Animal waste is generated at an increased rate, and its disposal is attracting wide public attention. Anaerobic digestion is considered the most promising option for reducing this waste, and simultaneously, it produces renewable energy. Lignin contained in lignocellulosic biomass is hardly biodegradable, thus pre-treatment has to be considered prior to digestion. The possibility of biological pre-treatment of chicken manure with sawdust using Pleurotus ostreatus fungi was investigated in our study. This animal waste was used as a substrate for further biogas production. To provide a better nutrient balance, we added two different co-substrates, wheat straw and Miscanthus. Mixtures with different mass ratios of chicken manure with sawdust/ordinary wheat straw, as well as chicken manure with sawdust/pre-treated wheat straw were incubated for 30 d. The same experiments were performed with Miscanthus. During incubation, samples were taken at predetermined time intervals, and the concentration of acid-insoluble lignin was determined. Additionally, concentrations of glucose and xylose in the filtrate taken at the end of the Klasson procedure were determined in the initial samples and in the samples after 30 d of incubation. Despite our expectations, almost no lignin degradation was observed. Insignificant decreases in glucose and xylose concentrations after 30 d is attributed to fungi ingestion. Obtained results show that Pleurotus ostreatus, as a white-rot fungi with a unique enzymatic system and as generally preferred organisms for lignin degradation, is, therefore, not suitable for delignification of this particular animal waste.

Irrigation expansion onto rainfed croplands is an important part of the portfolio of agricultural measures, contributing to a more resilient crop production while enhancing agricultural yields. Existing global assessments of irrigation illustrate the biophysical potential, but generally do not account for socioeconomic and environmental constraints to irrigation deployment. Here we provide scenarios of regionalized sustainable irrigation expansion linked to socioeconomic projections from the Shared Socioeconomic Pathways framework, while accounting for biophysical irrigation limits. Under a Sustainability scenario, we find that sustainable irrigation could feed 2 billion people globally by 2100. With an additional 90 million people, sub-Saharan Africa is the region with the highest percentage increase in people fed via sustainable irrigation deployment. However, even under the most optimistic scenarios only half of the theoretically possible global biophysical irrigation potential would be utilized after accounting for socioeconomic constraints. Our results highlight the need for appropriate representation of socioeconomic factors in scenarios of future irrigation deployment.

The purpose of this paper is to analyze and compare two different business models called business to business and business to consumer in Western Balkan countries and Bulgaria. The first, model - business to business (B2B) is defined as the transfer of goods and services between businesses or firms without interference of consumer. The second model, business to consumer (B2C) is customer oriented in which the goods and services are sold immediately to customers in the market. This study focuses on the performance of these two business models in regional countries which are: Albania, Bulgaria, Montenegro, North Macedonia and Serbia. Our analysis intends to provide information regarding the countries’ development on different sectors within B2B and B2C models that are affected by specific indicators such as net salaries, total employment level, investment and exports, and research & innovation. Using statistical methods such as t-test, z-test, F-test or ANOVA and regression, the data were analyzed and the results were compared among the listed developing countries. Finally, this dissection represents the relationship between two independent variables, Net Salaries and Employment where specific dependent variables significantly contribute in North Macedonia and Serbia.

The rapid increase in number of devices in Internet-of-Things generates astronomic amounts of data. Dealing with noisy and low quality data uses more effort than the data analysis itself. Dealing with noisy data at the source would significantly reduce the effort of pre-processing during analysis, as well as the storage and bandwidth overhead. In this paper we introduce an Adaptive Signal Processing Platform (ASPF) for CPS/IoT Ecosystems. It provides ability to dynamically detect noise variation in a signal and successfully filter these components out of the signal leaving only clean and useful data. The paper shows two approaches with different requirements on effort and scalability.

This paper introduces RVAF, a runtime verification (RV) extension of the Arrowhead Framework (AF) with container-based service-deployment and runtime-enforcement of a desired quality of service (QoS). AF is a service-oriented middleware architecture for IoT-applications, consisting of a set of core and auxiliary services and systems, respectively. The QoS manager (QoSM) is one AF’s most important auxiliary systems, which can be used to guarantee the application’s QoS for a wide set of parameters. In RVAF the QoS offered to a particular IoT-application is specified in signal temporal logic, and is continuously monitored by the RVAF-QoSM. In case of an imminent violation, RVAF automatically initiates a container-based reconfiguration, which is ensured to maintain the desired QoS. RVAF is beneficial to large IoT-applications, where the use of continuous-integration and continuous-deployment tools, is not only a recommended practice but also a necessity. Moreover, the use of RVAF is advantageous both during the development of an IoT application, and after its deployment. We describe the architecture of RVAF, provide its formal underpinning, and demonstrate the usefulness of RVAF supported by an industrial IoT application. The main contribution of this work is to show what it takes to incorporate RV concepts into modern SOA frameworks supporting the development of IoT applications.

The energy efficiency represents an international and multi-faceted phenomenon. It is especially important in the countries belonging to the Balkan’s region of the Southeastern Europe (SE). The research problem addressed in this paper focuses on the improvements in the inherent energy inefficiency by the means of quality financing of investment arrangements. This paper utilizes detailed literature review of multi-faceted sources, journal articles, private and government publications. Furthermore, the obstacles to attracting viable sources of private financing shall also be researched and addressed. Semi- developed and still developing Balkan countries have been experiencing severe lack of diversified financial instruments. The financial risks, energy poverty and low incomes, lack of appropriate understanding of the market and the absence of the appropriate regulatory framework have been identified as the major obstacles to attracting viable private financing. There are several issues impacting the attraction of private financing arrangements. These barriers could be summed up as the lack of appropriate regulatory framework, deficiencies in the proper market understanding, inherent presence of energy poverty and low incomes, multitude of financial risks, lack of skilled human resources, the presence of the so-called split incentives and fragmentation issues in common decision-making process. The so-called multiple benefits approach (MBA) to energy efficiency investments tend to widen the energy efficiency perspectives beyond the traditional measures of reducing energy demand and lowering greenhouse gas emissions. This approach looks into multiple spheres by assessing multitude of different benefits to stakeholders. In conclusion, the big disparity in size and variety or financial supporting instruments between the EU members and non-member states must be addressed and reduced.

Phthalates are widely used in consumer products. Exposure to phthalates can lead to adverse health effects in humans, with early-life exposure being of particular concern. Phthalate exposure occurs mainly through ingestion, inhalation, and dermal absorption. However, our understanding of the relative importance of different exposure routes is incomplete. This study estimated the intake of five phthalates from the residential indoor environment for 455 Swedish pregnant women in the SELMA study using phthalate mass fraction in indoor dust and compares these to total daily phthalate intakes back-calculated from phthalate metabolite concentrations in the women's urine. Steady-state models were used to estimate indoor air phthalate concentrations from dust measurements. Intakes from residential dust and air made meaningful contributions to total daily intakes of more volatile di-ethyl phthalate (DEP), di-n-butyl phthalate (DnBP), and di-iso-butyl phthalate (DiBP) (11% of total DEP intake and 28% of total DnBP and DiBP intake combined). Dermal absorption from air was the dominant pathway contributing to the indoor environmental exposure. Residential exposure to less volatile phthalates made minor contributions to total intake. These results suggest that reducing the presence of low molecular weight phthalates in the residential indoor environment can meaningfully reduce phthalate intake among pregnant women.

This paper presents a novel hierarchical motion planning approach based on Rapidly-Exploring Random Trees (RRT) for global planning and Model Predictive Control (MPC) for local planning. The approach targets a three-wheeled cycle rickshaw (trishaw) used for autonomous urban transportation in shared spaces. Due to the nature of the vehicle, the algorithms had to be adapted in order to adhere to non-holonomic kinematic constraints using the Kinematic Single-Track Model. The vehicle is designed to offer transportation for people and goods in shared environments such as roads, sidewalks, bicycle lanes but also open spaces that are often occupied by other traffic participants. Therefore, the algorithm presented in this paper needs to anticipate and avoid dynamic obstacles, such as pedestrians or bicycles, but also be fast enough in order to work in real-time so that it can adapt to changes in the environment. Our approach uses an RRT variant for global planning that has been modified for single-track kinematics and improved by exploiting dead-end nodes. This allows us to compute global paths in unstructured environments very fast. In a second step, our MPC-based local planner makes use of the global path to compute the vehicle's trajectory while incorporating dynamic obstacles such as pedestrians and other road users. Our approach has shown to work both in simulation as well as first real-life tests and can be easily extended for more sophisticated behaviors.

The worldwide spread of a new coronavirus (SARS-CoV-2) since December 2019 has posed a severe threat to individuals’ well-being. While the world at large is waiting that the released vaccines immunize most citizens, public health experts suggest that, in the meantime, it is only through behavior change that the spread of COVID-19 can be controlled. Importantly, the required behaviors are aimed not only at safeguarding one’s own health. Instead, individuals are asked to adapt their behaviors to protect the community at large. This raises the question of which social concerns and moral principles make people willing to do so. We considered in 23 countries (N = 6948) individuals’ willingness to engage in prescribed and discretionary behaviors, as well as country-level and individual-level factors that might drive such behavioral intentions. Results from multilevel multiple regressions, with country as the nesting variable, showed that publicized number of infections were not significantly related to individual intentions to comply with the prescribed measures and intentions to engage in discretionary prosocial behaviors. Instead, psychological differences in terms of trust in government, citizens, and in particular toward science predicted individuals’ behavioral intentions across countries. The more people endorsed moral principles of fairness and care (vs. loyalty and authority), the more they were inclined to report trust in science, which, in turn, statistically predicted prescribed and discretionary behavioral intentions. Results have implications for the type of intervention and public communication strategies that should be most effective to induce the behavioral changes that are needed to control the COVID-19 outbreak.

Abstract Healthcare waste (HCW) management is a complex and challenging problem. It is one of the priorities in health. An increase in the number of the health services provided leads to an increase in the amount of HCW, which has particularly been noticeable in recent years. Since this is the waste that may pose a risk to humans and the environment, it is necessary to ensure an adequate treatment of the same. HCW management is particularly important in developing countries, due to inappropriate disposal methods, underfunding and a lack of the infrastructure. In order to achieve the cost-effectiveness and sustainability of this area, HCW should be minimized through an adequate treatment of the same. The Public Enterprise Zdravstvo Brcko (Brcko Health System) has intensively been addressing the HCW management issue. They have decided to upgrade the HCW system by purchasing a new infectious waste treatment facility. The paper is aimed at creating a new original integrated multicriteria decision-making model based on D numbers for processing fuzzy linguistic information. This model will serve to support management in the procurement of the mentioned facility. The model integrates the benefits of different approaches and theories. An initial model was formed, consisting of the six potential solutions evaluated based on the 18 criteria classified into the following four groups: social, environmental, economic and technological. Four experts in this field evaluated the criteria and potential solutions. Then, a new Best-Worst Method based on D numbers (BWM-D) was applied in order to determine the significance of the criteria. After that, a Multi-Attributive Border Approximation Area Comparison Based on D numbers (MABAC-D) was developed and applied so as to evaluate and select an infectious waste treatment facility. The results have shown that the alternative A1 gives the best results, whereas the alternative A5 shows the worst results. Finally, a sensitivity analysis was performed to validate the obtained results. In this part of the paper, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS-D) and VIsekriterijumska Optimizacija Kompromisnog Resenja (VIKOR-D) were developed in order to validate the results. When procuring a new Contagious Waste Treatment System, the characteristics of the available devices need be perceived and all the criteria need be taken into account in order to provide a device which will solve the HCW problem in the best way. This paper has shown how D numbers can be used when making a selection of an HCW management device, and also how all the characteristics of such a device can be perceived and how the device demonstrating the best characteristics can be selected.

The impacts of climate change are affecting human societies today. In parallel, socio-economic development has increased the capacity of countries around the global to adapt to those impacts although substantial challenges remain. Ongoing climate change will continue to result in a pressure to adapt, while socio-economic development could make it easier to do so. Countries’ effectiveness in fostering climate resilience will depend on the pace of both developments under different socio-economic and emission pathways. Here we assess trajectories of adaptation readiness in comparison with the continued emergence of hot days as a proxy for climate change hazards for different emission and socio-economic pathways over the 21st century. Putting the future evolution of both indices in relation to the observed dynamics over the recent past allows us to provide an assessment of the prospects of future climate resilience building beyond what has been experienced to date. We show that only an inclusive and sustainable stringent mitigation pathway allows for effective climate resilient development over the 21st century. Less inclusive or fossil-fuel driven development will not allow for improvements in resilience building beyond the recent past. Substantial differences emerge already in the 2020s. Our findings underscore the paramount importance of achieving the Paris Agreement goals to enable climate-resilient, sustainable development.

The interference of matter waves is one of the intriguing features of quantum mechanics that has impressed researchers and laymen since it was first suggested almost a century ago. Nowadays, attosecond science tools allow us to utilize it in order to extract valuable information from electron wave packets. Intense laser fields are routinely employed to create electron wave packets and control their motion with attosecond and ångström precision. In this perspective article, which is based on our debate at the Quantum Battles in Attoscience virtual workshop 2020, we discuss some of the peculiarities of intense light-matter interaction. We review some of the most important techniques used in attosecond imaging, namely photoelectron holography and laser-induced electron diffraction. We attempt to ask and answer a few questions that do not get asked very often. For example, if we are interested in position space information, why are measurements carried out in momentum space? How to accurately retrieve photoelectron spectra from the numerical solution of the time-dependent Schrödinger equation? And, what causes the different coherence properties of high-harmonic generation and above-threshold ionization?

Rahmanzadeh et al. quantify—for the first time in vivo—the relative damage to myelin and axons across the multiple sclerosis spectrum, in different types of lesions and in normal-appearing tissue. The data confirm neuropathological findings and extend them by revealing the complexity of the disease in living patients.