SIMULATION OF DESIGN VARIABLES EFFECT ON PERFORMANCE OF A COMMON BEANS (Phaseolus vulgaris L) PORTABLE THRESHER

In Kenya, threshing of common beans is mainly by traditional method using sticks and animal tramping, which are slow, inefficient and tedious. Consequently, there is a need to develop portable threshers locally available in the market for small and medium-scale farmers. The objective of this study was to simulate design variables effect on the performance of a common beans portable thresher. Sizing of design variables and parameters was key in development of bean thresher. This could be achieved by costly experiments or use of prediction mathematical model equation. The later method was used by developing mathematical models from combination of Buckingham pi theorem and reference to other similar work in literature. The predicting equation for power requirement, grain losses, grain damages, efficiency and throughput capacity were developed and validated using experimental thresher from the same study. The results showed that there was a positive correlation with R2 of 0.9. Based on actual data and 10% absolute residual error interval, the prediction performance of the developed models were above 77%. The results noted that increase in cylinder peripheral speed of the pegs resulted into increase in power requirement, bean grains damages, threshing efficiency and throughput capacity. Also increase in effective cylinder diameter caused increase in threshing efficiency and grain damages.

Bayesian maximum entropy-based prediction of the spatiotemporal risk of schistosomiasis in Anhui Province, China

Background “Schistosomiasis” is a highly recurrent parasitic disease that affects a wide range of areas and a large number of people worldwide. In China, schistosomiasis has seriously affected the life and safety of the people and restricted the economic development. Schistosomiasis is mainly distributed along the Yangtze River and in southern China. Anhui Province is located in the Yangtze River Basin of China, with dense water system, frequent floods and widespread distribution of Oncomelania hupensis that is the only intermediate host of schistosomiasis, a large number of cattle, sheep and other livestock, which makes it difficult to control schistosomiasis. It is of great significance to monitor and analyze spatiotemporal risk of schistosomiasis in Anhui Province, China. We compared and analyzed the optimal spatiotemporal interpolation model based on the data of schistosomiasis in Anhui Province, China and the spatiotemporal pattern of schistosomiasis risk was analyzed. Methods In this study, the root-mean-square-error (RMSE) and absolute residual (AR) indicators were used to compare the accuracy of Bayesian maximum entropy (BME), spatiotemporal Kriging (STKriging) and geographical and temporal weighted regression (GTWR) models for predicting the spatiotemporal risk of schistosomiasis in Anhui Province, China. Results The results showed that (1) daytime land surface temperature, mean minimum temperature, normalized difference vegetation index, soil moisture, soil bulk density and urbanization were significant factors affecting the risk of schistosomiasis; (2) the spatiotemporal distribution trends of schistosomiasis predicted by the three methods were basically consistent with the actual trends, but the prediction accuracy of BME was higher than that of STKriging and GTWR, indicating that BME predicted the prevalence of schistosomiasis more accurately; and (3) schistosomiasis in Anhui Province had a spatial autocorrelation within 20 km and a temporal correlation within 10 years when applying the optimal model BME. Conclusions This study suggests that BME exhibited the highest interpolation accuracy among the three spatiotemporal interpolation methods, which could enhance the risk prediction model of infectious diseases thereby providing scientific support for government decision making.

Discrimination of Transformer Inrush Currents and Internal Fault Currents Using Extended Kalman Filter Algorithm (EKF)

The discrimination of inrush currents and internal fault currents in transformers is an important feature of a transformer protection scheme. The harmonic current restrained feature is used in conventional differential relay protection of transformers. A literature survey shows that the discrimination between the inrush currents and internal fault currents is still an area that is open to research. In this paper, the classification of internal fault currents and magnetic inrush currents in the transformer is performed by using an extended Kalman filter (EKF) algorithm. When a transformer is energized under normal conditions, the EKF estimates the primary side winding current and, hence, the absolute residual signal (ARS) value is zero. The ARS value will not be equal to zero for internal fault and inrush phenomena conditions; hence, the EKF algorithm will be used for discriminating the internal faults and inrush faults by keeping the threshold level to the ARS value. The simulation results are compared with the theoretical analysis under various conditions. It is also observed that the detection time of internal faults decreases with the severity of the fault. The results of various test cases using the EKF algorithm are presented. This scheme provides fast protection of the transformer for severe faults.

Case-based reasoning system for prediction of fuel consumption by haulage trucks in open-pit mines

The shovel-truck system is commonly used in open-pit mining operations. Truck haulage cost constitutes about 26% of open-pit mining costs as the trucks are mostly powered by diesel whose cost is escalating annually. Therefore, reducing fuel consumption could lead to a significant decrease in overall mining costs. Various methods have been proposed to improve fuel efficiency in open-pit mines. Case-based reasoning (CBR) can be used to estimate fuel consumption by haulage trucks. In this work, CBR methods namely case-based reasoning using forward sequential selection (CBR-FSS), traditional CBR, and Naïve techniques were used to predict fuel consumption by trucks operating at Orapa Mine. The results show that the CBR method can be used to predict fuel consumption by trucks in open-pit mines; the predicted values of fuel consumption using the CBR-FSS technique gave much lower absolute residual values, higher standardised accuracy values, and effect sizes than those of other prediction techniques on all the datasets used. The system will enable mine planners to know the fuel consumed per trip and allow them to take mitigation measures on trucks with high fuel consumption.

Refractive Status in Eyes Implanted with Toric and Nontoric Intraocular Lenses during Combined Cataract Surgery and Microhook Ab Interno Trabeculotomy

Purpose. To compare the refractive status between eyes implanted with toric and nontoric intraocular lenses (IOLs) during combined cataract surgery and microhook ab interno trabeculotomy (μLOT), a minimally invasive glaucoma surgery (MIGS). Methods. Twenty eyes of 20 patients who had open-angle glaucoma, cataract, and preexisting regular corneal astigmatism exceeding 1.5 diopters (D) and underwent combined μLOT and phacoemulsification were recruited retrospectively. Ten eyes were implanted with a toric IOL and 10 eyes with a nontoric IOL. The primary outcomes were the uncorrected visual acuity (UCVA) and refractive cylinder at 3 months postoperatively. Results. The mean UCVA of the toric IOL group (logarithm of the minimum angle of resolution (logMAR), 0.23 ± 0.25) was significantly better than that of the nontoric IOL group (logMAR, 0.45 ± 0.26) at 3 months postoperatively ( p < 0.05 ). The mean absolute residual refractive cylinder of the nontoric IOL group (2.25 ± 0.62 D) was significantly greater than that of the toric IOL group (1.30 ± 0.68 D) ( p < 0.05 ). Postoperatively, 60% of eyes in the toric IOL group and 10% in the nontoric IOL group had an absolute refractive astigmatism level of 1.5 D or less. Surgically induced astigmatism (0.77 ± 0.43 D for toric group and 0.60 ± 0.32 D for nontoric group) and IOP reduction (33.9 ± 15.6% for toric group and 29.4 ± 11.7% for nontoric group) were not different between groups. Conclusions. Use of toric IOL during combined cataract surgery and μLOT is possible and better than not, but physician should prevent their patient of persisting residual astigmatism. The study was registered at https://www.umin.ac.jp/, and the clinical trial accession number is https://clinicaltrials.gov/ct2/show/UMIN000043141.

Evaluation of Compatible Taper and Volume Models for Combretum hartmannianum and Lonchocarpus laxiflorus Tree Species.

This paper developed and evaluated the performance of the current functional tree taper and volume models. The models were applied to some selected economically important natural tree species common to central Sudan, namely, Combretum hartmannianum and, Lonchocarpus Laxiflorus. The tree variables measured were the diameter at breast height (DBH, cm), diameter at the base of the tree (d0, cm), upper stem diameters (di), total tree height (H), and height to the base of the crown (Hb). In total, 19 taper and 32 volume models were tested and evaluated (22 models were two-variable models (Diameter at breast height and total tree height or bole height) and 10 were three-variable models (Diameter at ground level, Diameter at breast height and total tree height or bole height). The model goodness of fit was evaluated in terms of adjusted coefficient of determination (Ra2), standard error (SE), mean absolute residual (MAR), bias (BI) Akaike’s information criterion (AIC), homogeneity of the residuals and significance of the regression parameters. As far as taper models is concerned, Models, some of the models were found to yield satisfactory results for the tow selected species with R2 range of 0.94 – 0.96. For the within species variation of models on the basis of the AIC values, the ranking of the models (smaller AIC first) were in consistant with the rankings due to SE and Ra2 values although AIC penalizes models in proportion to the number regression parameters. In general the results of the study indicated that higher residuals valuse are in most of the cases associated with the lower parts of the bole, the butress portion of the stem. This suggests that care should be taken during the application of such models for hardwood species, especially in open woodlands where butress is a common characteristic.The results for volume models revealed differences in the behaviour of different models for each species as the degree of significance of the regression parameters varies between tree species. However, the replacement of the total tree height by the bole height (merchantable height) improves both the level of parameter significance and the coefficient of determination. The results also reveal that inclusion of diameter at grown level to the original two variables (DBH, Ht) and the replacement of the original model total height with the bale height results in quite significant improvement of the Ra2 values. In general, the study concluded that taper and volume models can provide precise and accurate estimation of tree growth variables for the studied species with reasonable cost and time, but care should be taken when dealing with same model for the same species across varying growth and management condition, or when dealing with different species. country.

Taper and Volume Models for Some Terminalia Tree Species

The paper evaluated the performance of the current functional tree taper and volume models. The models were applied to some selected economically important natural Terminalia tree species common to central Sudan, namely, Terminalia laxiflora and, Terminalia brownii. 22 two-variable models (Diameter at breast height and total tree height or bole height) and 10 three-variables models (Diameter at ground level, Diameter at breast height and total tree height or bole height) were evaluated. The tree variables measured were the diameter at breast height (DBH, cm), diameter at the base of the tree (d0, cm), upper stem diameters (di), total tree height (H), and height to the base of the crown (Hb). Data were extracted from a natural reserved forest in the Blue Nile state. The models goodness of fit were evaluated in terms of adjusted coefficient of determination (Ra2), standard error (SE), mean absolute residual (MAR), bias (BI) Akaike’s information criterion (AIC), homogeneity of the residuals and significance of the regression parameters. Taper-17 and Taper-19 were found to be among the best two models for the two species with R2 range of 0.94 – 0.93, but with different rankings for each species. Comparison of the range of data for the tow studied species suggested that representation of various diameter at breast height (DBH, cm), diameter at the base of the tree (d0, cm), upper stem diameters (di), total tree height (H), and height to the base of the crown (Hb), had significant influence on the accuracy of prediction outside the range of the fitted data. This implies that application of the selected models is only useful at local stand level or at best in similar biological and stand structure conditions. For volume models, The results indicated that individual equations act differently in each species as there were great variations in the values of the same parameter of a given model accross the species. Some regression parameters of a given model were found to be significant in some species and insignificant in others. Comparison between the two versions of each group reveals that the replacement of the total tree height by the bole height (merchantable height) improves both the level of parameter significance and the coefficient of determination. From the first, the regression parameters of only 5 models (VOL-1, VOL-5, VOL-8, VOL-17, and VOL-20) were found to be significant at 0.05 probability level for all the tow species. The results also reveal that inclusion of variable D0 to the original two variables (DBH, Ht) to the volume equations results in insignificant improvement of the Ra2 values, while the replacement of the original model Ht variable with the Hb results in quite significant improvement of the Ra2 values. However, substantial improvement of the Ra2 values were obtained when both D0 and Hb were added. For this group of models, VOL-23, VOL-25- VOL-29 VOL30- and VOL-31were found to be the best for almost all the tow species. In general, the study concluded that taper and volume models can provide precise and accurate tree growth variables for the studied species with reasonable cost and time, but care should be taken when dealing with same model for the same species across the varying growth and management condition.

Secondary Piggyback Intraocular Lens for Management of Residual Ametropia after Cataract Surgery

Purpose: To investigate the indications, clinical outcomes, and complications of secondary piggyback intraocular lens (IOL) implantation for correcting residual refractive error after cataract surgery. Methods: In this prospective interventional case series, patients who had residual refractive error after cataract surgery and were candidates for secondary piggyback IOL implantation between June 2015 and September 2018 were included. All eyes underwent secondary IOL implantation with the piggyback technique in the ciliary sulcus. The types of IOLs included Sulcoflex and three-piece foldable acrylic lenses. Patients were followed-up for at least one year. Results: Eleven patients were included. Seven patients had hyperopic ametropia, and four patients had residual myopia after cataract surgery. The preoperative mean of absolute residual refractive error was 7.20 ± 7.92, which reached 0.42 ± 1.26 postoperatively (P < 0.001). The postoperative spherical equivalent was within ±1 diopter of target refraction in all patients. The average preoperative uncorrected distance visual acuity was 1.13 ± 0.35 LogMAR, which significantly improved to 0.41 ± 0.24 LogMAR postoperatively (P = 0.008). There were no intraor postoperative complications during the 22.4 ± 9.5 months of follow-up. Conclusion: Secondary piggyback IOL implantation is an effective and safe technique for the correction of residual ametropia following cataract surgery. Three-piece IOLs can be safely placed as secondary piggyback IOLs in situations where specifically designed IOLs are not available.

Sanctions as a Catalyst for Russia’s and China’s Balance of Trade: Business Opportunity

Economic sanctions are among the most powerful instruments of international policy. However, this study, using the example of the so-called anti-Russian sanctions, shows that in the global economy, countries are rapidly using other alternatives, and sanctions in the case analyzed act as a catalyst for balance of trade between the Russian Federation and the People’s Republic of China. The study is based on a highly topical sophisticated model of neural networks, which provides clear results confirming the unintended positive effect. The time series and aggregated data became inputs into multilayer perceptron networks, while the methodology used enabled eliminating of both too large averaging and extreme fluctuations of the equalized time series. Out of 10,000 networks created for each variable and each time lag, five showing the best characteristics given by correlation coefficients and absolute residual sums were retained. Thus, the created equalized time series were able to describe the basic trend of the actual development of export and import, while also capturing their local extremes. The interpolation of the two time series shows that the sanctions imposed on the Russian Federation in 2014 have clearly strengthened its balance of trade with the People’s Republic of China. The results of the study also predict further growth in the balance of trade between the Russian Federation and the People’s Republic of China, although this development may be delayed by current events.

Robust Bearing-Only Localization Using Total Least Absolute Residuals Optimization

Robust techniques critically improve bearing-only target localization when the relevant measurements are being corrupted by impulsive noise. Resistance to isolated gross errors refers to the conventional least absolute residual (LAR) method, and its estimate can be determined by linear programming when pseudolinear equations are set. The LAR approach, however, cannot reduce the bias attributed to the correlation between system matrices and noise vectors. In the present study, perturbations are introduced into the elements of the system matrix and the data vector simultaneously, and the total optimization problem is formulated based on least absolute deviations. Subsequently, an equivalent form of total least absolute residuals (TLAR) is obtained, and an algorithm is developed to calculate the robust estimate by dual ascent algorithms. Moreover, the performance of the proposed method is verified through the numerical simulations by using two types of localization geometries, i.e., random and linear. As revealed from the results, the TLAR algorithm is capable of exhibiting significantly higher localization accuracy as compared with the LAR method.