Quality Improvement and Cost Evaluation of Pellet Fuel Produced from Pruned Fruit Tree Branches

Biomass-based pellet is an important source of renewable energy. In this study, to obtain the high-quality fuel pellet via the densification of pruned branches of fruit trees, we investigated the optimization of blending ratios for different raw materials using branches from jujube (Ziziphus jujuba Mill.), which is a widely distributed waste biomass resource in China. Through the characterization of raw materials and pellets, the effects of different raw materials on the storage, transportation, and combustion performances of the pellets can be understood. The cost evaluation analysis showed that the two optimized, co-densified pellets had great cost advantages compared with the pure jujube branch pellets. This indicates the potential industrial value of optimized pellets. The results of this study can help to improve the application value of orchard residues and generate an additional profit for fruit plantations, simultaneously avoiding the environmental damage caused by its open combustion.

Validation of Spanish Erasmus-Modified Nottingham Sensory Assessment Stereognosis Scale in Acquired Brain Damage

Acquired brain injury (ABI) is the third leading cause of death in Spain. The disability derived from ABI can include considerable difficulties in upper-limb use due to somatosensory deficits. One of the assessments most commonly used to evaluate ABI is the Nottingham Sensory Assessment (NSA); however, there is no complete psychometric analysis or standardized version in Spanish. We aimed to develop and validate a Spanish version of the stereognosis component of the NSA for evaluating Spanish adults with ABI via a single-center, observational, cross-sectional study. The Spanish version of the NSA was developed in two steps. The first was based on the standardization and collection of normative data in 120 asymptomatic participants. For the second, we recruited 25 participants with ABI to establish concurrent criterion-related validity, internal consistency, and floor/ceiling effects. Criterion validity was assessed against two-point discrimination and tactile-localization tests. Our normative data showed significant differences among the various age groups (p < 0.05), supporting the validity of the Spanish-version assessment. For the ABI sample, we also found further evidence of validity with Spearman’s rho coefficient between the total scores and the two-point discrimination and tactile-localization tests, which showed low and moderate correlations (rho = 0.50–0.75, p < 0.05). Internal consistency was excellent, with a Cronbach’s alpha of 0.91. No ceiling or floor effects were found. We conclude that the stereognosis component of the NSA in its Spanish version is a valid scale that can be used to comprehensively and accurately assess stereognosis capacity in adults with ABI. As a low-cost evaluation, this assessment has great potential to be widely used in clinical practice and research settings.

Methodology for Constructing and Using a Mathematical Model for Assessing Labor Costs for the Development of Distance Learning Courses

Distance learning plays a significant role in solving the problem of the sustainable development of society. Unfortunately, the development and implementation of distance courses are still carried out intuitively, which does not allow practical implementation of effective mathematics methods and slows down the introduction of breakthrough technologies. The aim of the research was to develop a new model and a methodology for assessing the labor costs of designing distance learning courses by university teachers based on a comprehensive assessment of the courses’ quality. The suggested model originally extends the constructive cost evaluation model already used in IT industry. The developed criteria make it possible to assess labor costs in relation to the quality of course development. The paper provides and analyzes such calculations on the example of courses in the theory of algorithms and programming.

PECSA: Practical Edge Computing Service Architecture Applicable to Adaptive IoT-Based Applications

The cloud-based Internet of Things (IoT-Cloud) combines the advantages of the IoT and cloud computing, which not only expands the scope of cloud computing but also enhances the data processing capability of the IoT. Users always seek affordable and efficient services, which can be completed by the cooperation of all available network resources, such as edge computing nodes. However, current solutions exhibit significant security and efficiency problems that must be solved. Insider attacks could degrade the performance of the IoT-Cloud due to its natural environment and inherent open construction. Unfortunately, traditional security approaches cannot defend against these attacks effectively. In this paper, a novel practical edge computing service architecture (PECSA), which integrates a trust management methodology with dynamic cost evaluation schemes, is proposed to address these problems. In the architecture, the edge network devices and edge platform cooperate to achieve a shorter response time and/or less economic costs, as well as to enhance the effectiveness of the trust management methodology, respectively. To achieve faster responses for IoT-based requirements, all the edge computing devices and cloud resources cooperate in a reasonable way by evaluating computational cost and runtime resource capacity in the edge networks. Moreover, when cooperated with the edge platform, the edge networks compute trust values of linked nodes and find the best collaborative approach for each user to meet various service requirements. Experimental results demonstrate the efficiency and the security of the proposed architecture.