Seed-coat thickness explains contrasting germination responses to smoke and heat by Leucadendron species

Fire stimulates germination of most seeds in fire-prone vegetation. Fruits of Leucadendron (Proteaceae) are winged achenes or nutlets that correlate with their requirements for smoke and/or heat in promoting germination. We describe five possible smoke–heat dormancy-release/germination syndromes among plants, of which Leucadendron displays three (no response, smoke only, smoke and heat). As seed-coat thickness varies with seed-storage location (plant or soil) and morphology (winged or wingless), we tested its possible role in water uptake and germination. Species with winged seeds achieved 100% germination in the absence of smoke/heat, seed coats were an order of magnitude thinner, and their permeability greatly exceeded that of nutlets. As seed-coat thickness increased a) imbibitional water uptake declined at a decreasing rate, and b) the response to smoke, and to a lesser extent heat, increased linearly to reach levels of germination approaching those of winged seeds. For species responsive to smoke and heat, there was no additive effect when applied together, suggesting that they may have promoted the same physiological process. By what mechanisms a) the smoke response is greater the thicker the seed coat, and b) smoke chemicals could increase water permeability to explain the non-additive effect of smoke and heat, warrant further investigation.

Tambar Ni Hulit: An ancient medical manuscript in North Sumatera

Tambar ni hulit, which means skin medicine in Simalungun language, is the title of an old manuscript belonging to the Simalungun tribe. This manuscript is written on laklak material containing medicine information for various diseases. Moreover, this manuscript is relatively rare and written in characters and language that are no longer commonly used. The purpose of this study is to inventory, describe, transliterate, and translate the interpretation of the Tambar Ni Hulit contents. Tambar Ni Hulit is one of the results in searching for old manuscripts in various places in North Sumatra, like museums, libraries, and private collections. The inventory, description, transliteration, and translation were carried out by applying the philological method and content analysis was done to review the content. The result of the inventory described the information of the storage location of Tambar Ni Hulit, namely the North Sumatra Museum. The description analysis described the physical state of the manuscript. From the transliteration and translation results, it is concluded that the Tambar Ni Hulit contains various disease information accompanied by the ingredients of their respective medicine and treatment methods with incantations during the treatment.

Research on information classification and storage in cloud computing data center based on group collaboration intelligent clustering

In order to overcome the problems of long time and low accuracy of traditional methods, a cloud computing data center information classification and storage method based on group collaborative intelligent clustering was proposed. The cloud computing data center information is collected in real time through the information acquisition terminal, and the collected information is transmitted. The optimization function of information classification storage location was constructed by using the group collaborative intelligent clustering algorithm, and the optimal solutions of all storage locations were evolved to obtain the elite set. According to the information attribute characteristics, different information was allocated to different elite sets to realize the classified storage of information in the cloud computing data center. The experimental results show that the longest time of information classification storage is only 0.6 s, the highest information loss rate is 10.0%, and the highest accuracy rate is more than 80%.

Applying Clustering Methods to Develop an Optimal Storage Location Planning-Based Consolidated Picking Methodology for Driving the Smart Manufacturing of Wireless Modules

Picking operations is the most time-consuming and laborious warehousing activity. Managers have been seeking smart manufacturing methods to increase picking efficiency. Because storage location planning profoundly affects the efficiency of picking operations, this study uses clustering methods to propose an optimal storage location planning-based consolidated picking methodology for driving the smart manufacturing of wireless modules. Firstly, based on the requirements of components derived by the customer orders, this research analyzes the storage space demands for these components. Next, this research uses the data of the received dates and the pick-up dates for these components to calculate the average duration of stay (DoS) values. Using the DoS values and the storage space demands, this paper executes the analysis of optimal storage location planning to decide the optimal storage location of each component. In accordance with the optimal storage location, this research can evaluate the similarity among the picking lists and then separately applies hierarchical clustering and K-means clustering to formulate the optimal consolidated picking strategy. Finally, the proposed method was verified by using the real case of company H. The result shows that the travel time and the distance for the picking operation can be diminished drastically.

Estimating the Optimal Location for the Storage of Pellet Surplus

This paper deals with the problem of managing the surplus that arises during the seasonal production of pellets, which will be sold in the period of increased demand. Dijkstra’s algorithm is used in issues connected with finding a new storage place with a view of the optimisation of the transport costs of pellets produced by a company in 18 different towns in the Lubelskie Voivodeship in Poland. The most optimal location for the new pellet storage site has been determined, for which the total length of the traveled routes is the shortest, taking into account the actual shares of individual plants in the total production. The construction of the graph with the shortest paths was made on the basis of the existing network of available transport roads, and the nodes of the graph were their intersections. The most advantageous storage location of pellets was identified by the calculation the total transport cost using a minimum-cost tree of shortest paths. Based on the estimated transport assumptions, the lowest total cost of transport from all 18 plants was 3092.0 (km), which corresponds to an average distance to production plants of 89.7 km and 61.7 km to estimated selling distribution. The new storage point is suggested near the town of Piaski. Average cost of travel for all trees obtained for existing plant locations and subsequent distribution to points of sale was 4113.7 (km), while standard deviation 735.2 (km). Additionally, a relative increase in costs was estimated in the case of selecting other locations. Using spatial interpolation and geoprocessing tools, a map—showing the increase in pellet transport costs in relation to the most optimal solution—was developed. The constructed map allows for a better analysis of cost increases than a single point. It was stated that the increase in transport costs does not exceed 10% of lowest cost for 17.6% area of studied area. It was found that the most convenient area is shifted to the south of the voivodship and improperly adopted storage location can increase transport costs by up to 75%.

An Optimization Model of Integrated AGVs Scheduling and Container Storage Problems for Automated Container Terminal Considering Uncertainty

The running path of automated guided vehicles (AGVs) in the automated terminal is affected by the storage location of containers and the running time caused by congestion, deadlock and other problems during the driving process is uncertain. In this paper, considering the different AGVs congestion conditions along the path, a symmetric triangular fuzzy number is used to describe the AGVs operation time distribution and a multi-objective scheduling optimization model is established to minimize the risk of quay cranes (QCs) delay and the shortest AGVs operation time. An improved genetic algorithm was designed to verify the effectiveness of the model and algorithm by comparing the results of the AGVs scheduling and container storage optimization model based on fixed congestion coefficient under different example sizes. The results show that considering the AGVs task allocation and container storage location allocation optimization scheme with uncertain running time can reduce the delay risk of QCs, reduce the maximum completion time and have important significance for improving the loading and unloading efficiency of the automated terminal.

A Survey Study Report on Cloud Computing

In the recent years one of the major computing model in the Internet World is is Cloud Computing. It is giving birth to new business models and accelerating itself to technology adoption. It acts as a foundation for emerging technologies like the Internet Of Things (IOT). Cloud is used as a storage location. So, we can able to access the data stored in the cloud anytime and anywhere. This paper is about the Survey Report on IEEE Cloud Computing paper published by the author in the appropriate years and I have also reviewed about the Existing Algorithms /Techniques and its drawbacks, Methodologies used and Advantages of Proposed Algorithm which we can improve in future.

Survey Report on Cloud Security

Cloud computing is an architecture. Cloud DBMS is a distributed database that provides computing service to a group of shared resources namely networks, storage, servers, services and applications through the internet on requirement and pay as you use access without physically acquiring them. For resources, software and information over a network the web infrastructure is shared. The database stored in the cloud can be accessed and computed from anywhere and it is used as a storage location. In this paper I have discussed some of the literature review of cloud, the cloud topics and the papers published by the authors in the appropriate years, the existing methodology used with its drawbacks and proposed methodology with its benefits in which we can improve it in future.

Nurses Lack of Knowledge On Inhaler Devices In China: A Cross-Sectional Study

Background: To know the knowledge on inhaler devices in medical staff, this study surveyed knowledge of inhaled therapy and the use of inhaler devices in nurses in China.Methods: 1831 nurses were selected to survey on a new self-designed questionnaire online. The questionnaire has 11 questions, including the storage location of the inhaler devices, steps of using the inhaler device, and the common errors when using various devices, etc. Results: Among the 1831 participants, 816(44.57%), 122(6.66%) and 893(48.77%) nurses worked in community hospital, secondary hospital and tertiary hospital respectively. Adequate knowledge of inhaler devices was demonstrated by nurses working in community hospital(20.10%)、Secondary hospital(8.2%) and Tertiary hospital(13.1%). 27.70% nurses in community hospital knew operational key points in using inhaler compared to in secondary hospital (15.57%) and tertiary hospital (23.18%) P<0.01. Only 9.5%-26.00% of participants chosen correct answers about the ten questions about the use of inhaler. Question six (Which of the following is the wrong option when using Ellpta?) was the one with the highest percentage of correct answers (26.00%). The question with lowest rate of correct answers (9.50%) was question 3 (What are the main points that need to be followed when using DPI?). The most people of correct answers number is Ellpta(26.00%) and the least is Respimat(10.32%). Conclusion: The focus on community hospitals has some results in China. However, knowledge on inhaler devices should be continued to strengthen among nurses in hospital. It is necessary to create training opportunities for nurses to increase their awareness and knowledge of chronic respiratory diseases management.