Abbreviated Report of the WHO Western Pacific Region Workshop on National Plans of Action for Nutrition: Key Elements for Success, Constraints and Future Plans

A workshop on National Plans of Action for Nutrition: Constraints, Key Elements for Success, and Future Plans was convened and organized by the WHO Regional Office for the Western Pacific in collaboration with the Institute for Medical Research Malaysia and co sponsored with FAO and UNICEF from 25—29 October 1999. It was attended by representatives of 25 countries in the region and resource persons, representatives from WHO and other international agencies. The objectives of the workshop were to review the progress of countries in developing, implementing and monitoring national plans of action for nutrition (NPANs) in the Western Pacific Region and to identify constraints and key elements of success in these efforts. Most of the countries have NPANs, either approved and implemented or awaiting official endorsement. The Plan formulation is usually multisectoral, involving several government ministries, non governmental organizations, and international agencies. Often official adoption or endorsement of the Plan comes from the head of state and cabinet or the minister of health, one to six years from the start of its formulation. The NPAN has stimulated support for the development and implementation of nutrition projects and activities, with comparatively greater involvement of and more support from government ministries, UN agencies and non-governmental agencies compared to local communities, bilateral and private sectors and research and academic institutions. Monitoring and evaluation are important components of NPANs. They are, however, not given high priority and often not built into the plan. The role of an intersectoral coordinating body is considered crucial to a country's nutrition program. Most countries have an intersectoral structure or coordinating body to ensure the proper implementation, monitoring and evaluation of their NPANs. The workshop identified the constraints and key elements of success in each of the four stages of the NPAN process: development, operationalization, implementation, and monitoring and evaluation. Constraints to the NPAN process relate to the political and socioeconomic environment, resource scarcity, control and management processes, and factors related to sustainability. The group's review of NPAN identified successful NPANs as those based on recent, adequate and good quality information on the nutritional situation of the country, and on the selection of strategies, priorities and interventions that are relevant to the country and backed up by adequate resources. Continued high level political commitment, a multisectoral approach, and adequate participation of local communities are other key elements for success. The participants agreed on future actions and support needed from various sources for the further development, implementation, monitoring and evaluation of their NPANs. The recommendations for future actions were categorized into actions pertaining to countries with working NPAN, actions for countries without working NPAN and actions relevant to all countries. There was also a set of suggested actions at the regional level, such as holding of regular regional NPAN evaluation meetings, inclusion of NPAN on the agenda of regional fora by the regional organizations, and strengthening of regional nutrition networks.

Noise Action Plans for the Acoustic Protection of Urban Areas around the Athens International Airport （A.I.A.） Strategic Noise Maps 2006 ＆ 2011

Athens International Airport ＂Eleftherios Venizelos＂ （AIA） is considered a pioneer international Public-Private Partnership, being the first major int. airport constructed with the participation of the private sector with the BOOT method （Build, Own, Operate, and Transfer）. AIA＇s 1st day of operation was in March 2001 and the aircraft traffic on 2006 reached 191.000 movements ＆ 15.1 million passengers. According to the European Directive 49/2002 and the Joint Ministerial Decision 13586/724-28/3/06, Athens International Airport （AIA） is included in the category of＂large airports＂ and it consequently comes under the authority of the above mentioned legislation on the evaluation and management of environmental noise. A complete Study on Aircraft Noise [1], according to the European Directive 49/2002 [2] and Joint Ministerial Decision 13586/724-28/3/06 was undertaken under the auspices of the Ministry of Environment, Energy ＆ Climate Change, the Hellenic Civil Aviation Authority, and AIA S.A. In this article the following results are presented： （1） The 2006 Strategic Noise Map （SNM） of both indicators Lden and Lnight based on the ECAC.CEAC Doc 29 methodology ＂Report on Standard Method of Computing Noise Contours around Civil Airports＂, 1997 [3], （2） A statistical analysis of predicted vs measured noise levels based on the existing Noise Monitoring System, （3） Effects from the removal of marginally accepted chapter 3 aircraft, （4） A complete evaluation of results regarding calculation of area/land uses and number of individuals living in residences inside blocks exposed in various levels of noise, and （5） A full evaluation of Noise Action Plans （NAP） regrouping existing and foreseen actions FOR 2006 ＆ 2011 scenarios, especially regarding among others, noise abatement procedures, a comprehensive noise insulation legal framework.

BCCLR:A Skeleton-Based Action Recognition with Graph Convolutional Network Combining Behavior Dependence and Context Clues

In recent years,skeleton-based action recognition has made great achievements in Computer Vision.A graph convolutional network(GCN)is effective for action recognition,modelling the human skeleton as a spatio-temporal graph.Most GCNs define the graph topology by physical relations of the human joints.However,this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs,resulting in a low recognition rate for specific actions with implicit correlation between joint pairs.In addition,existing methods ignore the trend correlation between adjacent frames within an action and context clues,leading to erroneous action recognition with similar poses.Therefore,this study proposes a learnable GCN based on behavior dependence,which considers implicit joint correlation by constructing a dynamic learnable graph with extraction of specific behavior dependence of joint pairs.By using the weight relationship between the joint pairs,an adaptive model is constructed.It also designs a self-attention module to obtain their inter-frame topological relationship for exploring the context of actions.Combining the shared topology and the multi-head self-attention map,the module obtains the context-based clue topology to update the dynamic graph convolution,achieving accurate recognition of different actions with similar poses.Detailed experiments on public datasets demonstrate that the proposed method achieves better results and realizes higher quality representation of actions under various evaluation protocols compared to state-of-the-art methods.

Workout Action Recognition in Video Streams Using an Attention Driven Residual DC-GRU Network

Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in videostreams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enableinstant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing actiondatasets often lack diversity and specificity for workout actions, hindering the development of accurate recognitionmodels. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significantcontribution. WAVd comprises a diverse collection of labeled workout action videos, meticulously curated toencompass various exercises performed by numerous individuals in different settings. This research proposes aninnovative framework based on the Attention driven Residual Deep Convolutional-Gated Recurrent Unit (ResDCGRU)network for workout action recognition in video streams. Unlike image-based action recognition, videoscontain spatio-temporal information, making the task more complex and challenging. While substantial progresshas been made in this area, challenges persist in detecting subtle and complex actions, handling occlusions,and managing the computational demands of deep learning approaches. The proposed ResDC-GRU Attentionmodel demonstrated exceptional classification performance with 95.81% accuracy in classifying workout actionvideos and also outperformed various state-of-the-art models. The method also yielded 81.6%, 97.2%, 95.6%, and93.2% accuracy on established benchmark datasets, namely HMDB51, Youtube Actions, UCF50, and UCF101,respectively, showcasing its superiority and robustness in action recognition. The findings suggest practicalimplications in real-world scenarios where precise video action recognition is paramount, addressing the persistingchallenges in the field. TheWAVd dataset serves as a catalyst for the development ofmore robust and effective fitnesstracking systems and ultimately promotes healthier lifestyles through improved exercise monitoring and analysis.

Pursuit of Excellence:The Past Development and New Progress of the Human Rights Action Plans of China

Since the Vienna Declaration and programme of Action in 1993 recommended that countries formulate national human rights action plans,many countries have carried out relevant explorations.Since 2009,China has formulated four series of Human Rights Action plan of China,which is significant for promoting the development of human rights,enhancing the say in international human rights,reducing social risks and protecting individual rights.The formulation of the plan adheres to the principles of being laws and policies-based and human rights-oriented,and taking into account both the country and society.The first three series of the Action plans have undergone such evolution as upgrade of guiding principles and goals,refinement of rights content and measures,diversification of responsible subjects,increasingly reasonable framework structure,and more human rights consideration in discourse expression.The fourth series of the Action plan pays more attention to expanding public participation and the content,improving the supervision mechanism,and further promoting the formulation and implementation of the Action plan.

Three Categories of International Comments on National Human Rights Action Plans and Their Implications——An Analysis Based on UPR Reports

At least 57 countries have formulated and implemented 78 national human rights action plans, and the international assessment of them has had direct influence on their international human rights images of their issuers and the focuses of future planning According to related reports from the universal periodic review by the united nations Human rights Council, three categories of comments in a rough quantitative proportion of 1:4:2 have been made by the international community on these plans, which can be categorized as: Attention, Laudatory and expectation, representing objective attention, appreciation or encouragement and anticipation of further implementation or improvement, respectively In terms of regions, Asian countries have received the most Attention Comments, europe and Africa fewer, and America the least The marked achievements in the formulation and implementation of human rights action plans in China have attracted widespread attention and recognition, and further efforts should be made to implement steady and consistent human rights policies, improve the implementation mechanisms and integrate the external and internal functions of human rights action plans so as to promote the sustainable development of China’s human rights cause.

Connection Between Policies and Laws on Human Rights Protection:Case Study of the National Human Rights Action Plans

China’s National Human Rights Action Plans connect policies and laws on human rights protection in terms of ideas,procedures,and contents.The functions of the connections are the guidance to local policymaking,the promise of state commitment,and the linkage to international human rights goals.At the practical level,the enhancement of the connection between policies and laws will promote the effectiveness of human rights protection.In order to improve the rationality of human rights policies,there should be more researches on National Human Rights Action Plans,and more public participation in the process of the Plan drafting.

Assessment of Human Rights Action Plans and Use of Its Results from a Global Perspective

Since the World Conference on Human Rights in 1993,more than a quarter of the participating countries have developed National Human Rights Action Plans(NHRAPs)to promote human rights.An assessment of the NHRAPs can help to understand the realities of the implementation,improve the quality of the follow-up plan,and improve the effectiveness of the plan in the implementation process.From the texts and practices of the NHRAPs,such an assessment includes the 'self-assessments' of the plans’ implementers,comprehensive assessments of inter-departmental committees(groups),and evaluations of policy objects,social organizations and human rights experts.The assessment methods include field research,qualitative evaluation,indicator measurement and process monitoring,among other things.The results of the assessment can promote the cohesion between the NHRAPs in different periods,promote the accumulation and transmission of the implementation experience of the plan,and promote the optimization and adjustment of related matters during the implementation period.

General Optimal Trajectory Planning:Enabling Autonomous Vehicles with the Principle of Least Action

This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and efficiently.Firstly,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road centerline.Cartesian coordinates are then transformed to achieve the curvature continuity of the generated curve.Considering the road constraints and vehicle dynamics,limited polynomial candidate trajectories are generated and smoothed in a curvilinear coordinate system.Furthermore,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers’behavior and summarizing their manipulation characteristics of“seeking benefits and avoiding losses.”Finally,by integrating the idea of receding-horizon optimization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and adaptability.Extensive simulations and experiments are performed,and the results demonstrate the framework’s feasibility and effectiveness,which avoids both dynamic and static obstacles and applies to various scenarios with multi-source interactive traffic participants.Moreover,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers’manipulation.

基于LDA主题模型的GitHub Actions工作流项目推荐算法

在CI/CD实践中,自动化已成为软件开发实践中的一种规范。GitHub引入GitHub Actions为软件维护者提供自动化的持续集成工作流方案,尽管其为开发者提供了诸多便利,GitHub社区也提供了许多第三方的GitHub Actions服务,但仍然只有极少的项目在使用。为了满足开发人员对工作流自动化的需求,减少非开发任务工作量,提出一种基于隐含狄利克雷分布(LDA)主题模型和Jensen-Shannon距离的GitHub Actions工作流项目推荐算法。通过对GitHub Actions存储库的README文件进行主题建模,将GitHub的事件描述文本和用户输入作为模型输入,为正在开发的代码仓库推荐GitHub Actions服务。将该推荐模型与标准的基于余弦相似度的方法进行比较的实验结果表明,该方法能有效改善开源软件仓库的推荐精度。

Abnormal Action Recognition with Lightweight Pose Estimation Network in Electric Power Training Scene

Electric power training is essential for ensuring the safety and reliability of the system.In this study,we introduce a novel Abnormal Action Recognition(AAR)system that utilizes a Lightweight Pose Estimation Network(LPEN)to efficiently and effectively detect abnormal fall-down and trespass incidents in electric power training scenarios.The LPEN network,comprising three stages—MobileNet,Initial Stage,and Refinement Stage—is employed to swiftly extract image features,detect human key points,and refine them for accurate analysis.Subsequently,a Pose-aware Action Analysis Module(PAAM)captures the positional coordinates of human skeletal points in each frame.Finally,an Abnormal Action Inference Module(AAIM)evaluates whether abnormal fall-down or unauthorized trespass behavior is occurring.For fall-down recognition,three criteria—falling speed,main angles of skeletal points,and the person’s bounding box—are considered.To identify unauthorized trespass,emphasis is placed on the position of the ankles.Extensive experiments validate the effectiveness and efficiency of the proposed system in ensuring the safety and reliability of electric power training.

Unveiling health rights:A call to action for sex workers'HIV care in the Philippines

We are writing in response to the article titled“Addressing the needs and rights of sex workers for HIV healthcare services in the Philippines”[1].The article calls for attention on the significant challenges faced by sex workers in the Philippines in accessing HIV healthcare.We appreciate the article’s effort to examine these issues in depth.We would like to present a constant flow of thoughts in this letter while highlighting the positive aspects,potential obstacles,and additional points that contribute to this ongoing discussion.

Collective Action How the AU plans to combat the coronavirus pandemic on the continent

How the AU plans to combat the coronavirus pandemic on the continent At the turn of the new decade months ago,the world looked forward to a new year with hope and optimism.That sentiment was soon shattered,however,as the dark cloud of the novel coronavirus pandemic swept across the globe.The coronavirus disease 2019(COVID-19)was first detected in December 2019 in Wuhan。

Impact of Action Observation Therapy along with Usual Physiotherapy Intervention of Individual with Alzheimer’s Disease

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by cognitive impairments in the initial stage, which lead to severe cognitive dysfunction in the later stage. Action observation therapy (AOT) is a multisensory cognitive rehabilitation technique where the patient initially observes the actions and then tries to perform. The study aimed to examine the impact of AOT along with usual physiotherapy interventions to reduce depression, improve cognition and balance of a patient with AD. A 67 years old patient with AD was selected for this study because the patient has been suffering from depression, dementia, and physical dysfunction along with some other health conditions like diabetes and hypertension. Before starting intervention, a baseline assessment was done through the Beck Depression Inventory (BDI) tool, the Mini-Cog Scale, and the Berg Balance Scale (BBS). The patient received 12 sessions of AOT along with usual physiotherapy interventions thrice a week for four weeks, which included 45 minutes of each session. After four weeks of intervention, the patient demonstrated significant improvement in depression, cognition, and balance, whereas the BDI score declined from moderate 21/63 to mild 15/63 level of depression. The Mini-Cog score improved from 2/5 to 4/5, and the BBS score increased from 18/56 to 37/56. It is concluded that AOT along with usual physiotherapy intervention helps to reduce depression, improve cognition and balance of people with AD.

Abnormal Action Detection Based on Parameter-Efficient Transfer Learning in Laboratory Scenarios

Laboratory safety is a critical area of broad societal concern,particularly in the detection of abnormal actions.To enhance the efficiency and accuracy of detecting such actions,this paper introduces a novel method called TubeRAPT(Tubelet Transformer based onAdapter and Prefix TrainingModule).Thismethod primarily comprises three key components:the TubeR network,an adaptive clustering attention mechanism,and a prefix training module.These components work in synergy to address the challenge of knowledge preservation in models pretrained on large datasets while maintaining training efficiency.The TubeR network serves as the backbone for spatio-temporal feature extraction,while the adaptive clustering attention mechanism refines the focus on relevant information.The prefix training module facilitates efficient fine-tuning and knowledge transfer.Experimental results demonstrate the effectiveness of TubeRAPT,achieving a 68.44%mean Average Precision(mAP)on the CLA(Crazy LabActivity)small-scale dataset,marking a significant improvement of 1.53%over the previous TubeR method.This research not only showcases the potential applications of TubeRAPT in the field of abnormal action detection but also offers innovative ideas and technical support for the future development of laboratory safety monitoring technologies.The proposed method has implications for improving safety management systems in various laboratory environments,potentially reducing accidents and enhancing overall workplace safety.

HgaNets:Fusion of Visual Data and Skeletal Heatmap for Human Gesture Action Recognition

Recognition of human gesture actions is a challenging issue due to the complex patterns in both visual andskeletal features. Existing gesture action recognition (GAR) methods typically analyze visual and skeletal data,failing to meet the demands of various scenarios. Furthermore, multi-modal approaches lack the versatility toefficiently process both uniformand disparate input patterns.Thus, in this paper, an attention-enhanced pseudo-3Dresidual model is proposed to address the GAR problem, called HgaNets. This model comprises two independentcomponents designed formodeling visual RGB (red, green and blue) images and 3Dskeletal heatmaps, respectively.More specifically, each component consists of two main parts: 1) a multi-dimensional attention module forcapturing important spatial, temporal and feature information in human gestures;2) a spatiotemporal convolutionmodule that utilizes pseudo-3D residual convolution to characterize spatiotemporal features of gestures. Then,the output weights of the two components are fused to generate the recognition results. Finally, we conductedexperiments on four datasets to assess the efficiency of the proposed model. The results show that the accuracy onfour datasets reaches 85.40%, 91.91%, 94.70%, and 95.30%, respectively, as well as the inference time is 0.54 s andthe parameters is 2.74M. These findings highlight that the proposed model outperforms other existing approachesin terms of recognition accuracy.

Adjustment mechanism of blasting dynamic-static action in the water decoupling charge

Water decoupling charge blasting excels in rock breaking,relying on its uniform pressure transmission and low energy dissipation.The water decoupling coefficients can adjust the contributions of the stress wave and quasi-static pressure.However,the quantitative relationship between the two contributions is unclear,and it is difficult to provide reasonable theoretical support for the design of water decoupling blasting.In this study,a theoretical model of blasting fracturing partitioning is established.The mechanical mechanism and determination method of the optimal decoupling coefficient are obtained.The reliability is verified through model experiments and a field test.The results show that with the increasing of decoupling coefficient,the rock breaking ability of blasting dynamic action decreases,while quasi-static action increases and then decreases.The ability of quasi-static action to wedge into cracks changes due to the spatial adjustment of the blast hole and crushed zone.The quasi-static action plays a leading role in the fracturing range,determining an optimal decoupling coefficient.The optimal water decoupling coefficient is not a fixed value,which can be obtained by the proposed theoretical model.Compared with the theoretical results,the maximum error in the model experiment results is 8.03%,and the error in the field test result is 3.04%.

Developments in the study of Chinese herbal medicine's assessment index and action mechanism for diabetes mellitus

In traditional Chinese medicine(TCM),based on various pathogenic symptoms and the‘golden chamber’medical text,Huangdi Neijing,diabetes mellitus falls under the category‘collateral disease’.TCM,with its wealth of experience,has been treating diabetes for over two millennia.Different antidiabetic Chinese herbal medicines re-duce blood sugar,with their effective ingredients exerting unique advantages.As well as a glucose lowering effect,TCM also regulates bodily functions to prevent diabetes associated complications,with reduced side effects compared to western synthetic drugs.Chinese herbal medicine is usually composed of polysaccharides,saponins,al-kaloids,flavonoids,and terpenoids.These active ingredients reduce blood sugar via various mechanism of actions that include boosting endogenous insulin secretion,enhancing insulin sensitivity and adjusting key enzyme activity and scavenging free radicals.These actions regulate glycolipid metabolism in the body,eventually achiev-ing the goal of normalizing blood glucose.Using different animal models,a number of molecular markers are available for the detection of diabetes induction and the molecular pathology of the disease is becoming clearer.Nonetheless,there is a dearth of scientific data about the pharmacology,dose-effect relationship,and structure-activity relationship of TCM and its constituents.Further research into the efficacy,toxicity and mode of action of TCM,using different metabolic and molecular markers,is key to developing novel TCM antidiabetic formulations.

Experimental study on the movement of oil spill under freeze-thaw action

Oil leakages cause environmental pollution,economic losses,and even engineering safety accidents.In cold regions,researchers urgently investigate the movement of oil spill in soils exposed to freeze-thaw cycles.In this study,a series of laboratory model experiments were carried out on the migration of oil leakage under freeze-thaw action,and the distributions of the soil temperature,unfrozen water content,and displacement were analyzed.The results showed that under freeze-thaw action,liquid water in soils migrated to the freezing front and accumulated.After the pipe cracked,oil pollutants first gathered at one side of the leak hole,and then moved around.The pipe wall temperature affected the soil temperature field,and the thermal influence range below and transverse the pipe wall(35–40 cm)was larger than that above the pipe wall(8 cm)owing to the soil surface temperature.The leaked oil's temperature would make the temperature of the surrounding soil rise.Oil would inhibit the cooling of the soils.Besides,oil migration was significantly affected by the gravity and water flow patterns.The freeze-thaw action would affect the migration of the oil,which was mainly manifested as inhibiting the diffusion and movement of oil when soils were frozen.Unfrozen water transport caused by freeze-thaw cycles would also inhibit oil migration.The research results would provide a scientific reference for understanding the relationship between the movement of oil pollutants,water,and soil temperature,and for establishing a waterheat-mass transport model in frozen soils.

Research Progress on Purification Process, Content Determination and Pharmacological Action of Atractylodin

Atractylodis Rhizoma comes from the dry rhizome of Atractylis lancea or Atractylodes chinensis in the Compositae family,and it is suitable for preventing and treating diseases such as cold,edema,night blindness and rheumatic arthralgia.Atractylodin is the main active component extracted and isolated from Atractylodis Rhizoma.A large number of studies have found that atractylodin has excellent drug activity in improving gastrointestinal emptying,anti-inflammation,inhibiting malignant tumor and reducing blood lipid.In this paper,the purification process and pharmacological activity of Atractylodin were summarized to provide a theoretical basis for basic research,clinical application and further development and utilization of atractylodin.