Social media is an important source of real-world data for sentiment analysis. Hate speech detection models can be trained on data from Twitter and then utilized for content filtering and removal of posts which contain hate speech. This work proposes a new algorithm for calculating user hate speech index based on user post history. Three available datasets were merged for the purpose of acquiring Twitter posts which contained hate speech. Text preprocessing and tokenization was performed, as well as outlier removal and class balancing. The proposed algorithm was used for determining hate speech index of users who posted tweets from the dataset. The preprocessed dataset was used for training and testing multiple machine learning models: k-means clustering without and with principal component analysis, naïve Bayes, decision tree and random forest. Four different feature subsets of the dataset were used for model training and testing. Anomaly detection, data transformation and parameter tuning were used in an attempt to improve classification accuracy. The highest F1 measure was achieved by training the model using a combination of user hate speech index and other user features. The results show that the usage of user hate speech index, with or without other user features, improves the accuracy of hate speech detection.

This paper considers calculation methods for the electric field intensity and magnetic flux density in the vicinity of the overhead transmission lines, as well as the calculation of alternating current (AC) corona onset electric field intensity. Calculations within this paper are made using the 2D algorithms of Charge Simulation Method (CSM) and Biot-Savart (BS) law based method. In order to obtain more accurate results, calculations are made by representing each overhead transmission line conductor with a large number of electric and magnetic field sources. By applying this approach, bundle conductors can be represented in a more realistic way and also singularity problems can be avoided when calculating electric field intensity. The presented methods are applied to a real overhead transmission line configuration, and obtained results are compared with field measurement results over the lateral profile. For considered overhead transmission line, AC corona onset electric field intensity is calculated and compared with calculated electric field intensity on the conductor’s surface. A comparison of calculated and measured results shows that considered calculation methods give satisfactory results.

In the fields of computer vision and digital image processing, image segmentation denotes a process whereby an image is segmented into multiple regions. Image segmentation based on multilevel thresholding has received significant attention in recent literature. In this paper, a multilevel thresholding approach based on three different Rao algorithms and Kapur’s entropy is investigated. The performance of the considered thresholding methods is evaluated on a dataset of 10 standard benchmark images using the mean of objective function values, the standard deviation of objective function values, and the best objective function value obtained over a fixed number of independent runs. The experimental results demonstrate the effectiveness of the multilevel thresholding approach based on Rao algorithms and Kapur’s entropy.

Ghrelin, a stomach-produced hormone, is well-recognized for its role in promoting feeding, controlling energy homeostasis, and glucoregulation. Ghrelin’s function to ensure survival extends beyond that: its release parallels that of corticosterone, and ghrelin administration and fasting have an anxiolytic and antidepressant effect. This clearly suggests a role in stress and anxiety. However, most studies of ghrelin’s effects on anxiety have been conducted exclusively on male rodents. Here, we hypothesize that female rats are wired for higher ghrelin sensitivity compared to males. To test this, we systematically compared components of the ghrelin axis between male and female Sprague Dawley rats. Next, we evaluated whether anxiety-like behavior and feeding response to endogenous or exogenous ghrelin are sex divergent. In line with our hypothesis, we show that female rats have higher serum levels of ghrelin and lower levels of the endogenous antagonist LEAP-2, compared to males. Furthermore, circulating ghrelin levels were partly dependent on estradiol; ovariectomy drastically reduced circulating ghrelin levels, which were partly restored by estradiol replacement. In contrast, orchiectomy did not affect circulating plasma ghrelin. Additionally, females expressed higher levels of the endogenous ghrelin receptor GHSR1A in brain areas involved in feeding and anxiety: the lateral hypothalamus, hippocampus, and amygdala. Moreover, overnight fasting increased GHSR1A expression in the amygdala of females, but not males. To evaluate the behavioral consequences of these molecular differences, male and female rats were tested in the elevated plus maze (EPM), open field (OF), and acoustic startle response (ASR) after three complementary ghrelin manipulations: increased endogenous ghrelin levels through overnight fasting, systemic administration of ghrelin, or blockade of fasting-induced ghrelin signaling with a GHSR1A antagonist. Here, females exhibited a stronger anxiolytic response to fasting and ghrelin in the ASR, in line with our findings of sex differences in the ghrelin axis. Most importantly, after GHSR1A antagonist treatment, females but not males displayed an anxiogenic response in the ASR, and a more pronounced anxiogenesis in the EPM and OF compared to males. Collectively, female rats are wired for higher sensitivity to fasting-induced anxiolytic ghrelin signaling. Further, the sex differences in the ghrelin axis are modulated, at least partly, by gonadal steroids, specifically estradiol. Overall, ghrelin plays a more prominent role in the regulation of anxiety-like behavior of female rats.

The combination of reinforcement learning and deep learning has shown some remarkable results in many scientific fields. Deep reinforcement learning algorithms are particularly good at understanding and modeling adaptive decision-making in dynamic environments. In recent years, this concept has been successfully applied to smart grids. In this paper, we provide a brief introduction to the concepts of reinforcement and deep reinforcement learning to the power system engineers and present research progress and prospects in the field. Additionally, we identify smart grid engineering domains that need extensive pattern-based modeling as being particularly suitable for deep reinforcement learning.

AIMS European guidelines set low-density lipoprotein cholesterol (LDL-C) treatment goals <1.4 mmol/L after acute coronary syndrome (ACS), and <1.0 mmol/L for patients with recurrent cardiovascular events ≤2 years. Many ACS patients do not achieve these goals on statin alone. We examined actual goal achievement with alirocumab and projected achievement with ezetimibe, either added to optimized statin therapy. METHODS AND RESULTS The ODYSSEY OUTCOMES trial (NCT01663402) compared alirocumab with placebo in 18,924 patients with recent ACS and hyperlipidaemia despite high-intensity or maximum-tolerated statin therapy. This subanalysis comprised 17,589 patients with LDL-C ≥1.4 mmol/L at baseline who did not receive ezetimibe treatment. High-intensity statin treatment was used in 88.8%. Median (interquartile range) baseline LDL-C was 2.3 (1.9-2.7) mmol/L. With alirocumab, 94.6% of patients achieved LDL-C <1.4 mmol/L at ≥1 post-baseline measurement vs. 17.3% with placebo. Among 2236 patients with a previous cardiovascular event within 2 years (before the qualifying ACS), 85.2% vs. 3.5%, respectively, achieved LDL-C <1.0 mmol/L. Among patients not treated with ezetimibe, we projected that its use would have achieved LDL-C <1.4 and <1.0 mmol/L in 10.6% and 0%, respectively at baseline (assuming 18 ± 3% reduction of LDL-C). CONCLUSION Among patients with recent ACS and LDL-C ≥1.4 mmol/L despite optimized statin therapy, addition of alirocumab allowed 94.6% to achieve the 2019 European guideline LDL-C goal <1.4 mmol/L, and 85.2% of those with recurrent cardiovascular events to achieve <1.0 mmol/L. In contrast, addition of ezetimibe to optimized statin therapy was projected to achieve LDL-C <1.4 mmol/L in only 10.6% of patients at baseline.

PURPOSE OF THE STUDY The hip fracture is the leading cause of disability and deaths in elderly. If left untreated, the hip fracture results in inability to walk, and therefore the patient is dependent on the other's people help. The aim of this study was to determine the predictive values of the functional status, present comorbidities, and the types of treatment on the long-term functional status and mortality in patients with the hip fracture. MATERIAL AND METHODS We analyzed the data about the patients with the hip fractures treated in the period between 01.07.2006. and 01.07.2016., with the mean follow-up period between 34.3±4.9 months. The data included radiographs, age, comorbidities, functional status on admission, functional status on discharge, and follow-ups. RESULTS Female sex, increasing age, and poorer functional status upon admission, conservative treatment, trochanteric fracture, the presence of neurological or lung disease, diabetes, were all significant risk factors leading to poorer functional outcomes on the latest follow-up (p < 0.05). On the other hand, the patients who were mobile upon admission had a longer survival (38.1±3.51 months) as compared with the other patients (12.3±5.1 months; χ2=25.202, p = 0.001). Besides, the results of this study revealed that the direct, statistically significant relationship exists between the untreated internal and neurological diseases, and increased mortality and poorer functional outcomes on the latest follow-up. CONCLUSIONS These results are useful for the orthopedic and trauma surgeons, who are treating these patients, the physical medicine and rehabilitation specialists, who are performing the rehabilitation of these patients, but also the health policy makers, who may promote the programmes of healthy aging (treating the diseases, maintaining fitness, etc.) Key words: hip fracture; comorbidity; mortality; functional status.

Background Pharmacogenomics (PGx) testing can reduce toxicities and improve efficacy of several drugs used to treat cancer and associated symptoms. PGx results can be determined from germline whole-exome sequencing (WES), but somatic mutations may cause discordance between tumor and germline DNA. Since clinical diagnostic sequencing in oncology frequently only includes tumor DNA, there would be clinical value in calling germline PGx genotypes from tumor DNA. Thus, the purpose of this study was to assess the feasibility of using somatic WES data to call germline PGx genotypes. Methods Germline and somatic WES data were obtained as part of the clinical workflow for 64 patients treated at the solid molecular tumor board clinic at Indiana University. Aldy v3.3 was implemented in LifeOmic’s Precision Health Cloud™ to call PGx genotypes from somatic WES. Somatic Aldy calls were compared with previously validated Aldy germline calls for 8 genes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, and TPMT. Somatic read depth was >100x, except for the intronic CYP3A4*22 variant, which was >30x. Results Somatic and germline Aldy calls were compared for a total of 512 genotypes and 56 (11%) calls were discordant. Discordant calls were most common for CYP2B6 (23.4%), followed by CYP2D6 (14.1%), CYP2C19 (10.9%), CYP2C8 (6.3%), and DPYD (6.3%). In contrast, all Aldy calls were concordant for CYP3A5 and TPMT. 38 out of 64 subjects (59%) had discordant calls for at least one gene. The most common first cancer diagnoses in our cohort were colorectal (9.3%), breast (7.8%), and pancreatic (7.8%), and the rates of discordant Aldy calls did not differ by cancer type (p>0.05 for all cancer types). Based on our analyses of discordant calls, we anticipate that adjusting Aldy’s thresholds for variant calling may allow Aldy to determine genotypes from somatic WES data. Conclusion In most cases, genotype calls of drug metabolism genes from tumor DNA reflected the germline genotypes; however, additional work needs to be done to determine if the remaining discordant calls can be corrected by modifying the informatics tools or if they are due to somatic mutations. Citation Format: Wilberforce A. Osei, Tyler Shugg, Reynold C. Ly, Steven M. Bray, Benjamin A. Salisbury, Ryan R. Ratcliff, Victoria M. Pratt, Ibrahim Numanagić, Todd Skaar. Pharmacogenomics genotyping from clinical somatic whole exome sequencing: Aldy, a computational tool [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1151.

Quantification and scientific observations of the fate and transport of dissolved strontium in water systems, particularly cold climate water systems, are severely lacking. In this work, in an experiment conducted at a temperature of 6 °C, the observation of strontium precipitation along with calcium carbonate minerals from cold wastewater is investigated. ICP-MS is used for metal analyses where the distribution of the species and saturation state of minerals along with a surface complexation model was performed using the public-use USGS geochemical modeling software, PHREEQC (PH Redox Equilibrium (in C language)). Sample media were analyzed using XPS and Raman spectroscopy. The results suggest that the loss of strontium from natural waters is via the process of co-precipitation with calcite, a calcium carbonate polymorph. The observations and findings are intended to be useful to quantify the loss of 90Sr from the water, in the case of an unplanned release from a nuclear reactor-operated facility. The results indicate that the precipitation model is a robust and reliable approach to predicting and monitoring the behaviour and transport of strontium that may occur in natural environments as a result of an accidental nuclear release.

In this work, I analyze Nietzsche’s concept of the affirmation of life as one of the main concepts of his philosophy in general. To overcome the pessimism and decadence modern culture has fallen into, Nietzsche construes the concept of the affirmation of life as its main goal and imperative. Hence, for each individual, it is necessary to affirm life by achieving their own autonomy, i.e. pathos of distance. Only by achieving genuine pathos of distance, would human beings be able to overcome pessimism.

The growing need for autonomous systems in offshore industries has contributed to the increased use of machine learning methods. These systems promise to improve safety in operations. However, the methods as enablers of autonomy are susceptible to various failures while interpreting data and making decisions. Several studies have highlighted the lack of research on the reliability and resilience of autonomous systems powered by these standard methods. Recent research provides sets of data interpretation methods. Despite the popularity of machine learning, there is a significant drop in knowledge when these methods result in failures. These failures further support autonomous systems in making wrong decisions. For autonomous systems, resilience and safety management should be an integrated functionality for recovery from risky situations and reporting of incidents. This research proposes an overview of machine learning methods for interpreting sensor data captured by drones operated manually and autonomously. We apply Isolation Forest for anomaly detection analysis and evaluate the Decision tree, Random forest, kNN, Logistic Regression, SVM, and, Naive Bayes for classification analysis. The methods are chosen based on their adequacy and comparative research prevalence. Comparison between the two drone operation modes contributes to understanding the reliability level for autonomously collected data. This research’s results provide an evaluation of machine learning methods’ performance across sensor data.

The growing penetration of renewable resources such as wind and solar into the electric power grid through power electronic inverters is challenging grid protection. Due to the advanced inverter control algorithms, the inverter-based resources present fault responses different from conventional generators, which can fundamentally affect the way that the power grid is protected. This paper studied solar inverter dynamics focused on negative-sequence quantities during the restoration period following a grid disturbance by using a real-time digital simulator. It was found that solar inverters can act as negative-sequence sources to inject negative-sequence currents into the grid during the restoration period. The negative-sequence current can be affected by different operating conditions such as the number of inverters in service, grid strength, and grid fault types. Such negative-sequence responses can adversely impact the performance of protection schemes based on negative-sequence components and potentially cause relay maloperations during the grid restoration period, thus making system protection less secure and reliable.

Background: In last 2 decades, there have been substantial changes in the utilization patterns of antihypertensive medicines following new clinical trials and the introduction of new treatment guidelines. The aim of this study was to analyze utilization and prescribing patterns regarding antihypertensive medicines in the Republic of Srpska, Bosnia and Herzegovina during an 11-years follow-up according to national and European treatment guidelines. Methods: In this retrospective, observational study, medicine utilization data were analyzed between 2009–2019 period using the ATC/DDD methodology and expressed as the number of DDD/1,000 inhabitants/day (DID/TID). The medicine utilization 90% (DU90%) method was used for determine the quality of prescribing. Results: During the observed period, the use of antihypertensive medicines increased more than 3-times (125.97 DDD/TID in 2009 vs 414.95 DDD/TID in 2019), corresponding to a rise in the prevalence of hypertensive patients from 91.7/1,000 to 186.3/1,000 in the same period. This was mainly driven by increased use of angiotensin converting enzyme inhibitors with 241.69%, beta blockers with 146.87%, calcium channel blockers with 251.55%, and diuretics with 178.95%. Angiotensin receptor blockers were the fastest growing group of antihypertensive medicines in this period and their utilization increased nearly 40 times. Conclusions: The overall antihypertensive medicines utilization was largely influenced by national and ESH/ESC guidelines and strongly corresponded to the positive medicine list of the national health insurance fund. Antihypertensive medicines utilization is comparable with medicine utilization trends in other countries.

The paper analyzes the normative-formative framework that denotes the connection between memory and identity as a crucial origin of conflicts. In addition to concerns about memory politics, historical revisionism and ethnonational identity collectivism, the paper dissolves the connection between phenomena highlighting outcomes of the peace process, transitional justice, and its ethical/moral connotations. The study argues that Western Balkan’s sociopolitical stability depends on declining conflicting and contradictory memory order within radical sociopolitical processes. The revisionist contention memorializes conflicts and wars as the fundamental concept of ethnicity/religion/nation. It overlaps with the neoliberal and neoconservative reduction of all competitive relations, in which only the stronger have the right to existence. Discarding dominant ethnopolitical narratives is essential for conflict transformation and transitional justice for all ethnoreligious communities. The Balkan historical events and conflicting memory (WW2, Yugoslav wars) caused sociopolitical dominion shaping the collective behavior of ethnic groups. The damaging ethnic/religious practice of genocide denial and honoring war crimes within people’s social lives can become a matrix for future conflicts. Placing memory politics with radical populism is a critical condition of collective identity politics in the former Yugoslavia. Scientific rationality can provide a solid path through the anomalies in the form of political ideologies.

Abstract Background Specialty training in plastic, reconstructive and aesthetic surgery is a prerequisite for safe and effective provision of care. The aim of this study was to assess and portray similarities and differences in the continuing education and specialization in plastic surgery in Europe. Material and Methods A detailed questionnaire was designed and distributed utilizing an online survey administration software. Questions addressed core items regarding continuing education and specialization in plastic surgery in Europe. Participants were addressed directly via the European Leadership Forum (ELF) of the European Society of Plastic, Reconstructive and Aesthetic Surgery (ESPRAS). All participants had detailed knowledge of the organization and management of plastic surgical training in their respective country. Results The survey was completed by 29 participants from 23 European countries. During specialization, plastic surgeons in Europe are trained in advanced tissue transfer and repair and aesthetic principles in all parts of the human body and within several subspecialties. Moreover, rotations in intensive as well as emergency care are compulsory in most European countries. Board certification is only provided for surgeons who have had multiple years of training regulated by a national board, who provide evidence of individually performed operative procedures in several anatomical regions and subspecialties, and who pass a final oral and/or written examination. Conclusion Board certified plastic surgeons meet the highest degree of qualification, are trained in all parts of the body and in the management of complications. The standard of continuing education and qualification of European plastic surgeons is high, providing an excellent level of plastic surgical care throughout Europe. Zusammenfassung Hintergrund Die Facharzt-Weiterbildung für Plastische und Ästhetische Chirurgie ist eine Grundvoraussetzung für sichere und effektive Patientenversorgung. Ziel der vorliegenden Studie war die Darstellung von Gemeinsamkeiten und Unterschieden in der Weiterbildung für Plastische Chirurgie innerhalb von Europa. Materialien und Methoden Ein internetbasierter Fragebogen wurde mit Hilfe eines kostenlosen Formularerstellungstools erstellt und verteilt. Die Fragen betrafen Kernpunkte der Weiterbildung für Plastische Chirurgie in Europa. Die Teilnehmer wurden direkt über das European Leadership Forum (ELF) der European Society of Plastic, Reconstructive and Aesthetic Surgery (ESPRAS) kontaktiert. Alle Teilnehmer hatten weitreichende Kenntnisse über die Organisation und Struktur der plastisch-chirurgischen Weiterbildung in ihrem jeweiligen Land. Ergebnisse 29 Teilnehmer*innen aus 23 europäischen Ländern nahmen an der Umfrage teil. Die Weiterbildung für Plastische Chirurgie beinhaltet grundlegende Prinzipien und Techniken zur Wiederherstellung von Form und Funktion innerhalb der verschiedenen Säulen der Plastischen Chirurgie, sowie in allen Körperregionen. In den meisten europäischen Ländern ist eine Rotation in der Intensiv- und Notfallmedizin und die Behandlung kritisch kranker Patienten obligatorisch. Voraussetzung für die Facharztbezeichnung ist die mehrjährige, national organisierte Weiterbildung, der Nachweis einer festgelegten Anzahl selbstständig durchgeführter Operationen, sowie die mündliche und/oder schriftliche Abschlussprüfung. Schlussfolgerung Fachärzte für Plastische und Ästhetische Chirurgie sind hochqualifiziert und auch im Umgang mit Komplikationen geschult. Der Standard der Weiterbildung der europäischen Plastischen Chirurgen ist hoch, so dass innerhalb Europas eine hohe Qualität plastisch-chirurgischer Versorgung gewährleistet ist.