Search Results (4,933)

The rapid expansion of wind and solar generation has significantly increased the share of variable renewable energy in power systems worldwide, introducing new operational challenges. Among these, the simultaneous growth of renewable energy curtailment and persistent blackout risk reveals structural limitations in energy planning and system flexibility. This study conducts a Systematic Literature Review (SLR) following the PRISMA protocol to examine how the scientific literature has addressed the relationship between curtailment, energy security, and optimization strategies in high-renewable power systems. A total of 53 Q1-indexed articles published between 2021 and 2025 were analyzed using bibliometric and qualitative content analysis techniques. The results indicate that curtailment should not be interpreted solely as an operational inefficiency but rather as a potential flexibility asset when integrated with energy storage systems, power-to-X technologies, demand-side management, and stochastic optimization frameworks. The findings also highlight a shift from deterministic planning approaches toward robust and distributionally aware models capable of managing renewable uncertainty. Despite significant advances, geographic imbalances in case studies and limited integration between regulatory mechanisms and technical optimization remain key research gaps. This review contributes by synthesizing mitigation strategies into a structured flexibility framework and by outlining research directions for enhancing reliability in renewable-dominated systems. Full article

Direct sea discharge outlets served as critical conduits for urban sewage and industrial wastewater disposal, playing dual roles as pollutant dilution channels and hotspots for pathogens and antibiotic resistance genes. Traditional monitoring approaches relying on physicochemical parameters and fecal indicator bacteria failed to capture the latent and cumulative risks posed by complex microbial communities. In this review, a holistic microbiome perspective was adopted to systematically synthesize current knowledge on the bacterial community dynamics, assembly mechanisms, resistome–virulome coupling patterns, mobilome-associated risk characteristics, and emerging biomonitoring strategies in direct sea discharge outlets. By integrating high-throughput multi-omics technologies with ecological network analysis and machine learning, we delineated a paradigm shift from cataloging microbial presence to deciphering functional interactions, risk propagation dynamics, and proactive surveillance strategies. Furthermore, under the “One Health” framework, we discussed emerging research frontiers and future challenges in managing pollution at discharge outlets, aiming to provide a scientific basis for environmental risk management in coastal zones. Full article

The Ni-Al system contains five intermetallic compounds, out of which NiAl and Ni₃Al have received the vast majority of scientific and industrial interest over the past few decades. Ni₃Al is of major interest due to its unique properties, including a yield strength that increases with temperature. The combustion synthesis (CS) process for producing Ni₃Al from elemental powders of nickel and aluminum offers a low thermal budget and rapid processing, as well as purer products. This paper reviews the fundamentals of CS as applied to Ni₃Al and its composites, and focuses on research over the past 25 years, including mechanically and electrically activated combustion synthesis and combined combustion synthesis and bulk deformation processes to produce high-density products. Several new directions are suggested for future research in the field. Full article

An emerging environmental pollutant, microplastics have garnered global attention due to their widespread presence in soil and aquatic ecosystems. Early research primarily treated microplastics as single pollutants, focusing on their individual toxic effects. However, microplastics in the environment exist as a complex mixture, comprising various polymer types, sizes, shapes, and aging states. This diversity influences how microplastics regulate ecosystem carbon and nitrogen cycles and intervene through pathways such as direct carbon input, physical disturbance, microbial community restructuring, and coupled effects. This paper systematically reviews the characteristics of microplastic diversity and its mechanisms influencing carbon and nitrogen cycles: the chemical structure of polymers determines bioavailability and degradation rate, with biodegradable plastics altering carbon and nitrogen transformations more significantly than conventional plastics; microplastics of different sizes affect nitrogen transformation dynamics by modulating specific surface area and microbial colonization, with small-sized biodegradable microplastics particularly inhibiting plant nitrogen uptake; aging modifies surface properties and dissolved organic carbon release, thereby enhancing their role in promoting greenhouse gas emissions. Existing studies are largely confined to short-term laboratory simulations, leaving a gap in understanding the comprehensive effects of microplastic diversity under long-term, field conditions. Future research should focus on standardized methods and long-term experiments with multi-factor coupling to provide a scientific basis for ecological risk assessment of microplastic pollution. Full article

Background: Several factors have been reported to influence the prognosis of medullary thyroid cancer (MTC). This study aimed to identify prognostic variables associated with progression-free survival (PFS) and overall survival (OS) in a cohort of patients treated at our institution. Patients and Methods: We performed a retrospective analysis of 107 consecutive patients with histologically confirmed MTC who were followed for at least 12 months. Demographic, clinical, and pathological data were retrieved from medical records. The association between baseline variables and survival outcomes was evaluated using univariate Cox proportional hazards regression models. The study was approved by the local ethics committee. Results: The median age at diagnosis was 56 years (range, 10–80 years), and 63% of the patients were female. Germline REarranged during Transfection (RET) mutations were identified in 10% of cases. The median follow-up duration was 100 months (range, 12–464 months). At diagnosis, disease stages were distributed as follows: stage I, 52%; stage II, 12%; stage III, 17%; and stage IV, 19%. Female patients showed significantly longer PFS compared with males (Hazard Ratio (HR) = 0.41, 95% Confidence Interval (CI) (0.21–0.82); p = 0.012). Factors associated with PFS by Cox regression models were post-operative serum calcitonin (CT) values after 1 and 3 months of surgery (HR = 0.08, 95% CI (0.03–0.20); p < 0.001; HR = 0.03, 95% CI (0.01–0.11); p < 0.001, respectively), Tumor, Node, and Metastasis (TNM) stage III–IV (HR = 16.86, 95% CI (5.87–48.44); p < 0.001), presence of lymph nodes metastasis at diagnosis (HR = 9.6, 95% CI (3.59–25.63); p < 0.001), multifocal disease (HR = 2.37, 95% CI (1.07–5.28); p = 0.034) and capsular invasion (HR = 10.72, 95% CI (4.45–25.87); p < 0.001). Factors associated with OS by Cox regression models were age at diagnosis (HR = 1.07, 95% CI (1.01–1.12); p = 0.019) and TNM Classification of Malignant Tumours stage III-IV (HR = 6.69, 95% CI (1.42–31.62); p = 0.016). Although lymph node metastasis and capsular invasion were not significantly associated with overall survival (p = 0.178 and p = 0.094, respectively), both variables showed a trend toward an association with OS. Conclusions: The study confirmed that post-operative serum CT values, male sex, lymph nodes metastasis at diagnosis, TNM stage III and IV and capsular invasion were all associated with a lower PFS. Factors associated with OS were age at diagnosis, presence of lymph nodes metastasis, TNM stage III–IV and capsular invasion. Full article

Background/Objectives: The expansion of direct-to-consumer (DTC) genetic testing has generated civilian genomic databases containing tens of millions of profiles, some of which may be available, under specific conditions, for criminal investigations. Meanwhile, artificial intelligence (AI) is reshaping forensic genetics through applications such as kinship inference, DNA mixture deconvolution, probabilistic phenotyping, and the prioritization of investigative leads. This review examines the scientific, legal, and ethical implications of the convergence between DTC genetic databases, forensic investigative genetic genealogy (FIGG), and AI-assisted forensic analysis. Methods: This article presents a multidisciplinary narrative review at the intersection of forensic genomics, FIGG, artificial intelligence, genomic data governance, and bioethics, with particular attention to French, European, and international regulatory frameworks. Results: Six major dimensions structure the field: (i) the current state of forensic genomic technologies, including STRs, SNPs, and next-generation sequencing; (ii) the contribution of AI to forensic genetics and FIGG; (iii) the governance of large-scale genomic data; (iv) regulatory fragmentation across jurisdictions; (v) the principal bioethical tensions raised by the forensic use of DTC genetic databases; and (vi) future governance needs and operational recommendations. Across these dimensions, three findings emerge. First, genealogical matches and AI-supported outputs should be understood primarily as investigative leads rather than autonomous judicial evidence. Second, the relational nature of genomic data exposes non-consenting relatives to potential forensic scrutiny, thereby challenging traditional models of individual consent and privacy. Third, the absence of harmonized standards for validation, transparency, and oversight remains a major obstacle to legal certainty, judicial admissibility, and public legitimacy. Conclusions: The forensic use of DTC genetic databases should not be understood as a purely technical extension of conventional DNA profiling. It reflects a broader transformation in the relationship between genomic knowledge, criminal investigation, and fundamental rights. Its long-term legitimacy and operational viability will depend on the combined strength of scientific reliability, legal proportionality, ethical safeguards, and meaningful democratic oversight. Full article

Product design strategies play a pivotal role in advancing responsible production and consumption by enabling the transition toward more sustainable industrial practices. In this context, the rapid evolution of technology and artificial intelligence is fostering the development of innovative and sustainability-oriented strategies, which are increasingly embedded in the early stages of the design process, thereby facilitating the transformation and optimisation of contemporary industrial systems. This scoping review presents advances in product design strategies that promote responsible production and consumption, along with the impacts of their implementation, the associated challenges and limitations, and future perspectives. This manuscript was prepared according to the PRISMA^® guidelines, using scientific literature from databases and repositories such as Scopus, Web of Science, ScienceDirect, and Taylor & Francis. Document selection was conducted by two observers, yielding a Cohen’s Kappa coefficient of 0.840. A total of 147 articles were included for reference information extraction. The product design process plays a crucial role in promoting more sustainable production and guiding responsible consumption habits, as it has proven effective in reducing resource use and waste generation from a life cycle perspective. However, its impact also depends on human-related factors such as perceptions, habits, levels of trust, and usage conditions, highlighting the interaction between product design and consumer behaviour. Full article

This work addresses the design and implementation of an automated system for the handling and transportation of parts, integrating speed sensors, an optimized PID controller, an HMI interface, and an industrial robotic system. The speed sensors, powered by 5 V DC, enable continuous measurement of the conveyor belt’s speed and direction of rotation, providing the feedback signal required for the control loop. The core element of the system is the implementation of a PID controller applied to a direct current motor responsible for driving the conveyor belt. This controller regulates the motor speed by analyzing the error between the reference speed and the measured speed, using proportional, integral, and derivative actions to improve system stability, reduce steady-state error, and minimize oscillations. The application of PID control makes it possible to achieve an appropriate dynamic response, ensuring accuracy and reliability in the transportation process. System monitoring and operation are carried out through a human–machine interface (HMI) developed in LOGO Web Editor, which communicates with the PLC (LOGO V8) to visualize and control the status of the conveyor belt, sensors, and control elements in real time. This interface facilitates interaction between the operator and the system, allowing both virtual and physical operation. In addition, RAPID programming is used to control the IRB 14000 industrial robot, enabling the reading of PLC signals and the execution of coordinated trajectories between both arms. The operating sequence includes picking up a part with the left arm, placing it on the conveyor belt, and, after detection by sensors and PLC control, subsequent manipulation by the right arm to a specific point. Finally, both arms return to their original position, ensuring synchronized and collision-free operation. Lastly, this work integrates scientific knowledge related to the modeling, analysis, and control of dynamic systems, particularly in the implementation of closed-loop PID control optimized using genetic algorithms. This control is applied directly to an embedded system through the use of an Arduino board as the processing and control platform. Likewise, technological knowledge associated with industrial automation, PLC programming, HMI development, and industrial robotics is incorporated. The convergence of these scientific and technological approaches results in a comprehensive and compelling project that demonstrates the practical application of theoretical concepts in a functional automated system representative of real industrial environments. Full article

Polycyclic aromatic hydrocarbons (PAHs) represent a major class of ubiquitous environmental pollutants, posing significant risks to ecosystems and human health due to their persistence, toxicity, and potential for bioaccumulation. This review provides a comprehensive synthesis of current scientific knowledge on PAHs, integrating insights from chemical kinetics, environmental fate, and toxicological mechanisms. The fundamental structural chemistry of PAHs and its direct influence on their physicochemical properties and environmental properties are discussed. The major anthropogenic and natural sources of PAHs are detailed, alongside the chemical kinetics behind their formation during incomplete combustion and their transformation in environmental media. Unlike previous reviews that address PAH sources, remediation, or health effects as separate topics, this review uniquely traces the mechanistic continuum from molecular formation kinetics through physicochemical partitioning and environmental transport to toxicological endpoints, providing a causally linked framework for understanding how structural properties ultimately determine biological outcomes. A central focus is placed on the environmental fate and transport of PAHs across atmospheric, aquatic, and terrestrial compartments, highlighting processes such as gas–particle partitioning, sediment accumulation, and long-range transport. The review further elucidates the complex toxicological pathways of PAHs, including metabolic activation to reactive intermediates, DNA adduct formation, oxidative stress, and their roles in carcinogenesis and other systemic health effects. The analysis reveals strong scientific consensus on the carcinogenic mechanism of parent PAHs via CYP450-mediated metabolic activation to diol-epoxide intermediates while identifying critical areas of uncertainty: the current regulatory framework based on 16 priority PAHs underestimates total carcinogenic risk by a factor of 2–5, mixture toxicology remains poorly characterized, and dose–response relationships for non-cancer endpoints (cardiovascular, neurodevelopmental, immunotoxic) lack the quantitative data needed for robust risk assessment. Finally, human exposure pathways and health risk characterization approaches are discussed, highlighting the need for cumulative, mixture-based assessment frameworks. Full article

Circulating tumor DNA (ctDNA) has emerged as a transformative tool in cancer diagnostics, enabling the non-invasive detection of tumor-derived DNA fragments released into the bloodstream through cellular lysis or active secretion. ctDNA measurement has demonstrated its clinical usefulness, including early cancer detection, identification of resistance mechanisms, and screening of asymptomatic individuals. In addition to prognosis, ctDNA analysis is increasingly used to guide adaptive treatment strategies by detecting minimal residual disease and tracking tumor evolution in real time. Recent advances in artificial intelligence are poised to further enhance the clinical impact of ctDNA, transforming it from a passive monitoring biomarker into a dynamic molecular sensor integrated into predictive clinical decision models. However, broad implementation of ctDNA-based assays in routine practice requires rigorous prospective validation, cross-platform standardization, and regulatory approval to unlock its full potential in precision oncology. Full article

Recent advances in generative Artificial Intelligence (AI) have rapidly transformed research and practice across the Cultural Heritage domain. While several studies have investigated AI applications in documentation, analysis and dissemination, a focused and critical assessment of generative AI within 3D virtual reconstruction workflows is still lacking. This paper presents a systematic review of the literature addressing the use of generative AI in 3D heritage virtual reconstructions, with particular attention to methodological implications, scientific reliability and ethical challenges. A large-scale bibliographic analysis covering publications from 2015 to 2024 was conducted using OpenAlex, complemented by targeted manual searches. From an initial corpus of over 8700 papers on 3D heritage reconstruction, only 13 directly addressed generative AI-driven reconstruction processes. The analysis highlights a significant gap between the rapid technological development of AI-based tools and their cautious, often problematic, adoption in virtual reconstruction practices. Results reveal recurring issues related to terminological ambiguity, opacity of reconstruction processes, evaluation metrics focused on visual plausibility rather than scientific transparency and the risk of interpretative bias. The paper argues that current AI-driven approaches tend to privilege speed and aesthetic outcomes over heuristic, source-based reconstruction workflows. Finally, future research directions are discussed, emphasizing the potential role of AI as an evaluative and analytical support tool rather than a fully autonomous reconstruction agent, in alignment with established charters and principles of virtual archaeology. Full article

The aim of this review is to provide a narrative analysis of the role of Lactobacillus acidophilus as an active modulating factor in the prevention and treatment of cancer and allergic diseases. The paper discusses the molecular, metabolic, and bionanotechnological mechanisms of Lactobacillus acidophilus’s anticancer and immunomodulatory effects, which define this probiotic as an essential component of modern natural and functional medicine. A narrative review of the scientific literature was conducted, mainly from 2019–2026, focusing on the results of in vitro studies and studies on preclinical in vivo models, which analyzed the effect of live L. acidophilus strains, tyndallized bacteria (paraprobiotics) and cell-free supernatant from L. acidophilus cultures on, among others, immune system signaling pathways, tissue cytokine profile, and the integrity of the gastrointestinal epithelial cell barrier (enterocytes). Results indicate that L. acidophilus exerts significant antiallergic, antiproliferative, and proapoptotic effects against many types of cancer. Among other aspects, the ability of L. acidophilus to stimulate the production of anticancer exopolysaccharides and short-chain fatty acids, which directly influence the functioning of immune cells, is covered. The article thoroughly explains the immunomodulatory effects of L. acidophilus and the ability of this probiotic to regulate cytokine profiles, which helps promote an anti-inflammatory environment crucial for maintaining intestinal homeostasis. The article also discusses the direct interaction of L. acidophilus with immune cells, such as dendritic cells and macrophages, which leads to their activation and subsequent influence on the differentiation of T lymphocytes, which play a key role in the regulation of immune processes and in the development of immune tolerance. L. acidophilus is a universal mediator of immunological and metabolic homeostasis. Its ability to synergize with conventional therapies (chemotherapy, oncolytic virotherapy) and its innovative applications in the creation of postbiotics and paraprobiotics may provide a new approach to the treatment of inflammatory, allergic, and neoplastic diseases. Further clinical studies are necessary to assess the efficacy, safety, and optimal dose of this probiotic, which are essential for the widespread use of L. acidophilus in human therapy. Full article

Background/Objectives: Nurses’ engagement in research is essential to strengthen evidence-based practice, knowledge translation, and quality of care. However, individual, organisational, and cultural barriers may limit nurses’ participation in research activities. This study aimed to cross-culturally adapt and psychometrically test the Italian version of the Barriers to Nurses’ Participation in Research Questionnaire within the Italian cultural and healthcare organisational context, and to explore perceived obstacles to research engagement among nurses in Italy. Methods: A cross-sectional methodological study was conducted. The instrument was translated, back-translated, reviewed by the original instrument developer and an expert panel, and evaluated for content validity by 12 clinical research professionals. Data were collected online between September and October 2024 from 196 nurses working across Italian healthcare settings, including hospitals, university hospitals, IRCCS, primary care, and private hospitals. Exploratory Structural Equation Modelling was used to examine the factor structure. Results: A total of 196 nurses were enrolled in the study. A two-factor structure was identified, comprising Research Resources and Personal Relevance of Research, which explained 35.37% and 25.14% of the variance, respectively. Both factors demonstrated good reliability. The most prominent barrier was the lack of incentive or reward for nurses to engage in research, whereas the least relevant barrier was the perception that research was not interesting or valuable. Greater barriers were reported by younger nurses, those with fewer years of experience, and those without specific research training. Lack of time to conduct research emerged as a pervasive obstacle across the sample. Conclusions: The Italian version of the Barriers to Nurses’ Participation in Research Questionnaire provides preliminary evidence of validity and reliability for assessing perceived barriers to research participation among Italian nurses. Owing to the structural modifications introduced during adaptation, the instrument should be interpreted as a culturally adapted and modified Italian version rather than as a direct replication of the original structure. Its use may support organisational diagnosis, research mentorship, training planning, and future research-capacity-building initiatives, although further validation in larger and more heterogeneous samples is warranted. Full article

Autonomous vehicle open-road testing is a crucial component in the development of intelligent and connected vehicle (ICV) industries. The classification of road complexity plays a key role in ensuring the safety and efficiency of such tests. This study, based on the practices of the High-Level Autonomous Driving Demonstration Zone in Beijing, proposes a scientific and systematic framework for classifying road complexity. The framework integrates static road features, dynamic traffic flow indicators, and safety event metrics, employing the Analytic Hierarchy Process (AHP) to quantify road complexity and categorize roads into five distinct levels. The findings provide significant guidance for the phased opening of test roads, optimization of autonomous driving algorithms, construction of accident scenario databases, and deployment of infrastructure. This paper further explores the practical applications and future development directions of road complexity classification, aiming to offer theoretical and practical support for the testing and demonstration of intelligent and connected vehicles. Full article

Controversy persists on a global scale regarding the trade-offs between greenhouse gas (GHG) emissions, yield, the global warming potential (GWP), and GHG intensity (GHGI) following organic fertilizer substitution within vegetable cropping systems. This study aimed to quantify these effects under diverse conditions and elucidate the direct and indirect drivers governing these outcomes through a meta-analysis and structural equation modeling (SEM). We synthesized 655 paired observations from 69 published studies using random-effects meta-analysis, finding that organic fertilizer substitution significantly increased CH₄ emissions and GWP compared to inorganic fertilizer controls. Although this was the general trend, organic fertilizer could reduce GWP under specific climatic and soil conditions by reducing N₂O emissions, such as mean annual precipitation <400 mm or soil total nitrogen ≥3 g kg⁻¹. These conditions were also associated with substantially higher yield and lower GHGI. Furthermore, SEM demonstrated that field management practices exerted significant direct effects on N₂O emissions, GWP, and GHGI. Reductions in N₂O emissions, GWP, and GHGI could be achieved with fertilizer application duration ≥10 years, total N application rate ≥300 kg ha⁻¹, and field cultivation or plowing. GHGI was also reduced through yield enhancement under a moderate organic substitution rate (33–66%) or irrigation ≥300 mm. Our study provides a scientific basis for moving beyond universal recommendations towards precision organic management, which is essential for optimizing fertilization strategies to mitigate agricultural GHG emissions. Full article