Blending Academic Writing: The Use of Technology to teach amid Covid-19 Pandemic

Due to the Covid-19 pandemic, teachers have to hesitantly switch to the virtual world of teaching, known as enriched virtual blended learning in which technology, surely plays a significant role in material delivery and discussion. Studies related to blended learning in English language classes, especially in academic writing classes, have been done in many countries, but they are still lacking in the Indonesian setting. This study aimed to investigate the effectiveness of technology utilization in enriched blended learning to teach academic writing and the students' perspectives towards the use of technology in blended learning. This study involving forty-five students in a university in Jakarta applied both quantitative and qualitative methods. A pre-test and a post-test were assigned before and after the blended learning period to study the effectiveness of blended learning. In addition, surveys and interviews were conducted to investigate the students' perspectives. The results indicated that the use of technology in blended learning effectively helped students develop their academic writing skills despite being a new experience. Furthermore, despite some limitations, this strategy of using technology in teaching-learning was accepted with optimism as they started to get accustomed to it. Hence, the use of technology is promising for the future of learning. © 2023 IEEE.

IMPLICATIONS OF POTENTIAL NEW REGULATORY MEASURES TO ADDRESS AVIATION EMISSIONS

This work is an analysis of the implications of the potential new regulatory policies being recently proposed in the European Union, in particular the mandatory blending of SAF (on top of the already existing CORSIA or ETS), to address aviation emissions from a technical, operational and economic perspective. As a continuation of previous work from the Department of Aerospace Systems, Air Transport and Airports from the ETSIAE (Universidad Politécnica de Madrid), the air traffic structure of the European Union in 2019 has been analysed based on publicly available data from EUROCONTROL and EUROSTAT. The output has been used as the reference scenario for the implementation of the mandatory blending of SAF, expected to take over at the beginning of 2025, since it is expected that by then, air traffic will reach the pre-COVID levels. The results show that all the policy options considered so far have uneven impact among the different stakeholders and that before deciding going forward with any of the presented options, extra work needs to be done to overcome the different challenges that would potentially arise. © 2022 ICAS. All Rights Reserved.

Successful Application of Foamed Cement Slurry in an Ultradeepwater Well of 11,900-ft Water Depth (Claiming World Record)

Foamed cement was successfully used in the riserless section of an ultradeepwater well located in 11,900ft water depth. Foamed cement was selected to minimize operating costs and provide flexibility to adjust slurry density on a short notice. The seawater column exerted 5,319.1-psi hydrostatic pressure on the annulus. Consequently, nitrogen (N2) density could no longer be neglected. This paper presents simulations performed in preparation for the job, operational considerations, and post-job evaluation. The lead slurry needed a density of 1.25 SG and develops a compressive strength of at least 300 psi within 48 hr. Considering the cost and challenges associated with outsourcing resources under current Covid-19 pandemic restrictions, the foamed cement system was preferred over chemical-or particle-extended cement or blend systems. The N2 ratio for the foamed cement slurry system was 700 scf/bbl. With a base slurry pumping rate of 5 bbl/min, the required N2 pumping rate was 3,500 scf/min, which was greater than the capability of a single N2 pump (3,000-scf/min rate). Because the rig deck space could not accommodate three N2 pumps, one pump would serve as backup;thus, the final plan consisted of using two N2 pumps simultaneously. Two parallel foamed slurry treating lines were rigged up to reduce the fluid velocity in a single line. All laboratory testing was conducted locally. Additives used in the foamed slurry were environmentally friendly. A proprietary process-control system was used during the cementing operation and automatically synchronized the N2 pumps and foam pump rates with the base slurry rate. The cementing crew consisted of 11 individuals, including 2 client representatives. The entire pumping operation was completed in 10 hr. A total base slurry volume of 1016.2 bbl was continuously mixed and pumped at the density of 13.35 lbm/ gal (1.60 SG). The resulting foamed slurry volume was 1387.0 bbl with an average foam quality of 27.8% and foamed slurry density of 10.5 lbm/gal (1.26 SG). A total of 119 metric tonne of class G cement and 30,711 L of N2 were consumed during the pumping operation. The lead slurry was followed by 603.9 bbl of 15.86 lbm/gal (1.90 SG) class G cement tail slurry and 349.7 bbl of seawater for displacement. The final surface pressure was 594.6 psi. The lead slurry reached the seabed and the float shoe check was positive. No casing subsidence was observed. neglected when high-hydrostatic pressure is involved. © 2023, Offshore Technology Conference.

Enhancing the fuel properties of beverage wastes as non-edible feedstock for biofuel production

A few industries, such as the beverage industry, have experienced some growth in sales during the COVID-19 pandemic. Globally, beverage companies alone generate over 200 million tonnes of biomass annually, which largely ends up as animal feed or in landfills. With the UK government's commitment to reduce its carbon footprint by at least 68% in 2030, many companies, especially small and medium enterprises (SMEs), are exploring options to reduce carbon emissions and develop roadmaps to become carbon neutral. It has thus become imperative for beverage companies to find value in or repurpose their waste. This paper unlocks the potential for improving the fuel properties of beverage waste through a blending process and explores the determination of optimal fractions for the blends via characterization. With an initial moisture content of 82 and 58 wt.% brewery spent grain (BSG) and spent coffee grounds (SCG), respectively, the pre-treatment process reduced moisture content by approximately 10-15 wt.%. The study concludes that biomass blending improved the fuel properties of the biomass, providing a competitive comparison with coal for energy applications.

DECODING THE VIRUS: BLENDING PATTERNS BEHIND THE NAME "SARS-CoV-2”

The disruptive impact of the SARS-CoV-2 pandemic raised awareness of the need for elucidation of its' conceptual framework among contemporary linguists. This paper attempts to reconstruct the most fundamental conceptual relations within the compound "SARS-CoV-2” in terms of the Conceptual Blending. The main hypothesis for this research states that certain compression patterns and the structural specificity of the emerging blend make the compound "SARS-CoV-2” an efficient conceptual and formal template for multi-scope blending in future linguistic research concerning mutations of the coronavirus. The topology of mental spaces, the emergent structure within the blend, main compression patterns emerging from specific contextual constraints, the interplay of various vital relations, the dynamics of change and the potential to scale down vital relations (transmissibility and transmission dynamics of the SARS-CoV-2 virus) will be outlined. A seven-space-model of the SARS-CoV-2 conceptual integration network will be proposed. The results of analysis of intra-and outer-spatial vital relations connecting the input spaces and respective compression patterns will be demonstrated with reference to similarities and differences between SARS-CoV and SARS-CoV-2. © 2022, University of Economy. All rights reserved.

Nanokaolin reinforced carboxylated nitrile butadiene rubber/polyurethane blend-based latex with enhanced tensile properties and chemical resistance

The demand for gloves (e.g., disposable gloves, medical gloves) is increasing due to the Coronavirus disease 2019 (COVID-19) pandemic. Stability in the supply chain in the glove industry is important, and thus strategies are used to solve the problem of the shortage of nitrile gloves. The blending of nitrile butadiene rubber (NBR) with polyurethane (PU) and the use of the nanocomposite concept is among the feasible approaches. The present study aims to investigate the effects of nanokaolin (NK) on the tensile and chemical properties of carboxylated nitrile butadiene rubber (NBR)/polyurethane (PU) latex blends. Three different loadings of NK (10, 20, and 30 parts per hundred rubber) were added to the NBR/PU (at a blending ratio of 85/15). The zeta potential showed that all the NBR compounds exhibit good colloidal stability. The incorporation of NK increased the crosslink density and tensile strength of the NBR/PU latex blends. The highest tensile strength was achieved when the NK loading was 20 phr. All the NBR blends and nanocomposites (NBR/PU-based) possess tensile properties that fulfill the requirements for glove application. The chemical resistance of NBR compounds was increased by the incorporation of NK due to the higher crosslink density and barrier properties contributed by the NK. © The Author(s) 2023.

Πανεπιστήμιο στην περίοδο της υγειονομική κρίσης (COVID-19) και κριτική θεώρηση της εξ αποστάσεως εκπαίδευσης

This paper studies aspects of distance education and explores its contribution to educational processes in the evolving period (COVID-19). First, a historical review of the course of distance education is attempted and various implementations of distance education in higher education are presented. Considerations related to the use of distance education during the pandemic and its impact on students and academic staff will emerge. Finally, an introduction to the 'theoretical' debate on the link between distance education and lifelong learning in the context of a globalized society will be provided. © 2022, Academia (Greece). All rights reserved.

Environmental impact assessment of a newly developed solid oxide fuel cell-based system combined with propulsion engine using various fuel blends for cleaner operations

After the COVID-19 pandemic has spread throughout the world, many research institutions and industrial organizations are putting great efforts into producing environmentally friendly solutions for the transportation sector. This paper presents a newly developed combined solid oxide fuel cell system with a turbofan engine that can use five alternative fuels, such as dimethyl ether, methanol, hydrogen, methane, and ethanol, with different blending ratios to form five fuel blends. The proposed system is studied in this paper using exergoenvironmental analysis (which is known as environmental impact assessment by exergy) in order to quantify and evaluate the environmental impact. The combined turbofan has an exergetic efficiency of 82%, with total fuel and product exergy rates of 905 and 743 MW, respectively. The total environmental impact caused by emissions and exergy destructions has a range of 4000 to 9000 Pt/h for all the fuel blends. The specific exergoenvironmental impact values of electricity production vary from about 3 to 8 mPt/MJ for solid oxide fuel cells and 10 to 25 mPt/MJ for the three turbines. The exergoenvironmental impact of the thrust force is a minimum of 34 Pt/(h.kN) for the RF1 fuel and a maximum of 87 Pt/(h.kN) for the RF4 fuel. © 2022

Development of a Virtual Telecommunication System Research Laboratory

Researchers are utilizing cutting-edge technology to accelerate the discovery of solutions to stop the COVID-19 pandemic. Virtual reality (VR) also provides a vital role in the operation against this outbreak. Daily tasks have remained unchanged since life has entirely halted. The method for recovering people's lives and enabling them to work from home is described in this article. The digital Telecom Lab at Chulalongkorn University was developed using virtual 3D technology. Several methods were employed gradually to build this lab. The VR lab was developed using Unity, a cross-platform game engine, to deliver the greatest experience. The actual outcome, which was created with the expertise of Blender and Unity, is incredibly immersive. © 2022 Asia-Pacific of Signal and Information Processing Association (APSIPA).

Using topic-noise models to generate domain-specific topics across data sources.

Domain-specific document collections, such as data sets about the COVID-19 pandemic, politics, and sports, have become more common as platforms grow and develop better ways to connect people whose interests align. These data sets come from many different sources, ranging from traditional sources like open-ended surveys and newspaper articles to one of the dozens of online social media platforms. Most topic models are equipped to generate topics from one or more of these data sources, but models rarely work well across all types of documents. The main problem that many models face is the varying noise levels inherent in different types of documents. We propose topic-noise models, a new type of topic model that jointly models topic and noise distributions to produce a more accurate, flexible representation of documents regardless of their origin and varying qualities. Our topic-noise model, Topic Noise Discriminator (TND) approximates topic and noise distributions side-by-side with the help of word embedding spaces. While topic-noise models are important for the types of short, noisy documents that often originate on social media platforms, TND can also be used with more traditional data sources like newspapers. TND itself generates a noise distribution that when ensembled with other generative topic models can produce more coherent and diverse topic sets. We show the effectiveness of this approach using Latent Dirichlet Allocation (LDA), and demonstrate the ability of TND to improve the quality of LDA topics in noisy document collections. Finally, researchers are beginning to generate topics using multiple sources and finding that they need a way to identify a core set based on text from different sources. We propose using cross-source topic blending (CSTB), an approach that maps topics sets to an s-partite graph and identifies core topics that blend topics from across s sources by identifying subgraphs with certain linkage properties. We demonstrate the effectiveness of topic-noise models and CSTB empirically on large real-world data sets from multiple domains and data sources.

Recycling polypropylene from non-woven disposable masks in developing a three-dimensional printing filament

Non-woven disposable masks play a unique role in reducing the COVID-19 pandemic threat in transmission between people, but the huge amount of disposable non-woven masks generated every day are currently posing a serious challenge to our environment on a global-wide scale. In line with this emerging problem, a series of recycling processes were designed and conducted to evaluate the performance of material recovered from those waste masks for potential use in three-dimensional (3D) printing. A composite filament from recycled polypropylene (rPP) and an additive material, glass fiber (GF), was fabricated by melt-blending processing followed by single-screw extrusion. A variety of material properties, including the chemical/mechanical/microstructure property, thermal stability, printability, rheology performance, and geometrical accuracy toward GF/rPP composite filaments, were comprehensively analyzed. Our results demonstrated that two important mechanical properties, the compression strength and the tensile strength, to a 3D printed object by fused deposition modeling (FDM) from the GF/rPP composite were significantly higher than that of a FDM 3D printed object from GF/polypropylene composites. The specific warpage parameter (Wsp) and the surface roughness (Sa) for a 3D printed object from the GF/rPP composite at 30 wt% GF additive would have printing accuracy of 0.54% +/- 0.0014 and 21.1 +/- 0.76 mu m, respectively, and no clogging phenomenon was observed in the printer nozzle channel during the printing processing, suggested that this recycling method for a large number of non-woven waste masks was potentially applicable in serving as a FDM 3D printing material.

Augmented Reality in Clothing Consumer Customization in COVID-19 Pandemic: A Preliminary Study

Emergencies produce significant changes in people's habits and lifestyles. Further, it also impacts our clothing tastes and preferences because social interaction is reduced, and everyday activities are performed at home. Thus, this paper shows a psychographic analysis to determine the type, style, color, and other clothing characteristics users preferred across the pandemic. In addition, some considerations have been taken into account to understand the clothing characteristics users will look for in post-pandemic presential jobs. In this context, the first version of a smartphone app using augmented reality (AR) has been developed. Three-dimensional objects were designed using Blender, while the smartphone app was set up using Unity, accompanied by modules such as AR Foundation, ARCore XR Plugin, and DOTween. The application allows the overview of the selected three-dimensional garment and relevant information about its components. Statistical analysis shows a vital essential between the monthly income of the participants and their purchasing decision;likewise, between sex and upper garments usage. Experimental tests inside a retail store validate this proposal throughout a new sample of 44 people. Ultimately, they filled out a usability test (SUS) that confirmed the application acceptance with an 82.73%. Finally, they gave the corresponding feedback on their experience using the app. Consequently, relevant information that might be used in future research to understand the consumer needs in a matter of clothing emergencies or confinement is passing through has been exposed. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The Value of 3D Modeling of Cultural Heritage Monuments with the Method of Digital Photogrammetry for Use in Augmented Reality Applications

Nowadays, the need to digitize cultural heritage sites and present them to the public in original and easily accessible ways is very important. The advantages are many both in times when Museums and archeological sites are open, and in times of forced closure such as the Covid-19 pandemic. As a result, there is more motivation and interest from the spectators, young and old, easy access and from remote areas, the ability to travel the collection outside the museums. Also due to the limited space of the museums there are exhibits that remain in warehouses and are not exhibited in the collections. The digital documentation enables the enrichment and display of a large volume of exhibits virtually. The dynamics of Photogrammetry with the rapid and continuous evolution of software and the ability to utilize them by many specialties gives rise to this study. The basic premise is that with simple media such as a compact camera and the right software, 3D exhibits such as the funeral masks and personal belongings of the 18 21 fighters can be reproduced, many of which are in storage. The conjuncture of 200 years since the beginning of the Greek Revolution gave even greater impetus to the investigation of ways of presenting them using AR Technology. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Assistive Telexistence System Using Motion Blending

Robotic avatar and telexistence systems have risen in prominence after the covid-19 pandemic, where current telecommunication methods are limited in terms of physical interaction abilities. Most existing systems focus on manual control of the remote robot, where the robot's arms and head movements follow the user's movements. Despite the effectiveness of such controls in conveying high levels of embodiment, such control methods jeopardize the efficiency of controls, especially for complex physical manipulation tasks, unclear environments, or unstable communication. Therefore, we propose an assistive-manipulation method to augment users' control of a telexistence robot during physical manipulation tasks. Machine Learning (ML) was used in the remote environment to localize target objects. This information is sent to the local environment where an inverse kinematic (IK) solution to hold the intended object is generated. The generated IK solution is fused with the one generated by the user's arm movements. The system enables generating various levels of IK fusion. However, an essential aspect of telexistence is to maintain high levels of embodiment and body ownership over the remote robot. Therefore, the evaluation in this paper focuses on investigating the effect of haptic feedback and the level of IK fusion on body ownership. The results indicate that haptic feedback induced a sense of assurance of task completion and enabling assistance from the system improved the user's sense of control over the robotic arm. © 2022 IEEE.

Recent developments in lactose blend formulations for carrier-based dry powder inhalation.

Lactose is the most commonly used excipient in carrier-based dry powder inhalation (DPI) formulations. Numerous inhalation therapies have been developed using lactose as a carrier material. Several theories have described the role of carriers in DPI formulations. Although these theories are valuable, each DPI formulation is unique and are not described by any single theory. For each new formulation, a specific development trajectory is required, and the versatility of lactose can be exploited to optimize each formulation. In this review, recent developments in lactose-based DPI formulations are discussed. The effects of varying the material properties of lactose carrier particles, such as particle size, shape, and morphology are reviewed. Owing to the complex interactions between the particles in a formulation, processing adhesive mixtures of lactose with the active ingredient is crucial. Therefore, blending and filling processes for DPI formulations are also reviewed. While the role of ternary agents, such as magnesium stearate, has increased, lactose remains the excipient of choice in carrier-based DPI formulations. Therefore, new developments in lactose-based DPI formulations are crucial in the optimization of inhalable medicine performance.

Analysis of Teachers' Satisfaction With Online Learning During the Covid-19 Pandemic

After one and a half years of forced E-Learning in Jordan due to the COVID-19 pandemic, the Ministry of Higher Education approved a new regulation titled 'Blending E-Learning in Higher Education Institutes (HEI)', which comes hand in hand with an action plan, aiming to transform certain percentages of academic programs (AP) offered in HEI into online and blended learning. This study investigates the attitude of 174 staff members at University of Petra towards the newly stated regulation, and their readiness level to implement the action plan. It also investigates the satisfaction rate of the academic staff with the experience of e-learning during the COVID-19 pandemic in Jordan from March 2020-till Au-gust 2021. The study was conducted with a questionnaire distributed electronically. The results show that improvements need to be done on three areas: teachers' training on techniques to create and manage e-content, online assessment methods, and increasing the interactions of students in online courses. It also shows that staff members are satisfied with the new regulations to have percentages of courses fully online while others are blended courses;however, there is dissatisfaction with the pass\fail regulation set by the ministry during the pandemic period. © 2022 IEEE.

Strategies for the Digitalization of Cultural Heritage

The COVID-19 pandemic caused despair, poverty and, above all, pain and death across the planet. Nevertheless, there is no doubt that it has also given a strong global impetus to the digital world, asserting its importance, sustainability and richness of perspectives. With our work we intend to establish a set of best practices aimed at defining methods and technologies that will enable those fascinated by digital technologies to contribute effectively to the digitisation of cultural heritage on a large scale. Various aspects that play a crucial role in the digitisation of artifacts will be discussed, with a focus on the issues involved in the manual realisation of works using Blender and Unity software. For demonstration purposes, two very popular use cases in the Umbria region of Italy are presented: “Piazza IV Novembre” in Perugia with the magnificent “Fontana Maggiore”, the “Palazzo dei Priori” and the Duomo on one side and the Republic square in Foligno on the other, with the Duomo, the Bishop’s house and the Diocesan Museum, the Town Hall and “Palazzo Trinci”. The first realization was carried out using photogrammetry techniques, the software Blender and Unity, while the second was carried out exclusively with Blender and Unity. The theme is highly relevant in Europe, particularly Italy, where the topic is part of the post-COVID-19 National Recovery and Resilience Plan (NRRP). © 2022, The Author(s).

Ukucha: a video game for teaching experimental psychology

The COVID-19 pandemic has forced educational institutions to find a way to meet educational needs, within these those for experimentation. This article implements a video game for teaching experimental psychology in a private university. The research is of an applied type and experimental design. For the development of the software, the SUM methodology was used for the development of the video game and the OOHDM methodology for the development of the web page according to the video game. Additionally, cutting-edge tools have been considered to be able to make a scalable and robust application such as the use of Unreal Engine 4 in its version 4.27 for the development of the video game, Blender in its version 3.0 for 3D modeling and character animation, Django as a framework Python for web development in conjunction with PostgreSQL for the elaboration of the database through the software architecture Model Vista Template (MVT). © 2022 IEEE Computer Society. All rights reserved.

Blending camera and 77 GHz radar sensing for equitable, robust plethysmography

With the resurgence of non-contact vital sign sensing due to the COVID-19 pandemic, remote heart-rate monitoring has gained significant prominence. Many existing methods use cameras;however previous work shows a performance loss for darker skin tones. In this paper, we show through light transport analysis that the camera modality is fundamentally biased against darker skin tones. We propose to reduce this bias through multi-modal fusion with a complementary and fairer modality - radar. Through a novel debiasing oriented fusion framework, we achieve performance gains over all tested baselines and achieve skin tone fairness improvements over the RGB modality. That is, the associated Pareto frontier between performance and fairness is improved when compared to the RGB modality. In addition, performance improvements are obtained over the radar-based method, with small trade-offs in fairness. We also open-source the largest multi-modal remote heart-rate estimation dataset of paired camera and radar measurements with a focus on skin tone representation. © 2022 Owner/Author.

COVID-19 chest X-ray detection through blending ensemble of CNN snapshots.

The novel COVID-19 pandemic, has effectively turned out to be one of the deadliest events in modern history, with unprecedented loss of human life, major economic and financial setbacks and has set the entire world back quite a few decades. However, detection of the COVID-19 virus has become increasingly difficult due to the mutating nature of the virus, and the rise in asymptomatic cases. To counteract this and contribute to the research efforts for a more accurate screening of COVID-19, we have planned this work. Here, we have proposed an ensemble methodology for deep learning models to solve the task of COVID-19 detection from chest X-rays (CXRs) to assist Computer-Aided Detection (CADe) for medical practitioners. We leverage the strategy of transfer learning for Convolutional Neural Networks (CNNs), widely adopted in recent literature, and further propose an efficient ensemble network for their combination. The DenseNet-201 architecture has been trained only once to generate multiple snapshots, offering diverse information about the extracted features from CXRs. We follow the strategy of decision-level fusion to combine the decision scores using the blending algorithm through a Random Forest (RF) meta-learner. Experimental results confirm the efficacy of the proposed ensemble method, as shown through impressive results upon two open access COVID-19 CXR datasets - the largest COVID-X dataset, as well as a smaller scale dataset. On the large COVID-X dataset, the proposed model has achieved an accuracy score of 94.55% and on the smaller dataset by Chowdhury et al., the proposed model has achieved a 98.13% accuracy score.