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Throughout his career, Ludwig M. Lachmann theorized about how economies and societies achieve order in an uncertain world full of heterogeneous agents, heterogeneous production factors, and multilayered subjectivity. This article traces how he began his research agenda by expanding the conventional equilibrium framework of the 1930s to include (potentially diverging) expectations but gradually abandoned price coordination as the sole source of order in an economy. Instead, he set out to formulate an institutional theory of socially embedded plan coordination, which transcended the traditional division between commerce and community. This article illustrates this shift in Lachmann's focus by using two of his neglected German publications. Additionally, it lays out how Lachmann's effort in the “thinking in orders” tradition was principally rooted in his dissatisfaction with approaches to economics that reduced it to a “pure logic of choice.” Lachmann instead conceived of his discipline as being something closer to Max Weber's “socioeconomics,” and in this he was strongly influenced by the German historical school. This article explains how, ironically, this tradition, which historically positioned itself in stark opposition to the Austrian school, has—through the mediation of Lachmann—had considerable influence on the recent history of the Austrian school in the United States.

Urban stressors pose a health risk, and individual-level assessments provide necessary and fine-grained insight into exposure. An ever-increasing amount of research literature on individual-level exposure to urban stressors using data collected with personal monitors, has called for an integrated assessment approach to identify trends, gaps and needs, and provide recommendations for future research. To this end, a scoping review of the respective literature was performed, as part of the H2020 URBANOME project. Moreover, three specific aims were identified: (i) determine current state of research, (ii) analyse literature according with a waterfall methodological framework and identify gaps and needs, and (iii) provide recommendations for more integrated, inclusive and robust approaches. Knowledge and gaps were extracted based on a systematic approach, e.g., data extraction questionnaires, as well as through the expertise of the researchers performing the review. The findings were assessed through a waterfall methodology of delineating projects into four phases. Studies described in the papers vary in their scope, with most assessing exposure in a single macro domain, though a trend of moving towards multi-domain assessment is evident. Simultaneous measurements of multiple stressors are not common, and papers predominantly assess exposure to air pollution. As urban environments become more diverse, stakeholders from different groups are included in the study designs. Most frequently (per the quadruple helix model), civil society/NGO groups are involved, followed by government and policymakers, while business or private sector stakeholders are less frequently represented. Participants in general function as data collectors and are rarely involved in other phases of the research. While more active involvement is not necessary, more collaborative approaches show higher engagement and motivation of participants to alter their lifestyles based on the research results. The identified trends, gaps and needs can aid future exposure research and provide recommendations on addressing different urban communities and stakeholders.

Children and adolescents at higher grades of primary education have a level of understanding and education which can be effectively employed in fairly complex citizen science (CS) approaches. CS has been shown to be an effective tool in primary school curriculums. In our research, a group of 7th grade primary school pupils in Ljubljana, Slovenia, was engaged in a CS project exploring urban stressors, as part of the H2020 URBANOME project (www.urbanome.eu). They investigated differences in exposure to noise and air pollution by measuring respective parameters on alternative routes from home to school using next-generation sensing and monitoring devices. Provided with guidance on how to explore the question of exposure and health, they were encouraged to propose the tools and methods to conduct the experiments. Two devices that measure air quality, one measuring particulate matter and one measuring NO2 a smartphone with an external microphone measuring noise, and a smartwatch recording heart rate, activity and location, were provided by the research team. Walking routes included a high-traffic road or alternatively, smaller roads removed from the main road, which have much less traffic. The pupils were presented with the results, which showed that the concentrations of particulate matter and NO2 are higher near the busy road, as are the noise levels. They correctly identified how their personal choices can affect their exposure to various urban stressors. The CS approach showed that a hands-on experience gives pupils a better understanding of their environment and the importance of determining personal exposure to urban stressors.

Citizen Science (CS) is a rapidly growing field of research, increasingly used, among others, in various aspects of environmental health monitoring and health science, including environmental epidemiology. Its major advantage lies in the fact that CS facilitates inclusion of general public in scientific research processes. In recent years, there is a noticeable trend in CS projects - transition from more passive forms of participation, often limited to data collection, to active involvement of citizens in all project phases and research activities (co-created CS). This is largely supported by the rapid development of sensing and supporting information and communications technologies. While co-creation brings new opportunities, a number of challenges still exist and need to be considered when implementing respective CS activities. ln this contribution, some of these opportunities and challenges will be discussed, both of technological and non-technological natures, based on hands-on experience in selected past and on-going CS projects. The general aspects discussed comprise, but are not limited to, the following: (i) user-centered design of tools and their fitness for purpose evaluation; (ii) societal vs. scientific relevance of CS activities; (iii) levels of collaboration between researchers and citizen scientists in data analysing and knowledge generation; (iv) data governance and ownership, including intellectual property aspects; (v) management of volunteer motivations and expectations; (vi) educational value of CS when integrated in the school curriculum; and (vii) measuring the impact of citizen science including user-experience aspects.

Using low-cost portable air quality (AQ) monitoring devices is a growing trend in personal exposure studies, enabling a higher spatio-temporal resolution and identifying acute exposure to high concentrations. Comprehension of the results by participants is not guaranteed in exposure studies. However, information on personal exposure is multiplex, which calls for participant involvement in information design to maximise communication output and comprehension. This study describes and proposes a model of a user-centred design (UCD) approach for preparing a final report for participants involved in a multi-sensor personal exposure monitoring study performed in seven cities within the EU Horizon 2020 ICARUS project. Using a combination of human-centred design (HCD), human-information interaction (HII) and design thinking approaches, we iteratively included participants in the framing and design of the final report. User needs were mapped using a survey (n = 82), and feedback on the draft report was obtained from a focus group (n = 5). User requirements were assessed and validated using a post-campaign survey (n = 31). The UCD research was conducted amongst participants in Ljubljana, Slovenia, and the results report was distributed among the participating cities across Europe. The feedback made it clear that the final report was well-received and helped participants better understand the influence of individual behaviours on personal exposure to air pollution. This work has received funding from the European Union’s Horizon 2020 Programme for research technological development and demonstration under grant agreement No 690105 (Integrated Climate forcing and Air Pollution Reduction in Urban Systems (ICARUS)). This work reflects only the authors’ views, and the European Commission is not responsible for any use that may be made of the information it contains. Funding was received from the Young Researchers Program and P1-0143 program “Cycling of substances in the environment, mass balances, modelling of environmental processes and risk assessment”, both funded by the Slovenian Research Agency. The authors thank Research Infrastructure RECETOX RI (No LM2018121) financed by the Ministry of Education, Youth and Sports, and Operational Programme Research, Development and Innovation-project CETOCOEN EXCELLENCE (No CZ.02.1.01/0.0/0.0/17_043/0009632) for supportive background. Sí

Use of a multi-sensor approach can provide citizens with holistic insights into the air quality of their immediate surroundings and their personal exposure to urban stressors. Our work, as part of the ICARUS H2020 project, which included over 600 participants from seven European cities, discusses the data fusion and harmonization of a diverse set of multi-sensor data streams to provide a comprehensive and understandable report for participants. Harmonizing the data streams identified issues with the sensor devices and protocols, such as non-uniform timestamps, data gaps, difficult data retrieval from commercial devices, and coarse activity data logging. Our process of data fusion and harmonization allowed us to automate visualizations and reports, and consequently provide each participant with a detailed individualized report. Results showed that a key solution was to streamline the code and speed up the process, which necessitated certain compromises in visualizing the data. A thought-out process of data fusion and harmonization of a diverse set of multi-sensor data streams considerably improved the quality and quantity of distilled data that a research participant received. Though automation considerably accelerated the production of the reports, manual and structured double checks are strongly recommended. This work has received funding from the European Union’s Horizon 2020 Programme for Research, Technological Development, and Demonstration, under grant agreement No. 690105 (Integrated Climate forcing and Air Pollution Reduction in Urban Systems (ICARUS)). This work reflects only the authors’ views, and the European Commission is not responsible for any use that may be made of the information it contains. Funding was received from the Young Researchers Program and the P1-0143 program “Cycling of substances in the environment, mass balances, modelling of environmental processes and risk assessment“, both funded by the Slovenian Research Agency. The authors thank RECETOX Research Infrastructure (No. LM2018121) and ACTRIS-CZ Research Infrastructure (No. LM2018122) financed by the Ministry of Education, Youth and Sports and the Operational Programme Research, Development and Innovation (CZ.02.1.01/0.0/0.0/16_013/0001315 and CZ.02.1.01/0.0/0.0/16_013/0001761), as well as the CETOCOEN Excellence Project, supported by the Teaming Action of the EU Horizon 2020 programme (857560) and the Operational Programme Research, Development and Innovation (No. CZ.02.1.01/0.0/0.0/17_043/0009632). Sí

Gas samples were collected from 25 m long horizontal boreholes drilled into the excavation field at 10° inclination to the longwall face in two mining areas, Pesje and Preloge, in the Velenje Coal Mine, Slovenia, from 2013 to 2018. The degassing mechanism of coalbed gas and its stable isotopic composition (δ13CCO2, δ13CCH4, and δ2HCH4) were investigated in boreholes in advance of eight working faces. The major coalbed gas constituents were CO2 and methane. Gas concentrations and isotope values revealed that the methane is biogenic in origin with δ13CCH4 values of -69.4 to -29.5 ‰, δ2HCH4 values of -301 to -222 ‰, and a fractionation factor (αCO2-CH4) of 0.998-1.073, suggesting that methane derives from microbial acetate fermentation and CO2 reduction. The carbon dioxide methane index values ranged from 50.0-98.3 vol.% and δ13CCO2 values from -11.8 to -0.5 ‰, indicating that CO2 is biogenic and endogenic in origin. The degassing mechanism results in isotope fractionation of methane and CO2 for carbon isotopes up to 39.9 ‰ and up to 8.5 ‰, respectively, depending on the position of the excavation fields in space, e.g. under pre-mined coal area, fresh overburden.

Use of a multi-sensor approach can provide citizens a holistic insight in the air quality in their immediate surroundings and assessment of personal exposure to urban stressors. Our work, as part of the ICARUS H2020 project, which included over 600 participants from 7 European cities, discusses data fusion and harmonization on a diverse set of multi-sensor data streams to provide a comprehensive and understandable report for participants, and offers possible solutions and improvements. Harmonizing the data streams identified issues with the used devices and protocols, such as non-uniform timestamps, data gaps, difficult data retrieval from commercial devices, and coarse activity data logging. Our process of data fusion and harmonization allowed us to automate the process of generating visualizations and reports and consequently provide each participant with a detailed individualized report. Results showed that a key solution was to streamline the code and speed up the process, which necessitated certain compromises in visualizing the data. A thought-out process of data fusion and harmonization on a diverse set of multi-sensor data streams considerably improved the quality and quantity of data that a research participant receives. Though automatization accelerated the production of the reports considerably, manual structured double checks are strongly recommended.

The development of smart hydraulic press that allows rapid adaptation to high-volume variant production is a major challenge. Besides tool management, setting the control parameters, which can be considered as a correct press cycle, is an important part to achieve agile production. This paper presents a new approach to automatically generate a hydraulic press cycle where the important data of the production plan is known, such as the data or setting of the forming tool and the data of the product. In this case, RFID tracking system is used to read the tool/product data, which is input data for the mathematical algorithm for calculating the characteristic points of the hydraulic press cycle. The characteristic points are sent to the local PLC and stored as a matrix. The Beckhoff TwinCat platform is used for process control. Finally, a simple bending process is shown as a use case for concept verification.

In this multi-elemental study, 34 elements (Ag, As, Au, Ba, Br, Ca, Cd, Ce, Co, Cr, Cs, Eu, Fe, Ga, Hg, Hf, K, La, Mo, Na, Nd, Rb, Sb, Sc, Se, Sm, Sr, Ta, Tb, Th, U, Yb, Zn and Zr) were analysed in Slovenian coals from operative (Velenje) and non-operative (Kanižarica and Senovo) coal mines and an imported Indonesia coal using k0-Instrumental Neutron Activation Analysis (k0-INAA) and compared to inductively coupled plasma-mass spectroscopy (ICP-MS). Weaker regressions between both methods ICP-MS and k0-INAA are obtained for following elements: Cs, Co, Eu, Se, Sm and Tb with low concentration (below 1 mg/kg). The k0-INAA data are comparable to the ICP-MS data for the majority of elements. The levels of major elements measured with k0-INAA are as follows: Ca>Fe>K>Na>Sr>Ba. Minor and trace elements, as well as rare earth elements (REEs), are comparable with coal values worldwide. Data of trace elements in coal are important since they are related to air emissions. According to our data obtained with both methods (ICP-MS and k0-INAA) we can conclude that concentrations of trace elements, which impact to human health and are combusted (Indonesian and Velenje coal) in Slovenia are comparable to world averages coal.

Knowing what individuals are doing when they are exposed to elevated levels of pollution is crucial to implement plans to reduce possible harm. Merging new sensing technologies with machine learning methods can be used as a tool to recognize complex activities. In this work, a novel approach of providing a wearable airborne particulate matter and ambient sensor in combination with a motion tracking wrist device to 97 individuals involved in the ICARUS H2020 project in Ljubljana, Slovenia, was used. They were instructed to wear the devices for 7 days, while they manually recorded their hourly activities. The compiled dataset was cleaned and separated into a training and testing data set (each containing unique participants). As the activity data was in hourly intervals and sensor data in minute values, two approaches were used: a) transforming each hourly activity to 60-minute iterations and b) averaging sensor minute data to hourly values. These data sets were used in three different models, based on three classification algorithms: k-Nearest Neighbors (IBk), decision tree (J48) and random forest (RandomForest). The results of the models for hourly values showed an accuracy of 31.0%, 28.6% and 35.7% for IBk, J48 and RandomForest, respectively, and for minute values 23.1%, 22.0% and 23.0% for IBk, J48 and RandomForest, respectively. As expected, most misclassified instances were observed for activities with vague definitions, such as resting and playing. Low accuracy can also be explained with the differences in time scales. The accuracy could be improved by more clearly defining the activities and collecting minute value data. To this end, this research provides a crucial first step in determining the possibilities of combining information coming from various new sensing technologies for complex activity recognition.

Multi-elemental (Ca, Mg, Na, K, Al, As, Ba, Cd, Co, Cr, Cu, Fe, Li, Mn, Mo, Ni, P, Pb, Sb, Se, Tl, V, and Zn) and stable isotope (i.e., &delta, 2H, &delta, 18O, and &delta, 13CDIC) analyses were performed on 13 (8 Slovenian and 5 imported) bottled mineral and spring waters from the Slovenian market. In addition, 87Sr/86Sr isotope ratios were determined for the first time. In all analyzed bottled waters, the majority of elements were present although in low concentrations, and according to EU legislation, all were suitable for human consumption. Also, concentrations of major elements (Ca, Mg, Na, and K) were in general agreement with the values reported on the bottle labels, and any differences were the consequence of the natural variability of the water source used for bottling. The exception was one spring water, for which the source location changed, which was confirmed by the &delta, 13CDIC data. Two mineral waters had distinctive elemental compositions due to the particular geology of their recharge areas. The &delta, 13CDIC was also investigated to decipher the carbonate contribution in the bottled waters. The results suggest that dissolution of carbonates and non-equilibrium carbonate dissolution by carbonic acid produced from soil zone CO2 are the predominant geochemical processes influencing the &delta, 13CDIC values of bottled water.

Objectives The aims of this audit were twofold: (1) to demonstrate the contribution of the auditing process in evaluating the success of child and adolescent health policy in Slovenia between 2012 and 2019, and (2) to expand on the commentary published in the International Journal of Public Health in 2019 to demonstrate the benefits of auditing in improving public health policy in general. Methods The audit followed health, safety and environmental approaches as per the standards of public health policy. Results Due to poor intersectoral coordination and weak associations between environmental and health indicators, no clear evidence could be established that child and adolescent health policy contributed to positive changes in child and adolescent health from 2012 to 2019. Conclusions Auditing should become an essential component of measuring the success of public health policies. Attention should also be paid to the following issues affecting youth health: sleeping and eating habits, economic migration, poverty, etc.

In this paper, we summarise lessons learned conducting citizen science (CS) activities within the CitieS-Health H2020 project on the topic of noise exposure and health at a primary school in Ljubljana, Slovenia. Activities were organised in the form of a School Tech-Day Event (STDE) as part of the school&rsquo, s curriculum involving second-grade pupils, ages 7&ndash, 8. The STDE was aligned with the project&rsquo, s methodological framework, which is based on co-creation and co-design principles. To this end, the pupils initially were involved in identifying noise-related issues and translation of selected topics into research questions. Next, together with mentors, they participated in the process of hypothesis formulation and the designing of data collection protocols. Finally, they participated in three focussed noise measurement experiments, as well as data analysis and presentation. We report and critically evaluate the whole chain of activities, focussing on the participant dimension using selected components of the citizen science evaluation framework. The event was very well-received by both pupils and teachers, and their active participation and hands-on experience with scientific processes contributed to their improved scientific literacy. Overall, the demonstrated concept of CS activities has great potential for ongoing inclusion in the school curriculum in its current format, or else adjusted according to specifics from other science and technology fields.