Medicinal plants represent a valuable source of bioactive secondary metabolites with proven physiological and therapeutic effects. Ziziphus spina-christi is widely recognized for its rich phytochemical composition and traditional medicinal applications; however, its relationship with amino acid homeostasis and renal function remains insufficiently explored. This study aimed to investigate the correlation between Ziziphus secondary metabolites and amino acid homeostasis and to evaluate their effects on growth performance and renal biomarkers in a rabbit model. Fresh leaves of Ziziphus spina-christi were collected from the Green Mountain region, Libya, extracted using 70% ethanol, and analyzed for amino acid composition using high-performance liquid chromatography (HPLC). Ten healthy male rabbits were randomly assigned to either a Sidr-treated group, receiving 200 mg/kg body weight of the extract orally every other day for six weeks, or a control group receiving distilled water. Body weight was recorded weekly, and serum renal biomarkers, including urea, creatinine, and uric acid, were measured at the end of the experimental period. HPLC analysis revealed a diverse amino acid profile in Ziziphus leaf extract, with proline being the most abundant amino acid (23.10 mg/mL), followed by glutamine (19.60 mg/mL) and serine (16.02 mg/mL), indicating strong nitrogen metabolism and antioxidant potential. Sidr-treated rabbits showed a significant increase in final body weight compared to controls (P < 0.05). Moreover, serum urea, creatinine, and uric acid levels were significantly reduced in the treated group, reflecting improved renal function and nitrogen metabolism. In conclusion, Ziziphus spina-christi extract enhances growth performance and exerts a nephroprotective effect, likely mediated through its rich secondary metabolite content and its role in maintaining amino acid homeostasis. These findings support the potential application of Ziziphus as a natural therapeutic and nutritional agent for promoting metabolic balance and renal health.

This paper presents Dynamic Consensus Optimization (DCO) that integrates online feedback-control framework that augments a Raft-based ordering service with real-time parameter adaptation. DCO continuously monitors transaction arrival rates, queue lengths, and network conditions, and dynamically tunes core Raft parameters such as batching size, election timeouts, and heartbeat intervals without compromising Raft’s safety guarantees. We apply DCO to a simulated healthcare environment, where IoT-enabled devices, sensors, and inter-institution data transfers generate highly variable workloads. The proposed approach yields several advantages. First, the blockchain layer sustains low confirmation latency as IoT workloads vary in volume and complexity across participating institutions. Second, the system scales more gracefully: as the number of member hospitals or patient records grows, DCO dynamically adjusts resources to maintain responsiveness without manual reconfiguration or centralized bottlenecks. Third, decentralization is reinforced through leadership rotation and distributed validation tasks, mitigating centralization of power and reducing single points of failure. By continuously balancing speed, scalability, and safety, DCO enables healthcare providers to adopt blockchain-enabled data sharing with stronger performance guarantees and fewer operational frictions. The paper also outlines a formal argument for safety preservation under dynamic parameter updates and presents an evaluation plan to quantify latency, throughput, scalability, and resilience under heterogeneous IoT workloads.

Indonesia is a country with diverse cultures, customs, languages, and religions. This presents a great potential to become a nation rich in inclusive and multicultural values. However, it can often backfire if we fail to cultivate this diversity as a source of pride. It can even become the seed of radicalism or fanaticism among certain groups if it is not nurtured from an early age. Therefore, it is crucial to teach young children about inclusive and multicultural education—the meaning of cultural, customary, linguistic, and even religious diversity within a given context. This article was researched through observations of early childhood education environments, literature studies, and documentation. Through this article, it is hoped that all of us, especially those in early childhood education settings, will understand the importance of inclusive and multicultural education, which must be implemented from an early age to reduce intolerance.

This study investigates how column material selection reshapes the seismic response topology of space-frame roof systems through a hybrid causal–probabilistic framework. Rather than treating seismic performance as a deterministic outcome, the research conceptualizes space frames as stochastic force networks governed by boundary-defined interventions. Nonlinear spatial finite element modeling is integrated with Monte Carlo simulation, topology-informed robustness metrics, and Bayesian counterfactual inference to quantify how reinforced-concrete and steel columns alter axial force redistribution, nodal demand localization, and progressive failure mechanisms. Results demonstrate that steel-supported systems sustain higher axial force dispersion, greater load-path redundancy, and reduced uncertainty amplification, while reinforced-concrete supports promote force localization and accelerated yielding. Counterfactual analysis confirms statistically significant robustness gains under steel column substitution, with intervention benefits increasing nonlinearly under higher seismic demand. The findings establish column material as a primary causal control parameter governing adaptive seismic robustness in space-frame roofs, advancing resilience assessment beyond conventional response-based design toward topology-aware structural optimization.