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1
Selim, Abdelfattah, Ameer Megahed, Sahar Kandeel, Abdullah D. Alanazi, and Hamdan I. Almohammed. "Determination of Seroprevalence of Contagious Caprine Pleuropneumonia and Associated Risk Factors in Goats and Sheep Using Classification and Regression Tree." Animals 11, no. 4 (April 19, 2021): 1165. http://dx.doi.org/10.3390/ani11041165.
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Classification and Regression Tree (CART) analysis is a potentially powerful tool for identifying risk factors associated with contagious caprine pleuropneumonia (CCPP) and the important interactions between them. Our objective was therefore to determine the seroprevalence and identify the risk factors associated with CCPP using CART data mining modeling in the most densely sheep- and goat-populated governorates. A cross-sectional study was conducted on 620 animals (390 sheep, 230 goats) distributed over four governorates in the Nile Delta of Egypt in 2019. The randomly selected sheep and goats from different geographical study areas were serologically tested for CCPP, and the animals’ information was obtained from flock men and farm owners. Six variables (geographic location, species, flock size, age, gender, and communal feeding and watering) were used for risk analysis. Multiple stepwise logistic regression and CART modeling were used for data analysis. A total of 124 (20%) serum samples were serologically positive for CCPP. The highest prevalence of CCPP was between aged animals (>4 y; 48.7%) raised in a flock size ≥200 (100%) having communal feeding and watering (28.2%). Based on logistic regression modeling (area under the curve, AUC = 0.89; 95% CI 0.86 to 0.91), communal feeding and watering showed the highest prevalence odds ratios (POR) of CCPP (POR = 3.7, 95% CI 1.9 to 7.3), followed by age (POR = 2.1, 95% CI 1.6 to 2.8) and flock size (POR = 1.1, 95% CI 1.0 to 1.2). However, higher-accuracy CART modeling (AUC = 0.92, 95% CI 0.90 to 0.95) showed that a flock size >100 animals is the most important risk factor (importance score = 8.9), followed by age >4 y (5.3) followed by communal feeding and watering (3.1). Our results strongly suggest that the CCPP is most likely to be found in animals raised in a flock size >100 animals and with age >4 y having communal feeding and watering. Additionally, sheep seem to have an important role in the CCPP epidemiology. The CART data mining modeling showed better accuracy than the traditional logistic regression.
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Kyotos, Kitoga Byalungwa, Jemimah Oduma, Raphael Githaiga Wahome, Catherine Kaluwa, Faduma Abdulahi Abdirahman, Angela Opondoh, Jeanette Nkatha Mbobua, et al. "Gendered Barriers and Opportunities for Women Smallholder Farmers in the Contagious Caprine Pleuropneumonia Vaccine Value Chain in Kenya." Animals 12, no. 8 (April 14, 2022): 1026. http://dx.doi.org/10.3390/ani12081026.
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Most rural women smallholder farmers in Kenya generate income from the sale of small ruminant animals. However, diseases such as Contagious Caprine Pleuropneumonia (CCPP) prevent them from optimizing earnings. A crucial aspect for the control of CCPP is vaccination. In Kenya, CCPP vaccines are distributed through a government delivery mechanism. This study examines gaps and barriers that prevent women smallholder farmers from accessing CCPP vaccines. Qualitative data collection tools used were focus groups discussions, focus meals, jar voices and key informant interviews. Using outcome mapping (OM) methodology, critical partners and stakeholders in the CCPP vaccine value chain (CCPP-VVC) were identified to be the manufacturers, importers, distributors, agrovets, public and private veterinarians, local leaders, and farmers. Respondents highlighted the barriers to be limited access to vaccines due to cold chain problems, inadequate and late delivery of services, lack of information and training on vaccines, and financial constraints. Identified opportunities that can support women’s engagement in the CCPP-VVC are the Kenya Governments two-third gender rule, which requires that not more than two thirds of the members of elective or appointive bodies shall be of the same gender, and positive community perception of female veterinarians. We conclude that more resources and training should be made available to women farmers, and that gender perspectives on policy development related to livestock production and disease prevention are urgently needed to improve livestock productivity and increase agency for women.
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Rosas-Sánchez, Gustavo Armando, Zorba Josué Hernández-Estrada, Mirna Leonor Suárez-Quiroz, Oscar González-Ríos, and Patricia Rayas-Duarte. "Coffee Cherry Pulp by-Product as a Potential Fiber Source for Bread Production: A Fundamental and Empirical Rheological Approach." Foods 10, no. 4 (April 1, 2021): 742. http://dx.doi.org/10.3390/foods10040742.
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Effects of substituting of wheat flour with coffee cherry pulp powder (CCPP) (coffee by-product as fiber source) at 0, 1.2, 2.3, and 4.7% dry basis (0, 1.25, 2.5, and 5% wet basis) on dough and gluten rheological properties and baking quality were investigated. Rheological properties were analyzed during mixing, compression recovery, and creep-recovery. A rheological approach was adopted to study the viscoelasticity of dough enriched with fiber. The data obtained were analyzed with the Kelvin–Voigt model and the parameters were correlated to bread volume and crumb firmness to assess the effect of incorporating CCPP. A decrease in gluten’s elastic properties was attributed to the water-binding and gelling properties of CCPP. Stiffness of dough and crumb firmness increased as the level of CCPP increased and bread volume decreased. Stiffer dough corresponded with lower compliance values and higher steady state viscosity compared to the control. A follow-up study with 5% CCPP and additives is recommended to overcome the reduction in elastic recovery and bread volume.
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Zhu, Shun-Ye, Min-Lian Du, and Ting-Ting Huang. "An Analysis of Predictive Factors for the Conversion from Premature Thelarche into Complete Central Precocious Puberty." Journal of Pediatric Endocrinology and Metabolism 21, no. 6 (June 1, 2008): 533–38. http://dx.doi.org/10.1515/jpem-2008-210607.
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Abstract Aim: To determine the predictive factors for the conversion of premature thelarche (PT) into complete central precocious puberty (CCPP) in girls. Design: Prospective. Methods: One hundred and fifty-one girls with PT referred consecutively for evaluation of clinical, laboratory, and ultrasound data. Results: Twenty-one and a half percent of girls with PT converted into CCPP at a chronological age of 7.1 ± 0.7 years and bone age of 9.0 ± 1.1 years. Using logistic regression analysis, longitudinal diameter of uterus (OR = 1.215), Tanner breast stage at the time of first physical examination (OR = 3.334) 'and regression of breast development (OR= 3.921) were the most significant variables predicting the conversion from PT into CCPP. Compared with the nonconverted group, the converted groups had larger breast size at the time of diagnosis (z = 2.077, p = 0.038). A total of 69.5% (105/151) of patients experienced complete regression of breast development, 13.2% (14/105) of whom converted into CCPP; 21.5% (31/151) of patients had recurrent breast development, 32.3% (10/31) of whom converted into CCPP; 10% (15/151) of patients had constant breast development, 56.7% (7/15) of whom converted into CCPP, with the highest rate among the three breast development categories (x2 = 12.23, p = 0.002). Conclusion: PT is not often a self-limited condition and may sometimes convert into CCPP. The predictive factors for conversion were related to estrogen exposure including longitudinal diameter of the uterus, Tanner breast stage at the first consultation and the regressive categories of breast development.
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Arferiandi, Yondha Dwika, Wahyu Caesarendra, and Herry Nugraha. "Heat Rate Prediction of Combined Cycle Power Plant Using an Artificial Neural Network (ANN) Method." Sensors 21, no. 4 (February 3, 2021): 1022. http://dx.doi.org/10.3390/s21041022.
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Heat rate of a combined cycle power plant (CCPP) is a parameter that is typically used to assess how efficient a power plant is. In this paper, the CCPP heat rate was predicted using an artificial neural network (ANN) method to support maintenance people in monitoring the efficiency of the CCPP. The ANN method used fuel gas heat input (P1), CO2 percentage (P2), and power output (P3) as input parameters. Approximately 4322 actual operation data are generated from the digital control system (DCS) in a year. These data were used for ANN training and prediction. Seven parameter variations were developed to find the best parameter variation to predict heat rate. The model with one input parameter predicted heat rate with regression R2 values of 0.925, 0.005, and 0.995 for P1, P2, and P3. Combining two parameters as inputs increased accuracy with regression R2 values of 0.970, 0.994, and 0.984 for P1 + P2, P1 + P3, and P2 + P3, respectively. The ANN model that utilized three parameters as input data had the best prediction heat rate data with a regression R2 value of 0.995.
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Afzal, Asif, Saad Alshahrani, Abdulrahman Alrobaian, Abdulrajak Buradi, and Sher Afghan Khan. "Power Plant Energy Predictions Based on Thermal Factors Using Ridge and Support Vector Regressor Algorithms." Energies 14, no. 21 (November 3, 2021): 7254. http://dx.doi.org/10.3390/en14217254.
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This work aims to model the combined cycle power plant (CCPP) using different algorithms. The algorithms used are Ridge, Linear regressor (LR), and upport vector regressor (SVR). The CCPP energy output data collected as a factor of thermal input variables, mainly exhaust vacuum, ambient temperature, relative humidity, and ambient pressure. Initially, the Ridge algorithm-based modeling is performed in detail, and then SVR-based LR, named as SVR (LR), SVR-based radial basis function—SVR (RBF), and SVR-based polynomial regression—SVR (Poly.) algorithms, are applied. Mean absolute error (MAE), R-squared (R2), median absolute error (MeAE), mean absolute percentage error (MAPE), and mean Poisson deviance (MPD) are assessed after their training and testing of each algorithm. From the modeling of energy output data, it is seen that SVR (RBF) is the most suitable in providing very close predictions compared to other algorithms. SVR (RBF) training R2 obtained is 0.98 while all others were 0.9–0.92. The testing predictions made by SVR (RBF), Ridge, and RidgeCV are nearly the same, i.e., R2 is 0.92. It is concluded that these algorithms are suitable for predicting sensitive output energy data of a CCPP depending on thermal input variables.
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Mohamed Abdi, Omar. "Sero-Prevalence of Contagious Caprine Pleuropneumonia in Goats in Afgoye District Lower Shabelle Region, Somalia." Open Access Journal of Veterinary Science & Research 5, no. 2 (2020): 1–4. http://dx.doi.org/10.23880/oajvsr-16000203.
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Background: Contagious caprine pleuropneumonia (CCPP), caused by Mycoplasma capricolum subsp. Capripneumoniae (Mccp), is one of the most important goat diseases causing high morbidity and mortality, these results in heavy economic losses to countries like Somalia, which is a country affected the civil war of the 1990s. Objective: Generally, the disease presence has been reported in the country. However, there is no quantitative data on the prevalence and distribution of the disease has been scientifically reported in the country. Methods: A cross-sectional study was conducted from September 2019 to June 2020 in three villages of Afgoye district of Somalia to assess the seroprevalence and identify the associated risk factors for the occurrence of the CCPP. The risk factors considered included sex, age, and locations. Results: A total of 100 blood samples were collected and evaluated by Capri-Latex Agglutination Test (Capri-LAT). A total of 49/100 (49%, CI 95%: (38.86%-59.2%) goats were seropositive for anti-CCPP antibody. The epidemiological risk factors considered, sex, age and locations, were not significantly associated with the CCPP sero prevalence (p>0.05). However, the sero positivity was slightly higher in female (51%, 95% CI: 39.8-62.6), >3 years old goats (86.3%, 95% CI: 48.9-87.4) and Markazka village (56%, 95% CI: 41.3-70.0) compared to male (40%, 95% CI: 19.1-63.9), 1-3 years old (57.5%, 95% CI: 40.9- 73.0), and Shareeco (43.8%, 95% CI: 19.8-70.1) and Siinka (41.2%, 95% CI: 24.7-59.3) villages, respectively. Conclusion: The present study indicates the prevalence of CCPP in the studies areas and this requires practicable measures to be put in place towards the control of the disease.
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He, Dakuo, Zhengsong Wang, Le Yang, and Zhizhong Mao. "Optimization Control of the Color-Coating Production Process for Model Uncertainty." Computational Intelligence and Neuroscience 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/9731823.
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Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results.
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Yi, Qiu, Hanqing Xiong, and Denghui Wang. "Predicting Power Generation from a Combined Cycle Power Plant Using Transformer Encoders with DNN." Electronics 12, no. 11 (May 27, 2023): 2431. http://dx.doi.org/10.3390/electronics12112431.
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With the development of the Smart Grid, accurate prediction of power generation is becoming an increasingly crucial task. The primary goal of this research is to create an efficient and reliable forecasting model to estimate the full-load power generation of a combined-cycle power plant (CCPP). The dataset used in this research is a subset of the publicly available UCI Machine Learning Repository. It contains 9568 items of data collected from a CCPP during its full load operation over a span of six years. To enhance the accuracy of power generation forecasting, a novel forecasting method based on Transformer encoders with deep neural networks (DNN) was proposed. The proposed model exploits the ability of the Transformer encoder to extract valuable information. Furthermore, bottleneck DNN blocks and residual connections are used in the DNN component. In this study, a series of experiments were conducted, and the performance of the proposed model was evaluated against other state-of-the-art machine learning models based on the CCPP dataset. The experimental results illustrated that using Transformer encoders along with DNN can considerably improve the accuracy of predicting CCPPs power generation (RMSE = 3.5370, MAE = 2.4033, MAPE = 0.5307%, and R2 = 0.9555).
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Utami, Louise Indah, Ika Yuliyani, Yanti Suprianti, and Purwinda Iriani. "Load optimization on the performance of combined cycle power plant Block 4 PT Indonesia Power Priok POMU." Journal of Mechatronics, Electrical Power, and Vehicular Technology 13, no. 1 (July 29, 2022): 24–35. http://dx.doi.org/10.14203/j.mev.2022.v13.24-35.
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Combined cycle power plant (CCPP) is a closed-cycle power plant, where the heat from the gas turbine’s (GT) exhaust gas will be streamed to the heat recovery steam generator (HRSG) to be utilized by steam turbine (ST). CCPP Block 4 (Jawa-2) PT Indonesia Power Priok POMU has an installed capacity of 880 MW, consists of 2 GT units (301.5 MW each) and 1 ST unit (307.5 MW). The performance of a power plant depends on its load, as the efficiency of the turbine generator is low when operated at low loads. The data as of July 2019 showed that 2.2.1 (2 GT, 2 HRSG, 1 ST) configuration has been used in three conditions where the CC net load was around 30 - 45 %, which in fact could be compensated by the 1.1.1 (1 GT, 1 HRSG, 1 ST) configuration. This resulted in a decrease of the CC net efficiency up to 21.34 %. The optimization that can be done is to change the load configuration from 2.2.1 to 1.1.1 at 0 - 50 % of CC net load through simulations, by including the influence of the GT and HRSG start-up processes. The result of this optimization is that the CCPP performance increases due to higher performance of each turbine generator. Thus, the optimization results during July 2019 provided energy saving of 1,146.09 MMBTU or equivalent to cost saving of IDR 152,249,551.76.
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Khajehpour, Hossein, Nima Norouzi, and Maryam Fani. "An Exergetic Model for the Ambient Air Temperature Impacts on the Combined Power Plants and its Management Using the Genetic Algorithm." International Journal of Air-Conditioning and Refrigeration 29, no. 01 (February 26, 2021): 2150008. http://dx.doi.org/10.1142/s2010132521500085.
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4E analysis is used on a Brayton–Rankine combined cycle power plant (CCPP) with a dual pressure heat recovery steam generation (HRSG) system. A multi-objective genetic-based evolutionary optimization has been used to estimate the most optimal exergy efficiency status, exergy cost reduction, carbon emission reduction, and NOx emission reduction. For the validation of the data, the simulation results are compared with the plant’s data. This study investigates the effect of every decisive parameter on the objective performance parameters of the CCPP. The primary estimated results are the emission rates, efficiencies, and the exergoeconomic cost of the system. At the optimum operational state, the exergy efficiency may increase by 10%, while the total emissions may decrease by 14.6%. The conventional technical measures’ effectiveness to improve the combined cycle power plant’s energy performance is applied to the simulated case study. Results have shown that the main source of the exergy destruction in this system is the HRSG and the combustion chamber, and also the overall performance of the plant shows great sensitivity to the ambient air temperature. This fact has shown that climate change and global warming are effective in thermal power plants’ performance. Therefore, the effect of the climate change on the ambient air temperature impact on the power plant and the 4E performance of the simulated combined cycle power plant is also studied. The results show that, due to the global warming effect, the exergy efficiency of the CCPP unit is decreased by over 0.2% in the last two decades, which can be generalized to all thermal electricity generation units throughout the world based on the mean global temperature rise in the last decades.
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Santarisi, Nader S., and Sinan S. Faouri. "Prediction of combined cycle power plant electrical output power using machine learning regression algorithms." Eastern-European Journal of Enterprise Technologies 6, no. 8 (114) (December 24, 2021): 16–26. http://dx.doi.org/10.15587/1729-4061.2021.245663.
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In order to monitor the performance and related efficiency of a combined cycle power plant (CCPP), in addition to the best utilization of its power output, it is vital to predict its full load electrical power output. In this paper, the full load electrical power output of CCPP was predicted employing practically efficient machine learning algorithms, including linear regression, ridge regression, lasso regression, elastic net regression, random forest regression, and gradient boost regression. The original data came from an actual confidential power plant, which was working on a full load for 6 years, with four major features: ambient temperature, relative humidity, atmospheric pressure, and exhaust vacuum, and one target (electrical power output per hour). Different regression performance measures were used, including R2 (coefficient of determination), MAE (Mean Absolute Error), MSE (Mean Squared Error), RMSE (Root Mean Squared Error), and MAPE (Mean Absolute Percentage Error). Research results revealed that the gradient boost regression model outperformed other models with and without using the dimensionality reduction technique (PCA) with the highest R2 of 0.912 and 0.872, respectively, and had the lowest MAPE of 0.872 % and 1.039 %, respectively. Moreover, prediction performance dropped slightly after using the dimensionality reduction technique almost in all regression algorithms used. The novelty in this work is summarized in predicting electrical power output in a CCPP based on a few features using simpler algorithms than reported deep learning and neural networks algorithms combined. That means a lower cost and less complicated procedure as per each, however, resulting in practically accepted results according to the evaluation metrics used.
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Tsolas, Ioannis E. "Benchmarking Engineering, Procurement and Construction (EPC) Power Plant Projects by Means of Series Two-Stage DEA." Electricity 1, no. 1 (May 4, 2020): 1–11. http://dx.doi.org/10.3390/electricity1010001.
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A lot of companies in the power sector use Engineering, Procurement, and Construction (EPC) contracts for complex infrastructure projects such as power plants. This paper presents a series two-stage data envelopment analysis (DEA) approach for the ex ante benchmarking of EPC power plant projects. The current study aims to improve over single-stage DEA and evaluate the efficiency of a group of twelve domestic (located in Greece) and international natural gas-fired power plant projects of different technologies (combined cycle power plant (CCPP) projects with single and multi-shaft configuration, and open cycle power plant (OCPP) projects) by employing a series two-stage DEA model. In the first stage, performance of the EPC mode is evaluated, whereas in the second stage the plant annual operational efficiency is assessed. In the light of the results, there is a lower level of performance in the EPC mode than in operating efficiency. The OCPP projects have the best operating efficiency, whereas they are ranked in-between the CCPP projects with single and multi-shaft configuration in EPC mode performance.
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Bany Ata, Ammar, Peter Maximilian Seufert, Christian Heinze, Falah Alobaid, and Bernd Epple. "Optimization of Integrated Gasification Combined-Cycle Power Plant for Polygeneration of Power and Chemicals." Energies 14, no. 21 (November 3, 2021): 7285. http://dx.doi.org/10.3390/en14217285.
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Efficient and flexible operation is essential for competitiveness in the energy market. However, the CO2 emissions of conventional power plants have become an increasingly significant environmental dilemma. In this study, the optimization of a steam power process of an IGCC was carried out, which improved the overall performance of the plant. CCPP with a subcritical HRSG was modelled using EBSILON Professional. The numerical results of the model were validated by measurements for three different load cases (100, 80, and 60%). The results are in agreement with the measured data, with deviations of less than 5% for each case. Based on the model validation, the model was modified for the use of syngas as feed and the integration of heat into an IGCC process. The integration was optimized with respect to the performance of the CCPP by varying the extraction points, adjusting the steam parameters of the extractions and modifying the steam cycle. For the 100% load case, a steam turbine power achieved increase of +34.2%. Finally, the optimized model was subjected to a sensitivity analysis to investigate the effects of varying the extraction mass flows on the output.
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Ramphal, S. R., and M. S. Sibiya. "Optimization of coagulation-flocculation parameters using a photometric dispersion analyser." Drinking Water Engineering and Science 7, no. 2 (July 23, 2014): 73–82. http://dx.doi.org/10.5194/dwes-7-73-2014.
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Abstract. The size and structural characteristics of floc particles are important design and control parameters in water treatment and should be rapidly monitored with a reasonable amount of accuracy. In this study, a photometric dispersion analyser (PDA) coupled to standard jar test experiments was used to optimize coagulation-flocculation parameters while monitoring floc size and structure as well as the rate of floc formation during coagulation using alum. The optimal coagulation conditions were as follows: sample pH 8; alum dosage, 3 mg L−1 as Al3+; G value, 172 s−1; rapid mixing time, 20 s. These conditions resulted in unstable treated water having a calcium carbonate precipitation potential (CCPP) of −15 mg L−1 as CaCO3 and required a slaked lime dosage of 17 mg L−1 as CaCO3 to equilibrate CCPP to acceptable levels. PDA data revealed that aggregation rate and steady-state variance are primary parameters as both have substantial influence on coagulation-flocculation efficiency. However, the average steady state ratio, although an important parameter, had a lessened impact on coagulation-flocculation efficiency. The results of this study showed that the PDA instrument is an important tool in coagulation kinetic studies and can be employed as an additional tool in the optimization of coagulation conditions.
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Pettersson, Bertil, Göran Bölske, François Thiaucourt, Mathias Uhlén, and Karl-Erik Johansson. "Molecular Evolution of Mycoplasma capricolum subsp. capripneumoniae Strains, Based on Polymorphisms in the 16S rRNA Genes." Journal of Bacteriology 180, no. 9 (May 1, 1998): 2350–58. http://dx.doi.org/10.1128/jb.180.9.2350-2358.1998.
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ABSTRACT Mycoplasma capricolum subsp.capripneumoniae belongs to the so-called Mycoplasma mycoides cluster and is the causal agent of contagious caprine pleuropneumonia (CCPP). All members of the M. mycoidescluster have two rRNA operons. The sequences of the 16S rRNA genes of both rRNA operons from 20 strains of M. capricolum subsp.capripneumoniae of different geographical origins in Africa and Asia were determined. Nucleotide differences which were present in only one of the two operons (polymorphisms) were detected in 24 positions. The polymorphisms were not randomly distributed in the 16S rRNA genes, and some of them were found in regions of low evolutionary variability. Interestingly, 11 polymorphisms were found in all theM. capricolum subsp. capripneumoniae strains, thus defining a putative ancestor. A sequence length difference between the 16S rRNA genes in a poly(A) region and 12 additional polymorphisms were found in only one or some of the strains. A phylogenetic tree was constructed by comparative analysis of the polymorphisms, and this tree revealed two distinct lines of descent. The nucleotide substitution rate of strains within line II was up to 50% higher than within line I. A tree was also constructed from individual operonal 16S rRNA sequences, and the sequences of the two operons were found to form two distinct clades. The topologies of both clades were strikingly similar, which supports the use of 16S rRNA sequence data from homologous operons for phylogenetic studies. The strain-specific polymorphism patterns of the 16S rRNA genes of M. capricolum subsp.capripneumoniae may be used as epidemiological markers for CCPP.
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Ji, Siyu, and Chenglin Wen. "Data Preprocessing Method and Fault Diagnosis Based on Evaluation Function of Information Contribution Degree." Journal of Control Science and Engineering 2018 (July 2, 2018): 1–10. http://dx.doi.org/10.1155/2018/6565737.
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Neural network is a data-driven algorithm; the process established by the network model requires a large amount of training data, resulting in a significant amount of time spent in parameter training of the model. However, the system modal update occurs from time to time. Prediction using the original model parameters will cause the output of the model to deviate greatly from the true value. Traditional methods such as gradient descent and least squares methods are all centralized, making it difficult to adaptively update model parameters according to system changes. Firstly, in order to adaptively update the network parameters, this paper introduces the evaluation function and gives a new method to evaluate the parameters of the function. The new method without changing other parameters of the model updates some parameters in the model in real time to ensure the accuracy of the model. Then, based on the evaluation function, the Mean Impact Value (MIV) algorithm is used to calculate the weight of the feature, and the weighted data is brought into the established fault diagnosis model for fault diagnosis. Finally, the validity of this algorithm is verified by the example of UCI-Combined Cycle Power Plant (UCI-ccpp) simulation of standard data set.
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March, John B., Jason Clark, and Malcolm Brodlie. "Characterization of Strains of Mycoplasma mycoidessubsp. mycoides Small Colony Type Isolated from Recent Outbreaks of Contagious Bovine Pleuropneumonia in Botswana and Tanzania: Evidence for a New Biotype." Journal of Clinical Microbiology 38, no. 4 (2000): 1419–25. http://dx.doi.org/10.1128/jcm.38.4.1419-1425.2000.
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Four strains of Mycoplasma mycoides subsp.mycoides small colony type (MmmSC) isolated from recent outbreaks of contagious bovine pleuropneumonia (CBPP) in Africa have been investigated. One Botswanan strain, M375, displayed numerous and significant phenotypic differences from both contemporary field isolates and older field and vaccine strains (African, Australian, and European strains dating back to 1936). Differences include altered morphology, reduced capsular polysaccharide production, high sensitivity to MmmSC rabbit hyperimmune antisera in vitro, and unique polymorphisms following immunoblotting. While insertion sequence analysis using IS1634 clearly indicates a close evolutionary relationship to west African strains, hybridization with IS1296 shows the absence of a band present in all other strains of MmmSC examined. The data suggest that a deletion has occurred in strain M375, which may explain its altered phenotype, including poor growth in vitro and a relative inability to cause septicemia in mice. These characteristics are also exhibited byMycoplasma capricolum subsp. capripneumoniae(causal agent of contagious caprine pleuropneumonia [CCPP]), against which M375 antiserum exhibited some activity in vitro (unique among the various MmmSC antisera tested). These findings may have evolutionary implications, since CCPP is believed to be lung specific and without a septicemic phase (unlike CBPP). Since M375 was isolated from a clinical case of CBPP, this novel biotype may be fairly widespread but not normally isolated due to difficulty of culture and/or a potentially altered disease syndrome. Bovine convalescent antisera (obtained from contemporary naturally infected cattle in Botswana) were active against strain M375 in an in vitro growth inhibition test but not against any other strains of MmmSC tested. There exists the possibility therefore, that strain M375 may possess a set of protective antigens different from those of other strains of MmmSC (including vaccine strains). These findings have implications for the control of the current CBPP epidemic in Africa.
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Gafar, Natasha A., and Kai G. Schulz. "A three-dimensional niche comparison of <i>Emiliania huxleyi</i> and <i>Gephyrocapsa oceanica</i>: reconciling observations with projections." Biogeosciences 15, no. 11 (June 15, 2018): 3541–60. http://dx.doi.org/10.5194/bg-15-3541-2018.
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Abstract. Coccolithophore responses to changes in carbonate chemistry speciation such as CO2 and H+ are highly modulated by light intensity and temperature. Here, we fit an analytical equation, accounting for simultaneous changes in carbonate chemistry speciation, light and temperature, to published and original data for Emiliania huxleyi, and compare the projections with those for Gephyrocapsa oceanica. Based on our analysis, the two most common bloom-forming species in present-day coccolithophore communities appear to be adapted for a similar fundamental light niche but slightly different ones for temperature and CO2, with E. huxleyi having a tolerance to lower temperatures and higher CO2 levels than G. oceanica. Based on growth rates, a dominance of E. huxleyi over G. oceanica is projected below temperatures of 22 ∘C at current atmospheric CO2 levels. This is similar to a global surface sediment compilation of E. huxleyi and G. oceanica coccolith abundances suggesting temperature-dependent dominance shifts. For a future Representative Concentration Pathway (RCP) 8.5 climate change scenario (1000 µatm fCO2), we project a CO2 driven niche contraction for G. oceanica to regions of even higher temperatures. However, the greater sensitivity of G. oceanica to increasing CO2 is partially mitigated by increasing temperatures. Finally, we compare satellite-derived particulate inorganic carbon estimates in the surface ocean with a recently proposed metric for potential coccolithophore success on the community level, i.e. the temperature-, light- and carbonate-chemistry-dependent CaCO3 production potential (CCPP). Based on E. huxleyi alone, as there was interestingly a better correlation than when in combination with G. oceanica, and excluding the Antarctic province from the analysis, we found a good correlation between CCPP and satellite-derived particulate inorganic carbon (PIC) with an R2 of 0.73, p < 0.01 and a slope of 1.03 for austral winter/boreal summer and an R2 of 0.85, p < 0.01 and a slope of 0.32 for austral summer/boreal winter.
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Kozlovsky, V. V., and A. B. Larin. "Methods of monitoring water conditions of the circulatory cooling system of a combined heat and power plant." Vestnik IGEU, no. 3 (2019): 14–21. http://dx.doi.org/10.17588/2072-2672.2019.3.014-021.
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A common method of preventing scale formation on the internal surfaces of the condenser and heat ex-changers at thermal power plants with circulatory cooling systems (CCS) is correctional treatment with an addition of sulfuric acid for acidifying make-up water and reducing its alkalinity and the alkalinity of recycled water and dosing of oxyethylidenediphosphonic acid (OEDFK) for preventing scale deposit formation. The existing method of correction treatment does not provide the necessary degree of heat exchange equipment protection from scale formation. With this method of cleaning, it is impossible to completely remove deposits from the surface of the tubes to «pure» metal; the concentration of sulfates in the purge water often exceeds the permissible level. Improving the efficiency of water conditions requires developing a calculation method and creating a pilot plant for monitoring scale formation and corrosion through estimation of water chemistry directly in industrial conditions, which is the goal of this work. The circulating water corrosivity was studied on a stand that simulates the operation of circulatory cooling systems. The coil simulating water movement inside heat exchangers contained carbon steel and brass corrosion rate witness plates. A quantitative assessment of the biological contamination of the circulating water of the cooling system of the CCPP ПГУ-450 MW was carried out using total bacterial count (TBC) express tests. To estimate the probability of carbonate salt deposition in heat exchange equipment, we have proposed a method of calculating the existing values of the stabilization factor (calcium transport). The proposed method has been used to estimate the state of water chemistry of the circulatory cooling system of CHP PGU-450 MW. Calculations confirmed by the data of chemical analyzes of water and deposits have shown increased deposit mass values on the control samples (stabilization factor less than 85 %), including biological ones (the total bacterial count exceeded the permissible value by over 104 CFU / ml). The circulating water corrosivity also increased, and the corrosion rate of steel st. 20 exceeded the standard values (0,1 mm / year). The developed technique can be effectively used for analyzing the state of both the existing water conditions of circulatory cooling systems, and any other (alternative) water chemistry directly in industrial conditions of operation of a certain CCPP.
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Kidali, John, Simon Omondi, Irene Ogali, Jane Rutto, and Moses Orwa. "Establishment of Multi-Institutional Model for the Delivery of Livestock Technology Needs in Arid and Semi-Arid Areas of Kenya." Asian Journal of Agricultural Extension, Economics & Sociology 41, no. 6 (May 6, 2023): 139–46. http://dx.doi.org/10.9734/ajaees/2023/v41i61931.
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This study was carried out in Isiolo and Kajiado counties. Livestock production and marketing have been hampered by the unavailability and accessibility to livestock technologies, and information sharing. The overall objective of this study was to assess a multi-institutional model for enhancing the uptake of livestock technologies in Isiolo and Kajiado counties. The key parameters assessed were priority livestock constraints; technology needs; stakeholder partnerships; and technology delivery platform. The data were collected from 451 households belonging to Kenya Climate Smart Agricultural Production KCSAP groups red meat value chain of pastoralists, Common Interest Groups and Most Vulnerable Groups (CIGs and VMGs) using semi-structured questionnaires, Focus group discussions with groups, key informant interviews with public and private sector actors.
The results showed that in both Kajiado and Isiolo Counties, priority livestock production constraints in Kajiado County in Dalalekutuk ward were diseases, lack of feeds, limited access to water and inadequate veterinary services, and in Isiolo County were lack of feeds, limited access to water and diseases. Priority livestock diseases in Kajiado, County, Dalalekutuk ward were, Foot and Mouth Disease (FMD), anthrax; contagious caprine pleuropneumonia (CCPP) and cerebral coenurosis and enterotoxemia and cerebral coenurosis for the sheep. In Isiolo County, priority cattle diseases were FMD and trypanosomiasis,’ in the goats CCPP and cerebral coenurosis while in the sheep enterotoxemia and cerebral coenurosis. The reasons for persistent livestock production constraints were ranked and ranked as single organization interventions not sufficient to solve problems and lack of prioritization by stakeholders (water, pasture, diseases). The major livestock technology needs were: pasture, water, access to veterinary vaccines, capacity building of groups; training of para vets to support in the delivery of veterinary services; information sharing platform and market infrastructure. The multi-institutional technology exhibitions consisting of public and private sector actors were held in Kajiado and Isiolo Counties linking KCSAP pastoralist groups to technology and service providers. To enhance sharing of information, a mobile application(MITDP) was established linking CIGs and VMGs leaders with KALRO, KEVEVAPI, County Governments of Kajiado and Isiolo departments of livestock production and veterinary services; suppliers of drugs, vaccines and equipment; water technology suppliers; Agro-vets and Non-governmental organizations along the red meat value chain.
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Zanacic, Enisa, and Dena W. McMartin. "Calibration and Validation of Calcium Carbonate Precipitation Potential (CCPP) Model for Strontium Quantification in Cold Climate Aquatic Environments." Environments 9, no. 6 (June 18, 2022): 74. http://dx.doi.org/10.3390/environments9060074.
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The ability to robustly quantify the potential for strontium precipitation and scaling in both natural surface waters and water infrastructure systems is limited. In some regions, both surface and ground water supplies contain significant concentrations of naturally occurring radionuclides, such as strontium, that can accumulate in water, soils and sediments, media, and living tissues. Methods for quantifying and predicting the potential for these occurrences are not readily available nor have they been tested and calibrated to cold region aquatic environments. Through extensive literature review, it was determined that a modified calcium carbonate precipitation potential (CCPP) model offered a scientifically credible approach to filling that knowledge gap in both the science and engineering of strontium fate and transport in water. The results from previous field and laboratory experiments were compiled to not only elucidate the fate and transport of strontium in water systems, but also to calculate the logarithmic distribution coefficient, λ, for strontium under co-precipitation conditions. Lambda (λ) is both time- and water-quality sensitive and must be measured as water mixes from source to receiving environment to determine continuous loss of Sr from the water phase. The data were collected to develop the strontium precipitation potential model that can be used in surface water quality assessment. The tool was then applied to pre-existing, publicly available, and extensive datasets for several rivers in Saskatchewan, Canada, to validate the model and produce estimates for strontium precipitation potential in those rivers.
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Yohana, Eflita, and Rigo Muhammad Herriza. "ANALISIS EFISIENSI SIKLUS COMBINE CYCLE POWER PLANT (CCPP) GAS TURBINE GENERATOR TERHADAP BEBAN OPERASI PT KRAKATAU DAYA LISTRIK." ROTASI 18, no. 4 (October 1, 2016): 106. http://dx.doi.org/10.14710/rotasi.18.4.106-109.
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Turbin Gas Generator umumnya mengalami perubahan beban untuk memenuhi kebutuhan daya listrik yang berubah sewaktu-waktu, sesuai dengan permintaan konsumen. Beban dari turbin gas yang berubah-ubah akan berpengaruh terhadap kinerja dari tiap-tiap komponennya antara lain kompresor, combustion chamber, dan turbin gas. Dalam merespon perubahan beban yang terjadi, maka suplai bahan bakar, udara pembakaran, serta gas buang yang akan di proses di HRSG untuk mengoperasikan turbin uap ikut berubah pula. Hal tersebut akan berpengaruh pada kinerja dan efisiensi dari gas turbin tersebut. Dengan mengetahui efisiensi siklus pada tiap beban maka diperoleh grafik efisiensi siklus pada turbin gas generator sehingga diketahui perbedaan nilai efisiensi siklus pada tiap variasi pembebanan. Analisa efisiensi siklus Gas Turbin Generator dilakukan pada Pembangkit Listrik Tenaga Gas dan Uap melalui perhitungan efisiensi kompresor, dan efisiensi turbin gas, tanpa memperhitungkan efisiensi yang terjadi di ruang bakar. Selain itu analisa efisiensi gas turbin generator juga menghasilkan nilai efisiensi dari tiap pembebanan yang terjadi di turbin gas generator Pembangkit Listrik Tenaga Gas dan Uap. Data temperatur dan tekanan yang diperoleh telah tercatat melalui layanan sistem operasi interface. Dari hasil perhitungan pada turbin gas Pembangkit Listrik Tenaga Gas dan Uap diperoleh nilai efisiensi siklus turbin gas generator yang berbahan bakar gas alam (metan) sebesar 31.28% pada pembenanan 23 MW, 38.71% pada pembebanan 27MW, dan 45.56% pada pembebanan 33MW. Dari hasil perhitungan efisiensi pada 3 proses pembebanan diketahui bahwa semakin besar pembebanan dilakukan maka efisiensi yang dihasilkan mesin semakin tinggi
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Di Matteo, A., K. Mankia, L. Duquenne, E. Cipolletta, J. Nam, L. Garcia-Montoya, R. Wakefield, M. Mahler, and P. Emery. "POS0464 IS IT POSSIBLE TO IDENTIFY INDIVIDUALS AT IMMINENT-RISK OF SUB-CLINICAL JOINT INVOLVEMENT?" Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 463.2–464. http://dx.doi.org/10.1136/annrheumdis-2021-eular.2290.
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Background:In anti-CCP antibody (Ab) positive at-risk individuals with MSK symptoms but without clinical synovitis, the detection of ultrasound (US) subclinical inflammation is associated with an increased risk of progression to inflammatory arthritis (IA) 1. Studies suggest that in these at-risk individuals, MSK symptoms develop before subclinical joint inflammation occurs on US. As such, anti-CCP Ab positive individuals with MSK symptoms in the absence of clinical or sub-clinical inflammation may be at the critical time-point for preventive treatments, before joint inflammation occurs and eventually becomes established (i.e., before the ‘second-hit’ in RA pathogenesis); however, identifying these individuals is challenging.Objectives:To identify, in second generation anti-CCP Ab (CCP2+) at-risk individuals with MSK symptoms, but without clinical or sub-clinical synovitis, predictors of US sub-clinical synovitis.Methods:In 186 CCP2+ at-risk individuals with normal baseline US scan (i.e., no synovitis or bone erosions), and a complete dataset, US data were analyzed at 6, 12 months, then annually until occurrence of IA. US synovitis was identified according to the EULAR/OMERACT definitions2. Relevant demographic (age and gender), clinical [early morning stiffness (EMS), tenderness in the small joints of the hands] and serological [anti-CCP2 Ab level, third generation anti-CCP Ab (CCP3) and rheumatoid factor (RF)] data were collected at baseline. Regression analyses, Kaplan-Meier analysis and Log-Rank test were performed.Results:US synovitis was detected in ≥1 longitudinal US scan in 69/186 (37.1%) at-risk individuals (median time to first developing US synovitis: 53 weeks, IQR 27.0-105.8; median number of joints with US synovitis: 2.0, IQR 1.0-2.0). As shown in Table 1, only anti-CCP3 Ab were significantly associated with development of US sub-clinical synovitis in the multi-variable analysis while borderline results were observed with age.Table 1.Regression analyses for the development of US synovitis.Univariable analysisMultivariableanalysisOR (95% CI)p-valueOR (95% CI)p-valueGender (male)1.02 (0.52-2.02)0.95//Age1.03 (1.01-1.06)<0.011.03 (1.00-1.06)0.03Tenderness in the hands0.86 (0.46-1.61)0.64//EMS1.60 (0.87-2.95)0.13//Anti-CCP2 Ab (high titre)2.79 (1.37-5.67)<0.011.20 (0.50-2.89)0.69Anti-CCP3+4.44 (2.28-8.66)<0.013.30 (1.39-7.89)<0.01RF+2.96 (0.46-1.61)0.011.45 (0.68-3.11)0.33CCP2+ individuals with positive anti-CCP3 Ab show a significantly reduced sub-clinical synovitis-free survival rate compared with individuals with negative anti-CCP3 Ab (Figure 1). At 1- and 2-year follow-up, respectively 23.3% and 38.3% of individuals with dual CCP2/CCP3 positivity developed sub-clinical synovitis on longitudinal scans, compared with 8.4% and 13.3% of CCP2+ individuals with negative anti-CCP3 Ab (p=0.01) (Figure 1a).Similar results were observed in the subgroup of high level CCP2+ individuals. At 1- and 2-year follow-up, respectively 24.5% and 39.4% of high level CPP2/anti-CCP3+, but only 6.1% and 15.2% of CCP2+ individuals with negative anti-CCP3 developed sub-clinical synovitis on longitudinal scans (p<0.01) (Figure 1b).Figure 1.Kaplan-Meier analysis shows US sub-clinical synovitis free survival time in CCP2+ at-risk individuals.Conclusion:In anti-CCP2+ at-risk individuals with MSK symptoms, anti-CCP3 antibodies improve prediction of imminent development of subclinical joint inflammation. This may represent the critical time-point for interventions to prevent the onset of joint disease. This is also a unique population for investigating the drivers of joint involvement in the development of RA.References:[1]Duquenne L, et al. The Role of Ultrasound Across the Inflammatory Arthritis Continuum: Focus on “At-Risk” Individuals. 2020.[2]D’Agostino MA, et al. Scoring ultrasound synovitis in rheumatoid arthritis: a EULAR-OMERACT ultrasound taskforce — Part 1: definition and development of a standardised, consensus-based scoring system. 2017.Disclosure of Interests:Andrea Di Matteo Grant/research support from: This study was conducted while Andrea Di Matteo was an ARTICULUM Fellow., Kulveer Mankia Speakers bureau: KM reports personal fees from Abbvie, UCB and Eli Lilly (all <$10.000), outside the submitted work., Grant/research support from: Research grants from BMS, Eli Lilly (all <$10.000), Laurence Duquenne: None declared, Edoardo Cipolletta: None declared, Jacqueline Nam: None declared, Leticia Garcia-Montoya: None declared, Richard Wakefield Speakers bureau: RJW has received honoraria from Abbvie, Novartis and GE for ultrasound related educational activities (all <$10.000)., Michael Mahler Employee of: MM is employee of Inova Diagnostics, commercializing CCP3, Paul Emery Speakers bureau: PE reports consultant fees from BMS, AbbVie, Gilead, Galapagos, Lilly, MSD, Pfizer, Novartis, Roche, and Samsung outside the submitted work (all <$10.000)., Grant/research support from: He also reports research grants from UCB, AbbVie, Lilly, Novartis, BMS, Pfizer, MSD and Roche, outside the submitted work. PE is National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) director and BRC funds supported this work. Leticia Garcia-Montoya and Laurence Duquenne are NIHR BRC fellows.
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Kaluwa, Catherine, Jemimah Oduma, Faduma Abdullahi Abdirahman, Byalungwa Kyotos Kitoga, Angela A. Opondoh, John Muchibi, Brigitte Bagnol, et al. "Using the Women Empowerment in Livestock Index (WELI) to Examine Linkages between Women Smallholder Livestock Farmers’ Empowerment and Access to Livestock Vaccines in Machakos County of Kenya: Insights and Critiques." Vaccines 10, no. 11 (November 4, 2022): 1868. http://dx.doi.org/10.3390/vaccines10111868.
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Livestock diseases are a major barrier to productivity for both male and female livestock keepers in Africa. In Kenya, two of the most devastating livestock diseases are Newcastle Disease (ND) in poultry and Contagious Caprine Pleuropneumonia (CCPP) in goats. Female livestock keepers tend to own more small ruminants (goats, sheep, etc.) and poultry and their livelihoods are adversely affected if their herds are not vaccinated against these diseases. Livestock farming has gender specific challenges and opportunities, with implications for the empowerment of women smallholder farmers, their household well-being, food security, and livelihoods. There is a need to estimate the level to which women benefit personally, socially, and economically from keeping livestock, yet there are very few studies that can measure if livestock production does in fact empower women smallholder livestock farmers. This study was done to examine linkages between women’s empowerment and access and control over livestock products and vaccines. The Women Empowerment in Livestock Index (WELI) tool, which was customized to include questions on livestock vaccine access, was used to capture baseline data on empowerment scores for women in Machakos county, Kenya, prior to implementation of animal health and vaccine test models. In total, 400 participants were surveyed in two wards of Machakos County, Kola and Kalama, which were purposively selected. Women’s empowerment was mapped to three domains (3DE): intrinsic agency (power within), instrumental agency (power to), and collective agency (power with) measured against adequacy in 13 indicators. Our results indicate that the household structure (female headed or dual headed household), age of respondents and number of members in a household influence the adequacy score. Work balance was the most significant negative contributor to women’s disempowerment. Women contributed the most to livestock productive activities and attained adequacy in this area compared to men, directly impacting the WELI score. Women smallholder livestock farmers report low CCPP and ND vaccination rates, minimal knowledge on livestock diseases, a lack of access to cold chain storage and rarely visited veterinarians. The WELI score was 0.81 indicating a high level of empowerment for women in this community compared to men leading us to conclude that the overall WELI score was not an accurate indicator of women‘s empowerment in Machakos County. However, the decomposability of the index allows us to disaggregate the drivers of change and to examine how individual indicators contribute to disempowerment.
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Yeom, Chan-Uk, and Keun-Chang Kwak. "Performance Comparison of ANFIS Models by Input Space Partitioning Methods." Symmetry 10, no. 12 (December 3, 2018): 700. http://dx.doi.org/10.3390/sym10120700.
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In this paper, we compare the predictive performance of the adaptive neuro-fuzzy inference system (ANFIS) models according to the input space segmentation method. The ANFIS model can be divided into four types according to the method of dividing the input space. In general, the ANFIS1 model using grid partitioning method, ANFIS2 model using subtractive clustering (SC) method, and the ANFIS3 model using fuzzy C-means (FCM) clustering method exist. In this paper, we propose the ANFIS4 model using a context-based fuzzy C-means (CFCM) clustering method. Context-based fuzzy C-means clustering is a clustering method that considers the characteristics of the output space as well as the input space. Here, the symmetric Gaussian membership functions are obtained by the clusters produced from each context in the design of the ANFIS4. In order to evaluate the performance of the ANFIS models according to the input space segmentation method, a prediction experiment was conducted using the combined cycle power plant (CCPP) data and the auto-MPG (miles per gallon) data. As a result of the prediction experiment, we confirmed that the ANFIS4 model using the proposed input space segmentation method shows better prediction performance than the ANFIS model (ANFIS1, ANFIS2, ANFIS3) using the existing input space segmentation method.
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Yao, Kun, Ying Wang, Zongjie Li, Jiajia Li, Jie Wan, and Yong Cao. "Fault Detection and Isolation of Load Mutation Caused by Electrical Interference of Single-Shaft Combined Cycle Power Plant." Applied Sciences 12, no. 22 (November 11, 2022): 11472. http://dx.doi.org/10.3390/app122211472.
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Because the generator power-measuring equipment is often accompanied by electrical interference in a complex electromagnetic environment in an actual thermal power plant, the output signal will change or even distort while it passes through the devices of acquisition and conversion. Several practical cases have found that the abnormal generation change phenomenon, impulse or oscillation caused by electrical interference, has different effects on the load regulation of steam turbines. These faults also exist in combined-cycle power plants (CCPPs). However, the insufficient installed capacity and operating life of CCPPs domestically cause similar load mutation failures that are scarcely found. We had to acknowledge that CCPPs and steam turbine regulation characteristics differ. It is of great value to study the influence of differences in load mutation on the load regulation of single-shaft CCPPs. We extracted the fault characteristics of two sudden load change phenomena using the operation data of an actual steam turbine and analyzed them through simulation. Furthermore, a fault detection and isolation method for sudden load changes in a single-shaft CCPP was proposed and the simulation results verified the method’s effectiveness.
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Yohana, Eflita, and Rahmat Julyansyah. "ANALISIS TOTAL EFISIENSI HRSG (HEAT RECOVERY STEAM GENERATOR) PADA COMBINE CYCLE POWER PLANT (CCPP) 120 MW PT. KRAKATAU DAYA LISTRIK." ROTASI 18, no. 2 (April 1, 2016): 28. http://dx.doi.org/10.14710/rotasi.18.2.28-31.
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Heat Recovery Steam Generator (HRSG) adalah suatu komponen kesatuan antara turbin gas dan turbin uap pada sistem combine cycle power plant. HRSG berfungsi sebagai alat yang memanfaatkan energi panas gas buang dari gas turbin untuk memanaskan air pada tube - tube yang berada di dalam HRSG, sehingga air berubah menjadi uap panas lanjut untuk memutar turbin uap [1]. Analisa dilakukan pada HRSG Pembangkit Listrik Tenaga Gas dan Uap melalui perhitungan total efisiensi berdasarkan temperatur, tekanan, dan laju massa yang masuk dan keluar HRSG. Selain itu analisa ini untuk membandingkan total efisiensi HRSG pada saat commisioning process dengan bulan Januari 2016. Data temperatur, tekanan, dan laju massa yang diperoleh telah tercatat melalui layanan system operasi interface. Dari hasil perhitungan nantinya akan diketahui nilai total efisiensi HRSG commisioning sebesar 93,31% dengan nilai efisiensi high pressure sebesar 69,62% dan nilai efisiensi low pressure sebesar 23,69%, dibandingkan dengan nilai total efisiensi HRSG pada bulan Januari 2016 sebesar 79,88% dengan nilai efisiensi high pressure sebesar 66,47% dan nilai efisiensi low pressure sebesar 13,41%. Terjadi penurunan nilai efisiensi saat commisioning dengan bulan Januari 2016 yaitu sebesar 13,43%.
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Ramphal, S., and M. Sibiya. "Optimization of coagulation-flocculation parameters using a photometric dispersion analyser." Drinking Water Engineering and Science Discussions 7, no. 1 (February 6, 2014): 95–120. http://dx.doi.org/10.5194/dwesd-7-95-2014.
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Abstract. The size and structural characteristics of floc particles are important design and control parameters in water treatment and should be rapidly monitored with a reasonable amount of accuracy. In this study, a photometric dispersion analyser (PDA) coupled to standard jar test experiments was used to optimize coagulation-flocculation parameters while monitoring floc size and structure as well as the rate of floc formation during coagulation using alum. The optimal coagulation conditions were as follows: sample pH 8; alum dosage, 6 mg L−1 as Al3+; G value, 116 s−1; rapid mixing time, 20 s. These conditions resulted in unstable treated water having a calcium carbonate precipitation potential of −15 mg L−1 as CaCO3 and required a slaked lime dosage of 17 mg L−1 to equilibrate CCPP to acceptable levels. PDA data revealed that aggregation rate and steady-state variance are primary parameters as both have significant influence on coagulation-flocculation efficiency. However, the average steady state ratio, although an important parameter, had a lessened impact on coagulation-flocculation efficiency. The results of this study showed that the PDA instrument is an important tool in coagulation kinetic studies and can be employed as an additional tool in the optimization of coagulation conditions.
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Liu, Jiajia, Mengyuan Yang, Weiling Zhao, and Xiaobo Zhou. "CCPE: cell cycle pseudotime estimation for single cell RNA-seq data." Nucleic Acids Research 50, no. 2 (December 21, 2021): 704–16. http://dx.doi.org/10.1093/nar/gkab1236.
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Abstract Pseudotime analysis from scRNA-seq data enables to characterize the continuous progression of various biological processes, such as the cell cycle. Cell cycle plays an important role in cell fate decisions and differentiation and is often regarded as a confounder in scRNA-seq data analysis when analyzing the role of other factors. Therefore, accurate prediction of cell cycle pseudotime and identification of cell cycle stages are important steps for characterizing the development-related biological processes. Here, we develop CCPE, a novel cell cycle pseudotime estimation method to characterize cell cycle timing and identify cell cycle phases from scRNA-seq data. CCPE uses a discriminative helix to characterize the circular process of the cell cycle and estimates each cell's pseudotime along the cell cycle. We evaluated the performance of CCPE based on a variety of simulated and real scRNA-seq datasets. Our results indicate that CCPE is an effective method for cell cycle estimation and competitive in various applications compared with other existing methods. CCPE successfully identified cell cycle marker genes and is robust to dropout events in scRNA-seq data. Accurate prediction of the cell cycle using CCPE can also effectively facilitate the removal of cell cycle effects across cell types or conditions.
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Winn, M. D., P. Patel, and E. Krissinel. "Developments in data harvesting within CCP4." Acta Crystallographica Section A Foundations of Crystallography 60, a1 (August 26, 2004): s246. http://dx.doi.org/10.1107/s0108767304095121.
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Li, Xiaohui, Dongkai Yang, Jingsong Yang, Guoqi Han, Gang Zheng, and Weiqiang Li. "Validation of NOAA CyGNSS Wind Speed Product with the CCMP Data." Remote Sensing 13, no. 9 (May 7, 2021): 1832. http://dx.doi.org/10.3390/rs13091832.
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The National Aeronautics and Space Administration (NASA) Cyclone Global Navigation Satellite System (CyGNSS) mission was launched in December 2016, which can remotely sense sea surface wind with a relatively high spatio-temporal resolution for tracking tropical cyclones. In recent years, with the gradual development of the geophysical model function (GMF) for CyGNSS wind retrieval, different versions of CyGNSS Level 2 products have been released and their performance has gradually improved. This paper presents a comprehensive evaluation of CyGNSS wind product v1.1 produced by the National Oceanic and Atmospheric Administration (NOAA). The Cross-Calibrated Multi-Platform (CCMP) analysis wind (v02.0 and v02.1 near real time) products produced by Remote Sensing Systems (RSS) were used as the reference. Data pairs between the NOAA CyGNSS and RSS CCMP products were processed and evaluated by the bias and standard deviation SD. The CyGNSS dataset covers the period between May 2017 and December 2020. The statistical comparisons show that the bias and SD of CyGNSS relative to CCMP-nonzero collocations when the flag of CCMP winds is nonzero are –0.05 m/s and 1.19 m/s, respectively. The probability density function (PDF) of the CyGNSS winds coincides with that of CCMP-nonzero. Furthermore, the average monthly bias and SD show that CyGNSS wind is consistent and reliable generally. We found that negative deviation mainly appears at high latitudes in both hemispheres. Positive deviation appears in the China Sea, the Arabian Sea, and the west of Africa and South America. Spatial–temporal analysis demonstrates the geographical anomalies in the bias and SD of the CyGNSS winds, confirming that the wind speed bias shows a temporal dependency. The verification and comparison show that the remotely sensed wind speed measurements from NOAA CyGNSS wind product v1.1 are in good agreement with CCMP winds.
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Yu, Xiao, Jin Liu, Weiqiang Peng, and Xingyu Peng. "Improving Cross-Company Defect Prediction with Data Filtering." International Journal of Software Engineering and Knowledge Engineering 27, no. 09n10 (November 2017): 1427–38. http://dx.doi.org/10.1142/s0218194017400046.
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Defect prediction aims to estimate software reliability via learning from historical defect data. Cross-company defect prediction (CCDP) is a practical way that trains a prediction model by exploiting one or multiple projects of a source company and then applies the model to the target company. Unfortunately, larger irrelevant cross-company (CC) data usually makes it difficult to build a CCDP model with high performance. To address such issues, this paper proposes a data filtering method based on agglomerative clustering (DFAC) for CCDP. First, DFAC combines within-company (WC) instances and CC instances and uses agglomerative clustering algorithm to group these instances. Second, DFAC selects subclusters which consist of at least one WC instance, and collects the CC instances in the selected subclusters into a new CC data. Compared with existing data filter methods, the experiment results from 15 public PROMISE datasets show that DFAC increases the pd value, reduces the pf value and achieves higher [Formula: see text]-measure value.
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Ijaz, Muhammad Fazal, Muhammad Attique, and Youngdoo Son. "Data-Driven Cervical Cancer Prediction Model with Outlier Detection and Over-Sampling Methods." Sensors 20, no. 10 (May 15, 2020): 2809. http://dx.doi.org/10.3390/s20102809.
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Globally, cervical cancer remains as the foremost prevailing cancer in females. Hence, it is necessary to distinguish the importance of risk factors of cervical cancer to classify potential patients. The present work proposes a cervical cancer prediction model (CCPM) that offers early prediction of cervical cancer using risk factors as inputs. The CCPM first removes outliers by using outlier detection methods such as density-based spatial clustering of applications with noise (DBSCAN) and isolation forest (iForest) and by increasing the number of cases in the dataset in a balanced way, for example, through synthetic minority over-sampling technique (SMOTE) and SMOTE with Tomek link (SMOTETomek). Finally, it employs random forest (RF) as a classifier. Thus, CCPM lies on four scenarios: (1) DBSCAN + SMOTETomek + RF, (2) DBSCAN + SMOTE+ RF, (3) iForest + SMOTETomek + RF, and (4) iForest + SMOTE + RF. A dataset of 858 potential patients was used to validate the performance of the proposed method. We found that combinations of iForest with SMOTE and iForest with SMOTETomek provided better performances than those of DBSCAN with SMOTE and DBSCAN with SMOTETomek. We also observed that RF performed the best among several popular machine learning classifiers. Furthermore, the proposed CCPM showed better accuracy than previously proposed methods for forecasting cervical cancer. In addition, a mobile application that can collect cervical cancer risk factors data and provides results from CCPM is developed for instant and proper action at the initial stage of cervical cancer.
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Linhart, Jakub, and Jaromír Skorkovský. "Theory of Constraints and Its Application in a Specific Company." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 62, no. 6 (2014): 1343–52. http://dx.doi.org/10.11118/actaun201462061343.
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This article analyses the possibilities of the practical utilization of Critical Chain Project Management methodology. Our study analyzed key processes related to the implementation and utilization of such a tool in a concrete company. For this purpose an original program was created. The logic of this program is based on the fundamental principles of the CCPM methodology. The impetus for the design and creation of such a program stemmed from the almost non-existence of such a tool on the Czech market. The theoretical part of the article focuses concisely on the Theory of Constraints and Critical Chain principles, which the conceptual ideas of all algorithms included in the new program come from.The system was used for two years and it enabled the processing of requests significantly faster than before. The evaluation of economical and practical benefits based on real project data demonstrates that after implementation of the Appello system and corresponding rules of usage, project managers completed more tasks in the first year than in the previous two years in which the CCPM was not applied and nearly 85% of planned requests were either on time or delayed up to 30 days in comparison with the amount of work from the preceding two years.Currently, a significant number of project oriented companies are looking for competitive advantages which, allow for the mastering of the largest number of projects that have a delivery time specified within agreed time frames. The use of our system or similar ones designed according to CCMP rules fully ensures the fulfilment of such requirements.
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Alfons, Andreas, Christophe Croux, and Peter Filzmoser. "Robust Maximum Association Between Data Sets: The R Package ccaPP." Austrian Journal of Statistics 45, no. 1 (February 29, 2016): 71–79. http://dx.doi.org/10.17713/ajs.v45i1.90.
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An intuitive measure of association between two multivariate data sets can be defined as the maximal value that a bivariate association measure between any one-dimensional projections of each data set can attain. Rank correlation measures thereby have the advantage that they combine good robustness properties with good efficiency. The software package ccaPP provides fast implementations of such maximum association measures for the statistical computing environment R. We demonstrate how to use package ccaPP to compute the maximum association measures, as well as how to assess their significance via permutation tests.
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Blanke, Jordan M. "Protection for ‘Inferences Drawn’: A Comparison Between the General Data Protection Regulation and the California Consumer Privacy Act." Global Privacy Law Review 1, Issue 2 (June 1, 2020): 81–92. http://dx.doi.org/10.54648/gplr2020080.
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Inferences drawn from personal data have arguably become more dangerous to individual privacy than the vast collection and storage of the data itself. Recently there have been questions raised about whether the General Data Protection Regulation (GDPR) has sufficient protection for these inferences. Probably not surprisingly, and learning from this possible shortcoming, the California Consumer Privacy Act (CCPA) specifically includes ‘inferences drawn’ as part of its definition of personal information. This article explores the widespread use of inferential data and compares the protection provided under the GDPR and the CCPA for such inferences. privacy, data protection, inferences drawn, GDPR, CCPA
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Lu, Zhaoyang, Liujiang Kang, Song Gao, and Qiang Meng. "Determination of Minimum Distance to Obstacle Avoidance in the Singapore Strait." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 11 (September 1, 2018): 73–80. http://dx.doi.org/10.1177/0361198118794056.
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In the maritime simulation models of obstacle avoidance, the parameter of critical contact closest point of approach (CCPA) is defined as the minimum safe distance to avoid an obstacle contact. Although the parameter of CCPA plays a decisive role on the maneuvering of the ship for obstacle avoidance, it is generally set with an uncalibrated input value in many obstacle avoidance simulation models. This study focuses on the parameter calibration of the critical CCPA by utilizing the automatic identification system (AIS) data in the Singapore Strait and maneuver simulation experiments. First, an effective mathematical method is proposed to identify ship obstacle avoidance from the big AIS data. Together with several obstacles and the AIS data in the Singapore Strait, the average critical CCPA values are identified for different ship classes. Second, a series of maneuver simulation experiments on Dalian Maritime University navigational simulators are conducted by professional captains. Based on the experimental data, the simulation-based critical CCPA values are derived. Finally, these calibrated CCPA values from the above two methods are compared and analysed. The comparison result implies that these critical CCPA values, derived from AIS data and maneuver simulators, are matched and confirm the rationality of one another. It also reveals that the average critical CCPA value for each ship class has an increasing trend with the increased ship length.
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Sánchez-Botet, Abril, Eva Quandt, Núria Masip, Rubén Escribá, Laura Novellasdemunt, Laura Gasa, Vivian S. W. Li, Ángel Raya, Josep Clotet, and Mariana P. C. Ribeiro. "Atypical cyclin P regulates cancer cell stemness through activation of the WNT pathway." Cellular Oncology 44, no. 6 (October 4, 2021): 1273–86. http://dx.doi.org/10.1007/s13402-021-00636-7.
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Abstract Purpose Cancer stem cells represent a cancer cell subpopulation that has been found to be associated with metastasis and chemoresistance. Therefore, it is vital to identify mechanisms regulating cancer stemness. Previously, we have shown that the atypical cyclin P (CCNP), also known as CNTD2, is upregulated in lung and colorectal cancers and is associated with a worse clinical prognosis. Given that other cyclins have been implicated in pluripotency regulation, we hypothesized that CCNP may also play a role in cancer stemness. Methods Cell line-derived spheroids, ex vivo intestinal organoid cultures and induced-pluripotent stem cells (iPSCs) were used to investigate the role of CCNP in stemness. The effects of CCNP on cancer cell stemness and the expression of pluripotency markers and ATP-binding cassette (ABC) transporters were evaluated using Western blotting and RT-qPCR assays. Cell viability was assessed using a MTT assay. The effects of CCNP on WNT targets were monitored by RNA-seq analysis. Data from publicly available web-based resources were also analyzed. Results We found that CCNP increases spheroid formation in breast, lung and colorectal cancers, and upregulates the expression of stemness (CD44, CD133) and pluripotency (SOX2, OCT4, NANOG) markers. In addition, we found that CCNP promotes resistance to anticancer drugs and induces the expression of multidrug resistance ABC transporters. Our RNA-seq data indicate that CCNP activates the WNT pathway, and that inhibition of this pathway abrogates the increase in spheroid formation promoted by CCNP. Finally, we found that CCNP knockout decreases OCT4 expression in iPSCs, further supporting the notion that CCNP is involved in stemness regulation. Conclusion Our results reveal CCNP as a novel player in stemness and as a potential therapeutic target in cancer.
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Gunst, Simon, and Ferdi De Ville. "The Brussels Effect: How the GDPR Conquered Silicon Valley." European Foreign Affairs Review 26, Issue 3 (October 1, 2021): 437–58. http://dx.doi.org/10.54648/eerr2021036.
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In 2018, the Californian government adopted a new data protection framework. The flagship of this framework is the California Consumer Privacy Act (CCPA). As this new framework is widely considered to resemble the European Union’s (EU’s) General Data Protection Regulation (GDPR), this article intends to investigate whether the Brussels Effect could explain this resemblance. We apply process-tracing to test if the Brussels Effect causally connects the GDPR with the CCPA. The analysis is based on a careful evaluation of three sets of evidence. Firstly, privacy policies of Apple, Facebook, and Google are examined. Secondly, lobbying concerning the alignment of the implementation of the CCPA with the GDPR is scrutinized. Lastly, it is investigated whether the Californian government has used arguments linked to the Brussels Effect while drafting the CCPA and its subsequent implementing regulations. It is concluded that the Brussels Effect has indeed played a role in the adoption of the CCPA. Nevertheless, it has become clear that the impact of the Effect varies depending on exactly which provision of the GDPR is examined. Brussels Effect, process-tracing, California, CCPA, European Union, GDPR, Data Protection, Lobbying, Big Tech
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Nur Aida Sabrina, M. R., C. L. Too, A. Haziqah Itqan, A. A. Siti-Aisyah, A. F. Nurul-Aain, L. K. Tan, I. S. Lau, et al. "POS0457 CHANGES OF RF ISOTYPE PROFILE IN PATIENTS WITH RHEUsMATOID ARTHRITIS: DATA FROM 10 YEARS FOLLOW-UP STUDY." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 459–60. http://dx.doi.org/10.1136/annrheumdis-2021-eular.1714.
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Background:Presence of autoantibodies such as anti-cyclic citrullinated peptide (anti-CCP2) and rheumatoid factor (RF) is of considerable diagnostic and prognostic value in patients with rheumatoid arthritis (RA). Limited data are available for autoantibody profile changes over time in patients with RA.Objectives:Thus, we compared the presence of anti-CCP2 and different RF isotypes in individual RA patients at baseline and during 10 years follow-up.Methods:A total of 320 RA patients from the Malaysian Epidemiological Investigation of Rheumatoid Arthritis (MyEIRA) case-control study was included in this study. The presence of anti-CCP2, IgM RF, IgG RF, and IgA RF at baseline and at later time point (±10 years) were determined using enzyme-linked immunosorbent assays, with identical techniques in paired samples. Seropositive RA is defined by the presence of at least one autoantibody, whilst seronegative RA is defined by the absence of all investigated autoantibodies.Results:The proportion of seropositive RA were higher for the follow-up samples (n=263, 82.2%) as compared to the baseline samples (n=251, 78.4%). Among the baseline samples, 105 (41.8%) were positive for anti-CCP2 and all RF isotypes. Of these individuals, 85 (81.0%) remained positive for all antibodies at the follow-up, while 20 (19.0%) lost one or more RF isotypes (4 IgM RF, 19 IgG RF and 13 IgA RF). Interestingly, 14 (5.6%) RA patients who were seropositive at baseline became totally seronegative after follow-up. Among the 69 patients seronegative at baseline, 26 (37.7%) acquired one or more autoantibodies at follow-up (14 IgM RF, 2 IgG RF, 9 IgA RF and 8 anti-CCP2) (Figure 1).Conclusion:Anti-CCP2 present at baseline usually remained at follow-up. Among Malaysian RA patients, changes in status were mainly found for RF of all isotypes.References:[1]Barra, Lillian et al. “Lack of seroconversion of rheumatoid factor and anti-cyclic citrullinated peptide in patients with early inflammatory arthritis: a systematic literature review.” Rheumatology (Oxford, England) vol. 50,2 (2011): 311-6.[2]van Delft, Myrthe A M, and Tom W J Huizinga. “An overview of autoantibodies in rheumatoid arthritis.” Journal of autoimmunity vol. 110 (2020): 102392.Figure 1.Comparison of serum autoantibody profile in rheumatoid arthritis patients during baseline enrolment and 10 years follow-up.Acknowledgements:The authors would like to thank the Director General of Health, Ministry of Health Malaysia for supporting this study. The authors are also indebted to participants for their kind participation. This study was financially supported by the Ministry of Health, Malaysia (JPP-IMR 08-012; 18-051).Disclosure of Interests:None declared
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Evans, Phil. "CCP4 Tools for X-ray Integration and Data Processing." Nihon Kessho Gakkaishi 56, Supplement (2014): s24. http://dx.doi.org/10.5940/jcrsj.56.s24.
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Yang, W., and P. Briggs. "Towards data management for PX structure determination with CCP4." Acta Crystallographica Section A Foundations of Crystallography 62, a1 (August 6, 2006): s132. http://dx.doi.org/10.1107/s0108767306097376.
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Yi, Fu-Xian, and Ian M. Bird. "Pregnancy-Specific Modulatory Role of Mitochondria on Adenosine 5′-Triphosphate-Induced Cytosolic [Ca2+] Signaling in Uterine Artery Endothelial Cells." Endocrinology 146, no. 11 (November 1, 2005): 4844–50. http://dx.doi.org/10.1210/en.2005-0414.
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Vascular endothelial cells respond to extracellular ATP by inositol 1,4,5-trisphosphate-mediated Ca2+ release from the endoplasmic reticulum followed by Ca2+ influx and subsequent synthesis of vasodilators. In this study, the contribution of mitochondria in shaping the ATP-induced Ca2+ increase was examined in ovine uterine artery endothelial cells from nonpregnant and pregnant (late gestation) ewes (NP- and P-UAEC, passage 4). The mitochondrial protonophore carbonyl cyanide m-chlorophenylhydrazone (CCCP) induced a rapid mitochondrial depolarization. CCCP also slowly increased cytosolic [Ca2+] ([Ca2+]c), which then gradually declined to 10–20 nm above resting level. Pretreatment with CCCP for 30 min significantly inhibited both ATP and thapsigargin-induced [Ca2+]c, with inhibition in NP-UAEC more effective than in P-UAEC. Pretreatment of mitochondrial permeability transition pore inhibitor cyclosporine A did not affect CCCP-induced mitochondrial depolarization, but delayed CCCP-induced [Ca2+]c for about 12–15 min (we termed this the “window of time”). During the cyclosporine A-delayed window of time of CCCP-induced [Ca2+]c, ATP induced a normal Ca2+ response, but after this window of time, ATP-induced [Ca2+]c was significantly inhibited. Pretreatment of oligomycin B to prevent intracellular ATP depletion by F0F1-ATPase did not reduce the inhibition of ATP-induced [Ca2+]c by CCCP. Ruthenium red, a mitochondrial Ca2+ uptake blocker, did not mimic the inhibition of Ca2+ signaling by CCCP. In conclusion, our data show that mitochondrial Ca2+ depletion after dissipation of mitochondrial membrane potential with CCCP inhibits ATP-induced [Ca2+]c, mediated at the level of Ca2+ release from the endoplasmic reticulum. Moreover, our data revealed that P-UAEC is more resistant to the inhibitory effect of CCCP on [Ca2+]c than NP-UAEC.
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Krissinel, Eugene, Andrey A. Lebedev, Ville Uski, Charles B. Ballard, Ronan M. Keegan, Oleg Kovalevskiy, Robert A. Nicholls, et al. "CCP4 Cloud for structure determination and project management in macromolecular crystallography." Acta Crystallographica Section D Structural Biology 78, no. 9 (August 30, 2022): 1079–89. http://dx.doi.org/10.1107/s2059798322007987.
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Nowadays, progress in the determination of three-dimensional macromolecular structures from diffraction images is achieved partly at the cost of increasing data volumes. This is due to the deployment of modern high-speed, high-resolution detectors, the increased complexity and variety of crystallographic software, the use of extensive databases and high-performance computing. This limits what can be accomplished with personal, offline, computing equipment in terms of both productivity and maintainability. There is also an issue of long-term data maintenance and availability of structure-solution projects as the links between experimental observations and the final results deposited in the PDB. In this article, CCP4 Cloud, a new front-end of the CCP4 software suite, is presented which mitigates these effects by providing an online, cloud-based environment for crystallographic computation. CCP4 Cloud was developed for the efficient delivery of computing power, database services and seamless integration with web resources. It provides a rich graphical user interface that allows project sharing and long-term storage for structure-solution projects, and can be linked to data-producing facilities. The system is distributed with the CCP4 software suite version 7.1 and higher, and an online publicly available instance of CCP4 Cloud is provided by CCP4.
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Yang, William. "Economic Feasibility Study of DES/CCHP in Different Regions of China." Advanced Materials Research 616-618 (December 2012): 1374–76. http://dx.doi.org/10.4028/www.scientific.net/amr.616-618.1374.
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Recently China issued a series of policies that benefit the development of DES/CCHP. We are confident that DES/CCHP fueled by natural gas will boom in recent decades. Operation cost is the key factor that decides if a project will succeed. This paper analyzed three factors that influence the cost of DES/CCHP project: annual running time; comprehensive energy efficiency and the price of natural gas and electricity, reaching the conclusion that the price of natural gas and electricity is the determinant factor to a DES/CCHP project and gas-electricity price ratio is a comprehensive index that indicates the economic expectation of a DES/CCHP project. Considering that no survey has been conducted about the gas and electricity price distributions in China, we collected price data of natural gas and electricity, and got the conclusion that DES/CCHP is more competitive in Northwest region of China, especially Xinjiang, Ningxia.
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Lien, K., L. Yau, K. Van Aarsen, A. Wakabayashi, and M. Bhimani. "LO73: Are women under-represented in emergency medicine residency programs across Canada?" CJEM 22, S1 (May 2020): S34. http://dx.doi.org/10.1017/cem.2020.128.
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Introduction: 2018 data from the Canadian Medical Association website shows that of practicing emergency physicians country-wide, only 31% were female. While there are some studies that examine the number and proportion of Canadian female applicants applying to surgical specialties, there are very few studies that are specific to emergency medicine (EM), and none that are Canadian in scope. Given the changing gender ratio of graduating medical students in Canada, the primary objective of this study is to assess the mean proportion and trends in proportion of females who applied and matched to English-language Canadian EM programs including Canadian College of Family Physicians emergency medicine certificate (CCFP-EM) and Fellow of the Royal College of Physicians of Canada emergency medicine (FRCPC-EM), family medicine (CCFP) programs, and all specialties combined. Methods: A retrospective data analysis on residency match results from 2013-2019 inclusively was performed. Data was accessed through a freedom of information request from the Canadian resident matching service (CaRMS). The mean proportions and trends in the proportions of females applying and matching to CCFP-EM, FRCPC-EM, CCFP, and all specialties were computed. Cochrane-Armitage trend of test was used for analysis. Results: From 2013-2019, the mean (SD) percentage of females who applied and matched respectively were as follows: CCFP-EM [44.4 (3.5);46.0(4.5)]; FRCPC-EM [41.3(4.1);44.0 (4.5], CCFP [56.5(1.3);61.0(1.9)], all specialties [54.0(1.1);55.5(0.9)]. There was a significant increase in the proportion of female applying to the FRCPC-EM (p < 0.0001), CCFP (p = 0.0002), and all disciplines (p = 0.0013). There was no significant change in the proportion of females applying for the CCFP-EM program (p = 0.6435). Conclusion: Our study shows that there is an increasing trend in the percentage of female applicants in all programs except the CCFP-EM program, where it remained statistically the same over time. There was a consistent percentage of applied versus matched female applicants over time for both CCFP-EM and FRCPC-EM programs. However, the percentage of females applying or matching to both CCFP-EM and FRCPC-EM programs remained less than 50%. Further research could focus on evaluating reasons for program choice, in order to further increase the percentage of female medical students and residents applying and matching to both emergency medicine programs.
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Calzada, Igor. "Citizens’ Data Privacy in China: The State of the Art of the Personal Information Protection Law (PIPL)." Smart Cities 5, no. 3 (September 8, 2022): 1129–50. http://dx.doi.org/10.3390/smartcities5030057.
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The Personal Information Protection Law (PIPL) was launched on 1 November 2021 in China. This article provides a state-of-the-art review of PIPL through a policy analysis. This paper aims to compare the three main worldwide data privacy paradigms that exist at present: (i) the General Data Protection Regulation (GDPR) in the E.U., (ii) the California Consumer Privacy Act (CCPA) in the U.S., and (iii) PIPL in China. The research question is twofold: (i) how will PIPL affect the data privacy of Chinese citizens and consequently, (ii) how will PIPL influence the global digital order, particularly paralleling the existing GDPR and CCPA? In the first section, this article introduces the topic of data privacy as a global concern, followed in the second section by an in-depth policy context analysis of PIPL and a literature review on privacy that elucidates in particular the impact of the Social Credit System (SCS). In the third section, a comparative benchmarking is carried out between the GDPR, CCPA, and PIPL. Methodologically, policy documents around PIPL will be analyzed. In the fourth section, the case study of Shenzhen will be examined by undertaking a multi-stakeholder analysis following the Penta Helix framework. The article concludes by responding to the research questions, acknowledging limitations, and presenting future research avenues.
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Williams, Michael J., Mehwish Akram, Deimante Barkauskaite, Sourabh Patil, Eirini Kotsidou, Sania Kheder, Giovanni Vitale, et al. "CCAP regulates feeding behavior via the NPF pathway in Drosophila adults." Proceedings of the National Academy of Sciences 117, no. 13 (March 16, 2020): 7401–8. http://dx.doi.org/10.1073/pnas.1914037117.
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The intake of macronutrients is crucial for the fitness of any animal and is mainly regulated by peripheral signals to the brain. How the brain receives and translates these peripheral signals or how these interactions lead to changes in feeding behavior is not well-understood. We discovered that 2 crustacean cardioactive peptide (CCAP)-expressing neurons in Drosophila adults regulate feeding behavior and metabolism. Notably, loss of CCAP, or knocking down the CCAP receptor (CCAP-R) in 2 dorsal median neurons, inhibits the release of neuropeptide F (NPF), which regulates feeding behavior. Furthermore, under starvation conditions, flies normally have an increased sensitivity to sugar; however, loss of CCAP, or CCAP-R in 2 dorsal median NPF neurons, inhibited sugar sensitivity in satiated and starved flies. Separate from its regulation of NPF signaling, the CCAP peptide also regulates triglyceride levels. Additionally, genetic and optogenetic studies demonstrate that CCAP signaling is necessary and sufficient to stimulate a reflexive feeding behavior, the proboscis extension reflex (PER), elicited when external food cues are interpreted as palatable. Dopaminergic signaling was also sufficient to induce a PER. On the other hand, although necessary, NPF neurons were not able to induce a PER. These data illustrate that the CCAP peptide is a central regulator of feeding behavior and metabolism in adult flies, and that NPF neurons have an important regulatory role within this system.
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LOI, P. K., S. A. EMMAL, Y. PARK, and N. J. TUBLITZ. "IDENTIFICATION, SEQUENCE AND EXPRESSION OF A CRUSTACEAN CARDIOACTIVE PEPTIDE (CCAP) GENE IN THE MOTHMANDUCA SEXTA." Journal of Experimental Biology 204, no. 16 (August 15, 2001): 2803–16. http://dx.doi.org/10.1242/jeb.204.16.2803.
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SUMMARYThe crustacean cardioactive peptide (CCAP) gene was isolated from the tobacco hawkmoth Manduca sexta. The gene has an open reading frame of 125 amino acid residues containing a single, complete copy of CCAP. Analysis of the gene structure revealed three introns interrupting the coding region. A comparison of the M. sexta CCAP gene with the Drosophila melanogaster genome database reveals significant similarities in sequence and gene structure.The spatial and temporal expression patterns of the CCAP gene in the M. sexta central nervous system were determined in all major post-embryonic stages using in situ hybridization techniques. The CCAP gene is expressed in a total of 116 neurons in the post-embryonic M. sextacentral nervous system. Nine pairs of cells are observed in the brain, 4.5 pairs in the subesophageal ganglion, three pairs in each thoracic ganglion(T1-T3), three pairs in the first abdominal ganglion (A1), five pairs each in the second to sixth abdominal ganglia (A2-A6) and 7.5 pairs in the terminal ganglion. The CCAP gene is expressed in every ganglion in each post-embryonic stage, except in the thoracic ganglia of first- and second-instar larvae. The number of cells expressing the CCAP gene varies during post-embryonic life,starting at 52 cells in the first instar and reaching a maximum of 116 shortly after pupation. One set of thoracic neurons expressing CCAP mRNA shows unusual variability in expression levels immediately prior to larval ecdysis. Using previously published CCAP immunocytochemical data, it was determined that 91 of 95 CCAP-immunopositive neurons in the M. sexta central nervous system also express the M. sexta CCAP gene, indicating that there is likely to be only a single CCAP gene in M. sexta.