorphological community involved in statistical models has addressed the component pertaining to how large a landslide event may be by introducing the concept of landslide-event magnitude scale. This scale, which depends on the planimetric area of the given population of landslides, in analogy to the earthquake magnitude, has been expressed with a single value per landslide event. As a result, the geographic or spatially-distributed estimation of how large a population of landslide may be when considered at the slope scale, has been disregarded in statistically-based landslide hazard studies. Conversely, the estimation of the landslide extent has been commonly part of physically-based applications, though their implementation is often limited to very small regions.
• #### Tractable Bayes of Skew-Elliptical Link Models for Correlated Binary Data

(arXiv, 2021-01-06) [Preprint]
Correlated binary response data with covariates are ubiquitous in longitudinal or spatial studies. Among the existing statistical models the most well-known one for this type of data is the multivariate probit model, which uses a Gaussian link to model dependence at the latent level. However, a symmetric link may not be appropriate if the data are highly imbalanced. Here, we propose a multivariate skew-elliptical link model for correlated binary responses, which includes the multivariate probit model as a special case. Furthermore, we perform Bayesian inference for this new model and prove that the regression coefficients have a closed-form unified skew-elliptical posterior. The new methodology is illustrated by application to COVID-19 pandemic data from three different counties of the state of California, USA. By jointly modeling extreme spikes in weekly new cases, our results show that the spatial dependence cannot be neglected. Furthermore, the results also show that the skewed latent structure of our proposed model improves the flexibility of the multivariate probit model and provides better fit to our highly imbalanced dataset.
• #### A simple approach to proving the existence, uniqueness, and strong and weak convergence rates for a broad class of McKean--Vlasov equations

(arXiv, 2021-01-04) [Preprint]
By employing a system of interacting stochastic particles as an approximation of the McKean--Vlasov equation and utilizing classical stochastic analysis tools, namely It\^o's formula and Kolmogorov--Chentsov continuity theorem, we prove the existence and uniqueness of strong solutions for a broad class of McKean--Vlasov equations. Considering an increasing number of particles in the approximating stochastic particle system, we also prove the $L^p$ strong convergence rate and derive the weak convergence rates using the Kolmogorov backward equation and variations of the stochastic particle system. Our convergence rates were verified by numerical experiments which also indicate that the assumptions made here and in the literature can be relaxed.
• #### A Survey on Integrated Access and Backhaul Networks

(arXiv, 2021-01-04) [Preprint]
Benefiting from the usage of the high-frequency band, utilizing part of the large available bandwidth for wireless backhauling is feasible without considerable performance sacrifice. In this context, integrated access and backhaul (IAB) was proposed by 3GPP to reduce the fiber optics deployment cost of 5G and beyond networks. In this paper, we first give a brief introduction of IAB based on the 3GPP release. After that, we survey existing research on IAB networks, the integrations of IAB to cache-enabled network, optical communication transport network, and the non-terrestrial network. Finally, we discuss the challenges and opportunities that might arise while developing and commercializing IAB networks.
• #### Using BART for Multiobjective Optimization of Noisy Multiple Objectives

(arXiv, 2021-01-04) [Preprint]
Techniques to reduce the energy burden of an Industry 4.0 ecosystem often require solving a multiobjective optimization problem. However, collecting experimental data can often be either expensive or time-consuming. In such cases, statistical methods can be helpful. This article proposes Pareto Front (PF) and Pareto Set (PS) estimation methods using Bayesian Additive Regression Trees (BART), which is a non-parametric model whose assumptions are typically less restrictive than popular alternatives, such as Gaussian Processes. The performance of our BART-based method is compared to a GP-based method using analytic test functions, demonstrating convincing advantages. Finally, our BART-based methodology is applied to a motivating Industry 4.0 engineering problem.
• #### Engineered Microgels—Their Manufacturing and Biomedical Applications

(Micromachines, MDPI AG, 2021-01-01) [Article]
Microgels are hydrogel particles with diameters in the micrometer scale that can be fabricated in different shapes and sizes. Microgels are increasingly used for biomedical applications and for biofabrication due to their interesting features, such as injectability, modularity, porosity and tunability in respect to size, shape and mechanical properties. Fabrication methods of microgels are divided into two categories, following a top-down or bottom-up approach. Each approach has its own advantages and disadvantages and requires certain sets of materials and equipments. In this review, we discuss fabrication methods of both top-down and bottom-up approaches and point to their advantages as well as their limitations, with more focus on the bottom-up approaches. In addition, the use of microgels for a variety of biomedical applications will be discussed, including microgels for the delivery of therapeutic agents and microgels as cell carriers for the fabrication of 3D bioprinted cell-laden constructs. Microgels made from well-defined synthetic materials with a focus on rationally designed ultrashort peptides are also discussed, because they have been demonstrated to serve as an attractive alternative to much less defined naturally derived materials. Here, we will emphasize the potential and properties of ultrashort self-assembling peptides related to microgels.
• #### Uplink Massive Access in Mixed RF/FSO Satellite-aerial-Terrestrial Networks

(IEEE Transactions on Communications, IEEE, 2021) [Article]
This paper investigates the massive access for a satellite-aerial-terrestrial network (SATN), where a high-altitude platform (HAP) is deployed as a relay to assist the uplink transmission from terrestrial user equipment (UE) to satellite. Unlike previous works, we adopt radio frequency (RF) and free space optical for the aerial-terrestrial and satellite-aerial links, respectively. Specifically, by assuming that imperfect angular information (IAI) of each UE is known at the HAP, we develop a space division multiple access (SDMA) scheme to maximize the ergodic sum rate (ESR). To this end, we first exploit the IAI to calculate the analytical expression of channel correlation matrix. Then, by considering the limitation of array freedom, we propose a subspace-based UE grouping and scheduling scheme to cluster all UEs into groups. Next, we present a computationally effective beamforming (BF) scheme for each UE at HAP to efficiently implement SDMA in the RF link. Furthermore, a closed-form expression for the ESR of the SATN is derived to validate the proposed BF and SDMA schemes. Finally, simulation results corroborate the derived theoretical formulas and reveal the impacts of array size, angular estimation error, the number of UEs and scheduling threshold on the system performance.
• #### CIZSL++: Creativity Inspired Generative Zero-Shot Learning

(arXiv, 2021-01-01) [Preprint]
Zero-shot learning (ZSL) aims at understanding unseen categories with no training examples from class-level descriptions. To improve the discriminative power of ZSL, we model the visual learning process of unseen categories with inspiration from the psychology of human creativity for producing novel art. First, we propose CIZSL-v1 as a creativity inspired model for generative ZSL. We relate ZSL to human creativity by observing that ZSL is about recognizing the unseen, and creativity is about creating a likable unseen. We introduce a learning signal inspired by creativity literature that explores the unseen space with hallucinated class-descriptions and encourages careful deviation of their visual feature generations from seen classes while allowing knowledge transfer from seen to unseen classes. Second, CIZSL-v2 is proposed as an improved version of CIZSL-v1 for generative zero-shot learning. CIZSL-v2 consists of an investigation of additional inductive losses for unseen classes along with a semantic guided discriminator. Empirically, we show consistently that CIZSL losses can improve generative ZSL models on the challenging task of generalized ZSL from a noisy text on CUB and NABirds datasets. We also show the advantage of our approach to Attribute-based ZSL on AwA2, aPY, and SUN datasets. We also show that CIZSL-v2 has improved performance compared to CIZSL-v1.