Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint User Scheduling and Hybrid Beamforming Design for Cooperative mmWave Networks

This paper investigates hybrid beamforming for cooperative multi-user millimeter-wave (mmWave) multiple-input multiple-output (MIMO) networks. We aim to jointly design the user scheduling and hybrid beamforming to maximize the sum-rate subject to the transmit power of each base station. Due to the non-convexity of constant modulus of phase shifters and objective function, the problem is mathematically intractable. We propose a low-complexity two-step scheme, in which user scheduling and analog beamforming are first obtained to maximize the sum-beamforming-gain, followed by digital beamforming calculation based on weighted minimum-mean-square-error (wMMSE) approach. We further extend the hybrid beamforming design to dynamic sub-array architecture, where a novel antenna selection algorithm is developed. Simulation results demonstrate the effectiveness of the proposed algorithms, which can outperform other state-of-the-art approaches.
On the Ziv-Zakai Bound for Time Difference of Arrival Estimation in CP-OFDM Systems

We consider the pilot signal for time (difference) of arrival (ToA, TDoA) estimation in an orthogonal frequency division multiplexing system with a cyclic prefix (CP-OFDM). The Cramér-Rao and Ziv-Zakai lower bounds are used to assess the performance of different pilot signals, under the assumption that the delay is distributed uniformly within a certain range. We adapt the analysis from previous works that have analyzed the performance of waveforms in an AWGN channel, but have not considered CP-OFDM. We find that in a CP-OFDM system, the ZZLB of the estimate depends only on the power allocation on the subcarriers, but not on their phase, if the pilot symbol is detected with an uncertainty up to the duration of the CP prior to the T(D)oA estimation and the CP is dropped at the receiver. This simplifies pilot signal design. Numerical results for Dirac-rectangular and triangular power allocations show that the performance follows a similar trend as for (single carrier) waveforms with a Dirac-rectangular and triangular power spectral density. But for a small uncertainty in the delay and a small number of allocated subcarriers, there is no transition region and it is optimal to allocate the pilot signals to the edge subcarriers.
Secure Intelligent Reflecting Surface Assisted MIMO Cognitive Radio Transmission

Intelligent reflecting surface (IRS) has been proposed as a very promising technique for beyond 5G and 6G communications. In this paper, we apply IRS to enhance the secure transmission of secondary user in a multi-input multioutput (MIMO) cognitive radio (CR) wiretap channel. Since the study of secure IRS-assisted CR communication is still an open problem, all the existing numerical solutions for enhancing secure communications in non-CR setting as well as non-secure communications in CR setting in the literature fail to this work due to the complicated structure of objective functions as well as the constraints. Therefore, to maximize the secrecy rate of secondary user, an efficient alternating optimization (AO) algorithm is proposed to jointly optimize the transmit covariance at base station and phase shift coefficients at IRS. Simulation results show that our proposed algorithm have fast monotonic convergence as well as better performance on enhancing the secrecy rate than the benchmark schemes.
Performance Evaluation of C-V2X Mode 4 Communications

Cellular vehicular-to-everything (C-V2X), as a key technology of Internet of Vehicles (IoVs), is expected to improve road traffic safety and achieve intelligent transportation. C-V2X mainly supports two communication modes, Mode 3 and Mode 4. Mode 3 supports centralized control and management of network resources whereas Mode 4 allows vehicles to select radio resources independently for data transmission without the aid of network infrastructures. In this paper, we present an overview of C-V2X Mode 4 communication and stress several major enhancements compared to long term evolution (LTE), including subframe structure design, synchronization mechanism, resource pool configuration, and resource scheduling mechanism, i.e., sensing-based semi-persistent scheduling (S-SPS), etc. To evaluate the transmission performance of C-V2X, we set up a system-level simulation platform based on the integration of traffic simulator CarMaker and network simulator (NS)-3, where CarMaker is utilized to simulate real vehicle trajectories and NS-3 is applied to implement the communication protocols of C-V2X. Under various simulation scenarios, the transmission performance in terms of packet reception ratio (PRR) is examined and the impacts of resource scheduling parameters, including resource reselection probability, resource reservation interval and channel bandwidth on PRR are evaluated.
Building a Team Leadership Index Through Computational Methods

: To help monitoring and controlling the latent social dynamics associated with leadership, we test a methodological approach that makes use of computational techniques to mine the content of online communications and analyze group structure to identify students who behave as leaders. The results allow us to quantify each individual's contribution and summarize their engagement in the form of a leadership index. The proposed methodology is fully automated and has the potential to be easily replicable. The summary offered by the leadership index is intended as actionable information that can guide just-in-time interventions to help sustain student engagement.
Network-Coded Wireless Powered Cellular Networks: Lifetime and Throughput Analysis

In this paper, we study a wireless powered cellular network (WPCN) supported with network coding capability. In particular, we consider a network consisting of k cellular users (CUs) served by a hybrid access point (HAP) that takes over energy transfer to the users on top of information transmission over both the uplink (UL) and downlink (DL). Each CU has $k+1$ states representing its communication behavior, and collectively are referred to as the user demand profile. Opportunistically, when the CUs have information to be exchanged through the HAP, it broadcasts this information in coded format to the exchanging pairs, resulting in saving time slots over the DL. These saved slots are then utilized by the HAP to prolong the network lifetime and enhance the network throughput. We quantify, analytically, the performance gain of our network-coded WPCN over the conventional one, that does not employ network coding, in terms of network lifetime and throughput. We consider the two extreme cases of using all the saved slots either for energy boosting or throughput enhancement. In addition, a lifetime/throughput optimization is carried out by the HAP for balancing the saved slots assignment in an optimized fashion, where the problem is formulated as a mixed-integer linear programming optimization problem. Numerical results exhibit the network performance gains from the lifetime and throughput perspectives, for a uniform user demand profile across all CUs. Moreover, the effect of biasing the user demand profile of some CUs in the network reveals considerable improvement in the network performance gains.
Bidirectional Imputation of Spatio-Temporal Data based on LSTM with Parameter Transfer

In this paper, we propose a bidirectional imputation algorithm for spatio-temporal traffic speed data based on Long Short-Term Memory (LSTM) architecture with parameter transfer in vehicle to infrastructure (V2I) networks. We consider a scenario in V2I networks where an Road Side Units (RSU) on the road does not operate temporarily and thus the traffic speed data cannot be collected. This makes any services that rely on the traffic speed data at the RSU be unavailable. For uninterrupted and seamless V2I services, an efficient and low complexity data imputation algorithm is imperative. The proposed algorithm is based on the architecture that includes multiple LSTM layers with parameter transfers, which can explicitly take into account the spatio-temporal characteristics of the traffic speed data. By transferring parameters from one LSTM layer to its adjacent LSTM layer, the complexity associated with the algorithm can be significantly reduced. The proposed algorithm includes bidirectional imputation, which can further improve imputation accuracy. Our simulation and experiment results confirm that the time for training and data imputation of the proposed algorithm can be significantly reduced while maintaining imputation accuracy.
A Novel Learning-based Hard Decoding Scheme and Symbol-Level Precoding Countermeasures

In this work, we consider an eavesdropping scenario in wireless multi-user (MU) multiple-input single-output (MISO) systems with channel coding in the presence of a multi-antenna eavesdropper (Eve). In this setting, we exploit machine learning (ML) tools to design a hard decoding scheme by using precoded pilot symbols as training data. Within this, we propose an ML framework for a multi-antenna hard decoder that allows an Eve to decode the transmitted message with decent accuracy. We show that MU-MISO systems are vulnerable to such an attack when conventional block-level precoding is used. To counteract this attack, we propose a novel symbol-level precoding scheme that increases the bit-error rate at Eve by obstructing the learning process. Simulation results validate both the ML-based attack as well as the countermeasure, and show that the gain in security is achieved without affecting the performance at the intended users.
A MAC Protocol Based on Energy Scheduling for In-Vivo Wireless NanoSensor Networks

Terahertz based in-vivo Wireless NanoSensor Networks (iWNSNs) is a novel sensor network using electromagnetic waves in terahertz band as carrier and nanotechnology work in human body. Due to the different propagation characteristic of in-vivo terahertz channel and the limited resource of nano device, current MAC (Medium Access Control) protocol cannot be applied to Terahertz based iWNSNs. In this paper, a MAC protocol based on energy scheduling, called ES-MAC, is proposed. This protocol adopts nano energy harvesting system, designs a reward function based on the amount of transmitted data and the priority of data. Nano sensor nodes adopt Sarsa learning algorithm to make dynamic channel access decision according to their status. Simulation results show ES-MAC protocol can decrease average end-to-end delay and prolong lifetime of the network while providing differentiated services.
Context-aware Coordinated Anti-jamming Communications: A Multi-pattern Stochastic Learning Approach

This paper investigates the anti-jamming problems for multi-user scenarios. On the one hand, users in the networks should coordinate their channel selection strategies to avoid spectrum conflicts among different users. On the other hand, because of the openness characteristic of wireless communications, malicious jammers can disrupt the legitimate communications of legitimate users by sending jamming signals, thus users also need to fully consider how to defend against malicious jamming attacks. To cope with the internal coordination and external confrontation problem, a context-aware dynamic spectrum coordinated anti-jamming approach is proposed. In detail, the multiuser anti-jamming scenario is modeled as an anti-jamming local altruistic game, and the existence of Nash Equilibrium (NE) is demonstrated. Besides, the proposed game model is proved to be an exact potential game. To obtain NEs, a multi-pattern stochastic learning algorithm (MSLA) is designed. Through local information exchange and distributed learning, users can achieve global optimization under the dynamic jamming environment.
Translating Theory to Practice: Technology Solutions to Solve Practical Issues for Teaching Reading Comprehension at the Secondary Level

: We describe a theory-and evidence-based curriculum that improves reading comprehension skills needed to learn from difficult informational text and the theory’s translation into an online program that allows for individualized instruction for greater scalability in today’s technology-enhanced classrooms. Feature design is based on cognitive science, user input/experiences, and a configuration of highly flexible web-applications to provide interactive features necessary to adapt a teacher-led curriculum into one that is automated and tied to student achievement.
An Adaptive Full-Duplex Deep Reinforcement Learning-Based Design for 5G-V2X Mode 4 VANETs

This paper exploits full-duplex (FD) technology and deep reinforcement learning (DRL) algorithm jointly and adaptively to enhance the performance of 5G-V2X networks that operate based on the 5G-V2X Mode 4 standard. Specifically, we propose a novel physical- (PHY) and medium access control- (MAC) layer cross-layer design, in which collision detection capability is enabled during broadcasting without introducing redundant signalling. Besides, the resource reservation scheme, collision resolution mechanism and scheduling policy are also designed. As the proposed adaptive method is fully decentralised, vehicular users adapt to the unknown and fast-changing environment autonomously without any help from gNBs. Simulation results demonstrate the superiority of our proposed design over the standardised sensing-based semi-persistent scheduling (SB-SPS) protocol. Therefore, the proposed cross-layer design can be considered as a solution for future 5G-V2X VANETs.
Playing Well with Others: An Ethnographic Examination of a Cross-Disciplinary Science-Theatre Collaboration

This piece describes a participatory ethnographic study of a cross-disciplinary collaboration between science education researchers and theatre educators creating a sciencebased play for middle-school youth that aims to dismantle stereotypes about participating in science and becoming a scientist. The ethnography aimed to identify factors that contribute to successful cross-disciplinary collaborations and to understand why interdisciplinary collaboration is essential to designing learning environments that engage students unengaged with or intimidated by typical schooling contexts.
Easily attainable new approach to mass yield ferrocenyl Schiff base and different metal complexes of ferrocenyl Schiff base through convenient ultrasonication‐solvothermal method

A new alternative approach with crucial mass yield and high reaction rates is proposed for the synthesis of ferrocenyl Schiff bases using an ultrasonication-solvothermal method. Equimolar condensation of ferrocenecarboxaldehyde and 2-aminophenol interact with each other, giving 1-(1-[2-hydroxyphenyl-2-imino]methyl)-ferrocene (FcOH). Furthermore, this ligand forms 1:1 complexes with cobalt(II), nickel(II), copper(II), and palladium(II) ions. From the different spectral data, it is found that metal ions coordinate with ligands through the azomethine group and the deprotonated oxygen of the phenol groups. Moreover, FcOH and their complexes were characterized by elemental analysis, Fourier transform infrared, 1H nuclear magnetic resonance, and UV-visible spectrophotometry. The spectral data of FcOH and its metal complexes were discussed in connection with the structural changes due to complexation. Meanwhile, the information about geometric structures can be concluded from the electronic spectra and the magnetic moments. Plainly, electron spin resonance spectra of the Cu(II) complex revealed dx2−y2 as a ground state, suggesting a square planar geometry around the Cu(II) center. The direct optical band gap energy Eg values of cobalt, nickel, copper, and palladium complexes of FcOH are found to be 3.7, 3.9, 4.6, and 3.65 eV, respectively. 1-(1-[2-Hydroxyphenyl-2-imino]methyl)-ferrocene and its metal complexes were screened for antibacterial activity. The results depict that the metal complexes were found to be more strongly antibacterial than the guardian Schiff base ligand (FcOH) against one or more bacterial species. The minimum inhibitory concentrations of antimicrobial properties of the purified compound were determined using the broth microdilution method.
Solubility of phenobarbital in aqueous cosolvent mixtures revisited: IKBI preferential solvation analysis

ABSTRACT The preferential solvation parameters of phenobarbital in aqueous binary mixtures of 1,4-dioxane, t-butanol, n-propanol, ethanol, propylene glycol and glycerol were derived from solution thermodynamic properties by using the IKBI method. This drug is sensitive to preferential solvation effects in all these mixtures. The preferential solvation parameter by the cosolvent (δx1,3) is negative in almost all the water-rich mixtures but positive in mixtures with similar proportions of solvents and cosolvent-rich mixtures, except in 1-propanol + water mixtures, where negative values are also found in mixtures with x1 ≥ 0.70. Hydrophobic hydration around the non-polar ethyl and phenyl groups of this drug in water-rich mixtures could play a relevant role in drug solvation. Otherwise, in mixtures of similar solvent compositions and in cosolvent-rich mixtures the preferential solvation by cosolvent could be due to the acidic behaviour of the drug.
• SCREENING OF HEPATOPROTECTIVE POTENTIAL OF ETHANOLIC AND AQUEOUS EXTRACT OF TERMINALIA ARJUNA BARK AGAINST PARACETAMOL/CCL4 INDUCED LIVER DAMAGE IN WISTAR ALBINO RATS

S creening hepatoprotective potential of ethanolic and aqueous extract of Terminalia arjuna bark against paracetamol/ CCl4 induced liver damage in wistar albino rats. Hepatotoxicity was induced by paracetamol/CCl4 and the biochemical parameters such as serum glutamic pyruvic transaminase (sGPT), serum glutamic oxaloacetic transaminase (sGOT) and serum alkaline phosphatase (sALP), serum bilirubin (SB) and histopathological changes in liver were studied along with silymarin as standard hepatoprotective agents. The phytochemical investigation of the extracts showed presence of alkaloids, glycosides, steroids and flavonoids, saponin, tanins. Pre-treatment of the rats with ethanol and aqueous extract prior to paracetamol/CCl4 administration caused a significant reduction in the values of sGOT, sGPT, sALP and sB almost comparable to the silymarin. The hepatoprotective was confirmed by histopathological examination of the liver tissue of control and treated animals. From the results it can be concluded the Terminalia arjuna possesses hepatoprotective effect against paracetamol/CCl4 -induced liver damage in wistar albino rats.
ConDySTA: Context-Aware Dynamic Supplement to Static Taint Analysis

Static taint analyses are widely-applied techniques to detect taint flows in software systems. Although they are theoretically conservative and de-signed to detect all possible taint flows, static taint analyses almost always exhibit false negatives due to a variety of implementation limitations. Dynamic programming language features, inaccessible code, and the usage of multiple programming languages in a software project are some of the major causes. To alleviate this problem, we developed a novel approach, DySTA, which uses dynamic taint analysis results as additional sources for static taint analysis. However, naïvely adding sources causes static analysis to lose context sensitivity and thus produce false positives. Thus, we developed a hybrid context matching algorithm and corresponding tool, ConDySTA, to preserve context sensitivity in DySTA. We applied REPRODROID [1], a comprehensive benchmarking framework for Android analysis tools, to evaluate ConDySTA. The results show that across 28 apps (1) ConDySTA was able to detect 12 out of 28 taint flows which were not detected by any of the six state-of-the-art static taint analyses considered in ReproDroid, and (2) ConDySTA reported no false positives, whereas nine were reported by DySTA alone. We further applied ConDySTA and FlowDroid to 100 top Android apps from Google Play, and ConDySTA was able to detect 39 additional taint flows (besides 281 taint flows found by FlowDroid) while preserving the context sensitivity of FlowDroid.
Two Faces of Ciprofloxacin: Investigation of Proton Transfer in Solid State Transformations

Ciprofloxacin (CIP) can exist in two different forms: the zwitterion and the un-ionized form. While the crystal structure of each has been described independently, the ability of CIP to transform from one form to the other in the solid state has not been described. The crystal structures of un-ionized and zwitterionic CIP were therefore compared using computational methods, including their packing arrangement, hydrogen bonding, packing energy, intermolecular potentials, and highest occupied molecular orbital/lowest occupied molecular orbital energy gap. The pure amorphous form of CIP has also never been prepared or studied. Ball milling, cryomilling, and spray drying were used in this study to prepare partially and fully amorphous CIP for the first time. The physical characteristics were examined by powder X-ray diffraction, Fourier transform infrared spectroscopy, and differential scanning calorimetry. CIP proved to be very difficult to amorphize, and only spray drying in pure water resulted in a fully a.
Investigation of the relationship of apelin hormone response with some physiological parameters in Maedi-Visna infected sheep

In this study, the objective was to assess the serological characteristics of sheep, during lactation and pregnancy periods, and rams belonging to the Red Karaman and White Karaman–Kangal race infected with maedi-visna infection and body condition score (BCS) of ≤2, 33.5 and ≥4 (high) and to analyse the relationship between the level of apelin and its secretion. Apelin level in the blood serum samples obtained from the jugular veinof the sheeps was determined using ELISA method. As a result of the analyses, it was determined that the level of apelin was statistically different between the races; between lactating sheep and pregnant sheep; and sheep and rams. There was no difference between the BCS groups (p > 0.05). Race and sex interaction as well as race, sex and BCS triple interaction effects were found significant (p < 0.05). It was observed that the sheep belonging to the White Karaman–Kangal race were 18 times more likely to be infected with the virus. A decrease in apelin level was observed in the sheep with infection, and it was found that the risk of infection was 0.37 times higher in rams than in lactating sheep (p < 0.05).
PHNet: Parasite-Host Network for Video Crowd Counting

Crowd counting plays an increasingly important role in public security. Recently, many crowd counting methods for a single image have been proposed but few studies have focused on using temporal information from image sequences of videos to improve prediction performance. In the existing methods using videos for crowd estimation, temporal features and spatial features are modeled jointly for the prediction, which makes the model less efficient in extracting spatiotemporal features and difficult to improve the performance of predictions. In order to solve these problems, this paper proposes a Parasite-Host Network (PHNet) which is composed of Parasite branch and Host branch to extract temporal features and spatial features respectively. To specifically extract the transform features in the time domain, we propose a novel architecture termed as “Relational Extractor”(RE) which models the multiplicative interaction features of adjacent frames. In addition, the Host branch extracts the spatial features from a current frame which can be replaced with any model that uses a single image for the prediction. We conducted experiments by using our PHNet on four video crowd counting benchmarks: Venice, UCSD, FDST and CrowdFlow. Experimental results show that PHNet achieves superior performance on these four datasets to the state-of-the-art methods.11The code is at https://github.com/LeeJAJA/PHNet-pytorch.