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Understanding how morphology evolves requires identifying the types of mutations that contribute to changes in development. We integrated comparative genomics and transcriptomics to reconstruct the evolution and regulation offollistatinparalogs in relation to the evolution of aphid winged and wingless morphs. We find that different pea aphidfollistatinduplicates play an essential molecular role in both the male and female wing dimorphisms, linking the genetic and environmental control of morph determination in each sex, respectively. We also find that an ancestralfollistatingene likely had multiple promoters and that thefollistatinduplicates that evolved wingless-specific expression retained only the ancestral wingless-specific promoter. Our work provides a roadmap for how alternative promoter usage and subsequent gene duplication can enable the evolution of animal form. 

An air gap membrane distillation (AGMD) module was developed by incorporating a poly(etheretherketone) (PEEK) hollow fiber membrane (HFM) having a nonporous wall. This PEEK HFM was placed inside a polyvinylidene fluoride (PVDF) hydrophobic porous wall HFM with a larger bore diameter. The outside diameter (OD) of PVDF HFM is 925 μm, small enough to be capable of achieving a high surface area packing density of 1297 m2/m3. The air gap thickness was very small, 121 μm. Hot brine flowed on the outside of the PVDF HFM; the colder liquid was passed through the lumen of the PEEK-based condenser hollow fibers. Water vapor condensed in the air gap formed between the inner surface of the porous PVDF HFM and the outer surface of the nonporous condenser PEEK fiber. With 85o C hot brine flowing at 40 mL•min􀀀1 and 5o C coolant flowing at 8 mL•min􀀀1, the water vapor flux was 9.05 kg/m2•h with a salt rejection of 98.7 %. Simulation by COMSOL Multiphysics predicted water flux and interfacial temperature of HFM, which supported the experimental observations. Moreover, the influence of module geometry, membrane characteristics and internal flow configuration on permeate flux, thermal efficiency, gained output ratio (GOR), and temperature and concentration polarization were evaluated. Principal component analysis (PCA) was used to illustrate the interconnections among various parameters and their respective contributions to water flux and other performance indicators. Air gap thickness had the strongest influence on temperature polarization. 

Abstract Perfluoroalkyl and polyfluoroalkyl substances (PFASs) are now widely found in aquatic ecosystems, including sources of drinking water and portable water, due to their increasing prevalence. Among different PFAS treatment or separation technologies, nanofiltration (NF) and reverse osmosis (RO) both yield high rejection efficiencies (>95%) of diverse PFAS in water; however, both technologies are affected by many intrinsic and extrinsic factors. This study evaluated the rejection of PFAS of different carbon chain length (e.g., PFOA and PFBA) by two commercial RO and NF membranes under different operational conditions (e.g., applied pressure and initial PFAS concentration) and feed solution matrixes, such as pH (4–10), salinity (0‐ to 1000‐mM NaCl), and organic matters (0–10 mM). We further performed principal component analysis (PCA) to demonstrate the interrelationships of molecular weight (213–499 g·mol⁻¹), membrane characteristics (RO or NF), feed water matrices, and operational conditions on PFAS rejection. Our results confirmed that size exclusion is a primary mechanism of PFAS rejection by RO and NF, as well as the fact that electrostatic interactions are important when PFAS molecules have sizes less than the NF membrane pores. Practitioner PointsTwo commercial RO and NF membranes were both evaluated to remove 10 different PFAS.High transmembrane pressures facilitated permeate recovery and PFAS rejection by RO.Electrostatic repulsion and pore size exclusion are dominant rejection mechanisms for PFAS removal.pH, ionic strength, and organic matters affected PFAS rejection.Mechanisms of PFAS rejection with RO/NF membranes were explained by PCA analysis. 

Cache management is important in exploiting locality and reducing data movement. This article studies a new type of programmable cache called the lease cache. By assigning leases, software exerts the primary control on when and how long data stays in the cache. Previous work has shown an optimal solution for an ideal lease cache. This article develops and evaluates a set of practical solutions for a physical lease cache emulated in FPGA with the full suite of PolyBench benchmarks. Compared to automatic caching, lease programming can further reduce data movement by 10% to over 60% when the data size is 16 times to 3,000 times the cache size, and the techniques in this article realize over 80% of this potential. Moreover, lease programming can reduce data movement by another 0.8% to 20% after polyhedral locality optimization. 

Cache management is important in exploiting locality and reducing data movement. This paper studies a new type of programmable cache called the lease cache. By assigning leases, software exerts the primary control on when and how long data stays in the cache. Previous work has shown an optimal solution for an ideal lease cache. This paper develops and evaluates a set of practical solutions for a physical lease cache emulated in FPGA with the full suite of PolyBench benchmarks. Compared to automatic caching, lease programming can further reduce data movement by 10% to over 60% when the data size is 16 times to 3,000 times the cache size, and the techniques in this paper realize over 80% of this potential. Moreover, lease programming can reduce data movement by another 0.8% to 20% after polyhedral locality optimization. 

Data movement is a common performance bottleneck, and its chief remedy is caching. Traditional cache management is transparent to the workload: data that should be kept in cache are determined by the recency information only, while the program information, i.e., future data reuses, is not communicated to the cache. This has changed in a new cache design named Lease Cache . The program control is passed to the lease cache by a compiler technique called Compiler Assigned Reference Lease (CARL). This technique collects the reuse interval distribution for each reference and uses it to compute and assign the lease value to each reference. In this article, we prove that CARL is optimal under certain statistical assumptions. Based on this optimality, we prove miss curve convexity, which is useful for optimizing shared cache, and sub-partitioning monotonicity, which simplifies lease compilation. We evaluate the potential using scientific kernels from PolyBench and show that compiler insertions of up to 34 leases in program code achieve similar or better cache utilization (in variable size cache) than the optimal fixed-size caching policy, which has been unattainable with automatic caching but now within the potential of cache programming for all tested programs and most cache sizes.