Abstract: Quantum computing exploits the principles of quantum mechanics to perform computation. Information is stored in qubits and processed with a sequence of quantum gates arranged as circuits. Verifying the correctness of quantum circuits is becoming essential as hardware scales in qubit count and architectural complexity. Traditional testing and naive simulation do not scale and quickly become computationally infeasible because the state space grows exponentially. This creates a strong need for more powerful and scalable verification techniques. Formal methods offer a viable solution by providing mathematically rigorous and scalable verification techniques that address these scalability challenges through abstraction, symbolic reasoning, and probabilistic guarantees. This study examines how formal methods are applied to quantum circuit verification. Specifically, four families of formal techniques: barrier certificates, abstract interpretation, model checking, and theorem proving are examined, along with the theoretical foundations and practical applications of these techniques. Finally, the study highlights open challenges and identifies promising directions for future research. An extensive set of references is included to support further study and exploration.

Abstract: With the evolution of the new power system, the importance of substation grounding network performance is increasingly prominent, the optimization of the old substation renovation work is also gradually into the right track and attention. In this paper, the impact of resistive coupling between the grounding network system and its surrounding underground metal pipe network system in the substation renovation project is explored and analyzed in depth, and the electromagnetic field model of the grounding network and the pipe network is established respectively by using the research method of field-circuit coupling and the two simulation software CDEGS and ETAP are integrated to focus on the changes in key performance parameters during the renovation of substation grounding network, and it is found that its resistive coupling effect leads to some fluctuations in the key performance parameters. Based on the above research content, a series of optimized protection measures suitable for the actual reconstruction project are further proposed, aiming at guaranteeing the safe and stable operation of the grounding system as well as the surrounding metal pipe network under fault conditions. This study provides a theoretical basis and practical technical support for the optimization of substation grounding network and similar projects.

Abstract: This paper investigates the implementation of lean practices in Singapore's manufacturing industry. The primary objective is to evaluate the adoption of lean methodologies across Singapore's precision manufacturing sector. To facilitate this assessment, questionnaires were distributed to companies of various sizes, including small and medium-sized enterprises and large corporations in Singapore. The results reveal that approximately 50% of manufacturers perceive adopting lean practices as challenging. Our study shows that most small and medium-sized enterprises (SMEs) face significant obstacles in implementing lean manufacturing practices. The findings indicate that barriers to implementation related to experience, skill sets, and knowledge pose considerable impediments. Furthermore, our research has established that management support is pivotal to effective lean implementation. Additionally, factors such as employee training, goal alignment, and the establishment of a supportive environment are significant contributors. While the use of tools and external expertise is relevant, internal resources and organizational culture are more important.

Abstract: Abstract The rally to mitigate growing carbon emissions and climate change necessitates decarbonization strategies, with hydrogen emerging as a key candidate option across multiple sectors. This literature review examines the current state of the road to the hydrogen economy, including production, implementation, and associated risks. Hydrogen's versatility in industry, transportation, and energy storage is highlighted, alongside the challenges of transitioning from fossil fuel-based production. It explores hydrogen's potential across various sectors, including transportation, industry, and energy storage, while acknowledging the challenges associated with its production, storage, and implementation. The review analyzes the current state of hydrogen technologies, differentiating between green, blue, and grey hydrogen production methods, and highlights advancements in production techniques like thermochemical water splitting. Key findings shows that while green hydrogen offers the cleanest pathway, high production costs and infrastructure limitations remain significant barriers to widespread adoption. The study also addresses safety concerns and public perception, emphasizing the need for robust risk assessment methodologies and management approaches. Furthermore, the review underscores the importance of technological innovations, such as high-temperature electrolysis and synergies with renewable energy sources, to enhance efficiency and sustainability. Policy recommendations include financial incentives, regulatory frameworks, and international cooperation to accelerate hydrogen adoption and balance its development with other low-carbon solutions.

Abstract: The simulation of synthetic aperture radar (SAR) echo signals usually relies on complex hardware equipment and a large amount of scene data, which results in high costs and low efficiency. In order to simulate SAR echo signals of ship targets in the sea quickly and accurately in complex environments at a lower cost, this paper proposes a SAR echo simulation method based on model segmentation and electromagnetic scattering characteristic simulation. This method first implements the simulation of sea models under different sea conditions based on PM wave spectrum model and Monte Carlo method, and segments them according to the requirements of simulation resolution. Then, it uses Python API in Blender to segment the ship model automatically and optimize the visible surface elements and mesh for each sub-model. Next, it uses Lua API in Feko to simulate the electromagnetic scattering characteristics of each sub-model of the sea surface and the ship target automatically, and obtains the required radar cross section (RCS) data of ship target in the sea after processing. Finally, SAR echo simulation is realized through time-domain algorithm. To further verify the simulation result, the chirp scaling (CS) algorithm is used for imaging processing. The results show that this method can realize SAR echo simulation of various ship targets under different sea conditions in a quick, accurate and cost-effective manner without the need for any hardware equipment.

Abstract: Fenton-based processes are widely used advanced oxidation methods known for degrading persistent pollutants. However, these techniques often generate significant amounts of iron-containing sludge, which poses environmental disposal challenges due to its complex composition. Furthermore, the sludge produced by the Fenton process contains high content of Fe(III) compounds, which can serve as an iron source to stimulate dissimilatory iron reduction (DIR), enhancing the performance of anaerobic digestion. Based on the characterization results from a previous study, this work investigated the use of the ferrous precipitate generated by the electrochemical peroxidation process applied to tannery wastewater treatment as an additive to enhance volatile fatty acids (VFAs) production during dark fermentation. The performance of ferrous precipitate (R-Fe₃O₄) was compared to that of conventional magnetite (Fe₃O₄) during dark fermentation under high organic loading conditions, emphasizing their potential to enhance hydrolysis efficiency and VFAs production yields, while promoting sustainable resource recovery and reuse within a circular bioeconomy framework. The results showed that the addition of both Fe₃O₄ and R- Fe₃O₄ significantly increased VFAs yields, with a predominance of long-chain fatty acids. The presence of CaCO₃ in the ferrous precipitate contributed to maintaining a stable pH environment, supporting microbial activity and enhancing the hydrolysis of soluble compounds. Moreover, the availability of essential micronutrients within the ferrous precipitate favoured greater microbial diversity. Consequently, the addition of R-Fe₃O₄ promoted VFAs production even at higher organic loading rates, suggesting a promising application of Fenton-based by-products as functional additives to improve the economic and environmental performance of the dark fermentation process.

Abstract: Artisanal and illegal gold extraction in ecologically sensitive tropical landscapes can generate persistent environmental damage and public fiscal liabilities that accumulate even under formal mining prohibitions. A decision-grade pipeline is presented that converts observable environmental signals into (i) spatial prioritisation surfaces, (ii) phase-timed remediation portfolios, and (iii) present-value (PV) comparisons of legislative policy pathways under uncertainty, demonstrated for the Crucitas mining landscape (Cutris, northern Costa Rica). Five linked models are implemented. Remote-sensing change proxies are derived using consistent baseline (January 2019–December 2020) and recent (February 2024–January 2025) windows; multi-criteria indices then produce a 0–100 grid-cell prioritisation surface integrating land, water, and hydrologic dimensions. This prioritisation output is translated into a phased remediation portfolio across 1,324 costed grid cells, yielding a gross liability of US$548.0 million (10-year PV; 5% discount rate). PSA-related credits total US$167.3 million PV; enforcing a cell-level non-negativity floor yields a baseline net PV of US$408.0 million (simple gross-minus-credits would be US$380.8 million). Deterministic policy overlays produce policy-adjusted net PV of US$336.1 million under Exp. 24.717 (minimum 5% royalty case; Δ = −US$71.9 million vs baseline; modeled royalty PV = US$93.8 million), US$418.6 million under Exp. 24.675 (Δ = +US$10.6 million), and US$421.7 million under Law No. 8904 (Δ = +US$13.7 million). Royalty-rate sensitivity cases for Exp. 24.717 yielded deterministic policy-adjusted net PV of US$242.3 million (10%) and US$148.5 million (15%). Monte Carlo propagation yields a right-tailed baseline distribution (P10–P90 = US$385.4–519.1 million; P50 = US$450.1 million), with exceedance probabilities P(>US$400 million) = 0.8357 and P(>US$500 million) = 0.1786. Policy-adjusted uncertainty bounds indicate substantially reduced exceedance risk under Exp. 24.717 (5% royalty case; P(>US$400 million) = 0.3491; P(>US$500 million) = 0.0169), with further reductions at higher take-rates (10%: P(>US$400 million) = 0.0408; P(>US$500 million) = 0.0007; 15%: P(>US$400 million) = 0.0027; P(>US$500 million) = 0.0000), and increased exceedance risk under non-mining pathways. The results support PV-consistent, uncertainty-aware ranking of contested pathways, with outcomes conditional on enforceable offsets, credible enforcement effectiveness, and residual-risk provisioning. The framework is transferable to other contested mining landscapes where phased interventions and policy alternatives require fiscally comparable evaluation.

Abstract: This study presents an in situ synthesis of a novel Manganese Ferrite/Carbon (MF/C) composite material via citrate sol–gel route followed by calcination in an inert argon (Ar) atmosphere. The structural and morphological and porosity properties were characterized using X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDX), and N2 gas physisorption analysis. Electrochemical evaluation of the MF/C in 3M KOH electrolyte in a three – electrode configuration showed a high specific capacity of 39.26 mAh g⁻¹ at 1 Ag⁻¹ and a rate capability of 69% at 5 Ag⁻¹ an equivalent series resistance (ESR) of 0.798 Ω. Subsequently, an asymmetric hybrid supercapacitor device (MF/C//AC) was fabricated using MF/C as the positive electrode and human derived activated carbon (AC) as the negative electrode. The assembled device exhibited remarkable performance with a wide operating voltage window of 1.4 V, a high sweeping potential of 1 V s⁻¹, a specific capacity, energy, power and maximum power of 42.4 mAhg⁻¹, 16.35Wh kg⁻¹, 1944W kg⁻¹ and 236 kW kg⁻¹, respectively and excellent capacitance retention of 92% after 15,000 charge–discharge cycles. The in-situ preparation approach significantly reduced synthesis time and cost compared to conventional multi-step methods as less equipment were required, while still achieving comparable or superior electrochemical performance to other supercacitors in literature.

Abstract: Industrial maintenance is increasingly software defined and interconnected through the internet of things, which forces a redefinition of uptime as cyber incidents begin to behave like unplanned downtime as per International Electrotechnical Commission (IEC) [1]. ISO/IEC 17025:2017 is a widely used standard for demonstrating laboratory competence in testing and evaluation across many industrial areas and disciplines [2]. Despite its long-standing and broad use, it remains under-documented and challenging when applied to cybersecurity testing. This is due in part to the nature of the business, which is highly fragmented and unique and must be treated differently from traditional laboratory activities. Cybersecurity testing has its own specific characteristics, in which software, hardware, cloud services and other components are tested individually or as integrated systems and solutions.

Abstract: Maritime transport is energy-efficient but remains heavily dependent on fossil fuels. Renewable electricity–based ammonia (e-NH₃) has emerged as a promising alternative, particularly through small-scale, modular production. Assessing its economic viability is essential for future adoption, and techno-economic analysis offers a structured way to evaluate its feasibility. This study investigates the cost performance of a small-scale offshore e-NH₃ plant of 2.4 tpd at the Port of Santander, Spain, based on nitrogen obtained via membrane separation and hydrogen from electrolysis of pretreated seawater. The results include process simulation outcomes obtained with ASPEN v14, a detailed cost breakdown based on modular costing methodologies applied to preliminary process designs, and sensitivity analyses of the levelized cost of e-NH₃ (LCOA) with respect to the variables that have the strongest influence on overall costs. A comparative review of LCOA values reported in the literature for offshore and onshore e-NH₃ plants is provided. An estimated CAPEX of 5.99 M€ (equivalent to 0.53 M€/y), OPEX of 1.58 M€/y, and a LCOA of 2408 €/tNH₃ are obtained, with equipment investment and operating costs identified as the most influential parameters. The results highlight the need for supraregional techno-economic studies, considering optimal offshore wind availability within a collaborative interregional framework.

Abstract: In an era of rapid urbanisation and climate challenges, understanding how urban land patterns contribute to resilience is crucial for sustainable development. This theoretical review introduces a novel framework positing that greater heterogeneity in plot sizes and land uses enhances urban resilience by promoting long-term preservation of built en-vironments, multifunctional spaces, and socio-cultural adaptability. Drawing on urban morphology, assemblage theory, and resilience science, we argue that fragmented ownership in small-plot fabrics acts as a barrier to large-scale redevelopment, fostering diversity that buffers against shocks. Through comparative case studies of Venice (Italy), Tokyo (Japan), Hong Kong, Mexico City (Mexico), and York (UK), we illustrate how historical small-plot subdivisions have endured centuries, supporting ecological, eco-nomic, and social resilience. The analysis reveals common patterns: ownership frag-mentation preserves fine-grained urban forms, enabling adaptive reuse (exaptation) and inclusivity. This paper addresses a gap in the literature by synthesising plot-level het-erogeneity with broader resilience outcomes, offering policy implications for protecting such fabrics amid global urbanisation pressures. Findings align with land system science, emphasising multifunctionality for regenerative urbanism.

Abstract: Post-disaster reconstruction processes generate extraordinary demand for construction materials, often requiring the rapid deployment of temporary industrial production systems. Among these, concrete plants represent critical logistical infrastructure but also significant sources of environmental pressure and public health risk. This study examines the ecological and health implications associated with temporary concrete production facilities operating in accelerated post-disaster rebuilding environments. Focusing on reconstruction conditions observed following the 2023 Kahramanmaraş earthquake sequence in southern Türkiye, the research applies a qualitative documen-tary-based environmental assessment framework integrating institutional reports, regulatory publications, reconstruction documentation, and established environmental engineering impact pathways. The analysis identifies key environmental exposure mechanisms, including particulate emissions, transport-related dust dispersion, slurry discharge risks, noise pollution, and intensive water and energy consumption, all of which collectively generate cumulative ecological and public health pressures in al-ready fragile post-disaster landscapes. The findings demonstrate that reconstruction speed, regulatory flexibility, and emergency industrial siting practices can structurally amplify environmental risks unless supported by integrated governance controls. The study proposes a sustainability-oriented reconstruction management framework em-phasizing strengthened environmental assessment procedures, controlled industrial siting, adoption of green production technologies, circular material recovery strategies, and community-level monitoring mechanisms. By conceptualizing temporary concrete production systems as environmental governance nodes rather than purely technical facilities, the research contributes a transferable analytical framework for managing ecological risks in large-scale disaster reconstruction contexts worldwide. Rather than interpreting post-disaster concrete production as a purely technical construction ne-cessity, this study conceptualizes temporary concrete plants as critical environmental governance nodes and provides a transferable analytical framework for managing eco-logical and public health risks in accelerated reconstruction systems worldwide.

Abstract: This work presents an investigation of two cooling systems used in additive friction stir depositions (AFSD) and the related effect on process temperature, feed material, and life of processing equipment. A new AFSD cooling system, Mazak MegaStir Liquid-cooled Toolholder (LCTH), was integrated onto MELD Manufacturing AFSD machines using both continuous and discrete material feeding systems. The LCTH is compared to the original MELD cooling system to understand how process temperatures are controlled by the cooling system, how feed material interacts with the process under different cooling conditions, and how well the cooling systems protect the equipment. It is shown that both the original MELD cooling system and the LCTH can deposit Al-Mg-Si alloy (AA6061) for large scale depositions. Four configurations of tool and cooling system are discussed. Configurations with short working face to cooling distances shows the best potential robust operation of AFSD at bulk scales.

Abstract: Despite the development of the new, modern non-metallic materials, the steel materials are largely used in various branches of industry, while in some applications they are still irreplaceable. It is expected that such a trend will remain for certain number of years. This is why the necessity is present for development of the new types of steels, which would possess even better properties. The Chromium-Molybdenum (Cr-Mo) steels, with high vanadium content, belong to the group of newer steels characterized by high values of hardness and toughness. In this research, the tests were performed on samples made from the X180CrMo12-1 steel with varying percentage of vanadium within the limits of 0.5-3%. Vanadium, as a carbide-forming alloying element, creates a carbide network of the M7C3 type around the metal matrix, and finely dispersed carbides of the V6C5 type within the metal matrix. This research was focused on determining the carbides’ composition, observing the shape of metal grains and carbide network, testing the material’s resistance to friction and wear, including the electrochemical characterization, as well. The objective was to determine the carbides microstructure and morphology, as well as to evaluate their impact on the material's characteristics. The experimental investigation was performed using the scanning electron microscopy with energy dispersive spectrometry (SEM-EDS) and X-ray diffractometric analysis (XRD). Examination of the carbide composition confirmed that it was the M7C3 carbide.

Abstract: Achieving meaningful reductions in residential heating demand requires design strategies that can respond to climate-specific solar availability and envelope performance. Although passive solar principles are well established, their effectiveness remains highly context-dependent, and simplified prescriptive approaches may not capture interactions across different climates. This study presents an AI-guided evolutionary optimization framework for passive solar residential design, focusing exclusively on the reduction in annual space heating demand under standardized assumptions. A standardized single-story residential prototype is simulated across three climatic contexts: hot–dry (Riyadh), temperate (Barcelona), and cold (Toronto). Dynamic building performance simulations are conducted using EnergyPlus, coupled with DesignBuilder’s built-in NSGA-II evolutionary optimization engine. Envelope-related variables, including the window-to-wall ratio, orientation, glazing configuration, and thermal mass, are optimized using a single objective: minimizing the annual heating load under idealized heating conditions. The results demonstrate substantial climate-dependent reductions in heating demand. In Toronto, the annual heating demand is reduced from approximately 16,900 kWh to 9600 kWh (≈43%). In Barcelona, a reduction from approximately 5650 kWh to 1990 kWh (≈65%) is achieved, while in Riyadh, heating demand is reduced from approximately 990 kWh to 39 kWh (>95%). The optimized solutions reveal distinct climate-specific design logic rather than universal passive rules. The results demonstrate that evolutionary optimization can support early-stage envelope design by revealing climate-specific heating strategies under clearly defined and comparable assumptions.

Abstract: Calcium silicate boards are widely used in passive fire protection systems due to their high structural stability and excellent thermal insulation performance under extreme temperatures. The fireproofing efficiency of such materials strongly depends on their thermophysical properties and structural configuration. In this study, the effects of density, thickness, and thermal conductivity on the fire insulation performance of three commercially available calcium silicate boards were systematically investigated by fire testing. Temperature evolution on the unexposed surface was monitored and validated through numerical simulations to predict how the fireboards behave under various heating conditions. In addition, the microstructural and physical properties of the boards were characterized and correlated with their fire performance. The simulation results show good agreement with experimental data, revealing that density, thickness, and thermal conductivity play a critical role in determining the fireproofing efficiency of calcium silicate boards.

Abstract: Energy management systems under dynamic electricity pricing require fast and cost-optimal control strategies for the optimization of flexible loads such as heating, ventilation, and air conditioning (HVAC) systems and refrigeration units. While Mixed-Integer Linear Programming (MILP) can compute theoretically optimal control trajectories, its practical application is limited due to computationally expensive optimization, leading to limited real-time applicability, and its dependence on accurate forecasts of electrical loads and other relevant time-series signals including disturbances. This paper proposes a supervised imitation learning (IL) framework that learns to imitate MILP-optimal setpoint trajectories for a conventional proportional (P) controller using only electricity price signals and temporal features. Our IL model predicts setpoint trajectories in an open-loop manner without direct state feedback and a subsequent conventional P-controller provides closed-loop robustness in a two-stage control structure. In this study, our approach is validated for electrical load shifting of a refrigeration system in an industrial warehouse, including a systematic benchmark of multiple IL models. MILP achieves a cost reduction of 21.07% relative to baseline and serves as a theoretical upper bound. Among IL models, sequence-based architectures achieve the highest savings, with Transformer and Long Short-Term Memory (LSTM) models closely approximating MILP behavior, reaching 19.33% and 19.28% respectively. A closed-loop reinforcement learning (RL) controller achieves 19.69% savings and is included as an additional benchmark, while heuristic strategies reach at most 14.43% savings. From a computational perspective, IL models enable fast training and real-time inference, with Transformer inference requiring 526 ns per prediction compared to 22.8 s for a single MILP optimization. This makes the proposed approach well suited for real-time and edge computing applications. Overall, the results demonstrate that the proposed supervised IL approach can achieve near-optimal control performance with substantially reduced computational effort, providing a scalable and cost-efficient solution for energy management.

Abstract: Background/Objectives: The Human Performance Envelope (HPE) is a multidimen-sional model that represents the range in which an individual operator's performance is acceptable or begins to become dangerous. Although several alternative models have been proposed, HPE currently remains primarily a theoretical concept. The goal of the study was therefore to translate this theoretical concept into practical applications, seeking to characterise and measure how HPE manifests itself in real-world contexts. Methods: Multivariate Autoregressive Models (MVAR) have been used in the analysis of complex systems in which variables are interdependent and mutually influence their dynamics over time. Professional Air Traffic Controllers (ATCOs) were involved in the study and asked to deal with realistic traffic scenarios while their behavioural, subjec-tive and neurophysiological data were collected. Partial Information Decomposition - Least Absolute Shrinkage and Selection Operator (PID – LASSO) model was then em-ployed to estimate the interactions among ATCO’s Human Factors (HFs) and identify the most appropriate characterisation of the HPE. Results: The results showed high and significant correlations among each ATCO’s performance and the corresponding neu-rophysiological – based HPE values. Furthermore, high-performance conditions (Best) were characterized by a significantly higher HPE values and a higher inter-HFs con-nections compared to low-performance (Worst) states. This suggested that a densely interconnected network of HFs is a prerequisite for operational resilience. Conclusions: The study provides the first application of a neurophysiological framework to model the causal interactions between HFs, translating the theoretical HPE into a quantifiable model validated against operator performance.

Abstract: This paper presents a nonlinear time-history re-assessment of an existing reinforced concrete (RC) frame building designed in 2007 according to the Romanian seismic code P100-1/2006 and re-checked against current seismic demand. Two three-dimensional solid finite-element models were developed in ANSYS: a bare RC frame and an RC frame with masonry infill panels. A distinctive feature is the explicit representation of longitudinal and transverse reinforcement embedded in the concrete solids, enabling direct tracking of steel stress demand and post-cracking load transfer. The models were subjected to bidirectional ground motions from the Vrancea 1977 and 1990 earthquakes and the Türkiye 2023 earthquake, scaled to match the P100-1/2013 target spectrum for the investigated site (a_g=0.40g). Modal analysis shows a clear stiffness increase due to infills, with the fundamental frequency rising from 4.4669 Hz (RC) to 5.8680 Hz (RC+M). Under the scaled records, infills substantially reduce global deformation demand: peak roof displacements in the transversal direction decrease from 9.87–14.26 mm (RC) to 2.74–3.38 mm (RC+M), and peak interstorey drift increments decrease from 3.35–4.94 mm to 0.92–1.16 mm, with drift ratios remaining well below conservative serviceability thresholds. Roof peak accelerations also decrease, reaching 0.490 g for RC versus 0.211 g for RC+M in the governing VN90 case. Base-reaction resultants and F_y–roof displacement loops confirm a stiffer global response with reduced displacement excursions for the infilled configuration. Local fields indicate that, in the bare frame, plastic strain concentrates at perimeter column bases and beam ends, while in the infilled model inelastic indicators shift toward masonry discontinuities around openings and panel corners; reinforcement demand peaks at beam ends, column bases, and the staircase region, consistent with torsional participation. The results highlight that masonry infills can strongly govern stiffness and drift demand at current design-level intensity, while introducing localised concentration zones that are relevant for performance assessment of existing buildings.

Abstract: The evolution of future Internet and sixth-generation (6G) networks is driving a paradigm shift from classical bit-centric communication toward meaning-aware and task-oriented communication models. Traditional information theory, while fundamental for ensuring reliable symbol transmission, does not account for semantic relevance or task effectiveness, which are critical for emerging applications such as autonomous systems, immersive services, and ultra-low-latency communications. This article presents a comprehensive review of Semantic Communications (SemCom) from a future Internet perspective. The review systematically analyses representative extensions of classical information theory aimed at quantifying semantic information, including semantic information measures, semantic channel capacity, and semantic rate–distortion formulations. In addition, the main mathematical and computational frameworks enabling practical semantic communication systems are examined, including the Information Bottleneck principle, learning-based end-to-end communication architectures, and reinforcement learning approaches for task-oriented optimization under network constraints. The review further discusses the role of semantic metrics, contextual modelling, and task-driven performance evaluation in the design of semantic-aware communication systems. The analysis identifies key open challenges, particularly the lack of a unified theoretical framework, the need for robust and context-aware semantic performance metrics, and the integration of semantic awareness into network-level design. Overall, this review highlights Semantic Communications as a promising paradigm for future Internet and 6G networks, where communication efficiency is increasingly determined by semantic relevance and task effectiveness rather than bit-level fidelity alone.