Sci

Plants have been used in medicine for centuries to treat various diseases, with alcohol and ethanol being known as universal solvents for the extraction of medicinal plant substances. This article sheds light on Artemisia absinthium (wormwood) and absinthe usage in the history of medicine. The invention of absinthe in Switzerland in 1797 made it an integral part of everyday life and the harmful effects of the massive consumption of this product were labelled absinthism. The medicinal properties of wormwood and absinthe are explored from the earliest records of the use of wormwood from the Ebers Papyrus (copies of which date back to 1550 BC) to the military consumption of absinthe during the French invasion of Algiers in 1830. As widely accepted, A. absinthium has both anthelmintic and antiprotozoal properties. In addition, modern medicine has demonstrated antibacterial, antifungal and antibiofilm properties of the plant extracts. In order to fully utilise the therapeutic potential of A. absinthium, advances in pharmaceutical technology are essential. One promising solution could lie in nanotechnological delivery systems. In our opinion absinthe is another impressive example of how tonics containing various herbal substances were used in the history of medicine to manage infections before their efficacy was later proven in vitro and in vivo. Full article

Iron deficiency anemia remains a major public health concern in Brazil, particularly among children, pregnant women, and women of childbearing age. This scoping review aimed to map the trend line of public policies on iron supplementation and food fortification implemented between 1977 and 2025. The review followed PRISMA-ScR guidelines and the Joanna Briggs Institute methodology, and included searches in PubMed/MEDLINE, Scopus, Web of Science, Embase, Google Scholar, and official government documents. Three main strategies were identified: iron supplementation, mandatory food fortification, and nutrition education. Key milestones included the National Iron Supplementation Program, the 2002 ANVISA Resolution (RDC No. 344/2002) mandating wheat and corn flour fortification, and the launch of the NutriSUS program in 2014. Despite important normative and programmatic advances, persistent critical issues remain, including low adherence, inadequate monitoring, data discontinuity, and bureaucratic barriers. Strengthening intergovernmental coordination, improving information systems, and adopting more bioavailable iron compounds are essential to increase the effectiveness of public policies aimed at preventing and controlling iron deficiency anemia in Brazil. Full article

Cement production in Africa remains carbon-intensive, primarily due to the use of coal-based thermal energy. This study conducts a comparative cradle-to-gate life cycle assessment (LCA) of cement production using 100% coal (Scenario A) against partial substitution with refuse-derived fuel (RDF) at a 20% thermal input rate (Scenario B), with case studies in South Africa and Ethiopia. The LCA, modeled in SimaPro 9.2.0.1 with Ecoinvent v3.7.1 and regional data, evaluates midpoint environmental impacts across the following five stages: raw materials, clinker production, electricity, fuel use, and transportation. The results show that Scenario B reduces the global warming potential (GWP) by 3.3–4.2% per kg of cement, with minimal increases in other impact categories. When avoided landfill methane is accounted for, GWP reduction improves to 6.7%. Fossil resource depletion drops by 10%, and toxicity and particulate emissions show marginal improvements. Economic analysis under South Africa’s 2025 carbon policy reveals a modest net cost increase of $2–3 per ton of cement and an abatement cost of $64–87 per ton of CO₂. The study provides new insights by harmonizing LCA models across national contexts, linking emissions reductions to economic instruments, and quantifying the co-benefits of RDF for waste management. The results support RDF co-processing as a scalable mitigation strategy for the African cement sector, recommending substitution rates of 15–30%, policy alignment, and enhancement of the RDF supply chain to maximize impact. Full article

Large language models (LLMs) are rapidly being explored as tools to support learning and assessment in health science education, yet their performance across discipline-specific evaluations remains underexamined. This study evaluated the accuracy of two prominent LLMs on university-level pharmacognosy examinations and compared their performance to that of pharmacy students. Authentic exam papers comprising a range of question formats and content categories were administered to ChatGPT and DeepSeek using a structured prompting approach. Student data were anonymized and LLM responses were graded using the same marking criteria applied to student cohorts, and a Monte Carlo simulation was conducted to determine whether observed performance differences were statistically meaningful. Facility Index (FI) values were calculated to contextualize item difficulty and identify where LLM performance aligned or diverged from student outcomes. The models demonstrated variable accuracy across question types, with a stronger performance in recall-based and definition-style items and comparatively weaker outputs for applied or interpretive questions. Simulated comparisons showed that LLM performance did not uniformly exceed or fall below that of students, indicating dimension-specific strengths and constraints. These findings suggest that while LLM-resistant examination design is contingent on question structure and content, further research should refine their integration into pharmacy education. Full article

Abductive reasoning—the search for plausible explanations—has long been central to human inquiry, from forensics to medicine and scientific discovery. Yet formal approaches in AI have largely reduced abduction to eliminative search: hypotheses are treated as mutually exclusive, evaluated against consistency constraints or probability updates, and pruned until a single “best” explanation remains. This reductionist framing fails on two critical fronts. First, it overlooks how human reasoners naturally sustain multiple explanatory lines in suspension, navigate contradictions, and generate novel syntheses. Second, when applied to complex investigations in legal or scientific domains, it forces destructive competition between hypotheses that later prove compatible or even synergistic, as demonstrated by historical cases in physics, astronomy, and geology. This paper introduces quantum abduction, a non-classical paradigm that models hypotheses in superposition, allowing them to interfere constructively or destructively, and collapses only when coherence with evidence is reached. Grounded in quantum cognition and implemented with modern NLP embeddings and generative AI, the framework supports dynamic synthesis rather than premature elimination. For immediate decisions, it models expert cognitive processes; for extended investigations, it transforms competition into “co-opetition” where competing hypotheses strengthen each other. Case studies span historical mysteries (Ludwig II of Bavaria, the “Monster of Florence”), literary demonstrations (Murder on the Orient Express), medical diagnosis, and scientific theory change. Across these domains, quantum abduction proves more faithful to the constructive and multifaceted nature of human reasoning, while offering a pathway toward expressive and transparent AI reasoning systems. Full article

We conducted a techno-economic feasibility study and assessed the FP²O resilience of an industrial plant producing magnetized hydrogels from Peruvian Amarilla Reyna potato starch. The process includes alkaline pretreatment, grafting with acrylic acid, crosslinking with N, N′-methylenebisacrylamide, and in situ magnetization via Fe₃O₄ coprecipitation. A total of 12 techno-economic and three financial indicators were analyzed. At the base scale, the total capital investment was 49.78 MMUSD, with raw materials accounting for 92.4% of costs. The economic analysis indicates a payback period of 2.13 years, an IRR of 34.52%, and an NPV of 25.38 MMUSD. The break-even point is at 4760.84 USD/t, with 32.15% capacity utilization, demonstrating operational flexibility to handle demand variations or planned shutdowns. Compared to published techno-economic assessments of lignin- and chitosan-based hydrogels, which involve total capital investments of 236–1248 MMUSD and payback periods in the 6–30-year range, this scheme requires less capital investment and a payback period three to ten times shorter, underscoring its economic competitiveness on an industrial scale. Full article

Kalanchoe laetivirens is widely consumed as a medicinal plant in rural and urban communities, traditionally used in folk medicine for treating inflammatory conditions and cancer. However, little is known about its elemental composition and the potential health risks associated with different preparation methods. This study aimed to evaluate concentrations of Al, As, Ba, Co, Cu, Fe, Mg, Mn, Mo, Na, Ni, P, Pb, Se, V, and Zn in raw leaves, tea infusions, and aqueous extracts, and to assess associated health risks. Elemental analysis revealed significant differences among preparations, with raw leaves presenting the highest concentrations, tea showing intermediate values, and aqueous extracts the lowest. For example, potassium (K) reached 15,399.31 ± 131.55 mg/kg in leaves and 12,249.97 ± 240.17 mg/L in tea, while arsenic (As) and lead (Pb) were also detected at concerning levels, with As at 5.98 ± 1.64 mg/L and Pb at 3.82 ± 0.179 mg/L in tea. Risk assessment was performed using the Chronic Daily Intake (CDI), Hazard Quotients (HQs), Hazard Index (HI), and Incremental Lifetime Cancer Risk (ILCR), considering different exposure frequencies. Results indicated phosphorus (P) as the dominant contributor to non-carcinogenic risk, with HI values exceeding safety thresholds in all scenarios, while arsenic was the primary carcinogenic element, with ILCR values up to 10⁻³ in tea. These findings highlight the influence of preparation methods on exposure levels and reinforce the need for continuous monitoring and regulatory guidelines to ensure the safe medicinal use of K. laetivirens. Full article

Artificial intelligence (AI) is transforming pharmaceutical science by shifting drug delivery research from empirical experimentation toward predictive, data-driven innovation. This review critically examines the integration of AI across formulation design, smart drug delivery systems (DDSs), and sustainable pharmaceutics, emphasizing its role in accelerating development, enhancing personalization, and promoting environmental responsibility. AI techniques—including machine learning, deep learning, Bayesian optimization, reinforcement learning, and digital twins—enable precise prediction of critical quality attributes, generative discovery of excipients, and closed-loop optimization with minimal experimental input. These tools have demonstrated particular value in polymeric and nano-based systems through their ability to model complex behaviors and to design stimuli-responsive DDS capable of real-time therapeutic adaptation. Furthermore, AI facilitates the transition toward green pharmaceutics by supporting biodegradable material selection, energy-efficient process design, and life-cycle optimization, thereby aligning drug delivery strategies with global sustainability goals. However, challenges persist, including limited data availability, lack of model interpretability, regulatory uncertainty, and the high computational cost of AI systems. Addressing these limitations requires the implementation of FAIR data principles, physics-informed modeling, and ethically grounded regulatory frameworks. Overall, AI serves not as a replacement for human expertise but as a transformative enabler, redefining DDS as intelligent, adaptive, and sustainable platforms for future pharmaceutical development. Compared with previous reviews that have considered AI-based formulation design, smart DDS, and green pharmaceutics separately, this article integrates these strands and proposes a dual-framework roadmap that situates current AI-enabled DDS within a structured life-cycle perspective and highlights key translational gaps. Full article

This study is motivated by the severe tribological regime of PA6 composites in VR platforms operating under dry or boundary lubrication, where alternating shear during foot rotation, localised contact pressures, and third-body abrasion concurrently challenge wear resistance and retention of strength. This paper presents the results of research into the properties of composites based on polyamide PA6 and molybdenum disulphide, obtained by combining the components through high-intensity mechanochemical activation in a planetary mill and classical mixing in a turbulence mixer. We demonstrate that varying the energy of the premixing stage (mechanochemical activation versus low-energy premixing) serves as an effective means of interfacial engineering in PA6/MoS₂ composites, enabling simultaneous enhancement of mechanical and tribological properties at low filler contents. Analysis of experimental composite samples using Fourier-transform infrared spectroscopy (FTIR) indicates the interaction between MoS₂ and oxygen-containing groups of polyamide while maintaining its overall chemical composition. According to the TG-DSC curves, modification of polyamide leads to an increase in the melting temperature by 2 °C, while mechanical activation ensures stronger interaction between the matrix and the filler. Compared to pure PA6, the tensile strength of composites increases by 10–20% for mechanoactivated materials and by 5–10% for materials obtained by conventional methods. The mechanical activation effect is observed even at minimal amounts (0.25 and 0.5%) of MoS₂ in composites. The toughness of all composites, regardless of the mixing method, increases by 5–7% compared to pure polyamide. All composites show a 10–20% reduction in the coefficient of friction on steel. Simultaneously, the water absorption of composites becomes 5–20% higher than that of the original material, which indicates a change in structure and an increase in porosity. The obtained composite materials are planned to be used for manufacturing platforms for the movement of virtual reality (VR) operators. Full article

Despite its economic profitability, fur farming in Europe, responsible for half of global production, faces a growing ethical backlash. Animal welfare concerns, particularly regarding mink, foxes, and raccoon dogs kept in restrictive cages, have intensified due to advocacy, scientific reviews, and COVID-19 outbreaks. In response, several EU nations have implemented bans or stricter regulations. However, limited research exists on EU public opinion. This study analyses data from Eurobarometer 533 (March 2023), surveying 26,368 citizens across 27 EU countries, to assess attitudes toward fur farming. Respondents selected from three policy preferences: a full ban, EU-wide regulation, or acceptance of current practices. Multinomial logistic regression and chi-square tests revealed significant socio-demographic and ideological influences. Older individuals were more supportive of current practices (p = 0.001), while higher education levels correlated with support for a ban or stricter regulation (p = 0.003). Income positively influenced support for regulation (p = 0.002), and women (p = 0.008), urban residents (p = 0.001), and those with regular animal contact (p = 0.007) were more likely to support reform. Right-leaning respondents (p = 0.012) and residents of countries without fur farming bans (p < 0.001) were less supportive. These findings suggest that values, demographics, and national legislation significantly shape public opinion. Aligning policy with evolving societal values requires integrated legislative reform, public engagement, and equitable transition strategies to ensure meaningful and sustainable improvements in animal welfare across the EU. Full article

Honeycomb graphene aerogels offer a combination of graphene wall qualities, such as mechanical strength and binding, and the unique, engineered architecture of honeycombs. The honeycomb structure opens new opportunities for property modification, such as reinforcement with metal nanoparticles, which can increase strength and electrochemical performance. This study uses molecular dynamics simulations to examine the reinforcement of graphene honeycomb aerogels containing 2.7% and 5.8% randomly distributed Ni or Al nanoparticles. Metal nanoparticles considerably increase the resistance to compression: stress increase occurred for aerogels with Al nanoparticles at a density of 1.3 g/cm³, while for aerogels and filled with Ni, stress increase occurred at 2.0 g/cm³. The strengthening mechanism is volume repulsion when Al NPs repel the graphene cell walls, while Ni nanoparticles easily spread along the cell walls and provide less compression resistance, analogous to pure graphene aerogels. The tensile properties remained unaffected by the presence of either nanoparticle type since the same deformation mechanism (cell collapse) occurred for all aerogels. The maximal ultimate tensile strength achieved was 160 GPa. Temperatures ranging from 300 to 3000 K slightly affected the strength of all aerogels. Full article

This paper presents the design of an autonomous robot guide for a museum-like environment in a motorcycle assembly plant. The system integrates Industry 4.0 technologies such as artificial vision, indoor positioning, generative artificial intelligence, and cloud connectivity to enhance the visitor experience. The development follows the Design Inclusive Research (DIR) methodology and the VDI 2206 standard to ensure a structured scientific and engineering process. A key innovation is the integration of mmWave sensors alongside LiDAR and RGB-D cameras, enabling reliable human detection and improved navigation safety in reflective indoor environments, as well as the deployment of an open-source large language model for natural, on-device interaction with visitors. The current results include the complete mechanical, electronic, and software architecture; simulation validation; and a preliminary implementation in the real museum environment, where the system demonstrated consistent autonomous navigation, stable performance, and effective user interaction. Full article

In this paper, the dependence of the microstructure and properties on Spark Plasma Sintering modes of an AlN-35 β-SiC (wt.%) composite is investigated. It was found that the use of a heating rate of 100 °C/min during the sintering process of the AlN-35 β-SiC (wt.%) composite leads to the formation of a solid solution (AlN)_x–(SiC)_x−1 at 1900 °C during 5 min, and under a pressure of 50 MPa. It was observed that, at a heating rate of 50 °C/min and a pressure of 25 MPa, yttrium oxide used as a sintering additive impedes the diffusion of SiC into AlN. This impedes the formation of a solid solution (AlN)_x–(SiC)_x−1 and helps preserve SiC grains, which act as the main absorbing phase in the obtained composites. It is shown that the use of sintering additives and SPS technology allows obtaining samples with a density of 3.26 g/cm³, which coincides with the theoretical value of the composite. The dielectric characteristics and absorbing properties of sintered materials are determined in the frequency bands from 5.6 to 26 GHz. It has been discovered that the reflection, transmission, and absorption coefficients can be regulated depending on the thickness of the sample. In addition, it is shown that composites containing solid solutions and silicon carbide grains in their structures have the best absorbing properties. On the other hand, the material containing only solid solutions is a promising material that can be used as microwave filters. Full article

This study presents an analytical and multiscale investigation of the degradation of elastic properties in ordinary Portland cement (OPC) paste subjected to calcium leaching. Eight representative microstructures and three homogenization schemes (Mori–Tanaka, Hashin–Shtrikman, and Voigt) were evaluated to determine the most suitable configuration for predicting stiffness evolution. Model validation against benchmark experimental data at 14 and 56 days demonstrated good agreement, with prediction errors within 10%. Simulation results reveal that progressive decalcification leads to significant reductions in both bulk and shear moduli, with the calcium hydroxide (CH) phase being the most sensitive, followed by low-density (LD) and high-density (HD) calcium silicate hydrate (CSH). The overall stiffness loss increases with the water-to-cement ratio ($w/c$), exceeding 90% at $w/c=0.5$ under complete decalcification. A sensitivity analysis further shows that the rate of modulus degradation decreases with increasing $w/c$, reflecting a mechanical normalization effect rather than improved chemical stability. These findings highlight the dominant role of calcium preservation in maintaining mechanical integrity and provide a robust theoretical framework for predicting the chemo-mechanical degradation and long-term durability of cement-based materials in aggressive environments. Full article

This paper introduces a novel stochastic optimization framework for the optimal sizing of thyristor-switched capacitors (TSCs) in medium-voltage distribution networks. Unlike conventional deterministic approaches, the proposed model explicitly incorporates load demand variability through multiple probabilistic scenarios, thereby enhancing the robustness and reliability of reactive power compensation. The methodology employs advanced nonlinear programming techniques, i.e., the IPOPT solver within a scenario-based framework, in order to determine the TSC sizes that minimize the expected total system costs, including those associated with energy losses and investments. According to extensive simulations on a standard 33-bus distribution system, our stochastic approach yields cost savings of approximately 12.3–12.4% while significantly improving voltage stability and operational efficiency under various load conditions. Assessments regarding voltage profile performance and average processing times, as well as a comparative analysis considering deterministic results, were also conducted in order to validate the effectiveness and computational efficiency of the approach. This study underscores the importance of probabilistic modeling for a smarter, more resilient grid operation, laying a solid foundation for integrating adaptive reactive power devices to support sustainable and reliable power distribution in evolving smart grid environments. Full article

Pesticides play a critical role in food production by enhancing crop yields and protecting against pests and pathogens, such as insects, bacteria, fungi, and weeds. However, their extensive use raises significant environmental concerns. The paper reviews and describes the reported adverse effects of pesticides on terrestrial and marine life to raise awareness of the ecological impact of pesticide use across life niches. The adverse effects on soil microorganisms, arthropods, reptiles, and amphibians highlight the extensive ecological disruption caused by these chemicals. Understanding the mechanisms of pesticide toxicity and their impact on various organisms is crucial for developing effective bioremediation techniques and on-field management practices. By implementing these strategies and enhancing environmental biomonitoring, countries can mitigate the harmful effects of pesticides, ultimately protecting biodiversity and ensuring the health of their ecosystems. Full article

In this work, we fabricated activated carbon using the peel of musa paradisiaca (banana) as the carbonaceous material source. The activated carbon was obtained after applied a carbonization process under nitrogen atmosphere at 723.15 K. The activated carbon was chemically modified using three chemical agents (citric acid, tartaric acid, and EDTA). The surface properties of the materials were characterized by nitrogen sorptometry at 77 K. Furthermore, we determined the zero-load point of all materials. The kinetic and isothermal behavior of the materials to remove methylene blue from aqueous solution was studied. The thermodynamic parameters of the process for all materials were determined by applying the van’t Hoff equation. Results showed that after chemical activation, there was an increase in the content of oxygenated groups onto activated carbon. Furthermore, the BET surface area of activated carbon was reduced from 808 to 724 m² g⁻¹. The volume of micropores was smaller after chemical activation and the volume of mesopores was greater. The zero-load point of materials was in a range between 4.96 and 5.60. Kinetic and isothermal results showed that after chemical modification, the removal capacity increased from 30.2 for activated carbon to 52.6 mg g⁻¹ for activated carbon modified with EDTA. Finally, the thermodynamic parameters showed that methylene blue adsorption using all materials was an endothermic and spontaneous process; the ΔG° value of activated carbon was −4.35 kJ/mol, and the ΔG° value of activated carbon modified with EDTA was −6.28 kJ/mol. Full article

Recently, we found that combining various antimicrobial polypeptides (AMPs) with enzymes exhibiting lactonase activity results in an antifungal agent with significantly enhanced stability and antimicrobial action efficiency. In this context, this study aims to investigate the catalytic and antifungal activity and physical-chemical properties of antifungal enzyme combinations hydrolyzing fungal cell wall components with various AMPs, comparing them with enzymes exhibiting lactonase activity (capable of hydrolyzing lactones by ring opening). Additionally, combinations of enzymes targeting the fungal cell wall and/or hydrolyzing fungal lactone-containing Quorum-sensing molecules with polyamino acids (PAAs) supplemented with fungicides (PAAF) were studied for comparison with AMP-containing combinations. Interaction models for these antifungal enzyme combinations were simulated in silico using the molecular docking method. The most promising variants, which were predicted to possess high catalytic activity, were selected, and their catalytic and physical-chemical characteristics were further evaluated in vitro. The antifungal activity of the selected combinations of enzymes with AMPs or PAAF was assessed against a number of fungi, leading to the identification of several combinations as potential candidates for inclusion in antifungals. Unexpectedly, antifungal enzyme combinations with lactonase activity were, in most cases, more effective than those with fungal-cell-wall-degrading enzymes. Full article

The rapid development of genomic science beyond its molecular roots to impact many aspects of clinical and rehabilitative practice presents an epistemic challenge and a pressing ethical obligation in its use in occupational therapy. By reviewing interdisciplinary literature at the intersections of genomics, bioethics, and occupational therapy, this review article seeks to unpack the ways genomic knowledge influences the understandings of health, participation, and justice within the profession. Using critical bioethical theory and socio-technical frameworks, the review discusses the movement from reductionist genetic frameworks to relational and systems-based approaches to health that consider epigenetic, environmental, and social determinants. Key themes that emerged include the promise of new understandings of personalized rehabilitation, the potential to exacerbate existing inequities, and effects on professional autonomy and ethical responsibility. The article does not advocate for or against the inclusion of genomic science in occupational therapy, but instead, advocates for reflexive, justice-oriented ethics of genomics, and concludes with a discussion of a translational bioethical framework to help support its responsible use in occupational therapy practice and policy. Full article