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Book one of a high-octane thriller series. Fifteen-year-old Dom is cast out of his comfortable life in the Gold Coast's Halcyon Grove when he inherits an ancient debt. Now, he has six Herculean tasks to perform...or lose a pound of flesh. It's a beautiful day in paradise. The sun is shining. The birds are chirping. And Dom Silvagni, eldest brother, indifferent student and elite middle distance runner, is turning fifteen.But instead of cake and candles, Dom receives the most unlikely gift. An ancient family debt from an organisation so secretive and powerful, they are only known as The Debt. And The Debt have made it clear -- Dom must perform six Herculean tasks or lose a pound of flesh.The Debt has ways of making Dom believe and before long he has his first instalment. He must catch The Zolt -- the 17-year-old Facebook Bandit who has stolen light planes, boats and cars from'deserving'homes on nearby Reverie Island. But getting close to the Zolt means persuading his neighbour, the smug self-obsessed Tristan, to invite him to his sumptuous holiday home. And it seems Tristan has an angle too. and it involves Imogen, the only girl close to Dom's heart.Caught between a rock and a hard place, Dom has to honour his family. But the more he discovers about his father, the less he seems to know. Meanwhile The Debt wants its payment...now!

Raine, Ly'Tana and the others escape Brutal's trap, but with dire consequences. Kel'Ratan has been grievously injured, and Rygel must take him to safety to save his life. Yet, they are not out of danger. A monstrous storm called the Wrath of Usa'a'mah has halted their flight from Khalid and they must seek shelter within a remote monastery or die under the storm's power. But High King Brutal has allied himself with the deadly assassins, the Shekinah Tongu. The secretive clan has sworn out a Blood Oath against Rygel in retaliation for his leaving their brothers in the forest to die. With their hellish hounds and Brutal's dark wizard, Ja'Teel, they track Raine and Ly'Tana through the devastation left by the storm. Raine leads them into the west, toward Ly'Tana's home of Kel'Halla, with Brutal's menace confronting them at every turn. As he finds himself falling in love with the exotic Ly'Tana, Raine is plagued by a mysterious voice in his head. Is he going crazy? In Raine, Ly'Tana discovers the one man she cannot live without. However, an evil entity has targeted Ly'Tana, bent on her destruction. How can Raine, Rygel, Kel'Ratan and her griffin bodyguard, Bar, keep her safe from its vast, unseen power? Hunted by Brutal and his evil allies, Raine, Ly'Tana and their friends discover a new, and very strange, force dogging their trail – a pack of enormous, cunning wolves. Mysterious wolves who call to Raine in the night, and bring alive the secret he's kept hidden, even from himself. Taunted by nightmarish visions, Raine is forced to confront his own dark demon – the beast within. Who will catch Raine and Ly'Tana first? Brutal and his pets – or the wolves? Thus begins the second novel of the Saga of the Black Wolf series.

Fisheries based on short lived species are notoriously difficult to manage using traditional effort or catch quota controls. Such fisheries are often characterised by high fecundity, requiring only a small spawning stock to potentially produce a large biomass the following year. This stock, or at least its availability, is driven by unpredictable environmental conditions to a large extent, with the available biomass depleted over the fishing season though both natural and fishing mortality. In most instances, management of these fisheries has focused on ensuring sufficient escapement at the end of the season to allow sufficient recruitment the following year. Catch-rate triggers are one such management tool to determine when fishing should cease. In this study, the use of such triggers in the banana prawn sub-fishery of the Australian Northern Prawn Fishery are assessed. The fishery has an explicit objective of achieving maximum economic yield, and the triggers are set on an economic basis during the season based on price and cost information provided by the industry. The in-season estimates provided by industry were highly correlated with information derived retrospectively through an economic survey, with the industry-provided estimates generally resulting in a more conservative (i.e., higher) break-even catch-rate level. It is the profit maximising behaviour of the fishers, however, that results in the greatest benefits, with most boats leaving the fishery before the trigger catch-rate is reached. The catch-rate trigger operates more as a “safety-net” for the fishery, and possibly a nudge encouraging vessels to maximise their profits given their individual cost structures.

Historical catch data represent a key source of information for fisheries stock assessment models. Historically, commercial fishery catch statistics were estimated from the portion of catch landed in ports. However, many species with relatively low economic value have not been recorded on a species basis but instead as a part of an aggregate category. Reconstructing component species catch from an aggregate category is a common challenge for fisheries stock assessment efforts around the world. Skates are one group of species with low economic value for which landed catch has not been commonly reported by species. In this paper, we present a novel approach to disaggregate the historical catch of the two most abundant skate species on the West Coast of the United States, longnose skate (Caliraja rhina) and big skate (Beringraja binoculata), landed within the aggregated skate category, in ports of Washington State. We used a combination of fishery-dependent and fishery-independent data sources to account for changes in the spatial extent of the fishery over time, and differences in the depth distribution of these two skate species. While developed to disentangle aggregate catch of longnose and big skates, the approach is not limited to skates on the West Coast of the United States, but can be adapted for any species which landings have been reported within an aggregated category elsewhere.

Collecting accurate information on catch levels from marine recreational fishing can be challenging and often results in highly uncertain estimates of landings and discards. Sparse spikes are a common characteristic of these data, with isolated values much higher (e.g., 2–4 times) the surrounding values in a time series of annual estimates. In many cases, it is unclear whether these spikes represent observation error or true, even if anomalous, values. Utilizing multiple data sources simultaneously, integrated stock assessment models may be able to distinguish truth from error in sparse-spike catch estimates, however this supposition has not been well tested. Here, we developed a simulation study to elucidate conditions under which an integrated stock assessment model might perform well (or poorly) when confronted with sparse-spike catch estimates. We found that unconstrained estimation could distinguish truth from error in anomalous values, but only under specific conditions of supporting data. If the anomaly is known to be biased high, estimated catches can get closer to the true value. If the error mechanism is unknown, our results suggest that the true underlying value of a sparse spike is only recoverable when other input data are highly accurate, primarily a reliable index of abundance, but also age composition data in the same year.

Blast fishing is an illegal, ecologically destructive fishing method, fatal for many fish species at large scales. Blast fishing using dynamite is preferred by the fishers, especially small scale fisheries in Turkey, as it requires minimal effort but still results in higher catches. In the current study, demonstration of 20 controlled real-time blasting results involves species composition, size of fish, catch rates, catch composition, commercial/discard ratios, CPUE estimates and clinical observations of external and internal abnormality symptoms of fish species. Blasting trials were carried out with special permission in limited numbers because of its harmful effect. The collected data was tested using PRIMER v6 and diversity indices were also analysed. For the similarity between collected species cluster analysis was used to examine the stability of the results. Multidimensional scaling (MDS) was also applied for the assessment of fish species in the catch. A total of 1014 individuals (63.8 kg) were collected and 18 fish species belonging to seven families were examined. According to laboratory examinations, it was found that blasting caused different external and internal abnormality symptoms in the sampled fish species during the study.

The unexpected success of China's PV industry in technology catch-up has been noted. However, existing research has overlooked the multidimensional nonlinear complexities in its underlying mechanisms. This study introduces the "Seven-Element Diamond Model" theoretical framework and employs machine learning (ML) methods to address this. Using observed data from 84 listed China's PV companies from 2000 to 2021, we systematically examine the intricate mechanisms of technology catch-up in China's PV industry. Key findings include: 1) The self-enhancing mechanism stemming from R&D effort, government subsidies, and domestic demand is pivotal for the successful technology catch-up of China's PV industry. 2) Key regulatory directions are identified from R&D effort to market competition, technology spillover, productivity, and government subsidies. 3) R&D effort forms the underlying logic of China's PV industry technology catch-up, and domestic market demand is an extremely important driver for China's PV technology catch-up. Government subsidies exhibit a "blowout" incentive effect, and the synergistic coupling between key variables is also significant in driving China's PV technology catch-up. This study offers valuable insights into the catch-up of clean energy or sustainable technologies in China and other emerging economies.

Joining a technical standards alliance is becoming increasingly crucial for latecomer enterprises’ innovation catch-up in today's fast-paced technological environment. This study investigates the influence of latecomers’ ambidextrous innovation on technical standards alliances while highlighting the importance of alliance routines. A structural equation model is used to analyse a sample of 118 latecomer members and 45 technical standards alliances in China's strategic emerging industries. Several novel findings are reported. First, latecomers’ two types of innovation catch-up and the three dimensions of alliance routines promote alliance performance, all of which positively impact alliance performance. Second, alliance routines have different effects on latecomers’ Ambidextrous innovation catch-up. All three dimensions of the alliance routine promote utilisation innovation catch-up, whereas behavioural logic and interactive consensus hinder exploration innovation catch-up. Third, utilisation innovation completely mediates between alliance practice and performance, whereas exploration innovation only plays a partial mediating role. This study presents specific recommendations for latecomer enterprises and technical standards alliances.

Highlights •Much of the variation in images of fish in bulk is caused by clutter.•Clutter variation can be effectively simulated using few 3D-models of each species.•Detailed 3D models of fish can be created and used to generate synthetic data sets.•Neural networks trained on simulated data perform well across real-life domains.

In 2024, the Canadian government lifted the moratorium on fishing in what was once the world’s largest single-species fishery. Over the past thirty years, fisheries scientists and historians have debated the role of long-term exploitation in the fishery's collapse, but a lack of accurate historical catch data has hampered these discussions. This study introduces a groundbreaking reconstruction of historical cod catches in Newfoundland from 1508 to 2023. As the the longest, most comprehensive, and accurate reconstruction created to date, this dataset provides a crucial tool for unravelling the complex dynamics of the fishery's rise and fall. The data illuminate the historical trajectories of diverse national fishing fleets and maps the evolving spatial dimensions of the fishery. The dramatic decline of the fishery from centuries of relatively stable catches should prompt concern about the recent return to fishing, and historical data must play a role in informing the fishery's future.

Achieving energy-efficient, precise, and overall efficient production of Antarctic krill (Euphausia superba) is critical for realizing sustainable and ecological fisheries in the context of ongoing natural and anthropogenic climate change. In this study, we comprehensively analyzed commercial E. superba statistics and multivariate marine environmental data from 2010 to 2022 using the gravity center of the fishing ground method, dynamic sliding window, 3DCNN, and 3DCNN-ConvLSTM models. Results: 1) Inter-annual and inter-weekly catch varied significantly, with the total weekly catch evenly distributed between 0 and 2600 tons. The annual gravity center of the fishing grounds varied considerably between years and was mainly concentrated around the islands and in the strait. 2) Neither long- nor short-time-series historical data led to the best prediction. The optimal sliding window size for the 3DCNN was 4, whereas it was 11 for the 3DCNN-ConvLSTM model. 3) Climate change must be considered when selecting data, and the addition of biased data may negatively affect the model's predictive performance. 4) When using an optimal sliding window, the 3DCNN model outperformed the 3DCNN-ConvLSTM model. 5) The 3DCNN model tends to learn information about the environmental variables with the most significant differences in different categories of fishing grounds. This study aids in efficient selection of the most relevant historical data and an optimal model for developing a prediction model for high-catch fishing grounds, thereby providing a scientific foundation for clean production, sustainable development, and effective management of the E. superba fishery.

Small pelagic fishes play a crucial role in marine food webs, providing significant ecological support services. They are the largest target group in global commercial fisheries, accounting for 30 % of the total catch. However, their population status and spatial distribution are highly susceptible to environmental changes and economic development. This study is based on fishing data for 11 small pelagic fisheries in a long-term time series from 1963 to 2021. By integrating various machine learning methods and generalized additive models, we quantitatively assess the impacts and differences of typical climate change events (ENSO and AMO) as well as economic development on the catches of different small pelagic fisheries. Our findings reveal the complex nonlinear and asymmetrical effects of ENSO, AMO, and economic development on the catches, with varying degrees of influence. Economic factors predominantly drive changes in the exploitation of small pelagic fisheries. ENSO, AMO, and their lagged effects significantly influence regional fisheries through teleconnections, with ENSO exerting a particularly pronounced impact on the southeastern Pacific area. While most species are adversely affected by the positive phases of climate change, extreme negative phases do not always benefit. This research provides a systematic understanding of the impacts of climate change and economic expansion on small pelagic fisheries, offering valuable insights for government policymakers and stakeholders to formulate scientific fishing strategies and mitigate the risks of fishery resource depletion.