Researchers have shown that the physiological-based personal comfort models (PCM) are capable of addressing individual differences as well as transient thermal comfort. Given that physiological-based ...comfort modeling studies are often very resource-intensive, a well-developed Design of Experiment (DOE) framework could help by optimizing the experimental sequence and use of resources. This study critically reviewed 74 physiological-based PCMs studies and dissected each study based on a DOE framework, dividing the experiments into the experimental procedures, sequences and variables settings. The results indicate that skin temperature, subjects' thermal sensation and air temperature are the leading input variables for PCM. Additionally, the most dominant experiment settings include a 1-min physiological data sampling interval, 10 min interval for reporting thermal vote, a less than 3 h experimental duration, and a fixed clothing level. We found that the subjects' number is independent of the experimental duration (correlation coefficient of 0.0201). Different activity levels and submerging subjects' hands into hot water are also used as thermal stimuli, in addition to the change in air temperature. By applying diverse algorithms, the average predicting accuracy of PCM from selected studies could achieve 85%, and Support Vector Machines (SVM) shows a superior predicting performance. The prominent limitations of the existing studies include insufficient subject numbers, technical restrictions of sensing devices, cumbersome data collection interfaces, improper machine learning algorithms and lack of diversity consideration. Finally, the review suggested that more related studies in this field should be compiled for cross-validation, helping to trade off the most appropriate experiment designs corresponding to the study objectives.
Abstract
Research challenges encountered across science, engineering, and economics can frequently be formulated as optimization tasks. In chemistry and materials science, recent growth in laboratory ...digitization and automation has sparked interest in optimization-guided autonomous discovery and closed-loop experimentation. Experiment planning strategies based on off-the-shelf optimization algorithms can be employed in fully autonomous research platforms to achieve desired experimentation goals with the minimum number of trials. However, the experiment planning strategy that is most suitable to a scientific discovery task is
a priori
unknown while rigorous comparisons of different strategies are highly time and resource demanding. As optimization algorithms are typically benchmarked on low-dimensional synthetic functions, it is unclear how their performance would translate to noisy, higher-dimensional experimental tasks encountered in chemistry and materials science. We introduce
Olympus
, a software package that provides a consistent and easy-to-use framework for benchmarking optimization algorithms against realistic experiments emulated via probabilistic deep-learning models.
Olympus
includes a collection of experimentally derived benchmark sets from chemistry and materials science and a suite of experiment planning strategies that can be easily accessed via a user-friendly Python interface. Furthermore,
Olympus
facilitates the integration, testing, and sharing of custom algorithms and user-defined datasets. In brief,
Olympus
mitigates the barriers associated with benchmarking optimization algorithms on realistic experimental scenarios, promoting data sharing and the creation of a standard framework for evaluating the performance of experiment planning strategies.
Bottom-up proteomics is currently the dominant strategy for proteome analysis. It relies critically upon the use of a protease to digest proteins into peptides, which are then identified by liquid ...chromatography–mass spectrometry (LC-MS). The choice of protease(s) has a substantial impact upon the utility of the bottom-up results obtained. Protease selection determines the nature of the peptides produced, which in turn affects the ability to infer the presence and quantities of the parent proteins and post-translational modifications in the sample. We present here the software tool ProteaseGuru, which provides in silico digestions by candidate proteases, allowing evaluation of their utility for bottom-up proteomic experiments. This information is useful for both studies focused on a single or small number of proteins, and for analysis of entire complex proteomes. ProteaseGuru provides a convenient user interface, valuable peptide information, and data visualizations enabling the comparison of digestion results of different proteases. The information provided includes data tables of theoretical peptide sequences and their biophysical properties, results summaries outlining the numbers of shared and unique peptides per protease, histograms facilitating the comparison of proteome-wide proteolytic data, protein-specific summaries, and sequence coverage maps. Examples are provided of its use to inform analysis of variant-containing proteins in the human proteome, as well as for studies requiring the use of multiple proteomic databases such as a human:mouse xenograft model, and microbiome metaproteomics.
The aim of the work was to obtain mathematical static estimates of the influence of various factors on the degree of hydrostabilization of pyrocondensate obtained during the pyrolysis of straight-run ...gasoline, and an attempt to determine the most optimal process mode. The experimental data obtained earlier made it possible to determine the temperature range, duration, volume of the catalyst, and the ratio of hydrogen to feedstock necessary for the effective hydrostabilization of the pyrocondensate, which made it possible to narrow the range of variation of the process parameters. At the same time, the task was set to find the optimal conditions that ensure the maximum degree of hydrogenation of the condensate. The planning of the experiment was carried out according to the scheme of a full factorial experiment 24. According to the results of an active experiment carried out using mathematical planning methods, the major role of variable factors was determined, a mathematical model was obtained, and the optimal mode for conducting the pyro-condensate hydrostabilization process with the presence of a nickel-chromium catalyst was determined: temperature - 80° C, the ratio of hydrogen volume to raw material, equal to 0.3, catalyst volume - 5 sm3, process duration - 120 min. The temperature has the greatest influence on the degree of pyro-condensate hydrogenation.
Метою роботи було отримання математичних статичних оцінок впливу різних факторів на ступінь гідростабілізації піроконденсату, отриманого при піролізі прямогонного бензину, та спроба визначення найбільш оптимального режиму процесу. Отримані раніше експериментальні дані дозволили визначити необхідний для ефективної гідростабілізації піроконденсату діапазон температур, тривалість, об’єм каталізатора та співвідношення водню та вихідної сировини, що дозволило звузити діапазон варіювання параметрів процесу. При цьому ставилася задача знайти оптимальні умови, що забезпечують максимальний ступінь гідрогенізації конденсату. Планування експерименту проводили за схемою повного факторіалу 24. Параметри, від яких залежить процес гідростабілізації піроконденсату, наступні: Т – температура досліду; τ – тривалість досліду; Vкат – об’єм каталізатора; H2:C – співвідношення водню до сировини. За результатами активного експерименту, проведеного методами математичного планування, визначено основну роль змінних факторів, отримано математичну модель і оптимальний режим піротехніки. Визначено процес гідростабілізації конденсату за наявності нікель-хромового каталізатора: температура - 80°С, співвідношення об'єму водню до сировини 0,3, об'єм каталізатора – 5 см3, тривалість процесу - 120 хв. Найбільший вплив на ступінь гідрогенізації піроконденсату має температура. Порівняння результатів математичного моделювання із експериментальними даними свідчить про низьку розбіжність (0,8% відн.) та підтверджує достовірність розрахунків з використанням отриманого рівняння регресії.
Introduction. When using concrete and reinforced concrete structures, it is necessary to overcome problems associated with the quality of concrete to shrink in size and experience shrinkage during ...hardening and drying. To solve problems with shrinkage, special attention is paid to the materials that, when added to ordinary portland cement, make it possible to obtain non-shrinkable, expanding types of cements. A well-known way of producing expanding cements is to grind cement clinker, gypsum and a special additive together. In addition, the introduction of active mineral additives with pozzolanic properties allows to compact the structure of the cement stone, reduce porosity, increase strength and reduce shrinkage. They also save the clinker for the cement production, help to reduce the cost of production and help to reduce the burden on the environment. One of these mineral additives is tripoli. Materials and methods. The effect of additives content on the deformation property of the composite binger was studied using the experiment planning method. Deformation of cement at the age of 2, 3, 7, 14 and 28 days were determined in accordance with the method of results processing in accordance with GOST R 56727–2015, GOST 11052–74. The research was carried out in the laboratory of the Department of Construction Materials Science of the Moscow State University of Civil Engineering. Results. The results obtained are presented as the surface of a second level regression equation describing the dependence of the blinder deformation on the content of complex expanding and pozzolanic additives. As a result of the experiments conducted, the composition with the maximum expansion and the composition with maximum shrinkage using complex additives were obtained. The results will be further used to predict the deformation properties of the binder. Conclusions. Based on the results of this study, the authors will continue to study the properties of binders based on a complex expanding and pozzolanic additive in the future.
xrdPlanner is a software package designed to aid in the planning and preparation of powder X‐ray diffraction and total scattering beam times at synchrotron facilities. Many modern beamlines provide a ...flexible experimental setup and may have several different detectors available. In combination with a range of available X‐ray energies, it often makes it difficult for the user to explore the available parameter space relevant for a given experiment prior to the scheduled beam time. xrdPlanner was developed to provide a fast and straightforward tool that allows users to visualize the accessible part of reciprocal space of their experiment at a given combination of photon energy and detector geometry. To plan and communicate the necessary geometry not only saves time but also helps the beamline staff to prepare and accommodate for an experiment. The program is tailored toward powder X‐ray diffraction and total scattering experiments but may also be useful for other experiments that rely on an area detector and for which detector placement and achievable momentum‐transfer range are important experimental parameters.
xrdPlanner is a software designed to assist in the planning of powder X‐ray diffraction and total scattering experiments at synchrotron facilities. It provides a straightforward visualization of projected resolution intervals at different combinations of photon energy and detector geometry, and focus is put on an intuitive and fast presentation to facilitate live exploration of the available parameter space.
Pharmaceutical compounds can reach water bodies through sewage systems. The process of water treatment is insufficient for the removal of these contaminants. The ozonation has great potential to be ...integrated into the treatment, since it promotes the reduction of pharmaceuticals, reduces the generation of disinfection byproducts and can reduce operational costs. In this work, the integration of the ozonation process with water treatment was studied. The ozone was applied in the pre-oxidation and intermediate ozonation stages, to evaluate the dependence of different variables. Water samples were collected from Arroio Diluvio, a river of the city of Porto Alegre (Brazil). The doses of ozone were maintained between 0.5 and 1.0 mgO
L
while the coagulant was between 25 and 150 mg·L
. Pre-ozonation resulted in a removal of pharmaceuticals at pH 10.0, time of 15 min and coagulant concentration of 52.5 mgL
. The intermediate ozonation provided a removal with pH 10.0 and a time of 5 min of bubbling. Based on the results, it was confirmed that the synergy of the ozonation process with conventional water treatment is an effective, sensitive and fast method for the removal of pharmaceuticals from the aqueous medium.
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