This paper, for the goal of revealing the mechanism of compromise and change in coordination, will focus on US-Japan conflict over commercial whaling. The regime like the international whaling regulation, where countr...This paper, for the goal of revealing the mechanism of compromise and change in coordination, will focus on US-Japan conflict over commercial whaling. The regime like the international whaling regulation, where countries agree in general but disagree on coordination methods, is known as the Battle of the Sexes in game theory. It has been believed that in regimes presented as the Battle of the Sexes （BoS） situation, once the countries could somehow coordinate their interests and reach an agreement on the specific method of coordination, neither country would have the incentive to withdraw from that agreement. This case study, however, shows that this belief is not always true. From the analysis of this study, it will be concluded that coordination methods change over time even in regimes where the countries agree in general and disagree on coordination methods. In this case, ＂power,＂ ＂institution＂ and ＂consensus＂ are pointed out as incentives to make the two countries accept a specific coordination method.展开更多
This paper is to present a framework to analyse international relations regarding protection and exploitation of an endangered species. The question of how to balance conservation and consumption in order to maintain ...This paper is to present a framework to analyse international relations regarding protection and exploitation of an endangered species. The question of how to balance conservation and consumption in order to maintain the sustainability of resources and nature is not only the central challenge of conservation ecology, but also an international political and economic issue that frequently leads to confrontation between countries. In relation to whales, for example, Japan has long been subjected to criticism by anti-whaling countries such as the United States and Australia, and has faced off against them on the international stage. And, more recently, similar confrontations have begun to appear in relation to tuna and eel. It has been highlighted in recent years that Pacific Bluefin Tuna are becoming endangered, and there is considerable national and international concern with regard to their resource management. This paper first obtains an implication about the course of events that led to the fishing ban. The implication is applied to the case of Pacific Bluefin Tuna. Pacific Bluefin Tuna and the whaling issue reveals points of commonality. The conclusion is that history of the whaling issue implies that Japan will lose the support not only of countries opposed to fishing but also of neutral countries, if Tokyo continues to adopt policies which make light of resource conservation. Even a total ban on the fishing of Pacific Bluefin Tuna may result. This implication from the whaling issue is potentially helpful to predict the development of international relations and conservation regarding other endangered species.展开更多
The Whaling in the Antarctic Case (Australia v. Japan: New Zealand intervening) decided by the International Court of Justice (hereinafter "ICJ" or "the Court") on 31 March 2014 dealt with the inte...The Whaling in the Antarctic Case (Australia v. Japan: New Zealand intervening) decided by the International Court of Justice (hereinafter "ICJ" or "the Court") on 31 March 2014 dealt with the interpretation of specific provisions of the 1946 International Convention for the Regulation of Whaling (ICRW), in particular Article VIII.1, and its complementary instruments, i.e., the Schedule and the Annexes of the International Whaling Commission Scientific Committee. The decision of the Court was a remarkable good one. However, its rigorous reasoning focused almost exclusively on the required purpose of "scientific research" of the JARPA II Programme1 permits as set out in the ICRW, approaching the convention as an autonomous self-contained regime which leaves aside other additional grounds. Nonetheless, it would be beneficial for further jurisdictional developments to strengthen the scope of the ICWR system with the applicable provisions of the United Nations Convention on the Law of the Sea (UNCLOS) and other treaties and institutions impinging on whales and whaling, e.g., CITES, Bonn Convention, Antarctic Treaty System, among others. The query remains concerning the unexplored sources of international law ruling Antarctic spaces and species which are absent in the judgment of the Court but may allow an evolutive interpretation of the ICRW.展开更多
This paper explores the archaeology of whaling in Arctic prehistory,focusing on the emergence and development of whaling as a central component of cultural ecology among prehistoric Inuit and related societies.Drawing...This paper explores the archaeology of whaling in Arctic prehistory,focusing on the emergence and development of whaling as a central component of cultural ecology among prehistoric Inuit and related societies.Drawing on archaeological evidence from key sites across Alaska,the Chukchi Peninsula,and the Bering Strait region,the study examines how whaling technologies and practices evolved alongside climatic fluctuations,ecological shifts,and social transformations.Integrating ethnographic insights and paleoclimatic data,the study argues that Inuit engagement with whales was not only a subsistence strategy but a long-term,historically contingent relationship that shaped and was shaped by broader cultural systems.展开更多
Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devi...Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devices have made power load data increasingly complex and volatile.This places higher demands on the prediction and analysis of power loads.In order to improve the prediction accuracy of short-term power load,a CNN-BiLSTMTPA short-term power prediction model based on the Improved Whale Optimization Algorithm(IWOA)with mixed strategies was proposed.Firstly,the model combined the Convolutional Neural Network(CNN)with the Bidirectional Long Short-Term Memory Network(BiLSTM)to fully extract the spatio-temporal characteristics of the load data itself.Then,the Temporal Pattern Attention(TPA)mechanism was introduced into the CNN-BiLSTM model to automatically assign corresponding weights to the hidden states of the BiLSTM.This allowed the model to differentiate the importance of load sequences at different time intervals.At the same time,in order to solve the problem of the difficulties of selecting the parameters of the temporal model,and the poor global search ability of the whale algorithm,which is easy to fall into the local optimization,the whale algorithm(IWOA)was optimized by using the hybrid strategy of Tent chaos mapping and Levy flight strategy,so as to better search the parameters of the model.In this experiment,the real load data of a region in Zhejiang was taken as an example to analyze,and the prediction accuracy(R2)of the proposed method reached 98.83%.Compared with the prediction models such as BP,WOA-CNN-BiLSTM,SSA-CNN-BiLSTM,CNN-BiGRU-Attention,etc.,the experimental results showed that the model proposed in this study has a higher prediction accuracy.展开更多
Find It What do boat captai ns try to do?W hale and dolphin watching is a popular thing to do off the coast of Hualien.*It is an amazing adventure!Imagine this:You are on a boat.Then a big whale jumps out of the water.
1 Move over Simone Biles,because grey whales might just be the next Olympic champions.This conclusion can be drawn from a new study that filmed these amazing animals doing underwater headstands(头倒立)and other moves....1 Move over Simone Biles,because grey whales might just be the next Olympic champions.This conclusion can be drawn from a new study that filmed these amazing animals doing underwater headstands(头倒立)and other moves.2 As part of a seven-year project,scientists used drones(无人驾驶飞机)to observe a group of 200 grey whales off the coasts of Oregon,Washington,northern California and southern Canada.The new study findings,published in Animal Behaviour,revealed that grey whales do headstands by pressing their mouths against the ocean floor while searching for something to eat.Scientists also noticed that when doing headstands,grey whales move like human synchronized swimmers.展开更多
Cetaceans include the largest animals ever to have lived onearth and are uniparous(producing a single calf at each birth)across the infraorder.However,instances of multiple fetuseshave been observed naturally among un...Cetaceans include the largest animals ever to have lived onearth and are uniparous(producing a single calf at each birth)across the infraorder.However,instances of multiple fetuseshave been observed naturally among uniparous mammals,including cetaceans.Despite this,there is no known documented case of twins in cetaceans successfully carried to termin the wild(Perrin and Donovan 1984),and if such casesexist,they would be diffcult to detect.展开更多
China Launches“Blue Whale”-World’s First High-speed Uncrewed Submersible.The"Blue Whale,"a cutting-edge high-speed submersible unmanned surface vessel,was launched on April 28 in Zhuhai,south China's ...China Launches“Blue Whale”-World’s First High-speed Uncrewed Submersible.The"Blue Whale,"a cutting-edge high-speed submersible unmanned surface vessel,was launched on April 28 in Zhuhai,south China's Guangdong Province.展开更多
Neurodegeneration involves a wide range of neuropathological alterations affecting the integrity,physiology,and architecture of neural cells.Many studies have demonstrated neurodegeneration in different animals.In the...Neurodegeneration involves a wide range of neuropathological alterations affecting the integrity,physiology,and architecture of neural cells.Many studies have demonstrated neurodegeneration in different animals.In the case of Alzheimer's disease(AD),spontaneous animal models should display two neurohistopathological hallmarks:the deposition ofβ-amyloid and the arrangement of neurofibrillary tangles.However,no natural animal models that fulfill these conditions have been reported and most research into AD has been performed using transgenic rodents.Recent studies have also demonstrated that toothed whales-homeothermic,long-lived,top predatory marine mammals-show neuropathological signs of AD-like pathology.The neuropathological hallmarks in these cetaceans could help to better understand their endangered health as well as neurodegenerative diseases in humans.This systematic review analyzes all the literature published to date on this trending topic and the proposed causes for neurodegeneration in these iconic marine mammals are approached in the context of One Health/Planetary Health and translational medicine.展开更多
Recent studies employing deep learning to solve the traveling salesman problem(TSP)have mainly focused on learning construction heuristics.Such methods can improve TSP solutions,but still depend on additional programs...Recent studies employing deep learning to solve the traveling salesman problem(TSP)have mainly focused on learning construction heuristics.Such methods can improve TSP solutions,but still depend on additional programs.However,methods that focus on learning improvement heuristics to iteratively refine solutions remain insufficient.Traditional improvement heuristics are guided by a manually designed search strategy and may only achieve limited improvements.This paper proposes a novel framework for learning improvement heuristics,which automatically discovers better improvement policies for heuristics to iteratively solve the TSP.Our framework first designs a new architecture based on a transformer model to make the policy network parameterized,which introduces an action-dropout layer to prevent action selection from overfitting.It then proposes a deep reinforcement learning approach integrating a simulated annealing mechanism(named RL-SA)to learn the pairwise selected policy,aiming to improve the 2-opt algorithm's performance.The RL-SA leverages the whale optimization algorithm to generate initial solutions for better sampling efficiency and uses the Gaussian perturbation strategy to tackle the sparse reward problem of reinforcement learning.The experiment results show that the proposed approach is significantly superior to the state-of-the-art learning-based methods,and further reduces the gap between learning-based methods and highly optimized solvers in the benchmark datasets.Moreover,our pre-trained model M can be applied to guide the SA algorithm(named M-SA(ours)),which performs better than existing deep models in small-,medium-,and large-scale TSPLIB datasets.Additionally,the M-SA(ours)achieves excellent generalization performance in a real-world dataset on global liner shipping routes,with the optimization percentages in distance reduction ranging from3.52%to 17.99%.展开更多
The Māori people are indigenous to Aotearoa New Zealand,and their language and culture are considered vital components of the nation’s cultural heritage.However,Te Reo Māori is regarded as a lowresource language ou...The Māori people are indigenous to Aotearoa New Zealand,and their language and culture are considered vital components of the nation’s cultural heritage.However,Te Reo Māori is regarded as a lowresource language outside of New Zealand,and its literary works usually rely on English as a pivot language for translation and communication.Therefore,in the process of promoting Māori literature as part of world literature by translating it into non-English languages,the accurate translation of cultural keywords is crucial to prevent dilemmas such as information loss and cultural misappropriation.In this article,we aim to explore effective translation strategies to enhance the international visibility and readership of Māori literature by analysing the rendition of Māori cultural keywords in the Chinese translation of“The Whale Rider”.展开更多
Energy storage power plants are critical in balancing power supply and demand.However,the scheduling of these plants faces significant challenges,including high network transmission costs and inefficient inter-device ...Energy storage power plants are critical in balancing power supply and demand.However,the scheduling of these plants faces significant challenges,including high network transmission costs and inefficient inter-device energy utilization.To tackle these challenges,this study proposes an optimal scheduling model for energy storage power plants based on edge computing and the improved whale optimization algorithm(IWOA).The proposed model designs an edge computing framework,transferring a large share of data processing and storage tasks to the network edge.This architecture effectively reduces transmission costs by minimizing data travel time.In addition,the model considers demand response strategies and builds an objective function based on the minimization of the sum of electricity purchase cost and operation cost.The IWOA enhances the optimization process by utilizing adaptive weight adjustments and an optimal neighborhood perturbation strategy,preventing the algorithm from converging to suboptimal solutions.Experimental results demonstrate that the proposed scheduling model maximizes the flexibility of the energy storage plant,facilitating efficient charging and discharging.It successfully achieves peak shaving and valley filling for both electrical and heat loads,promoting the effective utilization of renewable energy sources.The edge-computing framework significantly reduces transmission delays between energy devices.Furthermore,IWOA outperforms traditional algorithms in optimizing the objective function.展开更多
This study integrates the individual photovoltaic(PV)and thermoelectric generator(TEG)systems into a PV-TEG hybrid system to improve its overall power output by reutilizing the waste heat generated during PV power pro...This study integrates the individual photovoltaic(PV)and thermoelectric generator(TEG)systems into a PV-TEG hybrid system to improve its overall power output by reutilizing the waste heat generated during PV power production to enhance its operational relia-bility.However,stochastic environmental conditions often result in partial shading conditions and nonuniform thermal distribution across the PV-TEG modules,which negatively affect the output characteristics of the system,thus presenting a significant challenge to maintaining their optimal performance.To address these challenges,a novel fitness-distance-balance-based beluga whale optimization(FDBBWO)strategy has been devised for maximizing the power output of the PV-TEG hybrid system under dynamic operation scenar-ios.A broader spectrum of complex and authentic operational contexts has been considered in case studies to examine the effectiveness and feasibility of FDBBWO.For this,real-world datasets collected from different seasons in Hong Kong have been used to validate the practical viability of the proposed strategy.Simulation results reveal that the FDBBWO based maximum power point tracking technique outperforms its competing methods by achieving the highest energy output,with a remarkable increase of up to 134.25%with minimal power fluctuations.For instance,the energy obtained by FDBBWO is 47.45%and 58.34%higher than BWO and perturb and observe methods,respectively,in the winter season.展开更多
In this paper,Isogeometric analysis(IGA)is effectively integrated with machine learning(ML)to investigate the bearing capacity of strip footings in layered soil profiles,with a focus on a sand-over-clay configuration....In this paper,Isogeometric analysis(IGA)is effectively integrated with machine learning(ML)to investigate the bearing capacity of strip footings in layered soil profiles,with a focus on a sand-over-clay configuration.The study begins with the generation of a comprehensive dataset of 10,000 samples from IGA upper bound(UB)limit analyses,facilitating an in-depth examination of various material and geometric conditions.A hybrid deep neural network,specifically the Whale Optimization Algorithm-Deep Neural Network(WOA-DNN),is then employed to utilize these 10,000 outputs for precise bearing capacity predictions.Notably,the WOA-DNN model outperforms conventional ML techniques,offering a robust and accurate prediction tool.This innovative approach explores a broad range of design parameters,including sand layer depth,load-to-soil unit weight ratio,internal friction angle,cohesion,and footing roughness.A detailed analysis of the dataset reveals the significant influence of these parameters on bearing capacity,providing valuable insights for practical foundation design.This research demonstrates the usefulness of data-driven techniques in optimizing the design of shallow foundations within layered soil profiles,marking a significant stride in geotechnical engineering advancements.展开更多
The uncertain nature of mapping user tasks to Virtual Machines(VMs) causes system failure or execution delay in Cloud Computing.To maximize cloud resource throughput and decrease user response time,load balancing is n...The uncertain nature of mapping user tasks to Virtual Machines(VMs) causes system failure or execution delay in Cloud Computing.To maximize cloud resource throughput and decrease user response time,load balancing is needed.Possible load balancing is needed to overcome user task execution delay and system failure.Most swarm intelligent dynamic load balancing solutions that used hybrid metaheuristic algorithms failed to balance exploitation and exploration.Most load balancing methods were insufficient to handle the growing uncertainty in job distribution to VMs.Thus,the Hybrid Spotted Hyena and Whale Optimization Algorithm-based Dynamic Load Balancing Mechanism(HSHWOA) partitions traffic among numerous VMs or servers to guarantee user chores are completed quickly.This load balancing approach improved performance by considering average network latency,dependability,and throughput.This hybridization of SHOA and WOA aims to improve the trade-off between exploration and exploitation,assign jobs to VMs with more solution diversity,and prevent the solution from reaching a local optimality.Pysim-based experimental verification and testing for the proposed HSHWOA showed a 12.38% improvement in minimized makespan,16.21% increase in mean throughput,and 14.84% increase in network stability compared to baseline load balancing strategies like Fractional Improved Whale Social Optimization Based VM Migration Strategy FIWSOA,HDWOA,and Binary Bird Swap.展开更多
The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACT...The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACTS)devices which include Thyristor-Controlled Series Compensator(TCSC),Thyristor-Controlled Phase Shifter(TCPS),and Static Var Compensator(SVC).SWEWOA expands Whale Optimization Algorithm(WOA)through the integration of sine and wormhole energy features thus improving exploration and exploitation capabilities for efficient convergence in complex non-linear OPF problems.A performance evaluation of SWEWOA takes place on the IEEE-30 bus test system through static and dynamic loading scenarios where it demonstrates better results than five contemporary algorithms:Adaptive Chaotic WOA(ACWOA),WOA,Chaotic WOA(CWOA),Sine Cosine Algorithm Differential Evolution(SCADE),and Hybrid Grey Wolf Optimization(HGWO).The research shows that SWEWOA delivers superior generation cost reduction than other algorithms by reaching a minimum of 0.9%better performance.SWEWOA demonstrates superior power loss performance by achieving(P_(loss,min))at the lowest level compared to all other tested algorithms which leads to better system energy efficiency.The dynamic loading performance of SWEWOA leads to a 4.38%reduction in gross costs which proves its capability to handle different operating conditions.The algorithm achieves top performance in Friedman Rank Test(FRT)assessments through multiple performance metrics which verifies its consistent reliability and strong stability during changing power demands.The repeated simulations show that SWEWOA generates mean costs(C_(gen,min))and mean power loss values(P_(loss,min))with small deviations which indicate its capability to maintain cost-effective solutions in each simulation run.SWEWOA demonstrates great potential as an advanced optimization solution for power system operations through the results presented in this study.展开更多
Reliable Cluster Head(CH)selectionbased routing protocols are necessary for increasing the packet transmission efficiency with optimal path discovery that never introduces degradation over the transmission reliability...Reliable Cluster Head(CH)selectionbased routing protocols are necessary for increasing the packet transmission efficiency with optimal path discovery that never introduces degradation over the transmission reliability.In this paper,Hybrid Golden Jackal,and Improved Whale Optimization Algorithm(HGJIWOA)is proposed as an effective and optimal routing protocol that guarantees efficient routing of data packets in the established between the CHs and the movable sink.This HGJIWOA included the phases of Dynamic Lens-Imaging Learning Strategy and Novel Update Rules for determining the reliable route essential for data packets broadcasting attained through fitness measure estimation-based CH selection.The process of CH selection achieved using Golden Jackal Optimization Algorithm(GJOA)completely depends on the factors of maintainability,consistency,trust,delay,and energy.The adopted GJOA algorithm play a dominant role in determining the optimal path of routing depending on the parameter of reduced delay and minimal distance.It further utilized Improved Whale Optimisation Algorithm(IWOA)for forwarding the data from chosen CHs to the BS via optimized route depending on the parameters of energy and distance.It also included a reliable route maintenance process that aids in deciding the selected route through which data need to be transmitted or re-routed.The simulation outcomes of the proposed HGJIWOA mechanism with different sensor nodes confirmed an improved mean throughput of 18.21%,sustained residual energy of 19.64%with minimized end-to-end delay of 21.82%,better than the competitive CH selection approaches.展开更多
Recognizing discontinuities within rock masses is a critical aspect of rock engineering.The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected ...Recognizing discontinuities within rock masses is a critical aspect of rock engineering.The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected from rock outcrops.In response,we propose a workflow that balances accuracy and efficiency to extract discontinuities from massive point clouds.The proposed method employs voxel filtering to downsample point clouds,constructs a point cloud topology using K-d trees,utilizes principal component analysis to calculate the point cloud normals,and employs the pointwise clustering(PWC)algorithm to extract discontinuities from rock outcrop point clouds.This method provides information on the location and orientation(dip direction and dip angle)of the discontinuities,and the modified whale optimization algorithm(MWOA)is utilized to identify major discontinuity sets and their average orientations.Performance evaluations based on three real cases demonstrate that the proposed method significantly reduces computational time costs without sacrificing accuracy.In particular,the method yields more reasonable extraction results for discontinuities with certain undulations.The presented approach offers a novel tool for efficiently extracting discontinuities from large-scale point clouds.展开更多
国际捕鲸委员会成立于第二次世界大战之后,最初的宗旨是有效利用鲸鱼资源。但是随着鲸鱼种类的濒临灭绝,1986年,该委员会做出决议,禁止对这一海洋哺乳动物进行商业性捕猎。随着执行保护措施后鲸鱼数量的增加,捕杀与保护之间的矛盾有所...国际捕鲸委员会成立于第二次世界大战之后,最初的宗旨是有效利用鲸鱼资源。但是随着鲸鱼种类的濒临灭绝,1986年,该委员会做出决议,禁止对这一海洋哺乳动物进行商业性捕猎。随着执行保护措施后鲸鱼数量的增加,捕杀与保护之间的矛盾有所激化。能否在商业利益和动物保护两者中间找到一个平衡点呢?To kill,or not to kill,that is a question.展开更多
文摘This paper, for the goal of revealing the mechanism of compromise and change in coordination, will focus on US-Japan conflict over commercial whaling. The regime like the international whaling regulation, where countries agree in general but disagree on coordination methods, is known as the Battle of the Sexes in game theory. It has been believed that in regimes presented as the Battle of the Sexes （BoS） situation, once the countries could somehow coordinate their interests and reach an agreement on the specific method of coordination, neither country would have the incentive to withdraw from that agreement. This case study, however, shows that this belief is not always true. From the analysis of this study, it will be concluded that coordination methods change over time even in regimes where the countries agree in general and disagree on coordination methods. In this case, ＂power,＂ ＂institution＂ and ＂consensus＂ are pointed out as incentives to make the two countries accept a specific coordination method.
文摘This paper is to present a framework to analyse international relations regarding protection and exploitation of an endangered species. The question of how to balance conservation and consumption in order to maintain the sustainability of resources and nature is not only the central challenge of conservation ecology, but also an international political and economic issue that frequently leads to confrontation between countries. In relation to whales, for example, Japan has long been subjected to criticism by anti-whaling countries such as the United States and Australia, and has faced off against them on the international stage. And, more recently, similar confrontations have begun to appear in relation to tuna and eel. It has been highlighted in recent years that Pacific Bluefin Tuna are becoming endangered, and there is considerable national and international concern with regard to their resource management. This paper first obtains an implication about the course of events that led to the fishing ban. The implication is applied to the case of Pacific Bluefin Tuna. Pacific Bluefin Tuna and the whaling issue reveals points of commonality. The conclusion is that history of the whaling issue implies that Japan will lose the support not only of countries opposed to fishing but also of neutral countries, if Tokyo continues to adopt policies which make light of resource conservation. Even a total ban on the fishing of Pacific Bluefin Tuna may result. This implication from the whaling issue is potentially helpful to predict the development of international relations and conservation regarding other endangered species.
文摘The Whaling in the Antarctic Case (Australia v. Japan: New Zealand intervening) decided by the International Court of Justice (hereinafter "ICJ" or "the Court") on 31 March 2014 dealt with the interpretation of specific provisions of the 1946 International Convention for the Regulation of Whaling (ICRW), in particular Article VIII.1, and its complementary instruments, i.e., the Schedule and the Annexes of the International Whaling Commission Scientific Committee. The decision of the Court was a remarkable good one. However, its rigorous reasoning focused almost exclusively on the required purpose of "scientific research" of the JARPA II Programme1 permits as set out in the ICRW, approaching the convention as an autonomous self-contained regime which leaves aside other additional grounds. Nonetheless, it would be beneficial for further jurisdictional developments to strengthen the scope of the ICWR system with the applicable provisions of the United Nations Convention on the Law of the Sea (UNCLOS) and other treaties and institutions impinging on whales and whaling, e.g., CITES, Bonn Convention, Antarctic Treaty System, among others. The query remains concerning the unexplored sources of international law ruling Antarctic spaces and species which are absent in the judgment of the Court but may allow an evolutive interpretation of the ICRW.
文摘This paper explores the archaeology of whaling in Arctic prehistory,focusing on the emergence and development of whaling as a central component of cultural ecology among prehistoric Inuit and related societies.Drawing on archaeological evidence from key sites across Alaska,the Chukchi Peninsula,and the Bering Strait region,the study examines how whaling technologies and practices evolved alongside climatic fluctuations,ecological shifts,and social transformations.Integrating ethnographic insights and paleoclimatic data,the study argues that Inuit engagement with whales was not only a subsistence strategy but a long-term,historically contingent relationship that shaped and was shaped by broader cultural systems.
文摘Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devices have made power load data increasingly complex and volatile.This places higher demands on the prediction and analysis of power loads.In order to improve the prediction accuracy of short-term power load,a CNN-BiLSTMTPA short-term power prediction model based on the Improved Whale Optimization Algorithm(IWOA)with mixed strategies was proposed.Firstly,the model combined the Convolutional Neural Network(CNN)with the Bidirectional Long Short-Term Memory Network(BiLSTM)to fully extract the spatio-temporal characteristics of the load data itself.Then,the Temporal Pattern Attention(TPA)mechanism was introduced into the CNN-BiLSTM model to automatically assign corresponding weights to the hidden states of the BiLSTM.This allowed the model to differentiate the importance of load sequences at different time intervals.At the same time,in order to solve the problem of the difficulties of selecting the parameters of the temporal model,and the poor global search ability of the whale algorithm,which is easy to fall into the local optimization,the whale algorithm(IWOA)was optimized by using the hybrid strategy of Tent chaos mapping and Levy flight strategy,so as to better search the parameters of the model.In this experiment,the real load data of a region in Zhejiang was taken as an example to analyze,and the prediction accuracy(R2)of the proposed method reached 98.83%.Compared with the prediction models such as BP,WOA-CNN-BiLSTM,SSA-CNN-BiLSTM,CNN-BiGRU-Attention,etc.,the experimental results showed that the model proposed in this study has a higher prediction accuracy.
文摘Find It What do boat captai ns try to do?W hale and dolphin watching is a popular thing to do off the coast of Hualien.*It is an amazing adventure!Imagine this:You are on a boat.Then a big whale jumps out of the water.
文摘1 Move over Simone Biles,because grey whales might just be the next Olympic champions.This conclusion can be drawn from a new study that filmed these amazing animals doing underwater headstands(头倒立)and other moves.2 As part of a seven-year project,scientists used drones(无人驾驶飞机)to observe a group of 200 grey whales off the coasts of Oregon,Washington,northern California and southern Canada.The new study findings,published in Animal Behaviour,revealed that grey whales do headstands by pressing their mouths against the ocean floor while searching for something to eat.Scientists also noticed that when doing headstands,grey whales move like human synchronized swimmers.
文摘Cetaceans include the largest animals ever to have lived onearth and are uniparous(producing a single calf at each birth)across the infraorder.However,instances of multiple fetuseshave been observed naturally among uniparous mammals,including cetaceans.Despite this,there is no known documented case of twins in cetaceans successfully carried to termin the wild(Perrin and Donovan 1984),and if such casesexist,they would be diffcult to detect.
文摘Neurodegeneration involves a wide range of neuropathological alterations affecting the integrity,physiology,and architecture of neural cells.Many studies have demonstrated neurodegeneration in different animals.In the case of Alzheimer's disease(AD),spontaneous animal models should display two neurohistopathological hallmarks:the deposition ofβ-amyloid and the arrangement of neurofibrillary tangles.However,no natural animal models that fulfill these conditions have been reported and most research into AD has been performed using transgenic rodents.Recent studies have also demonstrated that toothed whales-homeothermic,long-lived,top predatory marine mammals-show neuropathological signs of AD-like pathology.The neuropathological hallmarks in these cetaceans could help to better understand their endangered health as well as neurodegenerative diseases in humans.This systematic review analyzes all the literature published to date on this trending topic and the proposed causes for neurodegeneration in these iconic marine mammals are approached in the context of One Health/Planetary Health and translational medicine.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.72101046 and 61672128)。
文摘Recent studies employing deep learning to solve the traveling salesman problem(TSP)have mainly focused on learning construction heuristics.Such methods can improve TSP solutions,but still depend on additional programs.However,methods that focus on learning improvement heuristics to iteratively refine solutions remain insufficient.Traditional improvement heuristics are guided by a manually designed search strategy and may only achieve limited improvements.This paper proposes a novel framework for learning improvement heuristics,which automatically discovers better improvement policies for heuristics to iteratively solve the TSP.Our framework first designs a new architecture based on a transformer model to make the policy network parameterized,which introduces an action-dropout layer to prevent action selection from overfitting.It then proposes a deep reinforcement learning approach integrating a simulated annealing mechanism(named RL-SA)to learn the pairwise selected policy,aiming to improve the 2-opt algorithm's performance.The RL-SA leverages the whale optimization algorithm to generate initial solutions for better sampling efficiency and uses the Gaussian perturbation strategy to tackle the sparse reward problem of reinforcement learning.The experiment results show that the proposed approach is significantly superior to the state-of-the-art learning-based methods,and further reduces the gap between learning-based methods and highly optimized solvers in the benchmark datasets.Moreover,our pre-trained model M can be applied to guide the SA algorithm(named M-SA(ours)),which performs better than existing deep models in small-,medium-,and large-scale TSPLIB datasets.Additionally,the M-SA(ours)achieves excellent generalization performance in a real-world dataset on global liner shipping routes,with the optimization percentages in distance reduction ranging from3.52%to 17.99%.
基金supported by Victoria University of Wellington 2024 PhD Faculty Grant HSSE(Grant No.:FG-HSSE-12486).
文摘The Māori people are indigenous to Aotearoa New Zealand,and their language and culture are considered vital components of the nation’s cultural heritage.However,Te Reo Māori is regarded as a lowresource language outside of New Zealand,and its literary works usually rely on English as a pivot language for translation and communication.Therefore,in the process of promoting Māori literature as part of world literature by translating it into non-English languages,the accurate translation of cultural keywords is crucial to prevent dilemmas such as information loss and cultural misappropriation.In this article,we aim to explore effective translation strategies to enhance the international visibility and readership of Māori literature by analysing the rendition of Māori cultural keywords in the Chinese translation of“The Whale Rider”.
基金supported by the Changzhou Science and Technology Support Project(CE20235045)Open Subject of Jiangsu Province Key Laboratory of Power Transmission and Distribution(2021JSSPD12)+1 种基金Talent Projects of Jiangsu University of Technology(KYY20018)Postgraduate Research&Practice Innovation Program of Jiangsu Province(SJCX23_1633).
文摘Energy storage power plants are critical in balancing power supply and demand.However,the scheduling of these plants faces significant challenges,including high network transmission costs and inefficient inter-device energy utilization.To tackle these challenges,this study proposes an optimal scheduling model for energy storage power plants based on edge computing and the improved whale optimization algorithm(IWOA).The proposed model designs an edge computing framework,transferring a large share of data processing and storage tasks to the network edge.This architecture effectively reduces transmission costs by minimizing data travel time.In addition,the model considers demand response strategies and builds an objective function based on the minimization of the sum of electricity purchase cost and operation cost.The IWOA enhances the optimization process by utilizing adaptive weight adjustments and an optimal neighborhood perturbation strategy,preventing the algorithm from converging to suboptimal solutions.Experimental results demonstrate that the proposed scheduling model maximizes the flexibility of the energy storage plant,facilitating efficient charging and discharging.It successfully achieves peak shaving and valley filling for both electrical and heat loads,promoting the effective utilization of renewable energy sources.The edge-computing framework significantly reduces transmission delays between energy devices.Furthermore,IWOA outperforms traditional algorithms in optimizing the objective function.
基金supported by National Natural Science Foundation of China(62263014)Yunnan Provincial Basic Research Project(202401AT070344,202301AT070443).
文摘This study integrates the individual photovoltaic(PV)and thermoelectric generator(TEG)systems into a PV-TEG hybrid system to improve its overall power output by reutilizing the waste heat generated during PV power production to enhance its operational relia-bility.However,stochastic environmental conditions often result in partial shading conditions and nonuniform thermal distribution across the PV-TEG modules,which negatively affect the output characteristics of the system,thus presenting a significant challenge to maintaining their optimal performance.To address these challenges,a novel fitness-distance-balance-based beluga whale optimization(FDBBWO)strategy has been devised for maximizing the power output of the PV-TEG hybrid system under dynamic operation scenar-ios.A broader spectrum of complex and authentic operational contexts has been considered in case studies to examine the effectiveness and feasibility of FDBBWO.For this,real-world datasets collected from different seasons in Hong Kong have been used to validate the practical viability of the proposed strategy.Simulation results reveal that the FDBBWO based maximum power point tracking technique outperforms its competing methods by achieving the highest energy output,with a remarkable increase of up to 134.25%with minimal power fluctuations.For instance,the energy obtained by FDBBWO is 47.45%and 58.34%higher than BWO and perturb and observe methods,respectively,in the winter season.
文摘In this paper,Isogeometric analysis(IGA)is effectively integrated with machine learning(ML)to investigate the bearing capacity of strip footings in layered soil profiles,with a focus on a sand-over-clay configuration.The study begins with the generation of a comprehensive dataset of 10,000 samples from IGA upper bound(UB)limit analyses,facilitating an in-depth examination of various material and geometric conditions.A hybrid deep neural network,specifically the Whale Optimization Algorithm-Deep Neural Network(WOA-DNN),is then employed to utilize these 10,000 outputs for precise bearing capacity predictions.Notably,the WOA-DNN model outperforms conventional ML techniques,offering a robust and accurate prediction tool.This innovative approach explores a broad range of design parameters,including sand layer depth,load-to-soil unit weight ratio,internal friction angle,cohesion,and footing roughness.A detailed analysis of the dataset reveals the significant influence of these parameters on bearing capacity,providing valuable insights for practical foundation design.This research demonstrates the usefulness of data-driven techniques in optimizing the design of shallow foundations within layered soil profiles,marking a significant stride in geotechnical engineering advancements.
文摘The uncertain nature of mapping user tasks to Virtual Machines(VMs) causes system failure or execution delay in Cloud Computing.To maximize cloud resource throughput and decrease user response time,load balancing is needed.Possible load balancing is needed to overcome user task execution delay and system failure.Most swarm intelligent dynamic load balancing solutions that used hybrid metaheuristic algorithms failed to balance exploitation and exploration.Most load balancing methods were insufficient to handle the growing uncertainty in job distribution to VMs.Thus,the Hybrid Spotted Hyena and Whale Optimization Algorithm-based Dynamic Load Balancing Mechanism(HSHWOA) partitions traffic among numerous VMs or servers to guarantee user chores are completed quickly.This load balancing approach improved performance by considering average network latency,dependability,and throughput.This hybridization of SHOA and WOA aims to improve the trade-off between exploration and exploitation,assign jobs to VMs with more solution diversity,and prevent the solution from reaching a local optimality.Pysim-based experimental verification and testing for the proposed HSHWOA showed a 12.38% improvement in minimized makespan,16.21% increase in mean throughput,and 14.84% increase in network stability compared to baseline load balancing strategies like Fractional Improved Whale Social Optimization Based VM Migration Strategy FIWSOA,HDWOA,and Binary Bird Swap.
文摘The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACTS)devices which include Thyristor-Controlled Series Compensator(TCSC),Thyristor-Controlled Phase Shifter(TCPS),and Static Var Compensator(SVC).SWEWOA expands Whale Optimization Algorithm(WOA)through the integration of sine and wormhole energy features thus improving exploration and exploitation capabilities for efficient convergence in complex non-linear OPF problems.A performance evaluation of SWEWOA takes place on the IEEE-30 bus test system through static and dynamic loading scenarios where it demonstrates better results than five contemporary algorithms:Adaptive Chaotic WOA(ACWOA),WOA,Chaotic WOA(CWOA),Sine Cosine Algorithm Differential Evolution(SCADE),and Hybrid Grey Wolf Optimization(HGWO).The research shows that SWEWOA delivers superior generation cost reduction than other algorithms by reaching a minimum of 0.9%better performance.SWEWOA demonstrates superior power loss performance by achieving(P_(loss,min))at the lowest level compared to all other tested algorithms which leads to better system energy efficiency.The dynamic loading performance of SWEWOA leads to a 4.38%reduction in gross costs which proves its capability to handle different operating conditions.The algorithm achieves top performance in Friedman Rank Test(FRT)assessments through multiple performance metrics which verifies its consistent reliability and strong stability during changing power demands.The repeated simulations show that SWEWOA generates mean costs(C_(gen,min))and mean power loss values(P_(loss,min))with small deviations which indicate its capability to maintain cost-effective solutions in each simulation run.SWEWOA demonstrates great potential as an advanced optimization solution for power system operations through the results presented in this study.
文摘Reliable Cluster Head(CH)selectionbased routing protocols are necessary for increasing the packet transmission efficiency with optimal path discovery that never introduces degradation over the transmission reliability.In this paper,Hybrid Golden Jackal,and Improved Whale Optimization Algorithm(HGJIWOA)is proposed as an effective and optimal routing protocol that guarantees efficient routing of data packets in the established between the CHs and the movable sink.This HGJIWOA included the phases of Dynamic Lens-Imaging Learning Strategy and Novel Update Rules for determining the reliable route essential for data packets broadcasting attained through fitness measure estimation-based CH selection.The process of CH selection achieved using Golden Jackal Optimization Algorithm(GJOA)completely depends on the factors of maintainability,consistency,trust,delay,and energy.The adopted GJOA algorithm play a dominant role in determining the optimal path of routing depending on the parameter of reduced delay and minimal distance.It further utilized Improved Whale Optimisation Algorithm(IWOA)for forwarding the data from chosen CHs to the BS via optimized route depending on the parameters of energy and distance.It also included a reliable route maintenance process that aids in deciding the selected route through which data need to be transmitted or re-routed.The simulation outcomes of the proposed HGJIWOA mechanism with different sensor nodes confirmed an improved mean throughput of 18.21%,sustained residual energy of 19.64%with minimized end-to-end delay of 21.82%,better than the competitive CH selection approaches.
基金supported by the National Natural Science Foundation of China(Grant No.42407232)the Sichuan Science and Technology Program(Grant No.2024NSFSC0826).
文摘Recognizing discontinuities within rock masses is a critical aspect of rock engineering.The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected from rock outcrops.In response,we propose a workflow that balances accuracy and efficiency to extract discontinuities from massive point clouds.The proposed method employs voxel filtering to downsample point clouds,constructs a point cloud topology using K-d trees,utilizes principal component analysis to calculate the point cloud normals,and employs the pointwise clustering(PWC)algorithm to extract discontinuities from rock outcrop point clouds.This method provides information on the location and orientation(dip direction and dip angle)of the discontinuities,and the modified whale optimization algorithm(MWOA)is utilized to identify major discontinuity sets and their average orientations.Performance evaluations based on three real cases demonstrate that the proposed method significantly reduces computational time costs without sacrificing accuracy.In particular,the method yields more reasonable extraction results for discontinuities with certain undulations.The presented approach offers a novel tool for efficiently extracting discontinuities from large-scale point clouds.
文摘国际捕鲸委员会成立于第二次世界大战之后,最初的宗旨是有效利用鲸鱼资源。但是随着鲸鱼种类的濒临灭绝,1986年,该委员会做出决议,禁止对这一海洋哺乳动物进行商业性捕猎。随着执行保护措施后鲸鱼数量的增加,捕杀与保护之间的矛盾有所激化。能否在商业利益和动物保护两者中间找到一个平衡点呢?To kill,or not to kill,that is a question.
