Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal commitment in an open economy: Credibility vs. flexibility

Using a graphical method, a new way of determining the optimal degree of central bank conservativeness is developed in this paper. Unlike Lohmann (1992) and Rogoff (1985a), we are able to express the upper and lower bounds of the interval containing the optimal degree of conservativeness in terms of the structural parameters of the model. Next, we show that optimal central bank independence is higher, the higher the natural rate of unemployment, the greater the benefits of unanticipated inflation, the less inflation-averse society, the smaller the variance of productivity shocks, the smaller real exchange rate variability and the smaller the openness of the economy. These propositions are tested for nineteen industrial countries (Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Ireland, Italy, Japan, New Zealand, the Netherlands, Norway, Spain, Sweden, Switzerland, the United Kingdom and the United States) for the Bretton-Woods period and after (1960-1993). In testing the model we employ a latent variables method (LISREL) in order to distinguish between actual and optimal monetary regimes.
Systematic Review, Meta-Analysis and Radiomics Quality Score Assessment of CT Radiomics-Based Models Predicting Tumor EGFR Mutation Status in Patients with Non-Small-Cell Lung Cancer

Assessment of the quality and current performance of computed tomography (CT) radiomics-based models in predicting epidermal growth factor receptor (EGFR) mutation status in patients with non-small-cell lung carcinoma (NSCLC). Two medical literature databases were systematically searched, and articles presenting original studies on CT radiomics-based models for predicting EGFR mutation status were retrieved. Forest plots and related statistical tests were performed to summarize the model performance and inter-study heterogeneity. The methodological quality of the selected studies was assessed via the Radiomics Quality Score (RQS). The performance of the models was evaluated using the area under the curve (ROC AUC). The range of the Risk RQS across the selected articles varied from 11 to 24, indicating a notable heterogeneity in the quality and methodology of the included studies. The average score was 15.25, which accounted for 42.34% of the maximum possible score. The pooled Area Under the Curve (AUC) value was 0.801, indicating the accuracy of CT radiomics-based models in predicting the EGFR mutation status. CT radiomics-based models show promising results as non-invasive alternatives for predicting EGFR mutation status in NSCLC patients. However, the quality of the studies using CT radiomics-based models varies widely, and further harmonization and prospective validation are needed before the generalization of these models.
Trends and variability of polar mesopause region temperatures attributed to atmospheric dynamics and solar activity

The mesopause region can be considered a “boundary region” between the neutral atmosphere, where atmospheric constituents and momentum are transported mainly by winds and turbulent eddies, and the ionosphere, where the main transport mechanism is molecular diffusion. In the mesopause, complex interactions between dynamics and photochemistry occur, and we are far from a complete understanding of these interactions. This thesis aims to better understand the processes responsible for the large temperature fluctuations we observe in the polar mesopause region, especially the effects of atmospheric circulation and wave activity from lower atmospheric layers. Investigations of trends have also been conducted. To carry out these investigations, we have derived and examined mesopause temperatures from two high-latitude locations: Tromsø (70◦N, 19◦E) and Longyearbyen (78◦N, 16◦E), and turbopause height only from Tromsø. A long-term change in turbopause height may be important for understanding processes that are responsible for redistribution of atmospheric constituents. We examined winter season variations in the hydroxyl (OH*) airglow temperature record from Longyearbyen and identified local temperature maxima in mid-January and mid-February, as well as a minimum in the transition between December and January. We also identified a number of statistically significant periodic oscillations in temperatures derived from the Nippon/Norway Tromsø Meteor Radar, with periods ranging from 9 days to a year. The seasonal variation showed higher temperatures and variability during winter compared to summer. We also found local temperature enhancements just after spring equinox and summer solstice. Temperature variability and seasonal variation may, to a large extent, be explained by the large-scale circulation in the middle atmosphere and corresponding wave activity. The trends for the Longyearbyen OH* airglow winter temperature series and meteor radar derived temperatures from Tromsø, both annual and summer trends, were estimated to be near-zero or slightly negative. The Tromsø winter trend was negative, (−11.6± 4.1)Kdecade−1. We derived turbopause altitude from turbulent energy dissipation rates obtained from the Tromsø medium-frequency radar and found an increasing height in summer, (1.6± 0.3) kmdecade−1, during the time period from 2002 until 2015, while in winter turbopause height did not change significantly. We investigated the response of the change in turbopause height to a change in
Note on the exponential recursive k-ary trees

In the present paper, we consider exponential recursive trees with no node of outdegree greater than k, called exponential recursive k-ary trees (k ≥ 2). At each step of growing of these trees, every external node (insertion position) is changed into a leaf with probability p, or fails to do so with probability 1 — p. We investigate limiting behavior of fundamental parameters such as size, leaves and distances in exponential recursive k-ary trees.
Rock-ring detection accuracy improvement in infrared satellite image with sub-pixel edge detection

The projection of space circle can be used for relative pose measurement of satellite targets. The accuracy of elliptical parameters plays an important role in the accuracy of pose recovery. However, the quality of space visible and infrared image is poor. The traditional ellipse detection method is mainly based on the edge of pixel-accuracy-wise and the ellipse accuracy is low, resulting in pose measurement errors. In this study, a sub-pixel-accuracy-wise edge-based ellipse fitting method is proposed to improve the ellipse accuracy. To realise this goal, we improved the arc-based ellipse detection method and designed sub-pixel-edge-based ellipse detection method. Experimental results show that the ellipse accuracy fitted by sub-pixel edge coordinates is at least 50% higher than that by pixel edge coordinates, especially when the ellipse is incomplete. The author's method is the first one to propose and verify the sub-pixel edge coordinate which contributes to enhancing ellipse accuracy.
Equine Hoof Progenitor Cells Display Increased Mitochondrial Metabolism and Adaptive Potential to a Highly Pro-Inflammatory Microenvironment

Medicinal signaling cells (MSC) exhibit distinct molecular signatures and biological abilities, depending on the type of tissue they originate from. Recently, we isolated and described a new population of stem cells residing in the coronary corium, equine hoof progenitor cells (HPCs), which could be a new promising cell pool for the treatment of laminitis. Therefore, this study aimed to compare native populations of HPCs to well-established adipose-derived stem cells (ASCs) in standard culture conditions and in a pro-inflammatory milieu to mimic a laminitis condition. ASCs and HPCs were either cultured in standard conditions or subjected to priming with a cytokines cocktail mixture. The cells were harvested and analyzed for expression of key markers for phenotype, mitochondrial metabolism, oxidative stress, apoptosis, and immunomodulation using RT-qPCR. The morphology and migration were assessed based on fluorescent staining. Microcapillary cytometry analyses were performed to assess the distribution in the cell cycle, mitochondrial membrane potential, and oxidative stress. Native HPCs exhibited a similar morphology to ASCs, but a different phenotype. The HPCs possessed lower migration capacity and distinct distribution across cell cycle phases. Native HPCs were characterized by different mitochondrial dynamics and oxidative stress levels. Under standard culture conditions, HPCs displayed different expression patterns of apoptotic and immunomodulatory markers than ASCs, as well as distinct miRNA expression. Interestingly, after priming with the cytokines cocktail mixture, HPCs exhibited different mitochondrial dynamics than ASCs; however, the apoptosis and immunomodulatory marker expression was similar in both populations. Native ASCs and HPCs exhibited different baseline expressions of markers involved in mitochondrial dynamics, the oxidative stress response, apoptosis and inflammation. When exposed to a pro-inflammatory microenvironment, ASCs and HPCs differed in the expression of mitochondrial condition markers and chosen miRNAs.
Load Forecasting for the Laser Metal Processing Industry Using VMD and Hybrid Deep Learning Models

Electric load forecasting is crucial for the metallurgy industry because it enables effective resource allocation, production scheduling, and optimized energy management. To achieve an accurate load forecasting, it is essential to develop an efficient approach. In this study, we considered the time factor of univariate time-series data to implement various deep learning models for predicting the load one hour ahead under different conditions (seasonal and daily variations). The goal was to identify the most suitable model for each specific condition. In this study, two hybrid deep learning models were proposed. The first model combines variational mode decomposition (VMD) with a convolutional neural network (CNN) and gated recurrent unit (GRU). The second model incorporates VMD with a CNN and long short-term memory (LSTM). The proposed models outperformed the baseline models. The VMD–CNN–LSTM performed well for seasonal conditions, with an average RMSE of 12.215 kW, MAE of 9.543 kW, and MAPE of 0.095%. Meanwhile, the VMD–CNN–GRU performed well for daily variations, with an average RMSE value of 11.595 kW, MAE of 9.092 kW, and MAPE of 0.079%. The findings support the practical application of the proposed models for electrical load forecasting in diverse scenarios, especially concerning seasonal and daily variations.
Grasping the nature of the cell interior: from Physiological Chemistry to Chemical Biology

Current models of the cell interior emphasise its crowded, chemically complex and dynamically organised structure. Although the chemical composition of cells is known, the cooperative intermolecular interactions that govern cell ultrastructure are poorly understood. A major goal of biochemistry is to capture these myriad interactions in vivo. We consider the landmark discoveries that have shaped this objective, starting from the vitalist framework established by early natural philosophers. Through this historical revisionism, we extract important lessons for the bioinspired chemists of today. Scientific specialisation tends to insulate seminal ideas and hamper the unification of paradigms across biology. Therefore, we call for interdisciplinary collaboration in grappling with the complex cell interior. Recent successes in integrative structural biology and chemical biology demonstrate the power of hybrid approaches. The future roles of the (bio)chemist and model systems are also discussed as starting points for in vivo explorations.
Generation of Random Graphs for Graph Theory Analysis Applied to the Study of Brain Connectivity

One of the current frontiers in neurosciences is to understand brain connectivity both in healthy subjects and patients. Recent studies suggest that brain connectivity measured with graph theory is a reliable candidate biomarker of neuronal dysfunction and disease spread in neurodegenerative disorders. Widespread abnormalities in the topology of the cerebral networks in patients correlate with a higher risk of developing dementia and worse prognosis. In order to recognize such abnormalities, brain network graph measures should be compared with the corresponding measures calculated on random graphs with the same degree distribution. However, creating a random graph with prescribed degree sequence that has number of nodes of magnitude of 105 is a recognized problem. Existing algorithms have a variety of shortcomings, among which are slow run-time, non-uniformity of results and divergence of degree distribution with the target one. The goal of this thesis is to explore the possibility of finding an algorithm that can be used with very large networks. Multiple common algorithms were tested to check their scaling with increasing number of nodes. The results are compared in order to find weaknesses and strengths of particular algorithms, and certain changes are offered that speed up their runtimes and/or correct for the downsides. The degree distributions of the resulting random graphs are compared to those of the target graphs, which are constructed in a way that mimics some of the most common characteristics of brain networks, namely small-worldness and scale-free topology, and it is discussed why some of the models are more appropriate than others in this case. Simulations prove that the majority of algorithms are vastly inefficient in creating random large graphs with necessary limitations on their topology, while some can be adapted to showcase to a certain extent promising results.
Study on the clinical effect and safety of Kangfuxin liquid combined with microneedling in the treatment of facial skin photoaging

Background and Objectives: Microneedling has been introduced as a new technique to address the growing concern of facial skin photoaging. Kangfuxin liquid has been found to promote the process of skin wound repair, including reducing inflammatory response, improving immunity and enhancing antioxidant levels. In this prospective randomized double-blinded study, we wanted to explore the clinical efficacy and safety of Kangfuxin liquid combined with microneedling in treating facial skin photoaging. Methods: 57 patients with facial skin photoaging were randomly divided into two groups. The treatment group (28 cases) received microneedle therapy with Kangfuxin liquid, while the control group (29 cases) received microneedle therapy with physiological saline. The treatment interval was 4 weeks, and a total of 3 treatments were performed. Compare the VISIA scores of facial photoaging features such as wrinkles, texture, pores, spots and ultraviolet pigmentation between two groups of patients before and after treatment, Global Score for Photoaging, satisfaction evaluation, and record the occurrence of adverse reactions. Results: After treatment, the treatment group showed more significant improvement in wrinkles, texture, pores, spots and ultraviolet pigmentation, and the Global Score for Photoaging was better than the control group ( P < 0.05). The satisfaction rate with improving skin in the treatment group was 85.71%, which was higher than 75.86% in the control group ( P < 0.05). Both groups did not experience adverse reactions such as skin infection, pigmentation or hypopigmentation, scar formation, or worsening of melasma. Conclusion: Kangfuxin liquid combined with microneedling therapy has a good improvement effect on facial skin photoaging, with a low incidence of adverse reactions and high patient satisfaction. It is worthy of clinical promotion.
Boundary estimates of solutions mixed boundary problems for elliptic
equations with VMO coefficients

In this paper we obtain generalized weighted Sobolev – Morrey estimates with weights from the Muckenhoupt class A p by establishing boundedness of several important operators in harmonic analysis such as Hardy – Littlewood operators and Calderon –Zygmund singular integral operators in generalized weighted Morrey spaces. As a consequence, a priori estimates for the weak solutions mixed boundary problem uniformly elliptic equations of higher order in generalized weighted Sobolev – Morrey spaces in a smooth bounded domain Ω ⊂ R n are obtained.
Community Detection using Locality Statistics

The goal of community detection is to identify clusters and groups of vertices that share common properties or play similar roles in a graph, using only the information encoded in the graph. Our work analyzes two methods of identifying an anomalous community in temporal graphs and another method of identifying active communities in a static massive graph. All methods are based on locality statistics. In [50], an anomalous community is detected that shows growing connectivities in a time series of graphs. We formulate the task as a hypothesis-testing problem in stochastic block model time series. We derive the limiting properties and power characteristics of two competing test statistics built on distinct underlying locality statistics. In addition, we provide applicable implementations of two competing test statistics and detailed experimental results for a neural imaging application in [36]. In [51], active communities are detected in a static massive graph on which many community detection algorithms scale poorly. We propose a novel framework for detecting active communities that consist of the most active vertices. Our framework utilizes a parallelizable trimming algorithm based on a locality statistic to filter out inactive vertices, and then clusters the remaining active vertices via spectral decomposition of their
A New Repetitive Motion Planning Scheme With Noise Suppression Capability for Redundant Robot Manipulators

Repetitive motion planning (RMP) is a crucial issue encountered in studies on redundant robot manipulators. Numerous RMP schemes have been established in previous studies wherein simulations are assumed to be free of noise. However, noise is ubiquitous and can severely affect RMP schemes to the point of causing failure. This paper attempts address the limitations imposed by noise by providing the first RMP scheme with inherent noise-suppression capability. The new RMP scheme for redundant robot manipulators in a noisy environment is proposed on the basis of an equality criterion that is robust against additive noise. The equality criterion is established by incorporating the proportional and integral information of the desired end-effector path. The proposed scheme is reformulated as a quadratic program and is calculated by using a recurrent neural network. Comparative simulation results obtained with PA10 and four-link robot manipulators illustrate the effectiveness and superiority of the proposed RMP scheme over the traditional RMP scheme.
Students’ choice of major: An approach for academic advising

Abstract This study surveyed first-year business students to measure their intended academic major at the beginning and at the end of the semester, and the relative importance of the factors that influenced their choice. Results indicate that students’ independent research, family input, and potential income were the most significant factors of students’ choice of major in the initial survey. A t-test analysis revealed the relative importance of professors’ roles and course contents on students’ choice of major in the follow-up survey. These results have significant implications for the development of effective strategies for students’ recruitment, advising, retention, graduation, and career planning.
Influence of Social Media Usage on Generation Z’s Choice in Selecting Restaurants in Kathmandu

This paper examines the influence of social media usage on Generation Z’s choice in selecting a restaurant in the Kathmandu district. A hierarchical multiple regression model is used to examine the effect of the independent factors (perceived image, electronic word-of-mouth, sales promotion, and restaurant popularity) on the dependent variable (restaurant choice). The data is collected from Generation Z (Gen Z) residing in Kathmandu districts by adopting convenience sampling. The findings of this study suggest that the Gen Z residing in Kathmandu district tend to make restaurant choices based on their perceived image and electronic word-of-mouth (E-WOM), as indicated by the positive correlation and regression coefficients. On the other hand, despite showing a strong relationship in the correlation analysis, the regression coefficients of sales promotion and restaurant popularity do not seem to significantly impact consumers’ restaurant choice decisions among Generation Z of Kathmandu.
Solar magnetograms editing using discrete Morse theory

Solar magnetic field structure in active regions is complicated for modeling. We construct by magnetogram data a special structure - discrete Morse-Smale complex. We perform simplification of complex using persistence pair elimination. Finally, we obtain a simplified complex that stores main topological features of the magnetogram data and neighbourhood relation between them.
Immunoglobulin A levels and its correlation with neutrophil-to-lymphocyte ratio as inflammatory biomarkers for dry eye disease in type 2 diabetes: a retrospective study

Background The neutrophil-to-lymphocyte ratio (NLR) and immunoglobulin A (IgA) level are commonly used as biomarkers for inflammation. Patients with type 2 diabetes (T2D) may experience an imbalance of tear film and inflammation, which can result in dry eye disease (DED). This study aimed to assess the levels of IgA and explore its correlation with the NLR as potential inflammatory biomarkers for dry eye disease in patients with T2D. Methods A retrospective study was conducted at the cornea clinic and diabetes centre of King Abdulaziz Medical City (Jeddah, Saudi Arabia). The study included patients with DED and the number of available T2D-DED patients determined the sample size. Neutrophil, lymphocyte, IgA and CRP (C-reactive protein) laboratory values were obtained from medical records and correlational analyses were performed. Results The study included 85 patients with an average age of 54 ± 14.4 years for the DED group (n=32) and 62 ± 13.9 years for the T2D-DED group (n=53). The age difference between the two groups was statistically significant (p 0.0001). The NLR values of the T2D-DED and DED groups were 3.203 ± 0.66 and 2.406 ± 0.46, respectively, with no significant difference (p<0.285). Similarly, there were no significant differences in neutrophil and lymphocyte values between the two groups. The IgA levels showed no significant variation between T2D-DED and DED groups (p<0.364). Spearman’s correlation analysis in the DED group showed a significant negative correlation between IgA and lymphocyte (p=0.011; r= - 0.471) values and significant positive correlations between IgA and neutrophil (p=0.014; r=0.309) and NLR (p=0.052; r= - 0.283) values. In the T2D-DED group, a significant correlation was found between IgA and CRP values (p=0.032; r=0.33). Conclusion Although diabetic patients may exhibit higher levels of NLR and IgA that correlate with disease severity, our study did not find significant differences in NLR and IgA values between the two groups. These findings may guide future research and enhance understanding of the disease’s underlying mechanisms.