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The high spatial-temporal variability in fishing effort, combined with the difficulty of monitoring individual activities, hampers effective management of recreational fisheries. Angler smartphone applications (apps) offer a promising digital tool for self-reporting of fishing effort (E) and catch per unit of effort (CPUE). However, despite their growing use for data collection in recreational fisheries, the existing literature on their performance remains limited, raising concerns about potential biases in the data. Since 2019, daily trips inside the 12 partially protected Marine Protected Areas (MPAs) of the Balearic Islands (Spain) must be self-reported via the “Diari de Pesca Recreativa” app (the App), recording fishing E and CPUE. This study aimed to evaluate the App’s performance in reporting recreational fisheries data over a six-year period. Data obtained via the App (3672 trip self-reports) were compared to data collected through a standard method (360 on-site creel surveys). Importantly, the App represents complete fishing trips, whereas creel surveys record only partial trips, as they are conducted mid-activity. This methodological difference in trip duration reporting was expected to influence estimates of E (hours · angler · trip) and possibly CPUE (catch · E⁻¹). These estimates were compared across datasets overall, as well as stratified by month, fishing type, MPA, and for key target species. Data from the App tended to overestimate E, while creel surveys underestimated it, and significant differences were observed between whole datasets for E and CPUE. However, when stratified, most groups showed no statistically significant differences in E and CPUE estimates. With these generally comparable results, and given that the limitations of one are offset by the strengths of the other, combining both data sources will improve reliability. The App not only generates a higher volume of trip data but also digitizes data collection through a user-friendly platform for self-reporting, enabling automation and analytics for fisheries monitoring and management of recreational fisheries. Because reporting was mandatory in this case, biases commonly associated with voluntary apps (e.g. avidity, age bias) are unlikely to apply, making this study particularly relevant for assessing the utility of mandatory app-based data in fisheries management.

Background Short sleep has been associated with metabolic syndrome (MetS). Weekend catch-up sleep (WCS) serves as a compensatory strategy for sleep deficits, yet its association with MetS in children and adolescents remains unclear. This study aimed to investigate whether WCS is related to a decreased risk for MetS in sleep-deprived individuals of this population.Methods A total of 8930 participants aged 7–17 years with weekday sleep insufficiency were selected from the China Nutrition and Health Surveillance of Children and Lactating Women (2017). Sleeping hours on weekdays/weekends and WCS duration were calculated based on self-reported weekday/weekend sleep schedules. MetS was defined using Cook's criteria. Logistic regression and restricted cubic spline (RCS) regression models adjusting for covariates were used to assess the relationships between WCS and MetS.Results WCS had a significantly protective association with the prevalence of MetS (p 

Enhancing the efficiency of small pelagic purse-seine fisheries is essential for promoting responsible fisheries management in the Persian Gulf. Therefore, this study forecasts the spatiotemporal catch variations of Sind sardinella (Sardinella sindensis) and Buccaneer anchovy (Encrasicholina punctifer) caught by double-boat purse seiners in the northern Persian Gulf, Qeshm Island. To achieve this, a dataset comprising fishing records from 314 purse seine operations, along with associated environmental parameters obtained from satellite imagery—including sea surface temperature (SST), chlorophyll-a concentration, photosynthetically active radiation (PAR), wind speed, wind direction, depth, and distance—was compiled and analyzed using an advanced machine learning methodology covering the period from September 2014 to October 2023. The evaluation of the regression models used to predict sardine and anchovy catches—including Random Forest (RF), Boosting, and Support Vector Regression (SVR)—revealed varying levels of predictive performance across both species and model types. In the case of sardine, the Boosting Regression model yielded the highest predictive accuracy, characterized by a relatively low error (RMSE = 395.5) and moderate explanatory power (R2 = 0.41). Conversely, for anchovies, the SVR model with a radial basis function (RBF) kernel demonstrated superior performance relative to the other models, with an RMSE of 437 and an R2 of 0.35. The results suggest that anchovy catch prediction was more challenging and potentially influenced by additional unmodeled variables. The CPUE of sardine increases with rising chlorophyll-a concentrations up to approximately 2 mg/m3, but declines beyond this point. The optimal SST range was between 22 °C and 26 °C, whereas sardine catches declined at temperatures exceeding 30 °C. Because anchovy was consistently present across all sampling sets, distance from the shoreline emerged as the most influential parameter contributing to successful net captures. A negative relationship was observed between this factor and anchovy CPUE. As the second most important variable, the optimal SST range for anchovy was similar to that of sardine. Given the substantial fishing effort in the northern Persian Gulf, the findings of this study may help enhance regional fishing strategies by promoting the integration of climate change considerations into operational planning.

Bottom towed gears can have severe and long-lasting effects on sensitive marine habitats and species. Diversification of gear types in fisheries using bottom towed gears to encompass low environmental impact methods, such as static gear, is one way to reduce dependency on damaging fishing methods. Here we report on trials investigating how the use of white Light Emitting Diodes (LEDs; Fishtek Marine PotLights) affect catch rates of northern shrimp (Pandalus borealis; normally caught using trawls) across three different pot designs off the west coast of Scotland. We also caught the valuable Norway lobster (Nephrops norvegicus) and valueless poor cod (Trisopterus minutus) and considered occurrences and catch rates of these species. Illuminated pots resulted in significant increases in catch per unit effort (CPUE; ind. pot−1 24 h−1) of northern shrimp for all pot types up to maximum mean of 4.6 ± 4.5 shrimp pot−1 24 h−1 (illuminated shrimp tubes specifically designed to catch shrimp; range = 

Weekend catch-up sleep involves not only changes in sleep duration between weekdays and weekends but also changes in sleep timing. When people sleep less during the weekdays, they accumulate sleep debt and extend their sleep duration on weekends to compensate, which is related with the homeostatic process. Thus, extend their sleep duration on weekends seems to be a protectively strategy of daytime function, mental and physical health. However, not all studies support this protective effect. Sleep duration changes with sleep timing. The difference in sleep timing between weekdays and weekends might bring social jet lag (SJL). Sleep duration changes with sleep timing. The difference in sleep timing between weekdays and weekends can lead to SJL, representing the discrepancy between the biological clock and the social clock. This makes SJL an indicator of circadian misalignment, which is associated with poor daytime function, reduced nighttime sleep quality, and an increased risk of depression, metabolic disturbances, and other diseases. Paradoxically, the protective effect of weekend catch-up sleep duration on the homeostatic process (compensating for sleep debt) and the potential impact of weekend catch-up sleep timing on the circadian process (circadian misalignment) contradict each other. A more comprehensive understanding of weekend catch-up sleep is essential to investigate its mechanisms using the two-process model and other influencing factors.

Background: Prematurity and neonatal hypotrophy (defined as a Z-score below -2 for weight, length, or head circumference) increase the risk of perinatal morbidity, mortality, and long-term developmental disorders. This study examines the growth trajectories of Moroccan preterm infants and investigates the factors influencing their overall growth outcomes at six months, including weight, length, and head circumference. Study Design: A retrospective longitudinal cohort study Methods: This study was conducted at the National Reference Center for Neonatology and Nutrition in Rabat from April to October 2023. It included 686 premature newborns (24-36 weeks) hospitalized for ≥ 48 hours, with complete anthropometric data and follow-up of six months. Exclusion criteria were major malformations, chromosomal abnormalities, metabolic disorders, and incomplete data. ANOVA and multivariate logistic regression identified independent predictors of weight growth outcomes at six months (WAZ ≥ -2), adjusting for confounders (gestational age, gender, hospitalization, multiparity, phototherapy, antibiotics, and early food diversification). Results are reported as odds ratios (ORs) with 95% confidence intervals (CI). Growth curves were generated with Python. Significance was set at P < 0.05. Results: Gestational age of ≥ 32 weeks (OR = 6.66, 95% CI: 1.21, 36.72; P = 0.029) and multiparity (OR = 12.09, 95% CI: 2.12, 68.93; P = 0.005) predicted growth outcomes, while a hospital stay of ≥ 10 days reduced the likelihood (OR = 0.05, 95% CI: 0.01, 0.27; P = 0.001). Male gender and antibiotic use showed non-significant trends (P = 0.053). Conclusion: Close monitoring and targeted nutritional strategies are essential to improve postnatal growth in preterm infants.