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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.

Purpose Age-related hearing loss (ARHL) impacts quality of life and cognition in older adults, but its link to sleep patterns remains unclear. This study explores associations between ARHL and sleep duration, weekend catch-up sleep (WCS), and bedtime regularity in a Korean population.Methods Data from 6797 adults aged ≥ 40 years were analyzed using the Korea National Health and Nutrition Examination Survey (KNHANES, 2021–2022). Sleep patterns were assessed via self-reported questionnaires. ARHL was classified as mild (26–41 dB) or moderate and above (>41 dB) using audiometry. Poisson regression models examined associations between sleep characteristics and ARHL, adjusting for confounders.Results WCS (≥1 h) was significantly associated with a lower prevalence of both mild (adjusted prevalence ratio = 0.58, 95 % CI: 0.44–0.76) and moderate ARHL (aPR = 0.79, 95 % CI: 0.63–0.98). These associations remained robust in stratified analyses among middle-aged adults and men (p-interaction < 0.01). In contrast, sleep duration and bedtime regularity showed no significant associations with ARHL after adjustment.Conclusion Our findings indicate that WCS may be associated with a lower prevalence of ARHL, particularly in middle-aged adults and men, highlighting the potential role of sleep behavior in auditory health promotion.

Cats and dogs rule—and wreak humorous havoc—in this innovative picture book that reads from front to back and back to front! In this action-packed follow-up to Find Me: A Hide-and-Seek Book, readers will delight in tracking a sly cat, Big Meow, and an elusive dog, Little Woof, through 11 richly detailed scenes populated with dogs, cats, and other cute creatures. Finding each protagonist is made even more fun with vibrant color changes on every page. Open the book from the front to search for Big Meow, then open the book from the back to turn the tables and catch Little Woof. It's two seek-and-find experiences in one book!

Active recall, the act of recalling knowledge from memory, and games-based learning, the use of games and game elements for learning, are well-established as effective strategies for learning gross anatomy. An activity that applies both principles is Catch-Phrase, a fast-paced word guessing game. In Anatomy Catch-Phrase, players must get their teammates to identify an anatomical term by describing its features, functions, or relationships without saying the term itself. Once a teammate guesses the term, players switch roles and continue play with the next term(s) until time runs out. Meanwhile, the instructor notes common errors and reviews knowledge gaps with the team at the end of the round. Prior to the first exam, a seven-question evaluation was distributed to the health professional students. A total of 18 dissection lab groups (86%) played one round of Anatomy Catch-Phrase, with many groups playing multiple times. After the first exam, 73 students (61%) completed the evaluation. On a five-point scale, most students indicated they enjoyed Anatomy Catch-Phrase (4.3 ± 0.9), highly recommended it (4.2 ± 0.9), and wanted to play it in the future (4.3 ± 1.0). Most students also found the game relevant to the course material (4.5 ± 0.8), useful for reviewing (3.9 ± 0.9), and helped reinforce their knowledge (3.9 ± 0.9). Anatomy Catch-Phrase was highly rated, with a score of 4.3 ± 0.9. Multiple students also provided enthusiastic unsolicited comments, such as 'LOVED IT! A fun way to study anatomy!:)'. Overall, Anatomy Catch-Phrase was well-received as a fun activity for reviewing the anatomy relevant to the course.

Small‐scale fisheries often lack historical shark and ray catch information, hampering their management. We reconstructed historical catch trends and current fishing pressure by combining local ecological knowledge, satellite‐based vessel counts, and a short‐term landing‐site survey. To test the effectiveness of this method, we focused on the Bijagós Archipelago (Guinea‐Bissau, West Africa), where historical fisheries data are lacking. Benthic rays (stingrays [Dasyatidae] and butterfly rays [Gymnura spp.]), benthopelagic rays (duckbill eagle rays [Aetomylaeus bovinus] and cownose rays [Rhinoptera marginata]), guitarfish (Glaucostegus and Rhinobatos spp.), requiem sharks (Carcharhinidae), and hammerhead sharks (Sphyrna spp.) declined in abundance by 81.5–96.7% (species dependent) from 1960 to 2020. Fishing effort increased annually: fishing trip duration by 42.0% (SE 3.4), numbers of fishing vessels at sea as perceived by fishers by 36.3% (1.0) (1960–2020), and number of vessels by 12.0% (1.1) (2007–2022). We estimated that in 2020, fishing vessels collectively captured 61–264 sharks and 522–2194 rays per day in the archipelago, depending on the proportion of the fishing fleet that was active (i.e., low fleet activity of 18% and high fleet activity of 80%). We advocate for reducing shark and ray catches by regulating fleet size, reinforcing boundaries of protected areas, and collecting fisher‐dependent information on shark and ray landings to safeguard these vulnerable species and coastal livelihoods. We demonstrated the effectiveness of using this 3‐pronged approach to provide baseline data on shark fisheries, a common challenge in areas with small‐scale fisheries and limited research capacity. [ABSTRACT FROM AUTHOR]

The U.S. imposed sanctions on China focusing on cutting-edge technology. This study examines whether the US sanctions policy against China is effective. If it is effective, we would like to analyze why it is effective through the technical diffusion index and catch-up index. As the U.S. imposed sanctions on Chinese semiconductors and other cutting-edge technologies, the speed of catch-up and diffusion of China's cutting-edge technologies slowed down. From 1980 to 2022, macro data was collected from the IMF (2023) and ILO (2023). Approximately 300,000 patents related to semiconductors, AI, and Big data were used. The impact of advanced technical diffusion on GDP and per capita income was analyzed statistically rigorously using the general sequential logit model (VGAM, VGLM), difference-in-differences (DID) model, hierarchical mixed model, and Long-Short. -Term Memory (LSTM) model. We used LSTM to assess whether China could overtake the United States by 2030. In conclusion, U.S.'s sanction on China were partially effective. It appears that China is rapidly approaching the U.S. through the development of AI and Big data technologies. However, it is doubtful whether China will be able to catch up with the U.S. by 2030. If the U.S. cannot effectively control AI, the possibility of being overtaken by China may increase.

Long-range (LoRa) wireless networks have been widely proposed as efficient wireless access networks for battery-constrained Internet of Things (IoT) devices. However, applying the LoRa-based IoT network in search-and-rescue (SAR) operations will have limited coverage caused by high signal attenuation due to terrestrial blockages, especially in highly remote areas. To overcome this challenge, using unmanned aerial vehicles (UAVs) as a flying LoRa gateway to transfer messages from ground LoRa nodes to the ground rescue station can be a promising solution. In this paper, an artificial intelligence-empowered SAR operation framework using a UAV-assisted LoRa network in different unknown search environments is designed and implemented. The problem of the flying LoRa (FL) gateway control policy is modeled as a partially observable Markov decision process to move the UAV towards the LoRa transmitter carried by a lost person in the known remote search area. A deep reinforcement learning (RL)-based policy is designed to determine the adaptive FL gateway trajectory in a given search environment. Then, as a general solution, a deep meta-RL framework is used for SAR in any new and unknown environments. The proposed deep meta-RL framework integrates the information of the prior FL gateway experience in the previous SAR environments to the new environment and then rapidly adapts the UAV control policy model for SAR operation in a new and unknown environment. To analyze the performance of the proposed framework in real-world scenarios, the proposed SAR system is experimentally tested in three environments: a university campus, a wide plain, and a slotted canyon at Mongasht mountain ranges, Iran. Experimental results show that if the deep meta-RL-based control policy is applied instead of the deep RL-based one, the number of SAR time slots decreases from 141 to 50. Moreover, in the slotted canyon environment, the UAV energy consumption under the deep meta-RL policy is respectively 57% and 23% less than the deep RL and Actor-Critic RL policies.