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Research Article
Sea Surface Temperature Prediction in China Sea Based on SAM-LSTM Approach
Issue:
Volume 8, Issue 2, June 2024
Pages:
14-22
Received:
23 March 2024
Accepted:
17 April 2024
Published:
28 April 2024
Abstract: Sea Surface Temperature (SST), a critical environmental element in the ocean, significantly impacts the global atmosphere-ocean energy balance and holds the potential to trigger severe weather like droughts, floods, and El Niño events. Therefore, the prediction of future SST dynamics is crucial to identifying these extreme events and mitigating the damage they caused. In this study, we introduce a time series prediction method based on the Self-Attention Mechanism-Long Short-Term Memory (SAM-LSTM) model. In addition, the historical time-series satellite data of SST anomaly (SSTA) is used instead of SST itself considering that the fluctuations of SST are very small compared to their absolute magnitudes. The Seasonal-Trend decomposition using Loess (STL) method is adopted to decompose the complex non-linear SSTA time series into trend components, seasonal components, and residual components. Then, the deseasonalized time series data at 6 locations in the Bohai Sea are used to train and valid the developed SAM-LSTM model. After that, the validated models are applied to the Yellow Sea, East China Sea, and South China Sea. The experimental results show that the combination of STL time series decomposition and SAM-LSTM can achieve high-precision prediction of daily SSTA than LSTM. This suggests that the methodology used in this paper has a good application for short-term daily SST prediction.
Abstract: Sea Surface Temperature (SST), a critical environmental element in the ocean, significantly impacts the global atmosphere-ocean energy balance and holds the potential to trigger severe weather like droughts, floods, and El Niño events. Therefore, the prediction of future SST dynamics is crucial to identifying these extreme events and mitigating the...
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Research Article
Study on the Influence of Canopy Density on Cycling of Soil Available N in Different Landform of Loess Plateau in China
Issue:
Volume 8, Issue 2, June 2024
Pages:
23-40
Received:
7 April 2024
Accepted:
6 May 2024
Published:
10 May 2024
Abstract: In this paper, a total of 330 soil samples with 0-100cm soil depth of 66 planted square forest (10*10m) with different canopy density in the Loess Plateau were selected for the determination and analysis of soil N content in different soil layers, and the effects of different canopy density on soil N cycle under different topographic factors of planted forest were studied. The results showed as follows: (1) the migration mechanism of different N forms to the root surface was different, the migration of nitrate nitrogen to the root surface mainly depended on mass flow, there was enrichment phenomenon near the root, ammonium nitrogen mainly through diffusion, resulting in deficiency and loss in the near rhizosphere, and the leaching loss of nitrate nitrogen was affected by soil water and root growth. (2) The thickness, composition and decomposition rate of litter were different due to different canopy density, which affected the content of ammonium nitrogen and nitrate nitrogen in forest soil. (3) Although the change of different regions in this region was spatially different, keeping the stand cover in the middle and high range of 0.75-0.8 can be conducive to maintaining the balance between the consumption of soil nutrients by the stand and the supplement of nutrient consumption, which can also be conducive to the sustainable recovery and growth of the stand in this region.
Abstract: In this paper, a total of 330 soil samples with 0-100cm soil depth of 66 planted square forest (10*10m) with different canopy density in the Loess Plateau were selected for the determination and analysis of soil N content in different soil layers, and the effects of different canopy density on soil N cycle under different topographic factors of pla...
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Research Article
Noise Pollution Exposure Among Nurses in a Public Hospital in Palestine
May Ahmed Elafifi*,
Mohamed Yehia Elawady,
Ayesha Mohammed Alrifai
Issue:
Volume 8, Issue 2, June 2024
Pages:
41-48
Received:
28 April 2024
Accepted:
29 May 2024
Published:
14 June 2024
Abstract: Noise pollution affects our health adversely. At hospital, noise can harm health care professionals and patients too. It also affects the performance of the whole staff and therefore, the quality of the delivered services. This study aimed to assess noise levels nurses exposed to and to determine the sources of noise and nurses' complaints about it. A quantitative, descriptive cross sectional study was used. Noise levels at different departments in Palestine Medical Complex (PMC) were measured using an integrating sound level meter. A total of 180 nurses participated in the interviewing questionnaire. The results of the study showed that main sources of noise were: the loud arguments occurred between the health care staff and the relatives/visitors of the patients, loud conversations, the construction work and the renovation in the hospital, patients' crying/shouting, the medical equipment and the staff shouting. The main complaints were discomfort, bad communication, headache, fatigue, stress, irritability, low concentration, inattention, memory problems and noise effect on work efficiency. In most departments, morning shift was the noisiest shift and nurses (61.1%) considered work environment stressful and uncomfortable. Noise levels in all departments exceeded what is recommended by WHO with an average of 64.48 dBA. The minimum value of LAeq was 54.8 dBA in one CCU and the maximum one was 73.5 dBA in NICU. Conclusion: Different noise sources at PMC and many noise complaints were reported by nurses. Noise levels in different departments were above that recommended by WHO. The educational intervention should target nurses and the whole health care staff in order to increase their awareness about noise and to modify their behaviors to reduce it, as well as the effective management of medical devices and machines, repairing devices and physical space arrangement.
Abstract: Noise pollution affects our health adversely. At hospital, noise can harm health care professionals and patients too. It also affects the performance of the whole staff and therefore, the quality of the delivered services. This study aimed to assess noise levels nurses exposed to and to determine the sources of noise and nurses' complaints about it...
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,
Xueqing Zhang*
