Effect of Wastewater Treatment on Bacterial Community, Antibiotic-Resistant Bacteria and Endoparasites.

Wastewater and wastewater treatment plants serve as urban reservoirs of pathogenic microorganisms. Wastewaters frequently contain bacteria, antibiotic-resistant bacteria, and developmental stages of parasites with significant zoonotic potential. Five wastewater treatment plants in the central part of Slovakia were investigated to determine the effect of treatment on bacterial community, antibiotic-resistant bacteria, and the occurrence of helminth eggs. Although all monitored chemical factors (chemical oxygen demand, biochemical oxygen demand, N-NH4, total nitrogen, and total phosphorus) in the effluent were in line with the legislative standards for discharge into public waterways, the results of minimal inhibitory concentrations show that reclaimed water harbors E. coli resistant to several commonly used antibiotics (ampicillin, piperacillin, and tazobactam, combine ampicillin and sulbactam, cefotaxime, tetracycline). The presence of endoparasite developmental stages in wastewater and sludge (Ascaris spp., Hymenolepis nana, eggs from the Ancylostomatidae family, Giardia duodenalis) indicates potential health risks for humans and workers at these sites. Treatment such as composting before applying sludge to land is necessary to reduce human pathogens.

Neglected Diseases-Parasitic Infections among Slovakian Children from Different Populations and Genotypes of Giardia duodenalis.

Children are most prone to parasitic infections. The objectives of the study were to examine the occurrence of parasitic infections in children from different populations and to perform molecular characterization of human Giardia duodenalis isolates. We examined 631 stool samples from Roma and non-Roma children for the presence of parasitic developmental stages. Samples were collected from three eastern Slovakia districts. The ages of the children ranged from 1 months to 17 years. Subsequently, the molecular characterization of human G. duodenalis isolates by PCR detected triosephosphate isomerase (tpi) and beta-giardin (bg) genes was performed. The overall prevalence of parasitic infection was 19.8%. Ascaris lumbricoides eggs were the most frequent, with an occurrence of about 13.8%. G. duodenalis cysts were present in 6.3% of samples. G. duodenalis isolates obtained from 13 children were subjected to DNA sequencing with tpi and bg genes. Five isolates were categorized as bearing subassemblage BIII, the three isolates as subassemblage BIV, one person was infected with a mixture of subassemblages BIII and BIV, four children had subassemblage AII, and one isolate revealed a structure corresponding with subassemblage AI. Our work is proof that poverty and poor hygiene contribute the most to public health problems associated with neglected parasitic diseases.

An Image Encryption Algorithm Using Logistic Map with Plaintext-Related Parameter Values.

This paper deals with a plaintext-related image encryption algorithm that modifies the parameter values used by the logistic map according to plain image pixel intensities. The parameter values are altered in a row-wise manner, which enables the usage of the same procedure also during the decryption. Furthermore, the parameter modification technique takes into account knowledge about the logistic map, its fixed points and possible periodic cycles. Since the resulting interval of parameter values achieves high positive values of Lyapunov exponents, the chaotic behavior of the logistic map should be most pronounced. These assumptions are verified by a set of experiments and the obtained numerical values are compared with those reported in relevant papers. It is found that the proposed design that uses a simpler, but well-studied, chaotic map with mitigated issues obtains results comparable with algorithms that use more complex chaotic systems. Moreover, the proposed solution is much faster than other approaches with a similar purpose.

Multilayered Network Model for Mobile Network Infrastructure Disruption.

In this paper, the novel study of the multilayered network model for the disrupted infrastructure of the 5G mobile network is introduced. The aim of this study is to present the new way of incorporating different types of networks, such as Wireless Sensor Networks (WSN), Mobile Ad-Hoc Networks (MANET), and DRONET Networks into one fully functional multilayered network. The proposed multilayered network model also presents the resilient way to deal with infrastructure disruption due to different reasons, such as disaster scenarios or malicious actions. In the near future, new network technologies of 5G networks and the phenomenon known as the Internet of Things (IoT) will empower the functionality of different types of networks and interconnects them into one complex network. The proposed concept is oriented on resilient, smart city applications such as public safety and health and it is able to provide critical communication when fixed network infrastructure is destroyed by deploying smart sensors and unmanned aerial vehicles. The provided simulations shows that the proposed multilayered network concept is able to perform better than traditional WSN network in term of delivery time, average number of hops and data rate speed, when disruption scenario occurs.