Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulating galactic winds with the NIRVANA grid code

5 1 Preface/Introduction 7 1.1 Observations of galactic winds . 7 1.2 Theoretical work on galactic winds . 10 1.3 Aim of this work . 13 1.4 Units and constants . 14 2 Theory 15 2.1 Disc dynamics and external potentials . 15 2.1.1 Gravitational instability of rotating systems . 16 2.1.2 Jeans instability . 20 2.1.3 Rotational velocity . 23 2.1.4 Dark matter halo models . 28 2.2 Fluid mechanics . 30 2.2.1 Basic equations . 30 2.2.2 Interstellar shocks . 34 2.2. 3 The drivers of interstellar shocks . 39 3 Methods 45 3.1 Numerical hydrodynamics . 45
Assessment of the potential establishment of Lyme endemic cycles in Mexico

ABSTRACT: Although Lyme disease is currently classified as exotic in Mexico, recent studies have suggested that it might be endemic there. We assessed the potential risk for the establishment of Borrelia burgdorferi transmission in Mexico. To identify the potential routes of B. burgdorferi spread, Complex Inference Networks were used initially to identify potential vector-host interactions between hard ticks (Ixodes) and migratory birds in the U.S., and a model for predicting the most important potential bird hosts of hard ticks was then obtained. By using network metrics, keystone-vectors were identified as those species with highest connectivity within and between network communities and had the potential to keep the pathogen circulating with many birds and to be dispersed to several regions. The climatic profile where these interactions occur in the U.S. was characterized and a geographic model for each keystone-vector was built. The accuracy of these models to predict areas where hard ticks have been reported positive for B. burgdorferi allows one to identify areas of greater risk of Lyme disease emergence. These hard tick-bird interactions and their climatic profile were mapped into the winter ranges of birds in Mexico. Thus, those regions in Mexico with the highest potential for becoming endemic areas of Lyme disease through the arrival of hard ticks and birds infected by B. burgdorferi were identified. These areas are candidates for future surveillance programs.
Diversity and distribution of larval habitats of mosquitoes (Diptera: Culicidae) in northern Spain: from urban to natural areas

ABSTRACT: Studies of the biodiversity of mosquito larval habitats are important for vector-borne disease control programs and help to improve vector distribution maps. This study was designed to investigate the geographical distribution of mosquito species and their larval habitats in urban, rural, and natural areas in northern Spain. Pre-imaginal stages were collected over two sampling periods (spring and summer) in 2019. In the laboratory, immature specimens were reared to the adult stage for species identification by morphological taxonomy and/or molecular methods. In total, 2,182 specimens belonging to 13 different native mosquito species of five genera were collected from 135 sampling points of which 59.2% harbored larvae. Culex pipiens s.l. was the most abundant species (45.1%), followed by Culex torrentium (12.3%), Anopheles maculipennis s.l. (10.2%), Culex hortensis (9.5%), and nine other species with lower frequencies that accounted for less than 25%. By molecular identification, An. maculipennis s.s. was identified as the only species within the An. maculipennis species complex and Cx. pipiens pipiens as the predominant subspecies of the Cx. pipiens species complex. Margins in large sunlit water bodies were the most suitable sites for An. maculipennis s.l. , whereas Cx. pipiens s.l. was present in both natural and artificial habitats. The larval site index, species richness, and relative abundance of the mosquitoes were determined based on the characteristics of the sites where they were collected. The public health importance and ecology of some identified mosquitoes is also discussed.
Potential geographic distribution of Ixodes cookei, the vector of Powassan virus

ABSTRACT: Ixodes cookei Packard, the groundhog tick or woodchuck tick, is the main known vector of Powassan virus (POWV) disease in North America and an ectoparasite that infests diverse small- and mid-size mammals for blood meals to complete its life stages. Since I. cookei spends much of its life cycle off the host and needs hosts for a blood meal in order to pass to the next life stage, it is susceptible to changes in environmental conditions. We used a maximum-entropy approach to ecological niche modeling that incorporates detailed model-selection routes to link occurrence data to climatic variables to assess the potential geographic distribution of I. cookei under current and likely future climate conditions. Our models identified suitable areas in the eastern United States, from Tennessee and North Carolina north to southern Canada, including Nova Scotia, New Brunswick, eastern Newfoundland and Labrador, southern Quebec, and Ontario; suitable areas were also in western states, including Washington and Oregon and restricted areas of northern Idaho, northwestern Montana, and adjacent British Columbia, in Canada. This study produces the first maps of the potential geographic distribution of I. cookei. Documented POWV cases overlapped with suitable areas in the northeastern states; however, the presence of this disease in areas classified by our models as not suitable by our models but with POWV cases (Minnesota and North Dakota) requires more study.
University Crises in Africa: A Situational Crisis Communication Theory Case Study of Daystar University, Kenya

Abstract While disruption of learning has become a common, almost a permanent feature, of universities in Africa, crisis response strategies in these organisations remain understudied. This article reports on a case study which focused on Daystar University (DU) in Kenya that was plunged into a crisis leading to its closure when students boycotted lectures to protest poor infrastructure and fee increment. The study used Coombs Situational Crisis Communication Theory (SCCT) to analyse crisis response strategies utilised at DU. The study found that the reputational threat was severe and that the university identified with the victim cluster in its crisis response strategies to protect its positive reputational history. Specifically, the SCCT deny response strategies were applied in DU's initial communication utilising the corresponding scapegoat tactic. But later, deal response strategies were applied although ineffectively. Thus, the research recommends that in future, DU should broaden its crisis response strategies in order to effectively reach all constituencies and protect its reputational capital.
The Construction and Analysis of Music Influence Graph

A substantial number of audio files and articles regarding music appear online every day. However, research on the complex relationships between different musicians remains inadequate. In this paper, we make use of the context and content of music to analyze the influence of previously produced music on the latest original music. We construct an influence model, which included structural features of networks, to establish associations between a variety of musicians. Then, we apply this model to a case study containing a network of musicians, and investigate the scope of musical influences on a specific band. Finally, we build a matrix of high-level features to measure the similarities between different musicians and use it to distinguish various genres, thus demonstrating the effectiveness and application value of the model we construct.
Enhancing the Customer Experience by Mixed Reality in the Retail Industry

∗ Nowadays, customization by mixed reality to enhance the customer experience plays an important role in the retail industry. Customers can choose and customize products with their images and labels in a virtual reality environment. However, the existing asset creation pipelines are labor-intensive and time-consuming to display the images and labels (aka logos) on 3D product models, and cannot be easily customized by customers in real-time. In this paper, we thus propose a real-time 3D logo mapping framework for converting 3D logo mesh from a specified image and fitting it to the 3D product models. In the framework, Convolutional Neural Network (CNN) is adopted to reconstruct 3D logo/product models from their images. The detailed 3D information and the logo location provided by a customer are used to select the effective sampling points to mesh deformation. This method can preserve both the visual quality and details of 3D product models. Experimental results, carried out on various sizes of logos and types of products, show that our method can produce accurately and quickly customized logos on 3D product models.
Comparison of Supervised Learning Models for the Prediction of Coronary Artery Disease

Cardiovascular diseases and Coronary Artery Disease (CAD) are the leading causes of mortality among people of different ages and conditions. The use of different and not so invasive biomarkers to detect these types of diseases joined with Machine Learning techniques seems promising for early detection of these illnesses. In the present work, we have used the Sani Z-Alizadeh dataset, which comprises a set of different medical features extracted with not invasive methods and used with different machine learning models. The comparisons performed showed that the best results were using a complete set and a subset of features as input for the Random Forest and XGBoost algorithms. Considering the results obtained, we believe that using a complete set of features gives insights that the features should also be analyzed by considering the medical advances and findings of how these markers influence a CAD disease's presence.
Almost Linear Semantic XML Keyword Search

Many efforts have been deployed by the IR community to extend free-text query processing toward semi-structured XML search. Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. Yet, few of the existing approaches consider XML semantics, and the methods that process semantics generally rely on computationally expensive word sense disambiguation (WSD) techniques, or apply semantic analysis in one stage only: performing query relaxation/refinement over the bag of words retrieval model, to reduce processing time. In this paper, we describe the building blocks of a new approach for XML keyword search aiming to solve the limitations mentioned above. Our solution first transforms the XML document collection (offline) and the keyword query (on-the-fly) into meaningful semantic representations using context-based and global disambiguation methods, specially designed to allow almost linear computation efficiency. Consequently, the semantically augmented XML data tree is processed for structural node clustering, based on semantic query concepts (i.e., key-concepts), in order to identify and rank candidate answer sub-trees containing related occurrences of query key-concepts. Preliminary experiments highlight the quality and potential of our approach.
Defining interactions of WoT servients with causality relations

The communication between different IoT systems presents a series of challenges in the processing and analysis of the heterogeneous information managed by said systems. The W3C Web of Things (WoT) standard offers a common model to define those devices following the guidelines established by the Thing Description. One of the caveats of the WoT is that the Thing Description does not define behaviour, so there is no way to know if an interaction is the consequence of another one. Each IoT device is represented using a Thing Description as an individual entity by design. In this paper, we propose a mechanism to improve interoperability between devices, laying the foundations on how to establish a relation linking them. This relation is formed by two different entities: the "causes" and the "effects". These two entities are at the same time interactions affordances provided by the Thing Description schema of each thing involved. Cause-effect relations help to define how devices work with each other following an event communication strategy.
Glioma Image Segmentation Method on Fully Convolutional Neural Network

Aiming at the difference in the segmentation performance of the three segmentation target regions in the glioma image segmentation task based on the fully convolutional neural network, we propose a comprehensive evaluation method of neural network performance based on four evaluation indices. In addition, we analyze the performance and characteristics of neural network in the segmentation task of glioma, study the segmentation performance of neural network in the whole tumor (WT), tumor core (TC) and enhanced tumor (ET) regions, and propose a deep learning algorithm based on multiple networks in parallel. In this paper, the input image of the two-dimensional neural network is sliced, and the input of the three-dimensional neural network is processed in two ways: overlapping and non-overlapping, and in the image post-processing part, the three-dimensional image is reconstructed before the evaluation index is calculated. This article uses four evaluation indexes, which are Dice, Sensitivity, PPV, and Hausdorff, for the three segmentation target regions, and performs RSR* weight calculation, and finally performs a comprehensive evaluation. Experimental results show that Vnet has the best comprehensive segmentation performance, FCN-8s has the best segmentation performance in the TC area, Unet++ has the best segmentation performance in the ET area, and Vnet has the best segmentation performance in the WT area. Based on this, we propose a FUV multi-network parallel algorithm, combined with a reverse attention mechanism to improve the segmentation accuracy of the three segmentation target regions.
Determination of Stroke Order Relation in Chinese Character Writing by Robot NAO with Thinning Algorithm Based on Corner Detection and Depth Searching

There are a set of basic rules for stroke order in the traditional handwriting of Chinese characters, which may be listed as from left to right, from top to bottom, first inside then outside, and so on. Humanoid robot NAO is very famous in the world now, which has many sensors such as two cameras, infrared, IMU, bumper sensors and so forth. In this paper we explore how the humanoid robot NAO can write a Chinese character according to the traditional stroke order rules. As a matter of fact, the stroke order relation between any two strokes is very important in the whole stroke orders in order to lead a well writing. Therefore, the thinning algorithm is employed to propose an effective and useful method to determine the stroke order relation between any two strokes for Chinese character writing by robot NAO based on corner detection and depth-searching. Then the implementing algorithm is given for the determination of stroke order relation, and a series of experiments are carried out to validate its feasibility and effectiveness, the accuracy can achieve 90% so as to be a very satisfied result in the current stage.
Fabrication of lithium niobate fork grating by laser-writing-induced selective chemical etching

Abstract We propose and experimentally demonstrate a laser-writing-induced selective chemical etching (LWISCE) technique for effective micro-fabrication of lithium niobate (LN) crystal. Laser writing of LN crystal produces negative domains and domain walls. Also, it causes local lattice defects, in which the etching rates are significantly increased in comparison to the original LN crystal. In experiment, we use the LWISCE technique to fabricate various fork gratings in an X-cut LN crystal for the generation of vortex beams. In comparison to etching an untreated X-cut LN crystal, the etching rates of the laser-writing-induced boundaries and the central laser-irradiated areas are enhanced by a factor of 26 and 16, respectively. The width and depth of fork grating structure can be precisely controlled by laser writing parameters. Our method provides an efficient mask-free micro-fabrication technique for LN crystal, which can be readily applied to other ferroelectric crystals such as lithium tantalate, potassium titanyl phosphate and barium calcium titanate.
Ultrastructural and Functional Analysis of a Novel Extra-Axonemal Structure in Parasitic Trichomonads

Trichomonas vaginalis and Tritrichomonas foetus are extracellular flagellated parasites that inhabit humans and other mammals, respectively. In addition to motility, flagella act in a variety of biological processes in different cell types, and extra-axonemal structures (EASs) have been described as fibrillar structures that provide mechanical support and act as metabolic, homeostatic, and sensory platforms in many organisms. It has been assumed that T. vaginalis and T. foetus do not have EASs. However, here, we used complementary electron microscopy techniques to reveal the ultrastructure of EASs in both parasites. Such EASs are thin filaments (3–5 nm diameter) running longitudinally along the axonemes and surrounded by the flagellar membrane, forming prominent flagellar swellings. We observed that the formation of EAS increases after parasite adhesion on the host cells, fibronectin, and precationized surfaces. A high number of rosettes, clusters of intramembrane particles that have been proposed as sensorial structures, and microvesicles protruding from the membrane were observed in the EASs. Our observations demonstrate that T. vaginalis and T. foetus can connect to themselves by EASs present in flagella. The protein VPS32, a member of the ESCRT-III complex crucial for diverse membrane remodeling events, the pinching off and release of microvesicles, was found in the surface as well as in microvesicles protruding from EASs. Moreover, we demonstrated that the formation of EAS also increases in parasites overexpressing VPS32 and that T. vaginalis-VPS32 parasites showed greater motility in semisolid agar. These results provide valuable data about the role of the flagellar EASs in the cell-to-cell communication and pathogenesis of these extracellular parasites.
Agent-based Simulation of Cooperative Innovation

This paper introduces an agent-based simulation model representing the dynamic processes of cooperative R&D in the manufacturing sector of South Korea. Firmsi¯ behaviors were defined according to empirical findings on a dataset from the internationally standardized Korean Innovation Survey in 2005. Simulation algorithms and parameters were defined based on the determinants on firmsi¯ likelihood to participate in cooperation with other firms when conducting innovation activities. The calibration process was conducted to the point where artificially generated scenarios were equivalent to the one observed in the real world. The aim of this simulation game was to create a basic implementation that could be extended to test different policies strategies in order to observe sector responses (including cross-sector spillovers) when promoting cooperative innovation.
Tensor of Quantitative Equational Theories

We develop a theory for the commutative combination of quantitative effects, their tensor , given as a combination of quantitative equational theories that imposes mutual commutation of the operations from each theory. As such, it extends the sum of two theories, which is just their unrestrained combination. Tensors of theories arise in several contexts; in particular, in the semantics of programming languages, the monad transformer for global state is given by a tensor. We show that under certain assumptions on the quantitative theories the free monad that arises from the tensor of two theories is the categorical tensor of the free monads on the theories. As an application, we provide the first algebraic axiomatizations of labelled Markov processes and Markov decision processes. Apart from the intrinsic interest in the axiomatizations, it is pleasing they are obtained compositionally by means of the sum and tensor of simpler quantitative equational theories.
Pulsed measurements and modeling for electro-thermal effects

This paper presents a system and measurement methodology for generating a complete nonlinear model for bipolar junction transistors including static and dynamic thermal dependence. System configuration, measurement, and calibration issues am presented. The modeling process involves pulse mode DC and AC measurements from which isothermal measurements and subsequently isothermal parameters can be extracted. Using a combination of static and pulse mode measurements the device's dynamic temperature dependence can be explicitly determined and coupled back into the model via a self-consistent nonlinear electro-thermal model.
Physiotherapy results of a patient with critical illness polyneuropathy due to COVID-19: A case report

The aim of this study is to examine the results of physiotherapy in a patient with critical illness polyneuropathy (CIP) due to coronavirus disease 2019 (COVID-19). The 48-year-old male patient with CIP due to COVID-19 was enrolled in a physiotherapy program for 3 months with 5 sessions/week. Pain intensity, motor skills, daily living activities, fatigue level, cognitive status, and decubitus ulcer were evaluated with a visual analogue scale, the Medical Research Council-Sum Score, the Functional Independence Scale, the Fatigue Severity Scale, the Standardized Mini-Mental Test, and pressure wound staging, respectively. Positive improvements were achieved in functional level, fatigue, pain, and pressure sores with the physiotherapy program for this patient with CIP due to COVID-19. This report provides an idea about the effects of physiotherapy programs for COVID-19-related CIP to academics and clinicians working in this field.
Introduction – Forecasting global migration

ISSN 2223-5248 Joint Managing Editors: • Solon Ardittis (Eurasylum) • Frank Laczko (International Organization for Migration – IOM) Editorial Adviser: • Joanne van Selm (Eurasylum) Editorial Coordinator: • Valerie Hagger (International Organization for Migration – IOM) Editorial Assistants: • Laarni Alfaro (International Organization for Migration – IOM) • Anna Lyn Constantino (International Organization for Migration – IOM) Editorial Committee: • Aderanti Adepoju (Human Resources Development Centre, Lagos, Nigeria) • Jane Annear (Department of Home Affairs, Canberra) • Peter Bosch (European Commission, Brussels) • Howard Duncan (Metropolis, Ottawa, Canada) • Neli Esipova (Gallup World Poll, New York) • Araceli Azuara Ferreiro (Organization of American States – OAS, Washington, D.C.) • Marta Foresti (Overseas Development Institute – ODI, London) • Andrew Geddes (Migration Policy Centre – MPC, Florence) • Lukas Gehrke (International Centre for Migration Policy Development – ICMPD, Vienna) • Shahidul Haque (Ministry of Foreign Affairs, Government of the People’s Republic of Bangladesh) • Bela Hovy (UN Department of Economic and Social Affairs, New York) • Michelle Leighton (International Labour Office – ILO, Geneva) • Pietro Mona (Swiss Agency for Development and Cooperation, Federal Department of Foreign Affairs, Berne) • Dilip Ratha (World Bank, Washington, D.C.) • Hilmar Schneider (Institute for the Study of Labor – IZA, Bonn) • Nand Kishore Singh (Member of the Indian Parliament, New Delhi) • Stephanos Stavros (Council of Europe, Strasbourg) • Maia Welbourne (Citizenship and Immigration Canada – CIC, Ottawa) • Klaus F. Zimmermann (Global Labour Organization – GLO) Published jointly by the International Organization for Migration (IOM) and Eurasylum Ltd. A Bimonthly Journal for and by Policymakers Worldwide