This study presents a facial emotion recognition network based on UniRepLKNet to address the difficulty in effectively capturing feature information and preventing key facial information from occupying a more prominent position in the facial emotion recognition process. Moreover, to extract facial emotional features more accurately, the study designs a masked polarized self-attention module that combines U-Net and a polarized self-attention mechanism. This module can deeply mine the dependency between channels and spaces. It can also strengthen the influence of local key information of the face on emotion recognition through a multi-scale feature fusion strategy. The study optimizes UniRepLKNet, a universal large kernel Convolutional Neural Network (CNN), and proposes the EmoRepLKNet neural network structure. In EmoRepLKNet, the mask-polarized self-attention module enables the network to extract key information for facial emotion recognition. Combined with the wide receptive field of large kernel CNN, facial emotions can be recognized effectively. Experimental results show that on the facial emotion recognition dataset FER2013, EmoRepLKNet achieves an accuracy of 76.20%, outperforming existing comparison models and significantly improving facial emotion recognition accuracy compared to that of UniRepLKNet. Additionally, on the single-label portion of the RAF-DB dataset, the proposed method achieves an accuracy of 89.67%.
Abstract With the advent of 5G/6G technologies and the continued advancement of communication systems, the shift toward low-loss microwave dielectrics has become essential. In this context, inorganic complex microwave dielectric materials offer the potential for various combinations and partial or complete substitutions, resulting in a wide range of new compounds. The fabrication method, dopant concentration, and crystal structure significantly influence the electronic properties of these materials. Importantly, this work focuses on several recently reported titanium-, silicon-, and zirconium-based materials, such as CaTiO₃, MgTiO₃, MgSiO₃, and CaZrO₃. However, comprehensive review studies on microwave dielectric materials remain limited, and the fundamental relationship between their crystal structures and dielectric properties is still not fully understood. This review highlights microstructural characteristics-particularly grain size and density-in complex hybrid metal oxides. Additionally, it provides a comprehensive analysis of microwave dielectric properties, with a focus on ABX3 perovskites for electronic applications such as 5G/6G communication systems. To the best of our knowledge, there is no extensive reviews connecting the crystal structures of diverse hybrid complex metal oxides with their corresponding microwave dielectric properties.
The increasing adoption of Artificial Intelligence (AI) in several industries has created a demand for user-centered explanations that align with how users think and understand concepts. This paper presents EXACT (EXplainable AI with Cognitive Theories), a novel framework that combines cognitive theories that explain how people think and understand with cognitive functions, focusing on perception, memory and language abilities, to improve users’ comprehension of and engagement with artificial intelligence technologies. By aligning cognitive functions with the design principles of Human-Computer Interaction (HCI), which promote user-centered intuitive systems. the framework addresses challenges related to making AI understandable to users with various levels of cognitive abilities. As a proof-of-concept, a self-diagnosis tool was created to demonstrate the framework’s effectiveness. Then, 60 participants were divided into a control group and an experimental group. Participants completed six tasks designed to evaluate their perception, memory, and language-related cognitive functions. The experimental group outperformed the control group across all tasks, demonstrating significantly improved performance. Subjective metrics also supported these findings: the experimental group reported higher levels of understanding (4.60 vs. 2.87), confidence (4.67 vs. 3.07), and clarity (4.87 vs. 2.80) compared to the control group. These findings suggest that EXACT framework significantly enhances user’s functions when using AI systems. However, further research is needed to explore its broader applicability in other contexts and utilize other cognitive functions.
Amol U. Pawar, Ignasia H. Mahardika, Young S. Son
et al.
ABSTRACT Achieving carbon neutrality is urgent due to the critical issue of climate change. To reach this goal, the development of new, breakthrough technologies is necessary and urgent. One such technology involves efficient carbon capture and its conversion into useful chemicals or fuels. However, achieving considerable amounts of efficiency in this field is a very challenging task. Even in natural photosynthesis occurring in plant leaves, the CO2 conversion efficiency into hydrocarbons cannot exceed a value of 1%. Nevertheless, recently few reports show comparable higher efficiency in CO2 to gaseous products such as carbon monoxide (CO), but it is hard to find selective liquid fuel products with a high value of solar to liquid fuel conversion efficiency. Herein, a NiFe‐assisted hybrid composite dark cathode is employed for the selective production of solar‐to‐liquid fuels, in conjunction with a BiVO4 photoanode. This process results in the generation of significant amounts of formaldehyde, ethanol, and methanol selectively. The primary objective of this study is to design and optimize a novel photoelectrochemical (PEC) system to produce solar‐to‐liquid fuels selectively. This study shows the enhancement of the solar‐to‐fuel conversion efficiency over 1.5% by employing a hybrid composite cathode composed of NiFe‐assisted reduced graphene oxide (rGO), poly(4‐vinyl)pyridine (PVP), and Nafion.
Production of electric energy or power. Powerplants. Central stations
Thais N. Guerrero, Ruth M. Fisher, Ademir A. Prata
et al.
The beneficial reuse and recovery of biosolids is an attractive option instead of disposal. However, odour emissions present significant challenges to land application of biosolids, increasing operational costs and reducing community acceptance. This study aimed to assess the influence of conveying and storage conditions in wastewater treatment plants on the sensory impact from biosolids. For sensory assessment, samples of anaerobically digested biosolids were collected after centrifuge and during storage out-loading. The emissions were extracted over 15 days using a dynamic flux chamber and sensory analysis conducted using an ODP coupled to a TD-GC-MS. Odour descriptors and intensities (from 1 – weak to 4 – strong) were evaluated by expert panellists, providing insights into the sensory aspects of odour emissions. The ODP results showed variations in the number of occurrences, intensity and modified frequency of odour events across the stages of wastewater solids processing and laboratory storage. Conveying could potentially impact the release of volatile compounds due to the mechanical agitation that can aerate and disturb the structure and surface of the biosolids. On the other hand, storage can accelerate biological and chemical processes as a result of the development of anaerobic conditions leading to subsequent odour generation. The interplay between wastewater treatment processes and odour emissions is complex and requires targeted strategies. The application of sensorial analysis contributes to valuable insights into understanding and managing odour emissions in wastewater treatment plants, offering potential avenues for optimizing operational parameters to benefit biosolids reuse initiatives.
Keywords: Wastewater sludge; Anaerobic digestion; Biosolids; Beneficial reuse; Land application; Gaseous emissions; Sensory emissions; Sensory analysis; Odour detection port.
Chemical engineering, Computer engineering. Computer hardware
Manuel Tuniz, Armando Consiglio, Denny Puntel
et al.
Abstract Long-range electronic ordering descending from a metallic parent state constitutes a rich playground to study the interplay of structural and electronic degrees of freedom. In this framework, kagome metals are in the most interesting regime where both phonon and electronically mediated couplings are significant. Several of these systems undergo a charge density wave transition. However, to date, the origin and the main driving force behind this charge order is elusive. Here, we use the kagome metal ScV6Sn6 as a platform to investigate this problem, since it features both a kagome-derived nested Fermi surface and van-Hove singularities near the Fermi level, and a charge-ordered phase that strongly affects its physical properties. By combining time-resolved reflectivity, first principles calculations and photo-emission experiments, we identify the structural degrees of freedom to play a fundamental role in the stabilization of charge order, indicating that ScV6Sn6 features an instance of charge order predominantly originating from phonons.
Materials of engineering and construction. Mechanics of materials
Jaume Gomez-Caturla, Nestor Montanes, Luis Quiles-Carrillo
et al.
The present work reports on the development of environmentally friendly, completely biodegradable wood plastic composites based on polylactide (PLA) and tangerine peel flour (TPF), plasticized by α-terpinyl acetate (TA). The TPF varied in the 10–30 wt% while the PLA to TA (wt%/wt%) was set to 4 (i.e., 25 wt% TA plasticizer was added with regard to the PLA wt%). The developed composites were processed by extrusion and injection molding. The composites presented excellent elongation at break, achieving values of 300% for the PLA+TA sample. Elongation at break values of 200% for the PLA composite with 10 wt% TPF and plasticized with TA were obtained. Those results were confirmed by the appearance of filament-like structures observed in field emission scanning electron microscopy images. Differential scanning calorimetry and dynamic mechanical thermal analysis revealed a remarkable decrease in the glass transition temperature of PLA as a result of the plasticizing effect of TA. Glass transition was reduced from 63°C down to 41°C approximately. This implied an increase in the ductility of the material. The samples with TPF exhibited a dark brown color, making them perfect for wood plastic composite applications. Water contact angle results show that TA and TPF change the wetting properties of the obtained composites. A general decrease in the water contact angle was observed with the addition of TPF and TA. Finally, disintegration tests proved that the developed composites are fully biodegradable. All the samples except for neat PLA achieved 100% disintegration in controlled compost soil conditions after 5 weeks, while neat PLA reached complete disintegration in 6 weeks.
Materials of engineering and construction. Mechanics of materials, Chemical technology
Serena Lima, Antonino Biundo, Giuseppe Caputo
et al.
As known, microalgae are an appealing source of chemicals and high-value compounds which find application in nutraceuticals, cosmetics and pharmaceutics. Fatty acids (FA), in particular, have drawn attention to the possibility of employing them as a source of biodiesel alternatively to fossil fuels. In addition, several lipid derivatives have been found in microalgae and may be employed in several biotechnological applications. Hydroxy fatty acids can be substrates for several industrial applications thanks to their functionalization, which increases their reactivity and, for this reason, can be used as functional building blocks to produce a multitude of bio-based materials. Recently, a promising method for the chemical modification of unsaturated-FAs (U-FA) has appeared. In fact, U-FA may be modified by members of the hydratase enzyme family to produce saturated and unsaturated hydroxy fatty acids with high stereo- and regio-selectivity. These enzymes are able to introduce a water molecule to the double bond present in the free fatty acids (FFA) Oleic Acid (OA), Linoleic Acid (LA), producing 10-hydroxy fatty acids (10-hydroxy-FAs).
Furthermore, the carbohydrate component of the microalgal biomass may be converted into furfuryl compounds and, in particular in 5-hydroxyl methyl furfural (5-HMF). This is one of the chemical bio-compound different from petroleum-derived ones with the highest added value and may be obtained through lignocellulosic biomasses or hexoses sugars through acid catalysis. It is defined platform molecule because it is the precursor of several compounds for the chemical industry.
In this work, we aimed to optimize a circular bioprocess by performing, starting from the same biomass, two different processes: the biotransformation of microalgal FFAs through the employment of a genetically modified E. coli on one side, and the conversion of the remaining biomass in furfuryl products. The first process allowed the production of very interesting lipid derivatives with biotechnological applications, including 10 hydroxy-stearic acid and 10-hydroxy-octadecenoic acid. The second process was obtained through heterogeneous catalysis based on niobium phosphate. This procedure represents a high-innovative application of microalgal biomass and allows the simultaneous exploitation of FAs and carbohydrates. This may result in an increase in the commercial value of microalgal biomass.
Chemical engineering, Computer engineering. Computer hardware
The thermal stability and crystallization behaviors of La2O3 containing B2O3-CaO–Al2O3 glass waste forms were investigated to evaluate the stability of waste form during emergencies in deep geological disposal. For glasses containing 15% La2O3, LaBO3 phases were observed as major crystals from 780 °C and exhibited needlelike structures. Al, Ca, and O were homogeneously distributed throughout the entire specimen, while some portions of B and La were concentrated in some parts. By differential thermal analysis at various heating rates, the activation energy for grain growth and the crystallization rate of LaBO3 were calculated to be 12.6 kJ/mol and 199.5 kJ/mol, respectively. These values are comparable to other waste forms being developed for the same purpose.
In recent years, new methods concerning risk mitigation techniques in energy planning strategies have become popular. Delarue et al. introduced the integrated portfolio investment model to account for supply–demand constraints. This paper proposes a model which is suitable to the energy management problem of planning the capacity factors of renewable energy technologies used in a strategy with stochastic supply–demand constraints under reliability limitations and evaluating their associated costs. Therefore, we introduce the concept of Power-at-Risk, following the Value-at-Risk formulation to quantify risks on the supply side in an adequate way. This paper extends the integrated portfolio model and introduces a reliability level to account for issues related to the unpredictability in the power output. We analyze cost effects by considering increasing levels of reliability in the supply–demand constraint. The energy planning problem, illustrated in a use case, is solved numerically by the sample approach based on locally calibrated probability density functions of both wind and solar power available. The results quantify risk diversification in renewable energy technologies and show that the associated costs increase exponentially with increasing levels of reliability. Keywords: Risk management, Reliability based design optimization, Stochastic energy planning
The cross-view multimedia are widely existed and attract many attentions in recent years. Nevertheless, it is noted that the phenomenon, that data in different classes from same view are more similar than that in same class from different views, is usually presented for cross-view multimedia data. The intrinsic imperfection leads disappointing performance for cross-view multimedia recognition or classification. To solve this problem, in this paper, we propose a novel discriminative learning framework with low-rank constraint, which can be applied for view-invariant low-dimensional subspace learning. The advantages of our framework include three aspects. Firstly, to unlock the latent class structure and view structure, a self-expressed model by dual low-rank constraints are presented, which can separate the two manifold structures in the learned subspace. Secondly, two effective discriminative graphs are constructed to guide the affinity relationship of data in the above two low-dimensional projected subspaces respectively. Finally, the joint semantic consensus constraint is designed to be integrated into the learning framework, which can explore the shared and view-specific information for enforcing the view-invariant character in semantic space. Experimental results on several public cross-view multimedia datasets demonstrate that our proposed method outperforms existing excellent subspace learning approaches.
Brick elements are widely used for everything from designing toys to architectural designs. This article proposes an intelligent method to construct complex 3D brick models automatically. The proposed method is designed based on a set of core algorithms to generate a brick layout in accordance with a given 3D voxel model. In the system, each 3D model is sliced into tiers of flat vector polygons at first. Then, the vector polygons are converted to raster data for each tier. The bricks are built in a single tier until all tiers are completed. The proposed model is validated using two case studies: one is a series of solid sculpture models and the other is a building model. The results show that the proposed intelligent building system successfully builds visual models from brick assembly models. The proposed system can help engineers build large block models to improve the efficiency of constructing complex 3D building models.
AW-7xxx alloys have been nowadays considered for greater light weighting potential in automotive industry due to its higher strength compared to AW-5xxx and AW-6xxx alloys. However, due to their lower formability the forming processes are still in development. This paper investigates one such forming process called hot stamping. The investigation started by carrying out hot tensile testing of an AW-7xxx alloy, that is, AW-7921 at temperatures between 350°C and 475°C, to measure the strength and formability. Formability was found to improve with increasing temperature and was sensitive to the strain rate. Dynamic recovery is considered as usual reason for the formability improvement. However, examining the precipitation states of the as-received condition and after hot stamping using differential scanning calorimetry (DSC), the dissolution of precipitates was also believed to contribute to this increase in formability. Following solution heat treatment there was no precipitation during cooling across the cooling rates investigated (5–10°C/s). Samples taken from parts hot stamped at 10 and 20 mm s−1 had similar yield strengths. A 3-step paint baking heat treatment yielded a higher postpaint baking strength than a single step treatment.
Materials of engineering and construction. Mechanics of materials
Nano nitrocellulose/cyclotetramethylene tetranitramine (NC/HMX) composite particles were precipitated from their co-solutions by the spray drying method. The nano composite samples were characterized by scanning electron microscope, transmission electron microscope and X-ray diffraction. Impact sensitivity and thermal decomposition properties of nano composites were also measured and analyzed. Results show that the product particles are close to spherical in shape and range from 0.5 μm to 5 μm in size. In the product particles, β-HMX particles with size ranging from 50 nm to 100 nm are uniformly and discretely dispersed in NC binders. The drop height of nano NC/HMX composite particles (66.1 cm) is more than triple as high as that of raw HMX (21.6 cm), exhibiting considerably low impact sensitivity. Moreover, nano composite particles are easier to decompose and decomposed more rapidly than do raw HMX under the thermal stimulus due to the lower peak temperature and activation energy and higher reaction rate. Therefore, nano composites are expected to be candidates filled in high burning rate propellants.
Materials of engineering and construction. Mechanics of materials
With the envisioned era of internet of things, all aspects of Intelligent Transportation Systems will be connected to improve transport safety, relieve traffic congestion, reduce air pollution, enhance the comfort of transportation and significantly reduce road accidents. In internet of vehicles, regular exchange of current position, direction, velocity and so on, enables mobile vehicles to predict an upcoming accident and alert the human drivers in time or proactively take precautionary actions to avoid the accident. The actualisation of this concept requires the use of channel access protocols that can guarantee reliable and timely broadcast of safety messages. This study investigates the application of network coding concept to increase content of every transmission and achieve improved broadcast reliability with less number of retransmissions. In particular, the authors proposed Code Aided Retransmission‐based Error Recovery (CARER) scheme, introduced a request‐to‐broadcast/clear‐to‐broadcast (RTB/CTB) handshake to overcome hidden node problem and reduce packets collision rate. In order to avoid broadcast storm problem associated with the use of RTB/CTB packet in a broadcast transmission, they developed a rebroadcasting metric used to successfully select a vehicle to rebroadcast the encoded message. The performance of CARER protocol is clearly shown with detailed theoretical analysis and further validated with simulation experiments.
Arnaut Dierck, Frederick Declercq, Thomas Vervust
et al.
Designing textile antennas for real-life applications requires a design strategy that is able to produce antennas that are optimized over a wide bandwidth for often conflicting characteristics, such as impedance matching, axial ratio, efficiency, and gain, and, moreover, that is able to account for the variations that apply for the characteristics of the unconventional materials used in smart textile systems. In this paper, such a strategy, incorporating a multiobjective constrained Pareto optimization, is presented and applied to the design of a Galileo E6-band antenna with optimal return loss and wide-band axial ratio characteristics. Subsequently, different prototypes of the optimized antenna are fabricated and measured to validate the proposed design strategy.