Miracle-dz/UniFAR-FTUs huggingface dataset:
High-Robustness and Low-Complexity Joint Estimation of TOAs and CFOs for Multiuser SIMO OFDM Systems

We propose the first joint estimation scheme of time of arrivals (TOAs) and carrier frequency offsets (CFOs) for multiuser single-input multiple-output orthogonal frequency-division multiplexing systems. By designing carefully preambles of <inline-formula><tex-math notation="LaTeX">$K$</tex-math></inline-formula> users and utilizing the properties of the channels and CFO vectors, a complex <inline-formula><tex-math notation="LaTeX">$2K$</tex-math> </inline-formula>-dimensional joint multi-TOA and multi-CFO estimation problem is divided into <inline-formula> <tex-math notation="LaTeX">$2K$</tex-math></inline-formula> low-complexity 1-D problems. The integer and fractional parts of each user's CFO are estimated in an integral and closed form. Simulation results show that the proposed scheme provides higher TOA and CFO estimation accuracy than the existing methods, while at much lower computational complexity. The achieved TOA estimation performance is robust against CFOs and close to the idea case with no CFOs at the receiver.
A Tool for Traceable Evolution of Process Architectures

Evolving process architectures involves incremental enhancements to process components and inter-connections with time. In order to keep track of evolution of both parts and the whole, traceability through this evolution over a time continuum is essential. The paper presents a tool to manage and reason through evolution of process architectures. The tool uses graph based analysis techniques to facilitate reasoning through continuous modifications made to evolving process architecture. It implements a technique called Process Edification, achieving evolution and its traceability around both parts and the whole. The ideas behind the tool are illustrated and the tool is demonstrated with the help of a case of an evolving BPMN process.
Emergency Access Control Management Via Attribute Based Encrypted QR Codes

In dynamic environments such as disaster management, mechanisms for the controlled override of access restrictions, a.k. a. break-glass need to be supported. These access control mechanisms should ensure access to facilities, for example, an office building, in an emergency situation, without relying on the use of an online authentication server as connectivity might not be available. In this paper, we propose a break-glass access control mechanism based on a novel use of QR codes, Shamir's Secret Sharing Scheme and Attribute Based Encryption. Our proposed solution is such that a secret access key is split using Shamir's secret sharing scheme and encrypted using attribute based encryption, then encoded in a QR code. Subsequently, emergency actors scan the QR code and recover the individual secret key using their attributes satisfying an access policy associated with the ciphertext. The novelty of our solution lies in the fact that a flexible access control is ensured only when a sufficient number of authorized users collaborate to get access to a building without requiring an online third party. In addition, the access secret key is only decrypted by the authorized users thanks to the use of an attribute based encryption scheme. Finally, we demonstrate the feasibility and the efficiency of the solution by implementing a prototype and analysing its performance.
Tag Recommendation for Cultural Resources

We propose a new tag recommendation method for the public digit cultural resources we collected in related program. We use LDA and Word2Vec to preprocess the resource and tag, map them to different vector space respectively. After that, we calculate the relevance of each resource and all tags by using Deep Structured Semantic Model. Lastly, range the result of calculation and treat the top N tags as the extended tags of a resource. Result show the good performance of our tag recommendation method.
Cooperative Antijamming Relaying for Control Channel Jamming in Vehicular Networks

Radio Frequency jamming attacks constitute a major threat to the availability of the vehicular networks. In particular, if the control channel is under persistent jamming attacks, the victim vehicles may fail to receive the safety related messages from the Road Side Unit, which can possibly cause tremendous economic loss and claim human lives. In this paper, we propose a cooperative relaying scheme to circumvent the control channel jamming problem in the vehicular networks, whereby the vehicles outside of the jamming area serve as relays to help forward the received control channel signal to the victim vehicles through another jamming-free service channel. By combining the signals from all relays using the selection combining or maximum-ratio combining methods, the spatial diversity provided by the relays can be effectively exploited to reduce the outage probability of the victim vehicles. Theoretical models are developed to characterize the performance of this cooperative antijamming relaying scheme, which take into account both the large-scale path loss and small-scale channel fading between relaying and victim vehicles under different jamming scenarios. We also propose a relay selection scheme to optimize the performance of the victim vehicles under the relay number constraint. Simulation results are provided to show the performance of the proposed cooperative relaying scheme and relay selection algorithm under different network settings.
Liposome Bupivacaine Compared to Plain Local Anesthetics to Reduce Postsurgical Pain: An Updated Meta-Analysis of Randomized Controlled Trials

Objective Peripheral nerve blocks for postoperative analgesia have improved block success, but analgesia efficacy has been limited by the short duration of traditional local anesthetics. The results of randomized trials comparing liposome bupivacaine with conventional local anesthetic formulations (e.g., plain bupivacaine and ropivacaine) have generated conflicting results. This study was conducted to systematically review the effectiveness of analgesic efficacy of liposome bupivacaine infiltration at the surgical site versus plain local anesthetic bupivacaine or ropivacaine in patients undergoing surgery. Methods PRISMA statement guidelines were followed. A search of electronic databases National Library of Medicine's PubMed database, Cochrane Database of Systematic Reviews, Embase, and Google Scholar from January 2012 to September 2017 was performed. Among the 1,612 records identified, 9 randomized controlled trials involving 779 patients were eligible for data extraction and meta-analysis. Results Liposome bupivacaine did not reduce postsurgical pain at rest compared to plain local anesthetics at 24 and 48 hours after surgery. Moreover, liposome bupivacaine did not reduce postoperative opioid consumption at 24, 48, or 72 hours when compared to plain local anesthetics. Liposome bupivacaine did reduce postoperative nausea when compared to plain local anesthetics (P =<0.3). There was no significant difference in hospital length of stay between study groups, the use of plain bupivacaine or ropivacaine, or among orthopedic or nonorthopedic procedures. No manifestations of local anesthetic toxicity were reported. Conclusions Our results suggest that liposome bupivacaine does not have an analgesic advantage when compared to plain local anesthetics at the surgical site for patients undergoing surgical procedures.
A Comprehensive Survey for Low Rank Regularization

Low rank regularization, in essence, involves introducing a low rank or approximately low rank assumption for matrix we aim to learn, which has achieved great success in many fields including machine learning, data mining and computer version. Over the last decade, much progress has been made in theories and practical applications. Nevertheless, the intersection between them is very slight. In order to construct a bridge between practical applications and theoretical research, in this paper we provide a comprehensive survey for low rank regularization. We first review several traditional machine learning models using low rank regularization, and then show their (or their variants) applications in solving practical issues, such as non-rigid structure from motion and image denoising. Subsequently, we summarize the regularizers and optimization methods that achieve great success in traditional machine learning tasks but are rarely seen in solving practical issues. Finally, we provide a discussion and comparison for some representative regularizers including convex and non-convex relaxations. Extensive experimental results demonstrate that non-convex regularizers can provide a large advantage over the nuclear norm, the regularizer widely used in solving practical issues.
A New SDN-Based Next Generation Fronthaul Interface for a Partially Centralized C-RAN

Cloud Radio Access Network (C-RAN) is a promising concept that aims to improve the radio resource sharing, to reduce CAPEX/OPEX and to provide a better mobility management for the new mobile network generation. However, the strict requirements imposed by the C-RAN architecture (large bandwidth, high throughput and ultra-low latency) led the operators to define new functional splitting models between the Remote Radio Unit (RRU) and the Baseband Unit (BBU), less restrictive and adapted to the existing network infrastructures. Next Generation Fronthaul Interface (NGFI) is thus designed to address these challenges. In this paper, we propose a new NGFI-based C-RAN architecture that uses a partially centralized splitting model. To connect the radio unit to the baseband unit, we deploy a switched SDN network within the Fronthaul (FH). Moreover, we present our C-RAN implementation, based on OpenAirInterface (OAI) and we measure its FH performance under multiple network topologies.
Demand Side Management Using Hybrid Genetic Algorithm and Pigeon Inspired Optimization Techniques

In this paper, our goal is to minimize the electricity cost, electricity consumption at minimum user discomfort while considering the peak electricity consumption. Electricity consumption may not be the same in residential, commercial and industrial areas. It may vary from each and every area. It is a challenging task to maintain the balance between the conflicting objectives: electricity consumption and user comfort. To meet the rising electricity demand in residential area, scheduleable devices can be equally distributed to the available time slots on the basis of average power consumption. The main objective is to minimize the electricity usage during the electricity peak hours by distributing the electricity load during the off-peak hours. In this regard, Genetic Algorithm (GA), Pigeon Inspired Optimization (PIO) and our proposed hybridization of GA and PIO (HGP) in Demand Side Management(DSM) are applied for residential load management to optimize the fitness function. GA, PIO and HGP are evaluated on the basis of real time pricing scheme (RTP) for single home with three different operational time interval (OTI) and for multiple homes with a single OTI. Simulations results shows that GA, PIO and HGP are able to minimize electricity bill and electricity consumption while minimizing the user discomfort. The performance of HGP is better than GA, PIO with respect to PAR, electricity load and electricity cost for both single home and multiple homes scenario. The feasible region between electricity cost and electricity consumption is also represented. Moreover, the desired trade-off between electricity cost and user comfort is also achieved in both techniques.
Insights from the Molecular modeling, docking analysis of illicit drugs and Bomb Compounds with Honey Bee Odorant Binding Proteins (OBPs)

Analysis of honeybee PBPs is of interest in the development of Biosensor applications. We described the predicted binding of 19 such compounds with 43-honey bee OBPs using molecular modeling, docking and phylogenetic analysis. Therefore, training the honeybees using preferred compounds formulate the bees to identify the illicit drugs and bomb compounds. Consequently, high docking score produced complex such OBP16-N-Phenyl-2-Napthalamine (-12.25k/mol), 3BJH-Crack Cocaine (-11.75k/mol), OBP10-Methadone (- 11.71k/mol), 1TUJ-Dronobinal Cannabis (-11.66k/mol), OBP13-Plasticizer (-11.27k/mol) and OBP24-Ecstasy (-10.89 k/mol) can be used to identify the compounds using biosensor application. The chemical reaction of the compounds for olfactory sensory was analyzed using DFT (Density Functional Theory) studies. Some of these compounds show high binding OBPs across distant phylogeny.
Mixed Reality in Education: Recent Developments and Future Trends

Mixed reality (MR) is an emerging technology which could potentially shape the future of education. A text mining method was applied to 3330 articles to classify them into six different topics. The classification reveals the trends relating to each topic and the relations between them. This paper focuses on recent developments in each topic area and summarizes the advantages and disadvantages of using MR for education. Our objective is to help researchers focus on the research challenges where technological advancements in education MR are most needed.
Liquid-Metal-Fluidically Switchable Metasurface for Broadband and Polarization-Insensitive Absorption

This paper proposes a switchable metasurface for broadband and polarization-insensitive absorption, whose absorption spectrum can be fluidically switched using liquid metal. The proposed metasurface consists of a top metallic pattern, a flexible printed circuit board substrate, a polydimethylsiloxane substrate, and a bottom metallic ground plane. The proposed unitcell is inspired by a four-circular-sector structure. To maintain the symmetrical geometry and increase the switching range, a symmetrical microfluidic channel is designed with a circular ring capillary and four isolated patches. To measure the absorptivity of the proposed metasurface, $10\times10$ unitcells are fabricated with 20 inlets and 20 outlets. When the microfluidic channels of the metasurface are empty, the fabricated metasurface achieves an absorptivity of higher than 90%, from 6.23 to 12.14 GHz. When eutectic gallium–indium alloy is injected into the microfluidic channels, the fabricated metasurface achieves higher than 90% absorptivity, from 5.44 to 6.12 GHz. Thus, for both cases, the absorptivity is constant at different incident polarization angles.
A Novel Stability Criterion for a Class of Networked Control Systems Using Some Integral Inequalities

This paper is concerned with the stability problem of networked control systems in the continue-time domain. The network-induced delay is assumed to be differential with interval bounds, in which the delay derivative is also bounded in an interval. Some integral inequalities are employed to estimate some quadratic terms appearing in the time-derivative of the chosen Lyapunov-Krasovskii (LK) functional. This novel integral inequality technique can provide tighter upper bounds for some quadratic terms. Since we construct a tunable delay-partition-dependent LK functional, derived stability criterion has advantage over existing ones, in which the upper bounds of the derivative in quadratic terms are fully estimated. The stability condition can also work when upper bound of delay derivative is greater than one. Finally, two examples are given to show the merit and effectiveness of the proposed approach.
Signal Detection for Superposition Transmission Protocols for Optical Wireless Scattering Broadcast Channel

Due to the scattering events in the ultra-violet (UV) spectrum, UV optical wireless communication enables transmission from a single transmitter to multiple receivers, which forms a broadcast channel. In this paper, we address the transmission protocols for such a broadcast channel. Based on the degradeness of such a broadcast channel, we propose time-dilation and time-shrinking superposition transmission. For the former, the duration of the base-layer symbols is shorter than that of the enhancement-layer symbols; while for the latter, the duration of the base-layer symbols is longer. We propose the signal detection of the two types of superposition transmission protocols, analyze the detection error probability and the associated upper bounds, and formulate the problems of power allocation among the signal layers. The numerical results on the sum power obtained from the exact detection error probability and the upper bounds are provided. It is shown that for the superposition with two signal layers, the sum power based on the upper bounds can be close to that based on the exact detection error probability.
Genome-wide association mapping and examination of possible maternal effect for the pace trait of horses.

Previously, a single nucleotide polymorphism (SNP) related to gait type was identified at position 22 999 655 of chromosome 23 in the coding region of DMRT3 (DMRT3:Ser301Ter) by showing that a cytosine (C) to adenine (A) mutation of this SNP induced pace in the Icelandic horse. We investigated the effect of DMRT3:Ser301Ter on the gait of Hokkaido Native Horses, a Japanese native breed, and examined genetic factors other than DMRT3 by exploring genome-wide SNPs related to gait determination. All animals exhibiting pace were AA for DMRT3:Ser301Ter, confirming the association of DMRT3:Ser301Ter with gait determination; however, 14.3% of the animals exhibiting trot also had AA for DMRT3:Ser301Ter, suggesting the presence of another factor(s) cooperatively working with DMRT3:Ser301Ter for gait determination. SNPs on chromosomes 13 and 23 were detected by genome-wide association analysis (false discovery rate <0.05), although SNPs on chromosome 23 were all located in the vicinity of DMRT3:Ser301Ter, confirming the association with DMRT3. A genome-wide association study targeting only animals with AA for DMRT3:Ser301Ter to examine genetic factors cooperatively working with DMRT3:Ser301Ter for gait determination suggested associations of 23 SNPs on six chromosomes. In a series of analyses of the effect of a maternal factor (dam's gait) on gait determination, the effect was suggested in comparison of the frequencies of exhibiting pace in gait checks in only two animal groups having dams with different DMRT3:Ser301Ter genotypes (P < 0.05), suggesting that the gait of the dam does not have a major effect on whether progeny homozygous for the DMRT3:Ser301Ter mutation will preferentially pace or trot.
d-SHAM: An O(d) Scalable Routing Algorithm

Many lookup algorithms were proposed with a constraint of keeping the volume of the routing table at each node/peer minimized while working on reducing the lookup latency. The justification behind this is that large routing tables require maintenance efforts and increased network traffic in order to keeping them updated. However, constant degree overlays come as a practical choice to a minimized lookup latency with limited routing tables. We present d-SHAM, a simple, scalable and robust constant degree algorithm that can adapt to frequent changes in the status of the overlay. In d-SHAM, lookups are within O(d) and each peer holds entries for d.N 1/d other peers, where N is the number of nodes/peers in the overlay, and d is the number of its dimensions.
Comparison of Two Performance Optimization Approaches for Data-Driven Design of Fault-Tolerant Control Systems

In this paper, a residual generator-based data-driven fault-tolerant control (FTC) framework is reviewed. Based on that, the gradient descent and the reinforcement learning optimal control methods for dynamic compensator design of proposed FTC systems are reviewed. Both gradient descent and reinforcement learning methods can update the control strategy and improve system performance and robustness. By analyzing the theoretical characteristics of the two methods, it is determined whether the solutions of the two methods belong to the global or the local optimum. The effectiveness of the proposed two optimization approaches and the differences between the optimality of the solutions is tested and verified by using DC-motor benchmark case study.
Aurora-PLK1 cascades as key signaling modules in the regulation of mitosis

Precise spatiotemporal control enables the mitotic kinases Aurora and PLK1 to orchestrate distinct mitotic processes. Gloss Ever since its first observation under the microscope over a century ago, mitosis—the process wherein a cell divides into two genetically identical daughter cells—has captured the attention of biologists and physicians alike owing to its beauty, sophistication, and importance for the life cycle of eukaryotic organisms. The key factors that control mitosis primarily do so through protein phosphorylation and regulated degradation. In this review, which contains six figures, one table, and 432 references, we discuss the mechanisms by which only a handful of mitotic protein kinases control various mitotic events in distinct spatiotemporal contexts. We highlight the central role in this control of the two-tiered Aurora-PLK1 cascades that are organized by several multifunctional scaffold proteins and integrated within larger mitotic regulatory networks. Mitosis is controlled by reversible protein phosphorylation involving specific kinases and phosphatases. A handful of major mitotic protein kinases, such as the cyclin B–CDK1 complex, the Aurora kinases, and Polo-like kinase 1 (PLK1), cooperatively regulate distinct mitotic processes. Research has identified proteins and mechanisms that integrate these kinases into signaling cascades that guide essential mitotic events. These findings have important implications for our understanding of the mechanisms of mitotic regulation and may advance the development of novel antimitotic drugs. We review collected evidence that in vertebrates, the Aurora kinases serve as catalytic subunits of distinct complexes formed with the four scaffold proteins Bora, CEP192, INCENP, and TPX2, which we deem “core” Aurora cofactors. These complexes and the Aurora-PLK1 cascades organized by Bora, CEP192, and INCENP control crucial aspects of mitosis and all pathways of spindle assembly. We compare the mechanisms of Aurora activation in relation to the different spindle assembly pathways and draw a functional analogy between the CEP192 complex and the chromosomal passenger complex that may reflect the coevolution of centrosomes, kinetochores, and the actomyosin cleavage apparatus. We also analyze the roles and mechanisms of Aurora-PLK1 signaling in the cell and centrosome cycles and in the DNA damage response.
Analysis and Improvement of Reliability Through Coding for Safety Message Broadcasting in Urban Vehicular Networks

In this paper, we study the impact of obstacles (such as buildings) in the radio propagation in the urban vehicular network's environment. The impact has been realized not only by the network-level performance metrics, but also by the application-level performance metrics. A majority of the existing works consider perfect physical layer, which ignores the impact of path loss and shadowing effect in radio propagation caused by the urban canyon. First, we show that ignoring the impact of obstacles in radio propagation provides very high superficial network-level performance. Second, under obstacle shadowing, we perform analytical analysis and Ns-3 based realistic urban vehicular simulation of current dedicated short-range communication based safety message broadcasting to study the achievable performance of application-level performance metrics. This study reveals the answer of the key question, whether the achieved network-level performance metric is good enough for the safety-critical applications under the acute attenuation in radio propagation in urban environment. Third, we propose opportunistic vehicle-assisted or dedicated road side unit-assisted network coded relaying for improving reliability at road intersection. Simulation results show that the proposed approach improves more than 65% reliability for delay sensitive and around 25% reliability for less delay sensitive applications at intersections.