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Non-human animal rights jurisprudence in moral law and positive law: meta-philosophical disputations
(Jumuga Journal of Education, 2026-04) Kizito, Michael George
Non-Human animal rights have become the vogue since the beginning of the 20th century. Positivist oriented scholars especially from the disciplines of anthropology, law, and political science have contended that humans are not special and are far better than animals because they are all part of the evolutionary continuity. According to these scholars, it is scientifically proven that non-human animals also speak languages, have morality and empathy like humans. They thus propose that non-human animals should be accorded rights analogous to human rights enshrined in international human rights instruments such as; the Universal Declaration of Human Rights (UDHR), the International Covenant on Civil and Political Rights (ICCPR) and the International Covenant on Economic, Social and Cultural Rights (ICESCR). The failure to heed to this scientific predicament is regarded as equivocally consistent with human supremacism, exceptionalism and speciesism. This meta-philosophical master piece assesses the intricacies of instituting soft and hard law non-human animal rights instruments such as; the Universal Declaration of Non-Human Animal Rights (UDNHAR) and the International Covenant on Non-Human Animals’ Social and Economic Rights(ICNHASER). It is premised on the argument that non-human animals should be accorded justiciable sentient privileges, sympathies and empathies instead of rights because they are amoral beings. The article contends that guaranteeing nonhuman animals justiciable sentient privileges is tantamount to sentient realism and not human supremacism, exceptionalism and speciesism.
Deep learning based constraint aware design exploration of triply periodic minimal surface bone scaffolds
(Discov Mechanical Engineering, 2026-04-27) Bwengye, Innocent; Ahishakiye, Emmanuel; Wasswa, William; Obungoloch, Johnes
Bone tissue engineering scaffolds must provide structural support while permitting fluid transport and maintaining safe hydrodynamic conditions for cell activity. Triply Periodic Minimal Surface (TPMS) architectures such as Gyroid, Schwarz-P, and Diamond offer continuous curvature and tunable porosity, yet identifying configurations that simultaneously satisfy mechanical, transport, and manufacturability requirements remains computationally expensive. This study presents a constraint-aware computational framework for rapid exploration of TPMS scaffold design spaces by combining procedural geometry generation, analytical physics-consistent property estimation, and a geometry-aware deep learning surrogate model. A dataset of 1000 voxelized scaffolds (porosity 0.55–0.80; unit-cell size 0.8–1.2 mm) was used to train a multitask 3D convolutional neural network to approximate apparent modulus, permeability, effective diffusivity, and shear-exposure indicators derived from established mechanistic relations. The surrogate achieved a mean absolute error of approximately 3.9 GPa for predicted stiffness and reproduced transport trends on the order of 10−11 m2/s, enabling screening of more than 3000 candidate geometries without performing high-fidelity simulations. Pareto analysis revealed strong stiffness–transport trade-offs across TPMS families. Manufacturability constraints, particularly a minimum printable wall thickness of approximately 0.30 mm, eliminated many high-porosity designs. A near-feasible Schwarz-P configuration (ϕ ≈ 0.86, a ≈ 2.6 mm) exhibited moderate predicted stiffness (~ 2.1–2.5 GPa after thickness adjustment), effective diffusivity ≈3 × 10−11 m2/s, and permeability on the order of 10−10 m2, illustrating the competing requirements of structural support and perfusion. The proposed framework functions as a geometry-aware design-screening and prioritization tool that identifies candidate scaffold configurations prior to detailed finite-element, computational-fluid-dynamics, or experimental validation. The work provides a reproducible approach for accelerating early-stage scaffold design exploration and guiding subsequent biomechanical evaluation.
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Mechanistic modeling of crack propagation in hydraulically fractured reservoirs for predicting inter-well fracture communication during infill well stimulation
(Geomechanics for Energy and the Environment, 2026-04-20) Pidho, Justin Jordan; Wanasolo, William; Yan, Chuanliang; Cheng, Yuanfang
Inter well fracture communication is a persistent challenge in multi well infill stimulation, often reducing production efficiency and compromising reservoir integrity. This study develops a mechanistic framework based on the Extended Finite Element Method (XFEM) with phantom node enrichment to simulate multi fracture propagation between neighboring horizontal wells. The model couples poroelastic rock deformation, fracture-matrix fluid exchange, pressure dependent leak off, and fracture propagation governed by a traction-separation law, providing a fully integrated representation of hydraulic fracturing processes. Parametric analyses reveal that zero-stagger distance with simultaneous injection promotes complete fracture linking, while larger offsets or scheduled treatments mitigate communication through stress shadow effects. Increasing rock tensile strength enhances fracture repulsion and reduces tip to tip linking. Distinct pressure signatures differentiate linking fractures, which exhibit localized sagging, from non linking fractures with monotonic gradients. The framework was validated against Displacement Discontinuity Method (DDM) benchmarks, Kristianovich-Geertsma-de Klerk (KGD) analytical solutions, and field measured pressure data from the Daqing Oilfield, demonstrating strong goodness of fit and confirming model fidelity. This work finds useful application in designing perforation patterns, optimizing cluster spacing, and scheduling treatments in unconventional shale reservoirs. By enabling accurate prediction of fracture linking, coalescence, and repulsion, the framework provides practical guidance for maximizing stimulated reservoir volume while controlling unintended inter well interference.
A factory-level data-informed roadmap to industry 4.0 for low digital maturity steel manufacturing plants
(International Journal of Advanced Manufacturing Technology, 2026-04-25) Kangwagye, Samuel; Ssempijja, Maureen Nalubowa
This paper presents a factory-level, data-informed Industry 4.0 readiness and upgrade framework for steel manufacturing plants operating in low digital maturity environments, using Uganda as a representative case. Field data was collected at three medium-scale operational steel plants. Customized Digital Maturity Index (DMI) and cybersecurity risk (CSR) assessment criteria were developed and applied. Results show an overall DMI score of 1.8, indicating very low digital maturity with predominantly manual operations, absence of industrial robots, advanced automation, and integrated digital data systems. CSR assessment results show limited formal protection mechanisms. A phased, ROI-driven transition roadmap is proposed. A worked case using plant-level production data demonstrates that selective automation of four bottleneck stations could nearly double annual billet output and achieve an incremental payback period of approximately seven weeks under stated assumptions. Workforce transition modeling using a Markov approach indicates gradual role transformation over an expected horizon of about ten transition cycles rather than abrupt displacement.
Antimicrobial Activity of Isolated Compounds from Zanthoxylum gilletii Stem Bark Extract
(International Research Journal of Pure and Applied Chemistry, 2026-04-20) Niringiyimana, Eric; Twinomuhwezi, Hannington; Gumula, Ivan; Odokonyero, I; Byaruhanga, Ivan; Onen, Patrick
Background: Zanthoxylum gilletii, an important African medicinal plant, is widely used in traditional medicine for treating various ailments due to its rich phytochemical composition. However, despite its extensive ethnomedicinal applications, the specific bioactive compounds responsible for its antimicrobial properties remain insufficiently characterized. Aims: The study aims to isolate and characterize bioactive compounds from Zanthoxylum gilletii stem bark and evaluate their antimicrobial activity against selected bacterial and fungal pathogens. Methodology: Zanthoxylum gilletii stem bark was collected from Mabira Forest Reserve (0°23′54″N 33°0′59″E), Buikwe District, Uganda on 17th June 2022. The experiments were performed at the Department of Chemistry, Kyambogo University, between June 2022 and July 2023. Stem barks were shade dried, powdered, and extracted using Maceration technique with a mixture of methanol and dichloromethane (ratio 1:1) solvent. The extract was subjected to open column chromatography and identified using NMR spectroscopy and compared with literature information. Antimicrobial activity of crude extract and also the isolated compounds were assessed via disk diffusion against five bacterial and two fungal strains. Results: In this study, four known compounds: lupeol (1), stigmasterol (2), α-amyrin cinnamate (3) and α-amyrin acetate (4) were isolated from stem bark extracts of Zanthoxylum gilletii. This is the first-time compound 4 is reported in Zanthoxylum genus. The compounds had antimicrobial activities against Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Enterobacter cloacae, Candida albicans and Aspergillus fumigatus. The extract and the compounds displayed inhibition against the microorganisms with diameters measuring 3.0±0.0 mm to 19.0±0.0 mm. The minimal inhibitory concentrations (MICs and MFCs) for active strains ranged from 6.25 to 150 mg/mL. Conclusion: The observed activities support the traditional use of this plant in treating various ailments by Ugandan communities.