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CATCH-1 is the first pathfinder within the Chasing All Transients Constellation Hunters (CATCH) space mission. Its payloads include the Silicon Drift Detector (SDD) system and light-weight X-ray optics. The main goal of CATCH-1 is to validate key technologies of the timing satellites in the constellation, such as the electronics of the SDD detector system, Micro-Pore Optics (MPO), and the deployable mast. The SDD detector system is required to operate with high energy resolution and dead time to detect various transients. This paper presents the design and performance of the SDD electronics system of CATCH-1. The electronics system comprises front-end electronics (FEE) and a data acquisition system (DAQ). Test results demonstrate that the energy resolution of all four detector channels are better than 150 eV at 5.9 keV, with the energy band ranging from 0.5 to 8 keV, and the dead time is better than 10μs, meeting the design specifications.

In 1974, at the age of thirty-two, Les AuCoin became the first Democrat to win a US House seat in Oregon's First District. He was one of the post-Watergate reformers who shook up an insular, autocratic Congress and led fights for affordable housing, “trickle-up” economics, wilderness protection, abortion rights, and nuclear arms control. In the 1980s, the Oregonian called him “the most powerful congressman in Oregon.” In this compelling collection of life stories, AuCoin traces his unlikely rise from a fatherless childhood in Central Oregon to the top ranks of national power. Then came a painful defeat in one of the most controversial races in US Senate history, against incumbent Bob Packwood. A fly fisher, AuCoin uses “catch and release” as a metaphor for succeeding and letting go of loss with dignity and equanimity. His memories are in turn funny, suspenseful, and revealing. AuCoin takes us to the Kremlin, pre-industrial China, the Arctic National Wildlife Refuge, and into the tortuous politics of the Northwest spotted owl crisis. He interacted with world figures like Mikhail Gorbachev, Ronald Reagan, House Speakers Tip O'Neill and Jim Wright, and Oregon legends Tom McCall and Mark Hatfield. Closer to home, AuCoin allied himself with activists like Sidney Lasseigne of the Newport Fishermen's Wives. Catch and Release offers readers a revealing glimpse behind the scenes of congressional life, as lived by the 535 souls who inhabit the US House and Senate—including the author, who assesses his own strengths and foibles with humility and candor.

Purpose. To investigate the long-term dynamics of commercial catches of Leuciscidae in the Dnipro Reservoir and to determine sustainable catch limits as an aquatic bioresource. Methodology. The study was conducted in 2024–2025 at three commercial fishing areas of the Dnipro Reservoir (central part, lower part, Samara Bay), which differed in hydrology, ecology, and the level of human impact. Classical ichthyological methods were used. The study objects were members of the family Leuciscidae: common bream, chub, asp, roach, silver bream, blue bream, sabrefish, rudd, white-eye bream, vimba, and bleak. The analysis included species composition of commercial catches, age and size structure of fish populations, condition factors, catch dynamics over long-term series, and official commercial statistics (2014–2024). Findings. It was found that Leuciscidae species account for 54.1% of total catches in the Dnipro Reservoir cascade, with common bream, roach, and bleak being the main commercial species. Populations of these species are characterized by stable abundance and biomass. Based on biological and fishing parameters, fish stocks and catch limits for the Dnipro Reservoir in 2026 were calculated. Originality. For the first time in the Dnipro Reservoir, a comprehensive analysis of Leuciscidae commercial stocks was conducted, incorporating long-term data series, spatial-temporal population characteristics, and mortality coefficients. Differentiated fishing regimes for specific reservoir areas were proposed. Practical Value. The results allow optimization of fishery management, ensuring sustainable use of resources and biodiversity conservation, reducing the risk of stock depletion, and supporting the stability of commercial fishing. The proposed recommendations were used as the basis for establishing fish catch limits in the Dnipro Reservoir in 2026.

Fishery production surveys constitute the basis for assessing and managing fishery resources. A well-defined and reasonable sample size is essential for the accuracy and precision of survey outcomes. In this study, we aggregated production surveys from major economic fishing ports in the northern South China Sea from 2008 to 2018, totaling 36 499 forms. It was assumed that these data accurately reflected the catch per unit effort (CPUE) of Decapterus maruadsi employing various fishing gear. We focused on optimizing the investigations by analyzing the CPUE of D. maruadsi across five distinct fishing operations: otter trawl, twin trawl, light purse seine, gillnet, and light falling net. We organized the survey data by fishing type and stratified them according to engine power and survey time. We used a proportional allocation for the sample sizes and stratified random sampling without replacement for the simulations. We utilized computer simulations to resample the CPUE of D. maruadsi derived from five different fishing operation types, employing the relative estimation error (REE) and relative bias (RB) as evaluation metrics. We aimed to analyze the relationship between the CPUE of D. maruadsi and sample size in the northern South China Sea. The port catch sampling survey yielded production information for different fishing operation types, with each survey form reflecting the CPUE data for a single voyage. Because of the variability of the CPUE for D. maruadsi among different fishing operation types and across seasons within the same operation type, this study categorized the survey forms by operation type and season. We calculated the CPUE for each operation type in the different seasons and used these values as the true values for comparison. We consolidated the survey data from various fishing gears across different power ranges and computed the CPUE for these forms. Furthermore, we employed CPUE as a metric to compare the fishing capacity and efficiency of the different fishing gear targeting the species of interest. We observed seasonal variations in the CPUE estimates for D. maruadsi across different fishing operation types. By averaging the CPUE estimates over the four quarters, we discovered that the light purse seine method had the highest CPUE estimate at 3.577 kg/(kW·d), whereas the gillnet method had the lowest CPUE estimate at 0.143 kg/(kW·d). The results of this study revealed differences in the distribution range of REE values for catch rate estimates among different fishing operation types; however, the overall trend of change was similar. Particularly, with an increase in sample size, the boxplot of REE values for CPUE estimates of each fishing gear showed a gradually decreasing trend, whereas the RB values exhibited decreasing dispersion and tended to stabilize. Notably, the distribution range of REE values for the light purse seine and gill net methods was relatively smaller than that of other fishing gear. We found that the minimum sample sizes required for estimating CPUE varied among different fishing operation types, and the rules for determining these minimum sample sizes also differed. Otter trawl, pair trawl, and light purse seine determined the minimum sample size based on REE ≤ 10%, whereas gillnets and light falling nets (except in winter) determined the minimum sample size based on REE ≤ 5%. We also found that, as the sample size reached a specific threshold, the impact of increasing the number of survey forms on the estimation accuracy of the average catch rates gradually decreased. In the summer, when the sample size reached 600, the REE values for twin trawl, light purse seine, and light falling net were below 10%; when the sample size reached 800, the REE values for the otter trawl decreased to within 10%; and when the sample size increased to 1 200, the REE value for the gill net decreased to within 10%, whereas the REE values for other operation types remained below 5%. As the sample size continued to expand, the impact on sampling accuracy became increasingly minimal. In general, when the sample size reached a certain threshold, the changes in REE and RB tended to stabilize, and the redundant portion of the sample size could be optimized. Even with a reduced sample size, estimation accuracy could be ensured to a certain extent. In this study, the minimum acceptable sample size for CPUE estimation varied across fishing operation types. Assuming that the survey data from 2008 to 2018 accurately represented fishery production and considering an REE of less than 10%, the minimum number of survey trips required for CPUE estimation of D. maruadsi by operation type and season were as follows: otter trawl (91, 68, 59, and 86), twin trawl (41, 41, 82, and 52), light purse seine (164, 87, 95, and 57), gillnet (218, 218, 245, and 191), and light falling net with attractors (100, 81, 64, and 43). On average, these corresponded to 76 trips for the otter trawl, 54 for the twin trawl, 218 for the gillnet, 101 for the light purse seine, and 72 for the light falling net with attractors. In this study, we optimized sample size using the mean CPUE of D. maruadsi as the survey target, and the evaluation results may serve as a reference for catch surveys in northern South China Sea fishing ports.

Abstract Background Depression is a prevalent disorder with significant health impacts. Physical activity is known to protect against depression, but its effects may vary in populations with disrupted sleep patterns, such as weekend catch-up sleepers, which refers to participants who sleep longer on weekends than on weekdays. This study examines the dose-response relationship between physical activity and depression in this population. Methods Data from 1,906 participants in the National Health and Nutrition Examination Survey (2021–2023) were analyzed. Physical activity was measured in MET-minutes per week, and depression was assessed using the PHQ-9. Multivariate linear regression, restricted cubic spline, and two-part linear regression models were employed. Results In the adjusted model, physical activity showed a negative trend with depression, though this association did not reach statistical significance in the fully adjusted model. Stratified analyses revealed stronger associations in women (OR = 0.86, 95% CI: 0.75, 0.99, P = 0.0329) and individuals aged 40–60 years (OR = 0.79, 95% CI: 0.65, 0.97, P = 0.0237). A threshold effect was observed, with physical activity below 2.48 MET-min/1000-wk showing a negative association with depression (OR = 0.69, 95% CI: 0.56, 0.85, P = 0.0006). Beyond this threshold, the relationship changed. Conclusion A nonlinear relationship between physical activity and depression was identified in weekend catch-up sleepers, with moderate activity levels (2.48 MET-min/1000-wk) offering the greatest mental health benefits, particularly in women and individuals aged 40–60 years. Clinical trial number Not applicable. Graphical Abstract

Background We aimed to examine the effect of physical activity (PA) and weekend catch-up sleep (WCS) on depressive symptoms by evaluating their effects on high-sensitivity C-reactive protein (hsCRP) levels.Methods Data were collected from 10,715 adults aged ≥19 years. PA and depressive symptoms were assessed using self-report scales. The WCS was calculated by subtracting self-reported average weekday sleep hours from weekend sleep hours, and serum hsCRP levels were measured using immunoturbidimetric methods. Given that depressive symptoms are characterized by their multifaceted nature, we identified specific symptoms associated with hsCRP levels. Path analysis was used to investigate the association between PA, WCS, hsCRP, and depressive symptoms, and that between PA, WCS, hsCRP, and specific symptoms related to hsCRP.Results Higher levels of PA and WCS were associated with a decreased risk of depressive symptoms through lowering hsCRP levels. Among various depressive symptoms, sleep problems and appetite changes were associated with hsCRP. In pathway analyses using them as dependent variables, higher levels of PA and WCS were also associated with a decreased risk of sleep problems and appetite changes through lowering hsCRP levels.Limitations The current study employed a cross-sectional design, and WCS and PA were based on participants' self-reports rather than objective measurements.Conclusions Increased levels of PA and WCS may help alleviate depressive symptoms, particularly sleep problems and appetite changes, by mitigating chronic inflammation. Therefore, ensuring adequate exercise time and compensating for inadequate weekday sleep during weekends are crucial for maintaining mental well-being.

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.