Miracle-dz/UniFAR-FTUs huggingface dataset:
Muffin-Type Bakery Product Based on Mexican Mesquite (Prosopis spp.) Flour: Texture Profile, Acceptability, and Physicochemical Properties

In this research, muffin-type bakery products were developed based on wheat flour (WF) and mesquite flour (MF) in the following proportions: WFMF 90:10, WFMF 75:25, and WFMF 50:50. The products were characterized based on various properties in which it was possible to observe that the water activity (aw) did not show a significant change with the increase in the concentration of MF. In addition, the increase in the concentration of MF modified the sensory properties (color, odor, flavor, texture, and acceptance), further decreasing the luminosity and increasing the values of the a* and b* coordinates. Moreover, in the texture profile analysis, it was found that the increase in the MF concentration increased hardness, fracturability, and gumminess and decreased adhesiveness and cohesiveness. All the previously mentioned changes were more evident in the WFMF50:50 and, to a lesser degree, in WFMF75:25. In general, in most evaluations realized, the WFMF90:10 treatment was the most similar to the control (without MF). However, WFMMF75:25 provided a higher protein and fiber content and a lower fat content. Finally, it is possible to use the flour obtained from the mesquite fruit to make bakery products since it is an important source of food due to the wide distribution of mesquite in the country.
Sismicidad de la Península Ibérica en el periodo instrumental: 1985-2011.

espanolEn el ano 1985, el Instituto Geografico Nacional instalo una red sismica con instrumentacion homogenea y senal de tiempo comun. Esto supuso una mejora del registro de la sismicidad de la Peninsula Iberica. Este conocimiento se ha ido incrementando con cambios significativos, tanto en instrumentacion como en metodos de analisis. Se presenta en este articulo la distribucion geografica de esa sismicidad, tanto en magnitud como en profundidad. La sismicidad en la peninsula Iberica es moderada, con sismos importantes de grandes periodos de retorno y su localizacion condicionada a las areas de contacto de las placas Euroasiatica y Africana. Destacan algunos sismos moderados de mas de 500 km de profundidad. EnglishOur knowledge of the seismicity of the Iberian Peninsula has been increasing since 1985, when a homogeneous real time seismic network was installed. With the incorporation of the Sonseca Seismic Array to the routine location process, the knowledge of the Peninsula seismicity has improved, resulting in a very complete catalogue. In this paper we present the geographical distribution of the regional seismicity as a function of the magnitude and depth of the events. The contact areas between European and African tectonic hold most of the epicentres. Also, several very deep seismic sources at more than 500 km are registered in the southern Iberian Peninsula.
Influence of heterogeneity on undrained clay slope stability

This paper concentrates on the fact that natural materials are variable, and that representation of this variability appears crucial to getting a realistic understanding of certain geotechnical problems. In this case, finite elements have been used to assess the influence of heterogeneity on the stability of a clay slope, characterized by a spatially varying undrained shear strength cu. For low to intermediate values of the coefficient of variation (e.g. 0.1–0.3), as are often observed in practice, pointwize variability can be approximated by a normal distribution. Data on spatial variability are more scarce, although vertical scales of fluctuation are usually much smaller than horizontal scales of fluctuation, and will often be small relative to the height of a slope. The results show that, for a given factor of safety, reliability is greatest for cu constant with depth. For cu increasing linearly with depth, reliability decreases due to the greater range of possible rupture surfaces: hence, in conventional (deterministic) design, higher factors of safety (or lower characteristic values) would be needed. In this study, horizontal anisotropy (of the heterogeneity) causes modest changes in reliability. However, problems are identified in which anisotropy is likely to have a significant influence.
Brain volumetric changes in menopausal women and its association with cognitive function: a structured review

The menopausal transition has been proposed to put women at risk for undesirable neurological symptoms, including cognitive decline. Previous studies suggest that alterations in the hormonal milieu modulate brain structures associated with cognitive function. This structured review provides an overview of the relevant studies that have utilized MRI to report volumetric differences in the brain following menopause, and its correlations with the evaluated cognitive functions. We performed an electronic literature search using Medline (Ovid) and Scopus to identify studies that assessed the influence of menopause on brain structure with MRI. Fourteen studies met the inclusion criteria. Brain volumetric differences have been reported most frequently in the frontal and temporal cortices as well as the hippocampus. These regions are important for higher cognitive tasks and memory. Additionally, the deficit in verbal and visuospatial memory in postmenopausal women has been associated with smaller regional brain volumes. Nevertheless, the limited number of eligible studies and cross-sectional study designs warrant further research to draw more robust conclusions.
Temporal variation in the shear wave anisotropy detected using the Accurately Controlled Routinely Operated Signal System (ACROSS)

[1] Temporal variation in shear wave anisotropy was detected in a monitoring experiment using an accurately controlled, routinely operated signal system (Accurately Controlled Routinely Operated Signal System, ACROSS). We conducted an experiment that lasted for 15 months between January 2000 and April 2001 at a site near the Nojima fault, which ruptured during the 1995 Kobe earthquake (Mw 7.2) [Yamaoka et al., 2001; Ikuta et al., 2002]. Two vibration sources that generated 2 × 105 N with centrifugal force, which were firmly fixed on the ground, were used to emit elastic waves. Seismometers deployed at the bottom of 800-m- and 1700-m-deep boreholes near the ACROSS sources were used to receive the signal. We extracted small temporal changes in the travel time of the P and S wave by calculating cross-spectral density among the records every hour. During the experiment, sudden delays in travel times for the S wave were observed when the 2000 western Tottori earthquake (Mw 6.6) and the 2001 Geiyo earthquake (Mw 6.4) occurred. Their epicenters were 165 and 215 km away from the site, respectively. The travel times of the S waves between the surface and the bottom of 800-m-deep borehole abruptly slowed down and gradually speeded up with each earthquake. The delay in S was about 0.4% and 0.1% of the absolute travel time for the western Tottori earthquake and the Geiyo earthquake, respectively. The delays were polarized in a direction perpendicular to the Nojima fault in both cases. This indicates that the density of the cracks parallel to the fault increased in association with the earthquakes. These cracks can be regarded as opened by the increase in pore pressure. The small changes in P wave velocities support this interpretation. An additional experiment to determine the static anisotropy revealed that there was a preferred orientation of the cracks that was enhanced with the strong shaking of earthquakes in the middle distance.
Self-aware face emotion accelerated recognition algorithm: a novel neural network acceleration algorithm of emotion recognition for international students

With an increasing number of human-computer interaction application scenarios, researchers are looking for computers to recognize human emotions more accurately and efficiently. Such applications are desperately needed at universities, where people want to understand the students’ psychology in real time to avoid catastrophes. This research proposed a self-aware face emotion accelerated recognition algorithm (SFEARA) that improves the efficiency of convolutional neural networks (CNNs) in the recognition of facial emotions. SFEARA will recognize that critical and non-critical regions of input data perform high-precision computation and convolutive low-precision computation during the inference process, and finally combine the results, which can help us get the emotional recognition model for international students. Based on a comparison of experimental data, the SFEARA algorithm has 1.3× to 1.6× higher computational efficiency and 30% to 40% lower energy consumption than conventional CNNs in emotion recognition applications, is better suited to the real-time scenario with more background information.
Analysis of World Economic Growth Using Panel Data

In this paper, I consider panel data analysis of world economies to identify the relationship between GDP growth and the independent variables, and the nature of effect that may exist. Annual data for 161 countries from 1990 to 2020 sourced from the World Bank and UN are used. GDP is the independent variable while the independent variables are population, gross value added, total natural resources rent, and labor force. Firstly, a poolability test is performed to test for the joint significance of the fixed effects. The null hypothesis is rejected as there exist significant individual effects. Secondly, Huesman’s test is performed to test for consistency of fixed effect and random effect. The null hypothesis is rejected implying significant random effects exist. Thirdly, Bruesch-Pagan test for heteroscedasticity is performed, which shows the existence of heteroscedasticity. Finally, White’s covariance matrix estimator for random effect is performed which results to consistent and efficient parameter estimate in the presence of heteroscedasticity. The random effect model is statistically significant at the 5% level, with 68 % of the variation being explained by the model. All the explanatory variables are statistically significant at a 5 % level. They all have a positive effect on GDP with the labor force and population having the highest effect. The random effect is large and significant with a variance of 2.25±1.5 and 94.1 % share of the error component. Countries that have had consistent increases in either labor force or population growth or both, has over the period experienced consistent economic growth after controlling for the other variables and the random effect.
Tutorial: Power Analyses for Interaction Effects in Cross-Sectional Regressions

Interaction analyses (also termed “moderation” analyses or “moderated multiple regression”) are a form of linear regression analysis designed to test whether the association between two variables changes when conditioned on a third variable. It can be challenging to perform a power analysis for interactions with existing software, particularly when variables are correlated and continuous. Moreover, although power is affected by main effects, their correlation, and variable reliability, it can be unclear how to incorporate these effects into a power analysis. The R package InteractionPoweR and associated Shiny apps allow researchers with minimal or no programming experience to perform analytic and simulation-based power analyses for interactions. At minimum, these analyses require the Pearson’s correlation between variables and sample size, and additional parameters, including reliability and the number of discrete levels that a variable takes (e.g., binary or Likert scale), can optionally be specified. In this tutorial, we demonstrate how to perform power analyses using our package and give examples of how power can be affected by main effects, correlations between main effects, reliability, and variable distributions. We also include a brief discussion of how researchers may select an appropriate interaction effect size when performing a power analysis.
Geospatial forecast model for tsetse-transmitted animal trypanosomosis in Ethiopia

The aims of this study were to develop a geographic information systems (GIS) forecast and risk assessment model for cyclically transmitted trypanosomosis in Ethiopia by matching features in the environment to available information on the preferences and limits of tolerance of the parasite and its vector, and validate and further develop the GIS model using data from current and historical prevalence survey data and habitat microenvironment studies from trypanosomosis endemic areas. Results indicate that GIS model developed for parasitic diseases based on growing degree day (GDD) concept can be applied to tsetse-transmitted trypanosomosis. GIS for animal trypanosomosis was created using Food and Agriculture Organization – Crop Production System Zones (FAO-CPSZ) database and Normalized Difference Vegetation Index (NDVI) and maximum temperature (Tmax) from the Global Land 1km dataset. The two datasets used to determine the risk of tsetse flies and consequently animal trypanosomosis in Ethiopia indicated the magnitude of the disease and possible expansion of the “fly belt” in the future. The GIS model indicated the distribution and importance of tsetse-transmitted trypanosomosis in Ethiopia. Spatial and statistical analysis verified the use of GDD concept and climate forecast system that was developed to determine the suitability of a given environment for the proliferation of a biotype, in this case tsetse and trypanosomes. Results presented here indicate the importance of GDD and the two climatic variables (NDVI and Tmax) in the development of forecast model for tsetse-transmitted trypanosomosis in Ethiopia. Key words/phrases: Ethiopia, GIS, NDVI, Tmax, trypanosomosis SINET: Ethiopian Journal of Science Vol.27(1) 2004: 1-8
Differences between coastal and open ocean distributions of N 2 O in the oxygen minimum zone off Peru

Depth profiles of nitrous oxide (N2O) were measured during six cruises to the upwelling area and oxygen minimum zone (OMZ) off Peru in 2009 and 2012/13, covering both the coastal shelf region and the adjacent open ocean. N2O profiles displayed a strong sensitivity towards oxygen concentrations. Open ocean profiles showed a transition from a broad maximum to a double-peak structure towards the centre of the OMZ where the oxygen minimum was more pronounced. Maximum N2O concentrations in the open ocean were about 80 nM. A linear relationship between ΔN2O and apparent oxygen utilization (AOU) could be found for all measurements within the upper oxycline, with a slope similar to studies in other oceanic regions. N2O profiles close to the shelf revealed a much higher variability, with N2O concentrations in the upper oxycline reaching up to several hundred nanomoles per liter at selected stations. Due to the extremely sharp oxygen gradients at the shelf, these maxima occurred in very shallow water depths of less than 50 m. In this area, a linear relationship between ΔN2O and AOU could not be observed. N2O concentrations above 100 nM were observed at oxygen concentrations ranging from close to saturation to suboxic conditions. Our results indicate that the coastal upwelling off Peru at the shelf causes conditions that lead to extreme N2O accumulation.
On the biodiversity of diatom communities in lakes of East China: Geochemical effects dominated after eutrophication

Over the last century, lakes all over the world have experienced significant eutrophication and become more susceptible to critical transitions. This has prompted a growing need to understand how community dynamics shift following ecological perturbations. This study aims to elucidate the present status, spatial patterns and determinants of biological diversity, and how they have changed in response to alterations driven by eutrophication.
Designing for people you can’t meet: Persuasive design to nurture seniors’ participation in community services during the COVID-19 pandemic

Abstract During the COVID-19 pandemic, seniors were required to strictly isolate themselves, as the disease affects them disproportionately. Simultaneously, seniors had particular difficulty adjusting to the new reality because they had little experience using digital technologies. This paper presents a service design project implemented to alleviate the social isolation in senior homes during the pandemic. The team utilized a persuasive design strategy to create a six-step service design process with three cycles to nurture the participation of senior residents and facilitate coproduction. The outcome included technology education, communication channels, art events, and tools to support staff in continuing to coproduce the services.
Processes and boreal summer impacts of the 2004 El Niño Modoki: An AGCM study

The sea surface temperature anomalies (SSTA) of tropical Pacific in the boreal summer of 2004 show a distinct tripolar pattern with warm SSTA in the central tropical Pacific, flanked on both sides by cold SSTA. The distinct conditions during the boreal summer of 2004 and the following winter were catalogued as a new coupled phenomenon named El Niño Modoki in a recent generalized study. The 2004 event is unique in the sense that it occurred without any co‐occurring IOD, thereby without any possibility of external modulation of its processes and impacts in the tropics. Using observed data since 1979, we show that the 2004 event indeed involves the distinct equatorial coupled ocean‐atmosphere dynamics different from the conventional El Niño. Further, using an AGCM, we confirm that during boreal summer anomalous twin Walker circulation cells associated with the El Niño Modoki SSTA give rise to observed rainfall anomalies in the tropics.
Analysis of Functional Single-Nucleotide Polymorphisms (SNPs) and Leaf Quality in Tea Collection under Nitrogen-Deficient Conditions

This study discusses the genetic mutations that have a significant association with economically important traits that would benefit tea breeders. The purpose of this study was to analyze the leaf quality and SNPs in quality-related genes in the tea plant collection of 20 mutant genotypes growing without nitrogen fertilizers. Leaf N-content, catechins, L-theanine, and caffeine contents were analyzed in dry leaves via HPLC. Additionally, the photochemical yield, electron transport efficiency, and non-photochemical quenching were analyzed using PAM-fluorimetry. The next generation pooled amplicon–sequencing approach was used for SNPs-calling in 30 key genes related to N metabolism and leaf quality. The leaf N content varied significantly among genotypes (p ≤ 0.05) from 2.3 to 3.7% of dry mass. The caffeine content varied from 0.7 to 11.7 mg g−1, and the L-theanine content varied from 0.2 to 5.8 mg g−1 dry leaf mass. Significant positive correlations were detected between the nitrogen content and biochemical parameters such as theanine, caffeine, and most of the catechins. However, significant negative correlations were observed between the photosynthetic parameters (Y, ETR, Fv/Fm) and several biochemical compounds, including rutin, Quercetin-3-O-glucoside, Kaempferol-3-O-rutinoside, Kaempferol-3-O-glucoside, Theaflavin-3′-gallate, gallic acid. From our SNP-analysis, three SNPs in WRKY57 were detected in all genotypes with a low N content. Moreover, 29 SNPs with a high or moderate effect were specific for #316 (high N-content, high quality) or #507 (low N-content, low quality). The use of a linear regression model revealed 16 significant associations; theaflavin, L-theanine, and ECG were associated with several SNPs of the following genes: ANSa, DFRa, GDH2, 4CL, AlaAT1, MYB4, LHT1, F3′5′Hb, UFGTa. Among them, seven SNPs of moderate effect led to changes in the amino acid contents in the final proteins of the following genes: ANSa, GDH2, 4Cl, F3′5′Hb, UFGTa. These results will be useful for further evaluations of the important SNPs and will help to provide a better understanding of the mechanisms of nitrogen uptake efficiency in tree crops.
Constraining the area of rapid and deep‐seated exhumation at the St. Elias syntaxis, Southeast Alaska, with detrital zircon fission‐track analysis

The Chugach‐St. Elias orogen, Southeast Alaska/Southwest Yukon, formed in response to the ongoing Yakutat microplate subduction‐collision with the North American Plate. Due to heavy glaciation, the region is a prime location to study active convergent orogenesis and climate‐tectonic interactions. This study focuses on the long‐term distribution of deformation in the St. Elias syntaxis area, where dextral motion along the plate‐bounding Fairweather Fault transitions into convergence. We present 2718 new zircon fission‐track single‐grain ages from 26 glaciofluvial outwash samples. The grain ages range from 293 Ma to 0.2 Ma, and each sample contains two to five age populations with peaks between 267 ± 64 Ma and 1.2 ± 0.7 Ma (1σ). The rocks of the Yakutat microplate are dominated by latest Cretaceous and Eocene fission‐track ages, while the rocks of the North American Plate in the syntaxis region reveal two exhumation phases at ~5.1 Ma and ~2.7 Ma. The spatial pattern of ≤5 Ma cooling ages shows that the area of rapid and deep exhumation at the St. Elias syntaxis is more extensive than previously known and confined to the south by the Fairweather Fault, to the west by the Seward Glacier catchment, and to the east possibly by the inferred Connector Fault. The area seems to be ~4800 km2 large and may extend farther to the north. The new zircon fission‐track data further suggest a transpressional plate boundary since ~30 Ma and the onset of plate collision 15–12 Ma.
Single image dehazing using frequency-guided filtering and progressive physics learning

Abstract. Current learning-based dehazing methods simply rely on the paired synthetic datasets and physical models, which can hardly describe the complicated degradation for practical applications. These methods still struggle to achieve haze removal, color distortion, and detail restoration instantly, and they ignore the frequency characteristic differences and prior knowledge importance. To address these problems, we propose an unpaired stage-wise framework integrating frequency-guided filtering and progressive physics learning in an adversarial dehazing network, called FPD-Net. To be specific, a guided filter based on frequency information is employed to decompose the high and low frequency components for better feature extraction. We further merge the prior and physical knowledge to form progressive physics learning, which produces pleasing haze-free outputs with high visibility and reality. For better atmospheric light estimation, the variational auto-encoder and Kullback–Leibler loss are included to represent the illumination message. Extensive experiments on both synthetic and real datasets prove that our designed FPD-Net achieves better performance visually and quantitatively than the comparison dehazing models.