Miracle-dz/UniFAR-FTUs huggingface dataset:
Passivity, task segmentation, and relational capital: a study of interpersonal relationship formation among freshman medical students in team-based activities

Purpose Team-based learning in medical education facilitates the formation of interpersonal relationships, enhances academic achievement, and establishes future clinical connections. Despite medical schools’ distinct educational environments and curricula, research investigating students’ learning and behavioral characteristics within this context remains limited. This study aimed to investigate the specific characteristics of interpersonal relationship formation among freshmen medical students in team-based learning activities. Methods Focus group interviews were conducted with 11 students who participated in a team-based class held during the first semester of the premedical year. Results Medical students passively expressed their thoughts and feelings, such as active sympathy for the team’s opinions and self-censorship of SNS (social networking service) conversations. When performing team activities, students were excessively conscious of others and focused on evenly dividing their work, minimizing their opinions, and fulfilling their share to prevent potential interpersonal conflicts. Interpersonal activities were only superficial, as students intentionally maintained a certain distance from team members or used team activities as an opportunity to accumulate relational capital. Conclusion The results of this study are expected to provide a useful basis for designing and conducting team activity classes to enhance interpersonal relationship formation.
INVASIVE FUNGAL INFECTIONS IN CHILDREN TREATED FOR HEMATOLOGIC MALIGNANCIES – A FIVE-YEAR SINGLE CENTER EXPERIENCE

SUMMARY Invasive fungal infections (IFI) are life-threatening complications of intensive chemotherapy treatment, with the incidence in pediatric patients ranging from 2% to 21%. In this article, we describe our 5-year experience of IFI in pediatric oncology patients and its clinical manifestations with radiological findings, treatment and outcome. A retrospective and descriptive survey of IFI in children with hematologic neoplasms was conducted at the Department of Oncology and Hematology, Zagreb Children’s Hospital. Medical charts of children 0-17 years of age, of both sexes, treated for leukemias and lymphomas from January 2016 to December 2020 were reviewed. In a 5-year period, 60 patients were treated for hematologic malignancy, acute lymphoblastic leukemia (ALL) being the most prevalent diagnosis. IFI was verified in 9 (15%) children, predominantly in patients with ALL (75%). The specific causative agent was detected in one child, whereas other infections were classified as probable pulmonary aspergillosis. All the patients received standard prophylaxis with fluconazole and treatment with liposomal amphotericin B and voriconazole. The majority of our patients achieved recovery. IFI prevention, diagnosis and treatment remain a challenge. Uniform prophylaxis and therapy protocols, as well as environmental control are of vital importance for the development of better strategies in the prevention, early detection and treatment of IFI in pediatric hematology patients.
Multiscale anomaly detection and image registration algorithms for airborne landmine detection

Abstract : Multiscale techniques such as the wavelet transform have become a powerful tool for image compression, denoising, and analysis. This thesis outlines the use of such techniques for developing a multiscale processing stream for the purpose of airborne landmine detection. In this work, the Reed-Xiaoli (RX) multispectral anomaly detection algorithm is extended to perform detection within the shift-invariant wavelet representation of a given single-band image. A test statistic is derived and shown to better detect anomalies in a correlated noise background than the single-band RX algorithm. The results of a detection algorithm using the shift-invariant wavelet representation and a multi-layer perceptron neural network are also discussed. A scale-space image registration algorithm is presented, where the scale-invariant feature transform (SIFT) has been used to search for control points between two images. The use of SIFT allows for image features invariant to scaling, translation and rotation to be matched in feature space, resulting in more accurate image registration than traditional correlation-based techniques.
Performance of Prognostic Scoring Systems in MINOCA: A Comparison among GRACE, TIMI, HEART, and ACEF Scores

Background: the prognosis of patients with myocardial infarction with non-obstructive coronary arteries (MINOCA) is not benign; thus, prompting the need to validate prognostic scoring systems for this population. Aim: to evaluate and compare the prognostic performance of GRACE, TIMI, HEART, and ACEF scores in MINOCA patients. Methods: A total of 250 MINOCA patients from January 2017 to September 2021 were included. For each patient, the four scores at admission were retrospectively calculated. The primary outcome was a composite of all-cause death and acute myocardial infarction (AMI) at 1-year follow-up. The ability to predict 1-year all-cause death was also tested. Results: Overall, the tested scores presented a sub-optimal performance in predicting the composite major adverse event in MINOCA patients, showing an AUC ranging between 0.7 and 0.8. Among them, the GRACE score appeared to be the best in predicting all-cause death, reaching high specificity with low sensitivity. The best cut-off identified for the GRACE score was 171, higher compared to the cut-off of 140 generally applied to identify high-risk patients with obstructive AMI. When the scores were tested for prediction of 1-year all-cause death, the GRACE and the ACEF score showed very good accuracy (AUC = 0.932 and 0.828, respectively). Conclusion: the prognostic scoring tools, validated in AMI cohorts, could be useful even in MINOCA patients, although their performance appeared sub-optimal, prompting the need for risk assessment tools specific to MINOCA patients.
Patient perspectives on same-day discharge following catheter ablation for atrial fibrillation: results from a patient survey as part of the monocentric FAST AFA trial

Abstract Aims Same-day discharge (SDD) following catheter ablation (CA) of atrial fibrillation (AF) was already introduced in selected facilities in Europe, but a widespread implementation has not yet succeeded. Data on patients’ perspectives are lacking. Therefore, we conducted a survey to address patients’ beliefs towards SDD and identify variables that are associated with their evaluation. Methods and results As part of the prospective, monocentric FAST AFA trial, patients aged ≥20 years undergoing left atrial CA for AF were asked to participate in the survey consisting of a study-specific questionnaire, the AF knowledge scale, and pre-defined patient-reported outcome measures. The study cohort was stratified based on SDD willingness, and a logistic regression analysis was used to identify predictors for patients’ valuation. Between 26 July 2021 and 01 July 2022, 256 of 376 screened patients consented to study participation of whom 248 (mean age 61.8 years, 33.9% female) completed the SDD survey. Of them, 50.0% were willing to have SDD concepts integrated into their clinical course with increased patient comfort (27.5%), shorter waiting times (14.6%), and a cost-efficient treatment (14.0%) being imaginable benefits. In contrast, expressed concerns included uncertainties with occurring complaints (50.6%), the insufficient recognition (47.8%), and treatment (48.9%) of complications. European Heart Rhythm Association class at baseline and inpatient treatments within the preceding year were predictors for SDD willingness whereas comorbidity burden or AF knowledge were not. Conclusion We provide a detailed survey expressing patients’ beliefs towards SDD following left atrial CA. Our findings may facilitate adequate patient selection to improve the future implementation of SDD programs in suitable cohorts.
Infection prevention and early warning in neonatal intensive care unit based on physiological sensor monitoring

The infection rate in the Neonatal Intensive Care Unit (NICU) is very high, which is also one of the important causes of morbidity and even death in critically ill neonates and premature infants. At present, the monitoring system of the Neonatal Intensive Care Unit is not very complete, and it is difficult to provide early warning of neonatal illness. Coupled with the untimely response measures, it has brought certain difficulties to the ward’s infection prevention and control work. The rapid development of the Internet of Things (IoT) in recent years has made the application fields of various sensor devices more and more extensive. This paper studied infection prevention and early warning in the Neonatal Intensive Care Unit based on physiological sensors. Combined with a wireless network and physiological sensors, this paper built an intelligent monitoring system for the Neonatal Intensive Care Unit, which aimed to monitor various physiological data of newborns in real-time and dynamically, and gave early warning signals, so that medical staff could take preventive measures in time. The experiments showed that the monitoring system proposed in this paper could obtain the physiological information of neonates in time, which brought convenience to prevention and early warning work, and reduced the infection rate of neonatal wards by 7.39%.
Assessment of seasonality and normalization techniques for wastewater-based surveillance in Ontario, Canada

Introduction Wastewater-based surveillance is at the forefront of monitoring for community prevalence of COVID-19, however, continued uncertainty exists regarding the use of fecal indicators for normalization of the SARS-CoV-2 virus in wastewater. Using three communities in Ontario, sampled from 2021–2023, the seasonality of a viral fecal indicator (pepper mild mottle virus, PMMoV) and the utility of normalization of data to improve correlations with clinical cases was examined. Methods Wastewater samples from Warden, the Humber Air Management Facility (AMF), and Kitchener were analyzed for SARS-CoV-2, PMMoV, and crAssphage. The seasonality of PMMoV and flow rates were examined and compared by Season-Trend-Loess decomposition analysis. The effects of normalization using PMMoV, crAssphage, and flow rates were analyzed by comparing the correlations to clinical cases by episode date (CBED) during 2021. Results Seasonal analysis demonstrated that PMMoV had similar trends at Humber AMF and Kitchener with peaks in January and April 2022 and low concentrations (troughs) in the summer months. Warden had similar trends but was more sporadic between the peaks and troughs for PMMoV concentrations. Flow demonstrated similar trends but was not correlated to PMMoV concentrations at Humber AMF and was very weak at Kitchener (r = 0.12). Despite the differences among the sewersheds, unnormalized SARS-CoV-2 (raw N1–N2) concentration in wastewater (n = 99–191) was strongly correlated to the CBED in the communities (r = 0.620–0.854) during 2021. Additionally, normalization with PMMoV did not improve the correlations at Warden and significantly reduced the correlations at Humber AMF and Kitchener. Flow normalization (n = 99–191) at Humber AMF and Kitchener and crAssphage normalization (n = 29–57) correlations at all three sites were not significantly different from raw N1–N2 correlations with CBED. Discussion Differences in seasonal trends in viral biomarkers caused by differences in sewershed characteristics (flow, input, etc.) may play a role in determining how effective normalization may be for improving correlations (or not). This study highlights the importance of assessing the influence of viral fecal indicators on normalized SARS-CoV-2 or other viruses of concern. Fecal indicators used to normalize the target of interest may help or hinder establishing trends with clinical outcomes of interest in wastewater-based surveillance and needs to be considered carefully across seasons and sites.
Comprehensive Investigation of Fluoroquinolone Residues in Apis mellifera and Apis cerana Honey and Potential Risks to Consumers: A Five-Year Study (2014–2018) in Zhejiang Province, China

As a group of antibiotics largely used in China’s animal husbandry, fluoroquinolone (FQ) residues in honey may pose potential threats to human health. This study performed a five-year investigation on the occurrence of FQ residues in honey in 521 Apis mellifera and 160 Apis cerana honey samples collected from Zhejiang Province, China and compared FQ residue profiles in honey with a subgroup of various factors. Deterministic and probabilistic risk assessments of exposure to FQ residues in honey were further conducted. Overall, four FQs were detected in 6.9% (47/681) of analyzed samples; banned norfloxacin with the highest level (7890 μg·kg−1) and detection frequency (4.9%) was the primary safety risk factor associated with honeybees raised in China. FQ detection frequency and concentration of rape honey was highest among four of the largest and most stable honeys (rape, acacia, chaste, and linden) in China. Processed honey from commercial sale channels had a significantly higher detection frequency of FQ residues than raw honey from apiaries. Deterministic assessment showed that the noncarcinogenic hazard quotient (HQ) value of the dietary intake of FQs by the local population was between 4.75 × 10−6 and 1.18 × 10−3, less than 1.0, indicating that FQ residues in honey posed a low risk for consumers. The order of the HQ value was ciprofloxacin > norfloxacin > enrofloxacin > ofloxacin. Probabilistic assessment showed that at P95, the HQ of FQs for the age groups of children, adolescents, adults, and older adults over 65 years ranged from 2.39 × 10−5 to 0.217, less than 1, and the exposure risk for adults was higher than for children and adolescents. Sensitivity analysis showed that FQ concentrations were the major contributors to health risks. Although a low risk was found, a strict hive management is needed for beekeepers regarding troubles of food safety, international trade, and human bacterial resistance.
Experimental Investigations of Ice Rubble: Shear Box and Pile Testing

The largest part of an ice ridge consists of unconsolidated ice rubble, whose material properties decide the load from ridges on ships and structures. Material resistance is attributed to the initial freeze-bonds and the friction and interlocking between blocks. The objective of the thesis was to investigate rubble behaviour by two tests: shear box test at NTNU and pile test at HSVA. The shear box test was aimed at investigating freeze-bond mechanisms in rubble. The pile test was aimed at suggesting values for rubble properties for a model scale experiment. The shear box had dimensions 600 mm x 400 mm x 40 mm, and was filled with ice blocks of 60 mm x 22 mm x 40 mm simulating rubble. Confinement was added, the box was submerged for 10 minutes, and tested in a rig by forcing the rubble to fail in shear. Force vs. displacement was measured. Different types of saline ice and submerging water temperatures were used. Pile testing consisted of making an elongated pyramid-shaped pile, baseline 600 mm, of rubble collected from the ice tank at HSVA. The pile was tilted and geometry was measured before and after failure happened in the pile. Main results from the shear box tests were the observation of a first phase deformation of rubble, that displayed a near linear force-displacement relation and a first peak shear stress. Magnitude of first peaks was measured in the range 8.9 kPa to 59.7 kPa, and depended on submersion water temperature, salinity of ice, how blocks were cut in respect to crystal structure in the ice sheet and confining pressure. Pile tests had repose angles ranging from 36.0° to 47.3°, and cohesion for an assumed angle of friction of 30° was in the range of 172 Pa to 342 Pa. First phase shear stress was compared to shear strength of single freeze-bond tests of the same ice, and direct relations were found. The magnitude of first peak shear stress in tests varied most with ice salinity and crystal structure. The measured repose angles for pile tests give an upper limit for internal angles of friction, and values seemed reasonable. The ice was warm, and this may the reason for the low cohesions.
Declined Live Birth Rate from in vitro Fertilization Fresh Cycles Performed During Chinese New Year Holiday Season

Purpose This study aims to investigate the impact of the Chinese New Year (CNY) holiday season on the outcomes of In Vitro Fertilization (IVF) fresh embryo transfer cycles. Participants and Methods This retrospective study analyzed 4688 patients who received their first IVF fresh cycle attempt between January 2017 and October 2021. Of these, 4449 women underwent IVF during non-holiday seasons, while 239 women were treated during the CNY holiday season. The study included women who underwent IVF treatment during the specified time frame. The primary outcome was the live birth rate (LBR). Results The study found that the LBR of IVF performed during the CNY holiday season was 32.22%, which is significantly lower than that of the non-holiday season (43.38%, p<0.001). Multivariate logistic regression analysis showed that the CNY holiday season (OR=0.62, 95% CI 0.47–0.82, p=0.001) was an independent factor associated with the live birth rate. Propensity score matching (PSM) data analysis showed that the LBR in the CNY holiday season group was 31.78% compared to 42.64% in the non-holiday season group (p=0.005). Inverse probability of treatment weighting (IPTW) data also indicated that the CNY holiday season had a lower LBR than the non-holiday season (OR=0.64, 95% CI 0.47–0.87, p=0.005). Conclusion IVF performed during the CNY holiday season results in a lower live birth rate, potentially indicating that certain lifestyle adjustments during this period, such as unhealthy dietary, tobacco and alcohol usage, sleep disruption, and emotional stress experienced could have some influence on the outcomes.
Statistical Evaluation of 3D Manifolds Shape Retention during Simplification Stages

Simplification of 3D meshes is a fundamental part of most 3D workflows, where the amount of data is reduced to be more manageable for a user. The unprocessed data includes a lot of redundancies and small errors that occur during a 3D acquisition process which can often safely be removed without jeopardizing is function. Several algorithmic approaches are being used across applications of 3D data, which bring with them their own benefits and drawbacks. There is for the moment no standardized algorithm for cultural heritage. This investigation will make a statistical evaluation of how geometric primitive shapes behave during different simplification approaches and evaluate what information might be lost in a HBIM (Heritage-Building-Information-Modeling) or change-monitoring process of cultural heritage if each of these are applied to more complex manifolds.
A STABLE BEHAVIORAL MODEL FOR THE USE OF ORGANIZATIONAL PSYCHOLOGY IN PERSONNEL MANAGEMENT IN THE FRAMEWORK OF ENSURING FINANCIAL AND ECONOMIC SECURITY

The main purpose of the article is the formation of a new model for the use of organizational psychology in personnel management in the framework of ensuring financial and economic security. The object of research is the personnel management system. Within the framework of the study, a modern approach to the processes of using organizational psychology in personnel management in the system of ensuring financial and economic security was used. As a result of the study, a model for the use of organizational psychology in personnel management was presented. The innovativeness of the results obtained is presented in the form of a methodical approach to the formation of a stable behavioral model for the use of organizational psychology in personnel management in the framework of ensuring financial and economic security. The study is limited by not taking into account all aspects of organizational psychology. Thus, the prospects for further research will be devoted to expanding the use of organizational psychology in personnel management within the framework of a systematic approach. The difference between our results lies not only in the combination of psychology and safety but also in the use of a new modeling method.
Field rules and bias in random surveys with quota samples. An assessment of CIS surveys

Surveys applying quota sampling in their final step are widely used in opinion and market re- search all over the world. This is also the case in Spain, where the surveys carried out by CIS (a public institution for sociological research supported by the government) have become a point of reference. The rules used by CIS to select individuals within quotas, however, could be improved as they lead to biases in age distributions. Analysing more than 545,000 responses collected in the 220 monthly barometers conducted between 1997 and 2016 by CIS, we compare the empiri- cal distributions of the barometers with the expec ted distributions from the sample design and/or target populations. Among other results, we find, as a consequence of the rules used, significant overrepresentations in the observed propor tions of respondents with ages equal to the minimum and maximum of each quota (age and gender group). Furthermore, in line with previous litera- ture, we also note a significant overrepresentation of ages ending in zero. After offering simple solutions to avoid all these biases, we discuss some of their consequences for modelling and inference and about limitations and potentialities of CIS data.
Different topological patterns in structural covariance networks between high and low delay discounters

Introduction People prefer immediate over future rewards because they discount the latter’s value (a phenomenon termed “delay discounting,” used as an index of impulsivity). However, little is known about how the preferences are implemented in brain in terms of the coordinated pattern of large-scale structural brain networks. Methods To examine this question, we classified high discounting group (HDG) and low discounting group (LDG) in young adults by assessing their propensity for intertemporal choice. We compared global and regional topological properties in gray matter volume-based structural covariance networks between two groups using graph theoretical analysis. Results HDG had less clustering coefficient and characteristic path length over the wide sparsity range than LDG, indicating low network segregation and high integration. In addition, the degree of small-worldness was more significant in HDG. Locally, HDG showed less betweenness centrality (BC) in the parahippocampal gyrus and amygdala than LDG. Discussion These findings suggest the involvement of structural covariance network topology on impulsive choice, measured by delay discounting, and extend our understanding of how impulsive choice is associated with brain morphological features.