University of Carthage

Nanoparticles (NPs) have actively contributed to nanotechnologies advancement over the last years, due to the unique properties they possess compared to their pristine counterparts. Consequently, NPs found wide applications in various fields such as the medical, biomedical, chemical, agro-food industries, and cosmetology. NP's extensive uses could lead to their release into the environment, especially in the marine ecosystems, considered as NPs sink, resulting in harmful effects on organisms. Concerns regarding NPs' toxicity in aquatic organisms have emerged, however, several points remain unexplored. In the present study, the toxicity of chromium oxide (Cr2O3 = 42 nm) and aluminum oxide (Al2O3 = 38 nm) NPs (1 mg/L, 2.5 mg/L, and 5 mg/L) in the gills of the marine gastropod Stramonita haemastoma was assessed through time (7, 14, and 28 days) by a multi-biomarker, Integrated biomarkers response (IBR), and Histological analysis. Both NPs induced varied changes in the antioxidant system, suggesting the onset of oxidative stress marked by superoxide dismutase (SOD), catalase (CAT), acetylcholinesterase (AChE), metallothionein (MT), and malondialdehyde (MDA) levels imbalance. Varied histological alterations in the gills of S. haemastoma were also observed including inflammation, hypertrophy, and lamellar fusion, IBR proved to be a promising tool for assessing NPs toxicity in gastropods. In this study results indicated the co-response of reduced glutathione (GSH), glutathione S-transferase (GST), glutathione peroxidase (GPx), CAT, SOD, and MT after 28 days of exposure. S. haemastoma showed sensitivity to all exposure concentrations of NPs thus validating this species as a suitable indicator of NPs contamination and toxicity.

This study evaluates the potential of Lathyrus sativus as a sustainable feed ingredient for laying hens, particularly within Mediterranean arid environments where feed resources are scarce and sustainable agricultural practices are crucial. Two genotypes of Lathyrus sativus, distinguished by white and purple flowers, were chemically characterized and incorporated at 10% into the diet of laying hens. Eighteen hens (average age = 6 months; average weight = 1.4 ± 0.2 kg) fed these Lathyrus-enriched diets showed increased final body weight, with the white-flowered group reaching 1562.22 g, and no mortality was recorded. The average daily weight gain in the white-flowered group was 3.15 g.day⁻ 1 , slightly higher than the control, although the difference was not statistically significant (P > 0.05). The chemical analyses revealed no significant differences in protein, fat, or fiber content between the two Lathyrus genotypes. Furthermore, the Lathyrus-based diets contributed positively to egg quality, enhancing eggshell strength, and increasing crude protein content in the vitellus compared to the control. These findings confirm that Lathyrus sativus can be safely integrated into hen diets at 10%, enhancing egg quality without compromising growth performance. This reinforces the value of Lathyrus sativus as a locally available, resource-efficient, offering potential as a climate-resilient feed ingredient for arid Mediterranean environments. Its integration into poultry feed systems aligns with the goals of promoting sustainability, environmental resilience, and resource optimization in Mediterranean arid regions, offering a viable solution to feed scarcity and contributing to food security.

Human hair is a significant biological sample in forensic science, biomedical research, and the cosmetic industry, with the presence of essential nutrients like zinc, copper, and silicon being indicative of health. This study aimed to investigate the elemental composition of human hair using Laser‐Induced Breakdown Spectroscopy (LIBS) to assess differences across age groups. Nine volunteers provided hair samples, which were analyzed using the Foster + Freeman ECCO2 LIBS system. Quantitative analysis of elemental concentrations was performed, and elemental ratios, such as Mg/Ca, Mg/Si, Mg/Fe, and Fe/Mn, were calculated to compare the samples. Results demonstrated that LIBS is a fast, accurate, and non‐destructive method for detecting and quantifying mineral elements in human hair. The study highlights age‐related differences in elemental concentrations, offering insights into the use of hair analysis for monitoring nutritional and health status. LIBS could be a promising tool for further studies in clinical and forensic applications.

Background and Aims Assessing intra-specific trait covariation across populations is essential to understand species’ adaptive responses to climatic variation. However, in tree species, this is understudied for early-life stages despite they are more vulnerable to environmental changes and that climatic adaptations can differ between tree ages. In this paper, we studied the integrated phenotype of Quercus suber during the months following germination. For that, we assessed the covariation of key traits involved in seedlings’ water and C economies along a gradient of aridity at seed origin. Methods We performed a provenance trial with 157 Q. suber seedlings originating from 7 different populations across the species distribution. The seedlings were germinated and grown during 4 months under common conditions. Acorn mass along with 11 above- and below-ground traits involved in water and C use were measured. They were organized in latent variables and their covariation with increasing aridity and temperatures was analyzed using structural equation modelling (SEM). Individual traits were also analyzed with linear mixed-effects models to account for maternal effects. Key Results Seedlings from arid populations displayed higher leaf evaporative surface coupled with greater root development. They also depicted greater stomatal size and chlorophyll content, strongly linked to traits conferring drought and heat tolerance (low SLA and high flavonoids). The development of above- and below-ground tissues responded mainly to acorn mass, whereas leaf physiology variations were associated to populations’ climate. Conclusions Surprisingly, dry-origin seedlings display a more acquisitive strategy at the whole-plant level compared with seedlings from mesic provenances. This allows a greater water and carbon uptake capacities following germination, which is critical for their survival during their first summer. Leaf physiology adjustments to populations’ climate contrasts with observations by other studies addressing juvenile trees, highlighting Q. suber varying adaptive strategies at different ontogenic stages.

The present study reports a rapid and simple one-pot modified sol–gel process to prepare a hybrid Cu-doped Au@ZnO nanocomposite. Dimethyl sulfoxide (DMSO) was used as a solvent which plays a crucial role in elaborating this hybrid nanocomposite without any surfactant or ligand. Characterization techniques, including XRD, TEM, and UV–Visible highlighted the critical role of Cu in enhancing the photocatalytic activity of the sample. On the other hand, experimental studies on the structural, microstructural, and optical properties of the obtained nanomaterial have been reported. The resultant hybrid Cu-doped Au/ZnO heterostructures exhibit excellent photocatalytic activity in the photodegradation of diuron under UV light irradiation, which is much higher than Au/ZnO heterostructures. The performance of the prepared photocatalyst can be also attributed to the simple experimental protocol which generated highly pure nanoparticles with controllable size and shape. We expected that this method could be developed to prepare more semiconductor nanomaterials for different applications. Graphical Abstract

This paper proposes a method that combines a data completion algorithm with the Reciprocity Gap-Linear Sampling Method (RG-LSM) to detect cracks in a non-homogeneous multi-layer domain with a modified impedance boundary condition. The data completion algorithm recovers missing information using Cauchy data from the exterior boundary, extending the RG-LSM’s application in such domains. We validate the robustness of the method through a theoretical analysis and 3D numerical tests, showing its effectiveness on various crack shapes and different noise levels.

Biofilms are structured microbial communities embedded in a self-produced extracellular matrix. This lifestyle provides significant protection against environmental stressors such as desiccation, chemical treatments and even ionizing radiation. Radiation, while a well-established antibacterial strategy, can be less effective in biofilms. Biofilm superior resilience is due to several advantages such as the shielding provided by the matrix, the metabolic heterogeneity and adaptive stress responses of biofilm-associated cells. To address this challenge, researchers are increasingly employing combination strategies in antibiofilm treatment. Radiosensitizers, compounds originally developed to enhance the efficacy of radiation therapy in cancer treatment, have also garnered attention for their potential in antimicrobial applications. These compounds act by amplifying the effects of radiation, often through mechanisms such as increased oxidative stress or inhibition of DNA repair pathways. However, research on radiosensitizers in bacterial systems has focused on planktonic cultures, with limited studies exploring their effects on biofilms. Given the complexity and unique characteristics of biofilms, their response to radiosensitization remains poorly understood and requires further investigation. The use of radiosensitizers in conjunction with radiation presents a promising approach to overcome the inherent resilience of biofilms. By enhancing the susceptibility of biofilm-associated bacteria to radiation and simultaneously disrupting their protective structures, such approaches could lead to more effective and comprehensive solutions. Understanding the nuanced responses of biofilms to these combined treatments is essential for advancing both medical and environmental applications and addressing the challenge of biofilm persistence. Graphical Abstract

Unsupervised anomaly detection using generative adversarial networks (GANs) has gained significant traction in medical applications. However, existing GAN-based methods are often limited to detecting a single pathology per model, restricting their utility in diverse clinical environments. This paper introduces an innovative unsupervised multimodal approach to the detection of medical anomalies and image generation through a unified conditional framework. Our proposed model, the residual attention conditional GAN (RA-cGAN), consists of two conditional networks: a GAN and an encoder-tailored to specific conditions such as dataset type or region of interest (ROI). The GAN generates realistic images conditioned on these inputs, enabling multimodal image generation alongside anomaly detection, while the encoder maps normal images to their latent representations, facilitating efficient anomaly detection across multiple modalities. Uniquely, RA-cGAN is trained exclusively on normal data in a fully unsupervised manner, enabling generalized anomaly detection and multimodal image generation across diverse clinical contexts without requiring separate models. This unified framework not only simplifies training but also leverages multimodal information to improve generalization. Furthermore, our model leverages depthwise separable convolution (DSC) to improve computational efficiency and integrates the convolutional block attention module (CBAM) to emphasize relevant image regions, all while maintaining low computational complexity. We validate RA-cGAN on pulmonary and brain datasets and achieve state-of-the-art results on the MVTec AD benchmark. These results demonstrate the efficacy of the model in multimodal unsupervised anomaly detection and image generation, highlighting its potential for diverse clinical applications.

This study investigates the effect of additive manufacturing process parameters on the surface characteristics and performances of titanium Ti6Al4V, used for orthopedic implants. Parts were manufactured by selective laser melting, using a variety of volumetric energy densities, ranging from 58 to 152 J/mm³. Through a rigorous optimization of process parameters coupled with optical examinations of porosity distribution and morphology, a volumetric energy density of 58 J/mm³ was identified as an optimal manufacturing condition that resulted in extremely high densities of 99.8% in Ti6Al4V titanium alloy. X-ray diffraction measurements revealed the development of anisotropic residual stress states, characterized by elevated tensile stresses oriented along the build direction. Phase analysis results indicate a predominant martensitic acicular α′ structure, resulting from the rapid heating and cooling kinetics intrinsic to additive manufacturing, with a minor residual prior-β phase. Optical examinations reveal a microstructural transition from equiaxed prior-β grains to a columnar structure correlated with an increase in scanning speed (decrease in volume energy density). Corrosion tests were performed in Ringer’s solution at 37 °C to simulate physiological conditions. It has been established that the presence of elongated pores combined with high tensile residual stresses can significantly compromise the corrosion resistance of additively manufactured parts. Minimizing porosity, through optimized SLM process parameters, significantly improved corrosion resistance. This resulted in a continuous and dense passive film, reducing the corrosion rate by 72%, from 22 to 6 µm/year. These findings enable prosthesis manufacturers to enhance additively manufactured implant performances, extending their longevity.

Industry 4.0 represents a significant shift in industrial practices, presenting unique opportunities to improve manufacturing via advanced digital technologies and sustainable processes. The rapid growth of Industry 4.0 research has uncovered a significant knowledge gap and emphasized the need for studies adopting dynamic and longitudinal perspectives to understand this field’s evolution comprehensively. This study meticulously analyzes 10,176 articles to investigate the thematic evolution and knowledge transfer mechanisms within Industry 4.0. The examination reveals four distinct sub-periods, each characterized by thematic transitions, starting with foundational themes such as simulation and cyber-physical systems, progressing to later focuses on cloud computing, convolutional neural networks, and digital twin technologies. As research progresses, themes like production facilities, monitoring, and security highlight the shift towards automation, real-time monitoring, and strong data security measures. Five primary thematic domains are identified: (1) core enablers of sustainable smart manufacturing, (2) innovation and strategic transformation, (3) smart and secure manufacturing systems, (4) advanced data-driven manufacturing technologies, and (5) AI-driven real-time monitoring and production. These domains illustrate a transition from fundamental enablers like the Internet of Things (IoT) to more intricate AI-based applications. The main path analysis indicates a shift in emphasis, moving from essential digital integration towards sustainability, digital transformation, and resource efficiency applications. The findings reveal significant implications and highlight Industry 4.0 as a driving force for sustainable and resilient industrial ecosystems.

Microbial inoculants, single or consortia, are groups of microorganisms or their product that can be directly applied in soil or in plant. They have a positive impact on both soil and plant by restoring soil fertility and improving plant performance. Bacteria and fungi are essential components of plant ecosystems. These microbes include different kinds of groups as follows: plant growth-promoting microorganisms (PGPMs), biological control agents (BCAs), and symbiosis (SM). Many mechanisms of these microbes can service plants for growing and protection against biotic and abiotic stress by producing antimicrobial, mycoparasitism, biostimulation, and other useful compounds. Biostimulation is one of the measures that help plants to confront different stress and boost the growth. Biostimulants gained increasing attention as an alternative to chemical fertilizers and pesticides, due to their ability to promote plant growth, enhance nutrient uptake, and improve plant defense against stresses both biotic and abiotic. This current review aims to fill the gap in the current knowledge by citing the various aspects of biostimulants by PGPM and BCAs that comprise action mechanisms, application modes, types of microorganisms, and their influences on the management of plant diseases as well as plant vigor. It is relevant to determine the challenges and opportunities associated with the wide and commercial application of microbial inoculants to be a valuable alternative in sustainable agriculture.

New pillar[5]arene‐based molecular shuttles incorporating an axle component with two stations, namely a –(CH2)10– chain and a protonable triazole subunit, have been prepared. Detailed spectroscopic investigations supported by density functional theory calculations revealed that gliding motions of the pillar[5]arene occur over the full length of the molecular axle in the protonated state, while such molecular motions are limited over the decyl station in the neutral state. Finally, electrochemical investigations further revealed that the oxidation of the pillar[5]arene moiety of the protonated rotaxane also triggers conformational changes and the oxidized macrocycle is only located over the decyl station.

Climate change is predicted to drive geographical range shifts that will result in changes in species diversity and functional composition and have potential repercussions for ecosystem functioning. However, the effect of these changes on species composition and functional diversity (FD) remains unclear, especially for mammals, specifically bats. We used species distribution models and a comprehensive ecological and morphometrical trait database to estimate how projected future climate and land‐use changes could influence the distribution, composition, and FD of the European bat community. Future bat assemblages were predicted to undergo substantial shifts in geographic range and trait structure. Range suitability decreased substantially in southern Europe and increased in northern latitudes. Our findings highlight the potential for climate change to drive shifts in bat FD, which has implications for ecosystem function and resilience at a continental scale. It is important to incorporate FD in conservation strategies. These efforts should target species with key functional traits predicted to be lost and areas expected to experience losses in FD. Conservation strategies should include habitat and roost protection, enhancing landscape connectivity, and international monitoring to preserve bat populations and their ecosystem services.

The purpose of this work is to illustrate an exercise in system analysis and information system (IS) development to make a process of cigarette production streamlined, with a specific focus placed on a machine packer. The illustration shall utilize a specific cigarette packing machine. By employing system analysis and IS development, the research aims to illustrate the effect of such methodology to the overall improvement of the entire process of cigarette manufacturing. This work forms the basis for future research on integrating emerging technologies like machine learning and Industrial Internet of Things (IoT) for further enhanced monitoring and inspection of the process of packing cigarettes.

Devally is an AI-driven full-stack software development system that translates design assets and natural language requirements into functional front-end and back-end code. It supports multiple input modalities for frontend generation, including screenshots, figma-like designs, templates, and hand-drawn sketches, while backend functionality is derived from structured human-readable requirements. The system architecture consists of four core modules: (i) a code repository that can be enabled or disabled based on desired performance trade-offs and containing reusable code snippets and templates ; (ii) a requirements analyzer that classifies and processes inputs while leveraging stored code assets; (iii) a large language model (LLM) augmented with vision transformers to enhance contextual understanding during code generation; and (iv) an integration module that composes, adapts, and merges retrieved or newly generated code into fully functional applications. Devally automates key development tasks, optimizing time, cost, and effort while improving code quality, scalability, and maintainability. Empirical evaluations across multiple case studies demonstrate that Devally consistently produces production-ready applications, bridging the gap between design concepts and their technical implementation. With the code repository module disabled, Devally's performance remains comparable to state-of-the-art LLMs. When enabled, however, it significantly outperforms all other evaluated LLM-based approaches, demonstrating superior accuracy, efficiency, and adaptability in a variety of software development scenarios.

Marine ecosystem restoration success stories are needed to incentivize society and private enterprises to build capacity and stimulate investments. Yet, we still must demonstrate that restoration efforts can effectively contribute to achieving the targets set by the UN Decade on Ecosystem Restoration. Here, we conduct a meta-analysis on 764 active restoration interventions across a wide range of marine habitats worldwide. We show that marine ecosystem restorations have an average success of ~64% and that they are: viable for a large variety of marine habitats, including deep-sea ecosystems; highly successful for saltmarshes, tropical coral reefs and habitat-forming species such as animal forests; successful at all spatial scales, so that restoration over large spatial scales can be done using multiple interventions at small-spatial scales that better represent the natural variability, and scalable through dedicated policies, regulations, and financing instruments. Restoration interventions were surprisingly effective even in areas where human impacts persisted, demonstrating that successful restorations can be initiated before all stressors have been removed. These results demonstrate the immediate feasibility of a global ‘blue restoration’ plan even for deep-sea ecosystems, enabled by increasing availability of new and cost-effective technologies.