Miracle-dz/UniFAR-FTUs huggingface dataset:
Canine urinary lactate and cortisol metabolites in hypercortisolism, nonadrenal disease, congestive heart failure, and health

Spontaneous hypercortisolism (HC) is a common endocrine disease of senior dogs, often overlapping in selected clinical signs and hematologic and blood biochemical abnormalities with nonadrenal diseases (NADs). HC and NAD could differentially affect cortisol metabolism, which is a complex 10-enzymatic pathway process. HC might also affect blood and urine lactate levels through its effects on mitochondrial function. We aimed to differentiate between HC and NAD via a urinary cortisol metabolites and lactate panel. We prospectively recruited 7 healthy dogs and 18 dogs with HC, 15 with congestive heart failure (CHF), and 9 with NAD. We analyzed urine by gas chromatography–mass spectrometry and liquid chromatography–mass spectrometry. We normalized urinary lactate and cortisol metabolites to urine creatinine concentration, and then compared groups using a linear-mixed model and principal component (PC) analysis. A machine-learning classification algorithm generated a decision tree (DT) model for predicting HC. The least-squares means of normalized urinary 6β-hydroxycortisol and PC1 of the HC and CHF groups were higher than those of the healthy and NAD groups (p = 0.05). Creatinine-normalized urinary 6β-hydroxycortisol had better sensitivity (Se, 0.78; 95% CI: 0.55–0.91), specificity (Sp, 0.89; 95% CI: 0.57–0.99), and a likelihood ratio (LR; 7), than the Se (0.72; 95% CI: 0.49–0.88), Sp (0.89; 95% CI: 0.57–0.99), and LR (6.5) of PC1 for distinguishing HC from NAD. Lactate and dihydrocortisone had the highest decreasing node-weighted impurity value and were considered the most important features in the DT model; dihydrocortisol had no role in determining whether a dog had HC.
COVID-19-Driven Improvements and Innovations in Pharmacy Education: A Scoping Review

The COVID-19 pandemic led to many colleges of pharmacy having to make major changes relating to their infrastructure and delivery of their curriculum within a very short time frame, including the transition of many components to an online setting. This scoping review sought to summarize what is known about the impact of COVID-19 on pharmacy education and the effectiveness of adaptation strategies which were put in place. PubMed, Web of Science, OVID Medline, and MedEdPortal were searched to identify pharmacy education-related articles published since the beginning of the COVID-19 pandemic. For article inclusion, the following criteria had to be met: described original research, related directly to PharmD or PharmBS education, related to the impact of COVID-19 on pharmacy education, and was available in English. Out of a total of 813 articles, 50 primary research articles were selected for inclusion. Our review of these identified four domains relating to the impact of COVID-19 on pharmacy education and/or effectiveness of adaptation strategies: (1) lab-based courses and activities (including interprofessional education activities), (2) experiential education, (3) didactic education, and (4) student well-being. The key research findings are summarized and discussed. While the COVID-19 pandemic has clearly brought many challenges to pharmacy education, it has also led to key improvements and innovations.
KW-sections for exceptional type Vinberg's $\theta$-groups

Let $k$ be an algebraically closed field of characteristic not equal to 2 or 3, let $G$ be an almost simple algebraic group of type $F_4$, $G_2$ or $D_4$ and let $\theta$ be an automorphism of $G$ of finite order, coprime to the characteristic. In this paper we consider the $\theta$-group (in the sense of Vinberg) associated to these choices; we classify the positive rank automorphisms and give their Kac diagrams and we describe the little Weyl group in each case. As a result we show that all such $\theta$-groups have KW-sections, confirming a conjecture of Popov in these cases.
Statistics of thermal to shot noise crossover in chaotic cavities

Recently formulated integrable theory of quantum transport (Osipov and Kanzieper, 2008 Phys. Rev. Lett. 101 176804) is extended to describe sample-to-sample fluctuations of the noise power in chaotic cavities with broken time-reversal symmetry. Concentrating on the universal transport regime, we determine dependence of the noise power cumulants on the temperature, applied bias voltage and the number of propagating modes in the leads. Intrinsic connection between statistics of thermal to shot noise crossover and statistics of Landauer conductance is revealed and briefly discussed.
Non-Commutative Geometry, Categories and Quantum Physics

After an introduction to some basic issues in non-commutative geometry (Gel'fand duality, spectral triples), we present a "panoramic view" of the status of our current research program on the use of categorical methods in the setting of A.Connes' non-commutative geometry: morphisms/categories of spectral triples, categorification of Gel'fand duality. We conclude with a summary of the expected applications of "categorical non-commutative geometry" to structural questions in relativistic quantum physics: (hyper)covariance, quantum space-time, (algebraic) quantum gravity.
Smartening up Participatory Cultural Tourism Planning in Historical City Centers

ABSTRACT Radical developments in information and communication technologies (ICT) have widely affected urban sectors including cultural tourism. Furthermore, ICT have influenced modern spatial planning practices and have contributed to the advancement of interactive Web-GIS technologies that create new challenges and opportunities for spatial data management and potential for stakeholders’ engagement in planning. The convergence of culture, tourism, and ICT; developments in ICT-enabled planning; and interactive Web-GIS technologies have offered new opportunities for collaborative cultural planning. In such a context, the scope of this paper is to combine ICT-enabled, planning-related principles, cultural mapping, crowdsourcing, data management tools, and spatial models in an integrated framework, serving heritage-led development objectives. Focus is placed on broadening cultural planning perspectives through strengthening stakeholders’ engagement in the process of sustainably managing local assets and designing cultural tourism products that spread benefits to the local economy and reboot development processes. The study attempts to illustrate the added value of mature ICT-enabled approaches, tools, and technologies in the cultural tourism sector, reflecting the increasing smart tourism interest and applications that flourish in a smart city context.
Pixel-Reasoning-Based Robotics Fine Grasping for Novel Objects with Deep EDINet Structure

Robotics grasp detection has mostly used the extraction of candidate grasping rectangles; those discrete sampling methods are time-consuming and may ignore the potential best grasp synthesis. This paper proposes a new pixel-level grasping detection method on RGB-D images. Firstly, a fine grasping representation is introduced to generate the gripper configurations of parallel-jaw, which can effectively resolve the gripper approaching conflicts and improve the applicability to unknown objects in cluttered scenarios. Besides, the adaptive grasping width is used to adaptively represent the grasping attribute, which is fine for objects. Then, the encoder–decoder–inception convolution neural network (EDINet) is proposed to predict the fine grasping configuration. In our findings, EDINet uses encoder, decoder, and inception modules to improve the speed and robustness of pixel-level grasping detection. The proposed EDINet structure was evaluated on the Cornell and Jacquard dataset; our method achieves 98.9% and 96.1% test accuracy, respectively. Finally, we carried out the grasping experiment on the unknown objects, and the results show that the average success rate of our network model is 97.2% in a single object scene and 93.7% in a cluttered scene, which out-performs the state-of-the-art algorithms. In addition, EDINet completes a grasp detection pipeline within only 25 ms.
EWSR1::YY1 fusion positive peritoneal epithelioid mesothelioma harbors mesothelioma epigenetic signature: Report of 3 cases in support of an emerging entity

Mesothelioma is a rare, aggressive malignant neoplasm of mesothelial origin. A small subset of peritoneal mesothelioma is driven by recurrent gene fusions, mostly EWSR1/FUS::ATF1 fusions, with predilection for young adults. To date, only two cases of mesothelioma harboring EWSR1::YY1 fusions have been described. We present three additional cases of EWSR1::YY1‐fused peritoneal mesotheliomas, two localized and one diffuse, all occurring in the peritoneum of middle‐aged adults (2 females and 1 male), and discovered incidentally by imaging or during surgery performed for unrelated reasons. None presented with symptoms or had a known history of asbestos exposure. All three cases were cellular epithelioid neoplasms with heterogeneous architectural patterns comprising mostly solid nests and sheets with variably papillary and trabecular areas against collagenous stroma. Cytologically, the cells were monomorphic, polygonal, epithelioid cells with dense eosinophilic cytoplasm and centrally located nuclei. Overt mitotic activity or tumor necrosis was absent. All cases showed strong diffuse immunoreactivity for pancytokeratin, CK7, and nuclear WT1, patchy to negative calretinin, retained BAP1 expression, and were negative for Ber‐EP4 and MOC31. RNA‐sequencing confirmed in‐frame gene fusion transcripts involving EWSR1 exon 7/8 and YY1 exon 2/3. By unsupervised clustering analysis, the methylation profiles of EWSR1::YY1‐fused mesotheliomas clustered similarly with EWSR1/FUS::ATF1‐fused mesotheliomas and conventional mesotheliomas, suggesting a mesothelioma epigenetic signature. All three patients underwent surgical resection or cytoreductive surgery of the masses. On follow‐up imaging, no recurrence or progression of disease was identified. Our findings suggest that EWSR1::YY1‐fusion defines a small subset of peritoneal epithelioid mesothelioma in middle‐aged adults without history of asbestos exposure.
Assessment of Requisite Knowledge and its Impact on the Academic Performance of Political Science Graduates of University of Abuja

The objective of the study is to make an assessment of Requisite Knowledge and its Impact on the Academic Performance of Political Science Graduates of the The University of Abuja. The main objective of the study is to examine whether academic performance of political science graduates of The University of Abuja is premised on the requisite knowledge in English Language, Government, Economics and Mathematics. Sample of 400 Political Science graduates between 2014 and 2020 were drawn through a convenient sampling procedure from the population of 1010 graduates. Secondary data were collected from the database of the Political Science Department of the University. A multivariate linear regression model using ordinary least-square (OLS) was used to analyze the data collected. Findings reveal that requisite knowledge of English Language and Government significantly influence academic performance positively at 1% level while, Mathematics is significant at 10%. However, requisite knowledge in mathematics was found to be insignificant. The study recommends that JAMB, NUC and university management should continue to concentrate more on requisite knowledge in English Language, Government and Economics as requisites knowledge for admission into political science in the The University of Abuja for an enhanced optimal performance.
Predicting CT-Based Coronary Artery Disease Using Vascular Biomarkers Derived from Fundus Photographs with a Graph Convolutional Neural Network

The study population contains 145 patients who were prospectively recruited for coronary CT angiography (CCTA) and fundoscopy. This study first examined the association between retinal vascular changes and the Coronary Artery Disease Reporting and Data System (CAD-RADS) as assessed on CCTA. Then, we developed a graph neural network (GNN) model for predicting the CAD-RADS as a proxy for coronary artery disease. The CCTA scans were stratified by CAD-RADS scores by expert readers, and the vascular biomarkers were extracted from their fundus images. Association analyses of CAD-RADS scores were performed with patient characteristics, retinal diseases, and quantitative vascular biomarkers. Finally, a GNN model was constructed for the task of predicting the CAD-RADS score compared to traditional machine learning (ML) models. The experimental results showed that a few retinal vascular biomarkers were significantly associated with adverse CAD-RADS scores, which were mainly pertaining to arterial width, arterial angle, venous angle, and fractal dimensions. Additionally, the GNN model achieved a sensitivity, specificity, accuracy and area under the curve of 0.711, 0.697, 0.704 and 0.739, respectively. This performance outperformed the same evaluation metrics obtained from the traditional ML models (p < 0.05). The data suggested that retinal vasculature could be a potential biomarker for atherosclerosis in the coronary artery and that the GNN model could be utilized for accurate prediction.
Optimal paths on the space-time SINR random graph

We analyze a class of signal-to-interference-and-noise-ratio (SINR) random graphs. These random graphs arise in the modeling packet transmissions in wireless networks. In contrast to previous studies on SINR graphs, we consider both a space and a time dimension. The spatial aspect originates from the random locations of the network nodes in the Euclidean plane. The time aspect stems from the random transmission policy followed by each network node and from the time variations of the wireless channel characteristics. The combination of these random space and time aspects leads to fluctuations of the SINR experienced by the wireless channels, which in turn determine the progression of packets in space and time in such a network. In this paper we study optimal paths in such wireless networks in terms of first passage percolation on this random graph. We establish both ‘positive’ and ‘negative’ results on the associated time constant. The latter determines the asymptotics of the minimum delay required by a packet to progress from a source node to a destination node when the Euclidean distance between the two tends to ∞. The main negative result states that this time constant is infinite on the random graph associated with a Poisson point process under natural assumptions on the wireless channels. The main positive result states that, when adding a periodic node infrastructure of arbitrarily small intensity to the Poisson point process, the time constant is positive and finite.
Morse Theory of Attractors via Lyapunov Functions

This paper is concerned with the Morse theory of attractors for semiflows on complete metric spaces. First, we construct global Morse-Lyapunov functions for Morse decompositions of attractors. Then we extend some well known deformation results in the critical-point theory to Morse-Lyapunov functions which are only continuous. Based on these works, we finally introduce the concept of critical groups for Morse sets and establish Morse inequalities and Morse equations for attractors.
Development of Islamic Education Learning Tools Based on E-Learning to Enhance Students Digital Literacy

The purpose of this research is to develop islamic education learning tools based on e-learning that valid, practical and effective to use. The type of research is research and development by adopting the Thiagarajan development model, which consists of 4 stages, namely defining, designing, developing and disseminating. The research instruments used in this study were validation sheets and learning outcomes tests using the Jamboard application. Analysis of the data used in this study (1) By conducting a feasibility analysis on the e-learning learning module, Student Activity Sheet (LKM) and student learning outcomes tests. Based on the results of the validation, the overall learning tools in the form of e-learning modules for Islamic religious subjects, LKM and learning outcomes tests are generally declared valid. The details of the module validation scores are generally very valid (M = 3.62), the LKM is generally declared valid (3.31) and the learning outcomes test is declared to be (M = 3.43). (2) conducting trials on elearning and LKM learning modules. The learning tools developed can be said to be valid because the development process is based on a strong theoretical rationale and has internal consistency so that the teaching materials have high reliability and consistency, so that it can be used to enhance students’s digital literacy. Article History Received: 20-11-2021 Revised: 08-04-2022 Accepted: 24-05-2022 Published: 04-06-2022
Geopolitics, Paralysis and Health Policy: On the Implications of the Dayton Peace Accords for Bosnia & Herzegovina’s Transplantation System

ABSTRACT More than 25 years after Dayton Peace Accords (DPA), the shadows of the Yugoslav and of the subsequent construction of independent states based on ethnic division still looms over Bosnia & Hercegovina (BiH), its population, and the everyday life of people. The construction of its two major political entities – the Federation of Bosnia & Hercegovina (FBiH) and the Republika Srpska (RS) – is reflected in the health care system where it unfolds highly detrimental effects. Here, we can witness the severe impact on BiH’s ability to establish an effective system for organ donation and transplantation. Based on a series of 26 interviews with patients, patients’ organisations, clinicians and politicians BiH and its neighbours, the article identifies obstacles in clinical practices, post-Dayton bureaucracy as well as mistrust and corruption as major themes articulated by our respondents, ultimately imprisoning them in a Post-Dayton paralysis. Desperation amid the deadlocked structural conditions and contemplating alternatives ways of getting access to transplantation seem logical outcomes of a system widely regarded as deficient. This exemplifies the prosaic legacies of wars and the fragile state of BiH’s politico-administrative system.
Improvement of human myeloid and natural killer cell development in humanized mice via hydrodynamic injection of transposon plasmids containing multiple human cytokine genes

Humanized mice reconstituted with a functional human immune system (HIS) are instrumental in studying human immunity and immune disorders in vivo. The poor or lack of cross‐reactivity between mouse cytokines and human cells limits the development and/or function of human immune cell subsets including human myeloid, natural killer and B cells. Here we explored the potential to achieve long‐term production of human cytokines in immunodeficient mice using a transposon‐plasmid–based hydrodynamic injection approach. We constructed a transposon‐plasmid carrying five human cytokine coding sequences (named PB‐5F), and observed that four of the cytokines (granulocyte–macrophage colony‐stimulating factor, interleukin (IL)‐15, IL‐6 and IL‐3) were detectable in sera and three (granulocyte–macrophage colony‐stimulating factor, IL‐15 and IL‐6) showed long‐term production in immunodeficient mice that received a single hydrodynamic injection of PB‐5F plus the transposase plasmid (Super PB). Furthermore, a single injection of PB‐5F/Super PB markedly enhanced the reconstitution of human myeloid cells and natural killer cells, and promoted human B‐cell maturation in HIS mice. Taken together, our data revealed that hydrodynamic injection of the PB‐5F/Super PB vectors may serve as a convenient and efficacious means to promote human immune function in HIS mice.
Transition Indices of Sediment-Transport Modes on a Debris Flow Resulting from Changing Streambed Gradients

We conducted experiments using an experimental flume with two variable streambed gradients in the upstream and downstream parts with various debris flows, composition sizes, and supply flow rates. We investigated the transition processes of sediment transport modes along the longitudinal distances from the gradient change point using the transition mode indices, ICs¯x, Ih¯x, and IU¯x; these indices were calculated based on measurements of sediment transport concentrations, flow depths, and gravel migration velocities in the debris flow’s front in the downstream part. Using these indices, we postulated that after the debris flow passed the gradient change point, the transition of the sediment transport modes progressed by changing the measured parameters to those in the steady-state condition on the gradient of the downstream parts. In addition, these indices suggested that the gravel migration velocities in the flow front interior changed most rapidly after passing the gradient change point, and that flow depths tended to change most slowly. Finally, the indices suggested that as the debris flow material became finer and the supplied flow rates became larger, the longitudinal transition sections tended to be longer because the momentum needed to transport the material was less than the total debris flow momentum.
A Derivative-Free Approach to Total Variation Regularization

The goal of this paper is to present a novel approach for total variation regularization and Sobolev minimization, which are prominent tools for variational imaging. Thereby we use derivative free characterizations of the total variation semi-norm and Sobolev semi-norms of functions recently derived by Bourgain, Br\'ezis, Mironescu and D\'avila. Their analysis is to approximate the semi-norms of a function by singular integral operators. With this characterization we derive a series of novel regularization methods for total variation minimization which have as a novel feature a non-local double integral regularization term.