Abstract:

Hydrometallurgical pretreatment of pyrite-bearing concentrates and tailings by hydrothermal interaction with Cu(II) solutions is a promising route for chemical beneficiation and mitigation of acid mine drainage but is limited by passivation caused by elemental sulfur and secondary copper sulfides. Here, the effect of sodium lignosulfonate (SLS) on the hydrothermal reaction between natural pyrite and CuSO₄ in H₂SO₄ media at 180–220 °C was studied at [H₂SO₄]₀ = 10–30 g/dm³, [Cu]₀ = 6–24 g/dm³ and [SLS]₀ = 0–1.0 g/dm³. Process efficiency was evaluated by Fe extraction into solution and Cu precipitation on the solid phase, and products were characterized by XRD and SEM/EDS. SLS markedly intensified pyrite conversion: at 200 °C and 120 min Fe extraction increased from 14 to 26 % and Cu precipitation from 5 to 23 %, while at 220 °C Fe extraction reached 33.4 % and Cu precipitation 26.8 %. XRD confirmed the sequential transformation CuS → Cu_1.8S. SEM/EDS showed that SLS converts localized nucleation of Cu_xS on defect sites into the formation of a fine, loosely packed and well-dispersed copper sulfide phase. The results demonstrate that lignosulfonate surfactants efficiently suppress passivation and enhance mass transfer, providing a basis for intensifying hydrothermal pretreatment of pyrite-bearing industrial materials.

Abstract:

This paper presents a method for describing the differential equations of motion of mechanical systems using the Kuznetsov tensor. Traditional approaches to solving equations of motion rely on vector and matrix methods, but the proposed approach allows for significant simplification and generalization of problems by using a system state tensor. The paper discusses the main principles of working with the Kuznetsov tensor, which describes the evolution of the system in a unified context. Specifically, it outlines a method for integrating the equations of motion for various mechanical systems, such as oscillations in a two-mass spring system. Conditions for damping oscillations and controlling amplitude are also considered, expanding the applicability of the Kuznetsov tensor in engineering calculations. The advantages of the proposed approach include a more compact representation of the system of equations, ease of analyzing invariants and symmetries, and the ability to apply the method to multi-linked and multi-component systems. The use of the Kuznetsov tensor for modeling the dynamics of various systems represents a step toward a more universal approach in mechanics and engineering.

Abstract:

Background: Midlife is a period of heightened vulnerability to menopausal symptoms and body image concerns. However, little is known about how the experience of menopausal symptoms relates to the awareness of and attention toward internal body signals. Taking a dimensional approach, this study employed network analysis to examine how menopausal symptom domains relate to dimensions of interoceptive sensibility and body image in middle-aged women and identified the most influential and bridging features within this interconnected system. Methods: Two hundred and thirteen cisgender women aged 40–60 years residing in Ireland completed online measures of body appreciation (BAS-2), state body satisfaction (BISS), interoceptive sensibility (MAIA-2), and menopausal symptoms (Menopause Rating Scale). Results: Attention Regulation, Trusting, Body Appreciation, and Body Listening showed the highest expected influence. Body Appreciation emerged as the strongest bridge node, connecting interoceptive sensibility, body image, and menopausal symptoms. Trusting was negatively associated with psychological symptoms, whereas Noticing was positively associated with somatic symptoms. Regression analyses showed that lower body appreciation predicted greater somatic, urogenital, and psychological symptom severity, and lower Trusting predicted higher psychological symptom severity. Older age was associated with higher somatic and urogenital symptoms, while younger age was associated with higher psychological symptoms. Conclusions: Findings suggest that body appreciation and interoceptive trust are central, bridging processes in women’s experience of menopausal symptoms. Interventions that enhance body appreciation and interoceptive trust may help reduce psychological and physical symptom burden during the menopausal transition.

Abstract:

Background: Apelin-36 may be used to identify patients with ST-segment elevation myocardial infarction (STEMI) who are at risk for the no-reflow phenomenon. Patients presenting with STEMI were evaluated and stratified according to their apelin-36 levels. Methods: In this study, 161 patients presenting with STEMI within 12 hours of symptom onset and undergoing primary percutaneous coronary intervention (pPCI) were enrolled. Biochemical parameters, including apelin-36, troponin T, creatine kinase (CK), the MB fraction of creatine kinase (CK-MB), total cholesterol, triglycerides, and other routine laboratory parameters, were measured. Blood samples for apelin-36 measurement were collected prior to PCI, centrifuged to obtain serum, and preserved at -80⁰C until being assayed. Two-dimensional echocardiography was performed in all patients. Thereafter, patients were divided into two groups according to their level of Apelin-36. Results: Among the 161 consecutive STEMI patients, 115 (71.42%) had Apelin-36 levels ≤0.58ng/mL (group 1), whereas 46 (28.57%) had Apelin-36 levels >0.58ng/mL (group 2). In total, 51 (31.67%) STEMI patients experienced no-reflow phenomenon after PCI: 29 (18.01%) patients with apelin-36 ≤ 0.58ng/mL and 22 (13.66%) with a value > 0.58ng/mL (p < 0.001). In terms of Gensini score, the mean value in group 1 was (70.29 (±28.76), while in group 2, it was 81.95 (±23.82) (p=0.004). Overall, a positive correlation between apelin-36 and Gensini score was observed in both groups using Kendall’s correlation analysis (group 1: Figure 2, p=0.05; group 2: Figure 2, p<0.0001). Binary logistic regression analysis identified apelin-36 and diabetes mellitus as significant predictors at the 5% level, with p-values of 0.045 and 0.036, respectively. Patients with apelin-36 levels ≤ 0.58ng/mL had troponin T levels of 290.0 (8.5-9510.0), while those with a value > 0.58ng/mL had troponin T levels of 132.15 (9.4-5190.0) (p < 0.012). The receiver operating characteristics (ROC) curve of apelin-36 was used to plot the true positive rate against the false positive rate at different cut-off points, with AUC=0.67 (95% CI, 0.57-0.76), and the cut-off value for apelin-36 was 0.58ng/mL, with p=0.001. Conclusions: Significant associations were observed between apelin-36 and no-reflow phenomenon in patients with STEMI. An apelin-36 cut-off value of 0.58ng/mL, measured at admission, could be used to identify patients who were at increased risk of no-reflow phenomenon/reperfusion injury.

Abstract:

Anxiety and panic attacks are among the most prevalent mental health challenges today, significantly impacting individuals’ lives, emotional stability, and overall well-being. Despite the availability of effective therapeutic techniques many individuals struggle to apply these tools consistently, particularly during acute episodes. This gap reveals the need for accessible, personalized, and engaging digital interventions that support both prevention and crisis management. This article presents the design, development, and evaluation of a digital solution that leverages Virtual Reality (VR) to assist individuals in managing anxiety. To maximize user engagement, the solution incorporates gamification elements grounded in psychological principles. The prototype was evaluated through usability testing and qualitative feedback from both mental health experts and end-users. The results confirmed the high usability and therapeutic potential of the approach as participants reported increased feelings of calmness and being better able to cope with anxiety issues.

Abstract: Opinion mining is the process of analyzing the content people create, such as product reviews or social media posts, to determine if the feelings expressed are positive, negative, or neutral. Twitter, one of the most popular social platforms for sharing opinions, provides a lot of data that can be used to understand public sentiment. In this project, we developed a system for classifying sentiments that begins with a detailed preprocessing step using natural language processing techniques. After the data has been processed, the tweets are represented using the traditional Term Frequency-Inverse Document Frequency (TF-IDF) model to highlight the most important text features.To make these features even more relevant, we introduced the Egret Swarm Optimization Algorithm (ESOA), a method for selecting important features inspired by how Great and Snowy Egrets hunt. ESOA uses three strategies—waiting patiently, actively searching, and making decisions based on differences—to find a good balance between exploring new areas and focusing on known ones. This creates a flexible framework that works well in different situations. For sentiment classification, we use a Multi-Head Attention Mechanism (MHAM) that can understand various meanings in user text. We fine-tuned the model’s settings using the Dwarf Mongoose Optimization (DMO) algorithm, along with a strategy that helps each part of the attention mechanism focus on different aspects of the text. Testing our approach on the Sentiment140 dataset shows it works very well, achieving almost 97% accuracy, which is better than other methods that usually reach between 92% and 95%.

Abstract:

Kynurenic acid (KYNA) is a byproduct of the kynurenine pathway, which breaks down the amino acid tryptophan. KYNA acts as an antagonist of glutamate ionotropic excitatory amino acid (EAA) receptors and α7 nicotinic acetylcholine receptors (nAChRs). There is evidence that KYNA plays a significant role in various pathological conditions and the ageing process. It has also been suggested that KYNA contributes to memory impairment. This study investigated the impact of L-kynurenine, D-cycloserine, and Cerebrolysin on KYNA synthesis in the liver homogenate of Helix pomatia snails in vitro and in their ganglia in vivo. Furthermore, a memory model was established using these snails, wherein tentacle shortening served as an indicator of memory activity. In vitro experiments on Helix pomatia demonstrated the significant impact of L-kynurenine and anti-dementia drugs on KYNA synthesis. KYNA levels increased significantly in the presence of L-kynurenine, a bio-precursor, in liver homogenate. However, KYNA formation decreased when anti-dementia drugs, including Cerebrolysin or D-cycloserine, were administered to the snails’ liver homogenate. L-kynurenine has been shown to impair memory in vivo in snails, but an anti-dementia drug has been demonstrated to reverse this effect. Significant inhibition of tentacle lowering was observed in response to L-kynurenine treatment, which corresponded with elevated KYNA levels in the central nervous system. Administering D-cycloserine or Cerebrolysin alongside L-kynurenine reversed its effects. The Helix pomatia memory model is a valuable tool for studying learning and memory in various conditions and in the presence of different pharmacological agents. A drug or natural extract that blocks KYNA synthesis could be considered an anti-dementia agent. It may also protect against ageing and delay damage to the central nervous system related to memory.

Abstract: Mining activities generate vast quantities of waste each year, including mine tailings, bauxite residue, waste rock, and various metallurgical slags. Although these materials have traditionally been regarded as environmental liabilities, many possess physical and chemical properties that make them promising candidates for use in construction. This review synthesizes recent research on the utilization of major mining waste streams, with particular emphasis on pavement applications and other construction materials. The findings indicate that bauxite residue exhibits both pozzolanic and filler characteristics, demonstrating potential in asphalt mastics, asphalt mixtures, and other construction products. Nonetheless, its widespread adoption is constrained by issues such as high alkalinity, leaching risks, and concerns related to naturally occurring radioactivity. Mine tailings can substitute for fine aggregates and cement in a range of mixtures, though challenges including pronounced material variability and environmental risks persist. Waste rock offers favourable geotechnical properties for use in road bases and embankments, while metallurgical slags (e.g., copper, nickel, and lithium slags) provide functional pozzolanic activity and suitable aggregate qualities. Across all waste types, their incorporation into construction materials can conserve natural resources, reduce material costs, and support circular-economy and low-carbon development objectives. However, progress remains contingent upon advancements in material standards, pretreatment technologies, environmental protection measures, and large-scale field validation. Overall, this review underscores both the significant potential and the practical challenges associated with transforming mining waste into valuable and sustainable construction resources.

Abstract: Cannabidiol (CBD) is one of the most studied compounds of Cannabis sativa plant that gained much interest due to its therapeutic and beneficial properties, which have been confirmed in numerous preclinical and clinical studies over the last few years. A great advantage of CBD over the other widely known Cannabis sativa ingredient, Δ-9-tetrahydrocannabinol (THC), is that CBD does not exert intoxicating and psychoactive effects, making it an attractive candidate for therapeutic applications in neurological disorders. CBD has been proven to exert anti-oxidative, analgesic, anti-inflammatory, and neuroprotective effects that may serve as a therapeutic promise for various neurological conditions. To date, the only drug that consists solely of highly purified CBD is Epidiolex, which is used in the management of severe forms of epilepsy such as Dravet syndrome and Lennox-Gastaut syndrome. Another legal medication containing CBD (however with the addition of THC) is Sativex, used to alleviate spasticity in multiple sclerosis. Besides epilepsy, preclinical data suggest that CBD alone may be potentially beneficial in treating chronic pain, multiple sclerosis, Alzheimer's and Parkinson's diseases, or stroke. The safety profile of CBD is generally considered favorable, as the most commonly reported adverse effects are mild (e.g., somnolence, diarrhea). However, much attention should be paid as CBD-driven drug-drug interactions have been reported. This review article aims to assess the outcomes from already conducted preclinical and clinical research exploring CBD's effects in various neurological conditions, while also addressing potential risks and concerns related to its use.

Abstract:

Objective: To investigate the mediating role of career flexibility in the relationship between strategies for coping with career indecision and career distress among university students, and to conduct a psychometric validation of the Persian version of the Career Flexibility Inventory (CFI). Method: A two-phase, cross-sectional study was conducted with a sample of 517 Iranian university students. Phase one involved a Confirmatory Factor Analysis (CFA) to validate the CFI. Phase two tested the proposed mediation model using Structural Equation Modeling (SEM) with a bootstrapping procedure. Findings: The CFA confirmed th)e psychometric soundness and three-factor structure (Wavering, Adaptation, Flexible Thinking) of the Persian CFI, with excellent model fit (CFI = .975, RMSEA = .036). SEM results revealed that career flexibility partially mediated the relationship between coping strategies and career distress. Productive coping was associated with lower distress indirectly through its positive effect on Adaptation (Standardized Indirect Effect = –.124), while nonproductive coping was linked to higher distress indirectly through its positive effect on Wavering (Standardized Indirect Effect = .106). Conclusion: Career flexibility is a crucial mechanism explaining how coping strategies influence career distress; productive coping enhances active flexibility (Adaptation) to reduce distress, whereas nonproductive coping fosters passive flexibility (Wavering) that exacerbates it. The study provides a validated instrument for the Iranian context and highlights the importance of designing career interventions that build adaptive flexibility, rather than merely targeting distress.

Abstract: Bacteriophages, the most abundant and genetically diverse biological entities, have much of their diversity unexplored. Wastewater systems with intact microbial com-munities serve as reservoirs for diverse phages. This study recovered complete phage genomes from rural wastewater metagenomes to assess their genetic diversity. Meta-genomic sequences from six wastewater samples were assembled, viral contigs identi-fied using PHASTEST, yielding 17 high-confidence phage genomes. These were anno-tated and compared via pangenome analysis, gene-sharing networks, phylogenetic re-construction, and average amino acid identity. Heaps’ law and UpSet plots quantified pangenome openness and gene family intersections. The 17 phage genomes encoded 30–172 proteins each, sharing no core genes. Of 1,031 gene families, 98.7% were “cloud” and 94% unique, with only 13 “shell” families in >2 phages. Most shared no genes (average Jaccard similarity < 1%), 15 appearing as isolated nodes in networks. Phylogenetic trees exhibited star-like topology, reflecting distinct paths. The pange-nome was open (Heaps’ law α ≈ 0.026), with minimal overlap confirmed by UpSet, and ancestral reconstruction indicated stable genomes with occasional gains. In conclusion, bacteriophages exhibit extreme genomic diversity even in one environment, each ge-nome largely unique, highlighting the immense uncharted phage diversity and sup-porting high diversity in varied habitats.

Abstract: Background/Objectives: Thymic epithelial tumors (TETs) are rare, histologically heterogeneous neoplasms lacking robust molecular biomarkers. Hippo pathway dysregulation—driving YAP1/TEAD-dependent transcription—has been implicated across cancers, but transcript-level data in TETs are limited. Methods: We retrospectively profiled 26 formalin-fixed, paraffin-embedded (FFPE) specimens by SYBR real-time quantitative polymerase chain reaction (RT-qPCR) among different World Health Organization (WHO) subtypes with the focus on the hippo kinase core targets YAP1, TEAD4, MST1/STK4, SAV1, LATS1, and MOB1A. Expression was normalized to the geometric mean of HPRT1and TBP and summarized as 2^-ΔΔCq [log₂ fold changes (FC)] relative to pooled normal. Group differences were tested non-parametrically. Results: YAP1 and TEAD4 were upregulated across tumors, most prominently in type A (YAP1 ≈+3.43) and B3 (YAP1 ≈+2.78) thymomas, with TEAD4 strongly increased in thymic carcinoma (TC) (≈+3.49) and elevated in type A/B3. Upstream kinases were reduced, particularly in TC (MST1 ≈−1.38; LATS1 ≈−1.34), and modestly in B1. SAV1 was elevated in type A (≈+2.25) and B3 (≈+2.01), while MOB1A remained near baseline with slight subtype shifts. Differential expression among WHO subtypes was significant for YAP1 (p = 0.003), TEAD4 (p = 0.015), SAV1 (p = 0.004), MST1 (p = 0.012), and LATS1 (p = 0.036, all Kruskal–Wallis), but not for MOB1A (p = 0.09). Conclusions: TETs exhibit subtype-dependent Hippo pathway alterations, characterized by enhanced YAP1–TEAD4 transcriptional output and progressive reduction of the MST1/LATS1 kinase module, most pronounced in TC. These transcript-level patterns support the potential of Hippo-based biomarkers and may guide future therapeutic strategies.

Abstract: This study analyzes the provisioning strategy of the European Scops Owl (Otus scops) via continuous video monitoring of a breeding pair in a Mediterranean ecosystem (N = 724 deliveries). Invertebrates dominated numerically, with Orthoptera constituting 64.6%. Although vertebrates were scarce (1.8%), they contributed disproportionately to total biomass (20.8%), with rodents alone accounting for 20.3% of delivered energy. Parental effort followed a bimodal nocturnal rhythm, peaking at darkness onset (22:00 h) and before dawn. Crucially, we found a significant predation bias towards female orthopterans (65.6% vs. 34.3%; p < 0.001). While driven by Meconema thalassinum, selection in larger species like Tettigonia viridissima evidences a strategy focused on biomass profitability. Since Ensifera biomass scales allometrically (W ~ L^2.797), selecting females yields disproportionate energetic gains. We also report the systematic removal of ovipositors prior to delivery, a behavior that optimizes intake but renders high-value females undetectable in traditional pellet analyses. These results suggest O. scops exploits artificial light sources ("streetlight traps") to maximize foraging efficiency.

Abstract: This study introduces the Three-Line Heuristic Framework (TLHF) as a descriptive, multi-actor lens for AI-enabled smart-tourism governance. It conceptualizes three recurring trajectories: (i) government credibility rises once transparency becomes visible, (ii) firm-side trust stabilizes as efficiency gains taper, and (iii) user confidence accumulates through familiar, low-friction use. Satisficing Equilibrium (SE) denotes a mid–high adequacy band in which participation and perceived trust cluster once minimum transparency and usability thresholds are perceived as “good enough,” without implying optimality, causality, or a game-theoretic solution. A mixed-method design integrates a cross-national online survey (N = 1,590; replication = 1,840) and 35 institutional interviews. Kernel-density and LOESS diagnostics visualize distributional concentration, while binary logit with Average Marginal Effects (AME) summarizes associative patterns. Information Control Level (ICL) is treated as a formative composite with low local VIFs (≈ 1.03–1.10). Results are consistent with the TLHF/SE interpretation: the Positive Index is positively associated with safe-platform preference (Q8) (p < 0.05; AME ≈ +3.2 pp), whereas privacy concern and AI-use breadth are not significantly negative once visibility cues are included. The mid–high adequacy concentration remains visually robust under ±25% smoothing and across both datasets. The dataset is Asia-anchored and China-dominant (≈84%); findings are therefore descriptive and bounded. Overall, the evidence suggests that sustainable AI governance in tourism may be supported less by maximal regulation than by credible transparency, dependable service quality, and low-friction usability, with implications for SDGs 8, 12, and 17.

Abstract: BackgroundVertebral fractures are among the most common and clinically important outcomes of osteoporosis in older adults. They significantly contribute to pain, functional limitations, and a decline in quality of life. A significant proportion of these fractures remain clinically silent or present with vague symptoms, which often delays diagnosis. As a result, imaging plays a central role in detection. Distinguishing uncomplicated osteoporotic fractures from those caused by malignancy or infection is essential, as missed or delayed recognition may lead to inappropriate management and avoidable neurological complications.AimThis review aims to outline the typical radiological patterns of vertebral fractures in the elderly and to highlight key imaging “red flag” features that raise suspicion of secondary pathology or structural instability.MethodsA narrative review of the literature was conducted, drawing on published studies that address the epidemiology, imaging appearances, and management of vertebral fractures. The discussion focuses on the role of PET/CT, computed tomography, magnetic resonance imaging, nuclear medicine, and PET/CT, with particular attention to imaging features that help distinguish benign osteoporotic fractures from pathological fractures.ResultsPlain radiographs are useful for identifying vertebral deformity but have limited value in differentiating acute from chronic fractures. Computed tomography allows a more accurate assessment of cortical disruption, fracture morphology, and retropulsed fragments. Magnetic resonance imaging remains the reference standard for characterising vertebral fractures, as marrow signal changes, soft-tissue components, and posterior element involvement reliably separate benign from malignant causes. Nuclear medicine studies assist in assessing fracture chronicity, while PET/CT helps differentiate metastatic disease from benign lesions. Imaging features that should prompt concern include paraspinal soft-tissue masses, involvement of posterior elements, multiple contiguous vertebral lesions, and a convex posterior vertebral body margin.ConclusionCareful recognition of typical imaging patterns and associated red flag signs is fundamental in differentiating benign osteoporotic vertebral fractures from secondary causes. Accurate and timely diagnosis helps in appropriate management, minimises neurological complications, and ultimately improves outcomes in elderly patients.

Abstract:

The increasing use of integrated renewable energy sources (RES) is undoubtedly reshaping the structure of power systems. In such conditions, achieving energy efficiency and sustainability requires the development and integration of digital solutions to manage energy flows and resources optimization. This paper aims to provide a comprehensive overview of the successful integration of artificial intelligence (AI) in the energy sector, particularly in relation to the increasing utilization of renewable energy. The paper presents trends and potential scenarios in the digitalization of energy, along with the associated challenges. It analyzes particular applications of AI tools in strategic areas of the energy sector. The article also attempts to summarize the current status, goals, key areas, and activities in the irreversible transformation of power structures into digital intelligent ones. Five key areas in the energy sector have been identified in which AI tools are applied.

Abstract: The high-frequency divergence problem (ultraviolet catastrophe) encountered when the traditional Rayleigh-Jeans formula explains blackbody radiation originates from three fundamental errors in its theoretical derivation: first, the erroneous assumption that all electromagnetic standing wave modes satisfy the equipartition theorem; second, the failure to distinguish between "stationary modes" and "radiation modes" in electron motion; third, the misapplication of the equipartition theorem—suited for continuous quadratic systems—to the electromagnetic radiation process that is essentially a continuous energy transfer. This paper is based on the revised classical electrodynamics theory proposed by Zeng Jiqing [1], which posits that electrons radiate or absorb energy only when their frequency changes (during accelerated or decelerated motion), and that this process is continuous in terms of energy. We introduce the minimum energy unit ε (numerically equal to Planck's constant h) as a unit of measurement for energy transfer, used to quantify the continuous energy flow corresponding to a unit change in electron frequency [1,2]. Based on this, we re-derive the radiation energy density formula, which naturally exhibits exponential decay behavior in the high-frequency region, successfully eliminating the ultraviolet catastrophe and fully aligning with experimental observations. A comparison with Planck's quantization hypothesis shows that the "quantized" characteristics of the blackbody radiation spectrum can be explained entirely within a purely classical physics framework, without the need to introduce discrete energy packets or quantum hypotheses.

Abstract: This article discusses the process of spreading harmful impurities from traffic congestion. The process of spreading harmful impurities is considered by a three-dimensional model. The simulation of the spread of harmful impurities from traffic congestion is given, and algorithms for solving the three-dime nsional diffusion problem by the recurrent operator method are also given. In previous studies, we also used the recurrent operator method. The solution of the three-dimensional linear differential diffusion equation is sought in the form of a series. Where this series is inserted into each term of the linear differential equation, then making the indices shift in accordance with the recurrent operator method and taking out the common multiplier, we obtain the recurrent equation. Based on this recurrent equation, the coefficients of the series are searched for. Turning to the procedures for finding the coefficients of a series in the Maple software environment, the calculation of finding the coefficients was performed. Next, inserting the found coefficients into a series, we get the sum, which leads to a simpler solution convenient for differentiation. Further, partial derivatives in spatial coordinates are found based on software procedures in Maple. With this approach, the general solutions are expressed in terms of arbitrary functions and are not related to the solution of another equation. The obtained simulation results are shown in tables and illustrated in figures which are also obtained in the Maple software environment.

Abstract:

The accelerated digitalization of industrial ecosystems has positioned the Internet of Things (IoT) as a critical enabler of corporate sustainability within Industry 4.0. However, evidence on how IoT contributes to environmental, social, and economic performance remains fragmented. This study conducts a systematic literature review following PRISMA 2020 guidelines to consolidate the scientific advances linking IoT with sustainable corporate management. The search covered 2009–2025 and included publications indexed in Scopus, EBSCO Essential, and MDPI, identifying 62 empirical and conceptual studies that met the inclusion criteria. Bibliometric analyses—such as keyword co-occurrence mapping and temporal heatmaps—were performed using VOSviewer to detect dominant research clusters and emerging thematic trajectories. Results reveal four domains in which IoT significantly influences sustainability: (1) resource-efficient operations enabled by real-time sensing and predictive analytics; (2) energy optimization and green digital transformation initiatives; (3) circular-economy practices supported by data-driven decision-making; and (4) the integration of IoT with Green Human Resource Management to strengthen environmentally responsible organizational cultures. Despite these advances, gaps persist related to Latin American contexts, theoretical integration, and longitudinal assessment. This study proposes a conceptual model illustrating how IoT-enabled technologies enhance corporate sustainability and offers strategic insights for aligning Industry 4.0 transformations with the Sustainable Development Goals, particularly SDGs 7, 9, and 12.

Abstract:

Mycelium-based composites (MBCs)—biomaterials made from fungal-inoculated substrates—are promising candidates to replace conventional materials for thermal insulation. However, many MBCs are made from hemp, a plant material that is quite difficult to source in many countries for regulation reasons, and mobilizes agricultural field at the expense of food and feed crops. Meanwhile, many of our natural and urban ecosystems are subject to invasion by plants that are just burnt or even left on place, while they may be very good substrate for MBCs. This study investigated the comparative physical and thermal properties MBCs derived from two distinct lignocellulosic feedstocks: hemp shives (a traditional material) and biomass from the highly invasive species Reynoutria japonica. Polyisocyanurate (PIR) was included as a synthetic benchmark. The MBCs produced from R. japonica demonstrated as low thermal conductivity as hemp MBCs, but also as the PIR standard. However, they exhibited suboptimal physical characteristics: higher bulk density (166 vs 128 kg/m3 for hemp) and significantly greater water absorption (7.5% vs 3.5%volume uptake after 2 minutes). This suggest that they are a less viable alternative to hemp-based MBCs for heat insulation applications.