Special Case Research Articles

The data layer: the importance of sources critical appraisal

Abstract One of the main purposes of public health institute is to tracking the health status of its citizens and understanding its evolution over time. Given the absence of a singular, comprehensive data source, we developed a framework to select databases specific to each disease and outcome of interest. This process includes a thorough evaluation of the operational case definitions, as well as the strengths and weaknesses of each database, with a particular focus on their sensitivity and specificity. These qualities are appraised following a dedicated scoring form into different categories (i.e., high, medium, low). The selection criteria for data sources hinge on several key questions: Is the database exhaustive or merely a sample? Does the case definition rely on direct medical diagnoses or proxies? Does the source capture all cases? Is the data collected at regional or national level? Are there mechanisms for yearly or periodic updates? To establish the most accurate national prevalence estimates for each outcome, we often need to adjust for data misclassification-applying corrections for biases such as self-reported data and interpolating for missing entries. In some instances, a pooled estimate from multiple data sources is developed. A specific case will be presented to illustrate our approach in practice. This critical evaluation is pivotal, as the quality of data underpins the entire health information pyramid. The integrity of our data directly influences our ability to convert data into actionable health wisdom, ultimately affecting public health decision-making and policy formulation.

Towards ML Models’ Recommendations

AbstractArtificial Intelligence encompasses a range of technologies that replicate human-like cognitive abilities through computer systems, enabling the execution of tasks associated with intelligent beings. A prominent way to achieve this is machine learning (ML), which optimizes system performance by employing learning algorithms to create models based on data and its inherent patterns. Today, a multitude of ML models exist having diverse characteristics, including the algorithm type, training dataset, and resultant performance. Such diversity complicates the selection of an appropriate model for a specific use case, answering user demands. This paper presents an approach for ML models retrieval based on the matching between user inputs and ML models criteria, all described in a semantic ML ontology named SML model (Semantic Machine Learning model), which facilitates the process of ML models selection. Our approach is based on similarities measures that we tested and experimented to score the ML models and retrieve the ones matching, at best, user inputs.

Same term, but unequal understanding: differences in digital public health intervention features

Abstract Digital technologies have transformed healthcare delivery and public health, with many countries integrating interventions such as online consultations, electronic health records, and telemedicine to improve population health and healthcare accessibility. Multinational assessments for benchmarking system maturity ask for the degree of implementation of such tools. However, are these interventions as comparable as they claim to be? This talk presents a qualitative analysis of 179 digital public health (DiPH) interventions described in scientific articles. We categorized interventions based on their implementation stages, public health functions, and reported and non-technical features. Telemedicine, health apps, and electronic health record interventions dominated the diverse landscape. While these technology groups already differed greatly in their functions, we identified equally significant differences in the reported intervention characteristics within the groups. For example, telemedicine was not only used in healthcare settings for patients and health professionals but also in primary prevention and research for researchers, policymakers, and healthy individuals. Different interventions reported varying functions, such as remote monitoring, self-monitoring, alarm systems, patient motivation, and user empowerment modules. So, is there one common telemedical intervention? No. Instead, all individual technologies differed to varying degrees. The analysis underscored the diversity of DiPH interventions among and within intervention groups and highlighted the importance of precise terminology for effective planning and evaluation. Instead of using broad classifications like ‘telemedicine,’ interventions should be defined and communicated based on specific technological functions, non-technical characteristics, use cases, and user groups. This approach will promote cross-disciplinary collaboration and foster international comparability across DiPH systems.

Research ethics implications in the development of personalised therapy for pediatric SIRS patients

Abstract Background Pediatric Systemic Inflammatory Response Syndrome (SIRS) presents diagnostic and therapeutic challenge that can be addressed through personalised therapy. Related ethical challenges are understudied. Our report aims at identification and analysis of research ethics implications within the bigger ERA PerMed funded project of development of tailored immunotherapy for paediatric SIRS patients (TIPS) coordinated by Prof. Catharina Schütz from Technic University Dresden. Methods A sample of 10 experts with different backgrounds was studied through semi-structured interviews. Systematic literature review grounded the interview questionnaire. The transcripts were subjected to thematic analysis by two independent researchers. Results Five classical research ethics issues were identified: respect for autonomy; informed consent; risk-benefits ratio; data protection; social justice. All experts favoured the empowerment of children (N = 10) and obtainment of informed consent rather than assent was seen as a common goal (N = 5). The emergency context of SIRS research impeded the informed consent. Despite favourable risk-benefits ratio, no direct benefits resulted to study participants. Data anonymisation though necessary (N = 10), hinders proper dealing with incidental findings. Social justice issues apparently accompanied research design in personalised medicine (N = 2) but should not extend to access to personalised therapy. Conclusions The classical framework of research ethics is challenged by the new fields of medical research. Traditional concepts, such as informed consent in minors, are subject to rethinking. Current ethical and legal guidelines fall short of proper practical instructions in the specific case of SIRS pediatric patients. Thus, ethical aspects of new technology development should always be studied in parallel to the biometrics within personalised medicine projects so as to the development of guidelines is more evidence-based than precautionary driven. Key messages • Current ethical and legal guidelines fall short of proper practical instructions in the specific case of SIRS pediatric patients. • Ethical aspects of new technology development should always be studied within personalised medicine projects so as to the development of guidelines is more evidence-based than precautionary driven.

The Role of the Hemostasis and Thrombosis Unit in the Management of the Patients with Acquired Hemophilia.

Acquired hemophilia A (AHA) is a rare autoimmune disease characterised by the presence of autoantibodies against coagulation factor VIII (FVIII), leading to spontaneous haemorrhage in patients without a prior family or personal history of bleeding. This study describes the demographics, diagnosis, underlying disorders, bleeding characteristics, treatment, and outcomes of 41 AHA patients, along with specific case reports. Diagnosis and treatment occurred between 2005 and 2023. The median age at diagnosis was 67.8 years (range 15-93). Among the 41 patients, 10 (24%) were idiopathic, 4 (10%) were postpartum, 18 (44%) had autoimmune diseases, and 9 were diagnosed with cancer. Diagnostic delay exceeded 30 days in 15 out of the 41 cases (36.5%). A total of 38 out of the 41 (93%) patients presented with spontaneous bleeding, with mucocutaneous bleeding being the most common presentation (23/41, 56%). Four patients experienced postpartum bleeding. Clinical remission was achieved in 100% of patients, and no patient died. Haemostatic and Immunosuppressive therapy is essential in AHA, and it should be started as soon as possible in patients with bleeding. However, a significant delay in diagnosis was observed. The absence of mortality is likely attributable to the management of the disease within a specialised Haemostasis and Thrombosis Unit, which offers a clinical ward, a specialised laboratory, and a dedicated ambulatory service. The Italian Society for the Study of Haemostasis and Thrombosis (SISET) is working to secure recognition for this essential role in every hospital.

Analysis of Risk Management and Prevention Strategies in the International Operations of Enterprises

With the deepening of globalization, more and more enterprises are looking towards the international market in search of broader development space. However, international operations not only bring unprecedented opportunities but also accompany various risks. This article delves into the risks enterprises may encounter in international operations, including market, political, economic, exchange rate, legal, and cultural risks, and systematically analyzes the causes, manifestations, and impacts of these risks. Through specific case analyses, this article proposes a series of practical risk management and prevention strategies aimed at helping enterprises build a more robust international operation defense line, ensuring their steady progress in the complex and volatile international market.

Psychiatric comorbidity and hospitalization outcomes for AMI in portuguese public hospitals

Abstract Background Severe mental health disorders directly affect quality of life but may also indirectly relate to physical diseases and their prognosis. We test this hypothesis for the specific case of acute myocardial infarction (AMI), postulating a longer in-patient stay and an excess in-hospital mortality among patients suffering psychiatric comorbidities (PC). Methods A retrospective observational study was conducted using secondary data from public Portuguese hospitals, for all patients with a primary diagnosis of AMI (12,213 patients aged 18-80, for the years 2017-18). We used linear and logistic regression to model length of stay (LoS) and in-hospital mortality, respectively. Having at least one psychiatric comorbidity was the explanatory variable, and models were adjusted for age, sex, and the Charlson Comorbidity Index. Results The prevalence of PC was 12.95%. The in-hospital mortality rate was significantly higher in the group with PC (4.43%, OR = 1.372, 95%CI=1.041-1.784), than in the group without PC (3,38%). Stays were significantly longer among those with PC (mean=7.69 days), compared to those without PC (mean=6.87 days; adjusted β-coefficient=0.098, 95%CI=0.056-0.141). Conclusions Patients with AMI and comorbid mental disorders have poorer hospitalization outcomes than those without PC. This emphasizes the importance of promoting effective management strategies for comorbid psychiatric disorder, for instance, by improving the integration of mental health care in general hospitals, and empowering healthcare professionals to recognize and manage patients with PC. Key messages • Psychiatric comorbidity is related to longer inpatient stays and higher mortality risk among patients with AMI. • Efforts to integrate mental health care in general hospitals should be maintained.

Study of Contactless Computer Vision-Based Road Condition Estimation Methods Within the Framework of an Operational Design Domain Monitoring System

Deployment of Level 3 and Level 4 autonomous vehicles (AVs) in urban environments is significantly constrained by adverse weather conditions, limiting their operation to clear weather due to safety concerns. Ensuring that AVs remain within their designated Operational Design Domain (ODD) is a formidable challenge, making boundary monitoring strategies essential for safe navigation. This study explores the critical role of an ODD monitoring system (OMS) in addressing these challenges. It reviews various methodologies for designing an OMS and presents a comprehensive visualization framework incorporating trigger points for ODD exits. These trigger points serve as essential references for effective OMS design. The study also delves into a specific use case concerning ODD exits: the reduction in road friction due to adverse weather conditions. It emphasizes the importance of contactless computer vision-based methods for road condition estimation (RCE), particularly using vision sensors such as cameras. The study details a timeline of methods involving classical machine learning and deep learning feature extraction techniques, identifying contemporary challenges such as class imbalance, lack of comprehensive datasets, annotation methods, and the scarcity of generalization techniques. Furthermore, it provides a factual comparison of two state-of-the-art RCE datasets. In essence, the study aims to address and explore ODD exits due to weather-induced road conditions, decoding the practical solutions and directions for future research in the realm of AVs.

Ingenuidade e Inércia Cognitiva como Atributos para a Viralização de Fake News nas Redes Sociais Online

The dissemination of fake news on online social networks has created a scenario of disinformation in which manipulation and control are used to influence behavior and gain advantages. This phenomenon has motivated joint efforts to inhibit its spread. However, despite these initiatives, the problem persists. The assumption is that users of these channels, who are key agents in confronting this phenomenon, become contributors to disinformation when affected by naivety or cognitive inertia. The aim is to analyze the role of these users in the spread of fake news and identify factors that influence their uncritical stance. Conducted through a narrative review of the literature for theoretical purposes, this analysis adopts a reflective, exploratory and essayistic approach to the condition of co-participants of online social network users in the face of the problem of fake news, based on key themes such as post-truth and critical information competence, and illustrated by an empirical analysis of three specific cases of viral fake news. It is concluded that users of online social networks, when naive and inert, are part of the problem and, therefore, need to be more reactive, instead of, consciously or unconsciously, becoming agents of misinformation.

Paradigm changes in research: Kuhn meets socio-ecological transition theory

Recent research indicates that disruptiveness in science has decreased, triggering discussions about the reason for this. Earlier Thomas Kuhn discussed why revolutions in science are slow but inevitable processes. To better understand transition processes within a scientific discipline, this article draws on a novel transition concept. The concept combines ideas about the structure of scientific revolutions with the concept of adaptive cycles. Combining these two approaches facilitates theorization of the reasons for the reduced disruptiveness at the scientific discipline (system) level. To elucidate the interplay between individuals and the scientific discipline, and thus their role in processes of scientific paradigm shifts, the new model further integrates resilience theory. Factors determining the resilience of an adaptive system explain resistance to change at individual and system levels, as well as the interplay between these two levels. The discourse between environmental and ecological economics is used to illustrate the theoretical discussion and apply the novel transition concept to a specific case. The analysis shows that institutionalization, providing better answers to anomalies, and uncovering maladaptation are key in the transition process.

Dental implantation in patients with comorbid diseases: yes or no?

Patients with multiple pathologies are a high-risk group, which requires a personalized approach to surgical rehabilitation in dentistry. Inadequate diagnosis of clinical manifestations when a patient is in remission often leads to severe surgical complications. However, modern methods of dental implantation and rehabilitation are possible even in patients with oncology, those who underwent surgical therapy, chemo- or radiotherapy. Gilbert syndrome, one of the risk factors for post-surgery inflammatory complications, is associated with defects in bilirubin metabolism. It inhibits platelet activity. It is a genetic disease leading to a loss of liver enzyme activity and the accumulation of indirect bilirubin that can aggravate the course of other diseases in patients. In acute stages, it is characterized by jaundice of the skin, eyes, and mucosa and is followed by immunosuppression and the post-surgical complications associated with it. A patient with Gilbert syndrome was administered for surgical treatment of a chronic infection and follow-up rehabilitation via dental implantation and reconstruction of the bone. In this case, we faced Gilbert syndrome in association with polycythemia (a myeloproliferative disease in the compensation stage). In such cases, dental implantation cannot be achieved in the complex dental rehabilitation process. Such diseases require special attention from dental surgeons due to possible complications (bleeding, thrombosis, or disseminated intravascular coagulation). In this specific case, the patient belongs to the risk group, and its history, although in remission, is still a contraindication for dental surgery and dental implantation.

Augmented reality guidance improves accuracy of orthopedic drilling procedures

In several orthopedic procedures, the accurate use of surgical power tools is critical to avoid damage to surrounding tissues. As such, various guidance techniques and safety measures were developed. Augmented reality (AR) guidance shows promise but requires validation. We evaluated a new approach using an inside-out infrared tracking solution for the HoloLens to compensate for its limited tracking performance. Eighteen participants with varying levels of experience (student, trainee, expert) each drilled twelve trajectories (six perpendicular, six oblique) in equidimensional wooden logs. Three different techniques were evaluated: freehand drilling; proprioception-guided drilling towards the contralateral index finger; and AR-guided drilling using a tracked drill and a virtual overlay of the log with predefined guidance vectors. The angular errors between planned and performed trajectories were compared using a mixed-design ANOVA. The results demonstrated that guidance technique (p < 0.001) and drilling direction (p < 0.001) significantly affected drilling accuracy, while experience (p = 0.75) did not. AR outperformed both other techniques, particularly for oblique trajectories (p < 0.001). For perpendicular trajectories, it only outperformed proprioception guidance (p = 0.04). Target plots revealed an important scatter perpendicular to the longitudinal axis of the log during freehand and proprioception-guided drilling, especially for oblique trajectories. This inaccuracy disappeared during AR-guided drilling. As such, we were able to conclude that AR guidance using inside-out infrared tracking reduced angular uncertainty during directional drilling, resulting in improved drilling accuracy. This improvement was particularly noticeable for complex trajectories and angles. The benefits of AR guidance were observed across all experience levels, highlighting its potential for orthopedic applications. We believe this study opens the way for the methodical evaluation of AR guidance in specific orthopedic use cases.

Process mining in supply chain management: state-of-the-art, use cases and research outlook

Recent advances in process mining technology have extended its applicability beyond traditional domains such as healthcare, finance and manufacturing, making it increasingly relevant for addressing problems in supply chain management. In our research, we explore the integration of process mining techniques within the domain of supply chain management, focusing on uncovering inefficiencies, ensuring compliance, and identifying opportunities for improvement. Therefore, we first review the technological advances in process mining relevant to supply chain management and outline six relevant approaches. We then combine the identified methodologies with expert interviews to derive and validate six specific use cases where process mining can significantly contribute to supply chain efficiency and resilience. The paper presents a detailed description of these use cases, demonstrating how process mining can provide actionable insights for a wide range of supply chain problems. We discuss the implications of our findings for practitioners, who benefit from enhanced visibility and optimisation opportunities, and researchers, who are provided with a roadmap for exploration of this promising interdisciplinary field. To the best of our knowledge, this is the first work to explore potential use cases for process mining in a supply chain context, providing a comprehensive perspective on the potential benefits and challenges.

Las musas griegas en América Latina: de tuteladoras de la élite a inspiradoras de la cultura popular

This text shows the survival of classical mythology in Latin America through the specific case of the Greek Muses, who inhabited Latin American theater halls during the 19th and 20th centuries. After a diachronic tour of the halls where the presence of the Muses can be observed in the facades and interiors, we will try to get closer to the political meaning of the daughters of Zeus and Mnemosyne in these spaces of sociability. Once the corpus of coliseums with Muses has been located and systematized, we will propose that Euterpe, Melpomene, Thalia, Terpsichore and their sisters, beyond their ornamental or decorative dimension, could have been the expression of the Latin American bourgeois spirit during the Belle Époque (1870-1920). Later, from the second half of the 20th century, the Muses began to appear in popular and mass culture, democratizing their iconography and meaning without losing their inspirational character.

Assessing the Impact of Technology on the Efficiency and Effectiveness of Investment Banking Services

This paper evaluates the effect of innovation on the effectiveness and adequacy of venture managing an account administrations. It reflects on the way digital innovations such as artificial intelligence, blockchain, and data management systems have transformed such missions as securities underwriting, mergers and acquisitions, and client advisory services. By combining these technologies, investment banks optimize their processes, improve precision, and bring in enhanced customer experiences. Deliberating through critical review of literature and specific cases from the industry, this paper explores how artificial intelligence changes the decision-making processes, automates trading strategies, and enhances risk management, while blockchain changes back-office operations by making transactions faster and more secure. Advanced data management tools equally provide improved insight into the enhanced client services and decisions in investments for the banks. Although this brings cost-cutting and operational efficiency, these technologies pose challenges in cybersecurity and regulatory compliance due to the expansion of digital platforms, which provide increased opportunities for cyber-attacks and a need for strict adherence to ever-changing regulations. The paper provides a panoramic view of the current and future role of technology in evolving investment banking.

Знакомиться нельзя копировать, или История одной таможенной проверки

Although administrative procedures of customs control are regulated to a great extent, a review of the judicial practice provides evidence of violations of rights of verified persons during a customs inspection. The article uses the example of a specific legal case to review problems of protection of procedural rights of a non-public subject in customs relations. The author studies challenging problems of protection of rights and legal interests of persons audited by customs authorities based on materials of Ruling of the Constitutional Court of the Russian Federation No. 22-П of April 28, 2023. The paper reaches a conclusion about discretion of customs and judicial authorities not in favor of non-public subjects, which eventually is able to limit basic constitutional rights of citizens and organizations, in particular, the right to review documents and materials that directly relate to rights and freedoms of an individual in the interaction with public government authorities (Clause 2, Article 24 of the Constitution of the Russian Federation). The author assesses the position of customs and judicial authorities from the standpoint of mutual trust between government authorities and audited persons, fulfillment of legal expectations of an audited person, predictability of decisions and actions of government authorities, their responsibility for such decisions and actions.

Rational Design of an Activatable Near-Infrared Fluorogenic Platform for In Vivo Orthotopic Tumor Imaging and Resection.

Rational and effective design of a universal near-infrared (NIR) light-absorbed platform employed to prepare diverse activatable NIR fluorogenic probes for in vivo imaging and the imaging-guided tumor resection remains less exploited but highly meaningful. Herein, mandelic acid with a core structure of 4-hydroxylbenzyl alcohol to link recognition unit, a fluorophore and a quencher was employed to prepare activatable probes. We exemplified ester as carboxylesterase (CE)-recognized unit, ferrocene as quencher and phenothiazinium as NIR fluorophore to afford fluorogenic probes termed NBS-Fe-CE and NBS-C-Fe-CE. These probes enabled the conversion toward CE with significant fluorescence increases and successfully discriminate CE activity in cells. NIR light enhances the tumor penetration and enable imaging-guided orthotopic tumor resection. This specific case demonstrated that this platform can be effectively used to construct diverse NIR probes for imaging analytes in biological systems.

Streamlining management in thoracic trauma: radiomics- and AI-based assessment of patient risks.

In blunt chest trauma, patient management is challenging because clinical guidelines miss tools for risk assessment. No clinical scale reliably measures the severity of cases and the chance of complications. The objective of the study was to optimize the management of patients with blunt chest trauma by creating models prognosticating the transfer to the intensive care unit and in-hospital length of stay (LOS). The study cohort consisted of 212 cases. We retrieved information on the cases from the hospital's trauma registry. After segmenting the lungs with Lung CT Analyzer, we performed volumetric feature extraction with data-characterization algorithms in PyRadiomics. To predict whether the patient will require intensive care, we used the three groups of findings: ambulance, admission, and radiomics data. When trained on the ambulance data, the models exhibited a borderline performance. The metrics improved after we retrained the models on a combination of ambulance, laboratory, radiologic, and physical examination data (81.5% vs. 94.4% Sn). Radiomics data were the top-accurate predictors (96.3% Sn). Age, vital signs, anthropometrics, and first aid time were the best-performing features collected by the ambulance service. Laboratory findings, AIS scores for the lower extremity, abdomen, head, and thorax constituted the top-rank predictors received on admission to the hospital. The original first-order kurtosis had the highest predictive value among radiomics data. Top-informative radiomics features were derived from the right hemithorax because the right lung is larger. We constructed regression models that can adequately reflect the in-hospital LOS. When trained on different groups of data, the machine-learning regression models showed similar performance (MAE/ROV 8%). Anatomic scores for the body parts other than thorax and laboratory markers of hemorrhage had the highest predictive value. Hence, the number of injured body parts correlated with the case severity. The study findings can be used to optimize the management of patients with a chest blunt injury as a specific case of monotrauma. The models we built may help physicians to stratify patients by risk of worsening and overcome the limitations of existing tools for risk assessment. High-quality AI models trained on radiomics data demonstrate superior performance.

Impact of Various High Intensity Earthquake Characteristics on the Inelastic Seismic Response of Irregular Medium-Rise Buildings

In the twenty-first century, the seismic design of buildings seems to have become a fully recognized topic. There are guidelines and standards which should be taken into account by designers in seismic areas. Designers using modern international guidelines have ascertained that the behavior of structures is not as expected. New challenges in the construction industry result in the construction of structures with new, unusual shapes. These are structures that do not meet the assumptions of safe construction in seismic areas. Contemporary buildings are also characterized by their irregular distribution of structural elements. Such solutions are not beneficial from the point of view of seismic engineering and can lead to reduced dynamic resistance and damage in such structures. In this paper, a five-storey, irregular-shaped reinforced concrete (RC) building model was subjected to different earthquakes with varying magnitudes, PGA (peak ground acceleration) and PGV (peak ground velocity) values, and durations of the intense shock phase. Once the model was verified using previous in situ measurements, the building model was subjected to five earthquakes. A numerical nonlinear analysis of the building was performed using a verified FEA (finite element analysis) model in the time domain through non-linear time history analysis with the Broyden–Fletcher–Goldfarb–Shanno (BFGS) method. The building’s dynamic properties were measured using various methods of excitation. The model was influenced, among others, by two far-field representative events caused by the last earthquake in Turkey, which resulted in strong ground motion. The analysis results identified the locations of structural damage and allowed for the assessment of the structure’s dynamic resistance. The results of the calculations prove that the duration of the intensive phase of extortion is one of the reasons for building damage in earthquake-prone areas. Building damage occurs with earthquakes that are characterized by an intensive phase of excitation with a long duration and high values of velocity in the earthquake components. The article highlights the inadequate dynamic resistance of the building, leading to excessive displacements and unfavorable structural solutions. Damage to buildings at this earthquake intensity caused damage to the load-bearing structure, which was not designed for such intensities. This paper is a research report with a specific case study of medium-rise irregular RC buildings.

Scenario Generation Based on Ant Colony Optimization for Modelling Stochastic Variables in Power Systems

Uncertainty is an important subject in optimization problems due to the unpredictable nature of real variables in the power system area, which can condition the solution’s accuracy. The effective modelling of stochastic variables can contribute to the reduction in losses in the system under evaluation and facilitate the implementation of an effective response in advance. To model uncertainty variables, the most extended technique is the scenario generation (SG) method. This method evaluates possible combinations of complete curves. Classical scenario generation methods are founded on probability distributions or robust stochastic optimization. This paper proposes a novel approach for constructing scenarios using the Ant Colony Optimization (ACO) algorithm, referred to as ACO-SG. This methodology does not require a previous statistical study of uncertainty data to generate new scenarios. A historical dataset and the desired number of scenarios are the inputs inserted into the algorithm. In the case study, the algorithm used historical data from the Savona Campus Smart Polygeneration Microgrid of the University of Genoa. The approach was applied to generate scenarios of photovoltaic generation and building consumption. The low values of the Euclidean distance were used in order to check the validity of the scenarios. Moreover, the error deviation of the scenarios generated with the goal of daily power were 1.77% and 0.144% for the cases of PV generation and building consumption, respectively. The different results for both cases are explained by the characteristics of the specific cases. Despite these different results, both were significantly low, which indicates the capability of the algorithm to generate any kind of feature within curves and its adaptability to any case of SG.