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In-network caching constitutes a promising approach to reduce traffic loads and alleviate congestion in both wired and wireless networks. In this paper, we study the joint caching and routing problem in congestible networks of arbitrary topology (JoCRAT) as a generalization of previous efforts in this particular field. We show that JoCRAT extends many previous problems in the caching literature that are intractable even with specific topologies and/or assumed unlimited bandwidth of communications. To handle this significant but challenging problem, we develop a novel approximation algorithm with guaranteed performance bound based on a randomized rounding technique. Evaluation results demonstrate that our proposed algorithm achieves nearoptimal performance over a broad array of synthetic and real networks, while significantly outperforming the state-of-the-art methods. 

We present a deep learning based framework, called ROSE, to accurately predict ribosome stalling events in translation elongation from coding sequences based on high-throughput ribosome profiling data. Our validation results demonstrate the superior performance of ROSE over conventional prediction models. ROSE provides an effective index to estimate the likelihood of translational pausing at codon resolution and understand diverse putative regulatory factors of ribosome stalling. Also, the ribosome stalling landscape computed by ROSE can recover the functional interplay between ribosome stalling and cotranslational events in protein biogenesis, including protein targeting by the signal recognition particle (SRP) and protein secondary structure formation. 

The ALICE Collaboration reports measurements of the large relative transverse momentum ( $k_T$) component of jet substructure in $pp$and Pb-Pb collisions at center-of-mass energy per nucleon pair $\sqrt{s_{\mathrm{NN}}}=5.02\mathrm{TeV}$. Enhancement in the yield of such large- $k_{\mathrm{T}}$emissions in head-on Pb-Pb collisions is predicted to arise from partonic scattering with quasiparticles of the quark-gluon plasma. The analysis utilizes charged-particle jets reconstructed by the anti- $k_{\mathrm{T}}$algorithm with resolution parameter $R=0.2$in the transverse-momentum interval $60<p_{\mathrm{T},\mathrm{ch},\mathrm{jet}}<80\mathrm{GeV}/c$. The soft drop and dynamical grooming algorithms are used to identify high transverse momentum splittings in the jet shower. Comparison of measurements in Pb-Pb and $pp$collisions shows medium-induced narrowing, corresponding to yield suppression of high- $k_T$splittings, in contrast to the expectation of yield enhancement due to quasiparticle scattering. The measurements are compared to theoretical model calculations incorporating jet modification due to jet-medium interactions (“jet quenching”), both with and without quasiparticle scattering effects. These measurements provide new insight into the underlying mechanisms and theoretical modeling of jet quenching.