Miracle-dz/UniFAR-FTUs huggingface dataset:
Function of Chick Subcutaneous Adipose Tissue During the Embryonic and Posthatch Period

Since excess abdominal fat is one of the main problems in the broiler industry for the development of modern broiler and layer industry, the importance of subcutaneous adipose tissue has been neglected. However, chick subcutaneous adipose tissue appeared earlier than abdominal adipose tissue and more than abdominal adipose tissue. Despite a wealth of data, detailed information is lacking about the development and function of chick subcutaneous adipose tissue during the embryonic and posthatch period. Therefore, the objective of the current study was to determine the developmental changes of adipocyte differentiation, lipid synthesis, lipolysis, fatty acid β-oxidation, and lipid contents from E12 to D9.5. The results showed that subcutaneous adipose tissue was another important energy supply tissue during the posthatch period. In this stage, the mitochondrial copy number and fatty acid β-oxidation level significantly increased. It revealed that chick subcutaneous adipose tissue not only has the function of energy supply by lipidolysis but also performs the same function as brown adipose tissue to some extent, despite that the brown adipose tissue does not exist in birds. In addition, this finding improved the theory of energy supply in the embryonic and posthatch period and might provide theoretical basis on physiological characteristics of lipid metabolism in chicks.
Herbicides Tolerance in a Pseudomonas Strain Is Associated With Metabolic Plasticity of Antioxidative Enzymes Regardless of Selection

Agriculture uses many food production chains, and herbicides participate in this process by eliminating weeds through different biochemical strategies. However, herbicides can affect non-target organisms such as bacteria, which can suffer damage if there is no efficient control of reactive oxygen species. It is not clear, according to the literature, whether the efficiency of this control needs to be selected by the presence of xenobiotics. Thus, the Pseudomonas sp. CMA 6.9 strain, collected from biofilms in an herbicide packaging washing tank, was selected for its tolerance to pesticides and analyzed for activities of different antioxidative enzymes against the herbicides Boral®, absent at the isolation site, and Heat®, present at the site; both herbicides have the same mode of action, the inhibition of the enzyme protoporphyrinogen oxidase. The strain showed tolerance to both herbicides in doses up to 45 times than those applied in agriculture. The toxicity of these herbicides, which is greater for Boral®, was assessed by means of oxidative stress indicators, growth kinetics, viability, and amounts of peroxide and malondialdehyde. However, the studied strain showed two characteristic antioxidant response systems for each herbicide: glutathione-s-transferase acting to control malondialdehyde in treatments with Boral®; and catalase, ascorbate peroxidase, and guaiacol peroxidase in the control of peroxide induced by Heat®. It is possible that this modulation of the activity of different enzymes independent of previous selection characterizes a system of metabolic plasticity that may be more general in the adaptation of microorganisms in soil and water environments subjected to chemical contaminants. This is relevant to the impact of pesticides on the diversity and abundance of microbial species as well as a promising line of metabolic studies in microbial consortia for use in bioremediation.
Accuracy of the Short-Form Montreal Cognitive Assessment Chinese Versions

Background: There is a strong need for short and effective methods to screen for cognitive impairment. Recent studies have created short forms of the Montreal Cognitive Assessment (s-MoCA) in English-speaking populations. It is also important to develop a validated Chinese short version to detect cognitive impairment. Methods: Item response theory and computerized adaptive testing analytics were used to construct abbreviated MoCAs across a large neurological sample comprising 6,981 community-dwelling Chinese veterans. Results: Six MoCA items with high discrimination and appropriate difficulty were included in the s-MoCA. The Chinese short versions (sensitivity 0.89/0.90, specificity 0.72/0.77) are similar in performance to the full MoCA in identifying cognitive impairment (sensitivity 0.91, specificity 0.82). Conclusions: These short variants of the MoCA may serve as quick and effective instruments when the original MoCA cannot be feasibly administered in clinical services with a high patient burden and limited cognitive testing resources.
Genomic Insights Into the Admixture History of Mongolic- and Tungusic-Speaking Populations From Southwestern East Asia

As a major part of the modern Trans-Eurasian or Altaic language family, most of the Mongolic and Tungusic languages were mainly spoken in northern China, Mongolia, and southern Siberia, but some were also found in southern China. Previous genetic surveys only focused on the dissection of genetic structure of northern Altaic-speaking populations; however, the ancestral origin and genomic diversification of Mongolic and Tungusic–speaking populations from southwestern East Asia remain poorly understood because of the paucity of high-density sampling and genome-wide data. Here, we generated genome-wide data at nearly 700,000 single-nucleotide polymorphisms (SNPs) in 26 Mongolians and 55 Manchus collected from Guizhou province in southwestern China. We applied principal component analysis (PCA), ADMIXTURE, f statistics, qpWave/qpAdm analysis, qpGraph, TreeMix, Fst, and ALDER to infer the fine-scale population genetic structure and admixture history. We found significant genetic differentiation between northern and southern Mongolic and Tungusic speakers, as one specific genetic cline of Manchu and Mongolian was identified in Guizhou province. Further results from ADMIXTURE and f statistics showed that the studied Guizhou Mongolians and Manchus had a strong genetic affinity with southern East Asians, especially for inland southern East Asians. The qpAdm-based estimates of ancestry admixture proportion demonstrated that Guizhou Mongolians and Manchus people could be modeled as the admixtures of one northern ancestry related to northern Tungusic/Mongolic speakers or Yellow River farmers and one southern ancestry associated with Austronesian, Tai-Kadai, and Austroasiatic speakers. The qpGraph-based phylogeny and neighbor-joining tree further confirmed that Guizhou Manchus and Mongolians derived approximately half of the ancestry from their northern ancestors and the other half from southern Indigenous East Asians. The estimated admixture time ranged from 600 to 1,000 years ago, which further confirmed the admixture events were mediated via the Mongolians Empire expansion during the formation of the Yuan dynasty.
COVID-19 Beliefs, Self-Efficacy and Academic Performance in First-year University Students: Cohort Comparison and Mediation Analysis

Students’ learning contexts can influence their learning beliefs and academic performance outcomes; as such, students studying during the COVID-19 outbreak may be at risk of negative impacts on their academic self-efficacy and subject grades compared to other cohorts. They may also have specific beliefs about the impact of COVID-19-related changes on their capacity to perform, with potential consequences for self-efficacy and academic performance. Two weeks after the COVID-19-related transition to online-only learning, 89 first-year psychology students completed a measure of academic self-efficacy and indicated how they thought COVID-19-related changes would impact their capacity to perform in a psychology subject. At the end of the semester, subject grades were obtained from institutional records. Contrary to expectations, neither the self-efficacy beliefs nor the subject grades of the 2020 cohort were significantly different from those of a sample of 2019 first-year psychology students (n = 85). On average, 2020 students believed that COVID-19-related changes to their learning environment had a negative impact on their capacity to perform well. A mediation analysis indicated that students’ beliefs about the impact of COVID-19 on their capacity did not directly, or indirectly (via self-efficacy), predict grades. The only significant association in the model was between self-efficacy and grades. Although students reported believing that COVID-19-related changes would negatively impact their capacity to perform, there is little evidence that these beliefs influenced their academic self-efficacy or academic performance or that studying during the COVID-19 outbreak disadvantaged students in comparison with the previous years. A follow-up analysis indicated that self-efficacy was a stronger predictor of grades in the 2020 cohort than in the 2019 cohort. While there may be several unmeasured reasons for cohort differences, one potential interpretation is that, in the context of uncertainty associated with COVID-19, self-efficacy beliefs assumed relatively greater importance in terms of mobilising the resources required to perform well.
The Field-Frequency Lock for Fast Field Cycling Magnetic Resonance: From NMR to MRI

Magnetic field stability plays a fundamental role in Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI) experiments, guaranteeing accuracy and reproducibility of results. While high levels of stabilization can be achieved for standard NMR techniques, this task becomes particularly challenging for Fast Field Cycling (FFC) NMR and MRI, where the main magnetic field is switched to higher or lower levels during the pulse sequence, and field stabilization must be guaranteed within a very short time after switching. Recent works have addressed the problem with rigorous tools from control system theory, proposing a model based approach for the synthesis of magnetic field controllers for FFC-NMR. While an experimental proof of concept has underlined the correctness of the approach for a complete FFC-NMR setup, the application of the novel, model based Field-Frequency Lock (FFL) system to a FFC-MRI scanner requires proper handling of field encoding gradients. Furthermore, the proof of concept work has also stressed how further advances in the hardware and firmware could improve the overall performances of the magnetic field control loop. The main aim of this perspective paper is then discussing the key challenges that arise in the development of the FFL system suitable for a complete MRI scanner, as well as defining possible research directions by means of preliminary, simulated experiments, with the final goal of favoring the development of a novel, model based FFL system for FFC-MRI.
Horizontal and vertical spill-over in multilevel electoral systems

ABSTRACT A multilevel electoral system perspective reveals several ways in which electoral spill-over may occur. Vertical spill-over may be top-down from the national to the regional level or can be bottom-up from the regional to the national electoral arena. Horizontal spill-over happens when developments in one regional electoral arena impact electoral outcomes in another regional electoral arena. The literature on regional elections has mainly focused on vertical top-down spill-over. In this introduction, we discuss two main insights in relation to spill-over between electoral arenas that surface when considering the collection of articles and reports presented in this fourth annual review of regional elections. First, we discuss how horizontal spill-over can be identified and differentiated from diffusion of electoral developments driven by territorial cleavages. Second, we discuss several institutions that impact vertical spill-over. We conclude by considering a wider research agenda for the study of spill-over in multilevel electoral systems.
Patient Rights to Publicity versus Provider Rights to Privacy: Striking a Balance When Blogging in the Medical Setting

have anything to fear? British Medical Journal 335 (7621): 645–6. doi: 10.1136/bmj.39343. 478403.68. MacIntyre, M. R. , and J. M. Appel. 2019. Safety preempted: When EMTALA and restraining orders collide. American Journal of Emergency Medicine 37 (9):1758–9. doi:10. 1016/j.ajem. 2019.07. 014. Mamede, S. , T. Van Gog, S. C. E. Schuit, K. Van den Berge, P. L. A. Van Daele, H. Bueving, T. Van der Zee, W. W. Van den Broek, J. L. C. M. Van Saase, and H. G. Schmidt. 2017. Why patients’ disruptive behaviours impair diagnostic reasoning: A randomised experiment. BMJ Quality & Safety 26 (1):13–8. doi:10.1136/bmjqs2015-005065. Paul-Emile, K. 2019. How should organizations support trainees in the face of patient bias? AMA Journal of Ethics 21 (6):E513–520. Paul-Emile, K. , A. K. Smith, B. Lo, and A. Fern andez. 2016. Dealing with racist patients. New England Journal of Medicine 374 (8):708–11. doi:10.1056/NEJMp1514939. Ratnapalan, S. 2009. Shades of grey: Patient versus client. Canadian Medical Association Journal 180 (4):472. doi:10. 1503/cmaj.081694. Rosenstein, A. H. , and M. O’Daniel. 2008. Invited article: Managing disruptive physician behavior: Impact on staff relationships and patient care. Neurology 70 (17): 1564–70. doi:10.1212/01.wnl. 0000310641.26223. 82. Schmidt, H. G. , T. van Gog, S. Ce Schuit, K. Van den Berge, P. LA Van Daele, H. Bueving, T. Van der Zee, W. W Van den Broek, J. Lcm Van Saase, S. Mamede, et al. 2017. Do patients’ disruptive behaviours influence the accuracy of a doctor’s diagnosis? A randomised experiment. BMJ Quality & Safety 26 (1):19–23. doi:10.1136/ bmjqs-2015-004109.
Bayesian Conway–Maxwell–Poisson regression models for overdispersed and underdispersed counts

Abstract Bayesian models that can handle both overdispersed and underdispersed counts are rare in the literature, perhaps because full probability distributions for dispersed counts are rather difficult to construct. This note takes a first look at Bayesian Conway–Maxwell–Poisson regression models that can handle both overdispersion and underdispersion yet retain the parsimony and interpretability of classical count models. The focus is on providing an explicit demonstration of Bayesian regression inferences for dispersed counts via a Metropolis–Hastings algorithm. We illustrate the approach on two data analysis examples and demonstrate some favorable frequentist properties via a simulation study.
The effect of industrial relocations to central and Western China on urban construction land expansion

ABSTRACT Undertaking industrial transfers from the eastern region in China and other developed countries leads to the growth of urban construction in central and western China. This can result in serious problems, such as the reduction of the amount of cultivated land, thus endangering Chinese food security. This paper utilizes a system generalized method of moments (SYS-GMM) estimator and data from 2008 to 2015 for 17 provinces in central and western regions using a dynamic panel model to explore the effects of both domestic and foreign investments on urban construction land. The results show that both domestic and foreign investment have significant positive effects statistically and causally, although they can also have a complementary effect that lessens the positive effect. The impact of domestic investment is weaker than that of foreign investment. We propose land management suggestions with the aim of reducing the tension between industrial relocations and urban construction land.
Preparation and surface-functionalization of dye-doped bioconjugated poly(styrene-co-maleimide) nanoparticles

Standard methods used for detection of microbial contamination in water and food are based on culturing of samples to increase the number of bacteria present to a detectable level. These tests are however time-consuming (requiring one to two days for results to be generated) and labour intensive. The study described in this dissertation aims to develop dye-doped poly(styrene-co-maleimide) nanoparticles conjugated to antibodies for the rapid (within a few hours) detection of E. coli in water via clustering of the nanoparticles around bacteria to create a concentrated and localised fluorescent signal. Pristine and dye-doped nanoparticles were synthesised according to a one-step (published) method, and surface-functionalised with formaldehyde and three different diamine compounds. The percentage dye added to the particles was also varied in the study. The functionalised nanoparticles were characterised via FTIR, TEM, DSC, and Zetasizer. The emission properties of the dye-loaded NPs were measured with a spectrofluorometer. The functionalised nanoparticles were bioconjugated with avidin and antibodies. The extent of avidin attachment was quantified via the use of a biotin(5-fluorescein) conjugate and via an avidin titration assay. The functionality of the bioconjugated nanoparticles was tested via a sandwich assay and a centrifuge based assay with E. coli cultures. Fluorescence microscopy was also utilised to demonstrate the utility of the particles in creating localised fluorescent signals indicating the presence of E. coli cells. Stellenbosch University http://scholar.sun.ac.za
Soret and Radiation Effects on Mixture of Ethylene Glycol-Water (50%-50%) Based Maxwell Nanofluid Flow in an Upright Channel

In this article, ethylene glycol (EG) + waterbased Maxwell nanofluid with radiation and Soret effects within two parallel plates has been investigated. The problem is formulated in the form of partial differential equations. The dimensionless governing equations for concentration, energy, and momentum are generalized by the fractional molecular diffusion, thermal flux, and shear stress defined by the Caputo–Fabrizio time fractional derivatives. The solutions of the problems are obtained via Laplace inversion numerical algorithm, namely, Stehfest’s. Nanoparticles of silver (Ag) are suspended in a mixture of EG + water to have a nanofluid. It is observed that the thermal conductivity of fluid is enhanced by increasing the values of time and volume fraction. The temperature and velocity of water-silver nanofluid are higher than those of ethylene glycol (EG) + water (H2O)-silver (Ag) nanofluid. The results are discussed at 2% of volume fraction. The results justified the thermo-physical characteristics of base fluids and nanoparticles shown in the tables. The effects of major physical parameters are illustrated graphically and discussed in detail.
Information Entropy Based on Propagation Feature of Node for Identifying the Influential Nodes

For understanding and controlling spreading in complex networks, identifying the most influential nodes, which can be applied to disease control, viral marketing, air traffic control, and many other fields, is of great importance. By taking the effect of the spreading rate on information entropy into account, we proposed an improved information entropy (IIE) method. Compared to the benchmark methods in the six different empirical networks, the IIE method has been found with a better performance on Kendall’s Tau and imprecision function under the Susceptible Infected Recovered (SIR) model. Especially in the Facebook network, Kendall’s Tau can grow by 120% as compared with the original IE method. And, there is also an equally good performance in the comparative analysis of imprecise functions. The imprecise functions’ value of the IIE method is smaller than the benchmark methods in six networks.
A Natural Formalization of the Mutilated Checkerboard Problem in Naproche

N aproche is an emerging natural proof assistant that accepts input in a controlled natural language for mathematics, which we have integrated with L A TEX for ease of learning and to quickly produce high-quality typeset documents. We present a self-contained formalization of the Mutilated Checkerboard Problem in N aproche, following a proof sketch by John McCarthy. The formalization is embedded in detailed literate style comments. We also briefly describe the N aproche approach. 2012 ACM Subject Classification Theory of computation → Logic and verification
Practical Bipartite Tracking for Networked Robotic Systems via Fixed-Time Estimator-Based Control

In this paper, the fixed-time practical bipartite tracking problem for the networked robotic systems (NRSs) with parametric uncertainties, input disturbances, and directed signed graphs is investigated. A new fixed-time estimator-based control algorithm for the NRSs is presented to address the abovementioned problem. By applying a sliding surface and the time base generator (TBG) approach, a new stability analysis method is proposed to achieve the fixed-time practical bipartite tracking for the NRSs. We also derive the upper bound of the convergence time for employing the presented control algorithm to solve the practical bipartite tracking problem and further demonstrate that the convergence time is independent of the initial value. Finally, the simulation examples are given to verify the effectiveness of the presented algorithms.
Developing a Framework for Spatial Effects of Smart Cities Based on Spatial Econometrics

Department of Engineering Management, School of Civil Engineering, Central South University, Changsha, Hunan 410075, China School of Construction Engineering, Hunan Institute of Engineering, Xiangtan 411104, China Hunan Provincial Key Laboratory of Intelligent Disaster Prevention-Mitigation and Ecological Restoration in Civil Engineering, Hunan Institute of Engineering, Xiangtan 411104, China Department of Financial Mathematics, School of Science, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China Department of Building & Real Estate, Hong Kong Polytechnic University, Hung Hom 810005, Hong Kong School of Civil Engineering, Anhui Jianzhu University, Hefei, Anhui 230601, China Department of Civil Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
Evaluation of parallel and sequential deep learning models for music subgenre classification

In this paper, we evaluate two deep learning models which integrate convolutional and recurrent neural networks. We implement both sequential and parallel architectures for ﬁne-grain musical subgenre classiﬁcation. Due to the exceptionally low signal to noise ratio (SNR) of our low level mel-spectrogram dataset, more sensitive yet robust learning models are required to generate meaningful results. We investigate the eﬀects of three commonly applied optimizers, dropout, batch regularization
Quantitative Analysis of Comprehensive Influence of Music Network Based on Logistic Regression and Bidirectional Clustering

This paper makes a quantitative analysis of the comprehensive influence of music networks. Firstly, 11 music features are selected from energy, popularity, and other aspects to build a comprehensive evaluation index of music influence, and the PageRank algorithm is used to quantify the music influence. Secondly, the multiobjective logistic regression is used to construct the music similarity measurement model and, combined with music influence and music similarity, to judge whether the influence of different musicians is the actual influence. Thirdly, the influence and similarity of the same music genre and different music genres are analyzed by using the two-way cluster analysis method. Finally, the lasso region is used for feature selection to obtain the change factors in the process of music evolution and analyze the dynamic changes in the process of music development. Therefore, this paper uses network science to build a dynamic network to analyze the similarity of music, the evolution process, and the impact of music on culture, which has certain research significance and practical value in the fields of music, history, social science, and practice.