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Abstract The CODEX-βapparatus is a demonstrator for the proposed future CODEX-b experiment, a long-lived-particle detector foreseen for operation at IP8 during HL-LHC data-taking. The demonstrator project, intended to collect data in 2025, is described, with a particular focus on the design, construction, and installation of the new apparatus. 

Pediatric heart valve disease affects children worldwide and necessitates valve replacements that remodel and grow with the patient. Current valve manufacturing technologies struggle to create valves that facilitate native tissue remodeling for permanent replacements. Here, we present focused rotary jet spinning (FRJS) for implantable medical devices, such as heart valves, to address this challenge. Combining RJS and a focused air stream, FRJS prints FibraValves, micro- and nanofibrous heart valves, in minutes. The micro- and nanoscale features provide structural cues to orient cells at the biotic-abiotic interface, while the centimeter-scale valve shape regulates cardiac flow. We built valves using poly(L-lactide-co-Ɛ-caprolactone) fiber scaffolds, which supported rapid cellular infiltration and displayed native valve-like mechanical properties. Evaluating clinical translatability, we assessed acute performance in a large animal model using a transcatheter delivery approach. These tests indicate that FRJS is a viable method for manufacturing heart valves and future medical implants. 

Hydrogels are attractive materials for tissue engineering, but efforts to date have shown limited ability to produce the microstructural features necessary to promote cellular self-organization into hierarchical three-dimensional (3D) organ models. Here we develop a hydrogel ink containing prefabricated gelatin fibres to print 3D organ-level scaffolds that recapitulate the intra- and intercellular organization of the heart. The addition of prefabricated gelatin fibres to hydrogels enables the tailoring of the ink rheology, allowing for a controlled sol–gel transition to achieve precise printing of free-standing 3D structures without additional supporting materials. Shear-induced alignment of fibres during ink extrusion provides microscale geometric cues that promote the self-organization of cultured human cardiomyocytes into anisotropic muscular tissues in vitro. The resulting 3D-printed ventricle in vitro model exhibited biomimetic anisotropic electrophysiological and contractile properties. 

Food waste and food safety motivate the need for improved food packaging solutions. However, current films/coatings addressing these issues are often limited by inefficient release dynamics that require large quantities of active ingredients. Here we developed antimicrobial pullulan fibre (APF)-based packaging that is biodegradable and capable of wrapping food substrates, increasing their longevity and enhancing their safety. APFs were spun using a high-throughput system, termed focused rotary jet spinning, with water as the only solvent, allowing the incorporation of naturally derived antimicrobial agents. Using avocados as a representative example, we demonstrate that APF-coated samples had their shelf life extended by inhibited proliferation of natural microflora, and lost less weight than uncoated control samples. This work offers a promising technique to produce scalable, low-cost and environmentally friendly biodegradable antimicrobial packaging systems. 

Delegating managerial tasks is essential for firm growth. Most firms in developing countries, however, do not hire outside managers but instead rely on family members. In this paper, we ask if this lack of managerial delegation can explain why firms in poor countries are small and whether it has important aggregate consequences. We construct a model of firm growth where entrepreneurs have a fixed time endowment to run their daily operations. As firms grow large, the need to hire outside managers increases. Firms’ willingness to expand therefore depends on the ease with which delegation can take place. We calibrate the model to plant-level data from the United States and India. We identify the key parameters of our theory by targeting the experimental evidence on the effect of managerial practices on firm performance from Bloom et al. (2013). We find that inefficiencies in the delegation environment account for 11 percent of the income per capita difference between the United States and India. They also contribute to the small size of Indian producers, but would cause substantially more harm for US firms. The reason is that US firms are larger on average and managerial delegation is especially valuable for large firms, thus making delegation efficiency and other factors affecting firm growth complements. (JEL D22, G32, L25, L26, O14) 

Helical alignments within the heart’s musculature have been speculated to be important in achieving physiological pumping efficiencies. Testing this possibility is difficult, however, because it is challenging to reproduce the fine spatial features and complex structures of the heart’s musculature using current techniques. Here we report focused rotary jet spinning (FRJS), an additive manufacturing approach that enables rapid fabrication of micro/nanofiber scaffolds with programmable alignments in three-dimensional geometries. Seeding these scaffolds with cardiomyocytes enabled the biofabrication of tissue-engineered ventricles, with helically aligned models displaying more uniform deformations, greater apical shortening, and increased ejection fractions compared with circumferential alignments. The ability of FRJS to control fiber arrangements in three dimensions offers a streamlined approach to fabricating tissues and organs, with this work demonstrating how helical architectures contribute to cardiac performance. 

The locations of proton-proton collision points in LHC experiments are called primary vertices (PVs). Preliminary results of a hybrid deep learning algorithm for identifying and locating these, targeting the Run 3 incarnation of LHCb, have been described at conferences in 2019 and 2020. In the past year we have made significant progress in a variety of related areas. Using two newer Kernel Density Estimators (KDEs) as input feature sets improves the fidelity of the models, as does using full LHCb simulation rather than the “toy Monte Carlo” originally (and still) used to develop models. We have also built a deep learning model to calculate the KDEs from track information. Connecting a tracks-to-KDE model to a KDE-to-hists model used to find PVs provides a proof-of-concept that a single deep learning model can use track information to find PVs with high efficiency and high fidelity. We have studied a variety of models systematically to understand how variations in their architectures affect performance. While the studies reported here are specific to the LHCb geometry and operating conditions, the results suggest that the same approach could be used by the ATLAS and CMS experiments.