Hybrid Class Research Articles

The effect of hybrid classes on extrinsically motivated students

Emerging from the Covid19 pandemic, many higher education institutions rapidly improvised teaching students in a hybrid mode that concurrently combined online and in-person instruction. The varied engagement results from students and staff prompted many institutions to reconsider this hybrid approach (Raes et al., 2020), with opinions of both students and teachers divided on the merits of returning to an in-person classroom. While some studies (Peng & Wei, 2021) noted success at the ‘juggling act’ of supporting both an in-person class and an online class simultaneously, more studies found the emerging technology, split focus, resourcing and unfamiliar instructions to be a disengaging classroom experience (Aagaard et al, 2023). A lack of clear and quantitative evidence has been noted as a key issue with many of the studies of hybrid learning (Raes et al, 2020). The improvised nature of many pandemic teaching responses and the many variables that may confound engagement results, prompts a more considered and deliberate re-examination of hybrid learning which takes into account the motivational needs of students. If a student is motivated to attend a hybrid classroom, their subsequent evaluations of the experience seem likely to be related to their initial motives, expectations and reasons for attending. The lens of Self Determination Theory (SDT) offers a range of insights into the type of motivation felt by students and enables the disambiguation of whether a student is motivated intrinsically or extrinsically (Ryan & Deci, 2017). Intrinsic motivation being characterised by an internal locus of control –arising spontaneously from within. Extrinsic motivation conversely is characterised by an external locus of control – motivation is controlled by outside factors and compulsions that a student feels they ought to follow. Deci and Ryan’s Intrinsic Motivation Inventory (IMI) offers us additional insights into three descriptive sub-types of intrinsic and extrinsic motivation – autonomy, relatedness and mastery. The idea that an unfulfilled need for personal relatedness in some students might relate to levels of student engagement online and in-person was hoped might explain some of variable engagement responses from students. This presentation tells the story of how hundreds of students responded to a synchronous concurrent hybrid classroom intervention across four weeks of an otherwise online subject. Utilising high-quality hybrid learning technology available at the time, the advanced Class.com interface and a well-adapted pedagogy the journey of students with differing motivational needs was explored using the lens of Deci and Ryan’s (2017) IMI. Through regression modelling, network analysis and a broad analysis of associated demographic factors it was found in particular that low ATAR students with extrinsic motivation were more disengaged by the hybrid classroom environment, in comparison to other motivational subgroups. Contrary to expectation, students with a motivational need for relatedness were not found to respond differently to hybrid learning compared with other motivational subgroups. Recommendations for future iterations of synchronous concurrent hybrid classrooms and research are offered.

On a Hybrid Class of $p$-Laplacian Initial Value Problems with Modified Mittag-Leffler Kernel

In this work, we establish key results on the existence theory for a category of initial value problems (IVPs) involving hybrid fractional integro-differential equations (HFIDEs) with a $p$-Laplacian operator, utilizing the modified Mittag-Leffler kernel. By employing Krasnoselskii and Banach fixed point theorems (FPTs), we determine the conditions required for the existence of solutions. Additionally, we examine the Hyers-Ulam (H-U) stability of the problem. Lastly, we present an example to confirm our theoretical results.

Creation of true interspecies hybrids: Rescue of hybrid class with hybrid cytoplasm affecting growth and metabolism.

Interspecies hybrids have nuclear contributions from two species but oocyte cytoplasm from only one. Species discordance may lead to altered nuclear reprogramming of the foreign paternal genome. We reasoned that initial reprogramming in same species cytoplasm plus creation of hybrids with zygote cytoplasm from both species, which we describe here, might enhance nuclear reprogramming and promote hybrid development. We report in Mus species that (i) mammalian nuclear/cytoplasmic hybrids can be created, (ii) they allow development and viability of a previously missing and uncharacterized hybrid class, (iii) different oocyte cytoplasm environments lead to different phenotypes of same nuclear hybrid genotype, and (iv) the novel hybrids exhibit sex ratio distortion with the absence of female progeny and represent a mammalian exception to Haldane's rule. Our results emphasize that interspecies hybrid phenotypes are not only the result of nuclear gene epistatic interactions but also cytonuclear interactions and that the latter have major impacts on fetal and placental growth and development.

Pi Class – A Revolutionary Step Forward in Hybrid Class Management System

The COVID-19 pandemic has caused widespread disruptions globally, resulting in a state of health emergency with numerous deaths reported and an overall implementation of quarantine and isolation. Strict lockdowns have been implemented to curb the spread of the virus, requiring social distancing and limiting physical interactions. These measures had far-reaching impacts on all aspects of life, including education. Education was one of the most affected sectors, with difficulty delivering quality education in schools, colleges, and universities. It was hard to provide quality education, a basic need of humanity. In this research paper, we propose an adequate solution to overcome the difficulties of maintaining educational quality during and after the COVID-19 pandemic and its multiple variants. The proposed solution is a hybrid model for an autonomous lecture recording system that facilitates students to attend physical classes and attend lectures virtually. The solution proposed is a cost-effective and convenient way for students to access lectures. The application involves hardware and software components that record and preserve lectures' audio and visual aspects. The system will allow lectures to be delivered directly to the students' devices. The major modules of the project include Python scripting, model training, UI/UX design, and app development.

Equity in hybrid microeconomics classes: Effects on diverse student groups

The Covid-19 pandemic created a sudden increased uptake of online teaching, and though the end of the pandemic signaled a shift back to more in-person learning, many schools have used the existing infrastructure to expand their offerings of online and hybrid courses. While previous studies have identified the impact of online teaching on student score, little work has been done on the heterogenous impact that online and hybrid teaching can have, particularly for underrepresented groups of students. I utilize a randomized control trial in an introductory microeconomics course to test whether there are any differences in quiz score with a lecture delivered online as compared to in-person, mimicking a hybrid class environment. I find that when students watch a lecture online, they score 5 percentage points lower on average than attending a lecture in-person. This estimate is based on an intent-to-treat study design and estimates within-individual effects. I also assess heterogeneous effects across various demographic variables, including gender, race, and First-Generation status, and find that this result is particularly salient for non-White and first-generation students, highlighting the equity implications of moving to online teaching.

The impact of global and regional challenges on the decrease in tourist flows

The article presents a comprehensive analysis of the impact of global and regional events on the dynamics of tourist flows. The primary reasons for the decrease in inbound tourist flows have been identified and categorized into three main groups: military-political class, economic class, and natural-technological class. Additionally, a hybrid class was identified, to which COVID-19 was assigned. The article is based on causal and comparative analysis, utilizing statistical data on tourist flows provided by the World Bank and UNWTO, as well as an assessment of similar patterns among countries worldwide. The main characteristics of tourist flows from 1995 to 2022 have been identified, pinpointing leaders among countries in increasing and decreasing the number of tourists per year. During the study, countries with similar patterns of tourist flow dynamics were identified. It was concluded that relying solely on quantitative analysis has limited applicability in identifying these patterns. Therefore, it is recommended that quantitative analysis be complemented with expert assessments for a more comprehensive understanding. The basic strategies for responding to the identified classes of causes were outlined. The research will benefit tourism professionals, governmental authorities, and researchers in socio-economic and political disciplines.

Hybrid Class Balancing Approach for Chemical Compound Toxicity Prediction.

Computational methods are crucial for efficient and cost-effective drug toxicity prediction. Unfortunately, the data used for prediction is often imbalanced, resulting in biased models that favor the majority class. This paper proposes an approach to apply a hybrid class balancing technique and evaluate its performance on computational models for toxicity prediction in Tox21 datasets. The process begins by converting chemical compound data structures (SMILES strings) from various bioassay datasets into molecular descriptors that can be processed by algorithms. Subsequently, Undersampling and Oversampling techniques are applied in two different schemes on the training data. In the first scheme (Individual), only one balancing technique (Oversampling or Undersampling) is used. In the second scheme (Hybrid), the training data is divided according to a ratio (e.g., 90-10), applying a different balancing technique to each proportion. We considered eight resampling techniques (four Oversampling and four Undersampling), six molecular descriptors (based on MACCS, ECFP, and Mordred), and five classification models (KNN, MLP, RF, XGB and SVM) over 10 bioassay datasets to determine the configurations that yield the best performance. We defined three testing scenarios: without balancing techniques (baseline), Individual, and Hybrid. We found that using the ENN technique in the MACCS-MLP combination resulted in a 10.01% improvement in performance. The increase for ECFP6-2048 was 16.47% after incorporating a combination of the SMOTE (10%) and RUS (90%) techniques. Meanwhile, using the same combination of techniques, MORDRED-XGB showed the most significant increase in performance, achieving a 22.62% improvement. Integrating any of the class balancing schemes resulted in a minimum of 10.01% improvement in prediction performance compared to the best baseline configuration. In this study, Undersampling techniques were more appropriate due to the significant overlap among samples. By eliminating specific samples from the predominant class that are close to the minority class, this overlap is greatly reduced.

ON THE WAY WITH FRAMEWORK CURRICULA TOWARDS FOREIGN LANGUAGE TEACHING AT NON-PHILOLOGICAL FACULTIES FROM TOMORROW

The aim of our contribution is to show how the framework curricula for the teaching of German and foreign languages which were developed in ten countries during a project for cross-curricular university language education in the period 1998-2014 can support teachers, even under difficult circumstances such as during the pandemic. The holistic approach of these curricula leads teachers to create teaching materials which allow their students to enjoy learning and to develop not only their linguistic, but also methodological, social and personal competences relevant to their future careers. Teaching examples from online classes at Bocconi University (Italy) and hybrid classes at the University in Novi Sad, (Serbia) are presented, which prove that the motivation and creativity of learners, who often perceive professional and technical language as something dry and overly factual, can be stimulated by appropriate working methods and targeted teaching materials. Appropriate teaching materials can be created for German classes as well as for any other foreign language classes, since the indications of principles, objectives, contents and procedures contained in the framework curricula are cross-linguistic and are not bound to the teaching of a single language, although they have been written in German by German lecturers.

Influence of hybrid class and ensiling duration on deoxynivalenol accumulation and its derivative deoxynivalenol-3-glucoside while ensiling corn for silage.

In silage corn (Zea mays L.), Fusarium graminearum causes diseases and produces the mycotoxin deoxynivalenol (DON). The work presented here investigated DON accumulation and its fate during the ensiling of ground, whole-plant material obtained from dual-purpose (DP) and brown midrib (BMR) corn hybrids. Multi-year field trials arranged in a randomized complete block design were conducted in Wisconsin to evaluate BMR and DP corn hybrids in response to fungicide treatment. At harvest, the samples were chopped and vacuum sealed for a mini-silo time series assessment with silos opened following anaerobic fermentation for 0, 30, 60, 90 and 120 days. Repeated measures analysis of ensiled corn showed that hybrid (P < 0.01) and ensiling duration (P < 0.01) significantly impacted DON concentration through ensiling, while fungicide treatment had no significant effect (P > 0.05). Across hybrids and treatments, DON concentrations detected at harvest were the lowest with DON3G at harvest significantly (P < 0.01) and highly correlated (r = 0.74) with DON concentration 30-days post ensiling. These findings suggest that mycotoxin testing in corn should include not only DON but also for conjugates of DON that can be metabolized back to DON and increase the final DON concentration during ensiling.

A global argument-based algorithm for finding complex zeros and poles to investigate plasma kinetic instabilities

Root-finding is a common problem in various fields of physics and mathematics. The basic version of this problem can be formulated as an equation f(z)=0 where z∈ℂ and f is a meromorphic function on a complex plane ℂ. In some cases, a conjugated problem has to be solved as well to investigate the properties of the inspected system: f(z)−1=0. Iterative Householder-like methods show high convergence rate, however, the convergence itself is strongly dependent on the input parameters such as an initial guess. If the function f is complicated enough, there can be no prior information about its zeros and poles, and thus, no way to correctly pick the initial guess. The aim of the algorithm proposed in this article is to find all zeros and poles inside a selected region without any information about the local behavior of the function f. Additionally, the method is generalized to a parametric problem with continuous solutions: f(z)→f(z;p) where p∈Rd, d∈N∪{0}. The basis of the algorithm consists of a triangulation process and an implementation of the Cauchy’s argument principle to inspect the constructed subregions. The refinement process is accompanied by an absolute value gradient ∇ln|f| analysis that significantly decreases the number of points needed to correctly identify the locations of all zeros and poles. The algorithm is presented as a hybrid class for d∈{0,1} that can be directly used to solve corresponding problems.

Guaranteed cost control for a class of composite hybrid aerial/terrestrial precise manipulator with stochastic switching payloads

AbstractThis article investigates the modeling and attitude control of a class of composite hybrid aerial/terrestrial precise manipulator (Chat‐PM) with stochastic switching payloads when attaching to a vertical surface. The dynamics of the Chat‐PM for aerial locomotion are modeled by transferring the force and moment of the end‐effector to the body based on the recursive Newton–Euler equations. Furthermore, the attitude dynamics of the Chat‐PM under the wall‐attachment condition is obtained by limiting the attitude angle/angular velocity and introducing the friction torque acting on the passive wheels for the first time. Taking into consideration the complexity of the task and the stochastic nature of environmental changes, the payload attached to the end‐effector is modeled as a continuous‐time Markov process with mode‐dependent fixed sojourn time in this study. The proposed guaranteed cost controller results in the Chat‐PM capable of stably attaching to a wall under random switching loads, while guaranteeing the quadratic performance cost with an attainable upper bound. Additionally, a convex‐optimization‐based guaranteed cost controller is proposed to optimize the performance cost in the random switching part. Finally, the effectiveness of the proposed guaranteed cost controllers is demonstrated by illustrative examples.

The Role of Technological Knowledge on Student Engagement on Senior High School Students

This study examines the impact of technological knowledge on student engagement among senior high school students, focusing on the challenges posed by the Covid-19 pandemic. Technological knowledge is defined as individuals; proficiency in utilizing various information technologies to complete tasks. Student engagement is characterized by active participation in teaching and learning activities, leading to improved learning outcomes. The research addresses the concerning issue of low student engagement observed during the pandemic and investigates the potential of technological knowledge to foster increased engagement. The study includes a sample of 270 students selected through a non-probability random sampling method. Multiple regression analysis is employed to assess the relationship between variables. The findings reveal a significant positive influence of technological knowledge on student engagement. Furthermore, a comparison test indicates that grade 10 students exhibit higher levels of both technological knowledge and student engagement. Online class students demonstrate greater technological knowledge, while hybrid class students display higher emotional engagement. This study contributes valuable insights for enhancing student engagement through technological knowledge in the context of senior high school education during the pandemic.

Multifunctional Molecular Hybrids Photoreleasing Nitric Oxide: Advantages, Pitfalls, and Opportunities.

The multifaceted role nitric oxide (NO) plays in human physiology and pathophysiology has opened new scenarios in biomedicine by exploiting this free radical as an unconventional therapeutic against important diseases. The difficulties in handling gaseous NO and the strict dependence of the biological effects on its doses and location have made the light-activated NO precursors, namely NO photodonors (NOPDs), very appealing by virtue of their precise spatiotemporal control of NO delivery. The covalent integration of NOPDs and additional functional components within the same molecular skeleton through suitable linkers can lead to an intriguing class of multifunctional photoactivatable molecular hybrids. In this Perspective, we provide an overview of the recent advances in these molecular constructs, emphasizing those merging NO photorelease with targeting, fluorescent reporting, and phototherapeutic functionalities. We will highlight the rational design behind synthesizing these molecular hybrids and critically describe the advantages, drawbacks, and opportunities they offer in biomedical research.

Post-Pandemic Evaluation: Impact of Covid-19 Pandemic on Medical Students’ Mental Health, Self-Esteem, Social Interactions, and Academic Progression in Malaysia

Covid-19 pandemic has brought drastic and unprecedented challenges to the medical education and medical students, affecting them physically, mentally and emotionally. While progressing through the post-pandemic recovery phase, it is crucial to comprehensively evaluate the pandemic’s consequences and tackle the underlying problems. To investigate the impact of Covid-19 pandemic on medical students’ mental health, social well-being, and academic progression. A cross-sectional study was carried out with voluntary sampling of students from both government and private medical schools in Malaysia. A self-administered online survey form containing three validated psychological tools was distributed (Hospital Anxiety and Depression Scale HADS, Rosenberg Self-esteem Scale, NIH Toolbox Social Relationship Scales). There were also questions regarding the challenges faced by medical students and their academic performance during Covid-19 pandemic. Scores of each questionnaire were tabulated, analyzed and interpreted according to their specific cut-points. Two hundred and thirteen responses were received. 89.2% (n = 190) were domestic students while 10.8% (n = 23) were international students. Out of 32 medical universities in Malaysia, the participants were from 19 of them (9 public and 10 private universities). About half of the participants had contracted Covid-19 infection during the study period (n = 124, 58.2%). Majority had chosen “Lack of on-campus learning and training session causing incompetency” as the most relevant impact of Covid-19 on their academic progression (n = 85, 39.9%). Above 90% of participants passed their Final Academic Assessment in 2020 (91.5%) and 2021 (93.9%). About half of them (n = 86, 40.4%) were having symptoms considerable of anxiety while only 19.2% (n = 41) were having symptoms considerable of depression. Majority had normal self-esteem (n = 177, 83.1%). For social relationship, around two-third of them had great social support and companionship. However, more than half had social distress. The median for the period of time having absolute online classes, absolute physical classes and hybrid classes were 18, 4, and 9 months, respectively. Having absolute online classes of &gt;18 months was associated significantly with higher perceived hostility (16.49vs. 14.47, p = .012). In addition, being infected with Covid-19 was associated significantly with higher self-esteem (26.88vs. 25.85, p = .009). Large proportion of students were affected by Covid-19 pandemic. Absolute online classes has huge impact on emotions of medical students especially from the aspect of perceived hostility. Hence, implementation of online medical education during Covid-19 era requires modifications and improvements.

EKMGS: A HYBRID CLASS BALANCING METHOD FOR MEDICAL DATA PROCESSING

The field of medicine is witnessing rapid development of AI, highlighting the importance of proper data processing. However, when working with medical data, there is a problem of class imbalance, where the amount of data about healthy patients significantly exceeds the amount of data about sick ones. This leads to incorrect classification of the minority class, resulting in inefficient operation of machine learning algorithms. In this study, a hybrid method was developed to address the problem of class imbalance, combining oversampling (GenSMOTE) and undersampling (ENN) algorithms. GenSMOTE used frequency oversampling optimization based on a genetic algorithm, selecting the optimal value using a fitness function. The next stage implemented an ensemble method based on stacking, consisting of three base (k-NN, SVM, LR) and one meta-model (Decision Tree). The hyperparameters of the meta-model were optimized using the GridSearchCV algorithm. During the study, datasets on diabetes, liver diseases, and brain glioma were used. The developed hybrid class balancing method significantly improved the quality of the model: the F1-score increased by 10-75%, and accuracy by 5-30%. Each stage of the hybrid algorithm was visualized using a nonlinear UMAP algorithm. The ensemble method based on stacking, in combination with the hybrid class balancing method, demonstrated high efficiency in solving classification tasks in medicine. This approach can be applied for diagnosing various diseases, which will increase the accuracy and reliability of forecasts. It is planned to expand the application of this approach to large volumes of data and improve the oversampling algorithm using additional capabilities of the genetic algorithm.

Sliding Mode Control of a Class of Hybrid-Switched Systems with Disturbances

This paper investigates the problem of sliding mode control for a class of hybrid switched systems with matching disturbances. Firstly, a sliding mode surface is designed, and the corresponding sliding mode equation for the switched system is derived. Then, we analyzed the stability of the sliding mode equation using the Lyapunov function and average dwell time. Moreover, a sliding mode control law is designed with the approach law method to drive the system state to a bounded sliding mode region and then maintain it there subsequently. Finally, an illustrative example is given to demonstrate the efficiency of the approach.

Linking the UN sustainable development goals to life cycle impact applied to a university campus

Purpose The study aims to explore the relationship between the SDGs and the environmental and social impacts of university classes. It evaluates the potential contributions of different teaching models to the SDGs, providing insights into sustainable teaching systems. Findings In-person classes exhibited hotspots in transportation and energy consumption. Scenarios I and II, involving virtual and hybrid classes, increased eutrophication potential and water scarcity due to higher food consumption, negatively impacting SDGs. However, all scenarios showed positive contributions to SDGs 2, 3, 6, 9, 11, 12, 13, 14 and 15. Design/methodology/approach This research integrates Life Cycle Assessment (LCA) with the United Nations Sustainable Development Goals (SDGs) to assess the environmental and social impacts of classes at the Federal University of São Carlos, Sorocaba campus in Brazil. Three scenarios were analyzed: (I) virtual classes, (II) hybrid classes and (III) in-person classes with improved energy efficiency. Research limitations/implications The study primarily focuses on environmental and social impacts, excluding other factors like class quality. Integrating Life Cycle Costing and Life Cycle Sustainability Assessment could provide a more holistic evaluation in the future. Practical implications The methodology adopted offers valuable insights for managing the impacts of university performance and aligning teaching systems with the SDGs. It enables institutions to make informed decisions for sustainability in education. Social implications The research emphasizes the importance of considering social impacts alongside environmental ones when assessing sustainability in educational institutions. It encourages universities to engage stakeholders in sustainability efforts. Originality/value This research innovatively combines LCA and the SDGs in the context of university education providing a replicable methodology for evaluating and enhancing sustainability in teaching systems and from a more quantitative perspective.

Effect of Fungicide Application and Corn Hybrid Class on the Presence of Fusarium graminearum and the Concentration of Deoxynivalenol in Ear and Stalk Parts of Corn (Zea mays) Used for Silage.

In Wisconsin, the use of brown midrib (BMR) corn (Zea mays) hybrids for ensiling and subsequent feeding to dairy cows is quite common. The overall milk production from cows fed silage from BMR hybrids is typically higher than those fed silage made from dual-purpose hybrids. Gibberella diseases (ear and stalk rot) caused by Gibberella zeae (anamorph; Fusarium graminearum) and the accompanying accumulation of the mycotoxin deoxynivalenol (DON) can be significant issues during the field production of BMR hybrids. The work presented here aimed to understand the role of hybrid class on the distribution of F. graminearum DNA and DON in the ear and stalk parts of corn for silage. An ear and stalk partitioned sample experiment was conducted on silage corn from field trials in Arlington, Wisconsin, in 2020 and 2021. The trials were arranged in a randomized complete block design in both years, including one BMR hybrid, one dual-purpose hybrid, and seven fungicide application regimes. Paired ear and stalk samples were physically separated, dried, and ground at harvest before determining the concentration of F. graminearum DNA and DON in each sample. Across both years, the main effects of hybrid, treatment, and plant part were not significant (P > 0.1) on DON concentration. However, the hybrid-by-plant part interaction effect was significant (P < 0.01). Ears of the BMR hybrid accumulated the most DON, whereas the dual-purpose hybrid ears had the lowest DON concentration. The concentrations of DON and F. graminearum DNA were significantly (P < 0.01) and highly correlated in the ear (r = 0.73) but not in the stalk (r = 0.09, P = 0.33). These findings suggest that DON accumulation in the corn ear is a major contributor in the difference observed in the total DON between the hybrid classes. Therefore, growers and researchers are encouraged to focus production and breeding on hybrids in both classes that accumulate less DON in ears, resulting in lower total DON in corn chopped for silage.

Hybrids Diazine: Recent Advancements in Modern Antimicrobial Therapy.

Nowadays, antimicrobial therapies have become a very challenging issue because of a large diversity of reasons such as antimicrobial resistance, over consumption and misuse of antimicrobial agents, etc. A modern, actual and very useful approach in antimicrobial therapy is represented by the use of hybrid drugs, especially combined five and six-membered ring azaheterocycles. In this review, we present an overview of the recent advanced data from the last five years in the field of hybrid diazine compounds with antimicrobial activity. In this respect, we highlight here essential data concerning the synthesis and antimicrobial activity of the main classes of diazine hybrids: pyridazine, pyrimidine, pyrazine, and their fused derivatives.

New insides into chimeric and hybrid azines derivatives with antifungal activity.

During the last decades, five or six member rings azaheterocycles compounds appear to be an extremely valuable source of antifungal agents. Their use seems to be a very attractive solution in antifungal therapy and to overcome antifungal resistance in agriculture. The present review highlights the main results obtained in the field of hybrid and chimeric azine (especially pyridine, quinoline, phenanthroline, bypyridine, naphthyridine and their fused derivatives) derivatives presented in scientific literature from the last 10 years, with emphasis on antifungal activity of the mentioned compounds. A special attention was played to hybrid and chimeric azole-azine class, having in view the high antifungal potential of azoles.