Cyber threats continue to evolve in complexity, thereby traditional cyber threat intelligence (CTI) methods struggle to keep pace. AI offers a potential solution, automating and enhancing various tasks, from data ingestion to resilience verification. This paper explores the potential of integrating artificial intelligence (AI) into CTI. We provide a blueprint of an AI-enhanced CTI processing pipeline and detail its components and functionalities. The pipeline highlights the collaboration between AI and human expertise, which is necessary to produce timely and high-fidelity cyber threat intelligence. We also explore the automated generation of mitigation recommendations, harnessing AI’s capabilities to provide real-time, contextual, and predictive insights. However, the integration of AI into CTI is not without its challenges. Thereby, we discuss the ethical dilemmas, potential biases, and the imperative for transparency in AI-driven decisions. We address the need for data privacy, consent mechanisms, and the potential misuse of technology. Moreover, we highlight the importance of addressing biases both during CTI analysis and within AI models, warranting their transparency and interpretability. Lastly, our work points out future research directions, such as the exploration of advanced AI models to augment cyber defenses, and human–AI collaboration optimization. Ultimately, the fusion of AI with CTI appears to hold significant potential in the cybersecurity domain. Full article

The raw material purchasing (RMP) problem is to determine the purchasing quantities of raw materials in given periods or cycles. Raw material purchasing optimization is crucial for large-scale steel plants because it is closely related to the supply of raw materials and cost savings. The raw material purchasing of large-scale steel enterprises is characterized by many varieties, large quantities, and high costs. The RMP objective is to minimize the total purchasing cost, consisting of the price of raw materials, purchasing set-up costs, and inventory costs, and meet product demand. We present a mixed integer linear programming (MILP) model and a column generation (CG) solution for the resulting optimization problem. The column generation algorithm is the generalization of the branch and bound algorithm while solving the linear programming (LP) relaxation of MILP using column generation (CG), and its advantage is to handle large-sized MILPs. Experimental results show the effectiveness and efficiency of the solution. Full article

This work aims to evaluate the potential use of natural wastes (in particular, clam shells) to synthesize one of the most well-known and versatile materials from the phosphate mineral group, hydroxyapatite (HAP). The obtained material was characterized in terms of morphology and composition using several analytical methods (scanning electron microscopy—SEM, X-ray diffraction—XRD, X-ray fluorescence—XRF, Fourier transform infrared spectroscopy—FTIR, thermal analysis—TGA, and evaluation of the porosity and specific surface characteristics by the Brunauer–Emmett–Teller—BET method) in order to confirm the successful synthesis of the material and to evaluate the presence of potential secondary phases. The developed material was further doped with iron oxide (HAP-Fe) using a microwave-assisted method, and both materials were evaluated in terms of photocatalytic activity determined by the photodecomposition of methylene blue (MB) which served as a contaminant model. The best results (approx. 33% MB degradation efficiency, after 120 min. of exposure) were obtained for the hydroxyapatite material, superior to the HAP-Fe composite (approx. 27%). The utilization of hydroxyapatite obtained from clam shells underscores the importance of sustainable and eco-friendly practices in materials syntheses. By repurposing waste materials from the seafood industry, we not only reduce environmental impact, but also create a valuable resource with diverse applications, contributing to advancements in both healthcare and environmental protection. Full article

The management of early-stage hepatocellular carcinoma (HCC) is complex, with multiple treatment strategies available. There is a paucity of literature regarding variations in the patterns of care and outcomes between transplant and non-transplant centres. We conducted this real-world multi-centre cohort study in two liver cancer referral centres with an integrated liver transplant program and an additional eight non-transplant HCC referral centres across Australia to identify variation in patterns of care and key survival outcomes. Patients with stage Barcelona Clinic Liver Cancer (BCLC) 0/A HCC, first diagnosed between 1 January 2016 and 31 December 2020, who were managed at a participating site, were included in the study. Patients were excluded if they had a history of prior HCC or if they received upfront liver transplantation. A total of 887 patients were included in the study, with 433 patients managed at a liver cancer centre with a transplant program (LTC) and 454 patients managed at a non-transplant centre (NTC). Management at an LTC did not significantly predict allocation to resection (adjusted OR 0.75, 95% CI 0.50 to 1.11, p = 0.148). However, in those not receiving resection, LTC and NTC patients were systematically managed differently, with LTC patients five times less likely to receive upfront ablation than NTC patients (adjusted OR 0.19, 95% CI 0.13 to 0.28, p < 0.001), even after adjusting for tumour burden, as well as for age, gender, liver disease aetiology, liver disease severity, and medical comorbidities. LTCs exhibited significantly higher proportions of patients undergoing TACE for every tumour burden category, including those with a single tumour measuring 2 cm or less (p < 0.001). Using multivariable Cox proportional hazards analysis, management at a transplant centre was associated with reduced all-cause mortality (adjusted HR 0.71, 95% CI 0.51 to 0.98, p = 0.036), and competing-risk regression analysis, considering liver transplant as a competing event, demonstrated a similar reduction in risk (adjusted HR 0.70., 95% CI 0.50 to 0.99, p = 0.041), suggesting that the reduced risk of death is not fully explained by higher rates of transplantation. Our study highlights systematic differences in HCC care between large volume liver transplant centres and other sites, which has not previously been well-described. Further work is needed to better define the reasons for differences in treatment allocation and to aim to minimise unwarranted treatment variation to maximise patient outcomes across Australia. Full article

This paper investigates the incorporation of sustainable development within the Portuguese agri-food sector amid global environmental and resource challenges. It underscores the role of the Sustainable Development Goals (SDGs) and environmental, social, and governance (ESG) criteria in steering businesses towards sustainable practices. Through qualitative analysis, in-depth interviews with managers and experts explored sustainable business model adoption, highlighting SMEs’ unique challenges. The study reveals a divergence in sustainability practice maturity, advocating for integration into organizational culture and strategy. It points out SMEs’ reactive stance due to resource constraints and external pressures, contrasting with larger firms’ proactive approaches. The research supports a strategic reevaluation of business models for sustainability, emphasizing innovation, leadership, organizational commitment, and transparent communication. Practical contributions include embedding sustainability into core operations, enhancing competitiveness, fostering sustainable organizational culture, prioritizing employee well-being, and leveraging innovative marketing for sustainability communication. Recognizing its limitations, this study advocates exploring blockchain and AI for transparency, leadership’s role in sustainable models, and the importance of marketing in the agri-food sector for sustainable management. Insights indicate that innovation and strategic partnerships are crucial for enhancing organizational sustainability and achieving the SDGs. Full article

Conifers are an ecologically and economically important seed plant group that can provide significant insights into the evolution of land plants. Molecular phylogenetics has developed as an important approach in evolutionary studies, although there have been relatively few studies of conifers that employ large-scale data sourced from multiple nuclear genes. Target enrichment sequencing (target capture, exon capture, or Hyb-Seq) has developed as a key approach in modern phylogenomic studies. However, until now, there has been no bait set that specifically targets the entire conifer clade. REMcon is a target sequence capture probe set intended for family- and species-level phylogenetic studies of conifers that target c. 100 single-copy nuclear loci. We tested the REMcon probe set using 69 species, including 44 conifer genera across six families and four other gymnosperm taxa, to evaluate the efficiency of target capture to efficiently generate comparable DNA sequence data across conifers. The recovery of target loci was high, with, on average, 94% of the targeted regions recovered across samples with high read coverage. A phylogenetic analysis of these data produced a well-supported topology that is consistent with the current understanding of relationships among conifers. The REMcon bait set will be useful in generating relatively large-scale nuclear data sets consistently for any conifer lineage. Full article

Breast cancer presents a significant global health challenge with rising incidence rates worldwide. Despite current efforts, it remains inadequately controlled. Functional foods, notably tempeh, have emerged as promising candidates for breast cancer prevention and treatment due to bioactive peptides and isoflavones exhibiting potential anticancer properties by serving as antioxidants, inducing apoptosis, and inhibiting cancer cell proliferation. This study integrates pharmacoinformatics and cellular investigations (i.e., a multifaceted approach) to elucidate the antioxidative and anti-breast cancer properties of tempeh-derived isoflavones. Methodologies encompass metabolomic profiling, in silico analysis, antioxidant assays, and in vitro experiments. Daidzein and genistein exhibited potential therapeutic options for breast cancer treatment and as antioxidant agents. In vitro studies also supported their efficacy against breast cancer and their ability to scavenge radicals, particularly in soy-based tempeh powder (SBT-P) and its isoflavone derivatives. Results have demonstrated a significant downregulation of breast cancer signaling proteins and increased expression of miR-7-5p, a microRNA with tumor-suppressive properties. Notably, the LD₅₀ values of SBT-P and its derivatives on normal breast cell lines indicate their potential safety, with minimal cytotoxic effects on MCF-10A cells compared to control groups. The study underscores the favorable potential of SBT-P as a safe therapeutic option for breast cancer treatment, warranting further clinical exploration. Full article

Arabic gum, a high molecular weight heteropolysaccharide, is a promising prebiotic candidate as its fermentation occurs more distally in the colon, which is the region where most chronic colonic diseases originate. Baobab fiber could be complementary due to its relatively simple structure, facilitating breakdown in the proximal colon. Therefore, the current study aimed to gain insight into how the human gut microbiota was affected in response to long-term baobab fiber and Arabic gum supplementation when tested individually or as a combination of both, allowing the identification of potential complementary and/or synergetic effects. The validated Simulator of the Human Intestinal Microbial Ecosystem (SHIME^®), an in vitro gut model simulating the entire human gastrointestinal tract, was used. The microbial metabolic activity was examined, and quantitative 16S-targeted Illumina sequencing was used to monitor the gut microbial composition. Moreover, the effect on the gut microbial metabolome was quantitatively analyzed. Repeated administration of baobab fiber, Arabic gum, and their combination had a significant effect on the metabolic activity, diversity index, and community composition of the microbiome present in the simulated proximal and distal colon with specific impacts on Bifidobacteriaceae and Faecalibacterium prausnitzii. Despite the lower dosage strategy (2.5 g/day), co-supplementation of both compounds resulted in some specific synergistic prebiotic effects, including a biological activity throughout the entire colon, SCFA synthesis including a synergy on propionate, specifically increasing abundance of Akkermansiaceae and Christensenellaceae in the distal colon region, and enhancing levels of spermidine and other metabolites of interest (such as serotonin and ProBetaine). Full article

Degradation of ester-based polyurethane (PUR) foams results in extensive fragmentation, stickiness, and brittleness both at surfaces and in the bulk. Current methods to conserve museum objects comprising PUR foams include consolidation with solvent-based polymeric solutions. Besides the limitations of spray and brush application for deep consolidant penetration and the impracticality of immersing large-scale objects in solutions, these methods often require large amounts of toxic solvents that are harmful for both the user and environment. Carbon dioxide can be employed as a green solvent as it can be recovered, recycled, and reused without contributing to the greenhouse effect. Supercritical carbon dioxide (scCO₂)-assisted consolidation premises are that it may carry the consolidant deeper and deposit it consistently throughout the foam, whilst ensuring minimal interaction with the surface and avoiding material losses in severely degraded objects and the use of toxic solvents. The suitability of scCO₂ as a carrier is studied, and the results compared with spray application, a commonly used traditional method. Previous studies have shown that a mixture of alkoxysilanes has great potential for reinforcing the foam’s structure and hydrophobicity when applied by immersion and other impregnation techniques. In this study, scCO₂-assisted consolidation has proven to be an effective and green alternative to consolidation by spray, reducing hazardous solvent emissions. After treatment, no visual changes were detected, the samples became less sticky, and the foam flexibility improved significantly. Analytical techniques confirmed the presence of the consolidant in all tested samples, both on the top surface and in-depth layers, in contrast to foams treated by spray. Full article

Sustainable design and building information modeling have introduced challenges and opportunities to improve the efficiency of construction project management. The use of circular economy principles provides an opportunity to improve not only environmental indicators but also economic ones. This study addresses sustainable design and BIM in construction project management through circular economy principles. It aims to analyze the impact of using building information modeling on sustainability indicators measured through costs. For research purposes, the basic parameters of sustainability in the construction industry were defined as recycling rate and reductions in waste and CO2. The research questionnaire sample consisted of 199 respondents from Slovakia, Slovenia, and Croatia. Data were processed and evaluated through descriptive statistics, and then tests were used for data distribution. Statistical significance was determined through ANOVA and Kruskal–Wallis tests. Pearson’s correlation analysis was used for data processing. The trends in the research results suggest that sustainable design can be achieved using building information modeling. They also pointed to an impact on sustainability through increasing the recycling rate and reducing the amount of waste. Although these results indicated a trend, this was not confirmed by the statistical significance tests. Full article

For designing single-molecule devices that have both conjugation systems and structural flexibility, a hyperconjugated molecule with a σ–π bond interaction is considered an ideal candidate. In the investigation of conductance at the single-molecule level, since few hyperconjugation systems have been involved, the strategy of building hyperconjugation systems and the mechanism of electron transport within this system remain unexplored. Based on the skipped-conjugated structure, we present a rational approach to construct a hyperconjugation molecule using a hydroxyl group, which serves as a bridge to interact with the conjugated fragments. The measurement of single-molecule conductance reveals a two-fold conductance enhancement of the hyperconjugation system having the ‘bridging’ hydroxyl group compared to hydroxyl-free derivatives. Theoretical studies demonstrate that the hydroxyl group in the hyperconjugation system connects the LUMO of the two conjugated fragments and opens a through-space channel for electron transport to enhance the conductance. Full article

In recent years, with the continuous development and popularization of unmanned aerial vehicle (UAVs) technology, the surge in the number of UAVs has led to an increasingly serious problem of illegal flights. Traditional acoustic-based UAV localization techniques have limited ability to extract short-time and long-time signal features, and have poor localization performance in low signal-to-noise ratio environments. For this reason, in this paper, we propose a deep learning-based UAV localization technique in low signal-to-noise ratio environments. Specifically, on the one hand, we propose a multiple signal classification (MUSIC) pseudo-spectral normalized mean processing technique to improve the direction of arrival (DOA) performance of a traditional broadband MUSIC algorithm. On the other hand, we design a DOA estimation algorithm for UAV sound sources based on a time delay estimation neural network, which solves the problem of limited DOA resolution and the poor performance of traditional time delay estimation algorithms under low signal-to-noise ratio conditions. We verify the feasibility of the proposed method through simulation experiments and experiments in real scenarios. The experimental results show that our proposed method can locate the approximate flight path of a UAV within 20 m in a real scenario with a signal-to-noise ratio of −8 dB. Full article

Feline upper respiratory tract infections (URI) are of concern, especially in animal shelters. This scoping review identifies epidemiological literature on URI as caused by feline herpesvirus (FHV), feline calicivirus (FCV), Chlamydia felis, Mycoplasma felis and Bordetella bronchiseptica. Four databases were searched, studies were screened, and data were extracted on a standardised template. We described patterns in spatial locations of the studies, the range of pathogens and diagnostic tests, cohort characteristics and the findings of risk factor analyses. A total of 90 articles were selected for final data extraction. There was diversity in sampling methods, precluding quantitative meta-analysis of prevalence reports. FHV was most frequently studied (n = 57/90). The most popular sampling site was conjunctival swabbing (n = 43). Most studies (n = 57) used polymerase chain reaction (PCR) to confirm diagnosis. Approximately one-third (n = 32/90) of the studies included sheltered felines. This review explores the current state of knowledge on the epidemiology and risk factors of feline URI. Assessing the impact of risk factors has the potential to alleviate the severity of disease, especially in shelters; however, the results were not easily pooled as the studies used inconsistent approaches. We present recommendations for ongoing epidemiological research on feline URI to provide a more structured framework and define research questions for future systematic reviews. Full article

Pregnancy after organ transplantation is considered high-risk and requires supervision in specialized centers. The impact of immunosuppression on the developing fetus is still the subject of research. It has been shown that it affects lymphocyte populations in the first year of life. For this reason, researchers suggest postponing mandatory infant vaccinations. The aim of the study was to analyze the influence of intrauterine exposure of the fetus to immunosuppression on the immunogenicity of protective vaccinations against selected bacterial pathogens. The ELISA method was used to determine the concentration of post-vaccination IgG antibodies against diphtheria, tetanus, pertussis, tuberculosis, H. influenzae type B, and S. pneumoniae in 18 children of mothers who underwent organ transplantation. The results were compared with the control group (n = 21). A comparison of the incidence of adverse post-vaccination reactions between the analyzed groups was also performed. There were no statistically significant differences in the immunogenicity of the analyzed vaccines between children of mothers who underwent organ transplantation and the age-matched general pediatric population. There were no differences in the incidence of adverse post-vaccination reactions between the analyzed groups. The obtained results do not indicate the need to modify the current protective vaccination schemes against bacterial pathogens in children of mothers who underwent organ transplantation. Full article

Carbon dots (CDs) are luminescent carbon nanoparticles with significant potential in analytical sensing, biomedicine, and energy regeneration due to their remarkable optical, physical, biological, and catalytic properties. In light of the enduring ecological impact of non-biomass waste that persists in the environment, efforts have been made toward converting non-biomass waste, such as ash, waste plastics, textiles, and papers into CDs. This review introduces non-biomass waste carbon sources and classifies them in accordance with the 2022 Australian National Waste Report. The synthesis approaches, including pre-treatment methods, and the properties of the CDs derived from non-biomass waste are comprehensively discussed. Subsequently, we summarize the diverse applications of CDs from non-biomass waste in sensing, information encryption, LEDs, solar cells, and plant growth promotion. In the final section, we delve into the future challenges and perspectives of CDs derived from non-biomass waste, shedding light on the exciting possibilities in this emerging area of research. Full article

Smart Cities have emerged as a promising approach for transforming urban living into more sustainable and resilient systems through technology-driven innovations and data-driven governance. Despite its growing implementation and diffusion around the globe, many questions surrounding this topic have emerged. Many critics have emerged since its first conceptualization in the first decade of the current century. Smart Cities have been criticized for their utopian objectives and the security, safety, people’s freedom, and privacy within these systems. There are also capitalistic and neoliberalism-related critiques. Other critiques also highlight the current climate cost of Smart City initiatives. In the context of those critiques, bioclimatic and passive strategies might provide an interesting evolution of the concept but seem to be left in the background. This paper aims to contribute to the understanding of the linkages between environmental design approaches and the Smart City discourse. The contribution will explore to which extent bioclimatic and environmental design principles are present in the Smart City discourse and what the patterns are inside the current literature. The methodology of the research included a quali-quantitative analysis of the body of literature in Scopus and a bibliometric analysis using the VOS Viewer tool. Full article

Humanoid robots have rapidly become the focus of research in recent years, with the most impressive humanoids being hydraulically actuated. This is due to the capacity of hydraulic actuation to provide simultaneous high forces with dynamic motion. The scarcity of hydraulic robots is mainly due to the difficulty in managing hydraulic pipes. These decrease the robot’s social acceptance and safety and are the main source of leaks. Recently, there has been a new trend in hydraulically actuated robots that involves creating internal oil passages within the robotic parts to eliminate the need for external flexible tubes. Developing these parts using carbon composite materials provides an additional advantage of ensuring lightweight yet robust robotic parts. However, assembling hydraulically integrated parts is challenging due to the leakproof requirement and the high pressures involved. This article proposes a new, reliable, and effective method that ensures a strong, leakproof assembly. A mathematical model with 11 parameters describing the assembly zone and accounting for geometric parameters, material characteristic parameters, and porosity has been developed. A numerical model was conducted to evaluate the effect of these parameters on the state of the assembly. Experimental validation was conducted to evaluate the assembly force. A satisfactory convergence between the mathematical model and the experimental results was observed with a maximum deviation of $20\%$. Full article

A decision maker (DM) must choose between two projects or decide on no project. The expected benefits of these projects are correlated. The DM seeks advice from an agent with private information about the projects’ benefits. However, the agent’s divergent preferences for projects and lack of consideration for the DM’s implementation costs may introduce two types of biases: project bias, favoring the agent’s project, or pandering bias, favoring the project preferred by the DM. Our findings reveal that project correlation leads to these biases countervailing each other, facilitating the transmission of information. The agent typically recommends a project based on private information to dissuade the DM from choosing no project, as this would be detrimental to the agent. Additionally, we explore optimal delegation within organizations. In contrast to the prevailing literature advocating for delegation to biased agents for enhanced information elicitation, our study suggests limited benefits in the context of project correlation. Full article

Background: Large language models (LLMs) represent a recent advancement in artificial intelligence with medical applications across various healthcare domains. The objective of this review is to highlight how LLMs can be utilized by clinicians and surgeons in their everyday practice. Methods: A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Six databases were searched to identify relevant articles. Eligibility criteria emphasized articles focused primarily on clinical and surgical applications of LLMs. Results: The literature search yielded 333 results, with 34 meeting eligibility criteria. All articles were from 2023. There were 14 original research articles, four letters, one interview, and 15 review articles. These articles covered a wide variety of medical specialties, including various surgical subspecialties. Conclusions: LLMs have the potential to enhance healthcare delivery. In clinical settings, LLMs can assist in diagnosis, treatment guidance, patient triage, physician knowledge augmentation, and administrative tasks. In surgical settings, LLMs can assist surgeons with documentation, surgical planning, and intraoperative guidance. However, addressing their limitations and concerns, particularly those related to accuracy and biases, is crucial. LLMs should be viewed as tools to complement, not replace, the expertise of healthcare professionals. Full article

The Middle Ages and Early Modern periods saw the interpretation of reality through symbols, connecting the natural world to the divine using symbolic thinking and images. The idea of a correspondence between the human and universal macrocosm was prominent in various fields such as medicine, philosophy, and religion. Symbolism played a crucial role in approaching divine matters, with symbols serving as a means of direct presence and embodiment. Plato’s influence on Neoplatonist and Hermetic thinkers emphasized the role of dreams and eidola (images) for interpreting the divine. Contemplation of art and nature was an epistemological tool, seeking hidden cosmic harmony and understanding. Christianity embraced worshiping images as representations of the divine, granting believers a way to understand religious concepts. Icons were considered mirrors reflecting the spiritual and divine aspects. The medieval concept of speculum books as mirrors containing all knowledge offered instructional and subjective insights on various subjects. Speculum humanae salvationis illuminated books demonstrated the interplay between the Old and New Testaments, influencing artists like Rogier van der Weyden. Full article

Clustered data are a special type of correlated data where units within a cluster are correlated while units between different clusters are independent. The number of units in a cluster can be associated with that cluster’s outcome. This is called the informative cluster size (ICS), which is known to impact clustered data inference. However, when comparing the outcomes from multiple groups of units in clustered data, investigating ICS may not be enough. This is because the number of units belonging to a particular group in a cluster can be associated with the outcome from that group in that cluster, leading to an informative intra-cluster group size or IICGS. This phenomenon of IICGS can exist even in the absence of ICS. Ignoring the existence of IICGS can result in a biased inference for group-based outcome comparisons in clustered data. In this article, we mathematically formulate the concept of IICGS while distinguishing it from ICS and propose a nonparametric bootstrap-based statistical hypothesis-testing mechanism for testing any claim of IICGS in a clustered data setting. Through simulations and real data applications, we demonstrate that our proposed statistical testing method can accurately identify IICGS, with substantial power, in clustered data. Full article

Plants are an essential component of our daily diet, and their nutritional value has been thoroughly studied for many years. The ability of plants to adapt to changing environmental conditions through signaling systems is an essential component of their survival. Plants undergo an array of physiological alterations to respond to stress from biotic sources. Secondary compounds frequently accumulate in crops that are sensitive to stress, particularly those with several eliciting agents or signaling molecules. Plants contain various types of bioactive compounds, including phytosterols, alkaloids, glycosides, and polyphenols, which make them valuable for the food and pharmaceutical industries. The increased production of secondary metabolites via elicitation has opened up a new field of study with the potential to provide substantial financial gains for the pharmaceutical and nutraceutical industries. These elicitors are pharmacological compounds that activate specific transcription factors and up-regulate genes to activate metabolic pathways. Thus, the current review discusses the mechanism of biotic elicitation and various elicitation techniques using biotic (proteins, carbohydrates, rhizobacteria, fungi, and hormones) elicitors that may increase the yield of secondary metabolites, particularly in medicinal plants, which is advantageous to the agrochemical and therapeutic industries. Full article