Understanding the behaviour of a system’s API can be hard. Giving users access to relevant examples of how an API behaves has been shown to make this easier for them. In addition, such examples can be used to verify expected behaviour or identify unwanted behaviours. Methods for automatically generating examples have existed for a long time. However, state-of-the-art methods rely on either white-box information, such as source code, or on formal specifications of the system behaviour. But what if you do not have access to either? This may be the case, for example, when interacting with a third-party API. In this paper, we present an approach to automatically generate relevant examples of behaviours of an API, without requiring either source code or a formal specification of behaviour. Evaluation on an industry-grade REST API shows that our method can produce small and relevant examples that can help engineers to understand the system under exploration.

Castleman disease (CD) is a rare and heterogeneous lymphoproliferative disorder with shared lymph node (LN) histology. 1 While multicentric CD (MCD) involves multiple enlarged LNs, systemic inflammation

Child-robot interaction (CRI) has been mostly studied in labs and classroom settings. In this work, we share a CRI language processing study carried out in children’s homes. Any automated system deployed “in-the-wild” faces practical problems, but when the target users are children, these problems get even more sensitive and challenging. In this work we analyse how each language processing layer performs with children at home with no researcher present. We carried out an experiment with 7 families [N=14 children, 6-13 years old] cohabiting with a simulated robot for 2 weeks in their own homes. Our goal in this study is to evaluate the performance of voice recognition, language understanding and dialogue management when children interact with a robot at home. Our results indicate that dialogue management capabilities are becoming the key element in the language processing pipeline; they also denote that the dialogue engine should include mixed-initiative capabilities and show the relative usage of different common built-in intents.

Haru4Kids (H4K) is a system that emulates the physical, social, family-oriented robot Haru, designed with the goal to cohabitate with children in their home for extended periods of time. Seven families kept H4K for two net weeks in their homes. Throughout this period of cohabitation, we collected user logs comprised of the children users ’ head angles, the rotation angles of the platform, and the actions taken by H4K as well as captured images which were afterwards hand-annotated to estimate user engagement. We report the trends of these external metrics that we collected during every session of interaction. We also developed an annotation tool and report the Engagement Level Metric we chose to estimate child engagement throughout interactions “in-the-wild.” Overall, our platform offers a feasible system that can engage with children while also allowing us to monitor their engagement and behaviour throughout each interaction.

In this paper, we present an in-depth illustration of interaction failures relatively unexplored in the field of human-robot interaction (HRI). Our qualitative analysis of interactions between a social robot and 12 participants sheds light on different types of erroneous interactions initiated by human and robot actors and their outcomes. Our findings show that a small portion of observed failures had fatal impacts on interactions. In most cases, they had little negative effects on interactions or even led to favorable outcomes, causing laughter and giggling from participants, for example. Overall, our study calls for further examination of the roles of failures and contextual factors that influence the consequences of failures in HRI.

Robots may be able to significantly assist older adults through making activity recommendations. Prior research suggests that gender and age of a robot’s voice may affect how people respond to such recommendations, but few studies have explored how a robot’s voice is perceived by older adults, and whether their perceptions differ across cultures. We conducted a survey study with older adult participants (aged 65+) in the U.S. (N=225) and Japan (N=466), asking them to evaluate a humanoid robot speaking with three different voices (male, female, child). After seeing a video of a robot making recommendations, participants rated the fit of the voice to the robot, its sociality (via the Robotic Social Attributes Scale - RoSAS), and their willingness to use the robot in various contexts. We discovered that robot’s social attributes and participants’ culture impacted willingness to use the robot in both countries. Having positive social attributes and lower negative attributes increases willingness to use the robot. The U.S. older adults preferred the adult robot voices, had more positive social attributes, less negative social attributes, and were more likely to accept lifestyle recommendations than Japanese older adults. This study contributes to our understanding of older adults’ perceptions of robot voice and provides design implications for robots that make recommendations to older adults.

Previous work suggests that older adults’ meaning and happiness may be increased simply by having them engage in self-reflection exercises. Therefore, we design four modules to promote self-reflection, delivered by the QT robot. These modules were created with reference to three different time orientations — past, present, and future — and by incorporating aspects of life satisfaction and the PERMA model of well-being. Results show that about half of our older adult participants experienced subjective changes in meaning, happiness, and desire to make positive life changes during each module, with 11 of 15 participants experiencing changes to one of these measures after engaging in all four interactions. We make several suggestions for updating these modules for autonomous and longer-term deployment using the robot.

Socially-assistive robots (SARs) hold significant potential to transform the management of chronic healthcare conditions (e.g. diabetes, Alzheimer’s, dementia) outside the clinic walls. However doing so entails embedding such autonomous robots into people’s daily lives and home living environments, which are deeply shaped by the cultural and geographic locations within which they are situated. That begs the question whether we can design autonomous interactive behaviors between SARs and humans based on universal machine learning (ML) and deep learning (DL) models of robotic sensor data that would work across such diverse environments? To investigate this, we conducted a long-term user study with 26 participants across two diverse locations (United States and South Korea) with SARs deployed in each user’s home for several weeks. We collected robotic sensor data every second of every day, combined with sophisticated ecological momentary assessment (EMA) sampling techniques, to generate a large-scale dataset of over 270 million data points representing 173 hours of randomly-sampled naturalistic interaction data between the human and SAR. Models built on that data were capable of achieving nearly 84% accuracy for detecting specific interaction modalities (AUC 0.885) when trained/tested on the same location, though suffered significant performance drops when applied to a different location. Further analysis and participant interviews showed that was likely due to differences in home living environments in the US and Korea. The results suggest that our ability to create adaptable behaviors for robotic pets may be dependent on the human-robot interaction (HRI) data available for modeling.

Abstract The study aims to empirically determine whether a higher level of trade openness and the presence of better legal protection for investors enhances the impact of trade bloc membership on capital mobility based on four trading blocs: Eurasian Economic Union (EAEU), Central American and Dominican Republic Free Trade Agreement (CAFTADR), Central European Free Trade Agreement (CEFTA), and the Pacific Alliance. This study employs the fully modified and dynamic ordinary least squares estimators and a panel quantile regression cointegration estimator. The study finds that a country’s affiliation with a trade bloc improves capital mobility in the whole group and EAEU region, low capital mobility in the Pacific Alliance region and moderate low capital mobility in the CAFTA-DR region. The legal protection system alone provided for the investors does not improve the level of capital mobility unless its interaction with investment is included. Also the study reveals that high trade openness does not necessarily lead to better capital mobility for the studied trade blocs.

Distribution of radionuclides depends on various factors, and milk processing into cheese is recommended as one of the significant measures of radiation protection during radioactive contamination of the environment. A total of 16 milk and 16 cheese (soft and hard) samples were examined using HPGe gamma‐ray spectrometry to obtain 137Cs and 40K activity concentrations. The Pearson's correlation coefficients between 137Cs and 40K were determined (0.73, 0.68, 0.19, −0.23), followed by determination of distribution of 137Cs and 40K from cow milk to two types of cheeses using food processing retention factors (0.07–0.34). Transfer of 137Cs obtained could serve a great purpose for predicting its distribution during cheesemaking.

Biological activity of boron-containing compounds (BCCs) has been well-known. Growing interest and numerous applications for BCCs have been reported. Boron and boron-containing acids show low acute toxicity in mammals but data on halogenated boroxine (HB) - dipotassium-trioxohydroxytetrafluorotriborate, K 2 (B 3 O 3 F 4 OH) acute toxicity have not been reported before. This compound, characterized as a potential therapeutic for skin changes, exhibits no observable genotoxicity in doses lower that 0.1 mg/ml in vitro and 55 mg/kg in vivo. It has also been confirmed as an antitumour agent both in vitro and in vivo as well as an inhibitor of enzymes involved in antioxidant mechanisms. The aim of this study was to assess the acute toxicity of HB and to determine the maximum tolerated dose as well as a dose free of any signs of toxicity in different test organisms. Acute toxicity of HB was tested in Sprague-Dawley and Wistar rats and BALB/c mice after single parenteral application of different doses. We determined doses free of any sign of toxicity and LD 50 after single dose administration. LD 50 of HB ranges from 63 to 75 mg/kg in different test models, meaning that HB shows moderate toxicity.

Accurate determination of chromosome centromere location is of high importance in cytogenetics, particularly in karyotyping, chromosome classification and determination of exposure to genotoxic environmental effects. This study investigates the ability of CNN to accurately predict the human chromosome centromere location and the effect centering chromosomes in images, by predicted centromere location, has on classification accuracy. Dataset, used to train and test CNN models, contained 8283 annotated individual chromosome images. Prior to performing centromere detection, followed by chromosome classification, the individual chromosome images are preprocessed using sequence of filtering algorithms. The CNN model achieved an average error of 0.5586 and 0.4543 in predicting x and y coordinates of centromere location, respectively. The achieved classification accuracy of randomly oriented and centered chromosomes in images, is 71.10 and 96.73%, respectively. Achieved increase in chromosome classification accuracy of 25.63% highlights importance of chromosome centromere detection, importance of positional variation removal, and high performance of CNN in prediction of centromere location and chromosome classification.

To develop new antiphospholipid syndrome (APS) classification criteria with high specificity for use in observational studies and trials, jointly supported by the American College of Rheumatology (ACR) and EULAR.

Objective To develop new antiphospholipid syndrome (APS) classification criteria with high specificity for use in observational studies and trials, jointly supported by the American College of Rheumatology (ACR) and EULAR. Methods This international multidisciplinary initiative included four phases: (1) Phase I, criteria generation by surveys and literature review; (2) Phase II, criteria reduction by modified Delphi and nominal group technique exercises; (3) Phase III, criteria definition, further reduction with the guidance of real-world patient scenarios, and weighting via consensus-based multicriteria decision analysis, and threshold identification; and (4) Phase IV, validation using independent adjudicators’ consensus as the gold standard. Results The 2023 ACR/EULAR APS classification criteria include an entry criterion of at least one positive antiphospholipid antibody (aPL) test within 3 years of identification of an aPL-associated clinical criterion, followed by additive weighted criteria (score range 1–7 points each) clustered into six clinical domains (macrovascular venous thromboembolism, macrovascular arterial thrombosis, microvascular, obstetric, cardiac valve, and hematologic) and two laboratory domains (lupus anticoagulant functional coagulation assays, and solid-phase enzyme-linked immunosorbent assays for IgG/IgM anticardiolipin and/or IgG/IgM anti–β2-glycoprotein I antibodies). Patients accumulating at least three points each from the clinical and laboratory domains are classified as having APS. In the validation cohort, the new APS criteria vs the 2006 revised Sapporo classification criteria had a specificity of 99% vs 86%, and a sensitivity of 84% vs 99%. Conclusion These new ACR/EULAR APS classification criteria were developed using rigorous methodology with multidisciplinary international input. Hierarchically clustered, weighted, and risk-stratified criteria reflect the current thinking about APS, providing high specificity and a strong foundation for future APS research.

Dear Colleagues, We are delighted to share another issue (September 2023, Volume 29, Issue 3) of the European Journal of Therapeutics (Eur J Ther). We believe this issue’s valuable and exciting works will be read with interest. As you will notice at first glance, you will see that this issue contains many editorials and letters to the editor, unlike the previous issues. As the new editorial team, we aim to publish current developments, interesting notes, or important historical anecdotes in medicine as Editorials, Special Editorials, or Letters to the Editor. We would like to inform you that you can submit all of your articles that meet these criteria to our journal. In this editorial, we would like to share the developments that we think are important for Eur J Ther, since our previous editorial [1]. First, we would like to share that the Eur J Ther is approved for inclusion in ERIH PLUS [2]. Moreover, the Eur J Ther now also appears in the Journal Section of the ResearchGate [3]. In this way, it will be possible to follow the Eur J Ther through ResearchGate. We wish to inform you that our editorial team is diligently striving to deliver enhanced advancements in the forthcoming editions. Another significant development is that an application to the Index Copernicus was submitted for the Eur J Ther on July 31, 2023 [4]. In the previous issue, it was reported that some of the cited references made to the previous articles published in the Eur J Ther were not reflected in the Web of Science, and applications via “data changes form” were made to correct them [1]. Most of these applications have been completed, updated in the Web of Science database, and corrected missing references. With these corrections and new citations in the last three to four months, the average per-item value (total number of citations for all articles divided by the number of articles) of the Eur J Ther has increased from 0.52 to 0.78 [5]. In addition, the journal’s H-Index has risen from 8 to 10. The current metrics of Eur J Ther in the Web of Science are as follows, as of August 16, 2023 [5]. Total number of publications: 800 (between 2007 to 2023) Citing Articles (total): 593 Citing Articles (without self-citations): 558 Times Cited (total): 620 Times Cited (without self-citations): 570 Average per item: 0.78 (620/800) H-Index: 10 Although these metrics may be insufficient for Eur J Ther, which has been published for over thirty years, we, the New Editorial Team, anticipate that we can achieve better levels in the long run with our updated policies. Another significant development is that the Journal Impact Factor value of the Eur J Ther was calculated for the first time, and this value was 0.3. As is known, the Web of Science calculated Journal Impact Factors for the first time for journals in the E-SCI index as of 2023 [6]. Although a Journal Impact Factor of 0.3 is not satisfactory, it is not bad for a journal whose Journal Impact Factor is calculated for the first time. On the other hand, we believe that this value will increase in the coming years, as essential and valuable studies will be published in our journal. The previous issue reported that there are significant changes in the Editorial Board of Eur J Ther [1, 7]. We are pleased to inform you that we continue to expand our editorial team in this issue. Information about our esteemed editors, who have recently joined our team, is below. Ricardo Grillo, DDS, MBA, MSc, is a new Editorial Board Member of the Eur J Ther for Oral and Maxillofacial Surgery. Dr Grillo is the Head of the Department of Oral and Maxillofacial Surgery at IPESP (Brasília). He has more than 20 years of experience in Orthognathic Surgery, Oral Surgery and Maxillofacial Aesthetics. He is also a court expert in the topic. His special interest is related to new technologies including algorithms, virtual surgical planning, CAD and biotechnology. Figen Govsa (Gokmen), MD, finished her higher education at the Faculty of Medicine at Dokuz Eylul University in Izmir between 1982 and 1988. In 1989, she worked as a general practitioner at the Cal Health Center in Denizli Province. From 1990 to 1992, she served as an assistant at the Department of Anatomy at Ege University’s Faculty of Medicine. She worked as an associate professor at the Department of Anatomy between 1996 and 2001, and since 2001, she has been a professor. She has served in various faculty and upper management positions in Ege University’s institutional structure, continuing her education-focused administrative roles in several councils and committees at the Faculty of Medicine. She has contributed to undergraduate and postgraduate education across Ege University’s faculties, mentoring master’s, doctoral, and specialist students, helping them become academics in the field of anatomy. Her research interests include clinical anatomy (surgical anatomy, head and neck surgery, vascular surgery, reconstructive surgery), radio-anatomy, anatomy teaching, and personalized treatment algorithms. She is the founder of the Digital Imaging and Three-Dimensional Modeling Laboratory- Ege 3D Lab (www.ege3dlab.com), where personalized surgical plans have increased surgical success in complex cases involving orthopedics, general surgery, neurosurgery, eye surgery, radiation oncology, and thoracic surgery. With 150 SCI-expanded indexed academic journal articles, she has served as editor and chapter author for several scientific books published by national and international publishers. She has been an executor and researcher on numerous national projects in collaboration with national and international scientists. She is the Education and Terminology theme editor of the Surgical Radiological Anatomy journal and serves as an editor and reviewer for many foreign journals. She was the only anatomist from Turkey to be included in Stanford University's list of the World's Most Influential Scientists. Her joint publication with Prof. Dr. Yelda Pınar, titled "Anatomy of the superficial temporal artery and its branches: its importance for surgery", was ranked among the top 50 most-cited articles in the face rejuvenation theme by Mayo Clinic's Department of Plastic Surgery since 1950. It's the only study from Turkey in the "Landmarks in Facial Rejuvenation Surgery: The Top 50 Most Cited Articles. Aesthet Surg J, 2020." From 2010 to 2012, Govsa contributed as a member of the TÜBA Turkish Medical Terminology Dictionary Working Group and was invited to rejoin the TÜBA working group starting in 2021. Since its establishment, she has been a member of the Turkish Anatomy and Clinical Anatomy Association, serving on its Qualification Board and Ethical Committee. She is also a member of the European Clinical Anatomy Association (EACA). Özgür Kasapçopur, MD, is a Professor in Pediatrics at Istanbul University-Cerrahpasa, Cerrahpasa Medical Faculty, Department of Pediatrics, and is currently Head of Pediatric Rheumatology. He serves as the Chairman of the Institutional Review Board and Clinical Research Ethical Committee of Cerrahpasa Medical Faculty. Professor Kasapçopur received his undergraduate education in Medicine at Istanbul University, Cerrahpasa Medical Faculty and also completed here both his residency and fellowship in the Department of Pediatrics. Professor Kasapçopur is a member of the Pediatric Rheumatology European Society (PReS), the Pediatric Rheumatology International Trials Organization (PRINTO), the Turkish Pediatric Association and the Turkish National Society of Pediatric Rheumatology. Professor Kasapçopur’s research interests include vaccine response, cytokine pathway, and medical ethics, with clinical emphases on juvenile idiopathic arthritis, familial Mediterranean fever, autoinflammatory disease and juvenile systemic lupus erythematosus, dermatomyositis and scleroderma. Professor Kasapçopur has published 83 book chapters in Turkish medical textbooks, and more than 315 original peer-reviewed articles (and case reports) in medical journals. The h-index of Professor Kasapçopur is 55 in Google Scholar and 43 in Web of Science. He had more than 8800 citations in the Web of Science. Professor Kasapcopur is Editor-in-Chief of Turkish Archives Pediatrics. Additionally, Professor Kasapcopur is the Associate Editor of Archives of Rheumatology, Frontiers in Pediatrics, and Case Report in Pediatrics. He is also on the editorial board of many scientific national and international journals. Harry Pantazopoulos, PhD is a faculty member in the Department of Psychiatry and Human Behavior at the University of Mississippi Medical Center. Dr Pantazopoulos received his A.L.M. degree from Harvard University and his doctoral degree in Neurobiology from Northeastern University in Boston. He trained as a postdoctoral fellow and a Junior Faculty at Mclean Hospital, Harvard Medical School before joining the University of Mississippi. The research of the Pantazopoulos lab is focused on identifying the neuropathological correlates of psychiatric disorders with an emphasis on the role of the extracellular matrix and circadian rhythms. He pursues these questions using a combination of human postmortem and animal model approaches. His long-term research goal is to develop a foundation of changes in neurocircuitry in several diseases, including Autism Spectrum Disorders, Schizophrenia, Bipolar Disorder, Major Depression and Substance Use Disorders, that he can leverage to develop more effective treatments. In addition, he aims to identify basic biological mechanisms that will provide insight into how the circadian system and the extracellular matrix regulate neural functions in a brain region-specific manner, linked to specific behaviors. Ghada Shahrour, PhD, PMHCNS, RN is a faculty member at the Faculty of Nursing in Jordan University of Science and Technology. She is an associate professor in the field of psychiatric nursing and currently is the Chairman of the Community and Mental Health N