Application of an artificial intelligence segmentation for deep hyperthermia treatment planning in the pelvic region

During a microwave hyperthermia oncology treatment, the target region temperature is elevated to the temperatures of 40–44 °C, which improves the therapeutic effect of a standard radiotherapy and/or chemotherapy treatments. Amplitudes and phases of antenna input signals in the phased array setup surrounding the 3D patient model are optimised with respect to maximise the energy deposition in the target region. In this study, we successfully integrated an automatic artificial intelligence segmentation routine, used for patient-specific 3D model generation, into the hyperthermia treatment planning process. This allows us to apply more realistic patient 3D model for the online hyperthermia guidance including detailed retrospective analyses of the overall treatment quality, possibly leading to a widespread clinical use of the hyperthermia treatment planning

Der Kapitalmarkt in der Tschechischen Republik

Series: Arbeitspapiere des Forschungsinstituts für mittel- und osteuropäisches Wirtschaftsrech

Lance Design for Scrap Melting Aggregates

Metallurgical aggregates, which are used for metal waste melting, are equipped with lances for blowing gaseous media. These gaseous media allow especially scrap melting and intense homogenization of the resulting melt. In connection with this, the blowing systems are developed both for blowing of gaseous media itself on the bath surface or into the melt and for blowing of the gas mixture with powdered substances. When designing the blowing systems and the individual lance tips and nozzles, it is necessary to respect certain criteria, the derivation of which is based on long-term experience and acquired knowledge in this field. The submitted paper summarizes the design recommendations, including the determination of the selected design characteristics of the nozzles for blowing gaseous media on the bath surface in the metallurgical aggregate. These design characteristics help designers and engineers to design systems that meet the high demands on quality, efficiency and operational reliability

A Semantics-Based Measure of Emoji Similarity

Emoji have grown to become one of the most important forms of communication on the web. With its widespread use, measuring the similarity of emoji has become an important problem for contemporary text processing since it lies at the heart of sentiment analysis, search, and interface design tasks. This paper presents a comprehensive analysis of the semantic similarity of emoji through embedding models that are learned over machine-readable emoji meanings in the EmojiNet knowledge base. Using emoji descriptions, emoji sense labels and emoji sense definitions, and with different training corpora obtained from Twitter and Google News, we develop and test multiple embedding models to measure emoji similarity. To evaluate our work, we create a new dataset called EmoSim508, which assigns human-annotated semantic similarity scores to a set of 508 carefully selected emoji pairs. After validation with EmoSim508, we present a real-world use-case of our emoji embedding models using a sentiment analysis task and show that our models outperform the previous best-performing emoji embedding model on this task. The EmoSim508 dataset and our emoji embedding models are publicly released with this paper and can be downloaded from http://emojinet.knoesis.org/.Comment: This paper is accepted at Web Intelligence 2017 as a full paper, In 2017 IEEE/WIC/ACM International Conference on Web Intelligence (WI). Leipzig, Germany: ACM, 201

A Czech version of the Overall Anxiety Severity and Impairment Scale (OASIS):standardization and psychometric properties

BACKGROUND: The Overall Anxiety Severity and Impairment Scale (OASIS) is a transdiagnostic measure that assesses severity and impairment associated with anxiety disorders. However, its psychometric properties were primarily examined in English-speaking or western countries. Therefore, this study aims to examine its psychometric parameters in the Czech Republic. METHODS: A large representative sample (n = 1738), a clinical sample (n = 57) and a retest sample (n = 20) were used. In addition to the OASIS, conventional measures of anxiety, depression, personality traits, self-esteem, life satisfaction, and other scales were also administered. Moreover, we examined the latent structure, reliability, validity, and the cut-off score for the Reliable Change Index (RCI) and the Clinically Significant Change Index (CSI). RESULTS: Higher anxiety was found in females, religious non-church members, and students. The Confirmatory Factor Analysis supported the adequate fit of the unidimensional solution: x2(4) = 3.20; p < 0.525; CFI = 1.000; TLI = 1.000;RMSEA = 0, SRMR = 0. The measurement equivalence examination indicated that the OASIS measures anxiety invariantly between males and females. The validity of the OASIS was supported by positive associations with neuroticism, depression, perceived stress, guilt, shame, and the established anxiety measures. The internal consistency was excellent (Cronbach’s alpha = 0.96, McDonald’s omega = 0.96). The test-retest reliability was acceptable (r = 0.66). The cut-off for the CSI is 6 and the RCI is 5.32. CONCLUSIONS: The OASIS represents a reliable and valid instrument for assessing anxiety in adults. Due to its shortness, excellent psychometric properties, and percentile norms, it is especially useful for short and accurate screening of anxiety and mapping therapeutic changes in clinical practice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12888-022-04365-5

Operation and Planning of Energy Hubs Under Uncertainty - a Review of Mathematical Optimization Approaches

Co-designing energy systems across multiple energy carriers is increasingly attracting attention of researchers and policy makers, since it is a prominent means of increasing the overall efficiency of the energy sector. Special attention is attributed to the so-called energy hubs, i.e., clusters of energy communities featuring electricity, gas, heat, hydrogen, and also water generation and consumption facilities. Managing an energy hub entails dealing with multiple sources of uncertainty, such as renewable generation, energy demands, wholesale market prices, etc. Such uncertainties call for sophisticated decision-making techniques, with mathematical optimization being the predominant family of decision-making methods proposed in the literature of recent years. In this paper, we summarize, review, and categorize research studies that have applied mathematical optimization approaches towards making operational and planning decisions for energy hubs. Relevant methods include robust optimization, information gap decision theory, stochastic programming, and chance-constrained optimization. The results of the review indicate the increasing adoption of robust and, more recently, hybrid methods to deal with the multi-dimensional uncertainties of energy hubs

Remote energy lab. Experience and improvements of european cooperation in remote labs

Due to the COVID-19 pandemic, online teaching methods have gained more interest. Most formats of teaching can be easily transferred into an online format from a technical point of view. However, this is more difficult for practical courses in a laboratory. Together with partners from three European universities, we tackled the issue of providing a practical online course for higher education levels in the framework of the EuroTeQ university. In this work, we present our concept of the course and discuss the course goals and further improvements. We tested the remote lab setting in order to offer the course on a yearly basis in future. The remote lab was focused on energy engineering and was open to students from different engineering disciplines and countries. The course was comprised of three blocks, each consisting of one lecture on the broader context of the topic and one experimental laboratory session. The experimental session was streamed via a video broadcasting service. Students were required to either deliver a written report or to write a newspaper article for each of the three blocks. The learning outcome of the course was that students on the one hand learn about the technologies discussed in the course and on the other hand learn about intercultural communication skills. The goal was to show the diversity of technologies and to show the significance of each technology for a specific country. The online experimental sessions proved to deliver a clear explanation of the topic for the students when provided with sufficient course material adapted to online formats. Contrary, keeping a high level of interaction with students during remote experiments was found most challenging

INFRARED PHOTOLUMINESCENCE SPECTRA OF PBS NANOPARTICLES PREPARED BY LANGMUIR–BLODGETT AND LASER ABLATION METHODS

We optimized the optical setup originally designed for the photoluminescence measurements in the spectral range 400‒1100 nm. New design extends the spectral range into the near infrared region 900‒1700 nm and allows the colloidal solutions measurements in cuvettes as well as the measurements of nanoparticles deposited in the form of thin films on glass substrates. The infrared photoluminescence spectra of the PbS nanoparticles prepared by the Langmuir–Blodgett technique show the higher photoluminescence intensity and the shift to the shorter wavelengths compared to the infrared photoluminescence spectra of the PbS nanoparticles prepared by the laser ablation from PbS target. We aslo proved the high stability of PbS nanoparticles prepared in the form of thin layers

Neuropsychological Functioning and Temperament Traits in a Czech Sample of Children and Adolescents at Familial Risk of Bipolar Disorder

Background: Although a positive family history is the strongest predictor for bipolar disorder (BD), most offspring of BD parents (BO) will not develop the disorder. Identification of vulnerability markers for BD is essential for specific individual risk estimation. Impairments in cognitive functioning and the presence of specific temperament traits are considered promising candidates.Methods: Sixty-three BO (48% female; 11.8 ± 3.3 years) and 54 control offspring (CO; 44% female; 12.3 ± 3.2 years) comparable in sex (p = 0.4) and age (p = 0.4) were enrolled. Detection of current sub/threshold mood symptoms by the Kiddie Schedule for Affective Disorders and Schizophrenia and General Behavior Inventory was applied to separate BO into ultrahigh-risk (UHR) and high-risk (HR) subgroups. Cognitive functions were tested by the Developmental Neuropsychological Assessment II test battery, d2 Test of Attention, and Amsterdam Neuropsychological Tasks. Temperament was assessed by the Temperament in Middle Childhood and Early Adolescent Temperament Questionnaires.Results: The BO sample consisted of 5 BD, 17 UHR, and 41 HR participants. We did not observe any significant differences between the BO and CO groups or between the UHR, HR, and CO subgroups (Hedges' g = 0.21–0.39) in cognitive functioning. The BO differed significantly in some temperament traits from the CO (g = 0.42–0.61), while the UHR subgroup exhibited lower effortful control and attention focusing than both HR and CO participants (g = 0.92–1.19).Limitations: The cross-sectional design and wide age range of the sample limited our findings.Conclusions: Neuropsychological impairment does not seem to be a trait marker of BD in the premorbid stage. Temperament with low effortful control and low attention focusing might be associated with the development of mood disorders in BO