Miracle-dz/UniFAR-FTUs huggingface dataset:
Methodology for assessing the competitiveness of an enterprise’s business activities

It was found that when using the methodology for a comprehensive assessment of the competitiveness of an enterprise’s entrepreneurial activity, the systemic nature of the nature of the enterprise’s competitiveness and its industry characteristics. Also an effectiveness of this research will increase to find special proposals for increasing the competitiveness of an enterprise of a certain type of activity. Testing of the selected comprehensive methodology for studying the competitiveness of one of the enterprises in the construction industry in the region confirmed its practical significance.
Efficacy and Safety of Thrombolytic Therapy in Mongolian Young Adults with Acute Ischemic Stroke

Objectives: The study aimed to assess the safety and efficacy of intravenous thrombolysis (IVT) in Mongolian young patients with acute ischemic stroke (AIS). Methods: Data of 30 AIS patients aged <50 years who were treated with IVT between 2013 and 2023 at the Stroke Department of Third Central Hospital were retrospectively analyzed. For outcome comparison, 60 controls with AIS not treated with IVT and 60 older controls (>50 years) treated with IVT matched age, gender and baseline NIHSS score were selected. Functional outcome at three (3) months defined as “Favorable” and “Unfavorable” (modified Rankin Scale score 0-1 vs 2-6). Symptomatic intracerebral hemorrhage (sICH) was defined according to the SITS-MOSTStudy.Results: “Favorable” outcome at 3 months was significantly higher in young IVT-treated patients (53.3% vs 30.0%, p < 0.05) compared with their matched young and older controls treated with IVT (53.3% vs 26.7%, p = 0.019). The sICHoccurred in 3% of young IVT-treated patients and in 5% of older controls but this difference was nonsignificant. Mortality rate was 21.7% (p = 0.245) among older controls, whereas in young IVT-treated and matched young controls 10% during the 3months follow-up.Conclusions: IVT is safe and beneficial for Mongolian young adults with AIS.
Monthly Precipitation Reconstruction in Subtropical South America Using Seasonal Tree‐Ring Oxygen Isotopes

The South American Summer Monsoon (SASM) is one of the most important climate systems in the tropical and subtropical regions of South America, and transports Atlantic moisture to the South American continent. However, there are few high‐resolution tree ring based studies of the SASM due to the difficulty of crossdating and the lack of dependable moisture proxies based on tree‐ring width. In this study, we use intra‐annual tree‐ring oxygen isotope (δ18OTR) data (E.V.A 03w, E.V.Ar11e, E.V.Ar12e; the full name of sample code is Erval Velho ‐ Araucaria) for crossdating, and to extract climate signals and reconstruct monthly precipitation. Our data are from Araucaria angustifolia in southern Brazil, and each annual tree‐ring comprises four parts (parts 1, 2, 3, 4) during 1960–2016. The intra‐annual δ18OTR data show pronounced seasonal variations with a decreasing trend in the growing season. The intra‐annual δ18OTR data record variations in precipitation δ18O values, and the interannual δ18OTR data record a precipitation amount. The δ18OTR values of parts 1 and 2 of each ring show the strongest correlation with precipitation at the beginning of the SASM (i.e., December). δ18OTR values of Part 3 have the strongest correlation with precipitation during January–February, and those of Part 4 are strongly correlated with precipitation during February–June. The seasonal δ18OTR values can be used to reconstruct monthly precipitation in the growing season. Spatial correlations between monthly precipitation reconstruction and global sea surface temperatures reveal that EI Niño‐Southern Oscillation (ENSO) regulate seasonal precipitation and affect the δ18OTR values in southern Brazil.
New Metrics of the Tropospheric Biennial Oscillation in the East Asian Summer Monsoon and Its Interdecadal Shift

Abstract This study designed a simple index for measuring irregular tropospheric biennial oscillation (TBO) activities, which was used to determine that the TBO in the East Asian Summer Monsoon (EASM), the most important summer precipitation system for China, has strengthened rather than weakened since the late 1970s. The lead/lag correlations between the EASM and tropical Indian-Pacific sea surface temperature (SST) suggest a relationship between interbasin SST and EASM coupling processes and that this alternative correlation pattern is likely related to TBO. Significant correlation occurred only in recent decades, which implies a reinforcement of TBO in the EASM. From records of representative points in the Indian-Pacific, the interdecadal intrinsic SST modes of the areas can be obtained with ensemble empirical mode decomposition owing to its good temporal locality. Statistical results show Indian-Pacific SST interdecadal trends that include out-of-phase and in-phase warming before and after the late 1970s, respectively, which may be responsible for the TBO interdecadal augmentation present since the late 1970s.
Annual Review of Ecology, Evolution, and Systematics Variability in Plant–Herbivore Interactions

Plants and herbivores are remarkably variable in space and time, and variability has been considered a de fi ning feature of their interactions.Empirical research, however, has traditionally focused on understanding differences in means and overlooked the theoretically signi fi cant ecological and evolutionary roles of variability itself. We review the literature with the goal of showing how variability-explicit research expands our perspective on plant– herbivore ecology and evolution. We fi rst clarify terminology for describing variation and then review patterns, causes, and consequences of variation in herbivory across scales of space, time, and biological organization. We consider how incorporating variability improves existing hypotheses and leads to new ones. We conclude by suggesting future work that reports full distributions, integrates effects of variation across scales, describes nonlinearities, and considers how stochastic
NUMMULITE BIOSTRATIGRAPHY AT THE MIDDLE/UPPER EOCENE BOUNDARY IN THE NORTHERN MEDITERRANEAN AREA

Some larger foraminiferal assemblages (mostly nummulitids) near the Middle/Upper Eocene boundary have been investigated. Sections of the Veneto area (Berici and Lessini Mts., northern Italy) were studied and compared with others of the same age from Spain (Ebro basin) and Romania (Cluj-Napoca). In the Veneto area the results allow to split the upper Middle Eocene Nummulites brongniarti Zone into two biozones: a lower N. lyelli Zone and an upper N. biedai Zone. The N. aff. fahianii Zone is here renamed N. variolarias/incrassatus Zone. This subdivision can also be recognized in Spain and Romania. According to the current conceptions, the base of the Priabonian (= Upper Eocene) could correspond either to the base of the N. fabianii s.s. Zone or to the base of the N. vaiolarius / incras satas Zone. Anyway, the Mossano succession could be a potential Globai Stratotype Section and Point for the base of the Priabonian.
Risk Assessment on Food Crops Supply-Demand Balance under Climate Change in China

The term "risk" here mainly refers to the possible impacts of future climate change on food crops supply-demand balance.Based on the simulated results of food crops production under scenario B2 of climate change in RCMCA(regional crop model for Chinese agriculture),this study developed the food crops consumption scenario and set the criteria on food crops risks under climate change.It also analyzed the future variation in food crops supply and demand to determine the effect of climate change on food crops security in the short,medium and long terms at the county scale with the support of GIS.The results show that the climate change will hinder the food crops supply in general.With higher living standard,the gap between food crops supply and demand will be enlarged in the future,resulting in the increase of risk.The highest may occur in the medium term,the lowest in the near future,and the medium in the far future.Particularly in the medium term,66.99% of the counties in China will face risks.Among them,29.5%,occupying the largest area,will be with high and moderate risks;in the short-term,however,the situation will be easier,i.e.25.54% counties in moderate(14.82%) and high risks(10.72%). Moreover,counties with high risks are distributed mainly in Huang-Huai-Hai Region,Loess Plateau,Southwest China,and Eastern Margin of Qinghai-Tibet Plateau Region.The areas with lower risks are in Northeast Region,Gansu Province and Xinjiang Uygur Autonomous Region,and Inner Mongolia Autonomous Region and areas along the Great Wall.
Argumentation Writing Skills of Preservice Teacher in Higher Education: Mapping for Development

Argumentation skills are an important domain to be provided to students in higher education. This study aims to identify the level and category of scientific argumentation skills among students. The method used in this research is content analysis. Twenty-three students’ written scientific arguments about environmental issues were analyzed to be mapped. The mapping analysis of students’ written arguments is divided into two parts. Mapping analysis of students’ written arguments is grouped into two parts. First, the analysis focuses on the completeness of the argumentation components without considering their scientificity. Second, the analysis is more emphasized on the argumentation component and the scientific level of the argument. The research findings illustrate that the argumentation component without a scientific level is dominated by grade 2 (ie Data, Claims and/or Warrants). Meanwhile, the research results on the argumentation component and the scientific level of argumentation are dominated by the Unacceptable-Incorrect Scientific Knowledge (SU-2) category. Thus, written argumentation skills must be taught to students comprehensively. This study is important for lecturers because it provides an overview of the ability of scientific argumentation among students, which then helps lecturers in determining the next step in the learning process by adopting appropriate teaching strategies.
Advanced analysis and modelling tools for spatial environmental data. Case study: indoor radon data in Switzerland

The present work deals with development and adaptation of advanced geostatistical models and machine learning algorithms (statistical learning theory – Support Vector Machines) for comprehensive analysis and decision-oriented modelling of environmental spatial data. The real case study is based on indoor radon data. The inherent high variability at different spatial scales of noisy indoor radon measurements coupled with the heavy clustering effect of houses locations make this dataset an excellent candidate to assess the feasibility of traditional and advanced models, trend and risk mapping at local and regional scales. General methodology of spatial data analysis and modelling includes comprehensive exploratory data analysis, qualitative and quantitative description of monitoring networks, analysis and modelling of spatial anisotropic correlation structures, spatial predictions and simulations using geostatistical models and machine learning algorithms. In the present study this methodology is applied for the real case study of indoor radon data. The main attention in the present study is paid to the quantification of monitoring network clustering, modelling of spatial correlations, conditional stochastic simulations and risk mapping and application of statistical learning theory for regional classification. Regularised variography helps to improve the visibility of spatial structures on variograms of both raw and transformed data. Once modelled, the spatial correlation structures of data (variograms) are used to produce traditional maps with ordinary kriging. Due to the spatial variability of data, kriging induce a strong smoothing effect that make this approach only suitable for
Survival and grade of the glioma prediction using transfer learning

Glioblastoma is a highly malignant brain tumor with a life expectancy of only 3–6 months without treatment. Detecting and predicting its survival and grade accurately are crucial. This study introduces a novel approach using transfer learning techniques. Various pre-trained networks, including EfficientNet, ResNet, VGG16, and Inception, were tested through exhaustive optimization to identify the most suitable architecture. Transfer learning was applied to fine-tune these models on a glioblastoma image dataset, aiming to achieve two objectives: survival and tumor grade prediction.The experimental results show 65% accuracy in survival prediction, classifying patients into short, medium, or long survival categories. Additionally, the prediction of tumor grade achieved an accuracy of 97%, accurately differentiating low-grade gliomas (LGG) and high-grade gliomas (HGG). The success of the approach is attributed to the effectiveness of transfer learning, surpassing the current state-of-the-art methods. In conclusion, this study presents a promising method for predicting the survival and grade of glioblastoma. Transfer learning demonstrates its potential in enhancing prediction models, particularly in scenarios with limited large datasets. These findings hold promise for improving diagnostic and treatment approaches for glioblastoma patients.
A Study on the Value of Civic Practice in Collegiate Physical Education Curriculum Based on the Athletic Education Model

: This study focuses on the innovation of thinking politics in the physical education curriculum, with particular attention to the model of competitive education based on colleges and universities. The study aims to explore the strengths and weaknesses of this model and to examine its potential impact on the development of physical education curricula. The study uses a qualitative research approach to assess the effectiveness of the model through a literature review and case studies. The findings suggest that the competitive education model can enhance physical education programs, improve students' physical fitness, and promote healthy competition. However, there are potential drawbacks that must be considered. The paper concludes that a university-based model of competitive education can be an effective approach to physical education curriculum development, but the implications for students, faculty, and policy makers need to be carefully considered.
The research landscape of ferroptosis in cognitive function: A bibliometric and visualized analysis

: Ferroptosis, which is a new form of cell death distinct from apoptosis, necrosis and autophagy, is gradually gaining widespread attention in various research fields. There is now evidence from several studies that ferroptosis plays an important role in altered cognitive function. We used the Web of Science Core Collection (WoSCC) to search for "ferroptosis" and "cognitive function" as subject terms. A total of 37 published papers were included after filtering and deduplication were performed. CiteSpace (V6.1.R6) was used for bibliometric analysis and visualization to summarize the content and development process of the ferroptosis research in the field of cognitive function and to identify the current and possible future research hotspots and directions. The results show a rapidly increasing trend regarding studies related to cognitive function associated with ferroptosis. China is the world leader in terms of the number of studies and institutions publishing on related topics, with the United States at the center. There is less collaboration between researchers and institutions in this field. At present this research centers on the roles that oxidative stress, lipid peroxidation, and iron-related accumulation and regulation play in cognitive function, as well as their impacts, and these areas are likely to continue to be research hotspots in the future.
DNA Sensor for the Detection of Brucella spp. Based on Magnetic Nanoparticle Markers

Due to the limitations of conventional Brucella detection methods, including safety concerns, long incubation times, and limited specificity, the development of a rapid, selective, and accurate technique for the early detection of Brucella in livestock animals is crucial to prevent the spread of the associated disease. In the present study, we introduce a magnetic nanoparticle marker-based biosensor using frequency mixing magnetic detection for point-of-care testing and quantification of Brucella DNA. Superparamagnetic nanoparticles were used as magnetically measured markers to selectively detect the target DNA hybridized with its complementary capture probes immobilized on a porous polyethylene filter. Experimental conditions like density and length of the probes, hybridization time and temperature, and magnetic binding specificity, sensitivity, and detection limit were investigated and optimized. Our sensor demonstrated a relatively fast detection time of approximately 10 min, with a detection limit of 55 copies (0.09 fM) when tested using DNA amplified from Brucella genetic material. In addition, the detection specificity was examined using gDNA from Brucella and other zoonotic bacteria that may coexist in the same niche, confirming the method’s selectivity for Brucella DNA. Our proposed biosensor has the potential to be used for the early detection of Brucella bacteria in the field and can contribute to disease control measures.
An Interlayer Link Prediction Method Based on Edge-Weighted Embedding

Presently, users usually register accounts on online social networks (OSNs). Identifying the same user in different networks is also known as interlayer link prediction. Most existing interlayer link prediction studies use embedding methods, which represent nodes in a common representation space by learning mapping functions. However, these studies often directly model links within the pre-embedding layer as equal weights, fail to effectively distinguish the strength of edge relationships, and do not fully utilize network topology information. In this paper, we propose an interlayer link prediction model based on weighted embedding of connected edges within the network layer, which models the links within the network layer as weighted graphs to better represent the network and then uses appropriate embedding methods to represent the network in a low-dimensional space. After embedding, vector similarity and distance similarity are used as comprehensive evaluation scores. This paper has conducted a large number of simulation experiments on actual networks. The results show that our proposed model has higher prediction accuracy in all aspects than current advanced models and can achieve the highest accuracy when the training frequency is low, which proves the validity of the proposed model.
To Adapt or Not to Adapt , That is the Question : Towards a Decision Framework for Legacy-to Business Component Alignment Strategies

We have embarked on a exciting era of designing and developing enterprise applications: one that is based on assembling business components into electronic business processes. This contemporary paradigm for developing enterprise applications is rapidly gaining momentum in the business community. Coupled with the Internet, business component computing is believed to be able to create a class of enterprise applications that is flexible and relatively easy to maintain, upgrade and integrate. This up-and-coming breed of enterprise applications brings a realm of tantalizing possibilities for realizing innovative business models, e.g., integrated virtual supply chains, treating business software components as business processes, and vice versa. While trying to move to this arena, many “brick-and-mortar” companies are hindered by their heritage of “stovepipe” enterprise information systems that are typically large, heterogeneous, and, mission-critical systems. Unfortunately, it is commonplace that these inherited enterprise systems are strongly intertwined with existing business processes and policies. Although this allows efficient operations, it severely hinders their alignment with novel business processes. The replacement and renovation of these systems, most of which have become legacy systems during the passage of time, has proven to be a highly complicated, time-consuming, expensive and risky endeavor [4], as these systems are not only tightly coupled to the business workflow, but also suffer from a rigid and contrived architecture because of many years of ad-hoc patching and fixing, offering very limited openness to other systems. Given this situation, organizations are facing a unenviable dilemma. On the one hand, they want to get rid of their legacy systems as soon as possible to be able to reap the fruits of distributed business component technology significantly easing alignment of enterprise applications and business processes.
New On-Line MTPA Angle Search and Control Methods Based on Digital Twins for IPM Synchronous Motor Drives Considering Motor Non-Linearity

The main theme of this paper is to propose on-line MTPA angle search and control methods based on digital twins for IPM synchronous motor drives. The proposed method is developed based upon the ECE model, the finite element model of IPM synchronous motor. An on-line MTPA angle search method is developed to achieve the minimization of stator current for the specific output torque and speed. A new IPM synchronous motor control is proposed based upon its digital twins model to consider the non-linearity caused by magnetic saturation of motor which become more relevant especially under heavy load conditions. In the proposed IPM synchronous motor control method, two current controllers and the parameters for decoupling control are tuned on-line to adapt to the variation of motor parameters caused by the non-linearity of motor. Experiment results are shown to support the proposed methods. The motor for the application of electrical scooter with the rated specifications of 2 kW, 2000 rpm, 10 Nm, is used for test and comparison. Comparing with the conventional methods, the test results show the stator current can be reduced up to 17.23% under 2000 rpm and half load conditions. The efficiency improvement is up to 3.18 %. These results fully confirm the effectiveness of the proposed on-line MTPA angle search and control methods.