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967 papers found.
of the Department for 9 years.Charles' research is primarily in experimental atomic, molecular and optical physics, but he also has ongoing research efforts in remote sensing in
DOI: 10.18260/1-2--47552The summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,717 new measurements from 869 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Most of the 120 reviews are updated, including many that are heavily revised. The is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume 2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented in the Listings. The complete (both volumes) is published online on the website of the Particle Data Group () and in a journal. Volume 1 is available in print as the . A with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print, as a web version optimized for use on phones, and as an Android app. The 2024 edition of the Review of Particle Physics should be cited as: S. Navas et al. (Particle Data Group), Phys. Rev. D 110, 030001 (2024) © 2024 2024
DOI: 10.1103/physrevd.110.030001Generative artificial intelligence is a fast-growing area of research offering various avenues for exploration in high-energy nuclear physics. In this work, we explore the use of generative models for simulating electron-proton collisions relevant to experiments like the Continuous Electron Beam Accelerator Facility and the future Electron-Ion Collider (EIC). These experiments play a critical role in advancing our understanding of nucleons and nuclei in terms of quark and gluon degrees of freedom. The use of generative models for simulating collider events faces several challenges such as the sparsity of the data, the presence of global or eventwide constraints, and steeply falling particle distributions. In this work, we focus on the implementation of diffusion models for the simulation of electron-proton scattering events at EIC energies. Our results demonstrate that diffusion models can reproduce relevant observables such as momentum distributions and correlations of particles, momentum sum rules, and the leading electron kinematics, all of which are of particular interest in electron-proton collisions. Although the sampling process is relatively slow compared to other machine-learning architectures, we find diffusion models can generate high-quality samples. We foresee various applications of our work including inference for nuclear structure, interpretable generative machine learning, and searches of physics beyond the Standard Model. Published by the American Physical Society 2024
DOI: 10.1103/physrevd.110.016030A bstract Machine learning-based jet classifiers are able to achieve impressive tagging performance in a variety of applications in high-energy and nuclear physics. However, it remains unclear in many cases which aspects of jets give rise to this discriminating power, and whether jet observables that are tractable in perturbative QCD such as those obeying infrared-collinear (IRC) safety serve as sufficient inputs. In this article, we introduce a new classifier, Jet Flow Networks (JFNs), in an effort to address the question of whether IRC unsafe information provides additional discriminating power in jet classification. JFNs are permutation-invariant neural networks (deep sets) that take as input the kinematic information of reconstructed subjets. The subjet radius and a cut on the subjet’s transverse momenta serve as tunable hyperparameters enabling a controllable sensitivity to soft emissions and nonperturbative effects. We demonstrate the performance of JFNs for quark vs. gluon and Z vs. QCD jet tagging. For small subjet radii and transverse momentum cuts, the performance of JFNs is equivalent to the IRC-unsafe Particle Flow Networks (PFNs), demonstrating that infrared-collinear unsafe information is not necessary to achieve strong discrimination for both cases. As the subjet radius is increased, the performance of the JFNs remains essentially unchanged until physical thresholds that we identify are crossed. For relatively large subjet radii, we show that the JFNs may offer an increased model independence with a modest tradeoff in performance compared to classifiers that use the full particle information of the jet. These results shed new light on how machines learn patterns in high-energy physics data.
DOI: 10.1007/jhep07(2024)257This study employed a descriptive case study design to examine the integration of technology in science education, focusing on the professional development of student teachers in Ghana. Using the technological pedagogical and content knowledge (TPACK) framework as a theoretical lens, the study aimed to address the gaps in existing teacher education programs. Through a technology integration training workshop, the progress of four student teachers in developing their competencies for integrating technology into the teaching of high school physics using simulations was tracked and examined. Drawing on a combination of quantitative (survey) and qualitative data (focus group discussions, semi-structured interviews, observations, and lesson artefacts) sources, findings revealed that the student teachers improved their teaching with technology, which was evident in their developed TPACK, improved content knowledge and developed competencies in the exploration of Physics Education Technology simulation environments. These outcomes suggest a transformative shift in student teacher's teaching approaches, transitioning from a teacher-centered paradigm to a learner-centered one, particularly within the context of simulation environments. Despite initial challenges associated with insufficient content knowledge, establishment of relationships among physics content, teaching strategies and the identified affordances of the simulation environment as well as the shift from traditional to learner-centered approach, the study underscores the pivotal role played by the professional training arrangement implemented for the research.
DOI: 10.30935/conmaths/14688We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments.
DOI: 10.21468/scipostphys.16.5.130This study provides a comprehensive review of the cutting-edge intersections of biology and engineering in the realm of medical therapeutics, focusing on the advancements and applications of synthetic biology. The main objectives were to explore the historical evolution, define the scope, and analyze the current state-of-the-art in synthetic biology, particularly in drug development and treatment strategies. The methodology employed a systematic literature review and content analysis, utilizing a range of academic databases to gather relevant peer-reviewed articles published between 2013 and 2023. Key findings revealED that synthetic biology, through the integration of engineering principles and biological systems, has led to significant innovations in medical therapeutics. These include the development of novel drug delivery systems, targeted therapies, and personalized medicine approaches. The study highlights the challenges and limitations in current synthetic biology approaches, such as ethical concerns, regulatory hurdles, and the need for interdisciplinary collaboration. The future landscape of synthetic biology in medicine is marked by both challenges and prospects. The field holds immense potential for addressing complex diseases and enhancing healthcare delivery, yet faces significant challenges in ethical considerations and regulatory frameworks. Strategic recommendations are provided for researchers, industry leaders, and policymakers, emphasizing the need for continuous innovation, ethical applications, and comprehensive regulatory strategies. Finally, synthetic biology stands as a transformative force in medical therapeutics, with the potential to revolutionize healthcare. Future research should focus on overcoming current limitations and exploring new applications, ensuring the field's continued advancement and contribution to global healthcare. Keywords: Synthetic Biology, Medical Therapeutics, Drug Development, Bioengineering.
DOI: 10.51594/estj.v5i4.1041Digital Transformation Education has received greater attention in teaching and learning, however, there is a scarcity of studies on the challenges, effectiveness, and perceptions of Computer-Assisted Instruction (CAI), especially in the Colleges of Education (CoE). In addressing these, the study used the mixed method research design using 12 Physics tutors and 254 Physics students from 3 CoE purposively selected from the Sekyere South District and the Mampong Municipality. Interviews and questionnaires were used for data collection and data analysis was done using Statistical Package for Social Sciences ¬(IBM SPSS), version 26.1, employing descriptive statistics and thematic analysis. The results indicated that Physics tutors generally face a high level of challenges, with inadequate technological resources and limited financial support posing the greatest hindrances. In response, tutors employed various strategies including personal investment in internet bundles and advocacy for institutional intervention. It was again found that both quantitative and qualitative findings converged after merging and that the qualitative findings agreed with the quantitative findings. It was concluded that tutors of Physics in the CoE in the Mampong Municipality and the Sekyere South District encounter challenges during their integration of CAI in their Physics lessons. However, since students of Physics in the CoE perceive the use of CAI as very positive to their academic lives, it was recommended that using CAI for teaching and learning Physics in the colleges of education should be fortified.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0757/a.php" alt="Hit counter" /></p>
DOI: 10.46827/ejoe.v8i3.5204Cancer, a multifaceted and heterogeneous ailment, persists as a substantial global public health concern. Recent strides in cancer biology have profoundly augmented our comprehension of the intricate genetic and molecular mechanisms underlying the inception and advancement of cancer. This headway has propelled the formulation of innovative therapeutic strategies, embracing targeted interventions and immunotherapies, which have showcased promising outcomes in clinical assessments. However, a multitude of obstacles continue to challenge the creation of efficacious and individualized cancer treatments. This systematic review encapsulates an extensive vista of contemporary advancements in cancer biology and therapeutics, accentuating pivotal breakthroughs in our grasp of cancer's intricacies, while illuminating the latest therapeutic avenues for cancer management. Moreover, the paper elaborates on the quest's upcoming trajectories in cancer research and treatment, encompassing burgeoning technologies and uncharted domains of inquiry that might pave the way for more efficacious and personalized interventions for individuals afflicted by cancer.
DOI: 10.26538/tjnpr/v7i12.4Dear Editor, The vast expanse of medical physics, as a discipline, traverses far beyond the mere application of radiation in healthcare. Yet, there seems to be an inadvertent narrowing of its scope in both academic curricula and public perception. By sequestering the role of medical physics to predominantly radiation-based applications, we risk overlooking its comprehensive potential in revolutionizing patient care and clinical solutions. Medical physics involves the application of the concepts and methods of physics to medicine. Its footprint can be observed wherever physics aids in the prevention, diagnosis, and treatment of diseases. This understanding, reinforced by numerous scientists and authors, is also delineated in general literature, from encyclopedias to dictionaries. Consequently, the realm of medical physics extends across every nook and cranny of healthcare facilities. From assessments, such as temperature and pressure-related vitals, to diagnostic procedures involving medical imaging, and treatments encompassing cardiac defibrillators and artificial heart valves, medical physics plays an instrumental role. However, the current academic trend is concerning. A majority of graduate programs in medical physics seem to be anchored predominantly on diagnostic imaging, radiation therapy, and nuclear medicine physics. These subjects, while crucial, focus primarily on radiation's clinical, research, and industrial applications. This skewed emphasis has led to a scenario where the term “medical physics” evokes immediate associations with “diagnostic imaging physics, radiotherapy physics, and nuclear medicine physics.” This tunnel vision not only shapes public perception but also manifests itself in the job market. Hospitals tend to list radiologically-related roles when appointing medical physicists, perpetuating this limited scope. Through your esteemed journal, we wish to shed light on the need for a broader understanding and application of medical physics, extending beyond the radiation-centric narrative that currently prevails. We believe that diversifying the roles and responsibilities of medical physicists will significantly contribute to the advancement of healthcare and scientific communities. Thank you for considering our perspective. We look forward to your action in addressing this urgent matter for the betterment of healthcare and the scientific community at large. Yours sincerely, Corresponding author. Mr. Alhassan Mohammed Baidoo: Conception of research idea, writing of initial draft, review and approval of finished work. Stephanie Brako Boateng: Conception of research idea and writing of initial draft. Ruth Beulah Awotwe: Conception of research idea and rewriting of initial draft. Samuel Nii Adu Tagoe: Review and correction of written work. Philip Odonkor: Rewriting of initial draft. Anna Mamoud: Rewriting of initial draft. The authors have nothing to report. The authors declare no conflicts of interest.
DOI: 10.1002/acm2.14176The objective of this study was to use the practical activity method to improve the understanding and problem-solving skills of physics students at School A in the Eastern Region of Ghana. The study used 29 students in the Form 1. Sc. 1 class, of which 27 were boys and two were girls. The instruments used to gather data were achievement tests and observations. Simple statistical methods such as pre-intervention lessons were designed and administered to find the reasons students had problems understanding physics concepts and their inability to solve problems in physics. Several activities were undertaken to enhance students’ understanding and problem-solving skills. This research revealed that the use of practical activity-based methods in the teaching and learning process of physics enhanced students’ performance remarkably. The findings from this research showed that students’ performance was elevated during the series of lessons administered. The students got a better understanding of concepts and were able to make real-life applications of concepts. This subsequently increased their contributions and participation during lessons. Conclusions were drawn and suggestions were made for teachers who are faced with similar problems of improving students’ performance in physics.
DOI: 10.59573/emsj.7(4).2023.2BACKGROUND: There have been several proposals by researchers for the introduction of Artificial Intelligence (AI) technology due to its promising role in radiotherapy practice. However, prior to the introduction of the technology, there are certain general recommendations that must be achieved. Also, the current challenges of AI must be addressed. In this review, we assess how Africa is prepared for the integration of AI technology into radiotherapy service delivery. METHODS: To assess the readiness of Africa for integration of AI in radiotherapy services delivery, a narrative review of the available literature from PubMed, Science Direct, Google Scholar, and Scopus was conducted in the English language using search terms such as Artificial Intelligence, Radiotherapy in Africa, Machine Learning, Deep Learning, and Quality Assurance. RESULTS: We identified a number of issues that could limit the successful integration of AI technology into radiotherapy practice. The major issues include insufficient data for training and validation of AI models, lack of educational curriculum for AI radiotherapy-related courses, no/limited AI teaching professionals, funding, and lack of AI technology and resources. Solutions identified to facilitate smooth implementation of the technology into radiotherapy practices within the region include: creating an accessible national data bank, integrating AI radiotherapy training programs into Africa's educational curriculum, investing in AI technology and resources such as electronic health records and cloud storage, and creation of legal laws and policies to support the use of the technology. These identified solutions need to be implemented on the background of creating awareness among health workers within the radiotherapy space. CONCLUSION: The challenges identified in this review are common among all the geographical regions in the African continent. Therefore, all institutions offering radiotherapy education and training programs, management of the medical centers for radiotherapy and oncology, national and regional professional bodies for medical physics, ministries of health, governments, and relevant stakeholders must take keen interest and work together to achieve this goal.
DOI: 10.1016/j.ejmp.2023.102653Purpose: Our purpose was to assess physics quality assurance (QA) practices in less resourced radiation therapy (RT) centers to improve quality of care. Methods and Materials: A preliminary study was conducted in 2020 of 13 select RT centers in 6 countries, and in 2021, our team conducted onsite visits to all the RT centers in Ghana, one of the countries from the initial survey. The RT centers included 1 private and 2 public institutions (denoted as Public-1 and Public-2). Follow-up surveys were sent to 17 medical physicists from the site visit. Questions centered on the topics of equipment, institutional practice, physics quality assurance, management, and safety practices. Qualitative and descriptive methods were used for data analysis. Questions regarding operational challenges (machine downtime, patient-related issues, power outages, and staffing) were asked on a 5-point Likert scale. Results: The preliminary survey from 2020 had a 92% response rate. One key result showed that for RT centers in lower gross national income per capita countries there was a direct correlation between QA needs and the gross national income per capita of the country. The needs identified included film/array detectors, independent dose calculation software, calibration of ion chambers, diodes, thermoluminiscence diodes (TLDs), phantoms for verification, Treatment Planning System (TPS) test phantoms, imaging test phantoms and film dosimeters, education, and training. For the post survey after the site visit in 2021, we received a 100% response rate. The private and the Public-1 institutions each have computed tomography simulators located in their RT center. The average daily patient external beam workload for each clinic on a linear accelerator was: private = 25, Public-1 = 55, Public-2 = 40. The Co-60 workload was: Public-1 = 45, Public-2 = 25 (there was no Co-60 at the private hospital). Public-1 and -2 lacked the equipment necessary to conform to best practices in Task Group reports (TG) 142 and 198. Public-2 reported significant operational challenges. Notably, Public-1 and -2 have peer review chart rounds, which are attended by clinical oncologists, medical physicists, physicians, and physics trainees. All 17 physicists who responded to the post site visit survey indicated they had a system of documenting, tracking, and trending patient-related safety incidents, but only 1 physicist reported using International Atomic Energy Agency Safety in Radiation Oncology. Conclusions: The preliminary study showed a direct correlation between QA needs and the development index of a country, and the follow-up survey examines operational and physics QA practices in the RT clinics in Ghana, one of the initial countries surveyed. This will form the basis of a planned continent-wide survey in Africa intended to spotlight QA practices in low- and middle-income countries, the challenges faced, and lessons learned to help understand the gaps and needs to support local physics QA and management programs. Audits during the site visit show education and training remain the most important needs in operating successful QA programs.
DOI: 10.1016/j.adro.2023.101335BACKGROUND: Nearly half of the world is at risk of developing dengue infection. Dengue virus is the causative agent behind this public healthcare concern. Millions of dengue cases are reported every year, leading to thousands of deaths. The scientific community is working to develop effective therapeutic strategies in the form of vaccines and antiviral drugs against dengue. METHODS: In this review, a methodological approach has been used to gather data from the past five years to include the latest developments against the dengue virus. RESULTS: Different therapeutics and antiviral targets against the dengue virus are at different stages of development, but none have been approved by the FDA. Moreover, various vaccination strategies have also been discussed, including attenuated virus vaccines, recombinant subunit vaccines, viral vector vaccines, DNA vaccines, nanotechnology, and plant-based vaccines, which are used to develop effective vaccines for the dengue virus. Many dengue vaccines pass the initial phases of evaluation, but only two vaccines have been approved for public use. DENGVAXIA is the only FDA-approved vaccine against all four stereotypes of the dengue virus, but it is licensed for use only in individuals 6-16 years of age with laboratory-confirmed previous dengue infection and living in endemic countries. Takeda is the second vaccine approved for use in the European Union, the United Kingdom, Brazil, Argentina, Indonesia, and Thailand. It produced sustained antibody responses against all four serotypes of dengue virus, regardless of previous exposure and dosing schedule. Other dengue vaccine candidates at different stages of development are TV-003/005, TDENV PIV, V180, and some DNA vaccines. CONCLUSION: There is a need to put more effort into developing effective vaccines and therapeutics for dengue, as already approved vaccines and therapeutics have limitations. DENGVAXIA is approved for use in children and teenagers who are 6-16 years of age and have confirmed dengue infection, while Takeda is approved for use in certain countries, and it has withdrawn its application for FDA approval.
DOI: 10.3390/vaccines11081328The focus of this study is to ascertain the conceptual understanding students of Bolgatanga Girls Senior High School (BGSHS) have in “<i>gravity and free fall</i>”. Descriptive research design (cross-sectional survey) was used in this study as a method of collecting information. Out of 183 second and third year students, 43 of them were randomly selected and involved in the study. Students were given 10 conceptual based test items relating to “<i>gravity and free fall</i>” to respond to. Students were required to respond true/false and provide reasons for their response. It was found that majority of the students had the misconception that gravity is selective and therefore acts more on heavier objects compared to lighter objects. As a result, they are of the opinion that larger object should hit the ground first before a light object dropped from the same height, which is not scientifically accurate. Based on the findings of the study, it was recommended that physics teachers in BGSHS should carefully pay attention to students’ misconceptions and be guided by it when teaching.
DOI: 10.30935/ejsee/13444Abstract Ultrasound assisted extraction (UAE) is one of the preferred green extraction techniques widely used for the extraction of bioactive compounds from plant materials. It has attracted much attention and many studies have been done to understand its mechanism, effects and efficiency. However, no study has discovered and given enough attention to the superior role solvent‐to‐material ratio (SMR) plays in moderating UAE efficiency. This study therefore emphasizes the importance of SMR as the main determinant of UAE efficiency and further proves its mechanistic effects with ultrasound physics. It discusses SMR effects on extraction medium density, acoustic energy transfer, cavitation rate, power intensity attenuation and free hydroxyl radical generation during water‐based UAE. This understanding is needed to assist researchers in the design of their extraction experiments and optimizations. Without this insight, even optimization processes will be limited in giving the true conditions needed for the highest UAE efficiency. The study shows that low SMR increases acoustic energy scattering and absorption and attenuates ultrasound power intensity and vice versa. SMR can be controlled to either preserve bioactivity of compounds or produce free radicals for microbial inactivation and elimination and oxidative degradation of natural pigments in aqueous media. Practical application A comprehensive understanding of the mechanism and physics behind the effects of solvent‐to‐material ratio (SMR) during ultrasound assisted extraction (UAE) of bioactive compounds helps in fine‐tuning SMR purposely to ensure that ultrasound power attenuation is minimized. Ultrasound power defines UAE efficiency by virtue of acoustic cavitation. Due to the fact that UAE in aqueous media generates free hydroxyl radicals (*OH) from water autolysis, SMR can be deliberately tuned to induce controlled power attenuation to limit this phenomenon. This becomes a strategy to protect bioactive compounds that are prone to oxidative degradation. As ultrasound power is linked to energy consumption, fine‐tuning SMR to minimize power attenuation can significantly improve process efficiency and reduce treatment time, saving energy and enhancing profitability, especially during large scale industrial treatments.
DOI: 10.1111/jfpe.14339