We extensively studied serigraphic screen-printed commercial silver flake inks loaded with silicon inclusions in order to achieve pinning at the grain boundaries. Based on grain size measurements using electron backscattered diffraction (EBSD), commercial silver ink with silicon microparticle content of 5 wt.% shows a significant grain growth retardation compared to the pristine silver ink, which stabilizes electrical conductivity up to 700 ◦C via Zener pinning mechanism. The modified silicon-loaded silver ink experiences a two times increase in grain size when heated up to 700 ◦C, compared to a seven times increase for the pristine silver ink. In turn, this enables operation temperatures significantly higher than the conventional operational window of microparticle-based silver inks, which are usually limited to 400 ◦C. Using isothermal exposures of 10 minutes up to 4 hours this phenomenon is observed at temperatures ranging from 250 ◦C to 900 ◦C. The electrical conductivity stability, grain size evolution and oxide contents were studied up to 4 hours. The activation energy of silver ink with silicon inclusions is 54% lower than for the pristine silver ink due to pining effect, which retards grain growth via the Zener mechanism. Most importantly, the electrical resistivity becomes stable up to 700 ◦C, which is more than twice the operation limit for off-the-shelf screen-printable silver flake inks. Hence, we demonstrate that adding controlled amounts of silicon particles to silver inks towards grain structure engineering can open new vistas of possibilities for screen-printed metallic inks.

Herbicides are widely used in agriculture to control weeds and enhance crop productivity. However, their application can have significant impacts on soil health and nutrient dynamics. This paper reviews the effects of herbicides on soil properties, microbial communities, and nutrient availability, with a particular focus on calcium deficiency. The review synthesizes findings from peer-reviewed journals and reports, including research conducted in Australia. The correlation between herbicide application and calcium deficiency is explored, highlighting both positive and negative impacts. The paper concludes with recommendations for sustainable herbicide use and alternative weed management strategies.

Climate change poses a significant threat to European security, implicitly to Romania’s naval forces in the Black Sea. Rising sea levels, extreme weather events, and ocean acidification impact maritime operations, infrastructure, and personnel, with potential ramifications for regional stability. This paper explores the implications of climate change for the Romanian Navy and proposes "Green Defence" strategies to enhance resilience and sustainability. These strategies encompass energy efficiency, renewable energy integration, sustainable procurement, and the application of advanced functional materials in naval operations and infrastructure. By adopting a proactive and multifaceted approach, the Romanian Navy can adapt to the changing climate, ensuring operational effectiveness while minimizing environmental impact. This approach aligns with broader European security concerns and contributes to a more sustainable and resilient defence posture in the face of climate-related challenges.

This study investigates the potential inhibitory role of Amentoflavone against the Ebola virus, with a focus on the viral protein VP24 structure. Molecular docking simulations were conducted to assess the binding affinity and interaction between Amentoflavone and the VP24 protein. The results revealed promising docking scores, suggesting favorable binding of Amentoflavone to the VP24 structure. These findings provide valuable insights into the potential therapeutic efficacy of Amentoflavone against Ebola virus infection by targeting specific viral proteins. Further experimental validation is warranted to confirm these docking results and elucidate the mechanism of action underlying Amentoflavone's antiviral activity. This study contributes to the ongoing efforts to develop novel therapeutic strategies for combating Ebola virus disease.

Dengue virus infection poses a significant global health threat, particularly in tropical and subtropical regions. In this study, we employed molecular docking techniques to investigate potential inhibitors of Dengue virus type 1 envelope protein. Through a series of docking simulations, we identified Amentoflavone as a promising candidate with favorable binding affinity. Our results indicate that Amentoflavone exhibited a binding energy of -10 kcal/mol, suggesting strong interaction with the target protein. These findings highlight the potential of Amentoflavone as a therapeutic agent for combating Dengue virus infection. Further experimental validation is warranted to confirm its efficacy and safety profile. This study underscores the utility of in silico approaches in drug discovery and development against emerging infectious diseases like Dengue.

Advances in early detection of Breast cancer and treatment improvements have significant-ly increased survival rates. Traditional screening methods, including mammography, MRI, ultrasound, and biopsies, while effective, often come with high costs and risks. Recently, thermal imaging has gained attention due to its minimal risks compared to mammography, although it is not widely adopted as a primary detection tool since it depends on identifying skin temperature changes and lesions. The advent of machine learning (ML) and deep learning (DL) has enhanced the effectiveness of breast cancer detection and diagnosis using this technology. In this study a novel methodology for developing an interpretable computer-aided diagnosis (CAD) system for breast cancer detection, leveraging explaina-ble Artificial Intelligence (XAI) throughout its various phases. To achieve these goals, we proposed a new multi-objective optimization approach named Hybrid Particle Swarm Optimization algorithm (HPSO) and Hybrid spider Monkey Optimization algorithm (HSMO). These algorithms simultaneously combine the continuous and binary representations of PSO and SMO to effectively manage trade-offs between Accuracy, feature selection and hyperparameter tuning. We evaluate several CAD models and investigate the impact of handcrafted methods such as Local Binary Patterns (LBP), Histogram of Oriented Gradients (HOG), Gabor filters, and edge detection. We further shedding light on the effect of feature selection and optimization on feature attribution and model decision-making processes using the SHapley Additive exPlanations (SHAP) framework, with a particular emphasis on cancer classification using the DMR-IR dataset. The results of our experiments demonstrate in all trials that the performance of the model is improved. Also with HSMO our models achieved a high accuracy of 98.27% and F1- score of 98.15% while selecting only 25.78% of the HOG features. This approach not only boosts the performance of CAD models but also ensures comprehensive interpretability. This method emerges as a promising and transparent tool for early breast cancer diagnosis.

We consider the problem of finding the largest clique of a graph. This is an NP-hard problem and no exact algorithm to solve it exactly in polynomial time is known to exist. Several heuristic approaches have been proposed to find approximate solutions, Markov Chain Monte Carlo being one of those. In the context of Markov Chain Monte Carlo, we present a class of ``parallel dynamics'', known as Probabilistic Cellular Automata, which can be used in place of the more standard choice of sequential ``single spin flip'' to sample from a probability distribution concentrated on the largest cliques of the graph. We perform a numerical comparison between the two classes of chains both in terms of the quality of the solution and in terms of computational time. We show that the parallel dynamics are considerably faster than the sequential one while providing solutions of comparable quality.

This thesis presents a comprehensive review of cancer, with a particular focus on its physical and biochemical basis. Cancer, a leading cause of mortality worldwide, is characterized by the uncontrolled growth and spread of abnormal cells. Understanding the fundamental differences between cancerous and normal cells is essential for developing effective diagnostic tools and therapeutic strategies. The review begins by exploring the physical anomalies of cancer cells, including their irregular shape, size, and structural organization. These cells often exhibit altered cell membranes, disrupted cytoskeletal architecture, and irregularities in cell adhesion and communication, which contribute to their invasive and metastatic potential. The biochemical basis of cancer is examined in detail, with an emphasis on the dysregulation of key metabolic pathways. Cancer cells undergo profound metabolic reprogramming, often referred to as the Warburg effect, where they preferentially utilize glycolysis over oxidative phosphorylation, even in the presence of oxygen. This metabolic shift supports the rapid proliferation of cancer cells and their survival in hypoxic conditions. Additionally, cancer cells produce abnormal proteins that contribute to tumor progression, such as mutant p53, and fail to produce critical tumor suppressor proteins like RB1, leading to unchecked cell division and evasion of apoptosis. Furthermore, the thesis reviews the role of oncogenes and tumor suppressor genes in cancer development, highlighting how mutations and epigenetic alterations drive the transformation of normal cells into malignant ones. The complex interplay between these genetic changes and the tumor microenvironment is also discussed, emphasizing the importance of signaling pathways, immune evasion, and angiogenesis in cancer progression. This detailed review synthesizes current research and insights from authoritative sources, including peer-reviewed journals and foundational medical texts, to provide a thorough understanding of the physical and biochemical underpinnings of cancer. The findings underscore the importance of continued research in these areas to advance the diagnosis, treatment, and prevention of cancer.

Breakthrough Sparsity Theorem, derived independently by Donoho and Elad \textit{[Proc. Natl. Acad. Sci. USA, 2003]}, Gribonval and Nielsen \textit{[IEEE Trans. Inform. Theory, 2003]} and Fuchs \textit{[IEEE Trans. Inform. Theory, 2004]} says that unique sparse solution to NP-Hard $\ell_0$-minimization problem can be obtained using unique solution of P-Type $\ell_1$-minimization problem. In this paper, we derive noncommutative version of their result using frames for Hilbert C*-modules.

This paper delves into the intricate nature of the different essence interactions that shape our perceived reality, leveraging a blend of existing empirical data and original experiments. Through a multidisciplinary approach encompassing quantum mechanics, general physics, metaphysics, philosophy, and spiritualism, it seeks to elucidate the fundamental interplays governing phenomena such as gravity, mass, electromagnetism, force, motion, and quantum mechanics. This exploration promises a reexamination and unification of these principles, offering novel perspectives on the extraordinary phenomena that underpin our reality. By comprehending and manipulating these interactions, the potential arises to orchestrate reality towards desired ends. This study not only unveils compelling avenues for scientific advancement but also proposes transformative technologies and concepts, including light-speed transportation, remote viewing, communication with the deceased, alchemy, and the realization of what is commonly perceived as magic. These visionary notions not only push the boundaries of current understanding but also provide a captivating glimpse into the future possibilities that may await humanity.

With growing global emphasis on sustainable development and social responsibility, Environmental, Social, and Governance (ESG) ratings have emerged as critical metrics to evaluate commercial banks’ operating performance. The paper utilizes panel data spanning 2009 to 2022 from large state-owned and joint-stock commercial banks in China. It employs a two-way fixed effect model and robustness tests, alongside tests for heterogeneity analysis and moderating effect to conduct empirical analysis. The findings of the fixed effect model indicate that improvements in ESG performance have advantageous impacts on commercial banks’ operating performance, particularly with higher growth rate for operating income Robustness tests including mixed regressions, Tobit tests, variable substitutions, and tests of endogenous bias have validated that initial regression findings still hold. Tests of heterogeneity analysis reveal that among large state-owned commercial banks, banks with higher leverage, larger major shareholder ownership, and larger banks scales, ESG performance can significantly affect the banks’ operating performance, and the relationship exhibits positive. Furthermore, the paper finds that GDP growth rate, CPI and analysts’ coverage can strengthen the relationship between ESG performance and commercial banks’ operating performance through moderating effects. The research provides policy proposals and strategic recommendations tailored for policymakers, banks, and investors, building on these insights.

China has enacted a range of policies to improve its water ecosystem since the middle of the 20th Century. Some of these measures include the creation of Seven River Conservancy Commissions, the development (combination and recombination) of series of ministries and departments to address environmental pollution and degradation, and recently the implementation of the river chief system. To understand if the river chief system can transfer to other political jurisdictions the authors gathered data using key word searches of the Web of Science and Google Scholar, official government sites, media sites and key international organizations. Based on this the authors review the development of the river chief system in the context of broader ecological reforms, place the rise of the river chief in the context of potential lessons for future improvement, and speculate on the possibility that China could transfer the river chief to countries facing similar challenges in their water governance regimes.

This paper presents proof of Riemann's hypothesis by utilizing the golden ratio and the ellipse's eccentricity in six dimensions. This proof extends across all scientific fields. this research introduces logical and mathematical principles for distributing, recognizing, and categorizing prime numbers. It also explores the relationship between prime numbers and the complex conjugate of five prime numbers in various dimensions. Accordingly, it delves into the classification of even numbers based on prime numbers. This study examines the proof of Riemann's hypothesis from a geometric dimension perspective. Based on this, the mathematical structure of an integrated theory is defined. properties and principles associated with prime numbers reveal connections between quantum mechanics and general relativity.

Costa Rica, widely acknowledged for its environmental leadership, is now facing a significant challenge in managing waste, a situation that could potentially compromise both its environmental and public health achievements. This analysis delves into the waste management issues in Costa Rica, particularly in urban areas such as San José, responsible for nearly half of the country's waste. The study identifies several pressing concerns, including the heavy burden on landfill capacities, a recycling rate of just 9.6%, and substantial regional differences in waste management practices.To address these challenges, the research employs a combined methodology, utilizing Linear Regression (LR) and AutoRegressive Integrated Moving Average (ARIMA) models to project future trends in CO2e emissions and waste minimization from 2024 to 2050. This method underscores the vital need for public involvement and the introduction of innovative strategies in waste management. The research also introduces a Waste Management Innovation Index to compare Costa Rica’s practices with those of leading nations like Germany and South Korea, identifying key areas for improvement.Furthermore, the study incorporates insights from stakeholders, revealing the intricate balance of cultural, economic, and regulatory factors that shape waste management policies. Despite efforts by the government, such as the Environmental Health Route and the National Circular Economy Strategy, results show limited progress, particularly in rural regions. The study highlights the urgent need for better infrastructure, targeted public awareness campaigns, and the use of advanced technologies like Artificial Intelligence (AI) and blockchain to enhance sustainable waste management practices. The research provides strategic recommendations to help Costa Rica improve its waste management systems in line with international standards, ensuring long-term environmental sustainability and protection of public health.

The significant improvements in Generative Artificial Intelligence (GenAI) observed in recent years present Higher Education with both an opportunity and a significant challenge. Its successful integration will require careful planning and sound pedagogical underpinnings, both in regard to learning and teaching, as well as assessment and feedback. Drawing upon theories from the more-than-human world, as well as concepts such as originality, equality, and sustainability, it is possible to develop a dialogue around GenAI that places the students’ learning journey at the heart of the discussion.

In this paper, the P versus NP problem is studied based on a six-dimensional space-time perspective. The gap between the P-class and NP-class arises from the relationship between time and the solution, as well as the answer that is independent of time. The complexity of solving a problem depends on the time dependence of the answer. Solving problems whose answers do not depend on the passage of time is very difficult and impossible. Like the description of the gravitational factor in Newtonian physics, NP class problems require different mathematical tools. Based on the generalization of physical facts in mathematics, based on six-dimensional space-time, a method to solve problem P versus NP problem has been stated. The results of this study offer a fresh insight into information processing that occurs independent of the passage of time.

Two approaches are being proposed to complements existing practical implementations of quantum information processing; (a) Multiplexed Michelson interferometry for Linear Optical quantum computation which should in principle split further an initially split beam to yield new sets of beams which are scalable to multiple interferometric outputs beyond just the dual output in Mach Zehnder interferometry. Generally Interferometry is applied in quantum computation particularly linear optical quantum computation schemes such as K.L.M protocol using the Mach-Zehnder interferometer, however a multiplexed Michelson interferometry enables the production of scalable cross-correlated beams making it suitable for optical multi-qubit operations. (b) Coupled LDR Circuits for Quantum emulation which can model cross correlation and probabilistic qubit states to enable parallelization and Gating on Classical electrical circuits. The system is to be designed as a network of electrical circuits coupled to each other using electrical coupling elements and are equipped with a light dependent resistor (LDR) alternatively referred to as photo-resistor to provide variable resistance in response to varied intensity of incident light. The maximum threshold current state which is being defined for the circuit and a minimum current state corresponds to 1 and 0 binary states respectively, however an intermediate current state models a superposition of 1 & 0. Likewise varying the intermediate current values closer to either 1 or 0 is akin to a probability rotation of the qubit states which is achieved by varying resistance using the LDR where the multi-circuit coupling interaction helps emulates cross-correlation of multi-qubit systems. The proposed system can be useful at least as a tool for informative applications in a classical framework.

We define the function $Col: \mathbb{N} \to \mathbb{N}$ as the Collatz function, given by $3n + 1$ if $n$ is odd and $\displaystyle\frac{n}{2}$ if $n$ is even \cite{Lagarias1990}. The conjecture postulates that for any positive integer, at some point, its iteration will reach 1, or equivalently, every orbit will fall into the periodic cycle $\{4, 2, 1\}$. Two conditions would invalidate the conjecture: the existence of a divergent orbit or the presence of another cycle. In 2019 Terence Tao \cite{tao} proved that almost all orbits converge to the trivial cycle of $\{1,4,2\}$, in this work we will prove the non-existence of divergent orbits. The central idea is to decompose the dynamic system $Col$ into a binary dynamic system, generated by different compositions of two functions. This differs from a typical dynamic system, which is generated by the iteration of a single function. We consider the system generated by the functions $\theta, \psi: \mathbb{R} \to \mathbb{R}$, defined as $\displaystyle\theta(x) = \frac{x}{2}$ and $\displaystyle\psi(x) = \frac{3x + 1}{2}$, denoted as $\langle \theta, \psi \rangle$. We examine sequences of functions in $\langle \theta, \psi \rangle$ of the form $S_k(x) = s_k \circ S_{k-1}(x)$ with $s_k \in \{\theta, \psi\}$. We define a function that assigns to each element of these sequences an integer, called the minimum value positive integer or simply the minimum value. This corresponds to the smallest positive integer $n$ such that $S_k(n)$ is an integer. As we will prove later, the minimum value is monotonically increasing, meaning that increasing the terms of the sequence will never result in a value lower than the previous one. Based on this behavior, we distinguish two types of sequences: stable ones, where the minimum value is constant from a certain point, and unstable ones, where the minimum value is divergent. The main result for unstable sequences is that when the slope of the sequence is divergent, the sequence is unstable. From this result, we can prove that there are no divergent orbits for the function $Col$.

This paper contains a comparative review of existing Zitterbewegung models. It attempts to synthesize them by offering a toy model containing an extra hypothesis of electromagnetic self-oscillation at the Fermi scale (10−15m). Inspired by Bell violation experiments, Zitterbewegung models and hydrodynamic walker studies, we revisit standing waves in quantum mechanics, echoing de Broglie-Bohm pilot wave theories. Starting with the electromagnetic self-oscillation hypothesis at the Fermi scale we propose an emergent and deductive hierarchical electron structure across multiple scales. The model spans Fermi, Compton (10−13m), Bohr (10−11m) and finally de Broglie (>10−10m). At the Fermi scale, the hypothesis is one of "source-free chiral light", known as the "zilch", emerging as a self-oscillating electromagnetic field at the Schwinger limit. This self-interaction of retarded potentials due to real relativistic delays is a generic self-oscillation of Liénard-Wiechert potentials. This primary Fermi oscillation accounts for charge and mass at the Fermi scale. It generates secondary stable "auto-orbits" dynamics at the Compton scale, manifesting as observable spin and other quantum properties of the usual Dirac zitterbewegung models. These zitter models account for known electron characteristics, including mass, charge, spin and g/2 anomalous factors up to 9 digits precision. We explain the de Broglie wavelength through Doppler-shifted Compton-scale standing waves, in the tradition of de Broglie. The framework extends to electron-positron pair production at the Schwinger limit, described as a result of natural light focusing in non-homogeneous media, utilizing René Thom’s catastrophe theory. This offers a new perspective on baryogenesis and matter emergence from electromagnetic fields. We dub this toy model the "sub-standard" model of the electron.

Swamp soil presents significant challenges for infrastructure development due to its soft and deformable nature, which compromises the stability of structures. Traditional wood pillars, while cost-effective and locally available, suffer from degradation caused by moisture and biological organisms. This study investigates various methods to strengthen wood pillars, focusing on the combination of wood and concrete pillars to enhance durability and load-bearing capacity in swamp soil environments. Laboratory experiments and field tests demonstrate that encasing wood pillars in concrete or using composite materials significantly improves their mechanical strength and resistance to deformation. The results highlight the potential of these techniques to provide sustainable and economical solutions for construction in swamp areas, ensuring greater stability and longevity of the infrastructure.

This paper investigates location-based adaptive beamforming techniques, including Maximum Ratio Transmission (MRT) and Zero Forcing (ZF), in complex wireless environments. The study leverages a digital twin simulation of the University of Glasgow campus to evaluate the proposed schemes under realistic conditions, such as user mobility and multipath propagation. The results demonstrate significant performance improvements with the location-based beam steering approaches. In the open space scenario, the location-based schemes achieved up to 40\% higher Signal-to-Interference-plus-Noise Ratio (SINR) and 30\% higher received power, along with reduced interference. The gains were even more pronounced in the digital twin environment, with up to 50\% improvement in SINR and 40\% increase in received power. Furthermore, the study evaluates the energy efficiency of the location-based adaptive beamforming techniques, showing up to 20\% reduction in energy consumption compared to conventional fixed-beam approaches.

This paper presents a novel approach to decoding the Indus script, which was used by the Indus Valley Civilization (IVC) from approximately 3300 to 1900 BCE. The main focus of this research is the structural analysis of the signs within the Indus script. The central objective of the paper is to determine whether the Indus script can be classified as an alphabet, and it aims to provide compelling evidence regarding the number of primary signs. This includes establishing the actual count of Indus signs through the decomposition of compound signs, identifying diacritics and analyzing their consistent usage, as well as exploring the underlying concepts and implications associated with sign extraction. To comprehensively examine the Indus script, the paper analyzes over 400 signs, encompassing the entire script rather than a select subset of signs or texts. The visual decomposition of the signs employs a simple grid methodology. By summarizing the logical findings, the paper successfully identifies the primary signs and develops an understanding of their phonetic representation within the alphabet. The study recognizes the diverse writing styles used to combine the basic signs, The writing style of the Indus script incorporates variations in formation, composition, and combination, resulting in a significant number of signs. The research findings indicate that the Indus Script primarily consists of only 40 core signs.

It is commonly held that gravitation is a major force field influencing matter. Existing models regard gravitational interaction as a singular weak force; the weakest among the four fundamental forces defined in physics. Recent experimental findings, in both controlled laboratory experiments and natural occurrences, nevertheless, have unveiled the presence of a gravitational repulsion alongside gravitational attraction in the universe. This series of studies reveals that the observed gravitational force results from two immensely powerful distinct forces—gravitational repulsion and attraction—nearly equal and opposing thus in a state of near equilibrium in nature. While the theory of 'Universal Gravitation' established the proportionality of the gravitational force to mass, the recognition of gravitational repulsion force proportional to the temperature as a manifestation of thermal energy has only emerged from present experimental insights. Furthermore, the imbalance between these two forces has been identified as the Newtonian force, initiating the motion of an object. It provides a compelling explanation for the accelerating expansion of the universe: during atomic fusion in stars, a portion of mass is converted into energy. This process increases the energy and decreases the mass of stellar objects. The increase in energy enhances the repulsive force among them, while the reduction in mass diminishes their gravitational attraction, leading to the accelerating expansion of the universe.This paper introduces a model elucidating the characteristics of gravitational forces and the transmission of energy within matter through the concept of 'Gravitational Currents.' A set of postulates is formulated to elucidate the interaction of gravitational fields with matter and the presence of gravitational currents. The discussion is supported by experimental evidence substantiating these concepts.In this series of experiments, a gyroscope - a standard apparatus in the scientific community with a spinning wheel mounted at one end of a freely pivoted rod having full degrees of freedom - is utilized. When the wheel is set in rotation, the rod carrying the wheel precesses[1] around the vertical axis at the pivoted end, while levitating in free space defying the Earth's gravitational attraction. This paper establishes that the conventional explanation involving the cross product of two vectors—the torque due to weight and the angular force (change of angular momentum) of the wheel—fails to account for the observed revolving and lifting forces. Instead, it is demonstrated that these forces result from the upward shear force (which is the lifting force in this case) generated within the axis of the rod and the wheel itself. This phenomenon is attributed to the flow of energy, conceptualized as gravitational current, within the axial rod in the Earth's gravitational field. The described process can be envisioned as a gravitational motor with gravitational current flowing through matter in a gravitational field.The results of the experiments substantiate the conclusion that there exist two fields defined as the intrinsic field and the natural force fields. The intrinsic gravity field is innate (linked) to every object, matter or entity in the universe, and it is dispersed in all directions in free space independent of other entities. The actual force fields manifest between any two objects in the universe once they become cognizant of each other's existence through their intrinsic fields.The inherent force field exhibits a preference/tendency for existence within a medium rather than in free space, akin to the way a magnetic field runs within ferromagnetic materials rather than in open space. If external force fields pass/runs through the medium, it affects the internal force fields of the medium, depending on the magnitudes and the directions of the external force fields and intrinsic force fields. This implies that energy moves through the force field, and under the influence of the gravitational field, this energy flow can be conceptualized as a gravitational current.Gravitational waves and electromagnetic waves share similarities in their roles in transmitting energy through open space. The potential for an analogy within a unified theoretical framework connecting electromagnetic fields and gravitational fields has surfaced, echoing Einstein's attempted unified theory proposed in 1916. The paper delves into the parallels between electromagnetic motors and gravitational motors.Furthermore, alongside the concept of gravitational currents addressed in this paper, the research also elucidated a precise definition of the [Newtonian/mechanical] “force” and mechanism for its origination and function, termed: Intrinsic Energy Spin Force (IESpinF). The analysis presented here demonstrates that the Newtonian/mechanical force arises from a perturbation or imbalance within the equilibrium of gravitational IESpinF, which includes both repulsion and attraction forces. [1] One of the main properties of gyroscopic action is “precession”. Precession is a change in the orientation of the rotational axis of a rotating body. If the axis of rotation of a body is itself rotating about a second axis, that body is said to be precessing about the second axis.

Several studies report an impact of the neurotransmitter dopamine (DA) on human immune cells, with effects dependent on immune cell type addressed and their activation status. Another contributing factor appears to be sex, as sex-specific differences in the dopaminergic pathway are described in the neurological context as well as in autoimmune diseases. However, a deeper understanding of these differences in peripheral immune cells remains limited. In this study, we investigated the effects of dopaminergic stimulation on activation and cytokine secretion of peripheral blood mononuclear cells from women and men using flow cytometry, ELISA and multiplex assay. We found a B cell-driven downregulation in cytokine secretion of monocytes exclusively from women under physiological conditions. Moreover, B cells from men showed higher dopamine receptor (DR) expression, which was shown to be further increased by sex hormones only in men. In monocytes from women, an acute inflammatory stimulus via CpG combined with dopaminergic stimulation caused a switch to a proinflammatory phenotype, which was less pronounced in men. These novel findings in sex-specific responses to dopaminergic stimulation are crucial for understanding DA’s function in the healthy and activated immune system and provide evidence to treat DA-related pathologies in a sex-specific manner.

Kolmogorov–Arnold Network (KAN) is an emerging interpretable neural network compared to fully black-box MLPs. Recently, emerging works focus on comprehensive and fair comparisons between KAN and MLP in various tasks. However, these works didn't focus on the strongest advantage of KAN: generating symbolic outputs. The ability of KAN to provide scientific insights or even discover new science is under-examined. In this work, we propose several novel metrics to measure how well a KAN performs on symbolic function fitting: R^2-Mean, weighted R^2-complexity loss, and ranking metrics. We also propose a metric to determine mathematical complexity of a target function and evaluate KAN with several functions of different mathematical complexity. Additionally, we also tried inputs with different ranges to find the effect of normalization.

The study of supermassive black holes has significantly advanced our understanding of galaxy structures, yet fundamental questions remain, particularly concerning the structure and dynamics of massive black holes. This article addresses the core structure of massive black holes, defined as those originating from supernova events. Integrating the concept of "Dachus density," a state of maximum matter density, I propose that the core of all massive black holes exists at this density. The research investigates the size of these cores and their event horizons, using Cygnus X-1 and Sagittarius A* as examples. Calculations reveal that the core size is exceedingly small compared to the overall black hole, with the core's volume being up to ~155 orders of magnitude smaller than the event horizon volume in the case of Sagittarius A*. The article briefly explores the implications of a rotating Dachus core on the black hole's structure, including the "mantle" region between the core and the event horizon. The discussion extends to absolute zero temperature, asserting that for a non-spinning, static Massive black hole, the temperature of its core reaches 0[K] as in this state, particles do not move in relation to each other and do not have any kinetic and in particular rotational Energy.

Introduction – Elections are a cornerstone of democratic societies, enabling citizens to express their preferences and shape the direction of their governments. Economic conditions, political dynamics, and social factors often play pivotal roles in influencing voter behavior and determining electoral outcomes, making elections a key area of study in understanding governance and policy change. Objectives – This study examines how key economic factors like inflation, unemployment, and poverty influence election results in Ghana. It also looks at how these economic elements shape voter choices and predicts the possible outcomes of the 2024 general elections using past data. Methodology – The study used historical economic and political data from 1992 to 2023, applying statistical models like ARIMA (Auto-Regressive Integrated Moving Average) to forecast future election outcomes. Economic indicators such as inflation and unemployment were included to study their relationship with voter behavior. Findings - The results show that economic factors significantly impact voter turnout and party vote share. High inflation and unemployment rates tend to reduce voter support for incumbent parties. The model also predicts possible outcomes for the 2024 election based on these economic trends. Conclusion and Recommendation – The study concludes that improving economic conditions, such as reducing unemployment, could positively influence electoral outcomes for incumbents. It is recommended that policymakers focus on stabilizing the economy to enhance electoral success.

The border between Niger and Libya, often described as an "ungoverned space," epitomizes the complex interplay of economic, political, and security challenges within the Sahel region. Authorities and international actors have made various efforts to establish control, but tribal structures predominantly manage governance in these areas. These structures lack formal institutions and rely heavily on external security interventions to combat terrorism and irregular migration. The increasing militarization of the region raises significant concerns about the long-term efficacy of these approaches in achieving sustainable security. This study argues that enduring stability in such contexts requires a nuanced balance of economic, political, and social factors. The research methodology includes a comprehensive literature review of security issues, governance, state fragility, and counter-terrorism, utilizing scientific journals, books, reports, and newspapers. The study investigated the dual nature of ungoverned spaces, examining their role in facilitating terrorism and organized crime while highlighting the critical need for governance to enhance citizen welfare and support state functions. Recent developments in Libya and the Sahel under-score the urgency of addressing security and developmental challenges. The study concludes by advocating for sustainable political and development initiatives over militarization, emphasizing the necessity of a new social contract to address the security challenges in the Sahel region effectively.

This article explores the relationship between Wang Yangming's philosophy and the new quality productivity, revealing how the new quality productivity, while inheriting the core ideas of Yangming's philosophy, achieves a higher level through innovation and development. The new quality productivity emphasizes the integration and innovation of knowledge, technology, and information, characterized by knowledge-driven innovation, information technology support, sustainable green development, and global collaborative development. The fusion of Yangming's philosophy and the new quality productivity holds significant theoretical and practical implications.

A contemporary technique for calculating seismic risk is earthquake nowcasting (EN), which analyzes the progression of the earthquake (EQ) cycle in fault systems. 'Natural time' is a novel idea of time that serves as the foundation for EN assessment. The earthquake potential score (EPS), which has been discovered to have useful uses regionally and worldwide, is a unique tool EN uses to predict seismic risk. For the estimation of the EPS for the occurrences with the highest magnitude among these applications, we have since 2021 concentrated on Greece territory, applying sophisticated Artificial Intelligence (AI) algorithms, both wise (semi)supervised and unsupervised models, along with a customized dynamic sliding window technique that performs as a stochastic filter able to fine-tune the geo seismic occurrences. Long short-term memory (LSTM) neural networks, random forests, and clustering (geospatial) models are three machine learning techniques that are particularly good at finding patterns in vast databases and may be used to enhance earthquake prediction performance. In this study, we attempt to forecast whether practical Machine-learning and AI/Game-theoretic-based approaches can help predict big earthquakes and the normal future seismic cycle for 6-12 months. Specifically, we focus on answering two questions for a given region: (1) Is there a chance that a significant earthquake—say, one with a magnitude of M ≥ 6.0 will happen in the upcoming year? (2) What is the largest earthquake magnitude predicted in the upcoming year, and with which exact geographic coordinates (GCS)? Our results are quite promising and project a high precision accuracy score (≥ 98%) for seismic nowcasting in terms of four predictive parameters: the approximate (a) latitude, (b) longitude, (c) focal depth, and (d) magnitude of the phenomena.

This article investigates the fundamental principles that establish universal limits in physical phenomena, such as the uniformity of physical laws and Energy conservation, leading to the concepts of maximum speed, locality, and maximum density. These principles guide me to explore Quantum Black Holes—relativistically rotating, miniature charged black holes with a singular core at the highest possible density. Uniquely, these Quantum Black Holes maintain all quantized charges, including gravitational ones. The study further demonstrates that quarks and leptons are composed of these Quantum Black Holes, redefining them as the actual elementary particles.Exploring these particles reveals that they emit Energy outward, modifying the curvature of nearby space-time. This discovery provides new insights into local space-time dynamics, characterized by a single equation that includes the influence of all charges and hidden Energy. By the conclusion of this article, I show that Quantum Black Holes offer explanations for several Standard Model deficiencies: the nature of luminous, dark, and anti-Matter; the mass, size, and quantized charges of all elementary particles (including gravitational); the nature of neutrino oscillations; and the mechanism by which electric charges remain bound even though the same type of electric charge components must repeal each other.

The Polynomial coefficient function, from the complex hyperspace Cⁿ in itself, is the function Fⁿ that provides the coefficients of the polynomial (x - a₁)(x - a₂)... (x-a_n). A proof of the fundamental theorem of algebra is given where the surjectivity of this function is obtained from a Recurrent Coefficient Equation.

Financial technologies (Fintech) have become an indispensable part of most of the business infrastructure around the world. The Fintech ecosystem provides this solution by providing a suitable environment for all financial techno services to synergize. The objective of this paper is two folds; first, it aims to investigate & summarize Fintech programs products, and services in Saudi Arabia. Second, it maps the sustainable development goals (SDG) and indicators of the Fintech programs in Saudi Arabia. Secondary data was collected from published reports, institutional & governmental websites, official portals, and research papers focusing on the companies operating in Saudi Arabia. In the second step, the content analysis method was employed to investigate the features and characteristics of each program to map it to the sustainable development goals (SDGs). It was found that Fintech in Saudi Arabia is addressing SDGs goals 1, 2, 5 8 & 17. The paper also attempted to map further the SDG indicators with the products and services which Fintech companies are offering. This study will be beneficial for the institutions and policymakers of the Fintech industry to fill the gaps in addressing SDG goals which is a global agenda for eradicating poverty and offering sustainable development opportunities.

Maxwell's equations accurately describe the propagation of electromagnetic (EM) waves. However, the conventional formulation implies invariance to observers, posing challenges in explaining how the wave is perceived by different observers. For example, Doppler effect shows that observers perceive the same EM wave differently.By employing mathematical transformations, we derive a general form of Maxwell’s wave equations by incorporating a "time scaling" factor to account for observer perception. The original form is shown to be a special case when static. The Doppler effect and Sagnac effect are directly derived from Maxwell’s equations. All the results are consistent with established experiments.Our findings offer a fresh perspective, promising a deeper understanding and unification of EM phenomena. We extend Maxwell’s equations to describe not only the propagation of an EM wave, but also how it will be measured by different observers, say, antennas.

We introduce the notion of functional equiangular lines in finite rank modules over subrings of $\mathbb{R}$. We show that van Lint-Seidel relative and Gerzon universal bounds hold for this most general lines.

This paper investigates optimal maintenance strategies for centrifugal compressors with electrical motor drivers using a Weibull analysis approach combined with rank regression, Fisher matrix, and median ranks. By leveraging data from Oreda 6, the study proposes a methodology to establish baseline intervals for corrective, preventive, predictive, and proactive maintenance in the absence of comprehensive historical data. The analysis reveals key Weibull parameters, including shape and scale factors, and calculates reliability metrics such as the mean time to failure (MTTF) and mean remaining life (MRL). The results suggest effective maintenance intervals and highlight the utility of Weibull analysis in enhancing maintenance strategies. This approach offers a robust framework for optimizing maintenance practices, even with limited historical data.

This article reviews all the major stages in the origins of life. From the emergence of matter in the initial Big Bang to the modern, civilized human being. On an immaterial level, it is proposed and explained how consciousness necessarily takes precedence over matter. Next, we explain how consciousness, with its ability to process information, selected the water molecule to breathe life into the periodic table of elements. We also explain why the notion of entropy allows us to evolve: "Die Entropie der Welt strebt einem Maximum zu" (second principle) and, therefore, takes precedence over the notion of energy, which, on the contrary, encourages us to preserve what we have: "Die Energie der Welt bleibt konstant" (first principle). This is followed by a discussion of the importance of quantum coherence and the need to rely on a second quantization formalism for a proper understanding of the physical-biochemical properties of water. Moreover, throughout the argument developed on the best and most fundamental things science has to offer, care is taken to link this knowledge to the great philosophies of the West (Greece), the East (China, India) or even to practices of a shamanic nature (Africa, America). Hence, finally, the proposal to reconsider all musical practice within the framework of the diapason of water at a frequency of 429.62 Hz, as well as all therapeutic practice on the basis of seven clearly identified and established frameworks of thought.

Myelination, the process of forming a myelin sheath around nerve fibers, is critical not only during early development but also throughout adulthood. This article explores the multifaceted impacts of myelination on the adult brain, highlighting its importance in cognitive functions, neurological health, and overall brain efficiency. In adults, efficient myelination enhances information processing speed, supports memory consolidation, and contributes to cognitive reserve, potentially delaying the onset of neurodegenerative diseases. Myelination ensures synchronized neural activity and energy-efficient brain function, playing a key role in complex cognitive tasks and coordination. Despite a slower rate of plasticity compared to early development, the adult brain retains the ability to adapt and learn, with myelination facilitating these processes. This article also draws parallels between myelination in the brain and learning curves in deep learning Perceptrons, emphasizing how reduced stimulation and experience can significantly slow down cognitive and learning processes. Additionally, the clinical implications of myelination are discussed, including its role in multiple sclerosis and age-related cognitive decline, along with strategies to maintain and enhance myelin health through lifestyle choices and emerging pharmacological interventions. Understanding the ongoing significance of myelination in the adult brain, and its comparison to artificial neural networks, is crucial for developing interventions to support cognitive health and mitigate neurological disorders.

Quantum dots are semiconductor Nano-structures with Optical or photoelectric properties and Quantum mechanical properties such as Quantum confinement due to the Nano-scale size of the molecular structure where Quantum mechanical effects are dominant. Because of its Optical properties Quantum dots have found applications in the development of future Solar cells and Photovoltaic detectors. The developments of these Solar cells and detectors are made possible through the use of Spray-coated layering of colloidal solutions containing the quantum dots forming what can be regard as thin quantum dot films, of which the compound thickness of all the layers is in nanometers. These quantum dots are capable of detecting a very wide range of electromagnetic frequencies and even single photon sources with very fast response time overall promising enhanced sensitivity. The features of quantum dots films gives them desirable advantages for detecting minute phase changes in Laser interferometric observatories such as LIGO which was designed and developed to detect gravitational waves coming from distant astrophysical sources. However the detection of low frequency gravitational waves with longer wavelength and those of much lower amplitudes have been rather elusive even with the high sensitivity of LIGO, as its usual Photodetector may not be sensitive to the interferometric phase changes due to gravitational waves of longer wavelengths and low amplitudes. As a potential means of improving phase change detection in LIGO, the use of quantum dots as photodetectors is conceptually proposed exploiting the fast reaction times and its sensitivity to wider range of frequencies. Whether it detects the interferometric phase changes induced by subtle amplitude or low frequency gravitational waves or not, it still promises an improvement to the detection capabilities of LIGO. Other interferometric gravitational experiments can also be performed, such as interferometric detection of Phase difference due to gravitational time dilation, using two laboratory interferometers one of which is positioned at sea level and the other at much higher altitude leading to a difference in gravitational potential. Together with the use of Quantum dot films as Photo-detectors one can detect the small interferometric phase difference between both interferometers due to Gravitational time dilation at different altitudes.

Working as a researcher, associate professor, or full professor in the field of biomedicine in Norway involves supervising students preparing for various degrees, such as Bachelor's, Master's, PhD, and MD. Additionally, there are visiting students from other departments and institutions in Norway, as well as from abroad, including various types of exchange students. Departments and Faculties provide guidelines and regulations on what is expected from students and their communication with supervisors throughout the study course. However, these guidelines are often too general, allowing for significant flexibility and varied interpretations from both the students' and supervisors' perspectives. This article focuses on personal experiences supervising biomedical Master's students in Norway. It covers several aspects, including student recruitment, initial instructions, routine work, graduation, and post-graduation interaction. The focus is on the supervisor's point of view, while the students' perspectives on this topic are reserved for further research.

The vaccine industry has undoubtedly contributed massively in the medical world, with hundreds of millions of lives saved as a result of the successful development of prophylactic and therapeutic vaccines against various infectious and oncological diseases. Simultaneously, there has been an ongoing evolutionary battle between polymorphic microbes and the human immune system, and various microbes have developed counter-responses against the human host immune system, by creating diverse “holes” of vulnerability in the innate immune system. Such mechanisms may have resulted due to the lower prophylactic and therapeutic focus upon sharpening the innate immune lines as directly as necessary. The overall objective of vaccine-development should be the sharpening of all immune departments that are targeted by various microbial agents for the purpose of transient innate immune suppression and the distribution of the microbial count/load at a systemic level. Likewise, it could be viable for the clinical research community to start focusing upon filling in the “gaps” of vulnerability that are now present in the pathways responsible for the proper natural immune activation and proportionate signalling toward the adaptive immune system. Perhaps, through such a process, the “road” toward the adaptive immune system, which is “old” and filled with “holes”, could be gradually transformed into a perfectly uniform “highway”, with all the required signals transmitted robustly from the innate to the adaptive immune system, before microbes manage to translate the various pathogenic proteins that transiently prevent such transmission altogether, until it becomes too late for the immune response to possibly develop in a proportionate and non-harmful manner to the organism. Such a scenario would be possible, given that it is almost impossible for human evolutionary growth to eventually stall and not risk experiencing a decrease as a result. Simultaneously, it is important for human society to bind by the principles of maintaining a healthy and nature-friendly lifestyle, given the philosophical quote of “We are what we eat.” The overall objective should be the facilitation of human and animal immune evolution over viral and bacterial molecular self-camouflaging from all possible directions, as a sharper human and animal evolutionary growth resulting from such actions could “cost” the sharper evolutionary growth of microbes as such, given that evolutionary patterns are based upon the models observed in Physics, in Newton’s Third Law of Motion, as well as in the First Law of Thermodynamics, which concerns the Conservation of Energy.

This study investigated the influence of Teacher Availability -TAV (Number of Available Teachers, Teacher Punctuality -TP, Teacher Promptness to Class -TPC) on Student Academic Achievement (SAA) in Public Senior Secondary Schools (PSSS) in Southwestern Nigeria. The descriptive survey research design of correlational type was adopted while the multi-stage sampling procedure was used in the study. A simple random sampling technique was used to select three (Oyo, Ogun, and Ekiti) states out of the six in Southwestern Nigeria, as well as one Senatorial District (SD) from each state. The proportionate-to-size sampling technique was used to select 40% of the Local Government Areas (LGAs) in each SD and 50% (101) of the schools in the sampled LGAs. A class of 3,030 PSSS II was used; 202 Mathematics and English Language teachers and 202 Heads of Department (101 each from Science and Arts) were purposively sampled, while 101 school administrators were enumerated. The instruments were TP ( =0.75); TPC ( =0.82); English Language Achievement Test-ELAT (KR-20=7.47) and Mathematics Achievement Test-MAT (KR-20=7.46). Data were analysed using descriptive statistics. Respondents’ ages were 46.5±5.20 years (teachers) and 17.60±1.60 years (students). There were 59.0% male teachers and 57.0% female students. The SAA (ELAT=45.7% and MAT=38.4%) was low. Also, TAV ( =3.36) was high against the threshold of 2.5, and TAV (ß=0.59, t=7.29) significantly contributed to SAA. Teacher availability influenced the student academic achievement in public senior secondary schools in Southwestern Nigeria. Hence, all the education stakeholders should pay attention to this for improved student academic achievement.

This study presents a novel approach to understanding evolutionary dynamics through topological analysis of genotypic structures. We model the genome of a simple organism as a topological torus undergoing mutations at a constant rate of 1% per generation. Employing persistent homology and other topological data analysis techniques, we investigate how these mutations influence the overall topology of the genomic structure over time. Our simulations reveal that specific critical mutations lead to significant changes in the homotopic and homologic properties of the torus. We interpret these topological shifts as potential markers for the formation of new subspecies. By identifying the precise points of topological "breaks" within the toroidal genomic representation, our model provides a quantitative framework for observing the incremental transformations that underpin major evolutionary developments. The results offer new insights into the thresholds of speciation and adaptation, demonstrating how gradual genetic changes can accumulate to produce qualitative shifts in organismal traits. This approach bridges the gap between microscopic genetic mutations and macroscopic evolutionary outcomes, potentially revolutionizing our understanding of evolutionary processes. Our findings have implications for various fields, including theoretical biology, genetic engineering, and conservation biology. The model provides a novel perspective on genetic resilience and adaptability, offering a foundation for future research on the relationship between genomic topology and evolutionary trajectories. It also emphasizes the innovative nature of the research and its potential impact on multiple fields of study.

This research explores the application of ARIMA (Autoregressive Integrated Moving Average) models and parallel computing techniques to analyze and forecast anemia diagnoses in children under 36 months in the Junín region of Peru. Using health data from 2023-2024, including insurance type, patient information, diagnosis dates, hemoglobin levels, and treatment details, we develop predictive models to understand trends and patterns in childhood anemia. The study aims to demonstrate the effectiveness of time series analysis and high-performance computing in addressing this critical public health issue. Results indicate improved forecasting accuracy and computational efficiency, potentially aiding in resource allocation and policy development for anemia prevention and treatment programs.

The Third U.S. National Marine Environmental DNA Workshop on June 2–5, 2024 brought together researchers, practitioners, and policymakers to overview and discuss: (1) environmental (e)DNA – defined as “DNA in the environment” – as a strategic U.S. national priority, (2) eDNA tool readiness and approaches to support decision-making, (3) emerging eDNA technologies, and (4) plans for implementation and adoption for environmental monitoring and ecosystem assessment “from microbes through whales”. Uses and applications of eDNA have been revolutionizing exploration, measurement, and monitoring of biodiversity across ecosystems, including the marine and freshwater aquatic environments emphasized in the Workshop, as well as terrestrial and aerial systems. The Workshop featured the launch of the new U.S. National Aquatic Environmental DNA Strategy from the White House Office of Science and Technology Policy (2024), with aquatic defined as freshwater to ocean waters, across all salinities; the Strategy was developed using outputs and a taskforce from the 2022 Second Workshop. The 2.5-day Third Workshop included speaker presentations, panel discussions, and networking on eDNA tools, applications, use, upscaling, and their future. The Workshop led into Capitol Hill Ocean Week (CHOW) events (June 5–6, 2024), during World Ocean Week. Note that this summary paper represents the author’s take-away view and interpretation, and not necessarily the overall views or consensus of the U.S. Government, Smithsonian Institution, workshop organizers, or speakers.

It is often said in human society that it all starts from the mind, and this is true. The answer to the question “Why is it that pets require much fewer years to fully develop than humans?” could be headed to the Theory of Relativity and the perceived time according to the levels of instinct and rationality. It is perhaps no wonder that the French language translates the word “mind” as “l’esprit”, which also means “spirit” in the English language. Given that the Theory of Relativity applies to all physical matter, the theory applies to chemistry, biology and psychology as well. The level of instinct is proportional with the perceived speed of time and implicitly, to the speed of time itself for the whole organism, given that the nervous system coordinates all bodily functions. A pet may experience a few years as humans experience over a decade, making their perceived lifetime to be approximately equal to the human’s. The same applies to the perception of space and its components. This aspect would emphasise upon the fact that all life on Earth shows the same degree of value with regards to uniqueness. Nevertheless, the values represented by the hierarchy of competences among living organisms at the same time differs based on species. Honour of uniqueness and hierarchy of competences represent two scientific concepts that never overcross. As a result, there is no evidence to suggest that scientific facts as such constitute a form of contradiction to philosophical and religious ideas, given that religion refers to animals as companions of humans. With regards to the clock of the living organism; there are three kinds of clocks in a living organism: the emotional clock, the cognitive clock and the molecular clock. These three categories actually constitute the temporal layers of our dimension, so they are in a relationship of interdependence. When one has a feeling that time is slower or quicker, they are not fully experiencing that change in the time speed, but only partially. And one can profoundly experience the change of perceived time speed when they experience profound feelings, which sweep them away from reality. Complete, deep mental focus can bring about this profound change in perception, which will make the individual feel as if they are in a different form of reality. When one is more instinctive, the person in cause perceives time as slower and sees more opportunities within the same frame of time and space. When one experiences the “Fight or flight” mode, the person in the cause finds themselves to be in danger and has two options; to try to prevail over the danger or to flee it. Whilst experiencing such a mode, people are much more alert and therefore, time passes more slowly and the physical space dilates. When people are relaxed, however, time and space become smaller, and when they are in a deep state of resting, they become very small. And where there is a smaller dimension, there is a greater speed, just as the circulating air gains speed when it crosses narrow passages.

In the bar of our Milky Way, there should be another supermassive black hole B which is with the mass almost 10−2~10−5 the Sgr A* and with a distance almost 10,000 lightyears from the Sgr A*. The bar is formed by the stars that are orbiting around the two black holes Sgr A* and B. And, in the bar, a lots of stars orbit around B while another lots of stars around Sgr A*. The two orbits form the peanut shape with “x-shaped structure” in the bar, while the boxy core is formed with all of the three orbits. And, the orbits of the stars out of the bar could be repulsed to a distant place by the black hole B to form the galactic spiral arms.

This article presents a comprehensive overview of recent discoveries and advancements in the field of steroid chemistry, highlighting the isolation and characterization of various steroidal compounds from natural sources. The paper discusses a wide range of steroids, including pregnane steroids, steroidal alkaloids, ketosteroids, and novel triterpenoids, derived from marine organisms, fungi, and plants. Significant findings include the isolation of bioactive compounds such as the cytotoxic erectsterates from microorganisms, soft corals, the unusual tetracyclic steroid penicillitone from a fungal culture, and innovative steroidal derivatives with potential anti-inflammatory and anticancer activities. The synthesis of steroids from microorganisms as a tool for pharmaceutical development is also explored, showcasing the role of microbial biotransformation in generating steroidal drugs. Additionally, the paper emphasizes the ecological and medicinal relevance of these compounds, which are often used in traditional medicine and have potential therapeutic applications in treating diseases like cancer and microbial infections. This article serves as a vital resource for researchers interested in the chemical diversity of steroids and their applications in drug discovery and development.

This article underscores the immense potential for substantial economic growth and development that can be harnessed through effective participation in global value chains (GVCs). It emphasises the role of policymakers in adeptly navigating GVCs, prioritising tasks, exploring different forms of GVC governance, and fostering a conducive environment for foreign investments. By effectively managing power dynamics and supply chain risks, countries can attract valuable foreign investors, enhance market connectivity, and improve infrastructure and services, leading to significant economic growth. The potential benefits of GVC participation are vast, and policymakers can shape the situation by understanding and addressing strategic inquiries, laying the foundation for a prosperous future. Furthermore, the article explores the potential for a country to enhance its involvement in GVCs and progress to more lucrative activities by strengthening existing connections between GVCs and the local economy. By enhancing the capacity of local stakeholders to acquire knowledge, policymakers can play a crucial role in maximising the benefits from GVC spillovers, positively impacting a country's economic development.

The American Civil War has been commemorated with a great variety of monuments, memorials, and markers. These monuments were erected for a variety of reasons, beginning with memorialization of the fallen and later to honor aging veterans, commemoration of significant anniversaries associated with the conflict, memorialization sites of conflict, and celebration of the actions of military leaders. Sources reveal that during both the Jim Crow and Civil Rights eras, many were erected as part of an organized propaganda campaign to terrorize African American communities and distort the past by promoting a ‘Lost Cause’ narrative. Through subsequent decades, to this day, complex and emotional narratives have surrounded interpretive legacies of the Civil War. Instruments of commemoration, through both physical and digital intervention approaches, can be provocative and instructive, as the country deals with a slavery legacy and the commemorated objects and spaces surrounding Confederate inheritances. Today, all of these potential factors and outcomes, with internationally relevance, are surrounded by swirls of social and political contention and controversy, including the remembering/forgetting dichotomies of cultural heritage. The modern dilemma turns on the question: In today’s new era of social justice, are these monuments primarily symbols of oppression, or can we see them, in select cases, alternatively as sites of conscience and reflection encompassing more inclusive conversations about commemoration? What we save or destroy and assign as the ultimate public value of these monuments rests with how we answer this question. In this essay, drawing from the testimony of scholars and artists, I address the conceptual landscape of approaches to the presentation and evolving participatory narratives of Confederate monuments that range from absolute expungement and removal to more restrained ideas such as in situ re-contextualization, removal to museums, and preservation-in-place.

This paper honours the importance of creative practice as a way of staying in touch with the affective dimensions of human situations and experience. Drawing on observations, field notes, and documentation of artistic practice, the author explores the transfer of ‘felt’ experience through an emergent ‘body’ of artwork made in response to experiences and observations in/of a neurorehabilitation day service in the context of an art-based doctoral enquiry (Michaels 2022).[i] Broadening the scope of response art to the performative nature of ‘making’, the ‘work’ of art amplifies the resonance of emotional and sensory affect. This brings an ethics of care to the fore, giving voice to aspects of organisational culture that might easily be lost, as well as the need for time and space to mourn lost parts.

Lymphadenopathy is a common manifestation of both reactive and malignant diseases, and fine needle aspiration (FNA) is an effective and inexpensive screening method. It can prevent unnecessary invasive surgery and excisional biopsy, especially in benign cases. Unfortunately, the lack of universally accepted terminology for reporting results has hindered its widespread support. The Sydney system proposal for lymph node cytopathology categorization and reporting introduced five diagnostic categories to address the lack of universally accepted terminology for reporting results in lymphadenopathy. Our study analyzed 188 lymph node FNC samples from King Abdulaziz University Hospital, Saudi Arabia, examining clinical follow-up data, pathology records, patient information, and final diagnosis from January 2019 to December 2022. Most specimens were from axillary LNs, with 99.5% tissue correlation. The Sydney System Category classification identified 56.9% of cases as malignant, while 26.1% were benign. The final surgical specimen diagnosis revealed a higher percentage of malignant diagnoses, with the highest ROM in malignant/Category V. In conclusion, our study demonstrates that LN-FNAC offers high diagnostic accuracy for LN aspirates, with the Sydney approach potentially aiding risk stratification and achieving consistency in cytologic diagnosis, but further multi-centric research is needed.

It is widely recognized that rapid urbanization and urban change are defining traits of the contemporary era, bringing both daunting challenges and hopeful opportunities. It is therefore critical that we have a clear and actionable model of the nature of urban space and the dynamics of its functions and dysfunctions to guide policy and practice. Yet the field today includes a range of definitions that are often inconsistent and often conflating very different properties of urban land, often expressed in some version of the conflated characterization, “over half of humanity now lives in cities.” In the last several decades, more articulated theoretical models have been advanced, with notable differences and discrepancies as well as partial commonalities. Here we assess the various models, and we formulate a consolidated and “consilient” theoretical model that may help guide policy and practice through an era of increasingly daunting urban challenges. In particular, the model focuses upon the cellular network structure of public and private spaces, and the dynamics of their evolution under human control – a theoretical model we refer to as Place Network Theory.

This article presents a novel analysis of Indus Seal M-282 [1] excavated from Mohenjo-Daro, a key Indus Valley Civilization site. Utilizing the proposed Sindhu Prakrit alphabet, the study investigates the relationship between the seal's iconography and the inscribed text. By examining the potential for a close correlation between these elements, the analysis aims to decipher the meaning embedded within the seal's motifs, potentially offering new insights into Indus Valley communication and symbolism.

This study describes the relationship between the epikarst and the surface karst of climatic karsts. Bedrock resistivity values along VES measurements were measured and calculated. The elevation difference between the surface and the karstwater table and the annual distribution of precipitation were calculated in certain karst areas. The resistivity of the epikarst can be high (drawdown dolines) and low (subsidence dolines). In the former case, the cavity index and the vertical drainage of the epikarst are heterogeneous, while in the latter they are homogeneous. Considering the above characteristics, two types of doline development are possible. A feature development controlled by the epikarst (tajga karst, soil-covered karst of the temperate belt, glaciokarst), by the epikarst and the karstwater (polje karst, fengcong karst), and controlled predominantly by karstwater (intermountain plain of fenglin karst, tropical karren). At feature development controlled by the epikarst, drawdown dolines (soil-covered karst) and subsidence dolines (covered karst) develop, in the case of feature development controlled by the epikarst and karstwater, drawdown dolines, subsidence dolines and feature assemblages with subsidence dolines and katavotra (polje karst, fengcong karst) are formed. At feature development controlled predominantly by karstwater, subsidence dolines (intermountain plain of fenglin karst), and giant grikes (tropical karren) develop.

Digitized counter-diabatic (CD) optimization algorithms have been proposed and extensively studied to enhance performance in quantum computing by accelerating adiabatic processes while minimizing energy transitions. While adding approximate counter-diabatic terms can initially introduce adiabatic errors that decrease over time, Trotter errors from decomposition approximation persist. On the other hand, increasing the high-order nested commutators for CD terms may improve adiabatic errors but could also introduce additional Trotter errors. In this article, we examine the two-qubit model to explore the interplay between approximate CD, adiabatic errors, Trotter errors, coefficients and commutators. Through these analysis, we aim to gain insights into optimizing these factors for better fidelity, shallower circuit depth, and reduced gate number in near-term gate-based quantum computing.

Nowadays and in the web era, there is a huge amount of information available due to automatically and easily generated websites. This information has many shared opinions from people toward different entities. Over the last decade there was a significant huge interest to determine the sentiment of any type of text especially on twitter. Twitter provides unstructured text that has many misspelling words, slang words and shortened forms. More complexity and challenges have come to the sentiment analysis researchers in the context of twitter. In this paper we conducted a literature review of the recent research of Twitter sentiment analysis on different languages. After that, we investigated challenges related to twitter sentiment analysis of Arabic language. Then we found a new solution for Sentiment analysis of Arabic twitter. So, we designed the main component of the proposed system and presented its algorithm. Finally, we performed many experiments under two kinds of datasets. The system achieves highest accuracy and shows many important results..

Sugarcane Streak Mosaic Virus (SCSMV) poses a significant threat to sugarcane productivity. PRG sugarcane is a product of genetic engineering aimed at enhancing resistance to various environmental stresses, pests, and diseases. This study aimed to test and compare the resistance of two PRG sugarcane SPS events to SCSMV infection. The study was conducted using a single-factor Completely Randomized Design (CRD), comprising four treatments: Bululawang sugarcane variety as a control, PS 882 as a susceptible variety, PRG Sugarcane SPS 1, and PRG Sugarcane SPS 3, with 15 replications of 60 sugarcane mules each. PCR results indicated that mosaic infection in the sugarcane plants was most likely caused by SCSMV. Based on the morphological identification of the SCSMV virus and RT-PCR testing, the sugarcane plants positively infected with SCSMV were SPS1 U1 R1, SPS3 U2 R4, SPS3 U3 R3, and PS882 U3 R4. The highest incidence rate of the disease was observed in the SPS3 variety, while the lowest incidence rate was in the Bululawang variety. The PS882 variety exhibited the slowest SCSMV incubation period, showing symptoms of infection, whereas the SPS1 variety showed the fastest incubation period. The highest disease severity was recorded in the SPS3 variety, and the lowest in the PS882 variety. The sugarcane varieties with the highest klorofil content were SPS3, while the SPS1 variety had the lowest klorofil content.

A recent publication regarding a March 2023 Google Scholar search found Japan unique in healthcare providers’ reaction to COVID-19 vaccines. According to one article, negative sentiment by healthcare providers toward vaccines defines the research in this area, with concerns about side effects outweighing worries regarding infection. This current study investigates the anomaly through a scoping review of “COVID-19, Japan, vaccine hesitancy” in six relevant databases: Cochrane COVID-19 Study Register, OVID, ProQuest, PubMed, Scopus, and Web of Science. By following PRISMA guidelines, the intent is a more thorough examination of this unusual evalua-tion of COVID-19 vaccines by Japanese healthcare providers than offered by the March 2023 search. The finding is that of the 997 returns, only four were relevant for assessment inclusion. Of these four, three, published in Vaccines, support vaccine hesitancy in Japanese healthcare providers and their becoming more so regarding a subsequent dose of the vaccine. One article published in BMJ Open did not find this. Yet, the design of none of the studies was specific to investigating vaccine hesitancy in Japanese healthcare providers, making the conclusion questionable. Suggest-ed future research directions include investigating the primacy of those databases searched and the need for timeliness in examining COVID-19 anomalies.

The startup ecosystem in Peru has experienced remarkable growth in recent years, driven by technol- ogy and innovation across various industries. This article presents a web application developed in PHP, designed to centralize and facilitate access to information about startups, incubators, and investors in Peru. The methodology employed encompasses several stages, from establishing prerequisites to data preprocessing, model selection and training, rigorous evaluation, and the technical development of the platform. The application offers key functionalities such as exploring a comprehensive database of star- tups, detailed access to information about incubators and accelerators, identification of investors, and advanced analysis tools for market proposal prediction. Additionally, it integrates educational resources and allows users to suggest new startups through detailed surveys. The results demonstrate that the ap- plication improves access to relevant data, fosters collaboration among ecosystem actors, and supports informed decision-making. The platform also stands out for its security and privacy measures, as well as its ability to drive innovation and competitiveness in the market. In conclusion, the application has a sig- nificant impact on the Peruvian entrepreneurial ecosystem, and its continuous improvement is essential for the sustainable growth of startups in Peru and globally.

The Hyper-Torus Universe Model (HTUM) proposes a novel framework to unify quantum mechanics, cosmology, and consciousness. This paper introduces HTUM's core concept: a higher-dimensional hyper-torus encompassing all possible states of existence. HTUM suggests that the universe functions as a quantum system where all outcomes are inherently connected, with consciousness playing a significant role in actualizing reality. The model introduces several key innovations, including the universe's 4-dimensional toroidal structure (4DTS), providing a new geometric interpretation of spacetime. HTUM presents dark matter and dark energy as nonlinear probabilistic phenomena within this toroidal framework, offering a unique perspective on their nature and interactions. The model proposes a mechanism for wave function collapse through universal self-observation, bridging quantum mechanics and gravity. It introduces a Topological Vacuum Energy Modulator (TVEM) function, offering a potential resolution to the cosmological constant problem. Furthermore, HTUM integrates consciousness as a fundamental aspect of the universe, influencing quantum state actualization and potentially resolving the hard problem of consciousness. The model explores the implications of a timeless singularity and the emergence of time as a product of causal relationships within the toroidal structure. This framework addresses critical challenges in modern physics, including the nature of quantum entanglement, the origin and fate of the universe, and the relationship between mind and matter. The paper discusses the mathematical formulation of HTUM, its implications for quantum mechanics and cosmology, and its potential to bridge the gap between science and philosophy. We present detailed predictions for the cosmic microwave background (CMB) power spectrum, gravitational wave signatures, and large-scale structure formation, demonstrating how HTUM differs from the standard ΛCDM model. Our analysis reveals distinctive oscillatory patterns in the relative difference between HTUM and ΛCDM predictions, with deviations reaching up to ±20% at certain scales. The paper also explores the unification of fundamental forces within the HTUM framework, proposing novel approaches to particle physics and quantum field theory. It introduces the concept of unified mathematical operations, suggesting a more holistic approach to mathematical thinking that aligns with the model's interconnected view of the universe. Additional testable predictions and proposed experimental approaches are discussed, including advanced space-based tests and laboratory experiments probing quantum gravity effects. These specific, quantifiable predictions offer multiple avenues for empirical validation, highlighting HTUM's potential to be distinguished from ΛCDM and other alternative cosmological models. HTUM represents a significant new perspective in our understanding of the universe, inviting further research and exploration into the nature of reality, consciousness, and the fundamental structure of the cosmos. By providing a comprehensive framework that unifies various aspects of physics, cosmology, and consciousness studies, HTUM offers a promising path toward a more complete understanding of our universe.

Analysis of tRNA sequence structural features from forty mammals proves neither isoacceptors nor isodecoders are degenerate, and model organisms are inadequate representatives for multiple aspects of the translational process. It is proposed tRNA participate in protein construction beyond mere transport of amino acids to ribosomes: specifically, to facilitate amino acid modification and promote development of protein folding characteristics.

The objective of this work is to analyze publications on the Balanced Scorecard (BSC), since 1956 (in the last sixty-five years), identifying evolution trends. Based on bibliometric techniques, the study was carried out based on data available in the Web of Science database through a systematic literature review. Web of Science is one of the main databases in the world, indexing the most cited journals in different areas of research and thus providing a set of data, essential for systematic analyses, including areas of study, list of journals, year of publication, citations from articles, among other relevant information. Because the chosen database is very complete, multidisciplinary and access to the use of Vosviewer software, which we used in this study, is acceptable.From the systematic search, 694 articles published until December 2021 were identified. The analysis of these publications indicates a growing trend in the publication of articles on BSC, highlighting partnership publications as well as their dispersion across journals from different areas.Most are qualitative studies (namely case studies) and questionnaires, as the main method of data collection. The main themes studied, we found that there are several articles on the application or integration of the BSC as a management model and that the studies are essentially concentrated on large companies belonging to the private sector, to the detriment of small and medium-sized companies and public and non-profit organizations profitable.

Digitalization has fundamentally changed the global economy and will continue to do so. This study investigates how the US Federal Reserve and US Treasury may work together to use decentralized finance (DeFi) systems to promote economic growth in local communities. The study looks into the potential for transformation and the difficulties in incorporating DeFi into conventional financial institutions. Research shows that the use of cash as a means of payment is widely expected to decline in the future. As a result, the public’s ability to make transactions using central bank money may decline rapidly. This study's goals are to solve economic issues, promote innovation, and increase financial efficiency. The use of in-depth interviews, theme analysis, case studies, stakeholder perspectives, comparative analysis, and document analysis is suggested as part of a qualitative research methodology. The goal of these approaches is to offer a sophisticated comprehension of the dynamics of collaboration and the consequences of DeFi integration in the context of the Federal Reserve-Treasury relationship. Important data sources that are necessary to answer the research question are indicated, such as US Treasury statistics, Federal Reserve publications, DeFi platforms, and International Monetary Fund economic indicators. Informed decision-making and policy formation may pave the way for a more inclusive and efficient financial ecosystem, which will eventually drive regional economic growth in the United States and promote monetary sovereignty for the aforementioned monetary entities. This can be achieved by investigating creative collaboration tactics between the Federal Reserve and the US Treasury.

We introduce the notion of p-adic equiangular lines and derive the first fundamental relation between common angle, dimension of the space and the number of lines. More precisely, we show that if {τj} n j=1 is p-adic γ-equiangular lines in Qd p , then (1) |n| 2 ≤ |d| max{|n|, γ2 }. We call Inequality (1) as the p-adic van Lint-Seidel relative bound. We believe that this complements fundamental van Lint-Seidel [Indag. Math., 1966] relative bound for equiangular lines in the p-adic case. Keywords: Equiangular lines, p-adic Hilbert space.

Finance is increasingly dominating the entire economy and determining social life more and more. This credit economy is unstable. To ensure stability, central banks intervene massively in the financial market. As a result, credit is growing, but economic growth is lagging behind. This has serious consequences. The evolutionary balance between "credit" and "growth", on which society's confidence is based, is in danger. This Imbalance leads to a serious loss of trust in the foundation of the market economy. In order to secure trust and master the two upcoming transformations - the transition to green production and the splitting up of global economy to competitive areas -, the state, or more precisely the central bank, must also transform itself. The central bank can add a second orientation to its hitherto one-sided focus on the financial system by supporting the development of civil society with direct financial transactions.

This study investigates the transformation of Bubungan Tinggi, a traditional Banjar house with a high roof, into a modern home through the integration of modern facade design with traditional Bubungan Tinggi facade elements. Bubungan Tinggi is a monumental artifact in South Kalimantan representing the collective memory of the Banjar community with its distinctive typology and anatomy. This study uses a qualitative approach with design experiments to explore the integration of smart home systems, eco-friendly materials, and contemporary design principles. The findings highlight the potential of blending traditional architecture with modern innovations to create sustainable, smart, and culturally sensitive housing solutions.

The article "Ensuring Quality Medicine is Not a Single Event but a Combined Effort of a Pharmaceutical Company" explores the multifaceted approach required to maintain high standards in pharmaceutical manufacturing. It emphasizes that quality assurance in medicine production is not an isolated event but a continuous, integrated process involving multiple departments and stages. The article highlights the roles of research and development, rigorous clinical trials, regulatory compliance, and robust manufacturing practices in ensuring the efficacy and safety of medicines. It also discusses the importance of quality control measures, such as stringent testing protocols and regular audits, to detect and mitigate potential issues early. The collaboration between different teams within a pharmaceutical company, including scientists, engineers, and quality assurance professionals, is crucial for sustaining quality throughout the product lifecycle. Moreover, the article addresses the necessity of adhering to global standards and guidelines, such as Good Manufacturing Practices (GMP), to ensure consistency and reliability in drug production. By fostering a culture of continuous improvement and vigilance, pharmaceutical companies can effectively safeguard public health and maintain trust in their products. This holistic approach underscores that delivering quality medicine is an ongoing commitment requiring coordinated efforts across the entire organization.

The overall comfort experienced by an individual in an n-dimensional space can be theoretically constructed using a mathematical equation, that relates the comfort experienced by an individual in a particular point in space with spatial points associated with higher comfort attributes and the desirable factors affecting the current environmental space.

Predicting heart disease is crucial for early diagnosis and intervention, significantly improving patient outcomes and reducing mortality rates. This study compares various machine learning models, including Logistic Regression, Random Forest, Gradient Boosting, XGBoost, and Long Short-Term Memory (LSTM) networks, using the Cleveland Heart Disease dataset. Comprehensive preprocessing steps were undertaken, such as handling missing values, converting categorical variables to numeric forms, and binarizing the target variable for binary classification. Each model was rigorously evaluated using performance metrics, including accuracy, precision, recall, F1-score, and the area under the receiver operating characteristic curve (AUC-ROC). SHapley Additive exPlanations (SHAP) values were employed to provide insights into feature importance, ensuring model transparency and interpretability. The results indicate that XGBoost outperformed all other models, achieving an accuracy of 90% and an AUC-ROC of 0.94, demonstrating its superior ability to capture complex patterns in the data through advanced optimization techniques and regularization. This study highlights the significant potential of advanced machine learning techniques, particularly ensemble methods like Gradient Boosting and XGBoost, in enhancing heart disease prediction. These models offer higher accuracy and valuable interpretability, making them practical tools for early diagnosis in clinical settings. Future research should focus on integrating these models into healthcare systems and exploring hybrid approaches to further improve predictive performance and clinical applicability.

House construction is a unique characteristic of the swamp lands in Banjarmasin. Foundations for swampy soil require special handling. The weakness of wood materials and the inability of wood pillar foundations to support building loads are the primary causes of building problems in these swampy areas. Mistakes in foundation construction often arise from the need to expand houses to two stories or renovations. The load-bearing capacity of the wood pillar foundations used is very limited. This study aims to determine the weaknesses of wood pillar foundations to address signs of damage in house construction on swamp land. Field observation research, including the examination of house buildings and individual objects, was conducted at several construction sites in Banjarmasin as part of this study. Data presentation is descriptive. The results indicate that weak wood pillar foundation construction is characterized by damaged piles and floor subsidence. The small size of the wood pillars also limits the load-bearing capacity. The presence of broken 'sunduk' elements is one of the causes of this foundation damage. This research provides new insights into the weaknesses of wood pillar foundations and offers repair recommendations to enhance the resilience and stability of buildings on swamp land.

This paper introduces a ground-breaking approach to deciphering the Indus script, employed by the Indus Valley Civilization (IVC) from c. 3300 to 1900 BCE. Moving beyond previous methods, my research delves into the intricate structure of the script's signs, aiming to definitively settle the debate regarding its categorization. Specifically, I investigate whether the Indus script functions as an alphabet, presenting compelling evidence for the number of primary signs it comprises. My methodology meticulously examines over 400 signs, encompassing the entire corpus rather than relying on limited samples. This holistic approach utilizes a novel grid-based decomposition technique to visually dissect compound signs, identify diacritics with consistent usage patterns, and uncover the underlying principles of sign extraction. Through this rigorous analysis, I successfully isolate the essential primary signs and illuminate their potential phonetic representations within an alphabetic system. However, I acknowledge the intricate variations in writing styles present across the Indus corpus. These stylistic subtleties, encompassing formation, composition, and combination strategies, contribute to the apparent plurality of signs. Nonetheless, my findings reveal a core set of only 40 fundamental signs, suggesting a remarkably concise system beneath the surface complexity. By presenting this new paradigm for understanding the Indus script, I pave the way for further advances in its decipherment. Continued exploration of the identified core signs and their phonetic associations holds immense potential for unlocking the linguistic insights encoded within this enigmatic script, shedding light on a crucial chapter in human history.

This study aimed to determine the specific characteristics of extraglandular manifestations especially cutaneous involvement in patients with primary sjögren’s syndrome(pSS), focusing on the different clinical and histologic types of SS-associated vasculitis. A retrospective study was conducted and 402 patients (378 women and 24 men) with pSS were analyzed. Patients were categorized into three subgroups based on serological tests. These; 1) quadruple seropositive (positive for anti-Sjögren’s-syndrome-related antigen A antibodies (anti-SSA; anti-Ro) and anti-Sjögren’s-syndrome-related antigen B antibodies (anti-SSB; anti-La), rheumatoid factor (RF), and antinuclear antibody (ANA)), 2) double seropositive (positive for ANA and anti-SSA/Ro antibodies), 3) quadruple seronegative (negative for ANA, RF, anti-SSA/Ro and anti-SSB/La antibodies). The number of quadruple seropositive patients was 72 (18.6%), double seropositive 174 (43.2%), and quadruple seronegative was 85 (21.1%). The diagnosis age of quadruple seropositive pSS was 42.4±10.8, significantly younger than patients with double seropositive and quadruple seronegative pSS (p = 0.021, p=0.112). In terms of organ involvement, salivary gland enlargement, arthralgias, arthritis, Raynaud's phenomenon, lymphadenopathy, vasculitis-purpura, interstitial lung disease, neurological involvement, autoimmune thyroiditis, renal interstitial disease, anemia, leukopenia, hypergammaglobulinaemia and hypocomplementaemia were more common in quadruple seropositive pSS compared to quadruple seronegative (p

Digital marketing adoption in the multinational Fast-Moving Consumer Goods (FMCG) sector presents both challenges and opportunities that significantly impact organizational strategies and market competitiveness. This qualitative study explores the complexities surrounding digital marketing adoption through interviews with 45 participants from multinational FMCG companies. The research investigates key barriers such as organizational resistance, technological constraints, and concerns over data privacy and security, while also examining the benefits of enhanced consumer engagement, global market reach, and data-driven decision making. Findings reveal that organizational resistance remains a formidable barrier, driven by senior management's cautious approach to digital transformation and concerns over return on investment (ROI) amidst rapidly evolving digital landscapes. Technological challenges, including outdated systems and limited budgets for technology upgrades, further hinder comprehensive digital integration. Moreover, navigating regulatory frameworks and addressing consumer trust in data privacy emerge as critical considerations for FMCG companies seeking to leverage digital strategies effectively. Conversely, digital marketing adoption offers substantial opportunities. Enhanced consumer engagement through personalized and interactive campaigns allows companies to strengthen brand-consumer relationships and foster loyalty. The global reach facilitated by digital platforms enables multinational FMCG firms to expand market presence, penetrate new markets, and adapt marketing strategies to diverse consumer preferences worldwide. Data-driven decision making emerges as pivotal, leveraging analytics to optimize marketing strategies, measure campaign effectiveness, and anticipate consumer behaviors in real-time. Strategies for overcoming barriers emphasize building internal digital capabilities through training, recruitment, and cross-functional collaboration. Aligning digital strategies with overarching business objectives and integrating digital efforts with traditional marketing channels are crucial for creating cohesive and effective campaigns. Embracing innovation, flexibility, and agility in adapting to technological advancements are essential for maintaining competitiveness and relevance in a rapidly evolving digital landscape. Looking forward, emerging trends such as AI and machine learning integration for predictive analytics, sustainability-focused marketing initiatives, and the evolution towards omnichannel strategies are poised to reshape digital marketing practices in the FMCG sector. By aligning strategies with these trends, FMCG companies can harness digital technologies to drive sustainable growth, enhance market competitiveness, and meet evolving consumer expectations in a digitally-driven global marketplace.

The revolutionary idea of complementary intelligence involves a unique strategy in which artificial intelligence (AI) works with human cognitive abilities embodied by natural intelligence (NI), creating a harmonious partnership instead of engaging in a competitive relationship. This innovative concept can potentially revolutionize how we approach scientific research and discovery. This cutting-edge process capitalizes on pooling the vast information from various distinct and autonomous sources to generate forecasts that frequently outshine human perspectives by significant margins, leading to groundbreaking advancements in scientific development based on hybrid intelligence. Multilayer networks extend traditional network theory to adjacent layers linked through copula nodes. Artificial intelligence, with its retrieval capacity to collect and interpret big data, sharply increases the number of nodes and their linking interpretation. This process, amplified by multilayer networks, dramatically improves the scalability of the networked ecosystem. Multilayer networks can represent NI and AI in complementary hyperplanes, connecting them with copula nodes and edge properties. Thus, it is possible to measure the interaction of NI and AI, assessing their scalable value co-creation properties. This study examines the interaction of NI and AI with an innovative and multidisciplinary approach. A theoretical framework of these related concepts precedes practical insights for possible applications in future research.

The importance of XAI is undeniable in the current scenario and thus it's importance in considerable. Unfortunately, there are a couple of scenarios where the current XAI models fail. Additionally, attackers seek vulnerabilities in these models. This review paper is intended to cover some of the important scenarios where the existing XAI models may fail and some progresses made which shows their vulnerabilities and how to secure them.

While the history of Lough Derg is extremely well-documented, there have been com-paratively fewer ethnographic reports. Given the highly elaborate Lough Derg websites and multiple postings by Lough Derg pilgrims, this researcher anticipated that Lough Derg – like many other Irish pilgrimages - would attract mostly recreational tourists. It does not. Pilgrims to Lough Derg do not see the site as primarily a tourist destination. Instead, they see Lough Derg primarily as a locus of intense religious experience. Lough Derg 3-day pilgrimages are rigorous and entail considerable self-sacrifice: fasting, sleep deprivation, cold, bare feet, prayer, no cell phones, and exposure to jagged rocks. Lough Derg’s 3-day pilgrimages closely follow patterns established centuries ago. Lough Derg is both "modern" and "timeless." It selectively incorporates ancient ritual and 21st century technology. This paper looks at the impact of the covid19 epidemic on Lough Derg pilgrimages. The site was closed to pilgrims during the 2020-2021 season and an on-line virtual pilgrimage was offered as a substitute. One unintended consequence of this virtual pilgrimage is that many pilgrims to Lough Derg now give greater prominence to what Corin Braga has categorized as fisi (ecstatic revelations) than to the physical journey itself (i e. somanodias). Post-covid pilgrims highlight the Internet: production of virtual texts and Internet vlogs. As in most pilgrimages worldwide, contemporary pilgrims to Lough Derg arrive with varied expec-tations and myriad motives. This ethnographic report examines these motives and offers a critique of James L. Smith (2016), who, like Edith and Victor Turner (1978) before him – saw Lough Derg as a symbol of Irish nationalism. Smith highlighted Lough Derg’s “moral geography” which, he argued, stems from its long history of isolation. But Post- covid Lough Derg is no longer isolated. The site has become more accessible through organized bus tours, improved public transportation, and development of a commercial tourist infrastructure.

This project aims to simulate and analyze population dynamics in evolutionary systems, using stochastic differential equations and probabilistic rules for crossbreeding and benefits. The study employs advanced computational techniques to model the evolution of populations over an extended period. Specifically, we explore a scenario with ten distinct groups, each starting with an equal population and evolving under defined genetic and cooperative behaviors. The simulation spans 1000 years, incorporating individual lifespans, stochastic updates, and probabilistic interactions. To ensure robustness and reliability, the study includes detailed statistical analysis, encompassing descriptive statistics, confidence intervals, and ANOVA tests. We further visualize the temporal behavior of populations and subpopulations, providing insights into the evolutionary dynamics and stability of the system. The results demonstrate the effectiveness of balanced cooperation and genetic diversity in maintaining stable population distributions. The project showcases the integration of mathematical modeling, statistical analysis, and computational simulations, contributing valuable insights into evolutionary biology and complex systems. It highlights the importance of interdisciplinary approaches in understanding and predicting population behaviors, with implications for both theoretical research and practical applications in fields such as ecology, genetics, probability and social sciences.

This study examines the latest innovation in wooden pile foundation models using a combination of wood and concrete materials for house construction on swampy land. The focus of the research is on developing joints and materials that enhance the load-bearing capacity and stability of building structures on swampy terrain. The methods used include field observations, laboratory experiments, and descriptive analysis. The results show that the combination of wood and concrete in foundation piles can increase structural strength, reduce deformation, and extend the service life of buildings. The new joint techniques developed in this research are effective in improving structural integrity and minimizing the negative impacts of soft soil conditions. The conclusion emphasizes the importance of material innovation and joint techniques in construction on swampy land, providing practical guidance for construction practitioners and researchers in this field.

Introduction: The construction of a house with a stage structure is the uniqueness of Banjarmasin's swampland. Particularly, foundations for swampy terrain necessitate special handling. Building material defects and the basic inability to modify the use and design of wood pillar foundations are the main causes of house building problems. The very limited capacity of a wooden pillar foundation makes house buildings collapse frequently. Purpose of the study: The aim of the study is to determine the weaknesses of the wooden pillar foundations by examining the indications of damage to the house structure. Methods: Field observation investigations, including housing and individual object observations, will be carried out at multiple construction sites in Banjarmasin (Indonesia) as part of this study. The way the data is presented is descriptive. Result: The weak construction of a wooden pillar foundation explains some indications of house building damage, such as broken wooden pillars and floor settlement. The existence of evidence that there is a broken 'sunduk’ element is one of the causes of damage to this foundation. The small size of the wooden poles also makes the load-bearing capacity limited.

Elastic peak electron spectroscopy, abbreviated EPES, involves ana- lyzing the line shape found in the elastic peak. The reduction in the energy of electrons of the elastic peak is a result of energy transfer to the target atoms, a phenomenon known as recoil energy. EPES differs from other electron spectroscopies in its unique ability to identify hydrogen in polymers and hydrogenated carbon-based materials. This feature is particularly noteworthy because lighter elements exhibit stronger energy shifts. The energy difference between the positions of the elastic peak of carbon and the elastic peak of hydrogen tends to increase as the kinetic energy of the incident electrons increases. If, during electron irradiation of an insulating polymer, the number of secondary electrons emitted by the surface is less than the number of electrons absorbed in the sample, the surface floats energetically until it stabilizes at a potential energy eVs. As a result, the interaction energy changes and modifies the energy difference between the elastic peaks of hydrogen and carbon. In this study, the charge effects are evaluated using the Monte Carlo method to simulate the EPES spectra of electrons interacting with polystyrene and polyethylene.

The theory says that number interacts with spaces based on the meaning of mathematics, in this way it is possible to obtain numerical knowledge. The theory shows the possibility of using spaces related to each other to efficiently discover whether results and origins are even or odd, but always applying rules to make this work. the study uses equivalent representations of odd and even numbers. Thus, it is possible to discover the possibilities of origins and their results.

A previous related paper dealing with the density relaxation of polystyrene (PS) has shown that the equilibrium relaxation time (eq) has a purely exponential temperature dependence (ETD) below ≈ 100ºC. Such an ETD is now also confirmed based upon available dielectric-spectra data for PS. By combining the ETD behavior of eq (or aT) at low temperatures with a VFTH behavior at higher temperatures (based mainly on available recoverable-shear-compliance data), a composite correlation for eq (or aT) is developed which is continuous with continuous slope at a crossover temperature which is found to be 99.22ºC, where eq = 92.15 sec. This composite representation is shown to describe (without any adjustable parameters) available independent data for the segmental-relaxation time over a finite range both above and below Tcrossover (i.e. the glass-transition temperature).

Defining integrals over volume element in curved spacetime together with the mass and energy densities within that region of spacetime is apparently equivalent to the given energy and mass of that body or particle. With this in mind equations involving energies and masses can be rewritten in terms of their densities and the integral over the curved space-time volume element. The idea find its place in quantum mechanical frameworks systematically accounting for the effect of spacetime volume structures and gravity on dynamics of quantum systems. This article briefly explores these concepts and runs through various frameworks and equations relevant to this idea including the quantum stress energy tensor, and expressing Schrodinger’s equation in ways that are tied to general relativity it also discusses the cosmological constant and the cosmological constant problem.

Saturated fats are widely seen as undesirable components of a healthy diet, as a result of their illusive association with elevated serum cholesterol. The regulation of serum cholesterol is now better understood and polyunsaturated fatty acids rather than saturated fatty acids are responsible. Palmitic acid received further specious allegations of inciting inflammation when in fact it was found to play an auxiliary role as a precursor to ceramide biosynthesis. Studies of arthritic inflammation in lab animals showed dietary saturated fats are anti-inflammatory, whereas polyunsaturated oils are pro-inflammatory. Inflammation plays a role in numerous metabolic diseases, including insulin resistance, fatty liver disease and metabolic syndrome among others. Fat, as triglycerides in adipose tissue, is an efficient way for living organisms to store energy and reduce toxicity of other macronutrients. However, adipose tissue lipolysis releases fatty acids into the blood to provide many organs with an energy supply and spare glucose for brain tissue. Some metabolic disorders result in elevated nonesterified fatty acids in blood, leading to hepatic lipid accumulation, inflammation and insulin resistance. This paper will attempt to clarify the role of saturated fatty acids, and palmitic acid in particular, with regard to certain adverse health conditions.

This article briefly shows how particle’s moving at escape velocity can be described in a quantum mechanical frameworks, this is achieved by deriving quantum mechanical equations that puts escape velocity into consideration. The equations are derived from Hamiltonians and Hamiltonian operators formulated from classical kinetic and potential terms which are then quantized. Equations were also presented for specific situations of the particle at escape velocity. Situations such as free-particles at escape velocity, Self-gravitating situations of a charged or neutral particle even while free of the gravitational influence of the large massive body due to its escape velocity, leaving only the self-gravitation as the only gravitational influence on the particle which in the case of a massless, charge less particle reduces back to the equation of free-particle at escape velocity. Other very brief expositions on trajectories and more are also present in this brief article.

Brittle fracture of iron and steel above twinning temperatures are caused by cementite grain boundary wall cracks. These were revealed by an Atomic Force Microscope. At temperatures below the Ductile-Brittle Transition, cracks must propagate longitudinally within the cementite walls until the stress is sufficient high for the cracks to propagate across ferrite grains. Calculations using these concepts correctly predict the stress and temperature at the Ductile-Brittle Transition required for fracture to occur. At temperatures above the Ductile-Brittle Transition for hypoeutectoid ferritic steels, dislocations must fracture these walls transversely for plastic deformation to continue. This is responsible for the upper yield point at the elastic limit in these steels followed by a large drop in stress to the lower yield point. Here the walls surround completely all of the grains. Where the walls are segmented such as in iron, dislocations can pass around the walls resulting in a gradual change from elastic to plastic deformation. The Cottrell atmosphere theory of yielding is not supported experimentally. It was the best available until later experiments including those using the Atomic Force Microscope were obtained. Methods are presented here giving yield strength versus temperature and also the parameters for the Hall-Petch and Griffith equations.

Psychiatric disorders, characterized by complex and fluctuating patterns of thoughts, emotions, and behaviors, can be effectively modeled and visualized using mathematical wave equations. This study explores the representation of three major psychiatric conditions— Psychosis, Bipolar Disorder and Obsessive Compulsive Disorder (OCD)—through the application of differential equations, damping factors, and noise perturbations. Psychosis is modeled using Lissajous figures with high-frequency components, damping, and noise, symbolizing the irregular and erratic thought patterns characteristic of this condition. The inclusion of random perturbations and varying frequencies illustrates the chaotic and unpredictable nature of psychotic episodes, while damping effects reflect the temporary reductions in symptom intensity. For bipolar disorder, a system of partial differential equations simulates the cyclical nature of manic and depressive episodes. The model captures high-energy manic phases with periodic disturbances and the subsequent transition to lower-energy depressive states through damping effects. This representation highlights the oscillatory behavior and recurring episodes inherent to bipolar disorder. OCD is represented with Circumferential Complex Equations in Mult directions. The resulting graphical representations provide intuitive visual insights into the dynamics of these psychiatric disorders. By leveraging wave equations and mathematical modeling, this approach offers a novel perspective on understanding and analyzing the complex behaviors associated with OCD, bipolar disorder and psychosis. This method not only aids in the conceptualization of psychiatric phenomena but also underscores the potential of mathematical tools in the study of mental health conditions.

Autism spectrum disorder (ASD) is characterized by diverse patterns of social interaction, communication, and behavior. This study explores the application of clustering and stochastic migration models to visualize and understand the social and neural connectivity patterns associated with autism. The clustering model, with its strong internal connections and limited external connections, mirrors the tight-knit social groups and communication barriers often observed in individuals with autism. In contrast, the stochastic model, characterized by more dispersed connections and greater adaptability, represents the variability and flexibility seen in social interactions across typical individuals. By comparing these models, we can gain deeper insights into the unique challenges and strengths of individuals with autism, highlighting the importance of personalized interventions. Additionally, these models provide a visual framework for understanding the differences in brain connectivity patterns observed in autism, with implications for both behavioral and neural correlates. This study underscores the value of computational models in advancing our understanding of autism and guiding effective support strategies.

In recent studies, the circulation of a (SLG) super-Lorentz-Gaussian beam in a non-turbulent ‎troposphere has been investigated and used for laser applications. This method uses the extended ‎Huygens-Fresnel integral technique and refers to the multiplication of the Gaussian beam by the ‎Lorentz function. Formulas are derived for the normal density and approximate field of the Lo-‎Rentz-Gaussian beam in a non-turbulent troposphere. The average density power and the propagation characteristics of the SLG jet in the non-turbulent troposphere are numerically represented. ‎The characteristics of the beam boundaries at atmospheric non-turbulence for the propagation ‎distance of an SLG beam in a non-turbulent troposphere are also discussed in detail. They are ‎practical in an optical communication system used in lasers.

The Fergana Valley, a strategically significant and culturally rich region in Central Asia, exemplifies the complex interplay of modern international relations amidst geopolitical and ethno-cultural integration. This paper explores the fundamental principles guiding international interactions in the valley, considering the historical context, current geopolitical dynamics, and the unique cultural mosaic of its population. Key themes include the impact of regional power shifts, the role of transnational organizations, and the influence of ethno-cultural identities on diplomatic engagements. By analyzing case studies of cooperation and conflict, the paper highlights how integration efforts shape political stability, economic development, and social cohesion in the Fergana Valley. This study aims to provide a nuanced understanding of the region's international relations framework, offering insights into effective strategies for fostering harmonious and sustainable integration in a geopolitically sensitive and culturally diverse landscape.

In this study, we explore the impact of quantum effects on synaptic activity and their implications for the deterministic model of neural processes. By simulating synaptic events in a large-scale neural network, we demonstrate how small probabilistic quantum events can accumulate and introduce variability in neural behavior. Our model incorporates Dirac delta functions to simulate sudden changes in synaptic probabilities, creating a non-linear, seesaw effect in the cumulative synaptic activity curve. The results reveal that even minimal quantum effects, when scaled to the vast number of synapses in the human brain, can lead to significant dissociations in neural activity. These findings challenge the traditional deterministic view, suggesting that neural processes—and by extension, decision-making and movements—may inherently incorporate elements of randomness. This probabilistic perspective aligns with theories of free will and underscores the need for further empirical research to validate the role of quantum mechanics in neuroscience. Our study provides a theoretical framework for understanding the complex interplay between quantum effects and neural dynamics, opening new avenues for exploring the nature of consciousness and the fundamental principles governing reality.

O estudo apresenta uma afirmação e explicação de que ocorrem progressões numéricas maiores e menores que dependem da representação contida no espaço físico. Em casos gerais, números maiores são múltiplos e números menores são simples, porque vários números contêm mais números em muitos espaços físicos do que números simples. Em casos específicos, dependem da afirmação do que é a representação específica, podendo ocorrer realidades diferentes de casos gerais. Além disso, a teoria explica a mudança no número de números primos.

This work discusses the feasibility of multiple linear regression in predicting water/CO₂ relative permeability using training and testing datasets from two nearby wells, separately, of the Lower Cretaceous Lakota Sandstone, Jurassic Hulett Sandstone, and Pennsylvanian Minnelusa Formation at the Dry Fork Station site. The outcome is promising as the predicted and measured relative permeability data are decently comparable. Yet, whether this approach could be generally applicable needs more delicate models and larger training datasets to be determined.

The persistence of Traditional Ecological Knowledge (TEK) among Indigenous and local communities is often associated with socio-economic constraints, poverty, and lack of choices. Such a perspective argues against underpinning profound environmental consciousness and sustainable practices that underlie TEK. The paper challenges reductionism—viewing TEK solely as a creation of necessity—and tries to argue that it entails a sophisticated understanding of ecological balance and conservation ethics. Through various examples, the paper exemplifies how TEK contributes to environmental sustainability for biodiversity conservation, management and use of natural resources, and the enhancement of resilience to climatic change—the same elements crucial for culture, tradition, and community living.

The theory says that the first things to exist in the universe and the current moment were driven by an imperative need; that is, the intensities of the physical concept specify influence the existence of elements and facts based on the countless observations in physical spaces in relation to elements and facts. The existence of mandatory elements in space is motivated by the characteristics of the spaces that offer conditions for such an obligation. The theory states that the universe did not arise by chance; that is, the universe emerged through determination influenced by its surroundings. The objective of the study is to help explain the elements and facts of the universe from its origins to the present.

Multiple Sclerosis (MS) is a chronic autoimmune disorder characterized by the demyelination of neural fibers in the central nervous system. Understanding the impact of demyelination on neural network efficiency is crucial for elucidating the pathophysiological mechanisms underlying MS. This study aims to model the effects of demyelination on neural network efficiency, specifically focusing on how increased resistance and path lengths due to demyelination correlate with the clinical symptoms of MS. We employed a graph-theoretical approach to simulate neural networks, introducing varying degrees of demyelination. The demyelination was represented by increasing the resistance (weights) of selected edges within the network, affecting both random and clustered distributions of network connections. The primary metric analyzed was the average shortest path length, indicative of network efficiency. The models demonstrated a significant increase in the average shortest path length in demyelinated networks compared to intact ones. Specifically, networks with clustered demyelination exhibited localized inefficiencies, correlating with the focal nature of MS lesions. The increase in path length was associated with reduced signal transmission efficiency, providing insights into a range of MS symptoms including motor and sensory impairments, cognitive dysfunction, visual disturbances, and fatigue. The graph-theoretical model of neural network demyelination offers a novel perspective on how structural changes in the brain's connectivity due to MS can lead to diverse clinical manifestations. While the model simplifies the complexity of neural networks, it underscores the potential of computational approaches in understanding and predicting the course of neurological disorders like MS.

It is important to consider both requirements and limitations for the generation and sharing of genomic data. For example, human genomic sequence data should typically not be deposited publicly without the appropriate "explicit consent" to do so. This includes genetic identifying data that may exist within raw reads for bulk RNA Sequencing (RNA-Seq) data and genomic data from cell lines that are available to purchase. At the same time, data sharing is important for re-analysis and reproducibility/replication in the scientific community. A review of known rules and guidelines for genomic data sharing is provided. This includes specific rules for NIH-funded data for controlled access deposit of HeLa cell line data, including bulk RNA-Seq data. The ability to create “partial” Gene Expression Omnibus (GEO) public deposits with only processed data is described, with search criteria that can identify many “partial” GEO deposits for a variety of data types where reads were not made public for patient privacy concerns. However, it is the opinion of the author that this should be considered a short-term solution, and additional considerations and action should be carried out for genomic data generated in future experiments. Information about how to learn more about what is known for consent for cell line samples is also briefly provided, along with search results for genomic data from widely available cell lines that is deposited in controlled access databases. Finally, it should be made clear that this article presents some amount of opinion. Additionally, open feedback for this preprint is encouraged to further enhance knowledge and communication.

Drawing from literature and Geert Hofstede’s cultural dimensions, this study delves into the impact of cultural factors on family structures, roles, and relationships. Ghana and Latvia have different cultural and social orientations that influence family dynamics. Through a comparative lens, this paper will contribute to understanding how a country’s culture influences family dynamics, highlighting the influence of Power Dynamics of parenting style and Individualism vs. Collectivism on interaction levels within the family.

The practice of stormwater management has evolved from a singular focus on drainage to a multifaceted approach to support integrated urban development. By contributing to healthy, livable, ecological, and water sensitive cities, it is a key tool to promote Sustainable Development Goal 11 from neighborhood to metropolitan scales. A review of the knowledge base for stormwater management shows several attributes that favor an integrative approach to achieve co-benefits across several sectors. Functional areas of its contributions include drainage, flood control, flood plain management, water quality control, urban ecology, recreation, and city beautification. Legacy path dependance affects the potential to reform land use practices, while stormwater management practice is being affected by climate change, sea level rise, urbanization, inequality, and poor governance. Technical methods for stormwater management are well advanced, but integrative frameworks to address social, ecological and infrastructure needs are more challenging. The sensitivity of ecological issues is most evident in cities in coastal zones. Organizational initiatives are needed to counter neglect of essential maintenance and sustain flood risk reduction in cities. Stormwater management is related to other integrative tools, including IWRM, One Water, One Health, and integrated flood management, as well as the broader concept of urban planning. Stormwater capture and rainfall harvesting offer major opportunities to augment scarce water supplies. Nature-based solutions like low-impact development and the Sponge City concept show promise to transform cities. Major cities face challenges to sustain conveyance corridors for major flows and to store and treat combined sewer runoff. The neighborhood focus of stormwater management elevates the importance of participation and inclusion to advance environmental justice and strengthen social capital. Integrating organizational initiatives from local to city scale and funding improvements to stormwater systems are major challenges that require leadership from higher governance levels, although governments face resistance to change toward integration, especially in countries with poor land use and public works management systems. Finding solutions to neighborhood issues and the connectivity of water systems at larger scales requires complex approaches to urban planning and represent an important agenda for urban and water governance going forward.