bluuebunny/crossref_metadata_2025_split huggingface dataset:
MSCs and their exosomes: a rapidly evolving approach in the context of cutaneous wounds therapy
Authors: Marofi Faroogh , Alexandrovna Kozlitina Iuliia , Margiana Ria , Bahramali Mahta , Suksatan Wanich , Abdelbasset Walid Kamal , Chupradit Supat , Nasimi Maryam , Maashi Marwah Suliman 
Published: December 2021

AbstractCurrently, mesenchymal stem/stromal stem cell (MSC) therapy has become a promising option for accelerating cutaneous wound healing. In vivo reports have outlined the robust competences of MSCs to offer a solid milieu by inhibition of inflammatory reactions, which in turn, enables skin regeneration. Further, due to their great potential to stimulate angiogenesis and also facilitate matrix remodeling, MSCs hold substantial potential as future therapeutic strategies in this context. The MSCs-induced wound healing is thought to mainly rely on the secretion of a myriad of paracrine factors in addition to their direct differentiation to skin-resident cells. Besides, MSCs-derived exosomes as nanoscale and closed membrane vesicles have recently been suggested as an effective and cell-free approach to support skin regeneration, circumventing the concerns respecting direct application of MSCs. The MSCs-derived exosomes comprise molecular components including lipid, proteins, DNA, microRNA, and also mRNA, which target molecular pathways and also biological activities in recipient cells (e.g., endothelial cell, keratinocyte, and fibroblast). The secreted exosome modifies macrophage activation, stimulates angiogenesis, and instigates keratinocytes and dermal fibroblast proliferations as well as migrations concurrently regulate inherent potential of myofibroblast for adjustment of turnover of the ECM. In the present review, we will focus on the recent findings concerning the application of MSCs and their derivative exosome to support wound healing and skin regeneration, with special focus on last decade in vivo reports.
Role of PD-L1 in licensing immunoregulatory function of dental pulp mesenchymal stem cells
Authors: Di Tinco Rosanna , Bertani Giulia , Pisciotta Alessandra , Bertoni Laura , Pignatti Elisa , Maccaferri Monia , Bertacchini Jessika , Sena Paola , Vallarola Antonio , Tupler Rossella , Croci Stefania , Bonacini Martina , Salvarani Carlo , Carnevale Gianluca 
Published: December 2021

Abstract
Background
Dental pulp stem cells (DPSCs) are low immunogenic and hold immunomodulatory properties that, along with their well-established multi-potency, might enhance their potential application in autoimmune and inflammatory diseases. The present study focused on the ability of DPSCs to modulate the inflammatory microenvironment through PD1/PD-L1 pathway.

Methods
Inflammatory microenvironment was created in vitro by the activation of T cells isolated from healthy donors and rheumatoid arthritis (RA) patients with anti-CD3 and anti-CD28 antibodies. Direct and indirect co-cultures between DPSCs and PBMCs were carried out to evaluate the activation of immunomodulatory checkpoints in DPSCs and the inflammatory pattern in PBMCs.

Results
Our data suggest that the inflammatory stimuli trigger DPSCs immunoregulatory functions that can be exerted by both direct and indirect contact. As demonstrated by using a selective PD-L1 inhibitor, DPSCs were able to activate compensatory pathways targeting to orchestrate the inflammatory process by modulating pro-inflammatory cytokines in pre-activated T lymphocytes. The involvement of PD-L1 mechanism was also observed in autologous inflammatory status (pulpitis) and after direct exposure to pre-activated T cells from RA patients suggesting that immunomodulatory/anti-inflammatory properties are strictly related to their stemness status.

Conclusions
Our findings point out that the communication with the inflammatory microenvironment is essential in licensing their immunomodulatory properties.
Receiver selection for multi-target tracking in multi-static Doppler radar systems
Authors: Zhu Yun , Zhao Li , Zhang Yumei , Wu Xiaojun 
Published: December 2021

AbstractThis paper presents a novel receiver selection method for multi-target tracking in multi-static Doppler radar systems. The assumption is that in the surveillance volume of interest, a single transmitter with a known frequency is active and several spatially distributed radar receivers collect and report Doppler-only measurements. The Doppler measurements are not only affected by the additive noise but also contaminated by false and missed detections. In this paper, multi-target tracking is obtained by modeling the multi-target state as a labeled multi-Bernoulli random finite set and receiver selection is implemented during tracking. Receiver selection is solved under the partially observed Markov decision framework, and the variance of the cardinality estimate is used as the selection criterion. To increase the diversity of the selected sensors and overcome the low observability of the Doppler measurement, the receivers selected at previous time steps are taken into account by adding a window. Simulation studies demonstrate the tracking performance of the proposed method with different window lengths. The results show that the observability of the target state is a crucial factor in determining the performance of receiver selection. The proposed method with a suitable window length can effectively improve the tracking accuracy.
Detection of illicit cryptomining using network metadata
Authors: Russo Michele , Šrndić Nedim , Laskov Pavel 
Published: December 2021

AbstractIllicit cryptocurrency mining has become one of the prevalent methods for monetization of computer security incidents. In this attack, victims’ computing resources are abused to mine cryptocurrency for the benefit of attackers. The most popular illicitly mined digital coin is Monero as it provides strong anonymity and is efficiently mined on CPUs.Illicit mining crucially relies on communication between compromised systems and remote mining pools using the de facto standard protocol Stratum. While prior research primarily focused on endpoint-based detection of in-browser mining, in this paper, we address network-based detection of cryptomining malware in general. We propose XMR-Ray, a machine learning detector using novel features based on reconstructing the Stratum protocol from raw NetFlow records. Our detector is trained offline using only mining traffic and does not require privacy-sensitive normal network traffic, which facilitates its adoption and integration.In our experiments, XMR-Ray attained 98.94% detection rate at 0.05% false alarm rate, outperforming the closest competitor. Our evaluation furthermore demonstrates that it reliably detects previously unseen mining pools, is robust against common obfuscation techniques such as encryption and proxies, and is applicable to mining in the browser or by compiled binaries. Finally, by deploying our detector in a large university network, we show its effectiveness in protecting real-world systems.
Text-to-speech system for low-resource language using cross-lingual transfer learning and data augmentation
Authors: Byambadorj Zolzaya , Nishimura Ryota , Ayush Altangerel , Ohta Kengo , Kitaoka Norihide 
Published: December 2021

AbstractDeep learning techniques are currently being applied in automated text-to-speech (TTS) systems, resulting in significant improvements in performance. However, these methods require large amounts of text-speech paired data for model training, and collecting this data is costly. Therefore, in this paper, we propose a single-speaker TTS system containing both a spectrogram prediction network and a neural vocoder for the target language, using only 30 min of target language text-speech paired data for training. We evaluate three approaches for training the spectrogram prediction models of our TTS system, which produce mel-spectrograms from the input phoneme sequence: (1) cross-lingual transfer learning, (2) data augmentation, and (3) a combination of the previous two methods. In the cross-lingual transfer learning method, we used two high-resource language datasets, English (24 h) and Japanese (10 h). We also used 30 min of target language data for training in all three approaches, and for generating the augmented data used for training in methods 2 and 3. We found that using both cross-lingual transfer learning and augmented data during training resulted in the most natural synthesized target speech output. We also compare single-speaker and multi-speaker training methods, using sequential and simultaneous training, respectively. The multi-speaker models were found to be more effective for constructing a single-speaker, low-resource TTS model. In addition, we trained two Parallel WaveGAN (PWG) neural vocoders, one using 13 h of our augmented data with 30 min of target language data and one using the entire 12 h of the original target language dataset. Our subjective AB preference test indicated that the neural vocoder trained with augmented data achieved almost the same perceived speech quality as the vocoder trained with the entire target language dataset. Overall, we found that our proposed TTS system consisting of a spectrogram prediction network and a PWG neural vocoder was able to achieve reasonable performance using only 30 min of target language training data. We also found that by using 3 h of target language data, for training the model and for generating augmented data, our proposed TTS model was able to achieve performance very similar to that of the baseline model, which was trained with 12 h of target language data.
A recursive expectation-maximization algorithm for speaker tracking and separation
Authors: Schwartz Ofer , Gannot Sharon 
Published: December 2021

AbstractThe problem of blind and online speaker localization and separation using multiple microphones is addressed based on the recursive expectation-maximization (REM) procedure. A two-stage REM-based algorithm is proposed: (1) multi-speaker direction of arrival (DOA) estimation and (2) multi-speaker relative transfer function (RTF) estimation. The DOA estimation task uses only the time frequency (TF) bins dominated by a single speaker while the entire frequency range is not required to accomplish this task. In contrast, the RTF estimation task requires the entire frequency range in order to estimate the RTF for each frequency bin. Accordingly, a different statistical model is used for the two tasks. The first REM model is applied under the assumption that the speech signal is sparse in the TF domain, and utilizes a mixture of Gaussians (MoG) model to identify the TF bins associated with a single dominant speaker. The corresponding DOAs are estimated using these bins. The second REM model is applied under the assumption that the speakers are concurrently active in all TF bins and consequently applies a multichannel Wiener filter (MCWF) to separate the speakers. As a result of the assumption of the concurrent speakers, a more precise TF map of the speakers’ activity is obtained. The RTFs are estimated using the outputs of the MCWF-beamformer (BF), which are constructed using the DOAs obtained in the previous stage. Next, using the linearly constrained minimum variance (LCMV)-BF that utilizes the estimated RTFs, the speech signals are separated. The algorithm is evaluated using real-life scenarios of two speakers. Evaluation of the mean absolute error (MAE) of the estimated DOAs and the separation capabilities, demonstrates significant improvement w.r.t. a baseline DOA estimation and speaker separation algorithm.
An overview of generic tools for information-theoretic secrecy performance analysis over wiretap fading channels
Authors: Kong Long , Ai Yun , Lei Lei , Kaddoum Georges , Chatzinotas Symeon , Ottersten Björn 
Published: December 2021

AbstractPhysical layer security (PLS) has been proposed to afford an extra layer of security on top of the conventional cryptographic techniques. Unlike the conventional complexity-based cryptographic techniques at the upper layers, physical layer security exploits the characteristics of wireless channels, e.g., fading, noise, interference, etc., to enhance wireless security. It is proved that secure transmission can benefit from fading channels. Accordingly, numerous researchers have explored what fading can offer for physical layer security, especially the investigation of physical layer security over wiretap fading channels. Therefore, this paper aims at reviewing the existing and ongoing research works on this topic. More specifically, we present a classification of research works in terms of the four categories of fading models: (i) small-scale, (ii) large-scale, (iii) composite, and (iv) cascaded. To elaborate these fading models with a generic and flexible tool, three promising candidates, including the mixture gamma (MG), mixture of Gaussian (MoG), and Fox’sH-function distributions, are comprehensively examined and compared. Their advantages and limitations are further demonstrated via security performance metrics, which are designed as vivid indicators to measure how perfect secrecy is ensured. Two clusters of secrecy metrics, namely (i) secrecy outage probability (SOP), and the lower bound of SOP; and (ii) the probability of nonzero secrecy capacity (PNZ), the intercept probability, average secrecy capacity (ASC), and ergodic secrecy capacity, are displayed and, respectively, deployed in passive and active eavesdropping scenarios. Apart from those, revisiting the secrecy enhancement techniques based on Wyner’s wiretap model, the on-off transmission scheme, jamming approach, antenna selection, and security region are discussed.
Beyond private 5G networks: applications, architectures, operator models and technological enablers
Authors: Maman Mickael , Calvanese-Strinati Emilio , Dinh Lam Ngoc , Haustein Thomas , Keusgen Wilhelm , Wittig Sven , Schmieder Mathis , Barbarossa Sergio , Merluzzi Mattia , Costanzo Francesca , Sardellitti Stefania , Klessig Henrik , Kendre Savita Vitthalrao , Munaretto Daniele , Centenaro Marco , di Pietro Nicola , Liang Shuo-Peng , Chih Kuan-Yi , Luo Jack Shi-Jie , Kao Ling-Chih , Huang Jiun-Cheng , Huang Jen-Sheng , Wang Tzu-Ya 
Published: December 2021

AbstractPrivate networks will play a key role in 5G and beyond to enable smart factories with the required better deployment, operation and flexible usage of available resource and infrastructure. 5G private networks will offer a lean and agile solution to effectively deploy and operate services with stringent and heterogeneous constraints in terms of reliability, latency, re-configurability and re-deployment of resources as well as issues related to governance and ownership of 5G components, and elements. In this paper, we present a novel approach to operator models, specifically targeting 5G and beyond private networks. We apply the proposed operator models to different network architecture options and to a selection of relevant use cases offering mixed private–public network operator governance and ownership. Moreover, several key enabling technologies have been identified for 5G private networks. Before the deployment, stakeholders should consider spectrum allocation and on-site channel measurements in order to fully understand the propagation characteristic of a given environment and to set up end-to-end system parameters. During the deployment, a monitoring tools will support to validate the deployment and to make sure that the end-to-end system meet the target KPI. Finally, some optimization can be made individually for service placement, network slicing and orchestration or jointly at radio access, multi-access edge computing or core network level.
Shape adaptive IRS based SAG IoT network
Authors: Qi Fei , Li Wenjing , Yu Peng , Feng Lei , Zhou Fanqin 
Published: December 2021

Abstract6G technology connects physical and digital, and ubiquitous 6G services will provide convenience to users around the world. The concept of the world-earth integrated network is to seamlessly integrate these three subnets to better adapt to future development. This article introduces the world-earth integrated network and shape-adaptive IRS antenna technology. The shape-adaptive IRS antenna described in this article is made of flexible materials, and the physical shape of the antenna can be changed according to different situations, and specific radiation beams can be generated according to functional requirements. And the effectiveness of the shape-adaptive IRS antenna technology has been proven in the simulation results.
Effective capacity analysis of reconfigurable intelligent surfaces aided NOMA network
Authors: Li Geng , Liu Huiling , Huang Gaojian , Li Xingwang , Raj Bichu , Kara Ferdi 
Published: December 2021

AbstractThe future sixth generation (6G) is going to face the significant challenges of massive connections and green communication. Recently, reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) have been proposed as two key technologies to solve the above problems. Motivated by this fact, we consider a downlink RIS-aided NOMA system, where the source aims to communicate with the two NOMA users via RIS. Considering future network supporting real-time service, we investigate the system performance with the view of effective capacity (EC), which is an important evaluation metric of delay sensitive systems. Specifically, we derive the analytical expressions of the EC of the near and far users. To obtain more useful insights, we deduce the analytical approximation expressions of the EC in the low signal-to-noise-ratio approximation by utilizing Taylor expansion. Moreover, we provide the results of orthogonal multiple access (OMA) for the purpose of comparison. It is found that (1) The number of RIS components and the transmission power of the source have important effects on the performance of the considered system; (2) Compared with OMA, NOMA system has higher EC due to the short transmission time.
Existence of ground state solutions for a class of Choquard equations with local nonlinear perturbation and variable potential
Authors: Zhang Jing , Zhang Qiongfen 
Published: December 2021

AbstractIn this paper, we focus on the existence of solutions for the Choquard equation$$\begin{aligned} \textstyle\begin{cases} {-}\Delta {u}+V(x)u=(I_{\alpha }* \vert u \vert ^{\frac{\alpha }{N}+1}) \vert u \vert ^{ \frac{\alpha }{N}-1}u+\lambda \vert u \vert ^{p-2}u,\quad x\in \mathbb{R}^{N}; \\ u\in H^{1}(\mathbb{R}^{N}), \end{cases}\displaystyle \end{aligned}$${−Δu+V(x)u=(Iα∗|u|αN+1)|u|αN−1u+λ|u|p−2u,x∈RN;u∈H1(RN),where$\lambda >0$λ>0is a parameter,$\alpha \in (0,N)$α∈(0,N),$N\ge 3$N≥3,$I_{\alpha }: \mathbb{R}^{N}\to \mathbb{R}$Iα:RN→Ris the Riesz potential. As usual,$\alpha /N+1$α/N+1is the lower critical exponent in the Hardy–Littlewood–Sobolev inequality. Under some weak assumptions, by using minimax methods and Pohožaev identity, we prove that this problem admits a ground state solution if$\lambda >\lambda _{*}$λ>λ∗for some given number$\lambda _{*}$λ∗in three cases: (i)$2< p<\frac{4}{N}+2$2<p<4N+2, (ii)$p=\frac{4}{N}+2$p=4N+2, and (iii)$\frac{4}{N}+2< p<2^{*}$4N+2<p<2∗. Our result improves the previous related ones in the literature.
Stability criteria for nonlinear Volterra integro-dynamic matrix Sylvester systems on measure chains
Authors: Ayyalappagari Sreenivasulu , Bhogapurapu Venkata Appa Rao 
Published: December 2021

AbstractIn this paper, we establish sufficient conditions for various stability aspects of a nonlinear Volterra integro-dynamic matrix Sylvester system on time scales. We convert the nonlinear Volterra integro-dynamic matrix Sylvester system on time scale to an equivalent nonlinear Volterra integro-dynamic system on time scale using vectorization operator. Sufficient conditions are obtained to this system for stability, asymptotic stability, exponential stability, and strong stability. The obtained results include various stability aspects of the matrix Sylvester systems in continuous and discrete models.
Strategies for managing spring frost risks in orchards: effectiveness and conditionality—A systematic review protocol
Authors: Drepper Bianca , Bamps Brecht , Gobin Anne , Van Orshoven Jos 
Published: December 2021

Abstract
Background
Spring frosts pose an important threat to orchard productivity in temperate zones and predictions of future occurrences do not exclude damaging events. However, there is no up-to-date and systematic comparison of the effectiveness and conditionality of the existing passive and active damage prevention strategies. This review seeks to answer the questions “How do the performances of spring frost damage reduction strategies in temperate fruit orchards compare?” and “How do environmental conditions affect frost damage reduction strategies in temperate fruit orchards?”.

Methods and output
The review covers on-site frost damage prevention mechanisms and interventions for the most important temperate pome, stone and citrus fruit trees as well as grapevine. Searches include the core collection and regional databases on the Web of Science platform, Scopus, as well as specialized libraries like Agris, Agricola, CAB Abstracts, Groenekennis and selected institutional websites. Included studies report on the effectiveness of at least one intervention in reducing spring frost damage or increasing temperatures in the field. The validity of the studies will be evaluated based on their risk of general research bias and on topic-specific, stakeholder co-designed validity criteria. Data will be extracted regarding the study setup (study design, location, characteristics of frosts) and the resulting temperature increase, crop development alteration and/or damage reductions. The effectiveness of interventions will be evaluated in terms of yields, damage to flowers, ambient temperature and/or crop development. An Evidence Atlas will identify general and geographic research gaps, as well as research trends. Meta-regression of effectiveness on environmental conditions will be attempted.
Eco-friendly High-Strength Refractory Concrete Containing Calcium Alumina Cement by Reusing Granite Waste as Aggregate
Authors: Shirani Kourosh , Reisi Mohammad , Savadkoohi Mohammad Safari 
Published: December 2021

AbstractBesides preventing valuable natural resources from going to waste, using stone waste from stone processing plants in concrete helps reduce environmental pollution and, therefore, offers a convenient route to sustainable development. The present study aims to use granite waste (GW) in high-strength refractory concrete. Sixteen high-strength refractory concrete mixes, including two water-to-binder ratios (W/B = 0.17 and 0.2), two silica-fume-to-binder ratios (SF/B = 0.15 and 0.2), two binder contents (B = 1200 and 1400 kg/m3), and two replacement ratios of silica sand by granite waste (GW/Agg = 0 and 50%) were designed and prepared with high-alumina cement (HAC). The concrete specimens were exposed to 1200 °C. Compressive and flexural strength and scanning electron microscopy (SEM) tests were performed on specimens of concrete mixes before and after heating. It was found that in specimens with high binder content (1400 kg/m3), replacing 50% silica sand with GW (GW/Agg = 50%) in refractory concrete improves compressive and flexural strengths by 3–15 and 4–24% before heating, respectively. It was also shown that using GW to replace silica aggregates in concrete specimens with a 1200 kg/m3 binder content not only did not undermine, but also improved the compressive and flexural strengths of refractory concrete after heating by 20–78% and 15–60%, respectively, as a result of sintering. Meanwhile, in the case of the concrete with 1400 kg/m3 binder content, adding GW exacerbated its loss of compressive and flexural strengths after heating due to little or lack of sintering.