Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancement of Sea Wave Potential Energy with Under-Sea Periodic Structures: A Simulation and Laboratory Study

This paper is devoted to a theoretical investigation on the wave amplitude enhancement of surface sea water waves with under-sea periodic arrays of cylinders. A two-dimensional shallow water wave equation is derived and solved by using the plane-wave expansion method. The lattice types studied here include triangular, square and hexagonal lattices. These under-sea structures alter the sea bottom topography and induce constructive interference on the surface water waves. Given that the wave potential energy is dependent on the square of the wave amplitude, this mechanism can thus be used to increase the potential energy. It is shown that the enhancement factor depends on two geometric parameters and the maximum wave amplitude can be found by adjusting the two geometric parameters. Among the lattice types, the triangular and square lattice structures can induce more wave amplitude enhancement (and thus potential energy) than the hexagonal structures. Guided by numerical simulations, we have performed a reduced-scale water tank experiment to demonstrate the feasibility of the proposed idea. Preliminary experimental results show promising evidence of the predicted wave amplitude enhancement, suggesting perspective real-scale nearshore deployment and test.
Edge scour in current adjacent to stone covers

AbstractThis paper presents the results of an experimental investigation on edge scour adjacent to a stone cover laid on a sandy bed. The three-dimensional flow over the edge of the stone layer has been investigated by the use of particle image velocimetry. The flow measurements show a significant amount of turbulence in the primary flow near the junction between the stone layer and the sand bed and the formation of complex secondary-flow structures. The results show that the flow and the edge scour process in a steady current are governed by the size of the roughness elements and to some extent the side slope of the berm. The edge scour is caused by the combined action of the primary flow and the secondary flow. The primary flow stirs up the sediment and puts it into suspension, and the secondary flow carries it away from the junction between the stone layer and the sand bed, resulting in a scour hole forming adjacent to the toe of the stone layer. The measured scour depth attained a constant level of ap.
Community-based house improvement for malaria control in southern Malawi: Stakeholder perceptions, experiences, and acceptability

House improvement (HI) refers to the full screening or closing of openings such as windows, doors, and eaves, as well as the installation of ceilings, to reduce mosquito-human contact indoors. HI is a viable supplementary intervention that reduces malaria transmission further than the existing strategies alone. In Malawi, HI has not been widely implemented and evaluated for malaria control. Concerns about lack of local evidence, durability in different epidemiological and cultural settings, and the cost of large-scale implementation are among the reasons the strategy is not utilised in many low-income countries. This study assessed community perceptions, experiences, and acceptability of community-led HI in Chikwawa district, southern Malawi. This was a qualitative study where separate focus group discussions were conducted with members from the general community (n = 3); health animators (n = 3); and HI committee members (n = 3). In-depth interviews were conducted with community members (n = 20), and key-informant interviews were conducted with health surveillance assistants and chiefs (n = 23). All interviews were transcribed and coded before performing a thematic content analysis to identify the main themes. Coded data were analysed using Nvivo 12 Plus software. Study participants had a thorough understanding of HI. Participants expressed satisfaction with HI, and they reported enabling factors to HI acceptability, such as the reduction in malaria cases in their villages and the safety and effectiveness of HI use. Participants also reported barriers to effective HI implementation, such as the unavailability and inaccessibility of some HI materials, as well as excessive heat and darkness in HI houses compared to non-HI houses. Participants indicated that they were willing to sustain the intervention but expressed the need for strategies to address barriers to ensure the effectiveness of HI. Our results showed the high knowledge and acceptability of HI by participants in the study area. Intensive and continued health education and community engagement on the significance of HI could help overcome the barriers and improve the acceptability and sustainability of the intervention.
Tropical cyclone intensity prediction based on recurrent neural networks

The accurate prediction for the tropical cyclone (TC) intensity is a recognised challenge. Researchers usually develop dynamical models to address this task. However, since the TC intensity is highly influenced by various factors such as ocean and atmosphere conditions, it is difficult to build the very model which can explicitly describe the mechanism of TC. A new idea is developed, utilising the massive historical observation data by a deep learning approach, to conduct a completely data-driven TC intensity prediction model. All the TC intensity and track data which have been observed in Western North Pacific since 1949 are collected, and recurrent neural network for TC intensity prediction is constructed. In general, their motivation as well as novelty is to develop a data-driven approach instead of empirical models. There are very few researches similar to their exploratory work. The proposed method has presented 5.1 m ⋅ s − 1 error in 24 h prediction, which is better than some widely used dynamical models and is close to subjective prediction.
Moist Static Energy and Secondary Circulation Evolution Characteristics during the Rapid Intensification of Super Typhoon Yutu (2007)

A high-resolution Weather Research and Forecasting (WRF) model is used to simulate inner-core thermodynamic (such as moist static energy) and dynamic secondary circulation structure evolutions associated with the rapid intensification (RI) of Super Typhoon Yutu (2007). The results show that the column-integrated moist static energy (MSE) and the secondary circulation strength are significantly correlated to the typhoon intensity change. A rapid increase of the MSE during the RI period is primarily attributed to inner core temperature increase, due to enhanced subsidence within the eye and strengthened convective heating along the eyewall. The column-integrated MSE budget analysis shows that its rapid increase during the RI is mainly caused by surface latent heat flux. A further diagnosis of the Sawyer–Eliassen equation shows that the rapid strengthening of the secondary circulation during RI results from both the radially expanding positive diabatic heating over the eyewall and the occurrence of a second heating center outside the eyewall. While the radially expanding eyewall heating contributes about 70% of the secondary circulation change, the outer heating contributes about 30%.
Behavior Modeling of a Distributed Application for Anomaly Detection

: Computational clouds offer services in different formats, aiming to adapt to the needs of each client. This scenario of distributed systems is responsible for the communication, management of services and tools through the exchange of messages. Thus, security in such environments is an important factor. However, the implementation of secure systems to protect information has been a difﬁcult goal to achieve. In addition to the prevention mechanisms, a common approach to achieve security is intrusion detection, which can be carried out by anomaly detection. This technique does not require prior knowledge of attack patterns, since the normal behavior of the monitored environment is used as a basis for detection. This work proposes a behavioral modeling technique for distributed applications using the traces of operations of its nodes, allowing the development of a strategy to identify anomalies. The chosen strategy consists of modeling the normal behavior of the system, which is arranged in sets of n -grams of events. Our goal is to build functional and effective models, which make it possible to detect anomalies in the system, with reduced rates of false positives. The results obtained through the evaluation of the models highlight the feasibility of using n -grams to represent correct activities of a system, with favorable results in the false positive rate and also in terms of accuracy.
Characterisation of Pineapple Cultivars under Different Storage Conditions Using Infrared Thermal Imaging Coupled with Machine Learning Algorithms

The non-invasive ability of infrared thermal imaging has gained interest in various food classification and recognition tasks. In this work, infrared thermal imaging was used to distinguish different pineapple cultivars, i.e., MD2, Morris, and Josapine, which were subjected to different storage temperatures, i.e., 5, 10, and 25 °C and a relative humidity of 85% to 90%. A total of 14 features from the thermal images were obtained to determine the variation in terms of image parameters among the different pineapple cultivars. Principal component analysis was applied for feature reduction in order to prevent any effect of significant difference between the selected features. Several types of machine learning algorithms were compared, including linear discriminant analysis, quadratic discriminant analysis, support vector machine, k-nearest neighbour, decision tree, and naïve Bayes, to obtain the best performance for the classification of pineapple cultivars. The results showed that support vector machine achieved the best performance from the combination of optimal image parameters with the highest classification rate of 100%. The ability of infrared thermal imaging coupled with machine learning approaches can be potentially used to distinguish pineapple cultivars, which could enhance the grading and sorting processes of the fruit.
Adolescent Social Media Information Literacy Outside of School: A Scoping Review of the Literacy and Educational Technology Literature

The information literacy practices of adolescents on social media outside of school are worth considering, since adolescents use social media near ubiquitously and must grapple with all types of content they encounter incidentally or intentionally. This scoping review followed the PRISMA Extension for Scoping Reviews (PRISMA-ScR) to examine the extent and nature of scholarship on this topic from the perspective of educational technology and literacy scholarship, as both fields are uniquely poised to collaborate on this interdisciplinary topic. Surprisingly, only four articles fit the scope of our review. The literature found, and not found, revealed several themes. These themes were the imprecise use of keywords across scholarship, use of social media for community support, exposure to incidental information, evidence for different literacy practices on social media, and the need for addressing social media information literacy in school. Opportunities for future work and collaborative research between both fields is also discussed.
El trabajo terminográfico basado en corpus: el caso del recurso DicoAdventure

Los corpus textuales se han convertido en la actualidad en un recurso fundamental para el trabajo terminográfico, ya que permiten recabar información real, fiable y de calidad para estudiar cualquier campo de especialidad. Están presentes en todas las fases del trabajo, desde la extracción de terminología hasta la inclusión de información lingüística, semántica y pragmática en las entradas de los diccionarios. Por este motivo, el corpus especializado Advencor es la base del proyecto DicoAdventure, un proyecto de investigación que tiene como objetivo elaborar un recurso bilingüe (inglés-español) basado en la léxico-semántica sobre el turismo de aventura, el diccionario DicoAdventure. En este trabajo, presentamos las dos primeras fases de la metodología, a saber: la compilación del corpus y la extracción y selección de unidades especializadas para ilustrar el trabajo terminográfico basado en corpus.
Extrusion foaming of linear and branched polypropylenes – input of the thermomechanical analysis of pressure drop in the die

Abstract This paper aims at a better understanding of the polypropylene (PP) physical extrusion foaming process with the objective of obtaining the lowest possible foam density. Two branched PPs were compared to the corresponding linear ones. Their shear and elongation viscosities were measured as well as their crystalline properties. Trials were conducted in a single screw extruder equipped with a gear pump and a static mixer cooler to adjust the melt temperature at the final die. The effect of decreasing this temperature on the PP foamability and on the pressure drop in the die was analyzed. The foam density of branched PPs varies from high to low values while decreasing the foaming temperature. In the same processing conditions, the foam density of linear PPs does not decrease so much, as already evidenced in the literature. The foamability transition coincides with an increase of the pressure drop in the die. The originality of the work lies in the thermomechanical analysis of the polymer flow in the die which allows the identification of the relevant physical phenomena for a good foamability. The comparison of the experimental pressure drops in the die and the computed ones with the identified purely viscous behavior points out the influence of the foaming temperature and of the PP structure. At high foaming temperature the discrepancy between experimental measurements and the computed pressure drops remains limited. It increases when decreasing the foaming temperature, but the mismatch is much more important for branched PPs than for linear ones. This difference is analyzed as a combination of the activation energy of the viscosity, the elongational viscosity in the convergent geometry of the die which is much more important for branched PPs than for linear ones, and the onset of crystallization which occurs at higher temperature for branched PPs than for linear PPs.
Murine Langerin+ dermal dendritic cells prime CD8+ T cells while Langerhans cells induce cross-tolerance

Skin dendritic cells (DCs) control the immunogenicity of cutaneously administered vaccines. Antigens targeted to DCs via the C-type lectin Langerin/CD207 are cross-presented to CD8 + T cells in vivo. We investigated the relative roles of Langerhans cells (LCs) and Langerin + dermal DCs (dDCs) in different vaccination settings. Poly(I:C) and anti-CD40 agonist antibody promoted cytotoxic responses upon intradermal immunization with ovalbumin (OVA)coupled anti-Langerin antibodies (Langerin/OVA). This correlated with CD70 upregulation in Langerin + dDCs, but not LCs. In chimeric mice where Langerin targeting was restricted to dDCs, CD8 + T-cell memory was enhanced. Conversely, providing Langerin/OVA exclusively to LCs failed to prime cytotoxicity, despite initial antigen cross-presentation to CD8 + T cells. Langerin/OVA combined with imiquimod could not prime CD8 + T cells and resulted in poor cytotoxicity in subsequent responses. This tolerance induction required targeting and maturation of LCs. Altogether, Langerin + dDCs prime long-lasting cytotoxic responses, while cross-presentation by LCs negatively influences CD8 + T-cell priming. Moreover, this highlights that DCs exposed to TLR agonists can still induce tolerance and supports the existence of qualitatively different DC maturation
Trypsin-like Inhibitor Domain (TIL)-Harboring Protein Is Essential for Aedes aegypti Reproduction

Cysteine-rich trypsin inhibitor-like domain (TIL)-harboring proteins are broadly distributed in nature but remain understudied in vector mosquitoes. Here we have explored the biology of a TIL domain-containing protein of the arbovirus vector Aedes aegypti, cysteine-rich venom protein 379 (CRVP379). CRVP379 was previously shown to be essential for dengue virus infection in Ae. aegypti mosquitoes. Gene expression analysis showed CRVP379 to be highly expressed in pupal stages, male testes, and female ovaries. CRVP379 expression is also increased in the ovaries at 48 h post-blood feeding. We used CRISPR-Cas9 genome editing to generate two mutant lines of CRVP379 with mutations inside or outside the TIL domain. Female mosquitoes from both mutant lines showed severe defects in their reproductive capability; mutant females also showed differences in their follicular cell morphology. However, the CRVP379 line with a mutation outside the TIL domain did not affect male reproductive performance, suggesting that some CRVP379 residues may have sexually dimorphic functions. In contrast to previous reports, we did not observe a noticeable difference in dengue virus infection between the wild-type and any of the mutant lines. The importance of CRVP379 in Ae. aegypti reproductive biology makes it an interesting candidate for the development of Ae. aegypti population control methods.
Real-time Crowd Counting based on Wearable Ephemeral IDs

: Crowd Counting is a very interesting problem aiming at counting people typically based on density averages and/or aerial images. This is very useful to prevent crowd crushes, especially on urban environments with high crowd density, or to count people in public demonstrations. In addition, in the last years, it has become of paramount importance for pandemic management. For those reasons, giving users automatic mechanisms to anticipate high risk situations is essential. In this work, we analyze ID-based Crowd Counting, and propose a real-time Crowd Counting system based on the Ephemeral ID broadcast by contact tracing applications on wearable devices. We also performed some simulations that show the accuracy of our system in different situations.
A Processual Model of CEO Activism: Activities, Frames, and Phases

Chief executive officers (CEOs) engage in activism when they take public stances on sensitive socio-political issues. In this study, we address the less-explored activities that constitute CEO activism beyond single stances as the activism is maintained over time. The data cover 6 years of campaign and media materials from a case company with several CEO-initiated activist campaigns. Our findings from an inductive analysis contribute to CEO activism theorizing in three ways. First, we extend CEO activism conceptually by identifying five underlying activities that support a public stance: anchoring motivations, modeling action, taking agency, enduring criticism, and normalizing activism. Second, we bridge individual- and organization-level analyses by depicting how a CEO involves a company in activism through activities that justify interrelated topic frame and role frame. Third, we develop a processual model that includes the pre-stance, stance-taking, and post-stance phases and explains how the underlying activities are interrelated and follow a pattern that serves to maintain CEO activism. Accordingly, CEO activism includes activities, through the pre-stance, stance-taking, and post-stance phases, whereby a CEO deliberately engages personally and through a company in public debate about sensitive socio-political issues and the role of businesses in addressing them.
Design, Dynamics, and Control of Mobile Robotic Systems

Author(s): Morozovsky, Nicholas | Advisor(s): Bewley, Thomas | Abstract: Mobile robotic systems are increasingly prevalent in several fields of academia, industry, and everyday life. This dissertation outlines the development of several means of locomotion for such systems and the tools created and used to design them. Novel mechanical designs with minimal actuators are combined with advanced control systems to create dynamic locomotion behavior. A single, unified Lagrangian dynamics architecture is used to represent a variety of robotic systems, derived from first principles and applied programmatically. Model-based control methods are heavily used to take advantage of the known dynamics and are also applied programmatically for the automatic generation of control laws and gain scheduling lookup tables. Improvements to encoder velocity estimation across a wide velocity range are described in detail. A number of key hardware advances in different fields are exploited to create low-cost, but capable, mobile robotic systems: additive manufacturing (3D printing), powerful embedded microprocessors (Arduino, ARM, FPGA), solid state sensors (MEMS accelerometers and gyroscopes), and inexpensive brushed DC motors. This dissertation presents both notable results and tactical details of implementation that will be useful to those designing similar systems.Several novel robotic systems are presented in this dissertation. First, two incarnations of a mobile balancing platform with two coaxial wheels with the center of mass above the center of rotation are presented. Active feedback control is required to stabilize the system. Next, Switchblade is a patent pending treaded inverted pendulum designed for maximum mobility over a wide range of terrain including tight spaces and significant obstacles (e.g. stairs). Multiple variants of the design are explored, which shows that the vehicle concept is broadly applicable across different length scales and use cases. SkySweeper is an under-actuated robotic system designed for multimodal locomotion along wires and cables. Finally, RAPID is a reconfigurable, automated dynamometer for characterizing small DC motors, the primary purpose of which is identifying the operating parameters of motors used in vehicles with model-based control and estimation algorithms.
Two-Tier Cascaded Classifiers to Improve Electrical Power Quality

Although the manifestation of faults in electrical distribution networks is likely scarce, they deemed to be one of the most severe threats which encounter the reliability and stability of power systems. Thereby, most of research efforts in the last decade have been directed to characterize the faults and propose detection systems. However, the state-of-art of these systems still undergo serious shortcomings such as automation, integration and validation. To surpass these shortcomings, a two-tier system is proposed for both fault detection and fault classification in electrical distribution networks. Prior to deal with faults, the captured voltage signals pass through a preparatory unit to process the raw voltage signals. Afterwards, the optimized classifiers detect and classify the faults in the first and second tiers, respectively. Furthermore, the performance of the classifiers in both tiers is validated using the VSB dataset (real-time data for fault detection). Finally, the proposed two-tier system proved its efficiency in detecting electrical faults and their type as well.