Moisture buffering and mould growth characteristics of naturally ventilated lime plastered houses.

Lime plaster is a sustainable building material that can be an effective passive cooling strategy. The moisture buffering quality of lime causes adsorption and desorption of moisture which moderates the indoor relative humidity. Its vapour permeability is also influential in moisture transfer across the building envelope. Lime plaster also has a self-healing quality which prevents the formation of inner cracks. Moreover, its strength increases with time leading to a longer life span. In old structures, an important function is the breathability of ceilings and walls. Hence, it is often used in conservation projects where it improves the appearance and durability of old buildings. Often organic additives employed to impart certain qualities to the lime mortar/plaster led to mould growth. Mould growth degrades indoor air quality, and the occupant health is compromised. To avoid mould-related problems, it is necessary to understand the behaviour of lime plaster with respect to the indoor relative humidity and surface moisture content. This paper focuses on the hygrothermal performance of lime plaster in naturally ventilated residential spaces. Surveys were carried out in 45 traditional buildings in Ahmedabad in India with measurements of ambient variables, such as temperature, relative humidity, wall moisture content, etc. The mould growth patterns of these spaces are related to the measured variables and wall characteristics. Hygrothermal simulations of some spaces were also carried out to observe the moisture buffering of lime plaster. Experimental observations were then compared to simulation results to see if the predictions of the hygrothermal models were realistic.

On the relationship between water adsorption and surface chemistry in soda-lime silicate glasses.

Understanding how the surface structure affects the bioactivity and degradation rate of the glass is one of the primary challenges in developing new bioactive materials. Here, classical and reactive molecular dynamics simulations are used to investigate the relationship between local surface chemistry and local adsorption energies of water on three soda-lime silicate glasses.  The compositions of the glasses, (SiO2)(65-x)(CaO)35(Na2O)x with x = 5, 10, and 15, were chosen for their bioactive properties. Analysis of the glass surface structure, compared to the bulk structure, showed that the surface is rich in modifiers and non-bridging oxygen atoms, which were correlated with local adsorption energies. The reactivity of the glasses is found to increase with higher Na2O content, attributed to elevated Na cations and undercoordinated species at the glass surfaces. The current work provides insights into the relationship between the surface structure, chemistry, and properties in these bioactive glasses and offers a step toward their rational design.

Deep learning image analysis for filamentous fungi taxonomic classification: Dealing with small datasets with class imbalance and hierarchical grouping.

Deep learning applications in taxonomic classification for animals and plants from images have become popular, while those for microorganisms are still lagging behind. Our study investigated the potential of deep learning for the taxonomic classification of hundreds of filamentous fungi from colony images, which is typically a task that requires specialized knowledge. We isolated soil fungi, annotated their taxonomy using standard molecular barcode techniques, and took images of the fungal colonies grown in petri dishes (n = 606). We applied a convolutional neural network with multiple training approaches and model architectures to deal with some common issues in ecological datasets: small amounts of data, class imbalance, and hierarchically structured grouping. Model performance was overall low, mainly due to the relatively small dataset, class imbalance, and the high morphological plasticity exhibited by fungal colonies. However, our approach indicates that morphological features like color, patchiness, and colony extension rate could be used for the recognition of fungal colonies at higher taxonomic ranks (i.e. phylum, class, and order). Model explanation implies that image recognition characters appear at different positions within the colony (e.g. outer or inner hyphae) depending on the taxonomic resolution. Our study suggests the potential of deep learning applications for a better understanding of the taxonomy and ecology of filamentous fungi amenable to axenic culturing. Meanwhile, our study also highlights some technical challenges in deep learning image analysis in ecology, highlighting that the domain of applicability of these methods needs to be carefully considered.

Laboratory investigation of the swelling pressure of bentonite with quicklime and hydrated lime using ASTM-4546-96 and constant volume methods.

The swelling soils, also known as expansive soils, increase in volume due to an increase in moisture content. The settlement of expansive soils could be the main reason for considerable damage to roads, highways, structures, irrigation channel covers, and the protective shell of tunnels that use bentonite for wall stability. Therefore, it is important to determine the amount of swelling pressure in expansive soils. This research uses two laboratory swelling test methods with constant volume (CVS) and ASTM-4546-96 standard, the swelling pressure of lime-stabilized bentonite soil has been estimated. Based on the key findings of this study, the swelling pressure values of pure bentonite samples tested using the ASTM-4546-96 method, compared to the constant volume swelling test, show an approximately 170% increase.

Novel neuropharmacological activity of citrus lime (Citrus aurantifolia): A standardized lime peel supplement enhances non-rapid eye movement sleep by activating the GABA type A receptor.

Polyphenols have been well-established to exert sedative-hypnotic effects in psychopharmacology. Lime (Citrus aurantifolia) peel is rich in biologically active polyphenols; however, the effects of lime peel extract on sleep have not yet been demonstrated. A comparison was conducted in mice, between the sleep-promoting effects of a standardized lime peel supplement (SLPS) and a well-known hypnotic drug, zolpidem, and its hypnotic mechanism was investigated using in vivo and in vitro assays. The effects of SLPS on sleep were assessed using a pentobarbital-induced sleep test and sleep architecture analysis based on recording electroencephalograms and electromyograms. Additionally, a GABAA receptor binding assay, electrophysiological measurements, and in vivo animal models were used to elucidate the hypnotic mechanism. SLPS (200 and 400 mg/kg) was found to significantly decrease sleep latency and increase the amount of non-rapid eye movement sleep without altering delta activity. The hypnotic effects of SLPS were attributed to its flavonoid-rich ethyl acetate fraction. SLPS had a binding affinity to the GABA-binding site of the GABAA receptor and directly activated the GABAA receptors. The hypnotic effects and GABAA receptor activity of SLPS were completely blocked by bicuculline, a competitive antagonist of the GABAA receptor, in both in vitro and in vivo assays. To the best of our knowledge, this study is the first to demonstrate the hypnotic effects of SLPS, which acts via the GABA-binding site of the GABAA receptor. Our results suggest that lime peel, a by-product abundantly generated during juice processing, can potentially be used as a novel sedative-hypnotic.

Evaluating the Role of Mortar Composition on the Cyclic Behavior of Unreinforced Masonry Shear Walls.

The mechanical behavior of unreinforced masonry (URM) shear walls under in-plane cyclic loading is crucial for assessing their seismic performance. Although masonry structures have been extensively studied, the specific influence of varying lime content in cement-lime mortars on the cyclic behavior of URM walls has not been adequately explored. This study addresses this gap by experimentally evaluating the effects of three mortar mixes with increasing lime content, 1:0:5, 1:1:6, and 1:2:9 (cement:lime:sand, by volume), on the cyclic performance of brick URM walls. Nine single-leaf wall specimens 900 mm × 900 mm were constructed and subjected to combined vertical compression and horizontal cyclic loading. Key parameters such as drift capacity, stiffness degradation, and energy dissipation were measured. The results indicated that the inclusion of lime leads to a moderate improvement in drift capacity and ductility of the walls, with the 1:1:6 mix showing the highest lateral capacity (0.55 MPa), drift at cracking (0.08%), and drift at peak capacity (0.31%). Stiffness degradation and energy dissipation were found to be comparable across all mortar types. These findings suggest that partial substitution of cement with lime can enhance certain aspects of masonry performance. Further research is recommended to optimize mortar compositions for unreinforced masonry applications.

Influence of Accelerated Carbonation on the Physico-Mechanical Properties of Natural Fiber-Reinforced Lime Mortars.

Lime mortars are considered the most compatible material for monuments and historic buildings, and they are widely used in restoration works. A key factor determining the mechanical and physical properties of lime mortars is carbonation, which provides strength and hardness. This paper indicates the properties gained in lime mortars produced by Ca(OH)2 and CaO reinforced with different bio-fibers (hemp and lavender) when exposed to the natural environment and in accelerated carbonation. At 90 and 180 days of manufacture, the mechanical and physical properties of the produced composites have been tested. The results show that the carbonation reaction works faster in the case of hot lime mortars, increasing their compressive strength by up to 3.5 times. Hemp-reinforced mortars led to an enhancement in strength by up to 30%, highlighting the significance of bio-fibers in facilitating CO2 diffusion. This was also verified by the thermogravimetric analysis and the determination of the carbon content of the samples. Optimal mechanical properties were observed in mixtures containing quicklime and hemp fibers when conditioned with 3% CO2 at the tested ages.

The Elimination of Viroids through In Vitro Thermotherapy and a Meristem Tip Culture from a New Limonime Hybrid (Citrus x limon var. limon (L.) Burm. f. x Citrus latifolia var. latifolia).

Viruses and viroids pose a significant challenge in citriculture, and their control is crucial for plant health. This study evaluated the effectiveness of in vitro thermotherapy combined with a meristem tip culture for eliminating citrus exocortis viroid (CEVd) and hop stunt viroid (HSVd) from a new limonime hybrid (Citrus x limon var. limon x Citrus latifolia var. latifolia). The elimination success was confirmed by RT-PCR assays. The in vitro elimination rate for CEVd during the shoot proliferation stage (43%) was higher than for HSVd (21%). Accordingly, in the subsequent rooting stage, the in vitro elimination rate for CEVd (50%) was higher than for HSVd (33%). Successful CEVd and HSVd eradication at a 100% rate was confirmed in the ex vitro acclimatized plants in the greenhouse. The study also established an efficient micropropagation protocol. The optimal treatment for in vitro shoot induction was 0.5-2 mg L-1 benzyladenine (BA) + 0.5 mg L-1 gibberellic acid (GA3) + 0.25 mg L-1 naphthalene acetic acid (NAA), while for shoot elongation, it was 0.5 mg L-1 BA + 0.5 mg L-1 kinetin (KIN) + 0.5 mg L-1 GA3 + 0.25 mg L-1 NAA. Rooting was best promoted by 1 mg L-1 NAA. This study provides valuable insights for the mass production of viroid-free propagation material in this new lemon x lime hybrid, contributing to the conservation of genetic resources in citrus breeding programs through the combined application of in vitro thermotherapy and an in vitro meristem tip culture, a novel and highlighted achievement reported for the first time in this study.

Enhancing the Interpretability of Malaria and Typhoid Diagnosis with Explainable AI and Large Language Models.

Malaria and Typhoid fever are prevalent diseases in tropical regions, and both are exacerbated by unclear protocols, drug resistance, and environmental factors. Prompt and accurate diagnosis is crucial to improve accessibility and reduce mortality rates. Traditional diagnosis methods cannot effectively capture the complexities of these diseases due to the presence of similar symptoms. Although machine learning (ML) models offer accurate predictions, they operate as "black boxes" with non-interpretable decision-making processes, making it challenging for healthcare providers to comprehend how the conclusions are reached. This study employs explainable AI (XAI) models such as Local Interpretable Model-agnostic Explanations (LIME), and Large Language Models (LLMs) like GPT to clarify diagnostic results for healthcare workers, building trust and transparency in medical diagnostics by describing which symptoms had the greatest impact on the model's decisions and providing clear, understandable explanations. The models were implemented on Google Colab and Visual Studio Code because of their rich libraries and extensions. Results showed that the Random Forest model outperformed the other tested models; in addition, important features were identified with the LIME plots while ChatGPT 3.5 had a comparative advantage over other LLMs. The study integrates RF, LIME, and GPT in building a mobile app to enhance the interpretability and transparency in malaria and typhoid diagnosis system. Despite its promising results, the system's performance is constrained by the quality of the dataset. Additionally, while LIME and GPT improve transparency, they may introduce complexities in real-time deployment due to computational demands and the need for internet service to maintain relevance and accuracy. The findings suggest that AI-driven diagnostic systems can significantly enhance healthcare delivery in environments with limited resources, and future works can explore the applicability of this framework to other medical conditions and datasets.

Enhancing antioxidant properties of lime juice powder through polyelectrolyte microparticles of chitosan-alginate: Formulation, characterization and stability study.

Lime (Citrus aurantifolia) juice was reported to contain ascorbic acid (AA) and flavonoids, which has bioactivity as antioxidants. To develop an antioxidant product, improving its stability is necessary due to the perishable characteristics of compounds in lime. Therefore, the formulation of polyelectrolyte microparticles using chitosan and alginate was conducted to overcome the weaknesses. This study aims to evaluate the effect of various chitosan, alginate, and lime juice powder (LJP) concentrations on the physical characteristics and antioxidant activity of LJP encapsulated in chitosan-alginate microparticles (CALM). Microparticles with various concentrations of chitosan and alginate were prepared by ionic gelation method using CaCl2 as a crosslinker. The microparticles were evaluated for its physical properties and its antioxidant activity using 2-2-diphenyl-1-picrylhydrazyl reagent. A one-way ANOVA test and Tukey's honest significant difference post hoc were used to determine the effect of LJP amount on the antioxidant activity. The highest AA content in CALM was 0.14 mg/100 mg, with a % encapsulation efficiency of 18.38% ± 0.02%. Antioxidant activity tests revealed that LJP possessed the strong antioxidant activity with an IC50 value of 32.59 µg/mL, whereas IC50 values of the microparticles ranged from 24.79 ± 0.03 µg/mL to 39.96 ± 0.07 µg/mL. During storage, the IC50 of LJP decreased from 32.59 ± 0.13 µg/mL to 65.53 ± 0.03 µg/mL, whereas the IC50 of microparticles remained stable. This study concluded that the chitosan-alginate polyelectrolyte microparticle formulation can improve and protect LJP's antioxidant activity.

Discarded substrates from soilless hydroponic horticulture as potential amendments for metal-contaminated soils.

Soil contamination with metals is a major threat for the environment and public health since most metals are toxic to humans and to non-human biota, even at low concentrations. Thus, new sustainable remediation approaches are currently needed to immobilize metals in soils to decrease their mobility and bioavailability. In this work, we explore the application of discarded substrates from hydroponic cultivation, namely coconut shell and a mixture of coconut shell and pine bark, for immobilization of metals (Cd, Cr, Ni, Cu, Pb, Hg, Sb and As) in a naturally contaminated soil from a mining region in Portugal. The immobilization capacity of substrates (added to the soil at 5% mass ratio) was assessed both individually and also combined with other traditional agriculture soil additives (limestone and gypsum, at 2% mass ratio) and nanoparticles of zero-valent iron (nZVI) at 1-3% mass ratio. The overall results obtained after a 30-d incubation showed that the discarded substrates are a viable, economic, and environmental-friendly solution for metal remediation in soils, with the capacity of immobilization ranging from 20 to 91% for the metals and metalloids studied. Furthermore, they showed the capacity to reduce the soil toxicity (EC50 ∼ 6000 mg/L) to non-toxic levels (EC50 > 10000 mg/L) to the bacteria Aliivrio fischeri.

Milk vetch returning combined with lime materials alleviates soil cadmium contamination and improves rice quality in soil-rice system.

Milk vetch (Astragalus sinicus L.) returning and lime materials is employed as an effective strategy for remediating cadmium (Cd)-contaminated paddy fields. However, the combined effects of them on alleviating Cd pollution and the underlying mechanisms remain poorly explored. Therefore, this study investigated the impact of these combined treatments on soil properties, iron oxides, iron plaque, mineral elements, and amino acids through a field experiment. The following treatments were employed: lime (LM), limestone (LS), milk vetch (MV), MV + LM (MVLM), and MV + LS (MVLS), and a control (CK) group with no materials. Results demonstrated that treatments significantly decreased soil available Cd by 19.40-32.55 %, 10.20-39.58 %, and 25.36-40.66 % at tillering, filling, and maturing stages compared to CK, respectively. Moreover, exchangeable Cd was transformed into more stable fractions. Compared with individual treatments, MVLM and MVLS treatments further decreased available Cd and exchangeable Cd. Overall, Cd in brown rice was reduced by 18.97-77.39 % compared with CK. And the Cd in iron plaque decreased by 14.12-31.14 %, 24.65-61.60 %, 2.6-38.28 % across three stages. Furthermore, soil pH, dissolved organic carbon, and cation exchange capacity increased, along with 0.22-62.09 % and 0.57-10.66 % increases in free and amorphous iron oxide contents at all stages, respectively. Compared with lime alone, the integration of MV returning facilitated increased formation of Fed, Feo and enhanced the antagonistic effect among grain Ca with Cd; Additionally, it increased AAs in brown rice, improving rice quality and potentially reducing Cd transport. Mantel tests and Partial least squares path modeling revealed a significant positive correlation between Cd in IP and rice Cd uptake and a significant negative correlation between available Cd, Fed and Feo. These findings provide valuable insights into the mechanisms involved in mitigating soil Cd bioavailability using integrated approaches with MV returning and lime materials.

Effect of Thermoactivated Recycled Cement, Hardened Cement Powder and Hydrated Lime on the Compressive Strength of Mortars.

Thermoactivated recycled cement (RC) is a growing area of research and development in the cement industry. The approach represents a reversible process of cement hydration in which dehydrated compounds with similar characteristics to cement are obtained by means of thermal activation. To avoid CO2 emissions during the production of such RC, this study assesses the possibility of replacing ordinary Portland cement (OPC) with hardened cement powder (HCP) prepared with different proportions of hydrated lime (HL), relying on a second pozzolanic reaction, and compares it with RC mortars. Due to the thermal activation of HCP, the compressive strength increases by 11.5%. The addition of 8% HL produced an important increase in strength from 28 days to 90 days by 12.8%, although without surpassing the strength values of mortar produced only with HCP or with RC. The compressive strength results suggest the existence of a secondary pozzolanic reaction when using HCP from a cement paste source, but such a pozzolanic reaction was fully perceived in XRD patterns when using concrete as parent material, unlike cement paste, possibly due to large crystalline sand peaks that could have hindered the effective identification of smaller crystalline peaks.

Antibacterial Activity of Ethanol Extract from Australian Finger Lime.

Australian finger lime (Citrus australasica L.) has become increasingly popular due to its potent antioxidant capacity and health-promoting benefits. This study aimed to determine the chemical composition, antibacterial characteristics, and mechanism of finger lime extract. The finger lime extracts were obtained from the fruit of the Australian finger lime by the ethanol extraction method. The antibacterial activity of the extract was examined by detecting the minimum inhibitory concentration (MIC) for two Gram-positive and four Gram-negative bacterial strains in vitro, as well as by assessing variations in the number of bacteria for Candidatus Liberibacter asiaticus (CLas) in vivo. GC-MS analysis was used to identify the antibacterial compounds of the extract. The antibacterial mechanisms were investigated by assessing cell permeability and membrane integrity, and the bacterial morphology was examined using scanning electron microscopy. The extract demonstrated significant antibacterial activity against Staphylococcus aureus, Bacillus subtilis, and Gram-negative bacterial species, such as Escherichia coli, Agrobacterium tumefaciens, Xanthomonas campestris, Xanthomonas citri, and CLas. Among the six strains evaluated in vitro, B. subtilis showed the highest susceptibility to the antimicrobial effects of finger lime extract. The minimum inhibitory concentration (MIC) of the extract against the tested microorganisms varied between 500 and 1000 µg/mL. In addition, the extract was proven effective in suppressing CLas in vivo, as indicated by the lower CLas titers in the treated leaves compared to the control. A total of 360 compounds, including carbohydrates (31.159%), organic acid (30.909%), alcohols (13.380%), polyphenols (5.660%), esters (3.796%), and alkaloids (0.612%), were identified in the extract. We predicted that the primary bioactive compounds responsible for the antibacterial effects of the extract were quinic acid and other polyphenols, as well as alkaloids. The morphology of the tested microbes was altered and damaged, leading to lysis of the cell wall, cell content leakage, and cell death. Based on the results, ethanol extracts from finger lime may be a fitting substitute for synthetic bactericides in food and plant protection.

Effects of Lime Powder on the Properties of Portland Cement-Sulphoaluminate Cement Composite System at Low Temperature.

In order to reduce the risk of early freezing damage to cement-based materials in winter construction, lime powder was used to improve the properties of the Portland cement-sulphoaluminate cement (PC-CSA) composite system at low temperatures. In this study, the effects of lime powder dosage on the properties of a PC-CSA blended system with two proportions (PC:CSA = 9:1 and 7:3) at -10 °C were investigated, and the mechanisms of improvement were revealed. The results showed that the compressive strength of the PC-CSA composite system was effectively improved, and the setting time was shortened by the addition of lime powder. Lime powder could effectively act as an early heating source in the PC-CSA composite system, as the maximum temperature of samples exposed to sub-zero temperatures was increased and the time before dropping to 0 °C was prolonged by the addition of lime powder. The extra CH generated by the hydration of lime powder provided an added hydration path for C4A3S¯, which accelerated the formation of AFt at each stage. Frozen water as well as the early frost damage were effectively decreased by lime powder because of the faster consumption of free water at an early stage. The modification of the hydration products also contributed to the denseness of the microstructure.

Antibacterial Activity for Synthesized Coumarin Derivatives and a Coumarin Component of Lime Peel (Citrus aurantifolia).

In this study, we investigated the antibacterial activity of the coumarin component isolated from lime peel and coumarin derivatives synthesized using various techniques against eight types of food-poisoning bacteria. The minimum inhibitory concentration (MIC) for the 3b [5,7-dihydroxy-4-trifluoromethylcoumarin] derivative was measured as 1.5 mM in Bacillus cereus, Micrococcus luteus, Listeria monocytogenes, and Staphylococcus aureus subsp. aureus; that for the 3c [7-hydroxy-4-trifluoromethylcoumarin] derivative was 1.7 mM in Enterococcus facium; and that for the 3n [dicoumarol] derivative was 1.2 mM in L. monocytogenes. These results confirmed that coumarin derivatives with CF3 and OH substituents had enhanced antibacterial activity.

Study on fresh and hardened state properties of eco-friendly foamed concrete incorporating waste soda-lime glass.

Improper waste management is causing global environmental problems. Waste glass may have adverse impacts on the ecosystem. While a substantial amount of soda-lime glass bottle (SGB) undergoes recycling to create new glass items, a significant volume still ends up in landfills. Therefore, the aim of this study was to explore the potential use of SGB in foamed concrete (FC) production as an aggregate replacement. SGB was substituted for sand in different weight fractions, ranging from 5 to 50%. The fresh state, mechanical, thermal, pore structure, and transport properties were examined. The findings showed a significant enhancement in the FC's mechanical properties when SGB replaced 20% of sand. The compressive, flexural, and splitting tensile strengths exhibited a rise of up to 17.7, 39.4, and 43.8%, respectively. The findings also demonstrated that the addition of SGB improved the thermal conductivity, sorptivity, water absorption, and porosity. The scanning electron microscopy analysis indicated that the inclusion of 20% SGB caused a substantial decrease in void diameter and enhanced its uniformity. A comparison was made between the experimental data and predictions of the mechanical properties using various models of international standards, such as IS 456, ACI 318, NZS-3101, EC-02, AS 3600, and CEB-FIB, along with several references in the literature. The findings implied a strong correlation between the strength properties. The outcomes of this research offer valuable insights into both the possible advantages and constraints of using SGB in FC. Furthermore, this extensive laboratory investigation may serve as a guideline for future study and aid in the advancement of greener and more environmentally friendly FC alternatives.

An explainable AI-based blood cell classification using optimized convolutional neural network.

White blood cells (WBCs) are a vital component of the immune system. The efficient and precise classification of WBCs is crucial for medical professionals to diagnose diseases accurately. This study presents an enhanced convolutional neural network (CNN) for detecting blood cells with the help of various image pre-processing techniques. Various image pre-processing techniques, such as padding, thresholding, erosion, dilation, and masking, are utilized to minimize noise and improve feature enhancement. Additionally, performance is further enhanced by experimenting with various architectural structures and hyperparameters to optimize the proposed model. A comparative evaluation is conducted to compare the performance of the proposed model with three transfer learning models, including Inception V3, MobileNetV2, and DenseNet201.The results indicate that the proposed model outperforms existing models, achieving a testing accuracy of 99.12%, precision of 99%, and F1-score of 99%. In addition, We utilized SHAP (Shapley Additive explanations) and LIME (Local Interpretable Model-agnostic Explanations) techniques in our study to improve the interpretability of the proposed model, providing valuable insights into how the model makes decisions. Furthermore, the proposed model has been further explained using the Grad-CAM and Grad-CAM++ techniques, which is a class-discriminative localization approach, to improve trust and transparency. Grad-CAM++ performed slightly better than Grad-CAM in identifying the predicted area's location. Finally, the most efficient model has been integrated into an end-to-end (E2E) system, accessible through both web and Android platforms for medical professionals to classify blood cell.

Interpretable machine learning for dermatological disease detection: Bridging the gap between accuracy and explainability.

Research on disease detection by leveraging machine learning techniques has been under significant focus. The use of machine learning techniques is important to detect critical diseases promptly and provide the appropriate treatment. Disease detection is a vital and sensitive task and while machine learning models may provide a robust solution, they can come across as complex and unintuitive. Therefore, it is important to gauge a better understanding of the predictions and trust the results. This paper takes up the crucial task of skin disease detection and introduces a hybrid machine learning model combining SVM and XGBoost for the detection task. The proposed model outperformed the existing machine learning models - Support Vector Machine (SVM), decision tree, and XGBoost with an accuracy of 99.26%. The increased accuracy is essential for detecting skin disease due to the similarity in the symptoms which make it challenging to differentiate between the different conditions. In order to foster trust and gain insights into the results we turn to the promising field of Explainable Artificial Intelligence (XAI). We explore two such frameworks for local as well as global explanations for these machine learning models namely, SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME).

Circular design, material properties, service life and cradle-to-cradle carbon footprint of lime-based building materials.

The massive extraction of virgin raw materials has substantially intensified the focus on circular economy of building materials. As a Cradle-to-Cradle service life and circular approach for lime-based construction materials (LBCM) is lacking, the present study evaluates the environmental impact and feasibility of creating a fully recycled second-life render (SL) by designing a closed-loop upcycling process for first-life renders (FL). To achieve this, a second-life binder was thermally activated (900, 1000, 1100, 1200 °C), while its microstructure, compressive strength, and thermal conductivity were investigated. SL had up to 33 % open porosity (FL 29 %), its compressive strength ranged from 2.5 to 3.4 MPa (FL 4.4 MPa) and the thermal conductivity from 1.002 to 1.107 W/mK (FL 1.231 W/mK). Resistance of SL and FL against sulfate attack was found to be equivalent, measured based on the recent RILEM TC 271-ASC recommendation. The environmental impact indicators integrating material properties and durability confirm that the second life-render can reduce CO2 emissions up to 55 %. The present research provides insights into unlocking essential sustainability gains through circular practices in the life-cycle of LBCM.