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Somalia experienced its first wave of COVID-19 infections in March 2020 and has experienced fluctuating infection levels since. Longitudinal data on suspected cases of COVID-19, attitudes, and behaviours were collected by telephone interviews of cash-transfer programme beneficiaries from June 2020–April 2021. A multi-media Social and Behaviour Change Communication (SBCC) campaign was designed and implemented from February 2021 to May 2021. Between the end of the first wave and the onset of the second the perceived threat from COVID-19 increased, with the proportion of respondents viewing it as a major threat increasing from 46% to 70% (p = 0.021). Use of face coverings increased by 24% (p < 0.001) and hand shaking and hugging for social greeting decreased, with 17% and 23% more people abstaining from these practices (p = 0.001). A combined preventative behaviour score (PB-Score) increased by 1.3 points (p < 0.0001) with a higher score in female respondents (p < 0.0001). During wave 2, vaccine acceptance was reported by 69.9% (95% CI 64.9, 74.5), overall. Acceptance decreased with increasing age (p = 0.009) and was higher in males (75.5%) than females (67.0%) (p = 0.015). Awareness of the SBCC campaign was widespread with each of the 3 key campaign slogans having been heard by at least 67% of respondents. Awareness of 2 specific campaign slogans was independently associated with an increased use of face coverings (aOR 2.31; p < 0.0001) and vaccine acceptance (aOR 2.36; p < 0.0001). Respondents reported receiving information on the pandemic from a wide range of sources with mobile phones and radio the most common. Trust in different sources ranged widely.

Background During the COVID-19 pandemic, the importance of reliable public health data has been highlighted, as well as the multiple challenges in collecting it, especially in low income and conflict-affected countries. Somalia reported its first confirmed case of COVID-19 on 16 March 2020 and has experienced fluctuating infection levels since then. Objectives To monitor the impact of COVID-19 on beneficiaries of a long-term cash transfer programme in Somalia and assess the utility of a syndromic score case definition and rapid mortality surveillance tool. Methods Five rounds of telephone interviews were conducted from June 2020 – April 2021 with 1,046–1,565 households participating in a cash transfer programme. The incidence of COVID-19 symptoms and all-cause mortality were recorded. Carers of the deceased were interviewed a second time using a rapid verbal autopsy questionnaire to determine symptoms preceding death. Data were recorded on mobile devices and analysed using COVID Rapid Mortality Surveillance (CRMS) software and R. Results The syndromic score case definition identified suspected symptomatic cases that were initially confined to urban areas but then spread widely throughout Somalia. During the first wave, the peak syndromic case rate (311 cases/million people/day) was 159 times higher than the average laboratory confirmed case rate reported by WHO for the same period. Suspected COVID-19 deaths peaked at 14.3 deaths/million people/day, several weeks after the syndromic case rate. Crude and under-five death rates did not cross the respective emergency humanitarian thresholds (1 and 2 deaths/10,000 people/day). Conclusion Use of telephone interviews to collect data on the evolution of COVID-19 outbreaks is a useful additional approach that can complement laboratory testing and mortality data from the health system. Further work to validate the syndromic score case definition and CRMS is justified.

Abstract Background Along bacteria, yeasts are common in forages and forage fermentations as spoilage microbes or as additives, yet few studies exist with species-level data on these fungi’s occurrence in feedstuff. Active dry yeast and other yeast-based products are also common feed additives in animal husbandry. Here, we aimed to characterize both fermented and non-fermented milking cow feedstuff samples from Hungary to assess their microbial diversity in the first such study from Central Europe. Results We applied long-read bacterial metabarcoding to 10 fermented and 25 non-fermented types of samples to assess bacterial communities and their characteristics, surveyed culturable mold and yeast abundance, and identified culturable yeast species. Fermented forages showed the abundance of Aerococcaceae, Bacillaceae, Brucellaceae, Lactobacillaceae, Staphylococcaceae, and Thermoactinomycetaceae, non-fermented ones had Cyanothecaceae, Enterobacteriaceae, Erwiniaceae, Gomontiellaceae, Oxalobacteraceae, Rhodobiaceae, Rickettsiaceae, and Staphylococcaceae. Abundances of bacterial families showed mostly weak correlation with yeast CFU numbers, only Microcoleaceae (positive) and Enterococcaceae and Alcaligenaceae (negative correlation) showed moderate correlation. We identified 14 yeast species, most commonly Diutina rugosa, Pichia fermentans, P. kudriavzevii, and Wickerhahomyces anomalus. We recorded S. cerevisiae isolates only from animal feed mixes with added active dry yeast, while the species was completely absent from fermented forages. The S. cerevisiae isolates showed high genetic uniformity. Conclusion Our results show that both fermented and non-fermented forages harbor diverse bacterial microbiota, with higher alpha diversity in the latter. The bacterial microbiome had an overall weak correlation with yeast abundance, but yeasts were present in the majority of the samples, including four new records for forages as a habitat for yeasts. Yeasts in forages mostly represented common species including opportunistic pathogens, along with a single strain of Saccharomyces used as a feed mix additive.

This paper demonstrates a practical implementation of a dynamic line rating (DLR) system and an effective ice prediction and prevention method using line monitoring sensors within the FLEXITRANSTORE international project framework. The presented anti-icing system operated continuously for two years. As a part of the project, 4 line monitoring sensors and 2 weather stations were installed on that section of the power line where icing is most likely to occur. These sensors worked continuously and reliably during the demonstration period. The sensor measurements were supplemented with the load value from the SCADA system and weather forecasts, with the help of which, in addition to the real-time line rating and sag-clearance analysis, a predetermined line rating could also be determined. The investigated system also included an ice prediction subsystem as well as a sag-calculation-based ice detection subsystem. Based on the comparison of the measured and calculated parameters, it can be said that both the operation of the sensors and the quality of the data provided by them were satisfactory. In the case of conductor temperature calculation, the developed mathematical models, which can be applied independently, provided information to the system operator with almost similar accuracy than sensors’ measurements. During the observed period, the ice prediction and detection subsystem were also tested and functioned correctly. As an overview of the project, it can be concluded that an efficient DLR-sensor-based anti-icing system is possible to be realized on the high voltage distribution power grid.

In order to adjust the electric power network to today’s trends—such as the charging of electric vehicles, design of the Internal Electricity Market (IEM), headway of renewable energy sources, etc.—the demand for flexible network solutions is increasingly significant. Dynamic line rating (DLR) technology offers a flexible solution for the uprating of overhead lines. Moreover, the DLR methodology can be used in a wider system approach in order to establish a line management system, including functions such as ice prevention subsystems or the real-time tracking of clearances. Therefore, the extension possibilities and operational features of DLR-based systems have been extensively researched in the last few years, which is also confirmed by the high number of pilot projects funded for research and development on the topic of DLR. The key question during the implementation of a DLR system is the obtainable operational safety of such a system. This mainly depends on the installation places of the field equipment and the accuracy of the line rating calculation models. The aim of this article is the comparison of the so far available international line rating calculation models and also to propose another way for the determination of the real-time line rating. Moreover, laboratory measurements and case studies are presented for the confirmation of the proposed model’s reliability.

This paper presents a novel installation protocol to build a reliable and economical line monitoring system on high voltage power lines. The proposed method is able to iteratively determine the required number of sensors and their installation location for a predefined level of risk. First, it requires a general analysis of the transmission line, which ends with a critical span analysis. Then the risk arising from the variability of weather parameters along the transmission line must be determined. Finally, it is necessary to consider what kind of problem the thermal overheating can cause at the conductor (sagging, annealing) and which additional stages can be used to reduce the risk factor to the permissible level. A case study was investigated with the data of a Central-European high voltage power line to present how the proposed method works. The results showed that there are power lines on which only distributed sensor installation concepts result in a safe and economical solution. Applying the proposed method, a comprehensive and robust sensor system can be implemented, which can be a solid basis for any dynamic line rating (DLR) system.

Nowadays the reliable availability of electricity is expected by both industrial and residential consumers. However, the generation, transmission and distribution all pose engineering challenges in adapting to consumers and sustainable directives while maintaining operational safety. The increasing demand for electricity on the consumer side and the growing number of renewable energy sources (RES) on the generation side are supporting the spread of capacity uprating methods. Dynamic Line Rating (DLR) is a novel, cost-effective line management method with which system operators are able to utilize existing power lines with greater efficiency than with traditional techniques. While the use of DLR has many benefits, there are also challenges that system operators have to cope with at system-level implementation. One of the most significant of these challenges is to find the balance between the required infrastructure for DLR implementation and the reliability of the implemented system. The aim of this article is to present a novel methodology for critical span identification based on which the sensor measurements accurately represent the prevailing conditions along the whole overhead line. Contrary to current methods, the proposed critical span analysis method takes into account the clearance of the conductors, which provides compliance with legal requirements. Furthermore, the uncertainty caused by using weather data to determine local conductor annealing is also eliminated with the recommended method. This way a flexible power system can be created that meets current needs, such as the integration of renewable and distributed energy sources or cross-border energy trade, while at the same time it enhances the operational safety of overhead lines.

The purpose of this paper is to present the sensor placement strategies that currently determine the thermal monitoring of the phase conductors of high-voltage power lines. In addition to reviewing the international literature, a new sensor placement concept is presented based on a strategy centered on the following question: What are the chances of thermal overload if devices are only placed in certain tension sections? In this new concept, the number and installation location of the sensors are determined in three steps, and a new type of tension-section-ranking constant is introduced that is universal in space and time. The simulations based on this new concept show that the data-sampling frequency and the type of thermal constraint influence the number of sensors. The paper’s main finding is that there are cases when only a distributed sensor placement strategy can result in safe and reliable operation. However, due to requiring a large number of sensors, this solution means additional expenses. In the last section, the paper presents different possibilities to reduce costs and introduces the concept of low-cost sensor applications. These devices can result in more flexible network operation and more reliable systems in the future.

A korrupcióban részt vevő feleknek meg kell bízniuk egymásban. Jávor–Jancsics [2013] cikkükben a magyar korrupciós viszonyokat vizsgálták. Legérdekesebb eredményük, hogy a korrupcióban a felső és a középső réteg szorosan együttműködik a visszaélésekben. A középső réteg arra használja szakértelmét, hogy a felső réteg korrupciós tevékenysége papíron legálisnak tűnjön. Dolgozatunkban analitikus keretben és ágens alapú modell segítségével is megvizsgáltuk, milyen ösztönzők segítségével akadályozható meg a vállalati korrupció e forgatókönyv esetén. Azt is figyelembe vettük, hogy a már régóta együtt dolgozó felettesek és szakértők együttes tapasztalatukból fakadóan több jövedelmet képesek termelni a vállalat számára, ami viszont a jövedelmek eltitkolása révén a korrupció mértékét is növelheti. Analitikus és szimulációs eredményekkel is alátámasztjuk, hogy a korrupció visszaszorításának legkézenfekvőbb módja ilyen körülmények között a felső réteg megfelelő díjazása lehet.

„Workshop on Behavioral Economics and Industrial Organization” címmel rendezett nemzetközi workshopot a Budapesti Corvinus Egyetemen a Tasnádi Attila (BCE, Matematika Tanszék) vezette MTA–BCE „Lendület” Stratégiai Interakciók Kutatócsoport 2014 szeptember 1–2-án.

This paper aims to demonstrate the performance and reliability analysis of a dynamic line rating (DLR) system at the Bulgarian demonstration site of the FLEXITRANSTORE project. As part of the project, various manufacturers’ different line monitoring DLR sensors and weather stations were installed on a 110 kV double-circuit overhead line (OHL). These devices provided input parameters to the DLR system based on objective measurements. This paper used statistical tools to examine the reliability and accuracy of installed devices, thus making products from different manufacturers comparable. In addition, two independent line monitoring and DLR models have been developed: the black-box and extended white-box models. The performances of the two models were analyzed for the same input parameters and compared to the field measurements. Based on the presented results, the reliability and accuracy of the applied weather stations of different companies were almost the same. This conclusion cannot be said for DLR line monitoring sensors, where the devices could be differentiated based on reliability and measurement accuracy results. In terms of models, the usability of the extended white-box model seemed to be limited in certain weather conditions, implicating a more significant role for soft-computing-based DLR models in the future. In addition to the results, root causes for the errors and future directions that may provide a framework for further research are also presented.

Exceeding the electric field’s limit value is not allowed in the vicinity of high-voltage power lines because of both legal and safety aspects. The design parameters of the line must be chosen so that such cases do not occur. However, analysis of several operating power lines in Europe found that the electric field strength in many cases exceeds the legally prescribed limit for the general public. To illustrate this issue and its importance, field measurement and finite element simulation results of the low-frequency electric field are presented for an active 400 kV power line. The purpose of this paper is to offer a new, economical expert system based on dynamic line rating (DLR) that utilizes the potential of real-time power line monitoring methods. The article describes the expert system’s strengths and benefits from both technical and financial points of view, highlighting DLR’s potential for application. With our proposed expert system, it is possible to increase a power line’s safety and security by ensuring that the electric field does not exceed its limit value. In this way, the authors demonstrate that DLR has other potential applications in addition to its capacity-increasing effect in the high voltage grid.