Performance assessment of six bias correction methods using observed and RCM data at upper Awash basin, Oromia, Ethiopia

Selecting a suitable bias correction method is important to provide reliable inputs for evaluation of climate change impact. Their influence was studied by comparing three discharge outputs from the SWAT model. The result after calibration with original RCM indicate that the raw RCM are heavily biased, and lead to streamflow simulation with large biases (NSE = 0.1, R2 = 0.53, MAE = 5.91 mm/°C, and PBIAS = 0.51). Power transformation and linear scaling methods performed best in correcting the frequency-based indices, while the LS method performed best in terms of the time series-based indices (NSE = 0.87, R2 = 0.78, MAE = 3.14 mm/°C, PBIAS = 0.24) during calibration. Meanwhile, daily translation was underestimating simulated streamflow compared with observed and considered as the least performing method. Precipitation correction method has higher visual influence than temperature, and its performance in streamflow simulations was consistent and significantly considerable. Power transformation and variance scaling showed highly qualified performance compared to others with indicated time series value (NSE = 0.92, R2 = 0.88, MAE = 1.58 mm/°C and PBIAS = 0.12) during calibration and validation of streamflow. Hence, PT and VARI methods were the dominant methods which remove biasness from RCM models at Akaki River basin.

One down, 699 to go: or, synthesising compositional desugarings

Programming or scripting languages used in real-world systems are seldom designed with a formal semantics in mind from the outset. Therefore, developing well-founded analysis tools for these systems requires reverse-engineering a formal semantics as a first step. This can take months or years of effort. Can we (at least partially) automate this process? Though desirable, automatically reverse-engineering semantics rules from an implementation is very challenging, as found by Krishnamurthi, Lerner and Elberty. In this paper, we highlight that scaling methods with the size of the language is very difficult due to state space explosion, so we propose to learn semantics incrementally. We give a formalisation of Krishnamurthi et al.'s desugaring learning framework in order to clarify the assumptions necessary for an incremental learning algorithm to be feasible. We show that this reformulation allows us to extend the search space and express rules that Krishnamurthi et al. described as challenging, while still retaining feasibility. We evaluate enumerative synthesis as a baseline algorithm, and demonstrate that, with our reformulation of the problem, it is possible to learn correct desugaring rules for the example source and core languages proposed by Krishnamurthi et al., in most cases identical to the intended rules. In addition, with user guidance, our system was able to synthesize rules for desugaring list comprehensions and try/catch/finally constructs.

Resin Nano-Ceramic Material Surface Roughness, Color Stability, and Bacterial Adhesion Evaluation After Different Scaling Methods

Objectives: The study evaluated in vitro the changes in roughness, color stability, and bacterial count of a CAD/CAM Resin Nano-Ceramic material surface treated by various scaling procedures. Material and Methods: 70 disks (5mm diameter, 0.5 mm thickness) of Resin Nano-Ceramic (Lava ™Ultimate, 3M, ESPE) material were cemented in standardized cavities prepared in bovine teeth. A custom-made scaling apparatus of a double pan balance was used for different scaling methods, simulating standard clinical conditions. The specimens were assigned to three main groups: no scaling(C), ultrasonic scaling (U), and manual scaling (M). Each group was then divided into three subgroups according to scaling tip material; stainless steel tip (St), plastic tip (P), and titanium tip (Ti). The surface texture was analyzed quantitatively and qualitatively with a tactile profilometer and atomic force microscopy. A spectrophotometer was used for color measurement. Streptococcus mutans were counted in a colony counter. All the data were tabulated and statistically analyzed. Results: Two-way ANOVA was used to study the effect while One-way ANOVA was performed to compare between study groups. The significance level was set at p 0.05. The ultrasonic titanium tip(UTi) revealed the significant highest mean value of alterations (p < 0.001). The integrity of the material surface was altered in the form of deep scratches on the ultrasonically scaled surfaces and numerous smaller scratches on the hand-scaled surfaces. Conclusion: The plastic instrument would appear to be the instrument of choice during a routine maintenance procedure for Resin Nano-Ceramic materials. Keywords Bacterial biofilm; Dental ceramics; Color stability; Scaling; Surface roughness.

Analysis of extreme rainfall and drought events using statistical and fractal methods: A case study of Mauritius

Due to climate change, extreme rainfall and drought events are becoming more and more frequent in several regions of the globe. We investigated the suitability of employing statistical and fractal (or scaling) methods to characterise extreme precipitation and drought events. The case of the island of Mauritius was considered, for which monthly mean rainfall data for the period January 1950 to December 2016 were analysed. The generalised extreme value distribution was used to extract the 10- and 20-year return levels and the Standardised Precipitation Index (SPI) was used to identify anomalous wet and dry events. A log-term correlation analysis was also performed to characterise the relationship between maximum rainfall and its duration. The results indicate that the 10-year return level is approximately between 500 mm and 850 mm and the 20-year return level is between 600 mm and 1000 mm. Results also show that the extreme maximum rainfall events occur mostly during austral summer (November to April) and could be related to the effects of tropical cyclones and La Niña events, while anomalous dry events were found to be significantly persistent with very long periods of drought. Moreover, there was a strong correlation between maximum rainfall and its duration. The methodology used in this work could be very useful in similar studies for other Small Island Developing States.

Constraining the body mass range of Anzu wyliei using volumetric and extant-scaling methods

The ability to accurately and reliably estimate body mass of extinct taxa is a vital tool for interpreting the physiology and even behavior of long-dead animals. For this reason, paleontologists have developed many possible methods of estimating the body mass of extinct animals, with varying degrees of success. These methods can be divided into two main categories: volumetric mass estimation and extant scaling methods. Each has advantages and disadvantages, which is why, when possible, it is best to perform both, and compare the results to determine what is most plausible within reason. Here we employ volumetric mass estimation (VME) to calculate an approximate body mass for previously described specimens of Anzu wyliei from the Carnegie Museum of Natural History. We also use extant scaling methods to try to obtain a reliable mass estimate for this taxon. In addition, we present the first digital life restoration and convex hull of the dinosaur Anzu wyliei used for mass estimation purposes. We found that the volumetric mass estimation using our digital model was 216-280kg, which falls within the range predicted by extant scaling techniques, while the mass estimate using minimum convex hulls was below the predicted range, between 159-199 kg . The VME method for Anzu wyliei strongly affirms the predictive utility of extant-based scaling. However, volumetric mass estimates are likely more precise because the models are based on comprehensive specimen anatomy rather than regressions of a phylogenetically comprehensive but disparate sample.

IMPLEMENTATION STAGE FOR CIRCULAR ECONOMY IN THE DANISH BUILDING AND CONSTRUCTION SECTOR

The building and construction sector is selected by the European Commission as a key product value chain in the transition towards circular economy (CE) due to the major resource consumption, waste generation and GHG emissions from this sector. This paper reports the result from qualitative and semi-structured interviews with 30 Danish stakeholders from the sector on the current stage of implementation of CE and the research/innovation needs to scale circular construction from niche to mainstream. The interviews showed a large variety in the stakeholder’s stage of transition from hardly knowing the term to having CE as a major driver in their business. Some meant that scaling of CE is close to impossible and that material reuse will never develop to more than a niche, whereas others already offer full-scale circular solutions to clients. The interviews pointed at a need for a common definition and terminology for CE, methods for documenting the gains from the circular solutions (economic and environmental), methods for technical documentation of the quality of reused materials, processes which enables scaling, methods to implement CE in various systems such as digitalization and building passports, new value chains and framework conditions in support of circularity. Regardless these needs, demonstration projects of major importance to gain general knowledge have been built or are planned in Denmark. These demonstrations have different approaches: using todays waste from different industries as construction materials; reusing construction materials (the basic building, elements or processed materials); and designing new buildings for disassembly to enable future reuse.

Probabilistic Projection of Subnational Life Expectancy

Projecting mortality for subnational units, or regions, is of great interest to practicing demographers. We seek a probabilistic method for projecting subnational life expectancy that is based on the national Bayesian hierarchical model used by the United Nations, and at the same time is easy to use. We propose three methods of this kind. Two of them are variants of simple scaling methods. The third method models life expectancy for a region as equal to national life expectancy plus a region-specific stochastic process which is a heteroskedastic first-order autoregressive process (AR(1)), with a variance that declines to a constant as life expectancy increases. We apply our models to data from 29 countries. In an out-of-sample comparison, the proposed methods outperformed other comparative methods and were well calibrated for individual regions. The AR (1) method performed best in terms of crossover patterns between regions. Although the methods work well for individual regions, there are some limitations when evaluating within-country variation. We identified four countries for which the AR(1) method either underestimated or overestimated the predictive between-region within-country standard deviation. However, none of the competing methods work better in this regard than the AR(1) method. In addition to providing the full distribution of subnational life expectancy, the methods can be used to obtain probabilistic forecasts of age-specific mortality rates.