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Inclusion is an area of strategic importance in Aotearoa New Zealand and internationally, requiring that all learners have access to quality education. Nonetheless, children with disabilities in our schools are often excluded from rich learning opportunities, particularly in mathematics. Teaching through inclusive pedagogies, by contrast, supports teachers to plan for and teach all children; however, we know little about how teachers may apply these approaches to their teaching of mathematics. In this article, we report on a case study of one teacher’s practice as we develop a ‘research lesson’ approach that enhances the engagement and learning of all children, including those who are most at risk of being excluded in mathematics lessons. Participants described challenges to inclusive teaching mathematics such as differentiation, engaging contexts, children’s experience of anxiety, and children’s comfort with oral language and discussion. We found that research lesson reflections enabled solutions to be found for these challenges as part of the process of identifying them. We argue that an approach focussed on inclusion is a tool with potential to help teachers to rethink their mathematics classroom organisation and planning. Inclusive teaching may be enacted differently depending on the context; however, we found the key teaching practice to be planning for inclusion at the outset, followed by focussed reflections on teaching. Further, we suggest that research into innovative mathematics pedagogies is most likely to be successful when there is a focus on inclusive pedagogy.

Falls can pose a serious health threat, especially for older people, often leading to fractures, head injuries, or long-term disability. This highlights the need for reliable and non-invasive detection systems. Existing solutions often suffer from limitations such as user discomfort with wearables, constrained coverage of fixed sensors, or environmental challenges in vision-based methods. This paper proposes a dual-stream attention-guided robust indoor fall detection framework to solve the problem. The approach combines a pose-guided stream with a video stream, in which the former captures high-level skeletal features through MediaPipe and simultaneously processes spatiotemporal dynamics from raw RGB frames using a 3D Convolutional Neural Network (CNN) with a temporal attention module. In order to enhance classification precision, features from each stream are adaptively fused in a block based on attention mechanisms, which improves the model’s interpretation of posture and movement semantics. Testing on the KFall dataset reveals that the proposed method achieves 98.71% accuracy, surpassing pre-existing benchmarks. Triggering a visual alert by displaying a red rectangle on the screen upon the occurrence of this event is a subsequent outcome of this work. An ablation study highlights the effectiveness of each component. Finally, the proposed work advances fall detection by combining pose estimation and attention-based deep learning to deliver an accurate, interpretable, and deployable solution.

She's small-town. He's big-league. They broke up years ago… But is it really over?In the small town of Parker Falls, Jessica Parker spends her time serving pie and coming up with ideas to save the failing diner she inherited from her grandfather. A single mom to eight-year-old Wesley, she has enough to keep her busy well into the future. But when her old high school love, Chase Taynor, unexpectedly pops up, Jess finds herself thinking not of the future but of her past with the handsome professional baseball player. After a few bad pitches leave his dream career in limbo, Chase slides back home to Parker Falls…although the town may not be as safe as he'd expected. As Jess and Chase reconnect, old feelings return in a major-league way. With the possibility that Chase could return to the baseball diamond at any time, will their reunion be worth the risk to their hearts? Or will it be déjà vu all over again, with Chase choosing the limelight over the woman he loved before the fame? The book contains a free original recipe for Bacon & White Cheddar Burgers with Spicy Mustard Relish.

A Players of LA NovelTwo men.One night of passion.They never expected to see each other again.They were wrong.Tobias Bennett is a quiet and unassuming man who teaches yoga and enjoys parkour. Though he is proud to be gay, an abusive relationship with a domineering man has left Tobias wary of romance, and he keeps to himself in his tidy Los Angeles apartment.Pro football player Sullivan Archer is Tobias's complete opposite: loud, brash, fond of the spotlight… and deep in the closet. When a hamstring injury sends Van to Tobias as part of his therapy, neither of them is expecting to come face-to-face with his one-night stand. Now they're stuck together throughout Van's healing process, and the close proximity will force them to deal with some hard truths. For Tobias, it's realizing his hookup is a celebrity. For Van, it means accepting that he likes Tobias more than he wanted. They'll both have to acknowledge that if they choose to pursue a relationship, their lives will change in big ways.

What do you do when your love affair with Europe comes to an undignified end? On 24th June 2016, Mike McCarthy wakes up to the news that Britain has voted to leave the EU. A committed European, he is shattered. Over the coming weeks and months, he takes a long, hard look at himself, determined to uncover the reasons why this travesty has occurred, scrutinising the faces of everyone he meets for those he believes may have voted in or out. As he tries to cope with the looming horror of Brexit, Mike fondly recalls his visits to Europe as a young man, the relationships he formed and how these have moulded his pan-European outlook. Digging too deeply into issues has always been his problem. Mike begins to question the views he holds so dear and discovers new things about those closest to him. As McCarthy staggers on from The Referendum to the unthinkable triggering of Article 50, he finds himself plunged himself into a different world of social comment and political media. As the strategy for Bredit emerges, he wonders where his future lies and questions his commitment to a cause that may yet plunge his and Britain's hopes and dreams into the abyss.

The key stage of juvenile pink salmon monitoring is the survey of their fall feeding in the sea that detects the year-class strength. The results of this survey are used for forecasting of the pink salmon returns to the Karaginsky fishing subzone in Bering Sea and to the Okhotsk Sea and the landing in the next year. The trawl surveys with two research vessels have conducted in recent years that allows to cover vast areas in a short time and to exclude repeated counts of the same fish on neighbor transects. In 2024, such trawl survey for pink salmon counting was conducted in the western Bering Sea and Okhotsk Sea that provided representative data on the juveniles abundance used for forecasting their returns and catches in the Karaginsky fishing subzone and Okhotsk Sea. The abundance of pink salmon in the western Bering Sea was estimated in 452∙106 ind. that was about a half of their numbers in previous even years (2018, 2020, 2022). Their return to the Karaginsky fishing subzone in the next year is expected as 72∙106 ind. at the lower limit of confidence interval, that provides the catch of 49∙103 t with the expected weight of spawners about 1 kg and 32 % escapement to the spawning grounds. In the Okhotsk Sea, the abundance of pink salmon was estimated in 1077∙106 ind. that was lower than in 2020 and 2022. Their expected return to the Okhotsk Sea in the next year is expected as 123∙106 ind. at the lower limit of confidence interval, that provides the catch of 100∙103 t with the weight of 1.3 kg and escapement of 35 %. Abundance in «northern» and «southern» regional complexes of local stocks is estimated for pink salmon in the Okhotsk Sea using cluster analysis with the expectation-maximization algorithm (EM clustering); the «northern» group prevailed with the ratio 64:36 %.

This study evaluated the performance of chocolate squid (Todarodes pacificus) bait as a lower-cost alternative to traditional squid bait in a snow crab (Chionoecetes opilio) fishery in Eastern Canada. The results showed that pots with chocolate squid bait had significantly lower catch rates compared to pots with traditional squid bait. The chocolate squid bait significantly reduced the number of crabs caught per pot by 13.99% and the weight of crabs caught per pot by 2.88 kg. Although the chocolate squid bait is cheaper, the decrease in catch rates could require increased effort to reach individual quotas, which could lead to longer or more frequent fishing trips and more traps being fished, increasing fuel consumption and habitat disruption, resulting in negative environmental impacts. Finding alternative lower-cost baits that maintain catch rates remains a key priority for reducing operational costs and minimizing environmental impacts in the snow crab fishery.

Cantrang (boat Danish seine) has been illegal since 2015 but remains prevalent in Indonesia’s Java Sea. Despite known negative impacts, no comprehensive ecological assessment of cantrang fishing exists. This study evaluates its effects by analyzing catch data based on taxa, trophic level, habitat, and fishing vulnerability by a multivariate approach. In this study, the size of 60 cantrang vessel samples were grouped into 4, namely 20–30, 31–50, 51–100, and 101–200 gross tons (GT), representing the spatial distribution of the fishing grounds. Larger vessels catch more diverse and abundant fish, primarily reef-associated and demersal species groups. There was a significant difference in the fishing vessel’s size on the catch’s composition (analysis of similarities, ANOSIM R = 0.114, p = 0.024). The dominant catches were families of Loliginidae (Loligo sp., 24.38%) and Nemipteridae (Nemipterus nematophorus, 19.29%), trophic level 2.7 (34.41–43.18%), reef-associated and demersal fish (37.06–46.09%), and low vulnerability group of fish (58.01–64.56%). Additionally, 2.69–8.56% of the endangered, threatened, and protected species of wedgefish (Rhyncobatus sp.) were also caught by the cantrang. This study confirms the impacts of cantrang on fish resources in the Java Sea, Indonesia’s Fisheries Management Area 712. The findings emphasize the need to improve management strategies to achieve sustainable fish resources and marine biodiversity in the region.

Cikidang Fishing Port is one of the fishing ports that plays an important role in capture fisheries in Pangandaran, with drift gillnet as the main fishing gear. The high use of this tool encourages the analysis of the diversity and composition of the catch to assess fishery productivity and maintain resource sustainability. This study aimed to analyze the composition and diversity of drift gillnet catches landed at the PPI Cikidang Pangandaran. The methods used include the calculation of production amount and value, Catch Per Unit Effort, percentage of catch composition, and diversity index. The data analyzed were obtained from the Cikidang PPI statistical report during the 2019-2021 period. The results showed that white pomfret (Pampus argenteus) was the most dominant species in the catch, with an average contribution of 26.4% per year, whereas yellow mackerel (Selaroides leptolepis) had the least catch (only 0.62% per year). The catch diversity index showed a value of 2.77 in 2019, 2.19 in 2020, and 2.21 in 2021, which falls into the medium category. Habitat conservation efforts and increased awareness of fishermen are also needed so that fishery resources in the Cikidang Fishing Port remain sustainable and productive in the long term.

Abstract Background The high prevalence of hepatitis B weighs heavily on public health in China. In 2009, a catch-up vaccination program for children aged 8–15y was implemented to curb hepatitis B, while the effectiveness of this intervention has not been investigated. We aimed to evaluate the effectiveness of catch-up vaccination on the incidence of hepatitis B in Guangzhou, China. Methods We obtained individual data of all hepatitis B cases from 2005 to 2019 in Guangzhou from Guangzhou Center for Diseases Control and Prevention. Based on daily reported number of cases, we constructed generalized linear models to estimate the effectiveness of the intervention on the incidence of hepatitis B in each age group from 11 to 25 years. We further estimated the age-standardized effectiveness. Finally, we examined the effectiveness in different subgroups by sex and clinical types of hepatitis B. Results A total of 58,204 hepatitis B cases among individuals aged 11–25y were reported in Guangzhou from 2005 to 2019, with an average annual age-standardized incidence of 117.30 cases per 100,000 individuals. The catch-up vaccination contributed to an age-standardized 20.02% (95% confidence interval: 15.97%, 23.87%) decrease in the hepatitis B incidence among individuals aged 11–25y and prevented an annual age-standardized average of 17.40 (95% empirical confidence interval [eCI]: 9.24, 23.78) cases per 100,000 individuals from hepatitis B during the study period. The intervention could better protect males (excess incidence rate [EIR]: -21.82 [95% eCI: -30.51, -10.15] cases per 100,000 individuals), and prevent chronic cases (EIR: -24.27 [95% eCI: -30.62, -16.09] cases per 100,000 individuals). Conclusions The massive catch-up vaccination against hepatitis B among children plays an important role in alleviating the burden of hepatitis B.

This paper conducts a comprehensive examination of the sources of economic growth and catch-up of ASEAN countries since the Asian Financial Crisis, with comparative views of China and India. The study employs different decomposition frameworks to gain insights into the drivers of the Association’s economic performance over the 1997-2017 period. Three findings are most notable. First, all ten member states, except for Brunei, recorded a strong catch-up performance, with labour productivity being the leading driver in most countries. Second, the drivers of labour productivity catch-up exhibit some distinctive patterns among countries, which depend on the level of income and economic structure. Third, in all decomposition analyses, ASEAN countries are well below China and India across sources of growth, which tends to suggest that countries in the grouping could improve their performance by enhancing market integration and policy coordination. Although the long-term prospect of ASEAN is bright, the COVID-19 pandemic and the recent military coup in Myanmar have indicated that the road to future prosperity of the region is expected to face formidable challenges.

This paper is inspired by traditional rural fishing methods and proposes a new metaheuristic optimization algorithm based on human behavior: Catch Fish Optimization Algorithm (CFOA). This algorithm simulates the process of rural fishermen fishing in ponds, which is mainly divided into two phases: the exploration phase and the exploitation phase. In the exploration phase, there are two stages to search: first, the individual capture stage based on personal experience and intuition, and second, the group capture stage based on human proficiency in using tools and collaboration. Transition from independent search to group capture during the exploration phase. Exploitation phase: All fishermen will surround the shoal of fish and work together to salvage the remaining fish, a collective capture strategy. CFOA model is based on these two phases. This paper tested the optimization performance of CFOA using IEEE CEC 2014 and IEEE CEC 2020 test functions, and compared it with 11 other optimization algorithms. We employed the IEEE CEC2017 function to evaluate the overall performance of CFOA. The experimental results indicate that CFOA exhibits excellent and stable optimization capabilities overall. Additionally, we applied CFOA to data clustering problems, and the final results demonstrate that CFOA’s overall error rate in processing clustering problems is less than 20%, resulting in a better clustering effect. The comprehensive experimental results show that CFOA exhibits excellent optimization effects when facing different optimization problems. CFOA code is open at https://github.com/Meky-1210/CFOA.git.