In order to fully perform their functions and be durable, mortars for renders and plasters are requested to have a set of characteristics that can vary with the type of exposure to external environmental actions and the type of substrate. Generally, they need moderate strength, high deformability, some water protection capability, good adhesion to the substrate, and compatibility with the pre-existent materials. The presence of water and its movement inside the pore structure of the mortars are among the most significant causes of degradation. Moreover, several authors consider that the main factors for durability and good performance of lime-based mortars are mostly related with the good quality of the binder and the use of adequate aggregates. This paper intends to study the effect of ageing on the properties and durability of air lime mortars, using aggregates of different mineralogy. For this purpose, different mortars compositions are exposed to an accelerated weathering test under defined conditions. The obtained characteristics are discussed and compared with the results obtained with the same mortars tested in laboratory conditions. The effects of the aggregate type on the durability of mortars seem to be linked to their effects on the mortars porous structure.

Several lime mortars for the repair of painted plasters of the rock cut church of Ss. Pietro and Paolo in Matera were studied. They were designed taking into account both aesthetic criteria that need to be fulfilled in the field of paintings restoration, and physical-mechanical compatibility with the original materials on site, i.e. the pre-existing plasters and the supporting rock. Mixes with calcareous and silica aggregates, based on different grain size proportions, were prepared for filling missing portions of the original painted plaster. The effects of the mineralogical nature and size of the aggregates on the characteristics and properties of the mixes were investigated in relation to the microstructure, physical-mechanical features and resistance to salt ageing. At the end of the experimental campaign, the overall performances were evaluated.

The Church of the Company of Jesus in Quito (1605-1765) is one of the most remarkable examples of colonial religious architecture on the World Heritage List. This church has multiple constructive phases and several interventions with no clear record of the entire architectural site, including the historical mortars. A total of 14 samples of coating mortars inside the central nave were taken, with the protocols suggested by the research team and a comparative sample of the architectural group that does not have intervention. The analysis presented in this paper focuses on mineralogical characterization, semi-quantitative analysis by X-ray diffraction and scanning electron microscopy with microanalysis of the samples. The results showed the presence of volcanic aggregate lime and gypsum, used in lining mortars and joint mortars. Mineralogical and textural composition data have allowed the mortar samples to be relatively dated.

The pride of power of the Spanish preachers of religious art is reflected in the church of Santo Domingo built between 1541 and 1688. This work of heritage architecture, one of the first to be built in the colonized city, was affected by multiple earthquakes, interventions, and constructions that do not have a clear record. A total of 13 samples were taken from the lining mortar inside the cloister, central nave, and side chapel, following the nondestructive testing protocols and standards suggested by the research team. The analysis included mineral characterization studies and quantitative analysis by X-ray diffraction and scanning electron microscopy with microanalysis of the samples. The results showed the presence of volcanic aggregates and lime lining and joint mortars, mortars of rustic composition and coarse manufacture. The resolution of the data of mineralogical composition and texture has allowed us to corroborate the historical information described by the chroniclers and to date relatively the studied sites and to establish a hypothesis of constructive stages.

Philippine Lime or Calamansi is considered one of the Philippine high-value crops in Nueva Ecija province. This article presents some issues and problems of the calamansi industry in terms of marketing. The study used a descriptive survey of 56 farm-owners or calamansi growers. Findings revealed that lime production could be a stable income source if the growers can provide the necessary production inputs on a sustainable basis. Calamansi farmers in the province some often confronted with the following problems: the high cost of farm inputs, price fluctuations, price manipulation of big-time traders, and other intermediaries. The study also found out that the existing actors in the chain were limited to growers, laborers, agri-supply shops, nursery owners, intermediaries, and traders. In terms of trading, there is a high degree of competition among traders in the market. The findings and results from this study may have important factors in developing and designing effective agricultural marketing program and startegic development plan by the authorities in the region.

Philippine Lime or Calamansi is considered one of the Philippine high-value crops in Nueva Ecija province. This article presents some issues and problems of the calamansi industry in terms of marketing. The study used a descriptive survey of 56 farm-owners or calamansi growers. Findings revealed that lime production could be a stable income source if the growers can provide the necessary production inputs on a sustainable basis. Calamansi farmers in the province some often confronted with the following problems: the high cost of farm inputs, price fluctuations, price manipulation of big-time traders, and other intermediaries. The study also found out that the existing actors in the chain were limited to growers, laborers, agri-supply shops, nursery owners, intermediaries, and traders. In terms of trading, there is a high degree of competition among traders in the market. The findings and results from this study may have important factors in developing and designing effective agricultural marketing program and strategic development plan by the authorities in the region.

The Black Steel slag (Ss) and phosphogypsum (PG) are industrial wastes produced in Morocco. In order to reduce these two wastes and to evaluate their pozzolanic reactivity in the presence of water, they were incorporated into bentonite (B) mixed with lime (L). The studied mixtures (BLW, BL-PG-W and BL-PG-Ss-W) were analyzed by X-ray diffraction, Infrared spectroscopy, Raman spectroscopy and SEM/EDX analysis. Compressive strength tests were performed on hardened specimens. The results obtained show that the hydration kinetics of the B-L-W and B-L-PG-W mixtures are slow. The addition of PG to a bentonite-lime mixture induces the formation of new microstructures such as hydrated calcium silicate (C-S-H) and ettringite, which increases the compressive strength of the cementitious specimens. The addition of the Ss to a mixture composed by 8%PG and 8%L-B accelerates the kinetics of hydration and activates the pozzolanic reaction. The presence of C2S in the slag helps to increase the mechanical strength of the mixture B-L-PG-Ss. The compressive strength of the mixtures BL-W, BL-PG-W and BL-PG-Ss-W increases from 15 to 28 days of setting. After 28 days of setting, 8% of Sc added to the mixture 8% PG-8%L-B is responsible for an increase of the compressive strength to 0.6 MPa.

The objective of this study is to investigate the performance of incorporating petroleum sludge waste as raw materials into the cement clinker production. The burnability and the structural analysis of the produced clinker were studied. The results showed that the addition of petroleum sludge into the clinker matrices improved the burnability of the clinker by lowering the free lime content. Moreover, 2.5% and 5% of this waste was effective and did not affect the quality of the cement clinker negatively. This study, which is the first to investigate the incorporation of petroleum sludge into cement production, provides also a complete elimination of this waste from the environment.

The use of natural fibres is investigated in recent years in cement, lime or geopolymer mortars to increase their toughness, resistance, tensile strength and durability. These fibres, derived from sources such as jute, hemp, sisal, and flax, are added to the mortar mix to enhance its mechanical properties and reduce cracking. The choice of the natural source strongly depends on local availability of the plant, its use and harvesting. In this paper the fibres of Diss (Ampelodesmos Mauritanicus, Poir) were used as reinforcement for mortars prepared by using waste materials, such as waste glass powder and air hardening lime obtained by the kilning of marble slurry. The samples underwent artificial and natural ageing and were characterized by measuring apparent density, water sorption coefficient, compression and bending stress, indicating a positive role of fibres addiction in increasing mortars durability.

This study examined the economics of Philippine Lime or Calamansi production in selected Cities and Municipalities in Nueva Ecija, Philippines. The study was conducted within the rural farming households' framework, which constitutes the Philippine agricultural sector's backbone, producing about 5.8 percent of the total national agricultural output with the Central Luzon area, including the portion of the locale of the study. Using quota sampling, data collected from 50 selected calamansi grower- farmers from top 5 producing area in Nueva Ecija, the study measured the profitability of and the production efficiency of calamansi production in the area. Using a formal interview schedule, primary data was obtained from the sampled farming households. The study revealed that the typical calamansi farmer in the area as reflected in the instrument, thirty-two (32) or 64% which covers the majority of the respondents claimed that they fully owned the land they cultivated. Calamansi yield depends on its age as well. Fertilizer was found to harm output. Majority of them shared the same production and post–production practices, though a slight difference in terms of labor cost was observed. There were some who were already in the industry for quite a long time and learned other farming techniques and practices different from the conventional and were proven effective. For better efficiency, the land area cultivated, the farmers' educational status, accessibility to credit facility, and development of the rural areas and farmers' contact with the extension agents are some of the key issues to address. The local government in cities and municipalities may engage in an intensive campaign in encouraging capitalists to form cooperatives, processing and manufacturing houses to produce calamansi juice and other valuable products out of the calamansi fruit.

Acid lime [Citrus aurantifolia (Christm.) Swingle] is a fruit crop, enriched with high commercial value and is cultivated in 60 out of 75 districts representing all geographical landscapes of Nepal. Lack of high yielding cultivars is probably one of the main reason for its extremely reduced productivity which warrants a deep understanding of genetic diversity in existing germplasm. Hereby, we aim to access the genetic diversity of acid lime germplasm cultivated at 3-different ecological gradients of eastern Nepal employing PCR-based Inter-Simple Sequence Repeats markers (ISSR). Altogether, 21 polymorphic ISSR markers were used to assess the genetic diversity in 60 acid lime cultivars sampled from different geographical locations. Analysis of binary data matrix was performed on the basis of bands obtained, scoring of the data was done accordingly, and principal coordinate analysis and phenogram were constructed using different computer algorithms. ISSR profiling yielded 234 amplicons, of which 87.18% were found to be polymorphic. The number of amplified fragments ranged from 7-18 with amplicon size ranging from 250-3200 bp. The NTSYS based Cluster analysis using UPGMA algorithm taking Dice Similarity coefficient separated 60 accessions into 2-major and 3-minor clusters. The genetic diversity analysis revealed the highest for Terai and the lowest for High-hill zone. Cluster I comprised of accessions from High-hill and Mid-hill regions revealing the close genetic relationship, whereas cluster II comprised of accessions from all three agro-ecological zones and the exotic varieties. Furthermore, our results revealed the accessions harvested from different geographical gradients were not genetically distinct, but highest diversity was observed in Terai accessions in comparison to the regions belonging to the High and Mid-hills. Thus, our data indicate that the ISSR provides a better option for evaluating the genetic diversity of Nepalese Acid Lime cultivars and furnished significant information, assisting parental selection in current and future breeding programs and germplasm conservation which ultimately may help to provide a technological breakthrough for the farmers of the developing country like Nepal.

The reaction kinetics of burnt lime (CaO) in contact with sea water has been elucidated and compared to its behaviour in fresh water. In the first minutes of contact between burnt lime and water, it "slaked" as CaO reacted with water to yield calcium hydroxide (Ca(OH)2). Subsequently, calcium hydroxide reacted with magnesium, sulphate and carbonate from the sea water to yield magnesium hydroxide (Mg(OH)2), calcium sulphate dihydrate (gypsum, CaSO4·2H2O) and calcium carbonate (CaCO3), respectively. In a closed system of 1% CaO in natural sea water (where the supply of sulphate, magnesium and carbonate is limited), more than 90% reacted within the first 5 hours. It is foreseen that in an open system, like a marine fjord, it will react even faster. The pH 8 of sea water close to the CaO particle surface will immediately increase to a theoretical value of about 12.5 but will, in an open system with large excess of sea water, rapidly fall back to pH 10.5 being equilibrium pH of magnesium hydroxide. This is further reduced to < 9 due to the common ion effect of dissolved magnesium in sea water and then be diluted to the sea water background pH, about 8. Field test dosing CaO particles to sea water showed that the pH of water between the particles stayed around 8.

In this work, studies were carried out on the extraction of silver and gold from cakes of pressure oxidation leaching of sulfide concentrate containing pyrite and arsenopyrite. The addition of gypsum at a consumption of 0.1 g/g of concentrate helps to increase silver extraction from 13.4 to 95–98% at the cyanidation stage, with no conditioning operation. Gold recovery was 99%. An increase in gypsum consumption contributes to the formation of BFAS with an increased content of sulfate sulfur, and a decrease in the As/S(sulfate) molar ratio in the cake from 3.7 down to 0.88 contributes to an increase in silver extraction at the cyanidation stage up to 98%, and its further decrease from 0.88 down to 0.58 leads to a gradual reducing silver transfer into solution from 98 down to 75.1% at the cyanidation stage. Basic ferric sulfate (BFS) is not formed in this case, since according to EDS mapping the distribution of arsenic and sulfur over iron-containing particles is uniform. According to TCLP analysis, the cake obtained after pressure oxidation leaching with the addition of gypsum and cyanidation is stable and suitable for disposal, since the final concentration of arsenic in the solution was 0.45 mg/dm3.

This study evaluates the feasibility of stabilizing clay bricks with marble cutting waste (MCW). This waste currently discarded in huge quantities as a sludge resulted from sawing the marble blocks to slabs, grinding and polishing of marble processes to the landfills located around the marble processing factories located in the Shaq El-Thoban industrial zone, Cairo governorate, Egypt causing negative impacts on the environment, health and sustainable development. Experimental investigations were carried out to explore the effect of addition of the MCW in different clay-base mixes at different percentages up to 25% at the expense of the hydrated lime. Cement, hydrated lime and MCW are the three types of solidification agents used, clay and sand were also added in the formulations of the unfired clay brick specimens. Laboratory cylindrical stabilized and compressed specimens were made, and then they were cured in a humidity chamber for 2 and 4 weeks, then after were air dried, tested and evaluated according to the Egyptian code for the building by the stabilized and compressed earth soil (ECBS, 2016). To enhance the durability of the cured specimens, transparent silicon – based paint was used for this purpose. The laboratory results demonstrate high potential usage of MCW based additives up to 15% incorporating HL. In addition, the used paint could be an effective treatment way for the use of stabilized bricks in a wet environment. The use of eco-friendly building materials will be a great contribution for the environmental advantages and suggest a remarkable economical alternative to the fired building units.

Traditional lime-based materials have considerable potential for use as components of green materials for plastering and finishing building surfaces in both new construction and historic heritage conservation. The paper presents the preliminary results of a research activity aimed at developing pre-packaged products based on Traditional Lime Putty (TLP) by partially replacing natural aggregates with Stone Waste Sludge (SWS), with a low rate of recovery from Apricena limestone production district in Apulia. The mineralogical and chemical analysis carried out by means XRD (X-Ray Diffraction), TG-DTA (Thermo Gravimetry-Differential Thermal Analysis) and hydrochloric acid attack test showed that the SWS consisted of 98.4 % CaCO3 by mass. The particle sizes measured by laser diffraction technique are below 22.5 μm for the 92% by mass of the sample. The high fineness of the stone waste was confirmed by the Blaine specific surface method equal to 9273.79 cm2/gr. The behavior of three fresh mixtures for prepacked coarse plaster, fine plaster, and finishing plaster with 12.90%, 17.94%, and 18.90 by mass of SWS, respectively, was evaluated by spreading test and applicability tests on a perforated ceramic slab. The finishing plaster has the highest consistency value of 235 mm, while the fine plaster and the coarse plaster have values of 205 mm and 155 mm, respectively. The coarse plaster is suitable for the use as base plaster (arriccio) or second layer rendering (tonachino) up to a thickness of approximately 1 cm. Both the fine plaster and finishing plasters can be used for the surfaces finishing with the application of layers of a few millimeters thick.

This paper is part of a study of earthen mixtures for 3D printing of buildings. To meet the ever-growing environmental needs, the focus of the paper is on a particular type of biocomposite for the stabilization of earthen mixtures—the rice husk-lime biocomposite—and on how to enhance its effect on the long-term mechanical properties of the hardened product. Having assumed that the shredding of the vegetable fiber is precisely one of the possible ways to improve the mechanical properties, we compared the results of uniaxial compression tests performed on cubic specimens made with both shredded and unaltered vegetable fiber, for three curing periods. The results showed that the hardened earthen mixture is not a brittle material in the strict sense, because it exhibits some peculiar behaviors, anomalous for a brittle material. However, being a “designable” material, its properties can be varied with a certain flexibility to get as close as possible to the desired ones. One of the peculiar properties of the hardened earthen mixture deserves further investigation, rather than corrections. This is the vulcanization that occurs (in a completely natural way) in the long term, thanks to the mineralization of the vegetable fiber by carbonation of the lime.

The article presents the results of research work devoted to improving the characteristics of paint and varnish coatings based on aqueous dispersions of polyacrylates, it is proposed to modify them by introducing mineral raw materials as fillers and hydrated lime with subsequent processing in a vortex layer apparatus. Introduction of activated diatomite does not cause deterioration of covering power, adhesion and increase of porosity of the paint material. Modification of coatings contributes to the increase of their operational properties, which can be associated with the reduction of free volume in the composite, formation of polymer boundary layers with modified physical and chemical properties. The aim of the study is to obtain water-dispersion paint and varnish composition containing modified diatomite on polyacrylate basis and subsequent study of the main physical and mechanical parameters. The work has been carried out by the following method: determination of porosity, adhesion, elasticity, covering power of the control composition; determination of porosity, adhesion, elasticity, and covering power of the obtained composites using modified filler; investigation of the influence of radiation in the infrared spectrum of the paint coating surface using FLIRB620 thermal imager. As a result of research works it was noticed that modification of water dispersions with silica activated diatomite helps to eliminate the main disadvantages of materials and coatings based on acrylate binder - low water resistance and low physical and mechanical characteristics, introduction of modified diatomite into water emulsion paint on acrylate base does not lead to deterioration of the main performance characteristics of paint coatings - porosity, adhesion, elasticity and covering.

The primary distribution systems are comprised of power lines delivering power to utility feeders from substations. The inspection and maintenance of damaged and broken power system insulators are of paramount importance for continuous power supply and public safety. hence, to identify any faults and defects in advance a periodic inspection of power line insulators and other components be ensured beforehand. To automate the process and reduce operational cost and risk Unmanned Aerial Vehicles (UAVs) are being extensively utilized. As they present a safer and efficient way to examine the power system insulators and their components without closing the power distribution system ensuring continuous supply to the end-users. To achieve these objectives in this work a novel dataset is designed by capturing real images using UAVs and manually generated images collected to overcome the data insufficiency problem. Deep Laplacian pyramids based super-resolution network is implemented to reconstruct high-resolution training images. To improve the visibility of low light images a low light image enhancement technique is used for the robust exposure correction of the training images. Using computer vision-based object detection techniques to identify faults and classify them according to classes they belong. A different fine-tuning strategy is implemented for fine-tuning the object detection model to increase detection accuracy for the specific faulty insulators. To improve the faults detection several flight path strategies are proposed for efficient inspection. Such strategies overcome the shuttering effect of insulators along with providing a less complex, time, and energy-efficient approach for capturing video stream of the power system components. Performance of different object detection models is presented for selecting the suitable one for fine-tuning on the specific faulty insulator dataset. Our proposed approach gives a less complex and more efficient flight strategy along with better results. For defect detection, our proposed method achieved an F1-score of 0.81 and 0.77 on two different datasets. Our approach is based on real aerial inspection of in-service porcelain insulators by extensive evaluation of several video sequences showing robust faults recognition and diagnostic capabilities. Our approach is demonstrated on data acquired by a drone in Swat Pakistan.

Malaria and Typhoid fever are prevalent diseases in tropical regions, 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 confusable 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 ChatGPT, Gemini, and Perplexity, to clarify diagnostic results for healthcare workers, building trust and transparency in medical diagnostics. 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 Extreme Gradient Boost and Support Vector Machines and important features for predicting Malaria and Typhoid were identified with the LIME plots. Among LLMs, ChatGPT 3.5 demonstrates a comparative advantage over Gemini and Perplexity, hence highlighting how crucial it is to use a hybrid strategy that combines ML, XAI, and LLMs to improve diagnostic performance and reliability in healthcare applications. The study recommends implementing the integrated ML, LIME, and LLM processes because it streamlines the development and maintenance process's workflow overall, makes use of resources more effectively, and improves explainability by allowing the LLM to consider the complete context that LIME provides.

Deep learning architectures like ResNet and Inception have produced accurate predictions for classifying benign and malignant tumors in the healthcare domain. This enables healthcare institutions to make data-driven decisions and potentially enable early detection of malignancy by employing computer-vision-based deep learning algorithms. These Convolutional Neural Network algorithms, in addition to requiring huge amounts of data, can identify higher and lower-level features that are significant while classifying tumors into benign or malignant. However, these algorithms have limitations concerning explainability and identifying the exact features that are of importance and contributing to the final classification of tumors as benign or malignant. In this paper, we implement several explainable AI techniques, namely, LIME, Saliency Map, Occlusion Analysis, Grad-CAM, SHAP, and Smooth Grad to interpret the results of a custom ResNet60 classifier in the classification of ovarian tumors as benign or malignant. The ResNet60 model attained an accuracy of 97.50% for the test dataset.

INTRODUCTION: This study focusses on diagnosis of stages of AD (Alzheimer’s disease) including MCI (Mild Cognitive Impairment) from two data modalities - gene expression and clinical data of ADNI (Alzheimer’s Disease Neuroimaging Initiative ) participants using multiclassification. The gene expression dataset is highly imbalanced and of HDLSS (high-dimensional and low-sample-size) characteristics. This is the only study where multiclassification based AD stage diagnosis is done to identify multiple stages of Alzheimer. We are able to achieve the best multiclassification result in both the modalities and identify new genetic biomarkers. METHODS: Combination of XGBoost and SFBS (“Sequential Floating Backward Selection”) methods is used to select features. We are able to select the most effective 95 gene probsets out of 49,386. For clinical study data, 8 most effective biomarkers could be selected using SFBS. For both genomic and clinical data, DL (‘Deep Learning’) classifier is used to identify stages - CN (Cognitive Normal), MCI (Mild Cognitive Impairment), AD (Alzheimer’s Disease / Dementia). Because of high data imbalance in genomic data, border line oversampling is used for model training and original data for validation. RESULT & DISCUSSION: With clinical data, we achieved ‘ROC AUC’ scores 0.97, 0.95, 0.94 for CN, MCI, Dementia stage respectively . We achieve ‘ROC AUC’ scores 0.75, 0.74, 0.70 for CN, MCI, Dementia stage respectively and 0.67 for both micro average F1 scores and micro weighted F1 score. This is the best result so far for AD stage diagnosis from gene expression profile data through multiclassification with ADNI data. Results reflect that our multiclassification model can efficiently handle the imbalanced data of HDLSS nature to identify samples of minority class. MAPK14, ZNF835, MID1, HLA-DQA1, TEP1 are some of the new genes found to be associated with AD risk. DRAXIN, HSPA12B, USP47 etc. are found to be AD preventive or suppressor.

A scientific carbon accounting system can help enterprises reduce carbon emissions. This study took the enterprise in the Yangtze River basin as a case study. The accounting classification of carbon emissions in the life cycle of lime production was assessed, and the composition of the sources of carbon emission was analyzed, covering mining explosives, fuel (diesel, coal), electricity and high temperature limestone decomposition. Using the IPCC emission factor method, a carbon life cycle emission accounting model for lime production was established. We determined that a total of 354,200 tons of carbon emissions were generated from producing 321,000 tons of lime in a year. The decomposition of limestone at a high temperature was the largest carbon emission source, accounting for 62.34% of the total carbon emission. Coal combustion was also an important source of carbon emissions, accounting for 32.66% of total carbon emissions. The carbon emission for one ton of activated lime was 1.46kg, 1.49kg, 1100kg and 1102.95kg respectively for the open-pit, mining stage, crushing stage, and the calcination stage. Based upon the main sources of carbon emission for lime production, carbon emission reduction should focus on CO2 capture technology, fuel optimization and energy control. Using our analysis of carbon emissions, the carbon emission factor of producing unit quicklime of the lime enterprise in the Yangtze River basin was determined. Furthermore, the research into carbon emission reduction for lime production can provide a point of reference for the promotion of carbon neutrality in the same industry.

The process of anaerobic digestion used for methane production can be enhanced by incorporating stimulating materials. The effects of these materials are dependent on various factors including the processed substrate, process conditions, and the type and amount of the stimulating material used. As part of the study, three different stimulating materials - iron powder, lime, and milled porous ceramic - were added to the 30-day anaerobic digestion of the brewer's spent grain to improve its performance. Different doses ranging from 0.2 to 2.3 gTS×L-1 were tested, and methane production kinetics were determined using the first-order model. The results showed that the methane yield ranged from 281.4±8.0 to 326.1±9.3 ml×gVS-1, while substrate biodegradation ranged from 56.0±1.6 to 68.1±0.7%. The addition of lime reduced methane yield at almost all doses by -6.7% to -3.3%, while the addition of iron powder increased methane yield from 0.8% to 9.8%. The addition of ceramic powder resulted in a methane yield change ranging from -2.6% to 4.6%. These findings suggest that the use of stimulating materials should be approached with caution, as even slight changes in the amount used can impact methane production.

The present work aims to characterize the mechanical behavior of a new composite material for the conservation and development of the vast historical and architectural heritage that is particularly vulnerable to environmental and seismic actions. The new composite consists of natural hydraulic lime (NHL) -based mortar, reinforced by sisal short fibers randomly oriented in the mortar matrix. The NHL-based mortar ensures the chemical-physical compatibility with the original feature of the historical masonry structures (mostly in stone and clay) aiming to pursue both the effectiveness and durability of the intervention. The use of vegetable fibers (i.e. the sisal one) is an exciting challenge for the construction industry since they require a lower degree of industrialization for their processing, and therefore, their costs are also low, as compared to the most common synthetic/metal fibers. Beams of sisal-composite sizing 160x40x40 mm3 with a central notch are tested in three-point bending, aiming to evaluate both their bending strength and fracture energy. Also, tensile tests and compressive tests were performed on the composite samples, while water retention test and slump test were performed on the fresh mix. Finally, the tensile tests on the Sisal strand were carried out to evaluate the tensile strength of both strand and wire. A final comparison with unreinforced mortar specimens shows that the proposed composite ensures great workability and good performances in term of ductility and strength and it can be considered a promising alternative to the classic fiber-reinforcing systems.

This paper presents a comparative analysis of several decision models for detecting Structured Query Language (SQL) injection attacks, which remain one of the most prevalent and serious security threats to web applications. SQL injection enables attackers to exploit databases, gaining unauthorized access, and manipulating data. Traditional detection methods often struggle due to the constantly evolving nature of these attacks, the increasing complexity of modern web applications, and the lack of transparency in the decision-making processes of machine learning models. To address these challenges, we evaluated the performance of various models, including Decision Tree, Random Forest, XGBoost, AdaBoost, Gradient Boosting Decision Tree (GBDT), and Histogram Gradient Boosting Decision Tree (HGBDT), using a comprehensive SQL injection dataset. The primary motivation behind our approach is to leverage the strengths of ensemble learning and boosting techniques to enhance detection accuracy and robustness against SQL injection attacks. By systematically comparing these models, we aim to identify the most effective algorithms for SQL injection detection systems. Our experiments show that Decision Tree, Random Forest, and AdaBoost achieved the highest performance, with an accuracy of 99.50% and an F1 score of 99.33%. Additionally, we applied SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) for local explainability, illustrating how each model classifies normal and attack cases. This transparency enhances the trustworthiness of our approach in detecting SQL injection attacks. These findings highlight the potential of ensemble methods to provide reliable and efficient solutions for detecting SQL injection attacks, thereby improving the security of web applications.

Explainable AI (XAI) has emerged as a pivotal tool in healthcare diagnostics, offering much-needed transparency and interpretability in complex AI models. XAI techniques, such as SHAP, Grad-CAM, and LIME, enable clinicians to understand AI-driven decisions, fostering greater trust and collaboration between human and machine in clinical settings. This review explores the key benefits of XAI in enhancing diagnostic accuracy, personalizing patient care, and ensuring compliance with regulatory standards. However, despite its advantages, XAI faces significant challenges, including balancing model accuracy with interpretability, scaling for real-time clinical use, and mitigating biases inherent in medical data. Ethical concerns, particularly surrounding fairness and accountability, are also discussed in relation to AI's growing role in healthcare. The review emphasizes the importance of developing hybrid models that combine high accuracy with improved interpretability and suggests that future research should focus on explainable-by-design systems, reducing computational costs, and addressing ethical issues. As AI continues to integrate into healthcare, XAI will play an essential role in ensuring that AI systems are transparent, accountable, and aligned with the ethical standards required in clinical practice.