Effects of inbreeding Coho salmon (oncorhynchus kisutch)

Effects of inbreeding coho salmon (Oncorhynchus kisutch) on survival during early life history, growth, feed efficiency, and resistance to gas bubble disease were studied. No effect of inbreeding could be associated with either F=0.25 or F=0.125. Tetraploidy may help explain the absence of inbreeding depression at these levels

Clinical and molecular characterization of patients with YWHAG‐related epilepsy

Objective YWHAG variant alleles have been associated with a rare disease trait whose clinical synopsis includes an early onset epileptic encephalopathy with predominantly myoclonic seizures, developmental delay/intellectual disability, and facial dysmorphisms. Through description of a large cohort, which doubles the number of reported patients, we further delineate the spectrum of YWHAG-related epilepsy. Methods We included in this study 24 patients, 21 new and three previously described, with pathogenic/likely pathogenic variants in YWHAG. We extended the analysis of clinical, electroencephalographic, brain magnetic resonance imaging, and molecular genetic information to 24 previously published patients. Results The phenotypic spectrum of YWHAG-related disorders ranges from mild developmental delay to developmental and epileptic encephalopathy (DEE). Epilepsy onset is in the first 2 years of life. Seizure freedom can be achieved in half of the patients (13/24, 54%). Intellectual disability (23/24, 96%), behavioral disorders (18/24, 75%), neurological signs (13/24, 54%), and dysmorphisms (6/24, 25%) are common. A genotype–phenotype correlation emerged, as DEE is more represented in patients with missense variants located in the ligand-binding domain than in those with truncating or missense variants in other domains (90% vs. 19%, p < .001). Significance This study suggests that pathogenic YWHAG variants cause a wide range of clinical presentations with variable severity, ranging from mild developmental delay to DEE. In this allelic series, a genotype–phenotype correlation begins to emerge, potentially providing prognostic information for clinical management and genetic counseling

Eight Decades of Hatchery Salmon Releases in the California Central Valley: Factors Influencing Straying and Resilience

The California Central Valley contains the southernmost native populations of Chinook Salmon Oncorhynchus tshawytscha, which inhabit a highly variable, anthropogenically altered environment. To mitigate habitat loss and support fisheries, millions of fall‐run hatchery salmon are released each year, often transported downstream to avoid in‐river mortality, with consequences not fully understood. We synthesize historical trends in release location and timing (1941–2017), focusing on outcomes influencing stock resilience, adult straying, and ocean arrival timing. Over time, juveniles have been transported increasing distances from the source hatchery, particularly during droughts. Transport distance was strongly associated with straying rate (averaging 0–9% vs. 7–89% for salmon released on site vs. in the bay upstream of Golden Gate Bridge, respectively), increasing the effects of hatchery releases on natural spawners. Decreasing variation in release location and timing could reduce spatiotemporal buffering, narrowing ocean arrival timings and increasing risk of mismatch with peak prey production. Central Valley salmon epitomize the pervasive challenge of balancing short‐term (e.g., abundance) against long‐term (e.g., stability) goals

Neural equalizer with adaptive multidimensional spline activation functions

This paper presents a new neural architecture suitable for digital signal processing application. The architecture, based on adaptable multidimensional activation functions, allows one to collect information from the previous network layer in aggregate form. In other words the number of network connections (structural complexity) can be very low respect to the problem complexity. This fact, as experimentally demonstrated in the paper, improve the network generalization capabilities and speed up the convergence of the learning process. A specific learning algorithm is derived and experimental results, on channel equalization, demonstrate the effectiveness of the proposed architecture

Blind source separation of convolutive nonlinear mixtures by flexible spline nonlinear functions

In this paper a nonlinear deconvolving system, based on the use of the recently introduced flexible activation function whose control points are adaptively changed, is proposed