Miracle-dz/UniFAR-FTUs huggingface dataset:
Technological Spotlights of Digital Transformation in Tertiary Education

In the current globalization trend, digital transformation is an indispensable requirement that affects all aspects of life. Within the education domain, it creates opportunities for tertiary education institutions to replace traditional teaching, learning, research, and operation methods with more innovative, creative, and cost-effective methods. This article aims to examine recent technological advancements to promote the transformation in tertiary education. Our research methodology consists of two main activities: 1) identifying relevant literature on the use of technology to promote transformation in tertiary education by adopting PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines; 2) conducting a thematic analysis based on the findings of the literature review; to explore the relationships between them in order to better understand the link between technological trends and digital transformation in tertiary education. The findings indicate that the current technology trends that are being concerned and deployed in the educational environment are Artificial intelligence, the Internet of Things, blockchain technology, and other relevant platforms and technologies such as Social networks, Mobile platforms, Big data analytics, Cloud computing, Robotic Process Automation, Virtual reality and Augmented reality and Additive manufacturing. The article also discusses the adjustment of tertiary education in the process of digital transformation with the support of technology and points out the shortcomings as well as research directions in the coming time.
Genetic algorithms with analytical solution

We study a class of genetic algorithms (GA) based on a population of chromosomes with mutation and crossover, as well as fitness. The chromosomes in these algorithms also have another property we call "activity" (which determines how fast a chromosome may mutate or interact with other chromosomes). We represent these algorithms by a multi-dimensional Markov process, and provide a new closed form expression for the probability distribution of the number of chromosomes of each type. Specifically we prove that in steady-state: (i) the joint steady-state probability of the number of chromosomes of each type is the product of the marginal probabilities for each type of chromosome, and (ii) the marginal probability of the number of chromosomes of each type has a geometric distribution. Another question we address is that of the choice of the GA parameters for a specific problem. We show that it is possible to choose parameters using a gradient based learning algorithm of complextity O(n3) and we apply this concept to the choice of the fitness parameter for our GA model.
INTELLIGENT AGENT AND ITS APPLICATIONS IN E-COMMERCE

The technologies of the intelligent agents and multi-agent systems are becoming the most important approaches in which complex, distributed, open systems are conceptualized and implemented. This article presents the overview of the agent, after the history of agent is given, the article poses the theory of agent, also it includes a short review of current and potential applications of agent technologies, also the description of the IA based experimental E-Commerce platform of our research is given in this part, and it concludes the prospect of the IA technologies.
Genetic Population Flows of Southeast Spain Revealed by STR Analysis

The former Kingdom of Granada, comprising the provinces of Granada, Málaga, and Almería (GMA), was once inhabited for over 700 years (711–1492 AD) by a North African population, which influenced its creation and establishment. The genetic data on 15 autosomal short tandem repeats (STRs) in 245 unrelated donor residents were examined in order to assess any possible admixture. As the two surnames in Spain follow an inheritance similar to the Y chromosome, both surnames of all 245 unrelated individuals were queried and annotated. The Spanish Statistics Office website was consulted to determine the regions with the highest frequency of individuals born bearing each surname. Further, several heraldry and lineage pages were examined to determine the historical origin of the surnames. By AMOVA and STRUCTURE analysis, the populations of the three provinces can be treated genetically as a single population. The analysis of allele frequencies and genetic distance demonstrated that the GMA population lay in the Spanish population group but was slightly more similar to the North African populations than the remainder of the Spanish populations. In addition, the surnames of most individuals originated in Northern and Central Spain, whereas most surnames had higher frequencies in Southern Spain. These results confirm that the GMA population shows no characteristics that reflect a greater genetic influence of North African people than the rest of the populations of the Iberian Peninsula. This feature is consistent with the historical data that African inhabitants were expelled or isolated during the repopulation of the region with Spaniards from Northern Spain. The knowledge of present populations and their genetic history is essential for better statistical results in kinship analyses.
Intergroup relations affect depressive symptoms of Indigenous people: Longitudinal evidence

One thousand eight hundred thirty-five individuals who self-identified as Indigenous (with Mapuche being the largest group) participated in a two-wave longitudinal survey conducted in Chile with an 18 months lag. This was an approximately nationally representative sample of residents from culturally diverse communities. The aim of the study was to identify protective and adverse factors that are related to the development of depressive symptoms in Indigenous people. It was hypothesized that perceived social support would be negatively related to the development of depressive symptoms and that perceived discrimination would be positively associated with depressive symptoms, so that being on the receiving end of discrimination would make the manifestation of depressive symptoms more likely. Social support and perceived discrimination were themselves predicted to be affected by acculturation preferences and skin pigmentation. It was hypothesized that a positive acculturation orientation towards both the Indigenous group and members of non-Indigenous majority society would be associated with more perceived social support. Hence, preference for culture maintenance and preference for cross-group contact were expected to be positively related to social support. Further, it was hypothesized that darker skin pigmentation would be associated with more experiences of discrimination. Taken together, two processes were expected to affect depressive symptomatology: a protective effect of acculturation preferences mediated by social support and a deleterious effect of pigmentation mediated by experiences of discrimination. Results confirmed the predictions cross-sectionally but longitudinal effects were only found for the deleterious effect of pigmentation; the protective effect of acculturation preferences was notably weaker over time. These findings have both theoretical and applied implications.
Highly Sensitive QCM Humidity Sensor Based on Fullerenol-Assisted Dispersion of Nafion/MWCNTs Composites

Water seepage of building walls is a common problem in our lives. However, the lack of early seepage detection methods often makes the problem worse. To develop effective early wall seepage detection methods, an ultrasensitive quartz crystal microbalance (QCM) humidity sensor based on fullerenol (C60-OH)-assisted dispersion of Nafion/multiwalled carbon nanotubes (MWCNTs) composites is proposed. The prepared sensor shows almost seven times higher frequency shift than pure Nafion-based sensor, which reaches −10814 Hz. This is mainly attributed to the uniform dispersion of MWCNTs in the Nafion with the assistance of C60-OH to form a reticular structure that generates more voids, which greatly improves the diffusion ability of water molecules in the composite materials and thus further enhances humidity sensing properties of the sensor. The high-performance QCM humidity sensor is expected to be used for early detection of water seepage in building walls by monitoring air humidity changes near the wall surface.
Pyrus calleryana extracts reduce germination of native grassland species, suggesting the potential for allelopathic effects during ecological invasion

Invasive plant species’ success may be a result of allelopathy, or the release of secondary metabolites that are harmful for surrounding plant species. Allelopathy can be mediated through the abiotic environment by chemical sorption or transformation, so the substrate on which interactions occur can lead to differential outcomes in allelopathic potential. One aggressive invader, Pyrus calleryana, has become dominant in many ecosystems throughout Eastern US, and has reduced the abundance of native species where it invades. Thus, our goal was to identify if P. calleryana had allelopathic potential by testing the impact of leaf and flower leachate on gemination of six common grassland species (three grasses and three forbs) in either sterilized sand or field collected soils. Germination of five out of six tested species was reduced by P. calleryana leaf litter, with weaker impacts from flower leachate. This suggests that allelopathy is one mechanism driving the success of P. calleryana and that allelopathic effects may change with plant phenology. For instance, P. calleryana has late leaf senescence in the fall and copious blooming in the spring that may elongate the timeframe that allelopathic inhibition can occur. Further, germination was higher in sand than in soil, suggesting that the context of the abiotic environment can mediate this relationship. In our study, two grass species that could be overabundant in restored grasslands had higher germination rates in soil than sand and one was not altered by P. calleryana suggesting that this relationship could further promote the overabundance of grass species. Taken together, P. calleryana likely inhibits the germination of native species where it invades, but there is context dependency of this relationship with both soil chemistry and seasonality.
The F-transform in Terms of Image Processing Tools

In the proposed contribution, we have discussed the usefulness of the higher degree $F^p$-transforms, $p=0,1$, for various tasks of image processing. We show that an image can be efficiently represented as a matrix of its F-transform components. We analyze the details and discuss advantages of this type of representation. We show that in a particular case, components of the $F^0$-transform can be obtained with the help of the operation of convolution, and components of the $F^1$-transform can be obtained with the help of convolution with three different kernels. We give image illustrations of all made assertions.
Comparison of different survey and calculating methods of forestland area

In order to increase the accuracy of forestland area calculation, the authors compare several calculating methods, and compare the accuracies of surveying with instrument and those of measuring on map for forestland area. Results show that the accuracy of the former is higher, because the latter fails to eliminate the system error. At last, the authors emphasize on deducing Cubic Spline to survey forestland area, comparing simulation theories of ladder_shaped formula, Simpson formula, equate_interval Cubic Spline formula and Cubic Spline for the irregular curve of forestland area. Through the test on experimental plots of Chinese Science Society, the authors analyze the accuracies of above_mentioned four methods, and conclude that Cubic Spline has the highest accuracy and is convenient for RTD GPS operation.
ANALYSIS OF THE FLOW IN PIPE-NETWORK

For an incompressible fluid flowing in a line of pipes and pumps in series, Bernoulli's equation can be effectively applied to solve any particular flow problem. When the pipe system consists of a number of complicated branches and cycles, a systematic method for the analysis of the flow system is yet in need. In this article, by transforming the general formula of the pressure drop in pipes into the form, of linear element with respect to flow rate, and further, by introducing the idea of a "complete stream", a set of simultaneous linear equations can be obtained. Such equations can then be represented in the form of matrix, which, besides presenting the equations in a regular form, also makes possible the solution by using digital computers.
The impact of interior plasma dynamics on the shape and size of Saturn's magnetosphere

This thesis explores the impact of rotational and plasma dynamics on the geometry and variability of the location of Saturn's magnetopause, using data obtained by the Cassini spacecraft. A significant departure was identified between the observed location of the high-latitude magnetopause and that predicted by the axisymmetric Kanani et al. model. This model was derived from equatorial measurements made earlier in the mission. The departure demonstrated for the first time that Saturn's magnetosphere is subject to significant 'polar flattening'. It was found that variability in the suprathermal plasma pressure causes dramatic changes in the location of the magnetopause. Such variability had previously been attributed to changes in the solar wind dynamic pressure, but these observations showed that internally driven plasma dynamics imparts a similar degree of variability in the location of the standoff point (up to ~10-15 planetary radii). This effect was incorporated into an empirical magnetopause model and significantly improved the agreement between the observations and the model predictions. In the final part of this study, the structure of the magnetopause was examined in greater detail. Firstly, it was found that the magnetosphere extends further at dawn than dusk. This may be caused by the flow of plasma around the planet, which opposes the solar wind on the morning side of the magnetosphere, but flows in the same direction as the solar wind at dusk. The large dataset collected throughout this study also spans approximately nine years, a significant fraction of a Saturnian season. Additional analysis revealed that the geometry of the magnetopause changes with season, in agreement with theoretical studies. Specifically, a north-south asymmetry is introduced away from equinox whereby the magnetopause is further flattened in the winter hemisphere relative to the north-south symmetric equinoctial magnetopause. This is in addition to the contribution from the centrifugally confined thermal plasma.
Intellectual Virtues and Scientific Endeavor: A Reflection on the Commitments Inherent in Generating and Possessing Knowledge

In this essay, I reflect on the implications of intellectual virtues in scientific endeavor. To this end, I first offer a depiction of scientific endeavor by resorting to the notion of academic attitude, which involves aspects concerning the generation and possession of knowledge. Although there are differences between these activities, they have in common the engagement of diverse intellectual agents (scientists). In this sense, I analyze how intellectual virtues are linked to 1) scientific research tasks, such as theory appraisal, and 2) those tasks of vigilance and intervention in the uses of scientific knowledge. I conclude that intellectual virtues play a leading role in achieving higher quality scientific research and adequate foresight on the uses and impacts of scientific findings. In this order of ideas, I propose an agenda for further inquiries on these matters, highlighting the relevance of reflecting and empirically researching the relationship between intellectual virtues and science, as well as cultivating intellectual virtues in various stages of scientific training.
Don't Forget the Oy-sters When It Comes to Tolosa-Hunt Syndrome

In this issue of Neurology®, Yu and Chen published a Pearls & Oy-sters article on a case of Tolosa-Hunt syndrome with idiopathic inflammation of the cavernous sinus with orbital and intracranial extension,1 which raises some important learning points but also caution when it comes to using the term “Tolosa-Hunt syndrome. ”
Low carbon economic optimal allocation strategy of multi-storage for regional integrated energy system considering local consumption rate of wind and solar energy

With the promotion of energy internet, the development of integrated energy system and the emergence of various energy storage modes, the establishment of the operation mode of integrated energy station with multiple energy storage modes of electricity, gas, cooling, and heating can improve the utilization rate of distributed new energy. Based on the infrastructure and model of regional integrated energy system, this paper studied the collaborative optimal allocation of electricity storage, electricity to gas (P2G) technology, cooling storage and heating storage under the multi energy complementary coupling operation of CCHP units. And a multi energy storage and low-carbon economic optimal allocation model of regional integrated energy system was put forward. Finally, the benefits of energy storage equipment in regional integrated energy system were quantitatively analyzed through economic indicators and carbon emission indicators. The example results showed that the regional integrated energy system with four energy storage modes of electricity, gas, cooling and heating can absorb more distributed wind and solar new energy, improve economic benefits and reduce carbon emissions.
A New Remote Sensing Change Detection Data Augmentation Method Based on Mosaic Simulation and Haze Image Simulation

The quality of optical remote sensing images is largely affected by clouds and haze. In addition, the mosaicking image of multiple remote sensing images, due to objective factors such as acquiring time or climate conditions, will lead to large spectral differences in the area around the seamline. The aforementioned scenarios will seriously affect the accuracy of change detection models based on deep learning. However, there is still a lack of methods to address such issues. To solve these problems, from the perspective of training samples, this article proposed a simple but effective data augmentation method to improve the generalization ability of the deep change detection model in the region of haze cover and the seamline. First, from the characteristics of the optical remote sensing image itself, two image simulation methods are designed to conduct data augmentation, named mosaic simulation and haze image simulation. Then, the newly augmented training samples are mixed with the original training samples and then input into a deep learning model for model training. Finally, the change detection results indicate that the proposed data augmentation method can effectively improve the generalization ability of the change detection model in the region of haze cover and seamline, which has high practical value for improving the deep learning model's performance in real-world scenarios and also provides a simple but effective algorithm reference for other intelligent interpretation tasks from the perspective of training data.
Efficient dynamic resampling for dominance-based multiobjective evolutionary optimization

ABSTRACT Multi-objective optimization problems are often subject to the presence of objectives that require expensive resampling for their computation. This is the case for many robustness metrics, which are frequently used as an additional objective that accounts for the reliability of specific sections of the solution space. Typical robustness measurements use resampling, but the number of samples that constitute a precise dispersion measure has a potentially large impact on the computational cost of an algorithm. This article proposes the integration of dominance based statistical testing methods as part of the selection mechanism of evolutionary multi-objective genetic algorithms with the aim of reducing the number of fitness evaluations. The performance of the approach is tested on five classical benchmark functions integrating it into two well-known algorithms, NSGA-II and SPEA2. The experimental results show a significant reduction in the number of fitness evaluations while, at the same time, maintaining the quality of the solutions.
Identification and Validation of NK Marker Genes in Ovarian Cancer by scRNA-seq Combined with WGCNA Algorithm

Background As an innate immune system effector, natural killer cells (NK cells) play a significant role in tumor immunotherapy response and clinical outcomes. Methods In our investigation, we collected ovarian cancer samples from TCGA and GEO cohorts, and a total of 1793 samples were included. In addition, four high-grade serous ovarian cancer scRNA-seq data were included for screening NK cell marker genes. Weighted gene coexpression network analysis (WGCNA) identified core modules and central genes associated with NK cells. The “TIMER,” “CIBERSORT,” “MCPcounter,” “xCell,” and “EPIC” algorithms were performed to predict the infiltration characteristics of different immune cell types in each sample. The LASSO-COX algorithm was employed to build risk models to predict prognosis. Finally, drug sensitivity screening was performed. Results We first scored the NK cell infiltration of each sample and found that the level of NK cell infiltration affected the clinical outcome of ovarian cancer patients. Therefore, we analyzed four high-grade serous ovarian cancer scRNA-seq data, screening NK cell marker genes at the single-cell level. The WGCNA algorithm screens NK cell marker genes based on bulk RNA transcriptome patterns. Finally, a total of 42 NK cell marker genes were included in our investigation. Among which, 14 NK cell marker genes were then used to develop a 14-gene prognostic model for the meta-GPL570 cohort, dividing patients into high-risk and low-risk subgroups. The predictive performance of this model has been well-verified in different external cohorts. Tumor immune microenvironment analysis showed that the high-risk score of the prognostic model was positively correlated with M2 macrophages, cancer-associated fibroblast, hematopoietic stem cell, stromal score, and negatively correlated with NK cell, cytotoxicity score, B cell, and T cell CD4+Th1. In addition, we found that bleomycin, cisplatin, docetaxel, doxorubicin, gemcitabine, and etoposide were more effective in the high-risk group, while paclitaxel had a better therapeutic effect on patients in the low-risk group. Conclusion By utilizing NK cell marker genes in our investigation, we developed a new feature that is capable of predicting patients' clinical outcomes and treatment strategies.
The nonlinear multi-factor extension comprehensive evaluation of the science-technology development condition

Abstract In this paper, the nonlinear multi-factor extension mathematics comprehensive evaluation of the science-technology development conditions has been studied. The kinds of the influence factors of them are analyzed by the nonlinear multi-factor extension mathematics comprehensive evaluation method (NMEMCEM). The extension comprehensive evaluation’s matter-element model of the science-technology development condition is established by the matter-element theory, the extension set theory and the correlation function theory. A multi-factor comprehensive evaluation for the science-technology development condition in Jiangsu Province is presented by the NMEMCEM. The given example shows the practical application of the comprehensive evaluation method.