Representative Days and Hours with Piecewise Linear Transitions for Power System Planning

Electric demand and renewable power are highly variable, and the solution of a planning model relies on capturing this variability. This paper proposes a hybrid multi-area method that effectively captures both the intraday and interday chronology of real data considering extreme values, using a limited number of representative days, and time points within each day. An optimization-based representative extraction method is proposed to improve intraday chronology capturing. It ensures higher precision in preserving data chronology and extreme values than hierarchical clustering methods. The proposed method is based on a piecewise linear demand and supply representation, which reduces approximation errors compared to the traditional piecewise constant formulation. Additionally, sequentially linked day blocks with identical representatives, created through a mapping process, are employed for interday chronology capturing. To evaluate the efficiency of the proposed method, a comprehensive expansion co-planning model is developed, including transmission lines, energy storage systems, and wind farms

Capturing Chronology and Extreme Values of Representative Days for Planning of Transmission Lines and Long-Term Energy Storage Systems

The growing penetration of renewable energy sources (RESs) is inevitable to reach net zero emissions. In this regard, optimal planning and operation of power systems are becoming more critical due to the need for modeling the short-term variability of RES output power and load demand. Considering hourly time steps of one or more years to model the operational details in a long-term expansion planning scheme can lead to a practically unsolvable model. Therefore, a clustering-based hybrid time series aggregation algorithm is proposed in this paper to capture both extreme values and temporal dynamics of input data by some extracted representatives. The proposed method is examined in a complex co-planning model for transmission lines, wind power plants (WPPs), short-term battery and long-term pumped hydroelectric energy storage systems. The effectiveness of proposed mixed-integer linear programming (MILP) model is evaluated using a modified 6-bus Garver test system. The simulation results confirm the proposed model efficacy, especially in modeling long-term energy storage systems.Comment: IEEE PowerTech 202

A survey on peroxide content and acidity level of persian doughnuts in lorestan province, West of Iran

There are different chemical food contaminations that cause detrimental effects on human health. For example, presence of peroxide in fried foods causes free radical formation. Free radicals are not only responsible for food spoilage, but also cause damage to body tissues and cancer, inflammatory diseases, atherosclerosis, aging and so on. The aim of this study was to evaluate the peroxide content and acidity level in Zoolbia and Bamiehin of Lorestan province, West of Iran. 120 samples of Zoolbia and Bamieh doughnuts were purchased of Lorestan province distribution centers, during March 2014 to March 2015 and handled to Laboratory for chemical analysis and determination of their peroxide value and acidity. Present descriptive study results showed 56.92 and 43.07 % of the samples were out of standard limit and not suitable for consumption due to high levels of peroxides and acidity, respectively. The lowest and highest peroxide value were 1.1 and 2.9 mEq/kg, respectively. The minimum and maximum acidity of the samples were 0.7 and 2.9 wt%, respectively. Obtained results showed high peroxide contents in Persian doughnuts in Lorestan province than standard limit. Therefore, it seems educational programs about nutrition and using proper method for cooking and frying of foods is necessary. Continuous planning and surveillance, providing practical solutions by health authorities and regulatory organs, training of food staffs, using oils a few times and especial for food frying are recommended to reduce the peroxide content in Persian doughnuts (Zoolbia and Bamieh)

BD-KD: Balancing the Divergences for Online Knowledge Distillation

Knowledge distillation (KD) has gained a lot of attention in the field of model compression for edge devices thanks to its effectiveness in compressing large powerful networks into smaller lower-capacity models. Online distillation, in which both the teacher and the student are learning collaboratively, has also gained much interest due to its ability to improve on the performance of the networks involved. The Kullback-Leibler (KL) divergence ensures the proper knowledge transfer between the teacher and student. However, most online KD techniques present some bottlenecks under the network capacity gap. By cooperatively and simultaneously training, the models the KL distance becomes incapable of properly minimizing the teacher's and student's distributions. Alongside accuracy, critical edge device applications are in need of well-calibrated compact networks. Confidence calibration provides a sensible way of getting trustworthy predictions. We propose BD-KD: Balancing of Divergences for online Knowledge Distillation. We show that adaptively balancing between the reverse and forward divergences shifts the focus of the training strategy to the compact student network without limiting the teacher network's learning process. We demonstrate that, by performing this balancing design at the level of the student distillation loss, we improve upon both performance accuracy and calibration of the compact student network. We conducted extensive experiments using a variety of network architectures and show improvements on multiple datasets including CIFAR-10, CIFAR-100, Tiny-ImageNet, and ImageNet. We illustrate the effectiveness of our approach through comprehensive comparisons and ablations with current state-of-the-art online and offline KD techniques

Evaluation of antifungal activities of the essential oil and various extracts of Nigella sativa and its main component, thymoquinone against pathogenic dermatophyte strains

Objective. — Plant extracts and plant-derived compounds are valuable sources as folk medicine for the treatment and prevention of a wide range of diseases including infectious diseases. In the present study, the antifungal activities of the essential oil and various extracts Nigella sativa and its active principle, thymoquinone against Trichophyton mentagrophytes, Microsporum canis and Microsporum gypseum as pathogenic dermatophyte strains have been evaluated. In addition, the cytotoxic effects of N. sativa against murine macrophage cells were determined. Materials and methods. — In this study, the antifungal activity was studied by disk diffusion method and assessment of minimum inhibitory concentration (MIC) of extracts using broth macrodilution method. In addition, the cytotoxic activity of N. sativa was evaluated by colorimetric assay (MTT). The components of the N. sativa essential oil were also identified by gas chromatography/mass spectroscopy (GC/MS) analysis. Results. — The results showed that the essential oil and various extracts of N. sativa particularly thymoquinone have potent antifungal effects on T. mentagrophytes, M. canis and M. gypseum as pathogenic dermatophyte strains. In the assessment of the cytotoxicity activity, it could be observed that N. sativa had no significant cytotoxicity in the murine macrophages at low concentrations. While, thymoquinone in comparison with essential oil and various extracts of N. sativa showed higher cytotoxicity on murine macrophage cells. In the GC/MS analysis, thymoquinone (42.4%), p-cymene (14.1%), carvacrol (10.3%) and longifolene (6.1%) were found to be the major components of N. sativa essential oil. Conclusion. — The findings of this study suggest a first step in the search of new antidermatophytic drugs and aid the use of N. sativa seeds in the traditional medicine for dermatophytic infections

Children struggle beyond preschool-age in a continuous version of the ambiguous figures task

Children until the age of five are only able to reverse an ambiguous figure when they are informed about the second interpretation. In two experiments, we examined whether children’s difficulties would extend to a continuous version of the ambiguous figures task. Children (Experiment 1: 66 3- to 5-year olds; Experiment 2: 54 4- to 9-year olds) and adult controls saw line drawings of animals gradually morph—through well-known ambiguous figures—into other animals. Results show a relatively late developing ability to recognize the target animal, with difficulties extending beyond preschool-age. This delay can neither be explained with improvements in theory of mind, inhibitory control, nor individual differences in eye movements. Even the best achieving children only started to approach adult level performance at the age of 9, suggesting a fundamentally different processing style in children and adults

Agricultural productivity in Burkina Faso : The role of gender and risk attitudes

This study is an empirical investigation of how individual risk attitudes influence the agricultural productivity of men and women in a sub-Saharan African country, Burkina Faso. By analyzing a large representative panel survey of farmers from 2014 and 2015, the results indicate lower productivity on female-owned plots. Controlling for various socio-economic factors, the results show that as the female farmers’ increase risk taking, the productivity of female-owned plots goes down. These results are robust regarding alternative specifications. However, productivity differences vary by the type of crop cultivated, the agro-ecological zone, the share of female farmers in the region, the soil quality, type of seed used, and between consumption quantiles when comparing the poorest to the richest 20 per cent of the farm households. The results indicate that female farmers do not increase their plot yield by taking more risk. It is argued that agricultural policy interventions in Burkina Faso need to be gender sensitized when addressing issues related to credit constraints, improved inputs, and policies that support increase in productivity