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Data-driven urbanism is often entangled with the smart city and practiced in a way that prioritizes control over physical objects and downplays the human and political aspects of data. We label this approach 'hard city sensing' (HCS) and we argue that the rise of the 'digital city' offers the empirical foundation for more humanistic approaches. Driven by the ambition to untangle data-driven urbanism from HCS, this paper reviews two decades of scholarship that has used digital traces as an empirical ground for understanding urban phenomena. The review identifies four distinct ways of working with digital traces of which three pave the way for new ways of problematizing the city. Instead of abandoning the idea of data-driven urbanism, we propose the framework of 'soft city sensing' (SCS) as way to re-engage with it with inspiration from these pioneering works. However, this requires a willingness to revisit central epistemological commitments that currently serve as standards for how to "properly" do data projects. We therefore urge qualitative urban scholars to ponder the possibilities of furthering their urban interest by 'thinking with algorithms' while retaining their interpretative ambitions just as we identify a need for urban decion-makers to expand their criteria for what serves as valid data inputs to urban planning. • Data practices in the smart city prioritize control over physical objects and downplay human and political aspects of data. • Inspiration from computational humanities can motivate a form of 'Soft City Sensing' that emphasize the qualitative and explorative potential in urban digital traces. • Since 2000 we detect four approaches to work with digital traces in an urban context. Soft City Sensing is one of them. • Soft City Sensing have the potential to re-problematize the city and invite new experts into data-driven urbanism. • Soft City Sensing requires us to revisit assumptions concerning bias, the empirical ground and the ontology of maps. [ABSTRACT FROM AUTHOR]

Abstract: A one-step synthesis of the stable [4]helicenium dye, 1,13-dimethoxy-chromeno[2,3,4-kl]xanthenium hexafluorophosphate (DMCX+) from the readily available tris(2,6-dimethoxyphenyl)carbenium ion is reported. The crystal structure, the chemical stability, and dye properties of the DMCX+ helicenium system are described. [Copyright &y& Elsevier]

Abstract: Hydrodeoxygenation of waste fats and oils is a viable method for producing renewable diesel oil. In this study a model feed consisting of oleic acid and tripalmitin in molar ratio 1:3 was hydrotreated at 325°C with 20bars H2 in a stirred batch autoclave with a 5wt% Pt/γ-Al2O3 catalyst, and samples were extracted periodically and analyzed on GC. Despite the significant hydrogen pressure hydrogenation of both reactants were limited and decarboxylation or decarbonylation of the ester and carboxylic acid functionalities were highly favored, yielding carbon chain lengths of odd numbers. Moreover, Pd/γ-Al2O3 was observed to be slightly more active than Pt/γ-Al2O3 and had a higher ratio of decarboxylation and decarbonylation to hydrogenation, while Ni/γ-Al2O3 was substantially less active than Pt and also showed a markedly lower ratio of decarboxylation and decarbonylation to hydrogenation. Variation of the temperature showed that triglycerides as well as free fatty acids were converted at all investigated temperatures, but the conversion of oleic acid increased from 6% to 100% when the temperature was increased from 250°C to 325°C. The tripalmitin reacted via a palmitic acid intermediate, and its conversion was limited by formation of this free fatty acid. [Copyright &y& Elsevier]

Abstract: Background: Sentinel lymph node biopsy was implemented in the treatment of early breast cancer with the aim of reducing shoulder and arm morbidity. Relatively few prospective studies have been published where the morbidity was assessed by clinical examination. Very few studies have examined the impact on shoulder mobility of node positive patients having a secondary axillary dissection because of the findings of metastases postoperatively. Aim: We aimed to investigate the objective and subjective arm morbidity in node negative and node positive patients. Methods and materials: In a prospective study, 395 patients with tumors less than 4cm, were included. Patients were recruited from seven Danish breast cancer clinics. Both subjective and objective arm and shoulder morbidity were measured before, 6 and 18 months after the operation. Results: Comparing node negative patients having a sentinel lymph node biopsy with node negative patients having a lymph node dissection of levels I and II of the axilla, we found significant increase in arm volume among the patients who had an axillary dissection. Only minor, but significant, differences in shoulder mobility were observed comparing the two groups of node negative patients. Highly significant difference was found comparing sensibility. Comparing the morbidity in node positive patients who had a one-step axillary dissection with patients having a two-step procedure (sentinel lymph node biopsy followed by delayed axillary dissection) revealed no difference in objective or subjective arm morbidity. Conclusion: Node negative patients operated with sentinel lymph node biopsy have less arm morbidity compared with node negative patients operated with axillary lymph node dissection. Node positive patients who had a secondary axillary lymph node dissection after sentinel lymph node biopsy had no difference in either objective or subjective morbidity compared with node positive patients having a one-step axillary dissection. [Copyright &y& Elsevier]

A hybrid Bayesian network (BN) was developed for predicting the acute toxicity of chemicals to fish, using data from fish embryo toxicity (FET) testing in combination with other information. This model can support the use of FET data in a Weight-of-Evidence (WOE) approach for replacing the use of ju-venile fish. The BN predicted correct toxicity intervals for 69%–80% of the tested substances. The model was most sensitive to components quantified by toxicity data, and least sensitive to compo-nents quantified by expert knowledge. The model is publicly available through a web interface. Fur-ther development of this model should include additional lines of evidence, refinement of the discre-tisation, and training with a larger dataset for weighting of the lines of evidence. A refined version of this model can be a useful tool for predicting acute fish toxicity, and a contribution to more quantitative WOE approaches for ecotoxicology and environmental assessment more generally. Image 1 • A Bayesian network (BN) was developed to predict the toxicity of chemicals to fish. • The BN uses fish embryo toxicity data in a quantitative weight-of-evidence approach. • The BN integrates physical, chemical and toxicological properties of chemicals. • Correct toxicity intervals were predicted for 69–80% of test cases. • The BN is publicly available for demonstration and testing through a web interface. [ABSTRACT FROM AUTHOR]

The European spruce bark beetle ' Ips typographus L.' is the most serious disturbance agent for European forests. The complex interactions of many influencing factors need to be integrated into a model-based decision-support system to reduce the potential loss of forests. This paper compares two methodological approaches for spatially-explicit prediction of the predisposition for bark beetle infestations. The fuzzy analytic hierarchy process and the Bayesian belief networks were used in combination with a geographical information system to manage uncertainties. Using available data resources, the two approaches were evaluated to produce robust results for forest practitioners and to support measures to minimize the spread of bark beetles. The findings revealed that nearly 32% of the sites investigated in a case study were moderately-high or high risk categories. It is concluded that BBN is more efficient. Both methods can easily be used to analyze environmental problems involving complex interactions among various criteria. [Display omitted] • Comparison of the application of spatial BBN and fuzzy-AHP in forest ecology. • Spatially explicit evaluation of the predisposition of bark beetle infestation. • Participatory process to quantify expert and stakeholder perceptions. • BBN approach more efficient than fuzzy-AHP. [ABSTRACT FROM AUTHOR]

The paper demonstrates the use of Bayesian networks in multicriteria decision analysis (MCDA) of environmental design alternatives for environmental flows (eflows) and physical habitat remediation measures in the Mandalselva River in Norway. We demonstrate how MCDA using multi-attribute value functions can be implemented in a Bayesian network with decision and utility nodes. An object-oriented Bayesian network is used to integrate impacts computed in quantitative sub-models of hydropower revenues and Atlantic salmon smolt production and qualitative judgement models of mesohabitat fishability and riverscape aesthetics. We show how conditional probability tables are useful for modelling uncertainty in value scaling functions, and variance in criteria weights due to different stakeholder preferences. While the paper demonstrates the technical feasibility of MCDA in a BN, we also discuss the challenges of providing decision-support to a real-world habitat remediation process. Image 1 • Multi-criteria decision analysis (MCDA) of environmental flows and physical habitat restoration measures in a hydropower regulated river. • Conditional probability tables used to model uncertainty in value scaling functions and criteria weighting. • Object-oriented Bayesian network used to integrate expert judgement and quantitative model simulations in MCDA. [ABSTRACT FROM AUTHOR]