Traditional Techniques Research Articles

State-Difference Feedback Control for Discrete-Time Takagi–Sugeno Fuzzy Descriptor Systems with Parameter Uncertainties and External Noises

This research focuses on the development of state-difference feedback controllers for discrete-time (DT) nonlinear descriptor systems. Discrete-time nonlinear DA systems consist of difference and algebraic equations and play a crucial role in describing dynamic behavior and capturing the constraints or relationships within the system. However, analytical stability may pose additional challenges due to the unique characteristics of the system. Utilizing fuzzy model-based techniques, the DT nonlinear DA system discussed in this study can be effectively represented using the Takagi–Sugeno (T-S) fuzzy model. After linearizing the nonlinear system through the T-S fuzzy model, traditional linear control techniques become applicable. These techniques are then applied to T-S fuzzy systems to establish stability criteria. This article chooses the Lyapunov function as the method used to analyze system stability. Additionally, we use a free-weighting matrix to introduce additional degrees of freedom. In summary, this paper presents simulation results and discussions to verify the effectiveness of the proposed design approach.

Evaluating the impact of reinforcement learning on automatic deep brain stimulation planning.

Traditional techniques for automating the planning of brain electrode placement based on multi-objective optimization involving many parameters are subject to limitations, especially in terms of sensitivity to local optima, and tend to be replaced by machine learning approaches. This paper explores the feasibility of using deep reinforcement learning (DRL) in this context, starting with the single-electrode use-case of deep brain stimulation (DBS). We propose a DRL approach based on deep Q-learning where the states represent the electrode trajectory and associated information, and actions are the possible motions. Deep neural networks allow to navigate the complex state space derived from MRI data. The chosen reward function emphasizes safety and accuracy in reaching the target structure. The results were compared with a reference (segmented electrode) and a conventional technique. The DRL approach excelled in navigating the complex anatomy, consistently providing safer and more precise electrode placements than the reference. Compared to conventional techniques, it showed an improvement in accuracy of 2.3% in average proximity to obstacles and 19.4% in average orientation angle. Expectedly, computation times rose significantly, from 2 to 18min. Our investigation into DRL for DBS electrode trajectory planning has showcased its promising potential. Despite only delivering modest accuracy gains compared to traditional methods in the single-electrode case, its relevance for problems with high-dimensional state and action spaces and its resilience against local optima highlight its promising role for complex scenarios. This preliminary study constitutes a first step toward the more challenging problem of multiple-electrodes planning.

Evaluating the physico-mechanical performance of cement mortar reinforced with metakaolin/graphene oxide dual nano-additives

Researchers interested in producing high-mechanical-performance cement-based structures follow many strategies to achieve this purpose; one of these is the dual addition of materials. The current study was used thermal activation and chemical exfoliation to successfully prepare nano-metakaolin (NMK), whereas Hummers’ traditional technique was followed to prepare graphene oxide (GO). The key aim of this investigation was to promote the mechanical performance of cement mortars by incorporating both NMK and GO in the same matrix, where very few studies have examined the usage of both NMK and GO in the same cement matrix. For this purpose, six groups of plain and blended mortars were cast, with the cement being partially replaced with 10% NMK and GO being added at ratios of 0.01–0.04 wt.% of cement. The pore size distribution of the prepared mortars was studied using the nitrogen adsorption method, while phase composition/decomposition analysis was recognized by TGA and XRD. The microstructure was investigated by SEM. The obtained results revealed a great enhancement of splitting tensile strength by about 71% and about 20% for compressive strength, in addition to the refinement of the pore structure and promotion of the hydration reaction as confirmed by XRD, TGA, and SEM analysis.

An exploration and practice of an optimized online annotation solution based on PDF slicing and SVG

With the continuous development of network technology, online annotation has become an essential tool in fields such as education, training, and document collaboration. However, traditional annotation techniques are plagued by several limitations, including low security, non-erasable annotations after uploading, and difficulties in communication across different systems. To address these issues, this paper proposes an SVG-based online annotation technique that is built upon PDF file slicing. This approach aims to enhance the deficiencies of traditional annotation techniques and improve user interaction. The research begins by introducing the background and significance of online annotation technology, elucidating the application prospects of PDF slicing technology and SVG in annotation. The paper then provides a detailed description of the annotation algorithm and the implementation process. Additionally, it discusses the experimental setup, results, and analysis. The results indicate that the SVG-based online annotation technology can effectively enhance annotation efficiency and real-time interaction while enabling erasure of historical data and facilitating cross-platform communication. Compared to traditional annotation techniques, the SVG-based approach exhibits higher practicality and flexibility, making it suitable for various types of document annotations and collaborative scenarios.

Evaluating a virtual reality dementia training experience using psychophysiological methods: A randomised controlled study.

Virtual reality (VR) is increasingly used for training the dementia care workforce. It is unknown whether VR is superior to traditional training techniques in improving dementia care amongst practicing nurses. This study compared the impact of a VR application on nurses' knowledge and attitudes towards people living with dementia, to video-based, non-immersive training. Twenty-two registered and enrolled nurses were randomised to either interactive VR experience or video footage captured from within the app. Participants completed surveys pre- and post-training to assess their knowledge of dementia, attitudes towards dementia and person-centredness. Engagement with training was assessed objectively using facial electromyography, and subjectively with self-reported scales. Virtual reality evoked objectively significant greater positive and negative emotional responses than video (positive emotion fEMG: VR mean .012 mV vs. video .005 mV, F[1, 20] = 8.70, p = .01; negative emotion fEMG: VR mean .018 mV vs. video .008 mV, F[1, 20] = 18.40, p < .001). Self-ratings of engagement and emotional state were similar. There was little change in the VR group's knowledge of, and attitudes towards, dementia; the video group's dementia knowledge improved (total DKAS mean differences: VR .1 t = .07, df = 9, p = .95 vs. video -2.3 t = -2.265, df = 11, p = .045). Virtual reality is more engaging than traditional training in highly experienced dementia care practitioners. Despite this, VR may not be superior to traditional training techniques to improve knowledge and attitude for many learners. A focus of future research in the area should be on how to capitalise on VR's greater emotional engagement so that Australia's nursing workforce is better equipped to care for the increasing number of people living with dementia.

Exploring T7 RNA polymerase-assisted CRISPR/Cas13a amplification for the detection of BNP via electrochemiluminescence sensing platform

Brain natriuretic peptide (BNP) is considered to be an important biomarker of heart failure (HF) attracting attention. However, its low concentration and short half-life in blood lead to a low-sensitivity detection of BNP, which is a challenge that has to be overcome. In this work, we propose a highly specific, highly sensitive T7 RNA polymerase-assisted clustered regularly interspaced short palindromic repeats (CRISPR)/Cas13a system to detect BNP via an electrochemiluminescence (ECL) sensing platform and incorporate exonuclease III (Exo III)-hairpin and dumbbell-shaped hybridization chain reaction (HCR) technologies. In this detection scheme, the ECL sensing platform possesses low background signal and high sensitivity. Firstly, the T7 promoter-initiated T7 RNA polymerase acts as a signal amplification technique to generate large amounts of RNAs that can activate CRISPR/Cas13a activity. Secondly, CRISPR/Cas13a is able to trans-cleave the surrounding trigger strand to produce DNA1. Thirdly, DNA1 is involved in the co-amplification reaction of Exo III and hairpin DNA, which subsequently triggers a dumbbell-shaped HCR technology. Eventually, a large number of Ru (II) molecules are inserted into the interstitial space of the dumbbell-shaped HCR to generate a strong ECL signal. The CRISPR/Cas13a possesses outstanding specificity for a single base and increased sensitivity. The tightly conformed dumbbell-shaped HCR provides higher sensitivity than the traditional linear HCR amplification technique. Ultimately, the clever combination of several amplification reactions enables the limit of detection (LOD) as low as 3.2 fg/mL. It showed promise for clinical sample testing, with recovery rates ranging from 98.4% to 103% in 5% human serum samples. This detection method offered a valuable tool for early HF detection, emphasizing the synergy of amplification strategies and specificity conferred by CRISPR/Cas13a technology.

A Review of Research on Prediction Methods for Compressive Strength of Concrete

Concrete is one of the most widely used building materials in the world. The compressive strength of concrete is a crucial parameter in construction engineering as it directly affects the safety performance and stability of building structures. Therefore, accurately predicting the compressive strength of concrete has become a widely discussed issue across various fields. Both traditional prediction methods and machine learning techniques, which have gained popularity in recent years, play important roles in this field. Researchers have started applying these methods to predict the compressive strength of concrete. This article will introduce some methods used for predicting the compressive strength of concrete.

A multi-class brain tumor grading system based on histopathological images using a hybrid YOLO and RESNET networks

Gliomas are primary brain tumors caused by glial cells. These cancers’ classification and grading are crucial for prognosis and treatment planning. Deep learning (DL) can potentially improve the digital pathology investigation of brain tumors. In this paper, we developed a technique for visualizing a predictive tumor grading model on histopathology pictures to help guide doctors by emphasizing characteristics and heterogeneity in forecasts. The proposed technique is a hybrid model based on YOLOv5 and ResNet50. The function of YOLOv5 is to localize and classify the tumor in large histopathological whole slide images (WSIs). The suggested technique incorporates ResNet into the feature extraction of the YOLOv5 framework, and the detection results show that our hybrid network is effective for identifying brain tumors from histopathological images. Next, we estimate the glioma grades using the extreme gradient boosting classifier. The high-dimensional characteristics and nonlinear interactions present in histopathology images are well-handled by this classifier. DL techniques have been used in previous computer-aided diagnosis systems for brain tumor diagnosis. However, by combining the YOLOv5 and ResNet50 architectures into a hybrid model specifically designed for accurate tumor localization and predictive grading within histopathological WSIs, our study presents a new approach that advances the field. By utilizing the advantages of both models, this creative integration goes beyond traditional techniques to produce improved tumor localization accuracy and thorough feature extraction. Additionally, our method ensures stable training dynamics and strong model performance by integrating ResNet50 into the YOLOv5 framework, addressing concerns about gradient explosion. The proposed technique is tested using the cancer genome atlas dataset. During the experiments, our model outperforms the other standard ways on the same dataset. Our results indicate that the proposed hybrid model substantially impacts tumor subtype discrimination between low-grade glioma (LGG) II and LGG III. With 97.2% of accuracy, 97.8% of precision, 98.6% of sensitivity, and the Dice similarity coefficient of 97%, the proposed model performs well in classifying four grades. These results outperform current approaches for identifying LGG from high-grade glioma and provide competitive performance in classifying four categories of glioma in the literature.

Unraveling the mechanism of photo-induced surface enhanced Raman scattering on ZnO/Au thin films

Surface-enhanced Raman scattering (SERS) is a powerful technique for detecting pollutants. Recent studies have shown that the sensitivity of SERS can be further improved by using appropriate light excitation before or during Raman measurements, a phenomenon known as photo-induced enhanced Raman scattering (PIERS). In this study, we developed a highly sensitive SERS substrate by fabricating a ZnO/Au thin film using radio frequency magnetron sputtering and post-annealing processes. The resulting substrate exhibited high crystallinity and high sensitivity for pollutant detection. The study found that in situ UV excitation significantly enhanced the Raman signal, up to 5.5 times more efficiently than the traditional SERS technique. The excitation process was reversible, leading to a quick recovery of the Raman intensity to its initial level when the UV excitation was turned off. This relaxation process is attributed to the recombination of electrons and holes. The investigation shows that ZnO/Au thin films was able to detect fungicide thiram with a limit of detection of 10−8 M. PIER also helps to lower the detection threshold down to 10−9 M.

Additional cartilage reinforcement of the annulus in myringoplasty for subtotal perforation

ObjectiveIn this study, graft success, hearing outcome, and complications were compared following the repair of subtotal perforation using a cartilage reinforcement underlay technique (CRUT) versus the traditional cartilage underlay technique (TCUT). Study designRandomized controlled trial. Materials and methodsSeventy-six patients with subtotal perforations were prospectively randomized to the CRUT (n = 38) or TCUT (n = 38) group. The graft success rate, hearing outcome, and complications were compared at 12 months. ResultsThe mean operation time was 32.9 ± 4.2 (range: 26–47) min in the CRUT group and 51.8 ± 6.3 (range: 48–73) min in the TCUT group (P < 0.001). At 12 months postoperatively, no residual perforation was seen in either group. The graft success rate was 94.7 % (36/38) in the CRUT group and 92.1 % (35/38) in the TCUT group; the difference was not significant (P = 0.643). The postoperative air bone gap (ABG) was significantly improved compared to the preoperative value in both groups, without significant between-group differences in either the preoperative (P = 0.741) or postoperative (P = 0.865) ABG or the mean ABG gain (P = 0.812). Additionally, there were no significant between-group differences in the preoperative (P = 0.887) or postoperative (P = 0.753) mean bone-conduction pure tone average. In the TCUT group, seven (18.4 %) patients developed temporary hypogeusia and two (5.3 %) had external auditory canal scarring. Graft cholesteatoma was not observed in either group. ConclusionIn the treatment of subtotal perforations, lateral reinforcement of the annulus with additional cartilage is simpler than traditional cartilage underlay for achieving graft and hearing success. The technique also does not involve raising the tympanomeatal flap or removing perforation margins.

COMPARATIVE STUDY OF TRADITIONAL PWM INVERTERS AND MULTILEVELS INVERTERS

The need of higher powers in electrical drives has forced the researchers to develop new power source possibilities. Multilevel inverters have been presented as a cost effective solution for various high voltage and high power applications including power quality and motor drive problems. The traditional pulse width modulated (PWM) Inverter does not completely eliminate the unwanted harmonics in the output waveform. Using the multilevel inverter as an alternative to traditional PWM inverters for electric motor drive applications is investigated. The concept of the Optimized Harmonic Elimination Stepped-Waveform (OHESW) technique for a multilevel inverter is presented. The effectiveness of this technique in minimizing the inverter switching losses and its output voltage harmonic content which cause reducing harmonic losses and torque pulsations of an induction motor fed form is investigated analytically. Comparison between the Selective Harmonic Eliminated PWM (SHEPWM) as a traditional PWM technique for three-level inverter and the OHESW technique for multilevel inverter with regard to the switching losses, harmonic distortion, additional harmonic losses in the motor and the pulsating torques is also presented.

Doxycycline is a viable alternative to tetracycline for use in insect Tet-Off transgenic sexing systems, as assessed in the blowflies Cochliomyia hominivorax and Lucilia cuprina (Diptera: Calliphoridae).

Transgenic insect strains with tetracycline repressible (Tet-Off) female-lethal genes provide significant advantages over traditional sterile insect techniques for insect population control, such as reduced diet and labor costs and more efficient population suppression. Tet-Off systems are suppressed by tetracycline-class antibiotics, most commonly tetracycline (Tc) or doxycycline (Dox), allowing for equal sex ratio colonies of transgenic insects when reared with Tc or Dox and male-only generations in their absence. Dox is a more stable molecule and has increased uptake than Tc, which could be advantageous in some insect mass-rearing systems. Here, we evaluated the suitability of Dox for rearing Tet-Off female-lethal strains of Australian sheep blowfly, Lucilia cuprina (Wiedemann, 1830) (Diptera: Calliphoridae), and New World screwworm, Cochliomyia hominivorax (Coquerel, 1858) (Diptera: Calliphoridae), and the effects of dosage on strain performance. For both species, colonies were able to be maintained with mixed-sex ratios at much lower dosages of Dox than Tc. Biological yields of C. hominivorax on either antibiotic were not significantly different. Reduction of Dox dosages in C. hominivorax diet did not affect biological performance, though rearing with 10 or 25 μg/mL was more productive than 50 μg/mL. Additionally, C. hominivorax mating performance and longevity were equal on all Dox dosages. Overall, Dox was a suitable antibiotic for mass-rearing Tet-Off female-lethal L. cuprina and C. hominivorax and was functional at much lower dosages than Tc.

Primary Ankle Fusion Using an Antegrade Nail Into the Talus for Early Treatment of OTA Type C3 Distal Tibial Plafond Fractures: A Preliminary Report.

Type C3 distal tibial plafond fractures consistently show poor outcomes with high complication rates and significant risk of posttraumatic arthritis. We describe a minimally invasive technique of performing a primary ankle fusion using an anterograde tibial nail and compare our early results to traditional methods of fixation. During the acute admission, the patient undergoes an arthroscopic preparation of the ankle joint and insertion of an anterograde nail into the talus. This technique is described in detail and presented alongside a retrospective 5-year review of all adult C3 distal tibial plafond fractures from our center. Twenty-six patients (8 open fractures) had been fixed traditionally using open reduction internal fixation (24 patients) and circular frames (2 patients) with an average follow-up of 20 months. Those internally fixed had protected weightbearing for 3 months. Complications included deep infection (12%), nonunion (8%), malunion (4%), severe posttraumatic osteoarthritis (27%), and the secondary conversion to ankle replacement/fusion (12%) requiring an average of 3 reoperations.Six patients underwent primary fusion (3 open fractures) with an average follow-up of 18 months. Patients were allowed to immediately weightbear. There were no reported complications and the primary fusion group demonstrated shorter hospital stays, faster return to work, and higher mean self-reported foot and ankle score (SEFAS) compared to those treated with ORIF. C3 distal tibial plafond fractures are difficult to manage and there has not been a satisfactory method of treating them that allows early return to work, has a low risk of complications, and reduces the risk of posttraumatic tibiotalar arthritis.We present our initial results with a method that uses traditional arthroscopic techniques to prepare the tibiotalar joint together with minimally invasive anterograde tibiotalar nailing. In this initial report of a small group of patients, we found that surgery can be performed once the swelling has subsided after injury and that allowing weightbearing as tolerated did not appear to have a negative effect on initial outcomes. Level III, retrospective comparative study.

A comprehensive evaluation of OPTICS, GMM and K-means clustering methodologies for geochemical anomaly detection connected with sample catchment basins

The process of data-driven clustering to uncover geochemical anomalies linked to sample catchment basins (SCBs) includes a comprehensive framework to discern areas exhibiting unique geochemical attributes within a specified study area. The Ordering Points to Identify the Clustering Structure (OPTICS) method can serve as a robust methodology for detecting geochemical anomalies in SCBs. This is attributed to its capacity to effectively manage varying cluster densities, adaptively identify cluster numbers, exhibit resilience to noise, and display minimum sensitivity to parameters. A comparison was conducted in this research between the outcomes of the OPTICS clustering algorithm and two traditional clustering techniques, namely the Gaussian Mixture Model (GMM) and K-means clustering. In the following, the Expectation-Maximization (EM) technique is employed to train the GMM for clustering. Moreover, the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) as two validate statistical metrics implemented to ascertain the optimal number of components (clusters) belong to the GMM. It should be noted that the effectiveness of the clustering algorithms was further assessed using the Calinski-Harabasz (CH) index and the success-rate curves. OPTICS, a density-based clustering approach, was confirmed to be more effective than K-means and GMM for identifying MVT PbZn anomalies in Varcheh district, western Iran. Furthermore, the specified anomalies show a geo-spatial correspondence with the geological facts, and it has been observed that strong anomalies are more discoverable in close proximity to MVT PbZn occurrences. This work suggests a novel anomaly detection approach based on OPTICS, which exhibits superior performance and data-modeling efficiency. The main emphasis is on effectively distinguishing geochemical anomalies from sample data originating from populations with uncertain distributions.

Early prediction of gallstone disease with a machine learning-based method from bioimpedance and laboratory data.

Gallstone disease (GD) is a common gastrointestinal disease. Although traditional diagnostic techniques, such as ultrasonography, CT, and MRI, detect gallstones, they have some limitations, including high cost and potential inaccuracies in certain populations. This study proposes a machine learning-based prediction model for gallstone disease using bioimpedance and laboratory data. A dataset of 319 samples, comprising161 gallstone patients and 158 healthy controls, was curated. The dataset comprised 38 attributes of the participants, including age, weight, height, blood test results, and bioimpedance data, and it contributed to the literature on gallstones as a new dataset. State-of-the-art machine learning techniques were performed on the dataset to detect gallstones. The experimental results showed that vitamin D, C-reactive protein (CRP) level, total body water, and lean mass are crucial features, and the gradient boosting technique achieved the highest accuracy (85.42%) in predicting gallstones. The proposed technique offers a viable alternative to conventional imaging techniques for early prediction of gallstone disease.

A skin-interfaced, miniaturized platform for triggered induction, capture and colorimetric multicomponent analysis of microliter volumes of sweat

Eccrine sweat can serve as a source of biomarkers for assessing physiological health and nutritional balance, for tracking loss of essential species from the body and for evaluating exposure to hazardous substances. The growing interest in this relatively underexplored class of biofluid arises in part from its non-invasive ability for capture and analysis. The simplest devices, and the only ones that are commercially available, exploit soft microfluidic constructs and colorimetric assays with purely passive modes of operation. The most sophisticated platforms exploit batteries, electronic components and radio hardware for inducing sweat, for electrochemical evaluation of its content and for wireless transmission of this information. The work reported here introduces a technology that combines the advantages of these two different approaches, in the form of a cost-effective, easy-to-use device that supports on-demand evaluation of multiple biomarkers in sweat. This flexible, skin-interfaced, miniaturized system incorporates a hydrogel that contains an approved drug to activate eccrine sweat glands, electrodes and a simple circuit and battery to delivery this drug by iontophoresis through the surface of the skin, microfluidic channels and microreservoirs to capture the induced sweat, and multiple colorimetric assays to evaluate the concentrations of chloride, zinc, and iron. As demonstrated in healthy human participants monitored before and after a meal, such devices yield results that match those of traditional laboratory analysis techniques. Clinical studies that involve cystic fibrosis pediatric patients illustrate the use of this technology as a simple, painless, and reliable alternative to traditional hospital systems for measurements of sweat chloride.

Current On-Skin Flexible Sensors, Materials, Manufacturing Approaches, and Study Trends for Health Monitoring: A Review.

Due to an ever-increasing amount of the population focusing more on their personal health, thanks to rising living standards, there is a pressing need to improve personal healthcare devices. These devices presently require laborious, time-consuming, and convoluted procedures that heavily rely on cumbersome equipment, causing discomfort and pain for the patients during invasive methods such as sample-gathering, blood sampling, and other traditional benchtop techniques. The solution lies in the development of new flexible sensors with temperature, humidity, strain, pressure, and sweat detection and monitoring capabilities, mimicking some of the sensory capabilities of the skin. In this review, a comprehensive presentation of the themes regarding flexible sensors, chosen materials, manufacturing processes, and trends was made. It was concluded that carbon-based composite materials, along with graphene and its derivates, have garnered significant interest due to their electromechanical stability, extraordinary electrical conductivity, high specific surface area, variety, and relatively low cost.

Vulnerability of reinforced concrete frames using anti-seismic hysteretic devices for the Lorca earthquake (2011)

Many buildings around the world are extremely vulnerable to serious and moderate earthquakes. Base isolation and energy dissipators are the traditional techniques in anti-seismic designs. The present paper focuses on the suitability of using hysteretic energy dissipators in braced buildings in low-to-medium seismic zones, such as southeast Spain. To this end, static (Push-over) and dynamic analyses have been carried out using the record of the Lorca earthquake (2011) in its most unfavorable direction (N-S), using reinforced concrete frames of low (5 stories frame), medium (10 stories frame), and high height (15 stories frame) with hysteretic dissipators (based on metal plasticization) and economical and easy-to-use devices. The results show that this type of solution is appropriate in the case described and indicate the advantages and disadvantages of its use in buildings in the study area. The results show that the effectiveness of the dissipative devices increases with the height of the frames, in terms of displacements, resistance, and distribution of moments in the primary structural elements of the frames (beams and columns).

Tritordeum: Promising Cultivars to Improve Health.

Tritordeum is an amphiploides species resulting from the hybridization between durum wheat (T. durum) and wild barley (H. chilense). This new cereal is considered a natural crop as it is obtained by traditional breeding techniques. Given its appreciable organoleptic characteristics, agronomic features, presence of interesting components, and good technological properties, Tritordeum is of promising interest for the development of health-oriented foods. In this study, we evaluated two registered Tritordeum cultivars, Bulel and Aucan. T. durum (Provenzal) was employed as the positive control. The extracted proteins were digested by gastric/pancreatic proteases, and their biological effects on Caco-2 differentiated on transwell inserts were determined. Changes in cell viability, monolayer permeability, organization of F-actin microfilaments, and ER stress triggered by protein-digested samples (DPs) were inspected. Our results showed that exposure to Provenzal-DPs promptly disrupted the tight junction barrier. Conversely, Aucan-DPs did not enhance monolayer permeability, whereas Bulel-DPs exerted only slight effects. Provental-DPs-induced toxicity was also confirmed by changes in cell viability and by the deep reorganization of the enterocyte cytoskeleton. In contrast, Aucan-DPs and Bulel-DPs did not affect monolayer viability and cytoskeleton structure. Overall, our findings suggest that both Tritordeum cultivars could be potential candidates for mitigating the toxicity of wheat flour.

Life Cycle Assessment Comparison between an Earthbag Building and a Conventional Sahrawi Cement Blocks Building.

Growing environmental awareness has prompted a resurgence in traditional building techniques that rely on natural or recycled materials since many believe that structures made from these resources are ecologically friendly. Using Life Cycle Assessment (LCA) for construction materials offers valuable insights into the impacts produced during their production and construction processes. This study aims to assess the environmental impacts of two different constructions-an Earthbag Building (EB) and a conventional Sahrawi Cement Blocks Building (CBB). It also determines whether it is more environmentally beneficial to construct traditionally, utilizing local materials and aligning with the principles of the circular economy, which is one of the Sustainable Development Goals (SDGs) in Europe. This study specifically examines a cradle-to-gate LCA, using the software Simapro v. 9.4.0.1. Results show that in 21 out of the 22 impact categories analyzed, the CBB performs worse, in some cases presenting an impact of 70% higher than the EB. The highest impact is obtained for fine particulate matter formation and Global Warming related to Human Health categories, whilst impact categories related to water consumption and eutrophication obtained an impact of less than 0.001 for both constructions.