Customised-sampling approach for pipe failure prediction in water distribution networks.

This paper presents a new methodology for addressing imbalanced class data for failure prediction in Water Distribution Networks (WDNs). The proposed methodology relies on existing approaches including under-sampling, over-sampling, and class weighting as primary strategies. These techniques aim to treat the imbalanced datasets by adjusting the representation of minority and majority classes. Under-sampling reduces data in the majority class, over-sampling adds data to the minority class, and class weighting assigns unequal weights based on class counts to balance the influence of each class during machine learning (ML) model training. In this paper, the mentioned approaches were used at levels other than "balance point" to construct pipe failure prediction models for a WDN with highly imbalanced data. F1-score, and AUC-ROC, were selected to evaluate model performance. Results revealed that under-sampling above the balance point yields the highest F1-score, while over-sampling below the balance point achieves optimal results. Employing class weights during training and prediction emphasises the efficacy of lower weights than the balance. Combining under-sampling and over-sampling to the same ratio for both majority and minority classes showed limited improvement. However, a more effective predictive model emerged when over-sampling the minority class and under-sampling the majority class to different ratios, followed by applying class weights to balance data.

Soundscape analysis using eco-acoustic indices for the birds biodiversity assessment in urban parks (case study: Isfahan City, Iran).

Biophony and anthrophony analysis as part of the urban soundscape is an efficient approach to bird biodiversity monitoring and to studying the impact of noise pollution in urban parks. Here, we analyzed the soundscape composition to monitor the diversity of birds using acoustic indices and machine learning in 21 urban parks of Isfahan, Iran, in spring 2019. To achieve this purpose four-step method was considered: (i) choosing parks and sampling of sound and bird species; (ii) calculated the six acoustic indices; (iii) calculated the six biodiversity indices; and (iv) statistical analysis for predicting biodiversity index from acoustic indices. Three regression models including support vector machine (SVM), random forest (RF), and elastic net regularization (GLMNET) applied the acoustic indices with minimum and maximum recorded thresholds to feature extraction to measure biodiversity indicators. The optimization model was applied to reduce the independent variables. Generally, more than 18,000 samples were modeled for the dependent variables in each model. The regression results demonstrated that the highest R square was related to the songbird (0.93), evenness (0.92), and richness (0.9) indecies in the SVM model and the Shannon index (0.86) in the RF model. The results of acoustics analysis demonstrated that the Acoustic Entropy Index (H), Normalized Difference Soundscape Index (NDSI), Bioacoustics Index (BI), and Acoustic Complexity Index (ACI) indices were suitable because they could serve as proxies for bird richness and activity that reflect differences in habitat quality. Our findings offer using acoustic indicators as an efficient approach for monitoring bird biodiversity in urban parks.

The protective effect of cinnamon and ginger hydro-alcoholic extract on carbon tetrachloride-induced testicular damage in rats.

Sexual dysfunction of men is one of the most serious problems in human society. This study aimed to evaluate the protective effect of cinnamon and ginger extract on testicular damages induced by carbon tetrachloride (CCl4). Thirty-six male Wistar rats were randomly divided into 6 groups (n = 6): 1. Normal control; 2. Carbon tetrachloride (CCl4); 3. CCl4 + Cinnamon; 4. CCl4 + Ginger; 5. CCl4 + Cinnamon and Ginger; and 6. Cinnamon + Ginger. CCl4 (1 ml/kg) was injected intraperitoneally on the 14th day, and cinnamon (50 mg/kg, orally) and ginger (250 mg/kg, orally) were administered daily for 14 days. Fifty hours after the CCl4 injection, the testicles and epididymis were separated and examined as to histological alterations and oxidative stress markers. CCl4 significantly increased malondialdehyde level and decreased total antioxidant capacity when compared to the normal control group (p < .05). In addition, degenerative alterations in the testicular and epididymal tissue were observed in CCl4 group. The pre-treatment with ginger and cinnamon extract significantly improved these parameters when compared to the CCl4 group (p < .05). The results of this study indicated that co-treatment of ginger and cinnamon reduces the damages induced by CCl4 in testicular tissue by increasing antioxidant capacity and reducing lipid peroxidation.

A distributed algorithm for demand-side management: Selling back to the grid.

Demand side energy consumption scheduling is a well-known issue in the smart grid research area. However, there is lack of a comprehensive method to manage the demand side and consumer behavior in order to obtain an optimum solution. The method needs to address several aspects, including the scale-free requirement and distributed nature of the problem, consideration of renewable resources, allowing consumers to sell electricity back to the main grid, and adaptivity to a local change in the solution point. In addition, the model should allow compensation to consumers and ensurance of certain satisfaction levels. To tackle these issues, this paper proposes a novel autonomous demand side management technique which minimizes consumer utility costs and maximizes consumer comfort levels in a fully distributed manner. The technique uses a new logarithmic cost function and allows consumers to sell excess electricity (e.g. from renewable resources) back to the grid in order to reduce their electric utility bill. To develop the proposed scheme, we first formulate the problem as a constrained convex minimization problem. Then, it is converted to an unconstrained version using the segmentation-based penalty method. At each consumer location, we deploy an adaptive diffusion approach to obtain the solution in a distributed fashion. The use of adaptive diffusion makes it possible for consumers to find the optimum energy consumption schedule with a small number of information exchanges. Moreover, the proposed method is able to track drifts resulting from changes in the price parameters and consumer preferences. Simulations and numerical results show that our framework can reduce the total load demand peaks, lower the consumer utility bill, and improve the consumer comfort level.

Comparison of fecal antigen detection using enzyme linked immunosorbent assay with the auramine phenol staining method for diagnosis of human cryptosporidiosis.

BACKGROUND: Fecal antigen detection using the enzyme linked immunosorbent assay (ELISA) and oocyst detection using auramine phenol (AP) staining methods, are told to be more sensitive compared to other conventional methods, for diagnosis of cryptosporidiosis. OBJECTIVES: The aim of the present study was to evaluate the antigen-detection capacity in the stool specimens using ELISA and oocyst detection by AP staining methods, for the diagnosis of human cryptosporidiosis. MATERIALS AND METHODS: A total of 228 fecal samples were collected from residents of rural areas of Hamadan, West of Iran. Each fecal sample was divided into two parts, one kept frozen at -20˚C for Ag-capture ELISA and the other in 10% formalin for the AP staining method. Cryptosporidium Ag-detection ELISA procedure was performed according to the manual of the manufacturer. The preserved samples concentrated using the formalin-ether concentration technique were stained with AP and then investigated under florescent microscopy. RESULTS: Eight (3.5%) and three (1.3%) out of 228 fecal samples were positive for Cryptosporidium infection by ELISA and AP staining methods, respectively. Cryptosporidium Ag-detection using ELISA showed an increased frequency of the infection, compared to the AP staining method (P = 0.062). CONCLUSIONS: For epidemiological studies and diagnostic purposes of the Cryptosporidium infection, especially in asymptomatic individuals, Ag-detection ELISA is an easy to perform and accurate method, compared to other conventional microscopic methods.

Diversity and incrimination of sandflies (Psychodidae: Phlebotominae) captured in city and suburbs of Hamadan, Hamadan province, west of Iran.

OBJECTIVE: To investigate Phlebotomus sand fly fauna and their vectorial capacity in Hamadan, Iran. METHODS: During the three consecutive years (2010-2012), from May to October, sandflies were sampled monthly from residential areas of Hamadan and selected villages using sticky traps. RESULTS: A total of 3 089 sandflies comprising 12 species from 2 genera were collected, of which 6 species are known vectors of leishmaniasis in Iran and/or other parts of the world. About 75% of the collected sandflies were of two dominant species, Phlebotomus kandelaki (38%) and Phlebotomus papatasi (36.6%). These species in combination with Phlebotomus major (6.8%), Phlebotomus sergenti (6.3%), Phlebotomus caucasicus (5.3%), Phlebotomus wenyoni (1.3%), Sergentomyia sintoni (2.9%) and Sergentomyia dentate (2%) collectively comprised the majority of the sandflies. Other species including Phlebotomus halpensis, Phlebotomus longiductus, Phlebotomus comatus and Phlebotomus alexandri each comprised only less than 1% of collected samples. CONCLUSIONS: Although none of the 158 dissected female Phlebotomus kandelaki and Phlebotomus papatasi were infected with leishmania promastigote, it is probable that in the future, factors such as environmental changes, migration and urbanization can ease the transmission of leishmaniases in this area.