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Chemical engineering research and design 187, 164-173 (2022). doi:10.1016/j.cherd.2022.08.061 special issue: "100 years of IChemE", Published by Elsevier, Amsterdam

We identify a new variational inference scheme for dynamical systems whose transition function is modelled by a Gaussian process. Inference in this setting has either employed computationally intensive MCMC methods, or relied on factorisations of the variational posterior. As we demonstrate in our experiments, the factorisation between latent system states and transition function can lead to a miscalibrated posterior and to learning unnecessarily large noise terms. We eliminate this factorisation by explicitly modelling the dependence between state trajectories and the Gaussian process posterior. Samples of the latent states can then be tractably generated by conditioning on this representation. The method we obtain (VCDT: variationally coupled dynamics and trajectories) gives better predictive performance and more calibrated estimates of the transition function, yet maintains the same time and space complexities as mean-field methods. Code is available at: github.com/ialong/GPt., Comment: 10 pages, 4 figures, 3 tables. Published in the proceedings of the Thirty-sixth International Conference on Machine Learning (ICML), 2019

10.3767/003158513X675925 Novel species of microfungi described in the present study include the following from South Africa: Camarosporium aloes, Phaeococcomyces aloes and Phoma aloes from Aloe, C. psoraleae, Diaporthe psoraleae and D. psoraleae-pinnatae from Psoralea, Colletotrichum euphorbiae from Euphorbia, Coniothyrium prosopidis and Peyronellaea prosopidis from Prosopis, Diaporthe cassines from Cassine, D. diospyricola from Diospyros, Diaporthe maytenicola from Maytenus, Harknessia proteae from Protea, Neofusicoccum ursorum and N. cryptoaustrale from Eucalyptus, Ochrocladosporium adansoniae from Adansonia, Pilidium pseudoconcavum from Greyia radlkoferi, Stagonospora pseudopaludosa from Phragmites and Toxicocladosporium ficiniae from Ficinia. Several species were also described from Thailand, namely: Chaetopsina pini and C. pinicola from Pinus spp., Myrmecridium thailandicum from reed litter, Passalora pseudotithoniae from Tithonia, Pallidocercospora ventilago from Ventilago, Pyricularia bothriochloae from Bothriochloa and Sphaerulina rhododendricola from Rhododendron. Novelties from Spain include Cladophialophora multiseptata, Knufia tsunedae and Pleuroascus rectipilus from soil and Cyphellophora catalaunica from river sediments. Species from the USA include Bipolaris drechsleri from Microstegium, Calonectria blephiliae from Blephilia, Kellermania macrospora (epitype) and K. pseudoyuccigena from Yucca. Three new species are described from Mexico, namely Neophaeosphaeria agaves and K. agaves from Agave and Phytophthora ipomoeae from Ipomoea. Other African species include Calonectria mossambicensis from Eucalyptus (Mozambique), Harzia cameroonensis from an unknown creeper (Cameroon), Mastigosporella anisophylleae from Anisophyllea (Zambia) and Teratosphaeria terminal

10.3767/003158513X675925 Novel species of microfungi described in the present study include the following from South Africa: Camarosporium aloes, Phaeococcomyces aloes and Phoma aloes from Aloe, C. psoraleae, Diaporthe psoraleae and D. psoraleae-pinnatae from Psoralea, Colletotrichum euphorbiae from Euphorbia, Coniothyrium prosopidis and Peyronellaea prosopidis from Prosopis, Diaporthe cassines from Cassine, D. diospyricola from Diospyros, Diaporthe maytenicola from Maytenus, Harknessia proteae from Protea, Neofusicoccum ursorum and N. cryptoaustrale from Eucalyptus, Ochrocladosporium adansoniae from Adansonia, Pilidium pseudoconcavum from Greyia radlkoferi, Stagonospora pseudopaludosa from Phragmites and Toxicocladosporium ficiniae from Ficinia. Several species were also described from Thailand, namely: Chaetopsina pini and C. pinicola from Pinus spp., Myrmecridium thailandicum from reed litter, Passalora pseudotithoniae from Tithonia, Pallidocercospora ventilago from Ventilago, Pyricularia bothriochloae from Bothriochloa and Sphaerulina rhododendricola from Rhododendron. Novelties from Spain include Cladophialophora multiseptata, Knufia tsunedae and Pleuroascus rectipilus from soil and Cyphellophora catalaunica from river sediments. Species from the USA include Bipolaris drechsleri from Microstegium, Calonectria blephiliae from Blephilia, Kellermania macrospora (epitype) and K. pseudoyuccigena from Yucca. Three new species are described from Mexico, namely Neophaeosphaeria agaves and K. agaves from Agave and Phytophthora ipomoeae from Ipomoea. Other African species include Calonectria mossambicensis from Eucalyptus (Mozambique), Harzia cameroonensis from an unknown creeper (Cameroon), Mastigosporella anisophylleae from Anisophyllea (Zambia) and Teratosphaeria terminal

Introduction. Andropause and aging are associated with neuroendocrine dysfunctions. Growth hormone and testosterone play a significant role in several processes affecting adaptation and thereby also everyday functioning. The aim of this research project was to evaluate the effects of recombinant human growth hormone and testosterone enanthate injections on body mass and body composition, aerobic and anaerobic fitness and lipid profile in middle-aged men. Materials and method. The research group was comprised of 14 men aged 45 – 60 years. Two series of laboratory analyses were performed. Independent tests were carried out at baseline and after 12 weeks of the experiment. The data were analyzed using Statistica 9.1 software. Results. A two-way repeated measures ANOVA revealed a statistically significant effect of the intervention programme on fat-free mass (η2=0.34), total body fat (η2=0.79), total cholesterol (η2=0.30), high-density lipoprotein cholesterol (η2=0.31), low-density lipoprotein cholesterol (η2=0.42), triglyceride (η2=0.28), testosterone (η2=0.52), insulin-like growth factor 1 (η2=0.47) and growth hormone (η2=0.63). Furthermore, ANOVA revealed a statistically significant effect of the rhGH and T treatment on maximal oxygen uptake (η2=0.63), anaerobic threshold (η2=0.61) and maximal work rate (η2=0.53). Conclusion. It should be emphasized that the lipid profile was affected not only by rhGH+T replacement therapy, but also by the prescribed physical activity programme. The strength and endurance fitness programme alone did not cause significant changes in body mass and composition, nor the anaerobic and aerobic capacity. On the other hand, the rhGH=T treatment stimulated these changes significantly.

Target tracking has a wide range of applications in Internet of Things (IoT), such as smart city sensors, indoor tracking, and gesture recognition. Several studies have been conducted in this area. Most of the published works either use vision sensors or inertial sensors for motion analysis and gesture recognition [1, 2]. Recent works use a combination of depth sensors and inertial sensors for 3D ranging and tracking [3, 4]. This often requires complex hardware and the use of complex embedded algorithms. Stereo cameras or Kinect depth sensors used for high precision ranging are instead expensive and not easy to use. The aim of this work is to track in 3D a hand fitted with a series of precisely positioned IR LEDs using a novel Lensless Smart Sensor (LSS) developed by Rambus, Inc. [5, 6]. In the adopted device, the lens used in conventional cameras is replaced by low-cost ultra-miniaturized diffraction optics attached directly to the image sensor array. The unique diffraction pattern enables more precise position tracking than possible with a lens by capturing more information about the scene.

Chemical engineering as a skilled profession depends on the competencies of the individuals practicing it. Formal teaching of chemical engineering at universities only started in the 19th century. Informally, the subject has been in existence at least since Roman times. Highly skilled people have been recognised as a means to ensure prosperity and allow innovation for at least several centuries, as examples like the Bergakademie Freiberg show. It can be shown that skilled people flock to prosperous regions and prosperous regions develop where skilled people aggregate, modern examples include Silicon Valley and Northwestern Europe. The competences needed by a chemical engineer continue to broaden, e.g. sustainability, digitisation force changes in the education of engineers. The sheer volume of material cannot be covered in a tertiary study period and the speed of change makes knowledge obsolete very fast, which puts more focus on new life-long learning requirements. Modern, more individualised and context specific ways of education will develop, based sometimes on efficiency and cost of teaching and more often on effectiveness of learning.

Autonomous vehicle (AV) software is typically composed of a pipeline of individual components, linking sensor inputs to motor outputs. Erroneous component outputs propagate downstream, hence safe AV software must consider the ultimate effect of each component’s errors. Further, improving safety alone is not sufficient. Passengers must also feel safe to trust and use AV systems. To address such concerns, we investigate three under-explored themes for AV research: safety, interpretability, and compliance. Safety can be improved by quantifying the uncertainties of component outputs and propagating them forward through the pipeline. Interpretability is concerned with explaining what the AV observes and why it makes the decisions it does, building reassurance with the passenger. Compliance refers to maintaining some control for the passenger. We discuss open challenges for research within these themes. We highlight the need for concrete evaluation metrics, propose example problems, and highlight possible solutions.

Dysarthia is a common sequela of cerebral palsy (CP), directly affecting both the intelligibility of speech and the child's psycho-social adjustment. Speech therapy focused exclusively on the articulatory organs does not always help CP children to speak more intelligibly. The program of art therapy described here has proven to be helpful for these children.From among all the CP children enrolled in our art therapy program from 2005 to 2009, we selected a group of 14 boys and girls (average age 15.3) with severe dysarthria at baseline but no other language or cognitive disturbances. Our retrospective study was based on results from the Auditory Dysarthria Scale and neuropsychological tests for fluency, administered routinely over the 4 months of art therapy.All 14 children in the study group showed some degree of improvement after art therapy in all tested parameters. On the Auditory Dysarthia Scale, highly significant improvements were noted in overall intelligibility (p0.0001), with significant improvement (p0.001) in volume, tempo, and control of pauses. The least improvement was noted in the most purely motor parameters. All 14 children also exhibited significant improvement in fluency.Art therapy improves the intelligibility of speech in children with cerebral palsy, even when language functions are not as such the object of therapeutic intervention.

In image segmentation, there is often more than one plausible solution for a given input. In medical imaging, for example, experts will often disagree about the exact location of object boundaries. Estimating this inherent uncertainty and predicting multiple plausible hypotheses is of great interest in many applications, yet this ability is lacking in most current deep learning methods. In this paper, we introduce stochastic segmentation networks (SSNs), an efficient probabilistic method for modelling aleatoric uncertainty with any image segmentation network architecture. In contrast to approaches that produce pixel-wise estimates, SSNs model joint distributions over entire label maps and thus can generate multiple spatially coherent hypotheses for a single image. By using a low-rank multivariate normal distribution over the logit space to model the probability of the label map given the image, we obtain a spatially consistent probability distribution that can be efficiently computed by a neural network without any changes to the underlying architecture. We tested our method on the segmentation of real-world medical data, including lung nodules in 2D CT and brain tumours in 3D multimodal MRI scans. SSNs outperform state-of-the-art for modelling correlated uncertainty in ambiguous images while being much simpler, more flexible, and more efficient., Comment: Published at Neurips2020. 17 pages, 11 figures, 2 tables