Search Results (58,247)

Fluorinated greenhouse gases (FGGs) are classified as worldwide pollutants and have a high global warming potential compared to other greenhouse gases. Detecting the existence and concentration of new and older refrigerant gases is crucial for assessing system functionality and determining whether they can be recycled or need to be disposed of. Additional justifications for the necessity of quantitative measurements of these gases include the manufacturing of air conditioning components; leak detection is conducted to ensure they are free of leaks. Classical laboratory Fast Fourier transform spectrometers enable the detection and measurement of substances while being delicate, unwieldy, and costly, and typically requiring a skilled technician to operate them. For the estimation of refrigerants in the field, a portable, user-friendly, and cost-effective detection device must be deployed. This article provides an in-depth analysis of the categorization of refrigerant gases using an Internet of Things (IoT) gas detection device. The functionality in effectively differentiating between important refrigerant gases, like R-32 and R-134a, with low delay, is demonstrated through practical tests. With the portable device, this study utilizes Fourier-Transformed infrared spectra measured from the refrigerants R-32 and R-134a, collected using a custom-made 3D-printed tubular reactor equipped with two BaF₂ windows, suitable for use in the beamline of a Bruker IR Spectrometer. Calibration was performed by exposing the infrared sensor to controlled gas environments with varying amounts of refrigerant gases using accurately produced gas mixtures. Following the on-field analysis of the reclaimed refrigerants, the obtained data was immediately processed, and both the data and the results were uploaded to an IoT platform, making them available to business-to-business (B2B) clients. The functionality of the device is demonstrated. Full article

The ceramics industry has long embraced the principles of the circular economy, with a strong focus on the reuse and recovery of raw materials essential to the production cycle. This approach reduces costs by reintroducing secondary raw materials—such as production scraps and recycled materials—into the manufacturing process after appropriate recovery treatments. This study aims to contribute to the transition of the ceramic industry toward a circular economy by incorporating industrial by-products into monoporosa ceramic bodies, thereby transforming waste materials into valuable resources. Monoporosa is a porous, single-fired ceramic wall tile characterized by a high carbonate content and low bulk density. However, the role of secondary raw materials in monoporosa formulations, as well as their influence on processing behavior (e.g., during sintering) and on key technological properties, is not yet fully understood. This work investigates a standard monoporosa formulation based on conventional raw materials (sand, calcite, feldspars, and clays) and compares it with new formulations in which industrial waste materials from local and national sources—originating from other industrial processes—are used as partial or total substitutes for some of the traditional raw materials, particularly sand and calcite. The industrial by-products examined include biomass bottom ash, foundry sand, and marble cutting and processing sludge. All materials were characterized using chemical–mineralogical, thermal, and morphological analyses and were incorporated into the ceramic bodies at different substitution levels (10%, 50%, and 100%) to replace natural raw materials. Their behavior within the mixtures was evaluated to determine ceramic suitability and acceptable replacement ratios. Furthermore, the effects of these additions on water absorption, thermal expansion coefficient, and microstructural characteristics were assessed. Based on the positive results obtained, this study demonstrates the feasibility of using, in particular, two secondary raw materials—foundry sand and marble sludge—in monoporosa body formulations, allowing for the complete replacement of the original raw materials and thereby contributing to the development of more sustainable ceramic compositions. Full article

Structuring oils using oleogels (OGs) represents a promising strategy for developing semi-solid lipid matrices with applications in food and other soft systems. This study evaluated the thermal stability and physicochemical properties of an oleogel (OG) formulated with extra virgin olive oil (EVOO) and beeswax (BW, 6%). The oleogel and olive oil samples were initially characterized by thermogravimetric analysis (TGA/DTG). The beeswax and oleogel samples were initially characterized by texture analysis. An antioxidant capacity (ORAC) analysis was initially applied to the beeswax sample. An initial rheometric analysis was applied to the oleogel sample. Fatty acid profiling and infrared spectroscopy were applied initially and finally to the oleogel and olive oil samples. During the thermal processing (80 °C, 14 days) of the oleogel and olive oil, analyses of the percentage of polar compounds, refractive index, and absorption parameters (K₂₃₂ and K₂₇₀) were performed. The oleogel exhibited a soft, pseudoplastic network, with lower hardness and mechanical strength than pure beeswax. Gelation modified the thermo-oxidative stability of EVOO, showing lower levels of polar compounds (from day 7 of heating; p = 0.028) and a slight delay in the onset of thermal degradation (Tonset), suggesting partial protection against the formation of polar degradation compounds. Furthermore, the evolution of K₂₃₂ indicated differences in the formation of primary oxidation products (p = 0.027) over the 14 days of heating, while K₂₇₀ showed no differences in the formation of secondary oxidation compounds. This reflects the complex interaction between the gelled matrix and the lipid deterioration mechanisms. Overall, the results demonstrate that the incorporation of beeswax allows for a partial reduction in degradation compounds in high-temperature processes, producing technologically functional oleogels that offer a potential alternative source for structuring solid fats. This work provides relevant evidence for the rational design of oleogels based on unrefined oils and opens new opportunities for their application in food systems and gelled matrices with thermal processing requirements. Full article

The global shipping industry faces severe carbon emission challenges. Harbor tugs, as significant contributors to port emissions, require improved energy efficiency. However, their sailing conditions are complex and dynamic, making temporal feature characterization difficult with traditional static or simplistic clustering methods. To address this, this study proposes a novel method for constructing typical sailing conditions by integrating an enhanced clustering approach with Hidden Markov Models (HMM). First, kinematic segments are extracted from processed ship speed data, and key features are selected and reduced via Principal Component Analysis (PCA). Subsequently, an improved clustering model combining the Whale Optimization Algorithm (WOA) and K-means++ is developed to categorize segments into six distinct condition types. These clustered states then serve as the hidden states of an HMM, whose learned transition matrix synthesizes a 3600 s typical sailing condition profile. The constructed profile is validated through multi-dimensional comparison with original data, demonstrating high fidelity in statistical characteristics, temporal properties, and distribution similarity. The results confirm that the proposed method can accurately replicate the operational patterns of harbor tugs. This study provides a reliable data foundation for the energy efficiency assessment and optimization of harbor tugs and offers a new methodological perspective for constructing operational profiles for ships and other mobile machinery. Full article

Hakuin Ekaku 白隠慧鶴, the reviver of the Japanese Rinzai school 臨濟宗, introduced Chinese Daoist cosmology and views on the body through the narrative persona of the immortal Hakuyūshi 白幽子 in works such as Yasen Kanna 夜船閑話 (Chats on a Night Boat). He elaborated on specific techniques of Daoist internal alchemy (nèidān 內丹), such as focusing the mind on the dāntián 丹田 (elixir field) and regulating the breath to enter a state of tranquility, as methods to address “Zen sickness” and nurture both body and mind. This approach to self-cultivation exerted a profound influence in Japan. From the late Meiji into the Taishō period (early 20th century), practitioners such as Futaki Kenzo 二木謙三, Fujita Reisai 藤田靈齋, and Okada Torajirō 岡田虎二郎 developed their own health methods based on their respective understandings, forming practices such as the “abdominal breathing method” 腹式呼吸法 and the “method of harmonizing breath and mind” 息心調和法. These contributions promoted the popularization of quiet sitting within Japanese society. Related books were subsequently translated and introduced to China, inspiring modern scholars such as Jiang Weiqiao 蔣維喬 to reinterpret Chinese traditional self-cultivation methods in a new language, leading to the publication of health-preserving works like The Yinshizi’s Method of Quiet Sitting 因是子靜坐法. At the same time, the Chinese self-cultivation community engaged in reflection on and correction of potential drawbacks in the practice of sitting meditation. By tracing this cross-religious and cross-regional process of cultural transmission and transformation, this paper reveals the enduring vitality of Daoist practices during East Asia’s modernization, as well as their universal significance beyond the confines of any single religious tradition. Full article

Clathrates have gained considerable attention due to their potential impact on various industries, including oil and gas production, and more recently in the fields ranging from energy storage and transportation to environmental protection and gas separation processes, opening up new technological possibilities. Overall, the attention is focused on their spontaneous and uncontrolled formation/nucleation in offshore oil and gas pipelines, which can lead to numerous and serious operational problems. Accordingly, significant research efforts have focused on understanding the mechanisms of clathrate formation and inhibition or dissociation. Different approaches are being explored; some are ambitious and innovative, whereas others seek further validation. Among these, particular interest has emerged in the coupling of Terahertz (THz) radiation with the collective low-energy and/or vibrational modes of water, and/or other molecules, as well as their clusters. In this review, we summarize recent advances and findings in this promising research field, highlighting the potential applications of THz radiation and spectroscopy, future applications in the field of clathrates, and the technological progress toward the implementation of THz-based solutions in transportation and industrial processes. Full article

Diabetic osteoporosis (DOP) is a metabolic bone disease characterized by abnormal bone tissue structure and reduced bone strength in patients with diabetes. Its pathogenesis is complex, involving multiple factors rather than a single cause, and has not yet been fully elucidated. Cuproptosis, a novel form of programmed cell death discovered in 2022, differs mechanistically from apoptosis, necroptosis, and ferroptosis. This process relies on the accumulation of intracellular copper ions and is closely associated with mitochondrial respiration. Studies have indicated that cuproptosis is intimately linked to glucose metabolism and bone metabolism. This review explores the role of copper homeostasis in maintaining glucose metabolism and bone quality and systematically elucidates the potential associations between cuproptosis and these processes from molecular, cellular, and pathophysiological perspectives, aiming to provide new insights and prospects for future research directions in diabetic osteoporosis. Full article

A new species of Poecilia, subgenus Pamphorichthys, is described from the Cachoeirinha River, a tributary of the upper Paraguaçu River basin in the Chapada Diamantina, Bahia, Brazil. Pamphorichthys is diagnosed among the Poecilini by the strongly pigmented gonopodium in mature males and the equally pigmented urogenital region in females. The new species exhibits four diagnostic features defining the Pamphorichthys clade within Poeciliidae. Males display a unique combination of a reticulated body pattern with diffuse vertical bars and a highly modified pelvic fin. The male pelvic fin possesses a subterminal process on the second ray, similar to that found in the limbs of Pamphorichthys, but highly modified. Although it shares the unique pelvic-fin processes of Pamphorichthys, its gonopodium exhibits reduced ornamentation, resembling the condition in P. pertapeh and P. akroa. Its discovery in an isolated drainage within the Chapada Diamantina underscores the notable endemism of the region. However, the species faces an imminent conservation crisis. Its only known habitat has undergone severe degradation in the last few decades. An excessive water withdrawal has collapsed the Utinga River, one of the main tributaries of the upper Paraguaçu River, and anthropogenic degradation can lead to the disappearance of species, even before it becomes known. Full article

Ferrochrome alloy is a crucial additive in steelmaking, significantly enhancing the strength, hardness, and corrosion resistance of steel; investigating the melting behavior of ferrochrome alloy could provide a theoretical foundation for producing stainless steel with improved properties. To gain insight into the melting behavior and mechanism of ferrochrome alloy in molten steel, this paper employed a numerical simulation with ANSYS Fluent software to investigate the effects of bath temperature, bath chromium content, bath carbon content, alloy chromium content, alloy carbon content, alloy size, and alloy preheating temperature on the melting behavior of ferrochromium alloy. The results showed that when the ferrochrome alloy is immersed into the molten bath, a solidified layer formed on the surface of the alloy, and as immersion time increased, the thickness of the solidified layer initially increased and then decreased; subsequent to the complete melting of the solidified layer, the alloy body began to melt. The center temperature of the alloy remained the lowest throughout the melting process and raised with increasing immersion time. Additionally, as the bath temperature and bath carbon content increased, the formation time of the solidified layer on the surface of the alloy shortened, its maximum thickness decreased, the alloy’s melting rate accelerated from 0.49 × 10⁻⁴ m/s to 1.22 × 10⁻⁴ m/s, and the complete melting time decreased from 134.7 s to 41 s. Conversely, increasing the bath chromium content raised the melting point of the solidified layer, prolonged the time required for remelting, slowed the alloy’s melting rate from 2.47 × 10⁻⁴ m/s to 0.91 × 10⁻⁴ m/s, and increased the complete melting time from 67.6 s to 75.2 s. As the alloy carbon content and preheating temperature increased, the alloy chromium content and size decreased, the formation time of the solidified layer shortened, its maximum thickness initially increased and then decreased, the melting rate of the alloy accelerated from 0.47 × 10⁻⁴ m/s to 1.97 × 10⁻⁴ m/s, and the complete melting time reduced from 165.8 s to 18.1 s. Full article

The experiences and repercussions of the cross-border migration process on family life have not yet been synthesized. This study aimed to synthesize the best available qualitative findings on this theme. A systematic review of qualitative evidence with meta-synthesis was conducted. Articles were identified according to predefined extraction criteria in the first half of 2025, across seven databases: Web of Science, MEDLINE/PubMed, PsycINFO, LILACS, CINAHL, SCOPUS, and Social Science Citation Index. Two researchers independently screened and appraised the reports, assessing methodological quality and systematically recording and analyzing relevant information. A protocol was registered in PROSPERO (ID: CRD42024505655). Fifty studies were included, and three main themes emerged: (a) living in multiple possible contexts, where space and relationships influence family functionality, including reduced family time due to long working hours, substance use, fear of losing cultural roots, new financial responsibilities, and the desire to return to the country of origin; (b) challenges and repercussions on family life after migration, such as increased family conflicts, mental health problems, separation, and loss of ties; (c) strategies for maintaining family functioning, including role adjustment, strengthening of family ties, and support through cultural and religious practices. Families undergoing migration face multiple challenges in their new environments, revealing the complexity of adapting to diverse cultural and social contexts. These findings highlight the need to address the emotional and social demands of migrant families to improve well-being and integration. Understanding these dynamics allows healthcare professionals to design culturally sensitive interventions that promote reception and inclusion. Full article

Origami is frequently used in the design of deployable structures due to its large storage ratio and simple structure. A bistable characteristic is a common feature of origami-inspired structures. In this paper, a new configuration is designed with a bistable characteristic; the forming behavior and restoration process were investigated by experimental and finite element methods. The rod system was used to prove the bistable characteristic of the configuration; meanwhile, the geometric parameter analysis was used to analyze the bistable characteristic under different geometry parameters, including external border, initial angle, and displacement, respectively. An experimental test and finite element simulation for morphological changes and force–displacement curve characteristics were investigated during the forming and recovery process. The results show that the designed configuration has a bistable characteristic: it can be formed and recovered actively, and the finite element simulation and experimental results are consistent. Full article

High-resolution single-channel Sparker (1 kJ) profiles have been carried out to reconstruct the seismo-stratigraphic architecture of a sector of the Campania–Latium Tyrrhenian margin (Southern Tyrrhenian Sea, Italy). Seven seismic lines between the Volturno river mouth and the southern Latium margin were processed in IHS Kingdom^® software (4.0) at the University of Sannio (Benevento, Italy) and interpreted at the CNR-ISMAR (Naples, Italy) using seismic- and sequence-stratigraphic criteria. The Sparker dataset refines correlations with previously interpreted Chirp profiles and improves the imaging of fault patterns and key stratigraphic markers. Several seismo-stratigraphic units displaced by normal faults were recognized. Unit 1 represents the acoustic substratum of the high-resolution record, whereas Unit 2 corresponds to a thick relict prograding wedge that thickens toward the Volturno river mouth. A mounded lowstand unit is interpreted as deposits related to the Volturno river delta/fan system. Volcanic units, including the Villa Literno volcanic complex and local volcanic edifices, are locally identified. Overall, the results show that Sparker processing and interpretation provide robust constraints on the stratigraphic architecture and Late Quaternary tectono-sedimentary evolution of deltaic continental shelves. In particular, while previous Chirp studies have effectively constrained the stratigraphic architecture of the Late Quaternary depositional sequence and the geometry of the NYT reflector, this study provides new insights about deeper progradational seismo-stratigraphic units and related volcanic deposits and their tectono-stratigraphic setting. Full article

Quantum computing is a new discipline that uses the ideas of quantum physics to do calculations that are not possible with conventional computers. Quantum bits, called qubits, could exist in superposition states, making them suitable for parallel processing in contrast to traditional bits. When it comes to addressing complex challenges like proof simulation, optimization, and cryptography, quantum entanglement and quantum interference provide exponential improvements. This survey focuses on recent advances in entanglement routing, quantum key distribution (QKD), and qubit management for short- and long-distance quantum communication. It studies optimization approaches such as integer programming, reinforcement learning, and collaborative methods, evaluating their efficacy in terms of throughput, scalability, and fairness. Despite improvements, challenges remain in dynamic network adaptation, resource limits, and error correction. Addressing these difficulties necessitates the creation of hybrid quantum–classical algorithms for efficient resource allocation, hardware-aware designs to improve real-world deployment, and fault-tolerant architecture. Therefore, this survey suggests that future research focus on integrating quantum networks with existing classical infrastructure to improve security, dependability, and mainstream acceptance. This connection has significance for applications that require secure communication, financial transactions, and critical infrastructure protection. Full article

This study aims to elucidate the deterministic correlation between the microscopic fracture mechanisms and the multi-domain characteristics of acoustic emission in reinforced concrete beams under cyclic loading. Cyclic incremental tests were designed and conducted, with synchronized application of digital image correlation and AE techniques to capture the entire damage evolution process and corresponding signal responses throughout. The findings reveal that the damage stage division based on mechanical responses is consistent with that based on AE responses. Damage accumulation and irreversible processes can be clearly characterized by AE activity, and the systematic decrease in the Felicity ratio quantitatively verifies the irreversible accumulation of damage. Under cyclic loading, different microscopic fracture mechanisms generate AE frequency-domain signatures with statistically significant differences. A damage identification model integrating the Felicity ratio and multi-band energy features was developed, achieving an accuracy of 88.89% in identifying macroscopic damage stages. This research quantitatively confirms the effectiveness of AE characteristics as reliable identifiers of microscopic fracture mechanisms, providing a new basis for advancing structural health monitoring technologies grounded in fracture mechanism recognition. Full article

Amid the growing global environmental challenges, precise and efficient vehicle emission management plays a critical role in achieving energy-saving and emission reduction goals. At the same time, the rapid development of connected vehicles and autonomous driving technologies has generated a large amount of high-dimensional vehicle operation data. This not only provides a rich data foundation for refined emission accounting but also raises higher demands for the construction of accounting models. Therefore, this study aims to develop an accurate and efficient emission accounting model to contribute to the precise nitrogen oxide (NO_x) emission accounting for hybrid electric vehicles (HEVs). A systematic approach is proposed that combines incremental dimensionality reduction with advanced regression algorithms to achieve refined and efficient emission accounting based on multiple variables. Specifically, the dimensionality of the real driving emission (RDE) data is first reduced using the feature selection and t-distributed stochastic neighbor embedding (t-SNE) feature extraction method to capture key parameter information and reduce subsequent computational complexity. Next, an incremental dimensionality reduction method based on dictionary learning is employed to efficiently embed new data into a low-dimensional space through straightforward matrix operations. Given the computational cost of the dictionary learning training process, this study introduces the FISTA (Fast Iterative Shrinkage-Thresholding Algorithm) for accelerated iterative optimization and enhances the computational efficiency through parameter optimization, while maintaining the accuracy of dictionary learning. Subsequently, an NO_x emission factor correction factor prediction model is trained using the low-dimensional data obtained from t-SNE embeddings, enabling direct computation of the corresponding correction factor when presented with new incremental low-dimensional embeddings. Finally, validation on independent HEV datasets shows that parameter K improves to 1 ± 0.05 and R² increases up to 0.990, laying a foundation for constructing an emission accounting model with broad applicability based on multiple variables. Full article