Search Results (1,194)

A rapidly emerging approach within the scientific community involves the utilization of waste streams for renewable energy generation, particularly through biomethane production. A key aspect of this approach lies in the co-digestion of diverse waste streams, which can enhance process efficiency and contribute to a more effective reduction in the organic load. The present study investigates the anaerobic digestion of a mixture of food waste leachates and dairy waste (cheese whey wastewater), with a dual objective: to evaluate the reduction in organic-load efficiency of the mixed substrate and to assess the production of biogas enriched in biomethane content. Three distinct mixing ratios by volume of the two waste streams (25%/75%, 50%/50% and 75%/25%) were subjected to an anaerobic digestion process under the same SIR. The performance of each mixture was assessed in terms of both reduction in organic-load efficiency and biomethane yield, followed by a comparative analysis to identify the optimal mixing ratio. The results indicate that while the organic-load reduction remains consistently effective across all mixing ratios, the biomethane production potential is notably higher for the 25%/75% waste mixture, highlighting it as the most promising configuration for both energy recovery and waste treatment efficiency. Full article

Estimating runoff in ungauged catchments remains a major challenge in hydrology, particularly in remote Andean headwaters where limited accessibility and budgetary constraints hinder the long-term operation of monitoring networks. This study integrates satellite-derived rainfall data, hydrological modeling, and benthic macroinvertebrate diversity analysis to explore how short-term antecedent flow conditions relate to temporal variation in community structure. The research was conducted in a pristine 0.26 km² micro-catchment of the upper Collay basin (southern Ecuador). Daily simulated discharge was used to compute antecedent flow descriptors representing short-term variability and cumulative changes in stream conditions, which were related to taxonomic (i.e., H = Shannon diversity, E = Pielou evenness, and D = Simpson dominance) and functional indices (i.e., Rao = Rao’s quadratic entropy, FAD1 = Functional Attribute Diversity, and wFDc = weighted functional dendrogram-based diversity) using Generalized Additive Models. Results showed progressively higher hydrology–biology associations with increasing antecedent flow integration length, suggesting that biological variability responds more strongly to cumulative than to instantaneous flow conditions. Among hydrological descriptors, the cumulative magnitude of negative flow changes was consistently associated with taxonomic diversity. H and E showed more coherent and robust patterns than functional metrics, indicating a faster response of community composition to short-term hydrological variability, whereas functional diversity integrates slower ecological processes. While based on modeled discharge under severe hydrometeorological data limitations, this study provides a practical ecohydrological starting point for identifying short-term hydrological memory signals potentially relevant to aquatic biodiversity in ungauged headwater systems. Full article

This paper proposes a novel photonic crystal fiber-based 1 × 3 optical drop multiplexer design. According to numerical simulations, optical signals can be injected on the left core and divided into another core at various distances to separate the optical signals in a photonic crystal fiber structure. Throughout the length of the fiber, the innovative design controls the direction of light transmission between layers by alternating between multiple air-hole positions using pure silica layers. The optical systemic communications industry cannot function without wavelength multiplexers/demultiplexers. They function as a data combiner/separator. By employing an optical add-drop multiplexer, it becomes possible to add or remove signals from a stream of multiplexed signals without the need to be concerned about any potential interference with the existing signals, even when they are traveling at varying on-axis distances. This study provides findings about small optical drop multiplexers for fiber-to-the-home applications employing photonic crystal fiber at wavelengths of 0.85, 1.45, and 1.2 µm. Full article

In the proper management of construction, the use of BIM software allows for tracking of the entire lifecycle of buildings, enabling informed design and better management of the product lifecycle, easier collaboration among professionals, and a more efficient system. The combination of BIM tools and today’s information technologies allows the advantages of the BIM methodology to be amplified and expanded. In particular, creating a 3D model with BIM software and linking it to a data stream from sensors allows us to obtain a key component for a Digital Twin of a construction. By integrating BIM methodologies and Digital Twins, this manuscript describes the development of a Digital Twin prototype of a highway bridge, with a 3D model of the structure reproduced using BIM software serving as the core of the Digital Twin. To complete the Digital Twin architecture, an ADXL345 accelerometer sensor, a DTH22 humidity and temperature sensor, an ESP32 microcontroller, the Postgres database, Python (for communication between the backend and the frontend), and the JavaScript library CesiumJS were employed. This methodology produced a Digital Twin prototype capable of collecting vibration and temperature data from the previously mentioned sensors and displaying values through a graphical interface. It can be observed how this technology represents an expansion of the capabilities of BIM software, also highlighting the maintenance potential throughout the product lifecycle. Moreover, the technologies used make the methodology scalable, allowing additional BIMs to be added or the methodology to be applied in different contexts. Full article

This article presents an ontology-driven Digital Twin (DT) for hotel front-desk operations that fuses two real-time data streams: (i) physiological and activity signals from wrist-worn wearables assigned to staff, and (ii) 3D people-positioning and occupancy events captured by reception-area cameras using a proprietary implementation of Optical Camera Communication (OCC). Building on a previously proposed front-desk ontology, the semantic model is extended with positional events, zone semantics, and wearable-derived workload indices to estimate queue state, staff workload, and service demand in real time. A vendor-agnostic, property-based REST API specifies the DT interface in terms of observable properties, including authentication and authorization, idempotent ingestion, timestamp conventions, version negotiation, integrity protection for signed webhooks, rate limiting and backoff, pagination and filtering, and privacy-preserving identifiers, enabling any compliant backend to implement the specification. The proposed layered architecture connects ingestion, spatial reasoning, and decision services to dashboards and key performance indicators (KPIs). This article details the positioning pipeline (calibration, normalized 3D coordinates, zone mapping, and confidence handling), the wearable workload pipeline, and an evaluation protocol covering localization error, zone classification, queue-length estimation, and workload accuracy. The results indicate that a spatially aware, ontology-based DT can support more balanced staff allocation and improved guest experience while remaining technology-agnostic and privacy-conscious. Full article

The integration of extended reality (XR) into industrial robotics requires robust middleware solutions capable of bridging heterogeneous systems, protocols, and user interactions. This paper presents a novel middleware framework designed to connect industrial robots with XR devices such as the HoloLens. The architecture employs a hybrid communication layer that combines MQTT (Message Queuing Telemetry Transport) and ØMQ (Zero Message Queue), leveraging the Sparkplug Robotics API model for robot data and publisher–subscriber streaming for XR camera feeds. A Redis cache database is introduced to ensure efficient data handling and prevent data corruption. On the robot side, the system is built on ROS 2 (Robot Operating System) and connects to proprietary industrial protocols through dedicated bridges, enabling seamless interoperability. Spatial alignment between physical robots and XR overlays is achieved using ArUco marker-based synchronization, while real-time kinematic and process data are visualized directly in XR. The middleware further supports bidirectional interaction, allowing users to adjust parameters and issue commands through XR devices. Beyond functionality, safety considerations are incorporated by integrating human–robot interaction safeguards and ensuring compliance with industrial communication standards. The proposed solution demonstrates how middleware-driven XR integration enhances transparency, control, and safety in robotic manufacturing processes, laying the foundation for greater efficiency and adaptability in Industry 4.0 environments. Full article

Whey and its permeates constitute highly organic, low-alkalinity dairy streams whose management remains suboptimal in many processing facilities. This narrative review integrates recent evidence on the anaerobic digestion (AD) of whey, linking substrate composition and biodegradability with microbial pathways, inhibition mechanisms, biogas quality, and techno-economic and environmental feasibility in industrial settings. Data for sweet whey, acid whey, and their permeates are synthesized, with emphasis on operational windows, micronutrient requirements, and co-digestion or C/N/P/S balancing strategies that sustain resilient methanogenic communities. Options for biogas conditioning and upgrading towards combined heat and power, boiler applications, and compressed or liquefied biomethane are examined, and selection criteria are proposed based on impurity profiles, thermal integration, and methane-recovery performance. Finally, critical R&D gaps are identified, including mechanistic monitoring, bioavailable micronutrition, modular upgrading architectures, and the valorization of digestate as a recovered fertilizer. This review provides an integrated framework to guide the design and operation of technically stable, environmentally verifiable, and economically viable whey-to-biomethane schemes for the dairy industry. Full article

The rapid proliferation of connected vehicles equipped with both Vehicle-to-Vehicle (V2V) sidelink and cellular interfaces creates new opportunities for real-time vehicular applications, yet achieving ultra-reliable communication without prohibitive cellular costs remains challenging. This paper addresses reliable inter-vehicle video streaming for safety-critical applications such as See-Through for Passing and Obstructed View Assist, which require stringent Service Level Objectives (SLOs) of 50 ms latency with 99% reliability. Through measurements in Seoul urban environments, we characterize the complementary nature of V2V and Vehicle-to-Network-to-Vehicle (V2N2V) paths: V2V provides ultra-low latency (mean 2.99 ms) but imperfect reliability (95.77%), while V2N2V achieves perfect reliability but exhibits high latency variability ($P_{99}$: 120.33 ms in centralized routing) that violates target SLOs. We propose a hybrid framework that exploits V2V as the primary path while selectively retransmitting only lost packets via V2N2V. The key innovation is a dual loss detection mechanism combining gap-based and timeout-based triggers leveraging Real-Time Protocol (RTP) headers for both immediate response and comprehensive coverage. Trace-driven simulation demonstrates that the proposed framework achieves a 99.96% packet reception rate and 99.71% frame playback ratio, approaching lossless transmission while maintaining cellular utilization at only 5.54%, which is merely 0.84 percentage points above the V2V loss rate. This represents a $7\times$ cost reduction versus PLR Switching (4.2 GB vs. 28 GB monthly) while reducing video stalls by $10\times$. These results demonstrate that packet-level selective redundancy enables cost-effective ultra-reliable V2X communication at scale. Full article

Sustainable packaging has become a major area of academic and practical interest, reflecting growing environmental awareness, regulatory pressure, and changing consumer expectations. This study aims to synthesize existing knowledge on consumers’ behavior toward sustainable packaging and their willingness to pay (WTP) for environmentally friendly solutions. Following PRISMA guidelines, a systematic literature review was conducted, encompassing 78 peer-reviewed publications from 2019 to 2025. Bibliometric mapping using VOSviewer (version 1.6.20) identified three main research streams: consumer attitudes and determinants of behavior, willingness to pay for sustainable packaging, and perception of packaging materials and systems. The reviewed studies, conducted across Europe, Asia, Australia, and North America, employed diverse methods, including surveys, discrete choice experiments, structural equation modeling, and mixed designs. Results indicate that consumer behavior is shaped by environmental awareness, self-identity, perceived usefulness, and trust in labeling, while packaging material and functionality remain decisive for acceptance. Most studies show that consumers are willing to pay a premium of about 10–20% for sustainable packaging, though price sensitivity and hygiene concerns limit actual adoption. The findings highlight the conditional nature of consumer acceptance and emphasize the need for transparent communication, credible certification, and functional design. This study provides guidance for policymakers and businesses seeking to promote sustainable packaging solutions. Full article

Laboratory and field investigations were used to assess the toxicity of leachate from a closed sanitary landfill on benthic macroinvertebrates in coldwater trout streams located near a landfill in southeastern Minnesota, USA. Field-collected invertebrates were exposed to a range of concentrations (0–100%) of leachate during a series of 24 h and 7-day laboratory toxicity tests. Benthic macroinvertebrates also were collected from two stream sites on either side of the landfill and at a third site downstream to assess potential pollution exposure of the stream communities. Ten different taxa exposed to 100% leachate for 24 h exhibited survival ranging from 0 to 100%, with survivorship not correlated to published invertebrate pollution tolerance values. More extensive 24 h tests with the least tolerant Brachycentrus caddisfly larvae found 100% mortality at leachate concentrations > 70%, with the first mortalities observed after 3 h. Brachycentrus had 100% survival at leachate concentrations < 40%. During 7-day tests, Brachycentrus had 100% survival at all leachate concentrations of 40% and lower, but all Brachycentrus died after 2 days at concentrations of 60% and higher. Instream benthic communities, averaging 12 to 17 different taxa at the various stream sites, were rated from good to excellent based on biotic index values, with intolerant taxa present at all three stream sites. Landfill leachate has not impacted the benthic invertebrate communities in streams nearby, but leachate at higher concentrations has the potential to be toxic to a variety of local taxa. Full article

In complex wireless communication environments, automatic modulation classification (AMC) faces two critical challenges: the lack of robustness under low-signal-to-noise ratio (SNR) conditions and the inefficiency of integrating multi-scale feature representations. To address these issues, this paper proposes CAIC-Net, a robust modulation classification network that integrates a dynamic cross-attention mechanism with a cross-SNR contrastive learning strategy. CAIC-Net employs a dual-stream feature extractor composed of ConvLSTM2D and Transformer blocks to capture local temporal dependencies and global contextual relationships, respectively. To enhance fusion effectiveness, we design a Dynamic Cross-Attention Unit (CAU) that enables deep bidirectional interaction between the two branches while incorporating an SNR-aware mechanism to adaptively adjust the fusion strategy under varying channel conditions. In addition, a Cross-SNR Contrastive Learning (CSCL) module is introduced as an auxiliary task, where positive and negative sample pairs are constructed across different SNR levels and optimized using InfoNCE loss. This design significantly strengthens the intrinsic noise-invariant properties of the learned representations. Extensive experiments conducted on two standard datasets demonstrate that CAIC-Net achieves competitive classification performance at moderate-to-high SNRs and exhibits clear advantages in extremely low-SNR scenarios, validating the effectiveness and strong generalization capability of the proposed approach. Full article

The efficiency optimization of encryption and decryption algorithms in cloud environments is addressed in this study, where the processing speed of encryption and decryption is enhanced through the application of multi-threaded parallel technology. In view of the high-concurrency and distributed storage characteristics of cloud platforms, a multi-threaded concurrency mechanism is adopted for the direct processing of data streams. Compared with the traditional serial processing mode, four distinct encryption algorithms, namely AES, DES, SM4 and Ascon, are employed, and different data units are processed concurrently by means of multithreaded technology. Based on multi-dimensional performance evaluation indicators (including throughput, memory footprint and security level), comparative analyses are carried out to optimize the design scheme; accordingly, multi-threaded collaborative encryption is realized to improve the overall operation efficiency. Experimental results indicate that, in comparison with the traditional serial encryption method, the encryption and decryption latency of the algorithm is reduced by around 50%, which significantly lowers the time overhead associated with encryption and decryption processes. Simultaneously, the throughput of AES and DES algorithms is observed to be doubled, which leads to a remarkable improvement in communication efficiency. Moreover, under the premise that the original secure communication capability is guaranteed, system resource overhead is effectively reduced by SM4 and Ascon algorithms. On this basis, a quantitative reference basis is provided for cloud platforms to develop targeted encryption strategies tailored to diverse business demands. In conclusion, the proposed approach is of profound significance for advancing the synergistic optimization of security and performance in cloud-native data communication scenarios. Full article

The aim of this article is to present the social–ecological system (SES) as a unit of analysis for sustainable water management under conditions of anthropogenic pressure in Poland. In the face of accelerating climate change and growing human impacts, Polish water systems are exposed to increasing ecological stress and to material and immaterial losses affecting local communities. The SES approach provides an integrative analytical framework that links ecological and social components, enabling a holistic view of adaptive and governance processes at multiple spatial scales, from municipalities to areas that transcend administrative boundaries. Methodologically, this study triangulates three complementary approaches to strengthen explanatory inference. This conceptual SES review defines the analytical categories used in the paper, the bibliometric mapping (Scopus database with VOSviewer) identifies dominant research streams and underexplored themes, and the qualitative Polish case studies operationalize these categories to diagnose mechanisms, feedbacks, and governance vulnerabilities under anthropogenic pressure. The bibliometric analysis identifies the main research streams at the intersection of SES, water management and sustainable development, revealing thematic clusters related to climate change adaptation, environmental governance, ecosystem services and hydrological extremes. The case studies - the 2024 flood, the 2022 ecological disaster in the Odra River, and water deficits associated with lignite opencast mining in Eastern Wielkopolska - illustrate how anthropogenic pressure and climate-related hazards interact within local SES and expose governance gaps. Particular attention is paid to attitudes and social participation, understood as configurations of behaviors, knowledge and emotions that shape decision-making in local self-government, especially at the municipal level. This study argues that an SES-based perspective can contribute to building the resilience of water systems, improving the integration of ecological and social dimensions and supporting more sustainable water management in Poland. Full article

Eight Pacific Island Countries and Territories (PICTs) have been validated by the World Health Organization (WHO) as having eliminated lymphatic filariasis (LF) as a public health problem. WHO recommends that these countries implement post-validation surveillance (PVS) to ensure resurgence has not occurred. Some PICTs proactively conducted LF PVS even in the absence of specific recommendations or best-practice guidelines at the time of implementation. We aimed to explore the barriers and facilitators to implementing LF PVS in PICTs, with a view to informing context-specific strategies and regional guidelines. Key informant interviews were held between March and September 2024 with 15 participants involved in LF and/or neglected tropical disease surveillance. Transcripts were analysed thematically using a generalised deductive approach. A conceptual framework was developed to summarise themes with two main streams of barriers identified. Stream One Barriers included limited awareness of, and guidelines for, PVS requirements and competing national health priorities. Stream Two Barriers included cost, resource, and logistical barriers to conducting PVS. Participants called for clearer, contextually tailored guidelines, improved communication from WHO, and integration within existing systems. This study highlights the urgent need for operational guidance, policy advocacy, and capacity strengthening to ensure sustainable LF PVS in PICTs. Incorporating local context and leveraging existing health structures will be essential to prevent disease resurgence and maintain gains achieved through elimination programmes. Full article

This paper presents a comprehensive techno-economic assessment of a community battery energy storage system (BESS) participating concurrently in energy arbitrage and frequency control ancillary services (FCAS) markets, while also providing customer savings through coordinated demand management. The proposed framework employs a mixed-integer linear programming (MILP) model to co-optimize the charging, discharging, and reserve scheduling of the battery under dynamic market conditions. The model explicitly incorporates key operational and economic factors such as round-trip efficiency, degradation cost, market-participation constraints, and revenue from multiple value streams. By formulating the optimization problem within this MILP structure, both the operational feasibility and the economic profitability of the system are evaluated over annual market cycles. Simulation results demonstrate that integrating FCAS participation with conventional energy arbitrage substantially enhances total revenue potential and improves asset utilization, compared with single-service operation. Furthermore, the coordinated management of community demand contributes to additional cost savings and supports local grid reliability. The findings highlight the critical role of co-optimized control and multi-market participation strategies in improving the financial viability and grid-support capabilities of community-scale BESS deployments. Full article