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Search results for: PREDICTIVE CONTROL
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Association of Genes Related to Oxidative Stress with the Extent of Coronary Atherosclerosis
PublicationOxidative stress is believed to play a critical role in atherosclerosis initiation and progression. In line with this, in a group of 1099 subjects, we determined eight single nucleotide polymorphisms (SNPs) related to oxidative stress (PON1 c.575A>G, MPO c.463G>A, SOD2 c.47T>C, GCLM c.590C>T, NOS3 c.894G>T, NOS3 c.786T>C, CYBA c.214C>T, and CYBA c.932A>G) and assessed the extent of atherosclerosis in coronary arteries based on...
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Qualitative analysis of phospholipids and their oxidised derivatives – used techniques and examples of their applications related to lipidomic research and food analysis
PublicationPhospholipids (PLs) are important biomolecules that not only constitute structural building blocks and scaffolds of cell and organelle membranes, but also play a vital role in cell biochemistry and physiology. Moreover, dietary exogenous PLs are characterized by high nutritional value and other beneficial health effects, which are confirmed by numerous epidemiological studies. For this reason, PLs are of high interest in lipidomics...
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Variable‐fidelity modeling of antenna input characteristics using domain confinement and two‐stage Gaussian process regression surrogates
PublicationThe major bottleneck of electromagnetic (EM)-driven antenna design is the high CPU cost of massive simulations required by parametric optimization, uncertainty quantification, or robust design procedures. Fast surrogate models may be employed to mitigate this issue to a certain extent. Unfortunately, the curse of dimensionality is a serious limiting factor, hindering the construction of conventional data-driven models valid over...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublicationThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
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Experimental and theoretical studies on the Sulfamethazine-Urea and Sulfamethizole-Urea solid-liquid equilibria
PublicationThe miscibility of active pharmaceutical ingredients with excipients is an important aspect in pharmaceutical technology protocols. In this study, the differential scanning calorimetry (DSC) was used for Sulfamethazine-Urea (SI–U) and Sulfamethizole-Urea (SO–U) solid-liquid phase diagrams determination. Both sulfonamides form simple binary eutectics with Urea. The lack of new co-crystal phase formation was confirmed by inspection...
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Algorithmic Human Resources Management
PublicationThe rapid evolution of Digital Human Resources Management has introduced a transformative era where algorithms play a pivotal role in reshaping the landscape of workforce management. This transformation is encapsulated in the concepts of algorithmic management and algorithmic Human Resource Management (HRM). The integration of advanced analytics, predictive and prescriptive analytics and the power of Artificial Intelligence (AI)...
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Genetic variations as predictors of dispositional and dyadic empathy - a couple study
PublicationBiological drivers of empathy have been explored in an interdisciplinary manner for decades. Research that merges the psychological and genetic perspectives of empathy has recently gained interest, and more complex designs and analyses are needed. Empathy is a multidimensional construct that might be regarded both dispositionally (as a personality trait) and contextually (experienced and/or expressed in a particular relationship/situation)....
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublicationSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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Low-cost performance-driven modelling of compact microwave components with two-layer surrogates and gradient kriging
PublicationUtilization of electromagnetic (EM) simulation tools has become indispensable for reliable evaluation of microwave components. As the cost of an individual analysis may already be considerable, the computational overhead associated with EM-driven tasks that require massive simulations (e.g., optimization) may turn prohibitive. One of mitigation methods is the employment of equivalent network models. Yet, they are incapable of accounting...
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Unmasking the COVID-19 Pandemic Prevention Gains: Excess Mortality Reversal in 2022
PublicationObjectives: The purpose of this study was to assess the long-term effectiveness of COVID-19 pandemic prevention measures in saving lives after European governments began to lift restrictions. Study design: Excess mortality interrupted time series.Methods: Country-level weekly data on deaths were fitted to the Poisson mixed linear model to estimate excess deaths. Based on this estimate, the percentage of excess deaths...
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Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
PublicationTo date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging...
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An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics
PublicationThe establishment of a Digital Twin of an operating engineered system can increase the potency of Structural Health Monitoring (SHM) tools, which are then bestowed with enhanced predictive capabilities. This is particularly relevant for wind energy infrastructures, where the definition of remaining useful life is a main driver for assessing the efficacy of these systems. In order to ensure a proper representation of the physical...
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Analysing Ways to Achieve a New Urban Agenda-Based Sustainable Metropolitan Transport
PublicationThe New Urban Agenda (NUA) sets a new vision of sustainable urban development to help cities deal with the challenges of changing demography. While numerous articles have addressed how the NUA can be implemented at different levels and in different areas, this article points out the potential limitations in incorporating the NUA into metropolitan transport policies. The relevance of the limitations can be seen in three main fields:...
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Recent advances in high-frequency modeling by means of domain confinement and nested kriging
PublicationDevelopment of modern high-frequency components and circuits is heavily based on full-wave electromagnetic (EM) simulation tools. Some phenomena, although important from the point of view of the system performance, e.g., EM cross-coupling effects, feed radiation in antenna arrays, substrate anisotropy, cannot be adequately accounted for using simpler means such as equivalent network representations. Consequently, the involvement...
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Accuracy of Pretreatment Ultrasonography Assessment of Intra-Abdominal Spread in Epithelial Ovarian Cancer: A Prospective Study
PublicationThe aim of this study was to test the accuracy of ultrasonography performed by gynecological oncologists for the preoperative assessment of epithelial ovarian cancer (EOC) spread in the pelvis and abdominal cavity. A prospective, observational cohort study was performed at a single tertiary cancer care unit. Patients with suspected EOC were recruited and underwent comprehensive transvaginal and abdominal ultrasonography performed...
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Zintegrowane sterowanie predykcyjne stężeniem tlenu w reaktorze biologicznym
PublicationW pracy został opracowany nowy hierarchiczny system sterowania stężeniem tlenu w reaktorze biologicznym dla oczyszczalni ścieków pracującej w technologii osadu czynnego oraz została przeprowadzona jego walidacja na drodze symulacji działania w oparciu o dane rzeczywiste. Trajektoria tlenu do realizacji jest wyznaczona przez wyższą warstwę sterowania oczyszczalnią ścieków pracującej w technologii osadu czynnego lub też jest zadana...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublicationThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents
PublicationSolubility is not only a crucial physicochemical property for laboratory practice but also provides valuable insight into the mechanism of saturated system organization, as a measure of the interplay between various intermolecular interactions. The importance of these data cannot be overstated, particularly when dealing with active pharmaceutical ingredients (APIs), such as dapsone. It is a commonly used anti-inflammatory and...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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On Nature-Inspired Design Optimization of Antenna Structures Using Variable-Resolution EM Models
PublicationNumerical optimization has been ubiquitous in antenna design for over a decade or so. It is indispensable in handling of multiple geometry/material parameters, performance goals, and constraints. It is also challenging as it incurs significant CPU expenses, especially when the underlying computational model involves full-wave electromagnetic (EM) analysis. In most practical cases, the latter is imperative to ensure evaluation reliability....
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Lighting conditions in home office and occupant’s perception: Exploring drivers of satisfaction
PublicationThis paper depicts lighting home office conditions within different countries and continents, emphasizing the user’s satisfaction with the visual environment. The scope of this article is to investigate the drivers of participants’ satisfaction with the lighting conditions at the home office. The study was developed by a team of international experts working together on Subtask A: User perspective and requirements, Task 61 IEA...
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Development and validation of a model that includes two ultrasound parameters and the plasma D-dimer level for predicting malignancy in adnexal masses: an observational study
PublicationBackground: Pre-operative discrimination of malignant from benign adnexal masses is crucial for planning additional imaging, preparation, surgery and postoperative care. This study aimed to define key ultrasound and clinical variables and develop a predictive model for calculating preoperative ovarian tumor malignancy risk in a gynecologic oncology referral center. We compared our model to a subjective ultrasound assessment (SUA)...
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Coarse-grained simulation - an efficient approach for studying motions of large proteins
PublicationOne of the most important challenges in performing Molecular Dynamics (MD) simulations of large protein complexes is to accommodate the model accuracy and the simulation timescale. Hitherto, for the most relevant dynamics of protein aggregates in an explicit aqueous environment, the timescale reachable for the all-atoms simulations is of hundreds of nanoseconds. This range is four to six orders of magnitude smaller than processes...
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Decision making process using deep learning
PublicationEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublicationBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...