XM_HeatForecast: Heating Load Forecasting in Smart District Heating Networks

Forecasting is an important task for intelligent agents involved in dynamical processes. A specific application domain concerns district heating networks, in which the future heating load generated by centralized power plants and distributed to buildings must be optimized for better plant maintenance, energy consumption and environmental impact. In this paper we present XM_HeatForecast a Python tool designed to support district heating network operators. The tool provides an integrated architecture for i) generating and updating in real-time predictive models of heating load, ii) supporting the analysis of prediction performance and errors, iii) inspecting model parameters and analyzing the historical dataset from which models are trained. A case study is presented in which the software is used on a synthetic dataset of heat loads and weather forecast from which a regression model is generated and updated every 24 h, while predictions of load in the next 48 h are performed every hour. Software available at: https://github.com/XModeling Video available at: https://youtu.be/JtInizI4e_s

Assessment of Food Safety Knowledge, Attitudes and Practices of Food Service Staff in Bangladeshi Hospitals: A Cross-Sectional Study.

Food safety knowledge, attitudes and practices among hospital food service staff are crucial in the prevention of foodborne disease outbreaks, as hospitalized patients are more vulnerable to potential hazards. This study, therefore, sought to assess the food safety knowledge, attitudes and practices of food service staff in Bangladeshi hospitals. A cross-sectional study was conducted among 191 food service staff from seven different hospitals in Dhaka and Chattogram from October 2021 to March 2022 using pretested questionnaires. Multiple linear regression was used to identify the factors associated with the food safety knowledge, attitudes and practices. The findings showed moderate knowledge but high levels of attitudes and practices of food safety among hospital food handlers. Food safety knowledge was significantly higher among males, participants from private hospitals and participants working in a hospital that had a food service supervisor and dietitian in charge of food service operations. Moreover, participants from private hospitals and participants working in a hospital that had a food service supervisor and dietitian in charge of food service operations had more positive attitudes and better practices regarding food safety. Hospital management should consider these factors for enhancing food handlers' knowledge and increase training and supervision on food safety practices to reduce foodborne diseases and outbreaks

Feature extraction for the analysis of colon status from the endoscopic images

BACKGROUND: Extracting features from the colonoscopic images is essential for getting the features, which characterizes the properties of the colon. The features are employed in the computer-assisted diagnosis of colonoscopic images to assist the physician in detecting the colon status. METHODS: Endoscopic images contain rich texture and color information. Novel schemes are developed to extract new texture features from the texture spectra in the chromatic and achromatic domains, and color features for a selected region of interest from each color component histogram of the colonoscopic images. These features are reduced in size using Principal Component Analysis (PCA) and are evaluated using Backpropagation Neural Network (BPNN). RESULTS: Features extracted from endoscopic images were tested to classify the colon status as either normal or abnormal. The classification results obtained show the features' capability for classifying the colon's status. The average classification accuracy, which is using hybrid of the texture and color features with PCA (τ = 1%), is 97.72%. It is higher than the average classification accuracy using only texture (96.96%, τ = 1%) or color (90.52%, τ = 1%) features. CONCLUSION: In conclusion, novel methods for extracting new texture- and color-based features from the colonoscopic images to classify the colon status have been proposed. A new approach using PCA in conjunction with BPNN for evaluating the features has also been proposed. The preliminary test results support the feasibility of the proposed method

Personal and Financial Risk Typologies Among Women Who Engage in Sex Work in Mongolia: A Latent Class Analysis

Women engaged in sex work bear a disproportionate burden of HIV infection worldwide, particularly in low- to middle-income countries. Stakeholders interested in promoting prevention and treatment programs are challenged to efficiently and effectively target heterogeneous groups of women. This problem is particularly difficult because it is nearly impossible to know how those groups are composed a priori. Although grouping based on individual variables (e.g., age or place of solicitation) can describe a sample of women engaged in sex work, selecting these variables requires a strong intuitive understanding of the population.Furthermore, this approach is difficult to quantify and has the potential to reinforce preconceived notions, rather than generate new information. We aimed to investigate groupings of women engaged in sex work. The data were collected from a sample of 204 women who were referred to an HIV prevention intervention in Ulaanbaatar, Mongolia. Latent class analysis was used to create subgroups of women engaged in sex work, based on personal and financial risk factors.This analysis found three latent classes, representing unique response pattern profiles of personal and financial risk. The current study approached typology research in a novel, more empirical way and provided a description of different subgroups, which may respond differently to HIV risk interventions

IL-10 Blocks the Development of Resistance to Re-Infection with Schistosoma mansoni

Despite effective chemotherapy to treat schistosome infections, re-infection rates are extremely high. Resistance to reinfection can develop, however it typically takes several years following numerous rounds of treatment and re-infection, and often develops in only a small cohort of individuals. Using a well-established and highly permissive mouse model, we investigated whether immunoregulatory mechanisms influence the development of resistance. Following Praziquantel (PZQ) treatment of S. mansoni infected mice we observed a significant and mixed anti-worm response, characterized by Th1, Th2 and Th17 responses. Despite the elevated anti-worm response in PBMC's, liver, spleen and mesenteric lymph nodes, this did not confer any protection from a secondary challenge infection. Because a significant increase in IL-10-producing CD4+CD44+CD25+GITR+ lymphocytes was observed, we hypothesised that IL-10 was obstructing the development of resistance. Blockade of IL-10 combined with PZQ treatment afforded a greater than 50% reduction in parasite establishment during reinfection, compared to PZQ treatment alone, indicating that IL-10 obstructs the development of acquired resistance. Markedly enhanced Th1, Th2 and Th17 responses, worm-specific IgG1, IgG2b and IgE and circulating eosinophils characterized the protection. This study demonstrates that blocking IL-10 signalling during PZQ treatment can facilitate the development of protective immunity and provide a highly effective strategy to protect against reinfection with S. mansoni