Hydrotreating of tall oils on a sulfided NiMo catalyst for the production of base-chemicals in steam crackers

Development of new and innovative products through efficient technologies is essential for the implementation of sustainable developments in highly competitive chemical industries. Based on this context, raw materials originating from biomass have been widely used for the production of chemicals and materials. Steam cracking of bio-based or renewable feedstocks in a conventional steam cracking set-up is identified as a promising approach for the sustainable production of base-chemicals. In a two-step process for the production of base-chemicals, firstly, bio-derived feedstock is upgraded into a more suitable feedstock which comprises mainly paraffin range hydrocarbons with a lower oxygen content than the original feedstock; secondly, the upgraded feedstock is converted into base-chemicals by conventional steam cracking technology. This research work identifies wood-derived tall oil as a potential feedstock for the production of base-chemicals by catalytic upgrading and steam cracking methods. The main aim of this work was to carry out the catalytic hydrotreating of tall oil feedstocks such as tall oil fatty acid (TOFA), distilled tall oil (DTO) and crude tall oil (CTO) on a commercial, sulfided NiMo catalyst at different process conditions. The effects of space time and process temperatures on the distribution of products from the hydrotreatment of different tall oil feeds were investigated. Hydrotreating chemistry of oxygenates in tall oil were assessed based on the achieved conversion of reactants and product distribution under the investigated conditions. Furthermore, the steam cracking of hydrodeoxygented tall oil (HDO-tall oil) feeds was carried out, and evaluation of the yield of olefins in comparison with conventional steam cracking feeds such as naphtha and natural gas condensate (NGC)

Production of bio-Olefins: tall-oils and waste greases to green chemicals and polymers

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Adaptive Rationality in Strategic Interaction: Do Emotions Regulate Thinking about Others?

Forming beliefs or expectations about others’ behavior is fundamental to strategy, as it co-determines the outcomes of interactions in and across organizations. In the game theoretic conception of rationality, agents reason iteratively about each other to form expectations about behavior. According to prior scholarship, actual strategists fall short of this ideal, and attempts to understand the underlying cognitive processes of forming expectations about others are in their infancy. We propose that emotions help regulate iterative reasoning, that is, their tendency to not only reflect on what others think, but also on what others think about their thinking. Drawing on a controlled experiment, we find that a negative emotion (fear) deepens the tendency to engage in iterative reasoning, compared to a positive emotion (amusement). Moreover, neutral emotions yield even deeper levels of iterative reasoning. We tentatively interpret these early findings and speculate about the broader link of emotions and expectations in the context of strategic management. Extending the view of emotional regulation as a capability, emotions may be building blocks of rational heuristics for strategic interaction and enable interactive decision-making when strategists have little experience with the environment

Adaptive Rationality in Strategic Interaction: Do Emotions Regulate Thinking about Others?

Forming beliefs or expectations about others’ behavior is fundamental to strategy, as it co-determines the outcomes of interactions in and across organizations. In the game theoretic conception of rationality, agents reason iteratively about each other to form expectations about behavior. According to prior scholarship, actual strategists fall short of this ideal, and attempts to understand the underlying cognitive processes of forming expectations about others are in their infancy. We propose that emotions help regulate iterative reasoning, that is, their tendency to not only reflect on what others think, but also on what others think about their thinking. Drawing on a controlled experiment, we find that a negative emotion (fear) deepens the tendency to engage in iterative reasoning, compared to a positive emotion (amusement). Moreover, neutral emotions yield even deeper levels of reasoning. We tentatively interpret these early findings and speculate about the broader link of emotions and expectations in the context of strategic management. Extending the view of emotional regulation as a capability, emotions may be building blocks of rational heuristics for strategic interaction and enable interactive decision-making when strategists have little experience with the environment

Caste in the news – a computational analysis of Indian newspapers

Conflicts involving caste issues, mainly concerning the lowest caste rights, pervade modern Indian society. Caste affiliation, being rigorously enforced by the society, is an official contemporary reality. Although caste identity is a major social discrimination, it also serves as a necessary condition for affirmative action like reservation policy. In this article, we perform an original and rigorous analysis of the discourse involving the theme “caste” in India newspapers. To this purpose, we have implemented a computational analysis over a big dataset of the 2016 and 2017 editions of three major Indian newspapers to determine the most salient themes associated with “caste” in the news. We have used an original mix of state-of-the-art algorithms, including those based on statistical distributions and two-layer neural networks, to detect the relevant topics in the news and characterize their linguistic context. We concluded that there is an excessive association between lower castes, victimization, and social unrest in the news that does not adequately cover the reports on other aspects of their life and personal identity, thus reinforcing conflict, while attenuating the vocality and agency of a large section of the population. From our conclusion, we propose a positive discrimination policy in the newsroom.info:eu-repo/semantics/publishedVersio

A Fluidic Soft Robot for Needle Guidance and Motion Compensation in Intratympanic Steroid Injections

Intratympanic steroid injections are commonly employed in treating ear diseases, such as sudden sensorineural hearing loss or Meniere's disease through drug delivery via the middle ear. Whilst being an effective treatment, the procedure has to be performed by a trained surgeon to avoid delicate regions in the patient's anatomy and is considered painful despite the use of topical anaesthesia. In this letter we introduce a fluid-driven soft robotic system which aims at increasing patient-comfort during the injection by counteracting unwanted needle motion, reducing the cognitive load of the clinician by autonomously identifying sensitive regions in the ear and de-risking the procedure by steering the needle towards the desired injection site. A design comprising of six embedded fluidic actuators is presented, which allow for translation and rotation of the needle as well as adaptive stiffening in the coupling between needle and ear canal. The system's steering-capabilities are investigated and the differential kinematics derived to demonstrate trajectory tracking in Cartesian space. A vision system is developed which enables tracking of anatomical landmarks on the tympanic membrane and thus locating the desired needle insertion site. The integrated system shows the ability to provide a safe guide for the inserted needle towards a desired target direction while significantly reducing needle motion. The proposed tracking algorithm is able to identify the desired needle insertion site and could be employed to avoid delicate anatomical regions

Intra-Domain Adaptation for Robust Visual Guidance in Intratympanic Injections

Intratympanic steroid injections are commonly used for the treatment of ear diseases. During this treatment, an expert Ear, Nose & Throat (ENT) clinician delivers the drug by viewing through a large microscope that provides a close-up view of the anatomical landmarks on the middle ear. A steady hand and swift response to any patient movement are required to avoid improper placement of the needle. To assist the clinician during this treatment, a fluidic soft robot is proposed in \cite{lindenroth2021fluidic} that can steer inside a lumen for providing steady guidance for drug delivery. For robust visual guidance, stable anatomical landmarks (tympanic membrane, malleus, umbo) segmentation is required. In this work, we perform intra-domain adaptation to learn a generalized model that provides stable and consistent segmentation on unseen patients and phantom ear data

Intrinsic Force Sensing for Motion Estimation in a Parallel, Fluidic Soft Robot for Endoluminal Interventions

Determining the externally-induced motion of a soft robot in minimally-invasive procedures is highly challenging and commonly demands specific tools and dedicated sensors. Intrinsic force sensing paired with a model describing the robot's compliance offers an alternative pathway which relies heavily on knowledge of the characteristic mechanical behaviour of the investigated system. In this work, we apply quasi-static intrinsic force sensing to a miniature, parallel soft robot designed for endoluminal ear interventions. We characterize the soft robot's nonlinear mechanical behaviour and devise methods for inferring forces applied to the actuators of the robot from fluid pressure and volume information of the working fluid. We demonstrate that it is possible to detect the presence of an external contact acting on the soft robot's actuators, infer the applied reaction force with an accuracy of 28.1 mN and extrapolate from individual actuator force sensing to determining forces acting on the combined parallel soft robot when it is deployed in a lumen, which can be achieved with an accuracy of 75.45 mN for external forces and 0.47 Nmm for external torques. The intrinsically-sensed external forces can be employed to estimate the induced motion of the soft robot in response to these forces with an accuracy of 0.11 mm in translation and 2.47 in rotational deflection. The derived methodologies could enable designs for more perceptive endoscopic systems and pave the way for developing sensing and control strategies in endoluminal and transluminal soft robots