Miracle-dz/UniFAR-FTUs huggingface dataset:
Radio Galaxy Zoo: Giant Radio Galaxy Classification using Multi-Domain Deep Learning

In this work we explore the potential of multi-domain multi-branch convolutional neural networks (CNNs) for identifying comparatively rare giant radio galaxies from large volumes of survey data, such as those expected for new generation radio telescopes like the SKA and its precursors. The approach presented here allows models to learn jointly from multiple survey inputs, in this case NVSS and FIRST, as well as incorporating numerical redshift information. We find that the inclusion of multi-resolution survey data results in correction of 39% of the misclassifications seen from equivalent single domain networks for the classification problem considered in this work. We also show that the inclusion of redshift information can moderately improve the classification of giant radio galaxies.
STC-mix: Space, Time, Channel mixing for Self-supervised Video Representation

Contrastive representation learning of videos highly relies on the availability of millions of unlabelled videos. This is practical for videos available on web but acquiring such large scale of videos for real-world applications is very expensive and laborious. Therefore, in this paper we focus on designing video augmentation for self-supervised learning, we ﬁrst analyze the best strategy to mix videos to create a new augmented video sample. Then, the question remains, can we make use of the other modalities in videos for data mixing? To this end, we propose Cross-Modal Manifold Cutmix (CMMC) that inserts a video tesseract into another video tesseract in the feature space across two different modalities. We ﬁnd that our video mixing strategy STC-mix , i.e. preliminary mixing of videos followed by CMMC across different modalities in a video, improves the quality of learned video representations. We conduct thorough experiments for two downstream tasks: action recognition and video retrieval on two small scale video datasets UCF101, and HMDB51. We also demonstrate the effectiveness of our STC-mix on NTU dataset where domain knowledge is limited. We show that the performance of our STC-mix on both the downstream tasks is on par with the other self-supervised approaches while requiring less training data.
Modeling Demand Flexibility of RES-based Virtual Power Plants

In this paper, an approach to evaluate the benefits of demand flexibility for Virtual Power Plants (VPPs) is presented. The flexible demands chosen in this study are part of a renewable energy source-based VPP that participates in Day-Ahead Market (DAM) and Intra-Day Market (IDM) and has dispatchable and non-dispatchable assets. A demand model with bi-level flexibility is proposed: the first level is associated with DAM, whereas the second level is related to IDM sessions. Simulations are carried out considering a 12-node network to ascertain the eventual impacts of modeling demand flexibility on VPP operation. The market structure considered in the case study resembles the different trading floors in the Spanish electricity market. Results obtained show that the proposed demand flexibility scheme increases the overall profit of the VPP, as well as the revenues of the demand owners without disrupting the consumer's comfort.
Distributed Containment Reference Signal for Nonholonomic Planar Vehicles

Cooperative of multiple nonholonomic vehicles can be converted into tracking problems of a single-vehicle. The reference trajectory design within distributed features for each vehicle in the group is addressed in this note. The motivation is that nonholonomic vehicles cannot achieve asymptotical stabilization of non-feasible reference signals, and modifications about the virtual reference trajectory design are needed. Reduced-order design and time-varying technique, and some simple geometry tricks are applied to derive the dynamic reference trajectory.
A theory of optimal convex regularization for low-dimensional recovery

We consider the problem of recovering elements of a low-dimensional model from under-determined linear measurements. To perform recovery, we consider the minimization of a convex regularizer subject to a data fit constraint. Given a model, we ask ourselves what is the ``best'' convex regularizer to perform its recovery. To answer this question, we define an optimal regularizer as a function that maximizes a compliance measure with respect to the model. We introduce and study several notions of compliance. We give analytical expressions for compliance measures based on the best-known recovery guarantees with the restricted isometry property. These expressions permit to show the optimality of the ${\ell}$1-norm for sparse recovery and of the nuclear norm for low-rank matrix recovery for these compliance measures. We also investigate the construction of an optimal convex regularizer using the examples of sparsity in levels and of sparse plus low-rank models.
xFraud: Explainable Fraud Transaction Detection

At online retail platforms, it is crucial to actively detect the risks of transactions to improve customer experience and minimize financial loss. In this work, we propose xFraud, an explainable fraud transaction prediction framework which is mainly composed of a detector and an explainer. The xFraud detector can effectively and efficiently predict the legitimacy of incoming transactions. Specifically, it utilizes a heterogeneous graph neural network to learn expressive representations from the informative heterogeneously typed entities in the transaction logs. The explainer in xFraud can generate meaningful and human-understandable explanations from graphs to facilitate further processes in the business unit. In our experiments with xFraud on real transaction networks with up to 1.1 billion nodes and 3.7 billion edges, xFraud is able to outperform various baseline models in many evaluation metrics while remaining scalable in distributed settings. In addition, we show that xFraud explainer can generate reasonable explanations to significantly assist the business analysis via both quantitative and qualitative evaluations.
Galleria mellonella (Lepidoptera: Pyralidae) Hemocytes Release Extracellular Traps That Confer Protection Against Bacterial Infection in the Hemocoel

Abstract Extracellular traps (ETs) released from vertebrate and invertebrate immune cells consist of chromatin and toxic granule contents that are capable of immobilizing and killing microbes. This recently described innate immune response is not well documented in insects. The present study found that ETs were released by hemocytes of Galleria mellonella (Linnaeus) (Lepidoptera: Pyralidae) in vivo and ex vivo after bacterial stimulation. ET release (ETosis), hemolymph coagulation, and melanization likely contributed to the immobilization and killing of the bacteria. The injection of G. mellonella hemocyte deoxyribonucleic acid (DNA) in the presence of bacteria increased bacterial clearance rate and prolonged insect survival. Taken together, these results indicate the presence of insect hemocyte extracellular traps (IHETs) that protect the insect against microbial infection in the hemocoel and represent the first documentation of ETs in insects in vivo.
CONTROL FOR ROBOTIC MANIPULATORS WITH PROPORTIONAL INTEGRAL DERIVATIVE & COMPUTED TORQUE CONTROL

Inspite of long years of research, problem of manipulator path tracking control is the thrust area for researchers to work upon. Non-linear systems like manipulator are multi-input-multi-output, non-linear and time variant complex problem. A number of different approaches presently followed for the control of manipulator vary from classical PID (Proportional Integral Derivative) to CTC (Computed Torque Control) control techniques. This paper presents design and implementation of PID and CTC controller for robotic manipulator. Comparative study of simulated results of conventional controllers, like PID and CTC are also shown. Tracking performance and error comparison graphs are presented to show the performance of the proposed controllers.
The Added Value of Vessel Wall MRI in the Detection of Intraluminal Thrombus in Patients Suspected of Craniocervical Artery Dissection

Patients with craniocervical artery dissection (CCAD) have a high short-term risk of ischemic stroke, which is frequently associated with thromboembolism. Previous studies have demonstrated the utility of three-dimensional vessel wall MR imaging (3D-VWMRI) in the diagnosis of dissection. Few have investigated the value of 3D-VWMRI in the detection of intraluminal thrombus. The purpose of the current study was to evaluate the added value of 3D-VWMRI for thrombus identification in patients suspected of CCAD. One hundred and four patients (mean age, 44.2 years ± 13.2) suspected of CCAD and scheduled for digital subtraction angiography (DSA) were prospectively enrolled in the study and underwent VWMRI examination. The diagnostic performance of 3D-VWMRI for CCAD was evaluated using receiver operating characteristic (ROC) analysis with the final diagnosis results as the reference. The presence/absence of intraluminal thrombus on 3D-VWMRI/DSA was independently determined. The sensitivity and specificity of 3D-VWMRI for intraluminal thrombus detection were assessed with DSA serving as the reference. The odds ratio (OR) was used to evaluate the correlation between thrombus presented on 3D-VWMRI/DSA and ischemic stroke. The 3D-VWMRI had high sensitivity (90.0%) and specificity (94.3%) in identifying arteries with CCAD. The area under the ROC curve was 0.96. With DSA as the reference, the sensitivity and accuracy of 3D-VWMRI for the detection of intraluminal thrombus were 97.4% and 79.0%, respectively. An intraluminal thrombus present on 3D-VWMRI was strongly associated with a territorial ischemic stroke (OR: 30.0; 95% confidence interval: 9.1-98.4; P < .001). In conclusion, 3D-VWMRI with a 3.0-T MR system had a high diagnostic performance for CCAD and offered added value for detecting intraluminal thrombus.
Pharmacology and Potential Implications of Nicotinamide Adenine Dinucleotide Precursors

Coenzyme I (nicotinamide adenine dinucleotide, NAD+/NADH) and coenzyme II (nicotinamide adenine dinucleotide phosphate, NADP+/NADPH) are involved in various biological processes in mammalian cells. NAD+ is synthesised through the de novo and salvage pathways, whereas coenzyme II cannot be synthesised de novo. NAD+ is a precursor of coenzyme II. Although NAD+ is synthesised in sufficient amounts under normal conditions, shortage in its supply due to over consumption and its decreased synthesis has been observed with increasing age and under certain disease conditions. Several studies have proved that in a wide range of tissues, such as liver, skin, muscle, pancreas, and fat, the level of NAD+ decreases with age. However, in the brain tissue, the level of NADH gradually increases and that of NAD+ decreases in aged people. The ratio of NAD+/NADH indicates the cellular redox state. A decrease in this ratio affects the cellular anaerobic glycolysis and oxidative phosphorylation functions, which reduces the ability of cells to produce ATP. Therefore, increasing the exogenous NAD+ supply under certain disease conditions or in elderly people may be beneficial. Precursors of NAD+ have been extensively explored and have been reported to effectively increase NAD+ levels and possess a broad range of functions. In this review article, we discuss the pharmacokinetics and pharmacodynamics of NAD+ precursors.
Unmet need for family planning and associated factors among currently married women of reproductive age in Bishoftu town, Eastern Ethiopia

Background Unmet family planning is one of the common causes for low contraceptive prevalence rates in developing countries, including Ethiopia. Rapid urbanization had profound effect on population health, however, little is known about the unmet need of family planning in settings where there was increased industrializations and internal migrations in Ethiopia. This study aims to determine the unmet need for family planning services among currently married women and identify factors associated with it in Bishoftu town, Eastern Ethiopia. Methods Community-based cross-sectional study was conducted from 1st January to 28th February, 2021 among 847 randomly sampled currently married women of the reproductive age group. Data were collected using semi structured interviewer administered questionnaire. Multivariate logistic regression was used to identify factors associated with the outcome variable and a 95% confidence interval was used to declare the presence of statistical significance associations. Results Eight hundred twenty-eight women were participated in the study. The prevalence of unmet need for family planning among currently married women was 26% [95% CI: 23,29]. Maternal age [AOR, 3.00, 95% CI:1.51–5.95], educational status [AOR, 2.49, 95% CI:1.22–5.07], occupational status of self-employee [AOR, 1.98, 95% CI:1.15–3.39] and housewife [AOR, 1.78, 95% CI:1.02–3.12], being visited by health care provider in the last 12 months [AOR, 1.81, 95% CI: 1.26–2.60] and desired number of children less than two [AOR, 1.53, 95% CI:1.01–2.30] were significantly associated with unmet need for family planning. Conclusions Unmet need for family planning was higher in the study area compared with the United Nations sphere standard of unmet need for family planning and the national average, and slightly lower than the regional average. Socio-demographic, economic, and health institution factors were determinants of the unmet need for family planning in the study area. Therefore, health education and behaviour change communication related to family planning services should be strengthened and access to family planning services should be improved.
The impact of cardiac loading on a novel metric of left ventricular diastolic function in healthy middle‐aged adults: Systolic–diastolic coupling

Left ventricular (LV) restoring forces are primed by ventricular deformation during systole and contribute to cardiac relaxation and early diastolic suction. Systolic–diastolic coupling, the relationship between systolic contraction and diastolic recoil, is a novel marker of restoring forces, but the effect of left atrial pressure (LAP) is unknown. We tested preliminary methods of systolic–diastolic coupling comparing mitral annular velocities versus excursion distances and hypothesized a recoil/contraction distance ratio would remain unaffected across varying LAP, providing a surrogate for quantifying LV restoring forces.
Associations of the Dietary Inflammatory Index with total adiposity and ectopic fat through the gut microbiota, lipopolysaccharides, and C-reactive protein in the Multiethnic Cohort-Adiposity Phenotype Study.

Background Mechanisms linking a pro-inflammatory diet to obesity remain under investigation. The ability of diet to influence the gut microbiome (GM) in creating chronic low-grade systemic inflammation provides a plausible connection to adiposity. METHODS In the cross-sectional Multiethnic Cohort Adiposity Phenotype Study (812 men, 843 women, 60 to 77 years) we tested whether associations between the energy-adjusted Dietary Inflammatory Index (E-DIITM) score and total adiposity, visceral adipose tissue (VAT), and liver fat (% volume) function through the GM, lipopolysaccharides (LPS), and high-sensitivity C-reactive protein (hs-CRP). Dual energy X-ray absorptiometry (DXA)-derived total fat mass, MRI-measured VAT, and MRI-based liver fat were measured. Participants provided stool and fasting blood samples and completed a food frequency questionnaire (FFQ). Stool bacterial DNA was amplified and the 16S rRNA gene was sequenced at the V1-V3 region. E-DII score was computed from FFQ data, with a higher E-DII representing a more pro-inflammatory diet. The associations between E-DII score, GM (10 phyla, 28 genera, alpha diversity), and adiposity phenotypes were examined using linear regression and mediation analyses, adjusting for confounders. RESULTS There were positive total effects (c) between E-DII and total fat mass (c = 0.68; 95% CI = 0.47, 0.90), VAT (c = 4.61; 95% CI = 2.95, 6.27), and liver fat (c = 0.40; 95% CI = 0.27, 0.53). The association between E-DII score and total fat mass was mediated by LPS, Flavonifractor, [Ruminococcus] gnavus group, and Tyzzerella. The association between E-DII score and ectopic fat occurred indirectly through Fusobacteria, Christensenellaceae R-7 group, Coprococcus 2, Escherichia- Shigella, [Eubacterium] xylanophilum group, Flavonifractor, Lachnoclostridium, [Ruminococcus] gnavus group, Tyzzerella, [Ruminococcus] gnavus group (VAT only), and alpha diversity (liver fat only). There was no significant association between E-DII score and adiposity phenotype through hs-CRP. CONCLUSION Associations found between E-DII and adiposity phenotypes occurred through the GM and LPS.
A Literature Review on the Efficacy and Related Neural Effects of Pharmacological and Psychosocial Treatments in Individuals With Internet Gaming Disorder

Objective Internet gaming disorder (IGD) has attracted considerable attention as a serious mental and public health issue worldwide. Currently, there are no established treatment guidelines for IGD. Herein, we review the latest findings on the efficacy and related neural effects of pharmacological and psychosocial treatments for individuals with IGD. Methods A database search of relevant studies published between 2007 and 2020 was conducted using PubMed and Google Scholar. Twenty-seven studies were reviewed for current evidence related to the efficacy and neural effects of pharmacological and psychosocial IGD treatments. Results Pharmacological studies suggest that bupropion may play a significant role in IGD. Additionally, nuclear imaging studies on IGD have demonstrated functional impairment of the dopamine system, providing a neurobiological basis for the efficacy of dopamine-enhancing drugs. Among the various psychosocial interventions, current evidence suggests that cognitive behavioral therapy may be an effective intervention for IGD. Cognitive behavioral therapy and bupropion were found to influence resting-state functional connectivity within the cortico-subcortical circuit and default mode network, suggesting a possible neural mechanism. Innovative approaches, including virtual reality treatment, residential camps, voluntary abstinence, and transcranial direct current stimulation, have shown promising results. However, methodological limitations, such as the absence of proper controls, small sample sizes, short duration, inconsistency of inclusion criteria across studies, and self-report measures of outcome, hamper conclusions regarding the efficacy of treatments. Conclusion Ongoing basic research and clinical trials overcoming these limitations could add to the existing knowledge on IGD and contribute to the development of evidence-based treatments.
Valoración de contratos a plazo en mercados eléctricos: Aplicación al mercado ecuatoriano

Los mercados de energia electrica se caracterizan por la extremada volatilidad del precio spot. La incertidumbre asociada al precio es una fuente de riesgo tanto para los agentes vendedores (companias de generacion) como para los agentes compradores. Por este motivo, se hace necesario desarrollar herramientas y metodologias de analisis, valoracion y gestion del riesgo asociado al negocio de generacion. En este documento se propone, formula y desarrolla un procedimiento para la valoracion de contratos mayoristas de electricidad a largo plazo con el objetivo de lograr un adecuado equilibrio entre riesgo y rentabilidad en el contexto de las empresas de generacion que operan en el mercado electrico ecuatoriano.
Clinical Decision Support for Laboratory Testing.

BACKGROUND As technology enables new and increasingly complex laboratory tests, test utilization presents a growing challenge for healthcare systems. Clinical decision support (CDS) refers to digital tools that present providers with clinically relevant information and recommendations, which have been shown to improve test utilization. Nevertheless, individual CDS applications often fail, and implementation remains challenging. CONTENT We review common classes of CDS tools grounded in examples from the literature as well as our own institutional experience. In addition, we present a practical framework and specific recommendations for effective CDS implementation. SUMMARY CDS encompasses a rich set of tools that have the potential to drive significant improvements in laboratory testing, especially with respect to test utilization. Deploying CDS effectively requires thoughtful design and careful maintenance, and structured processes focused on quality improvement and change management play an important role in achieving these goals.
A Beamforming Network For Multibeam Antenna Arrays Based On Coherent Radiating Periodic Structures

In this work is introduced a practical application for a CORPS based BFN in the field of multibeam systems. An analytical study is also presented and a proof of Concept is built in order to corroborate the CORPS-BFN behaviour and its performance in a multibeam antenna application. (4 pages)
Context-aware business processes modelling: Concepts, issues and framework

Recent research activities on the design of business processes were driven by flexibility. Process flexibility can be achieved through the ability to trigger dynamic changes in the core of business process components in a timely manner and in response to business environment evolution. The drivers for business process flexibility can be found in the “Context” of a process which may include among others time, location, weather, legislation, and culture. Context-Aware Business Process Modelling extends traditional business process models with contextual variables that trigger a dynamic behavior under continuous change. However, as yet, most of the research work in this area has focused on some specific contextual information to model some varying parts such as business rules and goals. Little attention has given to the design and development of a general framework for context-aware business process modelling. In this paper, major business process components were extracted from the main existent business process design formalisms, amplified by contextual information, and integrated into a more a general framework. A case study of a well known European Logistics Enterprise is used to illustrate how contextual information should be integrated within existent business process modeling approaches.
Design and Test of a Self-Oscillating Driving ASIC for a Low-Q Gyroscope Based on PI Controller

In this work, closed-loop self-oscillating driving circuits for gyroscopes based on DC PI controller are analyzed in theory. The condition for oscillation is achieved by solving electrical differential equation, and the effects of key factors on magnitude stability are discussed. Further, an ASIC based on PI controller is designed, which is verified by simulation. The test results of manufactured chip correspond with the theoretical analysis, showing that this ASIC is capable of driving low-Q gyroscopes at normal temperate and pressure. This theory for analysis and the designed chip contribute to guide the design of closed-loop driving for gyroscopes, also improving stability for oscillating circuits.
Temperature-compensated thermoplastic high dielectric-constant microwave laminates

High dielectric-constant materials are increasingly needed in microwave circuit miniaturization for outdoor and indoor wireless applications. In this paper, we introduce temperature-stable high dielectric-constant thermoplastic polymer compositions and copper-laminated sheets made out of them for microwave circuits. The compositions are made by mixing suitable ceramics and polymers. The design, fabrication, and properties of these compositions are discussed. The effect of temperature on the resonance frequency of a patch antenna made out of the copper-laminated high dielectric-constant composite sheets is also discussed.