We report the synthesis and physical properties of a polycrystalline, hexagonal boride YRu$_3$B$_2$. Our resistivity and heat capacity measurements indicate that YRu$_3$B$_2$ is a weakly coupled superconductor, with critical temperature $T_c$ = 0.63 K and upper critical field $\mu_0 H_{c2}$ (0)=0.11 T. Density functional theory calculations, together with chemical-bonding analysis, reveal that the electronic states at and near the Fermi energy level are dominated by the Ru kagome sublattice.

Hierarchical Federated Learning (HFL) faces the significant challenge of adversarial or unreliable vehicles in vehicular networks, which can compromise the model's integrity through misleading updates. Addressing this, our study introduces a novel framework that integrates dynamic vehicle selection and robust anomaly detection mechanisms, aiming to optimize participant selection and mitigate risks associated with malicious contributions. Our approach involves a comprehensive vehicle reliability assessment, considering historical accuracy, contribution frequency, and anomaly records. An anomaly detection algorithm is utilized to identify anomalous behavior by analyzing the cosine similarity of local or model parameters during the federated learning (FL) process. These anomaly records are then registered and combined with past performance for accuracy and contribution frequency to identify the most suitable vehicles for each learning round. Dynamic client selection and anomaly detection algorithms are deployed at different levels, including cluster heads (CHs), cluster members (CMs), and the Evolving Packet Core (EPC), to detect and filter out spurious updates. Through simulation-based performance evaluation, our proposed algorithm demonstrates remarkable resilience even under intense attack conditions. Even in the worst-case scenarios, it achieves convergence times at $63$\% as effective as those in scenarios without any attacks. Conversely, in scenarios without utilizing our proposed algorithm, there is a high likelihood of non-convergence in the FL process.

Diversity schemes play a vital role in improving the performance of ultra-reliable communication systems by transmitting over two or more communication channels to combat fading and co-channel interference. Determining an appropriate transmission strategy that satisfies ultra-reliability constraint necessitates derivation of statistics of channel in ultra-reliable region and, subsequently, integration of these statistics into rate selection while incorporating a confidence interval to account for potential uncertainties that may arise during estimation. In this paper, we propose a novel framework for ultra-reliable real-time transmission considering both spatial diversities and ultra-reliable channel statistics based on multivariate extreme value theory. First, tail distribution of joint received power sequences obtained from different receivers is modeled while incorporating inter-relations of extreme events occurring rarely based on Poisson point process approach in MEVT. The optimum transmission strategies are then developed by determining optimum transmission rate based on estimated joint tail distribution and incorporating confidence intervals into estimations to cope with the availability of limited data. Finally, system reliability is assessed by utilizing outage probability metric. Through analysis of data obtained from the engine compartment of Fiat Linea, our study showcases the effectiveness of proposed methodology in surpassing traditional extrapolation-based approaches. This innovative method not only achieves a higher transmission rate, but also effectively addresses stringent requirements of ultra-reliability. The findings indicate that proposed rate selection framework offers a viable solution for achieving a desired target error probability by employing a higher transmission rate and reducing the amount of training data compared to conventional rate selection methods.

The main objective of this paper is to provide a comprehensive demonstration of recent results regarding the structures of the weighted Ces\`aro and Copson function spaces. These spaces' definitions involve local and global weighted Lebesgue norms; in other words, the norms of these spaces are generated by positive sublinear operators and by weighted Lebesgue norms. The weighted Lebesgue spaces are the special cases of these spaces with a specific set of parameters. Our primary method of investigating these spaces will be the so-called discretization technique. Our technique will be the development of the approach initiated by K.G. Grosse-Erdmann, which allows us to obtain the characterization in previously unavailable situations, thereby addressing decades-old open problems. We investigate the relation (embeddings) between weighted Ces\`aro and Copson function spaces. The characterization of these embeddings can be used to tackle the problems of characterizing pointwise multipliers between weighted Ces\`aro and Copson function spaces, the characterizations of the associate spaces of Ces\`aro (Copson) function spaces, as well as the relations between local Morrey-type spaces.

We have synthesized and characterized the physical properties of a layered, mixed valent oxypnictide $\mathrm{La_{3}Cu_{4}P_{4}O_{2}}$ via magnetization, electrical resistivity, and specific heat measurements. Although $\mathrm{La_{3}Cu_{4}P_{4}O_{2}}$ does not exhibit superconductivity down to T = 0.5 K, it demonstrates an intriguing resistivity minimum observed at $\mathrm{T_{min}}$ = 13.7 K. Disappearance of the resistivity minimum under an applied magnetic field of $\mathrm{\mu_{0}H}$ = 9 T together with the negative magnetoresistance at low and positive at high temperatures are observed, which are typical for both Kondo-like spin-dependent scattering and 3D weak localization. We argue that the Kondo scattering is a more plausible explanation due to the low-temperature deviation from a Curie-Weiss law observed in the magnetic susceptibility, consistent with the presence of magnetic interactions between paramagnetic $\mathrm{Cu^{2+}}$ ions and Kondo screening of these $\mathrm{Cu^{2+}}$ moments. We supplemented the experimental characterization with a detailed description of chemical bonding, employing density functional theory (DFT) calculations and crystal orbital Hamilton population (COHP) analysis for $\mathrm{La_{3}Cu_{4}P_{4}O_{2}}$ and isostructural $\mathrm{La_{3}Ni_{4}P_{4}O_{2}}$, which is a superconductor with $\mathrm{T_c = 2.2}$ K. Based on the calculations performed, we present the difference between $\mathrm{La_{3}Cu_{4}P_{4}O_{2}}$ and $\mathrm{La_{3}Ni_{4}P_{4}O_{2}}$ in the character of electronic states at the Fermi level. This discrepancy impacts structural stability and may cause a lack of superconductivity in $\mathrm{La_{3}Cu_{4}P_{4}O_{2}}$ down to T = 0.5 K.