IoT Blockchain Data Veracity with Data Loss Tolerance

Recent years have witnessed the advancement of the Internet of Things (IoT) and its emergence as a technology that could revolutionize many businesses. It helps considerably in creating data-driven business models with the insights it provides. IoT systems are deployed in data collection, monitor processes, provide insights and allow businesses to make data-driven productivity improvements. However, IoT systems are often experiencing data loss due to inevitable failures ranging from devices, networks, to the application layer, especially in scarce infrastructure resources environments. Data loss might be unrecoverable in many circumstances. As such, this research presents a blockchain based IoT model (framework) with the aim of circumventing data loss. We envisioned IoT blockchain technology in enhancing data veracity with data loss tolerance. That is, to have blockchain enhancing the IoT data veracity by leveraging on the features existed in its peer-to-peer network (P2P) and distributed ledger storage technology (DLT). Additionally, the edge computing of IoT blockchain technology is also conceptually workable; with intelligent small computing resources, it opens up a new era of bringing the intelligence of data collection, connectivity, computation and storage into the edge/device layer. A novel IoT blockchain strength monitoring system is also been studied to further enhance data veracity; this is achieved through a capacitance monitoring on the IoT blockchain system. The empirical results show that the proposed IoT blockchain with a strength monitoring model can alleviate data loss and thus enhance data veracity with data loss tolerance.

Physiological, morphological and ecological traits drive desiccation resistance in north temperate dung beetles

Background Increasing temperatures and changes in precipitation patterns threaten the existence of many organisms. It is therefore informative to identify the functional traits that underlie differences in desiccation resistance to understand the response of different species to changes in water availability resulting from climate change. We used adult dung beetles as model species due to their importance to ecosystem services. We investigated: (i) the effect of physiological (water loss rate, water loss tolerance, body water content), morphological (body mass) and ecological (nesting behaviour) traits on desiccation resistance; (ii) the role of phylogenetic relatedness in the above associations; and, (iii) whether relatively large or small individuals within a species have similar desiccation resistance and whether these responses are consistent across species. Results Desiccation resistance decreased with increasing water loss rate and increased with increasing water loss tolerance (i.e. proportion of initial water content lost at the time of death). A lack of consistent correlation between these traits due to phylogenetic relatedness suggests that the relationship is not determined by a shared evolutionary history. The advantage of a large body size in favouring desiccation resistance depended on the nesting behaviour of the dung beetles. In rollers (one species), large body sizes increased desiccation resistance, while in tunnelers and dwellers, desiccation resistance seemed not to be dependent on body mass. The phylogenetic correlation between desiccation resistance and nesting strategies was significant. Within each species, large individuals showed greater resistance to desiccation, and these responses were consistent across species. Conclusions Resistance to desiccation was explained mainly by the dung beetles’ ability to reduce water loss rate (avoidance) and to tolerate water loss (tolerance). A reduction in water availability may impose a selection pressure on body size that varies based on nesting strategies, even though these responses may be phylogenetically constrained. Changes in water availability are more likely to affect dweller species, and hence the ecosystem services they provide.

A Comparative Analysis of Soil Loss Tolerance and Productivity of the Olive Groves in the Protected Designation of Origin (PDO) Areas Norte Alentejano (Portugal) and Estepa (Andalusia, Spain)

Olive groves are Mediterranean systems that occupy more than 2.5 M ha in Spain and 0.352 M ha in Portugal. Assuming the differences between both countries in terms of olive grove regulation and considering their multifunctionality, it is useful to implement agronomic indices to estimate their sustainability. The Soil Loss Tolerance Index (SLTI) and the Soil Productivity Index (SPI) are two such indices. We calculated both indices in the Protected Designation of Origin (PDO) Norte Alentejano (Portugal). The SLTI index was adapted considering specific variables of the analysed olive groves (i.e., SLTIog). The values obtained were compared with those previously estimated for PDO Estepa (Spain). The negative impacts of erosion and the underlying agricultural practices on the sustainability of olive groves became evident, resulting in decreased soil productivity at the regional level. The SLTIog index showed higher values for crops, being a more realistic tool to analyse sustainability. A higher soil loss tolerance was detected for integrated groves in the PDO Norte Alentejano than for PDO Estepa due to the shorter age of olive cultivation in Portugal, with incipient soil impacts. These indices provide information on the degree of soil erosion, allowing farmers and decision-makers to apply practices to maximise the sustainability of olive groves.

Risk Tolerance Profiling Measure: Testing Its Reliability and Validities

This study examines the degree to which the customer risk profiling measure (CRPM), commonly used by financial institutions to determine loss tolerance of investors, is psychometrically valid in assessing risk tolerance and predicting anxiety after experiencing a significant investment loss. Data were collected online from 91 respondents with various investment experience, Results suggest that CPRM is significantly correlated with the Grable and Lytton's Financial Risk Tolerance Scale (G/L-RTS), a validated financial risk tolerance measure. CPRM is also able to predict anxiety after experiencing a significant investment loss. Furthermore, CRPM also demonstrates incremental predictive validity above and beyond G/L-RTS in predicting anxiety after investment loss.

Targeting, Deployment, and Loss-Tolerance in Lanchester Engagements

Incorporating Imperfect Targeting, Deployment Restrictions, and Morale into Combat Models