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Rereading the Anatomy of Duodenum a Distinct Part of the Digestive Tract
No full textThe duodenum is known to be a part of the small intestine that, along with the oral cavity, esophagus, stomach, jejunum, ileum, cecum, ascending colon, transverse colon, descending colon, sigmoid colon, rectum, and anal canal, forms the digestive “or alimentary” tract. The small intestine is commonly described as consisting of three parts: the duodenum, jejunum and ileum. In this article, we will explain the anatomy of the duodenum, focusing on its characteristics that distinguish it from the rest of the small intestine. The duodenum has a distinct anatomy that differs from the other small intestine sections in several aspects, including the reception of bile and pancreatic secretions and its location as a retroperitoneal structure. The jejunum and ileum form the coils of the small intestine that are exposed when the peritoneal cavity is opened during surgery. Therefore, it is important to distinguish the duodenum from the rest of the small intestine and consider it as an independent part of the digestive tract and not part of the small intestine, especially in medical education. This would make understanding its anatomy easier and eliminate confusion, especially for undergraduate medical students
Mathematical Modeling of Broadband Quantum Noise Suppression in Hybrid Quantum Networks for Acoustic Frequency Sensing
Get PDFThis study investigates the optimization of hybrid quantum networks, integrating two-color Einstein-Podolsky Rosen (EPR) light sources and tunable spin oscillators, to enhance Gravitational-Wave Detection (GWD) and distributed quantum sensing. Initial challenges with high quadrature amplitudes were addressed by adjusting frequency and coupling scales, significantly reducing noise below the standard quantum limit. Time evolution analyses demonstrated damped oscillations stabilizing over time, while Power Spectral Density (PSD) plots confirmed effective broadband noise suppression. Design enhancements, such as cryogenic cooling and low loss cavities, further lowered thermal noise and decay rates, improving system scalability. However, residual amplitude clipping and PSD peaks indicate potential nonlinearities and decoherence, suggesting areas for refinement. The study advocates for experimental validation using unclipped models and cost-effective cooling strategies, highlighting the framework’s potential for quantum-enhanced metrology in astrophysics and geophysics. Future research should address scalability and cost challenges to enable practical deployment
Enhancing Molecular Machine Learning with Quantum-Chemical Descriptors and Hybrid Modeling
Get PDFThe integration of quantum chemistry with Machine Learning (ML) offers transformative potential for molecular property prediction, critical for drug design and catalyst development. However, challenges like high computational costs and unreliable predictions in safety-critical applications necessitate robust frameworks. This study aims to develop and evaluate a quantum-enhanced ML framework using a Graph Neural Network (GNN) to predict properties like HOMO-LUMO gaps, binding affinities and reaction energies, focusing on Uncertainty Quantification (UQ), active learning and transfer learning to optimize efficiency and reliability. A GNN model, enhanced with quantum descriptors (MO energy, total electron density) from PySCF, was trained on simulated QM9 subsets and real-world proxies. Techniques included monte carlo dropout and ensemble methods for UQ, active learning to reduce quantum calculations and transfer learning for improved convergence. Performance was evaluated using Mean Absolute Error (MAE) across datasets, with visualization of loss, uncertainty and computational cost. The framework achieved a QM9 MAE of 3.406, outperforming baselines (MAE ~3.5-4.0), but showed higher errors (4.2-4.3) for drug and catalyst proxies due to limited quantum data. UQ provided reliable confidence intervals (e.g., [4.2, 5.4]) and active learning reduced costs by 50%. The framework demonstrates efficacy for QM9-like tasks but requires optimization for real-world applications. Future work should scale to larger datasets, integrate quantum computing and validate with experimental data
The Sustainability-Adjusted Valuation Model (SAVM): Extending Discounted Cash Flow For ESG and Climate Risk
Get PDFThe canonical Discounted Cash Flow (DCF) model remains the dominant framework for corporate and investment valuation, yet its reliance on purely financial parameters limits its ability to capture the material effects of Environmental, Social and Governance (ESG) factors and climate-related risks. This paper introduces the Sustainability-Adjusted Valuation Model (SAVM), a conceptual extension of DCF that explicitly integrates sustainability considerations into both projected cash flows and discount rates. By embedding ESG performance, regulatory transition pathways, physical climate risk and stakeholder externalities within a systematic valuation equation, SAVM aligns financial analysis with the realities of sustainable business performance. The model is situated within established disclosure and risk frameworks such as the task force on climate-related financial disclosures and the Network for Greening the Financial System (NGFS) and it offers a structured methodology for scenario analysis under varying climate and policy futures. SAVM aims to advance the literature on sustainable finance by providing a unified mathematical and conceptual tool for corporate managers, investors and policymakers seeking to reconcile long-term value creation with ESG and climate imperatives
Does Economics Push for an Innovative Idea in Human Society – A Case Study of VI as a Proposed Product in Digital Banking Services: Looking Through Consumer Choice Theory Lens?
Get PDFIn today’s world, it is widely accepted that the economics of digital banking services are vital & meaningful in economy of a country. However, digital-banking services are characterized by evolving many factors that are often unpredictable. It faces serious pitfalls being riskiness when it comes to choices digital banking, particularly bank-led digital banking services. In this busy world, most customers do not read terms & conditions of digital-banking services, and they do not even save contract copy(s) in general. These weaknesses cause abuse(s) in manifolds. On the other hand, by choosing digital-banking services, customers compete for time-saving options and banks compete driving higher profits. All these may further expedite abusive activities in digital-banking services in today’s business-drive world. To marginalize the dilemma of bank-led digital transaction-trends, attaching Voluntary Insurance (VI) as a product under Akim’s Model in e-banking services can ensure secure digital-transaction services. However, no economy country-wise has yet introduced VI as a product in bank-led digital services for ensuring absolute risk-free digital services. Since the bank-led digital transactions dilemmas are no new in economy, policymakers’ attentions on the economics of the VI as an innovative idea for adoption can be instrumental. Accordingly, a SWOT analysis for Voluntary Insurance (VI) in digital banking shows the strengths in enhanced customer trust, reduced bank costs, and new revenue streams, leveraging digital convenience. Adding this product and then its increasing economic value will keep banking-businesses growing. It will ensure risk-free bank-led digital services in economy. It is needed for greater interest in economy, society and for ensuring cashless human society soon where policymakers’ prompt effort will serve as a precondition of success
The Drastic Turn in Neurology: From Classical Disciplines to Neurogenetics
Get PDFThe field of neurology has undergone a profound transformation over the past two decades, shifting from traditional clinical and pathological approaches to a more genetically informed perspective. This essay explores the drastic turn in neurology from classical disciplines to neurogenetics, examining the factors that have contributed to this shift and the implications for clinical practice and research. The traditional approach to neurology, grounded in clinical examination, neuroanatomy, and neuropathology, has been effective in diagnosing and treating many conditions but has had limitations in understanding the etiology of complex and rare neurological disorders. The emergence of neurogenetics has been driven by advancements in genetic technologies, such as Next-Generation Sequencing (NGS) and Genome-Wide Association Studies (GWAS), as well as the recognition of the genetic basis of many neurological disorders. This shift has led to more accurate diagnoses, targeted treatments, and a deeper understanding of the molecular mechanisms underlying neurological disorders. However, challenges remain, including the complexity of genetic architecture and the ethical implications of genetic testing. The future of neurogenetics holds great promise for improving the diagnosis, treatment, and prevention of neurological conditions, with new technologies and interdisciplinary approaches poised to further advance the field.
 
Thromboembolic Risk and Testosterone Replacement Therapy: Debunking Myths and Clarifying Evidence with Recent Systematic Reviews and Meta-Analyses
Get PDFObjectives: To critically evaluate the relationship between testosterone replacement therapy (TRT) and thromboembolic events, addressing concerns raised by older studies while focusing on recent robust evidence. This review analyzes the methodological limitations of earlier studies and presents new, high-quality evidence that refutes these claims. Additionally, we assess the implications of different TRT formulations, patient-specific risk factors, and long-term coagulation effects.
Methods: A systematic review and meta-analysis were conducted, analyzing randomized controlled trials (RCTs) and cohort studies from 2000 to August 2024. The search strategy included PubMed, Embase, and the Cochrane Library, using combinations of terms such as “testosterone replacement therapy,” “thromboembolism,” “cardiovascular events,” “venous thromboembolism (VTE),” “deep vein thrombosis (DVT),” and “pulmonary embolism (PE).” Both earlier studies suggesting increased risk and newer studies refuting these concerns were included. Study quality was assessed using standardized risk of bias tools. Heterogeneity across studies was evaluated using the I² statistic, with subgroup analyses based on TRT formulations, follow-up duration, and patient age.
Findings: Recent meta-analyses and large-scale cohort studies demonstrate that TRT does not significantly increase the risk of thromboembolic events. The pooled relative risk (RR) for major adverse cardiovascular events (MACE) was 1.08 (95% CI: 0.89–1.31, p = 0.46), indicating no statistically significant increase in thromboembolic risk. Sensitivity analyses confirmed the robustness of these findings, and no significant differences were observed between TRT formulations (injections, gels, transdermal patches). However, a wide confidence interval suggests that a clinically relevant increased risk cannot be entirely ruled out, warranting careful patient selection and monitoring. The inconsistencies in previous studies are addressed, considering selection bias, short follow-up periods, heterogeneity in study designs, and lack of adjustment for confounders such as obesity, smoking, and pre-existing cardiovascular disease.
Conclusion: When prescribed appropriately and monitored regularly, TRT does not significantly elevate thromboembolic or cardiovascular risk. Earlier concerns about an increased risk of thromboembolic events were based on studies with methodological limitations, including biased patient selection and inadequate control for confounding variables. However, long-term data on the effects of TRT on thrombin generation and coagulation profiles remain limited, and further research is warranted. Clinicians should feel confident prescribing TRT in hypogonadal men, provided that individualized patient assessments, hematocrit monitoring, and cardiovascular risk evaluations are conducted
Acoustic-Based Species Recognition in Frogs (Order Anura) via Hidden Markov Models (HMMs)
Get PDFBiological indictors of ecosystem health often involve the investigation of various species of amphibians. Frogs (Order Anura) generate a variety of vocalizations (calls or croaks) to fend off predators and attract mates that can be automatically analyzed by utilizing machine learning methods on recordings from large repositories. Hidden Markov Models (HMMs) are widely-used classifiers that have been successfully applied in both human speech processing and bioacoustics to study vocalizations captured by recordings; however, there has been limited usage of HMMs in analyzing large-scale frog datasets, which highlights the need to evaluate their effectiveness for this application. The cepstral coefficients and time derivatives (feature extraction) were extracted from the 1459 vocalizations, and the HMMs were applied to model both the temporal and spectral variations of acoustically comparable vocalizations. Based on the experiments for automatic classification of 9 species of frogs using leave-one-out cross-validation, the classification accuracy ranged from 87.3886% (9 element feature vector, 1275/1459 correct classifications) to 100.0000% (39 element feature vector, 1459/1459 correct classifications). For future work, the HMMs could be applied to other species of frogs for automatic classification and detection of the vocalizations
The Rise and Fall of Nokia: An Important Lesson
Get PDFNokia’s failure to follow the market trend towards the end of the 2000s was the final nail in the coffin for this company. They were unable to maintain their lead until they were left out of the competition in the smartphone industry. This paper examines the contributing factors to Nokia’s rise and fall and attempts to assess the internal and external threats that constrained Nokia’s progress in the industry using the Strengths, Weaknesses, Opportunities and Threats (SWOT) Analysis and Porter’s Five Force Model External Analysis from 2005 until 2014. There has already been vast research carried out regarding Nokia, resulting in a voluminous body of literature about this topic. To make this study different from the existing study, an analysis based on the two different models as guidelines, supp orted by previous literature. In SWOT Analysis, the outcome shows there was a greater preference for Weaknesses and Threats faced by Nokia compared to Strengths and Opportunities. Porter’s Five Force Model External Analysis indicates that Nokia faced no is sues except for the threat of entry. The rest of the components, namely, the bargaining power of buyers, the threat of substitute products, the bargaining power of suppliers, and industry competitors’ rivalry among existing firms, did not show any severe t
hreat to Nokia. Limitations and future research recommendations are also discussed in the paper
Financial Stability and Financial Distortions: A Saddle Path Equilibrium between the Crowding Out Effect and the Financial Accelerator
Get PDFVarious methods of modeling based on stress testing and macrofinancial modeling have been adopted in the literature on financial stability assessment and all display merits as well as drawbacks. The literature on the subject matter of financial stability assessment is still in its infancy and requires novelties with respect to methodologies adopted in the assessment process. The eviction effect or the crowding out effect and the financial accelerator are two issues that are compromisingly involving for financial stability, economic policy making and the nexus between the macroeconomic imperfections and financial imbalances. As far as interactions between key determinants of financial stability are concerned, there is a longstanding dissensus on the impact of the crowding out effect on financial stability as it is an issue intertwined compromising public policy and financial matters whereby the crowding out effect is found to be acting like an actor partially offsetting and slowing down the negative effects of the financial accelerator on financial stability in what we call a saddle path unstable equilibrium following the tendency of the trend of the effect of the financial accelerator on financial stability temporarily then abruptly turning the tendency of the effect of the financial accelerator on financial stability sequentially to mitigate instability partially. This raises concerns about a novel method to assess financial stability and the likely merits of modeling financial stability taking into consideration these two items of commensurate relevance and importance to highlight two main economic effects namely the double dividend theory in presence of distortions and the close relationship of economic and financial matters in face of the hindrance of providing a clear insight into interactions and cross effects among determinants of financial stability. The main scope of going deeper into the intertwined relationship between the eviction effect and the financial accelerator is to better fathom financial stability while at the same time waiving the drawbacks of conventional methods of financial stability assessment that always impair features of commensurate relevance to herald specific concern about microfinancial considerations or macrofinancial considerations and in some instances prioritizing rare innovations or contrariwise neglecting them roughly. The proposed saddle path equilibrium modeling shows clearly the cross effects and interactions of relevant features composing financial stability assessment while at the same time including key microeconomic features relevant to systemic risk in a comprehensive way. The approach highlights indeed the role played by equity and credit in affecting financial
stability. It provides impetus on the effect of government bonds and securities between the credit market and the stock market sectors that makes improvement in stock market sector trading of government securities or attract ability to banking placement or incur draining loanable funds through increase in stock market profitability and deteriorates credit market financial stability by the demand pull effect through the effect of liquidity risk on credit risk in the face of limited tolerance to overall risk incurred by banks and the search for yield motivation of banks. The effect on financial stability through the Stock market sector or what we call the saddle path unstable equilibrium between crowding out effect and the financial accelerator constitutes the cornerstone of our research and will be thoroughly analyzed and scrutinized throughout the mathematical proofs provided in the research referring to the polynomial distributions of risk, the gaussian pivot for multivariate discrete functions, the saddle path unstable equilibrium and the reference to sensitivity analyses and constitutes the novelty provided by this research in face of the drawbacks of available measurement methods displayed in the literature of relevance for the subject matter