Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative terrestrial atmospheric circulation regimes in simplified global circulation models. Part II: Energy budgets and spectral transfers

The energetics of possible global atmospheric circulation patterns in an Earth‐like atmosphere are explored using a simplified global General Circulation Model (GCM) based on the University of Hamburg's Portable University Model for the Atmosphere (designated here as PUMA‐S), forced by linear relaxation towards a prescribed temperature field and subject to Rayleigh surface drag and hyperdiffusive dissipation. Results from a series of simulations, obtained by varying planetary rotation rate Ω with an imposed equator‐to‐pole temperature difference, were analysed to determine the structure and magnitude of the heat transport and other contributions to the energy budget for the time‐averaged, equilibrated flow. These show clear trends with rotation rate, with the most intense Lorenz energy cycle for an Earth‐sized planet occurring with a rotation rate around half that of the present‐day Earth (i.e., Ω∗ = Ω/Ω E = 1/2, where Ω E is the rotation rate of the Earth). Kinetic energy (KE) and available potential energy (APE) spectra, E K (n) and E A (n) (where n is total spherical wavenumber), also show clear trends with rotation rate, with n −3 enstrophy‐dominated spectra around Ω∗ = 1 and steeper (∼n −5) slopes in the zonal mean flow with little evidence for the n −5/3 spectrum anticipated for an inverse KE cascade. Instead, both KE and APE spectra become almost flat at scales larger than the internal Rossby radius, L d , and exhibit near‐equipartition at high wavenumbers. At Ω∗ < <1, the spectrum becomes dominated by KE with E K (n)∼(2–3)E A (n) at most wavenumbers and a slope that tends towards n −5/3 across most of the spectrum. Spectral flux calculations show that enstrophy and APE are almost always cascaded downscale, regardless of rotation rate. KE cascades are more complicated, however, with downscale transfers across almost all wavenumbers, dominated by horizontally divergent modes, for Ω ∗ ≲ 1 / 4 . At higher rotation rates, transfers of KE become increasingly dominated by rotational (horizontally nondivergent) components with strong upscale transfers (dominated by eddy–zonal flow interactions) for scales larger than L d and weaker downscale transfers for scales smaller than L d .
Why are proofs difficult?

For several years, the notion of ‘mathematical proof’ has been at the centre of much discussion, writing and educational research. To a very large extent the discussions have focused on the nature of the acceptability of the reasons for a mathematical conclusion. Admittedly there have been contributions concerning the role of proof in mathematics and also the mechanics of pupils‘ proof behaviour, including works which discuss both affective and pedagogical aspects, but the dominant context has usually been one of validation. That is to say, discussions have largely been in the domain of what ‘counts as a proof’ and for whom. However, I claim that there is another dimension to proof that is of central importance in the intellectual development of students at school and university. This relates to the phenomenon in mathematical thinking in which a section of mathematical structure is mentally compressed into a single unit, small enough to fit into the conscious focus of attention at a given time, and possessing an interiority which is able to both guide manipulation of the unit and also be subsequently expanded without loss of detail. This article discusses the role of this phenomenon in the manipulation of mathematical statements involved in proof. An analysis in these terms of the dynamics of certain types of mathematical proof suggests both an explanation for students’ difficulties and a possible means of help in some cases.
Looking Closer to the Transferability Between Natural and Medical Images in Deep Learning

Transfer-learning has rapidly become one of the most sophisticated and effective techniques in dealing with medical datasets. The most common transfer-learning method uses of a state-of-the-art model and its corresponding parameters as the starting point for new tasks. Recent studies have found that transfer-learning between medical and natural images has minimal advantages, attributed to their different characteristics, even with sufficient data and iterations. This study employs a meta-learning technique, building upon the traditional transfer learning approach, to explore the potential of natural tasks as a starting point for analyzing medical images. In addition, this study investigates the performance of transferring the searched augmentation from natural to medical images. Several studies proposing search algorithms for data augmentation argue that the augmentation techniques can be effectively transferred across different datasets. The results revealed that the transferability between natural and medical images leads to reduced performance owing to the characteristic difference between medical and natural searched augmentation.
Out-of-Pocket Health Expenditures Associated with Chronic Health Conditions and Disability in China

The objective of this study is to estimate the extra costs of living associated with chronic health conditions and disabilities in China. Leveraging the 2018 China Health and Retirement Longitudinal Study involving 13,530 respondents aged 50 and over, we apply both an ordinary least squares linear regression model and a logistic model to analyze the correlation between medical out-of-pocket expenditures (OOPEs) and chronic health conditions, as well as disabilities measured by Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL) limitations. This paper bridges the gap in the literature on OOPEs and their association with disabilities and chronic health conditions, respectively. We find that ADL limitations, IADL limitations, and chronic health conditions are consistently associated with higher OOPEs. The odds that older persons with disabilities and chronic health conditions incur OOPEs are two to three times higher than for persons without disabilities and chronic health conditions, respectively. Persons with disabilities and chronic health conditions have the highest OOPEs. The findings suggest that more policy and research attention is necessary to improve the financial protection of those with chronic health conditions and disabilities, including through access to comprehensive health insurance coverage.
Reversible Effects of Functional Mandibular Lateral Shift on Masticatory Muscles in Growing Rats

In this study, we aimed to determine the effects of functional mandibular lateral shift (FMLS) on the muscle mass, fiber size, myosin heavy chain fiber type, and related gene expression in masticatory muscles (masseter and temporalis), as well as whether the baseline levels could be recovered after FMLS correction in growing rats. The FMLS appliance was placed to shift the mandible leftward by approximately 2 mm. After FMLS placement for 2 and 4 weeks, the muscles on the left side had significantly lower wet weight, mean cross-sectional area, and proportion of type IIa fibers than those on the right side or in the control groups (p < 0.05), with downregulation and upregulation of IGF-1 and GDF-8 gene expression, respectively (p < 0.05). Following 2 weeks devoted to recovery from FMLS, the muscle parameters in the recovery group were not significantly different to those of the control group, and IGF-1 expression in the left-side muscles was enhanced and GDF-8 expression was simultaneously suppressed. These findings indicate that the masticatory muscle changes induced via FMLS tend to revert to normal conditions if the intervention is eliminated at an early stage. Therefore, appropriate orthodontic treatment for FMLS during the growth period is advisable to prevent asymmetric alterations in masticatory muscles.
Federated Learning Inspired Low-Complexity Intrusion Detection and Classification Technique for SDN-Based Industrial CPS

Unauthorized users may attack centralized controllers as an attractive target in software-defined networking (SDN)-based industrial cyber-physical systems (CPS). Managing high-complexity deep learning (DL)-based intrusion classification to recognize and prevent attacks in the industrial Internet of Things (IIoT) networks with low-latency requirements is challenging. Moreover, a centralized DL-based intrusion detection system (IDS) leads to privacy concerns and communication overhead issues during data uploading to a cloud server for training processes in IIoT environments. This study proposes federated learning (FL)-based low-complexity intrusion detection and classification in SDN-enabled industrial CPS. This framework utilizes Chi-square and Pearson correlation coefficient (PCC) feature selection methods to select potential features, which help reduce the model’s complexity and boost performance. The proposed model evaluated the SDN and IIoT-related InSDN and Edge-IIoTset datasets. The model measurement shows that the proposed model achieves high accuracy, low computational cost, and a low-complexity model architecture compared with state-of-the-art approaches.
Understanding Higher Education EFL Learners’ Motivation in Southeast Asia Context: A Systematic Literature Review

Motivation is regarded as one of the major factors in language learning. Therefore, it is very important for teachers to recognize and foster individual students’ motivation as well as identify and respond to their concerns. This systematic literature review study aimed to portray students’ motivational level, orientation, and factors that are dominantly affecting motivation among higher education students in the Southeast Asia context. There are two stages comprised in this study—selecting the pool of review studies and discussing the outcomes of the review. Having thorough sorting and eliminating irrelevant and duplicate articles from three databases (Sciencedirect, ProQuest and ERIC), 15 articles derived from Indonesia, Thailand and East Timor were finally selected. This study, then, found that students’ motivational levels were generally high, and they were more extrinsically than intrinsically motivated, in which most students learn English for their future better job (careers). It was reported that the key factors motivated students in the learning process were friends, and teachers (personality, competence, teaching method), and somehow female students have a different motivational level and orientation from male students. Hence, the English teachers are suggested to reconsider using a method or anything which can improve students’ motivation for both female and male students, both extrinsically and intrinsically. further studies are recommended to include a broader search database and also area part of countries.
Radio Tomographic Imaging using a Modified Maximum Likelihood Estimator for Image Reconstruction in Various Environments

Radio Tomographic Imaging (RTI) is an emerging Device-Free Passive Localization (DFPL) technology. Radio Tomographic Imaging (RTI) involves using a set of small low cost wireless transceivers to create a Wireless Sensor Network (WSN) around an Area of Interest (AoI). Furthermore, the Received Signal Strength (RSS) between transceiver pairs is utilized to reconstruct an image from the signal attenuation caused by an object disrupting the links. This image can then be utilized for multiple applications ranging from localization to target detection and tracking. This enhances the importance of image resolution in order to capture the actual size of the objects as well as the ability to resolve multiple objects in an AoI. The objective of this research is to propose a new image formation technique for a reconstructed image within a WSN. This was accomplished using a modified Maximum Likelihood Estimate (MLE) function that forces the desired solution to be positive. Other regularization techniques must implement different methods to mitigate the undesired singular values caused from a non-invertible matrix. Additionally, the research highlights the performance of the modified MLE estimator and the robustness of improved image resolution in three different environments.
Racial Attitudes and Vote Choice in National Canadian Elections

Abstract This article examines the effect of racial attitudes on the electoral performance of the New Democratic Party (NDP). Since 2017, the NDP has been led by Jagmeet Singh, the first non-white leader of a nationally competitive Canadian political party. Voters’ racial attitudes and the race of party leaders have a significant effect on vote choice in the United States. Less is known about whether similar effects exist in Canadian elections. I show that NDP vote choice polarized on the basis of racial attitudes following Singh's ascension to party leader. Voters with cold feelings toward racial minorities were less likely to vote for the NDP in 2019 and 2021 than in comparable historical elections. In contrast, there is no significant difference between 2019/2021 and prior elections in support for the Liberals and Conservatives among such voters. These results suggest that racial attitudes are salient in Canadian elections and that national parties may face an electoral penalty when selecting non-white party leaders.
Effect of mixtures of legume species on ruminal fermentation, methane, and microbial nitrogen production in batch and continuous culture (RUSITEC) systems

Abstract The effect of cicer milkvetch (Astragalus cicer L.) and sainfoin (Onobrychis viciifolia Scop.) on ruminal fermentation, methane production, and microbial nitrogen synthesis was assessed in two experiments. Experiment 1 analyzed two legumes, cicer milkvetch and sainfoin at two stages (vegetative and late flower) incubated with alfalfa (Medicago sativa) at five inclusion rates 0:100; 25:75, 50:50, 75:25, and 100:0 (as DM) in batch culture. Experiment 2 analyzed vegetative cicer milkvetch and alfalfa incubated in ratios of 25:75, 50:50, 75:25, and 100:0 (as DM) in continuous culture systems (RUSITEC). In batch culture, increased dry matter disappearance (DMD), and propionate percentage (%total), and reduced methane (mg·g−1 DMD) occurred with vegetative cicer milkvetch inclusion. In RUSITEC, DMD linearly increased (P < 0.01), acetate:propionate ratio quadratically decreased, while ammonia (NH3-N) concentration (P < 0.01) and butyrate percentage (%total) linearly decreased (P < 0.05) with increasing inclusion of cicer milkvetch. No differences were observed for methane (CH4) production (mg·g−1 DMD), or short chain fatty acid (SCFA) production (mmol·day−1). Microbial nitrogen synthesis and efficiency of protein synthesis linearly increased (P < 0.05) with increased inclusion of cicer milkvetch. Results suggest cicer milkvetch may result in synchronicity of energy and nitrogen during rumen fermentation, which could enhance cattle production.
Some monotonicity properties of parametric and nonparametric Bayesian bandits

One of two independent stochastic processes (arms) is to be selected at each of n stages. The selection is sequential and depends on past observations as well as the prior information. The objective is to maximize the expected future-discounted sum of the n observations. We study structural properties of this classical bandit problem, in particular how the maximum expected payoff and the optimal strategy vary with the priors, in two settings: (a) observations from each arm have an exponential family distribution and different arms are assigned independent conjugate priors; (b) observations from each arm have a nonparametric distribution and different arms are assigned independent Dirichlet process priors. In both settings, we derive results of the following type: (i) for a particular arm and a ﬁxed prior weight, the maximum expected payoff increases as the prior mean yield increases; (ii) for a ﬁxed prior mean yield, the maximum expected payoff increases as the prior weight decreases. Specializing to the one-armed bandit, the second result captures the intuition that, given the same immediate payoff, the less one knows about an arm, the more desirable it becomes because there remains more information to be gained when selecting that arm. In the parametric case, our results extend those of ( Ann. Statist. 20 (1992) 1625–1636) concerning Bernoulli and normal bandits (see also (In Time Series and Related Topics (2006) pp. 284–294 IMS)). In the nonparametric case, we extend those of ( Ann. Statist. 13 (1985) 1523–1534). A key tool in the derivation is stochastic orders.
Overview of miR-106a Regulatory Roles: from Cancer to Aging

MicroRNAs (miRNAs) comprise a class of non-coding RNA with extensive regulatory functions within cells. MiR-106a is recognized for its super-regulatory roles in vital processes. Hence, the analysis of its expression in association with diseases has attracted considerable attention for molecular diagnosis and drug development. Numerous studies have investigated miR-106 target genes and shown that this miRNA regulates the expression of some critical cell cycle and apoptosis factors, suggesting miR-106a as an ideal diagnostic and prognostic biomarker with therapeutic potential. Furthermore, the reported correlation between miR-106a expression level and cancer drug resistance has demonstrated the complexity of its functions within different tissues. In this study, we have conducted a comprehensive review on the expression levels of miR-106a in various cancers and other diseases, emphasizing its target genes. The promising findings surrounding miR-106a suggest its potential as a valuable biomolecule. However, further validation assessments and overcoming existing limitations are crucial steps before its clinical implementation can be realized.
Cardiac Biomarkers and Their Role in Identifying Increased Risk of Cardiovascular Complications in COVID-19 Patients

Cardiovascular disease (CVD) is a global health concern, causing significant morbidity and mortality. Both lifestyle and genetics influence the development of CVD. It is often diagnosed late, when the treatment options are limited. Early diagnosis of CVD with help of biomarkers is necessary to prevent adverse outcomes. SARS-CoV-2 infection can cause cardiovascular complications even in patients with no prior history of CVD. This review highlights cardiovascular biomarkers, including novel ones, and their applications as diagnostic and prognostic markers of cardiovascular complications related to SARS-CoV-2 infection. Patients with severe SARS-CoV-2 infection were shown to have elevated levels of cardiac biomarkers, namely N-terminal pro-brain natriuretic peptide (NT-pro-BNP), creatine kinase-myocardial band (CK-MB), and troponins, indicating acute myocardial damage. These biomarkers were also associated with higher mortality rates and therefore should be used throughout COVID-19 patient care to identify high-risk patients promptly to optimize their outcomes. Additionally, microRNAs (miRNAs) are also considered as potential biomarkers and predictors of cardiac and vascular damage in SARS-CoV-2 infection. Identifying molecular pathways contributing to cardiovascular manifestations in COVID-19 is essential for development of early biomarkers, identification of new therapeutic targets, and better prediction and management of cardiovascular outcomes.
Diagnosis of inflammatory bowel disease–Asian perspectives: the results of a multinational web-based survey in the 8th Asian Organization for Crohn’s and Colitis meeting

Background/Aims Inflammatory bowel disease (IBD) is no longer a rare disease in Asia, thus it needs to prepare recommendations relevant to Asian patients. This study aimed to identify disparities in the process of the diagnosis of IBD in Asian countries/regions. Methods In line with the 2020 Asian Organization for Crohn’s and Colitis annual meeting, a multinational web-based survey about Asian physicians’ perspectives on IBD was conducted. Results A total of 384 Asian physicians (99 in China, 93 in Japan, 110 in Korea, and 82 in other Asian countries/regions) treating IBD patients from 24 countries/regions responded to the survey. Most respondents were gastroenterologists working in an academic teaching hospital. About half of them had more than 10 years of clinical experience in caring for patients with IBD. The European Crohn’s Colitis Organisation guideline was used most commonly for the diagnosis of IBD except for Japanese physicians who preferred their own national guideline. The Mayo score and Crohn’s Disease Activity Index were the most commonly used activity scoring systems for ulcerative colitis and Crohn’s disease, respectively. Endoscopy, not surprisingly, was the main investigation in assessing the extent and activity of IBD. On the other hand, there were disparities across countries/regions with regard to the favored modalities of small bowel and perianal evaluation of Crohn’s disease, as well as the use of serologic markers. Conclusions Results of the present survey revealed practical behaviors of Asian physicians in the diagnosis of IBD. Investigating the reasons for different diagnostic approaches among countries/regions might help us develop Asian guidelines further.
The impacts of dynamic capabilities on SMEs' digital transformation process: The resource-based view perspective

Research background: SMEs' concern for the digital literacy of their workforce, their interest in increasing digital literacy among employees, and securing their digital platforms, have been major issues in their digital transformation process. To reduce those obstacles, the dynamic capabilities of SMEs included in the Resource-based View (RBV) might be an effective solution since they help companies be more competitive and proactive against the threats they face in the digitalization process. Purpose of the article: This research aims to investigate whether SMEs' dynamic capabilities positively contribute to their digital transformation process. Methods: In line with the proposed relationships, this paper analyzes SMEs from Czechia by running Ordinal Logistic Regression analyses. The research sample is created by stratified random sampling and purposive sampling methods. The research data is collected via telephone surveys. Findings & value added: This research does not find a positive relationship between the dynamic capabilities of SMEs and the digital transformation process. While the results related to digital literacy are negatively associated with digital transformation, no significant relationship exists between security actions and the digital transformation of SMEs. This paper extends the scope of RBV on the digital transformation of SMEs by analyzing various dynamic capabilities of SMEs that have not been included in a sole study. Moreover, the perceptions of SME executives are considered by this research to provide effective solutions for the problems they face in digital transformation. Having a joint venture agreement with well-experienced IT companies, having a network with partner firms, looking for funding opportunities in the EU, participating in some practical training, and providing internships for bachelor students might enable SMEs to hit their targets in digital transformation.