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Key messages The last decade has seen significant and marked improvements in the legal framework on mangrove protection, increased funding and involvement of non-state actors in mangrove protection and development, lower rates of mangrove forest loss and larger areas of planted mangroves in Vietnam. Despite these remarkable achievements, challenges remain for mangrove conservation, particularly when major drivers of mangrove deforestation and degradation have yet to be properly addressed as they are closely linked to national economic development priorities. Weak law enforcement, overreliance on inadequate central budget financing for mangrove protection, and inequitable distribution of benefits and rights relating to mangrove resources further challenge effective, efficient and equitable mangrove management. The government still affords more attention to planting new mangroves than providing strong incentives for conserving existing mangrove forests. Future mangrove protection and development in Vietnam requires stronger political will from the government to find a balance between economic development and mangrove conservation priorities, as well as participatory decision-making processes where the private sector and local communities are provided with better incentives to engage in mangrove protection.

Key messagesDespite being a new funding source, PFES now contributes 22% of total forestry sector investment.The impact of PFES funding differs by location and actor group.To enhance the scale of PFES, and its impacts as a key funding source, the sector must sustain and maximize the potential of existing revenue, carry out strategic investment and use of PFES revenue, and expand to include new potential PFES sources.

Key messagesDespite the great potential REDD+ shows for generating and contributing finance to support forestry in Vietnam, a reduction in both funds and funder commitment to REDD+, challenges in meeting funder requirements, and the significant finance required to implement the national REDD+ program in Vietnam, all imply that in reality REDD+’s contribution as a major financial source for the forestry sector is limited.Although the government has identified various public and private funding sources to cover the different phases of REDD+, the international public sector remains the primary funding source; limited contributions come from the private sector and state.To date the spending of REDD+ finance has been uncoordinated and fragmented, due to a lack of clarity on what Vietnam’s REDD+ priorities are.Effective and efficient implementation of REDD+ activities in Vietnam is being impeded by: limited and inaccurate data regarding REDD+ finance in Vietnam; an unclear definition of what REDD+ finance is; the absence of a national REDD+ financial tracking system; and limited technical capacity (within both government and civil society organizations) when it comes to monitoring REDD+ finance.To increase the potential for REDD+ to financially contribute to forestry in Vietnam, the following is required: better coordination across sectors and amongst donors and government agencies; enhanced capacity building on the tracking and management of REDD+ finance; development and effective implementation of REDD+ policies and measures, so that the government can access result-based payments from different international funding sources.

This CIFOR Occasional Paper assessed opportunities and challenges in mobilizing finance to implement the Vietnam Forestry Development Strategy (VFDS) for 2006-2020. After 10 years of VFDS implementation, the forestry sector has witnessed many achievements contributing to the development of the country. However, financial mobilization for implementation of the VFDS has always been limited.Investment into forest protection and development, especially for special use forests and protected forests, has to date been minimal, with state allocations insufficient to meet requirements. The potential contribution of the forestry sector in increasing national GDP has not been fully recognized by policymakers and therefore has not yet been maximized. In addition, no data have yet been collected and analyzed on forestry finance and nor have the opportunities and challenges for mobilizing financial resources for the forestry sector in Vietnam. This research was thus conducted to assess the current situation, analyzing both the opportunities and challenges of financial mobilization, both for implementation of the strategy as well as for forestry sector investment.Funding for VFDS already stems from ODA, FDI and the private sector. Payment for Forest Environmental Services (PFES) is a new financial incentive mechanism that provides incentives for forest users to better protect and develop forests, where investments from communities, individuals and enterprises are the main contributors responsible for increases in the budget from non-state sources.A transparent and accountable forestry finance system will help policymakers by improving financial planning for the forestry sector, as well as targeting financial resources for greater returns. Finding new sources of finance to complement existing ones is essential. The forestry sector also needs to continue to improve its legal mechanisms and policies and create a favorable legal environment to mobilize the maximum possible financial resources for forest protection and development.

A dosimetric complex is proposed for use in long-term manned space flight on the orbital station and for the planned Mars expedition. This complex includes thermoluminescence dosimeters with on-board readout, a channel for continuous monitoring of dose rate and a channel for continuous measurement of absorbed and equivalent doses, as well as measurement of the LET spectra. The last four parameters are measured by a tissue-equivalent proportional counter.

The key concern of our research is to investigate concepts ensuring an integration of information and processes available at the layers 1 up to 3 of the protocol stack to realize an overall optimization of both resource usage efficiency and performance in self-configurable and self-healing wireless networks (cellular and ad hoc). The essence of the research avenue lies in the fact that, from an information theoretical point of view, information available at different layers of the protocol stack contains per se a certain degree of redundancy that can be used for cross layer optimization. For example, processes of the physical and MAC layers like directional channel estimation, synchronization, bit error rate and signal strength can be used to obtain a quite good estimation of the range (distance) between senders and receivers. On the other hand, position and topology information, for example, can be used to optimize a series of processes at the other layers, for example, channel estimation & adaptive modulation, power control, and mobility management (including movement detection, dynamic guard channel schemes, handoff and load balancing).

In order to perform a wide range of locomotive tasks, a legged robot should be able to autonomously adjust its stride and properly move its legs so as to fit the current locomotion requirement. We develop an adaptive intelligent system that controls the movement of a jointed leg during a running stride. This paper focuses on the ballistic controller, which controls the movement of the leg from the point of takeoff from the ground to the point of landing. The controller learns from experience to move the leg along a specified series of configurations which provide a smooth transition from takeoff to landing. Learning is online, so the controller adapts to the requirements of the stride on the fly. It can handle strides of different sizes and can scale obstacles. Very accurate control is achieved even during the first learning attempt.

Kgroo, a simulated 3-link folding legged uniped robot is presented and locomotion training of Kgroo with fuzzy-neural control is discussed. It is observed that for the uniped locomotion problem, global training of a fuzzy or neural controller is subject to failure. It is shown that, starting with a single jump example, a multiagent cerebellum model (MAC-J) can enable Kgroo to learn different jumps with a geometrical learning rate based on a learning-tuning-brainstorming theory. Technically, this work introduces effective means for decomposing the high-dimensional locomotion control problem into kernel spaces; theoretically, incremental learning and coordinated cerebellar agent discovery provide a natural explanation to certain explosive learning behaviors in human and animal locomotion control.

Locomotion training of legged machines is a difficult and challenging problem in robotics and artificial intelligence. The work focuses on controlling the running stride of a three link leg. The objective is to control the height, distance and angular momentum of the stride, all of which are determined at takeoff from the ground. We use a CMAC neural network (J.S. Albus, 1975) to control the leg during takeoff. The CMAC network uses local learning and also permits incremental learning. This enables the net to be retrained online to produce the correct signals for locally changed conditions. The CMAC controller trains quickly and generalizes well.