Political Regimes and Anti-Corruption Legislation in Africa: A Comparative Study with Kenya as a Benchmark
This study examines how regime type influences anti-corruption enforcement in Africa through a comparative analysis of Kenya, Rwanda, Nigeria, and South Africa, using qualitative process tracing and governance indicators including the Corruption Perceptions Index and Mo Ibrahim Index. Findings reveal that legal comprehensiveness does not guarantee effective enforcement: democratic regimes enact robust legislation but suffer from inconsistent enforcement due to elite capture, authoritarian regimes like Rwanda achieve stronger enforcement (CPI: 53/100) through centralized control but with political selectivity, while hybrid regimes like Kenya demonstrate the most fragmented patterns with comprehensive laws undermined by politicized implementation (CPI: 31/100). The study concludes that institutional autonomy and regime incentives, rather than legislative design alone, determine anti-corruption outcomes, highlighting the need to insulate enforcement mechanisms from political capture for sustainable reform.
Derechos de autor 2025 Youth Science Journal
Simulation-Based Analysis of Thermally-Induced Stress Effects on Buried-Core Square Waveguide
The objective of this study was to understand and visualize the effects of thermally-induced stresses resulting from high-temperature manufacturing processes (thermal annealing) on the performance of the buried-core square silicon waveguide. In order to do so, the photoelastic effect, which relates principle stresses and refractive indices, and its impacts were analyzed and investigated. The analysis was performed in COMSOL Multiphysics, utilizing the Finite Element Method (FEM) for numerical calculations. The equivalent stress distribution and strains in the waveguide were determined by exploiting the plane strain assumption. The anisotropic stress distribution in the waveguide caused a change in the refractive indices along the principle axes, causing a change in birefringence. Due to birefringence, optical power density distribution in different modes has experienced variations. However, in higher modes, the variation was more evident as mode splits were exhibited alongside higher optical power confinement, noting that higher confinement is advantageous for low-loss optical waveguides. Thus, it was inferred that the effect of anisotropic stresses was more substantial on higher modes rather than fundamental modes. Finally, it was evident that the mechanical properties of the cladding and manufacturing conditions could be optimized to control birefringence and subsequent performance-governing parameters.
Molecular Dynamics Simulations of 53BP1 Structural Mechanisms in DNA Double-Strand Break Repair and Implications for Therapeutic Development
DNA double-strand breaks (DSBs) pose significant threats to genomic integrity, requiring precise repair mechanisms to maintain cellular health. 53BP1 serves as a critical regulator of DSB repair pathway choice, promoting non-homologous end joining (NHEJ) while inhibiting homologous recombination (HR). Despite extensive research on 53BP1 function, comprehensive understanding of its structural-functional relationships and dynamic regulation mechanisms remains limited. This study employed 3D computational molecular dynamics simulations using UCSF ChimeraX to elucidate the mechanistic, structural, and functional features of 53BP1 in DNA repair processes. Protein structures were obtained from the Protein Data Bank, with homology modeling applied where necessary to examine 53BP1 domain interactions with histone modifications and effector proteins. Simulations revealed stable, specific binding between the Tudor domain and dimethylated histone H4 lysine 20 (H4K20me2) with high affinity (Kd ≈ 20 nM), confirming its recruitment mechanism to damaged chromatin. The flexibility of BRCT repeats and oligomerization domains demonstrated their crucial role in forming liquid-like condensates at DSB sites, creating microenvironments that concentrate repair factors. Phosphorylation-dependent interactions with RIF1 and PTIP were validated through binding interface analysis, supporting experimental findings on regulatory mechanisms. These structural insights bridge existing knowledge gaps and provide a foundation for targeted bioengineering strategies in therapeutic development for genomic instability-related diseases, particularly cancer. The integration of computational modeling with experimental data offers new perspectives for understanding 53BP1's multifaceted role in maintaining genomic stability.
Optimizing Bioelectricity Generation from Plant-Microbial Fuel Cells Using Soil-Based Electrodes and Natural Substrates
Plant-assisted microbial fuel cells (P-MFCs) are a novel bio-electrochemical system that could convert solar energy into electricity through a mutually-beneficial association of plant roots and soil microbes. In the present study, P-MFC prototypes were constructed in soil with live plants, using metallic electrodes to serve as an anode and cathode conductor for the transformation of electrons in soil, to assess the potential of using P MFC. Continuous readings of voltage and current were collected to assess and compare the performance of different combinations of plant-soil, with a control MFC with no plants. In one design, the voltage achieved from a peak single cell was 0.75 V with a cumulative power density of 35 mW/m² of surface area, signifying that rhizodeposition from the plant assisted with microbial oxidation of root exudates to generate more electrons for the electrodes. Three P-MFCs combined in a series arrangement produced a total voltage of 2.1 V, with power density not significantly reduced, however any combination of more than three only provided minute changes in voltage (~10% increase). Again, this work suggests the importance of interaction with soil, plant species, and electrode design to optimize P-MFC operation. This work also supports a lower cost, environmental-friendly, offgrid, and easily scalable technology solution for energy generation in rural areas. This work provides implications for increasing bioelectricity outputs, as well as showcasing the ecological potential of plant microbial interactions in simple, engineered designs. Further, the capacity to improve bioelectricity density and efficiency related to electrode materials and stacking systems highlighted an agenda for novel developments for implementation of P-MFC technologies.
What is the future of bioprinting in tissue engineering?
This research paper summarizes the findings of previous research about 3D bioprinting in tissue engineering. Biofabrication, particularly in the field of regenerative medicine and 3D in vitro models, shows great potential in creating intricate tissue structures that closely resemble native tissues. Preprocessing steps involve imaging the tissue using various modalities, designing the 3D model using CAD software, and considering the characteristics of the tissue for proper cell line selection. The development of suitable bioinks combining printability, cytocompatibility, and biofunctionality remains a challenge. Imaging techniques play a crucial role in characterizing tissue engineering products. Conventional tissue engineering strategies involve scaffolds, isolated cells, or a fusion of the cells with scaffolds, while 3D bioprinting enables the creation of complex tissue-like structures. These advancements have the potential to revolutionize a broad and developing sphere of tissue engineering, regenerative medicine, and biomedical research. Used methods are questionnaires and interviews help in collecting information from experienced specialists and obtaining their true opinions on the topic. As a result, bioprinting has a full potential to develop in the future.
Derechos de autor 2024 Youth Science Journal
Underlying neural mechanism of schizophrenia
This study investigates the neural basis of schizophrenia and its implications for treatment development. Schizophrenia is a complex mental disorder characterised by hallucinations, delusions, and cognitive impairments. Neuroimaging studies consistently show abnormalities in brain regions involved in cognition and sensory processing. Genetic factors and environmental influences contribute to the risk of developing schizophrenia. Current treatments aim to address neural network dysfunction and symptom management. However, the findings emphasise the need for personalised and innovative treatments, ethical considerations, and continued research to enhance understanding and patient outcomes. The study recognizes the heterogeneity of schizophrenia and the importance of tailoring interventions to individual patients. Ethical considerations surrounding the treatment of schizophrenia patients are also highlighted, emphasising the significance of patient-centred care. Ongoing research efforts are crucial to deepen our understanding of the disorder, unravel complex neurobiological mechanisms, and develop novel interventions. By integrating scientific inquiry with compassionate care, we can work towards a future where individuals with schizophrenia can lead fulfilling lives and reach their full potential. The study underscores the urgency of advancing our knowledge and developing effective treatments to improve the lives of those affected by schizophrenia.
Ultimate security by combining Cloudflare’s and Akamai’s APIs and machine learning.
As of 2023, 30,000 websites are hacked daily, and 64% of companies worldwide have experienced at least one form of cyber-attack. As hacking increases, the need to implement a secure security system increases. This paper discusses the implementation of a security system that combines Cloudflare’s API, Akamai’s API, and machine learning (ML) algorithm. Machine learning and deep learning algorithms were used to determine which one gets the best accuracy. However, the XG Boost classifier determines the highest accuracy since it can deal efficiently with large datasets and its ensemble learning. Also, the XG Boost model was recompiled to interact with other APIs. This project can be used like any other API, but this project provides the features of the two used APIs, their security layer, and the ML algorithm. The secondary research, e.g., research papers and datasets, method is used to get all data used in the paper or for the implementation of the project. Qualitative data plays a crucial role in elucidating the characteristics and functionality of APIs- especially Cloudflare’s and Akamai’s APIs-. It is employed to articulate the purpose and mechanics of APIs, delineating how they function and their intended usage. The IPs were collected to be used as training data for the ML model. The data is filtered (removing the uncompleted IPs) and examined randomly to ensure its quality. The result was significant as the accuracy of this project was 97.6%. Therefore, the faults and bugs in Cloudflare’s API and Akamai’s API were fixed, enhancing the security of many datasets.
The Effect of Parasocial Relationships on the Personal Interactions, Emotions and Behaviors of Brazilian Adolescents and Young Adults
Nowadays, the internet plays a major role in people’s lives, especially in the formation of relationships in society. One major form of interaction that gained a lot of space because of the internet is the parasocial relationships, which is defined as one-sided connections with celebrities, media figures, or characters. Considering how much space social media figures have in adolescents’ routines and the fact that adolescents (approximately ages 10–22) are more easily influenced and emotionally reactive due to the maturing of the prefrontal cortex, it is important to investigate the relationships they are building and the content they are consuming. Because of that, this paper seeks to expand knowledge on the nature of parasocial relationships by investigating the effect of these relationships on Brazilian adolescents and young adults. The goal is to investigate how they impact their relationships, emotions, and behaviors. The research findings were based on analyses and discoveries made through a questionnaire designed by the writers and observational research conducted through the study of previous works. Through that, both positive and negative effects of parasocial relationships were discovered. It was found that the adolescents were indeed influenced, so strongly, in fact, that there was an increase in their consumerism habits according to what was promoted by their idols. However, parasocial relationships were not the main reason for young people's screen time, differing from the common belief. Additionally, these relationships have provided comfort to most participants, supporting the hypothesis that many parasocial relationships are established because they help individuals.
Quaternions and Octonions review, relationship with Cayley Dickson Construction, and Contribution to Quantum Mechanics Interpretations and 3D Rotation
Mathematics has always been the mother of sciences. The main reasons behind this are the broadness of mathematics and its compelling ability to translate theory into laws and algorithms to help us understand the universe better. The discovery of imaginary numbers was a critical moment in the history of mathematics, extending its horizon by solving undefinable polynomials with such a revolutionary idea. This paper aims to clear the common misconception about the existence of a finite number of numerical systems, explain their applications, and extend basic algebraic properties to conclude their origin. The focus of this paper is on the abstract mathematical approach to higher-dimensional complex systems, or hyper complex number systems, of Quaternions and Octonions, discussing the historical background of these systems, the related fundamental algebraic concepts, their construction, properties, operations, and finally their real-life applications. Hyper complex number systems are not only beneficial in computer science and theoretical physics but also groundbreaking within the fields of mathematics. Accordingly, this paper summarizes the findings throughout the history of hyper complex numbers and demonstrates their ability to be applied in physics, quantum mechanics, computer graphics, and more.
Predicting The Eventual Evolution of Neutron Stars into Blackholes Using a Supervised Machine Learning Model.
Although neutron stars are one of the most fascinating objects in the universe, they each have their own special characteristics, such as their magnetic field, deformation rate, and rotating speed. The lifetime of neutron stars that end up in black holes is facing insufficient focus in research and exploration. There is not enough data on this phenomenon, whereas studying this phenomenon opens doors in space exploration and research in this field. The objective of this research is to help scientists, astronomers, and space agencies be able to classify and detect these phenomena in space, improve their understanding of them, and make their space journeys more efficient and easier. This research will make a huge contribution to the understanding of this phenomenon, in addition to collecting more data on it that could turn space exploration into its highest state. A proposed supervised machine learning model (ML) was implemented based on a decision tree to solve multiple equations derived from popular theories, such as the equation of state of neutron-rich and dense matter and the Tolman-Oppenheimer-Volkoff limit. To classify the evolution of neutron stars in binary systems, whether they are about to collapse into black holes or not. Decisions would be based on the mass of the neutron star, and since the data gathered had fewer than clear results, the accuracy of the model was 100%, knowing that when having more sufficient data and following the methodology presented here, the accuracy would differ.
Since gaining independence in 1991, Kazakhstan has actively pursued friendly relations with other nations, particularly with fellow Turkic-speaking states. This paper examines Kazakhstan's role in Turkic integration, its current and future participation levels, and the potential benefits of Turkic unity for the country. The research employs a mixed-methods approach, including interviews with teachers and surveys among residents of Astana. Secondary research explores existing literature on Turkic integration and Kazakhstan's involvement. The findings suggest that Kazakhstan plays a significant role in Turkic integration, with a majority of respondents viewing the level of integration as high and Kazakhstan's role as substantial. The economy emerges as a crucial sphere of cooperation, with many respondents favoring the development of economic ties. Additionally, there is notable interest in political-military cooperation, including the possibility of Kazakhstan leaving existing alliances to form a Turkic military alliance. Overall, Turkic integration is seen as a valuable endeavor for Kazakhstan, offering geopolitical independence and economic benefits. However, the study acknowledges limitations, such as the sample size and geographic scope, and suggests future research to include a more diverse range of participants and explore Turkic integration from the perspectives of other Turkic nations. The research aligns with existing studies and supports the notion that Kazakhstan's active participation in Turkic integration has strategic importance for the country. It underscores the significance of strengthening ties with fellow Turkic-speaking states and pursuing a deeper level of cooperation, especially in the economic and political-military spheres.
Impact of Superconductor LK-99 on Quantum Computers Maintenance and Operational Costs.
This research explores the impact of the superconductor LK-99 on the maintenance and operational costs of quantum computers. Quantum computers have shown great potential in revolutionizing computing by leveraging the principles of quantum mechanics to achieve exceptional computational power. However, the fragility of qubits - the fundamental units of quantum computing - poses significant challenges in terms of errors and decoherence. Efficiently managing quantum errors requires complex error correction techniques and the cooling of qubits to ultra-low temperatures. The concept of room-temperature superconductivity, exemplified by LK-99, offers a transformative solution by potentially reducing the cooling requirements of quantum hardware. This breakthrough could enhance the stability and viability of quantum devices for widespread utilization. This paper investigates the potential benefits of LK-99 in quantum computer operations, highlighting their role in mitigating thermal noise and improving qubit stability. The findings provide valuable insights into the practical implications of integrating superconductors in quantum computing systems, paving the way for more efficient and cost-effective utilization of these powerful machines.
How did China manage to divert global attention to the human right abuses and genocide against the Uighur population?
This project is dedicated to the study of how China affected the infringement of the Uighur Nation, so that countries do not provide any help for this nation. Moreover, it explores which pressure China puts on the Uighur nation and how international organizations, countries impact this issue. This topic significantly impacts on the development of the Uighur nation, due to this there will be opportunities to identify problems and begin to solve them in the world market. Such questionnaires were completed by millions of people, who have shared their knowledge and experience. This scientific inquiry sheds light on the manipulation of media, diplomacy, and international relations, unveiling tactics that other governments might employ in the future. Furthermore, this research empowers international bodies, NGOs, and civil society to develop more robust mechanisms for safeguarding human rights. Armed with an in-depth understanding of how a nation effectively diverted attention, stakeholders can formulate proactive strategies to uphold the rights of marginalized populations and hold responsible parties accountable.
Fulfilling eco-needs with energy-efficient metrics in tropical-zone office buildings
Current office buildings in temperate climate zones may suffer from inefficient energy utilization that does not match the workers' demands. This research was inclined to detect the primary environmental need and determine energy-related metrics that help to sustain those environmental conditions. The study contained both qualitative and quantitative methods presented from other case studies due to the limitations we had. One of quantitative methods included surveys that helped us to comprehend the favorable environmental need to address from office occupants: indoor air quality. Another quantitative method involved analyzing energy records that served as a tool to define energy-efficiency metrics. Contrary, qualitative methods like interviews from experts were beneficial for understanding the specific problem with air quality systems, particularly regarding HVAC. To address the needs of refining air quality, we particularly found energy-efficient performance parameters-correlating metrics - containing such as HVAC consumption, outdoor temperature, and occupancy - and control systems strategies for air quality testing: BMS, VAV, and VFD. Altogether, this research found and promoted energy efficiency with occupants' needs in temperate climate office buildings, focusing on air quality improvement through refined control systems and performance metrics. Further research can potentially be conducted in office buildings located in more harsh climate zones. Moreover, due to research constraints, we were unable to conduct on-site visits to office buildings. Therefore, our future actions will focus on conducting in-person interviews during site visits to gain deeper insights into environmental requirements. We will also make efforts to obtain energy consumption records from the building administrations.
Enhancing Communication Abilities of the Deaf-Blind with AI-Embedded Gloves
The presented project is an enhanced version compared to existing solutions available for individuals who are blind and deaf. Firstly, the Braille TTY device, priced at $6,560, allows blind-deaf individuals to answer calls through writing and screen display. Secondly, the Orbit Reader, priced at $750, is a braille display device that connects to electronic devices, enabling writing and reading for this population. Lastly, the My Vox device facilitates communication between blind, deaf, deaf-blind, and unimpaired individuals, incorporating two keyboards, a braille display, and a regular screen. To develop the improved project, an Arduino device is utilized to control the project's components. Blind-deaf individuals primarily learn through kinesthetic learning and tactile experiences, utilizing tactile sign language, tracking, tactile fingerspelling, print on palm, and Braille. The impact of this project on the community is significant, as it empowers individuals with blind-deaf disabilities to lead more normal lives, addressing their needs instead of ignoring them. Our system has a vibration motor in each position. When a name is sent to the gloves, its letters are translated to braille language like the right side, and some vibration motors are turned according to the letter. All the vibration motors are turned when there is an object near. The prototype can detect the object by using a smartphone. The prototype of the project has been successfully tested in four systems: writing, reading, obstacle avoidance, and obstacle detection. The research methodology depends on a simulating survey and measuring the accuracy and time.
Detection of Dark Matter in Neutron Stars
Despite the latest advancements in the field of astrophysics, dark matter, the vague mysterious thing occupying vast parts of our universe, is still floating around with its obscure nature and very hard to detect components. This research is delving into different approaches for detecting dark matter present in neutron stars and calculating its mass. The approaches discussed are considered secondary techniques in the detection of dark matter and they are being scrutinized with the aim of developing a new way of detecting these vague particles. For instance, hybrid detection methods like star spectroscopy and Gravitational Red Shift Measurements, direct detection methods like scattering experiments, and indirect detection methods like neutrino emissions. Results have shown that some specific neutron stars have higher expectancy for the presence of dark matter particles and some specific techniques are more feasible than others in their detection. By making the most of the latest technology like high-resolution telescopes and software programs, it is possible to utilize dark matter’s effects on neutron stars to assist in its detection. We believe that the detection of dark matter and calculating its mass can pave the way for some revolutionary discoveries regarding the hidden intricacies of the universe.
Computational Biology Approach: A Journey from Gene Editing to Adult’s Mental Health
This research explores the intricate relationship between gene editing, DNA transcription, translocation mechanisms, and their impact on the mental health of individuals aged 18 and above. It seeks to contribute novel insights to this underexplored intersection, propose potential therapeutic interventions, and offer avenues for further exploration. The study extensively reviews two prominent gene-editing technologies: CRISPR-Cas9 and TALENs. It elucidates their mechanisms and identifies potential errors occurring during the final stages of Non-Homologous End Joining (NHEJ), which may lead to gene disruptions and mutations. These disruptions can significantly affect crucial gene functions related to neural regulation, brain development, and mental health disorders. Moreover, the study emphasizes the significance of Homology-Directed Repair (HDR) and its precision in effecting precise DNA sequence changes. It highlights the potential for errors during this process and their direct implications for neural processes and mental health. To address the impact of gene editing on mental health, a computational methodology using Python and the Biopython library is proposed. Focusing on the CRISPR-Cas9 method's activity on the IDH1 gene, which is associated with brain cancer, real-time monitoring through Bioluminescence Imaging (BLI) is recommended as a valuable tool for assessing gene editing efficiency and specific
Auroras as Habitability - Indicators Exploring the Conditions for Life on Exoplanets
For thousands of years, humans have marveled at auroras – lights from solar winds interacting with Earth's magnetic field. Although we know a lot about auroras in our solar system, we are just starting to study them on exoplanets. Studying these lights on other planets helps us learn about their magnetic fields, winds, and atmospheres. This review dived into emerging exoplanetary aurora research, studying how we detect them from far away. We discussed what these auroras can tell us about magnetism, habitability, and possible life beyond our solar system. The Aurora borealis indicates planet habitability by indicating a magnetic field, which is crucial for life as it helps to maintain water on the surface of the planet and protects it from harmful radiation from its parent star. The study of auroras in exoplanets is essential to our understanding of the universe and its diverse phenomena. We also explored the challenges of observing exoplanetary auroras, shedding light on future discoveries about these radiant displays. Delving more into potential biosignatures, it can be stated that the magnetic fields of the exoplanets can be one of the leading signals of their habitability. According to our analysis of various works such as those of Ramirez and Lazio, who considered magnetic fields to be of great importance in protecting habitable zones, we concluded that auroras are reliable indicators of any form of life on exoplanets.
AI and Cardiovascular Diseases: An Overview of Deep Neural Networks in Electrocardiogram Analysis
This paper gives an overview of the advancements in Artificial intelligence (AI) for the prognosis and treatment of cardiovascular disease (CVDs). AI techniques, inclusive of machine learning algorithms, have proven promise in analyzing medical photos for computerized detection of cardiac abnormalities and risk stratification. Decision-guide systems driven by way of AI useful resources in optimizing remedy strategies via leveraging patient facts for personalized interventions. Integration of AI with wearable devices and faraway monitoring structures allows real-time facts collection, early detection of cardiac activities, and powerful remote care control. However, demanding situations associated with information privateness, set of rules bias, and regulatory frameworks need to be addressed. Collaborative efforts amongst clinicians, researchers, and policymakers are crucial for harnessing the whole capacity of AI in CVD care.
A Comparative Study of the Perceived Stress Levels and Sources of Stress among STEM and Conventional Students in Egypt
Egypt's educational system, comprising public and private institutions across all levels, faces multiple issues affecting its quality, equity, and relevance. A recent study by Egypt's Ministry of Health identified that 29.8% of high school students experience mental health problems like anxiety, speech defects, depression, stress and tension, emphasizing the significance of addressing such concerns. Therefore, we aimed to conduct a random sample study of 130 students from the STEM and conventional educational systems in Egypt to compare their perceived stress levels. An online Arabic questionnaire was shared with the targeted population over a period of two weeks. The questionnaire included inquiries about academic and demographic information as well as the Perceived Stress Scale (PSS-10). Respondents were asked about their personal information, academic performance, extracurricular activities, average studying hours, and perceived stress levels. The PSS-10 assessed stress levels based on questions covering coping, control, unpredictability, and overload. Statistical analysis was conducted using the Statistical Package for the Social Sciences (SPSS) version 25. Major findings revealed that STEM students suffer from higher stress levels than conventional students, mainly due to fewer hours of sleep. Additionally, significant differences were found in stress levels between male and female students across the sample. These findings underscore the need to address academic pressures and establish appropriate mental health screening in STEM schools to mitigate negative emotional effects. They are crucial in developing effective strategies for minimizing student stress levels, and educational institutions should utilize this data to assess their curriculum and make any necessary changes.
A quantitative study: How inflammatory diet affects different neurotransmitters' function and their relation to memory disorders.
Alzheimer's disease has been a case study for a long time, discoveries brought hypotheses and reasons related to the disease mechanism. This study aims to bring a clear understanding of the significant impact of human actions such as diet and Alzheimer's disease. Diet indirectly impacts the human body and significantly the brain, in the case of memory disorder diet affects the neurotransmitters that play an important role in the function of the brain and memory. The study used various relations between variables, hypotheses show that a transmembrane protein plays a key role in neurodegeneration and later it disturbs the neurotransmitter’s function. Through the study, information showed that diet styles cause oxidative stress which is considered one of the main reasons that cause neurodegeneration. The study shows the impact of each variable on the other and leads these findings to the main case study of Alzheimer's disease.
A Novel Framework in Leveraging Optimization Physics Models using Quantum Computing: Techniques for the 2-D Hubbard Model
The new and emerging field of quantum computing harnesses the understanding of the complex dynamics of quantum systems, promising to advance and revolutionize scientific fields that can be applied in our world. However, realizing this potential currently faces its challenges: scaling error-corrected qubits, parameter spaces, and efficiently compiling quantum circuits given hardware constraints. This paper reviews techniques to address these obstacles by integrating automatically differentiable quantum circuits (ADQCs) with tensor networks (TN) to enable reverse-mode automatic differentiation for efficient optimization. We propose applying this ADQC-TN framework to the 2D Hubbard model, which is a foundational model of strongly correlated electron systems exhibiting rich phase diagrams, including unconventional superconductivity. This framework can elucidate detailed mechanisms, such as how dopant atoms influence superconducting electron pairing, by training the model’s hopping, interaction, chemical potential, and other parameters on experimental measurements. Robust optimization represents a pivotal bridge between quantum computing and experimental condensed matter physics to advance quantum-based materials modeling and discovery, which has already seen success from the extension of the ground state of quantum lattice models with low fidelities. Successfully trained Hubbard models could facilitate the analysis and understanding of the effects of parameter-tuning and the potential of defects on superconductivity that can aid in other future modeling discoveries through bridging the gap between quantum computing and physical engineering.
A genetic approach for tackling sickle cell disease
SCD is a serious inherited hemoglobinopathy that was responsible for the mortality of 376000 patients in 2021. The number of infants born with this genetic disorder was raised by 13.7% within the time interval from 2000 to 2021. Its fetal complications and painful VOC episodes are associated with a reduced quality of life and hospitalization and healthcare burden. Most SCD therapies are symptom-managing focused rather than curing the disease itself. This study mainly focused on the most life-threatening complications including cardiovascular complications and acute splenic sequestration, medications managing or curing them including hydroxyurea (HU) and gene therapy. HU was found to be effective in reducing cell sickling and was associated with improvements in organ functions represented in decreased acute chest syndromes and crises requiring blood transfusion. Its drawbacks were obvious in reduced sperm count and restricting erythroid cells’ growth. Curing SCD gives lentiviral Gene therapy an advantage compared to HU. However, more research should be done on developing gene therapy to find out the reason and solution of malignancies reported in some cases.
A comparison: galactic formation & evolution through semi-analytic and numerical hydrodynamic frameworks in the context of extragalactic astronomy
In our never-ending cosmic quest to understand the origin of the universe, galactic evolution is profound, as galaxies make up a considerable portion of our universe. Additionally, understanding galactic evolution and the phenomena involved will provide us with the necessary foundation to make predictions about the fate of galaxies and our Milky Way. Although many advances have been made in the field of cosmology, our knowledge of galactic formation and evolution still possesses key gaps. To understand galactic evolution, cosmologists design models of the universe and simulate galactic evolution under the effects of dark matter, dark energy, and baryonic matter. In this article, we mainly discussed two types of frameworks used in designing galactic simulation models: the semi-analytic and numerical hydrodynamic frameworks; we also talked briefly about the N-body and Lamda Cold Dark Matter frameworks. Numerical hydrodynamic simulations provide a tool for investigating the complex and dynamic interactions between numerous physical processes. Meanwhile, semi-analytic models use analytical approximation techniques to handle a range of variables. When choosing a simulation model, the computational complexity of the hydrodynamics framework and the uncertainty of the semi-analytic models prove to be a conundrum. So, we have discussed both frameworks, comparing their advantages and limitations. We concluded that currently both frameworks complete each other’s shortcomings, and for a superior understanding of galactic formation and evolution, a more comprehensive framework that combines both approaches is needed.
Utilizing Chemotactics to Stimulate Collective Cell Migration of Keratinocytes to Speed Second-degree Burn Wound Healing
Worldwide, severe burns cause over 180,000 fatalities every year, and millions of people with non-fatal burns undergo severe, life-long physical and psychological morbidities. In an adult organism, collective cell migration is essential for a proper immune response, wound healing, and tissue homeostasis. A cell's migration is often affected by a mechanism by which specific chemicals either attract or repel the cells of multicellular organisms, which is called chemotaxis. Various aspects of collective cell migration and chemotaxis are recommended to be utilized in the process of burn wound healing. This paper introduced a modern approach that will allow the treatment process of second-degree burn wounds to be faster and less painful. This is done by introducing chemotactics to the burn wound dressing. IFN, TGF-, IGF-1, and FGF-7 are examples of chemotactic proteins. These chemotaxes were specially chosen based on their availability and effectiveness in stimulating the keratinocyte cell migration in the dermis. To help future validation of the idea, three types of mathematical models have been investigated: agent-based models, continuous models, and local-versus-non-local models. Agent-based modelling facilitates the transfer from describing individual models (individual cells) to describing collective behavior. Unlike agent-based models, continuous models are not constrained by a lack of computational power, which makes them suitable for idea validation. One of the main classes of continuous models is reaction diffusion–advection (RDA) equations. The RDA equations use the local chemoattractant gradient to describe population drift. On the contrary, non-local models describe the overall behavior of the element inside its system.
Derechos de autor 2023 Youth Science Journal
Utilizing AOH1996 with chemotherapy delivered via drug nanocarriers; an advanced novel approach for cancer treatment especially Inflammatory Breast Cancer
Inflammatory Breast Cancer (IBC) is a rare disease but tends to be more aggressive than more common types of breast cancer. It accounts for 1–5% of new breast cancer cases. The treatment of IBC is comprised of chemotherapy in addition to targeted therapy as a neoadjuvant treatment, but it can be challenging to cure since IBC is a late-stage cancer. AOH1996 is a novel small molecule that has shown staggering results in inhibiting tumor growth in Phase Ⅰ clinical trials in multiple cancer types, including IBC. This compound is an orally active drug that was tested in vivo, inducing apoptosis in cancer cells without causing any discernable toxicity even at 6 times its effective dosage. Mechanistically, it enhances the PCNA-RPB1 interaction while interfering with TRC resolution, which results in DNA double-stranded breaks in a transcription-dependent manner. Besides apoptosis induction, AOH 1996 sensitizes tumor cells to cisplatin and topotecan treatments. Nonetheless, a promising approach to augmenting the efficacy of chemotherapeutic agents and decreasing their peripheral toxicity is delivering them via nanocarriers. Polymeric nanoparticles showed remarkable properties in delivering paclitaxel in the case of Abraxane (ABI-007). This paper investigates exploiting the AOH1996 drug with different chemotherapeutics delivered via nanocarriers to be used for most cancer types, especially IBC.
The role of narcissism in driving Ariel Castor’s notorious Cleveland kidnappings, and the effect his actions had on his second victim, Amanda Berry.
Narcissistic personality disorder, one of several types of personality disorders, is a mental condition in which people have an exaggerated sense of their own importance, an intense need for attention and admiration, troubled relationships, and a lack of empathy for others. What some people don’t know, however, is that narcissists can be very dangerous. Especially when ego-threatened, narcissists display extreme acts of violence such as abuse, torture, rape, and even murder. There are numerous cases of dangerous narcissists. One of the worst cases is the Cleveland kidnappings carried out by Ariel Castro from 2001 to 2013. Ariel Castro kidnapped three women and held them captive for a span of 10 years. During which they experienced multiple acts of torture and abuse, such as beatings and starvation. Castro was diagnosed with a narcissistic personality disorder with antisocial features. The following journal displays the role played by his narcissism in his violent actions while also covering the effects it might have had on his victims.
The Relationship between Drug Abuse and Academic Stress among Egyptian Undergraduate and High School Students
This literature review examines the relationship between drug abuse and academic stress among Egyptian undergraduate and high school students and other young people across the globe. The review also discusses the origin and impacts of drug abuse, as well as the bidirectional, strong relationship between drug abuse and academic stress. The findings showed that drug abuse is a persistent global problem, with family dysfunction, social pressure, and psychological factors being the major contributors. On the other hand, academic stress is mainly influenced by factors such as family and peer pressure, workload, and exam-related pressures. It has been found that students experiencing high levels of academic stress, e.g., practical educational students in Egypt, are more vulnerable to drug use. Additionally, the study emphasizes the persistent need for implementing intervention and prevention strategies in Egyptian schools and universities. The conclusion calls for the implementation of comprehensive programs to address these two issues, along with further empirical research to identify the best intervention strategies specially tailored to Egyptian students.
The Relation Between One and Two Dimensional Random Walks to Pascal’s Triangle and Analogous Higher-Dimensional Structures
This study aims to explore the use of Pascal's triangle and other analogous structures in higher dimensions to predict the position of particles inside a random walk after a certain number of steps. Pascal's triangle is a triangular array of numbers in which each number is the sum of the two numbers directly above it, and explores higher dimensional structures like Pascal’s pyramid (the three-dimensional equivalent of Pascal’s triangle). The first part of the study delves into the concept of Pascal's triangle and its fundamental properties. After that, Pascal's triangle was used in predicting the position of particles inside a random walk. A random walk is a mathematical model used to describe the movement of particles in a system where the direction and magnitude of each step are random. The probability of a particle ending up at a particular point after a certain number of steps in a random walk can be calculated using Pascal's triangle. The numerator of the fraction representing the probability is the value at the point in Pascal's triangle, while the denominator is the sum of the numbers in the corresponding row or layer of the triangle. The paper demonstrates how these concepts can be used to predict the position of particles inside a random walk and provide a real-life example of their application in the simulation of Brownian motion.
The Origin of Life and Terraforming Mars
The conditions for life to start and evolve have been researched thoroughly for the past few decades. New extreme conditions are being discovered to this day, which are setting the standard for scientists to search for habitability on planets other than the Earth. Also, the origin of life on Earth is of great interest to astrobiologists that are looking for signs of life on other planets. One planet is of particular significance – Mars, as it is the most Earth-like planet in the solar system. In this paper, the latest extreme conditions for life are reviewed, whether for simple or intelligent life. A history of the origin of life is also reviewed. Lastly, the environment on Mars is investigated in terms of habitability, and different ways to terraform Mars are explored.