Research papers

Teaching and Learning Physics in Senior High Schools in Ghana: The Challenges and the Way Forward

Isaac Sonful Coffie, Bans Bandoh Frempong, Eric Appiah

Aim: Considering the technological age that we find ourselves in this 21st century, it would be expected that, the number of students willing to study physics will increase exponentially. However, reports indicate a sharp reduction of students in physics classrooms. This study therefore sought to identify the challenges and way forward for improving physics teaching and learning in Senior High Schools in Ghana. Study Design: Descriptive cross-sectional survey was used for the study. Methodology: The main instrument used for the study was questionnaire. The sample size for the study comprised both physics teachers and students. The sample size for the teachers was made up of 38 teachers which comprised 34 males and 4 females who were selected using the convenient sampling approach. The sample size for the students consisted of 750 students selected by stratified sampling of which 520 were males and 230 were females. Results: While the teachers perceived the most important factor affecting the teaching and learning of physics to be students-related problem, the students on the other hand perceived the major challenge affecting the teaching and learning of physics to be teacher-related. For both teachers and students, provision of adequate resources like well-equipped laboratories for teaching and learning is an assured way of improving the teaching and learning of physics in senior high schools in Ghana. Conclusions: The challenges in teaching physics as perceived by both teachers and students are teacher related, student-related and resource-constraints It was recommended that the government must make conscious effort to provide the schools with adequate science resources to facilitate the practical approach to teaching and learning of physics.

Incivility among nursing faculty: A multi-country study

Mohammed Baqer Al‐Jubouri, Patience E. Samson‐Akpan, Sadeq AL‐Fayyadh, Felipe Machuca‐Contreras, Brigid Unim, Srđjan Stefano…

A conceptual map of invasion biology: Integrating hypotheses into a consensus network

Martin Enders, Frank Havemann, Florian Ruland, Maud Bernard‐Verdier, Jane A. Catford, Lorena Gómez‐Aparicio, Sylvia Haider, …

Abstract Background and aims Since its emergence in the mid‐20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied importance. Not only has the number of empirical studies increased through time, but also has the number of competing, overlapping and, in some cases, contradictory hypotheses about biological invasions. To make these contradictions and redundancies explicit, and to gain insight into the field’s current theoretical structure, we developed and applied a Delphi approach to create a consensus network of 39 existing invasion hypotheses. Results The resulting network was analysed with a link‐clustering algorithm that revealed five concept clusters (resource availability, biotic interaction, propagule, trait and Darwin’s clusters) representing complementary areas in the theory of invasion biology. The network also displays hypotheses that link two or more clusters, called connecting hypotheses , which are important in determining network structure. The network indicates hypotheses that are logically linked either positively (77 connections of support) or negatively (that is, they contradict each other; 6 connections). Significance The network visually synthesizes how invasion biology’s predominant hypotheses are conceptually related to each other, and thus, reveals an emergent structure – a conceptual map – that can serve as a navigation tool for scholars, practitioners and students, both inside and outside of the field of invasion biology, and guide the development of a more coherent foundation of theory. Additionally, the outlined approach can be more widely applied to create a conceptual map for the larger fields of ecology and biogeography.

Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019

Jianbo Lai, Simeng Ma, Ying Wang, Zhongxiang Cai, Jianbo Hu, Ning Wei, Jiang Wu, Hui Du, Tingting Chen, Ruiting Li, Huawei T…

Importance: Health care workers exposed to coronavirus disease 2019 (COVID-19) could be psychologically stressed. Objective: To assess the magnitude of mental health outcomes and associated factors among health care workers treating patients exposed to COVID-19 in China. Design, Settings, and Participants: This cross-sectional, survey-based, region-stratified study collected demographic data and mental health measurements from 1257 health care workers in 34 hospitals from January 29, 2020, to February 3, 2020, in China. Health care workers in hospitals equipped with fever clinics or wards for patients with COVID-19 were eligible. Main Outcomes and Measures: The degree of symptoms of depression, anxiety, insomnia, and distress was assessed by the Chinese versions of the 9-item Patient Health Questionnaire, the 7-item Generalized Anxiety Disorder scale, the 7-item Insomnia Severity Index, and the 22-item Impact of Event Scale-Revised, respectively. Multivariable logistic regression analysis was performed to identify factors associated with mental health outcomes. Results: A total of 1257 of 1830 contacted individuals completed the survey, with a participation rate of 68.7%. A total of 813 (64.7%) were aged 26 to 40 years, and 964 (76.7%) were women. Of all participants, 764 (60.8%) were nurses, and 493 (39.2%) were physicians; 760 (60.5%) worked in hospitals in Wuhan, and 522 (41.5%) were frontline health care workers. A considerable proportion of participants reported symptoms of depression (634 [50.4%]), anxiety (560 [44.6%]), insomnia (427 [34.0%]), and distress (899 [71.5%]). Nurses, women, frontline health care workers, and those working in Wuhan, China, reported more severe degrees of all measurements of mental health symptoms than other health care workers (eg, median [IQR] Patient Health Questionnaire scores among physicians vs nurses: 4.0 [1.0-7.0] vs 5.0 [2.0-8.0]; P = .007; median [interquartile range {IQR}] Generalized Anxiety Disorder scale scores among men vs women: 2.0 [0-6.0] vs 4.0 [1.0-7.0]; P < .001; median [IQR] Insomnia Severity Index scores among frontline vs second-line workers: 6.0 [2.0-11.0] vs 4.0 [1.0-8.0]; P < .001; median [IQR] Impact of Event Scale-Revised scores among those in Wuhan vs those in Hubei outside Wuhan and those outside Hubei: 21.0 [8.5-34.5] vs 18.0 [6.0-28.0] in Hubei outside Wuhan and 15.0 [4.0-26.0] outside Hubei; P < .001). Multivariable logistic regression analysis showed participants from outside Hubei province were associated with lower risk of experiencing symptoms of distress compared with those in Wuhan (odds ratio [OR], 0.62; 95% CI, 0.43-0.88; P = .008). Frontline health care workers engaged in direct diagnosis, treatment, and care of patients with COVID-19 were associated with a higher risk of symptoms of depression (OR, 1.52; 95% CI, 1.11-2.09; P = .01), anxiety (OR, 1.57; 95% CI, 1.22-2.02; P < .001), insomnia (OR, 2.97; 95% CI, 1.92-4.60; P < .001), and distress (OR, 1.60; 95% CI, 1.25-2.04; P < .001). Conclusions and Relevance: In this survey of heath care workers in hospitals equipped with fever clinics or wards for patients with COVID-19 in Wuhan and other regions in China, participants reported experiencing psychological burden, especially nurses, women, those in Wuhan, and frontline health care workers directly engaged in the diagnosis, treatment, and care for patients with COVID-19.

Comparative Molecular Biology Approaches for the Production of Poliovirus Virus-Like Particles Using <i>Pichia pastoris</i>

Lee Sherry, Keith Grehan, Joseph S. Snowden, Michael L. Knight, Oluwapelumi O. Adeyemi, David J. Rowlands, Nicola J. Stoneho…

Although the current poliovirus immunization program has been extremely successful in reducing the number of cases of paralytic polio worldwide, now more cases are caused by vaccine-derived polioviruses than by wild poliovirus. Switching to inactivated poliovirus vaccines will reduce this over time; however, their production requires the growth of large amounts of virus. This biosafety concern can be addressed by producing just the virus capsid. The capsid serves to protect the genetic material, which causes disease when introduced into a cell. Therefore, empty capsids (virus-like particles [VLPs]), which lack the viral RNA genome, are safe both to make and to use. We exploit yeast as a versatile model expression system to produce VLPs, and here we specifically highlight the potential of this system to supply next-generation poliovirus vaccines to secure a polio-free world for the future.

Functional Biology and Molecular Mechanisms of Host-Pathogen Interactions for Aflatoxin Contamination in Groundnut (Arachis hypogaea L.) and Maize (Zea mays L.)

Pooja Soni, Sunil S. Gangurde, Alejandro Ortega‐Beltran, Rakesh Kumar, Sejal Parmar, Hari Kishan Sudini, Yong Lei, Xinzhi Ni…

and closely related species that infect several agricultural commodities including groundnut and maize. The consumption of contaminated commodities adversely affects the health of humans and livestock. Aflatoxin contamination also causes significant economic and financial losses to producers. Research efforts and significant progress have been made in the past three decades to understand the genetic behavior, molecular mechanisms, as well as the detailed biology of host-pathogen interactions. A range of omics approaches have facilitated better understanding of the resistance mechanisms and identified pathways involved during host-pathogen interactions. Most of such studies were however undertaken in groundnut and maize. Current efforts are geared toward harnessing knowledge on host-pathogen interactions and crop resistant factors that control aflatoxin contamination. This study provides a summary of the recent progress made in enhancing the understanding of the functional biology and molecular mechanisms associated with host-pathogen interactions during aflatoxin contamination in groundnut and maize.

COVID-19: towards controlling of a pandemic

Juliet Bedford, Delia Enría, Johan Giesecke, David L Heymann, Chikwe Ihekweazu, Gary Kobinger, H. Clifford Lane, Ziad A. Mem…

The biology of ergothioneine, an antioxidant nutraceutical

Irina Borodina, Louise C. Kenny, Cathal McCarthy, Kalaivani Paramasivan, Etheresia Pretorius, Timothy J. Roberts, Steven A. …

Ergothioneine (ERG) is an unusual thio-histidine betaine amino acid that has potent antioxidant activities. It is synthesised by a variety of microbes, especially fungi (including in mushroom fruiting bodies) and actinobacteria, but is not synthesised by plants and animals who acquire it via the soil and their diet, respectively. Animals have evolved a highly selective transporter for it, known as solute carrier family 22, member 4 (SLC22A4) in humans, signifying its importance, and ERG may even have the status of a vitamin. ERG accumulates differentially in various tissues, according to their expression of SLC22A4, favouring those such as erythrocytes that may be subject to oxidative stress. Mushroom or ERG consumption seems to provide significant prevention against oxidative stress in a large variety of systems. ERG seems to have strong cytoprotective status, and its concentration is lowered in a number of chronic inflammatory diseases. It has been passed as safe by regulatory agencies, and may have value as a nutraceutical and antioxidant more generally.

The biology <b>,</b> function <b>,</b> and biomedical applications of exosomes

Raghu Kalluri, Valerie S. LeBleu

The study of extracellular vesicles (EVs) has the potential to identify unknown cellular and molecular mechanisms in intercellular communication and in organ homeostasis and disease. Exosomes, with an average diameter of ~100 nanometers, are a subset of EVs. The biogenesis of exosomes involves their origin in endosomes, and subsequent interactions with other intracellular vesicles and organelles generate the final content of the exosomes. Their diverse constituents include nucleic acids, proteins, lipids, amino acids, and metabolites, which can reflect their cell of origin. In various diseases, exosomes offer a window into altered cellular or tissue states, and their detection in biological fluids potentially offers a multicomponent diagnostic readout. The efficient exchange of cellular components through exosomes can inform their applied use in designing exosome-based therapeutics.

Holography for tensor models

Robert de Mello Koch, David Gossman, Nirina Hasina Tahiridimbisoa, Augustine Larweh Mahu

In this article we explore the holographic duals of tensor models using collective field theory. We develop a description of the gauge invariant variables of the tensor model. This is then used to develop a collective field theory description of the dynamics. We consider matrixlike subsectors that develop an extra holographic dimension. In particular, we develop the collective field theory for the matrixlike sector of an interacting tensor model. We check the correctness of the large $N$ collective field by showing that it reproduces the perturbative expansion of large $N$ expectation values. In contrast to this, we argue that melonic large $N$ limits do not develop an extra dimension. This conclusion follows from the large $N$ value for the melonic collective field, which has delta function support. The finite $N$ physics of the model is also developed and nonperturbative effects in the $1/N$ expansion are exhibited.

SciPy 1.0: fundamental algorithms for scientific computing in Python

Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Pete…

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

Radiological Safety Analysis for a Hypothetical Accident of a Generic VVER-1000 Nuclear Power Plant

Kwame Gyamfi, S.A. Birikorang, Emmanuel Ampomah-Amoako, J. J. Fletcher

Atmospheric dispersion modelling and radiological safety analysis have been performed for a postulated accident scenario of a generic VVER-1000 nuclear power plant using the HotSpot Health Physics code. The total effective dose equivalent (TEDE), the respiratory time-integrated air concentration, and the ground deposition concentration are calculated considering site-specific meteorological conditions. The results show that the maximum TEDE and ground deposition concentration values of 3.69 E – 01 Sv and 3.80 E + 06 kBq/m 2 occurred at downwind distance of 0.18 km from the release point. This maximum TEDE value is recorded within a distance where public occupation is restricted. The TEDE values at distances of 5.0 km and beyond where public occupation is likely to be found are far below the annual regulatory limits of 1 mSv from public exposure in a year even in the event of worse accident scenario as set in IAEA Safety Standard No. GSR Part 3; no action related specifically to the public exposure is required. The released radionuclides might be transported to long distances but will not have any harmful effect on the public. The direction of the radionuclide emission from the release point is towards the north east. It is observed that the organ with the highest value of committed effective dose equivalent (CEDE) appears to be the thyroid. It was followed by the bone surface, lung, red marrow, and lower large intestine wall in order of decreasing CEDE value. Radionuclides including I-131, I-133, Sr-89, Cs-134, Ba-140, Xe-133, and Xe-135 were found to be the main contributors to the CEDE.

The role of artificial intelligence in achieving the Sustainable Development Goals

Ricardo Vinuesa, Hossein Azizpour, Iolanda Leite, Madeline Balaam, Virginia Dignum, Sami Domisch, Anna Felländer, Simone D. …

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards.

The Rock Physics Handbook

Gary Mavko, Tapan Mukerji, Jack Dvorkin

Responding to the latest developments in rock physics research, this popular reference book has been thoroughly updated while retaining its comprehensive coverage of the fundamental theory, concepts, and laboratory results. It brings together the vast literature from the field to address the relationships between geophysical observations and the underlying physical properties of Earth materials - including water, hydrocarbons, gases, minerals, rocks, ice, magma and methane hydrates. This third edition includes expanded coverage of topics such as effective medium models, viscoelasticity, attenuation, anisotropy, electrical-elastic cross relations, and highlights applications in unconventional reservoirs. Appendices have been enhanced with new materials and properties, while worked examples (supplemented by online datasets and MATLAB® codes) enable readers to implement the workflows and models in practice. This significantly revised edition will continue to be the go-to reference for students and researchers interested in rock physics, near-surface geophysics, seismology, and professionals in the oil and gas industries.

Preparation of Medicinal Plants: Basic Extraction and Fractionation Procedures for Experimental Purposes

AbdullahiR Abubakar, Mainul Haque

Preparation of medicinal plants for experimental purposes is an initial step and key in achieving quality research outcome. It involves extraction and determination of quality and quantity of bioactive constituents before proceeding with the intended biological testing. The primary objective of this study was to evaluate various methods used in the preparation and screening of medicinal plants in our daily research. Although the extracts, bioactive fractions, or compounds obtained from medicinal plants are used for different purposes, the techniques involved in producing them are generally the same irrespective of the intended biological testing. The major stages included in acquiring quality bioactive molecule are the selection of an appropriate solvent, extraction methods, phytochemical screening procedures, fractionation methods, and identification techniques. The nitty-gritty of these methods and the exact road map followed solely depends on the research design. Solvents commonly used in extraction of medicinal plants are polar solvent (e.g., water, alcohols), intermediate polar (e.g., acetone, dichloromethane), and nonpolar (e.g., n-hexane, ether, chloroform). In general, extraction procedures include maceration, digestion, decoction, infusion, percolation, Soxhlet extraction, superficial extraction, ultrasound-assisted, and microwave-assisted extractions. Fractionation and purification of phytochemical substances are achieved through application of various chromatographic techniques such as paper chromatography, thin-layer chromatography, gas chromatography, and high-performance liquid chromatography. Finally, compounds obtained are characterized using diverse identification techniques such as mass spectroscopy, infrared spectroscopy, ultraviolet spectroscopy, and nuclear magnetic resonance spectroscopy. Subsequently, different methods described above can be grouped and discussed according to the intended biological testing to guide young researchers and make them more focused.

Artificial Intelligence in Education: A Review

Lijia Chen, Pingping Chen, Zhijian Lin

The purpose of this study was to assess the impact of Artificial Intelligence (AI) on education. Premised on a narrative and framework for assessing AI identified from a preliminary analysis, the scope of the study was limited to the application and effects of AI in administration, instruction, and learning. A qualitative research approach, leveraging the use of literature review as a research design and approach was used and effectively facilitated the realization of the study purpose. Artificial intelligence is a field of study and the resulting innovations and developments that have culminated in computers, machines, and other artifacts having human-like intelligence characterized by cognitive abilities, learning, adaptability, and decision-making capabilities. The study ascertained that AI has extensively been adopted and used in education, particularly by education institutions, in different forms. AI initially took the form of computer and computer related technologies, transitioning to web-based and online intelligent education systems, and ultimately with the use of embedded computer systems, together with other technologies, the use of humanoid robots and web-based chatbots to perform instructors' duties and functions independently or with instructors. Using these platforms, instructors have been able to perform different administrative functions, such as reviewing and grading students' assignments more effectively and efficiently, and achieve higher quality in their teaching activities. On the other hand, because the systems leverage machine learning and adaptability, curriculum and content has been customized and personalized in line with students' needs, which has fostered uptake and retention, thereby improving learners experience and overall quality of learning.

Influence of Teacher-Centered and Student-Centered Teaching Methods on the Academic Achievement of Post-Basic Students in Biology in Delta State, Nigeria

Ezurike Chidubem Precious, Ayo-Vaughan Adewunmi Feyisetan

Teaching methods are essential for effective teaching and learning and to a great extent influence academic achievement of students. The objective of this study therefore was to examine the influence of teaching methods on the academic achievement of senior secondary school students in Biology in Oshimili South Local Government Area of Delta State. The descriptive survey research method was adopted in the study. Two research questions were formulated to guide the study. The population of the study comprised 1,550 biology students in public schools in Oshimili South Local Government Area of Delta State. Simple random sampling technique was used to select forty biology students from five randomly selected schools making it a total of two hundred (200) students. A questionnaire titled “Influence of Teaching Methods on Students' Academic Achievement in Biology Questionnaire (ITMSAABQ) was the main instrument for data collection. Cronbach Alpha analysis was used to test for the reliability of the instrument and it was found reliable with a reliability co-efficient of 0.75. Data collected was analyzed using descriptive statistics of frequency counts, percentages, mean, and standard deviation. Findings from the study revealed that student-centered teaching method increases students’ academic achievement while teacher-centered teaching methods decreases students' academic achievement in biology. The study recommended that teachers should create an environment that will enable students participate fully in the teaching-learning process of biology. Also, State Education Boards should organize seminars to educate biology teachers on the need for and how to use innovative methods in teaching biology.

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

Alejandro Barredo Arrieta, Natalia Díaz-Rodríguez, Javier Del Ser, Adrien Bennetot, Siham Tabik, Alberto Barbado, Salvador G…

XAI—Explainable artificial intelligence

David Gunning, Mark Stefik, Jaesik Choi, Tim Miller, Simone Stumpf, Guang‐Zhong Yang

Explainability is essential for users to effectively understand, trust, and manage powerful artificial intelligence applications.

EXAMINING THE EFFECTIVENESS OF SIMULATION-BASED LESSONS IN IMPROVING THE TEACHING OF HIGH SCHOOL PHYSICS: GHANAIAN PRE SERVICE TEACHERS’ EXPERIENCES

Elizabeth Darko Agyei, Thuthukile Jita, Loyiso C. Jita

Teacher-dominated approach is still the most adopted teaching strategy in Ghanaian high schools despite the Government of Ghana’s initiatives to support technology-oriented, learner-centred and interactive teaching practices. This study examined the effectiveness of simulation-based lessons in improving the teaching of high school physics by adapting the five dimensions for meaningful learning with information and communication technology model by Howland, Jonassen and Marra (2012) as a theoretical lens. Using an explanatory case study design, eight pre-service physics teachers from the University of Cape Coast, Ghana were engaged to develop and design simulation-based physics lessons in design teams and enact these lessons among themselves in microteaching sessions. Results showed that the simulation-based lessons were effective in that the pre-service teachers’ teaching practices improved to be learner-centred and interactive. The results also suggested that although a combination of all the dimensions of meaningful learning was key to the effectiveness observed with each of the simulation-based lessons, the Cooperative dimension was found to possess a unique potential for sustaining the other dimensions in order to facilitate improvements in the teaching of physics with simulations. Keywords: high school physics, ICT, interactive teaching, pre-service teachers, simulation-based lessons.

Contrasting Computational Models of Mate Preference Integration Across 45 Countries

Daniel Conroy‐Beam, David M. Buss, Kelly Asao, Agnieszka Sorokowska, Piotr Sorokowski, Toivo Aavik, Grace Akello, Mohammad M…

Humans express a wide array of ideal mate preferences. Around the world, people desire romantic partners who are intelligent, healthy, kind, physically attractive, wealthy, and more. In order for these ideal preferences to guide the choice of actual romantic partners, human mating psychology must possess a means to integrate information across these many preference dimensions into summaries of the overall mate value of their potential mates. Here we explore the computational design of this mate preference integration process using a large sample of n = 14,487 people from 45 countries around the world. We combine this large cross-cultural sample with agent-based models to compare eight hypothesized models of human mating markets. Across cultures, people higher in mate value appear to experience greater power of choice on the mating market in that they set higher ideal standards, better fulfill their preferences in choice, and pair with higher mate value partners. Furthermore, we find that this cross-culturally universal pattern of mate choice is most consistent with a Euclidean model of mate preference integration.

Global guideline for the diagnosis and management of mucormycosis: an initiative of the European Confederation of Medical Mycology in cooperation with the Mycoses Study Group Education and Research Consortium

Oliver A. Cornely, Ana Alastruey‐Izquierdo, Dorothee Arenz, Sharon C.‐A. Chen, Éric Dannaoui, Bruno Hochhegger, Martin Hoeni…

Systematic review of research on artificial intelligence applications in higher education – where are the educators?

Olaf Zawacki‐Richter, Victoria I. Marín, Melissa Bond, Franziska Gouverneur

Abstract According to various international reports, Artificial Intelligence in Education (AIEd) is one of the currently emerging fields in educational technology. Whilst it has been around for about 30 years, it is still unclear for educators how to make pedagogical advantage of it on a broader scale, and how it can actually impact meaningfully on teaching and learning in higher education. This paper seeks to provide an overview of research on AI applications in higher education through a systematic review. Out of 2656 initially identified publications for the period between 2007 and 2018, 146 articles were included for final synthesis, according to explicit inclusion and exclusion criteria. The descriptive results show that most of the disciplines involved in AIEd papers come from Computer Science and STEM, and that quantitative methods were the most frequently used in empirical studies. The synthesis of results presents four areas of AIEd applications in academic support services, and institutional and administrative services: 1. profiling and prediction, 2. assessment and evaluation, 3. adaptive systems and personalisation, and 4. intelligent tutoring systems. The conclusions reflect on the almost lack of critical reflection of challenges and risks of AIEd, the weak connection to theoretical pedagogical perspectives, and the need for further exploration of ethical and educational approaches in the application of AIEd in higher education.

An exploration of the influences on under-representation of male pre-registration nursing students

Heather Whitford, Glenn Marland, Maggie Carson, Heather Bain, Jacqueline Eccles, John Lee, James G. Taylor