Impacts of Policy Measures on the Development of State-Owned Forests in Northeastern China: Theoretical Results and Empirical Evidence

State-owned forest enterprises (SOFEs) in northeast China and Inner Mongolia play important roles both in timber production and in the maintenance of ecological security. However, since the late 1970s, forest resource and economic crises have seriously restricted these functions. Based on a theoretical and an empirical analysis of the harvest and investment behavior of the SOFEs, we examined the effects of forest policies and the socioeconomic conditions on the behavioral choices of the SOFEs. Both the extent to which SOFE supervising authorities emphasized improvement of forest resources in their annual evaluations and the increases in expenses necessary to manage SOFEs had significant impacts on harvest and investment decisions as well as development of forest resources. Promoting the management and utilization of non-timber resources, as well as reforms to increase the efficiency of forest protection and management, have reduced timber harvests as intended, which in turn has increased investment and improved forest resources. The effects have been relatively small, however. In contrast, reforms aimed at timber harvest and afforestation activities actually contributed to increasing the timber harvest, which affected the development of the forest resources negatively.state-owned forest enterprise, “double crises,” sustainable forest management, forest policy

The strategies preventing particle transportation into the inlets of nuclear power plants: Mechanisms of physical oceanography

The formation of aquatic organism aggregations near the inlets of nuclear power plants (NPPs) has become an important global concern, as the aggregated organisms can block the cooling systems of NPPs, and, therefore, threaten their operational safety. In this study we focus on the trajectory of aquatic organisms, that is., how these organisms can be transported to the inlets of NPPs by physical ocean processes related to currents and waves. The Changjiang NPP, located on the west side of Hainan Island in China, is occasionally subject to serious gulfweed blocking events in spring. To study the physical mechanism, with the use of a three-dimensional numerical current–wave-coupled model, the current and wave conditions near the NPP were simulated. Based on the model, several particle-tracking simulations were run to evaluate the extent of the blocking that occurred in the inlet of the NPP’s cooling system with different forcings introduced. The results showed that the windage effect and the surface Stokes drift induced by waves were the main causes of blocking events in the Changjiang NPP, with the former transporting surface particles from upstream and the latter transporting surrounding particles onshore, into the NPP’s inlet. Further simulations revealed that bending of the inlet and changing the offshore mouth to downstream mouth could limit the blocking greatly, as particles were seldom transported into the mouth by cross-shore transport processes such as the Stokes drift. We suggest that such findings may provide a valuable reference for the development of strategies to prevent aquatic organism aggregation events in other NPPs

Self-Normalized Importance Sampling for Neural Language Modeling

To mitigate the problem of having to traverse over the full vocabulary in the softmax normalization of a neural language model, sampling-based training criteria are proposed and investigated in the context of large vocabulary word-based neural language models. These training criteria typically enjoy the benefit of faster training and testing, at a cost of slightly degraded performance in terms of perplexity and almost no visible drop in word error rate. While noise contrastive estimation is one of the most popular choices, recently we show that other sampling-based criteria can also perform well, as long as an extra correction step is done, where the intended class posterior probability is recovered from the raw model outputs. In this work, we propose self-normalized importance sampling. Compared to our previous work, the criteria considered in this work are self-normalized and there is no need to further conduct a correction step. Through self-normalized language model training as well as lattice rescoring experiments, we show that our proposed self-normalized importance sampling is competitive in both research-oriented and production-oriented automatic speech recognition tasks.Comment: Accepted at INTERSPEECH 202

Degradable composite aerogel with excellent water-absorption for trace water removal in oil and oil-in-water emulsion filtration

In this study, using chitosan (CS) and carboxymethyl cellulose (CMC) as backbone and introducing citric acid (CA)to enhance the electrostatic interaction of the system, citric acid/chitosan/carboxymethyl cellulose (CA/CS/CMC) aerogel is obtained by simple freeze-drying. CA/CS/CMC composite aerogel exhibits light weight, low density, high porosity, outstanding hydrophilic and water retention properties, and satisfactory underwater oleophobicity. The water adsorption capacity of the obtained aerogels can reach 43.87–80.28 g/g, which are far more than that of carboxymethyl cellulose and chitosan aerogels (14.27–20.08 g/g). In addition, with strong hydrophilicity, underwater oleophobicity and water retention endowed by the rough internal microstructure and the rich hydroxyl, amino, and carboxyl groups, the fabricated aerogel can also be used as a filter to achieve effective separation of oil-in-water emulsions and oil/water mixtures. The separation efficiency of aerogel for oil/water mixtures are higher than 90.7%. Because the developed preparation method is green, simple and mild and the raw materials are readily available and environmentally friendly, the obtained CA/CS/CMC aerogel with strong water absorption capacity and good separation efficiency displays a promising application in water-oil separation

Changes in bacterial community of soil induced by long-term straw returning

Straw returning is an effective way to improve soil quality. Whether the bacterial community development has been changed by long-term straw returning in non-calcareous soil is not clear. In this study, the following five treatments were administered: soil without fertilizer (CK); wheat and corn straw returning (WC); wheat straw returning with 276 kg N ha−1 yr−1 (WN); manure, 60,000 kg ha−1 pig manure compost (M) and wheat and corn straw returning with 276 kg N ha−1 yr−1 (WCN). The high-throughput 16S rRNA sequencing technology was used to evaluate the bacterial communities. The results showed that the community was composed mostly of two dominant groups (Proteobacteria and Acidobacteria). Bacterial diversity increased after the application of straw and manure. Principal component analyses revealed that the soil bacterial community differed significantly between treatments. The WCN treatment showed relatively higher total soil N, available P, available K, and organic carbon and invertase, urease, cellulase activities and yield than the WC treatment. Our results suggested that application of N fertilizer to straw returning soil had significantly higher soil fertility and enzyme activity than straw returning alone, which resulted in a different bacterial community composition, Stenotrophomonas, Pseudoxanthomonas, and Acinetobacter which were the dominant genera in the WC treatment while Candidatus, Koribacter and Granulicella were the dominant genera in the WCN treatment. To summarize, wheat and maize straw returning with N fertilizer would be the optimum proposal for improving soil quality and yield in the future in non-calcareous fluro-acquic-wheat and maize cultivated soils in the North China Plain in China

Baechi: Fast Device Placement of Machine Learning Graphs

Machine Learning graphs (or models) can be challenging or impossible to train when either devices have limited memory, or models are large. To split the model across devices, learning-based approaches are still popular. While these result in model placements that train fast on data (i.e., low step times), learning-based model-parallelism is time-consuming, taking many hours or days to create a placement plan of operators on devices. We present the Baechi system, the first to adopt an algorithmic approach to the placement problem for running machine learning training graphs on small clusters of memory-constrained devices. We integrate our implementation of Baechi into two popular open-source learning frameworks: TensorFlow and PyTorch. Our experimental results using GPUs show that: (i) Baechi generates placement plans 654 X - 206K X faster than state-of-the-art learning-based approaches, and (ii) Baechi-placed model's step (training) time is comparable to expert placements in PyTorch, and only up to 6.2% worse than expert placements in TensorFlow. We prove mathematically that our two algorithms are within a constant factor of the optimal. Our work shows that compared to learning-based approaches, algorithmic approaches can face different challenges for adaptation to Machine learning systems, but also they offer proven bounds, and significant performance benefits.Comment: Extended version of SoCC 2020 paper: https://dl.acm.org/doi/10.1145/3419111.342130

FAST Globular Cluster Pulsar Survey: Twenty-Four Pulsars Discovered in Fifteen Globular Clusters

We present the discovery of 24 pulsars in 15 Globular Clusters (GCs) using the Five-hundred-meter Aperture Spherical radio Telescope (FAST). These include the first pulsar discoveries in M2, M10, and M14. Most of the new systems are either confirmed or likely members of binary systems. M53C, NGC6517H and I are the only three pulsars confirmed to be isolated. M14A is a black widow pulsar with an orbital period of 5.5 hours and a minimum companion mass of 0.016 \Ms. M14E is an eclipsing binary pulsar with an orbital period of 20.3 hours. With the other 8 discoveries that have been reported elsewhere, in total 32 GC pulsars have been discovered by FAST so far. In addition, We detected M3A twice. This was enough to determine that it is a black widow pulsar with an orbital period of 3.3 hours and a minimum companion mass of 0.0125 \Ms.Comment: 12 pages, 2 figures, accepted by ApJL, comments are always welcomed

Effect of dietary Ginkgo biloba leaf on the growth performance and nonspecific immunity of red swamp crayfish Procambarus clarkii

This trial investigated the effect of dietary Ginkgo biloba leaf (GBL) on the growth performance and nonspecific immunity of red swamp crayfish Procambarus clarkii. 180 Crayfishes were randomly divided into three groups. One group was fed with basic diet, whereas the other two groups were fed with diets containing 1% and 3% GBL. After 32 days of feeding, GBL addition tended to increase the body weight gain rate compared with control. In 3% GBL group, the bodyweight gain rate of male crayfish was higher than that of female crayfish. While female crayfish were advantageous in terms of meat yield. Liver-related indexes were influenced by GBL addition and 3% GBL could reduce glutamic pyruvic transaminase and glutamic oxaloacetic transaminase as well as total cholesterol in male crayfish, showing its function in liver protection. Moreover, GBL addition effects on liver protection was better in male crayfish than female crayfish