Search Results (32,652)

Hexamethyldisiloxane (HMDSO) is an organosilicon compound with a modifiable bandgap, depending on the deposition conditions. This material has many unique properties due to its stability, low toxicity, and strong adhesion, making it useful as a protective barrier against corrosion, moisture, and oxidation. In this work, HMDSO films were deposited on glass substrates by the Plasma Enhanced Chemical Vapor Deposition (PECVD) technique at different deposition times. The optical properties of HMDSO films, such as dielectric permittivity, refractive index, extinction and absorption coefficients, and band gap energy, are inferred from transmission and reflection spectra. As the deposition time increased, the real part of the dielectric constant, the refractive index, and the bandgap energy showed a decrease, dropping from 4.24 to 3.40, from 2.06 to 1.84, and from 2.85 eV to 2.03 eV, respectively. The latter result is determined using classical models such as the O’Leary-Johnson-Lim (‘OJL’) interband transition and the harmonic oscillator model. HMDSO and Silver are used in this study for the fabrication of optical filters using two types of structures, a multiple cavity metal–dielectric (MCMD) and the Fabry–Perot structure. The silver layers are deposited by a sputtering process. The MCMD optical filter shows a higher transmittance of about 30%, but a wide range of wavelengths is transmitted. In contrast, the Fabry–Perot filter showed high contrast but a lower transmittance of about 20%. Full article

Under the increasingly competitive environment, some manufacturers may misreport costs to boost their own profits, potentially harming the overall interests of the supply chain. Conversely, some retailers may engage in corporate social responsibility (CSR) to promote sustainable development within the supply chain. Thus, this study considers a competitive supply chain comprising one retailer and two manufacturers, and investigates the impact of the manufacturer’s misreporting behavior on the chain supply members’ pricing decisions and performances as well as the impact of retailer CSR on the manufacturer’s misreporting behavior. When the retailer does not engage in CSR, the manufacturers’ misreporting behavior is solely influenced by misreporting factors. If the misreporting factors of both manufacturers are low, they can always benefit from their misreporting behavior. Interestingly, if one manufacturer has a high misreporting factor while the other has a low one, the manufacturer whose misreport factor is high does not misreport its cost, instead benefiting from the competitor’s misreporting behavior. When the retailer engages in CSR, the manufacturer’s misreporting behavior is influenced not only by their misreporting factors but also by the degree of product substitutability. If product substitutability is low, both manufacturers do not have an incentive to misreport their costs. If product substitutability is moderate and both misreporting factors are low, they can benefit from their misreporting behavior. However, when product substitutability is high, if one manufacturer misreports, the other will refrain from doing so. Full article

Artificial intelligence has significant applications in computer vision studies for cultural heritage. In this research field, visual inspection of historical buildings and the digitization of heritage using machine learning models stand out. However, the literature still lacks datasets for the classification and identification of Brazilian religious buildings using deep learning, particularly with images from the historic town of Ouro Preto. It is noteworthy that Ouro Preto was the first Brazilian World Heritage Site recognized by UNESCO in 1980. In this context, this paper aims to address this gap by proposing a new image dataset, termed ImageOP: The Image Dataset with Religious Buildings in the World Heritage Town of Ouro Preto for Deep Learning Classification. This new dataset comprises 1613 images of facades from 32 religious monuments in the historic town of Ouro Preto, categorized into five classes: fronton (pediment), door, window, tower, and church. The experiments to validate the ImageOP dataset were conducted in two stages: simulations and computer vision using smartphones. Furthermore, two deep learning structures (MobileNet V2 and EfficientNet B0) were evaluated using Edge Impulse software. MobileNet V2 and EfficientNet B0 are architectures of convolutional neural networks designed for computer vision applications aiming at low computational cost, real-time classification on mobile devices. The results indicated that the models utilizing EfficientNet achieved the best outcomes in the simulations, with accuracy = $94.5\%$, precision = $96.0\%$, recall = $96.0\%$, and F-score = $96.0\%$. Additionally, superior accuracy values were obtained in detecting the five classes: fronton ($96.4\%$), church ($97.1\%$), window ($89.2\%$), door ($94.7\%$), and tower ($95.4\%$). The results from the experiments with computer vision and smartphones reinforced the effectiveness of the proposed dataset, showing an average accuracy of $88.0\%$ in detecting building elements across nine religious monuments tested for real-time mobile device application. The dataset is available in the Mendeley Data repository: Full article

Printed batteries are increasingly being investigated for feeding small, wearable devices more and more involved in our daily lives, promoting the study of printing technologies. Among these, gravure is very attractive as a low-cost and low-waste production method for functional layers in different fields, such as energy, sensors, and biomedical, because it is easy to scale up industrially. Thanks to our research, the feasibility of gravure printing was recently proved for rechargeable lithium-ion batteries (LiBs) manufacturing. Such studies allowed the production of high-quality electrodes involving different active materials with high stability, reproducibility, and good performance. Going beyond lithium-based storage devices, our attention was devoted on the possibility of employing highly sustainable gravure printing for sodium-ion batteries (NaBs) manufacturing, following the trendy interest in sodium, which is more abundant, economical, and ecofriendly than lithium. Here a study on gravure printed anodes for sodium-ion batteries based on hard carbon as an active material is presented and discussed. Thanks to our methodology centered on the capillary number, a high printing quality anodic layer was produced providing typical electrochemical behavior and good performance. Such results are very innovative and relevant in the field of sodium-ion batteries and further demonstrate the high potential of gravure in printed battery manufacturing. Full article

As global demand for freshwater grows, seawater desalination has become one of the most promising methods for obtaining freshwater. Many coastal nations have included it in their sustainable development plans and are actively advancing related technologies. Compared with traditional desalination methods, such as distillation and membrane-based desalination, seawater freezing desalination offers the benefit of producing large amounts of freshwater at lower costs. This study provides an overview of the main methods and principles of seawater freezing desalination and summarizes the latest research progress. This paper also discusses experimental and simulation studies of different principles. Current research shows that both direct and indirect seawater freezing desalination technologies have become relatively mature, laying a foundation for practical applications. Hydrate-based desalination, eutectic freezing technology, and vacuum freezing technology offer cost-reduction benefits, but existing technologies have limitations, making these areas hot topics in research. Additionally, this paper discusses the experimental progress and simulation methods associated with this, elaborates upon, and analyzes the freezing crystallization process and desalination efficiency from the perspective of the bottom layer of crystal growth, offering valuable insights for future research. It concludes by summarizing and predicting the development of these technologies, emphasizing their great potential due to their low-cost and sustainable features. Full article

With the increasing use of online meetings, there is a growing need for efficient tools that can automatically generate meeting minutes from recorded sessions. Current solutions often rely on proprietary systems, limiting adaptability and flexibility. This paper investigates whether various open-source models and methods such as audio-to-text conversion, summarization, keyword extraction, and optical character recognition (OCR) can be integrated to create a meeting minutes generation tool for recorded video presentations. For this purpose, a series of evaluations are conducted to identify suitable models. Then, the models are integrated into a system that is modular yet accurate. The utilization of an open-source approach ensures that the tool remains accessible and adaptable to the latest innovations, thereby ensuring continuous improvement over time. Furthermore, this approach also benefits organizations and individuals by providing a cost-effective and flexible alternative. This work contributes to creating a modular and easily extensible open-source framework that integrates several advanced technologies and future new models into a cohesive system. The system was evaluated on ten videos created under controlled conditions, which may not fully represent typical online presentation recordings. It showed strong performance in audio-to-text conversion with a low word-error rate. Summarization and keyword extraction were functional but showed room for improvement in terms of precision and relevance, as gathered from the users’ feedback. These results confirm the system’s effectiveness and efficiency in generating usable meeting minutes from recorded presentation videos, with room for improvement in future works. Full article

In the UK, SMEs account for 99.9% of the business population, with from 43% to 53% of UK business emissions coming from SMEs. However, SMEs face specific barriers in relation to net zero targets, such as a lack of knowledge about strategies to achieve net zero targets. Despite the ongoing lack of a formal decarbonisation plan for SMEs, various types of projects have been designed to help SMEs to move towards the UK’s net zero target. The Eastern New Energy (ENE) project received funding from the European Regional Development Fund (ERDF) to support SMEs across significant economic areas of the UK, namely the East of England, to help address the barriers that prevent SMEs from decarbonising. The project provided a range of measures, including raising their level of knowledge and providing technical support to help with SME decarbonisation. Following the completion of our targeted support activities, semi-structured interviews (n = 21) were conducted with SME beneficiaries to evaluate the effectiveness of the support with the ambition of providing some policy recommendations based on understanding how national and strategic support can be effective for a diverse, often unconnected ecosystem of businesses. The findings from the interviews indicated that engagement in the ENE project had positive impacts on the SMEs’ understanding of net zero, or how to start their journey towards decarbonisation by identifying their source of emissions and learning how to calculate them. However, accounting for emissions from Scope 3 activities, transition costs and building restrictions were the main barriers that undermined the ENE recommendations. Our research concludes that in designing engagement projects and support, one needs to acknowledge such restrictions and barriers, which requires government interventions to cover all aspects of the SME decarbonisation journey, from nuanced and responsive policy making to developing bespoke knowledge transfer and supporting low-carbon material provision that can support a decarbonised marketplace. Full article

Background: The effectiveness of pre-exposure prophylaxis (PrEP) and non-occupational post-exposure prophylaxis (nPEP) in preventing HIV is well-established, yet their use in clinical practice remains low. Healthcare providers, especially those in primary and emergency care settings, play a crucial role in adopting and implementing these prevention strategies. We conducted a statewide survey with 519 healthcare providers in Texas to assess their knowledge, practices, and barriers related to prescribing PrEP and nPEP. Methods: The survey collected data on demographics, clinical experience, practice type, awareness of recommended guidelines, knowledge of PrEP and nPEP, prescribing practices, and challenges encountered to prescribe these medications. We used multiple regression analysis to identify factors associated with PrEP and nPEP prescribing behavior. Results: While most providers were familiar with CDC and/or USPSTF-recommended PrEP guidelines, fewer had adequate knowledge of nPEP. Key challenges identified by providers included concerns about cost (48%), limited time (40% for PrEP and 51% for nPEP), and insufficient education or training (40% for PrEP and 35% for nPEP). Providers who were more familiar with the recommended guidelines and had greater experience in sexual health assessment were more likely to prescribe both PrEP and nPEP. Conclusions: This study highlights the need for enhanced education and training to boost providers’ knowledge and confidence in prescribing PrEP and nPEP. It also underscores the importance of addressing cost-related barriers and simplifying care processes to better integrate these HIV prevention strategies into primary and emergency care settings. Full article

In the current study, we address the phase retrieval of one-dimensional phase objects from near-field diffraction patterns using the multiple-plane Gerchberg–Saxton algorithm, which is still widely used for phase retrieval. The algorithm was implemented in a low-cost digital signal processor capable of fast Fourier transform using Q15 arithmetic, which is used by the previously mentioned algorithm. We demonstrate similarity between one-dimensional phase objects, i.e., vectors cut out of a phase map of the tertiary spherical aberration retrieved by the multiple-plane Gerchberg–Saxton algorithm, and these vectors are measured with a non-contact profiler. The tertiary spherical aberration was induced by a phase plate fabricated using grayscale lithography. After subtracting the vectors retrieved by the algorithm from those measured with the profiler, the root mean square error decreased, while a corresponding increase in the Strehl ratio was observed. A single vector of size 64 pixels was retrieved in about 2 min. The results suggest that digital signal processors that are capable of one-dimensional FFT and fixed-point arithmetic in Q15 format can successfully retrieve the phase of one-dimensional objects, and they can be used for applications that do not require real-time operation, i.e., analyzing the quality of cylindrical micro-optics. Full article

With the development of the micro electromechanical system (MEMS), which widely adopts micro differential pressure sensors (MDPSs), the demand for high-performance MDPSs had continuously increased. Pressure sensors realized using MEMS technology integrated with biomedical catheters are of significant importance in the detection and treatment of various biological diseases. Biomedical catheters used in low-Fr applications (1Fr = 0.33 mm outer diameter) require miniaturized sensors that do not compromise their performance. For instance, catheters (5Fr) used for central venous pressure (CVP) monitoring require the integration of high-performance sensors with total dimensions smaller than 1.65 mm along at least two directions (length, width, or height). In this paper, a silicon-on-insulator (SOI)-based MDPS was designed and fabricated for micro-pressure detection in the range of 0–1 kPa. The dimension of the sensor is only 1 mm × 1 mm × 0.4 mm, with a sensitivity of 3.401 mV/V/kPa at room temperature, nonlinearity of 0.376% FS (full scale), and an overall accuracy of 0.59% FS. The sensor operates normally when the temperature is even increased to 160 °C, and its temperature coefficient of zero output (TCO) and temperature coefficient of sensitivity (TCS) are 0.093% FS/°C and −0.144% FS/°C. The dimension and performance results of this MDPS demonstrate its potential to play a significant role in biomedical catheters. In addition, it is fabricated using an 8-inch MEMS process, which significantly reduces the cost. Full article

The global prevalence of counterfeit and low-quality pharmaceuticals poses significant health risks and challenges in medical treatments, creating a need for rapid and reliable drug screening technologies. This study introduces a cost-effective electrochemical paper-based device (ePAD) modified with functionalized bamboo-derived biochar (BCF) for the detection of paracetamol in substandard medicines. The sensor was fabricated using a custom 3D-printed stencil in PLA, designed for efficient production, and a 60:40 (m/m) graphite (GR) and glass varnish (GV) conductive ink, resulting in a robust and sensitive platform. The electroactive area of the ePAD/BCF sensor was determined as 0.37 cm². Characterization via SEM and cyclic voltammetry (CV) verified its structural and electrochemical stability. The sensor demonstrated linear detection of paracetamol from 5.0 to 60.0 µmol L⁻¹ with a detection limit of 3.50 µmol L⁻¹. Interference studies showed high selectivity, with recoveries of over 90%, and the sensor successfully quantified paracetamol in commercial analgesic and anti-flu samples. This sustainable, bamboo-based ePAD offers a promising solution for rapid on-site pharmaceutical quality control, with significant potential to enhance drug screening accuracy. Full article

Sphere formation assay is an accepted cancer stem cell (CSC) enrichment method. CSCs play a crucial role in chemoresistance and cancer recurrence. Therefore, CSC growth is studied in plates and microdevices to develop prediction chemotherapy assays in cancer. As counting spheres cultured in devices is laborious, time-consuming, and operator-dependent, a computational program called the Automatic Quantification of Spheres Algorithm (ASQA) that detects, identifies, counts, and measures spheres automatically was developed. The algorithm and manual counts were compared, and there was no statistically significant difference (p = 0.167). The performance of the AQSA is better when the input image has a uniform background, whereas, with a nonuniform background, artifacts can be interpreted as spheres according to image characteristics. The areas of spheres derived from LN229 cells and CSCs from primary cultures were measured. For images with one sphere, area measurements obtained with the AQSA and SpheroidJ were compared, and there was no statistically significant difference between them (p = 0.173). Notably, the AQSA detects more than one sphere, compared to other approaches available in the literature, and computes the sphere area automatically, which enables the observation of treatment response in the sphere derived from the human glioblastoma LN229 cell line. In addition, the algorithm identifies spheres with numbers to identify each one over time. The AQSA analyzes many images in 0.3 s per image with a low computational cost, enabling laboratories from developing countries to perform sphere counts and area measurements without needing a powerful computer. Consequently, it can be a useful tool for automated CSC quantification from cancer cell lines, and it can be adjusted to quantify CSCs from primary culture cells. CSC-derived sphere detection is highly relevant as it avoids expensive treatments and unnecessary toxicity. Full article

For both human health and the environment, air pollution is a serious concern. However, the available air quality monitoring networks have important limitations, such as the high implementation costs, limited portability, and considerable operational complexity. In this context, unmanned aerial systems (UASs) are emerging as a useful technological alternative due to their ability to cover large distances and access areas that are difficult or impossible for humans to reach. This article presents the development of an integrated platform that combines an unmanned aerial system (UAS) with specialized sensors to measure key parameters in relation to air quality, such as carbon monoxide (CO), ozone (O₃), and nitrogen dioxide (NO₂). In addition, a web application called PTECA is developed to visualize the data gathered by the wireless sensor array in real time. The platform incorporates a system that allows real-time tracking of the UAS route and measurement values during sample collection, employing the LoRa communication protocol. This solution represents a low-cost alternative that mitigates some of the limitations of traditional monitoring networks by offering greater portability and accessibility in terms of data collection. Preliminary tests successfully demonstrate the viability of the proposed system in a controlled airspace using geofencing. Full article

This article is devoted to planning water-energy regimes for hydropower plants, taking into account economic and ecologic criteria. A new methodology based on a probabilistic model of water inflow has been proposed. The probabilistic method requires the calculation of low-water and average-water year typical hydrographs based on the probability curve. This allows the determination of the guaranteed hydropower plant generation schedule with a month time-step. According to the method considered, the mathematical model of the reservoir filling and normal power station operation has been designed. The software for the automated water-energy mode calculation is presented in this paper. The economic feasibility of maximum replacement of thermal power plants in the energy system with more environmentally friendly hydropower plant is substantiated. The methodology of water resources cost calculation and economic efficiency assessment under various hydropower plant regime scenarios have been proposed in the paper. Using the data and characteristics of HPPs and TPPs, an assessment of energy efficiency will be obtained in accordance with the developed methodology to determine the price of water for HPPs and all participants in the water management complex. The results of the implementation of the developed approach indicate that the price of electricity sales in a competitive electricity market can be brought into line with the price of electricity sales generated by thermal power plants, which increases the economic feasibility of the maximum replacement of thermal power plant capacity in the system with more economical and environmentally friendly hydropower plant. The developed method allows for an increase in the efficiency of water resources use and the efficiency of hydropower plant participation in the energy balance, which makes it possible to displace part of the power generated by thermal power plants. Full article

Mapping shallow-water bathymetry and morphology represents a technical challenge. In fact, acoustic surveys are limited by water depths reachable by boat, and airborne surveys have high costs. Photogrammetric approaches (either via drone or from the sea surface) have opened up the possibility to perform shallow-water surveys easily and at accessible costs. This work presents a simple, low-cost, and highly portable platform that allows gathering sequential photos and echosounder depth values of shallow-water sites (up to 5 m depth). The photos are then analysed in conjunction with photogrammetric techniques to obtain digital bathymetric models and orthomosaics of the seafloor. The workflow was tested on four repeated surveys of the same area in the Western Mediterranean and allowed obtaining digital bathymetric models with centimetric average accuracy and precision and root mean square errors within a few decimetres. The platform presented in this work can be employed to obtain first-order bathymetric products, enabling the contextual establishment of the depth accuracy of the final products. Full article