Miracle-dz/UniFAR-FTUs huggingface dataset:
The Chemical Composition and Biological Activities of Essential Oil from Korean Native Thyme Bak-Ri-Hyang (Thymus quinquecostatus Celak.)

Thymus quinquecostatus Celak. (Korean name: bak-ri-hyang) is an important medicinal and aromatic herb in Korea, which is named for the spread of its fragrance over a distance of approximately 40 km. In traditional Korean systems of medicine, T. quinquecostatus has been used to treat cancer, constipation, hepatic disease, arteriosclerosis, poor circulation in women, constipation, and menstrual irregularities. At present, T. quinquecostatus is used only for ornamental and ground cover purposes. A literature search was conducted to retrieve information regarding the essential oil composition and biological properties of T. quinquecostatus from PubMed, Science Direct, Wiley, Springer, Taylor and Francis, Wiley, and other literature databases. T. quinquecostatus can be divided into different chemotypes, such as γ-terpinene, thymol, phenol, carvacrol, and geraniol, according to the presence of major components in its essential oil. Further, the essential oil from T. quinquecostatus has been reported to possess various therapeutic properties such as antioxidant, antimicrobial, anticancer, anti-inflammatory, analgesic, sleep prolonging, soothing, skin protection and whitening, anti-aging, anti-obesity, and anti-acne properties. In conclusion, this review will be helpful for utilizing the T. quinquecostatus plant in different industries including food, pharmaceuticals, pesticides, perfumery, and cosmetics.
Data-Driven Evaluation and Optimisation of Livelihood Improvement Efficiency

In this study, we developed a data-driven approach for the evaluation and optimisation of livelihood improvement efficiency (LIE) to address slowing global economic growth and the decline in well-being in the broader population, enhance the quality of people’s livelihoods, and promote sustainable social development. We designed a questionnaire survey and constructed an evaluation index system based on a comprehensive consideration of economic resources, social security and employment, education, and health. Using principal component analysis, entropy weighting, and data envelopment analysis, we optimised the evaluation indicators and quantitatively assessed LIE. We used a Tobit regression model to analyse the factors influencing LIE and provide decision-making support for proposing countermeasures to optimise LIE. Based on the research data, we administered the questionnaire survey to 3125 residents in 16 cities in China’s Anhui Province and demonstrated the applicability of the aforementioned method. The results indicate that there is room for optimising LIE in cities in Anhui Province, which needs to be achieved through the following steps: controlling costs and avoiding waste, encouraging entrepreneurship, increasing income, guiding the direction of industrial growth, optimising regional population structure, and promoting public participation to enhance people’s livelihoods.
View Normalization of Object Size in the Right Parietal Cortex

Prior knowledge alters perception already on early levels of processing. For instance, judging the display size of an object is affected by its familiar size. Using functional magnetic resonance imaging, we investigated the neural processes involved in resolving ambiguities between familiar object size and physical object size in 33 healthy human subjects. The familiar size was either small or large, and the object was displayed as either small or large. Thus, the size of the displayed object was either congruent or incongruent with its internally stored canonical size representation. Subjects were asked to indicate where the stimuli appeared on the screen as quickly and accurately as possible, thereby ensuring that differential activations cannot be ascribed to explicit object size judgments. Incongruent (relative to congruent) object displays were associated with enhanced activation of the right intraparietal sulcus (IPS). These data are consistent with but extend previous patient studies, which found the right parietal cortex involved in matching visual objects presented atypically to prototypical object representations, suggesting that the right IPS supports view normalization of objects. In a second experiment, using a parametric design, a region-of-interest analysis supported this notion by showing that increases in size mismatch between the displayed size of an object and its familiar viewing size were associated with an increased right IPS activation. We conclude that the right IPS performs view normalization of mismatched information about the internally stored prototypical size and the current viewing size of an object.
Effect of semaglutide and liraglutide in individuals with obesity or overweight without diabetes: a systematic review

Background & Objective: Although data on the effects of liraglutide and semaglutide in patients with diabetes have been reviewed, their therapeutic outcomes in obese/overweight individuals without diabetes have not been summarized. We conducted a systematic review to evaluate their effects on the latter population. Methods: We searched the PubMed, EMBASE, Cochrane, CNKI, and Wanfang databases. Studies regarding obese/overweight adults without diabetes treated with liraglutide/semaglutide compared with other active agents or placebos were accessed. The primary outcomes were the proportions of adults with at least 5% and 10% weight reduction. The secondary outcomes included metabolic indicators and adverse events. Results: Eighteen studies with 10,938 obese/overweight adults without diabetes were included. When stratified by the categories of at least 5% and 10% weight loss, the pooled data showed medians 27.7% and 10.3% of control groups versus 65.3% and 30.7% of liraglutide 3 mg once daily, respectively; whereas medians 47.6% and 20.4% of control groups vs 86.6% and 75.3% of semaglutide 2.4 mg once weekly were found in the two categories, respectively. Both agents either improved or had no impact on lipid or glycemia. Liraglutide or semaglutide therapy had discontinuation rates of 2.4%–11.4% which overlapped with 0.7%–8.6% in control groups. The frequency of adverse events was comparable between the treatment groups and the control groups (66.5%–95.8% vs 46.9%–96.1%), which were mild to moderate graded by studies. Conclusion: Liraglutide and semaglutide therapy led to a clinically relevant (⩾5%) weight loss of 48.2%–88.7% among obese/overweight adults without diabetes. Both liraglutide and semaglutide are associated with weight loss and are well-tolerated.
Linear Growth Impairment in Patients With Pediatric Inflammatory Bowel Disease

Introduction Linear growth impairment (LGI) is one of the complications of pediatric inflammatory bowel disease (IBD). This study aimed to assess the linear growth of patients with pediatric IBD and to detect the frequency and the possible risk factors of LGI. Methods A retrospective cross-sectional review of medical records of patients with pediatric IBD was conducted in the pediatrics department, Salmaniya Medical Complex, Bahrain, from 1984 to 2019. Demographic and anthropometric data were gathered. World Health Organization (WHO) standards and references were used to define LGI. According to WHO, stunting and severe stunting were defined as length/height for age of <-2 standard deviations and <-3 standard deviations from age and sex-specific reference means, respectively. To determine the possible risk factors for LGI, stunted patients were compared with normal height patients in regard to demographic data, clinical presentations, and treatment used. Results Out of 130 patients with pediatric IBD, 88 (67.7%) had anthropometric data available. Fifty-five (62.5%) were males. Forty-seven (53.4%) had Crohn’s disease and 41 (46.6%) had ulcerative colitis. The mean age at presentation was 10.7±3.8 years. The median age at the time of growth measurement was 14.2 (interquartile range=12.1-24.4) years. Fifteen (17%) patients were stunted, and seven (46.7%) of those stunted patients were severely stunted. Weight at presentation was lower in stunted patients (21.6±5.9 kilograms) compared to normal height patients (31±13.4 kilogram) (p=0.048). Sex, delivery type, birth weight, height at presentation, age at presentation, age at growth measurements, IBD type, disease duration, presence of extraintestinal manifestations, and prednisolone and biologic therapy use were not significant factors of stunting. Conclusion Patients with pediatric IBD have a high prevalence of LGI compared to the general population. Low weight at disease presentation is the only significant risk factor for LGI. This might indicate that IBD as a disease by itself is having the main negative impact on linear growth.
Neuropsychological and affective assessment of teachers over 50 years old before and after an ICT-focused training program

The aging of the population raises several social and health related issues and is particularly high in Europe, where policies promoting Active Aging are being pursued. In Education, the aging of the teaching workforce poses significant challenges to the profession. The REKINDLE+50 project developed a training program on Information and Communications Technology (ICT) use for teachers with the parallel intent of promoting the abilities and motivation of teachers over 50 years old. Here we report on the pre- and post-test assessment of neuropsychological abilities (“cool” and “hot” executive functions), self-reported affective functioning and job satisfaction. We found that the training program was associated with increased satisfaction with the nature of the teachers’ work and with material working conditions. There were no significant changes in neuropsychological nor affective measures before and after the program. We also found that job satisfaction was positively associated with “hot” executive functions and negatively linked to affective symptoms (sub-clinical anxiety and depression). These findings, although tentative, suggest that the training program had a positive impact on teacher job satisfaction, and may have potential implications for the promotion of active aging in teachers. Overall, the aging of teachers remains a challenge for the future. The policies for promoting Active Aging provide a strategic outlook on how to tackle this issue, but a more detailed understanding of age-related cognitive and affective changes is likely required to devise effective measures.
Classification of Heterogeneous Mining Areas Based on ResCapsNet and Gaofen-5 Imagery

Land cover classification (LCC) of heterogeneous mining areas is important for understanding the influence of mining activities on regional geo-environments. Hyperspectral remote sensing images (HSI) provide spectral information and influence LCC. Convolutional neural networks (CNNs) improve the performance of hyperspectral image classification with their powerful feature learning ability. However, if pixel-wise spectra are used as inputs to CNNs, they are ineffective in solving spatial relationships. To address the issue of insufficient spatial information in CNNs, capsule networks adopt a vector to represent position transformation information. Herein, we combine a clustering-based band selection method and residual and capsule networks to create a deep model named ResCapsNet. We tested the robustness of ResCapsNet using Gaofen-5 Imagery. The images covered two heterogeneous study areas in Wuhan City and Xinjiang Province, with spatially weakly dependent and spatially basically independent datasets, respectively. Compared with other methods, the model achieved the best performances, with averaged overall accuracies of 98.45 and 82.80% for Wuhan study area, and 92.82 and 70.88% for Xinjiang study area. Four transfer learning methods were investigated for cross-training and prediction of those two areas and achieved good results. In summary, the proposed model can effectively improve the classification accuracy of HSI in heterogeneous environments.
A Lightweight Convolutional Neural Network Based on Hierarchical-Wise Convolution Fusion for Remote-Sensing Scene Image Classification

The large intra-class difference and inter-class similarity of scene images bring great challenges to the research of remote-sensing scene image classification. In recent years, many remote-sensing scene classification methods based on convolutional neural networks have been proposed. In order to improve the classification performance, many studies increase the width and depth of convolutional neural network to extract richer features, which increases the complexity of the model and reduces the running speed of the model. In order to solve this problem, a lightweight convolutional neural network based on hierarchical-wise convolution fusion (LCNN-HWCF) is proposed for remote-sensing scene image classification. Firstly, in the shallow layer of the neural network (groups 1–3), the proposed lightweight dimension-wise convolution (DWC) is utilized to extract the shallow features of remote-sensing images. Dimension-wise convolution is carried out in the three dimensions of width, depth and channel, and then, the convoluted features of the three dimensions are fused. Compared with traditional convolution, dimension-wise convolution has a lower number of parameters and computations. In the deep layer of the neural network (groups 4–7), the running speed of the network usually decreases due to the increase in the number of filters. Therefore, the hierarchical-wise convolution fusion module is designed to extract the deep features of remote-sensing images. Finally, the global average pooling layer, the fully connected layer and the Softmax function are used for classification. Using global average pooling before the fully connected layer can better preserve the spatial information of features. The proposed method achieves good classification results on UCM, RSSCN7, AID and NWPU datasets. The classification accuracy of the proposed LCNN-HWCF on the AID dataset (training:test = 2:8) and the NWPU dataset (training:test = 1:9), with great classification difficulty, reaches 95.76% and 94.53%, respectively. A series of experimental results show that compared with some state-of-the-art classification methods, the proposed method not only greatly reduces the number of network parameters but also ensures the classification accuracy and achieves a good trade-off between the model classification accuracy and running speed.
The Role of Expertise in Discovery. Comment on Sutton and Griffiths (2018). Using Date Specific Searches on Google Books to Disconfirm Prior Origination Knowledge Claims for Particular Terms, Words, and Names. Social Sciences 7: 66

In claiming that expertise are unnecessary for making discoveries that contribute to knowledge, Sutton and Griffiths made analogous comparisons with metal detection, then proceeded to provide six examples in support of their argument. This response demonstrates the fallacy of that analogy, and reveals how those examples were undermined by a lack of expertise in the relevant disciplines. The mistakes contained in Sutton and Griffiths make it evident that expertise are required to identify the validity of a discovery, and ensure that a claim is not false. This assurance is particularly needed for the bold claims made by Sutton & Griffiths.
External Financing for Inclusive Growth in Lower - Middle Income West African Countries: Foreign Direct Investment versus Official Development Assistance

ABSTRACT Most developing countries are plagued with harsh economic realities, which motivate them to seek sustainable economic growth and development in line with goal eight of the United Nations Sustainable Development Goals. To this end, this paper investigated the source of external financing that is most helpful for achieving inclusive growth in lower-middle-income West African countries. The study is a panel analysis of annual data extending from 2000 to 2019. The study employed the Emirmahmutoglu and Kose Bootstrap Granger Causality Test, Westerlund Cointegration Test, Common Correlated Mean Group estimation technique, and Augmented Mean Group estimation technique for econometric analyses. The long-run empirical results from the study showed that both foreign direct investment and foreign aid have positive and significant effects on inclusive growth, although the impact of foreign direct investment is greater than that of foreign aid. A bi-directional causality was also found to exist between inclusive growth and foreign direct investment, while no causal relationship was detected between inclusive growth and foreign aid. Given the study’s empirical outcomes, it is recommended that West African countries prioritize macroeconomic policy reforms that provide enabling conditions for foreign direct investment to thrive rather than pursue foreign aid that more often than not are misdirected.
Independent Quality Assessment of Essential Climate Variables: Lessons learnt from the Copernicus Climate Change Service

If climate services are to lead to effective use of climate information in decision-making to enable the transition to a climate-smart, climate-ready world, then the question of trust in the products and services is of paramount importance. The Copernicus Climate Change Service (C3S) has been actively grappling with how to build such trust; provision of demonstrably independent assessments of the quality of products, which was deemed an important element in such trust-building processes. C3S provides access to Essential Climate Variables (ECVs) from multiple sources to a broad set of users ranging from scientists to private companies and decision-makers. Here we outline the approach undertaken to coherently assess the quality of a suite of observation- and reanalysis-based ECV products covering the atmosphere, ocean, land and cryosphere. The assessment is based on four pillars: basic data checks, maturity of the datasets, fitness for purpose (scientific use cases and climate studies), and guidance to users. It is undertaken independently by scientific experts and presented alongside the datasets in a fully traceable, replicable and transparent manner. The methodology deployed is detailed, and example assessments are given. These independent scientific quality assessments are intended to guide users to ensure they use tools and datasets that are fit for purpose to answer their specific needs rather than simply use the first product they alight on. This is the first such effort to develop and apply an assessment framework consistently to all ECVs. Lessons learnt and future perspectives are outlined to potentially improve future assessment activities and thus climate services.
Regional Contributions and Climate Attributions to Interannual Variation of Global Net Ecosystems Production by an ECOSYSTEM Processed Model Driven by Remote Sensing Data over the Past 35 Years

Global climate change has significantly affected terrestrial carbon sinks. Net ecosystem production (NEP) plays a critical role in the global carbon cycle. However, interannual variability (IAV) of the NEP and its regional contributions and climate attributions are not well-understood on a global scale. This study used a diagnostic model driven by remote sensing leaf area index (LAI) to investigate the NEP IAV and analyze regional and climate contributions on a global scale from 1982 to 2016. We found large NEP IAV during the study period, with the NEP detrended anomaly ranging from −2.3 Pg C in 1998 to 1.6 Pg C in 2013 at a global scale. Furthermore, 63.7% and 34.1% of the areas showed positive and negative contributions to NEP IAVs globally, respectively. Evergreen broadleaf forest (EBF) contributed the most (31.1%) to NEP IAV, followed by cropland (21.7%) and grassland (20.8%). Temperature played the most critical roles in the global NEP IAV, with a contribution of 45.5%. However, the partial correlation between NEP and temperature was negative, and the correlation with precipitation was positive in most areas of the globe, indicating that global warming is not conducive to the global carbon sink, but abundant rainfall is important for the global carbon cycle. This study suggests that, to increase the global carbon sink, we should pay more attention to tropical forests (EBFs) and highlight the importance of water availability.
Relativistic Cosmological Perturbation Theory and the Evolution of Small-Scale Inhomogeneities

rst-order relativistic perturbation theory for the open, at or closed FriedmannLema^ tre-Robertson-Walker universe admits one, and only one, gauge-invariant quantity which describes the perturbation to the energy density and which becomes equal to the usual Newtonian energy density in the non-relativistic limit. The same holds true for the perturbation to the particle number density. These facts exclude all denitions of gauge-invariant quantities used to describe density perturbations in former theories. Using these two new quantities, a manifestly covariant and gauge-invariant cosmological perturbation theory, adapted to non-barotropic equations of state for the pressure, has been developed. The new theory is valid for all scales since metric gradients do not occur in the nal evolution equations. The new theory has an exact non-relativistic limit with a time-independent Newtonian potential. The usual Newtonian perturbation theory is inadequate to study the evolution of density perturbations. In the radiation-dominated era, perturbations in the particle number density are gravitationally coupled to perturbations in the total energy density, irrespective of the nature of the particles. This implies that structure formation can commence only after decoupling of matter and radiation. After decoupling of matter and radiation density perturbations evolve diabatically, i.e., they exchange heat with their environment. This heat loss of a perturbation may enhance the growth rate of its mass suciently to explain stellar formation in the early universe, a phenomenon not understood, as yet, without the additional assumption of the existence of Cold Dark Matter. This theoretical observation is the main result of this article.
Genes Impacting Grain Weight and Number in Wheat (Triticum aestivum L. ssp. aestivum)

The primary goal of common wheat (T. aestivum) breeding is increasing yield without negatively impacting the agronomic traits or product quality. Genetic approaches to improve the yield increasingly target genes that impact the grain weight and number. An energetic trade-off exists between the grain weight and grain number, the result of which is that most genes that increase the grain weight also decrease the grain number. QTL associated with grain weight and number have been identified throughout the hexaploid wheat genome, leading to the discovery of numerous genes that impact these traits. Genes that have been shown to impact these traits will be discussed in this review, including TaGNI, TaGW2, TaCKX6, TaGS5, TaDA1, WAPO1, and TaRht1. As more genes impacting the grain weight and number are characterized, the opportunity is increasingly available to improve common wheat agronomic yield by stacking the beneficial alleles. This review provides a synopsis of the genes that impact grain weight and number, and the most beneficial alleles of those genes with respect to increasing the yield in dryland and irrigated conditions. It also provides insight into some of the genetic mechanisms underpinning the trade-off between grain weight and number and their relationship to the source-to-sink pathway. These mechanisms include the plant size, the water soluble carbohydrate levels in plant tissue, the size and number of pericarp cells, the cytokinin and expansin levels in developing reproductive tissue, floral architecture and floral fertility.