Britain International of Exact Sciences (BIoEx) Journal

Spirals of Nature: Geometry, Growth, and the Dance of Entropy

2026-01-15T04:33:26+00:00

The concept of pasta serves as a unique lens to explore the interplay of physics and biology across scales, from everyday phenomena to cosmic events. This study integrates three phenomena spaghetti breaking, nuclear pasta in neutron stars, and spiral patterns in biological systems to illustrate fundamental principles like elasticity, wave propagation, extreme matter, and biological optimization. The purpose was to develop a unified computational framework to demonstrate how pasta bridges physics and biology, providing educational insights. Three simulations were conducted using Python. Spaghetti breaking was modeled as a 1D elastic rod, solving the wave equation to study stress wave propagation. Nuclear pasta was simulated via molecular dynamics, modeling 100 nucleons to identify gnocchi, spaghetti, and lasagna phases. Spiral patterns were generated using Vogel’s (1979) phyllotaxis model (r=c√n,θ=n∙〖137.5〗^o for 500 seeds, comparing their density to a circular arrangement. The spaghetti-breaking simulation showed stress waves causing multiple fractures, with 5.00 Joules of elastic energy released. Nuclear pasta exhibited a shear modulus of 1.23×1020 Pa, highlighting its role in gravitational wave production. The spiral simulation achieved a 15.22% density increase (bounding circle). Pasta effectively unifies physics and biology, offering a valuable educational tool despite density calculation discrepancies. Adjust parameters like c or the number of seeds in the spiral simulation and enhance models to 3D for accuracy.

Predicting the Borana Lunar-Stellar Calendar: An Astronomical Feature Engineering and Machine Learning Approach

2026-04-17T09:12:06+00:00

The Borana calendar of southern Ethiopia and northern Kenya is a unique lunar stellar system where months are defined by new moon conjunctions with specific anchor stars (Triangulum, Pleiades, Aldebaran, Bellatrix, Orion Saiph, Sirius). Unlike arithmetic calendars, it relies on empirical observation by Borana ayyantu (calendar keepers), making prediction challenging. This study aimed to formalize the Borana calendar's astronomical logic using machine learning, predicting new moon conjunction dates, month names (1–12 or intercalary), and day name indices (0–26) from celestial features. Synthetic astronomical data were generated based on synodic month variations, stellar longitudes, and intercalation rules. Features included Moon longitude, angular distance to anchor stars, and cumulative month counts. An LSTM network predicted conjunction dates, while Random Forest classifiers predicted month and day names. Performance was evaluated against baseline arithmetic models. The LSTM achieved Mean Absolute Error of 0.230 days for conjunction dates, improving 7.3% over the mean synodic month baseline. Month classification accuracy reached 94.1%, and day classification 87.5%. Feature importance confirmed angular distance to anchor stars as the strongest predictor. Borana New Year (2027–2070) was predicted between August 18 and October 22. Machine learning successfully captures the Borana calendar's empirical logic, though accurate long term forecasting requires high precision ephemerides and field validation. The framework provides a reproducible methodology for formalizing indigenous timekeeping systems. Future work should integrate JPL ephemerides, ethnographic field data, and open source software tools to support Borana calendar preservation and prediction.

Prioritizing Renewable Energy Systems in Ethiopia: A Fuzzy TOPSIS Framework Incorporating Climate Vulnerability and Grid Constraints

2026-04-20T07:12:26+00:00

Ethiopia derives approximately 98% of its electricity from renewable sources, predominantly hydropower. However, climate-induced droughts increasingly threaten hydropower reliability, while grid infrastructure limitations constrain variable renewable integration. Existing energy planning lacks a systematic framework to balance these competing priorities under uncertainty. Purpose: This study develops a fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) framework to prioritize five renewable energy systems large hydropower, wind, solar PV, hybrid solar-wind-battery, and geothermal for Ethiopia, explicitly incorporating climate vulnerability and grid constraints alongside technical, economic, environmental, socio-political, and risk criteria. Method: Triangular fuzzy numbers capture linguistic assessments from policy documents and stakeholder input. Fifteen sub-criteria are evaluated using fuzzy TOPSIS, with criteria weights derived from Ethiopian policy analysis emphasizing climate resilience and grid expansion. Sensitivity analyses test weight variations. Findings: Under baseline weighting (very high climate vulnerability weight), wind ranks first (closeness coefficient 0.645), followed by geothermal (0.614), hybrid (0.559), solar PV (0.506), and large hydropower (0.369). Hydropower’s low ranking results from extreme climate vulnerability, water consumption, and land use penalties. Sensitivity analysis shows hybrid systems become more competitive as grid constraint weight increases, while hydropower’s rank declines further when climate risk is emphasized. Conclusion: Incorporating climate vulnerability fundamentally reverses conventional hydropower-first prioritization. Diversification toward wind, geothermal, and hybrid-battery systems is essential for climate-resilient energy planning. Recommendation: Ethiopian policymakers should cap new large hydropower, accelerate wind and geothermal deployment, and promote hybrid storage solutions for weak-grid areas.

Pi as Cosmic Fingerprint: A Multidisciplinary Review of a Mathematical Constant in Science, Scripture, and the Argument from Design

2026-04-21T03:15:06+00:00

The mathematical constant π (approximately 3.14159) appears ubiquitously across geometry, physics, probability, and cosmology. Its universality and non-arbitrariness have prompted philosophical and theological questions about whether π is a human tool, a discovered law, or evidence of design. Purpose: This multidisciplinary review integrates mathematics, physics, astronomy, biblical hermeneutics, theology, and philosophy of science to evaluate the Argument from Design using π. The review synthesizes peer-reviewed literature, scriptural analysis (1 Kings 7:23), and philosophical critiques, including theistic and naturalistic counterarguments. π's universality, logical necessity, and unreasonable effectiveness (Wigner, 1960) are compatible with theism but do not prove it. Major counterarguments include π as human abstraction (Rosen, 2012), logical necessity (Carroll, 2016), no causal connection, God of the gaps (Stenger, 2007), and multiverse hypotheses (Tegmark, 2014). π functions as a "Rorschach test" for worldviews, scientists see a tool, and theologians see a signature. The design argument is probabilistic, not deductive. Future research should integrate empirical studies on mathematical cognition and cross-cultural perceptions of constants.