Miracle-dz/UniFAR-FTUs huggingface dataset:
Facial emotion detection using thermal and visual images based on deep learning techniques

ABSTRACT The main objectives of this study are (i) to determine the different emotions, such as happy, anger, neutral, and sad, based on the visual and thermal images for facial expression recognition of healthy individuals; (ii) to train the modified pre-trained models, such as DenseNet-121, ResNet-50, and VGG-19 based on transfer learning technique, using the visual and thermal image dataset, and (iii) to compare the three different customize model with that of three pre-trained models in terms of accuracy. The customized CNN models were proposed to classify the four classes of emotions with high efficiency. Among thermal and visual image dataset, the thermal images have produced highest classification accuracy of 95.8% using the Customized Net-3 model and have outperformed the three modified pre-trained models while classifying the four facial expressions. Thus, the proposed customized CNN model is proven effective for facial emotion recognition based on thermal imaging using deep learning techniques.
The Relations between Repetitive Behaviors and Family Accommodation among Children with Autism: A Mixed-Methods Study

Restricted and repetitive behaviors and interests (RRBI) are a significant component in diagnosing autism spectrum disorder (ASD). They often pose the main challenge in day-to-day functions for children with ASD and their families. Research addressing family accommodation behaviors (FAB) in the ASD population is scarce, and associations with the characteristics of the children’s behaviors are unclear. This sequential mixed-methods study assessed the correlation between RRBI and FAB within the ASD group to deepen the understanding of parents’ subjective experiences regarding their children’s RRBI. It included a quantitative phase with a follow-up qualitative study. A total of 29 parents of children with autism (5–13 yr) completed the study questionnaires; a total of 15 also were interviewed regarding their children’s RRBI and related FAB. We used the Repetitive Behavior Scale-Revised (RBS-R) to assess RRBI, and the Family Accommodation Scale (FAS-RRB) to assess FAS. In-depth interviews from phenomenological methodology were used in the qualitative phase. We found significant positive correlations between the RRBI and FAB overall and their subscores. Qualitative research supports these findings, adding descriptive examples of the accommodations families make to address the RRBI-related challenges. The results indicate relations between RRBI and FAB and the importance of practically addressing children with autism’s RRBI and their parents’ experiences. Both affect and are affected by the children’s behaviors.
Ferroelectric synaptic devices based on CMOS-compatible HfAlOx for neuromorphic and reservoir computing applications.

The hafnium oxide-based ferroelectric tunnel junction (FTJ) has been actively researched because of desirable advantages such as low power and CMOS compatibility to operate as a memristor. In the case of HfAlOx (HAO), the remanent polarization (Pr) value is high and the atomic radius of Al is smaller than that of Hf; therefore, ferroelectricity can be better induced without mechanical force. In this paper, we propose an FTJ using HAO as a ferroelectric layer through electrical analysis and experiments; further, we experimentally demonstrate its capability as a synaptic device. Moreover, we evaluate the maximum 2Pr and TER value of the device according to the difference in conditions of thickness and cell area. The optimized device conditions are analyzed, and a large value of 2Pr (>∼43 μC cm-2) is obtained. Furthermore, we show that paired-pulse facilitation, paired-pulse depression, and spike-timing-dependent plasticity can be utilized in HAO-based FTJs. In addition, this study demonstrates the use of an FTJ device as a physical reservoir to implement reservoir computing. Through a series of processes, the synaptic properties of FTJs are verified for the feasibility of their implementation as an artificial synaptic device.
LC-MS/MS Method Minimizing Matrix Effect for the Analysis of Bifenthrin and Butachlor in Chinese Chives and Its Application for Residual Study

The matrix effect refers to the change in the analytical signal caused by the matrix in which the sample is contained, as well as the impurities that are co-eluted with the target analyte. In crop sample analysis using LC–MS/MS, the matrix effect can affect the quantification results. Chinese chives are likely to exhibit a strong matrix effect when co-extracted with bifenthrin and butachlor due to the presence of phytochemicals and chlorophyll. A novel analytical method was developed to reduce the matrix effects of bifenthrin and butachlor to a negligible level in Chinese chives. The established method had a limit of quantitation of 0.005 mg/kg and correlation coefficients greater than 0.999 within the range of 0.005–0.5 mg/kg. Matrix effects were found to be negligible, with values ranging from −18.8% to 7.2% in four different sources of chives and two leafy vegetables. Compared to conventional analytical methods for the LOQ and matrix effect, the established method demonstrated improved performances. The analytical method was further applied in a residual study in chive fields. The active ingredient of butachlor 5 granule (GR) was not detected after soil admixture application, while that of bifenthrin 1 emulsifiable concentrate (EC) showed a range from 1.002 to 0.087 mg/kg after foliar spraying. The dissipation rate constant (k) of bifenthrin was determined to be 0.115, thus its half-life was calculated to be 6.0 days. From the results, PHI and safety use standards of both pesticides were suggested. The developed analytical method can be applied to accurately determine bifenthrin and butachlor residues in Chinese chives and provides a foundation for further research on the fate and behavior of these pesticides in the environment.
The Scary Black Box: AI Driven Recommender Algorithms as The Most Powerful Social Force

Recommender algorithms shape societies by individually exposing online users to everything they see, hear and feel in real time. We examine the development of recommender algorithms from the Page Rank and advertising platforms to social media trending tools to draw conclusions about their social effects. Decisions on how to simplify the complex world around us into dozens of possibilities immensely affect societies and individuals. Similar to our perceptive apparatus, algorithms are eyes and ears in the online world, as they focus our attention towards what they "think" should be important, which is similar to news priming. That is why recommender algorithms are compared to mass media, given their similar roles to sell products and prolong content exposure of online users. This inquiry concludes that AI driven recommender algorithms represent the most powerful social force at present.
Homogenization of Periodic Structures Using the Multimodal Transfer Matrix Method

This work presents a method for obtaining the constitutive parameters of periodic structures from the computation of their dispersion relation and average fields. The method uses the scattering parameters (S-parameters) of multiple Bloch modes of a single unit cell. The corresponding multimodal scattering matrix is obtained with a suitable general-purpose electromagnetic software. Further post-processing of this scattering matrix is then carried out, which allows for the computation of the dispersion relation of structures with realistic finite conductivity or made of lossy dielectrics, as well as the calculation of the attenuation constant and the retrieval of the impedance, permittivity, and permeability. The proposed method is applied to homogenize some systems of interest: an artificial electric plasma built with wires, a free-space matched left-handed metamaterial based on two laterally shifted split ring resonators, a high-permittivity artificial dielectric based on densely arranged square metal patches, and a $\mu $ -near-zero metamaterial made of metallic cubes embedded in a dielectric. The retrieved material parameters are found to accurately describe the scattering of finite samples of the corresponding homogenized structures. This research is limited to orthorhombic unit cells smaller than half the free-space wavelength to avoid diffracted beams. Besides, since only one propagation direction is considered, only the transverse components of constitutive parameters are retrieved.
Free and Low-Cost Aerial Remote Sensing in Archaeology

ABSTRACT Recent years have seen the rapid expansion of airborne and spaceborne remote-sensing products adopted by archaeologists for interpreting ancient landscapes and managing heritage resources. A growing and increasingly specialized literature attests to the promise and availability of commercial and publicly funded satellite imagery, as well as UAV-mounted sensors across a range of resolutions and price points. In the South Caucasus (including the countries of Armenia, Azerbaijan, and Georgia), a growing commitment to landscape approaches in archaeology is stimulating the adoption of satellite remote sensing as an important new tool for identifying and managing archaeological resources while tracing the impact of historic land-use alterations in survey areas. Nevertheless, budgetary challenges and a lack of training opportunities among international partners and heritage organizations outside of the funding streams of large academic institutions can lead to widening technological gulfs in the discipline that reinforce colonial relationships. Building on recent technical articles covering specific imagery datasets, this article aims to address this by providing a general review of free or low-cost remotely sensed datasets available to archaeologists, with the aim of broadening awareness of these important tools and their vocabularies, and illustrating them with recent published examples from the South Caucasus.
The generation mechanism and identification of spatially non-continuous error in integral multi-station measurement systems

The integral multi-station measurement system represented by indoor GPS, workshop Measuring and Positioning System or a multi-camera system, realizes high-precision 3D measurement in large-scale space by constructing a global measurement field within a unified temporal-spatial reference. In advanced equipment manufacturing sites such as robot machining, large component (the fuselage or wing of airplanes) assembly and monitoring, the integral multi-station measurement system overcomes the drawbacks of the single-station measurement system such as laser tracker that can hardly balance the measurement range and accuracy. However, with the improvement of automation and intelligence degree in equipment manufacturing, the requirements on accuracy and robustness has become more and more strict, which is a huge challenge to existing measuring technologies. Limited by the measurement principle of multi-observation intersection, the change of geometry constraint in the integral multi-station measurement field will lead to spatially non-continuous error, degrading the performance of the integral multi-station measurement system. In this paper we first analyze the mechanisms and characteristics of spatially non-continuous error at the geometry constraint level. Basing on the error propagation model, a criterion for evaluating the significance of non-continuous error is then proposed for error identification. Finally, simulations and experiments are carried out, and this proposed criterion is verified to be effective.
Nuevos desafíos para las universidades en países subdesarrollados

Las funciones tradicionales de las UUNN (docencia, investigación y extensión) se han visto, en los últimos años, enfrentadas a nuevas demandas y han sufrido cambios importantes en un proceso que no se ha detenido, sino que augura un crecimiento permanente de las demandas por parte de la sociedad. a la par con la creciente importancia del conocimiento en la vida económica. Esto implica un crecimiento exponencial de oportunidades, posibilidades, expectativas y, en consecuencia, responsabilidades para las instituciones universitarias. Dicha situación ha llevado a asumir un mayor protagonismo y diversificar sus funciones abarcando un campo de actuación más amplio y complejo, con el que han ampliado sus actividades, sus compromisos y su visibilidad y presencia en la sociedad. La relevancia del conocimiento como factor competitivo y su impacto en el desarrollo de las naciones y el bienestar de la sociedad refuerza la importancia de incrementar la apropiabilidad social de los resultados de las actividades desarrolladas por el campo científico. En base a esto, este trabajo explora el potencial que tienen las universidades de asumir un nuevo rol para catalizar procesos de apropiación de conocimiento, convirtiéndose así en Agencias de Desarrollo.
Impaired Melatonin Secretion, Oxidative Stress and Metabolic Syndrome in Night Shift Work

Metabolic syndrome has been associated in many studies with working in shifts. Even if the mechanistic details are not fully understood, forced sleep deprivation and exposure to light, as happens during night shifts, or irregular schedules with late or very early onset of the working program, lead to a sleep–wake rhythm misalignment, metabolic dysregulation and oxidative stress. The cyclic melatonin secretion is regulated by the hypothalamic suprachiasmatic nuclei and light exposure. At a central level, melatonin promotes sleep and inhibits wake-signals. Beside this role, melatonin acts as an antioxidant and influences the functionality of the cardiovascular system and of different metabolic processes. This review presents data about the influence of night shifts on melatonin secretion and oxidative stress. Assembling data from epidemiological, experimental and clinical studies contributes to a better understanding of the pathological links between chronodisruption and the metabolic syndrome related to working in shifts.
GEDI: A New LiDAR Altimetry to Obtain the Water Levels of More Lakes on the Tibetan Plateau

Remote sensing is an effective means for lake water level monitoring on the Tibetan Plateau (TP). The purpose of this study is to estimate water levels of lakes on the TP using the Global Ecosystem Dynamics Investigation (GEDI) and Cloud and Land Elevation Satellite-2 (ICESat-2), evaluate the performance of ICESat-2 and GEDI in estimating water levels, and analyze the differences of water level obtained by the two altimeters. The results showed that the average coefficient of determination (R2) values between the estimated water levels (GEDI and ICESat-2) and the datasets (DAHITI and Hydroweb) were greater than 0.80, respectively. The water level of DAHITI and Hydroweb are mainly from radar nadir altimeters. The average root mean square error (RMSE) between GEDI and DAHITI was 0.54 m, between GEDI and Hydroweb was 0.38 m for Qinghai Lake. The average RMSE of Qinghai Lake between ICESat-2 and DAHITI was 0.50 m, and between ICESat-2 and Hydroweb was 0.28 m. The comparison results showed that the accuracy of GEDI seems to be slightly lower than that of ICESate-2. The main impact indicators of the difference between the GEDI and ICESat-2 in lake level estimations were the viewing angles (VAs), solar elevation, air temperature, and wind. From 2019 to 2021, GEDI covered 770 more lakes than ICESat-2, and the lake level fluctuation mainly occurred in the Inner Plateau and Yangtze basins. The GEDI can effectively estimate lake levels, which provides more water levels for lakes and lays a foundation for future research on the TP.
Elliptic and parabolic equations with fractional diffusion and dynamic boundary conditions

We investigate a class of semilinear parabolic and elliptic problems with fractional dynamic boundary conditions. We introduce two new operators, the so-called fractional Wentzell Laplacian and the fractional Steklov operator, which become essential in our study of these nonlinear problems. Besides giving a complete characterization of well-posedness and regularity of bounded solutions, we also establish the existence of finite-dimensional global attractors and also derive basic conditions for blow-up.
On the Advancements in Boiling, Two-Phase Flow Heat Transfer, and Interfacial Phenomena

Phase change by boiling or evaporation is a highly efficient heat ransport mechanism, which accommodates large heat fluxes with elatively small driving temperature differences. This mode of eat transfer is in fact encountered in a wide spectrum of engieering systems that include, among others, energy conversion, efrigeration and air-conditioning, chemical thermal processing, eat treatment and manufacturing, microelectronic cooling, and umerous microscale devices microelectromechanical systems MEMS , MTMS, -TAS, sensors, microheat pipes, biochips or ab-on-chips, etc. that are emerging in the current wave of new evelopments and changing applications. The consequent research nterest, spanning more than two centuries of work with an everncreasing literature database, is therefore not surprising 1–10 . he energy crunch with attendant needs for higher thermal effiiencies and demands for mitigation of environmental degradation n recent years have further led to efforts to enhance boiling heat ransfer 11–15 . The explosive growth in research and its technical literature eneration in the last six decades or so 8–10,14,16,17 has conidered a variety of fundamental and applied aspects of this intrinically complex heat transport process in order to advance our asic understanding as well as provide design tools. The contined interest in the field is further articulated in the set of papers ppearing in this special issue of the Journal of Heat Transfer, and hey address the many technical challenges that are still presented y the intricacies of heat transfer by means of boiling and forcedonvective two-phase flow, and the concomitant interfacial pheomena. In its evolutionary essence, this field of scientific and ngineering engagement is at once quite ancient in its simplicity nd elegance of application, and yet complexly modern in its exerimental investigations, theoretical modeling, and computaional simulations 16,18–20 .
Uniform Geometrical Theory Of Diffraction

Keller's geometrical theory of diffraction (GTD) represents a major breakthrough in solving a wide variety of electromagnetic (EM) radiation and scattering problems at high frequencies. In particular, the GTD is an extension of geometrical optics to include the class of diffracted rays via a generalization of Fermat's principle. These diffracted rays are initiated at certain localized parts of an illuminated surface, e.g., edges, vertices, and shadow boundaries associated with smooth convex bodies. However, being a purely ray optical theory, the original GTD fails within the transition regions adjacent to geometric optical shadow boundaries. This and other limitations of the GTD can be overcome via a new uniform version of the GTD-or the UTD, which requires the diffracted field to make the total high frequency field continuous across the optical shadow boundaries. Attention is focussed on some UTD solutions developed recently at the O.S. U. ElectroScience Laboratory; e.g., for the problems of EM diffraction by perfectly-conducting edges, vertices and convex surfaces, and also by a thin dielectric half plane. A few selected applications of these UTD solutions to predict the EM radiation and scattering from complex structures such as aircraft, missile or spacecraft shapes are illustrated.
Complex particle swarm optimization algorithm for solving travelling salesman problem

Aimed at many fields' combinational optimization problems being transformed into travelling salesman problem(TSP),a complex particle swarm optimization(CPSO) algorithm was put forward to solve TSP.All points were arranged according to the fitness value in each iterative step of the algorithm,and the good points and the bad points were made pairs respectively.One place of line was confirmed by the ratio of midpoint fitness and good point fitness values in a pair points' line,and one point was selected from the place.The selected point and the difference point of bad point and best point were linearly combined,and a new point was formed to replace the bad point.Five operations for solution sequence of TSP were posed,and CPSO for solving TSP was obtained.The problems of 14 points TSP and optimal moving path for printed circuit board(PCB) were solved.Results show that compared with genetic algorithm and ant colony optimization,the proposed algorithm has more powerful search property,more stable and converges faster.
In Vitro Cytotoxic Effect of Aqueous Extracts from Leaves and Rhizomes of the Seagrass Posidonia oceanica (L.) Delile on HepG2 Liver Cancer Cells: Focus on Autophagy and Apoptosis

Simple Summary Posidonia oceanica is a widely distributed and abundant endemic seagrass in the Mediterranean area. In the attempt to identify new compounds that might inhibit specific targets in the signal transduction of liver carcinogenesis, aqueous extracts from green and brown (beached) leaves and rhizomes of the plant were prepared and tested for their cytotoxic activity on HepG2 hepatic cancer cells in culture. Here, we have identified the death-promoting mechanisms of green-leaf and rhizome extracts that involve the modulation of autophagy, apoptosis, and cell redox status, although partially differentiating conceivably due to their different compositions. These marine-derived natural materials are worth further exploration aimed at developing novel alternative prevention and/or treatment agents against liver tumors and beneficial supplements for the formulation of functional food and food-packaging material endowed with antioxidant and anticancer properties. Abstract Aqueous extracts from Posidonia oceanica’s green and brown (beached) leaves and rhizomes were prepared, submitted to phenolic compound and proteomic analysis, and examined for their potential cytotoxic effect on HepG2 liver cancer cells in culture. The chosen endpoints related to survival and death were cell viability and locomotory behavior, cell-cycle analysis, apoptosis and autophagy, mitochondrial membrane polarization, and cell redox state. Here, we show that 24 h exposure to both green-leaf- and rhizome-derived extracts decreased tumor cell number in a dose–response manner, with a mean half maximal inhibitory concentration (IC50) estimated at 83 and 11.5 μg of dry extract/mL, respectively. Exposure to the IC50 of the extracts appeared to inhibit cell motility and long-term cell replicating capacity, with a more pronounced effect exerted by the rhizome-derived preparation. The underlying death-promoting mechanisms identified involved the down-regulation of autophagy, the onset of apoptosis, the decrease in the generation of reactive oxygen species, and the dissipation of mitochondrial transmembrane potential, although, at the molecular level, the two extracts appeared to elicit partially differentiating effects, conceivably due to their diverse composition. In conclusion, P. oceanica extracts merit further investigation to develop novel promising prevention and/or treatment agents, as well as beneficial supplements for the formulation of functional foods and food-packaging material with antioxidant and anticancer properties.