Efficiency Index Values Research Articles

New secondary decomposition ensemble support vector regression for monthly drought index forecasting

Drought prediction on a monthly timescale is conducive to the timely identification of drought characteristics and provides a reference for drought mitigation. Current research is generally based on drought indices on timescales of three months or more for drought prediction, whereas the presence of highly nonlinear and drastic changes in the characteristics of drought indices leads to suboptimal drought prediction for drought index sequences on monthly timescales. In this study, a secondary decomposition model based on extreme-point symmetric mode decomposition (ESMD), variational mode decomposition (VMD), and support vector regression (SVR) was investigated to predict a monthly-scale drought index. To evaluate the predictive ability of the model, it was applied to 100 meteorological stations in the Pearl River Basin of China and compared and analyzed using four comparative models. The results showed that the model proposed in this study has better performance index values, and the prediction accuracies of all stations are improved compared with the four comparative models, with the most significant improvement in the Nash–Sutcliffe efficiency (NSE) index value, followed by the root mean square error (RMSE) and mean absolute error (MAE) index values, and the smallest improvement in the Wilmot consistency index (WIA) index value. The monthly-scale drought quadratic decomposition (ESMD-VMD) combined prediction model established in this study provides a novel method for drought prediction.

Comparison of the impact of R449-A and R290 on refrigerated display cabinets using life-cycle climate performance method

Due to the high energy consumption of refrigerated display cabinets used in supermarkets, a life cycle cooling performance analysis to increase energy efficiency and reduce environmental impacts is the main subject of this study. It also emphasizes the need for cabinets that consume less energy and provide environmentally friendly working conditions. The Life Cycle Climate Performance (LCCP) of the two refrigerants R290 and R449-A was evaluated using measured data to compare the environmental impact of the refrigerants over the entire fluid and equipment life cycle, including energy consumption. Both vapor-compressed cooling cycles were thermodynamically modeled with the parameters taken from the experiments and the efficiency of system was calculated by using the EES software. The results show that the cabinet using R290 has lower compressor power utilization. The COP of the R290 system increased by 13% compared to the R449A system. The total daily energy consumption was also significantly lower for the R290 system. The energy efficiency index provides a standardized metric that can be used to compare the performance of different cooling systems. In this study, the energy efficiency index value was 17.3 points lower for the R290 system, indicating higher energy efficiency. The energy classes are “E” for the R449-A system and “C” for the R290 system, with the R290 system two classes higher in terms of energy class labeling. The EEI value of the system with R290 refrigerant has been reduced by 33% in comparison with the system with R449A refrigerant. The system using R290 refrigerant achieved a 33% reduction in energy consumption compared to the system using R449A refrigerant. The study also assessed the life cycle climate performance of the two systems. It was found that the R449-A system emits 19032.45 kg CO2e more over its lifetime compared to the R290 system. This was attributed to the relatively high global warming potential and energy consumption of R449-A refrigerant. However, when considering safety (flammability), it was concluded that R-449A has a lower environmental impact than R-290.

Risk factors and clinical significance of lower perigastric lymph node metastases in Siewert type II and III esophagogastric junction adenocarcinoma: a retrospective cohort study

BackgroundNo consensus has been concluded with regarding to the scope of lymph node (LN) dissection for Siewert type II and III adenocarcinoma of the esophagogastric junction (AEG). This study aimed to explore risk factors for lower perigastric LN (LPLN) metastases (including no. 4d, 5, 6, and 12a LN stations) and analyze the indications for LPLN dissection.MethodsIn total, 302 consecutive patients with Siewert type II and III AEG who underwent total gastrectomy (TG) were enrolled. The logistic regression model was used to perform uni- and multivariate analyses of risk factors for LPLN metastases. Kaplan–Meier curves were used for survival analysis, and log-rank tests were used for group comparisons. Basing on the guidelines of Japanese Gastric Cancer Association, the LN metastases (LNM) as well as the efficiency index (EI) of each LN station was further evaluated.ResultsThe independent risk factors for LPLN metastases in patients with Siewert type II and III AEG were distance from the esophagogastric junction (EGJ) to the distal end of the tumor (> 4.0 cm), preoperative carcinoembryonic antigen (CEA) ( +), pT4 stage, and HER-2 ( +). LPLN metastases was an independent risk factor for overall survival following TG. The LNM and EI of LPLN were 8.6% and 2.31%, respectively. The LNM of LPLN > 10% under the stratification of the distance from the EGJ to the distal end of the tumor (> 4.0 cm), pT4, preoperative CEA ( +), and HER-2 ( +) exhibited EI values of 3.55%, 2.09%, 2.51%, and 3.64%, respectively.ConclusionsLPLN metastases was a malignant factor for the prognosis of patients with Siewert type II and III AEG. For patients with preoperative CEA ( +), pT4 stage, HER-2 ( +), and the distance from the EGJ to the distal end of the tumor (> 4.0 cm), TG with LPLN dissection is prioritized for clinical recommendation.

Clozapine-laden carbon dots delivered to the brain via an intranasal pathway: Synthesis, characterization, ex vivo, and in vivo studies

Clozapine, which is widely used to treat schizophrenia, shows low bioavailability due to poor solubility and high first-pass metabolism. The study aimed to design clozapine-loaded carbon dots (CDs) to enhance availability of the clozapine to the brain via intranasal pathway. The CDs were synthesized by pyrolysis of citric acid and urea at 200 °C by hydrothermal technique and characterized by photoluminescence, transmission electron microscopy (TEM), X-ray Photoelectron Spectrometer (XPS), and Fourier transform infrared spectrum (FTIR). The optimized clozapine-loaded CDs (CLZ-CDs-1:3–200) showed a quasi-spherical shape (9–12 nm) with stable blue fluorescence. The CDs showed high drug solubilization capacity (1.5 mg drug in 1 mg/ml CDs) with strong electrostatic interaction with clozapine (drug loading efficiency = 94.74%). The ex vivo release study performed using nasal goat mucosa showed sustained release of clozapine (43.89%) from CLZ-CDs-1:3–200 for 30 h. The ciliotoxicity study (histopathology) confirmed no toxicity to the nasal mucosal tissues using CDs. In the rat model (in vivo pharmacokinetic study), when CDs were administrated by the intranasal route, a significantly higher concentration of clozapine in the brain tissue (Cmax = 58.07 ± 5.36 μg/g and AUCt (µg/h*g) = 105.76 ± 12.31) was noted within a short time (tmax = 1 h) compared to clozapine suspension administered by intravenous route (Cmax = 20.99 ± 3.91 μg/g, AUC t (µg/h*g) = 56.89 ± 12.31, and tmax = 4 h). The high value of drug targeting efficiency (DTE, 486%) index and direct transport percentage (DTP, 58%) indicates the direct entry of clozapine-CDs in the brain via the olfactory route. In conclusion, designed CDs demonstrated a promising dosage form for targeted nose-to-brain delivery of clozapine for the effective treatment of schizophrenia.

Nowcast flood predictions in the Amazon watershed based on the remotely sensed rainfall product PDIRnow and artificial neural networks.

The aim of this study was to develop artificial neural network (ANN) models to predict floods in the Branco River, Amazon basin. The input data for the models included the river levels and the average rainfall within the drainage area of the basin, which was estimated from the remotely sensed rainfall product PDIRnow. The hourly water level data used in the study were recorded by fluviometric telemetric stations belonging to the National Agency of Water. The multilayer perceptron was used as the neural framework of the ANNs, and the number of neurons in each layer of the model was determined via optimization with the SCE-UA algorithm. Most of the fitted ANN models showed Nash-Sutcliffe efficiency index values greater than 0.9. It is possible to conclude that the ANNs are effective for predicting the flood levels of the Branco River, with horizons of 6, 12 and 24h; thus, constituting a viable option for use in river-flood warning systems in the Amazon basin. For the forecast with a 24-h horizon, it is essential to include the average rainfall of the basin that accumulated over the last 48h as input data into the ANNs, along with the levels measured by the streamflow stations. The indirect rainfall estimates provided by PDIRnow are an excellent alternative as input data for ANN models used to predict floods and constitute a viable solution for regions where the density of rain gauge stations is low, as is the case in the Amazon basin.

Power Mechanism and Practical Path of Agricultural Insurance to Help Rural Revitalization

Abstract This paper firstly explores the power mechanism of agricultural insurance to help rural revitalization from three aspects of agriculture, farmers and rural three farmers, respectively, and constructs the rural revitalization development index system by combining the entropy power method. Then, the three-stage DEA model and the three-stage Malmquist index model are used to measure the efficiency of agricultural insurance boosting rural revitalization by combining the selected agricultural insurance boosting indicators. Finally, taking province A as an example, after descriptive statistical analysis, the method of this paper is combined with empirical analysis, and the practical path of agricultural insurance to help farmers is proposed from the three aspects of the insurance system, publicity as well and supply. The results show that after the optimization of agricultural insurance, the value of technical efficiency is distributed in [0.600, 0.738], the value of pure technical efficiency is distributed in [0.716, 0.826], and the value of scale efficiency is distributed in [0.738, 0.833] from 2010 to 2019. The mean value of the agricultural technical efficiency index in each city is 1.091, the mean value of the progress index is 1.033, and the mean value of total factor productivity is 1.029, which is an upward trending technology, and all of them have a growth rate of more than 5%. Based on this study, agricultural insurance can help improve the efficiency of rural revitalization.

РЕЗУЛЬТАТЫ И ЭФФЕКТИВНОСТЬ РАБОТЫ ГОСУДАРСТВЕННОГО СЕКТОРА В РЕГИОНАХ СЕВЕРО-ЗАПАДНОГО ФЕДЕРАЛЬНОГО ОКРУГА

Studies of the spatial aspect of the public sector efficiency are relevant for Russia because there is a tendency to increase the inequality in the development of Russian regions. For the subject of this study stand the results of public sector activities in the Russian economy in regional context and costs of achieving them. PSE (Public Sector Efficiency) was assessed for 85 regions of the Russian Federation for two periods: 2008–2014 and 2015–2021, and a spatial visualization of the obtained values of the public sector efficiency index is presented. The efficiency rating was headed by the Nenets and Chukotka Autonomous Okrugs, the cities of Moscow and St. Petersburg turned out to be the least effective. The production possibility frontier of the public sector of the subjects of the Russian Federation has been constructed. An in-depth analysis of the results and efficiency of the public sector in the Northwestern Federal District was carried out, and practical recommendations for their increase were presented. A large interregional differentiation in the public sector efficiency in the NWFD has been revealed. The advantage of the NWFD regions was noted in almost all areas of public sector activity, especially in Environment and Economic Development, with a small lag in the Security block.

The energy efficiency and environmental analysis of open-type commercial display cabinet with a multi-flow air curtain design

Open vertical display case refrigerators are often preferred as commercial refrigerators. This is because, despite their high energy consumption they have a higher marketing potential with the product display and offer easy access. Commercial refrigeration system accounts for half of the energy consumption in supermarkets. Air curtains of different designs are used in open vertical cabinets to reduce heat and mass transfer between the cooled air and the indoor environment. Hence, an experimental study was conducted to evaluate the multi-flow designed air curtain effects on the energy efficiencies of open display case-type commercial refrigerators. The experiments were conducted with ISO 23953:2005 standard in a controlled test room. During the trials, four different temperatures of air flowed to the refrigerator: +25 °C, +11 °C, +2°C, and 0 °C respectively through the air curtains. As a result of the experiments, a higher Coefficient of Performance COP value and lower Energy Efficiency Index (EEI) value were obtained with multi-flow air curtains. The multi-flow designed air curtain has nearly 40 % eliminated the air entrained from the outside to the indoor environment. It has ensured that the interior temperature values remain at the desired level. The second polyurethane body has reduced heat transfer through the surface by about 30 %, thereby reducing cooling load and energy consumption.

Assessing Mediterranean agroforestry systems: Agro-economic impacts of olive wild asparagus in central Italy

The intensification of Mediterranean farming systems has adversely affected the environment. As a result, climate change, soil and land degradation, and biodiversity loss have been exacerbated. A potential solution for addressing these challenges and enhancing farm sustainability is diversification, such as implementing agroforestry systems. Specific indicators are commonly used to evaluate the potential of diversification practices. However, agreement on a common set of assessment indicators is rarely reached. Moreover, the different biophysical and socio-economic conditions between regions make it difficult to adopt practices based on standardized assessments. This study aims at developing a practical methodology to assess the sustainability of Mediterranean agroforestry systems, using a three-dimensional evaluation concept for agro-environmental, economic and social performances. The steps in this study were, (i) define a set of relevant indicators and selection criteria, (ii) validate and select indicators through a participatory approach and (iii) apply the indicators to assess the performance of olive-wild asparagus agroforestry systems in central Italy. Expert opinions and stakeholders’ participation were found to play an important role in identifying relevant indicators for assessing farming systems. The results showed that intercropping wild asparagus within olive orchards provides agro-environmental benefits and economic profitability, but also causes a higher workload. With a land equivalent ratio above one, the agroforestry system is more productive and results in a 50% higher income than olive sole cropping. With similar management practices, both systems had a comparable energy use efficiency and pesticide load index value. However, the annual workload, during the full production phase, increases by 75% in the agroforestry system mainly due to manual labor required for asparagus harvest. Furthermore, the agroforestry system had better economic resilience (positive net present value) in the face of drops in crop prices and rising production costs by up to 15%, whereas olive sole cropping generated negative net present value if costs increased by 10% or prices fell by 5%.

Mitigating Water Shortage via Hydrological Modeling in Old and New Cultivated Lands West of the Nile in Egypt

Middle East and North Africa (MENA) regions are increasingly concerned about water scarcity. Egypt, one of the arid MENA nations that relies primarily on Nile water, faces a water scarcity issue because of a mismatch between demand and supply. This study presents an integrated executive system for managing water resources in two regions of Egypt that have traits with many MENA regions facing water scarcities. Hydrological modeling is required for the modeling of water resources, and model calibration procedures should be implemented to compare the simulated values to the observed and measured values to minimize model errors. The Water Evaluation and Planning (WEAP) model was used in this study to simulate the network systems of Egypt’s Minia Governorate on the western bank of the Nile’s narrow valley and Nubariya in the West Nile Delta, the lower reaches of the Nile. Using field data and experience, as well as other inputs, geographic information system (GIS) software digitized streams using satellite-interpreted data. The models were run, calibrated, and validated. The main calibration objective was to reduce the discrepancy between the actual and modeled flows as much as possible. Nash–Sutcliffe efficiency (NSE), percentage BIAS (PBIAS), volumetric efficiency (VE), and agreement index (d) values were calculated for three calibration cases. For anticipating water shortages until 2050, two scenarios were examined: (1) climate change scenarios based on historical climatic data from 1960 to 1990 and from 1991 to 2020, which led to a prediction scenario (2021–2050) of increasing temperature in the areas leading to evapotranspiration (ET) increases of 5.42% and 5.13% and (2) canal lining scenarios, which found a flow saving in the areas, showing that we can overcome the anticipated water shortage progress if canal lengths are rehabilitated by 10% and 25% in Minia and Nubariya.

A Cost-Driven Method for Deep-Learning-Based Hardware Trojan Detection.

The Cyber-Physical System and even the Metaverse will become the second space in which human beings live. While bringing convenience to human beings, it also brings many security threats. These threats may come from software or hardware. There has been a lot of research on managing malware, and there are many mature commercial products, such as antivirus software, firewalls, etc. In stark contrast, the research community on governing malicious hardware is still in its infancy. Chips are the core component of hardware, and hardware Trojans are the primary and complex security issue faced by chips. Detection of hardware Trojans is the first step for dealing with malicious circuits. Due to the limitation of the golden chip and the computational consumption, the existing traditional detection methods are not applicable to very large-scale integration. The performances of traditional machine-learning-based methods depend on the accuracy of the multi-feature representation, and most of the methods may lead to instability because of the difficulty of extracting features manually. In this paper, employing deep learning, a multiscale detection model for automatic feature extraction is proposed. The model is called MHTtext and provides two strategies to balance the accuracy and computational consumption. After selecting a strategy according to the actual situations and requirements, the MHTtext generates the corresponding path sentences from the netlist and employs TextCNN for identification. Further, it can also obtain non-repeated hardware Trojan component information to improve its stability performance. Moreover, a new evaluation metric is established to intuitively measure the model's effectiveness and balance: the stabilization efficiency index (SEI). In the experimental results for the benchmark netlists, the average accuracy (ACC) in the TextCNN of the global strategy is as high as 99.26%, and one of its stabilization efficiency index values ranks first with a score of 71.21 in all comparison classifiers. The local strategy also achieved an excellent effect, according to the SEI. The results show that the proposed MHTtext model has high stability, flexibility, and accuracy, in general.

Factorial Design for the Optimization of Clindamycin HCl-Loaded Ethosome with various concentrations of Phospholipon 90g and Ethanol

Clindamycin HCl is a drug for the treatment of acne. Clindamycin can act as an anti-acne by interfering with bacterial protein synthesis. The concentration of clindamycin used in the treatment of acne is 1%. Still, the bioavailability of the drug in the serum only reaches 0.7 – 12.4% of the total active substance in the preparation, so it is necessary to develop preparations that can increase the bioavailability of the drug Clindamycin HCl, one of which is in the form of ethosomes. This study aimed to optimize the clindamycin HCl loaded ethosomes formula with variations in the concentration of Phospholipon 90G and ethanol using the 22 factorial design method to obtain four formulas. The concentrations of phospholipon 90G used were 2% and 4%, while ethanol was 20% and 40%, respectively. Ethosomes were prepared using the thin layer hydration method and characterized by percent entrapment efficiency (%EE), particle size, and polydispersity index to determine the optimum formula. Based on the factorial design analysis results, the concentration of Phosholipon 90G, ethanol, and their two interactions significantly affected the value of entrapment efficiency, particle size, and polydispersity index with p<0.05. The optimum formula was obtained using 2% phospolipon 90G and 40% ethanol with an entrapment efficiency of 98.31±0.06, a particle size of 179.6±8.6nm, and a polydispersity index of 0.361±0.015. The optimum formula also showed good solubility in distilled water and acid solvents and good physical stability.

Validation of the precipitation data (1981-2016) of the PISCO v2.1 product: Meteorological station, elevation, seasonality of the year, and climatic region in the Tumbes basin, Peru

The scarce information that is counted and its importance in hydrological studies helps us to understand, simulate, and predict the events associated with the behavior of water. I think it is necessary to check the gridded data PISCOpm V.2.1 monthly rainfall with the observations in our Tumbes basin. For this, a comparative study was carried out between the observed and estimated values, concerning the weather station, elevation, seasonality of the year, and climatic region. Indicators such as the Coefficient of Determination(R2), Nash-Sutcliffe Efficiency Index (NS), and Percentage Statistical Bias (PBIAS%) were considered. At the monthly level, good correlation results were obtained, with values greater than 0,61, in the Nash - Sutcliffe efficiency index values greater than 0,60 and a minimum variation in the Percentage Statistical Bias. Regarding the elevation of the basin, data were obtained with a minimum adjustment in all the indicators. For the seasonal arrangement, summer presents the best average fit, followed by fall and spring. Winter presents a very good adjustment for 4 out of 9. Finally, of the 3 climatic regions, the D(i)A' region presents the best adjustment in the 3 indicators. It was possible to verify the adjustment of the data, having different results according to the evaluated criterion. This supports the use of observed data and its usefulness for studies in the Tumbes basin such as floods, droughts, hydrological and hydraulic modeling, completion of missing data, etc. Based on the results, studies of water availability, analysis of extreme events, etc. can be carried out.

The trade-off between health system resiliency and efficiency: evidence from COVID-19 in European regions

The objective of this paper was to investigate the existence of a trade-off between health system resilience and the economic efficiency of the health system, using data for 173 regions in the European Union and the European Free Trade Association countries. Data Envelopment Analysis was used to measure the efficiency of regional health systems before the COVID-19 pandemic. Then, a spatial econometrics model was used to estimate whether this measure of efficiency, adjusted for several covariates, has a significant impact on regional health system resilience during the COVID-19 pandemic, measured by the number of COVID-19 deaths per hundred thousand inhabitants. The results show that COVID-19 death rates were significantly higher in regions with higher population density, higher share of employment in industry, and higher share of women in the population. Results also show that regions with higher values of the health system efficiency index in 2017 had significantly higher rates of COVID-19 deaths in 2020 and 2021, suggesting the existence of a trade-off between health system efficiency and health system resilience during the COVID-19 pandemic.

Investigation of the effects of fan control technique on energy consumption in industrial refrigerated display cabinet: An experimental study

With the increase in electricity consumption and price, energy efficiency in industrial refrigeration systems becomes an even more important issue. The performance of the industrial refrigeration system can be reported by creating energy labeling according to the energy efficiency index value. In this study, the industrial refrigeration system was evaluated in terms of energy performance with proposed a fan control technique and performed an environmentally friendly design using propane (R290) refrigerant. In addition, a new control process was developed for the management of evaporator and condenser fans, and the effect of this process on the cooled package temperatures and energy consumption was investigated. With this new technique, a 25.2% improvement was achieved in the total energy consumption of the industrial refrigeration system. It was observed that the cooled package temperatures were between −1 and +5°C throughout the experiment. The EEI value of the industrial refrigeration system has increased from class “E” to class “D” using a new control technique.

Evaluation of the use of diesel-biodiesel-hexanol fuel blends in diesel engines with exergy analysis and sustainability index

The present research examined the usability of diesel-biodiesel and diesel-biodiesel-hexanol fuel blends as an alternative to diesel fuel in a compression ignition engine. Energy and exergy analyses were conducted using the data obtained from the engine tests. In addition, the sustainability index was calculated. When selecting the most suitable fuel for diesel fuel, thermal and exergy efficiency and sustainability index values ​​were compared. The obtained results revealed that the most suitable alternative fuel for diesel fuel was the diesel-biodiesel binary fuel blend. In this fuel blend, thermal efficiency, exergy efficiency, and sustainability index values ​​are 3.8, 5.18, and 1.44 % higher, respectively, compared to pure diesel fuel at an engine load of 100 %. As the alcohol ratio increases in diesel-biodiesel-hexanol ternary blends, the sustainability index value decreases compared to diesel fuel. As the hexanol ratio increases in fuel blends, the sustainability index decreases. The highest sustainability index for ternary fuel blends is 1.26 at 100 % engine load in B45H10 fuel. The increase in engine load increases the sustainability index and exergy efficiency in all fuel blends.

Developing meta-heuristic optimization based ensemble machine learning algorithms for hydraulic efficiency assessment of storm water grate inlets

ABSTRACT This research explored the performance comparison of machine learning algorithms, i.e. random forest (RF) and Adaboost, each coupled with the genetic algorithm (GA) and particle swarm optimization (PSO), in intercepted discharge calculations. Thus, six different storm water grate inlets were evaluated through laboratory experiments, and the acquired data was used to construct the integrated prediction framework. Consequently, the RF-based models outperformed the models constructed with Adaboost. Overall, the PSO-RF was found as the best strategy with Nash-Sutcliffe Efficiency index and determination coefficient values of 0.8896 and 0.8990, respectively. In addition, the game-theoretical SHAP analysis demonstrated that the approach flow depth is the most influential variable for hydraulic efficiency evaluations, followed by the grate inlet width and transversal slope of the road. This study further concluded that the lower the grate inlet width, the lower the intercepted discharge capacity, while the increase in transversal slope results in an increase in hydraulic efficiency.

Numerical Investigation of Heat Transfer Characteristics of Pin-Fins with Roughed Endwalls in Gas Turbine Blade Internal Cooling Channels

In modern jet engines, the effective cooling structure design is essential to both increase turbine efficiency and, in the meantime, maintain structural integrality. Pin-fin arrays play a crucial role in the cooling mechanism of the turbine blade internal cooling system. In the context of investigating the efficiency of cooling techniques using pin-fins, while the other studies focus on the pin-fin configurations, the current study is a step towards optimizing cooling cascade endwalls for better maneuver and reservation of vortices which lead to higher heat transfer near the endwalls. This study presents the results from the investigations of the flow-field and heat transfer characteristics of the pin-fin arrays with roughed endwalls, i.e., recessed endwalls and extruded endwalls types. The heat transfer and pressure drop characteristics of the channel are numerically examined to compare with those of the flat endwalls case within a range of inlet Reynolds number, which varies from 7400 to 36000. Both the leading and trailing sides of the channel are divided into five regions in the streamwise direction to understand further the heat transfer capacity of the pin-fins and the endwalls. The results show that, with these new endwall configurations, the high heat transfer regions near the pin-fins are remarkably enlarged compared to the flat endwalls. And in the meantime, both the new endwall arrangements enhance the heat transfer capacity of the channel near the pin-fins. The two new designs outperform the baseline case, with the heat transfer efficiency index (HTEI) improved by 37.8% for the recessed endwalls and 15.9% for the extruded endwalls. By varying the height of the indentation and the protrusion, it is found that, with smaller heights, both configurations produce a much lower friction factor. However, with much higher heat transfer capacity, leading to relatively higher values of heat transfer efficiency index (HTEI), up to 77.7% and 41.5% of the recessed and extruded endwalls are higher than HTEI of the channel with flat endwalls. These results indicate the great potential for improving the heat transfer capability of pin-fins by optimizing endwall configurations.

Technical efficiency of beef cattle production in the regency of Minahasa Tenggara, province of North Sulawesi, Indonesia

A fattening cultivation of beef cattle in the Province of North Sulawesi is managed by the backyard farming, characterized by a lower productivity, small-scaled business, and traditional management. This type of business has become priority to satisfy the need of beef consumption. Then, the objective of this research is to analyze the extent of technical efficiency of beef cattle fattening. In detail, data collection was conducted in both Districts of Belang and Tombatu Timur, Regency of Minahasa Tenggara on January-February 2022. Two villages of the respective District were selected purposively as the sampling village. Additionally, the research used primary data, obtained from 60 farmers and selected by purposive sampling method. The data, then, was analyzed using the production function of the Stochastic frontier. In sum up, the results of analysis demonstrate that the fattening industry of beef cattle was feasible to perform, but the output of technical efficiency of beef cattle industry was still low, by its average of efficiency index value of 0.670. Meanwhile, the determining factors of beef cattle production were labor, green feed, and weight of feeder cattle. The access, therefore, to information sources, such as technical training and access to the improvement of total beef by capital increasing, is necessary to be developed.

Developing Intensity-Duration-Frequency (IDF) Curves Based on Rainfall Cumulative Distribution Frequency (CDF) for Can Tho City, Vietnam

Information on the relationship between rainfall intensity, duration and accumulation frequency or return period (IDF) is commonly utilized in the design and management of urban drainage systems. Can Tho City, located in the Vietnamese Mekong Delta, is a city which has recently invested heavily in upgrading its stormwater drainage systems in the hope of preventing reoccurring flood events. Yet, much of these works were designed based on obsolete and outdated IDF rainfall curves. This paper presents an updated IDF curve for design rainfall for Can Tho City. For each duration and designated return period, a cumulative distribution function (CDF) was developed using the Pearson III, Log-Pearson III, and Log-Normal distribution functions. In order to choose the best IDF rainfall curve for Can Tho City, the CDF rainfall curve and empirical formulas used in Vietnam and Asia (Vietnamese standard 7957:2008, Department of Hydrology, Ministry of Transportation, Talbot, Kimijima, and Bermard) were compared. The goodness of fit between the IDF relationship generated by the frequency analysis (CDF curve), and that predicted by the IDF empirical formulas was assessed using the efficiency index (EI), and the root mean squared error (RMSE). The IDF built from Vietnam’s standard TCVN 7957:2008 with new parameters (A = 9594, C = 0.5, b = 26, n = 0.96) showed the best performance, with the highest values of EI (0.84 ≤EI≤ 0.93) and the lowest values of RMSE (2.5 ≤RMSE≤ 3.2), when compared to the other remnants.