Miracle-dz/UniFAR-FTUs huggingface dataset:
Dosimetric measurements of 68Ga-High Affinity DOTATATE

Summary Purpose: 68Ga-labelled compounds are increasingly used for somatostatin-receptor scintigraphy because of their favourable biokinetic properties, a higher tumour-to- background contrast and higher diagnostic accuracy compared to the gamma-emitting tracer 111In-DTPA-octreotide. Recently, we have introduced the new tracer 68Ga-DOTA- 3-iodo-Tyr3-Thr8-octreotide (68Ga-HA-DOTA- TATE). The present study demonstrates the biodistribution and radiation dosimetry of this tracer in humans. Patients, methods: Seven men were enrolled in this analysis. Every patient underwent a 20 min dynamic PET scan after intravenous injection of about 114 ± 9 MBq of 68Ga-HA-DOTATATE. This was followed by two whole-body scans at 30 min p. i. and 120 min p. i. Blood radioactivity concentration was determined non-invasively from a ROI drawn over the aorta. Urine was collected until the time of the last scan. Liver, spleen, kidneys and urinary bladder wall were included in the dosimetric estimation that was carried out with the software package OLINDA 1.0. Results: Physiological 68Ga- HA-DOTATATE uptake was observed in the pituitary gland, thyroid, salivary glands, liver, spleen, kidneys, urinary bladder, adrenals and intestine. Organs with the highest absorbed dose were spleen (0.26 ± 0.11 mSv/MBq), kidneys (0.14 ± 0.03 mSv/MBq) and liver (0.12 ± 0.02 mSv/MBq). The estimated effective dose was 0.024 ± 0.001 mSv/MBq. Conclusion: Our study demonstrates biokinetics and radiation exposure of the 68Ga-labelled tracer HA-DOTATATE to be comparable to other 68Ga-labelled SSR analogues in clinical use.
Median Effective Dose of Dexmedetomidine Inducing Bradycardia in Elderly Patients Determined by Up-and-Down Sequential Allocation Method

Purpose: When dexmedetomidine is used in elderly patients, high incidence of bradycardia is reported. Given age-related physiological changes in this population, it is necessary to know the safety margin between the loading dose of dexmedetomidine and bradycardia. Therefore, we conducted this study to investigate the median effective dose (ED50) of dexmedetomidine causing bradycardia in elderly patients. Methods: Thirty patients with ages over 65 years undergoing elective general surgery were enrolled. The Dixon and Massay sequential method were applied to determine the loading dose of dexmedetomidine, starting from 1.0 µg/kg. The dose for the follow-up subjects increased or decreased according to the geometric sequence with the common ratio 1.2, based on the 'negative' or 'positive' response of the previous subject. Positive mean that the subject developed bradycardia during the test. Hemodynamic data including heart rate and systolic blood pressure were recorded. The level of sedation was assessed with the Observer Assessment of Alertness and Sedation Scale (OAA/S). Results: Bradycardia occurred in 13 patients (43.3%). The ED50 of dexmedetomidine causing bradycardia was 1.97 µg/kg (95% CI, 1.53-2.53 µg/kg). OAA/S scores at 10 min after the beginning of the dexmedetomidine infusion and 10 min after the termination of dexmedetomidine administration showed no significant differences between the positive and negative groups (P > 0.05). Conclusion: The ED50 of dexmedetomidine causing bradycardia in our cohort was higher than clinical recommended dose. A higher loading dose appears acceptable for a faster onset of sedation under careful hemodynamic monitoring. Trial registration: ChiCTR 15006368.
Prognostic Values of Combined Ratios of White Blood Cells in Glioblastoma: A Retrospective Study

In some malignant tumours, the changes in neutrophil counts in relation to other blood cells are connected with unfavourable prognosis. Nevertheless, the prognostic value of the combinations of the haematological components in glioblastoma (GBM) remains under dispute. The clinical significance of the neutrophil-to-lymphocyte ratio (NLR), systemic immune inflammation index (SII), and systemic inflammation response index (SIRI) was investigated in our study. We retrospectively studied 358 patients (males n = 195; females n = 163) aged 59.9 ± 13.5 yrs with newly diagnosed glioma and admitted to the Neurosurgery Centre. Routine blood tests and clinical characteristics were recorded within the first hour of hospital admission. The inflammatory variables: NLR, SII and SIRI exceeded the reference values and were significantly elevated in Grade 3 and Grade 4 tumour. The Cox model analysis showed that the age ≥ 63 years, NLR ≥ 4.56 × 103/µL, SII ≥ 2003 × 103/µL and SIRI ≥ 3.03 × 103/µL significantly increased the risk of death in Grade 4 tumour patients. In the inflammatory variables, NLR demonstrated the highest impact on the survival time (HR 1.56; 95% CI 1.145–2.127; p = 0.005). In the first Polish study including GBM patients, the age in relation to simple parameters derived from complete blood cell count were found to have prognostic implications in the survival rate.
Understanding Students’ Cyberslacking Behaviour in e-Learning Environments: Is Student Engagement the Key?

Abstract Many universities have slowly moved to online teaching due to the COVID-19 pandemic. Without the physical presence of instructors, students can easily engage in cyberslacking behaviour during online classes. Hence, the purpose of this research is to examine the association of student engagement with students’ cyberslacking behaviour during online classes. Both student engagement and cyberslacking are multidimensional constructs. Partial least square structural equation modelling (PLS-SEM) is used to analyse data from 194 university students using a survey method. The results reveal that psychological motivation, cognitive problem-solving, and interactions with instructors do not have a significant association with cyberslacking behaviour. On the other hand, peer collaboration, community support, and learning management are found to have different associations with different dimensions of cyberslacking behaviour. Learning management is identified as the most robust predictor of cyberslacking behaviour. This research fills the research gaps by investigating the associations of various dimensions of student engagement with different dimensions of students’ cyberslacking behaviour in the context of e-learning environments.
Separating the shortwave and longwave components of greenhouse gas radiative forcing

Many important greenhouse gases (including water vapour, carbon dioxide, methane and ozone) absorb solar radiation. When gas concentrations change, this absorption exerts a radiative forcing that modifies the thermal infrared (‘longwave’) radiative forcing which is predominant for most gases (ozone being a major exception). The nature of the solar forcing differs from the longwave forcing in several ways. For example, the sign of the instantaneous solar forcing can differ between the tropopause and top‐of‐atmosphere, and the sign can differ between gases. In addition, a significant part of the solar forcing can be manifested in the longwave, following stratospheric temperature adjustment, which can counteract or enhance the instantaneous solar forcing. Here the nature of solar forcing is examined via a mixture of idealised and more realistic calculations, which consider the effect of perturbations in carbon dioxide, methane and ozone. An apparent contradiction in the sign of the solar forcing of carbon dioxide is resolved; it is shown to be negative, reducing the net carbon dioxide forcing by about 2.3%. The relevance of this work to the effective radiative forcing concept is also discussed.
Mesh generation from imaging data

Digital images from computerized tomography (CT) and magnetic resonance (MR) scanners can be used to create computer models of anatomical shapes. These models are typically used in biomedical applications for the purpose of physical simulation and visualization. In this thesis, we describe new algorithms for creating models from 2D and 3D binary digital images. Our models are meshes of 2D shapes represented by 2D binary digital images, and meshes of the surface of 3D shapes represented by 3D binary digital images. More specifically, this thesis contains the following two contributions: First, we give an algorithm for converting constrained triangular meshes of polygonal domains into constrained and strictly convex quadrilateral meshes of the same domain. Our algorithm has linear time in the number of triangles of the input triangular mesh, produces a bounded number of quadrilaterals, offers better bounds than similar algorithms that also produce strictly convex quadrilateral meshes of bounded size, and tends to preserve the grading of the input triangular mesh. We also present examples to demonstrate that our algorithm can be successfully used to create quadrilateral meshes from 2D binary digital images of anatomical shapes, such as the human brain. Second, we provide a new algorithm for generating simplicial surface meshes that approximate the boundary of 3D shapes represented by 3D binary digital images. Our algorithm is based on a simplified version of one of two known algorithms for generating provably good quality simplicial approximations of smooth, implicit surfaces. Provably good quality simplicial surfaces are very desirable for visualization purposes, and the main advantage of our algorithm is to offer this provable quality guarantee.
Persuasive Strategies utilized in the Political Speeches of King Abdullah II: A Critical Discourse Analysis

Abstract This study investigates the persuasive strategies used in seven speeches of King Abdullah II of Jordan delivered before the UN, European Parliament, Islamic Countries Cooperation, and Arab League between 2007 to 2021. The study adopted the persuasive strategies: Intertextuality, Creativity and Metaphor, References, and Circumlocution to uncover how the King employed the rhetorical/persuasive strategies in his speeches. The discourse analysis approach of Fairclough is also adopted to analyze the speeches. The study revealed that King Abdullah II used creativity and metaphors, reference, circumlocution, and intertextuality. He used creativity strategy to highlight reality as it is. Besides, he uses intertextuality to convince the international community of his vision. On the other hand, the King utilizes neutral references (we, our, your, you) in his speeches to avoid impersonalistion. The study concluded that the King successfully used persuasive strategies to convey his vision toward political issues.
Approximating node-weighted Steiner subgraphs for multicast communication in wireless networks

We are motivated by the problem of computing multicast routing structures in wireless ad-hoc networks modelled by special classes of graphs including unit disk graphs, quasi-unit disk graphs and (λ + 1)-claw-free graphs. Multicast communication can be established by a tree known as Steiner tree. Wireless ad-hoc networks must operate using limited resources, therefore, the suitability of nodes for inclusion in a Steiner tree can vary widely between different nodes. We model this by assuming that each node of the network is assigned a weight that represents the cost of including it in the Steiner tree. Our goal is to compute a Steiner tree with minimum total node weight. However, in scenarios where nodes and links are not reliable, a tree has the drawback that it can be disconnected by the failure of even a single link or node in the network. Therefore, we also consider various fault-tolerant routing structures called 2-edge-connected Steiner subgraphs, k-edge-connected Steiner subgraphs, 2-vertex-connected Steiner subgraphs, and 2-edge-connected group Steiner subgraphs. The problems we consider are NP-hard, so we are interested in algorithms that compute provably good approximate solutions in polynomial time. We present a generalization of Steiner subgraph problems referred to as the node-weighted δ-Steiner subgraph problem, where δ represents connectivity requirements. We present an algorithm with approximation ratio 0. 5dρ for the node-weighted δ-Steiner subgraph problem, where d is the bounded maximum degree of the solution subgraph, and ρ is the approximation ratio of the edge-weighted version of the δ-Steiner subgraph problem. We then shown how to construct solution subgraphs of bounded maximum degree d in several graph classes for our problem variants. As a result, we obtain algorithms for the problems we consider, on graph classes that admit subgraphs of small degree, whose approximation ratios are better than the best known ratios for the same problems on general graphs.
HS‐UNET‐ID: An approach for human skin classification integrating between UNET and improved dense convolutional network

The Sun's ultraviolet radiation, toxic chemicals from industry, and other factors can cause problems to human skin. These factors have boosted the risk of humans contracting skin cancer. In identifying and detecting signals of skin cancer diseases, recent advancements in deep learning techniques significantly improve the accuracy of diagnosis. This work delves into processing techniques for human skin images with MorphologyEx (blackhat), thresholding, semantic segmentation with UNET, and several famous convolutional neural network architectures to improve skin classification performance. If skin cancer can be stopped in the first stage, the survival rate of the patient could be more than 95%, while it drops to just 5% if the detection is carried lately in Stage IV4. Due to its seriousness, the healthcare and research community has received considerable attention, and its most important goal is to be able to diagnose it at an early stage. However, the challenge due to the similarity in melanocytic and non‐melanoma skin lesions is inevitable. We achieved skin classification performances of 0.8560, 0.9672, 0.8063, and 0.8560 measured by overall accuracy, area under curve, Matthews correlation coefficient, and F1‐score, respectively. The proposed approach has been deployed into applications on Mobile and Web platforms.
Human leukocyte antigens: the unique expression in trophoblasts and their crosstalk with local immune cells

Trophoblasts differentiate and form the placenta during pregnancy in a complex and finely orchestrated process, which is dependent on the establishment of maternal-fetal immune tolerance and the proper function of trophoblasts. Trophoblasts express HLA-C and non-classical HLA-Ib molecules (HLA-E, HLA-F, and HLA-G). Numerous studies have shown that the unique expression pattern of the HLA molecules is closely linked to the successful acceptance of allogeneic fetus by the mother during pregnancy. However, some controversies still exist concerning the exact expression and recognition patterns of HLA molecules in different trophoblast subpopulations and cell lines. Thus, we summarize three types of trophoblast subpopulations as well as the common trophoblast lineages. Then, the classification and structural characteristics of HLA molecules were elucidated. Finally, the presence of HLA-C and non-classical HLA-Ib molecules (HLA-E, HLA-F, and HLA-G) in various trophoblasts and cell lines, as well as their potential role in establishing and maintaining normal pregnancy were also discussed. Together, this review will help people comprehensively understand the complex immune interactions between maternal and fetal crosstalk during pregnancy and ultimately better understand the physiological and pathological etiologies of pregnancy.
Causal Relations

: The goal of this paper is twofold. First, we aim to shed light on the need to distinguish French causal connectives which convey a semantic relation from those which convey a discourse relation. Next, we aim to put forward an analysis of coordination of causal relations, in comparison with coordination of facts. While the latter is well-known, the former has nearly never been studied.
Heterogeneity issues in the meta-analysis of cluster randomization trials.

An increasing number of systematic reviews summarize results from cluster randomization trials. Applying existing meta-analysis methods to such trials is problematic because responses of subjects within clusters are likely correlated. The aim of this thesis is to evaluate heterogeneity in the context of fixed effects models providing guidance for conducting a meta-analysis of such trials. The approaches include the adjusted Q statistic, adjusted heterogeneity variance (τ 2 c ) estimators and their corresponding confidence intervals and adjusted measures of heterogeneity (H a , R 2 a, I 2 a) and their corresponding confidence intervals. Attention is limited to meta-analyses of completely randomized trials having a binary outcome. An analytic expression for power of Q test is derived, which may be useful in planning a meta-analysis. The Type I error and power for the Q statistic, bias and mean square errors for the estimators and the coverage, tail errors and interval width for the confidence interval methods are investigated using Monte Carlo simulation. Simulation results show that the adjusted Q statistic has a Type I error close to the nominal level of 0.05 as compared to the unadjusted Q statistic which has a highly inflated Type I error. Power estimated using the algebraic formula had similar results to empirical power. For τ 2 c estimators, the iterative REML estimator consistently had little bias. However, the noniterative MVVC and DLVC estimators with relatively low bias may also be recommended for small and large heterogeneity, respectively. The Q profile confidence interval approach for τ 2 c had generally nominal coverage for large heterogeneity. The measures of heterogeneity had generally low bias for large number of trials. For confidence interval approaches, the MOVER consistently maintained nominal coverage for ‘low’ to ‘moderate’ heterogeneity. For the absence of heterogeneity, the approach based on the Q statistic is preferred. Data from four cluster randomization trials are used to illustrate methods of analysis.
The invariant manifolds of a finite straight segment

We give a method to compute explicitly the asymptotic expressions of some invariant manifolds in the vicinity of the collinear equilibrium points corresponding to the Hamiltonian system defined by the motion of a particle orbiting around a finite straight segment. For this we use normal form methods so that we make two different Lie transformations of the original Hamiltonian: (i) either we calculate the Hamilton function corresponding to the centre manifold of one of the collinear equilibrium points or (ii) either we determine the Hamiltonian related to the stable– unstable direction. By means of (i) we are able to parametrise the centre, the stable and the unstable manifolds of the original system using the direct changes of coordinates of the two transformations. Using (ii) we compute some 2D–tori and quasiperiodic orbits.
Precooling of Tomato Fruit for Shelf Life Extension

Tomato is a climacteric fruit grown widely in the world. After harvesting of tomato fruits its respiration continues and become more prone to microbial spoilage, water loss and decay due to field heat. Immediate precooling of fruits after harvesting removes the field heat and significantly extends the shelf life. Further, the storage of precooled tomato fruits at low temperature contributes to shelf life extension and retention of nutrition & sensory quality.
Naked-Eye Chromogenic Test Strip for Cyanide Sensing Based on Novel Phenothiazine Push–Pull Derivatives

Monitoring and detection of cyanide are of crucial interest as the latter plays versatile roles in many biological events, is ubiquitous in environment, and responsible for several acute poisoning and adverse health effects if ingested. We describe herein the synthesis and characterization of novel phenothiazine-based push–pull chromogenic chemosensors suitable for naked eye cyanide sensing. Indeed, specific detections were achieved for cyanide with a LOD of ca 9.12 to 4.59 µM and, interestingly, one of the new chemosensors has also revealed an unprecedented affinity for acetate with a LOD of ca 2.68 µM. Moreover, as proof of concept for practical applications, a paper test strip was prepared allowing its use for efficient qualitative naked eye cyanide sensing.
The Recommendation System of Innovation and Entrepreneurship Education Resources in Universities Based on Improved Collaborative Filtering Model

In the huge number of online university education resources, it is difficult for learners to quickly locate the resources they need, which leads to “information trek. ” Traditional information recommendation methods tend to ignore the characteristics of learners, who are the main subjects of education. In order to improve the recommendation accuracy, a recommendation algorithm based on improved collaborative filtering model is proposed in this paper. Firstly, according to the student behavior data, consider the behavior order to create the behavior graph and behavior route. Then, the path of text type is vectorized by the Keras Tokenizer method. Finally, the similarity between multidimensional behavior path vectors is calculated, and path collaborative filtering recommendations are performed for each dimension separately. The MOOC data of a university in China are introduced to experimentally compare the algorithm of the article as well as the control group algorithm. The results show that the proposed algorithm takes better values in evaluation indexes, thus verifying that this algorithm can improve the effectiveness of innovation and entrepreneurship education resources recommendation in universities.
Analysis of the Effects of Connected–Automated Vehicle Technologies on Travel Demand

Connected–automated vehicle (CAV) technologies are likely to have significant effects not only on how vehicles operate in the transportation system, but also on how individuals behave and use their vehicles. While many CAV technologies—such as connected adaptive cruise control and ecosignals—have the potential to increase network throughput and efficiency, many of these same technologies have a secondary effect of reducing driver burden, which can drive changes in travel behavior. Such changes in travel behavior—in effect, lowering the cost of driving—have the potential to increase greatly the utilization of the transportation system with concurrent negative externalities, such as congestion, energy use, and emissions, working against the positive effects on the transportation system resulting from increased capacity. To date, few studies have analyzed the potential effects on CAV technologies from a systems perspective; studies often focus on gains and losses to an individual vehicle, at a single intersection, or along a corridor. However, travel demand and traffic flow constitute a complex, adaptive, nonlinear system. Therefore, in this study, an advanced transportation systems simulation model—POLARIS—was used. POLARIS includes cosimulation of travel behavior and traffic flow to study the potential effects of several CAV technologies at the regional level. Various technology penetration levels and changes in travel time sensitivity have been analyzed to determine a potential range of effects on vehicle miles traveled from various CAV technologies.